Full text of Economic Review (Federal Reserve Bank of Atlanta) : December 1981, Volume 66, Number 8

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Economic

Review

FEDERAL RESERVE BANK OF ATLANTA

DECEMBER 1981

Success or Burden?
ALLBIG G O V T Federal Sector's Hidden Size
INCENTIVES Southeast Lures Foreign Investors
NOWS Competition in Southeastern Cities
FORECASTS State Models in Southeast

Economic h i
Review"
FEDERAL RESERVE BANK OF ATLANTA
President:
W i l l i a m F. Ford
Sr. Vice President
and Director of Research:
D o n a l d L. K o c h
Vice President
and Associate Director of Research:
W i l l i a m N. C o x
Financial Structure:
B. Frank K i n g , Research O f f i c e r
David D. Whitehead
National Economics:
Robert E. Keleher, Research Officer
Stephen O . Morrell
Regional and International Economics:
G e n e D . Sullivan, Research O f f i c e r
C h a r l i e Carter
W i l l i a m J. Kahley
Database Management:
D e l o r e s W. S t e i n h a u s e r
Visiting Scholars:
James R. Barth
G e o r g e W a s h i n g t o n University
G e o r g e J. B e n s t o n
University of R o c h e s t e r
Arnold A. Heggestad
University of Florida
John Hekman
University of N o r t h C a r o l i n a
Communications O f f i c e r :
D o n a l d E. Bedwell
Public Information Representative:
D u a n e Kline
Editing:
G a r y W. Tapp
Graphics:
S u s a n F. Taylor
Free subscription and additional copies
available upon request to the Information
Center, Federal Reserve Bank of Atlanta, P.O.
Box 1731, Atlanta, Georgia 30301. The views
expressed are not necessarily those of the
Federal Reserve Bank of Atlanta or of the
Federal Reserve System. Material herein may
be reprinted or abstracted, provided this
Review and the author are credited. Please
provide this Bank's Research Department
with a copy of any publication in which such
material is reprinted.

The Federal Reserve Bank of Atlanta also publishes Insight,
a newsletter on economic trendy in the Southeast. Insight,
published twice a month and mailed first class, is designed
to give readers fresh and timely data, analyses, and forecasts on
the Southeast's economy. Free subscriptions are available
from the Information Center, Federal Reserve Bank of
Atlanta, P.O. Box 1731, Atlanta, Georgia 30301.

DECEMBER 1981, E C O N O M I C REVIEW

T h e purpose of the Economic Review is to inform the public about Federal R e s e r v e policies and the
economic environment and, in particular, to narrow the g a p between specialists and concerned laymen.

Is the All-Savers Certificate a Success?
Evidence from the Southeast
4

NOW Competition
in Southeastern Cities

How much will the All-Savers program help the
thrift industry? How much will it cost in lost federal
revenues? A survey of over 3,000 All-Savers depositors in the Southeast suggests some answers.

Previous articles in this Review have traced the
competition for NOW dollars at the state level. But
how are banks and S&Ls faring in individual cities?
New reports show wide variations across the region.

Southeastern Pork Production:
A Clue to Future
Food Price Changes?

Hog prices are a major component of meat prices in
general. Since meat prices, in turn, govern the
majority of changes in consumer food prices, changes
in hog prices may indicate imminent changes in
consumer food prices. A comparison of pork production
in the Southeast and the M idwest sheds light on the
reliability of southeastern pork production as an
indicator of food price changes.

The Impact of State Incentives
on Foreign Investors'
Site Selections

High stakes in the bidding for foreign investment
have spawned increasing use of incentives by state
development agencies. What is the evidence that
these incentives actually affect foreign investment
decisions?

V O L U M E LXVI, N O . 8

Economic Forecasting
for Southeastern States

How Big is the
Federal Government?

Econometric models for individual states are flourishing in the Southeast. Where are the region's major
econometric forecasting projects? How do they
work, who are their clients, and how good are their
forecasts?

Polls indicate the public thinks the federal government is too large, wasteful and inefficient, yet the
number of federal employees per 1,000 of population actually dropped from 1959 to 1978. Is the
public impression wrong, or do conventional measures of government size fail to capture the true
extent of federal employment and spending?

Is the All-Savers Certificate A Success?
Evidence from the Southeast

A survey of southeastern All-Savers depositors suggests that the Certificate offers
some help to thrifts but presents little competition to money market funds. In fact,
the ASC's benefits to financial institutions appear small compared to the costs in
lost federal tax revenues.
The controversial All-Savers Certificate (ASC)
has been hailed by proponents as a boon to the
ailing thrift industry, but panned by critics as
offering too little help to thrifts at too much cost
to the Treasury. A spokesman for the mutual
funds industry painted a frightening picture of
the A S C as "a giant vacuum cleaner... drawing
funds away from normal investment with some
serious consequences." 1 The National League of
Cities worried that the A S C would be in direct
competition with tax-exempt municipal bonds,
forcing up the cost of running cities and raising
property taxes.2
But if the ASC is a vacuum cleaner, it seems to
be operating in neutral—merely churning up
funds within the same institution. Early evidence
from the Southeast reveals that, while the AllSavers program will provide modest relief for
thrift institutions, its cost to the U. S. Treasury is
likely to be substantially greater than its benefits
to thrifts. Specifically, a Federal Reserve Bank of
Atlanta survey suggests the following conclusions:
1. Consumers are not pulling funds from one
kind of institution (bank, thrift, or credit
union) and putting them into another.
2. Surprisingly, although the A S C provides a
lower level of tax benefits for families earning
less than $30,000 per year, over 40 percent
of new ASC depositors fall into that category.
3. The All-Savers Certificate is producing modest
cost savings for thrifts and banks.
4. Congress estimated the ASC will cost the
federal government about $3.3 billion in tax
revenues. Since we estimate that it will
increase thrift's earnings by at most $1.9
billion, for every dollar the ASC saves the
thrifts, it will cost the Treasury almost two
dollars.
4

5. Consumers are not putting much money
from passbook savings into the ASC.
6. The ASC is not presenting serious competition
to money market funds.
7. Most A S C deposits are coming from money
market certificates.
Why the All-Savers Certificate?
Background
In the Economic Recovery Tax Act of 1981,
Congress sought to address the financial problems
of the thrift industry by authorizing thrift institutions, commercial banks and credit unions to
issue a new type of certificate of deposit. A
portion of the earnings on this new certificatecalled the All-Savers Certificate—is exempt from
federal income taxes. This feature allows the
nation's depository institutions to offer a deposit
that costs them less than market indexed deposits,
such as money market certificates, and at the
same time, provides high returns to investors.
With the ASC, Congress sought to bolster the
earnings and financing capacity of thrift institutions.
Savings and loan associations and mutual savings
banks have been hard hit in the past two years by
portfolio imbalances: they have had to borrow at
rates often higher than longer-term rates at
which they lend. S&L earnings dropped from a
record $3.9 billion in 1978 to $.8 billion in 1980
to a loss of $1.8 billion during the first half of
1981. Their net worth declined by $3.2 billion,
9.8 percent, during the first three quarters of
1981.
The designers of the A S C hoped to attract
investors with higher incomes—people with greatDECEMBER 1981, E C O N O M I C REVIEW

er access to investments such as money market
mutual funds which compete with depository
institutions—by offering a tax-free yield of 70
percent of the investment yield on 52 week
Treasury Bills. For households with marginal tax
brackets of 30 percent or higher, the ASC's taxequivalent yield is equal to or above the 52 week
Treasury Bill yield. The A S C rate in effect for most
of October—12.14 percent—gave an after-tax
yield of 16.19 percent to taxpayers with a 1982
taxable income of $20,000-$24,000 and filing a
joint return; taxpayers filing a joint return with
taxable incomes of more than $85,000 would
earn an after-tax equivalent return of 24.28 percent.
Commercial banks and credit unions were also
allowed to issue ASCs at the same rates and
maturities as thrift institutions. Had they not
been allowed to do this, it is quite likely that
there would have been deposit flows from the
commercial banks and credit unions to thrift
institutions when the ASC was introduced. Since
ASC deposits would probably be taken out of
taxable instruments, federal tax revenue would
be lost. Congress sought to limit this loss of tax
revenue by limiting the time period in which it
could be issued and the amount of income from
the certificate that is covered by the tax-exemption.
The certificates may only be issued between
October 1, 1981 and December 31, 1982. For
persons filing individual tax returns, $1,000 of
income is tax exempt; for persons filing joint
returns, the exemption is $2,000.
To further aid the thrift institutions, the Depository Institutions Deregulation Committee rescinded early withdrawal penalties on certificates of
deposit that were converted into ASCs if the
original certificate paid a higher interestrate than
the ASC. The DI D C thus discouraged depositors
from converting lower cost certificates to ASCs
and encouraged them to convert higher cost
deposits.
What emerged from this blend of Congressional
objectives is a fairly simple concept bounded by
detailed law and regulation. Features which will
boost the financial industry are the tax exempt
status of earnings from the certificate, the indexing of the certificate's yield at 70 percent of
market yield on a similar instrument and the ease
of converting higher cost certificates to all savers
certificates. The main restrictions are the limits
on the amount of income from ASCs that may be
deducted and the limited time during which the
certificates may be offered.
FEDERAL RESERVE BANK OF ATLANTA

BOX 1
Main Features of the All Savers Certificate
T a x Exemption
T i m e Period

$1,000 individual return
$2,000 joint return
15 months (Oct. 1,1981 - Dec.
31, 1982)

for Issue
When Interest Paid

as accrues or at maturity

Highest
Minimum Deposit

$500

Buyers Eligible
for T a x Exemption

individuals, partnerships,
estates of purchasers

Interest T a x a b l e

if certificate redeemed,
used to secure a loan

Maturity

1 year

Interest Rate

70 percent of investment yield
on 52 week U.S. Treasury Bills,
most recent auction before
week A S C is issued.

Investment T i e s

Beginning first quarter 1982,
75 percent of lower of net new
retail time and savings deposits
or value of all savers certificates
issued during the previous quarter must go to residential or
agricultural financing. Otherwise, the institution must not
issue certificates until the requirement is met.

What Are
Residential a n d
Agricultural
Financing

•agricultural loans
• insured or guaranteed
home improvement loans
• mortgages on single or
multifamily dwellings
• new purchases of FNMA,
GNMA, F H L M C and
private mortgage pass through
or mortgage backed securities
• mobile home loans
•construction and
rehabilitation loans on
single and multifamily
residences

Is It Working?
Survey Results
In evaluating-the success of the A S C so far, we
need to ask two kinds of questions: (1) Is it
producing the intended effects, and (2) Is it
producing unintended effects? In order to gain
early insight into these questions, we surveyed
purchasers of ASCs from banks and savings and
loan associations in the Sixth Federal Reserve
District.
We solicited the voluntary cooperation of the
largest banks and S&Ls in the District. In our
invitation, we explained that participating institutions would be the first to receive survey results
and interpretations. Thus, from a "self-interest"
standpoint, the institutions could gain valuable
marketing information by participating. Within
30 days of the survey, the participating institutions
had the survey results and a profile of All-Savers
deposits in the region.
The institutions which participated in Alabama
represented 33 percent of the state's total deposits; in Florida, 18 percent; in Georgia, 22 percent;
in Louisiana, 4 percent; in Mississippi, 28 percent;
and in Tennessee, 23 percent. Both savings and
loans and commercial banks were represented
in all of the states except Alabama and Georgia,
where no S&Ls responded. Commercial bank
customers' responses made up 74 percent of the
total sample; savings and loans' customers comprised the remaining 26 percent. These propor-

Table 1. Alternative Instruments for Investment
of All-Savers Certificate F u n d s
Alternative
Instrument
Money Market Certificate
Small Saver Certificate
Fixed-Rate Time Certificate
or Passbook Sources
Other Internal Sources
Money Market Mutual Fund
State or Municipal Securities
U.S. Treasury Securities
Other External Sources
No Response

Percent of
A S C Funds
64.5
5.1
8.4
2.0
12.1
1.4
1.8
3.4
1.3

Note: items do not add to 100% because of rounding.

T a b l e 2. Institutional S o u r c e of
All-Savers Certificate F u n d s
Percent of
F u n d s from
Institution

Institution
Same
Institution
Other Depository
Institutions
Commercial Bank
S&Ls
Credit Union
Other Institutions
Multiple Institutions
No Response

61.2
12.7
8.9
.7
8.6
7.0
.9
100.0

tions roughly parallel the proportion of total
deposits held by these institutions in the Southeast.4
The institutions asked their customers who
invested in the A S C during October 1-7 period to
fill out a survey form. The key questions asked of
the customer were amount of deposit, institutional
source of funds, alternative financial instrument
for the funds, percent of the depositor's savings
invested in the ASC, and the depositor's age, and
income. Each institution chose 3-5 branches in
different parts of its state in which to conduct the
survey. The surveys were administered during
the first five working days of October. Nearly
3,200 completed forms were returned and processed, representing $28 million in All-Savers
deposits.
Is the ASC providing the intended benefits?
The primary question is whetherfunds comingin
to ASCs will come predominantly from high cost
or from low cost deposits. In the Southeast, the
evidence is that fears that the A S C would raise
the cost of funds are unfounded (see Table 1).
Savers reported that only eight percent of AllSavers' funds would have wound up in passbook
savings or fixed rate certificates of deposits, and
70 percent of the money would have gone into
higher cost money market certificates or small
savers certificates.
A second major purpose of the A S C was to
bring new money into depository institutions.
D E C E M B E R 1981, E C O N O M I C R E V I E W

All-Savers Survey Highlights
61 percent of All-Savers
depositors kept their funds
in the same
institution.

65 percent of ASC deposits came from
money
market
certificates.

Only 3.5 percent of ASC
deposits were taken out
of S&Ls and put into commercial banks. Only 4.3
percent went from banks
into S&Ls.

Only eight percent of ASC
deposits came from passbook savings and other
fixed rate time
deposits,
suggesting that consumers are still wary of committing these funds for
as long as a year.

The ASC represented very
little competition to money
market funds. About 12
percent of ASC funds in
the survey came
from
money market funds.

On this score, the ASC was only moderately
successful. Our survey showed that more than
60 percent of ASC deposits were transferred
from accounts within the same institution. Nineteen percent came from other sources outside of
the depository institutions, such as money market
funds, stocks, or securities.(See Table 2).
The ASC was also intended to stimulate certain
kinds of investment. Thrifts and banks must
invest 75 percent of their inflow of ASCs or of
their net inflow of consumer time and savings
deposits in "housing and agriculture." Housing
and agriculture are broadly defined in the Tax
Act to include securities of the Federal Home
Loan Mortgage Corporation, the Government
National Mortgage Corporation and the Federal
National Mortgage Corporation, as well as mortgage, construction, home improvement and farm
loans made to the private sector.
These investment requirements should not be
difficult for most institutions to fulfill. Thrift
institutions already invest predominantly in housing related assets. Commercial banks, while not
generally specializing in real estate and agricultural
loans, will be investing cash flow from ASC
deposits and other sources that provide substantial amounts of funds. This large flow of investment
relative to the ASC gains seems likely to allow
most banks to meet investment requirements
FEDERAL RESERVE BANK OF ATLANTA

Since most of the money
going into ASCs is being
rolled over from
higheryielding accounts,
some
institutions
may experience improvement
in interest
margins.
Even though the ASC's
tax advantages
are less
effective for families earning less than $30,000, over
40 percent of new ASC
depositors
fell into that
"lower income"
category.

without much difficulty.Conversations with several larger Southeastern banks indicate this to be
their expectation also.
Side Effects
The second kind of concern about the ASC has
to do with unintended side effects. To the extent
that ASCs promote inflows of funds into depository institutions, for example, they will take funds
from other institutions and instruments that
savers use. Most important of these to the thrifts
are the money market mutual funds. ASCs' tax
exempt feature also gives them some similarity
to state and municipal securities. ASCs may also
be substitutes in investment portfolios for shortterm obligations of the U. S. Treasury, and for
corporate securities.
To determine what financial instrument is
getting the most competition from the All-Savers,
we asked the customer, "Where would you
place these funds if the ASC were not available?"
Sixty-five percent answered the six-month money
market certificate. Even more, 71 percent, of the
money which was transferred within the same
institution was converted from money market
certificates.
The money market mutual funds lost only a
modest amount of money to All-Savers. During
7

October, their assets nationwide climbed almost
$9 billion to $170 billion. In the Southeast, we
found that only 12 percent of deposits flowing
into the all-savers certificates would have gone
into or remained in money market funds if allsavers had not existed. Much smaller percentages
of funds would have gone into state and municipal
securities or U. S. government securities.
Our survey revealed another public reaction to
the ASC which was surprising. A large proportion
of ASC depositors had gross incomes of less than
$30,000—indicative of marginal tax rates of less
than 30 percent for those filing joint returns. The
tax advantage for an individual is determined by
comparing the effective taxable yield he can
receive on the All-Savers Certificate to the current
yield on money market funds or other highpaying instruments. For a family in the 30 percent
tax bracket, the initial All-Savers yield of 12.61
percent was equal to a taxable yield of approximately 18 percent. For the family in the 20
percent bracket, a comparable taxable yield
would be 15.8 percent. Therefore, most analysts
expected that the lower income (but not necessarily low income) groups would choose to
invest in a money market fund where yields are
well over 16 percent than tie their money up in
the lower-yielding All-Savers Certificate. Our survey
indicates, however, that the largest proportion of
accounts and funds in ASCs came from depositors
with household incomes of less than $30,000.

and may be alien to individuals who do not
invest frequently or with any volume. It seems
likely that households with lower incomes would
keep a larger proportion of their assets in depository institutions. Those survey respondents in
the less than $30,000 income bracket who did
take money out of a money market fund to invest
in the ASC represented only 7 percent of the
deposits for that income group.
If money market funds are not perceived as a
viable investment alternative, then the ASC is
very attractive to an investor with less than $ 10,000
(which is the minimum investment in the six
month money market certificate) who does not
want to tie up money for V k years in the smallsavers certificate. The ASC's effective yield for an
investor in the 20 percent tax bracket has been
very close to the 2V2 year small-saver certificate
yield. This appeal of the A S C to lower income
groups could be part of the reason why money
market funds have suffered very little from its
introduction.
Higher income groups may recognize that, for
them, tax-free money market funds or municipal
bonds may yield a higher return than the ASC.
They may also want the liquidity of the money
market funds, something the ASC does not
provide.
The average size of deposit increased as income
increased. It ranged from $6,500 per deposit for
the under $30,000 income bracket to $12,000
per deposit in the over $60,000 income range.

Investment in All-Savers Certificate
by I n c o m e G r o u p

National Effects of the ASC

Household
Income

$0-30,000
30-39,999
40-49,999
50-59,999
60,000+
No Response

P e r c e n t of

Deposits

Accounts

30
21
15
10
15
9

41
20
12
7
11
9

There may be several explanations for this
trend. The lower income investors may be predominantly those who file individual tax returns.
Marginal tax rates and tax adjusted A S C yields
are higher for these taxpayers than for those filing
joint returns. Lower income groups may be less
likely to perceive money market funds as a viable
alternative investment. The funds are often handled by a brokerage firm or investment company
8

Since the All-Savers Certificate breaks new
ground, there is considerable difference of opinion about its projected impacts. Our survey
provides new evidenceon several features of the
public's response to the certificate. W e can use
these figures from the Southeast to estimate the
national effects of the all savers program on
competition among institutions, and on institutions' costs.
First, institutions apparently are not raiding
each other for A S C funds. Our survey indicated
that a majority of funds deposited in ASCs came
from within the same institution and that even
when funds moved between institutions there
was little crossover between banks and S&Ls.
Only a small proportion of A S C deposits at the
banks and S&Ls we surveyed came from credit
unions. In addition, we found that banks and
thrifts got similar percentages of their All-Savers
DECEMBER 1981, E C O N O M I C REVIEW

funds from outside sources such as money market
mutual funds. Banks' and thrifts' proportions of
ASC funds reported in the survey were very
similar to the proportion of consumer time and
savings deposits that they held. Our results
indicate that the ASC is producing only small
flows of funds among different types of institutions.
Second, the ASC seems likely to produce
modest savings in costs of funds for thrifts and
banks. We estimated the cost savings for thrift
institutions and commercial banks on the basis
of a maximum volume of ASC deposits of $110
billion.This estimate seems reasonable in light of
the first month's ASC experience. It is the midpoint
between recently revised estimates of $150
billion by Data Resources Incorporated (on the
high side) and the estimate of $70 billion which
is consistent with the tax loss estimates of the
Congress' Joint Committee on Taxation (on the
low side). The box explains the details of our
method. Since spreads between the costs of
ASCs and alternative sources of funds are crucial
to cost savings estimates, we made two estimates.
The first was based on yield spreads in 1980, a
year of high interest rates when short-term rates
were often above long-term rates. The second
was based on yield spreads in 1978 when interest
rates were lower and short-term rates were
generally below long rates.
On the basis of the larger 1980 rate spreads,
we estimate the 1982 cost savings to thrifts
would be $1.1 billion (1.7 percent of their 1980
cost of funds, almost twice their depressed 1980
earnings levels) (see Table 3). Banks would also
Table 3. C o s t S a v i n g s from A S C s C o m p a r e d
with C o s t s a n d E a r n i n g s of F i n a n c i a l Institutions
Cost savings 1982
1980 spreads (million $)
1978 spreads (million $)
Cost of funds 1980
Cost of deposits 1980
Net after-tax income
Cost savings as percent of:
Cost of funds
1980 spreads
1978 spreads
Cost of deposits
1980 spreads
1978 spreads
Net after-tax income
1980 spreads
1978 spreads

FEDERAL RESERVE BANK OF ATLANTA

Commercial
Banks

Thrifts

938.0
605.0
217.8
196.2
14.0

1061.0
691.0
58.6
52.2
.5

.4
.3

1.7
1.2

.5
.3

2.0
1.3

6.7
4.3

198.7
129.4

BOX 2
In order to project the ASC's impact on institutions' cost of funds, we examined three
factors: (1) the distribution of All-Savers deposits
among institutions, (2) the differences between
the rates paid for All-Savers deposits and the
rates the institutions would have paid for the
deposits from alternative sources, and (3) the
dollar volume of All-Savers deposits.
Our evidence supports the assumption that
All-Savers deposits are distributed among the
various types of institutions in the same proportion as are consumer time and savings deposits.
As of September 1981 .commercial banks held
44.7 percent of these deposits and thrift institutions held 49.9 percent. Credit unions held
the remaining 5.4 percent.
Having assumed the proportionate distribution of deposits among institutions, we are
faced with the task of projecting total AllSavers deposits. Early results seem to be
consistent with an estimate of $110 billion.
This estimate lies midway between the recent
$150 billion projection of Data Resources Inc.
and the $70 billion that can be derived from the
tax loss estimates of the Joint Committee on
.Taxation of the Congress. This will be our
primary estimate of all savers deposits at their
maximum level. That level should be reached
in late 1982. We further assumed that half of
the year end 1982 level would be deposited by
the end of 1981.
We know that the amount of A S C s outstanding on January 1, 1984 will be zero (at least
under the program passed this year) and we
assume that year end 1981 and 1982 values
would be $55 and $110 billion respectively.
From those totals we can compute yearly
average All-Savers deposits. These estimates
can be multiplied by the difference between
the All-Savers rate and rates on alternatives to
All-Savers deposits to estimate cost savings
brought to the targeted institutions by the ASC
(see Appendix).
Projecting rate spreads is quite chancy, so
instead we chose to use two sets of spreads.
For a high interest rate environment in which
the average yield curve had a slight negative
slope we chose 1980. For an example of lower
rates with positively sloping yield curve, we
chose 1978. (Rate spreads for an even lower
rate environment—1976—yielded the same
results as those for 1978.)

