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Review
Vol. 69, No. 9




Novem ber 1987

.") Is l i^ lilh D is tric t M a n u fa c tu r in g
K n d a n g rrc d ?
I(> T h c t i r r a t H u ll M a rk e ts 1924-29 a n d
I9S2--87: S p e c u la tiv e H u b b le s o r
K c o n o m ic F u n d a m e n ta ls ?

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F ederal Reserve Bank of St. Louis

Review
November 1987

In This Issue . . .




Manufacturing em ployment in the nation has declined since 1979, leading
some to conclude that "deindustrialization” has been taking place. Other mea­
sures o f manufacturing, such as output and productivity, however, suggest
substantial progress in the nation's manufacturing sector. Not all regions have
shared in this progress; industrial activity has shifted away from northern indus­
trial areas to the South and West in recent years. Given these regional variations,
Thomas B. Mandelbaum evaluates the performance o f manufacturing in the
Eighth Federal Reserve District in ‘‘Is Eighth District Manufacturing Endan­
gered?” He uses em ployment data and several measures o f output to compare
regional with national manufacturing activity between 1972 and 1985. M andel­
baum concludes that the expansion o f District manufacturing was closely similar
to that o f the nation as a w hole during this period; the District experienced
neither the severe manufacturing decline associated with the Rust Belt nor the
sharp expansions o f the South and West. The parallel growth o f District and
national manufacturing points out the similarities in industrial composition,
labor productivity and unit labor costs between the two.
*

*

*

Many people attribute the 1987 stock market crash to a bursting speculative
bubble, much like the one blam ed for the 1929 crash in stock prices. The belief
that speculation might cause a persistent deviation in stock prices from prices
consistent with the underlying fundamentals is important. At the time of the 1929
crash, this belief spawned legislative proposals designed to curb credit for
speculation, amend the National Banking and Federal Reseive Acts, impose an
excise tax on stock sales and regulate the activities o f stock exchanges and
investment trusts. Similarly, various proposals to alter the structure o f financial
markets have follow ed the recent crash in stock prices.
G. J. Santoni examines the “speculation issue” in the second article in this
Review, “The Great Bull Markets o f 1924—29 and 1982-87: Speculative Bubbles or
Economic Fundamentals?” Santoni compares a theoiv o f stock prices based on
fundamentals to one that allows for bubbles, then examines data from the 1920s
and 1980s to determine which theory is supported by the evidence. He concludes
that the evidence does not support the notion that speculation caused stock
prices to deviate persistently from those consistent with the fundamentals.

3




FEDERAL RESERVE BANK OF ST. LOUIS

NOVEMBER 1987

Is Eighth District Manufacturing
Endanger ed?
Thomas B. Mandelbaum

E l MPLOYMENT in U.S. manufacturing industries
has declined more than 9 percent since 1979, casting
doubt about the stability of our industrial base. Other
indicators o f manufacturing activity, however, suggest
a more favorable evaluation. Real output in manufac­
turing, for example, has increased 16.5 percent since
1979. This output growth, achieved with a shrinking
labor input, reflects a gain in productivity per worker.
Moreover, the proportion o f the nation’s real GNP
originating in manufacturing has remained remark­
ably stable over the past 40 years.1
Despite this stability at the national level, a major
shift o f the location of manufacturing activity among
regions has occurred. While declining in the "Rust
Belt,” manufacturing activity has posted solid gains in
the West and the "Sun Belt."- Between 1947 and 1985,
the share o f the nation’s manufactured goods pro­
duced in the Middle Atlantic and East North Central
census regions dropped from 60 to 40 percent.' Ibis
decline was offset by an increase in the South and

Thomas B. Mandelbaum is an economist at the Federal Reserve Bank
of St. Louis. Thomas A. Poilmann provided research assistance.
'For an analysis of the nation’s manufacturing performance, see
Tatom (1986aand 1986b). SeeO tt(1987)foralong-run perspective
on structural changes of the U.S. economy.
2See Crandall (1986), for an analysis of regional shifts of U.S.
manufacturing.
3This statement refers to the percentage of gross value added in
manufacturing, published by the U.S. Bureau of the Census in
Census of Manufactures and Annual Survey of Manufactures. Gross
value added is described in the shaded box on the next page. The
Middle Atlantic census region includes New Jersey, New York and
Pennsylvania; the East North Central region includes Illinois, Indi­
ana, Michigan, Ohio and Wisconsin.




West from 26 percent in 1947 to 46 percent in 1985
with little change in the share contributed bv New
England and the West North Central states.4
This article compares the performance o f manufac­
turing in the Eighth Federal Reserve District with that
in the nation. Its purpose is to determine whether
regional shifts of manufacturing noted elsewhere have
also occurred in the Eighth District, which is not
entirely in either the Sun or Rust Belts.1

MANUFACTURING PERFORMANCE IN
THE EIGHTH DISTRICT
In this article, em ployment data and three mea­
sures o f manufacturing output are used to evaluate
manufacturing performance in the District. These
three output measures are manufacturing product
IMP), gross value added (GVA), and value o f shipments
IVS). Each indicator is described in the shaded insert
on page 00. An appendix outlines the m ethodology
used to estimate the Eighth District’s MP. Several indi­
cators o f manufacturing output w ere used to gauge
the consistency of the analysis.

4The New England region includes Connecticut, Massachusetts,
Maine, New Hampshire, Rhode Island and Vermont; the West North
Central region includes Iowa, Kansas, Minnesota, Missouri, Ne­
braska, North Dakota and South Dakota. Except for the states in the
Middle Atlantic and East North Central regions the rest of the states
make up the South and the West.
5The Eighth Federal Reserve District includes Arkansas and parts of
Illinois, Indiana, Kentucky, Mississippi, Missouri and Tennessee.
Due to data limitations, however, only data from Arkansas, Ken­
tucky, Missouri and Tennessee are used in the analysis.

5

FEDERAL RESERVE BANK OF ST. LOUIS

NOVEMBER 1987

Measures of District Manufacturing Output
Three measures of District manufacturing output
were used in this article. Due to data limitations, the sum
of data for the four states that dominate the District’s
economy —- Arkansas, Kentucky, Missouri and Tennes­
see — is used to represent the District.
Manufacturing Product (MP) for the nation is the same
as "GNP originating in manufacturing” in the U.S. Com­
merce Department's national income and product ac­
counts (NIPA). It is conceptually similar to the economic
measure of value-added. This measure is not consist­
ently available on a state or regional basis and was
estimated for the District by the author using earnings,
employment, payroll and gross-value-added data. The
technical appendix describes the methodology used in
its construction.
The Value o f Shipments (VS), published by the U.S.
Bureau of the Census, is the received net selling value of
products shipped from manufacturing establishments,
f.o.b. plant after discounts and excluding freight charges
and excise taxes. The measure includes intermediate
manufactured products purchased as inputs, so that it
tends to be inflated by double-counting of products
made by one manufacturer and sold as inputs to an­
other. In addition, the value of shipments reflects the

All measures are adjusted for inflation (1982 prices)
using the nation's implicit price deflator for manufac­
turing. Due to data limitations, the District analysis
focuses on the 1972-85 period.

Manufacturing Growth: Eighth District
vs. the United States
Employment Trends. Chart 1 shows that the Dis­
trict's total wage and salary employment, which
equals about 7 percent of U.S. total employment,
closely follow ed movements in national employment
since the early 1970s. The similar growth o f total em ­
ployment in the region is not surprising; there is a
close similarity between the industrial compositions
o f the regional and national work forces. The largest
differences between the region’s and nation’s indus­
trial structures are a slightly smaller proportion o f the
District econom y accounted for by the services sector
and a slightly larger share accounted for by manufac­

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6
Federal Reserve Bank of St. Louis

costs of business services of the manufacturer, such as
maintenance and repair, engineering, consulting, re­
search and advertising. These services are assigned to
service-producing sectors rather than manufacturing in
the NIPA measures of manufacturing output. Since some
of the intermediate inputs and business services may be
purchased from other areas, a region’s value of ship­
ments may reflect production which originated in other
regions.
The value of shipments also differs from the NIPA
manufacturing output measure in that VS excludes the
output of establishments that perform the administra­
tive and auxiliary functions of a manufacturing enter­
prise, such as manufacturing headquarters.
Gross Value Added (GVA), published by the U.S. Bureau
of the Census, is the value of manufacturing shipments
minus the value of materials, supplies, fuel and pur­
chased electricity used in production. The gross-valueadded measure avoids the duplication in the value of
shipments data resulting from the use of products of
some manufacturing establishments as materials by oth­
ers. But unlike the NIPA output measure, the grossvalue-added data includes the value of business services
and excludes the output of administrative establish­
ments.

turing." In 1986, manufacturing em ployed 21.4 percent
of the District’s wage and salary workers and 19.1
percent o f the nation’s.
As chart 2 shows, District manufacturing em ploy­
ment has also followed national trends since 1972.7
The number o f manufacturing workers peaked in
1979, then declined cyclically through 1982. In the
current recovery period, manufacturing em ployment
rebounded sharply in 1984 before resuming its decline
in recent years. District manufacturing employment

6See Mandelbaum (1987) for a more complete discussion of the
similarities of the region’s and nation’s employment compositions.
7A t-test of the average difference between District and U.S. annual
growth rates of manufacturing employment, 1973-85, yields a tstatistic of - 0.46, indicating the difference is not statistically signifi­
cant at the .05 level. The period begins in 1973 rather than 1972,
because 1972 is the first observation and this observation is used in
calculating the 1973 growth rate.

