Russian monetary policy has been challenged by large and continuous private capital outflows and a sharp drop in oil prices during 2014. Both contributed to significant depreciation pressures on the ruble and led the central bank to give up its exchange rate management strategy. Against this background, this work estimates a small open economy model for Russia, featuring an oil price sector and extended by a specification of the foreign exchange market to correctly account for systematic central bank interventions. We find that shocks to the oil price and private capital flows substantially affect domestic variables such as inflation and output. Simulations for the estimated actual strategy and alternative regimes suggest that the vulnerability of the Russian economy to external shocks can substantially be lowered by adopting some form of inflation targeting. Strategies to target the nominal exchange rate or the ruble price of oil prove to be inferior.

This study analyzes business cycle characteristics for all 20 major contemporaneous economies bordering the Mediterranean Sea based on annual real gross domestic product series for the period from 1960 to 2019. The region we investigate corresponds to the Mare Internum region of the Imperial Roman Empire during the Nerva-Antonine and early Severan dynasty, i.e., at the time of the maximum extent of the Roman Empire around 100 to 200 CE. The covered area encircles the Mediterranean, including economies now belonging to the European Union as well as acceding countries, Turkey, and the Middle East and North African economies. Using a components-deviation-cycle approach, we assess level trends and relative volatility of output. We also quantify the contribution of various factors to the business cycle variability within a region. We find cyclic commonalities and idiosyncrasies are related to ancient and colonial history and to contemporaneous trade relationships. Caliphate and Ottoman Empire membership as well as colonial rule in the twentieth century and contemporary Muslim share of population are the most promising predictors of business cycle commonalities in the region.

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.

<p>Accurate macroeconomic forecasts are essential for effective policy decisions, yet their precision depends on the accuracy of the underlying assumptions. This paper examines the extent to which assumption errors affect forecast accuracy, introducing the average squared assumption error (ASAE) as a valid instrument to address endogeneity. Using double/debiased machine learning (DML) techniques and partial linear instrumental variable (PLIV) models, we analyze GDP growth forecasts for Germany, conditioning on key exogenous variables such as oil price, exchange rate, and world trade. We find that traditional ordinary least squares (OLS) techniques systematically underestimate the influence of assumption errors, particularly with respect to world trade, while DML effectively mitigates endogeneity, reduces multicollinearity, and captures nonlinearities in the data. However, the effect of oil price assumption errors on GDP forecast errors remains ambiguous. These results underscore the importance of advanced econometric tools to improve the evaluation of macroeconomic forecasts.</p>

<p>We show that the response of banks’ net interest margin (NIM) to monetary policy shocks is state dependent. Following a period of low (high) Federal Funds rates, a contractionary monetary policy shock leads to an increase (decrease) in NIM. Aggregate economic activity exhibits a similar state-dependent pattern. To explain these dynamics, we develop a banking model in which social interactions influence households’ attentiveness to deposit interest rates. We embed that framework within a nonlinear heterogeneous-agent NK model. The estimated model accounts well quantitatively for our key empirical findings.</p>

<p>We study the aggregate, distributional, and welfare effects of fiscal policy responses to Germany’s energy crisis using a novel Ten-Agents New-Keynesian (TENK) model. The energy crisis, compounded by the COVID-19 pandemic, led to sharp increases in energy prices, inflation, and significant consumption disparities across households. Our model, calibrated to Germany’s income and consumption distribution, evaluates key policy interventions, including untargeted and targeted transfers, a value-added tax cut, energy tax reductions, and an energy cost brake. We find that untargeted transfers had the largest short-term aggregate impact, while targeted transfers were most cost-effective in supporting lower-income households. Other instruments, as the prominent energy cost brake, yielded comparably limited welfare gains. These results highlight the importance of targeted fiscal measures in addressing distributional effects and stabilizing consumption during economic crises.</p>

I estimate a dynamic stochastic general equilibrium (DSGE) model for the United States that incorporates oil market shocks and risk shocks working through credit market frictions. The findings of this analysis indicate that risk shocks play a crucial role during the Great Recession and the Dot-Com bubble but not during other economic downturns. Credit market frictions do not amplify persistent oil market shocks. This result holds as long as entry and exit rates of entrepreneurs are independent of the business cycle.

This paper addresses a general problem with the use of surveys as source of information about the state of an economy: Answers to surveys are highly dependent on information that is publicly available, while only additional information that is not already publicly known has the potential to improve a professional forecast. We propose a simple procedure to disentangle the private information of agents from knowledge that is already publicly known for surveys that ask for general as well as for private prospects. Our results reveal the potential of our proposed technique for the usage of European Commissions‘ consumer surveys for economic forecasting for Germany.