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A new monthly index of the Texas business cycle

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  • Keith R. Phillips

Abstract

The timing, length and severity of economic recessions and expansions in a state are important to businesses seeking to set up operations or expand in those areas. Given a limited amount of data at the state level and their sometimes inconsistent movements, it is not straight forward to define a state business cycle. In this article I attempt to measure the Texas business cycle using a technique developed by Stock and Watson (1989,1991) that statistically estimates the underlying comovement in broad indicators of the state?s economy. The new Texas Coincident Index (TCI) is constructed with the Texas unemployment rate, a quarterly Real Gross State Product measure due to Berger and Phillips (1995), and a nonfarm employment series that is benchmarked quarterly and is seasonally adjusted using the two-step approach described in Berger and Phillips (1993). Use of these components and the Kalman filter, which smoothes across variables as well as over time, results in an index which is much smoother and gives clearer signals of turning points than the old TCI produced by Phillips (1988). The new TCI exhibits cyclical patterns that are highly correlated with those of employment and RGSP, and matches well with recessions and expansions that were independently identified.

Suggested Citation

  • Keith R. Phillips, 2004. "A new monthly index of the Texas business cycle," Working Papers 0401, Federal Reserve Bank of Dallas.
    • Handle: RePEc:fip:feddwp:04-01
    Note: Published as: Phillips, Keith R. (2005), "A New Monthly Index of the Texas Business Cycle," Journal of Economic and Social Measurement 30 (4): 317-333.
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    References listed on IDEAS

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    1. Franklin D. Berger & Keith R. Phillips, 1993. "Reassessing Texas employment growth," Southwest Economy, Federal Reserve Bank of Dallas, issue Jul, pages 1-3.
    2. Chow, Gregory C & Lin, An-loh, 1971. "Best Linear Unbiased Interpolation, Distribution, and Extrapolation of Time Series by Related Series," The Review of Economics and Statistics, MIT Press, vol. 53(4), pages 372-375, November.
    3. James H. Stock & Mark W. Watson, 1989. "New Indexes of Coincident and Leading Economic Indicators," NBER Chapters, in: NBER Macroeconomics Annual 1989, Volume 4, pages 351-409, National Bureau of Economic Research, Inc.
    4. John Thompson & Mine K. Yücel, 2002. "Texas economy stalled by recession," Southwest Economy, Federal Reserve Bank of Dallas, issue Nov, pages 1-8.
    5. Keith R. Phillips, 1988. "New tools for analyzing the Texas economy: indexes of coincident and leading economic indicators," Economic and Financial Policy Review, Federal Reserve Bank of Dallas, issue Jul, pages 1-13.
    6. Keith R. Phillips & Lucinda Vargas & Victor Zarnowitz, 1996. "New tools for analyzing the Mexican economy: indexes of coincident and leading economic indicators," Economic and Financial Policy Review, Federal Reserve Bank of Dallas, issue Q II.
    7. Neftici, Salih N., 1982. "Optimal prediction of cyclical downturns," Journal of Economic Dynamics and Control, Elsevier, vol. 4(1), pages 225-241, November.
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    Cited by:

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    2. Shyh-Wei Chen, 2007. "Using Regional Cycles to Measure National Business Cycles in the U.S. with the Markov Switching Panel Model," Economics Bulletin, AccessEcon, vol. 3(46), pages 1-12.
    3. Albu, Lucian Liviu, 2008. "A Model to Estimate the Composite Index of Economic Activity in Romania – IEF-RO," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 5(2), pages 44-50, June.
    4. repec:ebl:ecbull:v:3:y:2007:i:46:p:1-12 is not listed on IDEAS
    5. Lucian-Liviu Albu & Vasile Dinu, 2009. "How Deep and How Long Could Be the Recession in Romania," The AMFITEATRU ECONOMIC journal, Academy of Economic Studies - Bucharest, Romania, vol. 11(Number Sp), pages 675-683, November.
    6. Francis W. Ahking, 2015. "Measuring U.S. Business Cycles: A Comparison of Two Methods and Two Indicators of Economic Activities (With Appendix A)," Working papers 2015-06, University of Connecticut, Department of Economics.
    7. Donatella Baiardi & Carluccio Bianchi, 2012. "Un Indicatore per la Lombardia e per le Province di Milano e Pavia (Nuova versione)," Quaderni di Dipartimento 158, University of Pavia, Department of Economics and Quantitative Methods.

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