This is what the leading indicators lead

Journal of Applied Econometrics

Volumn 17, Issue 1, 2002, Pages 61-80

  Camacho, Maximo ^a   Perez Quiros, Gabriel ^b  

^a UNIVERSITY OF MURCIA   (Spain)

^b BANCO DE ESPAÑA   (Spain)

Author keywords

[No Author keywords available]

Indexed keywords

EID: 0036115607     PISSN: 08837252     EISSN: None     Source Type: Journal    
DOI: 10.1002/jae.641     Document Type: Article

References (26)

1. Abramson I. 1982. On bandwidth variation in kernel estimates - a square root law. Annals of Statistics 10: 1217-1223.
2. Birchenhall C, Jessen H, Osborn D, Simpson P. 1999. Predicting US business-cycle regimes. Journal of Business and Economic Statistics 17: 313-323.
3. Camacho M. 1998. Vector smooth transition regression representation of US GDP and CLI. Masters Thesis Dissertation.
4. Devroye L. 1997. Universal smoothing factor selection in density estimation. Test 6: 223-320.
5. Diebold F, Mariano R. 1995. Comparing predictive accuracy. Journal of Business and Economic Statistics 13: 253-263.
6. Diebold F, Rudebusch A. 1991. Forecasting output with the composite leading index: a real-time analysis. Journal of the American Statistical Association 86: 603-610.
7. Engle R, Granger C. 1987. Co-integration and error correction: representation, estimation and testing. Econometrica 55: 251-276.
8. Estrella A, Mishkin F. 1998. Predicting US recessions: financial variables as leading indicators. Review of Economics and Statistics 80: 45-61.
9. Filardo A. 1994. Business cycle phases and their transitional dynamics. Journal of Business and Economic Statistics 12: 279-288.
10. Filardo A. 1999. How reliable are recession prediction models. Federal Reserve Bank of Kansas City Quarterly Review Second quarter: 35-55.
11. Granger C, Ramanathan R. 1984. Improved methods of combining forecasts. Journal of Forecasting 3: 197-204.
12. Granger C, Teräsvirta T. 1993. Modelling Nonlinear Economic Relationships. Oxford University Press: New York.
13. Granger C, Teräsvirta T, Anderson H. 1993. Modelling nonlinearities over the business cycle. In Business Cycles Indicators, and Forecasting, Stock J, Watson W (eds). University of Chicago Press: Chicago; IL.
14. Hamilton J, Pérez-Quiros G. 1996. What do the leading indicators lead? Journal of Business 69: 27-49.
15. Härdle W, View P. 1992. Kernel regression smoothing of time series. Journal of Time Series Analysis 13: 209-232.
16. Hess G, Iwata S. 1997. Measuring and comparing business-cycle features. Journal of Business and Economic Statistics 15: 432-444.
17. Kim Ch. 1994. Predicting business cycle phases with indexes of leading and coincident economic indicators: a multivariate regime-shift approach. Working Paper. Korea University: Seoul.
18. Kwiatkowski D, Phillips P, Schmidt P, Shin Y. 1992. Testing the null hypothesis of stationarity against the alternative of a unit root. Journal of Econometrics 54: 159-178.
19. Li D, Dorfman J. 1996. Predicting turning points through the integration of multiple models. Journal of Business and Economics Statistics 14: 421-428.
20. Lobato I, Robinson P. 1998. A nonparametric test for I(0). Review of Economic Studies 65: 475-495.
21. Mitchell W, Burns A. 1938. Statistical Indicators of Cyclical Revivals. National Bureau of Economic Research: New York.
22. Silverman B. 1986. Density Estimation for Statistics and Data Analysis. Chapman and Hall: London.
23. Stock J, Watson M. 1988. Testing for common trends. Journal of the American Statistical Association 83: 1097-1107.
24. Stock J, Watson M. 1989. New indexes of leading and coincidental economic indicators. In NBER Macroeconomics Annual, Blanchard O, Fisher S (eds). MIT Press: Cambridge, MA.
25. Stock J, Watson M. 1993. A procedure for predicting recessions with leading indicators: econometric issues and recent experience. In Business Cycles, Indicators, and Forecasting, Stock S, Watson M (eds). The University of Chicago Press: Chicago, IL.
26. Stock J, Watson M. 1998. A comparison of linear and nonlinear univariate models for forecasting macroeconomic time series. Working Paper 6607, NBER.