IDEAS home Printed from https://ideas.repec.org/p/aep/anales/4660.html
   My bibliography  Save this paper

Regresiones SUR Espaciales. Análisis espacio-temporal del empleo sectorial en Argentina

Author

Listed:
  • Herrera Gomez Marcos
  • Fernández Pablo

Abstract

La creciente disponibilidad de datos multidimensionales que incluyen espacio y tiempo ha generado una alta demanda de herramientas específicas, como las desarrolladas desde la econometría espacial. En este trabajo revisamos los modelos SUR espaciales, pocos frecuentes en Economía, para estimar modelos multiecuacionales complejos. Los SUR espaciales permiten analizar la estructura espacio-temporal más allá de los modelos espaciales de datos de panel. Utilizando información a nivel sectorial del mercado laboral, agregada a nivel provincia y por periodos trimestrales previos y posteriores a la pandemia COVID-19, se ejemplifica la dinámica espacial entre sectores y la dinámica espacio-temporal intrasectorial. Nuestros resultados destacan que el empleo privado presenta una significativa pero heterogénea dependencia espacial entre sectores y patrones de dependencia espacio-temporal con diferentes dinámicas entre periodos previos y posteriores a la declaración de la pandemia, particularmente en el sector agropecuario.

Suggested Citation

  • Herrera Gomez Marcos & Fernández Pablo, 2023. "Regresiones SUR Espaciales. Análisis espacio-temporal del empleo sectorial en Argentina," Asociación Argentina de Economía Política: Working Papers 4660, Asociación Argentina de Economía Política.
  • Handle: RePEc:aep:anales:4660
    as

