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Federal Reserve Bank of Chicago
Self-Employment as an Alternative to
Unemployment
Ellen R. Rissman
WP 2003-34
Self-Employment as an Alternative to Unemployment
12/02/03
Ellen R. Rissman*
Federal Reserve Bank of Chicago
Research Department
230 S. LaSalle St.
Chicago, IL 60604
erissman@frbchi.org
*
The author would like to thank Dan Aaronson, Dan Sullivan, Bhashkar Mazumder, and Gadi Barlevy
for their helpful comments and insights. The views expressed here are not necessarily those of the
Federal Reserve Bank of Chicago or the Federal Reserve System.
1
Abstract
Data from the NLSY show that more than a quarter of all younger men experience
some period of self-employment. Many of them return to wage work. This paper
analyzes a simple model of job search and self-employment where self-employment
provides an alternative source of income for unemployed workers. Self-employment is
distinct from wage sector employment in two important respects. First, self-employment
is a low-income, low-variation alternative to wage work. Second, once a worker enters
self-employment, he loses eligibility to receive unemployment insurance benefits—at
least until he returns to wage sector employment. The model suggests that flows into
self-employment are countercyclical and flows out of self-employment are procyclical.
Data from the NLSY for males at least 21 years of age are used to investigate how
demographic and economic variables influence the decision to become self-employed.
Fixed effects and random effects logit results indicate that young men are more likely to
be self-employed when their wage work opportunities are more limited. Specifically,
higher local unemployment rates lead workers to self-select into self-employment, as
does past unemployment experience. The process is different for Whites and Nonwhites
with education being irrelevant for White self-employed workers. In contrast, for
Nonwhites higher education reduces the probability of entering self-employment.
2
I. Introduction
There are two divergent views of the self-employed. The first perception, the one
typically encountered in the literature, is one of the visionary or maverick in the mode of
Bill Gates. He is an entrepreneur—an independent worker who accepts risk in return for
a greater reward. His independent nature may add to his own valuation of selfemployment. He may have some kind of ability or entrepreneurial capital that confers
greater returns in self-employment than in wage work. His taste for risk may be different
from others’. Alternatively, the self-employed may be a discouraged wage worker who
finds his offered wages too low or his employment too sporadic in the wage sector. In
other words, he chooses self-employment not because the value of self-employment is so
high but because his value of wage work is so low.
Understanding which of these viewpoints is true is important. Frequently no
distinction is made between the two with researchers and policy-makers alike arguing
that the self-employed generate job growth, foment technological change, and promote
upward mobility.1 Entire institutions and various tax codes have been created to
encourage entrepreneurship and further the benefits these entrepreneurs create. These
alleged benefits may, in fact, be true for the entrepreneurs of the economy. However, for
those self-employed who are discouraged wage workers, the benefits may not be as clear.
For example, if self-employment is chosen because of a lack of opportunities in wage
work, then supplementing self-employment through tax breaks and less restrictive
lending standards may be an inferior way for workers to escape poverty. Increasing their
human capital and implementing policies aimed at reducing the cost of job search may
offer greater social rewards.
According to the household survey, in 2003 almost 7% of private nonagricultural
workers were self-employed. Data collected by the U.S. Census Bureau also provides
some evidence on the incidence of self-employment. The Census Bureau defines a
nonemployer business as one that has no paid employees, has annual business receipts of
$1,000 or more ($1 or more in the construction industries), and is subject to federal
1
Hellwig and Irmen (2001) and Lerner (2002) examine small businesses and technological change. The
notion that small businesses are responsible for a disproportionate share of job growth has been examined
3
income taxes. These nonemployers are typically self-employed individuals or
partnerships operating businesses that they have not chosen to incorporate.2 The number
of workers self-employed in these nonemployer firms is large. In 2000, there were close
to 16.5 million nonemployer businesses. At the same time, there were 134.4 million
nonagricultural worker. Assuming these nonemployer businesses employ only the
owner/proprietor, nonemployer businesses employed close to 12.3% of total
nonagricultural employment.3
Most nonemployer businesses are very small. In 2000 nonemployers accounted
for roughly 3% of business activity in terms of sales or receipts. At the same time
nonemployers accounted for nearly ¾ths of all businesses.
Not only do most small businesses have few to no employees aside from the
owner; they also require little in the way of start-up capital. Hurst and Lusardi (2002)
find that close to 25% of small businesses were started with less than $5,000.
Furthermore, 61% of new business owners in 1994 had less than $5000 of business
equity. Similarly, Meyer (1990) finds that 63% of non-minority males and 78% of black
business owners needed less than $8,700 in 1996 dollars to start their business.
Examining how nonemployers are distributed across industries gives an idea of
how important barriers to entry and start-up capital are to new businesses. This
distribution is shown in Table 1 for NAICS sectors. These self-employed workers were
concentrated in just a few industries. Professional, Scientific, & Technical Services had
the largest number of nonemployer establishments with 15% of the total. The majority of
these were concentrated in professional fields where education or certification acts as a
barrier to entry. These include legal advice; accounting, bookkeeping, and payroll
services; computer services; consulting services; research services; and other
professional, scientific, and technical services.
and dismissed by Davis, Haltiwanger and Schuh (1996). Entrepreneurs have been shown to be more
upwardly mobile than their wage worker counterparts in Bradford (2003) and Quadrini (2000)
2
Self-employed owners of incorporated businesses typically pay themselves wages or salary, so that the
business is an employer.
3
This is far more than the 7% figure obtained from the household survey for the self-employment rate.
There are far more nonemployer firms than there are people reporting that they are self-employed. This
can occur for several reasons. First, individuals may own more than one nonemployer firm. Additionally,
an owner of a nonemployer firm may also have a job in the wage sector. In contrast, data from the
household survey are based upon the respondent’s reply and refers to their latest employment or the job on
which they spend the most time.
4
Most of the remaining nonemployer firms are concentrated in industries or
occupations having little in the way of barriers to entry. For example, 14% of all
nonemployers are found in Other Services excluding public administration. These include
repair and maintenance, and personal care services—fields that require little start-up
capital. An additional 12% of nonemployer firms are found in Construction and ¾ths of
these are special trade contractors involved in plumbing, heating, air-conditioning,
painting and drywalling, electrical contractors, masonry, roofing, concrete contractors,
and carpentry. It can be argued that most of these jobs require little in the way of costly
equipment since the rental market is an available alternative so, again, barriers to entry
are relatively low. Retail Trade accounts for 11% of all nonemployer firms. Almost half
of these (45.4%) are concentrated in nonstore retailers and are direct selling
establishments requiring little overhead. Finally, Real Estate and Rental Leasing account
for 10% of nonemployer firms. These include real estate agents and brokers, and
property managers. Again, these are firms that require little in the way of start-up capital
and require little certification.
These simple data suggest that a large number of firms in the economy are owneroperated with no employees other than the owner, require little in the way of start-up
capital, and have few barriers to entry. One obvious reason for their proliferation may be
their low start-up costs. An alternative reason for the large number of nonemployer firms
may be that these businesses are lucrative. Workers may be attracted to these
proprietorships because they pay well relative to alternatives.
Some simple calculations put this notion in doubt. According to the U.S. Census
Bureau, in 1997 there were 15.4 million nonemployer firms collecting an average receipt
of $37,970 before expenses. Even if 25% of total receipts were profit, average profit per
nonemployer firm would be less than $10,000 in 1997. This figure is probably
understated with many businesses underreporting revenues to avoid taxes. On the other
hand, in order to be included in the sample, the firm needed to record revenues of at least
$1000 (less for construction firms). This censoring leads to an over-estimate of revenues.
Additionally, data from the Internal Revenue Service for Nonfarm Sole
Proprietorship Returns in 2000 show 19.9 million nonfarm businesses with an average
5
receipt of $51,398. Unlike nonemployer firms, these sole proprietorships may have
multiple employees. Net income per proprietorship after wages and salaries was a
relatively small $10,086 in 1997 dollars. On the surface, these businesses do not appear
to generate large incomes for their owners. The same underreporting to escape taxation
occurs here. Additionally, owners may pay themselves a wage or salary in addition to the
profits they receive further understating the benefit to self-employment.
Nevertheless, the average annual earnings of full time wage and salary workers
provides a useful point of comparison. In 1997 private nonagricultural production or
nonsupervisory workers had average weekly earnings of $431.04. This computes to
$22,414 for the year—more than twice the estimated income generated from sole
proprietorships and nonemployer firms.
