Hyung Joo Kim and Dong Hwan OhWe propose a novel estimation framework for option pricing models that incorporates local, state-dependent information to improve out-of-sample forecasting performance.
Marcos Mac Mullen and Soo Kyung WooThis paper studies the drivers of the US real exchange rate (RER), with a particular focus on its comovement with net trade (NT) flows. We consider the entire spectrum of frequencies, as the low-frequency variation accounts for 62 and 64 percent of the unconditional variance of the RER and NT, respectively.
Friederike Niepmann and Leslie Sheng ShenHow do banks respond to geopolitical risk, and is this response distinct from other macroeconomic risks? Using U.S. supervisory data and new geopolitical risk indices, we show that banks reduce cross-border lending to countries with elevated geopolitical risk but continue lending to those markets through foreign affiliates—unlike their response to other macro risks.
Todd PronoIn heavy-tailed cases, variance targeting the Student's-t estimator proposed in Bollerslev (1987) for the linear GARCH model is shown to be robust to density misspecification, just like the popular Quasi-Maximum Likelihood Estimator (QMLE). The resulting Variance-Targeted, Non-Gaussian, Quasi-Maximum Likelihood Estimator (VTNGQMLE) is shown to possess a stable limit, albeit one that is highly non-Gaussian, with an ill-defined variance.
Local projections (LPs) are widely used in empirical macroeconomics to estimate impulse responses to policy interventions. Yet, in many ways, they are black boxes. It is often unclear what mechanism or historical episodes drive a particular estimate. We introduce a new decomposition of LP estimates into the sum of contributions of historical events, which is the product, for each time stamp, of a weight and the realization of the response variable. In the least squares case, we show that these weights admit two interpretations. First, they represent purified and standardized shocks.
The distributive effects of carbon taxation are critical for its political acceptability and depend on both income and geographic factors. Using French administrative data, household surveys, and matched employer-employee records, we document that rural households spend 2.8 times more on fossil fuels than urban households and are employed in firms that emit 2.7 times more greenhouse gases. We incorporate these insights into a spatial heterogeneous-agent model with endogenous migration and wealth accumulation, linking spatial and macroeconomic approaches.
Local projections (LPs) are widely used in empirical macroeconomics to estimate impulse responses to policy interventions. Yet, in many ways, they are black boxes. It is often unclear what mechanism or historical episodes drive a particular estimate. We introduce a new decomposition of LP estimates into the sum of contributions of historical events, which is the product, for each time stamp, of a weight and the realization of the response variable. In the least squares case, we show that these weights admit two interpretations. First, they represent purified and standardized shocks.
The distributive effects of carbon taxation are critical for its political acceptability and depend on both income and geographic factors. Using French administrative data, household surveys, and matched employer-employee records, we document that rural households spend 2.8 times more on fossil fuels than urban households and are employed in firms that emit 2.7 times more greenhouse gases. We incorporate these insights into a spatial heterogeneous-agent model with endogenous migration and wealth accumulation, linking spatial and macroeconomic approaches.
We would like to thank Philipp Lane, Klaus Adam, Michael Ehrmann, Christophe Kamps, Timo Reinelt, Annalisa Ferrando, Philippine Cour-Thimann, Felix Hammermann, Davide Romelli, Andreas Kapounek, and colleagues from DG Communication for for their valuable feedback on earlier versions of this paper. This paper was presented at the 2025 AEA Conference in San Francisco, and we appreciate the feedback and suggestions received from the participants.
We would like to thank Philipp Lane, Klaus Adam, Michael Ehrmann, Christophe Kamps, Timo Reinelt, Annalisa Ferrando, Philippine Cour-Thimann, Felix Hammermann, Davide Romelli, Andreas Kapounek, and colleagues from DG Communication for for their valuable feedback on earlier versions of this paper. This paper was presented at the 2025 AEA Conference in San Francisco, and we appreciate the feedback and suggestions received from the participants.
