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on Forecasting |
| By: | Ralf Brüggemann (Department of Economics, University of Konstanz, Germany); Helmut Lütkepohl (Department of Economics, European University Institute, Italy) |
| Abstract: | Many contemporaneously aggregated variables have stochastic aggregation weights. We compare different forecasts for such variables including univariate forecasts of the aggregate, a multivariate forecast of the aggregate that uses information from the disaggregate components, a forecast which aggregates a multivariate forecast of the disaggregate components and the aggregation weights, and a forecast which aggregates univariate forecasts for individual disaggregate components and the aggregation weights. In empirical illustrations based on aggregate GDP and money growth rates, we find forecast efficiency gains from using the information in the stochastic aggregation weights. A Monte Carlo study confirms that using the information on stochastic aggregation weights explicitly may result in forecast mean squared error reductions. |
| Keywords: | Aggregation, autoregressive process, mean squared error |
| JEL: | C32 |
| Date: | 2011–04–21 |
| URL: | http://d.repec.org/n?u=RePEc:knz:dpteco:1123&r=for |
| By: | Kraas, Birk (Solar Millennium AG); Schroedter-Homscheidt, Marion (German Remote Sensing Data Center, German Aerospace Center (DLR)); Pulvermüller, Benedikt (Solar Millennium AG); Madlener, Reinhard (E.ON Energy Research Center, Institute for Future Energy Consumer Needs and Behavior (FCN), RWTH Aachen University) |
| Abstract: | Forecasts of power production are necessary for the electricity market participation of Concentrating Solar Power (CSP) plants. Deviations from the production schedule may lead to penalty charges. the mitigation impact on deviation penalties of an electricity production forecasting tool for Therefore, the accuracy of direct normal irradiance (DNI) forecasts is an important issue. This paper elaborates the 50 MWel parabolic trough plant Andasol 3 in Spain. A commercial DNI model output statistics (MOS) forecast for the period July 2007 to December 2009 is assessed and compared to the two-day persistence approach, which assumes yesterday’s weather conditions and electricity generation also for the following day. Forecasts are analyzed both with meteorological forecast verification methods and from the perspective of a power plant operator. Using MOS, penalty charges in the study period are reduced by 47.6% compared to the persistence case. Finally, typical error patterns of DNI forecasts and their financial impact are discussed. |
| Keywords: | direct normal irradiance; DNI; irradiance forecast; model output statistics; production forecast; CSP-FoSyS; CSP; Andasol; plant simulation; renewable energy |
| Date: | 2011–05 |
| URL: | http://d.repec.org/n?u=RePEc:ris:fcnwpa:2011_012&r=for |
| By: | Lidia Sanchis-Marco (Dpto. Análisis Económico y Finanzas); Antonio Rubia Serrano (Universidad de Alicante) |
| Abstract: | Most downside risk models implicitly assume that returns are a sufficient statistic with which to forecast the daily conditional distribution of a portfolio. In this paper, we address this question empirically and analyze if the variables that proxy for market liquidity and trading conditions convey valid information to forecast the quantiles of the conditional distribution of several representative market portfolios. Using quantile regression techniques, we report evidence of predictability that can be exploited to improve Value at Risk forecasts. Including trading- and spread-related variables improves considerably the forecasting performance. |
| Keywords: | Value at Risk, Basel, Liquidity, Trading Activity. |
| Date: | 2011–06 |
| URL: | http://d.repec.org/n?u=RePEc:ivi:wpasad:2011-14&r=for |
| By: | Massimiliano Caporin (Dipartimento di Scienze Economiche "Marco Fanno" (Department of Economics and Management), Università degli Studi di Padova); Michael McAleer (Econometrisch Instituut (Econometric Institute), Faculteit der Economische Wetenschappen (Erasmus School of Economics), Erasmus Universiteit, Tinbergen Instituut (Tinbergen Institute).) |
| Abstract: | In the last 15 years, several Multivariate GARCH (MGARCH) models have appeared in the literature. Recent research has begun to examine MGARCH specifications in terms of their out-of-sample forecasting performance. In this paper, we provide an empirical comparison of a set of models, namely BEKK, DCC, Corrected DCC (cDCC) of Aeilli (2008), CCC, Exponentially Weighted Moving Average, and covariance shrinking, using historical data of 89 US equities. Our methods follow part of the approach described in Patton and Sheppard (2009), and the paper contributes to the literature in several directions. First, we consider a wide range of models, including the recent cDCC model and covariance shrinking. Second, we use a range of tests and approaches for direct and indirect model comparison, including the Weighted Likelihood Ratio test of Amisano and Giacomini (2007). Third, we examine how the model rankings are influenced by the cross-sectional dimension of the problem. |
| Keywords: | Covariance forecasting, model confidence set, model ranking, MGARCH, model comparison. |
| JEL: | C32 C53 C52 |
| Date: | 2011 |
