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Journal of Economic Perspectives—Volume 7, Number 2—Spring 1993—Pages 41-59

Employment and Unemployment
in the 1930s
Robert A. Margo


he Great Depression is to economics what the Big Bang is to physics. As
an event, the Depression is largely synonymous with the birth of
modern macroeconomics, and it continues to haunt successive generations of economists. With respect to labor and labor markets, these facts
evidently include wage rigidity, persistently high unemployment rates, and
long-term joblessness.
Traditionally, aggregate time series have provided the econometric grist
for distinguishing explanations of the Great Depression. Recent research on
labor markets in the 1930s, however, has shifted attention from aggregate to
disaggregate time series and towards microeconomic evidence. This shift in
focus is motivated by two factors. First, disaggregated data provide many more
degrees of freedom than the decade or so of annual observations associated
with the depression, and thus may prove helpful in distinguishing macroeconomic explanations. Second, disaggregation has revealed aspects of economic
behavior hidden in the time series that may be essential to their proper
interpretation and, in any case, are worthy of study in their own right.
Although the substantive findings of recent research are too new to judge their
permanent significance, I believe that the shift towards disaggregated analysis is
an important contribution.
The paper begins by reviewing the conventional statistics of the United
States labor market during the Great Depression and the paradigms to explain
them. It then turns to recent studies of employment and unemployment using
disaggregated data of various types. The paper concludes with discussions of
• Robert A. Margo is Professor of Economics, Vanderbilt University, Nashville,
Tennessee, and Research Associate, National Bureau of Economic Research, Cambridge,


journal of Economic Perspectives

research on other aspects of labor markets in the 1930s and on a promising
source of microdata for future work. My analysis is confined to research on the
United States; those interested in an international perspective on labor markets
might begin with Eichengreen and Hatton's (1988) chapter in their edited
volume, Interwar Unemployment in International Perspective, and the various coun-

try studies in that volume.

Labor Statistics Revisited
Standard unemployment and wage statistics for the 1930s appear in
Table 1 (Baily, 1983, offers more detail). Two series of aggregate unemployment rates are shown, Stanley Lebergott's (1964) and Michael Darby's (1976),
and an index of real hourly earnings in manufacturing compiled by the Bureau
of Labor Statistics (BLS). The difference between Lebergott's and Darby's series
reflects the treatment of persons with so-called "work relief" jobs. For
Lebergott, persons on work relief are unemployed, while Darby counts them as
Between 1929 and 1933 the unemployment rate increased by over 20
percentage points, according to the Lebergott series, or by 17 percentage
points, according to Darby's series. For the remainder of the decade, the
unemployment rate stayed in, or hovered around, double digits. On the eve of
America's entry into World War II, between 9.5 and 14.6 percent of the labor
force was out of work, depending on how unemployment is measured.
In addition to high levels of unemployment, the 1930s witnessed the
emergence of widespread and persistent long-term unemployment (unemployment durations longer than one year) as a serious policy problem. According to
a Massachusetts state census taken in 1934, fully 63 percent of unemployed
persons had been unemployed for a year or more. Similar long-term unemployment was observed in Philadelphia in 1936 and 1937 (Margo, 1991,
p. 335).
In counting persons on work relief as unemployed, Lebergott (1964) was effectively following
census practice in 1940. Darby (1976, p. 5) challenged this practice, arguing that "[f]rom the
Keynesian viewpoint, labor voluntarily employed on contracyclical... government projects should
certainly be counted as employed. On the search approach to unemployment, a person who accepts
a job and withdraws voluntarily from the activity of search is clearly employed." The logic of
Darby's position can be debated. Although he claims that Keynesians would "certainly" count
persons on work relief as employed, he identifies no Keynesians who ever held this view. The
instructions to enumerators of the 1940 census specify several instances in which unemployed
persons who were not actively seeking work (for example, because there was no work to be found
in their occupation in their community) were still to be counted as unemployed (U.S. Bureau of the
Census, 1983, section 6, p. 27). Consistency with the search approach to unemployment would, at
the very least, require that such persons be separated out from the unemployed who were actively
searching for work, which Darby fails to do. I am grateful to Stanley Lebergott for these points. For
a detailed critique of Darby (1976), see Kesselman and Savin (1978).

Robert A. Margo


Table 1

Unemployment and Real Wages in the 1930s
Unemployment Rate









Real Wage Index
(1940 = 100)


Sources: Unemployment rates: Smiley (1983, p. 488). Real wage index: average hourly earnings of
production workers in manufacturing divided by the wholesale price index; hourly earnings is from
U.S. Bureau of the Census (1976, series D-802, pp. 169-170; wholesale price index is from U.S.
Bureau of the Census (1976, series E-40, p. 200).

