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Tracking the slowdown in long-run GDP growth

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  • Antolin-Diaz, Juan
  • Drechsel, Thomas
  • Petrella, Ivan
Abstract
Using a dynamic factor model that allows for changes in both the longrun growth rate of output and the volatility of business cycles, we document a significant decline in long-run output growth in the United States. Our evidence supports the view that most of this slowdown occurred prior to the Great Recession. We show how to use the model to decompose changes in long-run growth into its underlying drivers. At low frequencies, a decline in the growth rate of labor productivity appears to be behind the recent slowdown in GDP growth for both the US and other advanced economies. When applied to realtime data, the proposed model is capable of detecting shifts in long-run growth in a timely and reliable manner.

Suggested Citation

  • Antolin-Diaz, Juan & Drechsel, Thomas & Petrella, Ivan, 2016. "Tracking the slowdown in long-run GDP growth," LSE Research Online Documents on Economics 86243, London School of Economics and Political Science, LSE Library.
  • Handle: RePEc:ehl:lserod:86243
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    1. Perron, Pierre & Wada, Tatsuma, 2009. "Let's take a break: Trends and cycles in US real GDP," Journal of Monetary Economics, Elsevier, vol. 56(6), pages 749-765, September.
    2. N. Bloom, 2016. "Fluctuations in uncertainty," Voprosy Ekonomiki, NP Voprosy Ekonomiki, issue 4.
    3. Forni, Mario & Hallin, Marc & Lippi, Marco & Reichlin, Lucrezia, 2003. "Do financial variables help forecasting inflation and real activity in the euro area?," Journal of Monetary Economics, Elsevier, vol. 50(6), pages 1243-1255, September.
    4. Giannone, Domenico & Reichlin, Lucrezia & Small, David, 2008. "Nowcasting: The real-time informational content of macroeconomic data," Journal of Monetary Economics, Elsevier, vol. 55(4), pages 665-676, May.
    5. Robert J. Gordon, 2014. "A New Method of Estimating Potential Real GDP Growth: Implications for the Labor Market and the Debt/GDP Ratio," NBER Working Papers 20423, National Bureau of Economic Research, Inc.
    6. Jacquier, Eric & Polson, Nicholas G & Rossi, Peter E, 2002. "Bayesian Analysis of Stochastic Volatility Models," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(1), pages 69-87, January.
    7. Harvey, A. C. & Stock, James H., 1988. "Continuous time autoregressive models with common stochastic trends," Journal of Economic Dynamics and Control, Elsevier, vol. 12(2-3), pages 365-384.
    8. Orphanides, Athanasios, 2003. "The quest for prosperity without inflation," Journal of Monetary Economics, Elsevier, vol. 50(3), pages 633-663, April.
    9. Martin D. D. Evans, 2005. "Where Are We Now? Real-Time Estimates of the Macroeconomy," International Journal of Central Banking, International Journal of Central Banking, vol. 1(2), September.
    10. Fumio Hayashi & Edward C. Prescott, 2004. "The 1990s in Japan: a lost decade," Chapters, in: Paolo Onofri (ed.), The Economics of an Ageing Population, chapter 2, Edward Elgar Publishing.
    11. William Nordhaus, 2004. "Retrospective on the 1970s Productivity Slowdown," NBER Working Papers 10950, National Bureau of Economic Research, Inc.
    12. Bańbura, Marta & Giannone, Domenico & Modugno, Michele & Reichlin, Lucrezia, 2013. "Now-Casting and the Real-Time Data Flow," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 195-237, Elsevier.
    13. Ohanian, Lee E. & Raffo, Andrea, 2012. "Aggregate hours worked in OECD countries: New measurement and implications for business cycles," Journal of Monetary Economics, Elsevier, vol. 59(1), pages 40-56.
    14. John G. Fernald, 2015. "Productivity and Potential Output before, during, and after the Great Recession," NBER Macroeconomics Annual, University of Chicago Press, vol. 29(1), pages 1-51.
    15. James H. Stock & Mark W. Watson, 2012. "Disentangling the Channels of the 2007-09 Recession," Brookings Papers on Economic Activity, Economic Studies Program, The Brookings Institution, vol. 43(1 (Spring), pages 81-156.
    16. Jan J. J. Groen & Richard Paap & Francesco Ravazzolo, 2013. "Real-Time Inflation Forecasting in a Changing World," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 31(1), pages 29-44, January.
