ENFORCEMENT AND COMPLIANCE WITH LABOR REGULATIONS
Lucas Ronconi
Universidad Torcuato Di Tella, Buenos Aires, Argentina
Abstract
This paper empirically analyzes the effect of government enforcement on compliance with labor
regulations in Argentina, a country where only half of the workforce receives all the benefits to
which they are legally entitled. I construct a panel data set across provinces from 1995 to 2002.
Using the number of labor inspectors per capita as a proxy for enforcement, I assess the effect of
enforcement on the extent of compliance with six employment and social security regulations:
minimum wage, maximum hours, paid vacation time, annual extra monthly wage, workers
compensation insurance, and health insurance. Because of potential simultaneity between
enforcement and compliance, I explore instrumenting enforcement by electoral years. Two-stage
least squares estimates suggest enforcement increases compliance.
Acknowledgments: I thank Ruth Collier, Alain de Janvry, Jonathan Leonard, Andrea Moro,
Michael Reich and particularly Steven Raphael for helpful comments. This paper was supported
by the University of California Labor and Employment Research Fund.
1
Introduction
A large fraction of the labor force in developing countries faces poor working conditions.
Available estimates indicate about half of employees do not have any state-sponsored protection
against unemployment, work related injuries and diseases, or old age (IDB, 2004). Furthermore,
many work in unsafe environments. In Latin America and the Caribbean the reported
occupational fatality rate is 0.135 per 1,000 workers (Iunes, 2001), more than three times the
comparable rate for the U.S.
These poor working conditions are not driven by a lack of regulation. Most developing
countries have extensive labor regulations and social security systems with de jure universal
coverage. However, compliance is low.
The majority of workers whose labor rights are not realized are poor. Lack of compliance
with basic labor rights can produce a number of negative consequences, such as more workplace
accidents, and distortions in the allocation of resources. Noncompliance directly affects the
notion that the law equally applies to all, and since it usually implies payroll tax evasion,
noncompliance affects the fairness of fiscal policy and the state capacity to redistribute. These
are just a few of the normative considerations involved.
Given incomplete voluntary incentives to produce compliance with labor regulations, an
obvious policy lever is to enhance government enforcement. However, there is little empirical
research on the effects of enforcement on labor market outcomes in developing countries.1 In this
paper, I estimate the effect of variation in enforcement on the likelihood that employers violate
labor regulations in Argentina.
1
For developed countries see Ehrenberg and Schumann (1982), Flanagan (1989), Gray and Jones (1991), and
Weil (2005).
2
There are two main challenges to estimating a causal effect of enforcement on compliance.
First, adequate measures for both variables are not easily available: firms that do not obey the
law have incentives not to report their status, and data about government enforcement in
developing countries is simply lacking. I construct a panel data set spanning the time period from
1995 to 2002 across Argentina’s provinces. I use the number of labor inspectors working in
provincial public enforcement agencies (per 100,000 people) as a proxy for enforcement activity,
and measure compliance by the percentage of private sector employees who receive legallymandated benefits (i.e., minimum wage, maximum hours, paid vacation, annual extra monthly
wage,2 workers compensation insurance, and health insurance). All these measures of
compliance are obtained from the Permanent Household Survey where workers –not firmsreport their working conditions and benefits.
Second, a potential simultaneous relation between enforcement and compliance complicates
identification. On the one hand, firms’ propensities to comply with regulations depend on the
probability of being penalized, and, on the other hand, public enforcement agencies’ resources
are likely to be affected by the extent of compliance. To deal with the simultaneity between
enforcement and compliance I exploit the existence of an electoral cycle in labor inspector
staffing.3
2
Employees are legally entitled to receive their monthly wage thirteen times during the year. The “annual extra
monthly wage” (known as aguinaldo in Argentina) is literally the thirteenth wage, and it is usually paid half in June
and half in December.
3
Levitt (1997) uses electoral cycles in enforcement agencies’ staffing to estimate the effect of police on crime in
the U.S., and Hanson and Spilimbergo (1999) use it to estimate the effect of enforcement on illegal immigration at
the U.S.-Mexico border.
3
Measuring Enforcement and Compliance
Argentina is organized in 23 provinces and the autonomous City of Buenos Aires. According to
the Constitution, each province has the authority to enforce labor regulations within its territory.
Provincial enforcement agencies can impose fines against employers who do not comply with
employment regulations and who do not register their employees in the social security system,
but they cannot impose fines against evasion of the social security payroll tax. When they find
this violation, provinces have the authority only to notify the national government and
recommend employers to comply. This institutional configuration suggests that increases in
provincial enforcement efforts are likely to be more effective against lack of compliance with
employment regulations than they are against lack of compliance with social security
regulations.
Theory predicts that firms respond to the probability of being inspected times the size of the
expected penalty. Therefore, an ideal measure of enforcement should include the number of
inspections conducted and the value of fines imposed. In this paper, I use the number of labor
inspectors working in provincial enforcement agencies as a proxy for government enforcement
of labor regulations. The data is from the Argentine Labor Ministry and is available from 1995 to
2002.4 This is a rough measure of enforcement because inspectors’ productivity can change over
4
During this period, all provinces exercised their right to enforce regulations within their territory, except Jujuy
(until 1999) and the City of Buenos Aires where the enforcement authority was the national Labor Ministry.
Therefore, for Jujuy pre-1999 and for the City of Buenos Aires, I use the number of federal labor inspectors working
in each jurisdiction. The models I estimate below do not differentiate between provincial and federal inspectors.
Adding a federal inspector dummy does not affect the results in any substantive manner.
4
time and across provinces. The IDB (2004:278), however, presents information on provincial
labor inspectors’ productivity in Argentina from 1996 to 1998 (the only period for which data is
available), and shows that the correlation between the number of inspectors per worker and the
number of fines imposed per worker is 0.89, and the correlation between the number of fines
imposed per worker and the total value of fines imposed per worker is 0.99. Therefore, the
number of labor inspectors appears to be a credible proxy for government enforcement.5
A limitation of the data is the low number of observations: it is available from 1995 to 2002,
and figures are lacking for 33 out of the 192 province-year cells. The missing data is due to
provinces failing to report information to the national Labor Ministry. I test for selection bias
following Wooldridge (2002:581), and find no evidence that the pattern of missing observations
affects the results.6
While the direct measure of enforcement I use has limitations, it has obvious advantages over
other proxies used in past research. Ihrig and Moe (2004) use the inverse of seignorage (i.e., the
ratio of the price level to the percentage change in the money supply). Loayza (1997), and
Johnson, Kaufmann and Zoido-Lobaton (1998) use a “rule-of-law” index which is based on
subjective analysis (i.e., not based either on government enforcement resources or on
5
I construct a proxy for statutory sanctions from 1995 to 2002. The proxy includes penalties against employers
who do not register their workers and who evade the payroll tax. Adding this proxy does not affect the results in any
substantive manner. More details about this proxy and the results are in Appendix 1.
