|
on Forecasting |
| By: | Harin, Alexander |
| Abstract: | A general forecasting correcting formula, as a framework for long-use and standardized forecasts, is created. The formula provides new forecasting resources and new possibilities for expansion of forecasting including economic forecasting into the areas of municipal needs, middle-size and small-size business and, even, to individual forecasting. |
| Keywords: | forecasting; prediction; planning; correction; |
| JEL: | O2 H68 C53 D8 |
| Date: | 2009–06–03 |
| URL: | http://d.repec.org/n?u=RePEc:pra:mprapa:15533&r=for |
| By: | Rochelle M. Edge; Michael T. Kiley; Jean-Philippe Laforte |
| Abstract: | This paper considers the “real-time” forecast performance of the Federal Reserve staff, time-series models, and an estimated dynamic stochastic general equilibrium (DSGE) model – the Federal Reserve Board’s new Estimated, Dynamic, Optimization-based (Edo) model. We evaluate forecast performance using out-of-sample predictions from 1996 through 2005 – thereby examining over 70 forecasts presented to the Federal Open Market Committee (FOMC). Our analysis builds on previous real-time forecasting ex- ercises along two dimensions. First, we consider time-series models, a structural DSGE model that has been employed to answer policy questions quite different from forecast- ing, and the forecasts produced by the staff at the Federal Reserve Board. In addition, we examine forecasting performance of our DSGE model at a relatively detailed level by separately considering the forecasts for various components of consumer expenditures and private investment. The results provide significant support to the notion that richly specified DSGE models belong in the forecasting toolbox of a central bank. |
| Date: | 2008–12 |
| URL: | http://d.repec.org/n?u=RePEc:acb:camaaa:2009-03&r=for |
| By: | Roberto Patuelli (University of Lugano, Switzerland and The Rimini Centre for Economic Analysis, Italy); Aura Reggiani (University of Bologna, Italy); Peter Nijkamp (VU University Amsterdam, The Netherlands); Norbert Schanne (Institute for Employment Research (IAB), Nuremberg, Germany) |
| Abstract: | In this paper, we present a review of various computational experiments – and consequent results – concerning Neural Network (NN) models developed for regional employment forecasting. NNs are widely used in several fields because of their flexible specification structure. Their utilization in studying/predicting economic variables, such as employment or migration, is justified by the ability of NNs of learning from data, in other words, of finding functional relationships – by means of data – among the economic variables under analysis. A series of NN experiments is presented in the paper. Using two data sets on German NUTS 3 districts (326 and 113 labour market districts in the former West and East Germany, respectively), the results emerging from the implementation of various NN models – in order to forecast variations in full-time employment – are provided and discussed In our approach, single forecasts are computed by the models for each district. Different specifications of the NN models are first tested in terms of: (a) explanatory variables; and (b) NN structures. The average statistical results of simulated out-of-sample forecasts on different periods are summarized and commented on. In addition to variable and structure specification, the choice of NN learning parameters and internal functions is also critical to the success of NNs. Comprehensive testing of these parameters is, however, limited in the literature. A sensitivity analysis is therefore carried out and discussed, in order to evaluate different combinations of NN parameters. The paper concludes with methodological and empirical remarks, as well as with suggestions for future research. |
| Date: | 2009–01 |
| URL: | http://d.repec.org/n?u=RePEc:rim:rimwps:07-09&r=for |
| By: | Reitz, Stefan; Ruelke, Jan; Stadtmann, Georg |
| Abstract: | We use oil price forecasts from the Consensus Economic Forecast poll to analyze how forecaster build their expectations. Our findings point into the direction that the extrapolative as well as the regressive expectation formation hypothesis play a role. Standard measures of forecast accuracy reveal forecasters' underperformance relative to the random-walk benchmark. However, it seems that this result might be biased due to peso problems. |
| Keywords: | Oil price; survey data; forecast bias; peso problem |
| JEL: | D84 |
| Date: | 2009–06–05 |
| URL: | http://d.repec.org/n?u=RePEc:pra:mprapa:15607&r=for |
| By: | Carlos Llano (Universidad Autonoma de Madrid, Spain The Rimini Centre for Economic Analysis, Rimini, Italy); Wolfgang Polasek (Institute for Advanced Studies, Vienna, Austria and The Rimini Centre for Economic Analysis, Italy); Richard Sellner (Institute for Advanced Studies, Vienna, Austria) |
| Abstract: | Completing data sets that are collected in heterogeneous units is a quite frequent problem. Chow and Lin (1971) were the rst to develop a unied framework for the three problems (interpolation, extrapolation and distribution) of predicting times series by related series (the `indicators'). This paper develops a spatial Chow-Lin procedure for cross-sectional and panel data and compares the classical and Bayesian estimation methods. We outline the error covariance structure in a spatial context and derive the BLUE for the ML and Bayesian MCMC estimation. Finally, we apply the procedure to Spanish regional GDP data between 2000-2004. We assume that only NUTS-2 GDP is known and predict GDP at NUTS-3 level by using socio-economic and spatial information available at NUTS-3. The spatial neighborhood is dened by either km distance, travel time, contiguity and trade relationships. After running some sensitivity analysis, we present the forecast accuracy criteria comparing the predicted values with the observed ones. |
| Keywords: | Interpolation, Spatial panel econometrics, MCMC, Spatial |
| Date: | 2009–01 |
| URL: | http://d.repec.org/n?u=RePEc:rim:rimwps:05-09&r=for |
| By: | Reitz, Stefan; Stadtmann, Georg; Taylor, Mark P. |
| Abstract: | This paper investigates the determinants of forecast heterogeneity in the Yen-US dollar market using a panel data set from Consensus Economics. Regardless of the particular model specification and consideration of control variables we find that exchange rate misalignments increase forecast dispersion, while foreign exchange intervention of the Japanese Ministry of Finance dampens expectation heterogeneity. |
| Keywords: | Exchange rates; forecast heterogeneity; survey data |
| JEL: | D84 F31 |
| Date: | 2009–06–05 |
| URL: | http://d.repec.org/n?u=RePEc:pra:mprapa:15603&r=for |
| By: | Francesco Audrino; Kameliya Filipova |
| Abstract: | We propose an empirical approach to determine the various economic sources driving the US yield curve. We allow the conditional dynamics of the yield at different maturities to change in reaction to past information coming from several relevant predictor variables. We consider both endogenous, yield curve factors and exogenous, macroeconomic factors as predictors in our model, letting the data themselves choose the most important variables. We find clear, different economic patterns in the local dynamics and regime specification of the yields depending on the maturity. Moreover, we present strong empirical evidence for the accuracy of the model in fitting in-sample and predicting out-of-sample the yield curve in comparison to several alternative approaches. |
| Keywords: | Yield curve modeling and forecasting; Macroeconomic variables; Tree-structured models; Threshold regimes; GARCH; Bagging |
| JEL: | C22 C51 C53 E43 E44 |
| Date: | 2009–05 |
| URL: | http://d.repec.org/n?u=RePEc:usg:dp2009:2009-10&r=for |