Working Papers

• Nowcasting Economic Activity with Fat Tails and Outliers [Current ver.] [Abstract]
  Abstract: The COVID-19 presented macroeconomic models with unique challenges, marked by extreme outliers in economic data. This paper extends dynamic factor models by explicitly incorporating outliers, moving beyond conventional data screening practices. The methodological contribution includes introducing fat tails and outliers multiplicatively into innovation volatility, and two distinct approaches for modeling outliers are presented to address large jumps. Empirical findings demonstrate that outlier-augmented models consistently outperform benchmark models in point and density forecasting, with the most significant improvements observed in nowcasting horizons. Incorporating outliers becomes particularly crucial during major crises, enhancing forecasting accuracy by 44% compared to the benchmark. The uniform mixture approach is found to be more robust than the student-t models, as it targets extreme variations without disrupting the smoothness of the stochastic volatility process. Overall, this paper enhances macroeconomic modeling by explicitly addressing outliers, improving forecasting accuracy, and providing insights into economic dynamics during and after major crises like the COVID-19 pandemic.
  
  
  
  
• Risk Factors in International Capital Flows [Current ver.] [Abstract]
  Abstract: This paper explores the predictive relationship between financial indicators and gross capital flows – inflows and outflows – to emerging markets, with a focus on tail events. Using a dynamic factor model, I extract three indicators of commonality across a large set of financial indicators that capture global, emerging market, and country-specific conditions, respectively. I employ the factors in a quantile regression framework to explore the relationships between risk factors and capital flows to emerging economies. I report three main findings. First, I document evidences of asymmetric and nonlinear relationships between the global factor and both inflows and outflows. The asymmetric relationship is more muted for outflows. Second, the emerging market-specific factor delivers additional predictability for future inflows, while the country-specific factor has a minor role. Third, contrary to inflows, outflows show a strong correlation only with the US factor. This predictive signal is most evident during the Global Financial Crisis. These patterns hold for both in-sample and out-of-sample analyses.
  
  
  
  
• Global Transmission of the US Monetary Policy (with Riccardo Degasperi and Giovanni Ricco) [Current ver.] [Online Appendix] [Abstract]
  Abstract: US monetary policy shapes economic conditions globally due to the dominant role of the dollar in the world economy. We study the propagation of US monetary policy shocks abroad using a state-of-the-art high-frequency identification and a harmonised dataset covering 30 economies and over 150,000 datapoints. A policy tightening has large contractionary effects on both advanced and emerging economies. The propagation via financial variables limits foreign central banks' control over domestic economic conditions by increasing risk premia and by destabilising the medium-long segment of the yield curve. The responses of headline prices abroad are instead shaped by spillovers via commodity markets.
  
  
  
  

Work in Progress

• Identifying the US Government Spending Shocks: It's All About Information Flows (with Giovanni Ricco) [Draft available upon request]