6
Define sit =1 if the number of labor inspectors in province i and year t is observed, and zero otherwise. The test
consists of adding a lagged selection indicator, si,t-1, to the compliance equation, estimating the model by fixed
effects, and testing for the significance of si,t-1.
5
enforcement activities). Botero et al. (2004) utilize the workforce average education as a proxy
for labor law enforcement.7
Measuring compliance with labor regulations also presents some difficulties. Firms that break
the law have the incentive not to report their true behavior. Moreover, the measurement error is
expected to be correlated with enforcement, because non-compliers are less likely to report their
true status when the probability of being caught is higher. Therefore, measuring compliance
based on firms’ self-reported status is likely to produce biased estimates of the effect of
enforcement on compliance. Employees, on the other hand, are more likely to report their actual
working conditions since they are not fined if labor regulations are disobeyed. Moreover, it is
unlikely that a measure of compliance based on employees’ self-reported status is biased for
strategic reasons related to union status: less than five percent of workers in Argentina report
participating in a labor union, and the majority distrust labor unions.8
Another challenge is that several rules regulate labor relations, and so, it is not obvious how to
define compliance. According to the Argentine legislation, employers must comply with a
number of universally applicable norms. These include registering employees, providing a
healthy and safe work environment, complying with collective bargaining agreement provisions,
paying at least the minimum wage, and contributing to the social security system. Social security
7
The correlation between the number of inspectors per capita and average years of schooling in the sample I
study is negative (-0.19), and the correlation between the number of inspectors per capita and the inverse of
seignorage is statistically insignificant. This evidence warns about the reliability of results obtained using either
seignorage or education as proxies for labor law enforcement.
8
According to a poll conducted by Opinión Pública, Servicios y Mercados during 2006, 9 percent have a high
level of trust in labor unions, 21 percent have moderate trust, and 70 percent have low trust.
6
contributions provide workers insurance against illness, work-related injuries, unemployment,
and old age.
I measure compliance from the Permanent Household Survey (EPH), where workers report
their working conditions. The EPH is the main household survey in Argentina. It is a stratified
random sample and has been conducted twice a year (i.e., in May and in October) since 1974 by
the National Institute of Statistics (INDEC), which ensures confidentiality.9 The EPH is
particularly useful because it permits measuring compliance with several employment and social
security regulations since workers report their earnings, hours worked, and access to legallymandated benefits.10
I first restrict the population to private sector employees.11 Then I construct, for each province
and year, six measures of compliance: the percentage who earn wages that are above or equal to
the legal minimum, the percentage reporting their employer makes the legally-mandated
contribution to the workers compensation insurance system, to the health insurance system, the
9
In the EPH the interviewee does not report either his/her last name or his/her identification number. Moreover,
the questionnaire explicitly states the information will remain confidential.
10
The specific questions in the survey are, for example, “¿En esa ocupación goza usted de vacaciones?” A
close translation is “Do you have paid vacation time in your job?”
11
I also exclude domestic workers because they have different labor regulations and a special unit at the national
Labor Ministry is in charge of enforcing their rights. Similar institutional considerations apply to rural workers,
although they are automatically excluded because the EPH only covers urban agglomerates. Seven percent of private
sector employees are domestic workers in the sample, and ten percent of the population is rural according to the
2001 census.
7
percentage who receive paid vacation time, who receive the annual extra monthly wage, and the
percentage working no more hours than the legal maximum.12
I also compute the following: an overall measure of compliance with employment regulations
(defined as the share of private sector employees who earn at least the minimum wage, who do
not exceed the maximum number of hours, and who receive vacation time and the annual extra
monthly wage); an overall measure of compliance with social security regulations (defined as the
share of private sector employees reporting their employer makes the contribution to both the
workers compensation and health insurance systems); and, finally, an all-encompassing measure
of compliance, defined as the percentage of private sector employees who receive all of the six
legally-mandated benefits. All these measures are obtained from the EPH October surveys.13 The
province of Rio Negro is excluded since no survey was conducted until 2002.
The minimum wage was constant at $200 per month across all provinces during the analyzed
period. This benefit only applied to full-time employees. Part-time workers had to be paid at
least $1 per hour. These benefits were restricted to employees over 18 years-old. There was no
minimum wage for younger workers. Based on these statutory requirements I categorize each
worker as either below or not-below the minimum wage. For each province-year, then, I
compute the rate of compliance weighting each observation by its sample weight. I follow the
same procedure to measure compliance with the other labor regulations. All workers in the
12
Workers also report in the EPH access to a pension plan and severance pay. However, these two benefits are
not mandatory in certain labor contracts, and since workers do not report the type of contract they have, I cannot
measure compliance with respect to these two benefits.
13
No survey was conducted in La Rioja during October 1995 and in Córdoba during October 1996, so I use the
May 1996 and May 1997 surveys respectively.
8
analyzed sample are legally entitled to paid vacation time, maximum hours, annual extra
monthly wage, workers compensation insurance, and health insurance. The maximum hours
worked for younger workers is lower.14
Table 1 presents means and standard deviations for the measures of compliance, enforcement,
and the other variables used in this study. The unit of observation is a province-year.
<Table 1>
The extent of compliance varies greatly by labor regulation. Compliance with the minimum
wage, for example, is almost 95 percent while compliance with the legally-mandated health
insurance provision is only 55 percent. All measures are positively related, although the
magnitudes range from near perfect correlation between paid vacation and the annual extra
monthly wage, to a very weak correlation between the provision of health insurance and
compliance with maximum-hours regulation (results available upon request).
Table 2 presents the average rate of compliance along some demographic dimensions.
Immigrants, less-educated workers, and minors (i.e., 18 and younger) are less likely to receive
the benefits to which they are legally entitled.
<Table 2>
Combining the data on enforcement and compliance produces an unbalanced panel of 153
observations out of 184 province-year cells (i.e., annual data for 23 jurisdictions from 1995 to
14
Maximum hours regulations were as follows: For employees over 18 years-old, overtime work could not
exceed 48 hours per month between 1995 and 1999, and decreased to 30 hours per month in 2000 (overtime work is
defined as the number of hours in excess of 48 per week). For employees between 17 and 18 years old the total
maximum number of hours was constant at 48 per week; and for workers between 14 and 16 years old it was
constant at 36 hours per week.
9
2002). This is the sample I use in all regression models presented in the paper. This unbalanced
panel, however, provides limited information to graphically illustrate the evolution over time of
enforcement and compliance. The average number of inspectors across provinces in 1995, for
example, includes a different set of provinces than the average in 1996. A possibility is to restrict
the analysis to those provinces with figures for all years, but the resulting set includes only seven
provinces which is not very informative either. I impute the missing values assuming that the
number of labor inspectors in province i and year t is equal to the average between t-1 and t+1 in
province i. The imputation is used only for the purposes of Figures 1 and 2.
