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on Forecasting |
| By: | Coccia Mario (Ceris - Institute for Economic Research on Firms and Growth, Moncalieri (Turin), Italy) |
| Abstract: | The purpose of this paper is to forecast and analyse, by a demographic perspective, the organizational behaviour of public research labs. The research focuses on the biggest Italian public research body. Demographic models of growth, based on different human resource policies, show the uncertain and retrogressive evolutionary change of Italian public research bodies that would halve their research personnel over the forecast horizon. These results provide vital information to the public management about the weaknesses and environmental threats in order to support decisions for improving the strategic change and survival of public research institutions over time. |
| Keywords: | Organizational Studies, Forecasting, Public Research Institutions, Internal Demography |
| JEL: | I20 J11 J26 |
| Date: | 2009–12 |
| URL: | http://d.repec.org/n?u=RePEc:csc:cerisp:200909&r=for |
| By: | Coccia Mario (Ceris - Institute for Economic Research on Firms and Growth, Moncalieri (Turin), Italy) |
| Abstract: | The purpose of this essay is to determine the forecast horizon of the fifth, sixth and seventh long wave. As the period of each long wave can change according to the data, it has been used a deterministic approach, based on historical chronologies of USA and UK economies worked out by several scholars, to determine average timing, period and forecast error of future long waves. In addition, the analysis shows that long waves have average upwave period longer than average downwave one. This result is also confirmed by US Business Cycles that have average contractions shorter than expansions phase over time. |
| Keywords: | Forecast Horizon, Long Waves, Kondratieff Waves, Business Cycles, Asymmetric Path |
| JEL: | E30 E37 |
| Date: | 2009–12 |
| URL: | http://d.repec.org/n?u=RePEc:csc:cerisp:200904&r=for |
| By: | Alejandro Rodríguez; Esther Ruiz |
| Abstract: | Prediction intervals in State Space models can be obtained by assuming Gaussian innovations and using the prediction equations of the Kalman filter, where the true parameters are substituted by consistent estimates. This approach has two limitations. First, it does not incorporate the uncertainty due to parameter estimation. Second, the Gaussianity assumption of future innovations may be inaccurate. To overcome these drawbacks, Wall and Stoffer (2002) propose to obtain prediction intervals by using a bootstrap procedure that requires the backward representation of the model. Obtaining this representation increases the complexity of the procedure and limits its implementation to models for which it exists. The bootstrap procedure proposed by Wall and Stoffer (2002) is further complicated by fact that the intervals are obtained for the prediction errors instead of for the observations. In this paper, we propose a bootstrap procedure for constructing prediction intervals in State Space models that does not need the backward representation of the model and is based on obtaining the intervals directly for the observations. Therefore, its application is much simpler, without loosing the good behavior of bootstrap prediction intervals. We study its finite sample properties and compare them with those of the standard and the Wall and Stoffer (2002) procedures for the Local Level Model. Finally, we illustrate the results by implementing the new procedure to obtain prediction intervals for future values of a real time series. |
| Keywords: | NAIRU, Output gap, Parameter uncertainty, Prediction Intervals, State Space Models |
| Date: | 2010–01 |
| URL: | http://d.repec.org/n?u=RePEc:cte:wsrepe:ws100301&r=for |
| By: | Glady, Nicolas; Baesens, Bart; Croux, Christophe |
| Keywords: | Systems; Applications; Customer lifetime value; Value; |
| Date: | 2009–03 |
| URL: | http://d.repec.org/n?u=RePEc:ner:leuven:urn:hdl:123456789/174883&r=for |
| By: | Elena-Ivona Dumitrescu (LEO - Laboratoire d'économie d'Orleans - CNRS : UMR6221 - Université d'Orléans); Christophe Hurlin (LEO - Laboratoire d'économie d'Orleans - CNRS : UMR6221 - Université d'Orléans); Bertrand Candelon (Laboratoire d'Economie d'Orléans - Université d'Orléans - CNRS : FRE2783) |
| Abstract: | This paper proposes a new statistical framework originating from the traditional credit- scoring literature, to evaluate currency crises Early Warning Systems (EWS). Based on an assessment of the predictive power of panel logit and Markov frameworks, the panel logit model is outperforming the Markov switching specifications. Furthermore, the introduction of forward-looking variables clearly improves the forecasting properties of the EWS. This improvement confirms the adequacy of the second generation crisis models in explaining the occurrence of crises. |
| Keywords: | currency crisis; Early Warning System; credit-scoring |
| Date: | 2010–01–01 |
| URL: | http://d.repec.org/n?u=RePEc:hal:wpaper:halshs-00450050_v1&r=for |