FEDERAL RESERVE BANK OF ST. LOUIS

NOVEMBER 1987

C h a rt 1

Total Employment

in 1986 was 1.41 million, almost 8 percent below its
1979 peak level and roughly equal to its 1972 level.
Output Growth. In contrast to employment, District
manufacturing output, like that in the nation, has
grown substantially. As chart 3 shows, both regional
and national manufacturing output (MP) declined in
recession years but increased sharply during business
cycle upturns. The net result was a substantial output
gain over the period.
The chart also shows that the District’s manufactur­
ing output has closely followed national trends. The
first line o f table 1 shows the close similarity between
regional and national growth in various measures of
output. The District’s 2.6 percent average annual
growth MP during the 1973-85 period was statistically



indistinguishable from the nation's 2.9 percent pace.
Regardless o f the output measure used, there was
little difference between annual growth rates o f re­
gional and national manufacturing output."
The real value o f manufacturing output in the Dis­
trict, as measured by MP, was $50.6 billion (1982
prices) in 1985. This represents a 7.5 percent gain
between 1979 and 1985, a period in which declining
em ployment trends intensified concerns about the
health o f the manufacturing sector.

8T-tests of the average differences between District and U.S. annual
growth rates, 1973-85, of MP, GVA and VS yield t-statistics of 0.54,
-0 .2 8 and -1 .5 9 , respectively. None of these is significantly
different than zero, in the statistical sense, at the .05 significance
level.

7

NOVEMBER 1987

FEDERAL RESERVE BANK OF ST. LOUIS

C h a rt 2

M anufacturing Employment
M i l l i o ns

A n n u a l D a ta

Mi ll i o n s

1.55

19.00

18.25

Individual Industry Growth
The similarity o f manufacturing output growth in
the District and the United States could mask substan­
tial differences between the regional and national
growth in individual industry groups. Similar' growth
of total manufacturing output could result if stronger
gr owth o f some regional subsectors offset slowerthan-national growth in others.
Each o f the industry groups o f the Eighth District
manufacturing sector, however, grew at near the na­
tional pace. Although the growth rates o f output for
most o f the District industry groups differed som e­
what from the national rates (see table 1), none o f the
these differences is larger than w ould be expected due

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Federal Reserve Bank of St. Louis

to the chance var iation o f the data." This result holds
regardless o f the output measure used.

Industrial Composition
Even with identical regional and national growth
rates for each industry, overall manufacturing could
differ considerably if the industrial compositions of

9T-tests of the average differences between District and U.S. annual
growth rates for each output measure for each manufacturing indus­
try group were conducted. None of these is statistically different
from zero at the .05 level of significance.

FEDERAL RESERVE BANK OF ST. LOUIS

NOVEMBER 1987

Chart 3

Real M anufacturing O utput

1972

73

74

75

76

77

78

the regional and national manufacturing sectors var­
ied substantially. For example, if regional manufactur­
ing were concentrated in slow-growing industries
(like prim aiy metal production), then the District s
overall manufacturing growth w ould tend to trail the
national expansion.
The diversification o f regional and national manu­
facturing, however, has been quite similar. Chart 4
compares the percent distribution o f District and U.S.
manufacturing output in 1985 (as indicated bv MPI
among all the major industiy groups. Most are of
similar relative size. The sector in which the District
share varied the most from the national average in
1985 was nonelectrical machineiy. This sector ac­



79

80

81

82

83

84

85

1986

counted for 14.8 percent of District MP compared with
17.4 percent nationally, hardly a dramatic difference.
Earlier data show that overall structural similarity
between District and national manufacturing has ex­
isted at least since 1972.

Regional Productivity Gains
The increases in District manufacturing output
since 1972 with little change in manufacturing em ­
ployment imply an increase in labor productivity. In
fact, labor productivity o f District manufacturing (MP
per manufacturing worker I increased at a 2.5 percent

9

NOVEMBER 1987

FEDERAL RESERVE BANK OF ST. LOUIS

Table 1
Average Annual Growth Rates of Real Manufacturing Output by Industry: 1973-85
Manufacturing Product
District
Total Manufacturing
Durable Goods
Lumber and wood products
Furniture and fixtures
Primary metal industries
Fabricated metal products
Machinery, except electrical
Electronic equipment
Transportation equipment
Stone, clay and glass products
Instrument and related products
Miscellaneous industries
Nondurable Goods
Food and kindred products
Textile mill products
Apparel
Paper and allied products
Printing and publishing
Chemicals and allied products
Petroleum and coal products
Tobacco manufacturers
Rubber and miscellaneous
Leather and leather products

2.6%

U.S.
2.9%

Gross Value Added1
District
5.3%

U.S.
5.1%

Value of Shipments1
District
6.6%

U.S.
5.5%

1.2
2.3
0.0
3.5
8.6
3.9
2.7
1.9
6.3
3.3

1.7
2.4
-1 .7
1.7
7.0
6.6
2.8
1.2
5.7
2.9

2.3
3.4
4.8
4.7
13.3
5.6
9.3
1.8
N.A.
5.1

3.8
4.5
3.0
3.6
10.8
8.3
7.9
3.8
7.5
2.4

1.0
3.6
4.8
4.6
14.5
7.5
15.5
2.2
N.A.
3.9

3.5
4.9
2.6
3.9
11.8
8.1
9.5
4.3
7.8
2.8

2.3
1.1
0.9
4.1
2.9
1.7
3.8
-3 .2
5.8
-1 .1

2.1
2.0
1.4
3.0
2.4
3.0
0.2
- 1 .5
4.1
-1 .1

3.1
1.8
3.0
3.8
4.6
5.3
N.A.
N.A.
6.8
6.5

3.1
3.4
3.3
5.1
3.1
5.9
2.3
0.2
7.3
-0 .7

3.3
2.6
2.5
4.5
4.8
6.3
N.A.
N.A.
7.5
6.6

2.8
3.6
2.8
5.5
3.3
7.2
7.1
-1 .7
8.9
0.0

NOTE: N.A. indicates data not available.
'Data for 1979-81 are not available, so growth rates for 1979,1980,1981 and1982 are excluded from the average growth rates.

com pounded annual rate between 1972 and 1985.
Table 2 shows slightly faster growth when labor pro­
ductivity is measured by GVA per worker and VS per
worker."’
The growth of total manufacturing output and labor
productivity in the region indicate that, rather than
undergoing a dramatic decline or “deindustrializa-

'“Because no regional data for GVA and VS are available for 1979SI, it is impossible to compute average annual growth rates for
those variables that are comparable to the average annual growth
rates for MP. Therefore, compounded annual rates, which require
only the initial and terminal years of the periods, are used to indicate
average growth. In each productivity measure, the number of manu­
facturing workers are from the U.S. Bureau of the Census’ Annual
Survey of Manufactures and Census of Manufactures.


10


tion,” the District’s manufacturing sector — like the
nation’s — is expanding and becom ing more produc­
tive.

Operating Ratios
Labor productivity and unit labor costs o f a region’s
manufacturing sector relative to the rest o f the nation
are related to the region’s competitive position in
national markets. A comparison o f changes in the
regional and national operating ratios reveals whether
the District is keeping pace with improvements at the
national level.
Table 2 compares the 1985 levels and the com ­
pounded annual growth rates of labor productivity

FEDERAL RESERVE BANK OF ST. LOUIS

NOVEMBER 1987

Chart 4

Composition of District and U.S. Manufacturing
Output, 1985
Percent of t o t a l
Nonelectrical Machinery
T r a nsp orta tio n Equipment
Food and K i n d re d Products
E l ec t r i c a l E q u i p m e n t
Chemicals, A llied

Products

Fabricated Metals
Printing and Publishing
Rubber and Plastics
P a p e r and All ied Products
Primary

Metals

Apparel, Textile Products
S t o n e , C l a y and Glass
Lumber and

Wood

Products

Furniture and F ix tu re s
Tobacco Products
Instruments
Miscellaneous
Le a th e r Products
P e t r o l e u m , Coal Products
Textile

Mi l l Products

10

and unit labor costs using each o f the three measures
o f output. Unit labor costs are measured by payroll per
unit o f output." Total District payroll per dollar o f MP,

"The payroll data is published by the U.S. Bureau of the Census in
the Census of Manufactures and the Annual Survey of Manufactures.




15

20

measured in 1982 dollars, was $0.49, almost identical
to the $0.50 national level. In addition to similar levels,

It includes gross earnings paid to an employees, but excludes
employer contributions for social insurance and payments to propri­
etors or partners of unincorporated establishments.

11

FEDERAL RESERVE BANK OF ST. LOUIS

NOVEMBER 1987

Table 2
Manufacturing Unit Labor Costs and Labor Productivity
Compounded Annual
Growth Rate 1972-85

1985 Level

Labor Productivity
MP/worker
GVA/worker
VS/worker
Unit Labor Costs
Payroll/MP
Payroll/GVA
Payroll/VS

Eighth District

U.S.

