IDEAS home Printed from https://ideas.repec.org/a/spr/stmapp/v31y2022i3d10.1007_s10260-021-00594-2.html
   My bibliography  Save this article

A comparison between VAR processes jointly modeling GDP and Unemployment rate in France and Germany

Author

Listed:
  • Francesca Di Iorio

    (Università degli Studi di Napoli Federico II)

  • Umberto Triacca

    (Università degli Studi dell’Aquila)

Abstract

Investigating the relationship between Gross Domestic Product and unemployment is one of the most important challenges in macroeconomics. In this paper, we compare French and German economies in terms of the dynamic linkage between these variables. In particular, we use an empirical methodology to investigate how much the relationship between Gross Domestic Product and unemployment growth rates are dynamically different in the two major European economies over the period 2003–2019. To this aim, a Vector Autoregressive model is specified for each country to jointly model the growth rate of the two variables. Then a new statistical test is proposed to assess the distance between the two estimated models. Results indicate that the dynamic linkage between Gross Domestic Product and unemployment is very similar in the two countries. This empirical evidence does not imply identical product and labor markets in France and Germany, but it ensures that in these markets there are common dynamics. This could favor the process of economic convergence between the two countries.

Suggested Citation

  • Francesca Di Iorio & Umberto Triacca, 2022. "A comparison between VAR processes jointly modeling GDP and Unemployment rate in France and Germany," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 31(3), pages 617-635, September.
    • Handle: RePEc:spr:stmapp:v:31:y:2022:i:3:d:10.1007_s10260-021-00594-2
    DOI: 10.1007/s10260-021-00594-2
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s10260-021-00594-2
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s10260-021-00594-2?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
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Rafiq, M.S. & Mallick, S.K., 2008. "The effect of monetary policy on output in EMU3: A sign restriction approach," Journal of Macroeconomics, Elsevier, vol. 30(4), pages 1756-1791, December.
    2. Umberto Triacca, 2016. "Measuring the Distance between Sets of ARMA Models," Econometrics, MDPI, vol. 4(3), pages 1-11, July.
    3. Ilian Mihov, 2001. "Monetary policy implementation and transmission in the European Monetary Union," Economic Policy, CEPR, CESifo, Sciences Po;CES;MSH, vol. 16(33), pages 370-406.
    4. Malley, Jim & Molana, Hassan, 2008. "Output, unemployment and Okun's law: Some evidence from the G7," Economics Letters, Elsevier, vol. 101(2), pages 113-115, November.
    5. Prachowny, Martin F J, 1993. "Okun's Law: Theoretical Foundations and Revised Estimates," The Review of Economics and Statistics, MIT Press, vol. 75(2), pages 331-336, May.
    6. Caiado, Jorge & Crato, Nuno & Pena, Daniel, 2006. "A periodogram-based metric for time series classification," Computational Statistics & Data Analysis, Elsevier, vol. 50(10), pages 2668-2684, June.
    7. Zellner, Arnold & Palm, Franz, 1974. "Time series analysis and simultaneous equation econometric models," Journal of Econometrics, Elsevier, vol. 2(1), pages 17-54, May.
    8. James G. MacKinnon, 2002. "Bootstrap inference in econometrics," Canadian Journal of Economics/Revue canadienne d'économique, John Wiley & Sons, vol. 35(4), pages 615-645, November.
    9. Dimitris Christopoulos, 2004. "The relationship between output and unemployment: Evidence from Greek regions," Economics of Governance, Springer, vol. 83(3), pages 611-620, July.
    10. Sylvia Frühwirth-Schnatter, 2011. "Panel data analysis: a survey on model-based clustering of time series," Advances in Data Analysis and Classification, Springer;German Classification Society - Gesellschaft für Klassifikation (GfKl);Japanese Classification Society (JCS);Classification and Data Analysis Group of the Italian Statistical Society (CLADAG);International Federation of Classification Societies (IFCS), vol. 5(4), pages 251-280, December.
    11. Lee, Jim, 2000. "The Robustness of Okun's Law: Evidence from OECD Countries," Journal of Macroeconomics, Elsevier, vol. 22(2), pages 331-356, April.
    12. Lee, Kang-Soek & Mercurelli, Franceline, 2014. "Convergence in the Core Euro Zone under the Global Financial Crisis," Journal of Economic Integration, Center for Economic Integration, Sejong University, vol. 29, pages 20-63.
    13. Domenico Piccolo, 1990. "A Distance Measure For Classifying Arima Models," Journal of Time Series Analysis, Wiley Blackwell, vol. 11(2), pages 153-164, March.
    14. Nebot, César & Beyaert, Arielle & García-Solanes, José, 2019. "New insights into the nonlinearity of Okun's law," Economic Modelling, Elsevier, vol. 82(C), pages 202-210.
    15. Avraam Tapinos & Pedro Mendes, 2013. "A Method for Comparing Multivariate Time Series with Different Dimensions," PLOS ONE, Public Library of Science, vol. 8(2), pages 1-11, February.
