Forecasting Non-Stationary Economic Time Series

Product Description

Economies evolve & are subject to sudden shifts precipitated by legislative changes economic policy major discoveries & political turmoil. Macroeconometric models are a very imperfect tool for forecasting this highly complicated & changing process. Ignoring these factors leads to a wide discrepancy between theory & practice. In their second book on economic forecasting Michael P. Clements & 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 & delineate the sources of forecast failure. They show that forecast-period shifts in deterministic factors--interacting with model misspecification collinearity & 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 & modeling regime shifts; they emphasize the distinction between equilibrium correction (based on cointegration) & 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 & model-based policy analyses.