IDEAS home Printed from https://ideas.repec.org/p/ihs/ihsesp/232.html
   My bibliography  Save this paper

Catching Growth Determinants with the Adaptive LASSO

Author

Listed:
  • Schneider, Ulrike

    (Department of Statistics, University of Vienna, Vienna, Austria)

  • Wagner, Martin

    (Department of Economics and Finance, Institute for Advanced Studies, Vienna, Austria)

Abstract

This paper uses the adaptive LASSO estimator to determine the variables important for economic growth. The adaptive LASSO estimator is a computationally very simple procedure that performs at the same time both consistent parameter estimation and model selection. The methodology is applied to three data sets, the data used in Sala-i-Martin et al. (2004), in Fernandez et al. (2001) and a data set for the regions in the European Union. The results for the former two data sets are very similar in many respects to those found in the published papers, yet are obtained at a tiny fraction of computational cost. Furthermore, the results for the regional data highlight the importance of human capital for economic growth.

Suggested Citation

  • Schneider, Ulrike & Wagner, Martin, 2008. "Catching Growth Determinants with the Adaptive LASSO," Economics Series 232, Institute for Advanced Studies.
  • Handle: RePEc:ihs:ihsesp:232
    as

    Download full text from publisher

    File URL: https://irihs.ihs.ac.at/id/eprint/1878
    File Function: First version, 2008
    Download Restriction: no
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. Zou, Hui, 2006. "The Adaptive Lasso and Its Oracle Properties," Journal of the American Statistical Association, American Statistical Association, vol. 101, pages 1418-1429, December.
    2. Kevin D. Hoover & Stephen J. Perez, 2004. "Truth and Robustness in Cross‐country Growth Regressions," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 66(5), pages 765-798, December.
    3. Pötscher, Benedikt M. & Schneider, Ulrike, 2007. "On the distribution of the adaptive LASSO estimator," MPRA Paper 6913, University Library of Munich, Germany.
    4. Durlauf, Steven N. & Johnson, Paul A. & Temple, Jonathan R.W., 2005. "Growth Econometrics," Handbook of Economic Growth, in: Philippe Aghion & Steven Durlauf (ed.),Handbook of Economic Growth, edition 1, volume 1, chapter 8, pages 555-677, Elsevier.
    5. Magnus, J.R. & Powell, O.R. & Prüfer, P., 2008. "A Comparison of Two Averaging Techniques with an Application to Growth Empirics," Other publications TiSEM 0392dffa-51e0-4bc9-9644-f, Tilburg University, School of Economics and Management.
    6. Leeb, Hannes & Potscher, Benedikt M., 2008. "Sparse estimators and the oracle property, or the return of Hodges' estimator," Journal of Econometrics, Elsevier, vol. 142(1), pages 201-211, January.
    7. Carmen Fernandez & Eduardo Ley & Mark F. J. Steel, 2001. "Model uncertainty in cross-country growth regressions," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 16(5), pages 563-576.
    8. Robert J. Barro, 1991. "Economic Growth in a Cross Section of Countries," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 106(2), pages 407-443.
    9. N. Gregory Mankiw & David Romer & David N. Weil, 1992. "A Contribution to the Empirics of Economic Growth," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 107(2), pages 407-437.
    10. David F. Hendry & Hans‐Martin Krolzig, 2004. "We Ran One Regression," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 66(5), pages 799-810, December.
    11. David F. Hendry & Hans-Martin Krolzig, 2004. "We Ran One Regression," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 66(5), pages 799-810, December.
    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. Christoph Hanck, 2016. "I just ran two trillion regressions," Economics Bulletin, AccessEcon, vol. 36(4), pages 2037-2042.