Figure 1 presents the evolution of overall compliance and the balanced measure of
enforcement from 1995 to 2002. Both variables decreased over time. Overall compliance
declined from above 50 percent in 1995 to less than 40 percent in 2002. The average number of
inspectors per 100,000 people decreased almost 30 percent during the same period.
<Figure 1>
Figure 2 is a scatterplot that illustrates the relation between enforcement and compliance
across provinces. I compute the average rate of overall compliance for each province from 1995
to 2002, and the average number of labor inspectors per 100,000 people using the balanced
measure described above. Figure 2 shows that provinces with a higher number of labor
inspectors per capita are more likely to have higher compliance with labor regulations.
<Figure 2>
While these two figures provide evidence that enforcement and compliance are positively
correlated both across provinces and over time, this is not enough to claim enforcement has a
positive causal effect on compliance. A third factor could be driving the correlation, and reverse
causality is also a possibility.
10
The mutual relation between Enforcement and Compliance
Since the seminal works of Allingham and Sandmo (1972) and Ashenfelter and Smith (1979),
there has been a wealth of theoretical articles on tax evasion and minimum wage compliance.15 A
standard result is that a firm’s propensity to evade regulations is inversely related to the
probability of being caught times the expected fine.
Positive theories of enforcement agency’s behavior are less reliable than the theory of the firm
because there is less agreement about the agency’s objective function. The economic theory of
public enforcement of law is based on the assumption that public enforcers act so as to maximize
social welfare (Polinsky and Shavell, 2000). A second approach, more dominant in public
administration, tends to explain enforcement agencies’ behavior in terms of idiosyncratic aspects
of inspectors and the nature of the task (Bardach and Kagan, 1982). A third approach, usually
referred to as capture theory, emphasizes the importance of elected officials and lobby groups in
determining agency structure, tasks and budgets (Calvert, McCubbins and Weingast, 1989).
However, all these theories suggest that enforcement agencies respond to changes in task
environments, where lower compliance usually leads to more enforcement activities and
resources. First, the productivity of an extra labor inspection increases when compliance
decreases because it is less expensive to find offenders. If enforcement agencies are at least
partially guided by cost-benefit considerations, then less compliance produces more
15
Blakemore et al. (1996) model payroll tax evasion in the unemployment insurance program, Flanagan (1989)
models compliance under the National Labor Relations Act, and Ehrenberg and Schumann (1982) consider overtime
provisions.
11
enforcement. Second, when compliance is lower, policy makers are likely to face a larger
demand from the population to increase enforcement.16
Anecdotal evidence in Argentina suggests the government reacts to low compliance by
increasing enforcement efforts. The recent economic and political crisis produced a dramatic
reduction in compliance with labor regulations. The overall measure of compliance reached a
historic minimum level of 35.7 percent in 2003. That year, the Employment Regularization
Program was launched by the government “as a necessary measure given the high level of
unregistered employment” (Argentine Labor Ministry, 2004:1). A more recent incident provides
another example. In March 2006, six textile workers died in a fire in the City of Buenos Aires.
These workers were unregistered, and the building was not authorized to function as a textile
workshop. The event captured the attention of the public, and the media revealed the low levels
of enforcement and compliance with labor regulations that prevail in the city and the unsafe
working conditions faced by many unregistered workers. Immediately after, the government
increased the number of inspections.
Thus the theory and anecdotal evidence suggest that low compliance begets greater allocation
of resources to enforcement, in addition to the reverse causal effect of enforcement on
compliance via deterrence. In light of this reasoning, it is important that empirical research
16
Scholz and Wei (1986) mention that Occupational Safety and Health Administration (OSHA) officials in the
U.S. believe that enforcement resources are most effectively deployed where accident rates are higher, and find that
enforcement increases as a response to higher workplace accidents. Weil and Pyles (2005) find evidence that
compliant rates are higher in industries with more overtime violations and with higher workplace injuries, although
the relation is modest. Ashenfelter and Smith (1979) find that government enforcement efforts are concentrated on
sectors where minimum wage violations are most likely to occur.
12
accounts for the likely endogeneity of enforcement. To allow for such considerations, the
relationship between compliance and enforcement, for province i in year t, is modeled as a
system of two simultaneous equations
(1)
Complianceit = α1 + β1Enforcementit + Xitλ + ε1it
(2)
Enforcementit = α2 + β2Complianceit + Zitδ + ε2it,
where Compliance is the percentage of private sector employees who receive legally-mandated
labor benefits, Enforcement is the number of labor inspectors per capita, and X and Z are
matrices of covariates including province fixed effects. Two aspects of this specification are
worth discussing. First, this is a fixed effects model. An alternative is to regress changes in
compliance on changes in enforcement. Given the unbalanced nature of the data, however, a
fixed effects specification is more efficient because it uses all available information.17 Second,
the model assumes a contemporaneous effect of enforcement on compliance. This is reasonable
because labor inspectorate staffing decisions are usually implemented at the beginning of the
year and compliance reflects working conditions during October. I also briefly discuss the results
obtained using a lagged enforcement model.
The objective in this paper is to estimate β1, the causal effect of enforcement on compliance.
Estimating equation (1) by OLS results in an inconsistent estimator of β1 because it ignores that
enforcement agencies are affected by compliance. One strategy to address the identification
problem is to find a factor that affects enforcement agencies and has no direct effect on firms’
propensities to comply with labor regulations. Large tragedies, such as the one described above,
17
When the panel is balanced, the choice between fixed effects estimation and first differencing hinges on the
assumption about the errors. The fixed effects estimator is more efficient when the errors are serially uncorrelated,
while first differencing is more efficient when the error follows a random walk (Wooldridge 2002: 284).
13
can –to some extent- serve as natural experiments, but fortunately they have been rare.18 In this
paper I explore using electoral years as an exogenous determinant of enforcement.
Electoral Cycle in Labor Inspector Workforce Staffing
Two gubernatorial and presidential elections occurred during the studied period, the first in 1995
and the second in 1999. There are several reasons to suspect a link between elections and the
timing of changes in public enforcement agencies’ resources in Argentina. First, the executive
power controls enforcement agencies’ resources. Second, employment in general and the
protection of workers’ rights in particular, are important electoral issues. Therefore, it is likely
incumbent politicians will change the labor inspector force in advance of elections. The direction
of the change, however, is a priori ambiguous due to potential tradeoffs.19
Empirically, the relation appears to be positive: the average number of labor inspectors is 23.5
in election years compared with 19.8 in nonelection years. Table 3 models enforcement as a
function of election years. All regressions in this paper are weighted by the sample size used to
calculate compliance (i.e., the number of private sector employees in the survey). Column 1
regresses the number of labor inspectors per 100,000 people on the election year indicator only;
column 2 adds province fixed effects (FE) and a linear time trend. The number of labor
inspectors is significantly higher during electoral years. Provinces have, on average, about 1.3
more inspectors per 100,000 people in election years compared with nonelection years.
