Allocation of Time and Hateful Behavior: A Theoretical and Positive Analysis Of Hate and Hate Crimes - Statistical Data Included

American Journal of Economics and Sociology, The,  Oct, 1999  by Marshall H. Medoff

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IV

Empirical Results

EQUATION (7) WAS ESTIMATED USING ORDINARY LEAST SQUARES and the empirical results appear in Table 1, Column 1. [10] As hypothesized, a higher market wage rate has a statistically significantly negative impact on hateful activity. Hateful activity increases with unemployment, but at a decreasing rate. The lower value of time of the 15 to 19 year old age group results in a higher incidence of hateful crimes.

Law enforcement is found to have a statistically insignificant impact on deterring hateful consumption. The religion variable was negative but not statistically significantly different from zero. The result is consistent with the contention by some sociologists that religion plays no role in mitigating deviant behavior (Hirschi and Stark, 1969). [11]

The liberal ideology variable is statistically significantly positive suggesting that hate crimes are more likely to be committed in states where the population is liberally inclined. While this finding may seem perverse, it is consistent with the interpretation that liberal states, because they have more tolerant attitudes, have a lower search cost of identifying potential victims and hence a lower marginal cost of producing a unit of hateful activity.

The education variable is statistically significantly positive. This does not mean that a greater degree of knowledge is positively associated with greater intolerance. Rather, it suggests that hateful activity occurs proportionately more in states with a better educated populace (who may tend to have more tolerant [liberall attitudes).

It is important to point out the meaning of the phrase "statistically significant" used above. It means that under the null hypothesis the probability of obtaining a Student's t value is <5 percent. Hence the conclusion must be either that the sample is extremely improbable or else, as in this paper, the null hypothesis that the partial regression coefficient [b.sub.i] is not significantly different from zero is rejected. However, as noted by McCloskey and Ziliak (1996), the overwhelming majority of economic papers fail to distinguish between statistical significance and economic (or numerical) significance. An estimated coefficient may be statistically significant but economically insignificant. As McCloskey and Ziiak point out, in order to discern the economic impact of a coefficient it would be more appropriate to report the coefficient in terms of a confidence interval, in elasticity form, or in some other interpretable form. In this paper the interest is not in the economic significance of the coefficie nt, but rather in the implications of theory--that is, rejecting the null hypothesis of no association ([b.sub.i] = 0) between an independent variable and the dependent variable.

V

Alternative Theories

SOME PSYCHOLOGISTS HAVE ARGUED that hatred is more apt to be prevalent in urban areas which have more social disorganization (Newman, 1979). In terms of equation (6), a change in the environmental variable urbanization would result in more hateful activity if urbanization lowered the market value of time (dw/de [less than] 0) and/or lowered the amount of time or goods required to produce hateful activity ([d.sup.2][t.sub.h]/dEdH [less than] 0, [d.sup.2][x.sub.h]/dEdH [less than] 0) possibly by reducing the search costs of finding a potential victim or by reducing the probability of criminal apprehension. This hypothesis is tested by adding the variable, the percentage of state i's population living in an urban area, to equation (7). The empirical results appear in Table 1, Column 2. The urbanization variable is negative (contrary to psychologists contention), but not statistically significantly different from zero. Hateful activity is not found to be more prevalent in urban areas.