T a b l e 4. C o s t Impact of All-Savers Certificate
on C o m m e r c i a l B a n k s and Thrift Institutions
(billions $)
(Average S p r e a d 1 9 8 0 )

Commercial Banks
Alternative Instrument
Money Market Certificate
Small Savers Certificate
Other Internal Sources
Outside Funds
Total

1981
-.1
*

+ *
*

-.1

1982
-.7
-.1
+.1
-.3

1983
-.4

-.9

Thrifts
1981
-.1

+.1
-.2

Total
-1.2
-.1
+.2
-.6

-.6

-1.7

-.1

+ *
*

1982
-.7
-.1
+.1
-.4

1983
-.5
+.1
-.2

Total
-1.3
-.1
+.2
-.6

-1.1

-.7

-1.9

*Less than $.05 billion
Note: Items may not add to totals because of rounding.

benefit, saving about $.9 billion in 1982 (four
tenths of one percent of their 1980 cost of funds,
almost seven percent of their 1980 earnings)
(see Tables 4 and 5). The savings are only about
two-thirds as much when we use the lower 1978
spreads. The estimates for 1982 cost savings
computed with these spreads are $.7 billion for
thrifts and $.6 billion for banks.
Compared to the thrifts' estimated 1981 losses,
however, even the higher estimate of savings is
quite modest. Insured S&Ls lost $1.8 billion
during the first half of 1981; their net worth
declined by an additional $1.4 billion in the third
quarter. This loss is well above our higher estimate
of annual cost saving for the thrifts ($1.1 billion)
and more than two and one half times our lower
estimate ($.7 billion).
While the ASC's benefits may be modest
compared to recent thrift losses, our survey
found that the cost savings to issuing institutions
was higher than other recent estimates. For
example, we found almost 65 percent of AllSavers deposits had money market certificates
(at rates higher than ASCs) as an alternative while
the Federal Home Loan Bank Board recently
estimated that only 40 percent came from this
source. We found slightly more than 8 percent of
all savers funds had an alternative use in fixed
rate certificates and passbook accounts (at rates
lower than ASCs) while the same Home Loan
Bank Board estimate reported 30 percent from
this source. Our evidence, in short, suggests that
more money than expected came from highercost funds, and consequently, cost savings are
10

higher than indicated by other estimates.
The A S C will have a third impact on the
national economy—it will reduce tax revenues.
The Joint Conference Committee that drew up
the final version of the Economic Recovery Tax
Act estimated in its report that the A S C would
mean a $3.3 billion loss in federal tax revenue.
That estimate is quite similar to our higher
estimate of cost saving to financial institutions
and almost double our higher estimate of the
cost savings for thrift institutions. It is almost
three times our lower cost savings estimate for
the thrifts.
This estimate of federal tax losses represents
minimum tax costs associated with the ASC.
State tax collections may also be reduced. Since
interest on ASCs is not included in federal
taxable income, it would not be included in state
taxable income where the income for state taxes
is based on the federal level. There were 26 of
these states when the Economic Recovery Tax
Act was signed last August. Unless they change
their tax computation, each will bear some tax
cost of the ASC program.
If our survey results are indicative of public
behavior, the ASC appears unlikely to move
funds among the different types of depository
institutions, but rather to aliow each type to pull
in some new funds. These funds, our survey
indicates, will come primarily from money market
mutual funds, themselves intermediaries with
liquid assets to enable them to handle their
reduced inflows. Small effects on state and local
government and federal borrowing seem likely.
D E C E M B E R 1981, E C O N O M I C R E V I E W

Table 5. C o s t Impact of All-Savers Certificate
on C o m m e r c i a l B a n k s a n d Thrift Institutions
(billions $)
(Average Spread 1 9 7 8 )

Thrifts

Commercial Banks
Alternative Instrument
Money Market Certificate
Small Savers Certificate
Other Internal Sources
Outside Funds
Total

1981
- *

1982
-.4
_

-.1

1983
-.3
*

Total
-.7
-.1
*

-.2

-.1

-.3

-6

-.4

-1.1

1981
*

*
*
*

-.1

1982
-.4
_

1983
-.3
—

*
*

Total
-.8
-.1
*

-.2

-.1

-.3

-.7

-.5

-1.2

*Less than $.05 billion
Note: Items may not add to totals because of rounding.

Most funds shifted within institutions would
otherwise have been placed in higher yielding
alternatives. This means lower costs of funds—a
prime objective of the certificate. Banks are
likely to reap almost as much of these cost
savings as thrifts although their earnings have not
been seriously affected by the forces that have
hurt the thrifts. Banks' gains must be considered
a cost to the taxpayer of maintaining competitive
balance.
If one looks only at the cost savings of the
thrifts in comparison with the estimated tax
losses from the all savers program, one must
conclude that the program will be no bargain.
Our higher estimate of these cost savings is only a
little more than half of the Congress's estimate of
revenue lost as a result of the exemption of A S C
earnings from the federal income tax (in other
words, the A S C costs the U. S. Treasury almost
two dollars for every one dollar in cost savings to
thrifts); our lower estimate is only about 37
percent of the estimated loss of tax revenue. The
All-Savers program, then, seems likely to provide
moderate aid to the institutions at which it was
targeted and to do so without seriously disturbing
competition among thrift institutions, commercial
banks and credit unions. These benefits are likely
to be accomplished at costs to the Treasury that
are high relative to the benefits to the institutions
that it helps.
—Donald L. Koch, B. Frank King
and Delores W. Steinhauser

The writers wish to thank the participating banks
and S&Ls for their cooperation. The writers also
express appreciation for the contributions of
Ronnie Caldwell, Bob Sexton, Steve Collins,
Randy Elliot, Cheryl Cornish, Ethyl Jackson, Kathy
Fulton and Sherley Wilson.
1 Reginald Green, Investment Company Institute, in Congressional Quarterly, July 11, 1981, p. 1214.
2 Congressional Quarterly, July 11, 1981, p. 1214.
3 52 week Treasury Bills are auctioned monthly; therefore, a new auction
rate is set e a c h month.
4A more complete description of the survey is found in the Appendix.

APPENDIX
We computed the average monthly spreads
between the All-Savers rate that would have
held in the time period and rates on four
alternative sources of All-Savers deposits.
These four sources were:
1. Money Market Certificates (the auction
rate on six month U.S. Treasury Bills.)
2. Small Savers Certificates (the constant
maturity market rate on U.S. Treasury Notes
and Bonds of 21/a years maturity).*
3. Passbook accounts and fixed rate certificates (the 1978 average dividend paid by
S&Ls) .Because the average dividend
rate in 1980 included market indexed
certificates, we chose the weighted aver11

FEDERAL RESERVE B A N K O F ATLANTA

age rate on passbook, transactions accounts and fixed rate certificates for
savings and loans on September 30,
1980.
4. Three month certificates of deposit issued
by large commercial banks—(an estimate
of the alternative cost of raising outside
funds deposited in all savers certificates).
We multiplied these spreads by our estimates
of yearly average All-Savers deposits having
the various alternatives. This gave us the cost
savings for banks and for thrifts on deposits
with each alternative. We subtracted the quarter point differential from the rates on small
savers certificates and internal funds in our
computations for commercial banks. Table A1
gives our spreads.

T a b l e A 1 . A v e r a g e S p r e a d B e t w e e n All S a v e r s
Certificate Y i e l d s a n d Y i e l d s o n
Alternative U s e s of F u n d s
Average

Spread

(All S a v e r s R a t e L e s s A l t e r n a t i v e

Thrifts

Money Market Certificate
Small Savers Certificate
Other Internal Sources
Outside Sources

Rates)

1980

1978

-.0271
-.0307
.0199
-.0454

-.0162
-.0235
-.0061
-.0230

-.0271
-.0282
.0224
-.0454

-.0162
-.0210
-.0036
-.0230

Banks

Money Market Certificate
Small Savers Certificate
Other Internal Sources
Outside Sources

* T h e 2V4 y e a r r a t e w a s u n a v a i l a b l e i n 1 9 7 8 , s o w e s u b s t i t u t e d t h e 3 - 5
y e a r rate.

Participating Institutions
Universe

Oct. 7 Total
Deposits
($ bil.)

% of
Region's
Total
Deposits

Sample

%of
State's
Total
Deposits

N o . of
Inst it.
Parti.
in
Sur».

N o . of
Offices

Sur
veyed
Inst.
Dep.
as %
of S t .
Total
Dep.

No. of
Survey
Respon.

%of
Region's
Total
Survey
Respon.

%of
State's
Total
Survey
Respon.

A m o u n t of
Surveyed
All-Savers
Deposits
(S mil.)

% of
Region's
Surveyed
All-Savers
Deposits

%of
State's
Surveyed
Ail-Savers
Deposits

Alabama
CB
SL

17.5
13.1
4.4

100
75
25

3
3
0

30 33
30 33
0 0

395
395
0

100
100
0

3.56
3.56
0

100
100
0

Florida
CB
SL

83.2
37.6
45.6

100
45
55

5
3
2

31 18
20 14
4
11

555
291
264

100
52
48 ,

5.45
2.79
2.66

100
51
49

Georgia
CB
SL

25.4
15.7
9.7

100
62
38

3
3
0

24 22
24 22
0
0

227
227
0

100
100
0

; .88
1.88

100
100
0

Louisiana
CB
SL

27.9
20.6
7.3

100
74
26

2
1
1

18
14
4

4
3
1

256
174
82

100
68
32

2.21
1.38
0.83

100
62
38

Mississippi
CB
SL

11.8
9.4
2.4

100
80
20

4
2
2

22 28
13 21
9 7

568
408
160

100
72
28

4.88
3.27
1.60

100
67
33

Tennessee
CB
SL

24.0
17.9
6.1

100
75
25

5
3
2

48 23
34 20
3
14

1,192
883
309

100
74
26

9.93
7.34
2.59

100
74
26

189.8
114.4
75.4

100

3,193
2,378
815

100

100
74
26

27.935
20.240
7.695

100

100
72
28

TOTAL
CB
SL

CB=Commercial Bank
SL=Savings & Loan

100 22 173
60 15 135
7
38
40

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studies (2) Analyze the major U.S. payment
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electronic
banking
system.

• Expansion of Financial Powers
—Carter H. Golembe

• Future of C a s h

• Legislative Outlook for International Banking
—Peter Merrill

• Future of the C h e c k S y s t e m
—Brown R. Rawlings

• Interstate Banking

—Guy W. Botts

• Payment S y s t e m s T e c h n o l o g y
—Donald C. Long

• C h a n g i n g Competitive Environment
—George G. Kaufman

• Payments, Politics, and People
—Gerald M. Lowrie

• Investment C o m p a n i e s

• Future of Wire Transfer Services
—Bernhard W. Romberg

—Howard P. Colhoun

—William O. Adcock, Jr.

• Money Market Mutual F u n d s
—Alfred P. Johnson

• Future of A C H

• Banking

—John F. Fisher

• H o m e Delivery of Financial Services
—John F. Fisher

—Sanford Rose

• Future of Debit and Credit Cards
—Michael J. Hosemann

•"De-Intermediation"

—Allen H. Lipis

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Please indicate quantity and choice:
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BANKSNOWsS&LsBANKSNOWsS&LsBANKSNOWsS&LsBANKSNO
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SN O WsS & U B A N KSN O Ws S& Ls BAN K S N O

outheastern Citie

Although banks are doing better than
expected in the race against S&Ls for
NOW accounts, S&Ls are closing the
gap. An analysis of the competition in 43
southeastern cities shows that on July 1,
S&L market shares were still generally
lower than projections based on New
England's NOW experience.

Beginning on January 1, 1981, southeastern
savings and loans began competing with banks for
interest-bearing checking (NOW) accounts. Banks
generally set higher minimum balances for their
NOWs, perhaps relying on depositors' reluctance
to change financial institutions. S&Ls, in offering
checkable deposits for the first time, set lower
minimum balances to attract new customers.
Bankers and S&L officials alike were more than a
little anxious about where the N O W dollars would
go. Previous articles in this Review have shown
how N O W accounts started strongly, with banks
doing better than expected in the race for a share
of the market. Our earlier studies traced the
competition on a state-by-state basis.
In this article, we extend the description to 43
metropolitan areas throughout the Southeast. In
some cities, S&Ls were making the bankers even
more anxious, while in others, bankers noticed
hardly a ripple in their dominance of the market.
Daytona Beach S&Ls, for example, held an impressive 39 percent of the N O W balances on July 1,
while Florence, Alabama S&Ls were trailing the
banks 97 percent to three percent. (Our choice
14

to focus on S&L shares was arbitrary. Bank shares,
of course, represent the complement to all S&L
figures in this study.)
The diversity is due in part to the fact that S&Ls
with many offices in a city (compared to bank
offices) tend to gain a larger share of the market
than S&Ls with relatively few offices compared to
banks. Since N O W s are new accounts, even at
banks, a customer must make some effort to
open an account. Generally, people prefer to
open an account at an office near where they live
or work. Thus, the more offices an S&L has, the
larger its market share should be.
By July 1, 1981, the S&Ls had captured 11
percent of N O W dollars Districtwide, but their
share of the market varied widely. In general,
S&Ls have done better in urban areas, where
they have been gradually increasing their share
(see Box 1).

Market Share Patterns
From February (after the initial rush to open
accounts) through June, S&Ls steadily increased
their market share in all District cities except
Bradenton and Chattanooga. The degree of increase, however, was far from uniform. The areas
we studied fell into three broad categories. In
one group of cities, S&Ls held less than eight
percent of N O W dollars on July 1. In the largest
group of cities, S&Ls held between 8 and 18
percent. In the third group, S&Ls had captured
over 18 percent of the N O W dollars on July 1.
S&Ls which gained three percentage points or
more in market share between February 1 and
July 1 we classified as "strong gainers." A gain of
less than three points was "a weak gain." Grouping
the cities on the basis of these two variables,
several distinct patterns emerge (see Table 1).
DECEMBER 1981, E C O N O M I C REVIEW

Table 1
Metropolitan Areas in the Sixth District States
Grouped by Level and Gain of S&L Market Share 1

W E A K GAIN

(less than three percentage
points from Feb. 4 - July 1)

Low Share/Weak Gain
S&Ls in these
cities had a
low share
(8 percent
or below)
of NOW dollars
on J u l y l , 1981.

S&Ls in these
cities had a
moderate share
(between 8
and 18 percent)
of NOW dollars
on J u l y l , 1981.

S&Ls in these
cities had a
high share
(18 percent
or higher)
of NOW dollars
on July 1, 1981.

S T R O N G GAIN

(three or more percentage
points from Feb. 4 - July 1)

Low Share/Stong Gain

Anniston, Alabama
Florence, Alabama
Gadsden, Alabama
Montgomery, Alabama
Baton Rouge, Louisiana
Lafayette, Louisiana
Lake Charles, Louisiana
Nashville-Davidson, Tennessee

ClarkesvilleHopkinsville,
Tennessee

Moderate Share/Weak Gain

Moderate Share/Strong Gain

Bradenton, Florida
Fort Myers, Florida
Lakeland-Winter Haven,
Florida
Sarasota, Florida
Tallahassee, Florida
Columbus, Georgia
Jackson, Mississippi
Biloxi-Gulfport,
Mississippi

Birmingham, Alabama
Huntsville, Alabama
Tuscaloosa, Alabama
Albany Georgia
Atlanta, Georgia
Augusta, Georgia
Macon, Georgia
Savannah, Georgia
Alexandria, Louisiana
New Orleans, Louisiana
Kingsport, Tennessee
Knoxville, Tennessee

High Share/Weak Gain

High Share/Strong Gain

Mobile, Alabama
Gainesville, Florida
Daytona Beach, Florida
Jacksonville, Florida
Melbourne-Titusville-Cocoa
Florida
Miami, Florida
Panama City, Florida
Tampa-St. Petersburg, Florida
Pascagoula-Moss Point, Mississippi
Chattanooga, Tennessee

Ft. Lauderdale-Hollywood
Florida
Orlando, Florida
Pensacola, Florida
West Palm Beach-Boca Raton,
Florida

(NOW balances at savings and loan associations): (NOW balances at banks and savings and loan associations).

Projected Market Shares
and April-June Market Shares
As a rule, those cities with proportionately
more S&L offices could be expected to have
higher S&L market shares. That rule generally
held true. It is misleading, therefore, to compare
Baton Rouge S&Ls with Fort Lauderdale S&Ls,
because Fort Lauderdale S&Ls have many more
offices vis a vis banks than do their Baton Rouge
colleagues. To account for this difference and to
get some idea of the relative success of S&Ls in
various parts of the Southeast, we calculated a
"projected July 1 market share." Comparing
actual July 1 shares with projected July 1 shares
provides a better indication of how successfully
S&Ls are competing with banks across the Southeast (see Box 2).
As it turned out, Southerners converted checking accounts in banks to N O W accounts in much
greater numbers than we expected. Total bank
N O W balances and market shares were higher
than projected. Because of these early conversions,

S&Ls in almost all cities began with a worse than
expected showing in the race for N O W dollars.
In most cases, however, their share on July 1 was
not indicative of gains during the Spring. To
measure the success of S&Ls in attracting new
balances after the initial wave of conversions, we
calculated a market share for N O W balances
acquired from April through June, the "second
quarter" or"new" market share. In general, S&Ls
noticeably increased their share of N O W balances
during the second quarter.
Market Share Patterns in the Six States
N O W balances in both banks and S&Ls increased
during February and March. In the middle of the
second quarter, overall growth of N O W accounts in
the Southeast began to flatten out. In May,
however, the patterns for S&Ls and banks diverged.
From May 1 to July 1, S&L balances increased in
all six states, but bank N O W balances declined
in Alabama, Florida, Georgia, and Mississippi.

Box 1

Box 2

Under the rules of the Monetary Control Act of
1980, all but the smallest institutions are
required to post reserves against their NOW
account balances and to submit weekly reports
of those balances to the Federal Reserve.
This study takes advantage of that new source
of data. These newly available data are solely
dollar balances of NOWs, not the number of
accounts. With the dollar values from the
reporting institutions, we have calculated the
market share of NOW accounts captured by
the savings and loans in each city. For each
dollar of NOW accounts in a city, in other
words, how many cents worth are on the
books of S&Ls (and how many cents worth are
on the books of commercial banks). * It provides
one measure of how successful S&Ls have
been in capturing the NOW account dollar.

To compare actual and projected market shares,
we first determined the number of bank offices
and S&L offices in each SMSA. In order to
predict market shares with this information, it
was necessary to make assumptions about
the relative numbers of accounts in banks and
S&Ls and the respective average NOW balances An analysis of the NOW account experience
in New England suggested that thrifts would
be twice as aggressive in opening NOW accounts* We therefore assumed that S&Ls
would open twice as many NOW accounts per
office. Based on price (minimum balance) differences, we also expected that banks would
have 21A times the average balance that S&Ls
do.
With the office information and the assumption regarding relative average number of
accounts and balances, we projected market
shares. Keep in mind that these "projected
market shares" are based on the number of
offices only.