<Table 3>
18
I searched for tragic events in the two major Argentine national newspapers (La Nación and Clarín) and found
only two events during the period 1995-2002.
19
More enforcement, for example, can increase compliance but can also reduce employment.
14
This simple average, of course, does not take into account possible correlation between the
timing of elections and other factors. If elections are to serve as valid instruments, then the
correlation between elections and enforcement should be robust to controlling for all factors that
are affected by elections and that influence compliance.
The most obvious way in which elections might affect compliance (other than via changes in
the inspector force) is through politically induced fluctuations in economic performance. The
political business cycle literature suggests incumbent politicians usually implement expansionary
policies during electoral years to improve their chances of remaining in power. In Argentina, the
government usually “buys” votes by distributing social benefits to the population, particularly,
access to the public workfare program. This program is likely to reduce unemployment, mainly
among the least skilled, and in doing so, increases compliance. This is due to a few factors: First,
tighter labor markets increase employees’ bargaining power, and hence, their probability of
successfully demanding their employer to comply with labor regulations. Second, workfare
participants are predominantly low-skilled and it is likely many of them would have worked
without labor benefits in the absence of the workfare program. Expansionary policies can
generate price inflation, which in turn, reduces the real cost of some labor regulations, such as
the minimum wage, increasing firms’ incentive to comply with the law.
There could also be an electoral cycle in payroll taxes, and lower taxes reduce the cost of
compliance. Finally, it could be argued that firms anticipate more rigorous regulations in
advance of provincial elections in which pro-labor parties are favored to win. Compliance might
then be positively correlated with elections where those parties are favored to win, via
anticipatory behavior of employers.
15
Consequently, column 3 controls for provincial unemployment rates, inflation rates, number
of public workfare participants per capita, payroll tax rates, and an indicator equal to one if the
elected governor is Peronist (which is the labor-based party in Argentina). Column 4 also
controls for a set of demographic characteristics of the provincial private sector labor force (i.e.,
average age, share below 19 years old, percentage male, illiterate, born in another province,
foreign-born, and average firm size). The election coefficient remains statistically significant at
the 1 percent level. Having controlled for these factors, it seems plausible to argue that election
years is a valid instrument to estimate the effect of enforcement on compliance.20
Estimating the Effect of Enforcement on Compliance
I begin estimating equation (1) by OLS. Column 1 in Table 4 regresses compliance with
employment regulations on the number of inspectors per 100,000 people, a linear time trend, and
the same set of demographic characteristics of private sector employees used in Table 3, that is,
average age, share below 19 years old, percentage male, illiterate, born in another province,
foreign-born, and average firm size. Column 2 adds the same set of economic and political
controls used in Table 3: provincial unemployment rate, inflation, workfare beneficiaries per
capita, the payroll tax rate, and an indicator equal to one if the governor is Peronist. Column 3
includes province fixed effects. Columns 4 to 6 follow the same procedure, but using compliance
with social security regulations as the dependent variable.
<Table 4>
20
The election year coefficient obtained regressing changes in enforcement on the election year indicator and the
full set of controls (first-differenced), is positive and statistically significant at the 0.05 level. Results are available
upon request. This specification, however, drops valuable information because the panel is unbalanced.
16
The results in columns 1, 2, 4 and 5 show that provinces with more enforcement have higher
levels of compliance with both employment and social security regulations. These estimates,
however, do not control for unobserved heterogeneity and it is plausible that an unobserved third
factor is driving the correlation between enforcement and compliance across provinces.
Including province fixed effects eliminates the problem of unobserved heterogeneity, but at
the cost of restricting the estimation to variation within provinces. Columns 3 and 6 show that
the within-province variation in enforcement is not significantly correlated with compliance with
employment regulations and with compliance with social security regulations.
One interpretation is that, in Argentina, increasing enforcement agencies’ staff is an
ineffective policy to reduce noncompliance because inspectors are incompetent. This
interpretation, however, is at odds with available figures on inspectors’ activities. In 1998, the
average labor inspector examined 150 firms and imposed 68 fines.21 Furthermore, there are
reasons to suspect the fixed-effects estimate underestimates the causal effect of enforcement on
compliance, because it is likely that lower compliance increases enforcement agencies’ efforts as
argued before. I test for endogeneity using a Hausman test and reject the hypothesis that
21
The figures are based on 19 provinces. No data is available for Buenos Aires, Formosa, La Rioja, Misiones,
and Río Negro. Of course, there are other interpretations: First, the model lacks statistical power. That is,
enforcement has a positive effect on compliance, but the estimates are statistically insignificant due to the low
number of observations. Second, firms do not react to enforcement, either because they are irrational or because the
expected value of noncompliance is so low than an increase in enforcement is insufficient to produce compliance.
17
enforcement is exogenous in the compliance equation at the 1 percent level, suggesting OLS is
inconsistent.22
Given potential endogeneity, it is necessary to have an exogenous change in enforcement to
identify its effect on compliance. The previous section demonstrates a positive correlation
between elections and enforcement agencies’ staffing, and shows the relation holds after
controlling for factors that influence compliance and can be affected by elections.
Tables 5 and 6 present two-stage least squares (2SLS) estimates of the effect of enforcement –
instrumented by election years- on each measure of compliance. Table 5 presents estimates for
the aggregate measures of compliance, with and without controlling for economic and
demographic covariates, and Table 6 presents estimates for the individual measures of
compliance including the full set of controls.23
The 2SLS estimates are larger than the OLS estimates, and, while imprecisely estimated, are
statistically significant for overall compliance, compliance with employment regulations,
minimum wage, and overtime provisions. Column 3 in Table 5 indicates that an additional labor
22
The Hausman test is based on the observation that if enforcement is endogenous, then the error term in the
reduced form equation and the error term in the structural model are correlated. I first obtain the residual by
regressing the endogenous variable (enforcement) on all exogenous ones, and then include the residual in equation
(1). The residual is statistically significant, so the null of exogeneity is rejected.
23
I also compute 2SLS estimates of the effect of enforcement on compliance including a one-year lag in
enforcement. I find a positive and statistically significant effect on maximum hours but no significant effect for the
other individual measures of compliance (results available upon request). One interpretation is that enforcement has
a persistent effect only on compliance with the maximum-hours regulation. An alternative interpretation is the
lagged enforcement model lacks statistical power. The already small sample size becomes smaller when including a
one-year lag in enforcement due to the unbalanced nature of the enforcement data and the year dropped.
18
inspector per 100,000 people increases the share of private sector employees with all six legallymandated benefits by 1.40 percentage points. Given that average overall compliance in the
sample is 44.66 percent and the mean provincial population is 1.2 million, the estimate implies
that, on average, provinces can expect overall compliance to increase to 44.78 percent if one
extra inspector is hired. Columns 4 and 5 present the estimates for compliance with employment
and with social security regulations respectively. The former is positive and significant, while the
second is insignificant. I discuss below a potential interpretation of this result.