$ 38,400
50,800
124,300

$ 42,100
52,600
119,900

0.49
0.37
0.15

0.50
0.40
0.18

Eighth District
2.5%
3.0
3.8

- 2 .3
- 2 .7
-3 .4

U.S.
2.8%
3.0
3.5

-2 .7
-2 .9
-3 .4

NOTE: See text for variable definitions. Payroll and output data in constant 1982 dollars. Productivity
figures are rounded to the nearest $100.

table 2 shows that the decline in District and national
unit labor costs between 1972 and 1985 was also simi­
lar; unit labor costs (pavroll/MP) declined at a com ­
pounded annual rate of 2.3 percent in the District, and
2.7 percent rate in the nation. Similar results are found
when unit labor costs are measured by payroll/GVA or
payroll/VS.
Table 2 also shows the similarity o f both the level
and growth o f labor productivity. Whether measured
by MP/worker, GVA/worker, or VS/worker, the levels
and com pounded annual growth rates o f District and
LI.S. labor productivity w ere quite similar.
The overall resemblance in the levels and growth of
these operating ratios suggest that District manufac­
turing is maintaining its competitive position relative
to the rest o f the nation.1- This, and the fact that the
competitiveness o f the nation's manufacturing sector
has improved relative to its major foreign competitors,
suggests that District manufacturers are maintaining
their competitive position in international markets as
well as in domestic ones.0

,2ln addition to similar composition and operating ratios, District
manufacturing also resembled U.S. manufacturing in the relative
importance of export industries, a factor that could influence manu­
facturing growth. The U.S. Census Bureau’s Annual Survey of Manu­
factures (Origin of Exports of Manufactured Products, 1987) reported
that, in 1984, exports accounted for 5.8 percent of District manufac­
turing's shipments, compared with 6.7 percent nationally.
13See Tatom (1986a), pp. 14-15.


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Federal Reserve Bank of St. Louis

Uneven Growth and Structural Change
The declining growth o f some mature industries,
especially metal production, is sometimes cited as an
example o f the decline o f manufacturing. As table 1
shows, however, the growth o f primary metal produc­
tion is not typical o f manufacturing as a whole. While
the District's total MP expanded at a 2.6 percent pace
in the 1973—85 period, the average annual growth rate
o f regional prim aiy metals output was zero. Nation­
ally, total MP grew at a 2.9 percent rate while primaiy
metals output fell at a 1.7 percent rate. Because the
sector produced less than 10 percent o f regional or
national MP between 1973 and 1985, however, its slug­
gish performance was offset by the more rapid growth
in other manufacturing industiy groups. For example,
MP o f the nonelectrical m achineiy and electronic
equipment sectors grew at 8.6 and 3.9 percent rates in
the District and at 7 and 6.6 percent rates nationally.
These examples and the data in table 1 point out the
uneven growth among manufacturing's industiy
groups. Despite this diversity among the industries'
growth rates, the uneven growth led to only minor
changes in the industrial composition o f manufactur­
ing between 1972 and 1985. Chart 5 shows the propor­
tion o f total District MP contributed by each of the 10
largest industiy groups. Although there were some
changes in the components o f manufacturing — for
example, the rapid growth o f electronic equipment
output caused that industiy's share to increase, while

FEDERAL RESERVE BANK OF ST. LOUIS

NOVEMBER 1987

C h a rt 5

Composition of District M anufacturing Product, 1 9 7 2 -8 5
P e rc en t of total

80

P rim ary Metals
P a p e r and

Allied

Products

R u b b e r an d Plastics
Printing

and

Publishing

Fabricated M etals

Chemicals

Electrical E q u ip m e n t

Food

and

Kindred

Transportation

Products

Equipment

Nonelectrical M achinery

1972

74

76

the sluggish expansion o f prim aiv metals output
caused its share to shrink — overall, the composition
o f District manufacturing throughout this period re­
mained relatively constant.



78

80

82

1984

SUMMARY
In both the nation and the Eighth District, em ploy­
ment growth in the manufacturing sector has not kept

13

FEDERAL RESERVE BANK OF ST. LOUIS

pace with the rest o f the econom y’s employment
growth, leading some observers to view manufactur­
ing as an ailing industry. Output trends, however,
provide a different picture of manufacturing perfor­
mance. Nationally, real manufacturing output has
grown as fast as the other sectors o f the economy.
Labor productivity in manufacturing has grown faster
than in the rest o f the economy, allowing manufactur­
ing to produce a constant proportion o f national out­
put with a declining proportion o f its labor force.
Not all regions shared in the nation’s manufacturing
stability. Rapid growth in the South and West offset
declines in northern industrial areas. In the Eighth
District, however, the growth o f manufacturing em ­
ployment and output w ere quite similar to the na­
tional expansion in the 1972-85 period. This parallel
growth was made possible by similarities in com posi­
tion, labor productivity and unit labor costs.
Although some individual manufacturing indus­
tries contracted sharply since the early 1970s in terms
of real output, others grew briskly as the composition
of manufacturing evolved in response to consumer
demands and comparative advantage. The overall
trends point to the stability and increased productiv­
ity o f the Eighth District and U.S. manufacturing sec­
tors.


14


NOVEMBER 1987

REFERENCES
Crandall, Robert W. “The Transformation of U.S. Manufacturing,”
Industrial Relations (Spring 1986), pp. 118-30.
Kendrick, John W., and C. Milton Jaycox. “ The Concept and Esti­
mation of Gross State Product,” Southern Economic Journal
(March 1965), pp. 153-68.
Mandelbaum, Thomas B. “The Eighth District’s Economy: A Micro­
cosm of the Nation’s,” Business — An Eighth District Perspective
(Summer 1987).
Niemi, Albert W., Jr. “ Gross State Product and Productivity in the
Southeast, 1950-80,” Growth and Change (April 1983), pp. 3-8.
Ott, Mack. “ The Growing Share of Services in the U.S. Economy —
Degeneration or Evolution?” this Review (June/July 1987), pp. 5 22.

Tatom, John A. “ Domestic vs. International Explanations of Recent
U.S. Manufacturing Developments,” this Review (April 1986a), pp.
5-18.
________ _ “ Why Has Manufacturing Employment Declined?” this
Review (December 1986b), pp. 15-25.
U.S. Bureau of the Census. Annual Survey of Manufactures (Geo­
graphic Area Statistics). (GPO, various years).
________ _ Annual Survey of Manufactures, (Origin of Exports of
Manufactured Products). (GPO, 1987).
----------------Census of Manufactures (Geographic Area Statistics).
(GPO, various years).
Weber, Richard E. “ A Synthesis of Methods Proposed for Estimat­
ing Gross State Product,” Journal of Regional Science (March
1979), pp. 217-30.

FEDERAL RESERVE BANK OF ST. LOUIS

NOVEMBER 1987

Appendix
Computing District Manufacturing Product
Manufacturing product (MP) data com puted by the U.S.
Com m erce Department measures that portion o f the na­
tion's real GNP originating in manufacturing. No corres­
ponding measure is available at the state or regional level.
While the value o f shipments and gross value added are
related measures, the shaded insert explains h o w they
differ from MP.
T o com pute a measure o f District manufacturing output
corresponding to national MP, the m ethodology developed
by Kendrick and Javcox (1965) and m odified by Niem i (1983)
and W eber (1979) was follow ed. District MP is an estimate o f
the sum o f manufacturing output in the four states that
dom inate the District econom y — Arkansas, Kentucky, M is­
souri and Tennessee. MP was derived by estimating output
for each o f the District's 20 manufacturing industiy groups
and sum m ing over all industry groups.

(1) PMPiin= (MP„US/EI11,S)E11U
w here M P is real GNP originating in the nation's m anufac­
turing industiy group i, year t, E represents earnings, and
the US and D subscripts sym bolize the U.S. and the Eighth
District, respectively. Earnings and U.S. M P data are pub­
lished by the U.S. Com m erce Department. Earnings include
wages and salaries, other labor incom e and p roprietoiy
income.
The prelim inaiy estimates resulting from equation 1 will
be accurate to the extent that the ratio o f M P to E in each
industiy group is similar in the District and the nation. This
assumption has been interpreted as one o f similar prod u c­
tivity at the regional and national levels. In the second step
o f com puting District MP, the prelim inary estimates for
each industiy group w ere adjusted by a measure o f that
industry’s productivity in the District relative to the nation.
This procedure was developed by Niem i (1983). The m ea­
sure o f relative productivity is the ratio o f gross value added
p er dollar o f payroll for the District to gross value added per
dollar o f payroll in the nation, or

District MP was com puted in two steps. First, prelim inaiy
estimates w ere calculated assuming that the ratio o f output
to earnings in each manufacturing industiy was identical in
the District and the United States. In the second step, the
prelim inaiy estimates w ere adjusted to correct for produ c­
tivity differences betw een the District and the United States.

w here GVA and P are gross value added and payroll data

More specifically, the first step in estimating District MP
is to m ultiply the ratio o f national output to national earn­
ings in each o f the industiy groups bv District earnings in
that industiy. That is, the prelim inaiy estimate o f District
output originating in industiy group i, year t is:

published by the U.S. Bureau o f the Census’ Annual Survey
o f Manufactures and the Census o f Manufactures. For each
industry group, the relative productivity measure was m ul­
tiplied by the prelim inaiy estimates (PMP,,,,) to com pute the
final estimates. Total manufacturing output is the sum of
the final estimates for all industiy groups.




