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A nonlinear look at trend MFP growth and the business cycle: result from a hybrid Kalman/Markov switching model

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  • Mark W. French
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    Abstract

    The cycle in output and hours worked is not symmetric: it behaves differently around recessions than in expansions. Similarly, the trend in multifactor productivity (MFP) seems to pass through different regimes; there was an extended period of slow MFP growth from about 1973 through 1995, and faster growth thereafter. Typical linear models and linear filters such as the Kalman filter deal poorly with asymmetry and regime changes. This paper attempts to determine more accurately and quickly any shifts in trend MFP growth, using a nonlinear Kalman/Markov filter with a model of the unobserved components of output and hours. This hybrid model incorporates regime-switching in the business cycle and in the trend growth of MFP. Estimation results are promising. The hybrid model and associated filter appear to be faster than the basic Kalman filter in detecting turning points in the smoothed conditional mean estimate of trend MFP growth; in addition, the hybrid model avoids some of the Kalman filter's biases in reconstructing historical business cycles and the MFP trend.

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    Bibliographic Info

    Paper provided by Board of Governors of the Federal Reserve System (U.S.) in its series Finance and Economics Discussion Series with number 2005-12.

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    Date of creation: 2005
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    Handle: RePEc:fip:fedgfe:2005-12

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    Keywords: Business cycles ; Econometric models ; Nonlinear theories;

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    1. Kim, C-J & Nelson, C-R, 1997. "Friedman's Plucking Model of Business Fluctuations : Tests and Estimates of Permanent and Transitory Components," Working Papers 97-06, University of Washington, Department of Economics.
    2. Michael Dueker, 2004. "Non-Markovian Regime Switching with Endogenous States and Time-Varying State Strengths," Econometric Society 2004 Latin American Meetings 34, Econometric Society.
    3. Kahn, James A. & Rich, Robert W., 2007. "Tracking the new economy: Using growth theory to detect changes in trend productivity," Journal of Monetary Economics, Elsevier, vol. 54(6), pages 1670-1701, September.
    4. Neftci, Salih N, 1984. "Are Economic Time Series Asymmetric over the Business Cycle?," Journal of Political Economy, University of Chicago Press, vol. 92(2), pages 307-28, April.
    5. Chang-Jin Kim & Christian J. Murray, 2002. "Permanent and transitory components of recessions," Empirical Economics, Springer, vol. 27(2), pages 163-183.
    6. John M. Roberts, 2001. "Estimates of the productivity trend using time-varying parameter techniques," Finance and Economics Discussion Series 2001-08, Board of Governors of the Federal Reserve System (U.S.).
    7. Chang-Jin Kim & Charles R. Nelson, 1998. "Business Cycle Turning Points, A New Coincident Index, And Tests Of Duration Dependence Based On A Dynamic Factor Model With Regime Switching," The Review of Economics and Statistics, MIT Press, vol. 80(2), pages 188-201, May.
    8. Hamilton, James D, 1989. "A New Approach to the Economic Analysis of Nonstationary Time Series and the Business Cycle," Econometrica, Econometric Society, vol. 57(2), pages 357-84, March.
    9. James Morley & Jeremy M. Piger, 2005. "The importance of nonlinearity in reproducing business cycle features," Working Papers 2004-032, Federal Reserve Bank of St. Louis.
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