    2. Ofori, Isaac Kwesi, 2021. "Catching The Drivers of Inclusive Growth in Sub-Saharan Africa: An Application of Machine Learning," EconStor Preprints 235482, ZBW - Leibniz Information Centre for Economics.
    3. Piotr Wójcik & Bartłomiej Wieczorek, 2020. "We have just explained real convergence factors using machine learning," Working Papers 2020-38, Faculty of Economic Sciences, University of Warsaw.
    4. Savin Ivan, 2013. "A Comparative Study of the Lasso-type and Heuristic Model Selection Methods," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 233(4), pages 526-549, August.
    5. Isaac K. Ofori & Camara K. Obeng & Simplice A. Asongu, 2022. "What Really Drives Economic Growth in Sub-Saharan Africa? Evidence from The Lasso Regularization and Inferential Techniques," Working Papers of the African Governance and Development Institute. 22/061, African Governance and Development Institute..
    6. Krüger, Jens J. & Rhiel, Mathias, 2016. "Determinants of ICT infrastructure: A cross-country statistical analysis," Darmstadt Discussion Papers in Economics 228, Darmstadt University of Technology, Department of Law and Economics.
    7. Marcos Sanso-Navarro & María Vera-Cabello, 2015. "Non-linearities in regional growth: A non-parametric approach," Papers in Regional Science, Wiley Blackwell, vol. 94, pages 19-38, November.
    8. Martin Wagner & Achim Zeileis, 2019. "Heterogeneity and Spatial Dependence of Regional Growth in the EU: A Recursive Partitioning Approach," German Economic Review, Verein für Socialpolitik, vol. 20(1), pages 67-82, February.
    9. Martin Wagner & Achim Zeileis, 2012. "Heterogeneity of Regional Growth in the European Union," Working Papers 2012-20, Faculty of Economics and Statistics, Universität Innsbruck.
    10. Hajek, Petr & Henriques, Roberto & Hajkova, Veronika, 2014. "Visualising components of regional innovation systems using self-organizing maps—Evidence from European regions," Technological Forecasting and Social Change, Elsevier, vol. 84(C), pages 197-214.
    11. Wagner Martin & Hlouskova Jaroslava, 2015. "Growth Regressions, Principal Components Augmented Regressions and Frequentist Model Averaging," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 235(6), pages 642-662, December.
    12. Gross, Marco, 2011. "Corporate bond spreads and real activity in the euro area - Least Angle Regression forecasting and the probability of the recession," Working Paper Series 1286, European Central Bank.
    13. Ofori, Isaac K. & Quaidoo, Christopher & Ofori, Pamela E., 2021. "What Drives Financial Sector Development in Africa? Insights from Machine Learning," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, issue forthcomi.
    14. Jesus regstdpo-Cuaresma & Neil Foster & Robert Stehrer, 2011. "Determinants of Regional Economic Growth by Quantile," Regional Studies, Taylor & Francis Journals, vol. 45(6), pages 809-826.
    15. Jaroslava Hlouskova & Martin Wagner, 2013. "The Determinants of Long-Run Economic Growth: A Conceptually and Computationally Simple Approach," Swiss Journal of Economics and Statistics (SJES), Swiss Society of Economics and Statistics (SSES), vol. 149(IV), pages 445-492, December.
    16. Ning Xu & Jian Hong & Timothy C. G. Fisher, 2016. "Model selection consistency from the perspective of generalization ability and VC theory with an application to Lasso," Papers 1606.00142, arXiv.org.
    17. Wagner, Martin & Hlouskova, Jaroslava, 2009. "Growth Regressions, Principal Components and Frequentist Model Averaging," Economics Series 236, Institute for Advanced Studies.
    18. Crespo Cuaresma, Jesus & Grün, Bettina & Hofmarcher, Paul & Humer, Stefan & Moser, Mathias, 2016. "Unveiling covariate inclusion structures in economic growth regressions using latent class analysis," European Economic Review, Elsevier, vol. 81(C), pages 189-202.