<Table 5>
The results in columns 1 and 2 in Table 6 imply that, on average, hiring an additional labor
inspector increases compliance with the minimum wage by 0.04 percentage points (from 94.19
to 94.23), and with maximum-hours by 0.11 percentage points (from 83.38 to 83.49).
The estimates of the effects of enforcement on compliance with the two mandatory social
security provisions (i.e., workers compensation and health insurance) are positive but statistically
insignificant. One possible reason is larger measurement error in the dependent variable.24 A
more likely explanation is that provincial enforcement agencies are less effective enforcing
social security regulations because of the particular institutional configuration in Argentina.
Provinces can impose fines against lack of compliance with employment regulations and against
employers who do not register their employees in the social security system, but not against
evasion of social security contributions. When they find this violation, provinces have the
authority only to notify the National Tax Collection Agency (AFIP) about the problem and
recommend employers to comply. AFIP is the only agency with the authority to impose fines in
24
It could be argued, for example, that a worker is better informed about his wage than about having workers
compensation insurance. But workers are likely to be well aware of whether they have health insurance.
19
case of social security payroll tax evasion.25 If coordination problems between the agencies exist,
and if employers are aware of them, then we should expect provincial enforcement to be less
effective against lack of compliance with social security regulations.
The correlation between the other covariates and compliance usually has the expected sign,
but in most cases is quite inexact. A larger fraction of the labor force illiterate and foreign-born is
associated with lower rates of compliance suggesting employers take advantage of workers who
ignore their labor rights. Unemployment is negatively related with compliance and inflation is
positively related. When unemployment is higher, workers are willing to accept working more
hours than the legal maximum, presumably because they are afraid of losing their jobs. When
price inflation is higher, compliance with the minimum wage, paid vacation, and the annual extra
monthly wage are higher, which is consistent with the idea that employers decide whether to
breach the law depending on the real cost of regulations.
<Table 6>
As emphasized by Murray (2006), researchers should be doubly vigilant about omitted
variables when doing instrumental variable estimation because the estimates are biased if an
omitted variable that belongs to the model is correlated with the instrument. In other words, the
credibility of the 2SLS estimates depends on having controlled for every factor that affects
compliance and that is correlated with elections. While several controls have been included, the
results should be taken with caution because electoral years differ from non-electoral years in a
25
In practice, however, the agency enforces payroll tax payments only among firms that have already registered
their employees and usually only the large ones because it is considered to be more cost-effective (Colina, Giordano
and Torres, 2003).
20
number of dimensions. Labor unions’ strength, for example, might change during electoral years,
and it can affect compliance.
To control for this potential source of correlation between the instrument and the error in the
compliance equation, I use the percentage of provincial representatives in Congress who are
labor union leaders. In Argentina, given the high level of government intervention in labor
relations, this is a conceivable proxy for labor unions’ strength. An alternative proxy, such as
union density, is not available. The inclusion of this proxy does not affect the estimated effect of
enforcement on compliance in any substantive manner (see Appendix 1).
Conclusion
This paper constitutes one of the first attempts to estimate the effect of government enforcement
on compliance with labor regulations in a developing country. Particular attention is given to
measuring these variables as accurately as possible. I use the number of labor inspectors per
capita as a proxy for enforcement, and compute measures of compliance with six legallymandated employment and social security regulations: minimum wage, maximum hours, paid
vacation, extra annual monthly wage, workers compensation insurance, and health insurance.
To address the problem of potential simultaneity between enforcement and compliance, I
exploit the existence of an electoral cycle in enforcement agencies staffing. Although the
instrumental variable estimates are imprecise, the results do provide evidence suggesting more
labor inspectors reduces noncompliance.
From a policy perspective, however, this paper is limited because it does not provide
estimates of the effect of enforcement on other labor market outcomes. Theoretically, greater
enforcement can have either a positive or a negative effect on employment and wages depending
21
on a number of factors such as: the regulation being enforced, whether firms have monopsony
power, and whether access to labor benefits affects workers’ productivity and their labor supply.
In the absence of solid empirical research on these questions, it is unclear how policy makers
should react.
The economic effect of labor law has been extensively discussed. Enforcement and
compliance, however, has received less attention. This is somewhat reasonable when the analysis
is restricted to developed countries where compliance is usually high. The large majority of
workers, however, work in developing countries where labor laws are only partially enforced.
This paper constitutes an attempt towards filling that gap.
22
Figure 1 – Trends in Inspection Agency Staffing and Overall Compliance
10
60
50
8
Compliance
7
40
6
Inspection Agents
5
30
4
20
3
2
10
Percentage of private sector employees who receive all
legally-mandated benefits
Number of Labor Inspectors per 100,000 people
9
1
0
0
1995
1996
1997
1998
1999
2000
2001
2002
Year
Note: Overall compliance is the share of private sector employees with all six legally-mandated benefits: minimum wage,
maximum hours, paid vacation, annual extra monthly wage, workers compensation insurance, and health insurance. Election
years are 1995 and 1999.
23
Figure 2 – Average Inspection Agency Staffing and Overall Compliance by province from 1995
to 2002
Percentage of private sector employees who receive all legallymandated benefits
70
65
Tierra Fuego
60
Ciudad BsAs
Santa Cruz
La Pampa
55
Chubut
y = 0.93x + 39.7
R2 = 0.282
Neuquén
50
Santa Fe
45
Entre Ríos
La Rioja
San Luis
Buenos Aires
Cordoba
Catamarca
Mendoza
40
Chaco
San Juan Corrientes
Jujuy
Sgo Estero Misiones
35
Tucumán
Salta
30
Formosa
0
2
4
6
8
10
12
14
16
18
20
Number of Labor Inspectors per 100,000 people
Note: Overall compliance is the share of private sector employees with all six legally-mandated benefits: minimum wage,
maximum hours, paid vacation, annual extra monthly wage, workers compensation insurance, and health insurance.
24
Table 1 – Summary Statistics
Variable
Mean
Std. Dev.
Within-province
Std. Dev.