Given these patterns of unemployment, the behavior of real wages has
proven most puzzling. Between 1929 and 1940, annual changes in real wages
and unemployment, as shown in Table 1, were positively correlated. Real wages
rose by 16 percent between 1929 and 1932, while the unemployment rate
ballooned from 3 to 23 percent. Real wages remained high throughout the rest
of the decade, although unemployment never dipped below 9 percent, no
matter how it is measured.
This information poses two central questions. Why did unemployment
remain persistently high throughout the decade? How can unemployment rates
in excess of 10 to 20 percent be reconciled with the behavior of real wages,
which were stable or increasing?
One way of answering these questions is to devise aggregative models
consistent with the time series, and I briefly review these attempts in the next
section of the paper. Before doing so, however, it is important to stress that the
aggregate statistics are far from perfect. No government agency in the 1930s
routinely collected labor force information analogous to that provided by
today's Current Population Survey. The unemployment rates in Table 1 are
constructs, the differences between intercensal estimates of labor force participation rates and employment-to-population ratios. Because unemployment is
measured as a residual, relatively small changes in the labor force or employment counts can markedly affect the estimated unemployment rate. Although


journal of Economic Perspectives

some progress has been made on measurement issues, there is little doubt that
further refinements to the aggregate unemployment series would be beneficial.2
Stanley Lebergott (1989) has critically examined the reliability of BLS wage
series from the 1930s, like the one shown in Table 1. The BLS series drew
upon a fixed group of manufacturing establishments reporting for at least two
successive months. Lebergott notes several biases arising from this sampling
method. Workers who were laid off, he claims, were less productive and had
lower wages than average. Firms that went out of business were smaller, on
average, than firms that survived, and tended to have lower average wages. In
addition, the BLS oversampled large firms, and Lebergott suspects that large
firms were more adept at selectively laying off lower-productivity labor; more
willing to de-skill (that is, reassign able employees to less-skilled jobs); and more
likely to give able employees longer work periods. For example, Lebergott
(1989, p. 9) cites the cases of General Electric and Westinghouse which reassigned skilled labor and foremen to factory jobs, and which gave longer hours
to more able employees. Wage rates at the two companies fell 10 percent from
1929 to 1931, yet the industry average wage measured by the BLS (which,
according to Lebergott, was heavily influenced by these two firms) remained
A rough calculation suggests that accounting for these biases would produce an aggregate decline in nominal wages between 1929 and 1932 as much
as 48 percent larger than that measured by the BLS series. Although the details
of Lebergott's calculation are open to scrutiny, the research discussed elsewhere
in the paper suggests that he is correct about the existence of biases in the BLS
wage series.

Macroeconomic Studies
For much of the period since World War II, most economists blamed the
unemployment rates in Table 1 on wage rigidity. The demand for labor was a
downward sloping function of the real wage, but since nominal wages were
insufficiently flexible downward (relative to producer prices), the labor market
in the 1930s was persistently in disequilibrium. Labor supply exceeded labor
demand, with mass unemployment the unfortunate consequence.3

See Gene Smiley (1983) for a careful evaluation of the various attempts to date to measure
aggregate unemployment in the 1930s.
1 recognize that many economists believe that flexible wages and prices can be destabilizing, and
that this may have been the case between 1929 and 1932 (Rees, 1970, p. 308; De Long and
Summers, 1986; Greenwald and Stiglitz, 1993). However, most writers in the Keynesian tradition,
such as Peter Temin (1989), argue that lower wages after 1933 would have led to higher levels of

Employment and Unemployment in the 1930s


The frontal attack on the conventional wisdom was Robert E. Lucas and
Leonard Rapping (1969). The original Lucas-Rapping set-up continued to view
current labor demand as a negative function of the current real wage. Current
labor supply was a positive function of the real wage and the expected real
interest rate, but a negative function of the expected future wage (Lucas and
Rapping, eq. 11). If workers expect higher real wages in the future or a lower
real interest rate, current labor supply would be depressed, employment would
fall, unemployment rise, and real wages increase. Lucas and Rapping offer an
unemployment equation, relating the unemployment rate to actual versus
anticipated nominal wages, and actual versus anticipated price levels.
In a comment on Lucas and Rapping's paper, Albert Rees (1970, p. 308)
argued that it was unrealistic to think that unemployed workers in the 1930s
were simply waiting for times to get better. "How long," Rees asked, "[did] it
take workers to revise their expectations in light of the facts? ... [i]t is hard to
imagine the long-term unemployed holding out for jobs comparable with their
old jobs ... over periods up to ten years." Lucas and Rapping (1972) conceded
Rees's criticism for the period 1933 to 1941, but claimed victory for 1929 to
1933. As Ben Bernanke (1986, p. 83) pointed out, however, their victory rests
largely on the belief that expected real interest rates fell between 1929 and
1933, while "ex post, real interest rates in 1930-33 were the highest of the
century." Because nominal interest rates fell sharply between 1929 and 1933,
whether expected real rates fell hinges on whether deflation—which turned
out to be considerable—was unanticipated. Recent research suggests that the
deflation was, at least in part, anticipated, which appears to undercut Lucas
and Rapping's reply (Cecchetti, 1992).
Returning to the conventional wisdom, New Deal legislation has frequently
been blamed for the persistence of high unemployment and the perverse
behavior of real wages (Temin, 1989, 1990). In this regard, perhaps the most
important piece of legislation was the National Industry Recovery Act (NIRA) of
1933. The National Recovery Administration (NRA), created by the NIRA,
established guidelines that raised nominal wages and prices, and encouraged
higher levels of employment through reductions in the length of the workweek
(or "work-sharing").4
An influential study by Michael Weinstein (1980) econometrically analyzed
the impact of the NIRA on wages. Using aggregate monthly data on hourly
earnings in manufacturing, Weinstein showed that the NIRA raised nominal
wages directly through its wage codes and indirectly by raising prices
(Weinstein, 1980, Table 2.3, p. 53). The total impact was such that (p. 59) "[i]n
the absence of the NIRA, average hourly earnings in manufacturing would

The NIRA was declared unconstitutional in May 1935. Other important New Deal labor legislation
includes the National Labor Relations Act (1935), which promoted unions; and the Fair Labor
Standards Act (1938), which set minimum wages in certain industries and which empowered the
federal government to regulate working conditions.


