Illegal Labor Markets

Lent TermEc 423: Labour Economics

Lecture 9

Legal vs. Illegal Sectors So far have consider two roles of occupation

selection: High vs. Low skills human capital/ signaling model Gender/Race segregation

Can be other types of markets Informal: Legal jobs not reported/measured in

standard activity Black Market: Trade/activity often in illegal or

restricted goods Criminal Activity: Illegal actions performed for

gain but not necessarily for the purpose of trade

What’s Important about Illegal Markets? Important alternative way to allocate time

May have different returns to human capital May have distinct career paths/specific

capital/OTJ training

Externalities High potential social costs to criminal activities

themselves May generate costs for local areas (similar to

agglomeration issues for urban growth)

Link to Legal Sector Wages

Decision to enter or exit may be based on expected wages

Strong interaction here with: Returns to Education Education Production/Credit Constraints Discrimination

Occupation Mobility May be long-term costs to entry into illegal

sector Much more difficult to exit once detected

This Lecture Model of Criminal Participation

Focus on interaction with legal sector Wages in Legal vs. Illegal Sector Penalty for Participation Racial Composition

Next time: Focus on the Illegal Sector Taxing Participation Deterrence vs. Incapcitation

Extreme Test for Economics Inherently risky: attitudes toward risk are

critical in decision-making. Criminal behavior is subject to strategic

gaming by the police, criminals, and the public, per the Prisoner's Dilemma.

Psychology of Criminality

Basic Model Individual will choose to commit crimes in

a given time period rather than do legal work when:(1 - p)U(Wc) - pU(S) > u(w)

Wc is the gain from successful crime p the probability of being apprehended S the extent of punishment, W is earnings from legitimate work

Implications for legal wages Crime must pay a higher wage than

legitimate activities. If p= 0, U(Wc) > U(W) only if Wc > W As p rises the gap between Wc and W must

increase to maintain the advantage of crime. Successful crime must pay off more the greater

the chance of being apprehended May be non-pecuniary gains to crime (we’ll

sidebar this for now but come back to it)

Risk Aversion that attitudes toward risk are measured by

the curvature of U

Differences in responses to costs of crime changes in the chances of being apprehended changes in the extent of punishment

Heterogeneity Clearly not likely to be the same as average RA

in population May be lots of heterogeneity within those in the

illegal sector

Costs and Opportunity Costs If we accept that sentences “deter” crime,

must suggest that some individuals on the margin respond to costs the major factors that affect the decisions to

commit crime - criminal versus legitimate earnings, the chance of being caught, and the extent of sentencing - are intrinsically related.

If tougher sentences can theoretically reduce crime then so may improvements in the legitimate opportunities of criminals

Crime Supply To get the supply of crimes and criminal

participation equations for the population, aggregate to obtain the supply curves of crime: CPP = f(Wc,p, S, W)

CPP =f(1 - p)W c - pS - W),p) CPR = g(Wo,p, S, W)

CPR = g(1 - p)Wc - pS - W,p)

where the first term represents the expected value of crime versus legal work, and p measures risk.

Crime “Demand” For Informal and Black Market, ‘Crime’ demand is

just the demand for the products supplied Easy to imagine in the case of drugs or prostitution Generally, issue is elasticity of demand

Victims' crime more complicated to think about Should be negatively related to Wc or to the expected

reward to crime ((1 - p)Wc - pS - W) in a demand type relation.

Intuition 1: Additional crimes are likely to induce society to increase p or S, cutting the rewards to crime.

Intuition 2: As criminals commit more crimes, they will move from more lucrative crimes to less lucrative crimes.

Market Equilibrium An upward sloping supply curve to crime

and downward sloping "demand" relation produce a market clearing level of crime and rewards to crime comparable to the market clearing wages and

employment for other occupations or industries Important implication for the efficacy of mass

incarceration in reducing crimes. Simple demand-supply framework fails to

explain some important phenomenon concentration of crime in geographic areas or over

time Adverse effect of crime on legitimate earnings

Returns to Incarceration A major benefit of incarceration is that it removes

criminals from civil society so that they cannot commit additional offenses Given the wide variation in crimes committed by

criminals, incarceration of chronic offenders should have a particularly large effect in reducing crime.

