IDEAS home Printed from https://ideas.repec.org/a/sae/mareco/v14y2020i2p129-163.html
   My bibliography  Save this article

Technology Shocks and Non-stationary Hours in Emerging Countries and DSVAR

Author

Listed:
  • Sevgi Coskun

    (Sevgi Coskun is at the Faculty of Economics and Administrative Sciences, Ardahan University, Ardahan, Turkey, e-mail: sevgicoskun@ardahan.edu.tr)

Abstract

We test a standard DSGE (Dynamic Stochastic General Equilibrium) model on impulse responses of hours worked and real GDP after technology and non-technology shocks in emerging market economies (EMEs). Most dynamic macroeconomic models assume that hours worked are stationary. However, in the data, we observe apparent changes in hours worked from 1970 to 2013 in these economies. Motivated by this fact, we first estimate a structural vector autoregression (SVAR) model with a specification of hours in difference (DSVAR) and then set up a DSGE model by incorporating permanent labour supply (LS) shocks that can generate a unit root in hours worked, while preserving the property of a balanced growth path. These LS shocks could be associated with very dramatic changes in LS which look permanent in these economies. Hence, the identification restriction in our models comes from the fact that both technology and LS shocks have a permanent effect on GDP yet only the latter shocks have a long-run impact on hours worked. For inference purposes, we compare empirical impulse responses based on the EMEs data to impulse responses from DSVARs run on the simulated data from the model. The results show that a DSGE model with permanent LS shocks that can generate a unit root in hours worked is required to properly evaluate the DSVAR in EMEs as this model is able to replicate indirectly impulse responses obtained from a DSVAR on the actual data. JEL Classification: C32, E32

Suggested Citation

  • Sevgi Coskun, 2020. "Technology Shocks and Non-stationary Hours in Emerging Countries and DSVAR," Margin: The Journal of Applied Economic Research, National Council of Applied Economic Research, vol. 14(2), pages 129-163, May.
  • Handle: RePEc:sae:mareco:v:14:y:2020:i:2:p:129-163
    DOI: 10.1177/0973801020911587
    as

    Download full text from publisher

    File URL: https://journals.sagepub.com/doi/10.1177/0973801020911587
    Download Restriction: no

