Forecasting GDP at the regional level with many predictors

In this paper, we assess the accuracy of macroeconomic forecasts at the regional level using a large data set at quarterly frequency. We forecast gross domestic product (GDP) for two German states (Free State of Saxony and Baden- Württemberg) and Eastern Germany. We overcome the problem of a ’data-poor environment’ at the sub-national level by complementing various regional indicators with more than 200 national and international indicators. We calculate single– indicator, multi–indicator, pooled and factor forecasts in a pseudo real–time setting. Our results show that we can significantly increase forecast accuracy compared to an autoregressive benchmark model, both for short and long term predictions. Furthermore, regional indicators play a crucial role for forecasting regional GDP

Forecasting with many predictors - Is boosting a viable alternative?

This paper evaluates the forecast performance of boosting, a variable selection device, and compares it with the forecast combination schemes and dynamic factor models presented in Stock and Watson (2006). Using the same data set and comparison methodology, we find that boosting is a serious competitor for forecasting US industrial production growth in the short run and that it performs best in the longer run

Forecasting with many predictors - Is boosting a viable alternative?

This paper evaluates the forecast performance of boosting, a variable selection device, and compares it with the forecast combination schemes and dynamic factor models presented in Stock and Watson (2006). Using the same data set and comparison methodology, we find that boosting is a serious competitor for forecasting US industrial production growth in the short run and that it performs best in the longer run.Forecasting; Boosting; Cross-validation

Ranking Economists on the Basis of Many Indicators: An Alternative Approach Using RePEc Data

In socio-economic sciences the RePEc network (Research Papers in Economics) has become an essential source for the gathering and the spread of both existing and new economic research. Furthermore, it is currently the largest bibliometric database in economic sciences containing 33 different indicators for more than 30,000 economists. Based on this bibliographic information RePEc calculates well-known rankings for authors and academic institutions. We provide some cautionary remarks concerning the interpretation of some provided bibliometric measures in RePEc. Moreover, we show how individual and aggregated rankings can be biased due to the employed ranking methodology. In order to select key in-dicators describing and assessing research performance of scientist, we propose to apply principal component analysis in this data-rich environment. This approach allows us to assign weights to each indicator prior to aggregation. We illustrate the approach by providing a new overall ranking of economists based on RePEc data.RePEc, ranking aggregation, principal components analysis, economics profession

RePEc – An Independent Platform for Measuring Output in Economics

Bewertung; Netzwerk; Ranking-Verfahren; Deutschland

The European Union’s Trade Potential afterthe Enlargement in 2004

The objective of this paper is to investigate the trade potential of the fifteen old EU countries with the ten new members having joined on May 1st, 2004. Our focus lies not so much on the integration process already having taken place, but on the importance of institutional factors for trade. To this aim we estimate a standard gravity model applying both cross-section as well as static and dynamic panel data techniques. We conclude that there is further potential for trade resulting not from the formal accession to the EU, but rather from the successive alignment of the new members´ institutional frameworkto EU standards.European integration gravity model trade potential institutions

Ranking Economists and Economic Institutions Using RePEc: Some Remarks

In socio-economic sciences the RePEc network (Research Papers in Economics) has become an essential source both for the spread of existing and new economic research. Furthermore the calculation of rankings for authors and academic institutions play a central role. We provide some cautionary remarks on the ranking methodology employed by RePEc and show how the aggregated rankings maybe biased. Furthermore we offer anew ranking approach, based on standardization of scores, which allows interpersonal comparisons and is less sensitive to outliers. We illustrate our new approach with a large data set provided by RePEc based on 24,500 authors.Rankings, RePEc, ranking aggregation, standardization

Institutions, trade, and integration: what can be expected within the enlarged EU?

This paper investigates the potential for a further increase in trade between the fifteen old EU members and the twelve new countries having joined in 2004 and 2007 that results from a convergence of the new members' institutions towards the level of the EU-15 in accordance with the Acquis Communautaire. To this aim we estimate a gravity model applying both static and dynamic panel data techniques and incorporate detailed variables measuring institutional quality. We conclude that there is further potential for trade resulting from the successive convergence of the new members´ institutional framework towards EU standards. --European integration,institutions,gravity model,trade potential

Predictive Ability of Business Cycle Indicators under Test: A Case Study for the Euro Area Industrial Production

In this paper we assess the information content of seven widely cited early indicators for the euro area with respect to forecasting area-wide industrial production. To this end, we use various tests that are designed to compare competing forecast models. In addition to the standard Diebold-Mariano test, we employ tests that account for specific problems typically encountered in forecast exercises. Specifically, we pay attention to nested model structures, we alleviate the problem of data snooping arising from multiple pairwise testing, and we analyze the structural stability in the relative forecast performance of one indicator compared to a benchmark model. Moreover, we consider loss functions that overweight forecast errors in booms and recessions to check whether a specific indicator that appears to be a good choice on average is also preferable in times of economic stress. We find that on average three indicators have superior forecast ability, namely the EuroCoin indicator, the OECD composite leading indicator, and the FAZ-Euro indicator published by the Frankfurter Allgemeine Zeitung. If one is interested in one-month forecasts only, the business climate indicator of the European Commission yields the smallest errors. However, the results are not completely invariant against the choice of the loss function. Moreover, rolling local tests reveal that the indicators are particularly useful in times of unusual changes in industrial production while the simple autoregressive benchmark is difficult to beat during time of average production growth