Overall compliance (%)
Compliance with Employment regulations (%)
Minimum wage (%)
Maximum hours (%)
Annual extra monthly wage (%)
Paid vacation time (%)
Compliance with Social Security regulations (%)
Workers compensation insurance (%)
Health insurance (%)
Number of Labor Inspectors (per 100,000 people)
Election year
Total population (in thousands)
Private sector employees (in thousands)
Age
Percentage male
Percentage illiterate
Percentage born in another province
Percentage foreign-born
Firm size (No. of employees)
Unemployment rate
Inflation rate
Workfare beneficiaries (per 1,000 people)
Payroll tax rate
Peronist governor
Labor unions’ strength
Sanction payroll tax evasion
Sanction severance payment
Sanction interest rate
44.66
48.26
94.19
83.38
58.52
58.14
53.89
56.43
55.53
5.34
0.25
1,176
166.04
34.23
71.95
0.95
22.55
5.33
56.64
12.57
5.91
11.53
34.45
0.61
1.84
0.75
0.25
0.13
10.43
9.97
3.09
5.18
10.62
10.69
11.74
11.16
11.57
5.52
0.43
2,346
354.29
1.18
4.35
0.68
14.34
6.32
25.65
4.30
17.90
14.13
3.92
0.49
5.00
0.43
0.43
0.33
5.57
5.54
1.92
4.56
4.40
4.39
4.78
3.95
4.68
2.46
0.43
70
25.66
0.73
2.86
0.46
2.07
1.45
10.50
2.35
17.81
12.95
3.12
0.27
1.83
0.43
0.43
0.33
Notes: The unit of analysis is a province-year. Number of observations is 184, except for number of inspectors which is 153. The
sample includes all 24 Argentine jurisdictions (except Rio Negro) over the period 1995-2002. Compliance is measured as the
percentage of private sector employees with legally-mandated labor benefits. The demographic characteristics refer to private
sector employees. Firm size is the average value reported by workers in each province-year. Peronism is the labor-base party in
Argentina. Labor unions’ strength is defined as the percentage of provincial representatives in Congress who are labor union
leaders. The sanctions variables are dummies for the presence of each of the following three statutory changes: penal sanction
that applies to employers who evade the payroll tax (increased in 1997), severance payment employers have to pay to their
unregistered workers (increased in 2001), and the interest rate applied to debts that employers owe to their unregistered workers
(increased in 2002). Data on compliance and socioeconomic characteristics is from the Permanent Household Survey (EPH);
enforcement and workfare beneficiaries is from the Argentine Ministry of Labor; unemployment and inflation is from the
Argentine Ministry of the Economy; labor unions’ strength is from the Argentine Congress; and payroll tax and the sanction
dummies are constructed form the legislation.
25
Table 2 – Percentage of Private Sector Employees who receive Legally-Mandated Benefits, by
Demographic group and Labor Regulation
Minimum
wage
Maximum
hours
Paid
Vacation
Annual extra
wage
Workers
compensation
Health
insurance
Female
94.2
90.7
59.7
60.1
56.6
58.0
Male
94.2
80.0
57.0
57.4
54.8
56.5
69.7
12.5
12.7
11.0
11.2
Demographic group
(a)
Less than 19 years old
100
19 years old or more
94.0
84.0
59.6
59.9
57.0
58.7
High school dropout
92.6
79.6
49.5
50.0
47.6
49.1
Completed high school
96.0
87.5
67.1
67.3
64.0
65.7
Foreign-born
94.2
82.4
51.6
51.9
49.5
50.8
Native
94.2
83.4
58.3
58.7
55.8
57.4
Notes: The sample includes all 24 Argentine jurisdictions (except Rio Negro) over the period 1995-2002.
(a) There is no minimum wage for workers younger than 19 years old, so the rate of compliance is 100 percent by definition.
26
Table 3 – The Election Cycle as a predictor of the number of Inspection Agents
Variable
First-stage estimates (DV = No. Labor Inspectors per 100,000 people)
(1)
(2)
(3)
(4)
1.304***
(0.482)
1.110**
(0.474)
1.312***
(0.480)
1.378***
(0.475)
Unemployment rate
-
-
-0.026
(0.108)
-0.042
(0.116)
Inflation rate
-
-
-0.046
(0.029)
-0.053*
(0.030)
Payroll rate
-
-
-0.037
(0.095)
-0.044
(0.094)
Workfare p/c
-
-
0.102**
(0.051)
0.120**
(0.054)
Peronist governor
-
-
0.312
(0.762)
0.667
(0.843)
Average age
-
-
-
0.209
(0.460)
Share less 19 years old
-
-
-
-28.23
(22.23)
Share male
-
-
-
-0.433
(11.68)
Share migrant
-
-
-
7.28
(10.55)
Share foreign-born
-
-
-
4.11
(20.10)
Share illiterate
-
-
-
-28.15
(50.19)
Average firm size
-
-
-
Linear time trend
Province FE (23)
F-statistic
No
No
7.32
Yes
Yes
5.48
Yes
Yes
7.51
0.035*
(0.020)
Yes
Yes
8.41
Election year
Notes: All regression models are weighted by the sample size used to calculate compliance (i.e., the number of private sector
employees in the survey). Standard errors are in parentheses. Number of observations is 153. The F-statistic tests the hypothesis
the election year indicator is zero. * Significant at the .10 level, ** at the .05 level, *** at the .01 level.
27
Table 4 – OLS estimates of the effect of Enforcement on Compliance with Labor Laws
Variable
Compliance with Employment
Regulations
(1)
(2)
(3)
Compliance with Social Security
Regulations
(4)
(5)
(6)
Labor inspectors
0.461***
(0.091)
0.451***
(0.085)
0.116
(0.110)
0.611***
(0.122)
0.551***
(0.109)
0.016
(0.140)
Average age
2.408***
(0.553)
2.488***
(0.542)
1.280**
(0.597)
2.006***
(0.738)
2.139***
(0.693)
0.425
(0.757)
Share less 19 yrs.
-87.97**
(33.45)
-70.94**
(31.87)
-10.76
(28.81)
-69.35
(44.62)
-48.02
(40.79)
-26.40
(36.51)
Share male
-57.02***
(14.24)
-47.77***
(15.05)
-28.64*
(15.11)
-32.93*
(18.99)
-7.70
(19.25)
33.59*
(19.15)
Share migrant
35.14***
(4.08)
41.60***
(4.24)
2.34
(13.72)
33.20***
(5.44)
39.57***
(5.43)
-7.57
(17.38)
Share foreign-born
-37.47***
(10.88)
-47.94***
(10.55)
-66.96**
(26.07)
17.46
(14.51)
2.08
(13.50)
-71.31**
(33.04)
Share illiterate
-99.72
(79.95)
-139.8*
(73.63)
-113.4*
(65.11)
-65.05
(106.6)
-140.4
(94.2)
-76.70
(82.50)
Average firm size
0.022
(0.020)
-0.017
(0.021)
0.030
(0.027)
0.048*
(0.027)
-0.006
(0.027)
0.058*
(0.034)
Unemployment
-
-0.336***
(0.107)
-0.262*
(0.151)
-
-0.560***
(0.137)
-0.258
(0.192)
Inflation rate
-
0.031
(0.048)
0.034
(0.039)
-
0.047
(0.061)
0.010
(0.049)
Payroll rate
-
0.307**
(0.142)
0.074
(0.121)
-
0.593***
(0.181)
0.271*
(0.154)
Workfare p/c
-
-0.246***
(0.080)
-0.179**
(0.069)
-
-0.245**
(0.102)
-0.112
(0.087)
Peronist governor
-
-2.845***
(0.828)
-1.491
(1.097)
-
-5.227***
(1.060)
-0.921
(1.390)
Linear time trend
Province FE (23)
R-squared
Yes
No
0.70
Yes
No
0.75
Yes
Yes
0.88
Yes
No
0.62
Yes
No
0.71
Yes
Yes
0.87
Notes: Enforcement is measured as the number of labor inspectors per 100,000 people. Compliance with employment regulations
is the share of private sector employees who receive all of the following benefits: minimum wage, maximum hours, paid
vacation, extra monthly wage; Compliance with social security regulations is the share with workers compensation and health
insurance. All regression models are weighted by the sample size used to calculate the average serving as the dependent variable.
