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WHITE-LATINO RESIDENTIAL ATTAINMENTS AND SEGREGATION
IN SIX CITIES: ASSESSING THE ROLE OF MICRO-LEVEL FACTORS
January 2016
Working Paper Number:
CES-16-51
This study examines the residential outcomes of Latinos in major metropolitan areas using new methods to connect micro-level analyses of residential attainments to overall patterns of segregation in the metropolitan area. Drawing on new formulations of standard measures of evenness, we conduct micro-level multivariate analyses using the restricted-use census microdata files to predict segregation-relevant neighborhood outcomes for individuals by race. We term the dependent variables segregation-relevant neighborhood outcomes because the differences in average outcomes for each group on these variables determine the values of the aggregate measures of evenness. This approach allows me to use standardization and components analysis to quantitatively assess the separate contributions that differences in social characteristics and differences in rates of return make towards determining the overall disparity in residential outcomes ' that is, the level of segregation ' between Whites and Latinos. Based on our micro-level residential attainment analyses we find that for Latinos, acculturation and gains in socioeconomic status are associated with greater residential contact with Whites, in agreement with spatial assimilation theory, which promotes lower segregation. However, our standardization and components analyses reveals that a substantial portion of White-Latino disparities in residential contact with Whites can be attributed to differences in rates of return; that is White-Latino differences in the ability to translate acculturation and gains in socioeconomic status into more residential contact with Whites. This is further elaborated upon by assessing the changes in contact with Whites for Whites and Latinos after manipulating single variables while holding all others constant. This can be interpreted as the role of discrimination which is emphasized by place stratification theory. Therefore we conclude that while members of minority groups make gains in residential outcomes that reduce segregation by attaining parity with Whites on social characteristics as spatial assimilation theory would predict, a substantial disparity will persist as Latinos cannot translate those gains into greater contact with Whites at the rate that Whites can. At the aggregate level of analysis, this means that White-Latino segregation remains substantial even when groups are equalized on social and economic characteristics.
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Are firm-level idiosyncratic shocks important for U.S. aggregate volatility?
January 2016
Working Paper Number:
CES-16-47
This paper assesses the quantitative impact of firm-level idiosyncratic shocks on aggregate volatility in the U.S. economy and provides a microfoundation for the negative relationship between firm-level volatility and size. I argue that the role of firm-specific shocks through the granular channel plays a fairly limited role in the U.S. economy. Using a novel, comprehensive data set compiled from several sources of the U.S. Census Bureau, I find that the granular com-ponent accounts at most for 15.5% of the variation in aggregate sales growth which is about half found by previous studies. To bridge the gap between previous findings and mine, I show that my quantitative results require deviations from Gibrat's law in which firm-level volatility and size are negatively related. I find that firm-level volatility declines at a substantially higher rate in size than previously found. Hence, the largest firms in the economy cannot be driving a sub-stantial fraction of macroeconomic volatility. I show that the explanatory power of granularity gets cut by at least half whenever the size-variance relationship, as estimated in the micro-level data, is taken into account. To uncover the economic mechanism behind this phenomenon, I construct an analytically tractable framework featuring random growth and a Kimball aggrega-tor. Under this setup, larger firms respond less to productivity shocks as the elasticity of demand is decreasing in size. Additionally, the model predicts a positive (negative) relationship between firm-level mark-ups (growth) and size. I confirm the predictions of the model by estimating size-varying price elasticities on unique product-level data from the Census of Manufactures (CM) and structurally estimating mark-ups using plant-level information from the Annual Survey of Manufactures (ASM).
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Introduction of Head Start and Maternal Labor Supply: Evidence from a Regression
Discontinuity Design
January 2016
Working Paper Number:
CES-16-35
I use the non-public decennial censuses in 1970 to investigate the effect of the Head Start program on maternal labor supply and schooling in its early years. I exploit a discontinuity in county-level Head Start funding beginning in the late 1960s to explore differences in countylevel maternal employment and maternal schooling. The results provide suggestive evidence that the more availability of Head Start led to an increase the nursery school enrollment of children and a decrease in maternal labor supply. In addition, the ITT estimates imply a relatively large, negative effect of enrollment on maternal labor supply. However, the estimates are somewhat sensitive to addition of covariates and the standard errors are also large to draw firm inferences.