(2) (GVAil,)/Pill))/(GVAlll1s/P,ll(s),

15

FEDERAL RESERVE BANK OF ST. LOUIS

NOVEMBER 1987

The Great Bull Markets 1934—29
and 1983—87: Speculative Bubbles
or Economic Fundamentals?
G. J. Santoni

Every so often, it seems, humankind almost en masse has a com pulsion to
speculate, and it yields to that com pulsion with abandon.
— Robert T. Patterson, The Great Boom and Panic, p. xiii.

M

ANY people attribute the bull market o f 192429 and the subsequent collapse in stock prices to a
“speculative bubble.” 1 According to this view, the
crash was inevitable because it was only a matter of
time until the bubble burst (see shaded insert on
opposite page).
The same theoiy of stock price formation is used to
describe the bull market o f 1982-87. Recent discus­
sions have characterized this bull market as the prod­
uct o f "unexpected insanity,” subject to "trading fads
and frenzies rather than econom ic fundamentals” and
“out of control.”- Comparisons between the 1920s and
1980s like the one summarized in chart 1 have ap­
peared recently in the press.3 Chart 1, which plots
quarterly data on the levels o f the Dow Jones Indus­

G. J. Santoni is a senior economist at the Federal Reserve Bank of St.
Louis. Thomas A. Polimann provided research assistance.
'See the shaded insert on page

trial Index over the two periods, shows that the behav­
ior o f stock prices in both periods is similar.4Both bull
markets began in the second quarter o f the year; each
lasted 21 quarters; each hit its peak in the third quarter
with the timing o f the peaks separated by only a few
days (September 3, 1929, and August 25,1987); in each
case, 54 days elapsed between the peak and the crash;
and each crash stripped slightly more than 20 percent
from the stock market averages.
The belief that speculative bubbles might cause a
persistent deviation in stock prices from the price
consistent with the fundamentals is important. At the
time o f the 1929 crash, it spawned legislative proposals
that w ould curb credit for speculation, amend the
National Banking and Federal Reserve acts, impose an
excise tax on stock sales and regulate the activities o f
stock exchanges and investment trusts.' Furthermore,

and Kindleberger (1978), p. 17.

2“ Abreast of the Market” (1987) and Jonas and Farrell (1986).
3See, for example, Koepp (1987), Powell (1987), Schwartz and
Tsiantar (1987) and Wall Street Journal (1987).


16


4Scale (1982-87) = 8 x scale (1924-29).
r'New York Times (October 25, 1929).

NOVEMBER 1987

FEDERAL RESERVE BANK OF ST. LOUIS

Some Popular Notions Regarding the
Cause of the 1929 Crash
“Gambling in stock has become a national disease . . .
Neither assets nor earnings, large as the earnings have
been in many instances, warrant the market values of
hundreds of stock issues. There has been an inflation (in
stock prices) not free from the charge of criminality,... It
was inevitable that a day of reckoning would come and
the billions would be lost as the water and hot air were
eliminated from hundreds of stock issues.” Senator King,
New York Times (October 25, 1929).
“The bull market was created by phenomenal profits
in a few leading shares. Even in these shares there were
not sufficient profits to justify the prices which prevailed
before October 1928." Niebuhr (1930), p. 25.
“This growth (in stock prices) was matched by wide­
spread, intense optimism which in the end deteriorated
into lack of perspective and discipline. This optimism
went so far in places that people began to believe that
there was such a thing as 'permanent prosperity’ and
that economic crises could be eliminated.” Roepke
(1936).
"As already so often emphasized, the collapse in the
stock market in the autumn of 1929 was implicit in the
speculation that went before.” Galbraith (1955), p. 174.
“The most common explanation of the Crash to this
day is that the market was overpriced because of specu­

if stock price bubbles exist, econom ic policymakers
face a difficult problem because bubbles suggest that
plans to save and invest may be based on irrational
criteria and subject to erratic change.'1
The purpose o f this paper is to compare the im pli­
cations of a theoiy o f stock prices based on fundamen­
tals to one that allows for bubbles, then to examine

6Keynes (1935), p. 159. Keynes discussed erratic shifts in the invest­
ment schedule caused by changes in the "state of confidence” (pp.
153-55) and ' speculation” (p. 161). He argues that a
“ . . . boom which is destined to end in a slump is caused,
therefore, by the combination of a rate of interest, which in a
correct state of expectation would be too high for full employment,
with a misguided state of expectation which, so long as it lasts,
prevents this rate of interest from being in fact deterrent. A boom
is a situation in which over-optimism triumphs over a rate of
interest which, in a cooler light, would be seen to be excessive”
(p. 322).

See, as well, Gordon (1952), p. 378 and Varian (1979).




lation . . .” Wanniski (1978), p. 125.
"In the end, fright may have been what turned retreat
into rout. And that fright may have been partly motivated
by the perception of absurdly high stock prices . .
Schumpeter (1939), p. 876.
“Among the immediate or precipitating causes (of the
crash) were the unjustifiably high prices of common
stocks . . Patterson (1965), p. 215.
"The breakdown of 1929 was as nearly the result of
willful mismanagement and violation of every principle
of sound finance as such occurrence has ever been. It
was the outcome of vulgar grasping for gain at the ex­
pense of the community.” Willis (1930).
“It may be legitimately said that the boom and slump
were caused by the alternate domination of greed and
fear, and that the one was bound to resign sooner or later
in favor of the other,. . Hodson (1933).
“Never a boom and high prosperity without an out­
break of speculation. Never such an outbreak that has
not ended in a financial crisis.” Snyder 11940).
“Might one still suppose that this kind of stock market
crash (in 1929) was a rational mistake, a forecast error
that rational people might make? This paper . . . implies
that the answer is no.” Shiller (1981), p. 422.

evidence from the 1920s and the 1980s to determine
which set o f implications is supported by the data.
The behavior o f stock prices during these two periods
is particularly useful in testing asset prices for the
presence o f speculative bubbles. The 1924—29 experi­
ence is one o f the most significant bull markets in U.S.
history in both its duration and rate o f advance.
Though not quite as dramatic, the behavior o f stock
prices in the 1980s has been similar. If stock price
bubbles exist, these are likely places to look for them.

THE FUNDAMENTALS
OF STOCK PRICES
People value comm on stocks for their expected
return. Since investors may choose among broad cate­
gories o f stock, the expected return on any particular
stock must be equal to the expected return on other

17

FEDERAL RESERVE BANK OF ST. LOUIS

NOVEMBER 1987

Chart 1

The Bull M arketsof the 1920s and 1980s11
Dow Jones Industrial Index (Nominal Values)
1982
1

2

3

1983
4

1

2

3

1984
4

1

2

3

1985
4

1

2

3

1986
4

1

2

3

1987
4

1

2

3

4

| i i i i i i i i i i i i i i i i i i i i i i r~|
D o w Industrials
1 9 2 4 - 2 9 scale

D o w Industrials
1982-87 scaled

|_1_ Sources: Moore (1961), pp. 109 ,145 and Economic Report of the President.
Various years.
[ 2 Scale 1982-87 = 8x Scale 1924-29.


http://fraser.stlouisfed.org/
18
Federal Reserve Bank of St. Louis

NOVEMBER 1987

FEDERAL RESERVE BANK OF ST. LOUIS

stocks o f similar risk. For example, if a particular stock
is expected to yield a relatively lo w return, investors
w ill shun it causing its price to fall. This raises its
expected return. The reverse holds for any stock with
an expected return that is higher than other stocks o f
similar risk. An equilibrium exists when the expected
returns are equal across equally risky stocks. Econo­
mists call this equilibrium return the required dis­
count rate. Equation 1 calculates the expected return
from holding a stock for one year assuming dividends
are paid at year-end.7
(1) Expected Rate o f Return =
Forecast o f price at year end + Forecast
of dividend —Current Price
Current Price
Equation 2 solves equation 1 for the current price by
noting that the expected return is equal to the re­
quired discount rate in equilibrium.
(2) Current Price =
Forecast o f price at year-end + Forecast
o f dividend
(1 + Required discount rate)

The Price Depends on Forecasts
o f Future Outcomes
The important thing to note in equation 2 is that
the current price depends on forecasts o f fu tu re out­
comes which, o f course, are subject to change as new
information becomes available. The price does not
depend on dividends that are observed in the present
as Senator King and others have im plied in their
comments on the behavior o f stock prices during the
1920s (see shaded insert on page 17). The current price
may change even though observed dividends do not
and conversely.