| URL: | http://d.repec.org/n?u=RePEc:ucm:doicae:1120&r=for |
| By: | Philip Hans Franses; Chia-Lin Chang; Michael McAleer (University of Canterbury) |
| Abstract: | It is common practice to evaluate fixed-event forecast revisions in macroeconomics by regressing current revisions on one-period lagged revisions. Under weak-form efficiency, the correlation between the current and one-period lagged revisions should be zero. The empirical findings in the literature suggest that the null hypothesis of zero correlation between the current and one-period lagged revisions is rejected quite frequently, where the correlation can be either positive or negative. In this paper we propose a methodology to be able to interpret such non-zero correlations in a straightforward manner. Our approach is based on the assumption that forecasts can be decomposed into both an econometric model and expert intuition. The interpretation of the sign of the correlation between the current and one-period lagged revisions depends on the process governing intuition, and the correlation between intuition and news. |
| Keywords: | Evaluating forecasts; Macroeconomic forecasting; Rationality; Intuition; Weak-form efficiency; Fixed-event forecasts |
| JEL: | C22 C53 E27 E37 |
| Date: | 2011–06–01 |
| URL: | http://d.repec.org/n?u=RePEc:cbt:econwp:11/25&r=for |
| By: | Michael McAleer (Erasmus University Rotterdam, Tinbergen Institute, The Netherlands, Complutense University of Madrid, and Institute of Economic Research, Kyoto University); Philip Hans Franses (Econometric Institute Erasmus School of Economics Erasmus University Rotterdam); Chia-Lin Chang (Department of Applied Economics Department of Finance National Chung Hsing University Taichung, Taiwan) |
| Abstract: | It is common practice to evaluate fixed-event forecast revisions in macroeconomics by regressing current revisions on one-period lagged revisions. Under weak-form efficiency, the correlation between the current and one-period lagged revisions should be zero. The empirical findings in the literature suggest that the null hypothesis of zero correlation between the current and one-period lagged revisions is rejected quite frequently, where the correlation can be either positive or negative. In this paper we propose a methodology to be able to interpret such non-zero correlations in a straightforward manner. Our approach is based on the assumption that forecasts can be decomposed into both an econometric model and expert intuition. The interpretation of the sign of the correlation between the current and one-period lagged revisions depends on the process governing intuition, and the correlation between intuition and news. |
| Keywords: | Evaluating forecasts, Macroeconomic forecasting, Rationality, Intuition, Weak-form efficiency, Fixed-event forecasts. |
| JEL: | C22 C53 E27 E37 |
| Date: | 2011–06 |
| URL: | http://d.repec.org/n?u=RePEc:kyo:wpaper:779&r=for |
| By: | Philip Hans Franses (Econometric Institute, Erasmus School of Economics, Erasmus University Rotterdam); Chia-Lin Chang (Department of Applied Economics, Department of Finance, National Chung Hsing University Taichung, Taiwan); Michael McAleer (Econometrisch Instituut (Econometric Institute), Faculteit der Economische Wetenschappen (Erasmus School of Economics), Erasmus Universiteit, Tinbergen Instituut (Tinbergen Institute).) |
| Abstract: | It is common practice to evaluate fixed-event forecast revisions in macroeconomics by regressing current revisions on one-period lagged revisions. Under weak-form efficiency, the correlation between the current and one-period lagged revisions should be zero. The empirical findings in the literature suggest that the null hypothesis of zero correlation between the current and one-period lagged revisions is rejected quite frequently, where the correlation can be either positive or negative. In this paper we propose a methodology to be able to interpret such non-zero correlations in a straightforward manner. Our approach is based on the assumption that forecasts can be decomposed into both an econometric model and expert intuition. The interpretation of the sign of the correlation between the current and one-period lagged revisions depends on the process governing intuition, and the correlation between intuition and news. |
| Keywords: | Evaluating forecasts, Macroeconomic forecasting, Rationality, Intuition, Weak-form efficiency, Fixed-event forecasts. |
| JEL: | C22 C53 E27 E37 |
| Date: | 2011 |
| URL: | http://d.repec.org/n?u=RePEc:ucm:doicae:1124&r=for |
| By: | Miguel, Belmonte; Gary, Koop; Dimitris, Korobilis |
| Abstract: | In this paper, we forecast EU-area inflation with many predictors using time-varying parameter models. The facts that time-varying parameter models are parameter-rich and the time span of our data is relatively short motivate a desire for shrinkage. In constant coefficient regression models, the Bayesian Lasso is gaining increasing popularity as an effective tool for achieving such shrinkage. In this paper, we develop econometric methods for using the Bayesian Lasso with time-varying parameter models. Our approach allows for the coefficient on each predictor to be: i) time varying, ii) constant over time or iii) shrunk to zero. The econometric methodology decides automatically which category each coefficient belongs in. Our empirical results indicate the benefits of such an approach. |