Journal of Economic Perspectives

have been less than thirty-five cents by May 1935 instead of its actual level of
almost sixty cents (assuming unemployment to have been unaltered)".5
It is questionable, however, whether the NIRA really had this large an
impact on wages. Weinstein measured the direct effect of the codes by comparing monthly wage changes during the NIRA period (1933-35) with wage
changes during the recovery phase (1921-23) of the post-World War I recession (1920-21), holding constant the level of unemployment and changes in
wholesale prices. Data from the intervening years (1924-32) or after the NIRA
period were excluded from his regression analysis. In addition, Weinstein's
regression specification precludes the possibility that reductions in weekly
hours (work-sharing), some of which occurred independently of the NIRA, had
a positive effect on hourly earnings. A recent paper using data from the full
sample period and allowing for the effect of worksharing found a. positive but
much smaller impact of the NIRA on wages (see the discussion of Bernanke's
work in the next section).
Various developments in neo-Keynesian macroeconomics have filtered into
the interpretation of the statistics in Table 1. Martin Baily (1983) argues that
firms did not aggressively cut wages early in the 1930s because such a policy
would hurt worker morale and the firm's reputation, incentives that were later
reinforced by New Deal legislation.6 Richard Jensen (1989) invokes efficiency
wage theory in a provocative article. Beginning sometime after the turn of the
century, large firms began to adopt personnel policies that were "designed to
identify and keep the more efficient workers, and to encourage other workers
to emulate them" (Jensen, 1989, p. 561; see also Jacoby, 1985). Efficiency wages
were one such device, which presumably contributed to stickiness in wages.
The trend accelerated in the 1930s. According to Jensen, firms surviving
the initial downturn used the opportunity to lay off their least productive
workers but a portion of the initial decline in employment occurred among
firms that went out of business (Lebergott, 1989). Thus, when expansion
occurred, firms had their pick of workers who had been laid off. Personnel
departments used past wage histories as a signal, and higher-wage workers
were a better risk.7 Those with few occupational skills, the elderly (who were

According to Weinstein (1980, Table 2.3, eq. 2, p. 53), the direct effect alone (the wage codes) was
responsible for increasing hourly earnings at an annual rate of 2.0 percent per month (holding
constant changes in wholesale prices), or about 26 percent per year.
Anthony O'Brien (1989) suggests a similar explanation of why firms did not aggressively cut wages
early in the 1930s. In O'Brien's opinion, business leaders generally adhered to a belief that deep
wage cuts exacerbated the recession of 1920-21, and that this social norm carried over during the
early part of the Great Depression. According to O'Brien (p. 730), "[a]ny firm tempted to cut wages
at the beginning of the Depression would have faced a substantial penalty in the form of diminished
worker productivity" because it would have violated the social norm.
Jensen (1989, p. 567) cites a study of the reemployment of factory workers in Massachusetts who
lost their jobs in 1931. By 1933, only 40 percent had found regular employment; the probability
was much higher, however, among workers in the top third of the wage distribution (57 percent)
than in the bottom third (27 percent).

Robert A. Margo


expensive to retrain) and the poorly educated faced enormous difficulties in
finding work. Jensen argues that by 1935 the "reserve army" of long-term
unemployed no longer exerted much downward pressure on nominal wages
because employers simply did not view the long-term unemployed as substitutes for the employed at virtually any wage (see also Rees, 1970, p. 309).
A novel feature of Jensen's paper is its integration of microeconomic
evidence on the characteristics of the unemployed with macroeconomic evidence on wage rigidity. Consistent with his argument, there is no evidence that
wage differentials by skill or education level were wider overall in the late 1930s
compared with the 1920s, even though less skilled and less educated workers
were disproportionately unemployed throughout the decade (Goldin and
Margo, 1992, pp. 22-23). 8 It remains an open question, however, whether use
of efficiency wages and related personnel practices were as widespread as
Jensen alleges, and whether such use can account empirically for the persistence of high unemployment.9
In brief, the macro studies have not settled the debate over the proper
interpretation of the statistics in Table 1. This state of affairs has much to do
with the (supreme) difficulty of building a consensus macro model of the
depression economy. But it is also a consequence of the level of aggregation at
which empirical work has been conducted. The problem is partly one of sample
size, and partly a reflection of the inadequacies of discussing these issues using
the paradigm of a representative agent. These points are illustrated in the
research discussed in the next three sections.

