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on Forecasting |
| By: | J. Scott Armstrong; Kesten C. Green |
| Abstract: | We looked at evidence from comparative empirical studies to identify methods that can be useful for predicting demand in various situations and to warn against methods that should not be used. In general, use structured methods and avoid intuition, unstructured meetings, focus groups, and data mining. In situations where there are sufficient data, use quantitative methods including extrapolation, quantitative analogies, rule-based forecasting, and causal methods. Otherwise, use methods that structure judgement including surveys of intentions and expectations, judgmental bootstrapping, structured analogies, and simulated interaction. Managers' domain knowledge should be incorporated into statistical forecasts. Methods for combining forecasts, including Delphi and prediction markets, improve accuracy. We provide guidelines for the effective use of forecasts, including such procedures as scenarios. Few organizations use many of the methods described in this paper. Thus, there are opportunities to improve efficiency by adopting these forecasting practices. |
| Keywords: | Accuracy, expertise, forecasting, judgement, marketing. |
| JEL: | C53 M30 M31 |
| Date: | 2005–09 |
| URL: | http://d.repec.org/n?u=RePEc:msh:ebswps:2005-24&r=for |
| By: | Bouwman, Kees E.; Jacobs, Jan P.A.M. (Groningen University) |
| Abstract: | Real-time macroeconomic data are typically incomplete for today and the immediate past (‘ragged edge’) and subject to revision. To enable more timely forecasts the recent missing data have to be dealt with. In the context of the U.S. leading index we assess four alternatives, paying explicit attention to publication lags and data revisions. |
| Date: | 2005 |
| URL: | http://d.repec.org/n?u=RePEc:dgr:rugccs:200505&r=for |
| By: | Adolfson, Malin (Research Department, Central Bank of Sweden); Andersson, Michael K. (Monetary Policy Department, Central Bank of Sweden); Lindé, Jesper (Research Department, Central Bank of Sweden); Villani, Mattias (Research Department, Central Bank of Sweden); Vredin, Anders (Monetary Policy Department, Central Bank of Sweden) |
| Abstract: | There are many indications that formal methods based on economic research are not used to their full potential by central banks today. For instance, Christopher Sims published a review in 2002 where he argued that central banks use models that ”are now fit to data by ad hoc procedures that have no grounding in statistical theory”. There is no organized resistance against formal models at central banks, but the proponents of such models have not always been able to present convincing evidence of the models’ advantages. In this paper we demonstrate how BVAR and DSGE models can be used to shed light on questions that policy makers deal with in practice. We compare the forecast performance of BVAR and DSGE models with the Riksbank’s official, more subjective forecasts. We also use the models to interpret the low inflation rate in Sweden in 2003 - 2004. |
| Keywords: | Bayesian inference; DSGE models; Forecasting; Monetary policy; Subjective forecasting; Vector autoregressions |
| JEL: | E37 E47 E52 |
| Date: | 2005–09–01 |
| URL: | http://d.repec.org/n?u=RePEc:hhs:rbnkwp:0188&r=for |
| By: | Adolfson, Malin (Research Department, Central Bank of Sweden); Lindé, Jesper (Research Department, Central Bank of Sweden); Villani, Mattias (Research Department, Central Bank of Sweden) |
| Abstract: | This paper analyzes the forecasting performance of an open economy DSGE model, estimated with Bayesian methods, for the Euro area during 1994Q1-2002Q4. We compare the DSGE model and a few variants of this model to various reduced form forecasting models such as several vector autoregressions (VAR), estimated both by maximum likelihood and two different Bayesian approaches, and traditional benchmark models, e.g. the random walk. The accuracy of the point forecasts are assessed in a traditional out-of-sample rolling event evaluation using several univariate and multivariate measures. Forecast intervals are evaluated in different ways and the log predictive score is used to summarize the precision in the joint forecast distribution as a whole. We also discuss the role of Bayesian model probabilities and other frequently used low-dimensional summaries, e.g. the log determinant statistic, as measures of overall forecasting performance. |