| Keywords: | Forecasting; hierarchical prior; time-varying parameters; Bayesian Lasso |
| JEL: | C52 E37 C11 E47 |
| Date: | 2011–06–20 |
| URL: | http://d.repec.org/n?u=RePEc:pra:mprapa:31827&r=for |
| By: | Rebecca Hellerstein |
| Abstract: | This paper examines time-varying measures of term premiums across ten developed economies. It shows that a single factor accounts for most of the variation in expected excess returns over time, across the maturity spectrum, and across countries. I construct a global return forecasting factor that is a GDP-weighted average of each country’s local return forecasting factor and show that it has information not spanned by the traditional level, slope, curvature factors of the term structure, or by the local return forecasting factors. Including the global forecasting factor in the model produces estimates of spillover effects that are consistent with our conceptual understanding of these flows, both in direction and magnitude. These effects are illustrated for three episodes: the period following the Russian default in 1998, the bond conundrum period from mid-2004 to mid-2006, and the period since the onset of the global financial crisis in 2008. |
| Keywords: | Bonds ; Risk ; Forecasting |
| Date: | 2011 |
| URL: | http://d.repec.org/n?u=RePEc:fip:fednsr:499&r=for |
| By: | H. Takizawa; David Hauner; Jaewoo Lee |
| Abstract: | Using survey data of market expectations, we ask which popular exchange rate models appear to be consistent with expectation formation of market forecasters. Exchange rate expectations are found to be correlated with inflation differentials and productivity differentials, indicating that the relative PPP and Balassa-Samuelson effect are common inputs into expectation formation of market forecasters. |
| Keywords: | Economic forecasting , Exchange rates , Forecasting models , Interest rate differential , Purchasing power parity , |
| Date: | 2011–05–19 |
| URL: | http://d.repec.org/n?u=RePEc:imf:imfwpa:11/116&r=for |
| By: | Pedro C. Magalhães (University of Lisbon, Social Sciences Institute); Luís Francisco Aguiar (Universidade do Minho - NIPE); Michael S. Lewis-Beck (University of Iowa) |
| Abstract: | The behavior of the individual Spanish voter has come to be rather well-understood, thanks to a growing research literature. However, no models have appeared to explain, or to forecast, national election outcomes. The presence of this research gap contrasts sharply with the extensive election forecasting work done on other leading Western democracies. Here we fill this gap. The model, developed from core political economy theory, is parsimonious but statistically robust. Further, it promises considerable prediction accuracy of Spanish general election outcomes, six months before the contest actually occurs. After presenting the model, and carrying out extensive regression diagnostics, we offer an ex ante forecast of the 2012 general election. |
| Date: | 2011 |
| URL: | http://d.repec.org/n?u=RePEc:nip:nipewp:17/2011&r=for |
| By: | Angelica Gianfreda (Department of Economics (University of Verona)); Luigi Grossi (Department of Economics (University of Verona)) |
| Abstract: | In the last few years we have observed deregulation in electricity markets and an increasing interest of price dynamics has been developed especially to consider all stylized facts shown by spot prices. Only few papers have considered the Italian Electricity Spot market since it has been deregulated recently. Therefore, this contribution is an investigation with emphasis on price dynamics accounting for technologies, market concentration and congestions. We aim to understand how technologies, concentration and congestions affect the zonal prices since these ones combine to bring about the single national price (prezzo unico d’acquisto, PUN). Hence, understanding its features is important for drawing policy indications referred to production planning and selection of generation sources, pricing and risk–hedging problems, monitoring of market power positions and finally to motivate investment strategies in new power plants and grid interconnections. Implementing Reg–ARFIMA–GARCH models, we assess the forecasting performance of selected models showing that they perform better when these factors are considered. |
| Keywords: | Electricity prices, Production technologies, Market power (HHI, RSI), Congestions, Fractional Integration, Forecasting |
| JEL: | C1 Q4 |
| Date: | 2011–01 |
| URL: | http://d.repec.org/n?u=RePEc:ver:wpaper:01/2011&r=for |
| By: | Carlos Vieira (Departamento de Economia, CEFAGE-UE, Universidade de Évora); Isabel Vieira (Departamento de Economia, CEFAGE-UE, Universidade de Évora) |
| Abstract: | This paper formulates a model of demand for higher education in Portugal considering a wide range of demographic, economic, social and institutional explanatory variables. The estimation results suggest that the number of applicants reacts positively to demographic trends, graduation rates at secondary education, female participation, compulsory schooling and the recent Bologna process. Demand reacts negatively to the existence of tuition fees and to unemployment rates. Within an adverse demographic and economic context, forecasts of demand for the next two decades suggest the need to increase participation rates, to avoid funding problems in the higher education system and increase long-term economic development prospects. |