    17. Antonello D’Agostino & Domenico Giannone & Michele Lenza & Michele Modugno, 2016. "Nowcasting Business Cycles: A Bayesian Approach to Dynamic Heterogeneous Factor Models," Advances in Econometrics, in: Dynamic Factor Models, volume 35, pages 569-594, Emerald Group Publishing Limited.
    18. Giannone, Domenico & Reichlin, Lucrezia & Sala, Luca, 2006. "VARs, common factors and the empirical validation of equilibrium business cycle models," Journal of Econometrics, Elsevier, vol. 132(1), pages 257-279, May.
    19. Massimiliano Marcellino & Mario Porqueddu & Fabrizio Venditti, 2016. "Short-Term GDP Forecasting With a Mixed-Frequency Dynamic Factor Model With Stochastic Volatility," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 34(1), pages 118-127, January.
    20. Timothy Cogley & Thomas J. Sargent, 2005. "Drift and Volatilities: Monetary Policies and Outcomes in the Post WWII U.S," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 8(2), pages 262-302, April.
    21. Sangjoon Kim & Neil Shephard & Siddhartha Chib, 1998. "Stochastic Volatility: Likelihood Inference and Comparison with ARCH Models," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 65(3), pages 361-393.
    22. Goldin, Claudia, 2006. "The Quiet Revolution That Transformed Women’s Employment, Education, and Family," Scholarly Articles 2943933, Harvard University Department of Economics.
    23. Marco Del Negro & Christopher Otrok, 2008. "Dynamic factor models with time-varying parameters: measuring changes in international business cycles," Staff Reports 326, Federal Reserve Bank of New York.
    24. Reichlin, Lucrezia & Giannone, Domenico & Small, David, 2005. "Nowcasting GDP and Inflation: The Real Time Informational Content of Macroeconomic Data Releases," CEPR Discussion Papers 5178, C.E.P.R. Discussion Papers.
    25. Robert J. Gordon, 2010. "Okun's Law and Productivity Innovations," American Economic Review, American Economic Association, vol. 100(2), pages 11-15, May.
    26. John H. Cochrane, 1994. "Permanent and Transitory Components of GNP and Stock Prices," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 109(1), pages 241-265.
    27. Benati, Luca, 2007. "Drift and breaks in labor productivity," Journal of Economic Dynamics and Control, Elsevier, vol. 31(8), pages 2847-2877, August.
    28. Stock, James H. & Watson, Mark W., 1999. "Business cycle fluctuations in us macroeconomic time series," Handbook of Macroeconomics, in: J. B. Taylor & M. Woodford (ed.), Handbook of Macroeconomics, edition 1, volume 1, chapter 1, pages 3-64, Elsevier.
    29. Beveridge, Stephen & Nelson, Charles R., 1981. "A new approach to decomposition of economic time series into permanent and transitory components with particular attention to measurement of the `business cycle'," Journal of Monetary Economics, Elsevier, vol. 7(2), pages 151-174.
    30. Jushan Bai & Pierre Perron, 1998. "Estimating and Testing Linear Models with Multiple Structural Changes," Econometrica, Econometric Society, vol. 66(1), pages 47-78, January.
    31. James C. Morley & Charles R. Nelson & Eric Zivot, 2003. "Why Are the Beveridge-Nelson and Unobserved-Components Decompositions of GDP So Different?," The Review of Economics and Statistics, MIT Press, vol. 85(2), pages 235-243, May.
    32. João Paulo Pessoa & John Van Reenen, 2014. "The UK Productivity and Jobs Puzzle: Does the Answer Lie in Wage Flexibility?," Economic Journal, Royal Economic Society, vol. 0(576), pages 433-452, May.
    33. Robert J. Gordon, 2004. "Why was Europe Left at the Station When America's Productivity Locomotive Departed?," NBER Working Papers 10661, National Bureau of Economic Research, Inc.
    34. Forni, Mario & Giannone, Domenico & Lippi, Marco & Reichlin, Lucrezia, 2009. "Opening The Black Box: Structural Factor Models With Large Cross Sections," Econometric Theory, Cambridge University Press, vol. 25(5), pages 1319-1347, October.
    35. Whelan, Karl, 2003. "A Two-Sector Approach to Modeling U.S. NIPA Data," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 35(4), pages 627-656, August.
    36. Dave Reifschneider & William Wascher & David Wilcox, 2015. "Aggregate Supply in the United States: Recent Developments and Implications for the Conduct of Monetary Policy," IMF Economic Review, Palgrave Macmillan;International Monetary Fund, vol. 63(1), pages 71-109, May.
