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Firms Dynamics and Business Cycle: New Disaggregated Data

Author

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  • Lorenza Rossi

    (Department of Economics and Management, University of Pavia)

  • Emilio Zanetti Chini

    (Department of Economics and Management, University of Pavia)

Abstract

We provide stylized facts on firms dynamics by disaggregating U.S. yearly data from 1977 to 2013. To this aim, we use an unobserved component-based method, encompassing several classical regression-based techniques currently in use. Our series of entry and exit of firms at establishment level are feasible proxies of business cycle. Exit is a leading and countercyclical indicator, while entry is lagging and pro-cyclical. According to a standard structural econometric analysis, exit overshoots its average level in the medium-run. Several robustness checks confirm these results, hence supporting the most recent theoretical literature.

Suggested Citation

  • Lorenza Rossi & Emilio Zanetti Chini, 2018. "Firms Dynamics and Business Cycle: New Disaggregated Data," DEM Working Papers Series 151, University of Pavia, Department of Economics and Management.
  • Handle: RePEc:pav:demwpp:demwp0151
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    1. Filippo Altissimo & Antonio Bassanetti & Riccardo Cristadoro & Lucrezia Reichlin & Giovanni Veronese, 2001. "The construction of coincident and leading indicators for the euro area business cycler of the euro area business cycle," Temi di discussione (Economic working papers) 434, Bank of Italy, Economic Research and International Relations Area.
    2. Emilio Zanetti Chini, 2013. "Generalizing smooth transition autoregressions," CREATES Research Papers 2013-32, Department of Economics and Business Economics, Aarhus University.
    3. Terasvirta, T & Anderson, H M, 1992. "Characterizing Nonlinearities in Business Cycles Using Smooth Transition Autoregressive Models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 7(S), pages 119-136, Suppl. De.
    4. Federico Etro & Andrea Colciago, 2010. "Endogenous Market Structures and the Business Cycle," Economic Journal, Royal Economic Society, vol. 120(549), pages 1201-1233, December.
    5. Masashige Hamano & Francesco Zanetti, 2017. "Endogenous Turnover and Macroeconomic Dynamics," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 26, pages 263-279, October.
    6. Sichel, Daniel E, 1993. "Business Cycle Asymmetry: A Deeper Look," Economic Inquiry, Western Economic Association International, vol. 31(2), pages 224-236, April.
    7. Michael W. McCracken & Serena Ng, 2016. "FRED-MD: A Monthly Database for Macroeconomic Research," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 34(4), pages 574-589, October.
    8. Bartolucci, Francesco & Scaccia, Luisa & Farcomeni, Alessio, 2012. "Bayesian inference through encompassing priors and importance sampling for a class of marginal models for categorical data," Computational Statistics & Data Analysis, Elsevier, vol. 56(12), pages 4067-4080.
    9. Florin O. Bilbiie & Fabio Ghironi & Marc J. Melitz, 2012. "Endogenous Entry, Product Variety, and Business Cycles," Journal of Political Economy, University of Chicago Press, vol. 120(2), pages 304-345.
    10. Tamás Rudas & Wicher P. Bergsma, 2004. "On applications of marginal models for categorical data," Metron - International Journal of Statistics, Dipartimento di Statistica, Probabilità e Statistiche Applicate - University of Rome, vol. 0(1), pages 15-37.
    11. Thomas Richardson, 2003. "Markov Properties for Acyclic Directed Mixed Graphs," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 30(1), pages 145-157, March.
    12. Tommaso Proietti, 2006. "Temporal disaggregation by state space methods: Dynamic regression methods revisited," Econometrics Journal, Royal Economic Society, vol. 9(3), pages 357-372, November.
    13. Lippi, Marco & Reichlin, Lucrezia & Hallin, Marc & Forni, Mario & Altissimo, Filippo & Cristadoro, Riccardo & Veronese, Giovanni & Bassanetti, Antonio, 2001. "EuroCOIN: A Real Time Coincident Indicator of the Euro Area Business Cycle," CEPR Discussion Papers 3108, C.E.P.R. Discussion Papers.
    14. La Croce, Carla & Rossi, Lorenza, 2018. "Firms' Endogenous Entry And Monopolistic Banking In A Dsge Model," Macroeconomic Dynamics, Cambridge University Press, vol. 22(1), pages 153-171, January.
    15. Ntzoufras, Ioannis & Tarantola, Claudia, 2013. "Conjugate and conditional conjugate Bayesian analysis of discrete graphical models of marginal independence," Computational Statistics & Data Analysis, Elsevier, vol. 66(C), pages 161-177.