Employment: Industry and Firm-Level Studies
In a conventional short-run aggregate production function, the labor input
is defined to be total person-hours. For the postwar period, temporal variation
in person-hours is overwhelmingly due to fluctuations in employment. However, for the interwar period, variations in the length of the workweek account
for nearly half of the monthly variance in the labor input (Bernanke and

Weinstein (1980, p. 81) argues that the NIRA compressed differences in hourly wages between
skilled and unskilled labor, (although the effect was small; see pg. 82). There are two problems with
Weinstein's claim. First, he compares wage differentials under the NIRA with wage differentials
during the recovery phase from the post-World War I recession (1921-23). But wage differentials
were compressed during World War I, and it is unreasonable to believe that they had returned to
their long-run equilibrium level by 1921. Second, the data that Weinstein examines (from Beney,
1936) are relatively uninformative about movements in wage differentials in the 1930s because they
refer solely to production workers in large manufacturing firms, thereby excluding most of the
educated population who were not employed in manufacturing. See Goldin and Margo (1991,
p. 1).
See Temin (1990, pp. 302-303) and O'Brien (1989, p. 732) for critiques of the argument that
efficiency wages can explain wage rigidity in the 1930s.


Journal of Economic Perspectives

Powell, 1987). Declines in weekly hours were deep, prolonged, and widespread
in the 1930s. The behavior of real hourly earnings, however, may have not
been independent of changes in weekly hours.
This insight motivates Ben Bernanke's (1986) analysis of employment,
hours, and earnings in eight pre-World War II manufacturing industries.10
The (industry-specific) supply of labor is described by an earnings function,
which gives the minimum weekly earnings required for a worker to supply a
given number of hours per week; this minimum is a positive function of the
reservation level of utility a worker could get in a "secondary or alternative
sector" (Bernanke, 1986, p. 86). In Bernanke's formulation, the earnings
function is convex in hours and also discontinuous at zero hours (the discontinuity reflects fixed costs of working or switching industries). Production depends separately on the number of workers and weekly hours, and on nonlabor
inputs. Firms are not indifferent "between receiving one hour of work from
eight different workers and receiving eight hours from one worker" (Bernanke,
1986, p. 91). A reduction in product demand causes the firm to cut back
employment and hours per week. The reduction in hours means more leisure
for workers, but less pay per week. Eventually, as weekly hours are reduced
beyond a certain point, hourly earnings rise. Further reductions in hours
cannot be matched one for one by reductions in weekly earnings. But when
hourly earnings increase, the real wage then appears to be countercyclical.
To estimate the model, Bernanke uses monthly, industry-level data compiled by the National Industrial Conference Board (Beney, 1936; Sayre, 1940)
covering the period 1923 to 1939. The specification of the earnings function
(describing the supply of labor) incorporates a partial adjustment of wages to
prices, while the labor demand equation incorporates partial adjustment of
current demand to desired demand.11 Except in one industry (leather), the
industry demand for workers falls as real product wages rise; industry demands
for weekly hours fall as the marginal cost to the firm of varying weekly hours
rises; and industry labor supply is a positive function of weekly earnings and
weekly hours.12 Bernanke's estimates imply that the NIRA lowered weekly
hours and raised weekly earnings and employment, although the effects were
modest.13 In six of the industries (the exceptions were shoes and lumber),

The literature on work-sharing, during the 1930s and after, is voluminous; see the references
cited in Bernanke (1986) for details.
The inclusion of partial adjustment terms implies that, empirically, the actual supply of labor can
exceed the actual demand for labor (that is, unemployment results); see Bernanke (1986, p. 95).
The marginal cost to the firm of varying weekly hours is "the number of workers employed times
the increment to their earnings required to get them to work the extra time" (Bernanke, 1986,
p. 88).
The largest percentage impacts on the level of hourly earnings (estimated as the percentage effect
on weekly earnings minus the percentage effect on weekly hours) occurred in shoes, wool, and
lumber, at around 10 percent. This is the basis for the claim in the previous section of the paper
that Bernanke's estimate of the effects of the NIRA on wages are smaller than Weinstein's.

Employment and Unemployment in the 1930s


increased union influence after 1936 (measured with a proxy variable of days
idled by strikes) raised weekly earnings by 10 percent or more.
In a related paper, Bernanke and Martin Parkinson (1991) use an expanded version of the NICB data set covering ten industries to explore the
possibility that "short-run increasing returns to labor," or procyclical labor
productivity, characterized co-movements in output and employment in the
1930s. Using their expanded data set, Bernanke and Parkinson (1991) estimate
regressions of the change in output on the change in labor input, now defined
to be total person-hours. The coefficient of the change in the labor input is the
key parameter; if it exceeds unity, then short-run increasing returns to labor
are present. Bernanke and Parkinson find that short-run increasing returns to
labor characterized all but two of the industries under study (petroleum and
leather). The estimates of the labor coefficients are essentially unchanged if the
sample is restricted to just the 1930s. Further, a high degree of correlation
(r = 0.9) appears between interwar and postwar estimates of short-run increasing returns to labor for a matched sample of industries.
Thus, the procyclical nature of labor productivity appears to be an accepted fact for both the interwar and postwar periods. One explanation of
procyclical productivity, favored by real business cycle theorists, emphasizes
technology shocks. Booms are periods in which technological change is unusually brisk, and labor supply increases to take advantage of the higher wages
induced by temporary gains in productivity (caused by the outward shift in
production functions). In Bernanke and Parkinson's view, however, the high
correlation between the pre- and post-war estimates of short-run increasing
returns to labor poses a serious problem for the technological shocks explanation. The high correlation implies that the "real shocks hitting individual
industrial production functions in the interwar period accounted for about the
same percentage of employment variation in each industry as genuine technological shocks hitting industrial production functions in the post-war period"
(Bernanke and Parkinson, 1991, p. 451). However, technological change per se
during the Depression was concentrated in a few industries and was modest
overall (Bernstein, 1987). Further, while real shocks occurred—for example,
bank failures, the New Deal, international political instability—their effects on
employment, in Bernanke and Parkinson's opinion (p. 450), were felt through
shifts in aggregate demand, not through shifts in industry production
Other leading explanations of procyclical productivity are true increasing
returns or, popular among Keynesians, the theory of labor hoarding during
economic downturns. Having ruled out technology shocks, Bernanke and
Parkinson attempt to distinguish between true increasing returns and labor
hoarding. They devise two tests, both of which involve restrictions on excluding
proxies for labor utilization from their regressions of industry output. If true
increasing returns were present, the observed labor input captures all the


