Found 26 article(s) for author 'Raj Chetty'

Creating Moves to Opportunity: Experimental Evidence on Barriers to Neighborhood Choice

Creating Moves to Opportunity: Experimental Evidence on Barriers to Neighborhood Choice. Raj Chetty, Nathaniel Hendren, Lawrence Katz, August 2019, Paper, “Low-income families in the United States tend to live in neighborhoods that offer limited opportunities for upward income mobility. One potential explanation for this pattern is that families prefer such neighborhoods for other reasons, such as affordability or proximity to family and jobs. An alternative explanation is that they do not move to high-opportunity areas because of barriers that prevent them from making such moves. We test between these two explanations using a randomized controlled trial with housing voucher recipients in Seattle and King County. We provided services to reduce barriers to moving to high-upward-mobility neighborhoods: customized search assistance, landlord engagement, and short-term financial assistance. The intervention increased the fraction of families who moved to high-upward-mobility areas from 14% in the control group to 54% in the treatment group.Link

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Do Tax Cuts Produce more Einsteins? The Impacts of Financial Incentives Versus Exposure to Innovation on the Supply of Inventors

Do Tax Cuts Produce more Einsteins? The Impacts of Financial Incentives Versus Exposure to Innovation on the Supply of Inventors. Raj Chetty, April 12, 2019, Paper, “Many countries provide financial incentives to spur innovation, ranging from tax incentives to research and development grants. In this paper, we study how such financial incentives affect individuals’ decisions to pursue careers in innovation. We first present empirical evidence on inventors’ career trajectories and income distributions using deidentified data on 1.2 million inventors from patent records linked to tax records in the United States. We find that the private returns to innovation are extremely skewed—with the top 1% of inventors collecting more than 22% of total inventors’ income—and are highly correlated with their social impact, as measured by citations. Inventors tend to have their most impactful innovations around age 40 and their incomes rise rapidly just before they have high-impact patents. We then build a stylized model of inventor career choice that matches these facts as well as recent evidence that childhood exposure to innovation plays a critical role in determining whether individuals become inventors. The model predicts that financial incentives, such as top income tax reductions, have limited potential to increase aggregate innovation because they only affect individuals who are exposed to innovation and have essentially no impact on the decisions of star inventors, who matter most for aggregate innovation.Link

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Do Tax Cuts Produce More Einsteins? The Impact of Financial Incentives vs. Exposure to Innovation on the Supply of Inventors

Do Tax Cuts Produce More Einsteins? The Impact of Financial Incentives vs. Exposure to Innovation on the Supply of Inventors. Raj Chetty, January 2019, Paper, “Many countries provide financial incentives to spur innovation, ranging from tax incentives to research and development grants. In this paper, we study how such financial incentives affect individuals’ decisions to pursue careers in innovation. We _first present empirical evidence on inventors’ career trajectories and income distributions using de-identified data on 1.2 million inventors from patent records linked to tax records in the U.S. We find that the private returns to innovation are extremely skewed – with the top 1% of inventors collecting more than 22% of total inventors’ income – and are highly correlated with their social impact, as measured by citations. Inventors tend to have their most impactful innovations around age 40 and their incomes rise rapidly just before they have high-impact patents. We then build a stylized model of inventor career choice that matches these facts as well as recent evidence that childhood exposure to innovation plays a critical role in determining whether individuals become inventors.Link

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The American Dream Is Harder To Find In Some Neighborhoods

The American Dream Is Harder To Find In Some Neighborhoods. Raj Chetty, 10/1/18, Audio, “Does the neighborhood you grow up in determine how far you move up the economic ladder? A new online data tool being made public Monday finds a strong correlation between where people are raised and their chances of achieving the American dream.Link

Opportunity Atlas –

https://www.opportunityatlas.org/

 

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Race and Economic Opportunity in the United States: An Intergenerational Perspective

Race and Economic Opportunity in the United States: An Intergenerational Perspective. Raj Chetty, Nathaniel Hendren, March 2018, Paper, “We study the sources of racial and ethnic disparities in income using de-identified longitudinal data covering nearly the entire U.S. population from 1989-2015. We document three sets of results. First, the intergenerational persistence of disparities varies substantially across racial groups. For example, Hispanic Americans are moving up significantly in the income distribution across generations because they have relatively high rates of intergenerational income mobility. In contrast, black Americans have substantially lower rates of upward mobility and higher rates of downward mobility than whites, leading to large income disparities that persist across generations.Link

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Lost Einsteins: How exposure to innovation influences who becomes an inventor

Lost Einsteins: How exposure to innovation influences who becomes an inventor. Raj Chetty, January 23, 2018, Paper, “Relatively little is known about the factors that induce people to become inventors. Using data on the lives of over one million inventors in the US, this column sheds light on what policies can be most effective in increasing innovation. In particular, it shows that increasing exposure to innovation among women, minorities, and children from low-income families may have greater potential to spark innovation and growth than traditional approaches such as reducing tax rates.Link

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The Impact of Neighborhoods on Intergenerational Mobility II: County-Level Estimate

The Impact of Neighborhoods on Intergenerational Mobility II: County-Level Estimate. Raj Chetty, Nathaniel Hendren, 2016, Paper, “We characterize the effects of neighborhoods on children’s earnings and other outcomes in adulthood by studying more than five million families who move across counties in the U.S. We identify the causal effect of growing up in every county in the U.S. by estimating a fixed effects model identified from families who move across counties with children of different ages. We use these estimates to quantify the size of place effects, construct optimal forecasts of the causal effect for each place, and study the characteristics of places that cause higher (and lower) economic outcomes.Link

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The Fading American Dream: Trends in Absolute Income Mobility Since 1940

The Fading American Dream: Trends in Absolute Income Mobility Since 1940. Raj Chetty, 2016, Paper, “One of the defining features of the “American Dream” is the ideal that children have a higher standard of living than their parents. We assess whether the U.S. is living up to this ideal by estimating rates of “absolute income mobility” – the fraction of children who earn more than their parents – since 1940.Link

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Improving Opportunities for Economic Mobility

Improving Opportunities for Economic Mobility. Raj Chetty, Fall 2016, Paper, “The American dream is a complicated concept, but I’d like to distill it down to a simple statistic that we are able to measure with data: the probability that a child born to parents in the bottom fifth of the income distribution makes the leap all the way to the top fifth of the income distribution.Link

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The Association Between Income and Life Expectancy in the United States, 2001-2014

The Association Between Income and Life Expectancy in the United States, 2001-2014. Raj Chetty, April 10, 2016, Paper. “Importance: The relationship between income and life expectancy is well established but remains poorly understood.  Objectives” To measure the level, time trend, and geographic variability in the association between income and life expectancy and to identify factors related to small area variation.  Design and Setting: Income data for the US population were obtained from 1.4 billion deidentified tax records between 1999 and 2014. Mortality data were obtained from Social Security Administration death records. These data were used to estimate race- and ethnicity-adjusted life expectancy at 40 years of age by household income percentile, sex, and geographic area, and to evaluate factors associated with differences in life expectancy.Link

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