| Keywords: | Bayesian inference; Forecasting; Open economy DSGE model; Vector autoregressive models |
| JEL: | C11 C32 E37 E47 |
| Date: | 2005–09–01 |
| URL: | http://d.repec.org/n?u=RePEc:hhs:rbnkwp:0190&r=for |
| By: | Laurence Le Fouler; Annabelle Mourougane; Nigel Pain; Franck Sédillot |
| Abstract: | This paper provides a detailed description of recent research to re-estimate and re-specify the international trade volume and price equations that are used in the OECD Economics Department to analyse international trade developments. New panel data estimates of the factors affecting export performance, import penetration and exchange rate pass-through into trade prices are reported for both OECD and non-OECD economies. The model set out has already been used successfully to monitor the global consistency of the international trade projections in the Economic Outlook. <P>Le nouveau modèle du commerce international de l'OCDE Cette étude présente de façon détaillée la respecification et la réestimation des équations de commerce extérieur (prix et volumes) qui sont utilisées par le Département des Affaires Économiques de l'OCDE pour analyser les développements du commerce mondial. L'impact des facteurs influençant la performance à l'exportation, le taux de pénétration des importations et l'effet du taux de change sur les prix du commerce extérieur des zones OCDE et non OCDE est estimé par le biais de données de panel. Le model présenté a déjà été mis en oeuvre avec succès pour assurer la cohérence globale des prévisions des flux commerciaux publiées dans les Perspectives Économiques de l'OCDE. |
| Keywords: | forecasting model, international trade prices, international trade volumes, modèle de prévision, prix du commerce extérieur, volumes du commerce extérieur |
| JEL: | F14 F17 F47 |
| Date: | 2005–08–10 |
| URL: | http://d.repec.org/n?u=RePEc:oec:ecoaaa:440-en&r=for |
| By: | Carlo Favero; Massimiliano Marcellino |
| Abstract: | In this paper we assess the possibility of producing unbiased forecasts for fiscal variables in the euro area by comparing a set of procedures that rely on different information sets and econometric techniques. In particular, we consider ARMA models, VARs, small scale semi-structural models at the national and euro area level, institutional forecasts (OECD), and pooling. Our small scale models are characterized by the joint modelling of fiscal and monetary policy using simple rules, combined with equations for the evolution of all the relevant fundamentals for the Maastricht Treaty and the Stability and Growth Pact. We rank models on the basis of their forecasting performance using the mean square and mean absolute error criteria at different horizons. Overall, simple time series methods and pooling work well and are able to deliver unbiased forecasts, or slightly upward biased forecast for the debt-GDP dynamics. This result is mostly due to the short sample available, the robustness of simple methods to structural breaks, and to the difficulty of modelling the joint behaviour of several variables in a period of substantial institutional and economic changes. A bootstrap experiment highlights that, even when the data are generated using the estimated small scale multi country model, simple time series models can produce more accurate forecasts, due to their parsimonious specification. |
| URL: | http://d.repec.org/n?u=RePEc:igi:igierp:298&r=for |
| By: | Nymoen, Ragnar (Dept. of Economics, University of Oslo) |
| Abstract: | Failures are not rare in economic forecasting, probably due to the high incidence of shocks and regime shifts in the economy. Thus, there is a premium on adaptation in the forecast process, in order to avoid sequences of forecast failure. This paper evaluates a sequence of inflation forecasts in the Norges Bank Inflation Report, and we present automatized forecasts which are unaffected by forecast failure. One conclusion is that the Norges Bank fan-charts are too narrow, giving an illusion of very precise forecasts. The automatized forecasts show more adaptation once shocks have occurred than is the case for the official forecasts. On the basis of the evidence, the recent inflation forecast failure appears to have been largely avoidable. The central bank’s understanding of the nature of the transmission mechanism and of the strenght and nature of the disinflationly shock that hit the economy appear to have played a major role in the recent forecast failure. |