*ln many cases, credit unions have been offering share draft accounts
in the Southeast for several years. These accounts are functionally
equivalent to NOW accounts at the banks and thrifts, and comprise
about five percent of NOW-type balances of the region. Only a small
slice of the share draft accounts have been added since the beginning
of 1981, however, so we have not included the share drafts in our
discussion of market shares.

•William N. Cox, "NOW Accounts: Applying the Northeast's Experience to
the Southeast," Economic Review, Federal Reserve Bank of Atlanta,
September/October 1980, pp. 4-10.

D E C E M B E R 1981, E C O N O M I C R E V I E W

S&Ls gradually increased their share of the
market from February through June. This pattern
was repeated in most, but not all, of the local
markets in the District.
S&Ls in non-metropolitan areas followed about
the same pattern, although as Table 1 shows, S&L
market shares were consistently lower in nonmetro areas. Over the first half of 1981, however,
S&Ls steadily increased their market shares in
both metro and non-metro areas, with almost
identical patterns. Since there are more S&L
offices relative to bank offices in metro areas, it is
not surprising that the metro S&Ls have higher
market shares.
(The charts on page 22 show market share
patterns for Sixth District states and for each
local area.

S&L Market Shares 1 in Metro and Non-Metro
Areas in Sixth District States (percent)
Statewide
S&L Market
Shares
on 7/1/81

Alabama
Florida
Georgia
Louisiana2
Mississippi2
Tennessee2

9
22
11
8
8
8

Metropolitan3
Areas S&L
Market Share
on 7/1/81

Non-Metropolitan
Areas S&L
Market Share
on 7/1/81

11
23
13
10
9
10

6
16
5
4
6
4

(NOW Balances at S&Ls) -f- (NOW balances at commercial banks and
2
Savings and Loans)
Sixth District Portion of States only.
Metropolitan areas are here defined as the areas of the state lying within
the boundaries of an SMSA.

State-by-State Analysis
Alabama
The eight cities in Alabama demonstrated
three different patterns. As of July 1, depositors
had put 18 percent of the N O W dollars into S&Ls
in Mobile, but S&Ls there had held over 15
percent of the N O W market on February 4. This
placed Mobile in the High Share/Weak Gain
pattern. Birmingham, Huntsville and Tuscaloosa
each followed the Moderate Share/Strong Gain
market share pattern. In these three cities S&Ls
held from 10 to 14 percent of the N O W market,
generally gaining around 4 points since February.
The patterns in Anniston, Florence, Gadsden and
Montgomery were Low Share/Weak Gain.
On July 1, S&Ls in Alabama were not doing as
well as we had expected. In most cities, in fact,
S&L shares were less than half of what we
projected. There were other surprises as well.
Based on the number of offices, we expected
Tuscaloosa to have the highest S&L market share
followed by Birmingham and then Mobile. Instead,
we found that Mobile had the highest share,
followed by Tuscaloosa. Florence S&Ls had the
lowest share among Alabama cities and, in fact,
fell farther short of projections than S&Ls in any
other Alabama city.
Things
began to pick up for Alabama S&Ls in

S&L Portion of Total NOW Account Balances —
Alabama (percent)
Actual S&L
Market
Share on
July 1,1981

Anniston
Birmingham
Florence
Gadsden
Huntsville
Mobile
Montgomery
Tuscaloosa
Alabama Total State

Projected
S&L Market
Share

S&L Share of
NOW Balances
Added During
Second Quarter

5
11
3
5
12
18
8
13

7
26
20
15
19
25
20
31

10
24
11
51
37
25
22
100 '

'NOW Balances actually declined in Tuscaloosa banks.

the second quarter, however. Shares gained during
the second quarter were quite close to projections
in Mobile, Montgomery, Anniston, and Birmingham
and much higher than projections in Gadsden,
Huntsville, and Tuscaloosa. Only in Florence did
these new market shares fall markedly short of
projected levels.

Florida
In Florida cities the levels of market share were
in general higher and the February-June increases
smaller than in other metropolitan areas.
The sixteen metro areas of Florida experienced
market share patterns of three types. Tallahassee,
Fort Myers, Sarasota, Lakeland and Bradenton
had moderate shares but weak gains. S&Ls in a
large group of cities started fast, but then gained
less than three percentage points over the February-July 1 period. In this High Share/Weak Gain
category were Melbourne Jacksonville, Gainesville,
Miami, Daytona Beach, Panama City, and Tampa
S&Ls in the remaining cities, Ft. Lauderdale,
Orlando, Pensacola, and West Palm Beach, got
out of the starting blocks fast and then accelerated.
Fort Lauderdale S&Ls, for example, grabbed a
whopping 77 percent of new N O W dollars
during the second quarter.
While S&Ls did better in Florida compared to
cities in other states, their market shares were
still lower than projected in all cases. The degree
to which Florida S&Ls fell short of projections was
in general slightly less than in other Sixth District
cities. However, it appears that the relatively
high S&L market shares in Florida cities resulted
in large part from the proportionately high number of S&L offices in Florida.
In the majority of Florida cities, S&Ls did very
well in the second quarter, with new market
shares exceeding July 1 shares by a wide margin.
However, Florida is the only state with some
cities where the S&L share of new second quarter
balances was lower than total July 1 shares. In
Gainesville, Miami and Panama City, S&Ls lost
ground slightly during the second quarter. In
other Florida cities, including Bradenton, Ft Lauderdale, Melbourne, Pensacola, Sarasota and West
Palm Beach, S&Ls doubled their February-June
pace duringthe second quarter. In the remaining
metropolitan market areas, S&Ls were gaining at
more moderate rates.

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S&L Portion of Total NOW Account Balances —
Florida (percent)
Actual S&L
S&L Share of
Market
Projected NOW Balances
Share on S&L Market Added During
July 1,1981
Second Quarter
Share

Bradenton
Daytona Beach
Ft. Lauderdale
-Hollywood
Fort Myers
Gainesville
Jacksonville
Lakeland
-Winter Haven
-Bartow
Melbourne
-Titusville
-Cocoa
Miami
Orlando
Panama City
Pensacola
Sarasota
Tallahassee
Tampa
- St. Petersburg
West Palm
Beach Boca Raton
Florida Total State

16
38

36
52

38
45

27
13
21
18

45
36
31
37

77
23
19
28

26
23
31
21
19
16
14

37
38
36
33
25
52
26

66
21
43
16
38
40
14

&LsBANKSNO'
» M
NKSNOvi 's S&L
KSNOWs.f&Lsf A N ^ i n u w s v .
A'sSCxL BA SJKSI JMWqWI «P^N
/IUsBANKSNOV'sS&LsBANKSNÖ
C W s ^ ' . s *ANKSNOWsS&

D E C E M B E R 1981, E C O N O M I C R E V I E W

Georgia
S&Ls in Georgia fared moderately well in the
NOW competition. Customers in Augusta, Atlanta,
Albany, Macon, and Savannah were cautious at
first, but responded well to S&Ls later in the year.
Macon S&Ls scored the strongest gains, picking
up over six percentage points from February
through June.
By July 1, S&Ls in Savannah and Augusta had
captured close to the projected level of market
shares. S&Ls in all other Georgia cities fell significantly short of expectations, with the widest gap
occurring in Macon.
Comparing new second quarter shares with
projections, we found that S&Ls' share of new
N O W balances exceeded projections in all cities
except Atlanta. Second quarter shares were close
to the expected level in Atlanta and Columbus. In

S&L Portion of Total NOW Account Balances —
Georgia (percent)
Actual S&L
Market
Share on
July 1,1981

Projected
S&L Market
Share

S&L Share of
NOW Balances
Added During
Second Quarter

Albany
Atlanta
Augusta
Columbus
Macon
Savannah

11
13
15
13
12
17

27
28
20
20
34
19

43
27
42
24
44
45

Georgia Total State

Albany, Augusta, Macon and Savannah, S&Ls
were doing much better than projected, attracting
over 40 percent of the new N O W balances.

Louisiana
In the cities of Louisiana, market share varied
rather sharply. New Orleans and Alexandria S&Ls
fared reasonably well, with market shares of 13
percent and 11 percent respectively and share
gains of 3 points. Baton Rouge, Lafayette, and
Lake Charles S&Ls, on the other hand, followed
the Low Share/Weak Gain pattern. Lake Charles
and Lafayette had market shares around six
percent, while Baton Rouge's three percent S&L
market share was the lowest in any of the Sixth
District major cities.
As in Georgia and Alabama, Louisiana S&Ls' July
1 shares were markedly short of projected levels.
Comparing actual and projected shares, S&L
performance was relatively strong in Alexandria
and Lafayette and poor in Baton Rouge.
The new second quarter market shares for
Louisiana S&Ls were much higher than July 1
figures, suggesting that S&Ls in Louisiana were
attracting an impressive portion of the new N O W
balances. The higher level of the new shares was
more in line with projected share levels. The new
second quarter shares of Baton Rouge, Lake

S&L Portion of Total NOW Account Balances —
Louisiana

(percent)
Actual S&L
Market
Share1 on
July 1,1981

Alexandria
Baton Rouge
Lafayette
Lake Charles
New Orleans
Louisiana Total State

Projected
S&L Market
Share

S&L Share of
NOW Balances
Added During
Second Quarter

11
3
5
6
13

15
21
13
21
38

26
17
22
20
32

'Sixth District Portion only.

Charles and New Orleans were slightly less than
projected, while S&Ls in Alexandria and Lafayette
almost doubled the projections during the second
quarter.
19

FEDERAL RESERVE B A N K O F ATLANTA

Mississippi
The three metropolitan areas in Mississippi
followed two different patterns. Jackson and Biloxi
had moderate shares but weak gains. The patterns
of these two cities were at slightly different levels,
but the trend was much the same. Pascagoula fell
into the High Share/Weak Gain category,, but
S&Ls there experienced an initial dip in market
share, then a strong increase.
In Mississippi we observe the familiar pattern
of July market shares much lower than expected.
The ranks of Mississippi cities are in the same
order as predicted with the largest S&L share in
Pascagoula and the smallest in Jackson.
New second quarter shares were much higher
than July shares in all three metropolitan areas.
Second quarter shares in Biloxi and Pascagoula
were almost identical to the projected levels.
Jackson S&Ls greatly exceeded projected shares
in the second quarter alone.

Tennessee's five metropolitan areas showed
three different patterns. The highest level of S&L
penetration of the N O W market was in Chattanooga, where S&Ls had high shares but weak
gains. Knoxville and Kingsport S&Ls started moderately but picked up strongly as July approached.
S&Ls in Nashville and Clarkesville had the lowest
levels of S&L market share.
Chattanooga was the only city in the Sixth
District where the actual July S&L market share
exceeded projections. In the other Tennessee
cities July market shares were far below the
projected levels.
The situation brightened for S&Ls in the second
quarter, however, as new shares for all Tennessee
cities exceeded total July 1 shares, again indicating
that S&Ls are picking up steam. In Clarkesville,
Kingsport, and Knoxville, S&Ls' shares of new
balances were much higher than the projected
levels during the second quarter. The greatest
20

S&L Portion of Total NOW Account Balances —
M i s s i s s i p p i (percent)
Actual S&L
Market
Share1 on
July 1,1981

Biloxi Gulfport
Jackson
Pascagoula Moss Point
Mississippi Total State

Projected
S&L Market
Share

S&L Share of
NOW Balances
Added During
Second Quarter

11
8

'Sixth District Portion only.

success in attracting new N O W balances occurred
in Clarkesville, where S&Ls attracted 37 percent
of N O W dollars added during the second quarter.
D E C E M B E R 1981, E C O N O M I C R E V I E W

Conclusion
cities in those states did quite well. Pascagoula
S&Ls, for example, held 21 percent, and Chattanooga S&Ls held a respectable 18 percent of
the N O W balances in their markets.
Although the overall growth of N O W accounts
in the Southeast began to flatten in 1981's
second quarter, S&Ls throughout the region
steadily increased their share of the N O W market
by capturing an impressive portion of new N O W
balances during the second quarter.

We found that as of July 1, S&L shares of the
N O W market were lower than we expected
based on the New England experience with
NOWs. Customers were converting bank checking accounts to N O W accounts within the same
bank in larger numbers than we expected.
O n July 1, S&Ls held 11 percent of the N O W
balances Districtwide. This study, which focused
on market shares in the 43 metropolitan areas of
the Sixth District, found that S&L market shares
varied widely, ranging form three percent in
Baton Rouge to 39 percent in Daytona Beach. As
expected, those cities with
more S&L offices
relative to bank offices had higher S&L market
shares. Interestingly, even in states like Mississippi
and Tennessee where S&Ls had only an eight
percent share of the market, S&Ls in individual

—William N. Cox
and Pamela Van Pelt Whigham

Appendix
Identifying NOW Account Markets
Generally, the competition between banks and
savings and loan associations takes place in
markets which are less than statewide. The
SMSA (Standard Metropolitan Statistical Area) is
the most common definition of each city. For
some purposes, analysts of retail banking
competition have defined markets more narrowly than the SMSAs, which typically comprise
several counties* For other purposes, the
SMSA may be too limited a definition.** The
SMSA definition seems sensible in the case of
NOW accounts, however, because even where
institutions on one side of a market may not
compete directly with ones on the other side,
they were advertising NOW account terms
widely throughout the SMSA and perhaps over
a larger territory. As a result, branching institutions cannot price NOW accounts differently
within the same advertising market. This
advertising may also affect pricing patterns in
counties surrounding the SMSA. In addition to
advertising, another factor may work to expand
markets. As S&Ls begin providing other services

*David D. Whitehead, "Relevant Geographic Banking Markets: How
Should They Be Defined?" Economic review, Federal Reserve Bank
of Atlanta, January/February 1980, pp.20-28.
" A r n o l d A. Heggestad, "Nonlocal Competition for Banking Sen/ices,"
Economic Review, Federal Reserve Bank of Atlanta, August 1981,
pp.21-24.

F E D E R A L RESERVE B A N K O F A T L A N T A

more like those of banks, market concentration
will be reduced in some areas, and banking
markets will expand from sub-SMSA to SMSA.
The SMSA definition of banking markets
presented another problem, particularly in Florida. Some institutions, particularly S&Ls, are
headquartered within one city and report their
NOW balances to the Fed as one institution
located there, whereas in fact their report
includes NOW balances from branches outside
that city and in some cases across the state. In
these cases, some adjustments were necessary
to accurately reflect NOW balances actually
held in home offices and branch offices within
the SMSA. After some testing by telephone,
and recognizing again that NOWs are a new
product and that most checking account customers prefer to open their accounts in person and
have a physical office close enough to visit if
anything goes wrong, we therefore allocated
the NOW balances in multicity institutions according to the distribution of their branches.
Based on our survey, we also assumed that
when the home office is in a SMSA, the
branches in non-SMSA areas have balances
approximately 50 percent of the amounts in
metropolitan branches. For banks, we distributed the balances among branches in the same
proportion as demand deposits.

LEGEND
BIR-Birmingham
GAD-Gadsden
ANI-Anniston
FLO-Florence
MOB-Mobile
TUS-Tuscaloosa
HUN-Huntsville
MON-Montgomery
ALE-Alexandria
LAF-Lafayette
BAT-Baton Rouge
NEW-New Orleans
LAC-Lake Charles
BIL-Biloxi-Gulfport
JAC-Jackson
PAS-PascagoulaMoss Point
ATL-Atlanta
ALB-Albany
COL-Columbus
AUG-Augusta
MACMacon
SAV-Savannah

CHA-Chattanooga
KIN-Kingsport-Bristol
CLA-Clarkesville-Hopkinsville
KNO-Knoxville
NAS-Nashville-Davidson
DAV-Daytona Beach
PAN-Panama City
PEN-Pensacola
JAK-Jacksonville
TAL-Tallahassee
ORL-Orlando
MEL-Melbourne-Titusville-Cocoa
GAI-Gainesville
LAK-Lakeland-Winter Haven-Bartow
FTL-Fort Lauderdale-Hollywood
WPB-West Palm Beach-Boca Raton
MIA-Miami
BRA-Bradenton
TAM-TampaSt. Petersburg
SAR-Sarasota
FTM-Fort Myers

S&L NOW Market Share
já

25 —

Mobile S&Ls had state's
best NOW share.
% — 25

20 —

MOB

New Orleans S&Ls
showed strong growth.
25 — %

— 25

— 20

20 —

— 20

— 15

15 —

— 15

BIR
TUS
HUN
MON

o I—I—I—I—I—L
F

M A M J

I I I

M A M J

D E C E M B E R 1981, E C O N O M I C R E V I E W

S&Ls in Mississippi
picked up pace in
second quarter.

S&L share high in
Chattanooga, low in
Nashville.

CHA

— 15

15 —

25 —

KIN
KNO

— 10

NAS

— 5

20 —

CLA
15 —

101 I I I I
F

M A M J

Ol
F

M A M J

^v^A
Y\
V

Macon, Savannah S&Ls
scored rapid gains.

I I I I

M A M J

Daytona S&Ls were
Region's leaders in
NOW shares.

40 —

20 —

DAY

— 15

LAK

MAC

I I I

MIA
20

5 —

I I—I—L

M A M J

I 1 I 1 I

M A M J

BRA
TAM
SAR

—

151

— 25

—

FTM

o L_J

FTL
WPB

25 —

10 —

I I I I I15

M A M J

23
FEDERAL RESERVE BANK OF ATLANTA

Southeastern Pork Production:
A Clue to Future Food Price Changes?
Feed costs for pork producers are significantly higher in the Southeast than in the
Midwest Historically, the Southeast has not been a major pork producing area, but
when losses begin, southeastern producers have tended to cut production earlier
than their midwestern counterparts, a characteristic that could provide an early
indication of a reduction in national pork output
Food prices frequently have been a leading
source of inflation in the consumer price index
in recent years. The largest single food group in
the consumer food price series is the category
of meats and related products. Meats, poultry,
and fish account for about 22 percent of the
total consumer food price index. Since 1975,
month-to-month changes in the price index of
meats, poultry, and fish have explained 75 percent of the comparable changes in the index of
finished consumer food prices (see Table 1).
Meats and related products, then, have been
responsible for a major share of the volatility in
finished consumer food prices since 1975.
Changes in wholesale prices of meats, poultry, and fish are, in turn, heavily dependent on
variations in hog prices. Since 1975, month-tomonth changes in the index of prices received
for hogs have explained 43 percent of the comparable changes in the price index of the meat
group (see Table 1). The relationship with hog
prices was stronger than with either cattle or
poultry prices, the other major components of
the group. Thus, movements in hog prices
should give useful indications of price changes

in meats and related products which, in turn,
govern the majority of fluctuations in finished
consumer food prices.
Price changes for meats occur primarily in
response to changes in supply. Pork output,
although accounting for between 30 and 40
percent of total red meats, is responsible for a
disproportionate share of the volatility in total
meat supplies. Changes in pork production
occur more frequently and with sharper movements than changes in beef output. Since pork
production is a prime determinant of changes
in meat prices, prospective hog marketings and
inventory numbers are watched closely for
clues to upcoming price movements.
Farmers make their decisions to produce
hogs based on their evaluations of profit prospects. Profits are dependent on the relationship
between hog prices and production costs, and
feed is the largest single cost, accounting for
approximately half the cost of producing hogs
to usual market weights of 220 pounds. The
exact proportion may vary from 45 to 55 percent
depending upon the system of production and
fluctuations in prices of feed ingredients as well

DECEMBER 1981, E C O N O M I C REVIEW

Table 1
Statistical Analysis of Food Price Components
Dependent Independent Regression
Variable
Variable
Coefficient

t
Value

0.0228

14.29**

0.755'

0.0969

7.04**

0.429"

0.1471

6.32**

0.377'

0.0869

5.67**

0.327'

in approximately the same pattern as the majority of producers. The major observable difference would be a proportionately greater
volatility of supply in areas of marginal profitability.

= month-to-month changes in the index of finished consumer food
prices for January 1975 through August 1980.

= month-to-month changes in the index of wholesale prices of
meats, poultry, and fish from January 1975 through August 1980.

