Academic journal article Federal Reserve Bank of St. Louis Review

Comparing Manufacturing Export Growth across States: What Accounts for the Differences?

Academic journal article Federal Reserve Bank of St. Louis Review

Comparing Manufacturing Export Growth across States: What Accounts for the Differences?

Article excerpt

Until the reduction in manufacturing exports caused by the Asian crisis, U.S. manufacturing exports as a share of gross domestic product had trended upward since the mid-1980s. As shown in Figure 1, this share increased from 4.1 percent in 1986 to 7.3 percent in 1997, before decreasing to 7.0 percent in 1998. This feature of the internationalization of the U.S. economy has spread unevenly across regions and states. As shown in Table 1, from 1988 through 1998 the annual rate of change of manufacturing exports ranged from a low of -- 10.9 percent in Alaska to a high of 28.2 percent in New Mexico. [1] In this paper we examine the differences in the growth of manufacturing exports across states. Using a technique called shift-share analysis, we isolate the effects that account for the difference between a state's manufacturing export growth and U.S. manufacturing export growth between 1988 and 1998.

Applying the shift-share method generates a measure of each state's net relative change over the period. States in which manufacturing exports grew more (less) rapidly than the national average between 1988 and 1998 have a positive (negative) net relative change. In classic shift-share models a state's net relative change is separated into an industry mix effect and a competitive effect. The industry mix effect is the change due to differences in the initial industry makeup of the state relative to the nation. A positive (negative) industry mix effect indicates that a state's exports were relatively more concentrated in industries whose exports expanded faster (slower) than the overall national average. Meanwhile, the competitive effect in these models is the change in exports due to differences between the export growth of a state's industries and export growth at the national level, assuming the state's industry mix was the same as the nation's.

Recent work by Gazel and Schwer (1998) extended the classic shift-share model to incorporate the destination of a state's exports. This is potentially important because the geographic distribution of exports differs a great deal across states, a fact stressed by Erickson and Hayward (1991) and Cronovich and Gazel (1998) in general studies and by Coughlin and Pollard (2000) in a recent study of the impact of the Asian crisis on individual states. These studies highlight the importance of developments in foreign markets as a source of differential export performance across states. In the present context, a positive (negative) destination effect indicates that a state's manufacturing exports were initially relatively more concentrated in export markets that subsequently expanded faster (slower) than the overall national average.

In the following section we provide details on the data used in our study and the differences in export behavior across states. We also highlight the differences in the overall growth of manufacturing exports across states as well as the differences in the industrial compositions and geographic destinations of these exports. In the subsequent section we discuss shift-share analysis and the two models we calculate--a classic shift-share model and Gazel and Schwer's (1998) model. Next, we examine our results to assess the importance of the industry mix, competitive, and destination effects. A summary of the key findings completes the paper.


The data on state manufacturing exports used in this study were prepared by the Massachusetts Institute for Social and Economic Research (MISER) at the University of Massachusetts. These data are export shipments by state of origin of movement at the two-digit Standard Industrial Classification (SIC) industry level. The MISER export data are regarded as the best available data source for state exports; however, these data have some well-known weaknesses that have been discussed in Cronovich and Gazel (1999) and Coughlin and Mandelbaum (1991). One potentially important problem is that the identified export state may not be the state of manufacture, but rather the state of a broker (or wholesaler) or the state where a number of shipments were consolidated. …

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