This rudimentary comparison suggests that self-employment in general does not
pay well as compared to wage sector employment on average. If workers earn more in
wage sector work, why then would anyone choose to become self-employed? One part
of the explanation may be that self-employment offers nonpecuniary benefits that a
simple comparison of earnings does not capture.4 Additionally, the analysis overlooks
the fact that not all workers are able to locate acceptable work in the wage sector, so that
self-employment may be the best alternative available at the time.
The wage sector is dynamic with workers being laid off and seeking
reemployment. If a worker is unable to generate a job offer above his reservation wage,
he has the option of self-employment to supplement his income while continuing to
search for a wage sector job. Evans and Leighton (1989) and Carrasco (1999) examine
the effect of being unemployed on self-employment. Using different data sets, they find
that unemployment increases the likelihood of entering self-employment. In constast,
Blanchflower and Oswald (1991) find a negative relation between unemployment rates
and entering self-employment.
In Section II a search model of self-employment is formulated in which selfemployment is an option available to a worker searching for employment. The model
4
Hamilton (2000) infers that nonpecuniary benefits to self-employment are large. He bases this on
evidence that entrepreneurs have both lower initial earnings and lower earnings growth than in paid
employment.
6
emphasizes the effect of unemployment insurance on the decision facing an unemployed
worker. The worker selects between two alternatives: He can either search for wage
work from unemployment or he can search for wage work while self-employed. Selfemployment offers low but steady income, but pays no unemployment insurance benefit.
The model is simple in that the decision made this period does not influence the
probability of success or failure of an entrepreneurial endeavor in the future. There is no
learning by doing and no learning about a person’s entrepreneurial ability. Liquidity
constraints are also not incorporated.5
In Section III panel data from the NLSY is used to examine the likelihood of a
worker entering self-employment. The sample is restricted to males 21 years of age or
older. To preview the results, the local unemployment rate has a significant positive
effect on the probability of self-employment. This holds true for both Whites and
Nonwhites. Results suggest that Nonwhites select into self-employment because they
have more limited wage sector opportunities. Conclusions are found in Section IV.
II. A Simple Model
Many researchers have thought of self-employment as synonymous with
entrepreneurship. However, people may self-select into self-employment for other
reasons not usually considered in the literature on entrepreurship. For example, a worker
may choose self-employment as a way to supplement his income or self-insure until a
better paying job opportunity becomes available in the wage sector. The model presented
here focuses on the decisions facing these individuals rather than those who self-select
into self-employment because of perceived better entrepreneurial opportunities. The
distinction is an important one. In the model presented here, self-employment is a
“second best” alternative in that most workers would prefer to work in the wage sector if
an acceptable job opportunity arose. In a model of entrepreneurship, the opposite would
be the case with wage sector jobs being inferior to the potential rewards to starting one’s
own business.
5
The effect of liquidity constraints on entrepreneurship has been investigated by a number of researchers.
A partial list includes Evans and Leighton (1989), Evans and Jovanovic (1989), Blanchflower and Oswald
(1991), Cagetti and DeNardi (2002), Holtz-Eakin, Joulfaian, and Rosen (1994a and 1994b), , Dunn and
Holtz-Eakin (2000), and Hurst and Lusardi (2002).
7
The familiar paradigm of job search under uncertainty (Mortensen (1970)) serves
as a useful starting point for a model of self-employment for unemployed workers.
Workers experience periods of unemployment and receive unemployment insurance
benefits for a finite period of time. Searching for wage work is costly and uncertain in
outcome with job search not always eliciting an offer of wage work or producing an
acceptable offer.
In the standard model, the worker chooses optimally between unemployment and
employment in the wage sector. The model presented here differs in that the unemployed
have an alternative available aside from searching for work in the wage sector. A worker
can supplement his income during spells of unemployment with earnings generated from
self-employment. Fixed earnings, lower than those expected to be earned in wage work,
characterize self-employment. These earnings accrue each and every period the worker is
self-employed and are known to the worker. The model is more appropriately thought of
as describing the actions of discouraged workers. These individuals may find it difficult
to locate wage sector jobs, may experience frequent spells of unemployment, and may
find short spells of self-employment helpful in supplementing their income while
unemployed.
A worker can be either employed in the wage sector, unemployed, or selfemployed. Searching for wage sector employment from self-employment is more costly
than searching for wage sector work from unemployment. Let c¢ be the cost of search
for a self-employed worker. Furthermore, let p¢ be the probability that search will result
in an offer for this individual. Similarly, let c and p be respectively the cost of search
and the probability that search will result in an offer for an individual who is
unemployed. To capture the idea that search is more costly and less efficient if selfemployed, it is assumed that c¢ > c and p¢ < p .6 Additionally, it is costly and time
consuming to start a business, however small in scale that business might be. This start-
6
The higher cost of search from self-employment makes intuitive sense since the act of search involves
time spent away from self-employment. The effect of self-employment on the effectiveness of job search
in generating a job offer is not as clear. An alternative possibility is that self-employment makes it easier to
locate a job since the worker is already active in the labor market. This scenario has been ruled out.
8
up cost is fixed, known and given by k. These differing costs of search complicate the
choice decision and directly affect the valuations of search strategies.
Another distinction between wage work and self-employment is in eligibility for
unemployment insurance benefits. Unemployment that originates from wage work is
eligible for unemployment insurance benefits for a finite period of time t . However,
once the worker becomes self-employed, unemployment benefits are terminated.
Clearly, there is an incentive for workers to cheat and claim no self-employment income
so as to continue to receive unemployment benefits. This complication is ignored in the
analysis presented here so as to focus on the clearly defined choices of employment in the
wage sector, unemployment, and self-employment. Movements from employment
directly into self-employment are eliminated both because of the role of unemployment
insurance and because it takes time to set up a business. Consequently, workers enter
self-employment only through an intervening spell of unemployment.
The payoff to self-employment is given by p , which is fixed and known to the
worker. A wage offer in the wage sector is drawn from a wage offer distribution with
cumulative density function given by F ( w) , where w Î [ w, w] .7 The profit from self-
employment cannot be too large, otherwise all workers would select self-employment
over wage work or unemployment. Nor can it be too small since no one would choose
self-employment over the alternative of unemployment.
Let P (p ) be the value of self-employment for a worker who is self-employed
earning p and searching optimally for a job in the wage sector. Furthermore, let W ( w)
be the value of a job in the wage sector paying a wage w for someone who behaves
optimally. It follows that:
{
}
P (p ) = p - c¢ + b p¢[1 - F ( wse0 )]E éëW ( w ) | w > wse0 ùû + p¢F ( wse0 )P (p ) + (1 - p¢)P (p )
(1)
The first term p - c¢ is the net income in the current period from self-employment while
searching for a wage sector job. The discount rate is b . Job search is successful in
generating an offer next period with probability p¢ . However, this offer may or may not
be acceptable. The first term in brackets gives the expected value of an acceptable wage
7
In a model of entrepreneurship, the opposite arrangement would likely motivate the model. The payoff to
self-employment would be uncertain whereas the earnings from wage work would be fixed and constant.
9
offer, which occurs with probability p¢[1 - F ( wse0 )] . If the offer is not acceptable, an
event occurring with probability p¢F ( wse0 ) , the worker continues in his optimal search
while self-employed, which is valued at P (p ) . The third term in brackets captures the
event of no job offer in which case the worker continues to search optimally while selfemployed.
In order to ensure that a worker always prefers to seek wage sector employment to
continuous self-employment, it follows that:
P (p ) >
p
.
(1 - b )
After some manipulation, this requirement becomes:
E éëW ( w) | w > wse0 ùû -
p
c¢
>
(1 - b ) b p¢ éë1 - F ( wse0 ) ùû
.
The expected gain over continuous self-employment of a successful job in the wage
sector must exceed the potential cost of search appropriately discounted. In other words,
the potential wage sector opportunities must be large enough to compensate the selfemployed for giving up his profits while also covering his search costs.
The reservation wage is given by wse0 , which is the wage offer at which the selfemployed worker is indifferent between the two alternatives of continuing in selfemployment and searching optimally or accepting the wage sector job offer, which is
optimally valued at W ( w) . Thus,
W ( wse0 ) = P (p )
(2)
defines the reservation wage for a self-employed worker. The self-employed worker
accepts the job offer if the wage exceeds wse0 and rejects it if the wage offer is less than
the reservation wage.