    Download full text from publisher

    File URL: https://aaep.org.ar/works/works2023/4660.pdf
    Download Restriction: no
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. Alexander Chudik & M. Hashem Pesaran, 2016. "Theory And Practice Of Gvar Modelling," Journal of Economic Surveys, Wiley Blackwell, vol. 30(1), pages 165-197, February.
    2. Natalia Bailey & George Kapetanios & M. Hashem Pesaran, 2016. "Exponent of Cross‐Sectional Dependence: Estimation and Inference," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 31(6), pages 929-960, September.
    3. Elena Semerikova, 2015. "Spatial Patterns of German Labor Market: Panel Data Analysis of Regional Unemployment," AIEL Series in Labour Economics, in: Chiara Mussida & Francesco Pastore (ed.), Geographical Labor Market Imbalances, edition 127, chapter 0, pages 37-64, Springer.
    4. Kondo, Keisuke, 2015. "Spatial persistence of Japanese unemployment rates," Japan and the World Economy, Elsevier, vol. 36(C), pages 113-122.
    5. M. Hashem Pesaran, 2006. "Estimation and Inference in Large Heterogeneous Panels with a Multifactor Error Structure," Econometrica, Econometric Society, vol. 74(4), pages 967-1012, July.
    6. Badi Baltagi & Alain Pirotte, 2011. "Seemingly unrelated regressions with spatial error components," Empirical Economics, Springer, vol. 40(1), pages 5-49, February.
    7. J. Paul Elhorst & Marco Gross & Eugen Tereanu, 2021. "Cross‐Sectional Dependence And Spillovers In Space And Time: Where Spatial Econometrics And Global Var Models Meet," Journal of Economic Surveys, Wiley Blackwell, vol. 35(1), pages 192-226, February.
    8. Laura Helena KIVI & Tiiu PAAS, 2021. "Spatial interactions of employment in European labour markets," Eastern Journal of European Studies, Centre for European Studies, Alexandru Ioan Cuza University, vol. 12, pages 196-211, August.
    9. Valter Di Giacinto, 2006. "A Generalized Space-Time ARMA Model with an Application to Regional Unemployment Analysis in Italy," International Regional Science Review, , vol. 29(2), pages 159-198, April.
    10. Kapetanios, G. & Pesaran, M. Hashem & Yamagata, T., 2011. "Panels with non-stationary multifactor error structures," Journal of Econometrics, Elsevier, vol. 160(2), pages 326-348, February.
    11. Jesús Mur & Fernando López & Marcos Herrera, 2010. "Testing for Spatial Effects in Seemingly Unrelated Regressions," Spatial Economic Analysis, Taylor & Francis Journals, vol. 5(4), pages 399-440.
    12. Maria Francesca Cracolici & Miranda Cuffaro & Peter Nijkamp, 2007. "Geographical Distribution of Unemployment: An Analysis of Provincial Differences in Italy," Growth and Change, Wiley Blackwell, vol. 38(4), pages 649-670, December.
    13. Solmaria Halleck Vega & J. Paul Elhorst, 2014. "Modelling regional labour market dynamics in space and time," Papers in Regional Science, Wiley Blackwell, vol. 93(4), pages 819-841, November.
    14. Conley, Timothy G. & Molinari, Francesca, 2007. "Spatial correlation robust inference with errors in location or distance," Journal of Econometrics, Elsevier, vol. 140(1), pages 76-96, September.
    15. Valter Di Giacinto, 2003. "Differential Regional Effects of Monetary Policy: A Geographical SVAR Approach," International Regional Science Review, , vol. 26(3), pages 313-341, July.
    16. Baltagi, Badi H. & Bresson, Georges, 2011. "Maximum likelihood estimation and Lagrange multiplier tests for panel seemingly unrelated regressions with spatial lag and spatial errors: An application to hedonic housing prices in Paris," Journal of Urban Economics, Elsevier, vol. 69(1), pages 24-42, January.
    17. Pesaran, M. Hashem & Tosetti, Elisa, 2011. "Large panels with common factors and spatial correlation," Journal of Econometrics, Elsevier, vol. 161(2), pages 182-202, April.
    18. Alexander Chudik & M. Hashem Pesaran & Elisa Tosetti, 2011. "Weak and strong cross‐section dependence and estimation of large panels," Econometrics Journal, Royal Economic Society, vol. 14(1), pages 45-90, February.
    19. J. Paul Elhorst, 2003. "Specification and Estimation of Spatial Panel Data Models," International Regional Science Review, , vol. 26(3), pages 244-268, July.
    20. Mur, Jesús & Angulo, Ana, 2009. "Model selection strategies in a spatial setting: Some additional results," Regional Science and Urban Economics, Elsevier, vol. 39(2), pages 200-213, March.
    21. Kelejian, Harry H. & Prucha, Ingmar R., 2004. "Estimation of simultaneous systems of spatially interrelated cross sectional equations," Journal of Econometrics, Elsevier, vol. 118(1-2), pages 27-50.
    22. Anselin, Luc & Bera, Anil K. & Florax, Raymond & Yoon, Mann J., 1996. "Simple diagnostic tests for spatial dependence," Regional Science and Urban Economics, Elsevier, vol. 26(1), pages 77-104, February.
    23. Xiaokun Wang & Kara Kockelman, 2007. "Specification and estimation of a spatially and temporally autocorrelated seemingly unrelated regression model: application to crash rates in China," Transportation, Springer, vol. 34(3), pages 281-300, May.
    24. Maarten A. Allers & J. Paul Elhorst, 2011. "A Simultaneous Equations Model Of Fiscal Policy Interactions," Journal of Regional Science, Wiley Blackwell, vol. 51(2), pages 271-291, May.
    25. Elhorst, J. Paul, 2008. "Serial and spatial error correlation," Economics Letters, Elsevier, vol. 100(3), pages 422-424, September.
    26. M. Hashem Pesaran, 2015. "Testing Weak Cross-Sectional Dependence in Large Panels," Econometric Reviews, Taylor & Francis Journals, vol. 34(6-10), pages 1089-1117, December.
    27. Conley, T. G., 1999. "GMM estimation with cross sectional dependence," Journal of Econometrics, Elsevier, vol. 92(1), pages 1-45, September.
    28. repec:hal:journl:peer-00796743 is not listed on IDEAS
    29. Hsiao,Cheng, 2022. "Analysis of Panel Data," Cambridge Books, Cambridge University Press, number 9781009060752, October.