A2 = month-to-month changes in the index of prices received for hogs
from January 1975 through August 1980.
A, = month-to-month changes in the index of prices received for cattle
from January 1975 through August 1980.
A3 = month-to-month changes in the index of prices received for
poultry from January 1975 through August 1980.
"Indicates significance at or above the 99-percent level of probability.

as other inputs. The major cost other than feed
is the initial outlay for the feeder pig, which
typically accounts for around one-third of total
production costs.
Feed costs are the source of most of the
volatility of hog production costs since the
price of feeder pigs is also influenced by feed
expenses. Thus, changes in feed costs are a
major determinant of shifts in profitability of
hog production and of the quantity of pork
produced.
Pork producers for whom feed costs are
higher than usual and/or who receive lower
prices for hogs than the majority of producers
would likely be most sensitive to increases in
costs of feed or declines in prices of hogs. In
other words, the producers at the margin
would be expected to cut their production first
and by the greatest relative amount when
profits shrink or disappear. By contrast, they
should be the last to expand output when
returns grow more favorable because of the
greater risk of failure suffered by marginal producers when conditions turn unfavorable
again. If, however, marginal producers assess
risk of failure in the same way as all other
producers, they would expand hog production

Comparisions between the
Southeast and Iowa
The following analysis compares selected
data on hog production in the Southeast with
comparable series in Iowa, the major porkproducing state, to determine (1) if the Southeast is a marginal area of production, (2) if hog
production in the Southeast follows patterns
that would be expected in a marginal area, and
(3) if southeastern production is a reliable early
indicator of changes in total pork output.
Feed Costs
The southeastern region is an area of deficit
production of feed concentrates. Livestock
feeders in the states of the Sixth Federal
Reserve District must import significant proportions of feed requirements from other regions.
Thus, feed costs in the District would be
expected to exceed those in the Midwest, at
least by the amount of the cost of transporting
feed to the Southeast.
An examination of average prices paid for
feed ingredients by farmers in the Southeast
compared with those in Iowa reveals expected

Chart 1. Prices Paid for Corn Meal

25
FEDERAL RESERVE BANK OF ATLANTA

differences (see Table 2 and Charts 1 and 2).
C o r n meal prices in Sixth District states
averaged $2.41 per cwt. higher than prices in
Iowa during the six-year period from 1975
through 1980. Soybean meal prices in District
states averaged $0.81 per cwt. higher than in
Iowa during the same period. The probability
that differences this large could occur through
chance alone is less than one in one thousand
for corn meal and less than two in a hundred for
soybean meal. The greater relative difference
between prices of corn meal in the two areas
would be expected because the Southeast
produces a greater proportion of the soybean
meal it uses than of the corn meal. O n balance,
statistical analysis confirms that hog producers
in the Southeast pay significantly higher prices
for feed ingredients than do producers in Iowa.
Hog Prices
The relatively small number of hogs produced in District states (less than 10 percent of
the nation's supply) compared with major producing areas would lead one to expect differences in prices received by farmers in the
District as compared with Iowa. To the extent
that slaughtering plants are smaller and less
specialized in southeastern states, they would
not be expected to pay as much for hogs as
larger more efficiently operated plants in areas
of more concentrated hog production.
An analysis of average prices for market hogs
for the period of 1975 to 1980 reveals a slightly

Chart 2. Prices Paid for Soybean Meal:
44% Protein

Table 2
Statistical Comparisons of Selected Data
on Hog Production

Average

Standard
Deviation

Standard
Error of
Difference
Between
Means

Calculated
t

Corn Meal Prices ($ per cwt.)
District States $ 7.40
.651
Iowa
4.99
.632

.107

22.53*

Soybean Meal Prices ($ per cwt.)
District States
11.87
2.04
Iowa
11.06
1.95

.332

2.44*

Hog Prices ($ per cwt.)
District States
42.15
Iowa
43.01

6.39
6.63

1.085

0.793

"Indicates significance at or above the 98 percent level.

higher average price received by Iowa producers than District producers, but the difference is not statistically significant (see Table 2
and Chart 3). Thus, differences in relative
returns to hog producers in District states and
in Iowa would be attributable largely to differences in production costs between the two
areas rather than in the market prices received.

Chart 3. Prices Received for Hogs

D E C E M B E R 1981, E C O N O M I C R E V I E W

SCUMPtÊiragKïïr

FINANCE
OCT
1981
mnTF.n STATES
Commercial Bank Deposits
NOW
Credit Union Deposits
sniTTHRAST
Commercial Bank Deposits
NOW
Credit Union Deposits
ÀT.ARAMA
Commercial Bank Deposits
NOW
Credit Union Deposits
Savings & Time
PI .ORTI) A
Commercial Bank Deposits
NOW

SEPT
1981

DEC
1980

1,071,259 1,051,211 1,017,230
299,299 287,196 331,626
0
47,799 45,311
149,465 150,158 166,274
605,334 594,907 526,103
38,965 37,554 34,870
2,267
1,641
2,438
34,429 33,061 30,093
114,351 112,288 107,549
34,339 33,029 39,157
0
6,016
5,749
14,716 14,765 16,578
,63,018 61,662 53,704
3,209
3,704
3,534
244
192
264
3,061
2,797
3,204
13,112 12,903 12,280
3,972
3,499
3,280
0
529
509
1,754
1,557
1,565
7,844
6,746
8,008
551
521
570
41
53
48
479
494
510
37,589 37,034 36,141
12,394 11,875 14,577
0
2,612
2,504
6,332
7,333
6,321
17,349 17,143 14,471
1,491
1,602
1,684
139
106
145
1,177
1,322
1,253
15,730 15,151 14,550
5,758
6,793
5,942
0
882
836
1,683
1,592
1,585
7,912
7,011
8,291
543
689
711
12
21
19
517
659
673

ANN.
RATE
OF
CHG.
+7
-13
-13
+20
+15
+63
+19
+8
-16
-15
+23
+20
+49
+19
+9
-16
-15
+24
+12
+38
+8
+5
-20
-18
+26
+17
+48
+16
+11
-16
- 7
+24
+40
+98
+39
+13
-10
- 7
+25
+87
+98
+90

OCT
1981
Savings 5c Loans
Total Deposits
NOW
Savings
Time
Mortgages Outstanding
Mortgage Commitments
Savings & Loans
Total Deposits
NOW
Savings
Time
Mortgages Outstanding
Mortgage Commitments
Savings & Loans
Total Deposits
NOW
Savings
Time
Mortgages Outstanding
Mortgage Commitments
Savings & Loans
Total Deposits
NOW
Savings
Time
Mortgages Outstanding
Mortgage Commitments
Savings & Loans
Total Deposits
NOW
Savings
Time
Mortgages Outstanding
Mortgage Commitments
Savings & Loans
Total Deposits
NOW
Savings
Time
Mortgages Outstanding
Mortgage Commitments

SEPT
1981

DEC
1980

513,403 508,821 500,985
0
6,680
7,378
92,920 93,635 104,240
394,288
414,190 408,249
DEC
AUG
JUL
508,812 507,531 494,179
16,735 17,104 16,021
75,483
1,138
11,765
62,628
AUG
74,256
3,495

74,937
1,025
11,765
62,035
JUL
74,069
3,509

72,600
0
13,165
58,912
DEC
71,065
3,652

4,372
60
580
3,761
AUG
4,008
76
.
45,617
794
7,860
36,872
AUG
45,272
2,991

4,339
53
595
3,710
JUL
4,001
101

4,265
0
690
3,575
DEC
3,947
136

45,369
718
7,821
36,648
JUL
45,155
2,933

43,996
0
8,774
34,698
DEC
42,742
2,984

ANN.
RATE
OF
CHG.
-14
+7
+7
+5
-14
+8
- 6
-21
+7
-66
-14

+ 9
Share Drafts
+0
Savings 5c Time
GE
Commercial Bank Deposits
+ 6
9,237
9,688
9,563
Demand
107
0
120
NOW
-19
1,398
1,221
1,197
Savings
+ 9
7,835
8,402
8,255
Time
DEC
AUG
JUL
Credit Union Deposits
+ 2
9,332
9,476
9,475
Share Drafts
-41
183
140
133
Savings & Time
LOUISIANA
Commercial Bank Deposits
20,594 20,300 18,690
+9
7,215
6,865
7,330
Demand
5,982
5,856
6,461
0
62
69
NOW
808
776
0
1,257
- 7
1,194
1,193
Savings
2,385
2,395
2,529
+11
5,617
6,104
5,973
Time
12,064 11,755 10,093
DEC
JUL
AUG
Credit Union Deposits
95
95
57
+ 7
7,041
6,777
7,080
Share Drafts
7
6
4
221
-14
224
201
Savings & Time
88
88
52_
MISSISSIPPI
9,398
9,331
8,759
+10
Savings & Loans
Commercial Bank Deposits
+2
2,332
2,387
2,375
2,340
2,240
2,639
-15
Total Deposits
Demand
0
26
30
444
426
0
NOW
NOW
-14
262
236
234
723
733
842
-18
Savings
Savings
+4
2,132
2,067
2,125
Time
6,207
6,143
5,451
+18
Time
DEC
JUL
AUG
N.A.
N.A.
N.A.
Credit Union Deposits
+ 2
2,182
2,205
2,210
N.A.
N.A.
N.A.
Mortgages Outstanding
Share Drafts
58
-88
34
24
N.A.
N.A.
N.A.
Mortgage Commitments
Savings & Time
Savings <5t Loans
17,928 17,570 17,128
+6
Commercial Bank Deposits
+4
6,064
5,904
6,101
Total Deposits
-15
4,716
4,021
4,182
Demand
59
0
65
NOW
0
697
739
NOW
784
-14
699
699
Savings
-16
2,155
2,437
2,139
Savings
5,317
5,120
+ 6
5,364
Time
9,931 +15
11,099 10,865
Time
DEC
JUL
AUG
597
597 +10
644
Credit Union Deposits
+ 3
6,208
6,085
6,211
32
+40
Mortgages Outstanding
29
38
Share Drafts
70
0
77
+
9
567
70
572
611
Mortgage Commitments
Savings ¿c Time
Notes: All deposit data are extracted from the Federal Reserve Report of Transaction Accounts, other Deposits and Vault Cash (FR2900),
and are reported for the average of the week ending the 1st Wednesday of the month. This data, reported by institutions with
over $15 million in deposits as of December 31, 1979, represents 95% of deposits in the six state area. The annual rate of change
is based on most recent data over December 31, 1980 base, annualized. Savings and loan mortgage data are from the Federal
Home Loan Bank Board Selected Balance Sheet Data. The Southeast data represent the total of the six states. Subcategories were
chosen on a selective basis and do not add to total.
N.A. = fewer than four institutions reporting.
1

December 1981, E C O N O M I C

REVIEW

Federal Reserve Bank of Atlanta

EMPLOYMENT
SEPT
1981

AUG (R)
1981

SEPT
1980

Civilian Labor Force - thous.
Total Employed - thous.
Total Unemployed - thous.
Unemployment Rate - % SA
Insured Unemployment - thous.
Insured Unempl. Rate - %
Mfg. Avg. Wkly. Hours
Mfg. Avg. Wkly. Earn. - $
Civilian Labor Force - thous.
Total Employed - thous.
Total Unemployed - thous.
Unemployment Rate - % SA
Insured Unemployment - thous.
Insured Unempl. Rate - %
Mfg. Avg. Wkly. Hours
Mfg. Avg. Wkly. Earn. - $
ALABAMA
Civilian Labor Force - thous.
Total Employed - thous.
Total Unemployed - thous.
Unemployment Rate - % SA
Insured Unemployment - thous.
Insured Unempl. Rate - %
Mfg. Avg. Wkly. Hours
Mfg. Avg. Wkly. Earn. - $

105,964
98,277
7,687
7.5
N.A.
N.A.
39.3
320
13,138
12,100
1,038
8.1
N.A.
N.A.
39.9
280

107,771
100,013
7,758
7.2
2,725
3.1
39.8
319
13,977
11,334
977
7.8
273
2.8
40.4
282

104,720
97,256
7,464
7.4
3,123
3.6
39.8
295
12,786
11,867
918
7.5
309
3.2
40.3
258

1,626
1,466
159
9.5
N.A.
N.A.
40.1
289

17626
1,473
152
9.4
46
3.6
40.3
284

1,653
1,502
151
9.4
58
4.6
40.1
262

4,135
3,803
332
7.3
N.A.
N.A.
39.7
267

4,178
3,899
278
6.4
67
1.9
40.4
269

3,905
3,632
273
6.5
70
2.1
41.0
252

ANN.

SEPT
1981

CHG.

SEPT
1980

92,026
20,665
4,495
20,912
15,426
18,795
5,351
5,215
11,471
2,317
720
2,627
2,165
2,161
643
687
1,348
358
70
272
292
209
58
71

91,626
20,486
4,575
20,820
15,153
18,841
5,408
5,173
11,896
2,308
733
2,628
2,082
2,151
628
688
173 45
357
70
272
290
208
59
72

90,638
20,212
4,613
20,495
15,841
18,087
5,201
5,159

Nonfarm Employment- thous.
3,737
Manufacturing
474
+22
Construction
278
Trade
970
Government
634
Services
883
- 3
Fin., Ins., & Real Est.
286
+ 6
Trans. Com. & Pub. Util.
223
2,463
2,462
+ 2
2,405
Nonfarm Employment- thous.
2,163
2,312
2,315
2,247
+ 3
Manufacturing
524
151
147
158
- 4
Construction
99
6.3
5.7
6.7
Trade
487
N.A.
46
51
Government
, 429
N.A.
2.2
2.5
Services
360
39.5
40.3
40.2
- 2
Fin., Ins., & Real Est.
114
255
257
238
Trans. Com. & Pub. Util.
142
+7
Civilian Labor Force - thous.
1,803
1,793
1,759
+ 3
Nonfarm Employment- thous.
1,648
Total Employed - thous.
1,659
1,644
1,643 + 1
Manufacturing
217
Total Unemployed - thous.
144
150
116
+24
Construction
159
Unemployment Rate - % SA
8.2
8.5
6.9
Trade
367
Insured Unemployment - thous.
N.A.
38
34
Government
322
Insured Unempl. Rate - %
N.A.
2.5
2.4
Services
285
Mfg. Avg. Wkly. Hours
41.4
41.8
4l!o
+ 1
Fin., Ins., & Real Est.
76
Mfg. Avg. Wkly. Earn. - $
358
358
325
+10
Trans. Com. & Pub. Util.
128
Civilian Labor Force - thous.
1,019
1,300
1,037
Nonfarm Employment- thous.
844
Total Employed - thous.
935
920
961
- 3
Manufacturing
220
Total Unemployed - thous.
83
85
77
+10
Construction
42
Unemployment Rate - % SA
8.4
7.8
Trade
167
Insured Unemployment - thous.
28
30
N.A.
Government
189
Insured Unempl. Rate - %
3.6
3.8
N.A.
Services
123
Mfg. Avg. Wkly. Hours
39.5
40.0
39.3
Fin., Ins., & Real Est.
33
237
Avg. Wkly. Earn. - $
222
239
Trans. Com. & Pub. Util.
41
Civilian Labor Force - thous.
2,092
2,078
2,026
+ 3
Nonfarm Employment- thous.
1,731
Total Employed - thous.
1,925
1,911
1,882
+ 2
Manufacturing
524
Total Unemployed - thous.
168
167
144
+17
Construction
73
Unemployment Rate - % SA
8.7
8.4
7.7
Trade
365
Insured Unemployment - thous.
N.A.
48
67
Government
299
Insured Unempl. Rate - %
N.A.
2.9
4.0
Services
301
Mfg. Avg. Wkly. Hours
39.6
39.8
39.7
0
Fin.,
Ins.,
&
Real
Est.
76
Mfg. Avg. Wkly. Earn. - $
272
287
247
+10
Trans. Com, ic Pub. Util.
82
Notes: AU labor force data are from Bureau of Labor Statistics reports supplied by state agencies.
Only the unemployment rate data are seasonally adjusted.
The Southeast data represent the total of the six states.
The annual percent change calculation is based on the most recent data over prior year. R = revised.
N. A. = not available.

3,706
472
287
971
593
879
268
224
2,156
520
100
488
425
360
115
142

3,558
456
278
935
609
811
255
217
2,148
515
104
496
428
346
113
139

1,635
216
159
365
310
284
76
129

1,588
214
148
357
307
272
75

- 1
+ 3
+ 2
+13
- 1
+ 9
-

- 2

+ 5
0

+10

+ 6
+ 5

Nonfarm Employment- thous.
Manufacturing
Construction
Trade
Government
Services
Fin., Ins., ¿c Real Est.
Trans. Com. & Pub. Util.
Nonfarm Employment- thous.
Manufacturing
Construction
Trade
Government
Services
Fin., Ins., & Real Est.
Trans. Com. & Pub. Util.
Nonfarm Employment- thous.
Manufacturing
Construction
Trade
Government
Services
Fin., Ins., & Real Est.
Trans. Com. & Pub. Util.

AUG (R)
1981

811

220

42
167
178
120
33
41
1,720
523
75
366
287
300
77
81

ANN.
%
CHG.
+2
+2
- 3
+2
- 3
+4
+3
+ 1
+2
+3
-1
+1
+ 1
+5
+ 5
+ 1

11,201

2,258
728
2,598
2,145
2,049
612
680

1,3 5 0
354
74
273
296
206
59
71

+
+

0
1
5
0
1
1

- 2

0
+5
+4
0
+4
+4
+9
+12
+ 3
+ 1
+ 2
- 5
+ 0
+4
+ 1
+ 2
-

126

829
219
46
165
194
121
33
41
1,727
500
78
373
311
292
78
86

+ 2
+ 0
- 9
+ 1
- 3
+ 2
0
0
+ 0
+ 5
-

4
3
3
5

+
-

December 1981, ECONOMIC REVIEW

CONSTRUCTION

12-Month Cumulative Rate
UNITED STATES
Total Construction Contracts
Value - $ mil.
Nonresidential Contracts
Value - $ mil.
Sq. Ft. - mil.
Nonbuilding Contracts
Value - $ mil.
SOUTHEAST
Total Construction Contracts
Value - $ mil.
Nonresidential Contracts
Value - $ mil.
Sq. Ft. - mil.
Nonbuilding Contracts
Value - $ mil.
ALABAMA
Total Construction Contracts
Value - $ mil.
Nonresidential Contracts
Value - $ mil.
Sq. Ft. - mil.
Nonbuilding Contracts
Value - $ mil.
FLORIDA
Total Construction Contracts
Value - $ mil.
Nonresidential Contracts
Value - $ mil.
Sq. Ft. - mil.
Nonbuilding Contracts
Value - $ mil.
GEORGIA
Total Construction Contracts
Value - $ mil.
Nonresidential Contracts
Value - $ mil.
Sq. Ft. - mil.
Nonbuilding Contracts
Value - $ mil.
LOUISIANA
Total Construction Contracts
Value - $ mil.
Nonresidential Contracts
Value - $ mil.
Sq. Ft. - mil.
Nonbuilding Contracts
Value - $ mil.
MISSISSIPPI
Total Construction Contracts
Value - $ mil.
Nonresidential Contracts
Value - $ mil.
Sq. Ft. - mil.
Nonbuilding Contracts
Value - $ mil.
TENNESSEE
Total Construction Contracts
Value - $ mil.
Nonresidential Contracts
Value - $ mil.
Sq. Ft. - mil.
Nonbuilding Contracts
Value - $ mil.

SEPT
1981

AUG
1981

ANN.
%
CHG.

SEPT
1980

152,969 153,394 145,887
58,366 57,608 50,229
I., 203.8 1,208.9 1,208.9
28,664 28,321 34,419

5
+ 16
- 0
17

Residential Contracts
Value - $ mil.
Number of Units - Thous.
Residential Permits - Thous.
Number single-family
Number multi-family

7
22
7
18

Residential Contracts
Value - $ mil.
Number of Units - Thous.
Residential Permits - Thous.
Number single-family
Number multi-family

4
14
- 19
24

Residential Contracts
Value - $ mil.
Number of Units - Thous.
Residential Permits - Thous.
Number single-family
Number multi-family

6
32
17
39

Residential Contracts
Value - $ mil.
Number of Units - Thous.
Residential Permits - Thous.
Number single-family
Number multi-family

8
0
1
13

Residential Contracts
Value - $ mil.
Number of Units - Thous.
Residential Permits - Thous.
Number single-family
Number multi-family

11
24
38
19

Residential Contracts
Value - $ mil.
Number of Units - Thous.
Residential Permits - Thous.
Number single-family
Number multi-family

27,065
8,551
194.7
4,870

26,929
8,449
196.4
4,466

25,218
7,036
182.6
5,918

1,778
499
11.9
347

1,772
507
12.2
304

1,850
582
14.7
458

13,156
3,750
92.4
1,630

13,221
3,675
92.1
1,564

12,464
2,844
79.2
2,651

4,082
1,245
34.5
946

3,874
1,272
35.7
637

3,775
1,242
35.0
839

3,647
1,376
24.8
888

3,574
1,309
24.3
892

3,287
1,107
18.0
1,095

1,724
620
7.6
521

1,773
630
7.9
526

1,161
303
9.0
299

48
+105
16
+ 74

Residential Contracts
Value - $ mil.
Number of Units - Thous.
Residential Permits - Thous.
Number single-family
Number multi-family

2,678
1,062
23.6
537

2,714
1,056
24.1
543

2,680
959
26.8
575

- 0
+ 11
- 12
7

Residential Contracts
Value - $ mil.
Number of Units - Thous.
Residential Permits - Thous.
Number single-family
Number multi-family

+
+
-

+
+
+
-

+
-

+
+
+

SEPT
1981

AUG
1981

SEPT
1980

ANN.
%
CHG.

65,939
1,277.2

67,465
1,320.6

61,168
1,321.6

+ 8
- 3

642.5
459.6

681.1
482.4

709.0
470.6

- 9
- 2

13,644
299.7

14,013
311.6

12,264
299.9

+ 11
- 0

139.5
118.9

148.5
126.6

151.0
113.1

- 8
+ 5

931
24.5

962
25.6

810
23.0

+ 15
+ 7

7.1
8.0

7.6
8.0

8.3
6.3

- 14
+ 27

7,776
169.7

7,981
175.6

6,970
168.8

+ 12
+ 1

84.2
85.0

89.8
89.4

86.9
78.4

- 3
+ 8

1,891
41.6

1,965
44.2

1,694
42.6

+ 12
- 2

23.8
9.3

25.2
9.8

26.5
8.1

- 10
+ 15

1,384
27.1

1,373
27.6

1,085
23.6

+ 28
+ 15

10.9
9.1

11.5
9.1

11.7
7.5

- 7
+ 21

583
13.5

617
14.5

559
14.3

+ 4
- 6

4.1
3.0

4.5
3.7

4.8
3.9

- 15
- 23

1,079
23.3

1,115
24.3

1,146
27.5

- 6
- 15

9.3
4.5

10.0
6.6

12.7
8.7

- 27
- 48

Notes: Contracts are calculated from the F. W. Dodge Construction Potentials. Permits are calculated1 from the Bureau of the Census,
Housing Units Authorized By Building Permits and Public Contracts. The Southeast data represent the total of the six states. The
annual percent change calculation is based on the most recent month over prior year.