Journal of Economic Perspectives

relevant information about variations in output over the cycle. But if labor
hoarding were occurring, the rate of labor utilization, holding employment
constant, should account for output variation. Their results are mixed, but are
mildly in favor of labor hoarding in six of the ten industries under study.
Although Bernanke's (1986) modelling effort is of independent interest,
the substantive value of his and Parkinson's empirical research is enhanced
considerably by disaggregation to the industry level.14 It is obvious from their
work that industries in the 1930s did not respond identically to decreases in
output demand. However, further disaggregation to the firm level can produce
additional insights. Bernanke and Parkinson assume that movements in industry aggregates reflect the behavior of a representative firm. But according to
Lebergott (1989), much of the initial decline in output and employment
occurred among firms that exited. Firms that left, and new entrants, however,
were not identical to firms that survived.
These points are well-illustrated in Timothy Bresnahan and Daniel Raffs
(1991) study of the American motor vehicle industry. Their database consists of
manuscript census returns of motor vehicle plants in 1929, 1931, 1933, and
1935. By linking the returns from year to year, Bresnahan and Raff have
created a panel dataset, capable of identifying plants that exited, surviving
plants, and new plants. Plants that exited between 1929 and 1933 had lower
wages and lower labor productivity than plants that survived. Between 1933
and 1935, average wages at exiting plants and new plants were slightly higher
than at surviving plants. Output per worker was still relatively greater at
surviving plants than new entrants, but the gap was smaller than between 1929
and 1933.
Roughly a third of the decline in the industry's employment between 1929
and the trough in 1933 occurred in plant closures. The vast majority of these
plant closures were permanent. The shakeout of inefficient firms after 1929
ameliorated the decline in average labor productivity in the industry. Although
industry productivity did decline, productivity in 1933 would have been still
lower if all plants had continued to operate.
During the initial recovery phase (1933-35) about 40 percent of the
increase in employment occurred in new plants. Surviving plants were more
likely to use mass production techniques; the same was true of new entrants.
Mass production plants differed sharply from their predecessors (custom production plants) in the skill mix of their workforces and in labor relations. In the
motor vehicle industry, the early years of the Depression were an "evolutionary
event," permanently altering the technology of the representative firm
(Bresnahan and Raff, 1991, p. 331).
While the representative firm paradigm apparently fails for motor vehicles,
it may not for other industries. Some preliminary analysis of census
See Whaples (1990) for an application of Bernanke's model in explaining the decline in the
length of the workweek in the United States before World War I.

Robert A. Margo


manuscripts for another industry, blast furnaces, is revealing on this point
(Bertin, Bresnahan, and Raff, 1992). Blast furnaces were subject to increasing
returns and the market for the product (molten iron) was highly localized. For
this industry, reductions in output during a cyclical trough are reasonably
described by a representative firm, since "localized competition prevented
efficient reallocation of output across plants" (Bertin, Bresnahan, and Raff,
p. 25) and therefore the compositional effects occurring in the auto industry
did not happen.
These analyses of firm-level data have two important implications for
studies of employment in the 1930s. First, aggregate demand shocks could very
well have changed averaged technological practice through the process of exit
and entry at the firm level. Thus, Bernanke and Parkinson's rejection of the
technological shocks explanation of short-run increasing returns in the 1930s,
which is based in part on their belief that aggregate demand shocks did not
alter industry production functions, may be premature. Second, the empirical
adequacy of the representative firm paradigm is apparently industry-specific,
depending on industry structure, the nature of product demand, and initial
(that is, pre-Depression) heterogeneity in firm sizes and costs. Such phenomena, Bertin et al note (p. 25), "are invisible in industry data," and can only be
recovered from firm-level records, such as the census manuscripts.