Standard errors are in parentheses. Number of observations is 153. * Significant at the .10 level, ** at the .05 level, *** .01 level.
28
Table 5 – Two-stage least squares estimates of the effect of Enforcement on Compliance with
Labor Laws
(3)
Compliance
w/employment reg.
(4)
1.667
(0.948)
*
1.746
(0.944)
1.401**
(0.688)
1.276**
(0.591)
0.697
(0.588)
Average age
-
-0.032
(1.028)
0.721
(0.940)
0.928
(0.807)
0.219
(0.803)
Share less 19 yrs.
-
30.61
(54.06)
24.22
(46.57)
14.09
(39.96)
-11.83
(39.76)
Share male
-
25.87
(26.21)
8.154
(23.37)
-24.35
(20.06)
36.10*
(19.96)
Share migrant
-
-2.217
(24.43)
-5.038
(21.56)
-5.352
(18.50)
-12.08
(18.41)
Share foreign-born
-
-85.10*
(44.07)
-84.93**
(40.42)
-75.82**
(34.69)
-76.51**
(34.52)
Share illiterate
-
-94.59
(115.1)
-67.64
(100.9)
-91.30
(86.63)
-63.72
(86.20)
Average firm size
-
0.025
(0.050)
-0.001
(0.047)
-0.009
(0.040)
0.035
(0.057)
Unemployment
-
-
-0.472**
(0.235)
-0.209
(0.201)
-0.227
(0.200)
Inflation rate
-
-
0.061
(0.066)
0.085
(0.057)
0.040
(0.057)
Payroll rate
-
-
0.159
(0.187)
0.087
(0.160)
0.279*
(0.159)
Workfare p/c
-
-
-0.190
(0.121)
-0.281**
(0.104)
-0.172*
(0.103)
Peronist governor
-
-
-2.060
(1.747)
-2.277
(1.499)
-1.382
(1.492)
Linear time trend
Province FE (23)
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Overall Compliance
Variable
(1)
Labor Inspectors
(2)
*
Compliance w/
social security reg.
(5)
Notes: Enforcement is measured as the number of labor inspectors per 100,000 people. Compliance with employment regulations
is the share of private sector employees who receive all of the following benefits: minimum wage, maximum hours, paid
vacation, extra monthly wage. Compliance with social security regulations is the share with workers compensation and health
insurance. Overall compliance is the share who receives all six benefits. All regression models are weighted by the sample size
used to calculate the average serving as the dependent variable. Standard errors are in parentheses. Number of observations is
153. Enforcement is instrumented by election years in all the models. * Significant at the .10 level, ** at the .05 level.
29
Table 6 – Two-stage least squares estimates of the effect of Enforcement on Compliance with
individual Employment and Social Security regulations
Variable
Minimum
wage
Maximum
hours
Paid
Vacation
Extra annual
wage
Health
insurance
Workers
compensation
(1)
(2)
(3)
(4)
(5)
(6)
Labor Inspectors
*
0.443
(0.240)
**
1.306
(0.580)
0.647
(0.481)
0.697
(0.477)
0.643
(0.572)
0.174
(0.416)
Average age
-0.234
(0.328)
0.706
(0.792)
0.408
(0.657)
0.475
(0.652)
0.313
(0.782)
0.739
(0.568)
Share less 19 yrs.
20.72
(16.23)
52.95
(39.24)
-21.66
(32.52)
-17.63
(32.28)
-20.93
(38.72)
-25.32
(28.12)
Share male
2.030
(8.144)
-20.07
(19.69)
-3.01
(16.32)
-3.93
(16.20)
26.79
(19.43)
14.38
(14.11)
Migrant
-7.329
(7.513)
3.475
(18.17)
-11.71
(15.06)
-11.58
(14.94)
-6.65
(17.92)
-18.57
(13.02)
Foreign-born
-6.518
(14.09)
-50.09
(34.06)
-53.61*
(28.23)
-57.68**
(28.02)
-75.17**
(33.61)
-53.18**
(24.41)
Share illiterate
-66.21*
(35.18)
-46.16
(85.06)
-65.59
(70.50)
-79.41
(69.97)
-40.98
(83.94)
-120.45**
(60.96)
Average firm size
-0.019
(0.016)
-0.048
(0.039)
0.010
(0.033)
0.014
(0.032)
0.044
(0.039)
0.021
(0.028)
Unemployment
-0.046
(0.082)
-0.482**
(0.198)
0.160
(0.164)
0.176
(0.163)
-0.148
(0.195)
-0.032
(0.142)
Inflation
0.044*
(0.023)
0.007
(0.056)
0.091*
(0.046)
0.076*
(0.046)
0.036
(0.055)
0.019
(0.040)
Payroll rate
-0.041
(0.065)
-0.036
(0.157)
0.208
(0.130)
0.194
(0.129)
0.202
(0.155)
0.221*
(0.123)
Workfare p/c
-0.080*
(0.042)
0.013
(0.102)
-0.323***
(0.084)
-0.318***
(0.084)
-0.178*
(0.100)
-0.167**
(0.073)
Peronist governor
-0.293
(0.609)
-2.309
(1.472)
-1.959
(1.220)
-1.599
(1.211)
-1.081
(1.452)
-1.062
(1.055)
Linear time trend
Yes
Yes
Yes
Yes
Yes
Yes
Province FE (23)
Yes
Yes
Yes
Yes
Yes
Yes
Notes: Enforcement is measured as the number of labor inspectors per 100,000 people. The dependent variable is the share of
private sector employees who receive the legally-mandated benefit described in the top of the column. All regression models are
weighted by the sample size used to calculate the average serving as the dependent variable. Number of observations is 153.
Enforcement is instrumented by election years in all models. * Significant at the .10 level, ** at .05, *** at .01 level.
30
Appendix 1 – Additional 2SLS specification of the effect of Enforcement on Compliance
Overall
compliance
Compliance w/employment
regulations
Compliance w/social
security regulations
Labor Inspectors
1.400**
(0.706)
1.303**
(0.616)
0.494
(0.579)
Sanction payroll tax evasion
1.660
(1.979)
0.018
(1.726)
-0.926
(1.621)
Sanction severance payment
2.077
(2.823)
2.301
(2.471)
-0.499
(2.320)
Sanction interest rate
9.437
(7.522)
3.938
(6.561)
3.417
(6.162)
Labor Unions’ strength
-18.070
(26.918)
-12.529
(23.482)
-21.000
(22.051)
Average age
0.596
(0.937)
0.861
(0.817)
0.224
(0.767)
Share less 19 yrs.