Federal Reserve Bank

of Atlanta

GENERAL
SEPT
1981

ANN.
%
CHG.

AUG
1981

SEPT
1980

2,292.5
88.6
N.A.
8,638.7

2,088.5
80.6
N.A.
8,596.4

276.5

251.7

266.8
N.A.
4,148.5
1,425.8
N.A.

239.9
N.A.
3,443.4
1,522.1
N.A.

+ 14

31.4
N.A.
99.9
60.5
N.A.

31.1
N.A.
111.3
60.5
N.A.

28.3
N.A.
112.2
55.0
N.A.

+11
-11
+10

Personal Income-$ bil. SAAR
98.3
(Dates: 2Q, 1Q, 2Q)
65,301
Taxable Sales - $ mil.
Plane Passenger Arrivals (thous.) 1,425.3
97.4
Petroleum Prod, (thous. bis.)
SEPT
Consumer Price Index - Miami
150.2
Nov. 1977 = 100

95.3
64,759
1,889.8
98.0

84.7
56,466
1,451.3
114.6

+16
+16
- 2
-15

146.1

133.1

+13
+13

276.1

42.2
N.A.
1,462.0
N.A.
OCT
250.2

38.1
N.A.
265.3
1,172.0

34.0
N.A.
244.2
1,254.0

+15
- 3
- 7

N.A.

17.7
N.A.
32.1
95.4
N.A.

17.4
N.A.
33.5
95.3
N.A.

16.0
N.A.
34.0
98.5
N.A.

+11
- 6
- 3

38.8
N.A.
135.6
N.A.
N.A.

38.1
N.A.
135.6
N.A.
N.A.

35.0
N.A.
139.7
N.A.

+11

Personal Income-$ bil. SAAR
2,340.5
(Dates: 2Q, IQ, 2Q)
88.5
N.A.
Plane Passenger Arrivals (thous.)
8,640.2
Petroleum Prod, (thous. bis.)
279.3
1967=100

+12
+10
+ 1
+11

SOUTHEAST

Personal Income-$ bil. SAAR
(Dates: 2Q, IQ, 2Q)

272.8
N.A.
Plane Passenger Arrivals (thous.) 3,383.3
1,421.3
Petroleum Prod, (thous. bis.)
N.A.
1967=100

- 2
- 7

AT,ARAMA

Personal Ineome-$ bil. SAAR
(Dates: 2Q, 1Q, 2Q)
Taxable Sales - $ mil.
Plane Passenger Arrivals (thous.)
Petroleum Prod, (thous. bis.)
Consumer Price Index
1967=100
FI.ORTOA

JUL

SEPT

GEORGIA

Personal Income-$ bil. SAAR
47.6
(Dates: 2Q, 1Q, 2Q)
N.A.
Taxable Sales - $ mil.
Plane Passenger Arrivals (thous.) 1,454.2
N.A.
Petroleum Prod, (thous. bis.)
OCT
Consumer Price Index - Atlanta
281.5
1967 = 100
LOUISIANA
Personal Income-$ bil. SAAR
(Dates: 2Q, 1Q, 2Q) 39.1
Taxable Sales - $ mil.
N.A.
Plane Passenger Arrivals (thous.) 237.1
Petroleum Prod, (thous. bis.)
1,168.0
Consumer Price Index
1967 = 100
N.A.

46.8
N.A.
1,641.5
N.A.
AUG

- 1
+ 13

MISSISSIPPI

Personal Income-$ bil. SAAR
(Dates: 2Q, 1Q, 2Q)
Plane Passenger Arrivals (thous.)
Petroleum Prod, (thous. bis.)
Consumer Price Index
1967 = 100
TENNESSEE
Personal Income-$ bil. SAAR
(Dates: 2Q, 1Q, 2Q)
Taxable Sales - $ mil.
Plane Passenger Arrivals (thous.)
Petroleum Prod, (thous. bis.)
Consumer Price Index
1967 = 100

N.A.

- 3

SEPT
1981
Agriculture
Prices Rec'd by Farmers
145.0
Index (1977=100)
Broiler Placements (thous.) 77,721
63.30
Calf Prices ($ per cwt.)
26.8
Broiler Prices (<t per lb.)
6.29
Soybean Prices ($ per bu.)
Broiler Feed Cost ($ per ton) 222
Agriculture
Prices Rec'd by Farmers
117.5
Index (1977=100)
Broiler Placements (thous.) 30,723
58.08
Calf Prices ($ per cwt.)
25.8
Broiler Prices (<t per lb.)
6.43
Soybean Prices ($ per bu.)
Broiler Feed Cost ($ per ton) 219

AUG
1981

SEPT
1980

ANN.
%
CHG.

145.0
77,751
62.40
29.2
6.71
225

150.0
73,635
75.60
32.1
7.69
222

- 3
+6
-16
-17
-18
0

125.8
31,579
57.37
28.5
6.92
219

132.0
28,875
70.53
32.8
7.89
215

-11
+6
-18
-21
-19
+2

48,881
54.00
27.5
6.61
235

868
38,383
66.20
31.5
7.92
235

+8
+2
-22
-10
-20
0

9,530
58.30
28.5
6.61
240

3,007
6,717
75.20
32.0
7.92
225

- 3
+7
-17
-20
-20
+2

60,311
53.20
28.0
6.80
205

1,202
44,409
66.00
32.5
7.79
205

+15
+11
-15
-22
-19
+ 2

680
N.A.
60.60
27.0
6.52
245

N.A.
59.00
30.2
7.14
245

700
N.A.
69.00
34.0
7.99
225

"3
-12
-21
-18
+ 9

Agriculture
Farm Cash Receipts - $ mil.
1,032
(Dates: JUL, JUL)
Broiler Placements (thous.) 22,296
60.50
Calf Prices ($ per cwt.)
2.75
Broiler Prices ($ per lb.)
6.45
Soybean Prices ($ per bu.)
Broiler Feed Cost ($ per ton) 205

28,940
64.00
31.0
7.02
210

986
20,940
68.70
36.0
7.84
199

+ 5
+6
-12
-92
-18
+ 3

6,962
55.00
27.0
7.02
199

797
5,049
75.60
29.0
7.87
210

+ 4
+0
-25
-14
-18
- 7

Agriculture
Farm Cash Receipts - $ mil.
940
(Dates: JUL, JUL)
Broiler Placements (thous.) 39,080
51.50
Calf Prices ($ per cwt.)
28.5
Broiler Prices (<t per lb.)
6.32
Soybean Prices ($ per bu.)
Broiler Feed Cost ($ per ton) 235
Agriculture
Farm Cash Receipts - $ mil.
2,905
(Dates: JUL, JUL)
Broiler Placements (thous.) 7,201
62.30
Calf Prices ($ per cwt.)
25.5
Broiler Prices (<t per lb.)
6.32
Soybean Prices ($ per bu.)
Broiler Feed Cost ($ per ton) 230
Agriculture
Farm Cash Receipts - $ mil.
1,388
(Dates: JUL, JUL)
Broiler Placements (thous.) 49,250
56.40
Calf Prices ($ per cwt.)
25.5
Broiler Prices (<t per lb.)
6.34
Soybean Prices ($ per bu.)
Broiler Feed Cost ($ per ton) 210
Agriculture
Farm Cash Receipts - $ mil.
(Dates: JUL, JUL)
Broiler Placements (thous.)
Calf Prices ($ per cwt.)
Broiler Prices (4 per lb.)
Soybean Prices ($ per bu.)
Broiler Feed Cost ($ per ton)

Agriculture
Farm Cash Receipts - $ mil.
(Dates: JUL, JUL)
Broiler Placements (thous.)
Calf Prices ($ per cwt.)
Broiler Prices (4 per lb.)
Soybean Prices ($ per bu.)
Broiler Feed Cost ($ per ton)

829
5,066
57.00
25.0
6.45
195

Notes:
Personal Income data supplied by U. S. Department of Commerce. Taxable Sales are reported as a 12-month cumulative total. Plane
Passenger Arrivals are collected from 26 airports. Petroleum Production data supplied by U. S. Bureau of Mines. Consumer Price
Index data supplied by Bureau of Labor Statistics. Agriculture data supplied by U. S. Department of Agriculture. Farm Cash
Receipts data are reported as cumulative for the calendar year through the month shown. Broiler placements are an average weekly
rate. The Southeast data represent the total of the six states. N.A. = not available. The annual percent change calculation is based
on most recent data over prior year.

December 1981, ECONOMIC REVIEW

Net Returns Differ
Differences in feed costs between Sixth District states and the Midwest would account for
substantial differences in net returns to producers in the two areas, even though prices
received for hogs do not differ appreciably.
Because of the higher cost structure and lower
net returns in the Southeast, hog producers
would be expected to respond more slowly to
rising hog prices than their midwestern counterparts. Or, hog prices would need to rise
further and continue high for a longer period to
induce production expansion in the Southeast.
O n the other hand, when hog prices fall, southeastern producers would be expected to experience net losses more quickly than midwestern
producers and begin reducing production
more rapidly as a consequence.
Fluctuations in Hog Slaughter
Although periodic surveys are made of hog
producers' intentions, actual production sometimes deviates sharply from reported intentions. Monthly slaughter data are the most solid
information available on actual production by
state. Although hogs are shipped across state
borders for slaughter, on balance, the shipments are assumed to be largely offsetting so
that numbers slaughtered are a reasonably reliable indication of production, especially within
a relatively broad area such as the six states of
the Sixth Federal Reserve District.
From January 1975 through December 1980,
monthly slaughter numbers in Sixth District
states and in Iowa exhibited three major cycles
(see Chart4). Production declined through 1975
in response to the low livestock prices and high
feed costs during late 1974 and early 1975. A
trough was reached in November 1975 and
slaughter began a sharp upturn in December in
Iowa and in January 1976 in the District.
The next building period continued, with a
brief interruption in mid-1976, until early 1977.
The peak in District states was reached in January with a steep downturn beginning immediately. The peak in Iowa occurred in April, three
months later, although slowing growth was evident at the end of 1976. Iowa's production
began a sustained upturn in January 1978, but
District production did not increase appreciably until January 1979, a full year later. Hog

prices had risen from a relatively depressed
level in early 1978 which, along with reduced
feed prices, eventually provided southeastern
producers sufficient incentive to expand production.
The production expansion phase continued
throughout 1979 in both the District and Iowa.
Slowing growth was evident in the District,
however, by the end of 1979 when hog prices
had again dropped abruptly from the levels in
the first quarter of 1979. District hog production
continued to grow modestly until July 1980
when a downturn began. This drop came one
month prior to the downturn in Iowa's production in August 1980.
During the period studied, increases in District pork production lagged behind the
increases in Iowa's production from one to 12
months. O n the other hand, major downturns
in the District's pork production preceded
Iowa's downturn by one to three months.
Although this behavior fits the general pattern
expected, the variation from period to period
limits the specific usefulness of indications provided by the District's pork-producing industry.
In cases where movements in District hog
slaughter lead Iowa's movements by only one
month, the period of advance notice is too
short to be of practical importance.
Average Slaughter Weights
When hog production turns unprofitable and
growers become convinced that improved con-

Chart 4. Commercial Hog Slaughter as

27
FEDERAL RESERVE BANK OF ATLANTA

ditions are not foreseeable, they move to curtail their output by marketing their breeding
stock. Because increasing numbers of mature
sows are included in the volume of marketings,
the average weights of animals slaughtered
would be expected to increase (since sows are
typically 100 pounds or more heavier than the
usual market hogs). Data on sows as a proportion of total slaughter numbers are not
reported on a local (state) level although
weekly proportions of sow slaughter are provided at the national level. However, a rise in
average slaughter weights, information that is
provided at the state level, could serve to indicate when sow slaughter is increasing and when
a reduction in pork output is imminent.
An examination of the deviations in slaughter
weights from the average level for each month
over a period of six years failed to provide
conclusive indications of changes in hog
slaughter (see Chart 5). Although fluctuations
in average slaughter weights occurred, they do
not appear to be particularly related to the
fluctuations in hog slaughter shown in Chart 4.
It is apparent that slaughter weights can and
do change for reasons unrelated to intentional
changes in pork output. Growers sometimes
hold market hogs longer than usual waiting for

Chart 5. Variations in Slaughter Weight
of Hogs*

price improvement, so that when slaughter
eventually occurs, the weights of market hogs
may be several pounds heavier than normal. A
reduction in feed costs with hog prices holding
steady could stimulate producers to feed animals to heavier weights prior to marketing
because the last pounds added, though less
efficient than earlier gains, become increasingly profitable as feed costs decline.
Another possible explanation for the absence
of the expected relationship is that even though
increased sow marketings cause average
slaughter weights to rise, it need not necessarily indicate a nearby reduction in hog production. Producers can withhold young females
(gilts) from the market at the same time they are
selling sows so that breeding stock and production potential is being maintained in spite of an
increase in sow marketings. The proportion of
gilts in the flow of hogs to market is not
reported, so it is not possible to determine
when changed withholding rates of gilts may
indicate potential changes in future hog production.
Summary
The District is a marginal area of pork production because feed costs are significantly higher
than the most concentrated area of hog production in the Midwest. When economic incentives change, lower net returns in the Southeast
cause producers to tend to expand output later
and reduce output earlier than Iowa's producers. Changes in average slaughter weights
are not a reliable indicator of imminent changes
in southeastern production. The tendency for
southeastern producers to cut production early
when losses begin is not statistically strong enough
to confirm an imminent downturn in national
pork output and a consequent upturn in meat
prices. But the relationship may be useful when
taken together with other indicators.

—Gene D. Sullivan
DECEMBER 1981, E C O N O M I C REVIEW

Economic Forecasting
for Southeastern States
Major econometric models exist in all six southeastern states. Despite problems
with availability and accuracy of data, these models are capable of producing
detailed forecasts for legislatures, state agencies, and private clients. The models'
most appropriate application, say forecasters, is in simulating the results of specific
economic events or policies.
With the development in the 1960s of computerized models of the national economy, it was only
a matter of time before economists built models
for regional, state, and substate economies. Public
interest in econometric models was stimulated
in 1980 when Lawrence R. Klein of the University of
Pennsylvania Wharton School won the Nobel
Prize for his work in the development of models.
And even though blindfolded newspaper reporters throwing darts have been known to do as well
as some of the better known national forecasting
firms, demand for national forecasts remains
strong.1
State and substate models, while not as well
established, are in a growth stage. Private industry
represents the largest potential market for the
state models. Utilities, banks, S&Ls, developers,
energy firms, and large retail firms are all interested in projections of state income, employment,
and economic patterns. The projects at the
University of Florida and Georgia State University
are among the region's leaders in attracting
business from private industry.
At present, however, the largest part of the
market for state forecasts comes from the public
FEDERAL RESERVE BANK OF ATLANTA

sector. State legislatures and planning agencies
have a continuing need for forecasts of various
state tax revenues. The Tennessee model, for
example, is mandated by the state legislature to
establish the rate of anticipated growth of the
state economy. Similarly, the Mississippi project
provides estimates of revenue for the state
Commission of Budget and Accounting and also
maintains a cash-flow model forthe state government.
State models are also potentially useful in
some states whose constitutions require a balanced budget. In Georgia, for example, state
spending is tied to expected tax revenues. Even
states not required to balance their budgets
need reasonably accurate revenue projections
for budgetary purposes-i.e., to determine their
credit needs. (For their own reasons, state-budget
committees may not always use the exact forecast
produced by the model, but that is another
story.) State planning agencies also use models
to forecast highway construction costs, gasoline
consumption and tourist expenditures.
Utility companies, important clients of forecasting projects, use the state models to study the
29

impact of changes in rate structures on employment and income. Substate models (satellites to
the state models) have been used to estimate
the effects of new industry on employment.
State Forecasting Models
in the Southeast
Although econometric models exist for several
states and regions in the U. S., modeling efforts in
the Southeast are among the most vigorous.2
State universities are the primary suppliers of
state forecasting models in the Sixth Federal
Reserve District, but substantial modeling programs
are also underway at the Mississippi Research
and Development Center (a state agency) and at
the Tennessee Valley Authority (Table 1).
TVA's program, the oldest in the region, was
developed in response to federal water pollution
control needs in 1968. It is currently under the
direction of Robert A. Nakosteen, with Juan
Gonzalez. Hubert Hinote coordinates forecasting
for TVA's office of Planning and Budget. The
newest model, at the University of Alabama's
Center for Business and Economic Research,
issued its first forecast in 1980. The Alabama
model is directed by Carl E. Ferguson with David
Cheng.
Funding arrangements vary. Many combine
university support with grants from state planning
agencies. Others, like the University of Georgia's
project, are entirely self-supporting through private contracts and memberships or subscriptions.
The Georgia Economic Forecasting Project is
directed by John B. Legler. Albert W. Niemi is
responsible for the estimation of gross state
product and output. The Mississippi model,
directed by Huntley H. Biggs, is funded completely
by the state; TVA supports its model primarily for
in-house use.
Models' structural emphases typically reflect
the shape of each state's economy and the
interests of each project's particular clientele.
Thus, TVA's model concentrates on long-term
energy demand, while the Mississippi model
focuses on manufacturing activity. Mississippi

Magic Lantern

also features forecasts of 12 different state taxes,
an unusually large amount for a state model. The
Tennessee project, directed by David Hake,
emphasizes manufacturing and electrical output.'
Henry H. Fishkind at the Florida project has
pioneered in estimating population growth, migration patterns, construction, and tourism. Louisiana's
model, not surprisingly, focuses largely on oil and
gas production, but soon will be expanded to
full-scale. Loren C. Scott and James Richardson
have been the primary developers of the Louisiana
model thus far.
Some Theoretical Skepticism
Nobel Prize Winner Sirjohn Hicks has pointed
out that many of the "economic facts" buttressing
macroeconomic arguments "are subject to errors
and ambiguities...far in excess of those which in
most natural sciences would be regarded as
tolerable." 3 The precise predictive ability of a
science like physics, in other words, is somewhat
lacking in economics. Economists can, however,
use statistical analysis of historical trends to test
the degree of probability of a prediction. In a
1979 study for the American Enterprise Institute,
W. Allen Spivey and William J. Wrobleski concluded that "the jury is still out assessing the forecasting
performance of econometric models and their
use in policy assessment." And if national econometric models have difficulty hitting a large
target like aggregate economic growth, can we
expect them to have more success with a smaller
target? Some economists remain unconvinced.
Why?
Most state models assume that a state's economy
is similar to the economy of a small nation. Yet
states cannot be analyzed exactly as small nations
because, among other things, states cannot erect
trade barriers, cannot control labor and capital
flow across state lines, and cannot control their
own money supplies. Economic events outside
the state (the "foreign sector," populated by
mysterious "exogenous variables"), rapidly and
powerfully affect state income and employment.
Harvard's Robert Dorfman describes the model's relation to the real world this way: "A
growth model resembles the economy that it
purports to portray about the way that a map on a
scale of one inch to five hundred miles resembles
the United States. Only the broadest outlines
and the grossest structural characteristics can be
discerned. For some purposes, such a map and

DECEMBER 1981, E C O N O M I C REVIEW

such a portrayal are very useful, but we mustn't
take inferences from either of them too literally."4
As a result, the most difficult and creative
aspect of state modeling ("the biggest can of
worms," in the words of one forecaster) is to
identify the particular economic characteristics
of the state and chart them against expected
national and regional developments.
Since each state has a different mix of industries,
labor force, and natural and financial resources,
state economic cycles can occur earlier or later
and be more or less severe than national patterns.
"A state model...must be designed to include
both national and state factors," say LSU's James
A. Richardson and Loren C. Scott, "a task complicated at times by the fact that many state
peculiarities are not quantifiable, or, if they are,
they are not recorded systematically." 5
Generally, state models use a national forecast
to "drive" equations which contain state data. A
simplified example is:
Xm/Xus = f ( C m / C u s )
X m = mfg output in Mississippi
X u s = mfg output in U. S.
C m = unit cost in Mississippi
Cus = unit cost in U. S.
In English, this equation says that the expansion
of manufacturing industry in Mississippi ( X m )
depends on the predicted growth of the relevant
market nationally (X u s ) and on the competitiveness (unit cost) of production in Mississippi
versus the U. S.
Unfortunately, since state data are notoriously
incomplete, unavailable, or undisclosed, forecasters must often resort to data "smoothing," "massaging," or "fabricating" to estimate their equations.
Yet, the adjustments which the state forecasters
make (based on historical trends and available
current data) are often crucial to the model's
ultimate success. To see how these adjustments
are made, we need to take a closer look at the
structure of a state model.
Inside an Econometric Model
Most state models begin with input from a
national model (or "drive"). Many of the southeastern states use the model developed by
Wharton Econometric Forecasting Associates
(WEFA). Florida and Georgia State have developed

their own national models. The national model
provides projections for G N P based in turn on
projections for population, labor force, employment, hours paid, and productivity. In the Mississippi model, for example, the U. S. model provides
the "U. S. Manufacturing Output" block. The
national model then breaks those figures into
employment and earnings by industry. The state
models, in turn, contain the historical pattern for
the state's share of these industries.
The state share of an industry, however, is
continually changing. To account for this, the
forecaster must adjust his historical trend continually. If national demand in an industry is known,
for example, the state market share will depend
on how current output prices in the state compare
with output prices in the nation. These relative
output prices may not be available for some
industries. If not, the forecaster may substitute
"input prices" (e.g., costs of labor, energy and
taxes) with an adjustment for how closely these
input prices approximate final prices. The result
is a figure for current market share which can be
used to adjust the historical market share for the
state.
Once the forecaster has determined his state's
historical share of a given industry, he is ready to
make his projections. Since some industries
depend on others, however, he cannot project
them all separately. One method of accounting
for these dependencies and other differences
among industries is to identify "basic" industries
and "service" industries. A state's "basic" industries
(for example, farming, mining, manufacturing,
federal military, and transportation) derive earn31

