000			02280nam a2200265Ia 4500
999			_c1211 _d1211
003			DE-boiza
005			20191107121337.0
008			191008
020			_a0-262-03272-4
040			_cIZA
100			_aClements, Michael P. _9190
100			_aHendry, David F. _93514
245		0	_aForecasting Non-Stationary Economic Time Series
260			_c1999, _bMIT Press, _aCambridge, Mass et al.,
300			_a362 pages
340			_hC3 02
440			_aZeutehn Lecture Book Series _95504
520			_aEconomies evolve and are subject to sudden shifts precipitated by legislative changes, economic policy, major discoveries, and political turmoil. Macroeconometric models are a very imperfect tool for forecasting this highly complicated and changing process. Ignoring these factors leads to a wide discrepancy between theory and practice. In their second book on economic forecasting, Michael P. Clements and David F. Hendry ask why some practices seem to work empirically despite a lack of formal support from theory. After reviewing the conventional approach to economic forecasting, they look at the implications for causal modeling, present a taxonomy of forecast errors, and delineate the sources of forecast failure. They show that forecast-period shifts in deterministic factors—interacting with model misspecification, collinearity, and inconsistent estimation—are the dominant source of systematic failure. They then consider various approaches for avoiding systematic forecasting errors, including intercept corrections, differencing, co-breaking, and modeling regime shifts; they emphasize the distinction between equilibrium correction (based on cointegration) and error correction (automatically offsetting past errors). Finally, they present three applications to test the implications of their framework. Their results on forecasting have wider implications for the conduct of empirical econometric research, model formulation, the testing of economic hypotheses, and model-based policy analyses.
650			_aeconomy _9146
650			_aforecast _9590
650			_atime series analysis _9269
653			_aforecast failure
856			_uhttps://mitpress.mit.edu/books/forecasting-non-stationary-economic-time-series _yPublisher's website
942			_cBO _2ddc