D-Lab

Current Research Projects

Current Berkeley FSRDC Projects Using Data from the U.S. Census Bureau

"Quantifying the Eligibility, Enrollment, and Retention of Low- and Moderate-Income Populations in Means-Tested Programs" 

This research will quantify short-run earnings volatility among low- and moderate-income families in California to estimate the incidence of family income changes and gauge implications for means-tested public insurance program eligibility. Moreover, this project will examine uptake of insurance programs and assess causes of disenrollment. To identify low- and moderate-income families in California, quantify earnings volatility, and assess public insurance eligibility, we will use quarterly earnings records contained in the Employment History File from the Longitudinal Employer-Household Dynamics (LEHD) program linked to household records in the American Community Survey and Current Population Survey, and person-level characteristics in the LEHD Individual Characteristics File. To this, we will link Medicaid Statistics Information Systems records, in order to capture spells of enrollment to Medicaid and SCHIP. With this, we will generate measures of inappropriate disenrollment (program drop-out despite continuing eligibility) and legitimate disenrollment where return to these programs occurs in a short period of time (churning). In 2014, millions of Americans became eligible for government-subsidized health insurance programs where eligibility is determined by income falling within precisely defined ranges. We find it important to know whether eligible individuals have taken up benefits and, for families with more variable incomes, whether the costs of maintaining enrollment result in an increased likelihood of churning—moving off and then back on a program within a short period of time—which is costly both for households and programs.

"Energy and the Environment - Plant-Level Production and Market-Level Incidence"

The extent to which environmental, energy, and other types of regulations influence firm-level production decisions has important implications for aggregate welfare and distributional incidence. Empirical research in this area is limited though growing. Much economic research on environmental regulation and environmental goods still compares how "clean" versus "dirty" industries respond to different regulatory or economic forces. However, the availability of firm and plant-level data makes it possible to recognize that firms within an industry differ very widely. Even within a narrowly defined industry firms differ enormously in the quantity and mix of pollutants that they emit, in the stringency of regulations they face, in productivity, trade exposure, market power, product quality, input mix, and product mix. Some of these differences may reflect measurement error or idiosyncratic productivity shocks, but others reflect fundamental economic forces. The lack of high-quality, firm or plant level microdata has substantially limited research in this area. 

"Technology Lock-In: Evidence from U.S. Manufacturing"

This project aims to quantify the extent to which initial market conditions determine manufacturing establishments' subsequent input mix. We focus on the role of initial energy prices for short and long-run energy usage as an example of this technology lock-in. We propose to conduct this analysis using data from the Annual Survey of Manufactures, the Census of Manufactures, the Longitudinal Business Database, the Manufacturing Energy Consumption Survey, the Annual Capital Expenditure Survey, and the Survey of Pollution Abatement Costs & Expenditures from the Census Bureau, in combination with several external data sources on U.S. energy prices. First, we will use these data sets to provide new descriptive evidence on the importance of energy prices in the year of an establishment's entry for subsequent energy efficiency, summarizing the effects by entry cohort and by initial energy price. Second, we will estimate a dynamic structural model of entry, exit, and capital investment to simulate how the energy intensity of production would change for entrant and incumbent establishments under several counterfactual market conditions. Our goal is to use the structural model to study how raising energy prices and reducing capital adjustment costs affect the investment decisions and the input mix of U.S. manufacturing establishments.