FEDERAL RESERVE BANK OF ATLANTA

SOURCE: Mississippi Research and Development Center, June, 1981

ings from exports to other states. Many state
forecasters modify this list to suit the particular
characteristics of their states. Huntley Biggs at
Mississippi, for instance, includes only manufacturing, farming, and government as "basic" industries, which appear as "Mississippi Manufacturing
Output."
A state's "service" industries derive mainly
from purchases by businesses and households
within the state, e.g., construction, communication,
public utilities, trade, finance, real estate, and
civilian government. Again, forecasters generally
modify these sectors. Hotels, which might be a
"service" industry for Carl Ferguson in Alabama,
would be a "basic" industry for Henry Fishkind in
Florida (where most hotel earnings come from
out-of-state consumers). In the Mississippi model,
the "service" industries are the "Non-Export
Output" block.
A state's relative growth in earnings depends
principally on the demand for the output of its
"basic" industries, which in turn stimulate the
"service" industries in the state.
In a state model, "basic" industry trends are
projected by extending into the future the histor-

ical trend in the state's share of the national
industry. Models typically assume that the factors
which affected the share historically will continue to
affect it in the future, but less strongly, so the
projected change in share decelerates. (Except
for special cases like tourism in Florida or oil in
Louisiana, most state models assume that, over
the long run, states' shares of the national market
will move toward equilibrium.)
To arrive at earnings, the model multiplies the
projected state share for each "basic" industry by
projected earnings in the corresponding industry
nationally.
To project earnings in each service industry,
the models rely more on internal (state or regional)
variables such as personal disposable income
(PDI), Cross State Product (CSP), and state
population.
The "basic-service" method projects earnings
by industry for the state. To project personal
income, the state model first determines employment in each industry, again using national data,
historical state shares, and current state data.
Projections for population, wage rates and
unemployment are then applied to the employment data to project personal income figures for
the state. Once personal income is established,
the model applies various tax rates to arrive at
projected state tax revenues (the "General Fund"
block in the Mississippi model).
Problems: The Orange Juice Function
A basic problem plaguing state forecasters is
that as national data is broken down into smaller
units (regional, state, local), the data's volatility
expands dramatically.
In fact, "some of the data," according to
Florida's Henry Fishkind, "is bologna" Until recently, for example, Florida tourism figures were
based on visits to welcome stations at state
borders. Closer analysis revealed that welcome
station stops were actually a function of orange
juice prices, not tourist traffic. Even today, Fishkind
says, the tourism data is not particularly reliable.
A big stumbling block to developing state (and
especially substate) models is disclosure problems.
In an area dominated by a few businesses,
financial data for individual companies might be
derived from the disclosure of local statistics. (To
reduce the burden of reporting, data is collected
from a sample of businesses in each area.) For
this reason the Census Bureau and BEA are
prohibited from releasing much data on local
areas.
According to Georgia State's Donald Ratajczak:

D E C E M B E R 1981, E C O N O M I C R E V I E W

"we don't have good data for consumption,
investment, or inventories in the region." In
addition, there is little accurate consumer price
data that is comparable throughout the region.
As an example of the volatility of sub-state data,
Ratajczak points to the recent revision of employment growth figures for Atlanta, from 1.6 percent
to 9 percent. Labor input for the region, he says,
tends to be "sloppily defined."
The Tennessee model has been revised to
correct a problem endemic to state models: the
calculated elasticities (relative responses to change)
relevant at the national level are often inappropriate at the state level. Before this revision, the
Tennessee model.linked Tennessee wages to
national wages in a fixed way, without accounting
for growth in Tennessee vis-a-vis the nation. As a
result, the earlier model forecast "growing dominance of Tennessee in the nation over a long (20
years or longer) horizon." In some industries, this
deficiency caused the model to predict a 1.5 to 2
percent output growth in Tennessee for every
one percent growth in U. S. output.
A further difficulty facing southeastern economic forecasters is the uncertainty about whether
recent growth rates can be sustained. "Will the
Sunbelt growth mystique be maintained for a
prolonged period," asks one forecaster, "or will it
be short-lived, killed by increasing relative Sunbelt
costs?" Tennessee's present model predicts an
eventual convergence of southeastern and U. S.
economic growth.
How Good Are They?

had average errors of 2.1 percent for personal
income and 2.7 percent for employment. This is
significantly better than the plus or minus 3
percent error deemed acceptable, and Hake
says "it can be reasonably assumed that the
models will do about as well on revenue projections."
The Future of
State Forecasting Models
Despite skepticism from peers and competition
from large national forecasting firms, the state
forecasting projects in the Southeast are producing
useful estimates for a variety of purposes and
clients. The demand for their products is increasing.
Like a small-scale road map, however, the models
are best-suited for particular uses.
Econometric models can be used in three
basic ways. The first and most widely used is the
short-term forecast for a few major economic
indicators ("macrovariables"), like tax revenues,
personal income, and employment "Short-term"
generally means not much longer than one year.
"Long-term" forecasts range from three up to (in
the case of TVA's long-range energy projections)
20 years.
Forecasters caution that the models best suit is
not long-run forecasts. A ten year forecast for
state economic growth, says one District forecaster,
is "pretty speculative." In fact, he would prefer
to "forget anything over five years." Yet, state
legislatures, utilities, and other planningagencies
continue to request 10 and 20 year projections.

Despite these theoretical difficulties and data
problems, state forecasting models seem to work
fairly well. The Mississippi project's forecast for
general state revenues, for example, has always
been within 3 percent of actual revenues; and its
1980 forecast was within one-half percent of
actual revenues. The Alabama model, in its first
forecast, came within 1.3 percent for Cross State
Product and 5.6 percent for tax revenues. From
1976-1978, the Tennessee model projected changes in personal income within 1.9 percent (on
average) and changes in employment within 1.5
percent (on average).
In a recent study, David Hake and Carl Brooking
concluded that plus or minus three percent error
for a one year forecast for personal income and
employment was a reasonable expectation from
any regional model. The Hake-Brooking study,
one of the few comparative evaluations of state
model forecasts published thus far, found that
over four years, three southeastern state models
33
FEDERAL RESERVE BANK OF ATLANTA

The third application of state models is simulation studies. These are usually short-term analyses
which show a hypothetical scenario for a very
specific economic event—the impact of parimutual horse racing on Georgia's tax revenues,
for example. To do simulations, a model must be
reasonably "disaggregated" (the major economic
sectors must be broken down geographically
and structurally). The model thus becomes considerably more complex to develop and maintain.
The state models' real strength is in these
simulation studies. What effect would a proposed
railroad merger have on the Tennessee economy?
How will cutbacks in a major shipbuilding plant
in Mississippi affect local and state employment
and tax revenues? What will be the impact of the
federal spending cuts at the state level? Because
the state models generally have much more
detailed data and equations on state tax structure,
state and federal spending in the state, and state
employment patterns than do the national models,
the state forecasters are in good position to
analyze very specific economic events.
For state planners, the state models also offer a
way of simulating the results of different policy
options. Since all state models derive from a
national forecast, these simulations can incorporate the effects of national economic policy
decisions.
As mentioned, most but not all of the southeastern state models use the Wharton model for
their national input. Unfortunately, definitions of
terms, weighting of variables, and methods for
calculating state inputs often vary among state
models. As a result, no meaningful aggregation of
the state forecast data has been possible. Even if

FOOTNOTES
1 Victor Zarnowitz, in "How Well Do Economists Forecast Growth, Recession
and lnflation?"Economic Outlook USA (AnnArbor Survey Research Center
University of Michigan), concluded that "at the present time, the predictive
value of detailed forecasts reaching out further than a few quarters ahead
must be rather heavily discounted."
2This article is based on a workshop on Forecasting in the Southeast held at
the Federal Reserve Bank of Atlanta on J u n e 19, 1981.
3Cited by Adam Smith (George J.W. Goodman), "Why Not Call Up the
Economists?"Across the Board, July/August 1981, p. 60.

such a combined effort were possible, forecasters
express doubt about the demand for regional
projections, since few official regional agencies
have decision-making powers. Regional and national corporations might represent a potential
market for such forecasts, but not until a solid
track record has been established.
More consistency among state models might
facilitate some comparative studies. Are some
states, for example, suffering more
than others from outflows of money into money
market funds? Are there variations in home
financing strategies from state to state and, if so,
are they influencing migration patterns?
Since the primary market for the state modeling
projects thus far has been state legislatures,
agencies, and state-oriented utilities and corporations, the models are likely to remain strongly
oriented to the special features of the individual
states. Since all the models in the Southeast are
still in the early stages of development, they can
be expected to become even more detailed and
more accurate (especially in simulation studies)
than they are now. The new federal block grant
program to states should provide more funding
from state planning agencies. Data on employment, revenue, retail sales, and energy consumption are becoming increasingly accurate and
comprehensive. The "road maps" remain small
in scale, but they are being filled with more and
more detailed information. All signs point to
continuing demand and expansion for the state
econometric models in the Southeast.

—Gary W. Tapp

REFERENCES
F. Gerard Adams, Carl G. Brooking and Norman J. Glickman, "On the
Specification and Simulation of a Regional Econometric Model: A Model of
Mississippi," The Review of Economics and Statistis, 1977, pp. 286-298.
Comptroller's Office, State of Illinois, "The Illinois Economic Model: Phase I,
"November 1977. Unpublished paper.
J.W. Kendrickand C.M. JayCox, "The Concept and Estimation of Gross State
Product," The Southern Economic Journal, Vol. 32, October 1965
pp.153-168.
L.R. Klein, "The Specification of Regional Econometric Models," Papers
and Proceedings of the Regional Science Association, 23, 1969.

4Robert Dorfman, "Comment" on a paper by Edmund S. Phelps, "Some
Macroeconomics of Population Levelling," Research Reports from the
Commission on Population Growth and the American Future, Economic
Aspects of Population Change, edited by Elliott R. Morss and Ritchie H
Reed, 1972, p.89.

J a m e s A. Richardson and Loren C. Scott, "Income and Employment in a
State's Econometric Model: The C a s e of Louisiana," The Journal of
Economics, IV, 1978, pp. 151-155.

5"lncome and Employment in a State's Econometric Model: The C a s e of
Louisiana," The Journal of Economics, IV, 1978, p. 151.

,"A Short-Run Regional Oil and G a s
Model for Louisiana," Growth and Change, Vol. 10, No. 3, pp. 19-24.

6Cari G. Brooking and David A. Hake, "The Impact of the Regional Econometric
Model on the Policy Formation Decision Process,"Modeling the Multiregional
Economic System, F. Gerard Adams and Norman J. Glickman, eds.
Lexington, Mass: Lexington Books, 1980, pp.223-237.

"Regional and State Projections of Income, Employment, and Population to
the Year 2000," U.S. Department of Commerce, Bureau of Economic
Analysis, Survey of Current Business, November 1980, pp.44-70.

D E C E M B E R 1981, E C O N O M I C R E V I E W

State Econometric Modeling Projects in the Southeast
Organization

Address

Director

Center for Business and
Economic Research

Univ. of Alabama
Box AK
University, AL 35486

Carl E. Ferguson, Jr.

Florida

Bureau of Econ. and
Business Research

221 Matherly Hall
Univ. of Florida
Gainesville, FL 32611

Henry H. Fishkind

Georgia

Georgia Economic
Forecasting Project

Division of Research
College of Bus. Admin.
Univ. of Georgia
Athens, GA 30602

John B. Legier

Georgia State Univ.
Economic Forecasting
Project

Georgia State Univ.
University Plaza
Atlanta, GA 30303

Donald Ratajczak

Louisiana

Division of Research

Louisiana State Univ.
College of Business
Baton Rouge, LA 70803

James Richardson
Loren C. Scott

Mississippi

Mississippi Research and
Development Center

P.O. Drawer 2470
Jackson, MS 39205

Huntley H. Biggs

Tennessee

Center for Business and
Economic Analysis

Suite 100, Glocker
Business Building
Univ. of Tennessee
Knoxville, TN 37916

David Hake

Tennessee Valley Authority
Regional Analysis Staff

321 Summer Place Bldg.
Knoxville, TM 37902

Robert A. Nakosteen

U.S. Army Corps of
Engineers

510 Title Building
30 Pryor Street, S.W.
Atlanta, GA 30303

Owen D. Belcher

State

Alabama

U.S. Army

FEDERAL RESERVE BANK OF ATLANTA

The Impact of State Incentives
on Foreign Investors' Site Selections
State development agencies in the Southeast spent over $2 million in 1978 on
promoting foreign investment in their states. They are also increasing incentives to
foreign firms to locate in their states. Despite this increased activity, evidence
suggests that investors place more emphasis on investment climate than on special
incentives.
The classic vaudeville line, "now take my wife
. . . Please
seems increasingly applicable to
state development agencies across the United
States in their promotional efforts to attract
new investment. From the Snowbelt to the
Sunbelt, from the Sierras to the Appalachians,
individual states are knocking on doors in far
away places with strange sounding names in an
effort to arrange marriages between their states
and potential suitors (investors) — and, in many
cases, offering substantial doweries!
State development agencies in the Southeast
spent over $2 million on promotional activities
— investment trips, overseas offices, literature,
and presentations — in 1978. They also offered
an undetermined (but substantial) amount in
direct incentives — tax breaks, worker training,
road and site improvements, industrial revenue
bonds, gifts of land, and the like.
The motive behind this activity is clear: each
state desires to gain its share of economic
development vis-a-vis the nation as a whole and
other competing states. If the state is not successful, it will lose people, employment, investment and income to other states. Indeed, large
foreign investments are one of the most highly
publicized measures of competition between
states. Despite the recent explosion in promotional activities, however, current research suggests that foreign investors do not consider
incentives as important as the overall investment climate in a state.
'For more detail on the foreign investment promotional activities and costs of the
southeastern states, see the dissertation by Spero Peppas listed in the references
at the end of this article.

Why Do States Seek Foreign Investment?
One answer is that state agencies apparently
believe foreign investment offers greater benefits (jobs, incomes, taxes) than domestic investment. These investments are seen as new
injections of economic activity with new multiplier effects, rather than diversions of internal
activity. Another possibility is that while the
initial promotional costs are higher for attracting foreign investors, states find the subsequent costs are lower. A third possibility is that
foreign investment is somehow sexier, more
interesting, and more newsworthy in the eyes
of the state and local officials. After ten years of
research experience on foreign investments in
the U.S., I believe all three reasons are often at
work.
Foreign investment maintains its appeal
despite the fact that there are certain costs
associated with it — both in real and opportunity terms. First, scarce resources could be
better allocated to other areas. Second, additional and/or better investments could be
attracted.
In addition under U.S. law it is illegal (in most
cases) for a state to discriminate either in favor
of or against a foreign investor. Any basic incentive the state offers must be available to all
potential investors — in-state, out-of-state, or
out of the country. The problem for state
agencies, obviously, is that promotional problems and costs are greater in attracting true
foreign investment: there is a greater educational effort required (because foreign investors have less knowledge about a particular
D E C E M B E R 1981, E C O N O M I C R E V I E W

state); foreign investors have different needs
and often require special assistance (acculturation assistance for their foreign employees and
families); and promotion methods are more
expensive due to greater distances, maintenance of foreign offices, and adaptation/
translation of materials. Nevertheless, states
clearly believe the benefits of foreign investment outweigh the costs.
How Do Southeastern States Try
to Attract Foreign Investment?
In examining the promotional activities and
investment incentives of the southeastern
states,2 one finds few significant differences.
Virtually all of the respective state development
agencies conduct periodic investment missions
(primarily to Europe and the Far East), have
overseas offices or representatives (almost all
of them in Europe, and many in Japan), have
special divisions specifically charged with
increasing foreign investment in the state, and
offer special promotional packages for new

"Any basic incentive the state
offers must be available to all
potential
investors—instate,
out-of-state, or out of the country."
investors. The basic "pitch" used by the southeastern states is also very similar, stressing
abundant, low cost, hard working, non-union
labor; cheap and abundant land and utilities;
low work stoppage rates; low taxes; good
transportation; worker training programs; nice
climate; conservative, pro-business state government and a nice place to raise a family!
The basic homogeneity in the state's offerings reflects the area's similar characteristics.
And while hard-core southerners may adamantly refute the "commonalities" among
states in the region, the nuances are far too fine
to be understood by foreigners. What foreigners do understand are the basic differences
between the southeastern region and the other
major regions of the United States.
2

For this article, the s o u t h e a s t e r n states i n c l u d e V i r g i n i a , the C a r o l i n a s , Florida,
Georgia, Alabama, Mississippi, Louisiana and Tennessee.

Even this broad regional distinction however,
has only come about fairly recently. Until the
mid 1970s, few foreign investors could name
any of the southeastern states, and knew virtually nothing of the region except for its colonial
heritage or civil rights infamy. But with the
Carter Presidency came an increased global
awareness of the region and the entire "Sunbelt" phenomenon. Increased foreign awareness led to promotional strategies. As certain
nationalities and industries began to cluster in a
particular state, states began targeting them
more specifically. And somewhere along the
line, an intense competition emerged: virtually
all states stepped up their promotional activities and increased the range of incentives
offered to potential investors. These incentive
packages might include tax holidays or exemptions, free worker training, road paving, industrial r e v e n u e b o n d s , special water
considerations, and outright gifts of land.
As a first step in constructing the incentive
package, state agencies must ascertain whether
the investment climate (economic opportunity)
is itself strong enough to generate new investment, or whether some special incentives will
be necessary either to increase the profitability
or lower the risk (cost) for potential investors.
For example, state officials visiting potential
foreign investors can help identify and clarify
the investors' needs: how much and what kind
of land, how many and what kind of workers,
how much and what kinds of financial assistance, and so forth. Based on this information,
the state can then assess whether or not it
possesses what the foreign investor needs. In
this process, the state should also demonstrate
why its proposals better suit the needs of the
investor than those of other competing states.
Finally, the size and particular importance to
a state of a specific investment may play a role in
the importance and size of the incentives
offered. A state that desperately wants a major
foreign investment may feel compelled to offer
a truly substantial incentive package — much
more than typically offered (for example, Pennsylvania with Volkswagen, or Ohio with Honda
or Tennessee with Nissan).
What Are the Customers Looking For?
The "customers" of the state development
boards are the foreign investors: historically
the largest firms in their country's industries,
37

FEDERAL RESERVE BANK OF ATLANTA

and more recently, also the medium size and
even some smaller size firms.
These investors do not need to be sold on
the United States. In almost all cases, this decision has already been made. What the state
must sell is itself as the particular state for the
investment site. The basic "product" it offers is
a place: a profitable, safe, and pleasant
environment. In general, components of the
basic offering include logistical factors (ports,
highways, railroads), labor factors (wages, available supply, unionization levels, skill levels,
and productivity, absenteeism, turnover and
work stoppage rates), utility factors (availability
and cost of water, energy, etc.), construction
factors (availability and cost of land, construction costs, and so forth.), financial factors
(types and levels of taxes, financial assistance
packages), and lifestyle factors (climate, recreational and educational facilities, cultural activities, etc.). All but the lifestyle factors will jointly
determine the potential profitability of the
investment, along with providing some estimate of the risk.
For the customer to "buy" this product, the
state's offering must fit the needs of the customer and be competitive with the offerings of
other competing states. If both conditions are
not present, the state is wasting its time, money,
and effort in promotion, and could better use
them to rectify its weak areas. For example,
instead of spending hundreds of thousands of
dollars annually on unsuccessful promotion,
the state could construct a deep-water port,
fund worker training programs for new investors, or offer a tax holiday.
It might also conduct preliminary environmental impact studies for sites providing good
potential for heavy industry in order to help
speed up local, state, and federal approval once
a specific investment proposal is made. This
activity might also reveal potential community
acceptance problems (resistance to investment) of which the state is unaware, and which
might result in stopping the investment from
being made (and embarrassing the state development officials).
Another factor state agencies should be
aware of is that certain nationalities may have
more difficulty than others in getting money
out of their home countries to invest in the
United States, or bad economic conditions in
their home markets may have decreased the
38

parent's ability to fund sufficiently the American venture from internal sources. In such
cases, favorable financial incentives from state
or local authorities are likely to be perceived as
more important. Larger multi-national firms
also have greater access to lower cost financing
than smaller firms, and as a result, financial
incentives such as industrial revenue bonds,
gifts of land, free worker training and the like
may loom more important for smaller firms.
In addition, capital intensive and utility intensive industries generally require different conditions than labor intensive industries. Special
incentives involving water or energy conditions
may be more important for the first group than
they are for the latter, as would tax incentives
related to the use of heavy equipment and
machinery.
How Successful Are the State Efforts?
"General wisdom" seems to say that incentives play an important role. However, recent
studies on this question suggest that investors
do not consider incentives as important as
investment climates, and in many cases, do not
consider them important at all. Two of the most
recent studies of foreign investments in the
Southeast were those of Bernard Imbert and G.
Lynn Derrick.
Imbert studied the southeastern investments
of 16 French companies, and, among other
topics, asked for a ranking of the most important factors that influenced the companies to
locate in the Southeast and in the particular
state. Of the more than 15 factors listed, five
were mentioned as being "most important" by
two-thirds of the firms. These factors were, in
order of ranking: the attitude of the labor force,
the quantity and quality of labor, transportation
facilities, the life style of the area, and the
availability (and cost) of suitable plant sites.
Three other factors were cited by more than onethird of the firms as also being extremely important:
the availability and cost of water and energy,
salary levels, and the proximity and ease of
access to markets in the United States.
O n the other hand, inducements/incentives
of state and local authorities ranked eleventh
out of sixteen factors, and were ranked as a
"major" factor by only two firms, and an
"important" factor by only two other firms. In
DECEMBER 1981, E C O N O M I C REVIEW

the cases of the two French firms who ranked
the incentives as "most important," both parents were strapped for financial resources to
investment in the U.S., and were offered such
favorable conditions that it was almost impossible for them not to be taken into consideration :
long term taxation advantages, free or virtually
free land, state construction of a road to their
plant site, and so forth. However, both cases
occurred in the early 1960s, and such inducements by state and local authorities are now
seldom as extensive.
In Derrick's study of German investments in
South Carolina, he concluded that labor conditions had also been the most important factor in
German firms' decisions to locate in South
Carolina, along with the abundance of low cost
utilities and suitable plant sites. As was the case
with French investors, incentives of state and