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Cogeneration Technology Adoption in the U.S.
January 2016
Working Paper Number:
CES-16-30
Well over half of all electricity generated in recent years in Denmark is through cogeneration. In U.S., however, this number is only roughly eight percent. While both the federal and state governments provided regulatory incentives for more cogeneration adoption, the capacity added in the past five years have been the lowest since late 1970s. My goal is to first understand what are and their relative importance of the factors that drive cogeneration technology adoption, with an emphasis on estimating the elasticity of adoption with respect to relative energy input prices and regulatory factors. Very preliminary results show that with a 1 cent increase in purchased electricity price from 6 cents (roughly current average) to 7 cents per kwh, the likelihood of cogeneration technology adoption goes up by about 0.7-1 percent. Then I will try to address the general equilibrium effect of cogeneration adoption in the electricity generation sector as a whole and potentially estimate some key parameters that the social planner would need to determine the optimal cogeneration investment amount. Partial equilibrium setting does not consider the decrease in investment in the utilities sector when facing competition from the distributed electricity generators, and therefore ignore the effects from the change in equilibrium price of electricity. The competitive market equilibrium setting does not consider the externality in the reduction of CO2 emissions, and leads to socially sub-optimal investment in cogeneration. If we were to achieve the national goal to increase cogeneration capacity half of the current capacity by 2020, the US Department of Energy (DOE) estimated an annual reduction of 150 million metric tons of CO2 annually ' equivalent to the emissions from over 25 million cars. This is about five times the annual carbon reduction from deregulation and consolidation in the US nuclear power industry (Davis, Wolfram 2012). Although the DOE estimates could be an overly optimistic estimate, it nonetheless suggests the large potential in the adoption of cogeneration technology.
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The Management and Organizational Practices Survey (MOPS): An Overview*
January 2016
Working Paper Number:
CES-16-28
Understanding productivity and business dynamics requires measuring production outputs and inputs. Through its surveys and use of administrative data, the Census Bureau collects information on production outputs and inputs including labor, capital, energy, and materials. With the introduction of the Management and Organizational Practices Survey (MOPS), the Census Bureau added information on another component of production: management. It has long been hypothesized that management is an important component of firm success, but until recently the study of management was confined to hypotheses, anecdotes, and case studies. Building upon the work of Bloom and Van Reenen (2007), the first-ever large scale survey of management practices in the United States, the MOPS, was conducted by the Census Bureau for 2010. A second, enhanced version of the MOPS is being conducted for 2015. The enhancement includes two new topics related to management: data and decision making (DDD) and uncertainty. As information technology has expanded plants are increasingly able to utilize data in their decision making. Structured management practices have been found to be complementary to DDD in earlier studies. Uncertainty has policy implications because uncertainty is found to be associated with reduced investment and employment. Uncertainty also plays a role in the targeting component of management.
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Using Linked Survey and Administrative Data to Better Measure Income: Implications for Poverty, Program Effectiveness and Holes in the Safety Net
October 2015
Working Paper Number:
CES-15-35
We examine the consequences of underreporting of transfer programs in household survey data for several prototypical analyses of low-income populations. We focus on the Current Population Survey (CPS), the source of official poverty and inequality statistics, but provide evidence that our qualitative conclusions are likely to apply to other surveys. We link administrative data for food stamps, TANF, General Assistance, and subsidized housing from New York State to the CPS at the individual level. Program receipt in the CPS is missed for over one-third of housing assistance recipients, 40 percent of food stamp recipients and 60 percent of TANF and General Assistance recipients. Dollars of benefits are also undercounted for reporting recipients, particularly for TANF, General Assistance and housing assistance. We find that the survey data sharply understate the income of poor households, as conjectured in past work by one of the authors. Underreporting in the survey data also greatly understates the effects of anti-poverty programs and changes our understanding of program targeting, often making it seem that welfare programs are less targeted to both the very poorest and middle income households than they are. Using the combined data rather than survey data alone, the poverty reducing effect of all programs together is nearly doubled while the effect of housing assistance is tripled. We also re-examine the coverage of the safety net, specifically the share of people without work or program receipt. Using the administrative measures of program receipt rather than the survey ones often reduces the share of single mothers falling through the safety net by one-half or more.
