The department of macroeconomics analyses economic fluctuations of important economic indicators as GDP, employment, and interest rates in the short and medium horizon, the impact of economic policy on these, and the institutional framework that determines long term growth and the business cycle. Founded on this research, the department offers policy advice.
The department covers a wide range of macroeconomic issues. The research is focused on development, implementation and application of quantitative macroeconomic models and the analysis of the interaction between the financial markets and the real economy.
Tracking Weekly State-Level Economic Conditions
in: Review of Economics and Statistics, forthcoming
This paper develops a novel dataset of weekly economic conditions indices for the 50 U.S. states going back to 1987 based on mixed-frequency dynamic factor models with weekly, monthly, and quarterly variables that cover multiple dimensions of state economies. We find considerable cross-state heterogeneity in the length, depth, and timing of business cycles. We illustrate the usefulness of these state-level indices for quantifying the main contributors to the economic collapse caused by the COVID-19 pandemic and for evaluating the effectiveness of the Paycheck Protection Program. We also propose an aggregate indicator that gauges the overall weakness of the U.S. economy.
Monetary Policy in an Oil-dependent Economy in the Presence of Multiple Shocks
in: Review of World Economics, forthcoming
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.
Surges and Instability: The Maturity Shortening Channel
in: Journal of International Economics, forthcoming
Capital inflow surges destabilize the economy through a maturity shortening mechanism. The underlying reason is that firms have incentives to redeem their debt on demand to accommodate the potential liquidity needs of global investors, which makes international borrowing endogenously fragile. Based on a theoretical model and empirical evidence at both the firm and macro levels, our main findings are twofold. First, a significant association exists between surges and shortened corporate debt maturity, especially for firms with foreign bank relationships and higher redeployability. Second, the probability of a crisis following surges with a flattened yield curve is significantly higher than that following surges without one. Our study suggests that debt maturity is the key to understand the financial instability consequences of capital inflow bonanzas.
Total Factor Productivity Growth at the Firm-level: The Effects of Capital Account Liberalization
in: Journal of International Economics, forthcoming
This study provides firm-level evidence on the effect of capital account liberalization on total factor productivity (TFP) growth. We find that a one standard deviation increase in the capital account openness indicator constructed by Fernández et al. (2016) is significantly associated with a 0.18 standard deviation increase in firms’ TFP growth rates. The productivity-enhancing effects are stronger for sectors with higher external finance dependence and capital-skill complementarity, and are persistent five years after liberalization. Moreover, we show that potential transmission mechanisms include improved financing conditions, greater skilled labor utilization, and technology upgrades. Finally, we document heterogeneous effects across firm size and tradability, and threshold effects with respect to the country's institutional quality.
Business Cycle Characteristics of Mediterranean Economies: a Secular Trend and Cycle Dynamics Perspective
in: International Economics and Economic Policy, forthcoming
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.
BigTech Credit and Monetary Policy Transmission: Micro-level Evidence from China
in: IWH Discussion Papers, No. 18, 2022
This paper studies monetary policy transmission through BigTech and traditional banks. By comparing business loans made by a BigTech bank with those made by traditional banks, it finds that BigTech loans tend to be smaller, and the BigTech bank grants credit to more new borrowers compared with conventional banks in response to expansionary monetary policy. The BigTech bank‘s advantages in information, monitoring, and risk management are the potential mechanisms. The analysis also finds that BigTech and traditional bank credits to firms that have already borrowed from these banks respond similarly to changes in monetary policy. Overall, BigTech credit amplifies monetary policy transmission mainly through the extensive margin. In addition, monetary policy has a stronger impact on the real economy through BigTech lending than traditional bank loans.
Understanding Post-Covid Inflation Dynamics
in: Working Paper, 2022
We propose a macroeconomic model with a nonlinear Phillips curve that has a flat slope when inflationary pressures are subdued and steepens when inflationary pressures are elevated. The nonlinear Phillips curve in our model arises due to a quasi-kinked demand schedule for goods produced by firms. Our model can jointly account for the modest decline in inflation during the Great Recession and the surge in inflation during the Post-Covid period. Because our model implies a stronger transmission of shocks when inflation is high, it generates conditional heteroscedasticity in inflation and inflation risk. Hence, our model can generate more sizeable inflation surges due to cost-push and demand shocks than a standard linearized model. Finally, our model implies that the central bank faces a more severe trade-off between inflation and output stabilization when inflation is high.
Expectations, Infections, and Economic Activity
in: NBER Working Paper, No. 27988, April 2022
The Covid epidemic had a large impact on economic activity. In contrast, the dramatic decline in mortality from infectious diseases over the past 120 years had a small economic impact. We argue that people's response to successive Covid waves helps reconcile these two findings. Our analysis uses a unique administrative data set with anonymized monthly expenditures at the individual level that covers the first three Covid waves. Consumer expenditures fell by about the same amount in the first and third waves, even though the risk of getting infected was larger in the third wave. We find that people had pessimistic prior beliefs about the case-fatality rates that converged over time to the true case-fatality rates. Using a model where Covid is endemic, we show that the impact of Covid is small when people know the true case-fatality rate but large when people have empirically-plausible pessimistic prior beliefs about the case-fatality rate. These results reconcile the large economic impact of Covid with the small effect of the secular decline in mortality from infectious diseases estimated in the literature.
The Impact of Active Aggregate Demand on Utilisation-adjusted TFP
in: IWH Discussion Papers, No. 9, 2022
Non-clearing goods markets are an important driver of capacity utilisation and total factor productivity (TFP). The trade-off between goods prices and household search effort is central to goods market matching and therefore drives TFP over the business cycle. In this paper, I develop a New-Keynesian DSGE model with capital utilisation, worker effort, and expand it with<i> goods market search-and-matching (SaM)</i> to model non-clearing goods markets. I conduct a horse-race between the different capacity utilisation channels using Bayesian estimation and capacity utilisation survey data. Models that include goods market SaM improve the data fit, while the capital utilisation and worker effort channels are rendered less important compared to the literature. It follows that TFP fluctuations increase for demand and goods market mismatch shocks, while they decrease for technology shocks. This pattern increases as goods market frictions increase and as prices become stickier. The paper shows the importance of non-clearing goods markets in explaining the difference between technology and TFP over the business cycle.
The Effects of Sovereign Risk: A High Frequency Identification Based on News Ticker Data
in: IWH Discussion Papers, No. 8, 2022
This paper uses novel news ticker data to evaluate the effect of sovereign risk on economic and financial outcomes. The use of intraday news enables me to derive policy events and respective timestamps that potentially alter investors’ beliefs about a sovereign’s willingness to service its debt and thereby sovereign risk. Following the high frequency identification literature, in the tradition of Kuttner (2001) and Guerkaynak et al. (2005), associated variation in sovereign risk is then obtained by capturing bond price movements within narrowly defined time windows around the event time. I conduct the outlined identification for Italy since its large bond market and its frequent coverage in the news render it a suitable candidate country. Using the identified shocks in an instrumental variable local projection setting yields a strong instrument and robust results in line with theoretical predictions. I document a dampening effect of sovereign risk on output. Also, borrowing costs for the private sector increase and inflation rises in response to higher sovereign risk.