The decision of a person who is unemployed and has reached the end of his
unemployment insurance benefits can now be characterized. This person picks the better
of two alternatives. He can either remain unemployed, receiving no further
unemployment benefits while searching optimally for wage work. Or alternatively he
can pay a fee of k to set up his own business and search optimally thereafter for wage
10
sector work. The worker receives l while unemployed without benefits. This reflects the
value of leisure alone since there are no further unemployment benefits for which he is
eligible. Let U 0 be the optimal value of being unemployed with no further unemployment
benefits available. Then:
U 0 = max{U u0 ,U se0 }
(3)
u, se
The maximization is over the two actions of searching optimally for wage work from
unemployment and receiving U u0 , or becoming self-employed and searching optimally
from self-employment, receiving U se0 .
The value of searching for wage work for an individual who is unemployed and
receiving no benefits is:
{
}
U u0 = l - c + b p[1 - F ( wu0 )]E éëW ( w) | w > wu0 ùû + pF ( wu0 )U 0 + (1 - p )U 0 .
(4)
The first term l - c reflects the net value of leisure after paying search costs in the current
period. Search results in an offer with probability p. This offer is acceptable
with probability 1 - F ( wu0 ) and generates an expected value of E éëW ( w) | w > wu0 ùû . The
second term in brackets gives the expected value of a wage offer that is rejected because
it is not high enough. A person rejecting this offer receives U 0 , the value of being
unemployed and searching optimally. The last term within brackets is the expected value
of being unemployed and not receiving any offer—an event occurring with
probability (1 - p ) . Again, the worker receives U 0 .
The reservation wage wu0 in this equation is defined as the wage at which the
worker is indifferent between remaining unemployed and searching optimally or
accepting the wage offer. It is simply defined as:
W ( wu0 ) = U 0 .
(5)
Note that wu0 does not necessarily equal wse0 . If the value of being unemployed without
benefits exceeds the value of searching optimally from self-employment, i.e. U 0 > P (p ) ,
then wu0 > wse0 .
11
For a worker who is unemployed and not receiving benefits, the other alternative
is to set up a business and search optimally from self-employment. The one time start-up
cost of a business is k. The value of this alternative is given by:
{
}
U se0 = l - k - c¢ + b p¢[1 - F ( wse0 )]E éëW ( w) | w > wse0 ùû + p¢F ( wse0 )P (p ) + (1 - p¢)P (p ) .
(6)
The first term before the brackets shows net return in the current period of unemployment
after paying the set up cost of a business k while searching for a wage sector job. Job
search results in a job offer with probability p¢ . This job offer is acceptable if it exceeds
the reservation wage wse0 , which is reflected in the conditional expected value. If the
offer is unacceptable, the worker searches optimally from self-employment and receives
P (p ). This is captured by the second term within brackets. Finally, in the event that a
wage offer is not generated—an event occurring with probability (1 - p¢) , the selfemployed worker continues to search and receive P (p ). If there are no further
unemployment insurance benefits,
To examine the role of unemployment benefits, suppose that an unemployed
worker is eligible to receive unemployment benefits b for 1 more period provided that he
does not become self-employed. Once a worker enters self-employment, he is no longer
eligible to receive unemployment benefits until he has an intervening spell of wage work.
Let U 1 be the value of searching optimally for a wage sector job for someone who is
currently unemployed and is eligible for 1 more period of unemployment insurance
benefits. The worker chooses the better of two alternatives:
U 1 = max{U u1 ,U se1 } .
(7)
u, se
He can opt to remain unemployed and search for wage work while receiving
unemployment insurance benefits. The value of this option is given by U u1 .
Alternatively, he can enter self-employment while searching for wage sector work,
collecting unemployment benefits until he receives profits from the business. This
alternative is valued at U se1 .
The value of the option to search for wage work from unemployment is given by:
12
{
U u1 = b + l - c + b p[1 - F ( wu0 )]E éëW ( w) | w > wu0 ùû + pF ( wu0 )U 0 + (1 - p)U 0
U u1 = b + U u0
}
.(8)
The value of the option to enter self-employment and search for wage work is given by:
{
}.
U se1 = b + l - k - c¢ + b p¢[1 - F ( wse0 )]E éëW ( w) | w > wse0 ùû + p¢F ( wse0 )P (p ) + (1 - p¢)P (p )
1
se
0
se
U = b + U = b + l - k - p + P (p )
(9)
Thus,
U1 = b +U 0 .
(10)
For the person eligible to receive one more period of unemployment insurance benefits,
whichever option has the greatest value with 1 more period left of benefits also has the
greater value after benefits expire. The implication is that unemployed workers will
switch to self-employment sooner rather than later. With t periods of benefits available
a person will switch to self-employment no later than t - 1 periods after being laid off.
This result is due to the fact that he receives unemployment benefits for one more period
regardless of his choice of where to search.
The above discussion suggests that in order to have more complicated interactions
between unemployment benefits and the choices a worker makes upon entering
unemployment, it is necessary to have these benefits be contingent upon the worker’s
state, which in turn reflects the choices he makes. A richer description of unemployment
insurance benefits includes the possibility of receiving benefits for multiple periods, but
only so long as the worker is unemployed. Movements into self-employment eliminate
eligibility.8 This type of constraint on benefits alters the tradeoff between searching from
unemployment and searching from self-employment. It also alters the valuation of future
employment.
Let U s be the value of search for a worker who is currently laid off and is eligible
for s more periods of benefits, s = 1,K ,t . The worker must choose optimally between
8
Note that it is assumed that the government can completely monitor whether a person is unemployed or
self-employed.
13
searching for work from unemployment or the alternative of setting up a business and
searching optimally from there. If he searches from unemployment, he preserves his
eligibility to receive unemployment insurance next period even if he does not receive an
acceptable job offer. If he instead sets up a business and becomes self-employed, he
cannot receive unemployment insurance again until he accepts a wage sector job. U s is
given by:
U s = max {U us ,U ses } .
(11)
u , se
It follows that:
{
}.
U ses = b + l - k - c¢ + b p¢[1 - F ( wse0 )]E éëW ( w) | w > wse0 ùû + p¢F ( wse0 )P (p ) + (1 - p¢)P (p )
s
se
1
se
U = U = b +U
0
se
(12)
The value of becoming self-employed and searching optimally while currently eligible
for s more periods of benefits does not depend upon s. The value of this option depends
only upon whether benefits have expired.
Considering the value of searching for employment from unemployment,
{
}
U us = b + l - c + b p[1 - F ( wus -1 )]E éëW ( w) | w > wus -1 ùû + pF ( wus -1 )U s -1 + (1 - p)U s -1 .
The value of search from unemployment depends upon s. The reservation wage is the
wage at which the worker is indifferent between accepting a wage offer on the one hand
and searching optimally for a job next period from unemployment where there is one less
period of unemployment benefit eligibility. The reservation wage is given by:
W ( wus -1 ) = U s -1 .
It can be shown that the reservation wage is increasing in s. As eligibility expires, the
worker’s reservation wage declines so the chances of him accepting a wage sector job
offer increase. For workers who are unemployed longer, the value of searching from
unemployment declines and the relative value of switching to self-employment rises. A
worker will be more likely to switch to self-employment the longer he is unemployed .
Furthermore, a worker will find self-employment relatively more attractive than
unemployment the lower are unemployment insurance benefits b and the less time these
benefits are available t . The relative valuations will also depend upon the wage offer
14
(13)
distribution, the potential profits from self-employment, the costs of starting a business,
the relative costs of search, and the discount rate.
The value of a job paying w is given by:
W ( w) = w + b {lU t + (1 - l )W ( w)} .
The job earns a wage of w in the current period. The following period there is a
probability l that the worker will be laid off. If he loses his job, he receives the value of
being unemployed and receiving unemployment insurance benefits b for t periods, U t .
Otherwise, with probability (1 - l ) he receives the value of continued employment. Let
wut be the reservation wage. It is the wage offer at which the worker is indifferent
between unemployment paying a benefit b for t periods and accepting a job. It is given
by:
W ( wut ) = U t > U 0 .