    37. James H. Stock & Mark W. Watson, 2003. "Has the Business Cycle Changed and Why?," NBER Chapters, in: NBER Macroeconomics Annual 2002, Volume 17, pages 159-230, National Bureau of Economic Research, Inc.
    38. Tilmann Gneiting & Roopesh Ranjan, 2011. "Comparing Density Forecasts Using Threshold- and Quantile-Weighted Scoring Rules," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 29(3), pages 411-422, July.
    39. Arabinda Basistha & Richard Startz, 2008. "Measuring the NAIRU with Reduced Uncertainty: A Multiple-Indicator Common-Cycle Approach," The Review of Economics and Statistics, MIT Press, vol. 90(4), pages 805-811, November.
    40. Peter K. Clark, 1987. "The Cyclical Component of U. S. Economic Activity," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 102(4), pages 797-814.
    41. Clark, Todd E. & McCracken, Michael W., 2012. "In-sample tests of predictive ability: A new approach," Journal of Econometrics, Elsevier, vol. 170(1), pages 1-14.
    42. Giorgio E. Primiceri, 2005. "Time Varying Structural Vector Autoregressions and Monetary Policy," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 72(3), pages 821-852.
    43. Alan J Auerbach, 2011. "Long-term fiscal sustainability in major economies," BIS Working Papers 361, Bank for International Settlements.
    44. Marta Bańbura & Michele Modugno, 2014. "Maximum Likelihood Estimation Of Factor Models On Datasets With Arbitrary Pattern Of Missing Data," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 29(1), pages 133-160, January.
    45. Joris de Wind & Luca Gambetti, 2014. "Reduced-rank time-varying vector autoregressions," CPB Discussion Paper 270.rdf, CPB Netherlands Bureau for Economic Policy Analysis.
    46. Stephen D. Oliner & Daniel E. Sichel, 2000. "The Resurgence of Growth in the Late 1990s: Is Information Technology the Story?," Journal of Economic Perspectives, American Economic Association, vol. 14(4), pages 3-22, Fall.
    47. Nelson, Charles R. & Plosser, Charles I., 1982. "Trends and random walks in macroeconmic time series : Some evidence and implications," Journal of Monetary Economics, Elsevier, vol. 10(2), pages 139-162.
    48. Matteo Luciani & Lorenzo Ricci, 2014. "Nowcasting Norway," International Journal of Central Banking, International Journal of Central Banking, vol. 10(4), pages 215-248, December.
    49. 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.
    50. Durbin, James & Koopman, Siem Jan, 2012. "Time Series Analysis by State Space Methods," OUP Catalogue, Oxford University Press, edition 2, number 9780199641178.
    51. Jushan Bai & Peng Wang, 2015. "Identification and Bayesian Estimation of Dynamic Factor Models," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 33(2), pages 221-240, April.
    52. Roberto S. Mariano & Yasutomo Murasawa, 2003. "A new coincident index of business cycles based on monthly and quarterly series," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 18(4), pages 427-443.
    53. María Dolores Gadea-Rivas & Ana Gómez-Loscos & Gabriel Pérez-Quirós, 2014. "The two greatest. Great recession vs. great moderation," Working Papers 1423, Banco de España.
    54. Boivin, Jean & Ng, Serena, 2006. "Are more data always better for factor analysis?," Journal of Econometrics, Elsevier, vol. 132(1), pages 169-194, May.
    55. James H. Stock & Mark W. Watson, 2003. "Has the business cycle changed?," Proceedings - Economic Policy Symposium - Jackson Hole, Federal Reserve Bank of Kansas City, pages 9-56.
    56. Diebold, Francis X & Mariano, Roberto S, 2002. "Comparing Predictive Accuracy," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(1), pages 134-144, January.
    57. Claudia Goldin, 2006. "The Quiet Revolution That Transformed Women's Employment, Education, and Family," American Economic Review, American Economic Association, vol. 96(2), pages 1-21, May.
    58. Lant Pritchett & Lawrence H. Summers, 2013. "Asia-phoria meet regression to the mean," Proceedings, Federal Reserve Bank of San Francisco, issue Nov, pages 1-35.
    59. Cogley, Timothy, 2005. "How fast can the new economy grow? A Bayesian analysis of the evolution of trend growth," Journal of Macroeconomics, Elsevier, vol. 27(2), pages 179-207, June.
    60. Margaret M. McConnell & Gabriel Perez-Quiros, 2000. "Output fluctuations in the United States: what has changed since the early 1980s?," Proceedings, Federal Reserve Bank of San Francisco, issue Mar.