    30. Michael Beenstock & Daniel Felsenstein, 2019. "The Econometric Analysis of Non-Stationary Spatial Panel Data," Advances in Spatial Science, Springer, number 978-3-030-03614-0.
    31. Hsiao,Cheng, 2022. "Analysis of Panel Data," Cambridge Books, Cambridge University Press, number 9781316512104, October.
    32. Fernando A. López & Pedro J. Martínez-Ortiz & Juan-Gabriel Cegarra-Navarro, 2017. "Spatial spillovers in public expenditure on a municipal level in Spain," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 58(1), pages 39-65, January.
    33. Bera, Anil K. & Yoon, Mann J., 1993. "Specification Testing with Locally Misspecified Alternatives," Econometric Theory, Cambridge University Press, vol. 9(4), pages 649-658, August.
    34. Hubert Jayet & Julie Le Gallo & Luc Anselin, 2008. "Spatial Econometrics and Panel Data Models," Post-Print hal-02389412, HAL.
    35. Lee, Lung-fei & Yu, Jihai, 2010. "Some recent developments in spatial panel data models," Regional Science and Urban Economics, Elsevier, vol. 40(5), pages 255-271, September.
    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. Fernando López & Jesús Mur & Ana Angulo, 2014. "Spatial model selection strategies in a SUR framework. The case of regional productivity in EU," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 53(1), pages 197-220, August.
    2. Jesús Mur & Fernando López & Marcos Herrera, 2010. "Testing for Spatial Effects in Seemingly Unrelated Regressions," Spatial Economic Analysis, Taylor & Francis Journals, vol. 5(4), pages 399-440.
    3. Debarsy, Nicolas & Ertur, Cem, 2010. "Testing for spatial autocorrelation in a fixed effects panel data model," Regional Science and Urban Economics, Elsevier, vol. 40(6), pages 453-470, November.
    4. Cynthia Fan Yang, 2021. "Common factors and spatial dependence: an application to US house prices," Econometric Reviews, Taylor & Francis Journals, vol. 40(1), pages 14-50, January.
    5. Cem Ertur & Antonio Musolesi, 2014. "Dépendance individuelle forte et faible : une analyse en données de panel de la diffusion internationale de la technologie," Working Papers halshs-01015208, HAL.
    6. Philip Kerner & Torben Klarl & Tobias Wendler, 2021. "Green Technologies, Environmental Policy and Regional Growth," Bremen Papers on Economics & Innovation 2104, University of Bremen, Faculty of Business Studies and Economics.
    7. Halleck Vega, Solmaria & Elhorst, J. Paul, 2016. "A regional unemployment model simultaneously accounting for serial dynamics, spatial dependence and common factors," Regional Science and Urban Economics, Elsevier, vol. 60(C), pages 85-95.
    8. Alexander Chudik & M. Hashem Pesaran, 2013. "Large panel data models with cross-sectional dependence: a survey," Globalization Institute Working Papers 153, Federal Reserve Bank of Dallas.
    9. Elhorst, J. Paul & Emili, Silvia, 2022. "A spatial econometric multivariate model of Okun's law," Regional Science and Urban Economics, Elsevier, vol. 93(C).
    10. Lina Lu, 2017. "Simultaneous Spatial Panel Data Models with Common Shocks," Supervisory Research and Analysis Working Papers RPA 17-3, Federal Reserve Bank of Boston.
    11. Román Mínguez & Roberto Basile & María Durbán, 2020. "An alternative semiparametric model for spatial panel data," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 29(4), pages 669-708, December.
    12. Luc Anselin, 2010. "Thirty years of spatial econometrics," Papers in Regional Science, Wiley Blackwell, vol. 89(1), pages 3-25, March.
    13. R. Golinelli & I. Mammi & A. Musolesi, 2018. "Parameter heterogeneity, persistence and cross-sectional dependence: new insights on fiscal policy reaction functions for the Euro area," Working Papers wp1120, Dipartimento Scienze Economiche, Universita' di Bologna.
    14. Fernando A. López & Román Mínguez & Jesús Mur, 2020. "ML versus IV estimates of spatial SUR models: evidence from the case of Airbnb in Madrid urban area," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 64(2), pages 313-347, April.
    15. Ciccarelli, Carlo & Elhorst, J.Paul, 2018. "A dynamic spatial econometric diffusion model with common factors: The rise and spread of cigarette consumption in Italy," Regional Science and Urban Economics, Elsevier, vol. 72(C), pages 131-142.
    16. Giuseppe Arbia, 2011. "A Lustrum of SEA: Recent Research Trends Following the Creation of the Spatial Econometrics Association (2007--2011)," Spatial Economic Analysis, Taylor & Francis Journals, vol. 6(4), pages 377-395, July.
    17. Chi-Young Choi & Alexander Chudik, 2017. "Geographic Inequality of Economic Well-being among U.S. Cities: Evidence from Micro Panel Data," Globalization Institute Working Papers 330, Federal Reserve Bank of Dallas.
    18. Cem Ertur & Antonio Musolesi, 2017. "Weak and Strong Cross‐Sectional Dependence: A Panel Data Analysis of International Technology Diffusion," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 32(3), pages 477-503, April.
    19. Burridge, Peter & Iacone, Fabrizio & Lazarová, Štěpána, 2015. "Spatial effects in a common trend model of US city-level CPI," Regional Science and Urban Economics, Elsevier, vol. 54(C), pages 87-98.
    20. Baltagi, Badi H. & Feng, Qu & Kao, Chihwa, 2016. "Estimation of heterogeneous panels with structural breaks," Journal of Econometrics, Elsevier, vol. 191(1), pages 176-195.

    More about this item

    JEL classification:

    • C33 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Models with Panel Data; Spatio-temporal Models
    • R23 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Household Analysis - - - Regional Migration; Regional Labor Markets; Population

    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:aep:anales:4660. 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: Juan Manuel Quintero (email available below). General contact details of provider: https://edirc.repec.org/data/aaeppea.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.