Geographic Variation
Analyses of industry and firm-level data are one way to explore heterogeneity in labor utilization. Geography is another. A focus on national or even
industry aggregates obscures the substantial spatial variation in bust and recovery that characterized the 1930s. Two recent studies show how spatial variation
suggests new puzzles about the persistence of the Depression as well as providing additional degrees of freedom for discriminating between macroeconomic
State-level variation in employment is the subject of an important article by
John Wallis (1989). Using data collected by the Bureau of Labor Statistics,
Wallis has constructed annual indices of manufacturing and nonmanufacturing
employment for states from 1930 to 1940. Wallis's indices reveal that declines
in employment between 1930 and 1933 were steepest in the East North Central
and Mountain states; employment actually rose in the South Atlantic states,
however, once an adjustment is made for industry mix (Wallis, p. 60). The
South also did comparatively well during the recovery phase of the Depression
(1933-40). Wallis tests whether the southern advantage during the recovery phase might reflect lower levels of unionization and a lower proportion of employment affected by the passage of the Social Security Act
(1935), but controlling for percent unionized and percent in covered


Journal of Economic Perspectives

employment in a regression of employment growth does not eliminate the
regional gap.15 "What comes through clearly," according to Wallis (p. 61), "is
that the [employment] effects of the Depression varied considerably throughout
the nation" and that a convincing explanation of the southern difference
remains an open question.
Curtis Simon and Clark Nardinelli (1992) exploit variation across cities to
put forth a particular interpretation of economic downturn in the early 1930s.
Specifically, they study the empirical relationship between "industrial diversity"
and city-level unemployment rates before and after World War II. Industrial
diversity is measured by a city-specific Herfindahl index of industry employment shares. The higher the value of the index, the greater is the concentration
of employment in a small number of industries. Using data from the 1930
federal census and the 1931 Special Census of Unemployment, Simon and
Nardinelli show that unemployment rates and the industrial diversity index
were positively correlated across cities at the beginning of the Depression.
Analysis of similar census data for the post-World War II period reveals a
negative correlation between city unemployment rates and industrial diversity.
Simon and Nardinelli (1992) explain this finding as the outcome of two
competing effects. In normal economic circumstances, a city with a more
diverse range of industries should have a lower unemployment rate (the
"portfolio" effect), because industry-specific demand shocks will not be perfectly correlated across industries and some laid-off workers will find ready
employment in expanding industries (p. 385). The portfolio effect may fail,
however, during a large aggregate demand shock (the early 1930s) if firms and
workers are poorly informed, misperceiving the shock to be industry-specific,
rather than a general reduction in demand. Firms in industrially diverse cities
announce selective layoffs rather than reduce wages, because they believe that
across-the-board wage cuts would cause too many workers to quit (workers in
industrial diverse cities think they can easily find a job in another industry
elsewhere in the same city), thus hurting production. Firms in industrially
specialized cities, however, are more likely to cut wages than employment
because they believe lower wages "would induce relatively fewer quits" than in
industrially diverse cities (pp. 386-87).
Thus, Simon and Nardinelli (1992) conclude, wages in the early 1930s
were more rigid in industrially-diverse cities, producing the positive correlation
between industrial diversity and unemployment. Improvements in the quantity, quality, and timeliness of economic information, they conjecture, have
caused the portfolio effect to dominate after World War II, producing the
postwar negative correlation. Although one can question the historical relevance of Simon and Nardinelli's model, and the specifics of their empirical
The hypothesis is that unionization and social security coverage should have reduced employment growth (by making labor more expensive to hire). The hypothesis is confirmed for unions,
but not for social security; see Wallis (1989, p. 63).

Employment and Unemployment in the 1930s


analysis, their paper is successful in demonstrating the potential value of spatial
data in unravelling the sources of economic downturn early in the Depression.16

Unemployment: The 1940 Census Sample
Postwar macroeconomics has tended to proceed as if the unemployment
rates of Table 1 applied to a representative worker, with a certain percentage of
that worker's time not being used. As a result, disaggregated evidence on
unemployment has been slighted. Such evidence, however, can provide a
richer picture of who was unemployed in the 1930s, a better understanding of
the relationship between unemployment and work relief, and further insights
into macroeconomic explanations of unemployment.
To date, the source that has received the most attention is the public use
tape of the 1940 census, a large random sample of the population in 1940 (U.S.
Bureau of the Census, 1983). The 1940 census is a remarkable historical
document. It was the first American census to inquire about educational
attainment, wage and salary income and weeks worked in the previous year;
and the first to use the "labor force week" concept in soliciting information
about labor force status. Eight labor force categories are reported, including
whether persons held work relief jobs during the census week (March 24-30,
1940). For persons who were unemployed or who held a work relief job at the
time of the census, the number of weeks of unemployment since the person last
held a private or nonemergency government job of one month or longer was
recorded. The questions on weeks worked and earnings in 1939 did not treat
work relief jobs differently from other jobs. That is, earnings from and time
spent on work relief are included in the totals.
I have used the 1940 census sample to study the characteristics of unemployed workers and of persons on work relief, and the relationship between
work relief and various aspects of unemployment (Margo, 1988, 1991). It is
clear from the public use sample that unemployed persons who were not on
work relief were far from a random sample of the labor force. For example, the
unemployed were typically younger, or older, than the average employed
worker (unemployment followed a U-shaped pattern with respect to age); the
unemployed were more often nonwhite (see also Sundstrom, 1992); and they
were less educated and had fewer skills than employed persons, as measured by
occupation. Such differences tended to be starkest for the long-term unemployed (those with unemployment durations longer than a year); thus, for
Simon and Nardinelli (1992) provide no direct evidence that firms in industrially-diverse cities
misperceived the shock in the manner described by their model; their regression specification
excludes all determinants of unemployment other than the Herfindahl index, an industry mix
variable, and a dummy for Western cities; and they do not estimate an equation for 1940, even
though one would expect misperceptions to have vanished by that date.