Inelastic Supply: if you lock up someone who commits, l0 muggings a year, no one replaces that criminal in the alley, the number of muggings should drop by 10

Perfectly Elastic Supply: if you lock someone who commit, instant replacement and no decline in crime

Supply and Demand with Incarceration

WC

LC

Demand

Supply

L1L2

w1

w2

Theory and Evidence Based on Model Effect of Legal Employment/wages on

criminal participation Does increased unemployment increase crime? Do increases in wages in certain sectors

reduce crime? Does inequality affect crime?

Exclusivity of Illegal and Legal Sectors Typically for ease, we think of

crime/legitimate work decision a dichotomous one, The border between illegal and legal work is

porous, persons commit crimes while employed -

doubling up their legal and illegal work. Some persons use their legal jobs to succeed in

crime Some criminals shift between crime and work

over time, depending on opportunities.

Maximization Problem chooses time at market work (tm) and time

committing crime (tv)

Individual then subject to a budget constraintand a time constraint

For simplicity set nonlabor income A=0 and define the marginal rate of substitution

Participation conditions The individual’s reservation wage = u0. participation in the two sectors requires

that w > u0 p'(0) > u0

the returns to the first hour of work in either sector is greater than the reservation utility of an individual

Participation in the Insurgency An individual working in both the legal and

illegal sectors will choose their optimal time allocation to satisfy: p'(tV) = w

to participate in both sectors: p'(0) > w

Three groups Only Legal: p'(0) ≤ 0 : tv=0, tm>0 Both: p'(0) > 0: tv >0, tm > 0 Only Illegal: p'(0) >> 0: tv >0, tm = 0

Extensive vs. Intensive Margin In theory, can change crime labor supply

both by changing number participating and/or number of hours available

Can put this together to estimate

Unobservability of participation Difficult to observe true participation Use production function of crime in an

area j at time t as Ajt = f (Ljt, Kjt) Can Observe total number of crimes (i.e.

output) Can now return this to our standard labor

economics framework For many types of crime, extremely labor

intensive, don’t need to worry about K Labor:

Evidence: Unemployment and Crime Large sociology/criminology literature

doesn’t find much Depends heavily on macroeconomic and time

series variation Unclear what underlying forces drive market

activity and crime—typically left out of analysis

Not much “natural experiment” evidence on this Control for a bunch of stuff Structural model

Mechanisms linking Crime and Economic Conditions Lots of things happen when the economy is

worse Worse legitimate employment opportunities, More criminal opportunities Increased consumption of criminogenic

commodities (alcohol, drugs, guns) Changes in the response of the criminal justice

system.

Rafael and Winters use this breakdown and then use military contracts as an instrument for employment opportunities

First Stage

Bottom line: Not much Evidence Controlling for other factors, almost all of these

studies report a statistically significant but substantively small relationship between unemployment rates and property crime (consistent across lots of evidence)

Can explain an estimated 2 percent decline in property crime (out of an observed drop of almost 30 percent)

Violent crime does not change May operate in indirect channels of state and local

government budgets. increased spending on police prisons

Issues with Estimation Most criminals have limited education and labor

market skills, poor employment records, and low legitimate earnings. For instance, the 1991 Survey of State Prison Inmates

reports that two-thirds had not graduated high school, though many had obtained a general equivalency degree

Among 25-34 year olds, approximately 12% of all male high school dropouts were incarcerated in 1993.

The average AFQT score of criminals is below that of non-criminals.

A disproportionate number of criminals report that they were jobless in the period prior to their arrest.

Issues with Existing Evidence Those business cycles may not

significantly affect the outcomes of the worst off Changes in unemployment not operating on

correct margin Not observing same set of people affected by

jobs/wages/etc.

Crimes that may be most affected may be least observable

Incarceration in the US

Long-term Labor Market Consequences Crime rates not just negative externality,

but huge costs for individuals in terms of lost earnings

Why? Signal of quality Depreciation of human capital Loss of experience

Identification issue Prison is not independent of other things

Worse offenders in prison longer Least able in prison (?)

Can try to separate out 3 effects Type of person who would be in prison (if

prison itself is unobservable) Ever in prison Duration in Prison

Evidence on Incarceration - 1 Freeman's studies of the effects of criminal activity on the

labor market outcomes for youth finds incarceration was significantly linked to lower future employment and weeks worked, Cannot say whether the link is due to the sentencing or to the

fact that only youths deeply involved in crime are incarcerated. In the NLSY young men who were incarcerated worked around 12

weeks less per year as other young men over an ensuing seven year period, giving a 25% lower rate of work activity.

