The first six chapters consider the structure of the economy and adopt an essentially static point of view. These chapters analyse successively : 1. The last three chapters adopt an essentially dynamic viewpoint and analyse various aspects of growth. Chapter 7 successively considers the development of mechanization, the contradiction between socialization of production and concentration of capital, the expansion of waged labour and market production, the human and ecological costs of growth.
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Based on Beckers theoretical model, the present paper estimates econometricallythe determinants of the crime rate in Argentina for the period. Likeprevious empirical applications for Argentina, a significant deterrence effectwas found.
However unlike them we find a strong socio-economic effect on thecrime rate. The unemployment rate and the income inequality indicator werefound to have a positive and significant effects on the crime rate.
El presente documento estima economtricamente los determinantes de la tasade criminalidad en Argentina para el perodo basndose en el modeloterico de Becker. Como otras investigaciones empricas precedentes para esepas, se encontr un efecto significativamente disuasivo. Sin embargo, adiferencia de los estudios previos se identificaron tambin indicios de un fuerteefecto socioeconmico en la tasa de criminalidad.
As, un incremento en lastasas de desempleo y en los indicadores de desigualdad del ingreso tendra unimpacto positivo en la tasa de criminalidad. We wish to thank Ana Mara Claramunt, Leonardo Gasparini and Osvaldo Larraagafor constructing comments and suggestions and Santiago Avellaneda for able researchassistance.
The usual disclaimer applies. Universidad Nacional de Tucumn, P. Box Tucumn ArgentinaE-mail: acerro herrera. The affluence of the rich excites the indignationof the poor, who are often both driven by want,and prompted by envy, to invade his possessions.
It is only under the shelter of the civil magistratethat the owner of that valuable property, whichis acquired by the labour of many years, or per-haps of many successive generations, can sleepa single night in security. Following the lead of Gary Becker a large literature on the econom-ics of crime has been developed to test the theoretical implications of his model. This literature typically estimates the supply of offenses, where crime per 10,inhabitants is related to the probability of arrest, the probability of conviction,the severity of punishment, the expected income from the criminal activity, thereturns from alternative legal activities, and other socio-economic factors.
The hypothesis that unemployment, income distribution and other variablescharacterizing the economic environment of the region or province affects crimecan be traced out to Adam Smith, as shown by the introductory paragraph, andhave been empirically tested widely. For example, Wong in a time seriesstudy, explains criminal behavior in England and Wales for using socio-economic variables, like the unemployment rate.
In a cross- section analysis for, Zhang also finds that income inequality, measured by the GiniIndex, and the unemployment rate positively affects the crime rate.
Ehrlich in a panel data study for U. Unlike studies with U. Kessler and Molinari report that only a measure of education of the population is significantat usual confidence levels. Likewise, Chambouleyron and Willington find that only cars per capita a proxy for GDP per capita is statistically signifi-cant but the inequality indicator is weakly significant and the unemploymentrate is not significant at all. Interestingly, during the 90s Argentina experienceda huge increase in the unemployment rate particularly since and a wors-ening in income distribution.
Many academics, politicians and opinion moldershave related the worsening in unemployment and income distribution figures tothe hike in crime rate, however, as mentioned earlier, only weak evidence hasbeen provided to support that view. Is Argentina so different from the rest of the world? To answer this questionthe present paper, based on Beckers theoretical model, estimates a supply foroffenses with panel data that spans over the decade and all 24Argentinean provinces.
The rest of the paper is organized as follows. Section 2 characterizes crimi-nal activity in Argentina. Section 3 is concerned with theoretical analysis andempirical evidence. Section 4 presents the theoretical model and the data usedin the estimations. Section 5 shows the results of empirical analysis whereasSection VI is reserved for the conclusions. Recent opinion surveys show that most people view unemployment andcrime to be the most important problems in Argentina. According to officialstatistics, the crime rate, calculated on the basis of reported crimes, has grownfrom crimes per 10, inhabitants in , to in , which gives anaverage annual rate of 6.
As shown in figure I, following adecrease in the crime rate has been growing strongly year after year. Inter-estingly, reported criminal activity exhibits an important dispersion among prov-inces the standard deviation of the crime rate relative to the mean was 0. For example, in the crime ranking per province was headed by the FederalDistrict Capital Federal and the province of Mendoza with and crimesper 10, inhabitants respectively, while the provinces of Jujuy, Misiones,Formosa, Entre Ros, San Luis, La Rioja and Tucumn showed crime ratesbelow The most populated district of Argentina, Buenos Aires, had crimes per 10, inhabitants for the same year.
As reported in Table 1, the districts with the fastest crime rate expansionduring the 90s were Capital Federal with an average annual growth rate of The provinces with the lowest annual growthrate for the same period were Santiago del Estero 1.
One of the characteristics of the crime rate in Argentina is that all the prov-inces had similar pattern relative to the type of crime: the most common crimesin each province were those against property robbery, burglary, larceny. Capital Federal Another important feature, related to police efficiency in deterring the crimi-nal activity, is that on average for the period , only 40 out of crimesreported had identified suspects. It is worth remarking that on average, the relationship betweenreported crimes with identified subjects and those with unidentified subjectspractically experimented no changes throughout the decade.
However, the dis-persion among provinces was significant, as mentioned above. Still another key variable for analyzing criminal activity in Argentina is thebehavior of the probability of conviction defined as the percentage of condem-natory sentences relative to the number of arrests , which has been decliningthroughout the 90s.
During the early 90s Argentina carried out deep structural reforms that re-sulted in economic stabilization inflation dropped from hyperinflation to single-digit rates and vigorous growth,. Log in Get Started. See Full Reader. Download for free Report this document. Embed Size px x x x x Resumen El presente documento estima economtricamente los determinantes de la tasade criminalidad en Argentina para el perodo basndose en el modeloterico de Becker.
Keywords: Criminal rate, Argentina. Inequality and unemployment During the early 90s Argentina carried out deep structural reforms that re-sulted in economic stabilization inflation dropped from hyperinflation to single-digit rates and vigorous growth,.
DETERMINANTS OF THE CRIME RATE IN of the crime rate / Estudios de Economía. Vol. 27 - Nº 2,...
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