IDEAS home Printed from https://ideas.repec.org/a/jbl/ref000/v6y2022i2id192.html

Application of the vector-autoregression VAR model in the analysis of unemployment hysteresis in the context of Okun’s Law

Author

Listed:
  • Patryk Kołbyko

    (Maria Curie-Skłodowska University, Lublin, Poland)

Abstract

Unemployment is an important macroeconomic issue both in theoretical terms and for economic reality. On the theoretical ground, the unemployment rate, which is a measure of the share of unemployed units of the labour supply in the economy, determines the output gap at a certain adjustment parameter determined by the marginal productivity of labour. One of the causes of rising or persistent unemployment in the economy is the phenomenon of unemployment hysteresis, which occurs as a result of changes in the marginal disutility of labour, the strength of the wage bargain and other exogenous conditions arising in previous periods. The purpose of the study conducted in the following paper is to investigate the phenomenon of hysteresis in the labour market by analysing the significance of the impact of the unemployment rate in previous periods. In addition, the work aims to study Okun’s Law as an effect of production dynamics on the unemployment rate. The study of the dependence was carried out through the estimation of a macroeconometric time series model—vector-autoregression (VAR) on the example of statistical data for Poland obtained from Statistics Poland (Stat.gov.pl) and complied raports about national accounts in the quarterly sequence for the years 2015–2021.

Suggested Citation

  • Patryk Kołbyko, 2022. "Application of the vector-autoregression VAR model in the analysis of unemployment hysteresis in the context of Okun’s Law," Research Papers in Economics and Finance, Poznań University of Economics and Business, vol. 6(2), pages 68-85, February.
  • Handle: RePEc:jbl:ref000:v:6:y:2022:i:2:id:192
    DOI: 10.18559/ref.2022.2.4
    as

    Download full text from publisher

    File URL: https://journals.ue.poznan.pl/REF/article/view/192
    File Function: Abstract page
    Download Restriction: no

    File URL: https://journals.ue.poznan.pl/REF/article/download/192/96
    File Function: Full text
    Download Restriction: no

    File URL: https://libkey.io/10.18559/ref.2022.2.4?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. Lutz Kilian, 2013. "Structural vector autoregressions," Chapters, in: Nigar Hashimzade & Michael A. Thornton (ed.), Handbook of Research Methods and Applications in Empirical Macroeconomics, chapter 22, pages 515-554, Edward Elgar Publishing.
    2. Malcolm Rutherford, 1987. "Wesley Mitchell: Institutions and Quantitative Methods," Eastern Economic Journal, Eastern Economic Association, vol. 13(1), pages 63-73, Jan-Mar.
    3. A. Hatemi-J & R. S. Hacker, 2009. "Can the LR test be helpful in choosing the optimal lag order in the VAR model when information criteria suggest different lag orders?," Applied Economics, Taylor & Francis Journals, vol. 41(9), pages 1121-1125.
    4. Neil Dias Karunaratne, 1995. "Paradox of Hysteresis and Real-Wage Flexibility in Australia," Journal of Post Keynesian Economics, Taylor & Francis Journals, vol. 17(4), pages 503-514, July.
    5. Hall, Stephen George & Roudoi, Andrei & Albu, Lucian Liviu & Lupu, Radu & Calin, Adrian Cantemir, 2014. "Lawrence R. Klein and the Economic Forecasting – A Survey," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(1), pages 5-14, March.
    Full references (including those not matched with items on IDEAS)

