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Short-Run Forecasting of Argentine GDP Growth

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  • Marcos Dal Bianco
  • Jaime Martinez-Martín
  • Maximo Camacho

Abstract

In this paper, we propose a small-scale dynamic factor model for monitoring Argentine GDP in real time using economic data at mixed frequencies (monthly and quarterly). Our model not only produces a coincident index of the Argentine business cycle in striking accordance with professional consensus and the history of the Argentine business cycle, but also generates accurate short-run forecasts of Argentine GDP growth. By using a simulated real-time empirical evaluation, we are able to demonstrate that our model produces reliable backcasts, nowcasts and forecasts well before the official data is released.

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Bibliographic Info

Paper provided by BBVA Bank, Economic Research Department in its series Working Papers with number 1314.

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Length: 19 pages
Date of creation: Apr 2013
Date of revision:
Handle: RePEc:bbv:wpaper:1314

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Keywords: Real-time forecasting; Argentine GDP; business cycles; state-space models; mixed frequencies;

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References

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  1. S. Boragan Aruoba & Francis X. Diebold & Chiara Scotti, 2008. "Real-Time Measurement of Business Conditions," NBER Working Papers 14349, National Bureau of Economic Research, Inc.
  2. Mark Aguiar & Gita Gopinath, 2007. "Emerging Market Business Cycles: The Cycle Is the Trend," Journal of Political Economy, University of Chicago Press, vol. 115, pages 69-102.
  3. Stock, J.H. & Watson, M.W., 1989. "New Indexes Of Coincident And Leading Economic Indicators," Papers 178d, Harvard - J.F. Kennedy School of Government.
  4. Serena Ng & Pierre Perron, 1997. "Lag Length Selection and the Construction of Unit Root Tests with Good Size and Power," Boston College Working Papers in Economics 369, Boston College Department of Economics, revised 01 Sep 2000.
  5. Domenico Giannone & Lucrezia Reichlin & David Small, 2005. "Nowcasting GDP and inflation: the real-time informational content of macroeconomic data releases," Finance and Economics Discussion Series 2005-42, Board of Governors of the Federal Reserve System (U.S.).
  6. S. Boragan Aruoba & Francis X. Diebold, 2010. "Real-Time Macroeconomic Monitoring: Real Activity, Inflation, and Interactions," PIER Working Paper Archive 10-002, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.
  7. Camacho, Maximo & Pérez-Quirós, Gabriel & Poncela, Pilar, 2012. "Markov-switching dynamic factor models in real time," CEPR Discussion Papers 8866, C.E.P.R. Discussion Papers.
  8. Alejandro Simone, 2001. "In Search of Coincident and Leading Indicators of Economic Activity in Argentina," IMF Working Papers 01/30, International Monetary Fund.
  9. Maximo Camacho & Gabriel Perez-Quiros, 2008. "Introducing the EURO-STING: Short Term INdicator of Euro Area Growth," Banco de Espa�a Working Papers 0807, Banco de Espa�a.
  10. Máximo Camacho & Rafael Doménech, 2012. "MICA-BBVA: a factor model of economic and financial indicators for short-term GDP forecasting," SERIEs, Spanish Economic Association, vol. 3(4), pages 475-497, December.
  11. Maximo Camacho & Jaime Martíinez-Martin, 2012. "Real-time forecasting US GDP from small-scale factor models," Working Papers 1210, BBVA Bank, Economic Research Department.
  12. Arthur F. Burns & Wesley C. Mitchell, 1946. "Measuring Business Cycles," NBER Books, National Bureau of Economic Research, Inc, number burn46-1.
  13. Liu, Philip & Matheson, Troy & Romeu, Rafael, 2012. "Real-time forecasts of economic activity for Latin American economies," Economic Modelling, Elsevier, vol. 29(4), pages 1090-1098.
  14. Lane, Philip R, 2003. "Business Cycles and Macroeconomic Policy in Emerging Market Economies," International Finance, Wiley Blackwell, vol. 6(1), pages 89-108, Spring.
  15. Máximo Camacho & Gabriel Pérez-Quirós, 2005. "Jump-and-rest effect of U.S. business cycles," Banco de Espa�a Working Papers 0507, Banco de Espa�a.
  16. Aguiar, Mark & Gopinath, Gita, 2007. "Emerging Market Business Cycles: The Cycle is the Trend," Scholarly Articles 11988098, Harvard University Department of Economics.
  17. Tom Stark & Dean Croushore, 2001. "Forecasting with a real-time data set for macroeconomists," Working Papers 01-10, Federal Reserve Bank of Philadelphia.
  18. Roberto S. Mariano & Yasutomo Murasawa, 2003. "A new coincident index of business cycles based on monthly and quarterly series," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 18(4), pages 427-443.
  19. Diebold, Francis X & Mariano, Roberto S, 1995. "Comparing Predictive Accuracy," Journal of Business & Economic Statistics, American Statistical Association, vol. 13(3), pages 253-63, July.
  20. Juan Mario Jorrat & Ana María Cerro, 2000. "Computing turning point monthly probability of the Argentinian economy according to the leading index: 1973 - 2000," Estudios de Economia, University of Chile, Department of Economics, vol. 27(2 Year 20), pages 279-295, December.
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