| Keywords: | Inflation forecasts; Monetary policy; Forecast uncertainty; Fan-charts; Structural change; Econometric models. |
| JEL: | C32 C53 E37 E44 E47 E52 E58 |
| Date: | 2005–08–10 |
| URL: | http://d.repec.org/n?u=RePEc:hhs:osloec:2005_022&r=for |
| By: | Darrel Duffie (Graduate School of Business, Stanford University); Leandro Saita (Graduate School of Business, Stanford University); Ke Wang (Faculty of Economics, University of Tokyo) |
| Abstract: | We provide maximum likelihood estimators of term structures of conditional probabilities of corporate default, incorporating the dynamics of ?rm-specific and macroeconomic covariates. For U.S. Industrial firms, based on over 390,000 firm-months of data spanning 1979 to 2004, the level and shape of the estimated term structure of conditional future default probabilities depends on a firm's distance to default (a volatility-adjusted measure of leverage), on the firm's trailing stock return, on trailing S& P 500 returns, and on U.S. interest rates, among other covariates. Variation in a firm's distance to default has a substantially greater effection the term structure of future default hazard rates than does a comparatively significant change in any of the other covariates. Default intensities are estimated to be lower with higher short-term interest rates. Theout-of-samplepredictive performance of the model is an improvement over that of other available models. |
| Date: | 2005–09 |
| URL: | http://d.repec.org/n?u=RePEc:tky:fseres:2005cf373&r=for |
| By: | Vandevoorde, S.; Vanhoucke, M. |
| Abstract: | Earned value project management is a well-known management system that integrates cost, schedule and technical performance. It allows the calculation of cost and schedule variances and performance indices and forecasts of project cost and schedule duration. The earned value method provides early indications of project performance to highlight the need for eventual corrective action. Earned value management was originally developed for cost management and has not widely been used for forecasting project duration. However, recent research trends show an increase of interest to use performance indicators for predicting total project duration. In this paper, we give an overview of the state-of-the-art knowledge for this new research trend to bring clarity in the often confusing terminology. The purpose of this paper is three-fold. First, we compare the classic earned value performance indicators SV & SPI with the newly developed earned schedule performance indicators SV(t) & SPI(t). Next, we present a generic schedule forecasting formula applicable in different project situations and compare the three methods from literature to forecast total project duration. Finally, we illustrate the use of each method on a simple one activity example project and on real-life project data. |
| Keywords: | Earned value; earned duration; earned schedule; project duration forecasting |
| Date: | 2005–10–05 |
| URL: | http://d.repec.org/n?u=RePEc:vlg:vlgwps:2005-16&r=for |
| By: | Jeffrey Grogger |
| Abstract: | Forecasting welfare caseloads, particularly turning points, has become more important than ever. Since welfare reform, welfare has been funded via a block grant, which means that unforeseen changes in caseloads can have important fiscal implications for states. In this paper I develop forecasts based on the theory of Markov chains. Since today's caseload is a function of the past caseload, the caseload exhibits inertia. The method exploits that inertia, basing forecasts of the future caseload on past functions of entry and exit rates. In an application to California welfare data, the method accurately predicted the late-2003 turning point roughly one year in advance. |
| JEL: | I3 |
| Date: | 2005–10 |
| URL: | http://d.repec.org/n?u=RePEc:nbr:nberwo:11682&r=for |
| By: | Pablo Antolin; Christine de la Maisonneuve; Frédéric Gonand; Joaquim Oliveira-Martins; Kwang-Yeol Yoo |