    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. Claudio Morana, 2014. "Factor Vector Autoregressive Estimation of Heteroskedastic Persistent and Non Persistent Processes Subject to Structural Breaks," Working Papers 273, University of Milano-Bicocca, Department of Economics, revised May 2014.
    2. Xu Sun & Lide Su & Bo Zhou & Te Bu & Yang Zhang, 2024. "Systematic evaluation of integration between China’s digital economy and sports industry: Two-stage grey relational analysis and vector autoregressive model," PLOS ONE, Public Library of Science, vol. 19(5), pages 1-25, May.
    3. Istiak, Khandokar & Serletis, Apostolos, 2020. "Risk, uncertainty, and leverage," Economic Modelling, Elsevier, vol. 91(C), pages 257-273.
    4. Paolo Guarda & Philippe Jeanfils, 2012. "Macro-financial linkages: Evidence from country-specific VARs," BCL working papers 71, Central Bank of Luxembourg.
    5. Zaid Ashiq Khan & Mansoor Ahmed Koondhar & Noshaba Aziz & Uzair Ali & Liu Tianjun, 2020. "Revisiting the effects of relevant factors on Pakistan's agricultural products export," Agricultural Economics, Czech Academy of Agricultural Sciences, vol. 66(12), pages 527-541.
    6. Adugna Olani, 2016. "Dynamic Capital Inflow Transmission Of Monetary Policy To Emerging Markets," Working Paper 1358, Economics Department, Queen's University.
    7. André M. Marques, 2022. "Reviewing demand regimes in open economies with Penn World Table data," Manchester School, University of Manchester, vol. 90(6), pages 730-751, December.
    8. Klodiana Istrefi & B. Vonnak, 2015. "Delayed Overshooting Puzzle in Structural Vector Autoregression Models," Working papers 576, Banque de France.
    9. Arnaut, Javier L., 2022. "The importance of uranium prices and structural shocks: Some implications for Greenland," Energy Policy, Elsevier, vol. 161(C).
    10. Porqueddu Mario & Venditti Fabrizio, 2014. "Do food commodity prices have asymmetric effects on euro-area inflation?," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 18(4), pages 419-443, September.
    11. Kristina Bluwstein & Fabio Canova, 2016. "Beggar-Thy-Neighbor? The International Effects of ECB Unconventional Monetary Policy Measures," International Journal of Central Banking, International Journal of Central Banking, vol. 12(3), pages 69-120, September.
    12. Victoria Nuguer, 2016. "Financial Intermediation in a Global Environment," International Journal of Central Banking, International Journal of Central Banking, vol. 12(3), pages 291-344, September.
    13. Kohonen, Anssi, 2013. "On detection of volatility spillovers in overlapping stock markets," Journal of Empirical Finance, Elsevier, vol. 22(C), pages 140-158.
    14. Lanne, Markku & Meitz, Mika & Saikkonen, Pentti, 2017. "Identification and estimation of non-Gaussian structural vector autoregressions," Journal of Econometrics, Elsevier, vol. 196(2), pages 288-304.
    15. Etienne, Xiaoli L. & Irwin, Scott H. & Garcia, Philip, 2013. "Dissecting Corn Price Movements with Directed Acyclic Graphs," 2013 Annual Meeting, August 4-6, 2013, Washington, D.C. 151279, Agricultural and Applied Economics Association.
    16. Cross, Jamie & Nguyen, Bao H., 2017. "The relationship between global oil price shocks and China's output: A time-varying analysis," Energy Economics, Elsevier, vol. 62(C), pages 79-91.
    17. Efstathios Polyzos & Costas Siriopoulos, 2024. "Autoregressive Random Forests: Machine Learning and Lag Selection for Financial Research," Computational Economics, Springer;Society for Computational Economics, vol. 64(1), pages 225-262, July.
    18. repec:rza:wpaper:704 is not listed on IDEAS
    19. Helmut Lütkepohl, 2013. "Vector autoregressive models," Chapters, in: Nigar Hashimzade & Michael A. Thornton (ed.), Handbook of Research Methods and Applications in Empirical Macroeconomics, chapter 6, pages 139-164, Edward Elgar Publishing.
    20. Amine Ben Amar, 2022. "On the role of Islamic banks in the monetary policy transmission in Saudi Arabia," Eurasian Economic Review, Springer;Eurasia Business and Economics Society, vol. 12(1), pages 55-94, March.
    21. Yin, Libo & Ma, Xiyuan, 2018. "Causality between oil shocks and exchange rate: A Bayesian, graph-based VAR approach," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 508(C), pages 434-453.

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;

    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:jbl:ref000:v:6:y:2022:i:2:id:192. 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: Anna Bogajewska-Szymańska (email available below). General contact details of provider: https://journals.ue.poznan.pl/REF .

    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.