JSTOR is a not-for-profit service that helps scholars, researchers, and students discover, use, and build upon a wide range of content in a trusted digital archive. We use information technology and tools to increase productivity and facilitate new forms of scholarship. For more information about JSTOR, please contact support@jstor.org.. University of Wisconsin Press andThe Board of Regents of the University of Wisconsin System are collaborating with JSTOR to digitize, preserve and extend access to The Journal of Human Resources. ABSTRACTSeveral studies have shown that the unemployed in distressed regions of the U.S. have been reluctant to move to areas of greater employment opportunities. By establishing a negative correlation between weeks of job search and the probability of migration, this study is able to provide a partial explanation for the lack of a positive and statistically significant relationship between out-migration rates and the unemployment rate in the local labor market. It is our contention here that those regions that have experienced long periods of high unemployment possess a long-term unemployed population that is less likely to undertake a geographic move.Migration studies focusing on the unemployed have not heretofore directly tested the relationship between the propensity to migrate and the time spent searching for work. It is our contention in this paper that among the unemployed, the length of time spent searching is an important determinant of the decision to migrate. By establishing a negative relationship between the length of job search and the probability of migration, this study provides an explanation for the computation of an unexpected negative (Greenwood [4]) or statistically insignificant (Fabricant [2], Lowry [11]) relationship between out-migration and local unemployment rates in the estimated migration equation.Few researchers have provided meaningful explanations for this ap-

No abstract

No abstract

The ability to forecast freight to support transportation infrastructure decisions is limited by data availability at a level of detail meaningful to the transportation planner. The Freight Analysis Framework Version 2 is a national, comprehensive public freight database. The difficulty that transportation planners encounter when using this data is due to extensive aggregation. In this paper, the authors develop a methodology for creating freight analysis zones (FAZs) at a sub-state level by partitioning a state into meaningful zones that support freight transportation planning and analysis. The authors concl

Abstract