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Private Banking Credit and Economic Growth in Mexico: A State Level Panel Data Analysis 2005-2018

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  • Torre Cepeda Leonardo E.
  • Flores Segovia Miguel A.

Abstract

The paper investigates the effect of banking credit to private agriculture, industrial and services sectors, on per capita GDP growth in Mexico using panel data at the state level for the period 2005-2018. The estimation controls for variables related to infrastructure, public expenditure, exports, inflation, human capital, a dummy for the 2008-2009 global financial crisis, and introduces a lag of the dependent variable in order to consider its likely persistence. Using the Generalized Method of Moments in order to control for possible endogenous effects among the variables, it is estimated that a 10%increase in the ratio of banking credit to GDP increases per capita GDP growth at the state level between 0.61 and 0.81 percentage points. These results underline the relevance of policy measures designed to promote a healthy functioning of the financial system in Mexico.

Suggested Citation

  • Torre Cepeda Leonardo E. & Flores Segovia Miguel A., 2020. "Private Banking Credit and Economic Growth in Mexico: A State Level Panel Data Analysis 2005-2018," Working Papers 2020-17, Banco de México.
    • Handle: RePEc:bdm:wpaper:2020-17
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    1. D. Levy, 2002. "Cointegration in frequency domain," Journal of Time Series Analysis, Wiley Blackwell, vol. 23(3), pages 333-339, May.
    2. Marvin Goodfriend & Robert G. King, 2013. "The Great Inflation Drift," NBER Chapters, in: The Great Inflation: The Rebirth of Modern Central Banking, pages 181-209, National Bureau of Economic Research, Inc.
    3. Kilian,Lutz & Lütkepohl,Helmut, 2018. "Structural Vector Autoregressive Analysis," Cambridge Books, Cambridge University Press, number 9781107196575, January.
    4. Michael Dotsey & Shigeru Fujita & Tom Stark, 2018. "Do Phillips Curves Conditionally Help to Forecast Inflation?," International Journal of Central Banking, International Journal of Central Banking, vol. 14(4), pages 43-92, September.
    5. Thomas Sargent & Noah Williams & Tao Zha, 2009. "The Conquest of South American Inflation," Journal of Political Economy, University of Chicago Press, vol. 117(2), pages 211-256, April.
    6. Dimitris Georgoutsos & Georgios Kouretas, 2004. "A Multivariate I(2) cointegration analysis of German hyperinflation," Applied Financial Economics, Taylor & Francis Journals, vol. 14(1), pages 29-41.
    7. Benati, Luca & Lucas, Robert E. & Nicolini, Juan Pablo & Weber, Warren, 2021. "International evidence on long-run money demand," Journal of Monetary Economics, Elsevier, vol. 117(C), pages 43-63.
    8. Pagan, Adrian R & Wickens, M R, 1989. "A Survey of Some Recent Econometric Methods," Economic Journal, Royal Economic Society, vol. 99(398), pages 962-1025, December.
    9. Pedro Teles & Harald Uhlig & João Valle e Azevedo, 2016. "Is Quantity Theory Still Alive?," Economic Journal, Royal Economic Society, vol. 126(591), pages 442-464, March.
    10. Charles Engel & Kenneth D. West, 2005. "Exchange Rates and Fundamentals," Journal of Political Economy, University of Chicago Press, vol. 113(3), pages 485-517, June.
    11. James H. Stock & Mark W. Watson, 2007. "Why Has U.S. Inflation Become Harder to Forecast?," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 39(s1), pages 3-33, February.
    12. James H. Stock & Mark W. Watson, 2007. "Erratum to "Why Has U.S. Inflation Become Harder to Forecast?"," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 39(7), pages 1849-1849, October.
    13. Jennifer Castle & David Hendry, 2007. "Forecasting UK Inflation: the Roles of Structural Breaks and Time Disaggregation," Economics Series Working Papers 309, University of Oxford, Department of Economics.
    14. Campbell, John Y & Shiller, Robert J, 1987. "Cointegration and Tests of Present Value Models," Journal of Political Economy, University of Chicago Press, vol. 95(5), pages 1062-1088, October.
    15. Julia Campos & Neil R. Ericsson, 1999. "Contructive data mining: modeling consumers' expenditure in Venezuela," Econometrics Journal, Royal Economic Society, vol. 2(2), pages 226-240.