"Despite the recent explosion in
promotional
activities,...current
research suggests that foreign
investors do not consider
incentives as important as the
overall investment
climate
in a state."

local authorities were not ranked as critical
factors.
Other studies have touched in part on the
relative importance of incentives: Young and
Kedia (for Louisiana), Arpan and Ricks (for the
U.S.), and H. C. Tong (for the U.S.). The Young
and Kedia study of Louisiana revealed that most
of the investments were made via acquisition of
existing Louisiana companies, and, as a result,
government incentives did not play a major
role. For those investments not made by
acquisition, incentives still played a very minor
role compared to investment climate factors.
However, their study did show that state incentives were relatively more important in foreign
firms' decisions to expand in Louisiana once

the investment had been made.
Arpan and Ricks'study of foreign investments
in the entire U.S. also showed that incentives
did not play a major role in the site selection
process compared to investment climate factors, and Tong's study of foreign investors' reasons for choosing a particular site consistently
showed government incentives to rank in the
bottom sixth of factors mentioned (although
local tax rates usually ranked near the middle).
Thus, it is difficult to reconcile the apparent
differences in importance placed on government incentives by investors and government
authories. Government authorities apparently
perceive such incentives to be important to
potential investors, while the admittedly scant
empirical evidence suggests that the incentives
are not that important.
Yet, it can still be argued that from an individual state perspective, or even possibly a
regional perspective, such competition is necessary. So long as a competitive state offers
such incentives, there is considerable pressure
for the other states to offer comparable packages. In other words, all things being equal in
terms of investment climate and possibly even
life style, a special incentive may make a difference. And from an individual state's perspective, it clearly does make a difference whether
the firm involved makes the investment in their
state rather than in another state.
The real key issue, however, appears to be
the significantly higher importance placed by
firms on the investment climate, rather than on
special incentives. Investment is a long term,
profit-oriented decision, and virtually no
amount of special incentives (particularly those
which are short term in nature) is likely to
attract and keep a firm in an area in which the
long term profitability criteria are not present.
This suggests that state and local authorities
should examine more carefully their investment climate before going overboard on incentives. If the state doesn't already possess them,
it would be advised in the long run to spend its
time, money, and effort on developing these
preferred investment climate factors rather
than on special incentives. And, in terms of
special incentives, the state should determine
scientifically which ones are most likely to
result in increased investment, rather than simply matching the overall offerings of competing
states.
39

FEDERAL RESERVE BANK OF ATLANTA

Foreign Investment in the Southeast
As of year end 1979, FDI (Foreign Direct
Investment) in the United States totaled $52.3
billion, up 23 percent from 1978 (in which a
similar percentage increase had taken place).
This increase was more than twice the average
annual percentage increase from 1975 to
1977, and nearly three times larger than from
1968 to 1972.
The gross book value of all FDI in the Sixth
District at the end of 1977 was over $8.5 billion,
an increase of 46 percent from 1974. Louisiana
had by far the largest single amount (36 percent of the total), followed by Georgia (16
percent), Tennessee (15 percent), Alabama
and Florida (14 percent each) and Mississippi
(5 percent).
Because of growth rates in excess of 140
percent for four of the six states in the district,
and a 31 percent disinvestment in Louisiana,
Louisiana's rank in the district in manufacturing
FDI fell from an overwhelmingly dominant first
position (41 percent) to a third place tie with
Georgia (19 percent each), while Tennessee
moved from second place into first (25 percent). In terms of nationalities, the British dominate with nearly 120 companies (31 percent of
all), followed by the Canadians and West Germans (17 percent each), the French and the
Dutch (9 percent each), and the J a p a n e s e
(six percent).*
Within the manufacturing sector, FDI in the
chemical industry led by a wide margin in terms
of both employment and gross book value of
property, plant and equipment. These chemical
investments were heavily concentrated in Louisiana, Alabama, and Tennessee.
What these numbers suggest is that foreign
investment in the Sixth District increased dra-

Direct Employment of FDI
in 6th District, by State: 1977
Total Number
of Employees
(thousands)

Alabama
Florida
Georgia
Lousiana
Mississippi
Tennessee
6th District Total

Total Number
of Employees
in Manufacturing
(thousands)

14
26
29
18
5
25

10
12
18
7
3
21

117

Source: Survey of Current Business, July 1980, p. 39, and Office of
Foreign Investment in the US, US Department of Commerce.

matically from 1974 to 1977 and is heavily
concentrated in British hands. However, different states received different types of investment. FDI in Louisiana and Mississippi was
primarily in the petroleum sector; in Tennessee,
Alabama, and Georgia in the manufacturing
sector, and in Florida in the real estate sector,
followed by the manufacturing sector. Thus
there appeared to be an East-West split within
the Sixth District, based largely on state comparative advantage. The comparative labor
advantages of Tennessee, Alabama, Georgia,
and Florida attracted foreign investment in
manufacturing, while the oil advantages of Louisiana and Mississippi attracted foreign investment in the petroleum sector.

•Japanese investment in the region has increased since the cut-off date
(1979) for data in this article.

D E C E M B E R 1981, E C O N O M I C R E V I E W

Gross Book Value of Property, Plant, and Equipment in 6th District by State:
1974 & 1977
(millions of dollars)
All FDI

Manufacturing & Industrial FDI
% increase

% increase

Alabama
Florida
Georgia
Louisiana
Mississippi
Tennessee

1974

1977

1974-1977

1974

1977

1974-1977

645
904
639
2616
330
736

1214
1163
1373
3032
473
1283

88%
29%
114%
16%
43%
74%

328
188
358
1059
30
644

889
502
731
732
72 +
980 +

171%
167%
104%
(-31%)
140%
152%

5870

8538

46%

2607

3896 +

50%

Total

Source: For 1974 data, US Department of Commerce, Foreign Direct Investment In the United States (Washington, DC, GPO, 1976).
For 1977 data, Survey of Current Business, July 1980, p. 36.

FDI in 6th District's Manufacturing & Petroleum Sectors, 1977
Number of Employees

Alabama

Florida

10
1
2
3

12
1

All M a n u f a c t u r i n g

Food
Paper
Chemicals
Metals
Machinery
Other
Petroleum

(+)
1
3

(+)

(+)
5
1
3
2
1

Georgia

18 "
2

(+)
3
1
2
9
1

(thousands)

Louisiana

Mississippi

7
1

3
1

(+)
3
1

(+)
1
4

(+)
1
1
1

(+)
(+)

Tennessee

(+)
1
7
3
8
2
1

Gross Bnnk Value of Plant & Equipment ($ millions)
Alabama

Florida

Georgia

Louisiana

Mississippi

Tennessee

850
3
(D)
438
4
(D)
198
(D)

362
9
2
(D)
26
20
(D)
71

693
(D)
(D)
(D)
50
19
178
129

700
33
(D)
538
(D)
(D)
39
1920

72
(D)
(D)
(D)
13
7
4
236

980
4
(D)
426
281
(D)
12
980

All M a n u f a c t u r i n g

Food
Paper
Chemicals
Metals
Machinery
Other
Petroleum

Source: Office of Foreign Investment in US, US Department of Commerce.
D data suppressed for disclosure reasons
+ = less than one thousand

FEDERAL RESERVE BANK OF ATLANTA

Number of Foreign Owned Manufacturing/Petroleum Firms in 6th District,
by State and Nationality of Owner: 1979
Canada

France

Japan

Netherlands

Sweden

1
5
5
0
1

8
15
18
7
5
9

5
8
17
6
0
1

2
5
15
0
0
3

1
8
5
10
0
7

4
5
1
1
0
2

Belgium

Alabama
Florida
Georgia
Louisiana
Mississippi
Tennessee

Switzerland

United
Kingdom

w.
Germany

3
5
1
4
0
6

11
26
38
23
1
18

6
20
12
9
3
14

117

1979
Total

1974
Total

1
4
8
9
1
7

41
97
120
74
9
68

7
10
36
25
4
17

409

Other

Source: Jeffrey Arpan and David Ricks, "Directory of Foreign Owned Manufacturers in the United States (Atlanta, Georgia: Business Publishing Division, College of Business
Administration, Georgia State University; 1st edition, 1974, and 2nd edition, 1979.)

—Jeffrey S. Arpan

REFERENCES
Jeffrey S. Arpan, "Foreign Direct Investments in South
Carolina," a paper presented at a conference on "The Costs
and Benefits of Foreign Investment from a State's Perspective," sponsored by the Southern Center for International
Studies and the U.S. Department of Commerce, Atlanta,
Georgia, February 27, 1981.
"Regulation of Foreign Direct Investment
in the United States: Quo Vasit, Quo Vadit," Journal of
Contemporary Business, Autumn 1977, Volume 6, No. 4.
Reprinted in The C.F.A. Digest, Winter 1979, Vol. 9, No. 1.
Jeffrey Arpan and David Ricks, Directory of Foreign Manufacturers in the U.S., Revised Edition (Georgia State University, Business Publishing Services Division, Atlanta, 1979).
"Foreign Direct Investments
in the U.S. and Some Attendant Research Problems," Journal of International Business Studies, Spring 1974.
with Ed Flowers, "Foreign
Direct Investments in the United States: The State of the Art
of Research," Journal of International Business Studies, the
10th Anniversary Commemorative Issue, forthcoming 1981.
Jack Behrman, "Impacts of Inward Direct Investment in
North Carolina Development," a paper presented at the
conference on Costs and Benefits of Foreign Investments
from a State Perspective, op. cit.
G. Lynn Derrick, Jr., "Major Factors Which Influenced
German Companies to Invest in South Carolina," graduate
business thesis, University of South Carolina, Columbia,
November 1980.

Bernard Imbert, "French Investment in the American
Southeast," Report #CS-10, Georgia World Congress Institute, Atlanta, Georgia, 1979.
Spero Peppas, "A Comparative Study of Promotional Activities to Attract Foreign Investment: An Application of Marketing Theory to the Efforts of the Southeastern States,"
Ph.D. dissetation, Georgia State University, Atlanta, Georgia, 1979.
Cedric Suzman, "Foreign Direct Investments in the Southeastern United States: A Comparative Analysis," conference on The Costs and Benefits of Foreign Investment from
a State Perspective," op. cit.
H. M. Tong, Plant Location Decision of Foreign Manufacturing Investors, (Ann Arbor, Michigan: UMI Research
Press, 1979).
United States Government, General Accounting
Office.
Department of Housing and
Urban Development, "Impact of U.S. Foreign Direct Investment on U.S. Cities and Regions," prepared by Robert B.
Cohen, Analytical Sciences Corp., 27 February 1979, TR1716-1.
Mira Wilkins, Foreign Direct Investment in Florida, Costs
and Benefits, paper presented at conference on "The Costs
and Benefits of Foreign Investment from a State Perspective," op. cit.
S. Young and B. Kedia, "Costs and Benefits of Foreign Direct
Investment from a State Perspective: The Case of Louisiana," paper presented at conference on "The Costs and
Benefits of Foreign Investment from a State Perspective,"
op. cit.

D E C E M B E R 1981, E C O N O M I C R E V I E W

How Big Is
the Federal Government?
The number of Federal employees per 1,000 of population declined from 1959 to
1978. Standard measures of government employment and spending, however, do
not account for a substantial shift toward "invisible workers," consultants, white
collar workers, and higher grade levels. Future financial liabilities and regulatory
costs also should be added to the "hidden burden" of the federal sector.
In recent years, public opinion surveys have
revealed a strong and growing dissatisfaction
with government in general and with the federal
government in particular. Respondents often
express a feeling that the public sector is too
large, wasteful, inefficient and unresponsive to
the needs of citizens. 1 This widespread attitude
contributed to the election victory of President
Reagan, who campaigned on a platform of
cutting federal taxes and spendingand reducing
the size and scope of federal activity. Although
there may be a generally accepted attitude that
the federal government has become "too big" in
recent years, there is much less understanding
of the federal establishment's actual size and
growth.2
Measuring the Size and Growth *
of the Federal Sector
Measuring the federal public sector's size and
growth rate is a very complex problem, for the
primary issue is how to assess the burden which
the federal government places on the private

1
T h e e x p a n s i o n of the federal public sector has been the subject of intensive study by
scholars for decades, a n d the conclusions that g o v e r n m e n t has grown too rapidly a n d
b e c o m e too intrusive are hardly new. For e x a m p l e . H e n r y W e s t c o n c l u d e d in his b o o k
Federal Power: Its Growth and Necessity, p u b l i s h e d in 1918, that " w e have, without
protest a n d even with satisfaction, a c c o r d e d the g o v e r n m e n t a control over corporate
and individual existence w h i i h infinitely transcends the wildest dreams of t h o s e w h o
advocate centralized authority." Based o n statistical e v i d e n c e of the e x p a n s i o n in federal
expenditures b e t w e e n 1894 and 1918, West w a r n e d of the "dangers of drifting into
socialism b e c a u s e " t h e growth of federal power will b e u n c h e c k e d . " For a s u m m a r y of
typical surveys, s e e S e y m o u r Martin Lipset a n d William Schneider, " L o w e r Taxes a n d
M o r e Welfare: A Reply to Arthur Seldon," journal of Contemporary Studies (Spring
1981), pp. 89-94
2 H e n r y Litchfield West, Federal Power: Its Growth and Necessity ( N e w York: G e o r g e H.
D o r a n C o m p a n y , 1918), pp. vii-ix a n d pp. 101-102.

sector. Federal employment and expenditures
give some indication of this burden—as the
number of federal employees and the level of
federal spending increase, resources are clearly
diverted from the private to the public s e c t o r but the total impact of the federal government is
far greater.
Data on the number of employees do not
reflect the qualitative changes that occur over
time in the federal work force. For example, the
economic effects of hiring an additional 50
workers to maintain a federal building are vastly
different from hiring 50 additional professionals
to develop regulations. Data on expenditures
capture only the federal government's current
outlays, yet many spending commitments are
made which involve taxes and outlays that
extend far into the future. Moreover, many of
the costs which the federal government imposes
on the private sector do not appear explicitly in
the federal accounting system.
With but one exception, all studies of federal
government growth have examined only the
direct or quantitative aspects of public sector
expansion. 3 Indirect or qualitative changes in the
size of government are much more difficult to
measure and are generally not reported in widely
used publications; nevertheless, they are a significant component of recent increases in the
federal government.

5 For a survey of studies of federal g o v e r n m e n t growth, s e e J a m e s T. Bennett a n d M a n u e l
H . Johnson, T h e Political E c o n o m y o f F e d e r a l G o v e r n m e n t G r o w t h : 1 9 5 9 - 1 9 7 9
( C o l l e g e Station, Texas: Texas A & M University, 1980), pp. 7-26.

43
FEDERAL RESERVE BANK OF ATLANTA

T a b l e 1. Federal Full-Time Civilian Employment, Total Labor Force, a n d Population
by Year, 1 9 5 9 - 1 9 7 8 with Average A n n u a l C o m p o u n d Rates of Growth, R
Year

Employees
(E)

Labor F o r c e b
(LF)'OOOs

Population
(POP)'OOOs

E
1,000LF

E
1 ,OOOPOP

1959
1960
1961
1962
1963
1964
1965
1966
1967
1968
1969
1970
1971
1972
1973
1974
1975
1976
1977
1978

2,230,097
2,237,338
2,291,001
2,371,589
2,387,021
2,370,437
2,398,033
2,574,257
2,784,087
2,867,365
2,879,483
2,806,469
2,766,099
2,682,000
2,537,976
2,547,129
2,581,870
2,556,753
2,502,020
2„483,273

70,921
72,142
73,031
73,442
74,571
75,830
77,178
78,893
80,793
82,272
84,240
85,903
86,929
88,991
91,040
93,240
94,793
96,917
99,534
102,537

177,830
180,671
183,691
186,538
189,242
191,889
194,303
196,560
198,712
200,706
202,677
204,878
207,053
208,846
210,410
211,901
213,559
215,142
216,820
218,500

31.57
31.01
31.37
32.29
32.01
31.26
31.07
32.63
34.46
34.85
34.18
32.67
31.82
30.14
27.88
27.32
27.24
26.38
25.14
24.22

12.59
12.38
12.47
12.71
12.61
12.35
12.34
13.10
14.01
14.29
14.21
13.70
13.36
12.84
12.06
12.02
12.09
11.88
11.54
11.36

R,%

0.69

1.96

1.06

-1.25

-0.37

Source: aU.S. Civil Service Commission, Federal Civilian Manpower Statistics: Pay Structure of the Federal Civil Service, various years.
bU.S. Department of Commerce, Survey of Current Business, various years.

Conventional (Quantitative)
Measures
Employment. Considerthe data on federal fulltime civilian employment shown for the period
1959-1978 in Table I. Both the size of the labor
force and population grew far more rapidly than
did federal employment. In 1959, there were
31.57 federal employees for each 1,000 in the
labor force; the comparable figure in 1978 was
only 24.22, a decline of 22.6 percent. The number
of federal employees per 1,000 population fell
from 12.59 in 1959 to 11.36 in 1978. Though it
runs counter to conventional wisdom, the conclusion is inescapable: When measured by employment, the relative size of the federal government
has declined and its absolute size has increased
very modestly.
Expenditures. As Table 2 shows, for the years
1959-1978, federal spending fluctuated between
18.0 and 22.7 percent of C N P. Total output grew
44

very rapidly, though not as rapidly as federal
expenditures, but the average annual growth
rate of 1.71 percent in federal spending as a
percent of G N P can be described as quite
modest. On a per capita basis, federal spending
in current dollars was almost four times as much
in 1978 as in 1959; when price changes are taken
into account, however, per capita spending in
1978 was less than twice as much as it was 20
years earlier. The average annual growth rate of
real per capita federal spending is only 3.56
percent.
Overall, the quantitative statistics on federal
government size and growth are startling, not so
much because they show that the federal public
sector has grown in recent years, but because
they indicate it has not expanded very rapidly.
After all, since 1959, four major cabinet-level
departments have been formed (Housing and
Urban Development, Transportation, Energy, and
Education) and an enormous increase has ocD E C E M B E R 1981, E C O N O M I C R E V I E W

Table 2. Federal Government Expenditures and Gross National Product and C o n s u m e r Price Index
by Y e a r 1959-1978 with Average Annual C o m p o u n d Rates of Growth, R
Year

Expenditures
(G) $ bil.

GNP
$ bil.

CPI

1959
1960
1961
1962
1963
1964
1965
1966
1967
1968
1969
1970
1971
1972
1973
1974
1975
1976
1977
1978

91.0
93.1
101.9
110.4
114.2
118.2
123.8
143.6
163.7
180.6
188.4
204.2
220.6
244.7
265.0
299.3
357.1
386.3
423.5
461.3

486.5
506.0
523.3
563.8
594.7
635.7
688.1
753.0
796.3
868.5
935.5
982.4
1,063.4
1,171.1
1,306.6
1,412.9
1,528.8
1,706.5
1,889.6
2,107.6

87.3
88.7
89.6
90.6
91.7
92.9
94.5
97.2
100.0
104.2
109.8
116.3
121.3
125.3
133.1
147.7
161.2
170.5
181.5
195.4

R,%

9.22

8.06

4.35

(G/GNP)

Real G
$ bil.

