Retail Vacancy Rates: The Influence of National and Local Economic Conditions
Benjamin, John D., Jud, G. Donald, Winkler, Daniel T., Journal of Real Estate Portfolio Management
Executive Summary. This study examines the extent to which local retail vacancy rates are influenced by vacancy rates in surrounding communities versus the overall national vacancy rate in the retail sector. Consistent with prior research, our simultaneous spatial autoregressive analyses of pooled retail market vacancy rates suggests that there is considerable spatial correlation in vacancy rates among neighboring metropolitan areas. There is also evidence of substantial temporal correlation in local vacancy rates. While spatial correlation dominates the national vacancy rate in explaining variation in the level of vacancy rates, changes in the national vacancy rate explain a statistically significant portion of the variation in the changes in local vacancy rates. The nature and extent to which changes in national rates of fect local rates is found to differ markedly across MSAs.
It is often said that "all real estate markets are local." But how strongly do national market conditions influence the performance of local property markets? This question is important to lenders, planners, developers, real estate investment trust portfolio managers and others who make or analyze real estate investment and portfolio decisions. Research by Hanink (1996) examines this question using office market data, finding that regional market conditions have a much stronger influence on local office markets than do conditions in the overall national market. Eppli, Shilling and Vandell (1996) provide similar findings. They report that very little of the variation in retail property returns are explained by contemporaneous macroeconomic events.
This study examines how local vacancy rates in the retail market are influenced by national market conditions. Our data track the retail real estate sector in forty-six metropolitan markets from 1981 through the first quarter of 1996. The next sections discuss the theoretical background, the pooled retail data, the empirical methodology and the empirical results. The final section is the conclusion.
Retail markets traditionally have been considered to be primarily local in nature because retail market sizes and business volumes are derived from local economic and demographic conditions (DiPasquale and Wheaton, 1996). However, national economic conditions may also affect the demand for products produced by export-based industries located in a local area and thereby may affect the level of employment, income and local-market retail demand. Further, national credit market conditions may influence the cost and availability of capital and credit in a local area and thereby may influence the pace of new retail construction.
Because real estate markets (including retail) have a strong local orientation, they do not move in perfect accord with aggregate national market conditions. Regional diversification has been shown to reduce the level of unsystematic risk in real estate portfolios (for example, Hartzell, Shulman and Wurtzebach, 1987; Malizia and Simons, 1991; and Mueller, 1993).1 Research in this area has focused on the formulation of portfolio diversification strategies among geographic areas, property types and industrial sectors. Mueller (1993) tests a number of these strategies and concludes that diversifying along purely economic-base lines provides the best efficient frontier. Mueller's work suggests that the dominant employment base of an area drives local economic conditions and that real estate returns follow local market conditions. Nevertheless, national economic conditions may yet influence local markets (as Mueller acknowledges) through their effects on the levels of income and employment in the dominant economic-base industry and the ef fects of national credit-market conditions on the supply of local market space.
Hanink (1996) examines quarterly movements of the office market vacancy rates in thirty-one metropolitan markets using a mixed spatial autoregression analysis. …