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Discussion Paper
How Have Racial and Ethnic Earnings Gaps Changed after COVID-19?
Chatterji-Len, Kasey; García, Daniel I.; Pinkovskiy, Maxim L.; Chakrabarti, Rajashri (2022-10-20)
Racial and ethnic earnings disparities have been salient features of the U.S. economy for decades. Between the pandemic-driven recession in 2020 and the rising inflation since 2021, workers’ real and nominal earnings have seen rapid change. To get a sense of how recent economic conditions have affected earnings disparities, we examine real and nominal weekly earnings trends for Asian, Black, Hispanic, and white workers. We find that average real weekly earnings have been declining in the past year, but less so for Black and Hispanic workers than for white and Asian workers. Black and ...
Liberty Street Economics , Paper 20221020a

Discussion Paper
Understanding the Racial and Income Gap in COVID-19: Social Distancing, Pollution, and Demographics
Chakrabarti, Rajashri; Pinkovskiy, Maxim L.; http://fedora:8080/fcrepo/rest/objects/authors/; Meyerson, Lindsay (2021-01-12)
This is the third post in a series looking to explain the gap in COVID-19 intensity by race and by income. In the first two posts, we have investigated whether comorbidities, uninsurance, hospital resources, and home and transit crowding help explain the income and minority gaps. Here, we continue our investigation by looking at three additional potential channels: the fraction of elderly people, pollution, and social distancing at the beginning of the pandemic in the county. We aim to understand whether these three factors affect overall COVID-19 intensity, whether the income and racial gaps ...
Liberty Street Economics , Paper 20210112c

Discussion Paper
Understanding the Racial and Income Gap in COVID-19: Essential Workers
Avtar, Ruchi; Chakrabarti, Rajashri; Pinkovskiy, Maxim L. (2021-01-12)
This is the fourth and final post in this series aimed at understanding the gap in COVID-19 intensity by race and by income. The previous three posts focused on the role of mediating variables—such as uninsurance rates, comorbidities, and health resource in the first post; public transportation, and home crowding in the second; and social distancing, pollution, and age composition in the third—in explaining the racial and income gap in the incidence of COVID-19. In this post, we now investigate the role of employment in essential services in explaining this gap.
Liberty Street Economics , Paper 20210112d

Report
Newer need not be better: evaluating the Penn World Tables and the World Development Indicators using nighttime lights
Pinkovskiy, Maxim L.; Sala-i-Martin, Xavier X. (2016-06-01)
Nighttime lights data are a measure of economic activity whose measurement error is plausibly independent of the errors of most conventional indicators. Therefore, we can use nighttime lights as an independent benchmark to assess existing measures of economic activity (Pinkovskiy and Sala-i-Martin 2016). We employ this insight to find out which vintages of the Penn World Tables (PWT) and of the World Development Indicators (WDI) better estimate true income per capita. We find that revisions of the PWT do not necessarily dominate their predecessors in terms of explaining nighttime lights (and ...
Staff Reports , Paper 778

Discussion Paper
Why New York City Subway Delays Don't Affect All Riders Equally
Pinkovskiy, Maxim L.; Gorton, Nicole (2018-06-27)
The state of the New York City subway system has worsened considerably over the past few years. As a consequence of rising ridership and decaying infrastructure, the network is plagued by delays and frequently fails to deliver New Yorkers to their destinations on time. While these delays are a headache for anyone who depends on the subway to get around, they do not affect all riders in the same way. In this post, we explain why subway delays disproportionately affect low-income New Yorkers. We show that wealthier commuters who rely on the subway are less likely to experience extensive issues ...
Liberty Street Economics , Paper 20180627

Report
Understanding the Linkages between Climate Change and Inequality in the United States
Avtar, Ruchi; Blickle, Kristian S.; Chakrabarti, Rajashri; Janakiraman, Janavi; Pinkovskiy, Maxim L. (2021-11-01)
We conduct a review of the existing academic literature to outline possible links between climate change and inequality in the United States. First, researchers have shown that the impact of both physical and transition risks may be uneven across location, income, race, and age. This is driven by a region’s geography as well as its adaptation capabilities. Second, measures that individuals and governments take to adapt to climate change and transition to lower emissions risk increasing inequality. Finally, while federal aid and insurance coverage can mitigate the direct impact of physical ...
Staff Reports , Paper 991

Discussion Paper
Rural Households Hit Hardest by Inflation in 2021-22
Chakrabarti, Rajashri; Garcia, Dan; Pinkovskiy, Maxim L. (2023-01-18)
To conclude our series, we present disparities in inflation rates by U.S. census region and rural status between June 2019 and the present. Notably, rural households were hit by inflation the hardest during the 2021-22 inflationary episode. This is intuitive, as rural households rely on transportation, and especially on motor fuel, to a much greater extent than urban households do. More generally, the recent rise in inflation has affected households in the South more than the national average, and households in the Northeast by less than the national average, though this difference has ...
Liberty Street Economics , Paper 20230118c

Report
Estimating dynamic panel models: backing out the Nickell Bias
Pinkovskiy, Maxim L.; Hausman, Jerry A. (2017-10-01)
We propose a novel estimator for the dynamic panel model, which solves the failure of strict exogeneity by calculating the bias in the first-order conditions as a function of the autoregressive parameter and solving the resulting equation. We show that this estimator performs well as compared with approaches in current use. We also propose a general method for including predetermined variables in fixed-effects panel regressions that appears to perform well.
Staff Reports , Paper 824

Discussion Paper
Did State Reopenings Increase Consumer Spending?
Chakrabarti, Rajashri; Heise, Sebastian; Melcangi, Davide; Pinkovskiy, Maxim L.; Topa, Giorgio (2020-09-18)
The spread of COVID-19 in the United States has had a profound impact on economic activity. Beginning in March, most states imposed severe restrictions on households and businesses to slow the spread of the virus. This was followed by a gradual loosening of restrictions (“reopening”) starting in April. As the virus has re-emerged, a number of states have taken steps to reverse the reopening of their economies. For example, Texas and Florida closed bars again in June, and Arizona additionally paused operations of gyms and movie theatres. Taken together, these measures raise the question of ...
Liberty Street Economics , Paper 20200918b

Discussion Paper
The Affordable Care Act and For-Profit Colleges
Chakrabarti, Rajashri; Pinkovskiy, Maxim L. (2020-02-05)
Getting health insurance in America is intimately connected to choosing whether and where to work. Therefore, it should not be surprising that the U.S. health insurance market may influence, and be influenced by, the market for higher education—which itself is closely tied to the labor market. In this post, and the staff report it is based on, we investigate the effects of the largest overhaul of health insurance in the United States in recent decades—the Patient Protection and Affordable Care Act of 2010 (ACA) -- on college enrollment choices.
Liberty Street Economics , Paper 20200205

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