One reason for the huge incarceration effect in the NLSY is that persons incarcerated have a high probability of engaging in crime again and being re-incarcerated and thus not able to work even if they wanted to do so.

even among non-institutionalized young men, those who have been to jail/prison have lower employment rates than others and a lower rate of employment than they had before going to jail or prison (

Nagin and Waldfogel (1995) find a positive effect of conviction on employment in a sample of British youths.

Evidence on Incarceration - 2 Bushway's (1996) analysis of the National Youth Survey 32 found adverse

effects from being arrested on both weeks worked and weekly earnings. Within three yem's of an arrest, respondents who were arrested worked seven

weeks less, and earned $92 per week less, than would otherwise be expected without an arrest

Grogger (1995) merged longitudinal arrest records from the California correctional system with unemployment insurance earnings records to examine the effects of arrests and sanctions on male employment and earnings.

Men who were arrested, convicted, or sent to jail or prison had lower earnings and employment than others, but more in the short-term than in the long run.

Workers who went to prison had about a 20% lower earnings than others, while those who went to jail experienced about a 15% lower earnings

Attributed about one-third of black-white differences in non-employment to the effect of arrests on future employment. Waldfogel (1992) finds a large effect of incarceration on earnings and employment

The negative earnings effect is more pronounced among white collar criminals,

10-30% less 5-8 years after release than those convicted but not incarcerated. Conviction for embezzlement and larceny reduces the future legitimate incomes by

about 40%, Lott (1993a) shows even greater drops in legitimate income, presumably due to

reduced time in legitimate work, for persons convicted of drug dealing.

Effect of Duration on Earnings What is the effect of longer incarceration

rates on earnings? (Kling AER paper): Variation in judges generates variation in

sentencing Judges are randomly assigned Look at earnings and recidivism rates (we’ll

focus on the first one)

Earnings by Duration in Prison

Source: Kling, AER (1999)

Identification Begin with simple OLS specification of earnings

(Y) on sentence length (S) controlling for individual characteristics, X,

Data used in the paper has very small sample size of observations on both pre- and post-spell outcomes for the same individuals to estimate the extent of any pre-existing differences,

he imposes a modeling assumption that the association between incarceration length and pre-spell outcomes is stable over time.

How he estimates—OLS Fixed effects model:

Assume things are the same for individuals and any deviation due to incarcerations so look at same individuals, pre and post incarceration

Control for actual pre-existing differences and then compare changes over time

Source: Kling, AER (1999)

How he estimates—IV Model exogenous variation in sentence

length itself as function of judge (Z)

Identifying assumption Judge Assignment is random Some judges have ‘preference’ for longer

sentences Preference independent of underlying case

characteristics (or at least conditionally independent)

Source: Kling, AER (1999)

Bottom line on Duration no substantial evidence of a negative effect of

incarceration length on employment or earnings. In the medium term, seven to nine years after

incarceration spells began, the effect of incarceration length on labor market outcomes is negligible.

In the short term, one to two years after release, longer incarceration spells are associated with higher employment and earnings -- a finding which is largely explained by differences in offender characteristics and by incarceration conditions, such as participation inwork release programs.

Bottom-line on Incarceration Involvement with the criminal justice system affects future labor

market outcomes. Incarceration is negatively correlated with future outcomes while the

correlation between arrest and conviction and ensuing work activity is generally more moderate.

The question remains open, however, about the causal mechanisms, if any, that underlie the links.

Moreover, the effects probably vary among groups and over time and across prison experiences.

As more and more men are sent to jail or prison Any stigma attached to incarceration in the job market may fall (it is

less of signal) The adverse relation between incarceration and labor outcomes may

also have a strong age component, being larger among younger men and smaller among older men in the declining part of the age-crime curve.

Some evidence that prisoners who receive job training or who work in prison have better employment experiences after release than others.

Is there a ‘stigma’ to incarceration? The labor market prospects of ex-offenders

are likely to be impacted by whether employers have access to their criminal history records. Employers may be reluctant to hire job applicants

with criminal histories for fear that such applicants may harm a customer or be more likely to steal.

If employers can and do review criminal history records, individuals with past convictions are likely to be excluded from consideration.

Given the high proportion of blacks who have served time, one might argue that such exclusion should have particularly adverse consequences for African-Americans.