How Far Ahead?
The discussion so far indicates that investors
must forecast the price o f the stock next period. What
are the fundamentals for this future price? In princi­
ple, the future price depends on the stream o f divi­
dends and the required discount rate investors expect
to prevail over the life o f the firm. Typically this re­
quires forecasts that extend into the distant future and
suggests that the job o f analyzing stock prices is formi-

7See Brealey (1983), pp. 67-72, and Brealey and Meyers (1984), pp.
43-58.




dable. It is sometimes possible to simplify the calcula­
tion, however. If dividends are expected to grow at a
constant annual rate and the discount rate is con­
stant, the calculation can be simplified as shown in
equation 3.8
(3) Current Price =
Forecast o f dividend
Required discount rate - Expected growth
rate o f dividends

The Price Fundamentals
Restating the solution for the current price as in
equation 3 is particularly useful for the purposes o f
this paper. Equation 3 is a list o f the price fundamen­
tals: the forecast o f the dividend next period, the
required discount rate, and the expected (forecast)
growth rate o f dividends. The solution for the current
price in equation 3 is called the fundamentals price.
Furthermore, the equation can be used to show how
relatively small changes in forecasts can account for
relatively large changes in the fundamentals price. For
example, suppose investors forecast a year-end divi­
dend o f $.60 per share, an annual dividend growth rate
o f 6 percent and the required discount rate is 8 per­
cent. Equation 3 indicates that the fundamentals price
is $30 per share [ = .6/( 08 —.06)]. N ow suppose that
new information leads investors to low er the forecast
o f dividend growth to 5 percent. This is a decline of
about 17 percent in expected growth [ = (.01/.06)100].
The fundamentals price, however, declines to $20
[ = .6/(.08 — .05)], or more than 30 percent. Notice that a
large decline in price may occur even though observed
dividend payments do not change. It is even possible
for the price to decline when observed dividends rise.

STOCK PRICES AND MEASURES
OF THE FUNDAMENTALS
Table 1 shows annual average growth rates o f the
D ow Jones Industrial Index in each year during the
two bull markets.9 The index rose rapidly during the

“Brealey (1983), p. 69. The current price is defined by equation 3 only
if the expected growth rate in dividends is less than the required
discount rate.
9The data on stock prices used in this paper are daily closing levels of
the Dow Jones Industrial Index. Daily closing levels of this index are
available on a consistent basis from January 1915. See Pierce
(1982). When possible, the statistical results obtained with this data
were checked against results using daily closing levels of the
Standard and Poor’s Composite Index. In no case were any qualita­
tive differences observed.

19

FEDERAL RESERVE BANK OF ST. LOUIS

NOVEMBER 1987

Table 1
Growth Rates in Stock Prices (annual
average growth rates)1
Panel A: 11/1924-111/1929
Period

Dow Industrials

11/1924 —IV/1924
IV /1 92 4- IV/1925
IV /1 92 5- IV/1926
IV /1 92 6- IV/1927
IV/1927 - IV/1928
IV /1 92 8- 111/1929

32.8%
34.6
1.5
21.5
32.7
37.7

Average 11/1924 - III/19292

25.7%

Panel B: 11/1982-111/1987
Period

Dow Industrials

11/1982 - IV/1982
IV/1982 - IV/1983
IV/1983 - IV/1984
IV /1 98 4- IV/1985
IV/1985 - IV/1986
IV/1986 —111/1987

40.1%
20.9
-4 .4
17.8
26.8
31.5

Average 11/1982-III/1 9 8 7 2

20.0%

’Computed from quarterly averages of seasonally adjusted data.
See Moore (1961), pp. 106-09.
2ln computing this average, the growth rates for each period are
weighted by the length of the period.

initial phases o f the bull markets, slowed down con­
siderably in 1926 and 1984, then rose rapidly through
the third quarters o f 1929 and 1987.
A rapid advance in stock prices is not surprising if it
results from changes in the fundamentals. The investi­
gator, however, seldom has the luxury o f direct obser­
vation o f the fundamentals. Instead, other variables
(proxies) that are believed to provide information
about the behavior o f the unobserved fundamentals
must be used. For example, credit market interest
rates and actual dividend payments have been used to
proxy the required discount rate and the expected
stream o f future dividends. It is important to recognize
that, at best, the behavior o f these (or other) proxies
may give only a rough approximation o f the behavior
o f the fundamentals and, on occasion, they may be
entirely misleading. The 1920s may be an example of
the latter case.

20


Long-term rates w ere roughly constant from 1924—
29.'“ Data on actual per share dividends are very
sketchy for this period. One estimate, however, indi­
cates that actual dividends increased at an annual rate
o f about 8.8 percent from 1924—29." W hile this is a
fairly rapid rate o f increase, it is far less than the
growth observed in stock values. (See shaded insert on
opposite page for a more precise estimate o f the rela­
tionship between stock prices and these proxy vari­
ables.) When the market crashed, people like Senator
King pointed to these proxy variables and claimed that
stock prices before October 1929 contained “water
and hot air.” An alternative explanation is that the
proxies give a misleading impression o f the behavior o f
the fundamentals.

FUNDAMENTALS, FOOLS AND
BUBBLES
In order to evaluate the notion that stock prices in
the 1920s and 1980s w ere driven by psychological
factors extraneous to the fundamentals, it is necessary
to be clearer about the implications the alternative
hypotheses have for variables that can be observed by
the investigator. This paper considers three different
theories that potentially explain stock prices: the ef­
ficient market hypothesis, the greater fool theory and
the theory o f rational bubbles.

Efficient Markets and Fundamentals
A long-standing proposition in both economics
and finance is that stock prices are form ed in efficient
markets.'2This means that all o f the relevant informa­
tion currently known about interest rates, dividends
and the future prospects for firms is contained in
current stock prices. Stock prices change only when
new information regarding the fundamentals is ob­
tained bv someone. N ew information, by definition,
cannot be predicted ahead o f its arrival; because the
news is just as likely to be good as it is to be bad, jumps
in stock prices cannot be predicted in advance.
Many present-day stock market analysts are skepti­
cal o f the efficient markets hypothesis.13 Similarly,

10See Friedman and Schwartz (1982), table 4.8, and Homer (1977), p.
352.
"S ee Cowles (1938), p. 389.
12See Brealey and Meyers (1984), pp. 266-81; Malkiel (1981), pp.
171-79; Brealey (1983), pp. 15-18; Leroy (1982) and Fama(1970).
13See Malkiel (1981), pp. 126-79.

FEDERAL RESERVE BANK OF ST. LOUIS

NOVEMBER 1987

The Relationship Between Growth in Stock Prices,
Dividends Per Share and the Interest
Hate: 1872-1930
The following regression estimate relates first differ­
ences in the natural log of the Cowles Commission index
of stock prices, ALnP, to first differences in the natural
logs of the Cowles Commission estimate of per share
dividend payments, ALnD, and the interest rate on long­
term bonds, ALnR. The data are annual and span the
period 1872-1930. The regression estimate is intended to
illustrate the results that are obtained when observed
values of dividends and credit market interest rates are
used to proxy expected dividends and the required
discount rate.
ALnP = .16 + 49ALnD-1.26ALnR.
(.11) (4.54)
(4.07)
Rho
RSQ
SE

= .03
(.23)
= .39
= 10.40

The estimated coefficients of these proxy variables are
significantly different from zero and the qualitative rela­
tionship between stock prices and these proxies is the
same as that expected for their theoretical counterparts.

traders in the 1920s generally did not subscribe to it
(see shaded insert on following page). But that is not
important. If the behavior o f stock prices is consistent
with the implications o f the theoiy, the hypothesis
helps both to understand bow stock markets work
and to evaluate the claim that the bull markets were
products o f price bubbles.
If the efficient markets hypothesis is correct, past
price changes contain no useful information about
future price changes. With some added assumptions,
this can be translated into useful empirical proposi­
tions. If the expected return to holding stock is con­
stant and the volatility o f stock prices does not change
during the time period examined, the efficient market
hypothesis implies that observed changes in stock
prices should be uncorrelated and that price changes
should not exhibit long sequences o f successive
changes that are greater or less than the median
change for the sample.



There is a considerable amount of "noise” in the esti­
mate, however, in the sense that variation in the proxy
variables explains a relatively small amount (about 40
percent) of the variation in stock prices.
More importantly, the estimated equation performs
veiy poorly in 1929 and 1930. For example, the percent­
age change in stock prices predicted by the regression
estimate for 1929 is -1.24 percent. Stock prices actually
rose in 1929 bv 23.86 percent. The deviation of the actual
from the predicted value is 25.10 percent. This deviation
exceeds two standard errors of the estimate, indicating
that such a large deviation is not likely to result from
chance. In short, it suggests that the large increase in
stock prices in 1929 was unrelated to movements in the
proxy variables. In the case of 1930, the actual decline in
stock prices exceeds the predicted decline by more than
two standard errors. This pattern — a significantly larger
percentage increase in stock prices than predicted for
1929 and a significantly larger decrease in stock prices
than predicted for 1930 — appears to be consistent with
the notion that a speculative bubble was responsible for
a boom in prices and a crash when the bubble burst.

The above propositions should hold even if the level
o f stock prices appears to drift upward or downward.
These propositions concern the relationship between
the sequence of price changes, not the average change
over some specific period. Clearly, stock prices drifted
upward during both bull markets; but that does not
necessarily mean that price changes w ere correlated
or that there were long runs o f positive changes that
exceeded the median change for these periods. Put
differently, it does not necessarily mean that market
participants w ere able to predict future changes in
stock prices by observing the past.