Thus, the reservation wage for a person receiving unemployment insurance benefits b is
higher than for a person who does not receive any benefits.
For a worker who has recently entered self-employment, the presence of a stream
of future unemployment insurance benefits encourages him to have a higher reservation
wage than he otherwise would have. If he is not successful at obtaining an acceptable job
offer, as these benefits approach expiration, the reservation wage declines. The presence
of a self-employment option provides an additional safety net for the worker and supports
a higher reservation wage. If the self-employment payoff is high enough, it will induce
the worker to switch to self-employment and continue to search.
The model suggests that tax incentives to small businesses and other programs
that encourage self-employment may not be appropriate. Suppose that the effect of these
policies is to artificially raise p , the payoff to self-employment. Workers respond to this
by setting a higher reservation wage than they would have otherwise. Consequently,
workers return to wage work less quickly because of the relative attractiveness of selfemployment. A better use of resources might be to encourage matches between workers
and employers through an information clearinghouse or to subsidize skill programs that
make workers more attractive to potential employers.
15
III. The Data
From the simple model of the previous section, transitions into self-employment
or wage work originate in unemployment. This is an artifact of the way in which search
is modeled. More broadly, the decision to enter or exit from self-employment depends
upon a comparison of the expected values associated with accepting an opportunity in
self-employment and the expected utility of the wages a person could command in wage
work.
It is assumed that the decision to enter self-employment depends upon personal
characteristics that affect the valuations of the alternatives. The model suggests that
cyclical conditions can also affect the decision. These cyclical conditions in the model of
Section II are the layoff probability and the hiring probability. In the model, it is
assumed that cyclical factors do not influence the payoff to self-employment p . Instead,
these cyclical variables act mainly through their effect on the expected valuation of wage
sector employment. An increase in the layoff probability reduces the expected value of
wage work making it more likely that a worker who has been laid off will enter selfemployment. A reduction in the effectiveness of job search from unemployment will also
result in transfers to self-employment. The extension of the time period for which the
unemployed are eligible for unemployment insurance benefits will reduce the flow of
workers into self-employment.
Assuming that the distribution of wage offers can be given by a logistic
distribution, let the net value of self-employment for individual i at time t, yit* , be
described as an unobserved variable with:
yit* = xit1 b1 + xit2 b 2 + e it .
(14)
The net value of self-employment is assumed to depend upon variables that affect the
returns to self-employment, xit1 , and those that affect the return to wage work, xit2 . Some
variables have an effect on both. For example, age, experience, education, and race may
all have an effect on the return to self-employment. However, these variables influence
the wages a person can command in the salaried sector as well. In addition, yit* depends
upon the availability and returns to wage work. As the unemployment rate rises, the
16
availability of work in the wage sector declines and workers self-select into selfemployment.
The net value of self-employment is not observable. Instead, the econometrician
observes whether the worker is self-employed. More formally, the data are described by
the following standard model:
ìï 1 if y*it > 0
yit = í
*
ïî0 if y it < 0.
(15)
If the worker is self-employed, then yit = 1 . If the worker is employed in the wage sector,
then yit = 0 .
The data used in the empirical analysis come from the NLSY panel data covering
the years from 1979 to 1998. Females were excluded from the analysis because of the
more complicated joint determination of their labor force participation and selfemployment decisions. The NLSY follows a group of individuals over time. In 1979
these participants ranged in age from 14 to 22 and included many individuals who had
not yet finished their education. The focus of the empirical work is on the self-selection
of workers whose decisions to enter self-employment are not complicated by the parttime and summer jobs of students. In an attempt to control for this, only workers who are
older than age 21 are included.9
Entrepreneurship is a difficult concept to define and to measure. The empirical
work presented here concentrates instead on self-employment. In each interview year
with the exception of 1994, the NLS inquired as to the class of worker at the current or
most recent job. Responses include working for a private company, the government, selfemployed, and working without pay. In the empirical work that follows, an individual is
defined as self-employed if the worker classifies himself as self-employed and is defined
as a wage worker if he is employed in the private sector or works for the government.
Table 2 below provides information on employment status. Only 7.4% of the
people-years for those 21 years of age or older represents self-employment. The
remaining 92.7% are wage workers. Nonetheless, more than a quarter of the men aged
9
Certainly some individuals will not have completed their formal education by the time they are 21.
Additional work was done focusing on older individuals with little change in the results.
17
21 or older (26.7%) have experienced some self-employment, while almost all have been
in the wage sector at one time or another during the sample period. Once workers are in
the wage sector, they tend to remain in the wage sector. Conditional on ever being
employed in the wage sector, 93% of the observations show employment in the wage
sector. In contrast, self-employment is a more fluid state. Conditional on ever being selfemployed, these individuals are self-employed 26.1% of the time. These figures do not
necessarily imply that workers return to wage work from self-employment. The
normalized within percentage is 79% indicating that the two labor market states are
highly persistent. Similar patterns hold for Whites and Nonwhites, although Nonwhites
tend to be less likely to be self-employed and less likely to stay self-employed.10
Table 3 shows transition probabilities for wage workers and self-employed for the
total sample and for Whites and Nonwhites separately. Only a small percentage of wage
workers transfer into self-employment the following year. About 97% remain in wage
work and 3% transit to self-employment. This general pattern holds true for both Whites
and Nonwhites. Transitions from self-employment back to wage work are relatively high
with 36% and 47% of Whites and Nonwhites moving from self-employment to wage
work while 65% and 53% respectively remain self-employed the following year. The
data support the notion that a substantial percentage of people entering self-employment
do so for short periods of time and subsequently return to wage work.
The model was estimated using a fixed effects conditional logit model. The
estimation was performed for the entire sample and for Whites and Nonwhites separately.
The dependent variable is the indicator of self-employment status. Many different
independent variables were investigated. These include such standard demographic
variables as marital status (MARRY=1 if married and 0 otherwise), urban status
(URBAN=1 if the respondent lives in an urban environment and 0 otherwise),
educational attainment (discussed below), region of residence, AGE and AGE2. Local
labor market conditions were captured by the unemployment rate in the labor market of
the respondent’s current residence.
10
Fairlie and Meyer (2000) provide evidence on White/Nonwhite differentials in self-employment over
time.
18
A person’s health status (ILL=1 if the respondent has health problems that limit
his ability to work) was included to investigate the effect of health limitations on the
decision to enter self-employment. The hypothesized sign of this effect is ambiguous.
People whose health limits the time they can spend working should gravitate to selfemployment if self-employment hours are more flexible. However, the presence of
health benefits in the wage sector may encourage workers with health problems to remain
in the wage sector
Several different specifications were employed to evaluate the effect of education
on the self-employment decision. In addition to GRADE, which is defined as the highest
grade completed, more simple specifications were investigated. These other variables
divided educational attainment into several categories including less than high school,
high school, some college, and college graduate or above. Whichever way education is
measured, the relation between educational attainment and self-employment is
complicated. Those who are better educated may have more labor market opportunities
available and will therefore tend to gravitate to wage sector jobs. At the same time, those
with poor wage sector options may self-select into the self-employment sector.
Alternatively, a higher education may make it easier for workers to recognize and
evaluate self-employment opportunities. But more education may not confer any special
entrepreneurial ability. This ambiguity of the influence of education makes it difficult to
sign a priori the effect of education in the analysis.
Table 4 below shows estimation results for the entire sample and for Whites and
Nonwhites separately. Higher local unemployment rates increase the likelihood of selfemployment for both Whites and Nonwhites. This empirical fact holds true for a wide
variety of specifications. In terms of the model of the previous section, higher
unemployment rates can be interpreted as higher layoff rates and lower job offer rates for
wage sector jobs. The lack of wage sector opportunities pushes workers into selfemployment.
Education affects the decision to enter self-employment for Nonwhites but not for
Whites. In the results of Table 4, the effect of education on the probability of becoming
an entrepreneur is captured by GRADE, which is defined as the highest grade attained.
For Nonwhites, those with higher education levels are less likely to choose self-
19
employment. This suggests that, at least for Nonwhites, self-employment is a reaction to
limited labor market opportunities.
Interestingly, results are unaffected by the urban status of the worker. However,
the marginal significance level for Urban status of Nonwhites is 11.0%, suggesting that
for this group self-employment is more of an urban phenomenon. Marital status does not
have much of an empirical effect for Whites. Although for Nonwhites, the coefficient on
marital status is insignificant at traditional confidence levels, its marginal significance is
10.6% and suggests that for Nonwhites, married workers are less likely to be selfemployed.
