RAJINDAR K. KOSHAL* AND MANJULIKA KOSHAL*

C R I M E S AND S O C I O - E C O N O M I C E N V I R O N M E N T S

AnSrRACr. The purpose of this note is to study the relationship between crimes and the socio-economic environment in the metropolitan areas of the United States. In this study we define total crime rate per 100,000 population as a linear function of (i) per capita personal income, (ii) the unemployment rate (iii) the migration rate, (iv) racial imbalance, (v) climate, and (vi) males as a percentage of total population. Our statistical results confirm the hypothesis that social and economic conditions cause crime.

One of the greatest social problems facing mankind is 'crime'. In the United States the overall crime rate per 100,000 population has increased from 1,116 in 1960 to 2,907 in 1971 - an increase of about 176% in 11 years. 1 Countless volumes have been written on crime and the criminal. The President's Commission on Law Enforcement notes: "crime is not a single, simple phenomenon that can be examined, analyzed and described in one piece. It occurs in every part of the country and in every stratum of society. Its practitioners and its victims are people of all ages, incomes and backgrounds." 9

Socio-economic environments are important forces for generating crimes, and this fact was even considered by sociologists during the last century, a However, the attention of the early contributors to criminal ecology was largely directed to the comparative study of the rural and the urban crime pattern. Marxist followers, like Filippo Turati, have also proposed that the economic factors are virtually the only causes of crimi- nality. 5 Recently in the United States, it has been recognized that crimes are dependent upon the overall socio-economic environment. The Presi- dent's Commission on Law Enforcement states:

In a sense, social and economic conditions "cause" crime. Crime flourishes, and always has flourished, in city slums, those neighborhoods where overcrowding, economic depredation, social disruption and racial discrimination are endemic. Crime flourishes in conditions of affluence when there is much desire for material goods and many op- portunities to acquire them illegally. 6

The purpose of this note is to study the relationship between crimes and the socio-economie environment in the metropolitan areas of the United

Social Indicators Research 2 (1975) 223-227. All Rights Reserved Copyright �9 1975 by D. Reid.el Publishing Company, Dordrecht-HoUand

224 R A J I N D A R K. KOSHAL AND M A N J U L I K A K O S H A L

States. The metropolitan areas are chosen as units of this study because these areas have the highest crime rates per unit of population.

In this study the total crime rate per 100,000 population, Cr, in a given metropolitan area is defined as a linear function of (1) Y - per capita personal income, (ii) U - the unemployment rate, (iii) M - the migra- tion rate, (iv) R - a measure of racial imbalance, (v) T - annual average temperature in Fahrenheit degrees and (vi) P - males as a percentage of total population. Specifically, the function is:

(1) C r f a + b Y + c U + d M + e R + f T + g P + E .

where a is a constant, b, c, d, e, f and g are marginal rates of crimes with respect to Y, U, M, R, T and P. E is a random error term.

In this study per capita personal income also measures per capita wealth. Per capita personal income is a superior measure of overall wealth since per capita income takes into account not only physical wealth but also human wealth. Ireland has pointed out that the explanation for the rising rate of crime is not a relaxation of punishment levels, or an in- creased willingness to commit crimes but, that victims have become less willing to defend themselves against criminal acts. Since wealth, in general, has diminishing marginal utility, then people are less willing to risk their lives to defend parcels of property as wealth increases. 7 It may be pointed out that this important fact has been ignored by Becker s and Stigler. 9

Furthermore, the gain from criminal activities would be directly related with the affluence of the region, other things being equal. This is due to the fact that an affluent region would have more expensive goods in personal possession to be stolen than a depressed region, x0 These hypotheses imply that OCr /O Y > O.

It has been recognized that the idleness of unemployment offers the time and often the opportunity to engage in unlawful conduct.ll,ls This implies that OCr/O U > O.

M is the migration rate between 1960 and 1970. Many studies have shown that crimes are associated with the disorganization and depriva- tion experienced by new immigrant or migrant groups as they strive to gain a foothold in the economic and social life of the city. is Furthermore, most of the immigrants and migrants are not familiar with the urban way of life; therefore, they are more than likely to become victims of criminals,

CRIME AND THE E N V I R O N M E N T 225

especially in terms of rape, burglary and larceny. We expect that aCr/OM > O. Racial imbalance is measured by the ratio of white population to non-

white population. This implies that R will have a lower value where the proportion of non-white people is high. Eberts and Schwirian's study 14 shows that crime rates are highest where the low income population is a distinct local minority. This may be due to the frustration caused by dis- crimination in housing, employment and education. We expect c~Cr/c3R <0.

