Economic Restructuring, Moehr
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place actually experienced less out-migration and a greater reduction in the poverty rate
than was predicted from the spatial error model. On the other hand, Santa Clara,
California could be said to epitomize the technology and service sector driven new
economy. Table 3 shows that the heart of Silicon Valley experienced a slight increase in
the poverty rate, which was in direct contrast to the moderate decrease predicted in the
model. These brief examples are certainly not conclusive and they do not come with any
sort of statistical test of significance; however, they do shed light on the effects of
economic restructuring in different locations.
DISCUSSION
The purpose of this paper is to assess the effects of economic restructuring on net
migration and poverty in the U.S. during the 1990s. The use of a spatial model shows
that much of the error in the original structural model may arise from the violation of the
assumption that the economic change variables are geographically independent.
Correcting for the spatial heterogeneity allowed for better prediction of net migration
rates and changes in poverty rates; however, it was still not a perfect integration of
structural and spatial methodologies. Future research should continue to develop this
approach because this paper suggests that the socio-economic system can only be
understood in a spatial context.
Additionally, the models I have proposed suffer from many of the limitations
imposed by the types of social and economic data available. First, the use of net
migration rates as an indicator of the social outcomes of economic restructuring may be
too broad. Using data that measures out-migration and in-migration separately would be
preferable. Two counties with the same net migration rates but with drastically different
Convention