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In most empirical work, the investigator's understanding of the economic process under study is only minimally reflected in the econometric methodology. This paper suggests that in many cases, the construction of a small-scale simulation can "prepare" the data for regression in a manner which takes cognizance of the theory of the process. Regression is then used to scale the output of the simulation up to observed magnitudes of the variable to be predicted. The simulation has the function of exploring for the nature of the non-linearities and interactions and thus replaces the usual search for a form which maximizes R². The simulation may also be helpful where colinear data are a problem. An example is presented in which the effects of wages, unemployment rates, and labor turnover on poverty are studied through a "prepared" regression. [ABSTRACT FROM AUTHOR]

The article focuses on a procedural aspect of the war on poverty, namely the role of the office of economic opportunity as coordinator of the antipoverty war. While coordination is a procedural task, it has clear implications for the substance and impact of public policy. Coordination involves the common direction of policies or programs to eliminate conflicts and divergencies and to insure their focus on a common goal for its better attainment.

The article comments on anti-poverty policy. With respect to anti-poverty policy, two major positions have emerged-one emphasizing a structural approach, the other an aggregative approach. These positions are not mutually exclusive, their difference being a question of relative emphasis. Both hold that there is some link between the rate of economic growth and the rate at which poverty incidence is reduced. The essential point of departure between the two points of view lies with the strength of this linkage: the structural position holding that, although economic growth opens up possibilities to escape poverty, a substantial proportion of the poor are not able to exploit these opportunities and are thus left behind in a poverty backwash. In short, the crucial distinction between the two theses is disagreement over the effect of economic growth in reducing poverty incidence. The higher levels of poverty incidence among minority families indicates, of course, that family poverty is relatively more concentrated among these groups and is what one would expect to be likely.

The article focuses on the relationship of unemployment to crime and delinquency. It would appear that rises in juvenile crime go hand in hand with industrialization and economic affluence. In India, a country with a generally low delinquency rate, a sudden rise of delinquency in Orissa province coincided with the erection of a new steel plant and anew urban, industrial center in the area. Advocates of rapid industrialization stress the positive social effects of economic well being, pointing out that providing employment opportunities gives people the means of escaping from the antisocial consequences of poverty. In order to have a clear look at the relationship between employment and crime, one must discard the idea that a simple cause and effect relationship can be isolated. It is necessary to explore the exact nature and operation of the variables intervening between these two conditions. Initially, rates of adult crime and rates of juvenile crime must be separately examined since considerable evidence suggests that they are not positively correlated.