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Forecast Evaluation (forecast + evaluation)
Selected AbstractsHow do changes in monetary policy affect bank lending?JOURNAL OF APPLIED ECONOMETRICS, Issue 3 2006An analysis of Austrian bank data Using a panel of Austrian bank data we show that the lending decisions of the smallest banks are more sensitive to interest rate changes, and that for all banks, sensitivity changes over time. We propose to estimate the groups of banks that display similar lending reactions by means of a group indicator which, after estimation, indicates each bank's classification. Additionally, we estimate a state indicator that indicates the periods during which the lending reaction differs from what we normally observe. Bayesian methods are used for estimation; a sensitivity analysis and a forecast evaluation confirm our model choice. Copyright © 2006 John Wiley & Sons, Ltd. [source] Quarterly real GDP estimates for China and ASEAN4 with a forecast evaluationJOURNAL OF FORECASTING, Issue 6 2004Tilak Abeysinghe Abstract The growing affluence of the East and Southeast Asian economies has come about through a substantial increase in their economic links with the rest of the world, the OECD economies in particular. Econometric studies that try to quantify these links face a severe shortage of high-frequency time series data for China and the group of ASEAN4 (Indonesia, Malaysia, Philippines and Thailand). In this paper we provide quarterly real GDP estimates for these countries derived by applying the Chow,Lin related series technique to annual real GDP series. The quality of the disaggregated series is evaluated through a number of indirect methods. Some potential problems of using readily available univariate disaggregation techniques are also highlighted. Copyright © 2004 John Wiley & Sons, Ltd. [source] The homogeneity restriction and forecasting performance of VAR-type demand systems: an empirical examination of US meat consumptionJOURNAL OF FORECASTING, Issue 3 2002Zijun Wang Abstract This paper compares the forecast performance of vector-autoregression-type (VAR) demand systems with and without imposing the homogeneity restriction in the cointegration space. US meat consumption (beef, poultry and pork) data are studied. One up to four-steps-ahead forecasts are generated from both the theoretically restricted and unrestricted models. A modified Diebold,Mariano test of the equality of mean squared forecast errors (MSFE) and a forecast encompassing test are applied in forecast evaluation. Our findings suggest that the imposition of the homogeneity restriction tends to improve the forecast accuracy when the restriction is not rejected. The evidence is mixed when the restriction is rejected. Copyright © 2002 John Wiley & Sons, Ltd. [source] 4D-Var assimilation of MERIS total column water-vapour retrievals over landTHE QUARTERLY JOURNAL OF THE ROYAL METEOROLOGICAL SOCIETY, Issue 644 2009Peter Bauer Abstract Experiments with the active assimilation of total column water-vapour retrievals from Envisat MERIS observations have been performed at the European Centre for Medium-Range Weather Forecasts (ECMWF), focusing on the summer 2006 African Monsoon Multidisciplinary Analysis (AMMA) field campaign period. A mechanism for data quality control, observation error definition and variational bias correction has been developed so that the data can be safely treated within 4D-Var, like other observations that are currently assimilated in the operational system. While data density is limited due to the restriction to daylight and cloud-free conditions, a systematic impact on mean moisture analysis was found, with distinct regional and seasonal features. The impact can last 1--2 days into the forecast but has little effect on forecast accuracy in terms of both moisture and dynamics. This is mainly explained by the weak dynamic activity in the areas of largest data impact. Analysis and short-range forecast evaluation with radiosonde observations revealed a strong dependence on radiosonde type. Compared with Vaisala RS92 observations, the addition of MERIS total column water-vapour observations produced neutral to positive impact, while contradictory results were obtained when all radiosonde types were used in generating the statistics. This highlights the issue of radiosonde moisture biases and the importance of sonde humidity bias correction in numerical weather prediction (NWP). Copyright © 2009 Royal Meteorological Society [source] | ||||||||||