    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. Wagner, Martin & Hlouskova, Jaroslava, 2009. "Growth Regressions, Principal Components and Frequentist Model Averaging," Economics Series 236, Institute for Advanced Studies.
    2. Mark F. J. Steel, 2020. "Model Averaging and Its Use in Economics," Journal of Economic Literature, American Economic Association, vol. 58(3), pages 644-719, September.
    3. Steven N. Durlauf & Andros Kourtellos & Chih Ming Tan, 2008. "Empirics of Growth and Development," Chapters, in: Amitava Krishna Dutt & Jaime Ros (ed.), International Handbook of Development Economics, Volumes 1 & 2, volume 0, chapter 3, Edward Elgar Publishing.
    4. Melisa Chanegriha & Chris Stewart & Christopher Tsoukis, 2017. "Identifying the robust economic, geographical and political determinants of FDI: an Extreme Bounds Analysis," Empirical Economics, Springer, vol. 52(2), pages 759-776, March.
    5. R Burger & S du Plessis, 2011. "Examining the Robustness of Competing Explanations of Slow Growth in African Countries," Studies in Economics and Econometrics, Taylor & Francis Journals, vol. 35(3), pages 21-47, December.
    6. John Knight & Sai Ding, 2008. "Why has China Grown so Fast? The Role of Structural Change," Economics Series Working Papers 415, University of Oxford, Department of Economics.
    7. Ulaşan, Bülent, 2011. "Cross-country growth empirics and model uncertainty: An overview," Economics Discussion Papers 2011-37, Kiel Institute for the World Economy (IfW Kiel).
    8. Magnus, Jan R. & Powell, Owen & Prüfer, Patricia, 2010. "A comparison of two model averaging techniques with an application to growth empirics," Journal of Econometrics, Elsevier, vol. 154(2), pages 139-153, February.
    9. Rup Singh, 2015. "Forces of economic growth in China, India, and other Asian countries," Asian-Pacific Economic Literature, The Crawford School, The Australian National University, vol. 29(1), pages 62-81, May.
    10. Ulaşan, Bülent, 2012. "Cross-country growth empirics and model uncertainty: An overview," Economics - The Open-Access, Open-Assessment E-Journal (2007-2020), Kiel Institute for the World Economy (IfW Kiel), vol. 6, pages 1-69.
    11. Peter Jensen, 2010. "Testing the null of a low dimensional growth model," Empirical Economics, Springer, vol. 38(1), pages 193-215, February.
    12. Jaroslava Hlouskova & Martin Wagner, 2013. "The Determinants of Long-Run Economic Growth: A Conceptually and Computationally Simple Approach," Swiss Journal of Economics and Statistics (SJES), Swiss Society of Economics and Statistics (SSES), vol. 149(IV), pages 445-492, December.
    13. Antonio Ciccone & Marek Jarociński, 2010. "Determinants of Economic Growth: Will Data Tell?," American Economic Journal: Macroeconomics, American Economic Association, vol. 2(4), pages 222-246, October.
    14. Sai Ding & John Knight, 2011. "Why has China Grown So Fast? The Role of Physical and Human Capital Formation," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 73(2), pages 141-174, April.
    15. Altinok, Nadir & Aydemir, Abdurrahman, 2017. "Does one size fit all? The impact of cognitive skills on economic growth," Journal of Macroeconomics, Elsevier, vol. 53(C), pages 176-190.
    16. Derek Headey, 2008. "The Principal Components of Growth in the Less Developed Countries," Kyklos, Wiley Blackwell, vol. 61(4), pages 568-598, November.
    17. Feng, Guohua & Gao, Jiti & Peng, Bin, 2022. "An integrated panel data approach to modelling economic growth," Journal of Econometrics, Elsevier, vol. 228(2), pages 379-397.
    18. Capolupo, Rosa, 2009. "The New Growth Theories and Their Empirics after Twenty Years," Economics - The Open-Access, Open-Assessment E-Journal (2007-2020), Kiel Institute for the World Economy (IfW Kiel), vol. 3, pages 1-72.
    19. Rockey, James & Temple, Jonathan, 2016. "Growth econometrics for agnostics and true believers," European Economic Review, Elsevier, vol. 81(C), pages 86-102.
    20. Jesus regstdpo-Cuaresma & Neil Foster & Robert Stehrer, 2011. "Determinants of Regional Economic Growth by Quantile," Regional Studies, Taylor & Francis Journals, vol. 45(6), pages 809-826.

    More about this item

    Keywords

    Adaptive LASSO; Economic convergence; Growth regressions; Model selection;
    All these keywords.

    JEL classification:

    • C31 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models; Quantile Regressions; Social Interaction Models
    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
    • O11 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development - - - Macroeconomic Analyses of Economic Development
    • O18 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development - - - Urban, Rural, Regional, and Transportation Analysis; Housing; Infrastructure
    • O47 - Economic Development, Innovation, Technological Change, and Growth - - Economic Growth and Aggregate Productivity - - - Empirical Studies of Economic Growth; Aggregate Productivity; Cross-Country Output Convergence

    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:ihs:ihsesp:232. 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: Doris Szoncsitz (email available below). General contact details of provider: https://edirc.repec.org/data/deihsat.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.