Real G
Per Capita,$

18.7
18.4
19.5
19.6
19.2
18.6
18.0
19.1
20.6
20.8
20.1
20.8
20.7
20.9
20.3
21.2
23.2
22.7
22.4
21.9

511
515
555
592
603
616
637
731
824
900
929
997
1,065
1,172
1,259
1,412
1,672
1,796
1,953
2,111

104.2
105.0
113.7
121.9
124.5
127.2
131.0
147.7
163.7
173.3
171.6
175.6
181.9
195.3
199.1
202.6
221.5
226.6
233.3
236.1

586
581
619
653
658
663
674
751
824
863
847
857
879
935
946
956
1,037
1,053
1,076
1,080

1.71

8.07

4.67

3.56

(G/POP)

Source: U.S. Department of Commerce,Survey of Current Business, various years.

curred in the regulatory powers of the federal
government to deal with such issues as environmental protection, occupational health and safety,
drug abuse, equal employment opportunity and
affirmative action, mine safety, consumer product
safety, and so on. Social programs to provide
food stamps, law enforcement assistance, Medicare/Medicaid benefits, student loans, school
lunches, black lung benefits and supplemental
security income have proliferated as well. Given
the marked expansion in the scope of federal
government activities, one would expect a much
larger increase in its size than the employment
and expenditure data indicate. Why do these
increases not show up in the data?
The answer is that federal government outlays
and employment provide only a partial picture of
thetrue changes in the dimensions of the federal
sector burden over time. Important shifts have
occurred in the qualitative aspects of employment and expenditure as well.
F E D E R A L RESERVE B A N K O F A T L A N T A

Qualitative Factors
Employment: The White Collar Explosion and
"Invisible" Workers. The data on full-time civilian
employment do not account for four important
qualitative changes in the work force:
(1) composition of the federal work force has
shifted from blue-collar to white-collar employees;
(2) grade levels have increased rapidly within
the white-collar ranks;
(3) many full-time workers are counted as
part-time to avoid employment ceilings;
and,
(4) a vast number of contractors and consultants
are employed indirectly by the federal
government, even though they are not
counted as such in official statistics.
As an illustration of these concepts, consider
the classification of employees over time in
45

Table 3. T h e Distribution of Federal Full-Time Civilian Employment by Category and the N u m b e r
E m p l o y e d in Washington, D.C., by Year 1959-1 g 7 8

March 31

General
Schedule

Wage
Systems

Postal

Other
Systems

Working
in D . C .

1959
1960
1961
1962
1963
1964
1965
1966
1967
1968
1969
1970
1971
1972
1973
1974
1975
1976
1977
1978

969,529
973,242
1,008,040
1,057,729
1,083,707
1,090,401
1,112,687
1,189,306
1,252,839
1,298,647
1,288,169
1,286,948
1,297,300
1,281,996
1,301,557
1,322,313
1,349,104
1,358,491
1,390,494
1,396,265

687,403
666,727
662,099
675,903
658,818
625,795
621,091
682,178
757,271
745,786
673,552
674,250
630,670
603,450
547,440
535,929
528,080
514,543
470,175
461,726

474,688
483,265
504,020
517,006
520,370
523,866
534,761
568,911
604,147
656,522
673,552
673,482
663,863
665,136
549,739
552,667
556,149
548,144
527,992
522,094

107,477
114,104
116,841
120,951
124,125
130,374
131,892
133,861
169,829
178,527
171,194
171,789
171,498
131,418
139,240
136,220
138,537
135,575
113,359
103,188

221,671
225,971
231,391
241,902
250,637
253,636
263,783
280,594
297,897
305,225
305,905
304,885
309,803
303,066
282,991
297,759
303,071
307,774
312,411
312,829

Source: U.S.Civil Service Commission, Federal Civilian Work Force Statistics: Pay Structure of the Federal Civil Service,

Table 3. General Schedule (CS) workers are
white-collar employees within the federal establishment. Wage system federal workers perform
blue-collar jobs. Over the entire 20-year span,
with only minor exceptions, there has been a
steady increase in white-collar workers and a
steady decline in blue-collar employees. GS
employees increased by 44 percent between
1959 and 1978, while wage system workers
declined by 33 percent Although the total number
of employees changed very little over time, a
significant change occurred in the type of work
performed. Moreover, federal government activities became increasingly concentrated in the
nation's capital.
Employees in executive grades GS-13 to 18
increased by 134,049—the number in 1978 was
three times as large as the 1959 figure—while
those in the lower grades fell by almost 90,000.
Thus, policymakers and regulators gained rapidly

in employment at the expense of lower level
employees: A massive shift in grade structure
occurred which is not apparent in the statistics
on total employment. From a private sector
perspective,there are critical differences between a
government clerk and a policymaker who promulgates regulations. A clerical worker's principal
cost to the public is the payment of salary and
fringe benefits. A regulator, on the other hand,
may impose costs on the private sector far in
excess of salary and perquisites.
The Office of Management and Budget places
employment ceilings on every executive agency,
but the constraints apply only to full-time employees. Each March 31, agencies report their
employment statistics and, on this date, thousands
of workers are switched from full-time to parttime status. So pervasive is this practice that
these full-time/part-time bureaucrats are known
as "25-and-ones," a term descriptive of the fact

D E C E M B E R 1981, E C O N O M I C R E V I E W

T a b l e 4 . Federal Government Liabilities a n d C o m m i t m e n t s by Category at the E n d of e a c h F i s c a l
Year for the Period 1967-1977, with C o m p o u n d Average Annual Growth Rates
Federal Government C o m m i t m e n t s (millions of $)
Liabilities
Orders
(1)

Undelivered
Contracts

(ID

Long-Term
of Annuity
(III)

1967
1968
1969
1970
1971
1972
1973
1974
1975
1976
1977

$378,128
405,933
407,960
423,325
452,373
486,973
520,697
544,325
613,022
726,193
789,030

$ 77,320
77,197
74,106
70,010
74,843
88,265
102,095
105,618
130,007
266,281
322,109

$ 2,759
8,086
8,436
7,905
8,356
8,397
8,916
9,727
1 2,838
13,002
15,126

R,°/o

7.45

14.51

11.68

Year

Total

Deficiency
Contingencies
Programs
$

234,076
311,041
222,536
496,438
550,439
251,551
578,035
1,717,861
2,593,248
4,638,727
5,394,847
39.22

(IV)
$

912,261
1,002,432
970,041
1,298.435
1,483,572
1,380,907
1,964,542
2,954,706
4,301,987
6,511,647
7,381,103
24.76

S o u r c e : U . S . D e p a r t m e n t of t h e T r e a s u r y , F i s c a l S e r v i c e , B u r e a u o f G o v e r n m e n t F i n a n c i a l O p e r a t i o n s , S t a t e m e n t o f L i a b i l i t i e s a n d O t h e r
Financial Operations, S t a t e m e n t of Liabilities a n d Other Financial C o m m i t m e n t s of t h e United States G o v e r n m e n t v a r i o u s
years.

that for 25 of the 26 federal pay periods each
year, the workers are classified as full-time, but in
the one pay period in which the headcount is
taken, these workers are officially placed on parttime or "invisible" status to evade hiring constraints. Estimates vary as to the extent of this
practice. A 1977 Comptroller General Report
(which was not a full-scale investigation) discovered several thousand instances. Without doubt,
then, current figures understate total federal
employment. 4
The issue of accurately counting federal employees raises an even more fundamental question:
What, in fact, is a federal employee? If consultants,
contractors, and state and local government
workers whose pay comes directly from the
Treasury were included, then reported employment represents only the tip of the bureaucratic
iceberg. As secretary of HEW, Joseph Califano
testified in 1979 that his department was paying
the salaries of 980,217 persons in think tanks,
universities, and other units of government. The
Department of Defense pays an additional 2.05

million workers through contractors and subcontractors.5 One estimate has placed this "indirect"
federal employment at about eight million workers.6 To the extent that the federal government
has increasingly relied on workers not counted in
reported employment data, the size and growth
of the federal establishment have been greatly
understated.
Expenditures: Delayed Repercussions and Uncounted Liabilities. As is the case with employment, federal expenditure statistics do not accurately reflect the spending patterns and financial
commitments of the federal sector. Expenditures
consist primarily of outlays in a given year; they
do not include future financial liabilities and commitments. A useful, but somewhat simplistic,
analogy would be for an individual to count his
dollar outlays in a given year as the total of his
financial commitments and liabilities without
including future spending dictated by loans,
mortgages, installment payments, and goods and
services on order. For the federal government, as
shown in Table 4, liabilities and other financial
5 D o n a l d Lambro, "In and O u t at H EW: Doing Well by Doing G o o d Through Consulting."

Personnel C e i l i n g s - A Barrier to Effective M a n p o w e r Management," A Report to the
C o n g r e s s b y the Comptroller General of the U. S-, J u n e 2, 1977, pp. 4- 10.

Policy R e v i e w (3Winter 1979), p. 109.
«-Barbara Blumenthal, " U n c l e Sam's Army of Invisible Employees," N a t i o n a l ( o u r n a l
(May 5 , 1 9 7 9 ) , p. 732.

47
FEDERAL RESERVE B A N K O F ATLANTA

commitments are reported for four categories:
(1) Liabilities: Public Debt, Checks Outstanding, Accrued Interest, and Accounts Payable;
(2) Undelivered Orders: Obligations incurred
under law against appropriations andfunds
for goods and services not yet received;
(3) Long-Term Contracts: Subject to future
modification or cancellation in advance of
delivery of goods or services; and
(4) Contingencies: Government Guarantees (insuring private lenders against losses), Insurance Commitments, Actuarial Status of Annuity Programs, Unadjudicated Claims, and
International Commitments.
The data in Table 4 must be interpreted with
caution, for in a strict sense, some of the aggregates
shown in each category are not additive because
the data were computed on different bases.
Further, the data indicate the maximum potential
liability of the federal government, not the most
probable amounts that will be expended in the
future. For instance, guaranteed loans will be
paid only if the lender defaults. Nevertheless,
the growth rates at the bottom of the table reveal
that the financial commitments and liabilities of
the federal government have increased far more
rapidly than expenditures. In only the 11 years
between 1967 and 1977, total contingencies
rose from $912 billion to $7.38 trillion dollars—
an eight-fold increase.
The Actuarial Deficiency of Annuity Programs
was presented separately to show the increase in
financial commitments due to social security
payments, civil service pensions, and retirement
pay for military personnel. The actuarial deficiency
is the amount by which expected future payments
exceeds anticipated contributions—a sum in
excess of $5 trillion. Federal contingencies for
this item doubled, on the average, about every
two years. Such a growth rate cannot long be
sustained without either substantially increasing
taxes or reducing benefit payments. Government
decisions, therefore, have long-term tax and
expenditure implications—not adequately reflected in annual data on current federal expenditures. If one considers these future federal liabilities and contingencies, a much higher rate of
growth is indicated than shown by expenditures
alone, regardless of whether price and population
increases are taken into account. It is also apparent
that many of the financial repercussions of federal
activities are not felt immediately, but are delayed.

Regulations and Red Tape
Even after adjustment for the qualitative changes
in federal employment and financial operations,
these two traditional measures still grossly understate the federal sector's impact on the private
economy. The government's actions, primarily
through regulations and red tape, impose enormous costs on the private sector that are not
included in either employment or finance statistics.
Because government bears only a small portion
of the regulatory costs, they may be regarded as
"hidden taxes" borne by the private sector.
In the five-year period 1974-1978, Congress
adopted no fewer than 25 major pieces of
regulatory legislation including the Energy Policy
and Conservation Act, the Fair Debt Collection
Practices Act, the Employment Retirement Income
Security Act, and the Real Estate Settlement
Procedures Act. The costs of such regulations
have grown rapidly. According to Murray Weidenbaum, chairman of the Council of Economic
Advisers, the total cost of federal regulation
exceeded $66 billion in 1976 (in excess of $300
per capita) and had grown to more than $102
billion in 1979, an increase of 55 percent in only
three years.7 The administrative costs of these
actions, the only costs reported in federal expenditures, represent only about 5 percent of the
total; the remaining 95 percent is borne by the
private sector as hidden taxes.
In 1977, the Commission on Federal Paperwork
estimated that, although difficult to calculate
precisely, the total cost of processing federal
paperwork (including that associated with regulation) was approximately $100 billion each
year. Of this amount, the federal government
spent $42 billion. The Internal Revenue Service
alone employs some 13,200 different forms and
form letters. About 613 million man-hours were
expended by individuals and businesses in 1978
just completing this paperwork.
As of June 1972, the Office of Management
and Budget (OMB) reported that federal government agencies (excluding IRS) used 5,567 forms
that generated more than 418 million responses
from the private sector. As staggering as such
statistics appear, they apparently underestimate
the burden greatly. Many forms used are not
even known to OMB; single-use forms such as
those used in one-time surveys are not included,
and many regulatory agencies noted for their
' M u r r a y L. W e i d e n b a u m , T h e Future o f B u s i n e s s R e g u l a t i o n ( N e w Y o r k : A m a c o m
B o o k s , Inc., 1 9 7 9 ) , p p . 1 5 - 2 3 .

DECEMBER 1981, E C O N O M I C R E V I E W

burdensome paperwork are exempted from reporting paperwork to OMB. By almost any standard of comparison, the nation is awash in a sea
of federal forms.8
The total social costs of government are enormous when the hidden burden of the federal
sector is taken into account.
Conclusions
The federal government's growth in recent
years is widely recognized and, apparently, often
resented by the American taxpayer. The current
debate over a Constitutional amendment to balance the budget indicates that the voter wishes
to restrain government expansion if not decrease
its absolute size. The statistics that have been
used to measure the size and growth rate of
8For a more c o m p l e t e discussion of federal paperwork, see J a m e s T . B e n n e t t and M a n u e l
H. Johnson, "Paperwork a n d Bureaucracy," Economic Inquiry (July 1979) pp. 4 3 5 - 4 5 1 .

government employment and expenditures do
not adequately capture all the dimensions of the
public sector.
Substantial qualitative shifts have occurred in
the composition and structure of the federal
labor force, many individuals who work for the
federal sector are not counted, the indirect costs
of regulation and paperwork do not appear in
reported expenditures and current outlays do
not incorporate the large and rapidly growing
future liabilities and financial commitments which
portend an increasing tax burden in the future.
No conclusive answer can be given to the
question, "How big is the federal government?"
One can, however, confidently assert that it is
much larger than the reported data indicate, that
it has grown very rapidly in the recent past, and
that the Reagan administration faces a massive
problem in shrinking or even slowing the growth
of the federal leviathan.
—James T. Bennett

Index
for

1981

AGRICULTURE
The Impact of Drought
Gene D. Sullivan, September, 26
The Impact of Florida's Freeze on Vegetable
Prices
Gene D. Sullivan, June, 1 8
Renewable Energy Sources from the Farm
Gene D. Sullivan, April, 4
Southeastern Agriculture in the 80s
Gene D. Sullivan, May, 12
Southeastern Farmers Face Bleak Prospects
Gene D.Sullivan, February, 10
Southeastern Pork Production:
A Clue to Future Food
Price Changes?
Gene D. Sullivan, December, 24
Water Allocation in the East
Clyde Kiker, June, 27
BANKING
Atlanta Study Finds Check Growth Has Slowed
June, 22
The Future of the Financial Services
Industry: Conference Excerpts
September, 32
49

FEDERAL RESERVE BANK OF ATLANTA

BANKING (continued)
The Future of the Financial Services Industry:
Conference Excerpts
October, 30
International Deposits in Miami—
A Profile
Donald E. Baer, May, 28
Is the All-Savers Certificate
a Success? Evidence from the Southeast
Donald L. Koch,
B.Frank King,
and Delores W. Steinhauser, December, 4
New Competition for Consumer
Financial Business
B. Frank King, April, 24
A Primer on Financial Institutions
in the Sixth District States
B. Frank King, February, 4
Sources for Country Risk Analysis
Donald E. Baer, June, 37
Survey: Georgia S&Ls Take Lead in New Services
William N. Cox, June, 13
DEREGULATION
Bank-Thrift Competition in the New
Environment: The Southeastern Evidence
So Far
William N.Cox, August, 11
Deregulation, Innovation, and New Competition
in Financial Services Markets: An Overview
B. Frank King, August, 8
Deregulation: The Attack on Geographic Barriers
John M. Godfrey, February, 17
The Effects of the Deregulation Act and
Potential Geographic Deregulation on the
Safety and Performance of Depository
Institutions
Joseph F. Sinkey,Jr., August, 33
The Financing of Small Business
Peter Eisemann and Victor L. Andrews,
August, 1 6
Nonlocal Competition for Banking Services
Arnold A. Heggestad, August, 21
Performance Implications of New Competition
Duane B. Graddy, August, 25
Savings and Loans in the New
Financial Environment
James A. Verbrugge, August, 28
ECONOMIC HISTORY
The Other Adam Smith
James T. Laney, October, 26

FINANCIAL STRUCTURE
Bank-Thrift Competition in the New
Environment: The Southeastern
Evidence So Far
William N. Cox, August, 11
Behind Miami's Surge in International Banking
Donald E. Baer, April, 9
Deregulation, Innovation, and New Competition
in Financial Services Markets: An Overview
B. Frank King, August, 8
Deregulation: The Attack on Geographic Barriers
John M. Godfrey, February, 17
The Effects of the Deregulation Act and
Potential Geographic Deregulation on
the Safety and Performance of
Depository Institutions
Joseph F. Sinkey, Jr., August, 33
The Financing of Small Business
Peter Eisemann and Victor L. Andrews,
August, 16
The Future of the Financial Services Industry:
Conference Excerpts
September, 32
The Future of the Financial Services Industry:
Conference Excerpts
October, 30
International Deposits in Miami—A Profile
Donald E. Baer, May, 28
Is the All-Savers Certificate a Success?
Evidence from the Southeast
Donald L. Koch,
B. Frank King
and Delores W. Steinhauser, December, 4
Nonlocal Competition for Banking Services
Arnold A. Heggestad, August, 21
NOW Competition: S&Ls Start Fast, Banks More
Conservative
William N. Cox, April, 27
NOW Competition in Southeastern Cities
William N. Cox
and Pamela Van Pelt Whigham, December, 14
NOW Pricing: Perspectives and Objectives
William N. Cox, February, 22
Performance Implications of New Competition
Duane B. Graddy, August, 25
A Primer on Financial Institutions in the
Sixth District States
B. Frank King, February, 4
Savings and Loans in the New
Financial Environment
James A. Verbrugge, August, 28
Survey: Georgia S&Ls Take Lead in New Services
William N. Cox, June, 13

DECEMBER 1981, E C O N O M I C R E V I E W

FISCAL POLICY
Supply-Side Effects of Fiscal Policy: Some
Historical Perspectives (Working Paper Review)
Robert Keleher and William Orzechowski,
February, 26
Supply-Side Tax Policy: Reviewing the Evidence
Robert Keleher, April, 16
HOUSING
Will Second-Mortgage Financing be the
REITs of Today?
Donald L. Koch and Delores W. Steinhauser,
October, 1 2
INFLATION
The Fed vs. Inflation
Otto Eckstein, April, 6
Inflation Experiences in Seven Major Countries:
An Overview
Charles J. Haulk, April, 31
INTERNATIONAL E C O N O M I C S
Assessing Economic Country Risk
William J.Kahley, June, 32
Behind Miami's Surge in International Banking
Donald E. Baer, April, 9
Inflation Experiences in Seven Major
Countries: An Overview
Charles J. Haulk, April, 31
Sources for Country Risk Analysis
Donald E. Baer, June, 37
MONETARY POLICY
1981 Monetary Policy
Paul A. Volcker, September, 22
The 1981 Monetary Targets
Paul A. Volcker, April, 22
NATIONAL E C O N O M I C S
Faulty Diagnosis: The CNP Revisions
Charles J. Haulk,May, 17
How Big is the Federal Government?
James T. Bennett, December, 43
The Reagan Program for Economic Recovery:
Economic Rationale (A Primer on
Supply-Side Economics)
James R. Barth, September, 4
The Reagan Program for Economic Recovery:
An Historical Perspective
James R. Barth, October, 4

NATIONAL E C O N O M I C S ( c o n t i n u e d )
Supply-Side Effects of Fiscal Policy:
Some Historical Perspectives
(Working Paper Review) Robert Keleher and
William Orzechowski,
February, 26
Supply-Side Tax Policy: Reviewing the Evidence
Robert Keleher, April, 16
The U.S. Economic Outlook: No Instant Miracles
Robert F. Lanzillotti, May, 25
NOW ACCOUNTS
Now Competition: S&Ls Start Fast,
Banks More Conservative
William N. Cox, April, 27
NOW Competition in Southeastern Cities
William N. Cox
and Pamela Van Pelt Whigham,
December, 14
NOW Pricing: Perspectives and Objectives
William N. Cox, February, 22
REGIONAL E C O N O M I C S
Economic Forecasting in Southeastern States
Gary W. Tapp, December, 29
The Effects of Proposed Federal Spending Cuts
on the Southeast
Charlie Carter, June, 4
The Impact of Drought
Gene D. Sullivan, September, 26
The Impact of Florida's Freeze on Vegetable
Prices
Gene D. Sullivan, June, 18
The Impact of State Incentives on
Foreign Investors' Site Selections
Jeffrey S. Arpan, December, 36
The Income Elasticity of the Georgia
Income Tax
Charlie Carter, September, 15
Regional Repercussions of a Chrysler Failure
Charlie Carter, May, 23
Renewable Energy Sources from the Farm
Gene D. Sullivan, April, 4
Southeastern Agriculture in the 80s
Gene D. Sullivan, May, 12
The Southeast in the 1980s
William J. Kahley, May, 4
Southeastern Farmers Face Bleak Prospects
Gene D. Sullivan, February, 10
Water Allocation in the East
Clyde Kiker, June, 27

51
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Full text of Economic Review (Federal Reserve Bank of Atlanta) : December 1981, Volume 66, Number 8

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