Qual VAR Revisited: Good Forecast, Bad Story
Makram El-Shagi, Gregor von Schweinitz
Abstract
Due to the recent financial crisis, the interest in econometric models that allow to incorporate binary variables (such as the occurrence of a crisis) experienced a huge surge. This paper evaluates the performance of the Qual VAR, i.e. a VAR model including a latent variable that governs the behavior of an observable binary variable. While we find that the Qual VAR performs reasonably well in forecasting (outperforming a probit benchmark), there are substantial identification problems. Therefore, when the economic interpretation of the dynamic behavior of the latent variable and the chain of causality matter, the Qual VAR is inadvisable.
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Does Central Bank Staff Beat Private Forecasters?
Makram El-Shagi, Sebastian Giesen, A. Jung
IWH Discussion Papers,
Nr. 5,
2012
Abstract
In the tradition of Romer and Romer (2000), this paper compares staff forecasts of the Federal Reserve (Fed) and the European Central Bank (ECB) for inflation and output with corresponding private forecasts. Standard tests show that the Fed and less so the ECB have a considerable information advantage about inflation and output. Using novel tests for conditional predictive ability and forecast stability for the US, we identify the driving forces of the narrowing of the information advantage of Greenbook forecasts coinciding with the Great Moderation.
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The Performance of Short-term Forecasts of the German Economy before and during the 2008/2009 Recession
Katja Drechsel, Rolf Scheufele
International Journal of Forecasting,
Nr. 2,
2012
Abstract
The paper analyzes the forecasting performance of leading indicators for industrial production in Germany. We focus on single and pooled leading indicator models both before and during the financial crisis. Pairwise and joint significant tests are used to evaluate single indicator models as well as forecast combination methods. In addition, we investigate the stability of forecasting models during the most recent financial crisis.
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Flow of Conjunctural Information and Forecast of Euro Area Economic Activity
Katja Drechsel, L. Maurin
Journal of Forecasting,
Nr. 3,
2011
Abstract
Combining forecasts, we analyse the role of information flow in computing short-term forecasts up to one quarter ahead for the euro area GDP and its main components. A dataset of 114 monthly indicators is set up and simple bridge equations are estimated. The individual forecasts are then pooled, using different weighting schemes. To take into consideration the release calendar of each indicator, six forecasts are compiled successively during the quarter. We found that the sequencing of information determines the weight allocated to each block of indicators, especially when the first month of hard data becomes available. This conclusion extends the findings of the recent literature. Moreover, when combining forecasts, two weighting schemes are found to outperform the equal weighting scheme in almost all cases. Compared to an AR forecast, these improve by more than 40% the forecast performance for GDP in the current and next quarter.
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Macroeconomic Challenges in the Euro Area and the Acceding Countries
Katja Drechsel
Dissertation, Fachbereich Wirtschaftswissenschaften der Universität Osnabrück,
2010
Abstract
deutscher Titel: Makroökonomische Herausforderungen für die Eurozone und die Beitrittskandidaten
Abstract: The conduct of effective economic policy faces a multiplicity of macroeconomic challenges, which requires a wide scope of theoretical and empirical analyses. With a focus on the European Union, this doctoral dissertation consists of two parts which make empirical and methodological contributions to the literature on forecasting real economic activity and on the analysis of business cycles in a boom-bust framework in the light of the EMU enlargement. In the first part, we tackle the problem of publication lags and analyse the role of the information flow in computing short-term forecasts up to one quarter ahead for the euro area GDP and its main components. A huge dataset of monthly indicators is used to estimate simple bridge equations. The individual forecasts are then pooled, using different weighting schemes. To take into consideration the release calendar of each indicator, six forecasts are compiled successively during the quarter. We find that the sequencing of information determines the weight allocated to each block of indicators, especially when the first month of hard data becomes available. This conclusion extends the findings of the recent literature. Moreover, when combining forecasts, two weighting schemes are found to outperform the equal weighting scheme in almost all cases. In the second part, we focus on the potential accession of the new EU Member States in Central and Eastern Europe to the euro area. In contrast to the discussion of Optimum Currency Areas, we follow a non-standard approach for the discussion on abandonment of national currencies the boom-bust theory. We analyse whether evidence for boom-bust cycles is given and draw conclusions whether these countries should join the EMU in the near future. Using a broad range of data sets and empirical methods we document credit market imperfections, comprising asymmetric financing opportunities across sectors, excess foreign currency liabilities and contract enforceability problems both at macro and micro level. Furthermore, we depart from the standard analysis of comovements of business cycles among countries and rather consider long-run and short-run comovements across sectors. While the results differ across countries, we find evidence for credit market imperfections in Central and Eastern Europe and different sectoral reactions to shocks. This gives favour for the assessment of the potential euro accession using this supplementary, non-standard approach.
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Should We Trust in Leading Indicators? Evidence from the Recent Recession
Katja Drechsel, Rolf Scheufele
Abstract
The paper analyzes leading indicators for GDP and industrial production in Germany. We focus on the performance of single and pooled leading indicators during the pre-crisis and crisis period using various weighting schemes. Pairwise and joint significant tests are used to evaluate single indicator as well as forecast combination methods. In addition, we use an end-of-sample instability test to investigate the stability of forecasting models during the recent financial crisis. We find in general that only a small number of single indicator models were performing well before the crisis. Pooling can substantially increase the reliability of leading indicator forecasts. During the crisis the relative performance of many leading indicator models increased. At short horizons, survey indicators perform best, while at longer horizons financial indicators, such as term spreads and risk spreads, improve relative to the benchmark.
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Forecasting Currency Crises: Which Methods signaled the South African Crisis of June 2006?
Tobias Knedlik, Rolf Scheufele
South African Journal of Economics,
2008
Abstract
In this paper we test the ability of three of the most popular methods to forecast South African currency crises with a special emphasis on their out-of-sample performance. We choose the latest crisis of June 2006 to conduct an out-of-sample experiment. The results show that the signals approach was not able to forecast the out-of-sample crisis correctly; the probit approach was able
to predict the crisis but only with models, that were based on raw data. The Markov-regime- switching approach predicts the out-of-sample crisis well. However, the results are not straightforward. In-sample, the probit models performed remarkably well and were also able to detect, at least to some extent, out-of-sample currency crises before their occurrence. The recommendation is to not restrict the forecasting to only one approach.
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Three methods of forecasting currency crises: Which made the run in signaling the South African currency crisis of June 2006?
Tobias Knedlik, Rolf Scheufele
IWH Discussion Papers,
Nr. 17,
2007
Abstract
In this paper we test the ability of three of the most popular methods to forecast the South African currency crisis of June 2006. In particular we are interested in the out-ofsample performance of these methods. Thus, we choose the latest crisis to conduct an out-of-sample experiment. In sum, the signals approach was not able to forecast the outof- sample crisis of correctly; the probit approach was able to predict the crisis but just with models, that were based on raw data. Employing a Markov-regime-switching approach also allows to predict the out-of-sample crisis. The answer to the question of which method made the run in forecasting the June 2006 currency crisis is: the Markovswitching approach, since it called most of the pre-crisis periods correctly. However, the “victory” is not straightforward. In-sample, the probit models perform remarkably well and it is also able to detect, at least to some extent, out-of-sample currency crises before their occurrence. It can, therefore, not be recommended to focus on one approach only when evaluating the risk for currency crises.
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The out of sample performance of leading indicators for the German business cycle. Single vs combined forecasts
Christian Dreger, Christian Schumacher
Journal of Business Cycle Measurement and Analysis,
Nr. 1,
2005
Abstract
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