A consistent result is that for both Whites and Nonwhites, age and its square are
significant determinants of the probability of self-employment. As people age, they are
more likely to become self-employed. This age effect peaks at 34.5 years for Whites and
39.8 years for Nonwhites. (The oldest person in the sample is 41 years old.) Because the
sample is limited to younger men, the age effect may not capture forces at work for
middle-aged males.
To investigate urban and regional effects, an interaction term was included. If the
respondent lives in the North East in an urban area, the interaction term equals 1 and is 0
otherwise. The interaction terms are similarly defined for the North Central, South, and
West regions. The results of these urban-region interactions are also found in Table 3.
Interestingly, a regional pattern appears with urban Whites being less likely to choose
self-employment in the North Central region. A different pattern emerges for Nonwhites
with nonwhites in urban areas of the South tending to self-selecting into selfemployment.
In addition to the results presented in Table 4, other specifications were examined.
Adding the measure of health status, ILL, does not significantly alter the results.
Including regional dummies without the urban interaction term also has no effect on the
results. Estimation was also carried out investigating the effect of the presence of
children on the probability of self-employment. Several different specifications were
evaluated. These include dummy variables indicating the presence of minor children age
17 or younger, young children age 6 or less, and interaction terms with the presence of
children interacted with marital status. None of these variables were significant.
20
Alternative specifications of age were investigated. Specifically, AGE26_30 is 1
for respondents who are between the ages of 26 and 30 and 0 otherwise. OLD takes on
the value of 1 if the respondent is over 30 years of age and is 0 otherwise. The results are
similar to those presented in Table 3 and are unreported here.
Although the model presented in Section II does not incorporate a liquidity
constraint, other researchers have found that access to capital may be an important
determinant of self-employment status. Those who are better able to self-finance are less
likely to be restricted by liquidity constraints. Thus, people with more wealth should be
more likely to enter self-employment than their wealth-constrained counterparts.
As an attempt to capture this liquidity constraint, lagged household income is
added to the specification. Household income is used rather than a measure of wealth
because of the difficulty in obtaining such a measure. The results for both fixed effects
and random effects conditional logits are found in Table 5. Examination of the fixed
effects estimates show results largely consistent with previous results. Specifically,
higher unemployment increases the likelihood of self-employment. This effect is
significant for Whites only—the effect on Nonwhites is no longer significant. Age and
its square continue to be significant determinants of self-employment. For Nonwhites
education has a significant negative impact on the likelihood of self-employment, as does
marriage. This does not hold true for Whites in the sample.
The effect of lagged income on self-employment is consistent with the liquidity
constraint story. Specifically, the larger is past household income, the more likely are
workers to switch to self-employment. However, there are other reasons why lagged
household income may be an important determinant of current self-employment status
aside from the liquidity hypothesis. For example, high past household income may
indicate the presence of another household wage earner who provides an opportunity for
the partner to be less actively engaged in the wage sector. The analysis does not shed any
light on this conjecture.
It is notable that for the fixed effects estimates, the unemployment rate is no
longer significant for Nonwhites once lagged household income is incorporated. This
finding suggests that lower household income for Nonwhites is correlated with higher
persistent local unemployment rates for Nonwhites. While the notion that liquidity
21
constraints hinder movement into self-employment has some validity for Whites, it is
possible that for Nonwhites the effect is really one of restricted access to labor market
opportunities.
Random effects estimates are also shown in Table 5. Interestingly in this
specification, the unemployment rate has a positive and significant effect on the
likelihood of Nonwhites entering self-employment, as does lagged income. The effect of
marital status becomes more sharply estimated for Nonwhites and clearly has a negative
and significant effect on Nonwhite self-employment. In contrast to the estimates of Table
4 and the fixed effects estimates of Table 5, urban white workers are less likely to be selfemployed in North East, Central, and South regions. Nonwhites are more likely to be
self-employed in the North East, South, and West. The differing regional impact between
the fixed effects and random effects estimates is likely due to the relative lack of
variation in geographic location of respondents. The fixed effects estimates are
dominated by movers. The random effects estimates do not have the same interpretation.
To investigate the idea that unemployment pushes workers towards selfemployment, the employment status at the time of the previous interview was included as
an explanatory variable. If self-employment is a response to poor market opportunities,
then a person who is employed should be less likely to enter self-employment
subsequently than a person who is unemployed. A dummy variable indicating whether a
person was employed in the previous year was included in a fixed effects logit model.
The results are reported in Table 6. For Whites, the higher unemployment rates
significantly increase the probability of self-employment. Interestingly, if a white person
was employed in the previous year (either self-employed or working for a wage), they are
significantly less likely to switch to self-employment in the current period. Results
unreported for unemployment status in the prior year show that the likelihood of being
self-employed in the current year increases significantly if the person was unemployed in
the previous survey year. Prior household income is still associated with an increase in
the likelihood of self-employment. The results suggest that at least for those Whites who
have experienced unemployment, self-employment offers an alternative. For Nonwhites,
the effect of employment in the prior year is not significant. This insignificance holds
true for prior unemployment status as well. However, for Nonwhites the current
22
unemployment rate is not significant after including both the income and lagged
employment status variable. As before, the reason is likely due to the high correlation
among the variables for Nonwhites.
IV. Conclusions
The simple model of selection into self-employment models the choices that
workers make in selecting between wage work on the one hand and unemployment or
self-employment on the other. Self-employment is specifically modeled as an alternative
to unemployment. It offers a steady income but pays no unemployment insurance
benefits. Workers who have not been successful in their job search are more likely to
enter self-employment as a stop-gap measure until they successfully locate wage sector
work.
The simple model is deficient in a number of areas. Specifically, the model is
static in that previous decisions do not have a lasting effect upon the selection problem
the worker faces. The only avenue for past decisions to influence the current state is
through the assumption that unemployment benefits terminate once self-employment is
entered. Obviously, this is an oversimplification that has many options for
complications. The accumulation of wealth and the introduction of liquidity constraints
are one avenue that many researchers have explored. Learning about one’s
entrepreneurial ability is another. Still another avenue for expansion stems from the
human capital literature where workers learn about being an entrepreneur through
experience. In addition to adding these dynamics, the model can be criticized as being a
partial equilibrium analysis. If workers find self-employment more desirable than wage
sector employment, the wages in the wage sector must rise. The more fundamental
question is what determines the returns to self-employment.
The correct interpretation of the factors influencing selection into one sector or
the other is an important one for policy-makers. The empirical results for younger men
suggest that self-employment may be less desirable than wage sector employment
because it is a reaction to limited wage sector opportunities. For Whites and Nonwhites,
workers enter self-employment in response to increasing unemployment. This result
holds consistently across models estimated. For Whites, education does not appear to be
23
an important determinant of the decision to enter self-employment. This does not hold
true for Nonwhites. As education increases and presumably opportunities available to
Nonwhites become more available, the likelihood of entering self-employment declines.
The same discrepancy holds for marital status with Nonwhites who are married tending
to remain in the wage sector. As numerous others have found, greater prior household
wealth or income increases the likelihood of self-employment. This effect holds true for
both Whites and Nonwhites. If self-employment is less desirable than a wage sector job,
as the empirical work suggests, then policies touting self-employment as a panacea for
unemployment, poverty, and economic growth should be rethought or at least evaluated
more carefully. The more pertinent question is whether the self-employed are better off
economically than they would have been had they remained in the wage sector. As is the
norm, more work remains to be done.
