Predicting Gross State Product Growth with the Chicago Fed's Midwest Economy Index

By Brave, Scott; Wang, Norman | Chicago Fed Letter, December 2011 | Go to article overview

Predicting Gross State Product Growth with the Chicago Fed's Midwest Economy Index


Brave, Scott, Wang, Norman, Chicago Fed Letter


This article explains how the Federal Reserve Bank of Chicago's Midwest Economy Index (MEI) can be used to produce quarterly estimates of the annual gross state product (GSP) growth of each state in the Seventh Federal Reserve District.

The U.S. Bureau of Economic Analysis (BEA) produces measures of gross state product, which are the state-level counterparts to the nation's gross domestic product (GDP) . Unlike the GDP data that are updated on a quarterly basis by the BEA, the GSP data are available only annually.1 In this Chicago Fed Letter, we describe a framework for producing quarterly estimates of GSP growth for the five states of the Seventh Federal Reserve District. To do so, we exploit the historical correlation between GSP growth in each of the five states and the Chicago Fed's Midwest Economy Index.

The MEI and GSP

Earlier this year, the Chicago Fed unveiled a new index measuring growth in nonfarm business activity in the five Seventh District states called the Midwest Economy Index.2 The index is a weighted average of 134 state and regional indicators of four broad sectors of the Midwest economy: 1) manufacturing, 2) construction and mining, 3) services, and 4) consumer spending. The weight each indicator receives is constructed such that greater influence in the index is given to those indicators that have historically been better able to explain broader fluctuations in the Midwest economy.

MEI values correspond to deviations of growth in Midwest economic activity around its historical trend, or long-run average. Values above zero indicate growth above its historical trend, and values below zero indicate growth below trend. Over long periods, growth in Midwest economic activity around its trend has tended to track similar deviations in national economic activity. However, over shorter periods this has not always been the case, particularly around the beginnings and ends of recessions. To highlight such differences, we construct two separate index values: an absolute value and a relative value.

The MEI (absolute value) captures both national and regional factors driving Midwest economic growth, while the relative MEI (relative value) provides a picture of the Midwest's economic conditions relative to the nation's. A positive value of the relative MEI indicates that regional growth is further above its trend than would typically be suggested based on the current deviation of national growth from its trend, while a negative value indicates the opposite.

The MEI and GSP measure growth in economic activity in complementary fashions, although their methods of accounting for it differ. Consider figure 1, which plots the MEI against the annual growth rate of gross state product for Wisconsin. The correlation coefficient between the two, at 0.87, is quite high. Among the Seventh District states, Wisconsin has the highest correlation coefficient between the MEI and GSP, although it is followed closely by Indiana, at 0.86; Illinois, at 0.84; and Michigan, at 0.83. In contrast, for Iowa the correlation coefficient drops to 0.60.

That said, the MEI and relative MEI provide a picture of the Seventh District's state economies that is timelier than the BEA's GSP data. In what follows, we show that the two indexes can be used to form real-time inferences on GSP growth for each Seventh District state; and in doing so, we gain a sense of how important regional growth factors summarized in the MEI and relative MEI have historically been in explaining economic growth for the Seventh District states relative to national and state-specific growth factors.

Predicting GSP growth

We construct a statistical model - more specifically, we estimate a simple linear regression - to explain the annual growth in GSP for each Seventh District state.3 The model succinctly summarizes the historical relationships between national, regional, and state-specific factors driving each Seventh District state's GSP growth since 1979.

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