In this paper we analyze the small sample properties of full information and limited information estimators in a potentially misspecified DSGE model. Therefore, we conduct a simulation study based on a standard New Keynesian model including price and wage rigidities. We then study the effects of omitted variable problems on the structural parameter estimates of the model. We find that FIML performs superior when the model is correctly specified. In cases where some of the model characteristics are omitted, the performance of FIML is highly unreliable, whereas GMM estimates remain approximately unbiased and significance tests are mostly reliable.

This paper analyzes the role of common data problems when identifying structural breaks in small samples. Most notably, we survey small sample properties of the most commonly applied endogenous break tests developed by Brown et al. (J R Stat Soc B 37:149–163, 1975) and Zeileis (Stat Pap 45(1):123–131, 2004), Nyblom (J Am Stat Assoc 84(405):223–230, 1989) and Hansen (J Policy Model 14(4):517–533, 1992), and Andrews et al. (J Econ 70(1):9–38, 1996). Power and size properties are derived using Monte Carlo simulations. We find that the Nyblom test is on par with the commonly used F type tests in a small sample in terms of power. While the Nyblom test’s power decreases if the structural break occurs close to the margin of the sample, it proves far more robust to nonnormal distributions of the error term that are found to matter strongly in small samples although being irrelevant asymptotically for all tests that are analyzed in this paper.

Fiscal spending multiplier calculations have attracted considerable attention in the aftermath of the global financial crisis. Much of the current literature is based on VAR estimation methods and DSGE models. In line with the Keynesian literature we argue that many of these models probably underestimate the fiscal spending multiplier in recessions. The income-expenditure model of the fiscal spending multiplier can be seen as a good approximation under these circumstances. In its conventional form this model suffers from an underestimation of the multiplier due to an overestimation of the import intake of domestic absorption. In this article we apply input-output calculus to solve this problem. Multipliers thus derived are comparably high, ranging between 1.4 and 1.8 for many member states of the European Union. GDP drops due to budget consolidation might therefore be substantial in times of crisis.

In this paper we develop an open economy model explaining the joint determination of output, inflation, interest rates, unemployment and the exchange rate in a multi-country framework. Our model -- the Halle Economic Projection Model (HEPM) -- is closely related to studies published by Carabenciov et al. Our main contribution is that we model the Euro area countries separately. In doing so, we consider Germany, France, and Italy which represent together about 70 percent of Euro area GDP. The model combines core equations of the New-Keynesian standard DSGE model with empirically useful ad-hoc equations. We estimate this model using Bayesian techniques and evaluate the forecasting properties. Additionally, we provide an impulse response analysis and a historical shock decomposition.

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.

In this paper, a simple integrated model for the joint assessment of epidemic and economic dynamics is developed. The model can be used to discuss mitigation policies like shutdown and testing. Since epidemics cause output losses due to a reduced labor force, temporarily reducing economic activity in order to prevent future losses can be welfare enhancing. Mitigation policies help to keep the number of people requiring intensive medical care below the capacity of the health system. The optimal policy is a mixture of temporary partial shutdown and intensive testing and isolation of infectious persons for an extended period of time.

This paper examines the extent to which errors in economic forecasts are driven by initial assumptions that prove to be incorrect ex post. Therefore, we construct a new data set comprising an unbalanced panel of annual forecasts from different institutions forecasting German GDP and the underlying assumptions. We explicitly control for different forecast horizons to proxy the information available at the release date. Over 75% of squared errors of the GDP forecast comove with the squared errors in their underlying assumptions. The root mean squared forecast error for GDP in our regression sample of 1.52% could be reduced to 1.13% by setting all assumption errors to zero. This implies that the accuracy of the assumptions is of great importance and that forecasters should reveal the framework of their assumptions in order to obtain useful policy recommendations based on economic forecasts.

In the fight against global warming, the reduction of greenhouse gas emissions is a major objective. In particular, a decrease in electricity generation by coal could contribute to reducing CO2 emissions. Using a multi-region dynamic general equilibrium model, this paper studies potential economic consequences of a coal phase-out in Germany. Different regional phase-out scenarios are simulated with varying timing structures. We find that a politically induced coal phase-out would lead to an increase in the national unemployment rate by about 0.10 percentage points from 2020 to 2040, depending on the specific scenario. The effect on regional unemployment rates varies between 0.18 to 1.07 percentage points in the lignite regions. However, a faster coal phase-out can lead to a faster recovery. The coal phase-out leads to migration from German lignite regions to German non-lignite regions and reduces the labour force in the lignite regions by 10,000 people by 2040.

This paper analyses whether and since when East and West German business cycles are synchronised. We investigate real GDP, unemployment rates and survey data as business cycle indicators and employ several empirical methods. Overall, we find that the regional business cycles have synchronised over time. GDP-based indicators and survey data show a higher degree of synchronisation than the indicators based on unemployment rates. However, recently synchronisation among East and West German business cycles seems to become weaker, in line with international evidence.

Inflation and earnings growth can push some tax payers into higher brackets in the absence of inflation-indexed schedules. Moreover, inflation may affect the composition of individuals’ income sources. As a result, depending on the relative tax burden of labour and capital, inflation may decrease or increase the difference between before-tax and after-tax income. However, whether some and if so which percentiles of the income distribution net benefit from inflation via taxation is a widely unexplored question. We make use of a novel dataset on U.S. pre-tax and post-tax income distribution series provided by Pike ty et al. (2018) for the years 1962 to 2014 to answer this question. To this end, we estimate local projections to quantify dynamic effects. We find that inflation shocks increase progressivity of taxation not only contemporaneously but also with some repercussion of several years after the shock. While particularly the bottom two quintiles gain in share, it is not the top but the fourth quintile that lastingly loses.