Automatic leading indicators versus macroeconometric structural models: A comparison of inflation and GDP growth forecasting |
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| Authors: | Duo Qin Marie Anne Cagas Geoffrey Ducanes Nedelyn Magtibay-Ramos Pilipinas Quising |
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| Institution: | aQueen Mary, University of London, UK;bAsian Development Bank (ADB), Philippines;cUniversity of the Philippines, Philippines |
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| Abstract: | This paper compares the forecast performance of automatic leading indicators (ALIs) and macroeconometric structural models (MESMs) commonly used by non-academic macroeconomists. Inflation and GDP growth form the forecast objects for comparison, using data from China, Indonesia and the Philippines. ALIs are found to outperform MESMs for one-period-ahead forecasts, but this superiority disappears as the forecast horizon increases. It is also found that ALIs involve greater uncertainty in choosing indicators, mixing data frequencies and utilizing unrestricted VARs. Two ways of reducing the uncertainty are explored: (i) give theory priority in choosing indicators, and include theory-based disequilibrium shocks in the indicator sets; and (ii) reduce the VARs by means of the general-to-specific modeling procedure. |
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| Keywords: | Dynamic factor models Equilibrium/error correction Model reduction VAR |
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