Research

Heat Waves and Warming Trends: The Economic Impact of  Low and High Frequency  Climate Changes

with Nikolay Gospodinov and Serena Ng

November 2024

Abstract: Frequent heat waves and warming long-term trends are posing an imminent threat to all aspects of society, including sustainable economic development. In this paper, we study the separate effects of low-frequency and high-frequency changes in temperature on economic growth using cross-country and U.S. state data. We characterize the long-run covariability in the low-frequency components of temperature and growth, the presence of a common factor in these components as well as some interesting heterogeneity in the loadings of the individual low-frequency processes.

A Jackknife Variance Estimator for_Panel Regressions

with Richard K. Crump and Nikolay Gospodinov

FRBNY Staff Reports – October 2024

Abstract: We introduce a new jackknife variance estimator for panel-data regressions. Our variance estimator can be motivated as the conventional leave-one-out jackknife variance estimator on a transformed space of the regressors and residuals using orthonormal trigonometric basis functions. We prove the asymptotic validity of our variance estimator and demonstrate desirable finite-sample properties in a series of simulation experiments. We also illustrate how our method can be used for jackknife bias-correction in a variety of time-series settings.

A Simple Diagnostic for Time Series and Panel-Data Regressions

with Richard K. Crump and Nikolay Gospodinov

FRBNY Staff Reports – October 2024

Abstract: We introduce a new regression diagnostic, tailored to time-series and panel-data regressions, which characterizes the sensitivity of the OLS estimate to distinct time-series variation at different frequencies. The diagnostic is built on the novel result that the eigenvectors of a random walk asymptotically orthogonalize a wide variety of time-series processes. Our diagnostic is based on leave-one-out OLS estimation on transformed variables using these eigenvectors. We illustrate how our diagnostic allows applied researchers to scrutinize regression results and probe for underlying fragility of the sample OLS estimate. We demonstrate the utility of our approach using a variety of empirical applications.

The Nonlinear Case Against Leaning Against the Wind

with Nina Boyarchenko, Richard K. Crump, Keshav Dogra, and Leonardo Elias

FRBNY Staff Reports – May 2024

Abstract: We re-examine the relationship between monetary policy and financial stability in a setting that allows for nonlinear, time-varying relationships between monetary policy, financial stability, and macroeconomic outcomes. Using novel machine-learning techniques, we estimate a flexible “nonlinear VAR” for the stance of monetary policy, real activity, inflation, and financial conditions, and evaluate counterfactual evolutions of downside risk to real activity under alternative monetary policy paths. We find that a tighter path of monetary policy in 2003-05 would have increased the risk of adverse real outcomes three to four years ahead, especially if the tightening had been large or rapid. This suggests that there is limited evidence to support “leaning against the wind” even once one allows for rich nonlinearities, intertemporal dependence, and crisis predictability.

Analyzing Recent Price Anomalies in Argentina: Global Influences and Domestic Distortions

with Emiliano Basco, Emilio Blanco, and Luis Libonatti

forthcoming Latin American Journal of Central Banking

Abstract: This paper examines the evolution of goods prices in Argentina using a model with three key components: observable factors that affect marginal costs, local responses to global price trends, and time-varying markups. We estimate this model using a monthly international panel and compare the results across countries to assess how Argentina's price dynamics diverge from the global norm in the post-COVID period. Our findings suggest that exchange rate controls, non-tariff import barriers, and other economic policies have played a significant role in driving large markups, creating considerable deviations from the global norm and amplifying inflationary pressures.

"Zoned out of Opportunity": Causal Effect of Land Use Regulations on Adult Incomes

Senior Honors Thesis

Abstract: This paper uses a novel natural language processing technique – denominated concept recovery – to extract latent variables from the text of a large corpus of municipal regulations, in particular three 'concepts' relating to land use: 1) restrictions on intensive and extensive development, 2) minimum consumption requirements, and 3) 'regulatory taxes' (i.e. regulations that do not interdict development, but make it more expensive). With these estimands, we derive estimates of the causal effect of land-use regulations on the incomes in adulthood of children born in 2000 that grow up in urbanized areas. We find that land-use regulations have clear distributional consequences, advantaging children born to parents in the 75th percentile of the income distribution, while disadvantaging children born to parents in the 25th percentile of the income distribution.

Remote Learning and Parental Labor Market Outcomes

Junior Honors Term Paper

Abstract: This paper estimates the effects of remote learning on parental labor market outcomes. Using mobility indices, it captures school closures as they occur in real time, obviating the need for possibly erroneous or outdated survey data. The results suggest that if a parent having one child learning remotely corresponds to a 13% reduction in the odds of being employed, ceteris paribus. Disaggregating this effect by parental sex, it finds that school closures have an ambiguous impact on fathers, whereas mothers are affected at the intensive and extensive margin. These results are robust to alternative specifications, including to the use of a time-invariant state-level instrument and a Bartik instrument (as in Goldsmith-Pinkham et al. [2020]).

Look Out for Outlook-at-Risk

with Nina Boyarchenko, Richard K. Crump, and Leonardo Elias

Liberty Street Economics – May 2023

Introduction: The timely characterization of risks to the economic outlook plays an important role in both economic policy and private sector decisions. In a February 2023 Liberty Street Economics post, we introduced the concept of “Outlook-at-Risk”—that is, the downside risk to real activity and two-sided risks to inflation. Today we are launching Outlook-at-Risk as a regularly updated data product, with new readings for the conditional distributions of real GDP growth, the unemployment rate, and inflation to be published each month. In this post, we use the data on conditional distributions to investigate how two-sided risks to inflation and downside risks to real activity have evolved over the current and previous five monetary policy tightening cycles.

What is "Outlook-at-Risk"?

with Nina Boyarchenko, Richard K. Crump, and Leonardo Elias

Liberty Street Economics – February 2023

Introduction: The Federal Open Market Committee (FOMC) has increased the target range for the federal funds rate by 4.50 percentage points since March 16, 2022. In tightening the stance of monetary policy, the FOMC balances the risk of inflation remaining persistently high if the economy continues to run “hot” against the risk of unemployment rising as the economy cools. In this post, we review a quantitative approach to measuring the evolution of risks to real GDP growth, the unemployment rate, and inflation that is inspired by our previous work on “Vulnerable Growth.” We find that, in February, downside risks to real GDP growth and upside risks to unemployment moderated slightly, and upside risks to inflation continued to decline.