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This paper provides evidences of heterogeneous human-capital externality using CHIP 2002, 2007 and 2013 data from urban China. After instrumenting city-level education using the number of relocated university departments across cities in the 1950s, one year more city-level education increases individual hourly wage by 22.0 percent, more than twice the OLS estimate. Human-capital externality is found to be greater for all groups of urban residents in the instrumental variable estimation.
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We demonstrate that data from digital platforms such as Yelp have the potential to improve our understanding of gentrification, both by providing data in close to real time (i.e. nowcasting and forecasting) and by providing additional context about how the local economy is changing. Combining Yelp and Census data, we find that gentrification, as measured by changes in the educational, age, and racial composition within a ZIP code, is strongly associated with increases in the numbers of grocery stores, cafes, restaurants, and bars, with little evidence of crowd-out of other categories of businesses. We also find that changes in the local business landscape is a leading indicator of housing price changes, and that the entry of Starbucks (and coffee shops more generally) into a neighborhood predicts gentrification. Each additional Starbucks that enters a zip code is associated with a 0.5% increase in housing prices.
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The economic convergence of American regions has greatly slowed, and rates of long-term non-employment have even been diverging. Simultaneously, the rate of non-employment for working age men has nearly tripled over the last 50 years, generating a terrible social problem that is disproportionately centered in the eastern parts of the American heartland. Should more permanent economic divisions across space lead American economists to rethink their traditional skepticism about place-based policies? We document that increases in labor demand appear to have greater impacts on employment in areas where not working has been historically high, suggesting that subsidizing employment in such places could particularly reduce the not working rate. Pro-employment policies, such as a ramped up Earned Income Tax Credit, that are targeted towards regions with more elastic employment responses, however financed, could plausibly reduce suffering and materially improve economic performance.
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How do regions acquire the knowledge they need to diversify their economic activities? How does the migration of workers among firms and industries contribute to the diffusion of that knowledge? Here we measure the industry, occupation, and location specific knowledge carried by workers from one establishment to the next using a dataset summarizing the individual work history for an entire country. We study pioneer firms-firms operating in an industry that was not present in a region-because the success of pioneers is the basic unit of regional economic diversification. We find that the growth and survival of pioneers increase significantly when their first hires are workers with experience in a related industry, and with work experience in the same location, but not with past experience in a related occupation. We compare these results with new firms that are not pioneers and find that industry specific knowledge is significantly more important for pioneer than non-pioneer firms. To address endogeneity we use Bartik instruments, which leverage national fluctuations in the demand for an activity as shocks for local labor supply. The instrumental variable estimates support the finding that industry related knowledge is a predictor of the survival and growth of pioneer firms. These findings expand our understanding of the micro-mechanisms underlying regional economic diversification events.
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How much does the appearance of a house, or its neighbors, impact its price? Do events that impact the incentives facing homeowners, like foreclosure, impact the maintenance and appearance of a home? Using computer vision techniques, we find that a one standard deviation improvement in the appearance of a home in Boston is associated with a .16 log point increase in the home's value, or about $68,000 at the sample mean. The additional predictive power created by images is small relative to location and basic home variables, but external images do outperform variables collected by in-person home assessors. A home's value increases by .4 log points, when its neighbor's visually predicted value increases by one log point, and more visible neighbors have a larger price impact than less visible neighbors. Homes that went through foreclosure during the 2008-09 financial crisis experienced a .04 log point decline in their appearance-related value, relative to comparable homes, suggesting that foreclosures reduced the incentives to maintain the housing stock. We do not find more depreciation of appearance in rental properties, or more upgrading of appearance by owners before resale.
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This paper provides evidences of heterogeneous human-capital externality using CHIP 2002, 2007 and 2013 data from urban China. After instrumenting city-level education using the number of relocated university departments across cities in the 1950s, one year more city-level education increases individual hourly wage by 22.0 percent, more than twice the OLS estimate. Human-capital externality is found to be greater for all groups of urban residents in the instrumental variable estimation.
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How do regions acquire the knowledge they need to diversify their economic activities? How does the migration of workers among firms and industries contribute to the diffusion of that knowledge? Here we measure the industry, occupation, and location specific knowledge carried by workers from one establishment to the next using a dataset summarizing the individual work history for an entire country. We study pioneer firms-firms operating in an industry that was not present in a region-because the success of pioneers is the basic unit of regional economic diversification. We find that the growth and survival of pioneers increase significantly when their first hires are workers with experience in a related industry, and with work experience in the same location, but not with past experience in a related occupation. We compare these results with new firms that are not pioneers and find that industry specific knowledge is significantly more important for pioneer than non-pioneer firms. To address endogeneity we use Bartik instruments, which leverage national fluctuations in the demand for an activity as shocks for local labor supply. The instrumental variable estimates support the finding that industry related knowledge is a predictor of the survival and growth of pioneer firms. These findings expand our understanding of the micro-mechanisms underlying regional economic diversification events.
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