IDEAS home Printed from https://ideas.repec.org/p/new/wpaper/2013.html
   My bibliography  Save this paper

Corridor stability of the Kaleckian growth model: a Markov-switching approach

Author

Listed:
  • Brian Hartley

    (Department of Economics, New School for Social Research)

Abstract

To assess the conditional stability properties of the Kaleckian growth framework in the mediumrun, we investigate behavioral corridors where investment will be unresponsive to departures of actual from desired utilization rates - thus providing for the episodic incidence of Harrodian instability. We empirically assess this relationship using two-state Markov-Switching Structural Vector Auto-Regression fit on non-residential fixed investment and the rate of capacity utilization for the United States. To directly assess the relevance of a behavioral corridor for the cyclical dynamics of the endogenous variables, the probabilities governing the transition between hidden states are modelled as a time-varying function of gap between realized utilization rates and their long-run average. Results suggest the response of investment to structural utilization shocks is highly regime-dependent and predominantly occurs during business cycle downturns.

Suggested Citation

  • Brian Hartley, 2020. "Corridor stability of the Kaleckian growth model: a Markov-switching approach," Working Papers 2013, New School for Social Research, Department of Economics, revised Nov 2020.
    • Handle: RePEc:new:wpaper:2013
    as

    Download full text from publisher

    File URL: http://www.economicpolicyresearch.org/econ/2020/NSSR_WP_132020.pdf
    File Function: First version, 2020
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Robert A. Blecker, 2016. "Wage-led versus profit-led demand regimes: the long and the short of it," Review of Keynesian Economics, Edward Elgar Publishing, vol. 4(4), pages 373-390, October.
    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. Marc Lavoie & Gabriel Rodriguez & Mario Seccareccia, 2004. "Similitudes and Discrepancies in Post-Keynesian and Marxist Theories of Investment: A Theoretical and Empirical Investigation," International Review of Applied Economics, Taylor & Francis Journals, vol. 18(2), pages 127-149.
    4. Joe, Harry, 2006. "Generating random correlation matrices based on partial correlations," Journal of Multivariate Analysis, Elsevier, vol. 97(10), pages 2177-2189, November.
    5. Christopher A. Sims & Tao Zha, 2006. "Were There Regime Switches in U.S. Monetary Policy?," American Economic Review, American Economic Association, vol. 96(1), pages 54-81, March.
    6. Ozlem Onaran & Thomas Obst, 2016. "Wage-led growth in the EU15 member-states: the effects of income distribution on growth, investment, trade balance and inflation," Cambridge Journal of Economics, Cambridge Political Economy Society, vol. 40(6), pages 1517-1551.
    7. Bhaduri, Amit & Marglin, Stephen, 1990. "Unemployment and the Real Wage: The Economic Basis for Contesting Political Ideologies," Cambridge Journal of Economics, Cambridge Political Economy Society, vol. 14(4), pages 375-393, December.
    8. 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.
    9. Matthew Stephens, 2000. "Dealing with label switching in mixture models," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 62(4), pages 795-809.
    10. Hamilton, James D, 1989. "A New Approach to the Economic Analysis of Nonstationary Time Series and the Business Cycle," Econometrica, Econometric Society, vol. 57(2), pages 357-384, March.
    11. Anwar Shaikh, 2009. "Economic Policy In A Growth Context: A Classical Synthesis Of Keynes And Harrod," Metroeconomica, Wiley Blackwell, vol. 60(3), pages 455-494, July.
    12. Trezzini, Attilio, 2017. "Harrodian Instability: a Misleading Concept," Centro Sraffa Working Papers CSWP24, Centro di Ricerche e Documentazione "Piero Sraffa".
    13. 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.
    14. Eckhard Hein & Marc Lavoie & Till van Treeck, 2012. "Harrodian Instability And The ‘Normal Rate’ Of Capacity Utilization In Kaleckian Models Of Distribution And Growth—A Survey," Metroeconomica, Wiley Blackwell, vol. 63(1), pages 139-169, February.
    15. Jonah Gabry & Daniel Simpson & Aki Vehtari & Michael Betancourt & Andrew Gelman, 2019. "Visualization in Bayesian workflow," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 182(2), pages 389-402, February.
    16. Florian Botte, 2017. "Estimating normal capacity utilization rates and their tolerable ranges of values: A comment on Setterfield," Post-Print hal-01543643, HAL.
    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. Mark Setterfield, 2021. "Harrodians and Kaleckians: a suggested reconciliation and synthesis," Working Papers 2111, New School for Social Research, Department of Economics, revised Jan 2022.