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Wealth, Tastes, and Entrepreneurial Choice
October 2015
Working Paper Number:
CES-15-34
The nonpecuniary benefits of managing a small business are a first order consideration for many nascent entrepreneurs, yet the preference for business ownership is mostly ignored in models of entrepreneurship and occupational choice. In this paper, we study a population with varying entrepreneurial tastes and wealth in a simple general equilibrium model of occupational choice. This choice yields several important results: (1) entrepreneurship can be thought of as a normal good, generating wealth effects independent of any financing constraints; (2) nonpecuniary entrepreneurs select into small-scale firms; and (3) subsidies designed to stimulate more business entry can have regressive distributional effects. Despite abstracting from other important considerations such as risk, financing constraints, and innovation, we show that nonpecuniary compensation is particularly relevant in discussions of small businesses.
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The Promise and Potential of Linked Employer-Employee Data for Entrepreneurship Research
September 2015
Working Paper Number:
CES-15-29
In this paper, we highlight the potential for linked employer-employee data to be used in entrepreneurship research, describing new data on business start-ups, their founders and early employees, and providing examples of how they can be used in entrepreneurship research. Linked employer-employee data provides a unique perspective on new business creation by combining information on the business, workforce, and individual. By combining data on both workers and firms, linked data can investigate many questions that owner-level or firm-level data cannot easily answer alone - such as composition of the workforce at start-ups and their role in explaining business dynamics, the flow of workers across new and established firms, and the employment paths of the business owners themselves.
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Statistics on the International Trade Administration's Global Markets Program
September 2015
Working Paper Number:
CES-15-17
Recent mandates for evidence-based policy choices from both the Executive and Legislative branches of the federal government underscore the importance of understanding the relationship between program participation and business outcomes. In this paper, we examine the correlations between participation in an export-promotion program and business outcomes. We use this experience to provide more general lessons learned about combining program data on treatments with Census Bureau micro data that can be used as a control. Note this paper does not evaluate a program, but instead provides critical information about a program.
The mission of the Commercial Service/Global Markets program is to help companies either start or increase their exports of goods and services. It pursues this mission through advocacy, events, and counseling. This study looks at a very small part of the overall program. While we cannot rule-out several sources of bias in our results, we do observe several consistent patterns across our models. In particular, program participation is positively correlated with export growth and change and, for small businesses, also with positive employment growth. However, overall, and for large firms in particular, there is a negative correlation with employment growth and counseling. The paper concludes with a 'Lessons Learned' section that highlights areas where measurement can be improved.
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Business Dynamics of Innovating Firms: Linking U.S. Patents with Administrative Data on Workers and Firms
July 2015
Working Paper Number:
CES-15-19
This paper discusses the construction of a new longitudinal database tracking inventors and patent-owning firms over time. We match granted patents between 2000 and 2011 to administrative databases of firms and workers housed at the U.S. Census Bureau. We use inventor information in addition to the patent assignee firm name to and improve on previous efforts linking patents to firms. The triangulated database allows us to maximize match rates and provide validation for a large fraction of matches. In this paper, we describe the construction of the database and explore basic features of the data. We find patenting firms, particularly young patenting firms, disproportionally contribute jobs to the U.S. economy. We find patenting is a relatively rare event among small firms but that most patenting firms are nevertheless small, and that patenting is not as rare an event for the youngest firms compared to the oldest firms. While manufacturing firms are more likely to patent than firms in other sectors, we find most patenting firms are in the services and wholesale sectors. These new data are a product of collaboration within the U.S. Department of Commerce, between the U.S. Census Bureau and the U.S. Patent and Trademark Office.
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