    File URL: https://libkey.io/10.1177/0973801020911587?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Bridgman, Benjamin & Duernecker, Georg & Herrendorf, Berthold, 2018. "Structural transformation, marketization, and household production around the world," Journal of Development Economics, Elsevier, vol. 133(C), pages 102-126.
    2. Blanchard, Olivier Jean & Quah, Danny, 1989. "The Dynamic Effects of Aggregate Demand and Supply Disturbances," American Economic Review, American Economic Association, vol. 79(4), pages 655-673, September.
    3. Jordi Galí & Pau Rabanal, 2005. "Technology Shocks and Aggregate Fluctuations: How Well Does the Real Business Cycle Model Fit Postwar US Data?," NBER Chapters, in: NBER Macroeconomics Annual 2004, Volume 19, pages 225-318, National Bureau of Economic Research, Inc.
    4. Miles S. Kimball & John G. Fernald & Susanto Basu, 2006. "Are Technology Improvements Contractionary?," American Economic Review, American Economic Association, vol. 96(5), pages 1418-1448, December.
    5. Cristiano Cantore & Miguel León-Ledesma & Peter McAdam & Alpo Willman, 2014. "Shocking Stuff: Technology, Hours, And Factor Substitution," Journal of the European Economic Association, European Economic Association, vol. 12(1), pages 108-128, February.
    6. 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.
    7. Javier Garcia-Cicco & Roberto Pancrazi & Martin Uribe, 2010. "Real Business Cycles in Emerging Countries?," American Economic Review, American Economic Association, vol. 100(5), pages 2510-2531, December.
    8. Minford, Patrick & Wickens, Michael & Xu, Yongdeng, 2016. "Comparing different data descriptors in Indirect Inference tests on DSGE models," Economics Letters, Elsevier, vol. 145(C), pages 157-161.
    9. Cogley, Timothy & Nason, James M, 1995. "Output Dynamics in Real-Business-Cycle Models," American Economic Review, American Economic Association, vol. 85(3), pages 492-511, June.
    10. Canova, Fabio & Sala, Luca, 2009. "Back to square one: Identification issues in DSGE models," Journal of Monetary Economics, Elsevier, vol. 56(4), pages 431-449, May.
    11. Mark Aguiar & Gita Gopinath, 2007. "Emerging Market Business Cycles: The Cycle Is the Trend," Journal of Political Economy, University of Chicago Press, vol. 115, pages 69-102.
    12. Hall, Robert E, 1997. "Macroeconomic Fluctuations and the Allocation of Time," Journal of Labor Economics, University of Chicago Press, vol. 15(1), pages 223-250, January.
    13. Cantore, Cristiano & Ferroni, Filippo & León-Ledesma, Miguel A., 2017. "The dynamics of hours worked and technology," Journal of Economic Dynamics and Control, Elsevier, vol. 82(C), pages 67-82.
    14. Timo Boppart & Per Krusell, 2020. "Labor Supply in the Past, Present, and Future: A Balanced-Growth Perspective," Journal of Political Economy, University of Chicago Press, vol. 128(1), pages 118-157.
    15. Francis, Neville & Ramey, Valerie A., 2005. "Is the technology-driven real business cycle hypothesis dead? Shocks and aggregate fluctuations revisited," Journal of Monetary Economics, Elsevier, vol. 52(8), pages 1379-1399, November.
    16. Matthew D. Shapiro & Mark W. Watson, 1988. "Sources of Business Cycle Fluctuations," NBER Chapters, in: NBER Macroeconomics Annual 1988, Volume 3, pages 111-156, National Bureau of Economic Research, Inc.
    17. Neville Francis & Valerie A. Ramey, 2006. "The Source of Historical Economic Fluctuations: An Analysis Using Long-Run Restrictions," NBER Chapters, in: NBER International Seminar on Macroeconomics 2004, pages 17-73, National Bureau of Economic Research, Inc.
    18. Sims, Christopher A, 1980. "Macroeconomics and Reality," Econometrica, Econometric Society, vol. 48(1), pages 1-48, January.
    19. Gospodinov, Nikolay, 2010. "Inference in Nearly Nonstationary SVAR Models With Long-Run Identifying Restrictions," Journal of Business & Economic Statistics, American Statistical Association, vol. 28(1), pages 1-12.
    20. Lawrence J. Christiano & Martin Eichenbaum & Robert Vigfusson, 2003. "What Happens After a Technology Shock?," NBER Working Papers 9819, National Bureau of Economic Research, Inc.
    21. Chaudourne, Jeremy & Fève, Patrick & Guay, Alain, 2014. "Understanding the effect of technology shocks in SVARs with long-run restrictions," Journal of Economic Dynamics and Control, Elsevier, vol. 41(C), pages 154-172.
    22. Neville Francis & Valerie A. Ramey, 2009. "Measures of per Capita Hours and Their Implications for the Technology-Hours Debate," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 41(6), pages 1071-1097, September.
    23. Nan Li, 2011. "Cyclical Wage Movements in Emerging Markets Compared to Developed Economies: the Role of Interest Rates," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 14(4), pages 686-704, October.
    24. 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.
    25. Dupaigne, M. & Fève, P. & Matheron, J., 2005. "Technology Shock and Employment: Do We Really Need DSGE Models with a Fall in Hours?," Working papers 124, Banque de France.
    26. Jordi Galí, 2004. "On The Role of Technology Shocks as a Source of Business Cycles: Some New Evidence," Journal of the European Economic Association, MIT Press, vol. 2(2-3), pages 372-380, 04/05.
