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Real-time forecasting US GDP from small-scale factor models

  • Maximo Camacho


  • Jaime Martinez-Martin


We show that the single-index dynamic factor model developed by Aruoba and Diebold (Am Econ Rev, 100:20–24, 2010 ) to construct an index of the US business cycle conditions is also very useful to forecast US GDP growth in real time. In addition, we adapt the model to include survey data and financial indicators. We find that our extension is unequivocally the preferred alternative to compute backcasts. In nowcasting and forecasting, our model is able to forecast growth as well as AD and better than several baseline alternatives. Finally, we show that our extension could also be used to infer the US business cycles very precisely. Copyright Springer-Verlag Berlin Heidelberg 2014

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Article provided by Springer in its journal Empirical Economics.

Volume (Year): 47 (2014)
Issue (Month): 1 (August)
Pages: 347-364

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Handle: RePEc:spr:empeco:v:47:y:2014:i:1:p:347-364
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  1. Camacho, Maximo & Pérez-Quirós, Gabriel & Poncela, Pilar, 2012. "Extracting nonlinear signals from several economic indicators," CEPR Discussion Papers 8865, C.E.P.R. Discussion Papers.
  2. Tom Stark and Dean Croushore, 2001. "Forecasting with a Real-Time Data Set for Macroeconomists," Computing in Economics and Finance 2001 258, Society for Computational Economics.
  3. S. Boragan Aruoba & Francis X. Diebold & Chiara Scotti, 2007. "Real-Time Measurement of Business Conditions," PIER Working Paper Archive 07-028, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.
  4. Maximo Camacho & Rafael Domenech, 2010. "MICA-BBVA: A Factor Model of Economic and Financial Indicators for Short-term GDP Forecasting," Working Papers 1021, BBVA Bank, Economic Research Department.
  5. Angel De la Fuente & Jose Emilio Bosca, 2011. "Gasto educativo por regiones y niveles en 2005," Working Papers 1119, BBVA Bank, Economic Research Department.
  6. S. Boragan Aruoba & Francis X. Diebold, 2010. "Real-time macroeconomic monitoring: real activity, inflation, and interactions," Working Papers 10-5, Federal Reserve Bank of Philadelphia.
  7. 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.
  8. Stark, Tom & Croushore, Dean, 2002. "Reply to the comments on 'Forecasting with a real-time data set for macroeconomists'," Journal of Macroeconomics, Elsevier, vol. 24(4), pages 563-567, December.
  9. Giannone, Domenico & Reichlin, Lucrezia & Small, David H., 2006. "Nowcasting GDP and inflation: the real-time informational content of macroeconomic data releases," Working Paper Series 0633, European Central Bank.
  10. Francis X. Diebold & Robert S. Mariano, 1994. "Comparing Predictive Accuracy," NBER Technical Working Papers 0169, National Bureau of Economic Research, Inc.
  11. Maximo Camacho & Gabriel Perez-Quiros, 2010. "Introducing the euro-sting: Short-term indicator of euro area growth," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 25(4), pages 663-694.
  12. Hamilton, James D, 1989. "A New Approach to the Economic Analysis of Nonstationary Time Series and the Business Cycle," Econometrica, Econometric Society, vol. 57(2), pages 357-84, March.
  13. Javier Alonso & David Tuesta & Jasmina Bjeletic & Carlos Herrera & Soledad Hormazabal & Ivonne Ordonez & Carolina Romero, 2009. "Un balance de la inversion de los fondos de pensiones en infraestructura: la experiencia en Latinoamerica," Working Papers 0920, BBVA Bank, Economic Research Department.
  14. Jean Boivin & Serena Ng, 2003. "Are More Data Always Better for Factor Analysis?," NBER Working Papers 9829, National Bureau of Economic Research, Inc.
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