The Postpandemic U.S. Immigration Surge: New Facts and Inflationary Implications
Joint with Anton Cheremukhin, Sewon Hur, Ronald Mau, Karel Mertens, and Xiaoqing Zhou
New: September 27, 2024
Abstract: The U.S. experienced an extraordinary postpandemic surge in unauthorized immigration. This paper combines administrative data on border encounters and immigration court records with household survey data to document two new facts about these immigrants: They tend to be hand-to-mouth consumers and low-skilled workers that complement the existing workforce. We build these features into a model with capital, household heterogeneity, and population growth to study the inflationary effects of this episode. Contrary to the popular view, we find little effect on inflation, as the increase in supply was largely offset by an increase in demand.
Geopolitical Oil Price Risk and Economic Fluctuations
Joint with Lutz Kilian and Michael Plante
Revised: July 19, 2024
Abstract: This paper seeks to understand the general equilibrium effects of time-varying geopolitical risk in oil markets. Answering this question requires simultaneously modeling downside risk from disasters, oil storage, and the endogenous determination of oil price and macroeconomic uncertainty. We find that shocks to the probability of geopolitically driven oil production disasters can have sizable effects on the oil market and macroeconomy but are not a major driver of macroeconomic fluctuations. Shocks to the probability of macroeconomic disasters are an important driver of oil price uncertainty, which helps explain why higher oil price uncertainty has been associated with lower real activity.
Estimating Macroeconomic News and Surprise Shocks
Joint with Lutz Kilian and Michael Plante
Revised: July 23, 2024
Abstract: The importance of understanding the economic effects of news and surprise shocks to TFP is widely recognized in the literature. A common VAR approach is to identify responses to TFP news shocks by maximizing the variance share of TFP over a long horizon. Under suitable conditions, this approach also implies an estimate of the surprise shock. We find that these TFP max share estimators tend to be strongly biased when applied to data generated from DSGE models with shock processes that match the TFP moments in the data, both in the presence of TFP measurement error and in its absence. Incorporating a measure of TFP news into the VAR model and adapting the identification strategy substantially reduces the bias and RMSE of the impulse response estimates, even when there is sizable measurement error in the news variable. When applying this method to the data, we find that news shocks are slower to diffuse to TFP and have a smaller effect on real activity than implied by the TFP max share method.
Macroeconomic Responses to Uncertainty Shocks: The Perils of Recursive Orderings
Joint with Lutz Kilian and Michael Plante
Revised: April 24, 2024
Abstract: A common practice in empirical macroeconomics is to examine alternative recursive orderings of the variables in structural vector autoregressive (VAR) models. When the implied impulse responses look similar, the estimates are considered trustworthy. When they do not, the estimates are used to bound the true response without directly addressing the identification challenge. A leading example of this practice is the literature on the effects of uncertainty shocks on economic activity. We prove by counterexample and show by simulation that this practice is invalid, whether the data generating process is a structural VAR model or a dynamic stochastic general equilibrium model. Simulation evidence suggests that the underlying identification challenge can be addressed using an instrumental variables estimator.
COVID-19: A View from the Labor Market
Joint with Joshua Bernstein and Nathaniel Throckmorton
Abstract: This paper examines the response of the U.S. labor market to a large and persistent job separation rate shock, motivated by the ongoing economic effects of the COVID-19 pandemic. We use nonlinear methods to analytically and numerically characterize the responses of vacancy creation and unemployment. Vacancies decline in response to the shock when firms expect persistent job destruction and the number of unemployed searching for work is low. Quantitatively, under our baseline forecast the unemployment rate peaks at 19.7%, 2 months after the shock, and takes 1 year to return to 5%. Relative to a scenario without the shock, unemployment uncertainty rises by a factor of 3. Nonlinear methods are crucial. In the linear economy, the unemployment rate "only'' rises to 9.2%, vacancies increase, and uncertainty is unaffected. In both cases, the severity of the COVID-19 shock depends on the separation rate persistence.
Income Inequality and Current Account Imbalances
Joint with Michael Kumhof, Claire Lebarz, Romain Ranciere, and Nathaniel Throckmorton
Abstract: Econometric evidence shows that when higher income inequality and financial liberalization are added to a set of conventional explanatory variables, they predict significantly larger current account deficits in a cross-section of advanced economies. To study this mechanism, we develop a DSGE model where investors' income share increases at the expense of workers, and where workers respond by obtaining loans from domestic and foreign investors. This supports aggregate demand but generates current account deficits, especially if domestic financial markets are simultaneously liberalized. In emerging markets, because domestic workers cannot borrow, investors deploy their surplus funds abroad, leading to current account surpluses.
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