Journal of Economic Perspectives

example, the long-term unemployed had even less schooling than the average
unemployed worker.
Although the WPA drew its workers from ranks of the unemployed, the
characteristics of WPA workers did not merely replicate those of other unemployed persons. For example, single men, the foreign-born, high school
graduates, urban residents, and persons living in the Northeast were underrepresented among WPA workers, compared with the rest of the unemployed.
Perhaps the most salient difference, however, concerns the duration of unemployment. Among those on work relief in 1940, roughly twice as many had
been without a non-relief job for a year or longer as had unemployed persons
not on work relief.
The fact that the long-term unemployed were concentrated disproportionately on work relief raises an obvious question. Did the long-term unemployed
find work relief jobs after being unemployed for a long time, or did they
remain with the WPA for a long time? The answer appears to be mostly the
latter. Among nonfarm males ages 14 to 64 on work relief in March 1940 and
reporting 65 weeks of unemployment (that is, the first quarter of 1940 and all
of 1939), close to half worked 39 weeks or more in 1939 (Margo, 1991, p. 338).
Given the census conventions, they had to have been working more or less full
time for the WPA.17
For reasons that are not fully clear, the incentives were such that a
significant fraction of persons who got on work relief, stayed on.18 One possible
explanation is that some persons on work relief preferred the WPA, given
prevailing wages, perhaps because their relief jobs were more stable than the
non-relief jobs (if any) available to them. Or, as one WPA worker was quoted in
E. W. Bakke (1940, pp. 421-22): "Why do we want to hold onto these [relief]
jobs? ... [W]e know all the time about persons.. just managing to scrape
along. .. My advice, Buddy, is better not take too much of a chance. Know a
good thing when you got it." Alternatively, working for the WPA may have
stigmatized individuals, making them less desirable to non-relief employers the
longer they stayed on work relief (Jensen, 1989). Whatever the explanation,
the continuous nature of WPA employment makes it difficult to believe that the
WPA did not reduce, in the aggregate, the amount of job search done by
unemployed workers in the late 1930s.
In addition to the duration of unemployment experienced by individuals,
the availability of work relief may have dampened the increase in labor supply
of secondary workers in households in which the household head was
According to a WPA study conducted in 1939, fully 59 percent of persons with relief jobs in
September 1937 held them continuously through February of 1939 (Margo, 1988, p. 34).
This claim may surprise readers familiar with the statistics of work relief, because rates of
assignment to, and separation from, WPA projects suggest a very high rate of turnover. Separation
from project employment, however, was not the same as permanent separation from the WPA;
accessions always included persons reassigned from other projects that had ended (U.S. Federal
Works Agency, 1946, p. 32).

Robert A. Margo


unemployed, the so-called "added worker" effect (Woytinsky, 1942). Specifically, wives of unemployed men not on work relief were much more likely to
participate in the labor force than wives of men who were employed at
non-relief jobs. But wives of men who worked for the WPA were far less likely
to participate in the labor force than wives of otherwise employed men.19 The
relative impacts were such that, in the aggregate, no added worker effect can be
observed as long as persons on work relief are counted among the unemployed
(Margo, 1988, p. 348).
Although my primary goal in analyzing the 1940 census sample was to
illuminate features of unemployment obscured by the aggregate time series, the
results bear on several macroeconomic issues. First, the heterogenous nature of
unemployment implies that a representative agent view of aggregate unemployment cannot be maintained for the late 1930s. Whether the view can be
maintained for the earlier part of the Depression is not certain, but the
evidence presented in Jensen (1989) and Margo (1991, p. 334) suggests that it
cannot. Because the evolution of the characteristics of the unemployed over the
1930s bears on the plausibility of various macroeconomic explanations of
unemployment (for example, Jensen, 1989), further research is clearly
Second, the heterogenous nature of unemployment is consistent with
Lebergott's (1989) claim that aggregate BLS wage series for the 1930s are
contaminated by selection bias, because the characteristics that affected the
likelihood of being employed (for example, education) also affected a person's
wage. Again, a clearer understanding of the magnitude and direction of bias
requires further work on how the characteristics of the employed and unemployed changed as the Depression progressed.
Third, macroeconomic analyses of the persistence of high unemployment
should not ignore the effects of the WPA—and, more generally, those of other
federal relief policies—on the economic behavior of the unemployed. In particular, if work relief was preferred to job search by some unemployed workers,
the WPA may have displaced some growth in private sector employment that
would have occurred in its absence.20 An estimate of the size of this displacement effect can be inferred from a recent paper by John Wallis and Daniel
Benjamin (1989). Wallis and Benjamin estimate a model of labor supply, labor
demand, and per capita relief budgets using panel data for states from 1933 to
1939. Their coefficients imply that elimination of the WPA starting in 1937
would have increased private sector employment by 2.9 percent by 1940, which
The reason is not yet clear, but may have to do with eligibility requirements for work relief.
Specifically, a working wife might cause family income to exceed limits set by local relief authorities,
thereby causing a worker to be ineligible for employment with the WPA. T. Aldrich Finegan and I
are currently investigating this issue further using the 1940 census sample (Finegan and Margo,
1992). On eligibility requirements for work relief, see Howard (1943).
See Kesselman (1978) for a thorough and insightful discussion of the possible microeconomic and
macroeconomic effects of work relief.