    16. Hatanaka, Michio, 1996. "Time-Series-Based Econometrics: Unit Roots and Co-integrations," OUP Catalogue, Oxford University Press, number 9780198773535.
    17. Hendry, David F & Ericsson, Neil R, 1991. "An Econometric Analysis of U.K. Money Demand in 'Monetary Trends in the United States and the United Kingdom' by Milton Friedman and Anna Schwartz," American Economic Review, American Economic Association, vol. 81(1), pages 8-38, March.
    18. Granger, C. W. J. & Newbold, P., 1974. "Spurious regressions in econometrics," Journal of Econometrics, Elsevier, vol. 2(2), pages 111-120, July.
    19. Marco Del Negro & Marc P. Giannoni & Frank Schorfheide, 2015. "Inflation in the Great Recession and New Keynesian Models," American Economic Journal: Macroeconomics, American Economic Association, vol. 7(1), pages 168-196, January.
    20. Sargent, Thomas J & Wallace, Neil, 1973. "Rational Expectations and the Dynamics of Hyperinflation," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 14(2), pages 328-350, June.
    21. 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.
    22. Toda, Hiro Y. & Yamamoto, Taku, 1995. "Statistical inference in vector autoregressions with possibly integrated processes," Journal of Econometrics, Elsevier, vol. 66(1-2), pages 225-250.
    23. Juselius, Katarina, 2006. "The Cointegrated VAR Model: Methodology and Applications," OUP Catalogue, Oxford University Press, number 9780199285679.
    24. James H. Stock & Mark W. Watson, 2007. "Erratum to “Why Has U.S. Inflation Become Harder to Forecast?”," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 39(7), pages 1849-1849, October.
    25. Barro, Robert J, 1979. "Money and the Price Level under the Gold Standard," Economic Journal, Royal Economic Society, vol. 89(353), pages 13-33, March.
    26. Ball, Laurence, 2012. "Short-run money demand," Journal of Monetary Economics, Elsevier, vol. 59(7), pages 622-633.
    27. Lawrence J. Christiano, 1989. "P*: not the inflation forecaster's holy grail," Quarterly Review, Federal Reserve Bank of Minneapolis, vol. 13(Fall), pages 3-18.
    28. Neil R. Ericsson & James G. MacKinnon, 2002. "Distributions of error correction tests for cointegration," Econometrics Journal, Royal Economic Society, vol. 5(2), pages 285-318, June.
    29. Roberts, John M, 1995. "New Keynesian Economics and the Phillips Curve," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 27(4), pages 975-984, November.
    30. Ronald Macdonald & Mark P. Taylor, 1993. "The Monetary Approach to the Exchange Rate: Rational Expectations, Long-Run Equilibrium, and Forecasting," IMF Staff Papers, Palgrave Macmillan, vol. 40(1), pages 89-107, March.
    31. Robert J. Gordon, 2013. "The Phillips Curve is Alive and Well: Inflation and the NAIRU During the Slow Recovery," NBER Working Papers 19390, National Bureau of Economic Research, Inc.
    32. Gail E. Makinen & G. Thomas Woodward, 1988. "The Transition from Hyperinflation to Stability: Some Evidence," Eastern Economic Journal, Eastern Economic Association, vol. 14(1), pages 19-26, Jan-Mar.
    33. James H. Stock & Mark W. Watson, 2007. "Why Has U.S. Inflation Become Harder to Forecast?," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 39(s1), pages 3-33, February.
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    More about this item

    Keywords

    Banking Credit; Economic Growth; Regional Analysis; Mexico;
    All these keywords.

    JEL classification:

    • O47 - Economic Development, Innovation, Technological Change, and Growth - - Economic Growth and Aggregate Productivity - - - Empirical Studies of Economic Growth; Aggregate Productivity; Cross-Country Output Convergence
    • G21 - Financial Economics - - Financial Institutions and Services - - - Banks; Other Depository Institutions; Micro Finance Institutions; Mortgages
    • R11 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General Regional Economics - - - Regional Economic Activity: Growth, Development, Environmental Issues, and Changes
    • R15 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General Regional Economics - - - Econometric and Input-Output Models; Other Methods

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