24
Table 1: Nonemployers by Industry, 2000
NAICS
Forestry
Mining
Utilities
Construction
Manufacturing
Wholesale Trade
Retail Trade
Transportation & Warehousing
Information
Finance & Insurance
Real Estate & Rental Leasing
Professional, Scientific, & Technical Services
Administration & support and waste management and remediation
services
Educational Services
Health Care & Social Assistance
Arts, Entertainment, & Recreation
Accomodation & Food Services
Other services (except public administration)
Total
Firms
223,175
85,626
13,879
2,014,035
285,118
388,300
1,743,474
746,529
238,425
691,765
1,696,311
2,420,023
% of Total
1%
1%
0%
12%
2%
2%
11%
5%
1%
4%
10%
15%
1,032,306
283,231
1,317,393
781,691
218,447
2,350,227
16,529,955
6%
2%
8%
5%
1%
14%
100%
Source: http://www.census.gov/epcd/nonemployer/
25
Table 2:
The Incidence of Wage Work and Self Employment
1979-1998, Males, Age >20
Overall
Wage Work
Self-Employed
Total
Wage Work
Self-Employed
Total
Wage Work
Self-Employed
Total
Freq
46385
3679
50064
Percent
92.65%
7.35%
100.00%
Between
Within
Freq
Percent
4577
99.37%
1231
26.73%
5808
126.10%
(n = 4606)
Percent
93.05%
26.06%
78.85%
Overall
Freq
Percent
34250
91.87%
3032
8.13%
37282 100.00%
White
Between
Freq
Percent
3385
99.33%
961
28.20%
4346
127.52%
(n = 3408)
Within
Percent
92.32%
27.31%
77.95%
Overall
Freq
Percent
12135
94.94%
647
5.06%
37282 100.00%
Nonwhite
Between
Freq
Percent
1192
99.50%
270
22.54%
1462
122.04%
(n = 1198)
Within
Percent
95.18%
21.45%
81.56%
Source: NLSY
26
Table 3:
Transitions between Wage-Work and Self Employment
Males over Age 21, 1979-1998
Total
Wage Work
Wage Work
96.65%
nobs
36301
SE
36.92%
nobs
1048
Total
92.47%
White
SE Wage Work
3.35%
96.38%
1266
27055
63.08% 35.55%
1752
834
7.53%
91.69%
SE
3.62%
1015
64.45%
1512
8.31%
Nonwhite
Wage Work SE
97.36%
2.64%
9246
251
47.14%
52.86%
214
240
95.07%
4.93%
Source: NLSY
27
Table 4:
Estimation Results for Conditional Fixed Effects Logit Model of SelfEmployment, by Race*
Dependent Variable=1 if Self-Employed, Standard Errors are in Parentheses
UR
GRADE
URBAN
AGE
AGE2
MARRY
North East
Total
White
Nonwhite
Total
White
Nonwhite
0.12287***
0.11040***
0.15676**
0.12426***
0.11081***
0.16173**
(0.03070)
(0.03413)
(0.07117)
(0.03072)
(0.03414)
(0.07152)
-0.02352
0.02759
-0.37865***
-0.02715
0.02394
-0.37844***
(0.04743)
(0.05204)
(0.12709)
(0.04749)
(0.05208)
(0.12708)
-
-
-
-0.06906
-0.15050
0.51800
(0.10134)
(0.10775)
(0.32399)
0.63779***
0.67359***
0.50203***
0.63458***
0.66916***
0.50276***
(0.05876)
(0.06661)
(0.12594)
(0.05887)
(0.06672)
(0.12613)
-0.00895***
-0.00966***
-0.00631***
-0.00902*** -0.00975*** -0.00631***
(0.00098)
(0.00112)
(0.00209)
(0.00098)
(0.00112)
(0.00210)
0.02612
0.08804
-0.28037
0.02248
0.08396
-0.28072
(0.07068)
(0.07821)
(0.17321)
(0.07074)
(0.07826)
(0.17737)
-
-
-
0.10808
0.01974
0.58186
(0.18325)
(0.19975)
(0.50823)
-0.36486**
-0.40191***
0.13345
(0.16106)
(0.16742)
(0.62456)
0.02468
-0.08992
0.5706673*
(0.13267)
(0.14856)
(0.32982)
0.02468
-0.03376
0.49528
(0.17407)
(0.18457)
(0.57274)
North Central
-
-
-
South
-
-
-
West
NOBS
N_GROUPS
-
-
-
13,266
10,393
2,873
13,266
10,393
2,873
1,181
920
261
1,181
920
261
* *** indicates significance at the 2% level, ** indicates significance at the 5% level, and * indicates significance
at the 10% level.
28
Table 5:
Estimation Results for Conditional Fixed Effects and Random Effects
Logit Model of Self-Employment, by Race*
Dependent Variable=1 if Self-Employed, Standard Errors are in Parentheses
Total
UR
GRADE
AGE
0.15316*** 0.15036***
North East
North Central
South
West
Income(t-1)
Constant
NOBS
N_GROUPS
0.12691
0.13856***
0.12256***
0.20439***
(0.04034)
(0.09493)
(0.03429)
(0.03734)
(0.08433)
-0.08603
-0.04290
-0.46286***
-0.03089
-0.02509
-0.20792***
(0.05450)
(0.05902)
(0.16264)
(0.02187)
(0.02409)
(0.07260)
0.48037***
0.66318***
0.71920***
0.47140***
(0.16639)
(0.06750)
(0.07485)
(0.15893)
-0.00584***
-0.00964***
-0.01069***
-0.00585**
(0.00130)
(0.00275)
(0.00113)
(0.00126)
(0.00265)
0.68773*** 0.72840***
(0.07803)
-0.00993*** -0.01076***
(0.00118)
MARRY
Random Effects
Total
White
Nonwhite
(0.03694)
(0.07054)
AGE2
Fixed Effects
White
Nonwhite
0.00379
0.07437
-0.39895*
-0.03073
0.02079
-0.57418***
(0.08336)
(0.09061)
(0.22462)
(0.07411)
(0.07982)
(0.19328)
-0.07065
-0.12396
0.20125
-0.25388*
-0.39911***
0.64326*
(0.21206)
(0.23356)
(0.57082)
(0.13897)
(0.15236)
(0.35652)
-0.32268*
-0.37852**
0.64155
-0.38315***
-0.41456***
0.10352
(0.18397)
(0.19081)
(0.78084)
(0.14053)
(0.13992)
(0.35756)
-0.13833
-0.21162
0.33077
-0.20107*
-0.29422**
0.50019*
(0.15313)
(0.16878)
(0.39981)
(0.12054)
(0.13040)
(0.30355)
-0.02218
-0.07507
0.36985
-0.02565
-0.18166
0.85198**
(0.19840)
(0.20888)
(0.70189)
(0.13977)
(0.15834)
(0.39061)
0.00233**
(0.00107)
-
0.00150***
(0.00029)
-15.87654***
(1.12914)
29,729
0.00247***
(0.00087)
-12.02637***
(2.52318)
8,713
3,334
1,161
0.00114*** 0.00108***
(0.00028)
(0.00030)
9,392
7,779
1613
0.00160***
(0.00027)
-15.31576***
(1.03333)
38,442
991
797
194
4,495
* *** indicates significance at the 2% level, ** indicates significance at the 5% level, and * indicates significance at
the 10% level.
29
Table 6:
Estimation Results for Conditional Fixed Effects Logit Model of
Self-Employment, by Race*
Dependent Variable=1 if Self-Employed, Standard Errors are in
Parentheses
Total
White
0.14822***
0.14434**
0.12456
(0.03703)
(0.04047)
(0.09502)
-0.08249
-0.03872
-0.45866***
(0.05443)
(0.05899)
(0.16197)
AGE
0.70251***
0.74569***
0.48876***
(0.07095)
(0.07856)
(0.16685)
AGE2
-0.01016***
-0.01103***
-0.00597**
(0.00118)
(0.00131)
(0.02757)
0.00775
0.07821
-0.39581*
(0.08343)
(0.09067)
(0.22497)
UR
GRADE
MARRY
North East
North Central
South
West
Income(t-1)
Employed(t-1)
Nonwhite
-0.06980
-(0.12170)
0.19482
(0.21211)
(0.23342)
(0.57250)
-0.32588*
-0.38507**
0.67090
(0.18369)
(0.19048)
(0.78236)
-0.13312
-(0.20587)
0.33522
(0.15313)
(0.16882)
(0.40037)
-0.01491
-(0.06417)
0.35530
(0.19863)
(0.20920)
(0.70289)
0.00116***
0.00110***
0.00235**
(0.00028)
(0.00298)
(0.00107)
-0.20395**
-0.22830**
-0.14199
(0.08880)
(0.10125)
(0.18653)
NOBS
9,392
7,779
1,613
N_GROUPS
991
797
194
* *** Indicates significance at the 2% level; ** indicates significance at the 5% level;
and * indicates significance at the 10% level.
30
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33
Working Paper Series
A series of research studies on regional economic issues relating to the Seventh Federal
Reserve District, and on financial and economic topics.
