
Economic Development and Public Finance Working Paper Series
REP 06-01, The Role of Geographic Proximity And Industrial Structure In
Metropolitan Area Business Cycles, by Michael Hollar, Anthony Pennington-Cross and Anthony Yezer.
Measurement and prediction of aggregate economic fluctuations at the region, state, and metropolitan area level is a major challenge. As data quality and analytical techniques have improved, the analysis of coincident economic cycle indicators (CEI) has progressed from national to regional to state levels. This paper continues the trend of geographic disaggregation by
constructing and analyzing CEI at the MSA level. The theoretical advantage of MSA level indexes is that they reflect labor market areas.
Given lack of quarterly economic time series at the MSA level, we construct a new variable, the
EPI (export price index). The EPI is an index number constructed to measure changes in the prices of
goods produced by major industries located in metropolitan areas. Using non-agricultural employment
and the EPI as MSA-specific variables, we are able to estimate following a Stock/Watson type single
factor models. We find that, for larger states, with multiple MSAs, there is substantial variation in the
amplitude and timing of cycles across MSAs. Further tests group MSAs within states by applying cluster
analysis to the state series for the MSAs within a state. The groupings are interesting for two reasons.
First, they confirm the differences observed within states. Secondly, and perhaps most important, the
groupings of cyclically similar MSAs are not always based on geographic proximity as might be
expected. It appears that industrial similarity of the MSA economies is also important for cyclical
performance.
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