| Abstract: | This paper examines the channels through which ageing will shape the main economic factors that in turn affect potential growth; identifies current policy settings that may in fact amplify the adverse impact of demographic trends; and sets out policy reforms that will work to temper the effects of ageing on growth. The paper begins with a brief discussion of demographic issues. The analysis first focuses on the impact of these trends on the future level and structure of consumption, which may affect aggregate saving and the structure of the economy, respectively. Then, it explores the main channels through which ageing affects the supply side of the economy following a production function approach: capital markets, labour markets and productivity. The empirical analysis focuses on a subset of large OECD countries with differing ageing patterns and generosity of pension systems. Using a simple general equilibrium overlapping generations model and considering alternative reform scenarios, some illustrative simulations are presented decomposing the effects of ageing on potential GDP per capita growth and economic convergence within OECD countries. <P>Effets du vieillissement sur la demande, les marchés des facteurs de production et la croissance Cette étude examine les canaux par lesquels le vieillissement de la population est susceptible d'affecter l'économie et la croissance potentielle. Elle identifie les dispositifs actuels qui pourraient amplifier les effets négatifs induits par les tendances démographiques et analyse les réformes pouvant limiter ces effets. L'étude commence par une brève discussion relative aux évolutions démographiques. Leur effet sur le niveau et la structure de la consommation est ensuite analysé, ainsi que leur impact sur le niveau d'épargne agrégé et la structure de l'économie. L'effet sur l'offre est analysé suivant une approche de type fonction de production: marchés des capitaux, du travail et productivité. L'analyse empirique se concentre sur un sousensemble de grands pays de l'OCDE qui diffèrent par leurs profils de vieillissement et par la générosité de leurs systèmes de pension. Utilisant un modèle simple d'équilibre général avec des générations imbriquées et des scénarios alternatifs de réforme, l'étude présente des simulations illustrant l'impact du vieillissement sur le PIB potentiel par tête et la convergence économique entre pays de l'OCDE. |
| Keywords: | ageing populations, vieillissement de la population, pension reform, economic convergence, longevity, old workers, overlapping generation model, réforme des systèmes de pensions, convergence économique, longévité, travailleurs âgés, modèle à générations imbriquées |
| JEL: | C68 D91 G10 J11 J26 |
| Date: | 2005–03–29 |
| URL: | http://d.repec.org/n?u=RePEc:oec:ecoaaa:420-en&r=for |
| By: | Juan M.C. Larrosa (CONICET-Universidad Nacional del Sur) |
| Abstract: | This survey reviews diverse academic production on compositional dynamic series analysis. Although time dimension of compositional series has been little investigated, this kind of data structure is widely available and utilized in social sciences research. This way, a review of the state-of-the-art on this topic is required for scientist to understand the available options. The review comprehends the analysis of several techniques like autoregresive integrate moving average (ARIMA) analysis, compositional vector autoregression systems (CVAR) and state space techniques but most of these are developed under Bayesian frameworks. As conclusion, this branch of the compositional statistical analysis still requires a lot of advances and updates and, for this same reason, is a fertile field for future research. Social scientists should pay attention to future developments due to the extensive availability of this kind of data structures in socioeconomic databases. |
| Keywords: | compositional data analysis, time series |
| JEL: | C1 C2 C3 C4 C5 C8 |
| Date: | 2005–10–13 |
| URL: | http://d.repec.org/n?u=RePEc:wpa:wuwpem:0510002&r=for |
| By: | Isao Ishida (Faculty of Economics, University of Tokyo) |
| Abstract: | This paper introduces new ways to construct probability integral transforms of random vectors that complement the approach of Diebold, Hahn, and Tay (1999) for evaluating multivariate conditional density forecasts. Our approach enables us to "scan" multivariate densities in various di.erent ways. A simple bivariate normal example is given that illustrates how "scanning" a multivariate density from particular angles leads to tests with no power or high power. An empirical example is also given that applies several di.erent probability integral transforms to specification testing of Engle's (2002) dynamic conditional correlation model for multivariate financial returns time series with multivariate normal and t errors. |
| Date: | 2005–09 |
| URL: | http://d.repec.org/n?u=RePEc:tky:fseres:2005cf369&r=for |