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Forecasting Aggregate Productivity using Information from Firm-Level Data

Author

Listed:
  • Eric J. Bartelsman

    (VU University Amsterdam)

  • Zoltan Wolf

    (VU University Amsterdam)

Abstract

Published in 'The Review of Economics and Statistics' , 2014, 96(4), 745-755. This paper contributes to the productivity literature by using results from firm-level productivity studies to improve forecasts of macro-level productivity growth. The paper employs current research methods on estimating firm-level productivity to build times-series components that capture the joint dynamics of the firm-level productivity and size distributions. The main question of the paper is to assess whether the micro-aggregated components of productivity---the so-called productivity decompositions---add useful information to improve the performance of macro-level productivity forecasts. The paper explores various specifications of decompositions and various forecasting experiments. The result from these horse-races is that micro-aggregated components improve simple aggregate total factor productivity forecasts. While the results are mixed for richer forecasting specifications, the paper shows, using Bayesian model averaging techniques (BMA), that the forecasts using micro-level information were always better than the macro alternative.

Suggested Citation

  • Eric J. Bartelsman & Zoltan Wolf, 2009. "Forecasting Aggregate Productivity using Information from Firm-Level Data," Tinbergen Institute Discussion Papers 09-043/3, Tinbergen Institute.
  • Handle: RePEc:tin:wpaper:20090043
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    References listed on IDEAS

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    1. Jaimovich, Nir & Floetotto, Max, 2008. "Firm dynamics, markup variations, and the business cycle," Journal of Monetary Economics, Elsevier, vol. 55(7), pages 1238-1252, October.
    2. Ravazzolo, F. & van Dijk, H.K. & Verbeek, M.J.C.M., 2007. "Predictive gains from forecast combinations using time-varying model weights," Econometric Institute Research Papers EI 2007-26, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    3. Olley, G Steven & Pakes, Ariel, 1996. "The Dynamics of Productivity in the Telecommunications Equipment Industry," Econometrica, Econometric Society, vol. 64(6), pages 1263-1297, November.
    4. Charles R. Hulten, 1978. "Growth Accounting with Intermediate Inputs," Review of Economic Studies, Oxford University Press, vol. 45(3), pages 511-518.
    5. James Levinsohn & Amil Petrin, 2003. "Estimating Production Functions Using Inputs to Control for Unobservables," Review of Economic Studies, Oxford University Press, vol. 70(2), pages 317-341.
    6. 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.
    7. Gábor Kátay & Zoltán Wolf, 2008. "Driving Factors of Growth in Hungary - a Decomposition Exercise," MNB Working Papers 2008/6, Magyar Nemzeti Bank (Central Bank of Hungary).
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    Cited by:

    1. Rockey, James & Temple, Jonathan, 2016. "Growth econometrics for agnostics and true believers," European Economic Review, Elsevier, vol. 81(C), pages 86-102.
    2. Christina Poetzsch, 2017. "Technology transfer on a two-way street: R&D spillovers through intermediate input usage and supply," Review of World Economics (Weltwirtschaftliches Archiv), Springer;Institut für Weltwirtschaft (Kiel Institute for the World Economy), vol. 153(4), pages 735-751, November.
    3. Ayyagari, Meghana & Demirguc-Kunt, Asli & Maksimovic, Vojislav, 2011. "Do Phoenix miracles exist ? firm-level evidence from financial crises," Policy Research Working Paper Series 5799, The World Bank.
    4. Jensen Christian, 2016. "On the macroeconomic effects of heterogeneous productivity shocks," The B.E. Journal of Macroeconomics, De Gruyter, vol. 16(1), pages 1-23, January.
    5. Gorji, Narges Mirzaie & Fami, Hossein Shabanali & Iravani, Hooshang, 2017. "Investigating Factors that Affecting Citrus Waste Production in Mazandaran Province, Iran," International Journal of Agricultural Management and Development (IJAMAD), Iranian Association of Agricultural Economics, vol. 7(1), March.
    6. Zhong, Sheng, 2016. "The dynamics of vehicle energy efficiency: Evidence from the Massachusetts Vehicle Census," MERIT Working Papers 2016-014, United Nations University - Maastricht Economic and Social Research Institute on Innovation and Technology (MERIT).
    7. Pantea, Smaranda & Sabadash, Anna & Biagi, Federico, 2017. "Are ICT displacing workers in the short run? Evidence from seven European countries," Information Economics and Policy, Elsevier, vol. 39(C), pages 36-44.
    8. Fornaro, Paolo & Luomaranta, Henri, 2017. "Small and Medium Firms, Aggregate Productivity and the Role of Dependencies," ETLA Working Papers 47, The Research Institute of the Finnish Economy.

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    More about this item

    Keywords

    Economic growth; production function; total factor productivity; aggregation; firm-level data data; Bayesian analysis; forecasting;

    JEL classification:

    • C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • 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
    • C33 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Models with Panel Data; Spatio-temporal Models
    • D24 - Microeconomics - - Production and Organizations - - - Production; Cost; Capital; Capital, Total Factor, and Multifactor Productivity; Capacity
    • O12 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development - - - Microeconomic Analyses of Economic Development
    • 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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