Journal of Economic Perspectives

corresponds to about half of persons on work relief in that year.21 Displacement
was not one-for-one, but may not have been negligible.22

Other Aspects of Labor Markets
My discussion thus far has emphasized the value of disaggregated evidence
in understanding certain key features of labor markets in the 1930s—the
behavior of wages, employment and unemployment—because these are of
greatest general interest to economists today. I would be remiss, however, if I
did not mention other aspects of labor markets examined in recent work. What
follows is a brief, personal selection from a much larger literature.
The Great Depression left its market on racial and gender differences.
From 1890 to 1930 the incomes of black men increased slightly relative to the
incomes of white men, but the trend in relative incomes reversed direction in
the 1930s (Smith, 1984).25 Migration to the North, a major avenue of economic
advancement for Southern blacks, slowed appreciably. There is little doubt that
if the Depression had not happened, the relative economic status of blacks
would have been higher on the eve of World War II. Labor force participation
by married women was hampered by "marriage bars," implicit or explicit
regulations that allowed firms to dismiss single women upon marriage or
prohibited the hiring of married women. Although marriage bars existed
before the 1930s, their use spread during the Depression, possibly because
social norms dictated that married men were more deserving of scarce jobs
than married women (Goldin, 1990).
Although they have not received much attention from economists, some of
the more interesting effects of the Depression were demographic or life-cycle in
nature. Marriage rates fell sharply in the early 1930s, and fertility rates
remained low throughout the decade (Eichengreen and Hatton, 1988, p. 47).
An influential study by the sociologist Glen Elder, Jr. (1973) traced the
Labor demand in Wallis and Benjamin's model is a function of the real wage, lagged employment, and various exogenous variables. Labor supply depends on the real wage, per capita relief
budgets, and exogenous variables. After a three-year period the reduced form elasticity of employment with respect to relief budgets is —0.042 (calculated from Wallis and Benjamin, Table 4).
Multiplying by —0.693 (69.3 percent is the WPA's share of all relief expenditures in 1937,
calculated from Wallis and Benjamin's Tables 1 and 2) gives the predicted percentage change in
employment (2.9 percent). Assuming that the elimination of work relief would have had no effect
on aggregate labor force participation, the employed share of the labor force in 1940 would have
been 87.9 percent instead of 85.4 percent (= 1.029 X 85.4; from my Table 1). Since 5.1 percent of
the labor force was on work relief in 1940 (see my Table 1), displacement would have equalled 49
percent (= 2.5/5.1). If aggregate labor force participation were higher in the absence of the WPA
because of the added-worker effect (see the text and Finegan and Margo, 1992), displacement
would be smaller, because the employment effect would be the same but the labor force would have
been larger in size.
See Kesselman and Savin (1978) for the alternate view, that work relief did not displace private
Other important studies containing information on the experiences of blacks in the Depression
include Wolters (1970), Whatley (1983), and Wright (1986).

Employment and Unemployment in the 1930s


subsequent work and life histories of a sample of individuals growing up in
Oakland, California, in the 1930s. Children from working class households
whose parents suffered from prolonged unemployment during the Depression
had lower educational attainment and less occupational mobility than their
peers who were not so deprived. Similar findings were reported by Stephan
Thernstrom (1973) in his study of occupational mobility of Boston men.

Concluding Remarks
The Great Depression was the premier macroeconomic event of the 20th
century, and I am not suggesting that economists abandon macroeconomic
analysis of it. I am suggesting, however, that exclusive focus on aggregate labor
statistics runs two risks: the "facts" so derived may be artifacts in certain
respects, and much of what may be informative about labor market behavior in
the 1930s is rendered invisible. The people and firms whose experiences make
up the aggregates deserve to be studied in their diversity, not as representative
I have mentioned census microdata, such as the public use sample of the
1940 census or the manufacturing census manuscripts collected by Bresnahan
and Raff, in this survey. In closing, I would like to highlight another source that
could be examined in future work.
The source is the "Study of Consumer Purchases in the United States"
conducted by the BLS in 1935-36. Approximately 300,000 households, chosen
from a larger random sample of 700,000, supplied basic survey data on income
and housing, with 20 percent furnishing additional information. The detail is
staggering: labor supply and income of all family members; personal characteristics (for example, occupation, age, race); family composition; housing characteristics; and a long list of durable and non-durable consumption expenditures
(the 20 percent sample). Because the purpose of the study was to provide
budget weights to update the CPI, only families in "normal" economic circumstances were included (this is the basis for the reduction in sample size from
700,000 to 300,000). Thus, for example, persons whose wages were very low or
who experienced long-term unemployment are unlikely to be included in the
1935-36 study. Even so, the data could prove invaluable for studies of wage
determination; of labor supply decisions within families; and of the impact of
unemployment on consumption expenditures. A pilot sample, drawn from the
original survey forms (stored at the National Archives) and containing the
responses of 6,000 urban households, is available in machine-readable format
from the Inter-University Consortium for Political and Social Research at the
University of Michigan (ICPSR Study 8908).
- I am grateful to Stanley Engerman, Claudia Goldin, Jonathan Kesselman, Stanley
Lebergott, Daniel Raff, Carl Shapiro, Richard Steckel, Joseph Stiglitz, Timothy Taylor,


Journal of Economic Perspectives

Peter Temin, John Walks, Eugene White, Gavin Wright, and seminar participants at the
National Bureau of Economic Research for helpful comments.

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