    27. Chang, Yongsung & Schorfheide, Frank, 2003. "Labor-supply shifts and economic fluctuations," Journal of Monetary Economics, Elsevier, vol. 50(8), pages 1751-1768, November.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Sedegah Kordzo & Odhiambo Nicholas M., 2021. "A Review of the Impact of External Shocks on Monetary Policy Effectiveness in Non-WAEMU Countries," Studia Universitatis „Vasile Goldis” Arad – Economics Series, Sciendo, vol. 31(3), pages 37-59, September.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Ramey, V.A., 2016. "Macroeconomic Shocks and Their Propagation," Handbook of Macroeconomics, in: J. B. Taylor & Harald Uhlig (ed.), Handbook of Macroeconomics, edition 1, volume 2, chapter 0, pages 71-162, Elsevier.
    2. Justiniano, Alejandro & Primiceri, Giorgio E. & Tambalotti, Andrea, 2010. "Investment shocks and business cycles," Journal of Monetary Economics, Elsevier, vol. 57(2), pages 132-145, March.
    3. Andrei Polbin & Sergey Drobyshevsky, 2014. "Developing a Dynamic Stochastic Model of General Equilibrium for the Russian Economy," Research Paper Series, Gaidar Institute for Economic Policy, issue 166P, pages 156-156.
    4. Chari, V.V. & Kehoe, Patrick J. & McGrattan, Ellen R., 2008. "Are structural VARs with long-run restrictions useful in developing business cycle theory?," Journal of Monetary Economics, Elsevier, vol. 55(8), pages 1337-1352, November.
    5. Chaudourne, Jeremy & Fève, Patrick & Guay, Alain, 2014. "Understanding the effect of technology shocks in SVARs with long-run restrictions," Journal of Economic Dynamics and Control, Elsevier, vol. 41(C), pages 154-172.
    6. Jordi Gali, 2005. "Trends in hours, balanced growth, and the role of technology in the business cycle," Review, Federal Reserve Bank of St. Louis, vol. 87(Jul), pages 459-486.
    7. Patrick Fève & Alain Guay, 2010. "Identification of Technology Shocks in Structural Vars," Economic Journal, Royal Economic Society, vol. 120(549), pages 1284-1318, December.
    8. Rujin, Svetlana, 2019. "What are the effects of technology shocks on international labor markets?," Ruhr Economic Papers 806, RWI - Leibniz-Institut für Wirtschaftsforschung, Ruhr-University Bochum, TU Dortmund University, University of Duisburg-Essen.
    9. Christopher J. Erceg & Luca Guerrieri & Christopher Gust, 2005. "Can Long-Run Restrictions Identify Technology Shocks?," Journal of the European Economic Association, MIT Press, vol. 3(6), pages 1237-1278, December.
    10. Cantore, Cristiano & Ferroni, Filippo & León-Ledesma, Miguel A., 2017. "The dynamics of hours worked and technology," Journal of Economic Dynamics and Control, Elsevier, vol. 82(C), pages 67-82.
    11. Fernald, John G., 2007. "Trend breaks, long-run restrictions, and contractionary technology improvements," Journal of Monetary Economics, Elsevier, vol. 54(8), pages 2467-2485, November.
    12. Sean Holly & Ivan Petrella, 2008. "Factor demand linkages and the business cycle: interpreting aggregate fluctuations as sectoral fluctuations," CDMA Conference Paper Series 0809, Centre for Dynamic Macroeconomic Analysis.
    13. Francesco Busato & Alessandro Girardi & Amadeo Argentiero, 2005. "Technology and non-technology shocks in a two-sector economy," Economics Working Papers 2005-11, Department of Economics and Business Economics, Aarhus University.
    14. Ambler, Steve & Guay, Alain & Phaneuf, Louis, 2012. "Endogenous business cycle propagation and the persistence problem: The role of labor-market frictions," Journal of Economic Dynamics and Control, Elsevier, vol. 36(1), pages 47-62.
    15. Peter Ireland & Scott Schuh, 2008. "Productivity and U.S. Macroeconomic Performance: Interpreting the Past and Predicting the Future with a Two-Sector Real Business Cycle Model," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 11(3), pages 473-492, July.
    16. Chevillon, Guillaume & Mavroeidis, Sophocles & Zhan, Zhaoguo, 2016. "Robust inference in structural VARs with long-run restrictions," ESSEC Working Papers WP1702, ESSEC Research Center, ESSEC Business School.
    17. Kascha, Christian & Mertens, Karel, 2009. "Business cycle analysis and VARMA models," Journal of Economic Dynamics and Control, Elsevier, vol. 33(2), pages 267-282, February.
    18. Shingo Watanabe, 2012. "The Role Of Technology And Nontechnology Shocks In Business Cycles," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 53(4), pages 1287-1321, November.
    19. Francis, Neville & Ramey, Valerie A., 2005. "Is the technology-driven real business cycle hypothesis dead? Shocks and aggregate fluctuations revisited," Journal of Monetary Economics, Elsevier, vol. 52(8), pages 1379-1399, November.
    20. Giancarlo Corsetti & Luca Dedola & Sylvain Leduc, 2008. "Productivity, External Balance, and Exchange Rates: Evidence on the Transmission Mechanism among G7 Countries," NBER Chapters, in: NBER International Seminar on Macroeconomics 2006, pages 117-194, National Bureau of Economic Research, Inc.

    More about this item

    Keywords

    Non-stationary Hours; DSGE Models; DSVAR Approach;
    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
    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:sae:mareco:v:14:y:2020:i:2:p:129-163. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: SAGE Publications (email available below). General contact details of provider: http://www.ncaer.org/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.