This paper documents the behavior of key macro aggregates in the wake of the Covid epidemic. We show that a unique feature of the Covid recession is that the peak-to-trough decline is roughly the same for consumption, investment, and output. In contrast to the 2008 recession, there was only a short-lived rise in financial stress that quickly subsided. Finally, there was mild deflation between the peak and the trough of the Covid recession. We argue that a New Keynesian model that explicitly incorporates epidemic dynamics captures these qualitative features of the Covid recession. A key feature of the model is that Covid acts like a negative shock to the demand for consumption and the supply of labor.

We argue that the COVID epidemic disproportionately affected the economic well-being and health of poor people. To disentangle the forces that generated this outcome, we construct a model that is consistent with the heterogeneous impact of the COVID recession on low- and high-income people. According to our model, two-thirds of the inequality in COVID deaths reflect preexisting inequality in comorbidity rates and access to quality health care. The remaining third stems from the fact that low-income people work in occupations where the risk of infection is high. Our model also implies that the rise in income inequality generated by the COVID epidemic reflects the nature of the goods that low-income people produce. Finally, we assess the health-income trade-offs associated with fiscal transfers to the poor and mandatory containment policies.

A resolution of the missing deflation puzzle is proposed. Our resolution stresses the importance of nonlinearities in price- and wage-setting when the economy is exposed to large shocks. We show that a nonlinear macroeconomic model with real rigidities resolves the missing deflation puzzle, while a linearized version of the same underlying nonlinear model fails to do so. In addition, our nonlinear model reproduces the skewness of inflation and other macroeconomic variables observed in post-war U.S. data. All told, our results caution against the common practice of using linearized models to study inflation and output dynamics.

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. We study potential economic consequences of a coal phase-out in Germany, using a multi-region dynamic general equilibrium model. Four regional phase-out scenarios before the end of 2040 are simulated. We find that the worst case phase-out scenario would lead to an increase in the aggregate unemployment rate by about 0.13 [0.09 minimum; 0.18 maximum] percentage points from 2020 to 2040. The effect on regional unemployment rates varies between 0.18 [0.13; 0.22] and 1.07 [1.00; 1.13] percentage points in the lignite regions. 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 10,100 [6300; 12,300] people by 2040. A coal phase-out until 2035 is not worse in terms of welfare, consumption and employment compared to a coal-exit until 2040.

We analyze 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 we 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, synchronisation among East and West German business cycles seems to have become weaker again recently.

Using data from the European Central Bank‘s Survey of Professional Forecasters, we analyse the role of ex-ante conditioning variables for macroeconomic forecasts. In particular, we test to which extent the heterogeneity, updating and ex-post performance of predictions for inflation, real GDP growth and the unemployment rate are related to assumptions about future oil prices, exchange rates, interest rates and wage growth. Our findings indicate that inflation forecasts are closely associated with oil price expectations, whereas expected interest rates are used primarily to predict output growth and unemployment. Expectations about exchange rates and wage growth also matter for macroeconomic forecasts, albeit less so than oil prices and interest rates. We show that survey participants can considerably improve forecast accuracy for macroeconomic outcomes by reducing prediction errors for external conditions. Our results contribute to a better understanding of the expectation formation process of experts.

We study the dynamic impact of Covid-19, economic mobility, and containment policy shocks. We use Bayesian panel structural vector autoregressions with daily data for 44 countries, identified through sign and zero restrictions. Incidence and mobility shocks raise cases and deaths significantly for two months. Restrictive policy shocks lower mobility immediately, cases after one week, and deaths after three weeks. Non-pharmaceutical interventions explain half of the variation in mobility, cases, and deaths worldwide. These flattened the pandemic curve, while deepening the global mobility recession. The policy tradeoff is 1 p.p. less mobility per day for 9% fewer deaths after two months.

Exploiting the heteroscedasticity of the changes in short-term and long-term interest rates and exchange rates around the FOMC announcement, we identify three structural monetary policy shocks. We eliminate the predictable part of the shocks and study their effects on financial variables and macro variables. The first shock resembles a conventional monetary policy shock, and the second resembles an unconventional monetary shock. The third shock leads to an increase in interest rates, stock prices, industrial production, consumer prices, and commodity prices. At the same time, the excess bond premium and uncertainty decrease, and the U.S. dollar depreciates. Therefore, this third shock combines all the characteristics of a central bank information shock.

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.