    61. Pérez-Quirós, Gabriel & Camacho, Máximo & Alvarez, Rocio, 2012. "Finite sample performance of small versus large scale dynamic factor models," CEPR Discussion Papers 8867, C.E.P.R. Discussion Papers.
    62. Hansen, Bruce E., 1992. "Testing for parameter instability in linear models," Journal of Policy Modeling, Elsevier, vol. 14(4), pages 517-533, August.
    63. Domenico Giannone & Lucrezia Reichlin & David Small, 2008. "Nowcasting: the real time informational content of macroeconomic data releases," ULB Institutional Repository 2013/6409, ULB -- Universite Libre de Bruxelles.
    64. Joris de Wind & Luca Gambetti, 2014. "Reduced-rank time-varying vector autoregressions," CPB Discussion Paper 270, CPB Netherlands Bureau for Economic Policy Analysis.
    65. Edge, Rochelle M. & Laubach, Thomas & Williams, John C., 2007. "Learning and shifts in long-run productivity growth," Journal of Monetary Economics, Elsevier, vol. 54(8), pages 2421-2438, November.
    66. Luo, Sui & Startz, Richard, 2014. "Is it one break or ongoing permanent shocks that explains U.S. real GDP?," Journal of Monetary Economics, Elsevier, vol. 66(C), pages 155-163.
    67. Charles A. Fleischman & John M. Roberts, 2011. "From many series, one cycle: improved estimates of the business cycle from a multivariate unobserved components model," Finance and Economics Discussion Series 2011-46, Board of Governors of the Federal Reserve System (U.S.).
    68. Harvey, A C, 1985. "Trends and Cycles in Macroeconomic Time Series," Journal of Business & Economic Statistics, American Statistical Association, vol. 3(3), pages 216-227, June.
    69. Gneiting, Tilmann & Raftery, Adrian E., 2007. "Strictly Proper Scoring Rules, Prediction, and Estimation," Journal of the American Statistical Association, American Statistical Association, vol. 102, pages 359-378, March.
    70. John G. Fernald, 2012. "A quarterly, utilization-adjusted series on total factor productivity," Working Paper Series 2012-19, Federal Reserve Bank of San Francisco.
    71. Harvey, David & Leybourne, Stephen & Newbold, Paul, 1997. "Testing the equality of prediction mean squared errors," International Journal of Forecasting, Elsevier, vol. 13(2), pages 281-291, June.
    72. Gneiting, Tilmann & Ranjan, Roopesh, 2011. "Comparing Density Forecasts Using Threshold- and Quantile-Weighted Scoring Rules," Journal of Business & Economic Statistics, American Statistical Association, vol. 29(3), pages 411-422.
    73. Nigel Pain & Christine Lewis & Thai-Thanh Dang & Yosuke Jin & Pete Richardson, 2014. "OECD Forecasts During and After the Financial Crisis: A Post Mortem," OECD Economics Department Working Papers 1107, OECD Publishing.
    74. G. Elliott & C. Granger & A. Timmermann (ed.), 2013. "Handbook of Economic Forecasting," Handbook of Economic Forecasting, Elsevier, edition 1, volume 2, number 2.
    75. Robert J. Gordon, 2014. "The Demise of U.S. Economic Growth: Restatement, Rebuttal, and Reflections," NBER Working Papers 19895, National Bureau of Economic Research, Inc.
    76. Stock J.H. & Watson M.W., 2002. "Forecasting Using Principal Components From a Large Number of Predictors," Journal of the American Statistical Association, American Statistical Association, vol. 97, pages 1167-1179, December.
    77. James H. Stock & Mark W. Watson, 2012. "Disentangling the Channels of the 2007-09 Recession," Brookings Papers on Economic Activity, Economic Studies Program, The Brookings Institution, vol. 44(1 (Spring), pages 81-156.
    78. Chang-Jin Kim & Charles R. Nelson, 1999. "State-Space Models with Regime Switching: Classical and Gibbs-Sampling Approaches with Applications," MIT Press Books, The MIT Press, edition 1, volume 1, number 0262112388, April.
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    More about this item

    Keywords

    Long-run growth; Business cycles; Productivity; Dynamic factor models; Real-time data;
    All these keywords.

    JEL classification:

    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • E23 - Macroeconomics and Monetary Economics - - Consumption, Saving, Production, Employment, and Investment - - - Production
    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles
    • O47 - Economic Development, Innovation, Technological Change, and Growth - - Economic Growth and Aggregate Productivity - - - Empirical Studies of Economic Growth; Aggregate Productivity; Cross-Country Output Convergence

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