S t u d I o s d e

REFERENCIAS BIBLIOGRÁFICAS 

ALEXANDROV, T.A.; BIANCONCINI, S.; DAGUM, E.B.; MAASS, P. and MCELROY, S.T. 

(2010): “Review of some modern approaches to the problem of trend extraction”, 

Econometric Reviews, Forthcoming. 

BACKUS, D.K. and KEHOE, P.J. (1992): “International Evidence of the Historical Properties 

of Business Cycles”, American Economic Review, American Economic Association, vol. 

82 (4), pp. 864-88. 

BAXTER, M. and KING, R.G. (1999): “Measuring business cycles: Approximate band-pass 

filters for economic time series“, Review of Economic Statistics, vol. 81, pp. 575-593. 

BERNANKE, Ben S. (2004): The Great Moderation, Federal Reserve Board, Remarks by 

Governor Ben S. Bernanke, February 2004. 

BOYÁN, J. (2004): “Asymmetric Cycles,” Review of Economic Studies, Blackwell Publishing, 

vol. 73 (1), pp. 145-162. 

BRY, G. and BOSCHAN, C. (1971): Cyclical Analysis of Time Series: Selected Procedures 

and Computer Programs. National Bureau of Economic Research, New York. 

BURNS, A.F. and MITCHELL, W.C. (1946): Measuring business cycles, New York, National 

Bureau of Economic Research. 

BURNS, A.F. (1951): Introduction, in Wesley C. Mitchell, What happens during business 

cycles: A progress report. New York, National Bureau of Economic Research. 

BUSE, A. and LIM, L. (1977): "Cubic Splines as a Special Case of Restricted Least 

Squares" Journal of the American Statistical Association, vol. 72, pp. 64-68. 

BUTTERWORTH, S. (1930): “On the Theory of Filter Amplifiers” in Wireless Engineer (also 

called Experimental Wireless and the Wireless Engineer), vol. 7, pp. 536-541. 

CAPITANIO, A. (1996): "Un metodo non parametrico per l'analisi della dinamica della 

temperatura basale" STATISTICA, anno LVI, n. 2, pp. 189-200. 

CASTLES, I. (1987): “A guide to smoothing time Series Estimates of Trend“, Catalogue No 

1316,Australian Bureau of Statistics. 

CHAUVET, M. and HAMILTON, J.D. (2006): “Dating Business Cycle Turning Points” in 

Milas, C. Rothman, P.A. van Dijk, D. and Wildasin, E. Nonlinear Time Series Analysis of 

Business Cycles, Elsevier Science Ltd, Amsterdam, North Holland. 

CHHAB, N.; MORRY, M. and DAGUM, E.B. (1999): “Further Results on Alternative Trend-

cycle Estimators for Current Economic analysis“ Revista Estadistica, Vol. 49-51, Nos. 

152-157, pp. 231-257. 

CHOLETTE, P.A. (1981): “A Comparison of Various Trend-cycle Estimators“, in O.D. 

Anderson and M.R. Perryman ed.Time Series Analysis, North Holland, Amsterdam, pp. 

77-87. 

CLEVELAND, W.S. (1979): “Robust Locally Regression and Smoothing Scatterplots”. 

Journal of the American Statistical Association, 74, pp. 829-836. 

CLEVELAND, R.; CLEVELAND, W.S.; MCRAE, J.E.; TERPENNING, I. (1990): “STL: A 

Seasonal-Trend Decomposition Procedure Based on LOESS“, Journal of Official 

Statistics, vol. 6, pp. 3-33. 

DAGUM, E.B. (1980): The X-11-ARIMA Seasonal Adjustment Method. Statistics Canada, 

Ottawa, Canada. 

DAGUM, E.B. (1988): The X11ARIMA/88 Seasonal Adjustment method: foundations and 

user’s Manual,Statistics Canada, Canada. 

DAGUM, E.B., and LANIEL, N. (1987): “Revisions of Trend-cycle Estimators of Moving 

Averages Seasonal Adjustment Methods“, Journal of Business and Economic Statistics, 

vol. 5, pp. 177-189. 

DAGUM, E.B. (1996): " A New Method to Reduce Unwanted Ripples and Revisions in 

Trend-cycle Estimates from X11ARIMA" Survey Methodology, vol. 22, No. 1, pp. 77-83. 

DAGUM, E.B. and CAPITANIO, A. (1998): “Smoothing Methods for short-term Trend 

analysis: Cubic splines and Henderson Filters“ Statistica, Anno LVIII, vol. 1, pp. 5-24. 

---

B

USINESS 

C

YCLES AND 

C

URRENT 

E

CONOMIC 

A

NALYSIS