Greater Fools
The notion that self-feeding speculative bubbles,
on occasion, can drive stock prices is known as the
“greater fool theoiy.” According to this theoiy, people
regard the fundamentals as irrelevant. Rather, they
buy stock on the belief that some (bigger?) fool will buy

21

FEDERAL RESERVE BANK OF ST. LOUIS

NOVEMBER 1987

What Some Big Plungers Thought of
Efficient Markets1
William C. Durant

Arthur W. Cutten

Durant had been acquiring a large interest in Ameri­
can Smelters and its share price had risen from $119 to
$140. One day during this period a friend burst into his
office and exclaimed, “Now look here, Billy, what are you
doing with Smelters? You know it’s not worth $140."
"Possibly not,” Durant said, "but take my advice and
don’t sell me any more of it, because it’s going much
higher.” The stock went to $390 on a split share basis.

"Yes, I have taken my bit out of the market. Oh, quite
a bit. But I would advise other men to stay away from it. If
I had a son I wouldn’t let him touch it with a ten-foot
pole.

Jesse Livermore
"A gambler is a man who doesn't know the market.
He goes to a broker and says, 'What can I do to make a
thousand dollars?’ He is only an incident. The specula­
tive investor buys or sells against future conditions on
his knowledge of what has happened in the past under a
similar set of conditions."

Louis W. Zimmerman
Zimmerman employed a team of experts to study
the market constantly. He never purchased a stock until
he received a final report from the analysts concerning
the condition of the company.

the shares from them at a higher price in the future.
People maintain this belief because they think “that
market values will rise — as they did yesterday or last
week — and a profit can be made.” '4Once the specula­
tion begins, stock prices continue rising because peo­
ple, seeing the rise in the previous period, demand
additional shares in the belief that prices w ill continue
to rise. This pushes prices still higher.
The greater fool theory is based on the presumption
that there are times when past movements in stock
prices matter. According to this theoiy, during the
“fooling” periods, there should be positive correlation
in the past sequence of price changes and long runs o f
positive changes that exceed the median change for
the sample period.

There are too many wrecks down there in the pit.
People call them brokers. They are only part of that —
the broke part.”
* *

*

The efficient markets hypothesis (EMH) suggests that
Durant was lucky. He could not have known that the
price of American Smelters would rise. Livermore's eval­
uation of the "gambler’s” strategy vs. the "investor's”
contradicts the implication of EMH that the strategy of
each is just as likely to succeed (or fail). Similarly, EMH
suggests that hiring teams of experts, as Zimmerman
did, is not expected to result in raising the return from
stock purchases above a normal return. This applies to
Cutten's comment regarding brokers who, according to
EMH, are expected to earn a normal return on their stock
trades, not a negative return as suggested by Cutten.

’ See Sparling (1930), various pages.

Rational Bubbles
Recently, some economists have discussed the
possibility that stock prices may contain "rational”
bubbles.15The theoiy o f rational price bubbles is based
on the belief that some asset prices (for example,
stock, gold and foreign currency prices) are too vari­
able to be justified by variation in the fundamentals.16
(A more formal theoiy of price bubbles is summarized
in the appendix to this paper.) Briefly, the th eoiy says
that there may be occasions w hen stock prices deviate
from the price that is consistent with the fundamen­
tals. The deviation is called a bubble.

,5See Flood and Garber (1980 and 1982), Blanchard and Watson
(1982), West (1986), Diba and Grossman (1985 and 1986) and the
appendix to the paper.
'"Galbraith (1955), p. 23. See, as well, Malkiel (1981), pp. 31-49.


http://fraser.stlouisfed.org/
22
Federal Reserve Bank of St. Louis

,6See, for example, Shiller (1981) and Mankiw, Romer and Shapiro
(1985).

FEDERAL RESERVE BANK OF ST. LOUIS

Bubbles must possess certain characteristics if they
are to have econom ic significance:
Bubbles must be persistent so that a forecast o f stock
prices based solely on the fundamentals is biased.
This means that forecast errors (actual price minus
forecast price) w ill tend to have the same sign and not
average out. The persistence o f one-sided errors is
important because random variation in the data gen­
erally w ill cause the actual price to differ from any
well-constructed forecast o f the price even though a
bubble is not present. If bubbles w ere only a name
used to describe random variation in the data, they
w ould not be very interesting.
Bubbles must be explosive in the sense that they
must grow at a rate that compensates the stock pur­
chaser for the additional amount invested in the stock
due to the bubble. In addition, there may be a risk
premium to compensate stockholders for the addi­
tional risk that the bubble may burst.17This character­
istic causes the price to deviate further and further
from the fundamentals for as long as the bubble lasts.
Bubbles can not be negative. A negative bubble
means that stock prices are less than im plied by the
fundamentals. The explosive characteristic o f bubbles
means that the prices im plode with some chance that
stock prices w ill be negative at some future date.18
Negative stock prices, however, are impossible; they
are inconsistent with the liability rules associated with
com m on stock which limit potential losses to the
extent o f the initial investment.

RATIONAL BUBBLES AND STOCK
PRICE BEHAVIOR
The theory o f rational bubbles has implications
for the behavior o f stock prices that are different than
the theory o f efficient markets.19This is shown in table
2, which makes use o f the fundamentals theory o f
stock price determination discussed above. One im ­
portant assumption o f this example is that, at each
m oment in time, investors expect dividends to grow at
a constant rate over the future. To keep things simple,
the example assumes that subsequent events conform

,7See Diba and Grossman (1985 and 1986), Blanchard and Watson
(1982), Flood and Garber (1980), West (1986) and the appendix to
this paper.
,8See Diba and Grossman (1985 and 1986) and Blanchard and
Watson (1982).
19See Diba and Grossman (1985) and the appendix.




NOVEMBER 1987

to the expectations o f investors (perfect foresight, an
extreme version o f rational expectations) and that the
dividend is initially expected to be $2. The expected
dividend is constant in panel A (expected growth rate
is zero) but grows in panel B at an expected annual
rate o f 2 percent. The required discount rate is 10
percent, and a bubble o f $1 occurs in period zero.
Column 3 o f panel A computes the fundamentals
price, P[. This is simply the expected dividend, E,(D, t,)
= $2, (assumed constant in panel A) divided by the
difference between the required discount rate, r = .10,
and the expected growth rate in dividends, g = 0. The
fundamentals price is $20 each period.
The fourth colum n computes the bubble com p o­
nent o f the price. As discussed above, the bubble
expands over time at the required discount rate, r. The
observed price, P,, is the sum o f the fundamentals
price and the bubble as in column 5.
Column 6 calculates the percentage changes in the
price. These are positive. More importantly, the num­
bers in column 6 rise over time indicating that this
bubble produces a time series o f observed price
changes that are positively correlated. The observed
price does not follow a random walk. O f course, the
real w orld is never so neat. Changes in the fundamen­
tals — r,g, E,(Dt+1) — may cause the observed price to
change in a w ay that masks the bubble. If that occurs,
however, it is not clear that the bubble is very im por­
tant since an investor’s behavior under the theory of
rational bubbles depends on his ability to detect the
presence o f bubbles.
The example in panel B is similar to the example in
panel A except that dividends are expected to grow at
a 2 percent annual rate. Notice that this does not
change the qualitative result with respect to the ob­
served price changes. These rise over time and w ill be
positively correlated. The only difference between the
two examples is that the fundamentals price in panel
B rises (drifts upward) over time at a constant 2 per­
cent rate (see column 7). This results from the growth
in dividends. W hile the fundamentals price drifts up­
ward at a constant rate o f 2 percent, the sequence o f
changes in the fundamentals price are uncorrelated.
The fundamentals price w ill follow a random walk
with drift.
An important thing to note is that both the greater
fool theory and the theory o f price bubbles discussed
in this paper im ply that stock prices behave similarly.
Both reject the efficient markets hypothesis, which
implies that stock prices follow a random walk.

23

NOVEMBER 1987

FEDERAL RESERVE BANK OF ST. LOUIS

Table 2
Fundamentals vs. Bubbles: An Example
Panel A: Expected growth of dividends is zero
Years

Ei(Dt ,,)

P!

