Das makroökonometrische Modell des IWH: Eine angebotsseitige Betrachtung

Diese Arbeit beschreibt das makroökonometrische Modell des IWH: ein auf Quartalsdaten gestütztes, strukturelles Modell für die deutsche Volkswirtschaft. Der Beitrag konzentriert sich auf die Spezifikation und Schätzungen der angebotsseitigen Aspekte des Modells. Dieser Ansatz gewährleistet ein theoretisch fundiertes langfristiges Modellgleichgewicht. Somit verbindet das Modell kurzfristig gewünschte Prognoseeigenschaften mit langfristigen theoretischen Anforderungen. Für einige makroökonomische Aggregate werden kurz- bis langfristige Auswirkungen von Angebots- und Nachfrageschocks dargestellt. Zudem werden durch Modellsimulationen die Auswirkungen außenwirtschaftlicher Schocks auf das Gesamtmodell illustriert.This paper describes the IWH macroeconometric model, a quarterly structural model for the German Economy. It focuses on the specification and estimation on supply-side aspects of the model. This approach guarantees a theoretical derived long-run model equilibrium. It combines short-run forecasting requirements with a long-run theoretical foundation. For some macroeconomic aggregates short- and long-run effects of supply- and demand shocks are illustrated. Additionally, effects of external shocks are investigated through model simulations to illustrate aggregate model characteristics

Is East Germany Catching Up? A Time Series Perspective

This paper assesses whether the economy of East Germany is catching up with the West German region in terms of welfare. While the primary measure for convergence and catching up is per capita output, we also look at other macroeconomic indicators such as unemployment rates, wage rates, and production levels in the manufacturingsector. In contrast to existing studies of convergence between regions of reunified Germany, our approach is purely based upon the time series dimension and is thus directly focused on the catching up process in East Germany as a region. Our testing setup includes standard ADF unit root tests as well as unit root tests that endogenously allow for a break in the deterministic component of the process. In our analysis, we find evidence of catching up for East Germany for most of the indicators. However, convergence speed is slow, and thus it can be expected that the catching up process will take further decades until the regional gap is closed.east germany, catching up, convergence, unit root tests

Three methods of forecasting currency crises: Which made the run in signaling the South African currency crisis of June 2006?

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.currency crises, forecast, predictability, signals approach, probit approach, markov regime switching approach, south africa

Das makroökonometrische Modell des IWH: Eine angebotsseitige Betrachtung

This paper describes the IWH macroeconometric model, a quarterly structural model for the German Economy. It focuses on the specification and estimation on supply-side aspects of the model. This approach guarantees a theoretical derived long-run model equilibrium. It combines short-run forecasting requirements with a long-run theoretical foundation. For some macroeconomic aggregates short- and long-run effects of supply- and demand shocks are illustrated. Additionally, effects of external shocks are investigated through model simulations to illustrate aggregate model characteristics.macroeconometric model, German economy, policy simulations

The Financial Crisis from a Forecaster’s Perspective

This paper analyses the recession in 2008/2009 in Germany, which is very different from previous recessions, in particular regarding its cause and magnitude. We show to what extent forecasters and forecasts based on leading indicators fail to detect the timing and the magnitude of the recession. This study shows that large forecast errors for both expert forecasts and forecasts based on leading indicators resulted during this recession which implies that the recession was very difficult to forecast. However, some leading indicators (survey data, risk spreads, stock prices) have indicated an economic downturn and hence, beat univariate time series models. Although the combination of individual forecasts provides an improvement compared to the benchmark model, the combined forecasts are worse than several individual models. A comparison of expert forecasts with the best forecasts based on leading indicators shows only minor deviations. Overall, the range for an improvement of expert forecasts during the crisis compared to indicator forecasts is relatively small.leading indicators, recession, consensus forecast, non-linearities

Evaluating the German (New Keynesian) Phillips Curve

This paper evaluates the New Keynesian Phillips Curve (NKPC) and its hybrid variant within a limited information framework for Germany. The main interest rests on the average frequency of price re-optimization of firms. We use the labor income share as the driving variable and consider a source of real rigidity by allowing for a fixed firm-specific capital stock. A GMM estimation strategy is employed as well as an identification robust method that is based upon the Anderson-Rubin statistic. We find out that the German Phillips Curve is purely forward looking. Moreover, our point estimates are consistent with the view that firms re-optimize prices every two to three quarters. While these estimates seem plausible from an economic point of view, the uncertainties around these estimates are very large and also consistent with perfect nominal price rigidity where firms never re-optimize prices. This analysis also offers some explanations why previous results for the German NKPC based on GMM differ considerably. First, standard GMM results are very sensitive to the way how orthogonality conditions are formulated. Additionally, model misspecifications may be left undetected by conventional J tests. Taken together, this analysis points out the need for identification robust methods to get reliable estimates for the NKPC

Should We Trust in Leading Indicators? Evidence from the Recent Recession

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.leading indicators, forecast evaluation, forecast pooling, sructural breaks

Three methods of forecasting currency crises: Which made the run in signaling the South African currency crisis of June 2006?

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.In diesem Beitrag wird die Prognosefähigkeit von drei populären Ansätzen anhand der südafrikanischen Währungskrise im Juni 2006 getestet. Von besonderem Interesse ist die Out-of-sample-Prognosegüte der Methoden. Deshalb wird die jüngste Währungskrise in Südafrika als Out-of-sample-Experiment genutzt. Im Ergebnis zeigt sich, dass der Signalansatz nicht in der Lage war die Währungskrise vorherzusagen; Probit-Ansätze konnten die Krise vorhersagen wenn sie auf Rohdaten und nicht auf Signalen des Signalansatzes basierten. Auch die Verwendung eines Markov-regime-switching-Ansatz führte zu korrenkten Prognosen der Out-of-sample-Krise. Die Antwort auf die Titelfrage des Beitrags, welche Methode die Krise vom Juni 2006 am besten vorhersagen konnte ist: der Markov-regime-switching-Ansatz, weil dieser die meisten Vorkrisenperioden korrekt erkannte. Dennoch ist der "Sieg" nicht überragend. So ist die In-sample-Prognosegüte des Probit-Ansatzes besser und dieser Ansatz ist auch in der Lage zumindest einige der Vorkrisenperioden als solche zu erkennen. Es kann daher nicht empfohlen werden Währungskrisenprognosen auf nur einen Ansatz zu stützen

Should We Trust in Leading Indicators? Evidence from the Recent Recession

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 tability 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.Dieses Papier untersucht die Prognosegüte konjunktureller Frühindikatoren für das Bruttoinlandsprodukt sowie die Industrieproduktion in Deutschland vor und während der Krise. Die Prognosegüte einzelner und durch verschiedene Gewichtungsschemata kombinierter Prognosen basierend auf Frühindikatoren wird durch gemeinsame Signifikanztests bewertet. Des Weiteren geben End-of-sample Instabilitätstests Auskunft über die Stabilität der Prognosemodelle während der aktuellen Finanzkrise. Es wird gezeigt, dass nur wenige Einzelindikatoren vor der Krise genauere Prognosen liefern als das AR-Modell. Durch Kombination kann die Prognosegüte von Frühindikatoren erheblich verbessert werden. Während Umfragedaten für die Kurzfristprognose die Prognosegüte erheblich verbessern, liefern Finanzmarktdaten, wie bspw. Zinsspreads und Risikoaufschläge, bessere Prognosen als die Benchmark für längerfristige Prognosehorizonte