Climate is an important variable for crimes. A region with a warm climate offers more opportunity to commit crimes than a colder region because first, more potential victims are in the streets for a longer time and second, criminals are able to work more efficiently in a warmer climate. This suggests that c~Cr/c3T>O. As regards the sex ratio, it is an established fact that males are more likely to commit crimes than females. The reasons for differences in crime rates among males and females are cultural, that is, the set of expectations regarding behavior that constitu- tes the guidelines by which males and females are reared and the criteria by which they are judged as 'acceptable '16. Accordingly, we expect that aCr/aP >0.

Data for this study pertains to 73 standard statistical metropolitan areas (SMSA) for 1970. le We test our model for (i) total crimes, (ii) property crimes, and (iii) crimes against persons: 7 Statistical results based or the ordinary least squares method are summarized in Table I. The values in parentheses below the coefficients are their t-values and R e is the coefficient of determination. F-ratio tests the overall fit.

In general, these results are impressive, since all the coefficients have signs according to the expectations. The relationships (2) and (3) explain more than 50% of the variations in total and property crimes respectively. However, relationship (4) explains only 41 per cent of the variations in crimes against persons. This needs further investigation, is

According to the statistical relationships (2), (3), and (4), socio- economic environments are important variables for explaining the crime rates in various SMSA's in the United States. Our results confirm the President's Commission on Law Enforcement and Administrative of Justice's hypothesis that social and economic conditions cause crime. It is interesting to note that unemployment is an important controllable (by fiscial and monetary policies) variable in determining crime rates. The recent experience in the United States also suggests that increasing

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CRIME AND THE ENVIRONMENT 227

unemployment may bc accompanied by the higher crime rates. 10 Ac- cordingly, on account of these externalities, unemployment has greater social loss than is usually considered, s0

NOTES

* The authors are indebted to Lowell Gallaway for his comments and suggestions. All calculations were made at the Ohio University Computer Center. 1 U.S. Department of Commerce, Statistical Abstract o f the United States, 1972, U.S. Government Printing Press, Washington D.C. 1972. s President's Commission on Law Enforcement and Administration of Justice, The Challenge of Crime in a Free Society, U.S. Government Printing Press, 1967, p. 1. s Schafer, Stephen, Theories in Criminology, Random House, New York, 1969, p. 227. 4 Ibid., p. 228. 5 Turati Filippo, II delitto e la questione sociale (Milan 1883), quoted in Schafer Stephen, op. cit., p. 265. e President's Commission on Law Enforcement and Administration of Justice, op. eit. p. 17. Italics are ours. v Ireland, Thoman, R. 'Optimal Enforcement of Laws: A Comment', J.P.E. (1972) 421. 8 Becker, Gary S. 'Crime and Punishment: An Economic Approach", J.P.E. 76 (1968) 169-217. g Stigler, George, 'Optional Enforcement of Laws', J.P.E. 78 (1970) 526--36. 10 President's Commission on Law Enforcement, op. cit., p. 29. 11 Report o f the President's Commission on Crime in the District o f Columbia, U.S. Government Printing Office, Washington D.C. (1966), p. 795. is Guttentag, Marcia, 'The Relationship of Unemployment to Crime and Delinquency', Journal o f Social Issues 14 (1972) 421. is Block, Herbert A. and Geis, Gilbert, Man, Crime and Society, Random House, New York, 1970, p. 154. 14 Eberts, Paul and Schwirian, Kent P., 'Metropolitan CHine Rates and Relative Depreciation', Criminological 5 (1968), 43-52. is Mulvihill, Donald, J., Tumin, M. M., and Curtis, L. A., Crimes o f Violence, voL 12, U.S. Government Printing Office, Washington D.C. (1969). le Complete set of data is available only for 73 SMSA's. iv Property crimes consist of burglary, larceny $50 and over, and auto theft. Crimes against persons consist of murder and non-negligent manslaughter, forcible rape, robbery and aggravated assult. 18 It must be noted that these two sub-categories are sum total of a number of hetero- geneons crimes. In two forthcoming papers - one dealing with property crimes and other with crimes against persons, the authors show that explanatory power of model (1) is higher when such functions are fitted to specific crime categories. For specific categories see note 17. 19 For example, total crime rate increased from 3,949 in 1969 to 4,116 in 1973 while unemployment rate during the same period increased from 3.5 to 4.9. It must be re- membered that this is only one of the several variables which may affect ~rhae rates in a society. s0 Production loss is usually considered as social loss of unemployment.