Bt=(1 +r)'B0

P ,= P |+ B t

0
1
2
3
4
5

$2.00
2.00
2.00
2.00
2.00
2.00

$20.00
20.00
20.00
20.00
20.00
20.00

$1.00
1.10
1.21
1.33
1.46
1.61

$21.00
21.10
21.21
21.33
21.46
21.61

.48%
.52
.57
.61
.70

0.0%
0.0
0.0
0.0
0.0

%AP,

%APi

Panel B: Expected growth of dividends is 2 percent
Years

E,(Dti1)

P|

B, = (1 +r)'B0

Pt = P |+ B ,

%APt

%APJ

0
1
2
3
4
5

$2.00
2.04
2.08
2.12
2.17
2.21

$25.00
25.50
26.01
26.53
27.06
27.60

$1.00
1.10
1.21
1.33
1.46
1.61

$26.00
26.60
27.22
27.86
28.52
29.21

2.31%
2.33
2.35
2.37
2.42

2.00%
2.00
2.00
2.00
2.00

Where:

E, (D,.,) = the expected dividend next period
PJ
B,
r
P,
g

=
=
=
=
=

the
the
the
the
the

fundamentals price in period t
bubble in period t and B0 is the initial bubble
required discount rate
observed price in period t
expected growth rate in dividends

P, = P! + B, = E'<D- > + B,
r-9

SOME PROBLEM S WITH BUBBLES
The notion that stock prices are influenced by
bubbles is troublesome because it is not based on a
well-specified theory. A com plete theory o f bubbles
should identify the cause o f bubbles in terms o f some
phenom enon that can be observed separately from
bubbles themselves. On those occasions when the
cause is observed, a bubble should also be observed
and conversely. This allows a direct test o f the theory
and explains w hy bubbles may be observed on some
occasions but not others.
In contrast, the greater fool and rational bubble
theories do not suggest a cause o f bubbles that can be
observed separately. Rather, unusual price behavior
(the bubble) is attributed to “ intense optimism,” “a
compulsion to speculate” and "manias.” These do not

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24
Federal Reserve Bank of St. Louis

identify the cause o f the bubble; they merely give the
bubble a different name.211
These criticisms suggest that attributing crashes in
stock prices to bursting bubbles adds nothing to our
understanding o f w hy crashes occur or how to pre­
vent similar occurrences in the future. To illustrate,

“ Brunner and Meltzer (1987) note that
Some further reflections on bubbles and sunspots equilibria
should make us doubt their contribution to a useful reconciliation
of analysis with critical observations. The bubble term refers
neither directly nor indirectly to any observable entities. It is
fundamentally inconsistent with any rational exploitation of infor­
mation invoked by the same analysis (p. 2).

See, as well, Singleton (1987), pp. 28-30. Slrkin (1975) and Sch­
wartz (1981), p. 25, question the bubble hypothesis as an explana­
tion of the 1929 crash.

NOVEMBER 1987

FEDERAL RESERVE BANK OF ST. LOUIS

Wesley Clair Mitchell (a noted student o f business
cycles) wrote that
By a com bination o f various agencies such as public
regulation o f the prospectuses o f n ew companies, leg­
islation supported by efficient administration against
fraudulent prom otion, m ore rigid requirements on the
part o f stock exchanges concerning the securities ad­
m itted to official lists, m ore efficient agencies forgivin g
investors information, and m ore conservative policy
on the part o f the banks toward speculative booms, w e
have learned to avoid certain o f the rashest errors
com m itted bv earlier generations.21

Mitchell made this statement in 1913 in reference to
the legislative and regulatory precautions instituted
after the Panic o f 1907. Like the crash in 1929, the 1907
crash had been attributed to a speculative bubble.

EFFICIENT MARKETS VS. PRICE
BUBBLES: SOME EVIDENCE
The efficient markets hypothesis suggests that
stock prices follow a random walk. The hypothesis has
no implication for the drift in stock prices. Prices may
be higher or low er at the end o f the period being
examined. Neither o f these events is necessarily in­
consistent with the hypothesis. Rather, the hypothesis
implies that the sequence o f price changes are unre­
lated; they behave as random variables. In contrast,
the greater fool theory and the theory o f rational
bubbles discussed here imply that changes in stock
prices are not random but are positively related.
Which explanation is better supported by the evi­
dence for the 1924—29 and 1982-87 bull markets?
To evaluate these theories, data on the level o f the
D ow Jones Industrial Index are used. Tw o periods are
examined. One extends from January 3, 1928, through
September 3, 1929. The second runs from January 2,
1986, through August 25, 1987. The data are first differ­
ences o f the log of the D ow ’s daily closing level multi­
plied by 100 and are approximately equal to the daily
percentage change in the index. Each sample contains
more than 400 observations. Stock prices advanced
very rapidly in these periods. If bubbles were present,
they should be apparent in these data.

Were Stock Prices A Random Walk?
Table 3 presents the results o f a test (called a BoxPierce test) based on the estimated autocorrelations of
percentage changes in the Dow Jones Industrial In-

21Mitchell (1950), p. 172.




Table 3
Autocorrelation Coefficients and
Box-Pierce Statistics (first differences of
logs of Dow Industrial Index)
January 3,1928 - September 3,1929
To
lag

Autocorrelation
coefficient

Box-Pierce
statistic

1
2
3
6
12
18
24

.0196
- .0325
- .0494
.0200
.0069
- .0521
.0213

.18
.70
1.91
10.41
16.43
21.65
29.58

Mean of series = .128*
= 2.57
t-score
January 2,1986 - August 25,1987
To
lag

Autocorrelation
coefficient

Box-Pierce
statistic

1
2
3
6
12
18
24

.0553
-.0 1 4 0
- .0095
-.0151
- .0076
- .0044
.0024

1.28
1.36
1.40
4.66
7.86
13.14
14.24

Mean of series = .136*
t-score
= 2.83
'Statistically significant at the 5 percent level

dex. This test is designed to determine w hether there
is significant autocorrelation in the data, that is,
whether current changes in the index are related to
past changes. Recall that the efficient markets hypoth­
esis implies that past changes in stock prices are
unrelated to (contain no information about) current or
future changes. An empirical counterpart of this prop­
osition is that changes in the index are not correlated.
Conversely, if the hypothesis that stock prices were
influenced by self-feeding bubbles is correct, percent­
age changes in the index should be positively correl­
ated.
Table 3 shows test results for the two periods dis­
cussed above. None of the test statistics indicate signi-

25

FEDERAL RESERVE BANK OF ST. LOUIS

NOVEMBER 1987

C hart 2

An Illustration of a Random Sequence Vs.
Correlated O bservations11
Panel A : R a n d o m sequence


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26
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FEDERAL RESERVE BANK OF ST. LOUIS

NOVEMBER 1987

Table 4
Runs Test
Sample period

Number of
observations

Observed number
of runs

Expected number
of runs

Variance

Jan. 3 ,1 9 2 8 Sept. 3,1929

495

233

248.0

123.50

Jan. 2, 1 9 8 6 A u g .2 5 ,1987

417

220

209.0

104.00

Expected number of runs = (Number of observations + 1)/2
Variance = (Number of observations - 1 )/4

ficant correlation at conventional confidence levels.22
Stock prices follow ed a random walk, which is consist­
ent with the efficient markets hypothesis.
Table 3 also shows the mean change for each p e­
riod. The means are positive and significantly different
from zero in a statistical sense. Today, the upward
drift in stock prices during these time periods is obvi­
ous. At that time, however, the upward drift is not
something that investors could have bet on with any
confidence.

Runs Test
A run is the number o f sequential observations
that are greater or less than the sample median (the
m iddle value o f the sample). If a series o f observations
exhibits too few runs relative to what is expected for
independent observations, the data are positively cor­
related or drawn from different populations.
The efficient markets hypothesis suggests that ob­
served changes in stock prices are uncorrelated, that
is, the changes are independent o f one another. This
means, for example, that there is no tendency for a
large positive change to be follow ed by another large
positive change. Consequently, the sequence o f ob­
served changes w ill move back and forth across the
median change for the sample fairly frequently as
shown in panel A o f chart 2. If changes in stock prices

22Daily data between October 22, 1929, and March 31, 1930, show
significant autocorrelation at various lags. This is likely a statistical
artifact produced by a substantial increase in the variance of the
data at the time of the crash in October and November that appears
to taper off over time. Consequently, the significant correlations do
not suggest the presence of a bubble. Furthermore, stock prices
were declining at this time and bubbles can not be negative.




are correlated as im plied by the bubble hypothesis,
however, a plot o f the observations in the order that
they appear w ill indicate some tracking as shown in
panel B. This plot crosses the sample median infre­
quently. The example exhibits relatively long and, con­
sequently, few er runs than expected o f independent
observations.23
Table 4 presents the results of a runs test for the bull
markets o f the 1920s and 1980s. The third column of
the table shows the number o f runs observed for daily
percentage changes in the D ow Jones Industrial Index
during each period o f rapidly increasing stock prices.
Column 4 gives the number o f runs expected for a
series o f (495 and 417) independent observations and
column 5 gives the variance o f this series. Since the
observed number o f runs is not much different than
expected, the hypothesis that percentage changes in
the D ow Index behaved randomly during the sample
periods is not rejected by this data.
The evidence on the behavior o f stock prices (as
characterized by the D ow Index) is not consistent with
the notion that stock prices w ere driven by self­
feeding speculative bubbles during the 1920s and
1980s.

CONCLUSION
Many people attribute the stock market crashes of
1929 and 1987 to bursting speculative bubbles. The
perception that stock prices may be driven by bubbles
presents econom ic policymakers with an important
problem because such bubbles suggest that plans to

?3See Wonnacott and Wonnacott (1977), pp. 486-88.

27

FEDERAL RESERVE BANK OF ST. LOUIS

save and invest may be based on irrational criteria and
subject to erratic behavior.
This paper has examined data on stock prices
around the time o f the Coolidge and Reagan bull
markets. The paper provides evidence contrary to the
notion that the crashes w ere the result o f bursting
speculative bubbles. No evidence was found that
changes in stock prices w ere autocorrelated or that
the data contained long runs. Rather, the data suggest
that stock prices follow ed a random walk. This evi­
dence is consistent w ith the efficient markets hypoth­
esis, which is based on the proposition that all rele­
vant and ascertainable information regarding stock
price fundamentals (interest rates, dividends, future
prospects, etc.) is contained in current stock prices.