Dynamic Monetary Equilibrium in a Random-Matching Economy
Edward J. Green and Ruilin Zhou
WP-00-1
The Effects of Health, Wealth, and Wages on Labor Supply and Retirement Behavior
Eric French
WP-00-2
Market Discipline in the Governance of U.S. Bank Holding Companies:
Monitoring vs. Influencing
Robert R. Bliss and Mark J. Flannery
WP-00-3
Using Market Valuation to Assess the Importance and Efficiency
of Public School Spending
Lisa Barrow and Cecilia Elena Rouse
Employment Flows, Capital Mobility, and Policy Analysis
Marcelo Veracierto
Does the Community Reinvestment Act Influence Lending? An Analysis
of Changes in Bank Low-Income Mortgage Activity
Drew Dahl, Douglas D. Evanoff and Michael F. Spivey
WP-00-4
WP-00-5
WP-00-6
Subordinated Debt and Bank Capital Reform
Douglas D. Evanoff and Larry D. Wall
WP-00-7
The Labor Supply Response To (Mismeasured But) Predictable Wage Changes
Eric French
WP-00-8
For How Long Are Newly Chartered Banks Financially Fragile?
Robert DeYoung
WP-00-9
Bank Capital Regulation With and Without State-Contingent Penalties
David A. Marshall and Edward S. Prescott
WP-00-10
Why Is Productivity Procyclical? Why Do We Care?
Susanto Basu and John Fernald
WP-00-11
Oligopoly Banking and Capital Accumulation
Nicola Cetorelli and Pietro F. Peretto
WP-00-12
Puzzles in the Chinese Stock Market
John Fernald and John H. Rogers
WP-00-13
The Effects of Geographic Expansion on Bank Efficiency
Allen N. Berger and Robert DeYoung
WP-00-14
Idiosyncratic Risk and Aggregate Employment Dynamics
Jeffrey R. Campbell and Jonas D.M. Fisher
WP-00-15
1
Working Paper Series (continued)
Post-Resolution Treatment of Depositors at Failed Banks: Implications for the Severity
of Banking Crises, Systemic Risk, and Too-Big-To-Fail
George G. Kaufman and Steven A. Seelig
WP-00-16
The Double Play: Simultaneous Speculative Attacks on Currency and Equity Markets
Sujit Chakravorti and Subir Lall
WP-00-17
Capital Requirements and Competition in the Banking Industry
Peter J.G. Vlaar
WP-00-18
Financial-Intermediation Regime and Efficiency in a Boyd-Prescott Economy
Yeong-Yuh Chiang and Edward J. Green
WP-00-19
How Do Retail Prices React to Minimum Wage Increases?
James M. MacDonald and Daniel Aaronson
WP-00-20
Financial Signal Processing: A Self Calibrating Model
Robert J. Elliott, William C. Hunter and Barbara M. Jamieson
WP-00-21
An Empirical Examination of the Price-Dividend Relation with Dividend Management
Lucy F. Ackert and William C. Hunter
WP-00-22
Savings of Young Parents
Annamaria Lusardi, Ricardo Cossa, and Erin L. Krupka
WP-00-23
The Pitfalls in Inferring Risk from Financial Market Data
Robert R. Bliss
WP-00-24
What Can Account for Fluctuations in the Terms of Trade?
Marianne Baxter and Michael A. Kouparitsas
WP-00-25
Data Revisions and the Identification of Monetary Policy Shocks
Dean Croushore and Charles L. Evans
WP-00-26
Recent Evidence on the Relationship Between Unemployment and Wage Growth
Daniel Aaronson and Daniel Sullivan
WP-00-27
Supplier Relationships and Small Business Use of Trade Credit
Daniel Aaronson, Raphael Bostic, Paul Huck and Robert Townsend
WP-00-28
What are the Short-Run Effects of Increasing Labor Market Flexibility?
Marcelo Veracierto
WP-00-29
Equilibrium Lending Mechanism and Aggregate Activity
Cheng Wang and Ruilin Zhou
WP-00-30
Impact of Independent Directors and the Regulatory Environment on Bank Merger Prices:
Evidence from Takeover Activity in the 1990s
Elijah Brewer III, William E. Jackson III, and Julapa A. Jagtiani
Does Bank Concentration Lead to Concentration in Industrial Sectors?
Nicola Cetorelli
WP-00-31
WP-01-01
2
Working Paper Series (continued)
On the Fiscal Implications of Twin Crises
Craig Burnside, Martin Eichenbaum and Sergio Rebelo
WP-01-02
Sub-Debt Yield Spreads as Bank Risk Measures
Douglas D. Evanoff and Larry D. Wall
WP-01-03
Productivity Growth in the 1990s: Technology, Utilization, or Adjustment?
Susanto Basu, John G. Fernald and Matthew D. Shapiro
WP-01-04
Do Regulators Search for the Quiet Life? The Relationship Between Regulators and
The Regulated in Banking
Richard J. Rosen
Learning-by-Doing, Scale Efficiencies, and Financial Performance at Internet-Only Banks
Robert DeYoung
The Role of Real Wages, Productivity, and Fiscal Policy in Germany’s
Great Depression 1928-37
Jonas D. M. Fisher and Andreas Hornstein
WP-01-05
WP-01-06
WP-01-07
Nominal Rigidities and the Dynamic Effects of a Shock to Monetary Policy
Lawrence J. Christiano, Martin Eichenbaum and Charles L. Evans
WP-01-08
Outsourcing Business Service and the Scope of Local Markets
Yukako Ono
WP-01-09
The Effect of Market Size Structure on Competition: The Case of Small Business Lending
Allen N. Berger, Richard J. Rosen and Gregory F. Udell
WP-01-10
Deregulation, the Internet, and the Competitive Viability of Large Banks
and Community Banks
Robert DeYoung and William C. Hunter
WP-01-11
Price Ceilings as Focal Points for Tacit Collusion: Evidence from Credit Cards
Christopher R. Knittel and Victor Stango
WP-01-12
Gaps and Triangles
Bernardino Adão, Isabel Correia and Pedro Teles
WP-01-13
A Real Explanation for Heterogeneous Investment Dynamics
Jonas D.M. Fisher
WP-01-14
Recovering Risk Aversion from Options
Robert R. Bliss and Nikolaos Panigirtzoglou
WP-01-15
Economic Determinants of the Nominal Treasury Yield Curve
Charles L. Evans and David Marshall
WP-01-16
Price Level Uniformity in a Random Matching Model with Perfectly Patient Traders
Edward J. Green and Ruilin Zhou
WP-01-17
Earnings Mobility in the US: A New Look at Intergenerational Inequality
Bhashkar Mazumder
WP-01-18
3
Working Paper Series (continued)
The Effects of Health Insurance and Self-Insurance on Retirement Behavior
Eric French and John Bailey Jones
WP-01-19
The Effect of Part-Time Work on Wages: Evidence from the Social Security Rules
Daniel Aaronson and Eric French
WP-01-20
Antidumping Policy Under Imperfect Competition
Meredith A. Crowley
WP-01-21
Is the United States an Optimum Currency Area?