10.28
(47.94)
2.90
(41.83)
-24.57
(39.28)
Share male
3.34
(23.78)
-28.79
(20.74)
34.13*
(19.48)
Migrant
-9.25
(22.57)
-4.51
(19.69)
-10.92
(18.49)
Foreign-born
-80.68**
(40.34)
-72.71**
(35.20)
-74.05**
(33.05)
Share illiterate
-70.17
(100.18)
-88.23
(87.39)
-59.36
(82.07)
Average firm size
-0.014
(0.050)
-0.019
(0.044)
0.040
(0.041)
Unemployment
-0.459
(0.298)
-0.321
(0.260)
-0.318
(0.244)
Inflation
-0.042
(0.106)
0.034
(0.093)
-0.021
(0.087)
Payroll rate
0.094
(0.241)
-0.015
(0.210)
0.325*
(0.197)
Workfare p/c
-0.310*
(0.165)
-0.331**
(0.144)
-0.165
(0.135)
Peronist governor
-1.634
(1.914)
-2.140
(1.670)
-0.790
(1.568)
Variable
Notes: The sanctions variables are dummies for the presence of each of the following three statutory changes: penal sanction that
applies to employers who evade the payroll tax (increased in 1997), severance payment employers have to pay to their
unregistered workers (increased in 2001), and the interest rate applied to debts that employers owe to their unregistered workers
31
(increased in 2002). These penalties apply to all provinces equally. Provincial enforcement agencies also impose fines against
employers who do not comply with the law, but I have not been able to collect this information. Other variable definitions are in
Table 1. All regression models are weighted by the sample size used to calculate the average serving as the dependent variable,
and include province fixed-effects and a linear time trend. Number of observations is 153. Enforcement (measured as the number
of labor inspectors per 100,000 people) is instrumented by election years in all regressions. * Significant at the .10 level, ** at the
.05 level.
32
References
Allingham, Michael, and Agnar Sandmo. 1972. “Income Tax Evasion: A Theoretical Analysis.”
Journal of Public Economics, Vol. 1, No. 3-4 (November), pp. 323-38.
Argentine Labor Ministry. 2004. Plan Nacional de Regularización del Trabajo, Buenos Aires.
Ashenfelter, Orley, and Robert Smith. 1979. “Compliance with the Minimum Wage Law.”
Journal of Political Economy, Vol. 87, No. 2 (April), 333-50.
Bardach, Eugene, and Robert Kagan. 1982. Going by the Book: The Problem of Regulatory
Unreasonableness. Philadelphia, PA: Temple University Press.
Blakemore, Arthur, Paul Burgess, Stuart Low, and Robert St. Louis. 1996. “Employer Tax
Evasion in the Unemployment Insurance Program.” Journal of Labor Economics, Vol. 74, No. 2
(April), pp. 210-30.
Botero, Juan, Simeon Djankov, Rafael La Porta, Florencio Lopez-de-Silanes, and Andrei
Shleifer. 2004. “The Regulation of Labor.” Quarterly Journal of Economics, Vol. 119, No. 4
(November), pp. 1339-82.
Calvert, Randal, Matthew McCubbins, and Barry Weingast. 1989. “A Theory of Political
Control and Agency Discretion.” American Journal of Political Science, Vol. 33, No. 3
(August), pp. 588-611.
Colina, Jorge, Osvaldo Giordano, and Alejandra Torres. 2003. “La Masividad del Empleo No
Registrado en la Argentina.” Documento de discusión No.1, Instituto para el Desarrollo Social
Argentino.
Ehrenberg, Ronald, and Paul Schumann. 1982. “Compliance with the Overtime Pay Provisions
of the Fair Labor Standards Act.” Journal of Law and Economics, Vol. 25, No. 1 (April), pp.
159-81.
33
Flanagan, Robert. 1989. “Compliance and Enforcement Decisions under the National Labor
Relations Act.” Journal of Labor Economics, Vol. 7, No. 3 (July), pp. 257-80.
Gray, Wayne, and Carol Jones. 1991. “Are OSHA Health Inspections Effective? A Longitudinal
Study in the Manufacturing Sector.” Review of Economics and Statistics, Vol. 73, No. 3
(August), pp. 504-8.
Hanson, Gordon, and Antonio Spilimbergo. 1999. “Illegal Immigration, Border Enforcement,
and Relative Wages: Evidence from Apprehensions at the U.S.-Mexico Border.” American
Economic Review, Vol. 89, No. 5 (December), pp. 1337-57.
Ihrig, Jane, and Karine Moe. 2004. “Lurking in the shadows: the informal sector and government
policy.” Journal of Development Economics, Vol. 73, No. 2 (April), pp. 541-57.
IDB (Inter-American Development Bank). 2004. Good Jobs Wanted: Labor Markets in Latin
America. Washington D.C.: IDB.
Iunes, Roberto. 2001. “Occupational Safety and Health in Latin America and the Caribbean:
Overview, Issues and Policy Recommendations.” Presented at the Seminario Técnico de
Consulta sobre temas laborales, Ciudad de Panamá, Noviembre 2001.
Johnson, Simon, Daniel Kaufmann, and Pablo Zoido-Lobaton. 1998. “Regulatory discretion and
the unofficial economy.” American Economic Review, Vol. 88, No. 2 (May), pp. 387-92.
Levitt, Steven. 1997. “Using Electoral Cycles in Police Hiring to Estimate the Effect of Police on
Crime.” American Economic Review, Vol. 87, No. 3 (June), pp. 270-90.
Loayza, Norman. 1997. “The economics of the informal sector: a simple model and some
empirical evidence from Latin America.” World Bank Policy Research Working Paper 1727,
Washington D.C.
34
Murray, Michael. 2006. “Avoiding Invalid Instruments and Coping with Weak Instruments.”
Journal of Economic Perspectives, Vol. 20, No. 4 (Fall), pp. 111-32.
Polinsky, Mitchell, and Steven Shavell. 2000. “The Economic Theory of Public Enforcement of
Law.” Journal of Economic Literature, Vol. 38, No. 1 (March), pp. 45-76.
Scholz, John, and Feng Heng Wei. 1986. “Regulatory Enforcement in a Federalist System.”
American Political Science Review, Vol. 80, No. 4 (December), pp. 1249-1270
Weil, David. 2005. “Public Enforcement/ Private Monitoring: Evaluating a New Approach to
Regulating the Minimum Wage.” Industrial and Labor Relations Review, Vol. 58, No. 2
(January), pp. 238-57.
Weil, David, and Amanda Pyles. 2005. “Why Complain? Complaints, Compliance, and the
Problem of Enforcement in the U.S. Workplace.” Comparative Labor Law and Policy Journal,
Vol. 27, No. 1, pp. 59-92.
Wooldridge, Jeffrey. 2002. Econometric Analysis of Cross Section and Panel Data. Cambridge,
MA: MIT Press.
35