    16. Jurgen A. Doornik & Henrik Hansen, 2008. "An Omnibus Test for Univariate and Multivariate Normality," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 70(s1), pages 927-939, December.
    17. Corduas, Marcella & Piccolo, Domenico, 2008. "Time series clustering and classification by the autoregressive metric," Computational Statistics & Data Analysis, Elsevier, vol. 52(4), pages 1860-1872, January.
    18. Di Iorio, Francesca & Triacca, Umberto, 2013. "Testing for Granger non-causality using the autoregressive metric," Economic Modelling, Elsevier, vol. 33(C), pages 120-125.
    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. Umberto Triacca, 2016. "Measuring the Distance between Sets of ARMA Models," Econometrics, MDPI, vol. 4(3), pages 1-11, July.
    2. Durech, Richard & Minea, Alexandru & Mustea, Lavinia & Slusna, Lubica, 2014. "Regional evidence on Okun's Law in Czech Republic and Slovakia," Economic Modelling, Elsevier, vol. 42(C), pages 57-65.
    3. Elhorst, J. Paul & Emili, Silvia, 2022. "A spatial econometric multivariate model of Okun's law," Regional Science and Urban Economics, Elsevier, vol. 93(C).
    4. Francesca Di Iorio & Umberto Triacca, 2014. "Testing for A Set of Linear Restrictions in VARMA Models Using Autoregressive Metric: An Application to Granger Causality Test," Econometrics, MDPI, vol. 2(4), pages 1-14, December.
    5. Revoredo-Giha, Cesar & Leat, Philip M.K. & Renwick, Alan W., 2012. "The relationship between output and unemployment in Scotland: A regional analysis," Working Papers 131465, Scotland's Rural College (formerly Scottish Agricultural College), Land Economy & Environment Research Group.
    6. Shabir Mohsin Hashmi & Ali Gul Khushik & Muhammad Akram Gilal & Zhao Yongliang, 2021. "The Impact of GDP and Its Expenditure Components on Unemployment Within BRICS Countries: Evidence of Okun’s Law From Aggregate and Disaggregated Approaches," SAGE Open, , vol. 11(2), pages 21582440211, June.
    7. Celia Melguizo, 2017. "An analysis of Okun’s law for the Spanish provinces," Review of Regional Research: Jahrbuch für Regionalwissenschaft, Springer;Gesellschaft für Regionalforschung (GfR), vol. 37(1), pages 59-90, February.
    8. Mahmoudi, Mohammad Reza, 2021. "A computational technique to classify several fractional Brownian motion processes," Chaos, Solitons & Fractals, Elsevier, vol. 150(C).
    9. De Gregorio, Alessandro & Maria Iacus, Stefano, 2010. "Clustering of discretely observed diffusion processes," Computational Statistics & Data Analysis, Elsevier, vol. 54(2), pages 598-606, February.
    10. Mohammed, Mikidadu, 2018. "Do Import Tariffs Generate Stagflationary Tendencies?," MPRA Paper 95128, University Library of Munich, Germany, revised 09 Apr 2019.
    11. Sonia Díaz & José Vilar, 2010. "Comparing Several Parametric and Nonparametric Approaches to Time Series Clustering: A Simulation Study," Journal of Classification, Springer;The Classification Society, vol. 27(3), pages 333-362, November.
    12. Bod’a, Martin & Považanová, Mariana, 2021. "Output-unemployment asymmetry in Okun coefficients for OECD countries," Economic Analysis and Policy, Elsevier, vol. 69(C), pages 307-323.
    13. Di Iorio, Francesca & Triacca, Umberto, 2013. "Testing for Granger non-causality using the autoregressive metric," Economic Modelling, Elsevier, vol. 33(C), pages 120-125.
    14. Bande, Roberto & Martín-Román, Ángel, 2018. "Regional differences in the Okun’s Relationship: New Evidence for Spain (1980-2015)," INVESTIGACIONES REGIONALES - Journal of REGIONAL RESEARCH, Asociación Española de Ciencia Regional, issue 41, pages 137-165.
    15. Pierpaolo D’Urso & Livia Giovanni & Riccardo Massari & Dario Lallo, 2013. "Noise fuzzy clustering of time series by autoregressive metric," METRON, Springer;Sapienza Università di Roma, vol. 71(3), pages 217-243, November.
    16. E. Otranto, 2011. "Classification of Volatility in Presence of Changes in Model Parameters," Working Paper CRENoS 201113, Centre for North South Economic Research, University of Cagliari and Sassari, Sardinia.
    17. PERUGINI, Cristiano, 2009. "Employment Intensity Of Growth In Italy. A Note Using Regional Data," Regional and Sectoral Economic Studies, Euro-American Association of Economic Development, vol. 9(1).
    18. Koutroulis, Aristotelis & Panagopoulos, Yannis & Tsouma, Ekaterini, 2016. "Asymmetry in the response of unemployment to output changes in Greece: Evidence from hidden co-integration," The Journal of Economic Asymmetries, Elsevier, vol. 13(C), pages 81-88.
    19. Liu, Shen & Maharaj, Elizabeth Ann, 2013. "A hypothesis test using bias-adjusted AR estimators for classifying time series in small samples," Computational Statistics & Data Analysis, Elsevier, vol. 60(C), pages 32-49.
    20. Otranto, Edoardo, 2008. "Clustering heteroskedastic time series by model-based procedures," Computational Statistics & Data Analysis, Elsevier, vol. 52(10), pages 4685-4698, June.

    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:spr:stmapp:v:31:y:2022:i:3:d:10.1007_s10260-021-00594-2. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    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.