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New Evidence on Balanced Growth, Stochastic Trends, and Economic Fluctuations

  • Whelan, Karl

The one-sector Solow-Ramsey growth model informs how most modern researchers characterize macroeconomic trends and cycles, and evidence supporting the model's balanced growth predictions is often cited. This paper shows, however, that the inclusion of recent data leads to the balanced growth predictions being rejected. An alternative balanced growth hypothesis---that the ratio of nominal consumption to nominal investment is stationary---is put forward, and new measures of the stochastic trends and cycles in aggregate US data are derived based on this hypothesis. The contrasting behavior of real and nominal ratios is consistent with a two-sector model of economic growth, with separate production technologies for consumption and investment and two stochastic trends underlying the long-run behavior of all macroeconomic series. Empirical estimates of these stochastic trends are presented based on a structural VAR and the role played in the business cycle by shocks to these trends is discussed.

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Paper provided by University Library of Munich, Germany in its series MPRA Paper with number 5910.

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Date of creation: Jun 2006
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Handle: RePEc:pra:mprapa:5910
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  1. Jordi Gali, 1999. "Technology, Employment, and the Business Cycle: Do Technology Shocks Explain Aggregate Fluctuations?," American Economic Review, American Economic Association, vol. 89(1), pages 249-271, March.
  2. Chang-Jin Kim & Jeremy Piger, 2000. "Common Stochastic Trends, Common Cycles, and Asymmetry in Economic Fluctuations," Econometric Society World Congress 2000 Contributed Papers 1465, Econometric Society.
  3. Lawrence J. Christiano & Martin Eichenbaum & Robert Vigfusson, 2003. "What Happens After a Technology Shock?," NBER Working Papers 9819, National Bureau of Economic Research, Inc.
  4. Robert G. King & Charles I. Plosser & James H. Stock & Mark W. Watson, 1991. "Stochastic trends and economic fluctuations," Working Paper Series, Macroeconomic Issues 91-4, Federal Reserve Bank of Chicago.
  5. Gordon, Robert J., 1990. "The Measurement of Durable Goods Prices," National Bureau of Economic Research Books, University of Chicago Press, edition 1, number 9780226304557.
  6. L. Slifman & C. Corrado, 1996. "Decomposition of productivity and unit costs," Staff Studies 1, Board of Governors of the Federal Reserve System (U.S.).
  7. Johansen, Soren, 1995. "Likelihood-Based Inference in Cointegrated Vector Autoregressive Models," OUP Catalogue, Oxford University Press, number 9780198774501.
  8. Serena Ng & Pierre Perron, 1997. "Lag Length Selection and the Construction of Unit Root Tests with Good Size and Power," Boston College Working Papers in Economics 369, Boston College Department of Economics, revised 01 Sep 2000.
  9. Charles I. Jones, 2004. "The Shape of Production Function and the Direction of Technical Change," NBER Working Papers 10457, National Bureau of Economic Research, Inc.
  10. Jonas D. M. Fisher, 2006. "The Dynamic Effects of Neutral and Investment-Specific Technology Shocks," Journal of Political Economy, University of Chicago Press, vol. 114(3), pages 413-451, June.
  11. Greenwood, J. & Hercowitz, Z. & Krusell, P., 1995. "Long-Run Implications of Investment-Specific Technological Change," UWO Department of Economics Working Papers 9510, University of Western Ontario, Department of Economics.
  12. Michael J. Boskin, 1998. "Consumer Prices, the Consumer Price Index, and the Cost of Living," Journal of Economic Perspectives, American Economic Association, vol. 12(1), pages 3-26, Winter.
  13. Graham Elliott & Thomas J. Rothenberg & James H. Stock, 1992. "Efficient Tests for an Autoregressive Unit Root," NBER Technical Working Papers 0130, National Bureau of Economic Research, Inc.
  14. Greenwood, Jeremy & Hercowitz, Zvi & Krusell, Per, 2000. "The role of investment-specific technological change in the business cycle," European Economic Review, Elsevier, vol. 44(1), pages 91-115, January.
  15. Cochrane, John H, 1994. "Permanent and Transitory Components of GNP and Stock Prices," The Quarterly Journal of Economics, MIT Press, vol. 109(1), pages 241-65, February.
  16. Karl Whelan, 2001. "A two-sector approach to modeling U.S. NIPA data," Finance and Economics Discussion Series 2001-04, Board of Governors of the Federal Reserve System (U.S.).
  17. Fama, Eugene F., 1992. "Transitory variation in investment and output," Journal of Monetary Economics, Elsevier, vol. 30(3), pages 467-480, December.
  18. Rotemberg, Julio J & Woodford, Michael, 1996. "Real-Business-Cycle Models and the Forecastable Movements in Output, Hours, and Consumption," American Economic Review, American Economic Association, vol. 86(1), pages 71-89, March.
  19. Whelan, Karl, 2002. "A Guide to U.S. Chain Aggregated NIPA Data," Review of Income and Wealth, International Association for Research in Income and Wealth, vol. 48(2), pages 217-33, June.
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