nep-for New Economics Papers
on Forecasting
Issue of 2009‒08‒08
nine papers chosen by
Rob J Hyndman
Monash University

  1. Forecasting the World Economy in the Short-Term. By Audrone Jakaitiene; Stéphane Dées
  2. Are more data always better for factor analysis? Results for the euro area, the six largest euro area countries and the UK. By Giovanni Caggiano; George Kapetanios; Vincent Labhard
  3. Inflation forecasting in the new EU member states. By Olga Arratibel; Christophe Kamps; Nadine Leiner-Killinger
  4. The forecasting power of international yield curve linkages. By Michele Modugno; Kleopatra Nikolaou
  5. Forecast evaluation of small nested model sets. By Kirstin Hubrich; Kenneth D. West
  6. How Accurate are Government Forecast of Economic Fundamentals? By Chang, C-L.; Franses, Ph.H.B.F.; McAleer, M.
  7. Optimal Prediction Pools. By John Geweke; Gianni Amisano
  8. Real Time’ early warning indicators for costly asset price boom/bust cycles - a role for global liquidity. By Lucia Alessi; Carsten Detken
  9. Forecast and Simulation Analysis of Mexican Meat Consumption at the Table Cut Level: Impacts on U.S. Exports. By Lopez, Jose A.; Malaga, Jaime E.

  1. By: Audrone Jakaitiene (Institute of Mathematics and Informatics, Akademijos st. 4, LT-08663 Vilnius, Lithuania.); Stéphane Dées (European Central Bank, Kaiserstrasse 29, D-60311 Frankfurt am Main, Germany.)
    Abstract: Forecasting the world economy is a difficult task given the complex inter relationships within and across countries. This paper proposes a number of approaches to forecast short-term changes in selected world economic variables and aims, first, at ranking various forecasting methods in terms of forecast accuracy and, second, at checking whether methods forecasting directly aggregate variables (direct approaches) outperform methods based on the aggregation of country-speci.c forecasts (bottom-up approaches). Overall, all methods perform better than a simple benchmark for short horizons (up to three months ahead). Among the forecasting approaches used, factor models appear to perform the best. Moreover, direct approaches outperform bottom-up ones for real variables, but not for prices. Finally, when country-specific forecasts are adjusted to match direct forecasts at the aggregate levels (top-down approaches), the forecast accuracy is neither improved nor deteriorated (i.e. top-down and bottom-up approaches are broadly equivalent in terms of country-specific forecast accuracy). JEL Classification: C53, C32, E37, F17.
    Keywords: Factor models, Forecasts, Time series models.
    Date: 2009–06
    URL: http://d.repec.org/n?u=RePEc:ecb:ecbwps:20091059&r=for
  2. By: Giovanni Caggiano (Department of Economics, University of Padua, Via del Santo 33, 35123 Padova, Italy.); George Kapetanios (Department of Economics, Queen Mary University of London, Mile End Road, London E1 4NS, United Kingdom.); Vincent Labhard (European Central Bank, Kaiserstrasse 29, D-60311 Frankfurt am Main, Germany.)
    Abstract: Factor based forecasting has been at the forefront of developments in the macroeconometric forecasting literature in the recent past. Despite the flurry of activity in the area, a number of specification issues such as the choice of the number of factors in the forecasting regression, the benefits of combining factor-based forecasts and the choice of the dataset from which to extract the factors remain partly unaddressed. This paper provides a comprehensive empirical investigation of these issues using data for the euro area, the six largest euro area countries, and the UK. JEL Classification: C100,C150,C530.
    Keywords: Factors, Large Datasets, Forecast Combinations.
    Date: 2009–05
    URL: http://d.repec.org/n?u=RePEc:ecb:ecbwps:20091051&r=for
  3. By: Olga Arratibel (European Central Bank, Kaiserstrasse 29, D-60311 Frankfurt am Main, Germany.); Christophe Kamps (European Central Bank, Kaiserstrasse 29, D-60311 Frankfurt am Main, Germany.); Nadine Leiner-Killinger (European Central Bank, Kaiserstrasse 29, D-60311 Frankfurt am Main, Germany.)
