The Inflation Aversion of the Bundesbank: A State Space Approach

A simple backward-looking Taylor rule is estimated in a time-varying coefficient framework with quarterly German data for the period 1975-1998. Markov switching models and the Kalman Filter are used to extract the unobservable paths of the coefficients. The main finding is that the inflation aversion of the Bundesbank was not constant over time and exhibits some sudden and large shifts during the period of monetary targeting. There are phases with low and with high inflation aversion. This could for example explain why the estimated value of the inflation coefficient in backward-looking Taylor rules often does not exceed one and so violates the implications of theoretical monetary policy models. Moreover, the results provide evidence that the Bundesbank followed the so-called "opportunistic approach" to disinflationTaylor rule; state space models; Markov switching models; Kalman Filter

Declining Output Volatility in Germany: Impulses, Propagation, and the Role of Monetary Policy

This paper investigates the effect of economic integration on the ability of firms to maintain a collusive understanding about staying out of each other's markets. The paper distinguishes among different types of trade costs: ad valorem, unit, fixed. It is shown that for a sufficient reduction of ad valorem trade costs, a cartel supported by collusion on either quantities or prices will be weakened, thus integration is pro-competitive. If integration consists of a reductions in unit (fixed) trade costs a price setting cartel is strengthened (unaffected), while a quantity setting one is weakened.Output; Volatility; Monetary policy; Markov switching model; State space model; Spectral analysis; DSGE model

Do Leading Indicators Help to Predict Business Cycle Turning Points in Germany?

Using a binary reference series based on the dating procedure of Artis, Kontolemis and Osborn (1997) different procedures for predicting turning points of the German business cycles were tested. Specifically, a probit model as proposed by Estrella and Mishkin (1997) as well as Markov-switching models were taken into consideration. The overall results indicate that the interest rate spread, the longterm interest rate as well as some monetary indicators and some survey indicators can help predicting turning points of the business cycle.Business cycle, leading indicators, probit model, McFadden's R2, Markov switching models

Unemployment and Portfolio Choice: Does Persistence Matter?

We use a life cycle model of consumption and portfolio choice to study the effects of social security on the investment decisions of households for the European case. Our model is mainly based on the one developed by Cocco, Gomes, and Maenhout (2005). We extend it by unemployment risk using Markov chains to model the transition between different employment states. In contrast to most models in the life cycle literature, our model allows for three different states, namely employment, short-term as well as long-term unemployment. This allows us to examine the effects of persistence in the unemployment process on portfolio choice. Our main findings are, first, that in case of short-term unemployment only, social security systems as those established in the EU are able to offset the negative impact of unemployment risk on the portfolio-share invested in risky assets. Second, the simulation results reveal that when allowing for long-term unemployment the equity-share is suppressed, especially for young investors. We show that this negative effect of unemployment is mainly driven by its persistence.Precautionary savings, unemployment insurance, long-term unemployment, income uncertainty

Analysing Convergence in Europe Using a Non-linear Single Factor Model

We investigate convergence in European price level, unit labor cost, income, and productivity data over the period of 1960-2006 using the non-linear time-varying coefficients factor model proposed by Phillips and Sul (2007). This approach is extremely flexible on order to model a large number of transition paths to convergence. We find regional clusters in consumer price level data. GDP deflator data and unit labor cost data are far less clustered than CPI data. Income per capita data indicate the existence of three convergence clubs without strong regional linkages; Italy and Germany are not converging to any of those clubs. Total factor productivity data indicate the existence of a small club including fast-growing countries and a club consisting of all other countries.Price level, Income, Productivity, Convergence, Factor Model, European Monetary Union

Asymmetric Monetary Policy Effects in Germany

In a small structural model we find asymmetries in the effects of monetary policy in Germany depending on whether the economy is in an upswing or a downswing. These two different regimes are also identified using a Markov-switching model and the Kalman filter. Our results indicate that the effects of monetary policy are significantly higher in a downswing than in an upswing. It follows not only that monetary policy has to raise interest rates markedly if an economy is overheating but also that once a downturn is discernible, interest rates have to be lowered rapidly so as to prevent an overly large reaction of the real economy.Asymmetry; Monetary policy; Markov switching; Structural model

Global Business Cycles: Degree of Synchronization in the Current Downturn Is Unprecedented

Empirical data analysis shows that the business cycles of industrialized nations demonstrate a fairly strong degree of synchronization in periods of growth, and a lesser degree of synchronization during periods of contraction. The current recession, however, breaks this pattern: the business cycles of industrialized nations have exhibited an unprecedented degree of synchronization since the start of the crisis. In the worst economic downturn since the end of the Second World War, the most important national economies have been drawn one after another into the maelstrom of global recession. In this paper we present a method for measuring business-cycle synchronization between individual countries. In our comparison of the current crisis with previous recessions, a focus is placed on the G7 nations and Germany's most important trading partners.Business cycle synchronisation, Markov switching models

Unit labor cost growth differentials in the Euro area, Germany, and the US: lessons from PANIC and cluster analysis

Inflation differentials in the Euro area are mainly due to a sustained divergence of wage developments across the Euro area, and narrower differences in labour productivity growth (Alvarez et al., 2006). We investigate convergence of inflation using unit labour cost (ULC) growth and applying PANIC (Bai and Ng, 2002, 2004) and cluster procedures (Hobijn and Franses, 2000, Busetti et al., 2006) to Euro area countries as well as US States, US Census Regions and German Laender. Euro area differs in that dispersion in general (and its fraction due to idiosyncratic factors in specific) is larger and common factors are much less important in explaining the variance of ULC growth. We report evidence for convergence clusters in all countries.Unit labor costs, inflation, European Monetary Union, Germany, United States of America, convergence, convergence clubs, panel unit root tests, PANIC

Pooling versus Model Selection for Nowcasting with Many Predictors: An Application to German GDP

This paper discusses pooling versus model selection for now- and forecasting in the presence of model uncertainty with large, unbalanced datasets. Empirically, unbalanced data is pervasive in economics and typically due to di¤erent sampling frequencies and publication delays. Two model classes suited in this context are factor models based on large datasets and mixed-data sampling (MIDAS) regressions with few predictors. The specification of these models requires several choices related to, amongst others, the factor estimation method and the number of factors, lag length and indicator selection. Thus, there are many sources of mis-specification when selecting a particular model, and an alternative could be pooling over a large set of models with di¤erent specifications. We evaluate the relative performance of pooling and model selection for now- and forecasting quarterly German GDP, a key macroeconomic indicator for the largest country in the euro area, with a large set of about one hundred monthly indicators. Our empirical findings provide strong support for pooling over many speci.cations rather than selecting a specific model.nowcasting, forecast combination, forecast pooling, model selection, mixed-frequency data, factor models, MIDAS