    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. Brian Hartley, 2022. "Episodic incidence of Harrodian instability and the Kaleckian growth model: A Markov‐switching approach," Metroeconomica, Wiley Blackwell, vol. 73(1), pages 268-290, February.
    2. Netsunajev, Aleksei, 2013. "Reaction to technology shocks in Markov-switching structural VARs: Identification via heteroskedasticity," Journal of Macroeconomics, Elsevier, vol. 36(C), pages 51-62.
    3. Eckhard Hein, 2017. "Post-Keynesian macroeconomics since the mid 1990s: main developments," European Journal of Economics and Economic Policies: Intervention, Edward Elgar Publishing, vol. 14(2), pages 131-172, September.
    4. Christian Schoder, 2012. "Effective demand, exogenous normal utilization and endogenous capacity in the long run. Evidence from a CVAR analysis for the US," IMK Working Paper 103-2012, IMK at the Hans Boeckler Foundation, Macroeconomic Policy Institute.
    5. Jinho Bae & Chang-Jin Kim & Dong Kim, 2012. "The evolution of the monetary policy regimes in the U.S," Empirical Economics, Springer, vol. 43(2), pages 617-649, October.
    6. Mark Setterfield & Joana David Avritzer, 2020. "Hysteresis in the normal rate of capacity utilization: A behavioral explanation," Metroeconomica, Wiley Blackwell, vol. 71(4), pages 898-919, November.
    7. Magnus Reif, 2020. "Macroeconomics, Nonlinearities, and the Business Cycle," ifo Beiträge zur Wirtschaftsforschung, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, number 87.
    8. Carboni, Giacomo, 2014. "Term premia implications of macroeconomic regime changes," Working Paper Series 1694, European Central Bank.
    9. Mark Setterfield, 2019. "Long-run variation in capacity utilization in the presence of a fixed normal rate," Cambridge Journal of Economics, Cambridge Political Economy Society, vol. 43(2), pages 443-463.
    10. Serena Ng & Jonathan H. Wright, 2013. "Facts and Challenges from the Great Recession for Forecasting and Macroeconomic Modeling," Journal of Economic Literature, American Economic Association, vol. 51(4), pages 1120-1154, December.
    11. Xiaoshan Chen & Ronald Macdonald, 2012. "Realized and Optimal Monetary Policy Rules in an Estimated Markov‐Switching DSGE Model of the United Kingdom," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 44(6), pages 1091-1116, September.
    12. Bekaert, Geert & Engstrom, Eric & Ermolov, Andrey, 2021. "Macro risks and the term structure of interest rates," Journal of Financial Economics, Elsevier, vol. 141(2), pages 479-504.
    13. James Bullard & Aarti Singh, 2012. "Learning And The Great Moderation," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 53(2), pages 375-397, May.
    14. Santiago José Gahn & Alejandro González, 2022. "On the empirical content of the convergence debate: Cross‐country evidence on growth and capacity utilisation," Metroeconomica, Wiley Blackwell, vol. 73(3), pages 825-855, July.
    15. Giorgio Canarella & WenShwo Fang & Stephen M. Miller & Stephen K. Pollard, 2008. "Is the Great Moderation Ending? UK and US Evidence," Working Papers 0801, University of Nevada, Las Vegas , Department of Economics.
    16. Mumtaz, Haroon & Zanetti, Francesco, 2012. "Neutral technology shocks and employment dynamics: results based on an RBC identification scheme," Bank of England working papers 453, Bank of England.
    17. Lanne, Markku & Lütkepohl, Helmut & Maciejowska, Katarzyna, 2010. "Structural vector autoregressions with Markov switching," Journal of Economic Dynamics and Control, Elsevier, vol. 34(2), pages 121-131, February.
    18. Chauvet, Marcelle & Potter, Simon, 2013. "Forecasting Output," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 141-194, Elsevier.
    19. Christian Schoder, 2014. "Effective Demand, Exogenous Normal Utilization and Endogenous Capacity in the Long Run: Evidence from a Cointegrated Vector Autoregression Analysis for the USA," Metroeconomica, Wiley Blackwell, vol. 65(2), pages 298-320, May.
    20. Inoue, Tomoo & Okimoto, Tatsuyoshi, 2008. "Were there structural breaks in the effects of Japanese monetary policy? Re-evaluating policy effects of the lost decade," Journal of the Japanese and International Economies, Elsevier, vol. 22(3), pages 320-342, September.

    More about this item

    Keywords

    Kaleckian Growth Model; Growth and Distribution; Harrodian Instability; Hidden Markov Models; Structural Vector Auto-Regression; Bayesian Econometrics;
    All these keywords.

    JEL classification:

    • B50 - Schools of Economic Thought and Methodology - - Current Heterodox Approaches - - - General
    • C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
    • E11 - Macroeconomics and Monetary Economics - - General Aggregative Models - - - Marxian; Sraffian; Kaleckian

    NEP fields

    This paper has been announced in the following NEP Reports:

    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:new:wpaper:2013. 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: Mark Setterfield (email available below). General contact details of provider: https://edirc.repec.org/data/denewus.html .

    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.