Holzer, Rafael, Stoller (2006)

The effect of Criminal Background Checks Use variation in legality of employment

checks to measure likelihood of background checks

Look at employment rates of blacks Follow-up studies in sociology using ‘names’

approach on resume finds more mixed results Hard to know how much is really due to

incarceration statistical discrimination vs. other stuff

Costs for Non-Criminals Employer review criminal history records may

also impact the labor market prospects of individuals without criminal records. If accessibility to criminal history information is limited

(due to cost, state prohibitions, or the incompleteness of state and federal records), employers may infer the likelihood of past criminal activity from race

Such statistical discrimination would adversely affect the employment outcomes of individuals with clean histories that belong to demographic groups with high conviction rates.

How big is the effect? about 30% of employers do not want to hire ex-

offenders but do not check criminal records. For these employers, there is a total employment

reduction of 1.0-1.3 percentage points on a base of roughly 10 percent (Table 2).

These data imply that statistical discrimination of this type reduces the demand for labor among black men by 10-13 percent, which can be regarded as a lower bound to the true effect.

The extent to which this reduced demand translates into wage and employment reductions then depend, of course, on the relevant labor demand and supply elasticities for this group

The Illegal Sector Slightly outside the bounds of labor

economics Prostitution/drugs/ etc. typically performed by

organized crime Markets for illegal activity linked with markets

for informal activity Negative externalities:

Increased crime in neighborhoods Reduced property values worse public goods, etc.

Big Issue: Observability Very hard to observe

Prices Quantities Labor Supply/Demand

Not clear how well defined market is Extortion/risk/costs of business Inelastic demand

Growing work Economics of Organized Crime

Mostly Theoretical on networks or organization Increasing Empirical focus, largely due to

international terrorism issues

Economics of Drugs/Drug Markets Addiction Penalties Rehabilitation

Innovation in Illegal Markets: Crack Crack cocaine is a smoked version of cocaine

that provides a short, but extremely intense, high.

The invention of crack represented a technological innovation that dramatically widened the availability and use of cocaine in inner cities.

Sold in small quantities in relatively anonymous street markets, crack provided a

lucrative market for drug sellers and street gangs

Observing Crack Really hard to do

At the time, didn’t really know what was happening so not much data collection

Now, hard to observe ex-post Outcomes and correlates the same thing—hard to test what

the causal effect was Previous literature has mixed up outcomes

Homicides Foster care Birthweight

Hard to know what the true contribution of crack might be

Outcomes vs. Proxies Inputs into the index

cocaine arrests and cocaine-related ER visits frequency of crack cocaine mentions in

newspapers, Cocaine-related drug deaths the number of DEA drug seizures and undercover

drug buys that involve cocaine.

Outcomes - 1

Outcomes - 2

Drugs and Gangs An important aspect of illegal markets is

that the finance illegal activities

Most frequent concern is the role of drugs in financing gangs and thus encouraging violence Akerloff and Yellen (1994) model: need 3

parties: the gang, the police and the populace Concerns over negative externalities here are

very large

Gang Organization

Data Really not many sources Levitt and Venkatesh collect data in

Chicago gangs We don’t know how externally valid these are Provide important insight into gangs

Average Financing of Gangs

How much money per sale? ‘‘back-of-the envelope’’ suggest these

estimates are reasonable. Using these revenue figures and average dollars

per sale of $10 the number of sales per hour by a drug-

selling team ranges from five to twelve over the sample.

That frequency of sale is consistent with self-reports of the participants as well as other observational data

Expenditures nonwage costs:

costs of drugs sold payments to higher levels of the gang Weapons payments to mercenary fighters funeral costs/ payments to families of the deceased

The greatest nonwage expenditure of the gang was the regular tribute payment to higher levels of the gang. almost 20 percent of total revenues.

Returns to Gang Membership the gang leader retains between $4,200 and

$10,900 a month as profit, for an annual wage of $50,000–130,000

This value is well above what leaders could hope to earn in the legitimate sector given their education and work experience. otherwise would have been,

The officers each earn roughly $1000 per month. These tasks are generally full-time jobs (in the

sense that the people who perform them would be unlikely to be concurrently employed in the legitimate sector)

Return to gang-membership - 2 Relatively low wages in the first few years

In year four: wages shoot up. Why? On the job training? Increased promotion/weeding out Tournament

Evidence of Gang Tournament

Next Time Economics of Crime: The Costs side

What happens if we increase the cost of crime? Increased Sentence Length Increase Probability of Detection

Does response depend on type of crime?

Does response depend on type of criminal?