Abstract

Evaluating regional industrial structures remains an inexact process as traditional aggregation schemes often lump superficially similar but behaviorally distinct industries together. We use pairwise cointegration methods to apply econometric criteria to aggregate detailed industries into behaviorally similar sectors. Based on these aggregations, cointegration guides the proper specification of a regional system to analyze the export versus local nature of core sectors. These methodologies are applied to Denver metropolitan data to demonstrate their utility. The findings indicate previous aggregation schemes are statistically inferior to those generated by this paper’s approach.

Highlights

  • Sufficient data exists to pursue time-series analysis of regional economies at the same level of rigor as has been the norm in macroeconomics for several years

  • See Isserman (1980) for a survey of methods. This survey was part of a larger study performed by the Demographers Office as they attempted to understand the role of export industries in determining Colorado’s economic structure and activity

  • We develop a time series system of these eight sectors that can capture their interrelationships, evaluate their roles as export and local sectors

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Summary

INTRODUCTION

Sufficient data exists to pursue time-series analysis of regional economies at the same level of rigor as has been the norm in macroeconomics for several years. Other researchers have used standard one-digit SIC aggregates to estimate as many as eight sectors in a time series model. Brown, Coulson, and Engle (1992) examined monthly employment data from Philadelphia from 1975-1987 using location quotient estimates to aggregate industries into basic and non-basic groupings. Phillips (1991) and Johansen (1992) demonstrate theoretically that excluding important variables in cointegration analysis can lead to an incorrect number of vectors and biased estimates of coefficients These problems surfaced in the money demand literature when a number of researchers had difficulty estimating a stable money demand function.

AGGREGATION OF A REGIONAL SYSTEM
Determining the Basic and Non-Basic Sectors
Aggregating Regional Time Series Through Pairwise Cointegration Tests
General Approach
Aggregating Denver Industries
Specifying and Analyzing the Denver Economy
Speeds of Adjustment
Notes:
Comparing Alternative Aggregation Schemes and Specification Issues
Impulse Response Functions
Findings
CONCLUSIONS
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