| Keywords: | Demand for higher education; determinants of university participation; applications forecasting. |
| JEL: | I20 I22 I28 |
| Date: | 2011 |
| URL: | http://d.repec.org/n?u=RePEc:cfe:wpcefa:2011_15&r=for |
| By: | Song Song; Peter J. Bickel |
| Abstract: | One popular approach for nonstructural economic and financial forecasting is to include a large number of economic and financial variables, which has been shown to lead to significant improvements for forecasting, for example, by the dynamic factor models. A challenging issue is to determine which variables and (their) lags are relevant, especially when there is a mixture of serial correlation (temporal dynamics), high dimensional (spatial) dependence structure and moderate sample size (relative to dimensionality and lags). To this end, an \textit{integrated} solution that addresses these three challenges simultaneously is appealing. We study the large vector auto regressions here with three types of estimates. We treat each variable's own lags different from other variables' lags, distinguish various lags over time, and is able to select the variables and lags simultaneously. We first show the consequences of using Lasso type estimate directly for time series without considering the temporal dependence. In contrast, our proposed method can still produce an estimate as efficient as an \textit{oracle} under such scenarios. The tuning parameters are chosen via a data driven "rolling scheme" method to optimize the forecasting performance. A macroeconomic and financial forecasting problem is considered to illustrate its superiority over existing estimators. |
| Date: | 2011–06 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:1106.3915&r=for |
| By: | Wintenberger, Olivier; Cai, Sixiang |
| Abstract: | We introduce the notion of continuously invertible volatility models that relies on some Lyapunov condition and some regularity condition. We show that it is almost equivalent to the volatilities forecasting efficiency of the parametric inference approach based on the Stochastic Recurrence Equation (SRE) given in Straumann (2005). Under very weak assumptions, we prove the strong consistency and the asymptotic normality of an estimator based on the SRE. From this parametric estimation, we deduce a natural forecast of the volatility that is strongly consistent. We successfully apply this approach to recover known results on univariate and multivariate GARCH type models where our estimator coincides with the QMLE. In the EGARCH(1,1)model, we apply this approach to find a strongly consistence forecast and to prove that our estimator is asymptotically normal when the limiting covariance matrix exists. Finally, we give some encouraging empirical results of our approach on simulations and real data. |
| Keywords: | Invertibility; volatility models; parametric estimation; strong consistency; asymptotic normality; asymmetric GARCH; exponential GARCH; stochastic recurrence equation; stationarity. |
| JEL: | C13 C32 C53 C01 |
| Date: | 2011–06–20 |
| URL: | http://d.repec.org/n?u=RePEc:pra:mprapa:31767&r=for |
| By: | Herman Stekler; Prakash Loungani; Natalia T. Tamirisa |
| Abstract: | We document information rigidity in forecasts for real GDP growth in 46 countries over the past two decades. We investigate: (i) if rigidities are lower around turning points in the economy, such as in times of recessions and crises; (ii) if rigidities differ across countries, particularly between advanced countries and emerging markets; and (iii) how quickly forecasters incorporate news about growth in other countries into their growth forecasts, with a focus on how advanced countries‘ growth forecasts incorporate news about emerging market growth and vice versa. |
| Date: | 2011–06–01 |
| URL: | http://d.repec.org/n?u=RePEc:imf:imfwpa:11/125&r=for |
| By: | Tin Cheuk Leung (The Chinese University of Hong Kong); Kwok Ping Tsang (Virginia Tech and Hong Kong Institute for Monetary Research) |
| Abstract: | We offer an explanation of why changes in house prices are predictable. Extending the static model in Leung and Tsang (2010), we analyze the housing market with loss averse sellers and anchoring buyers in a dynamic setting. A buyer's current offer price increases with the housing unit's previous purchase price, and the seller has the tendency to delay the sale of a housing unit that has a loss. We show that when both cognitive biases are present, changes in house prices are predicted by price dispersion and trade volume. Using a sample of housing transactions in Hong Kong from 1992 to 2006, we find that price dispersion and transaction volume are indeed powerful predictors of housing return. For forecasting both in and out of sample, the two variables perform as well as conventional predictors like real interest rate and real stock return. |
| Keywords: | Housing Return Predictability, Price Dispersion, Anchoring, Loss Aversion, Hong Kong Housing Market |
| JEL: | R31 C53 |
| Date: | 2011–05 |
| URL: | http://d.repec.org/n?u=RePEc:hkm:wpaper:162011&r=for |