Crime and Savings in Brazil: an Empirical Investigation João Manoel P. de Mello Eduardo Zilberman LACEA, 2005

Motivation Main focus of the crime literature is on the determinants of crime Another branch of this literature tries to estimate the cost associated with crimes –Material cost –Welfare cost

Motivation The effects of crime on economic variables have not been studied extensively If crime distorts agents’ decisions, it represents another source of cost to the society, generally unaccounted for by the literature.

Research Question How do crime and savings relate empirically? Results: –Property crime seems to increase savings; –Violent crime as a whole is not significant; –Savings appear to affect negatively property crimes, but it does not affect violent crimes.

Theoretical Reasons Through probability of death: –Crime raises  probability of death increases  consumption increases  savings reduce –This channel should be stronger for violent crimes Through the precautionary motive: –Crime raises  future flows of income are more volatile  savings raise –How important is the precautionary motive? Lusardi (1998) – It exists but is not very large Gourinchas e Parker (2001) – It is important at low wealth levels

Theoretical Reasons Through the marginal utility: –If marginal utility of consumption is decreasing on crime, an increase in crime will reduce consumption  Savings will be higher –A caveat: Instead of substitute consumption intertemporally, people could substitute one type of good, that is “taxed” by crime, for another, that is not “taxed” by crime.  No effect on savings However, if crime rate is expected to fall, people will postpone consumption of “taxed” goods

Theoretical Reasons

Descriptive Statistics (São Paulo 2000) (reported crimes)

Dados Unit of observation: city in São Paulo state, Savings measure: total amount of deposits in savings accounts and long-term CDs (Certificates of Deposit). Crime measure: total number of crimes reported.

OLS Regressions

OLS Regressions: Interpretations 1.For violent crime, effects could be offsetting themselves; 2.Channels are more relevant for property crime; 3.Expectations is relevant only for property crime; 4.In Brazil, people can protect themselves better from violent crimes (example: avoiding pass in isolated areas at night).

OLS regressions: property crimes

Dealing with the reverse causality Focus: property crime Assumption: savings decrease crime  Coefficient is unambiguously positive Strategies for identification: –Look for exogenous variation in crime –Estimate the reverse effect

Exogenous variation in property crimes Instruments used: –Number of pay phones per habitants –Drug trafficking apprehensions per habitants –Drug consumption apprehension per habitants –Others instruments used (updated version): Maternal mortality in 1984 Victims of car accidents per habitants

Instrument: drug trafficking and drug consumption Inclusion condition: does the drug market affect crime? –Robberies and thefts are means used by gangs to finance themselves; –Gangs need young poor people and guns to protect their “market”; –Addicted people could commit crimes to sustain their addiction.

Instrument: drug trafficking and drug consumption Exclusion condition: does not the drug market affect savings above and beyond demographics and income? –Most of the drug dealers are poor and young people that probably would not save if they were not linked to this activity –Most of the drug consumers are young people that probably would not save if they were not addicted

First Stage

Instrument: pay phones Inclusion condition: does the pay phone affect the perception of crime? –Pay phones: easier to report crime; –Disque Denúncia program, which encourages people to report potential and actual crimes; –One caveat: This instrument seems to alter the number of reported crimes, but not crimes de facto However, crime perception is also important to determine savings decision –Pay phones may capture the confidence on public services, that makes people more prone to report crimes to the police.

Instrument: pay phones (first stage)

2SLS regressions: second stage

Why do we believe that DrugCons100 is a better instrument than DrugTraf100? Some cities may have a disproportionate amount of documented trafficking inasmuch as they could be distribution centers Drug trafficking is a more infrequent occurrence, and produces more outliers

Other stuff on the paper Savings, when instrumented for by the number of banks per capita, decrease property crime, while has no effect on violent crime We check robustness by –Controlling for regional fixed effects –Changing the saving measure for residential capital per capita