An Empirical Analysis of Regional Business Cycles
Michael A. Kouparitsas
WP-01-22
A Note on the Estimation of Linear Regression Models with Heteroskedastic
Measurement Errors
Daniel G. Sullivan
WP-01-23
The Mis-Measurement of Permanent Earnings: New Evidence from Social
Security Earnings Data
Bhashkar Mazumder
WP-01-24
Pricing IPOs of Mutual Thrift Conversions: The Joint Effect of Regulation
and Market Discipline
Elijah Brewer III, Douglas D. Evanoff and Jacky So
WP-01-25
Opportunity Cost and Prudentiality: An Analysis of Collateral Decisions in
Bilateral and Multilateral Settings
Herbert L. Baer, Virginia G. France and James T. Moser
WP-01-26
Outsourcing Business Services and the Role of Central Administrative Offices
Yukako Ono
WP-02-01
Strategic Responses to Regulatory Threat in the Credit Card Market*
Victor Stango
WP-02-02
The Optimal Mix of Taxes on Money, Consumption and Income
Fiorella De Fiore and Pedro Teles
WP-02-03
Expectation Traps and Monetary Policy
Stefania Albanesi, V. V. Chari and Lawrence J. Christiano
WP-02-04
Monetary Policy in a Financial Crisis
Lawrence J. Christiano, Christopher Gust and Jorge Roldos
WP-02-05
Regulatory Incentives and Consolidation: The Case of Commercial Bank Mergers
and the Community Reinvestment Act
Raphael Bostic, Hamid Mehran, Anna Paulson and Marc Saidenberg
Technological Progress and the Geographic Expansion of the Banking Industry
Allen N. Berger and Robert DeYoung
WP-02-06
WP-02-07
4
Working Paper Series (continued)
Choosing the Right Parents: Changes in the Intergenerational Transmission
of Inequality Between 1980 and the Early 1990s
David I. Levine and Bhashkar Mazumder
WP-02-08
The Immediacy Implications of Exchange Organization
James T. Moser
WP-02-09
Maternal Employment and Overweight Children
Patricia M. Anderson, Kristin F. Butcher and Phillip B. Levine
WP-02-10
The Costs and Benefits of Moral Suasion: Evidence from the Rescue of
Long-Term Capital Management
Craig Furfine
WP-02-11
On the Cyclical Behavior of Employment, Unemployment and Labor Force Participation
Marcelo Veracierto
WP-02-12
Do Safeguard Tariffs and Antidumping Duties Open or Close Technology Gaps?
Meredith A. Crowley
WP-02-13
Technology Shocks Matter
Jonas D. M. Fisher
WP-02-14
Money as a Mechanism in a Bewley Economy
Edward J. Green and Ruilin Zhou
WP-02-15
Optimal Fiscal and Monetary Policy: Equivalence Results
Isabel Correia, Juan Pablo Nicolini and Pedro Teles
WP-02-16
Real Exchange Rate Fluctuations and the Dynamics of Retail Trade Industries
on the U.S.-Canada Border
Jeffrey R. Campbell and Beverly Lapham
WP-02-17
Bank Procyclicality, Credit Crunches, and Asymmetric Monetary Policy Effects:
A Unifying Model
Robert R. Bliss and George G. Kaufman
WP-02-18
Location of Headquarter Growth During the 90s
Thomas H. Klier
WP-02-19
The Value of Banking Relationships During a Financial Crisis:
Evidence from Failures of Japanese Banks
Elijah Brewer III, Hesna Genay, William Curt Hunter and George G. Kaufman
WP-02-20
On the Distribution and Dynamics of Health Costs
Eric French and John Bailey Jones
WP-02-21
The Effects of Progressive Taxation on Labor Supply when Hours and Wages are
Jointly Determined
Daniel Aaronson and Eric French
WP-02-22
5
Working Paper Series (continued)
Inter-industry Contagion and the Competitive Effects of Financial Distress Announcements:
Evidence from Commercial Banks and Life Insurance Companies
Elijah Brewer III and William E. Jackson III
WP-02-23
State-Contingent Bank Regulation With Unobserved Action and
Unobserved Characteristics
David A. Marshall and Edward Simpson Prescott
WP-02-24
Local Market Consolidation and Bank Productive Efficiency
Douglas D. Evanoff and Evren Örs
WP-02-25
Life-Cycle Dynamics in Industrial Sectors. The Role of Banking Market Structure
Nicola Cetorelli
WP-02-26
Private School Location and Neighborhood Characteristics
Lisa Barrow
WP-02-27
Teachers and Student Achievement in the Chicago Public High Schools
Daniel Aaronson, Lisa Barrow and William Sander
WP-02-28
The Crime of 1873: Back to the Scene
François R. Velde
WP-02-29
Trade Structure, Industrial Structure, and International Business Cycles
Marianne Baxter and Michael A. Kouparitsas
WP-02-30
Estimating the Returns to Community College Schooling for Displaced Workers
Louis Jacobson, Robert LaLonde and Daniel G. Sullivan
WP-02-31
A Proposal for Efficiently Resolving Out-of-the-Money Swap Positions
at Large Insolvent Banks
George G. Kaufman
WP-03-01
Depositor Liquidity and Loss-Sharing in Bank Failure Resolutions
George G. Kaufman
WP-03-02
Subordinated Debt and Prompt Corrective Regulatory Action
Douglas D. Evanoff and Larry D. Wall
WP-03-03
When is Inter-Transaction Time Informative?
Craig Furfine
WP-03-04
Tenure Choice with Location Selection: The Case of Hispanic Neighborhoods
in Chicago
Maude Toussaint-Comeau and Sherrie L.W. Rhine
WP-03-05
Distinguishing Limited Commitment from Moral Hazard in Models of
Growth with Inequality*
Anna L. Paulson and Robert Townsend
WP-03-06
Resolving Large Complex Financial Organizations
Robert R. Bliss
WP-03-07
6
Working Paper Series (continued)
The Case of the Missing Productivity Growth:
Or, Does information technology explain why productivity accelerated in the United States
but not the United Kingdom?
Susanto Basu, John G. Fernald, Nicholas Oulton and Sylaja Srinivasan
WP-03-08
Inside-Outside Money Competition
Ramon Marimon, Juan Pablo Nicolini and Pedro Teles
WP-03-09
The Importance of Check-Cashing Businesses to the Unbanked: Racial/Ethnic Differences
William H. Greene, Sherrie L.W. Rhine and Maude Toussaint-Comeau
WP-03-10
A Structural Empirical Model of Firm Growth, Learning, and Survival
Jaap H. Abbring and Jeffrey R. Campbell
WP-03-11
Market Size Matters
Jeffrey R. Campbell and Hugo A. Hopenhayn
WP-03-12
The Cost of Business Cycles under Endogenous Growth
Gadi Barlevy
WP-03-13
The Past, Present, and Probable Future for Community Banks
Robert DeYoung, William C. Hunter and Gregory F. Udell
WP-03-14
Measuring Productivity Growth in Asia: Do Market Imperfections Matter?
John Fernald and Brent Neiman
WP-03-15
Revised Estimates of Intergenerational Income Mobility in the United States
Bhashkar Mazumder
WP-03-16
Product Market Evidence on the Employment Effects of the Minimum Wage
Daniel Aaronson and Eric French
WP-03-17
Estimating Models of On-the-Job Search using Record Statistics
Gadi Barlevy
WP-03-18
Banking Market Conditions and Deposit Interest Rates
Richard J. Rosen
WP-03-19
Creating a National State Rainy Day Fund: A Modest Proposal to Improve Future
State Fiscal Performance
Richard Mattoon
WP-03-20
Managerial Incentive and Financial Contagion
Sujit Chakravorti, Anna Llyina and Subir Lall
WP-03-21
Women and the Phillips Curve: Do Women’s and Men’s Labor Market Outcomes
Differentially Affect Real Wage Growth and Inflation?
Katharine Anderson, Lisa Barrow and Kristin F. Butcher
WP-03-22
Evaluating the Calvo Model of Sticky Prices
Martin Eichenbaum and Jonas D.M. Fisher
WP-03-23
7
Working Paper Series (continued)
The Growing Importance of Family and Community: An Analysis of Changes in the
Sibling Correlation in Earnings
Bhashkar Mazumder and David I. Levine
WP-03-24
Should We Teach Old Dogs New Tricks? The Impact of Community College Retraining
on Older Displaced Workers
Louis Jacobson, Robert J. LaLonde and Daniel Sullivan
WP-03-25
Trade Deflection and Trade Depression
Chad P. Brown and Meredith A. Crowley
WP-03-26
China and Emerging Asia: Comrades or Competitors?
Alan G. Ahearne, John G. Fernald, Prakash Loungani and John W. Schindler
WP-03-27
International Business Cycles Under Fixed and Flexible Exchange Rate Regimes
Michael A. Kouparitsas
WP-03-28
Firing Costs and Business Cycle Fluctuations
Marcelo Veracierto
WP-03-29
Spatial Organization of Firms
Yukako Ono
WP-03-30
Government Equity and Money: John Law’s System in 1720 France
François R. Velde
WP-03-31
Deregulation and the Relationship Between Bank CEO
Compensation and Risk-Taking
Elijah Brewer III, William Curt Hunter and William E. Jackson III
WP-03-32
Compatibility and Pricing with Indirect Network Effects: Evidence from ATMs
Christopher R. Knittel and Victor Stango
WP-03-33
Self-Employment as an Alternative to Unemployment
Ellen R. Rissman
WP-03-34
8
@FedFRASER