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Wall Street Journal, January 26,1987.

NOVEMBER 1987

Hodson, H. V. Economics of a Changing World (Harrison Smith and
Robert Haas, 1933), p. 164.
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A History of Interest Rates (Rutgers University

Jonas, Norman, and Christopher Farrell. “ Program Trading: Let the
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Keynes, John Maynard. The General Theory of Employment, Interest
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pp. 44-46.

Manias, Panics and Crashes (Basic

“ How Ripe for a Crash?” Time (October 5,1987),

Leroy, Stephen F. “ Expectations Models of Asset Prices: A Survey
of Theory,” Journal of Finance (March 1982), pp. 185-217.
Malkiel, Burton G. A Random Walk Down Wall Street (W. W. Norton
and Company, 1981).
Mankiw, N. Gregory, David Romer, and Matthew D. Shapiro. “An
Unbiased Reexamination of Stock Market Volatility," Journal of
Finance (July 1985), pp. 677-87.
Mitchell, Wesley Clair. Business Cycles and Their Causes (Univer­
sity of California Press, 1950).

Blanchard, Oliver J., and Mark W. Watson. “ Bubbles, Rational
Expectations, and Financial Markets,” in Paul Wachtel, ed., Crises
in the Economic and Financial Structure (Lexington Books, 1982),
pp. 295-315.

New York Times

Brealey, R. A. An Introduction to Risk and Return from Common
Stocks (The MIT Press, 1983).

Niebuhr, Reinhold. "The Speculation Mania," The World of Tomor­
row (January 1930), pp. 25-27.

Brealey, Richard, and Stewart Meyers.
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Patterson, Robert T.
Company, 1965).

Principles of Corporate Fi­

Brunner, Karl. “ Epilogue: Understanding the Great Depression,” in
Karl Brunner, ed., The Great Depression Revisited (Martinus Nijhoff, 1981), pp. 316-58.
Brunner, Karl, and Allan H. Meltzer. “ Bubbles and Other Essays,”
Carnegie-Rochester Conference Series on Public Policy (Spring
1987), pp. 1-8.
Cowles, Alfred III, and Associates.
1937 (Principia Press, 1938).

Common-Stock Indexes, 1871-

Diba, Behzad T., and Herschel I. Grossman. “ Rational Bubbles in
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_________“ On the Inception of Rational Bubbles in Stock Prices,”
(National Bureau of Economic Research, Working Paper 1990,
1986).
Fama, Eugene F. “ Efficient Capital Markets: A Review of Theory
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(May 1970), pp. 383-417.
Flood, Robert P., and Peter M. Garber. “ Bubbles, Runs, and Gold
Monetization,” in Paul Wachtel, ed., Crises in the Economic and
Financial Structure (Lexington Books, 1982), pp. 275-93.
_________“ Market Fundamentals versus Price-Level Bubbles:
The First Tests,” Journal of Political Economy (August 1980), pp.
745-70.
Friedman, Milton, and Anna J. Schwartz. Monetary Trends in the
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sity Press, 1982).

Moore, Geoffrey H. Business Cycle Indicators, vol. 2 (Princeton
University Press, 1961).
(September 6, October 24, and 25,1929).

The Great Boom and Panic (Henry Regnery

Peters, William S., and George W. Summers. Statistical Analysis for
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Powell, Bill. “The Prophets of Gloom ’87,” Newsweek (September
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The Dow Jones Averages 1885-1980 (Dow Jones-

Roepke, William. Crises and Cycles (William Hodge and Company,
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Schumpeter, Joseph A.

Business Cycles (McGraw-Hill, 1939J, vol.

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Schwartz, Anna J. "Understanding 1929-1933,” in Karl Brunner,
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Schwartz, John, and Dody Tsiantar. “The Market’s Latest Bull
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on Public Policy (Spring 1987), pp. 9-56.
Sirkin, Gerald. “The Stock Market of 1929 Revisited: A Note,”
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________ A Monetary History of the United States, 1867-1960
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Gordon, Robert A.
1952).


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Federal Reserve Bank of St. Louis

The Great Crash (Houghton Mifflin, 1955).

Business Fluctuations (Harper and Brothers,

Mystery Men of Wall Street (Blue Ribbon Books,

Wall Street Journal.

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Wanniski, Jude.
116-48.

NOVEMBER 1987

The Way the World Works (Basic Books, 1978), pp.

Willis, Parker H. “ Who Caused the Panic of 1929?” North American
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West, Kenneth D. “ Dividend Innovations and Stock Price Volatility,”
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1986).

Wonnacott, Thomas H., and Ronald J. Wonnacott. Introductory
Statistics for Business and Economics (John Wiley and Sons,
1977).




29

FEDERAL RESERVE BANK OF ST. LOUIS

NOVEMBER 1987

Appendix
Price Bubbles
The following assumes rational investors with infinite
time horizons and a complete set of markets. With these
assumptions, the solution for the expected price of a share
of stock next period given the information set in t,
E,(P,+1 |wt), is its price this period, P„ plus appreciation
during the period at the market rate of discount, r, • P,, less
the expected dividend in t + 1, E,(Xt+1 |w,l.‘ This relation­
ship is summarized in equation 1.
ID E,(Pt*, |w,l = P, + r,P, - E.IX,,, |w,l
The fundamentals price is the discounted present value of
the expected future stream of dividends. This is shown in
equation 2 for the price in period t.z Note that r, is the i'h
period interest rate.
00

12) P, =

2 e.E.IX,., I wt)
i= l

e , = 1/(1 + r, I1< 1

If the expected dividend receipt is the same in each future
period, E,(XI+I |w,) = E,(X,+1 |w t) for alii; and the yield curve
is flat so that r, = r, for all i, equation 2 can be rewritten in
the following form.3
(3) P, = E,(X1+1 |w,)/r, .
Substituting (3) into (1) and collecting terms gives the solu­
tion that the expected price in period t +1 is the price in
period t.

The notion (expressed by Sen. King and others) that the
Coolidge market was the product of a price bubble that
eventually burst is approximated by a theory that allows
share prices to deviate from the fundamentals price in
period t by bubble, B„ with probability tt.4 The average
duration of the bubble is 1 / ( 1 - t t ) periods before it crashes.
Given the assumptions regarding expected future divi­
dends and the shape of the yield curve, a solution for the
price that allows for bubbles, P,', is:
(5) P,' = E,(X1+1 I Cj),l/r, + B,
B, = t t G' B, , + U, w ith p ro b a b ility

tt

B, = U, w ith probability 1 —tt
E,(U, I <J>, ,) = 0.
Substituting (5) into (1) and collecting terms gives the solu­
tion that the expected price of a share next period is its
price this period plus the appreciation in price due to the
period t bubble.
(61 E,(p;„ I <|>,l = P,'., + r,B,
As long as the bubble lasts, the actual rate of return from
holding the stock exceeds the market rate of discount, r.
This compensates for the risk of a crash in the share price
should the bubble burst.
The price in t 4-1 is the sum of the expected price and a
white-noise error term.
(7) P,\, = E,(P1+1|()V + e, = P,' + r,B, + 6,

E,(P,+1 |w,) = P,.
The observed price in t +1 can be expressed as the period t
expectation of the price in t +1 (which, by the above argu­
ment, is equal to Pt) and a white noise error term, e1+1, as in
equation 4.
(4) Pltl = P, + €ttl
Equation 4 is consistent with the efficient markets solution
for asset prices. It implies that prices follow a random walk.

(81 E,(P,'+, —P,') = r,B, = r.iTe-’B,^ > 0
Notice that the expected change grows over time at rate r so
the market price is expected to deviate further from the
fundamentals price in each subsequent period for as long
as the bubble lasts.
Furthermore, as shown below, the expected percentage
change in the price is not constant.
(9) E,[(P,'

’ See Brealey and Meyers (1984), pp. 45-47, and Blanchard and
Watson (1982), pp. 296-97.
2See Shiller (1981), Blanchard and Watson (1982), West (1986) and
Mankiw, Romer and Shapiro (1985).
3The data are consistent with this assumption during the period
analyzed in the shaded insert on page 21. For example, the average
difference between the yield on high-grade corporate bonds and the
call money rate was -30 basis points, which is not significantly
different from zero (t-score = .74). Furthermore, the data are con­
sistent with the assumption regarding expected dividends. It is not
possible to reject the hypothesis that dividends per share followed a
random walk. The first differences of dividends per share are a white
noise process. The Box-Pierce statistics at lags 6 ,1 2 ,1 8 and 24 are
6.94, 12.33, 14.10 and 17.47. The dividend data are from Cowles
(1938). The data are annual for the period 1871-1930.


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30Bank of St. Louis
Federal Reserve

—P.'l/P,'] = r,B/P,'

Substituting for P ' from (5) and noting that the fundamen­
tals price, P| = E,(X1+l |<|>t)/r,, gives
(10) E,[(P,\,-P,')/P,'] = r,B,/(P; + B,) = r,/(PJ/B, —1).
Since B, grows at rate r, the percentage change in price is
expected to rise over time.
In contrast to the efficient markets solution, bubbles
imply that share prices do not exhibit random walk proper­
ties.

4See Blanchard and Watson (1982), pp. 297-98.