Does the use of a big data variable improve monetary policy estimates? Evidence from Mexico

Authors

  • Luis Alberto Delgado-de-la-Garza Departamento de Economía, Universidad de Monterrey (UDEM, Mexico)
  • Gonzalo Adolfo Garza-Rodríguez Departamento de Economía, Universidad de Monterrey (UDEM, Mexico)
  • Daniel Alejandro Jacques-Osuna Departamento de Economía, Universidad de Monterrey (UDEM, Mexico)
  • Alejandro Múgica-Lara Departamento de Economía, Universidad de Monterrey (UDEM, Mexico)
  • Carlos Alberto Carrasco Departamento de Economía, Universidad de Monterrey (UDEM, Mexico) http://orcid.org/0000-0002-5439-4960

DOI:

https://doi.org/10.17811/ebl.10.4.2021.383-393

Abstract

We analyse the performance improvement on a monetary policy model of introducing non-conventional market attention (NCMA) indices generated using big data. To address this aim, we extracted top keywords by text mining Banco de Mexico’s minutes. Then, we used Google search information according to the top keywords and related queries to generate NCMA indices. Finally, we introduce as covariates the NCMA indices into a bivariate probit model of monetary policy and contrast several specifications to examine the improvement in the model estimates. Our results show evidence of the statistical significance of the NCMA indices where the expanded model performed better than models only including conventional economic and financial variables.

Author Biography

Carlos Alberto Carrasco, Departamento de Economía, Universidad de Monterrey (UDEM, Mexico)

Associate Professor of Economics, Departamento de Economía, Universidad de Monterrey (UDEM, Mexico) and member of the National System of Researcher (SNI-CONACyT, Mexico)

References

Abdi, H. and Williams, L.J. (2010) Principal component analysis, Wiley Interdisciplinary Reviews Computational Statistics, 2(4), 433-459.

Armah, N. (2013) Big Data Analysis: The Next Frontier, Bank of Canada Review, Summer, 32-39.

Avdjiev, S., and Zeng, Z. (2014) Credit Growth, Monetary Policy, and Economic Activity in a Three-Regime TVAR Model, Applied Economics, 46(24), 2936-2951.

Baghestani, H., and Danila, L. (2014) Interest rate and exchange rate forecasting in the Czech Republic: Do analysts know better than a random walk? Finance a Uver - Czech Journal of Economics and Finance, 64(4), 282-295.

Barro, R.J. and Gordon, D.B. (1983) Rules, discretion and reputation in a model of monetary policy, Journal of Monetary Economics, 12(1), 101-121.

Bjørnland, H., and Halvorsen, J. (2014) How does Monetary Policy Respond to Exchange Rate Movements? New International Evidence, Oxford Bulletin of Economics and Statistics, 76(2), 208-232.

Carrasco, C. A. and Ferreiro, J. (2013) Inflation Targeting and Inflation Expectations in Mexico, Applied Economics, 45(23), pp. 3295-3304.

Chague, F., De-Losso, R., Giovannetti, B., and Manoel, P. (2015) Central Bank Communication Affects the Term-Structure of Interest Rates, Revista Brasileira de Economia, 69(2), 147–162.

Choi, H., and Varian, H. (2009) Predicting Initial Claims for Unemployment Benefits, Google Inc, 1-5 < https://research.google.com/archive/papers/initialclaimsUS.pdf >.

Clarida, R., Galí, J., and Gertler, M. (1999) The science of monetary policy: A new Keynesian perspective, Journal of Economic Literature, 37(4), 1661-1707.

Crespo-Cuaresma, J., Doppelhofer, G., Feldkircher, M., and Huber, F. (2016) US monetary policy in a globalized world, CESifo Working Paper Series 5826, CESifo.

Cuevas-Camarillo, A. (2003) Los determinantes de la decisión de aumentar la restricción monetaria en México, Mimeo. < http://200.74.197.135/Upload/Eventos/VIIIReunion/mexico_cuevas.pdf >

Durán-Bustamante, M., Hernandez-del Valle, A., and Ortiz-Ramírez, A. (2019) The Google Trends Effect on the behavior of the exchange rate Mexican peso - US dollar, Contaduría y Administración, 64(2), 1-14.

Hayo, B., and Neuenkirch, M. (2013) Do Federal Reserve presidents communicate with a regional bias?, Journal of Macroeconomics, 35, 62-72.

Jansen, D.-J., and De Haan, J. (2009) Has ECB Communication Been Helpful in Predicting Interest Rate Decisions? An Evaluation of the Early Years of the Economic and Monetary Union, Applied Economics, 41(16), 1995–2003.

Jung, A. (2018) Have money and credit data releases helped markets to predict the interest rate decisions of the European Central Bank?, Scottish Journal of Political Economy, 65(1), 39-67.

Lanne, M., and Nyberg, H. (2016) Generalized Forecast Error Variance Decomposition for Linear and Nonlinear Multivariate Models, Oxford Bulletin of Economics and Statistics, 78(4), 595-603.

Laopodis, N. (2006) Dynamic Interactions among the Stock Market, Federal Funds Rate, Inflation, and Economic Activity, The Financial Review, 41(4), 513-545.

Lucca, D.O., and Trebbi, F. (2009) Measuring Central Bank Communication: An Automated Approach with Application to FOMC Statements, NBER Working Paper No. 15367.

McMillan, D.G. (2009) Non-linear interest rate dynamics and forecasting: Evidence for US and Australian interest rates, International Journal of Finance and Economics, 14(2), 139-155.

Pereira, L.F. and Valls-Pereira, Pedro L. (2018) Effects of official and unofficial central bank communication on the Brazilian interest rate curve, Textos para discussão 470, FGV EESP - Escola de Economia de São Paulo, Fundação Getulio Vargas, Brazil.

Schintler, L.A. and Kulkarni, R. (2014) Big Data for Policy Analysis: The Good, The Bad, and The Ugly, Review of Policy Research, 31(4), 343-348.

Silverstovs, B., and Wochner, D. S. (2018) Google Trends and Reality: Do the Proportions Match? Appraising the Informational Value of Online Search Behavior: Evidence from Swiss Tourism Regions, Journal of Economic Behavior & Organization, 145, 1–23.

Svensson, L.E.O. (1997) Inflation forecast targeting: Implementing and monitoring inflation targets, European Economic Review, 41(6), 1111-1146

Taylor, J. B. (1993) Discretion versus policy rules in practice, Carnegie-Rochester Conference Series on Public Policy, 39, 195-214.

Téllez-León, I. E., and Venegas, F. (2013) Principales determinantes en las decisiones de política monetaria de México: Un análisis econométrico, Estudios Económicos, 28(1), 79–108.

Wohlfarth, P. (2018) Measuring the impact of monetary policy attention on global asset volatility using search data, Economics Letters, 173, 15–18.

Downloads

Published

09-12-2021

How to Cite

Delgado-de-la-Garza, L. A., Garza-Rodríguez, G. A., Jacques-Osuna, D. A., Múgica-Lara, A., & Carrasco, C. A. (2021). Does the use of a big data variable improve monetary policy estimates? Evidence from Mexico. Economics and Business Letters, 10(4), 383–393. https://doi.org/10.17811/ebl.10.4.2021.383-393

Issue

Section

Articles