Second Quarter 1996
Federal Reserve Bank of Dallas

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New Tools for Analyzing the Mexican Economy: Indexes of Coincident and Leading Economic Indicators
Keith R. Phillips, Lucinda Vargas, and Victor Zarnowitz

New composite indexes presented in this article could prove useful in analyzing and forecasting the Mexican economy. Keith Phillips, Lucinda Vargas, and Victor Zarnowitz present composite indexes of leading and coincident indexes for Mexico. In constructing the indexes, the economists use an approach similar to that developed by the National Bureau of Economic Research to create the composite indexes of U.S. economic activity. The authors classify peaks and troughs in the Mexican business cycle since 1980. Using these business cycle turning points, the authors determine which indicators consistently turned down prior to recessions and turned up prior to expansions. Eight of the best performing indicators are combined to create a composite index of leading economic indicators.

Forecasting M2 Growth: An Exploration In Real Time
Evan F. Koenig

Evan Koenig presents a model that has proved successful at reproducing the pattern of M2 growth over the first half of the decade of the 1990s. The model suggests that a large gap between long-term bond yields and M2 deposit rates contributed importantly to the slow money growth that persisted through the end of 1994. The increased availability of bond market mutual funds may also have played a role in the money growth slowdown. The model can be combined with real-time published forecasts of spending and interest rates to yield predictions of future changes in money growth. It has generally performed well in this regard. However, in 1995 a sharp flattening of the yield curve led to a more-pronounced-than-expected acceleration of M2 growth, calling the future forecasting performance of the model into question. Results for an M2 aggregate expanded to include household bond funds are similar.

The Interest Rate Sensitivity of Texas Industry
Lori L. Taylor and Mine K. Yucel

A key factor in forecasting a region's growth is anticipating how a region will respond to changes in national policy. One important way national policy affects a region is through real interest rates. Forecasting regional growth, therefore, requires good estimates of the interest rate sensitivity of regional industries. In this study, Lori Taylor and Mine Yucel use vector autoregression analysis to examine the relationship between changes in real short-term interest rates and changes in Texas industry employment. They find that while a few industries are moderately sensitive to interest rate movements, most Texas industries are insensitive to changes in real interest rates. Moreover, they find that Texas total nonagricultural employment is insensitive to changes in real interest rates. As such, their analysis suggests that real interest rate movements influence the composition of Texas employment rather than its level.