    16. Lewis, Vivien, 2009. "Business Cycle Evidence On Firm Entry," Macroeconomic Dynamics, Cambridge University Press, vol. 13(5), pages 605-624, November.
    17. 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.
    18. Arthur F. Burns & Wesley C. Mitchell, 1946. "Measuring Business Cycles," NBER Books, National Bureau of Economic Research, Inc, number burn46-1, March.
    19. Lewis, Vivien & Poilly, Céline, 2012. "Firm entry, markups and the monetary transmission mechanism," Journal of Monetary Economics, Elsevier, vol. 59(7), pages 670-685.
    20. Lorenza Rossi & Emilio Zanetti Chini, 2016. "Firms’ Dynamics and Business Cycle: New Disaggregated Data," DEM Working Papers Series 123, University of Pavia, Department of Economics and Management.
    21. Bahjat F. Qaqish & Anastasia Ivanova, 2006. "Multivariate logistic models," Biometrika, Biometrika Trust, vol. 93(4), pages 1011-1017, December.
    22. Bergin, Paul R. & Corsetti, Giancarlo, 2008. "The extensive margin and monetary policy," Journal of Monetary Economics, Elsevier, vol. 55(7), pages 1222-1237, October.
    23. Filippo Altissimo & Antonio Bassanetti & Riccardo Cristadoro & Mario Forni & Marco Lippi & Lucrezia Reichlin & Giovanni Veronese, 2001. "A real time coincident indicator of the euro area business cycle," Temi di discussione (Economic working papers) 436, Bank of Italy, Economic Research and International Relations Area.
    24. Mathias Drton & Thomas S. Richardson, 2008. "Binary models for marginal independence," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 70(2), pages 287-309, April.
    25. Robin J. Evans & Thomas S. Richardson, 2013. "Marginal log-linear parameters for graphical Markov models," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 75(4), pages 743-768, September.
    26. Filippo Altissimo & Riccardo Cristadoro & Mario Forni & Marco Lippi & Giovanni Veronese, 2010. "New Eurocoin: Tracking Economic Growth in Real Time," The Review of Economics and Statistics, MIT Press, vol. 92(4), pages 1024-1034, November.
    27. Robin J. Evans, 2016. "Graphs for Margins of Bayesian Networks," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 43(3), pages 625-648, September.
    28. Miguel Casares & Jean-Christophe Poutineau, 2014. "A DSGE model with endogenous entry and exit," Carleton Economic Papers 14-06, Carleton University, Department of Economics.
    29. John G. Fernald & Kyle Matoba, 2009. "Growth accounting, potential output, and the current recession," FRBSF Economic Letter, Federal Reserve Bank of San Francisco, issue aug17.
    30. Michael Siemer, 2014. "Firm Entry and Employment Dynamics in the Great Recession," Finance and Economics Discussion Series 2014-56, Board of Governors of the Federal Reserve System (U.S.).
    31. 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.
    32. Monia Lupparelli & Giovanni M. Marchetti & Wicher P. Bergsma, 2009. "Parameterizations and Fitting of Bi‐directed Graph Models to Categorical Data," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 36(3), pages 559-576, September.
    33. Johansen, Soren, 1991. "Estimation and Hypothesis Testing of Cointegration Vectors in Gaussian Vector Autoregressive Models," Econometrica, Econometric Society, vol. 59(6), pages 1551-1580, November.
    34. Tamás Rudas & Wicher P. Bergsma & Renáta Németh, 2010. "Marginal log-linear parameterization of conditional independence models," Biometrika, Biometrika Trust, vol. 97(4), pages 1006-1012.
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    Cited by:

    1. Savagar, Anthony & Dixon, Huw, 2020. "Firm entry, excess capacity and endogenous productivity," European Economic Review, Elsevier, vol. 121(C).
    2. Emilio Zanetti Chini, 2013. "Generalizing smooth transition autoregressions," CREATES Research Papers 2013-32, Department of Economics and Business Economics, Aarhus University.
    3. Lorenza Rossi & Emilio Zanetti Chini, 2016. "Firms’ Dynamics and Business Cycle: New Disaggregated Data," DEM Working Papers Series 123, University of Pavia, Department of Economics and Management.

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    More about this item

    Keywords

    Bayesian VAR; Entry; Exit; Productivity; State Space Models.;
    All these keywords.

    JEL classification:

    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: 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
    • C40 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - General
    • E30 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - General (includes Measurement and Data)
    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles

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