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on Forecasting |
| By: | D'Agostino, Antonello (Central Bank and Financial Services Authority of Ireland); Bermingham, Colin (Central Bank and Financial Services Authority of Ireland) |
| Abstract: | The issue of forecast aggregation is to determine whether it is better to forecast a series directly or instead construct forecasts of its components and then sum these component forecasts. Notwithstanding some underlying theoretical results, it is gener- ally accepted that forecast aggregation is an empirical issue. Empirical results in the literature often go unexplained. This leaves forecasters in the dark when confronted with the option of forecast aggregation. We take our empirical exercise a step further by considering the underlying issues in more detail. We analyse two price datasets, one for the United States and one for the Euro Area, which have distinctive dynamics and provide a guide to model choice. We also consider multiple levels of aggregation for each dataset. The models include an autoregressive model, a factor augmented autoregressive model, a large Bayesian VAR and a time-varying model with stochastic volatility. We find that once the appropriate model has been found, forecast aggrega- tion can significantly improve forecast performance. These results are robust to the choice of data transformation. |
| Date: | 2010–08 |
| URL: | http://d.repec.org/n?u=RePEc:cbi:wpaper:8/rt/10&r=for |
| By: | Roel Beetsma; Massimo Giuliodori; Mark Walschot; Peter Wierts |
| Abstract: | Using real-time data from the annual budget over the period 1958-2009, we explore the planning and realization of fiscal policy in the Netherlands . Our key findings are the following. First, planned surpluses are on average unbiased, although they are overoptimistic during the first half of the sample and too pessimistic during the second half of the sample. The latter is the result of cautious real-time revenue estimates by the Dutch Ministry of Finance during this period. Second, real growth projections by the official Dutch forecasting agency are unbiased. This contrasts with the experience of the EU as a whole where biased growth projections represent an important source of fiscal slippage. Third, general economic conditions and the state of the public finances are important determinants of both fiscal plans and their implementation. Fourth, this is also the case for political and institutional factors. Expenditure overruns are partly related to political factors , whereas cautious revenue forecasts relate to the institutional setting. In particular, the most recent regime of the “trendbased budget policy” has worked well for fiscal discipline in the Netherlands |
| JEL: | E6 H6 |
| Date: | 2010–08 |
| URL: | http://d.repec.org/n?u=RePEc:dnb:dnbwpp:260&r=for |
| By: | Bandiera, Luca; Cuaresma, Jesus Crespo; Vincelette, Gallina A. |
| Abstract: | This paper uses model averaging techniques to identify robust predictors of sovereign default episodes on a pooled database for 46 emerging economies over the period 1980-2004. Sovereign default episodes are defined according to Standard&Poor’s or by non-concessional International Monetary Fund loans in excess of 100 percent of the country’s quota. The authors find that, in addition to the level of indebtedness, the quality of policies and institutions is the best predictor of default episodes in emerging market countries with relatively low levels of external debt. For emerging market countries with a higher level of debt, macroeconomic stability plays a robust role in explaining differences in default probabilities. The paper provides evidence that model averaging can improve out-of-sample prediction of sovereign defaults, and draws policy conclusions for the current crisis based on the results. |
| Keywords: | Debt Markets,External Debt,Bankruptcy and Resolution of Financial Distress,Economic Theory&Research,Currencies and Exchange Rates |
| Date: | 2010–08–01 |
| URL: | http://d.repec.org/n?u=RePEc:wbk:wbrwps:5401&r=for |
| By: | Evans, Richard W.; Phillips, Kerk L. |
| Abstract: | The overlapping generations (OLG) model is an important framework for analyzing any type of question in which age cohorts are affected differently by exogenous shocks. However, as the dimensions and degree of heterogeneity in these models increase, the computational burden imposed by rational expectations solution methods for non-stationary equilibrium transition paths increases exponentially. As a result, these models have been limited in the scope of their use to a restricted set of applications and a relatively small group of researchers. In addition to providing a detailed description of the benchmark rational expectations computational method, this paper presents an alternative method for solving for nonstationary equilibrium transition paths in OLG life cycle models that is new to this class of model. We find that our alternate model forecast method reduces computation time to 15 percent of the benchmark time path iteration computation time, and the approximation error is less than 1 percent. |
| Keywords: | Computable General Equilibrium Models; Heterogeneous Agents; Overlapping Generations Model; Distribution of Savings |
| JEL: | D31 C68 C63 D91 |
| Date: | 2010–08–20 |
| URL: | http://d.repec.org/n?u=RePEc:pra:mprapa:24548&r=for |
| By: | Peers, Y.; Fok, D.; Franses, Ph.H.B.F. |
| Abstract: | Although high frequency diffusion data is nowadays available, common practice is still to only use yearly figures in order to get rid of seasonality. This paper proposes a diffusion model that captures seasonality in a way that naturally matches the overall S-shaped pattern. The model is based on the assumption that additional sales at seasonal peaks are drawn from previous or future periods. This implies that the seasonal pattern does not influence the underlying diffusion pattern. The model is compared with alternative approaches through simulations and empirical examples. As alternatives we consider the standard Generalized Bass Model and ignoring seasonality by using the basic Bass model. One of our main findings is that modeling seasonality in a Generalized Bass Model does generate good predictions, but gives biased estimates. In particular, the market potential parameter will be underestimated. Ignoring seasonality gives the true parameter estimates if the data is available of the entire diffusion period. However, when only part of the diffusion period is available estimates and predictions become biased. Our model gives correct estimates and predictions even if the full diffusion process is not yet available. |
| Keywords: | new product diffusion;seasonality |
| Date: | 2010–07–15 |
| URL: | http://d.repec.org/n?u=RePEc:dgr:eureri:1765020378&r=for |