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Alchool and Misbehavior: Evidence from Sales Restrictions in the São Paulo Metropolitan Area João De Mello (PUC-RIO) and Alexandre Schneider (EAESP- FGV.

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Presentation on theme: "Alchool and Misbehavior: Evidence from Sales Restrictions in the São Paulo Metropolitan Area João De Mello (PUC-RIO) and Alexandre Schneider (EAESP- FGV."— Presentation transcript:

1 Alchool and Misbehavior: Evidence from Sales Restrictions in the São Paulo Metropolitan Area João De Mello (PUC-RIO) and Alexandre Schneider (EAESP- FGV and São Paulo Mayorship)

2 Research Question Is there evidence that restricting alcohol sales in bars has an impact on violent crime?

3 Is it relevant for policy? Several Latin-American cities have adopted similar restrictions –Bogotá 1994 is the most prominent example –Diadema often cited as successful crime fight The Economist, 10/20/2005 Several historical examples of similar legislation –American Prohibition

4 Is it relevant for policy? On the other hand... – Sales restrictions also entail welfare losses Therefore: –Is there an effect on violent crime? –Is it first-order? –Are there less intrusive means of offsetting (alleged) adverse effects of alcohol consumption?

5 Is it relevant for policy? Mr. Churchill on the later point: “In our country, just as in ours, an enormous problem of misery, poverty, and crime... resulted from alcohol. We, however, used different weapons. We used the weapons of regulation and taxation," Winston Churchill, referring to the prohibition, on a US tour speech in 1931

6 Overview The Law The Chronology of Events Data The Empirical Strategy Results Conclusion

7 The Law Diadema, for example:

8 The Law Other cities that adopted have very similar laws It varies slightly on –Specific times –Specific days of the week

9 The Chronology of Events Mês/Ano da Aprovação da Lei Seca - Municípios da Região Metropolitana de São Paulo Município Data da Lei BarueriMar-01 JandiraAug-01 ItapeviJan-02 DiademaMar-02 JuquitibaMaio-02 São Lourenço da SerraJun-02 SuzanoJun-02 ItapecericaJul-02 MauáJul-02 PoáAgo-02 Ferraz de VasconcelosSet-02 EmbuDez-02 OsascoDez-02 Embu – GuaçuAbr-03 Vargem Grande PaulistaDec-03 São CaetanoJul-04 Kahn, Túlio e Zanetic, André. Municípios na Segurança Pública – Em Estudos Criminológicos 4, Julho 2005. There is variation in adoption timing 16 cities out of 39 in the SPMA

10 The Chronology Cities that have not adopted –Franco da Rocha, Guararema, Guarulhos, Biritiba Mirim, São Bernardo do Campo, Santa Isabel, Arujá, Itaquaquecetuba, Mairiporã, Mogi da Cruzes, Rio Grande da Serra, São Paulo, Pirapora do Bom Jesus, Ribeirão Pires, Taboão da Serra, Santana do Parnaíba, Santo André, Salesópolis, Cotia, Francisco Morato, Cajamar, Caieiras, Carapicuíba –23 out of 39 cities in the SPMA

11 Data City level data on Homicides from Jan-1999 to Dec 2004 –Secretaria de Segurança Pública do Estado de São Paulo City population –IBGE Presence of Alcohol Law (and timing), Municipal Justice Secretary, Municipal Policing –Kahn and Zanetic [2005]

12 The Empirical Strategy Difference-in-Difference Model –Compare the evolution of homicides, before and after the adoption, between cities that adopted and cities that have not adopted the Law –Cities that have not adopted the law are the “control group” It decreases significantly the possibility of capturing spurious effects due to –Time trends –Concurrent events

13 The Empirical Strategy i = City t = Month Homicides per thousand inhabitants Dummy for the cities that adopted the law Dummy for the cities that adopted the law and for the periods after adoption City specific Dummy Month specific Dummy Municipal police and Municipal Justice Secretary

14 The Empirical Strategy The Hypothesis: γ 2 < 0 if the law has an effect on homicides

15 The Empirical Strategy Our model: Traditional ? No uniform treatment period Monthly dummies do the job

16 The Empirical Strategy Model for the Variance –Huge heterogeneity in city-size –Homicide is not such a common occurrence –Observations from small cities much noisier than large cities –We weight the data to “turn the model heteroskedastic”

17 The Empirical Strategy: Caveats Unobserved heterogeneity between control (non-adoption) and treatment (adoption) groups Endogeneity of adoption Spillover effects

18 Caveats: Unobserved Heterogeneity Police reaction to increases in crime –Adopting cities adopt in high crime periods. –Policing also react to high crime periods Why doesn’t it hurt us too bad? –Decision level: state government –Difference in the timing of reaction –Rigidity of allocation of police force –Size of police force does not respond to crime: By law, city-level police force is determined by population Any major changes have implies changes in the law

19 Caveats: Endogeneity of Adoption We want to estimate: But LawCrime Law

20 Caveats: Endogeneity of Adoption Sign of the OLS bias: Hard to determine –Crime before affects adoption –Adoption affects crime after –Sign of bias would depend on the dynamics of homicide

21 Caveats: Endogeneity of Adoption The scenario that would hurt us: –Cities adopt in periods of historically high homicide –Homicide is a mean-reversing period

22 Caveats: Endogeneity of Adoption Does homicide look mean-reversing?

23 Caveats Law induces more drinking in neighboring cities –Solution: compare only far away cities

24 Results Persistence in homicide

25 Results Control group: similar size and not contiguous to Diadema

26 Results Economic significance and contrafactuals –Is it first-order? 0.585 (all treated) = 77% of a standard deviation of homicides If São Paulo had adopted (Back-of- envelope calculations based on estimate): –0.585x100x12=702 annual homicides

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