    Abstract: To the best of our knowledge, our paper is the first systematic study of the predictive power of monetary aggregates for future inflation for the cross section of New EU Member States. This paper provides stylized facts on monetary versus non-monetary (economic and fiscal) determinants of inflation in these countries as well as formal econometric evidence on the forecast performance of a large set of monetary and non-monetary indicators. The forecast evaluation results suggest that, as has been found for other countries before, it is difficult to find models that significantly outperform a simple benchmark, especially at short forecast horizons. Nevertheless, monetary indicators are found to contain useful information for predicting inflation at longer (3-year) horizons. JEL Classification: C53, E31, E37, E51, E52, E62, P24
    Keywords: Inflation forecasting, leading indicators, monetary policy, information content of money, fiscal policy, New EU Member States
    Date: 2009–02
    URL: http://d.repec.org/n?u=RePEc:ecb:ecbwps:20091015&r=for
  4. By: Michele Modugno (European Central Bank, Kaiserstrasse 29, D-60311 Frankfurt am Main, Germany.); Kleopatra Nikolaou (European Central Bank, Kaiserstrasse 29, D-60311 Frankfurt am Main, Germany.)
    Abstract: This paper investigates whether information from foreign yield curves helps forecast domestic yield curves out-of-sample. A nested methodology to forecast yield curves in domestic and international settings is applied on three major countries (the US, Germany and the UK). This novel methodology is based on dynamic factor models, the EM algorithm and the Kalman …lter. The domestic model is compared vis-á-vis an international one, where information from foreign yield curves is allowed to enrich the information set of the domestic yield curve. The results have interesting and original implications. They reveal clear international dependency patterns, strong enough to improve forecasts of Germany and to a lesser extent UK. The US yield curve exhibits a more independent behaviour. In this way, the paper also generalizes anecdotal evidence on international interest rate linkages to the whole yield curve. JEL Classification: F31.
    Keywords: Yield curve forecast, Dynamic factor model, EM algorithm, International linkages.
    Date: 2009–04
    URL: http://d.repec.org/n?u=RePEc:ecb:ecbwps:20091044&r=for
  5. By: Kirstin Hubrich (European Central Bank, Kaiserstrasse 29, D-60311 Frankfurt am Main, Germany.); Kenneth D. West (University of Wisconsin, Madison, Department of Economics,  1180 Observatory Drive,  Madison, WI 53706, USA.)
    Abstract: We propose two new procedures for comparing the mean squared prediction error (MSPE) of a benchmark model to the MSPEs of a small set of alternative models that nest the benchmark. Our procedures compare the benchmark to all the alternative models simultaneously rather than sequentially, and do not require reestimation of models as part of a bootstrap procedure. Both procedures adjust MSPE differences in accordance with Clark and West (2007); one procedure then examines the maximum t-statistic, the other computes a chi-squared statistic. Our simulations examine the proposed procedures and two existing procedures that do not adjust the MSPE differences: a chi-squared statistic, and White’s (2000) reality check. In these simulations, the two statistics that adjust MSPE differences have most accurate size, and the procedure that looks at the maximum t-statistic has best power. We illustrate, our procedures by comparing forecasts of different models for U.S. inflation. JEL Classification: C32, C53, E37.
    Keywords: Out-of-sample, prediction, testing, multiple model comparisons, inflation forecasting.
    Date: 2009–03
    URL: http://d.repec.org/n?u=RePEc:ecb:ecbwps:20091030&r=for
  6. By: Chang, C-L.; Franses, Ph.H.B.F.; McAleer, M. (Erasmus Econometric Institute)
    Abstract: A government’s ability to forecast key economic fundamentals accurately can affect business confidence, consumer sentiment, and foreign direct investment, among others. A government forecast based on an econometric model is replicable, whereas one that is not fully based on an econometric model is non-replicable. Governments typically provide non-replicable forecasts (or, expert forecasts) of economic fundamentals, such as the inflation rate and real GDP growth rate. In this paper, we develop a methodology to evaluate non-replicable forecasts. We argue that in order to do so, one needs to retrieve from the non-replicable forecast its replicable component, and that it is the difference in accuracy between these two that matters. An empirical example to forecast economic fundamentals for Taiwan shows the relevance of the proposed methodological approach. Our main finding is that it is the undocumented knowledge of the Taiwanese government that reduces forecast errors substantially.
    Keywords: government forecasts;generated regressors;replicable government forecasts;non- replicable government forecasts;initial forecasts, revised forecasts;E37
    Date: 2009–07–23
    URL: http://d.repec.org/n?u=RePEc:dgr:eureir:1765016264&r=for
  7. By: John Geweke (Departments of Statistics and Economics, University of Iowa, Iowa City, IA, USA.); Gianni Amisano (European Central Bank, Kaiserstrasse 29, D-60311 Frankfurt am Main, Germany.)
    Abstract: A prediction model is any statement of a probability distribution for an outcome not yet observed. This study considers the properties of weighted linear combinations of n prediction models, or linear pools, evaluated using the conventional log predictive scoring rule. The log score is a concave function of the weights and, in general, an optimal linear combination will include several models with positive weights despite the fact that exactly one model has limiting posterior probability one. The paper derives several interesting formal results: for example, a prediction model with positive weight in a pool may have zero weight if some other models are deleted from that pool. The results are illustrated using S&P 500 returns with prediction models from the ARCH, stochastic volatility and Markov mixture families. In this example models that are clearly inferior by the usual scoring criteria have positive weights in optimal linear pools, and these pools substantially outperform their best components. JEL Classification: C11, C53.
    Keywords: forecasting, GARCH, log scoring, Markov mixture, model combination, S&P 500 returns, stochastic volatility.
    Date: 2009–03
    URL: http://d.repec.org/n?u=RePEc:ecb:ecbwps:20091017&r=for
  8. By: Lucia Alessi (Directorate General Statistics, European Central Bank, Kaiserstrasse 29, D-60311 Frankfurt am Main, Germany.); Carsten Detken (Directorate General Research, European Central Bank, Kaiserstrasse 29, D-60311 Frankfurt am Main, Germany.)
    Abstract: We test the performance of a host of real and financial variables as early warning indicators for costly aggregate asset price boom/bust cycles, using data for 18 OECD countries between 1970 and 2007. A signalling approach is used to predict asset price booms that have relatively serious real economy consequences. We use a loss function to rank the tested indicators given policy makers’ relative preferences with respect to missed crises and false alarms. The paper analyzes the suitability of various indicators as well as the relative performance of financial versus real, global versus domestic and money versus credit based liquidity indicators. We find that global measures of liquidity are among the best performing indicators and display forecasting records,, which provide useful information for policy makers interested in timely reactions to growing financial imbalances, as long as aversion against type I and type II errors is not too unbalanced. Furthermore, we explore out-of-sample whether the most recent wave of asset price booms (2005-2007) would be predicted to be followed by a serious economic downturn. JEL Classification: E37, E44, E51.
    Keywords: Early Warning Indicators, Signalling Approach, Leaning Against the Wind, Asset Price Booms and Busts, Global Liquidity.
    Date: 2009–03
    URL: http://d.repec.org/n?u=RePEc:ecb:ecbwps:20091039&r=for
  9. By: Lopez, Jose A.; Malaga, Jaime E.
    Abstract: An analysis of current and forecasted Mexican meat consumption and imports is presented at the table cut level of disaggregation. Unlike previous studies, this study uses adult equivalence scales, a price imputation approach, a consistent censored demand system, and estimation techniques from stratified sampling. The results indicate that most Mexican consumption and imports of table cuts of meats grow at different rates. In addition, Mexico seems to be following the U.S. preferences for beef cuts, but it does not seem to be following the U.S. preferences for chicken cuts. The study may help U.S. and Canadian meat exporters in forecasting future exports to Mexico, conducting long-term meat investment decisions, or identifying trends in the consumption of specific table cuts of meats.
    Keywords: forecast of Mexican meat consumption, forecast of Mexican imports, U.S. meat exports to Mexico, Mexican meat demand elasticities, meat analysis at the table cut level, censored demand system, two-step estimation procedure, stratified sampling, Agribusiness, Agricultural and Food Policy, Consumer/Household Economics, Demand and Price Analysis, Food Consumption/Nutrition/Food Safety, International Relations/Trade, Q11,
    Date: 2009–07
    URL: http://d.repec.org/n?u=RePEc:ags:aaea09:51986&r=for

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