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Within and Across County Variation in SNAP Misreporting: Evidence from Linked ACS and Administrative Records
July 2014
Working Paper Number:
carra-2014-05
This paper examines sub-state spatial and temporal variation in misreporting of participation in the Supplemental Nutrition Assistance Program (SNAP) using several years of the American Community Survey linked to SNAP administrative records from New York (2008-2010) and Texas (2006-2009). I calculate county false-negative (FN) and false-positive (FP) rates for each year of observation and find that, within a given state and year, there is substantial heterogeneity in FN rates across counties. In addition, I find evidence that FN rates (but not FP rates) persist over time within counties. This persistence in FN rates is strongest among more populous counties, suggesting that when noise from sampling variation is not an issue, some counties have consistently high FN rates while others have consistently low FN rates. This finding is important for understanding how misreporting might bias estimates of sub-state SNAP participation rates, changes in those participation rates, and effects of program participation. This presentation was given at the CARRA Seminar, June 27, 2013
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A METHOD OF CORRECTING FOR MISREPORTING APPLIED TO THE FOOD STAMP PROGRAM
May 2013
Working Paper Number:
CES-13-28
Survey misreporting is known to be pervasive and bias common statistical analyses. In this paper, I first use administrative data on SNAP receipt and amounts linked to American Community Survey data from New York State to show that survey data can misrepresent the program in important ways. For example, more than 1.4 billion dollars received are not reported in New York State alone. 46 percent of dollars received by house- holds with annual income above the poverty line are not reported in the survey data, while only 19 percent are missing below the poverty line. Standard corrections for measurement error cannot remove these biases. I then develop a method to obtain consistent estimates by combining parameter estimates from the linked data with publicly available data. This conditional density method recovers the correct estimates using public use data only, which solves the problem that access to linked administrative data is usually restricted. I examine the degree to which this approach can be used to extrapolate across time and geography, in order to solve the problem that validation data is often based on a convenience sample. I present evidence from within New York State that the extent of heterogeneity is small enough to make extrapolation work well across both time and geography. Extrapolation to the entire U.S. yields substantive differences to survey data and reduces deviations from official aggregates by a factor of 4 to 9 compared to survey aggregates.
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Optimal Stratified Sampling for Probability-Based Online Panels
September 2025
Working Paper Number:
CES-25-69
Online probability-based panels have emerged as a cost-efficient means of conducting surveys in the 21st century. While there have been various recent advancements in sampling techniques for online panels, several critical aspects of sampling theory for online panels are lacking. Much of current sampling theory from the middle of the 20th century, when response rates were high, and online panels did not exist. This paper presents a mathematical model of stratified sampling for online panels that takes into account historical response rates and survey costs. Through some simplifying assumptions, the model shows that the optimal sample allocation for online panels can largely resemble the solution for a cross-sectional survey. To apply the model, I use the Census Household Panel to show how this method could improve the average precision of key estimates. Holding fielding costs constant, the new sample rates improve the average precision of estimates between 1.47 and 17.25 percent, depending on the importance weight given to an overall population mean compared to mean estimates for racial and ethnic subgroups.
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Individual Changes in Identification with Hispanic Ethnic Origins: Evidence from Linked 2000 and 2010 Census Data
August 2018
Working Paper Number:
carra-2018-08
Population estimates and demographic profiles are central to both academic and public debates about immigration, immigrant assimilation, and minority mobility. Analysts' conclusions are shaped by the choices that survey respondents make about how to identify themselves on surveys, but such choices change over time. Using linked responses to the 2000 and 2010 Censuses, our paper examines the extent to which individuals change between specific Hispanic categories such as Mexican origin. We first examine how changes in identification affect population change for national and regional origin groups. We then examine patterns of entry and exit to understand which groups more often switch between a non-Hispanic, another specific origin, or a general Hispanic identification. Finally, we profile who is most likely to change identification. Our findings affirm the fluidity of ethnic identification, especially between categories of Hispanic origin, which in turn carries important implications for population and compositional changes.
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The Cross-Section of Labor Leverage and Equity Returns*
January 2017
Working Paper Number:
CES-17-70
We study labor-induced operating leverage. Theoretically, we show that if labor markets are frictionless, two sufficient conditions for the existence of labor leverage are (a) relatively smooth wages and (b) a capital-labor elasticity of substitution strictly less than one. Our model provides theoretical support for the use of labor share'the ratio of labor expenses to value added'as a measure of labor leverage. We provide evidence for conditions (a) and (b), and we demonstrate the economic significance of labor leverage: High labor-share firms have operating profits that are more sensitive to economic shocks and have higher expected returns.
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Examining Racial Identity Responses Among People with Middle Eastern and North African Ancestry in the American Community Survey
March 2024
Working Paper Number:
CES-24-14
People with Middle Eastern and North African (MENA) backgrounds living in the United States are defined and classified as White by current Federal standards for race and ethnicity, yet many MENA people do not identify as White in surveys, such as those conducted by the U.S. Census Bureau. Instead, they often select 'Some Other Race', if it is provided, and write in MENA responses such as Arab, Iranian, or Middle Eastern. In processing survey data for public release, the Census Bureau classifies these responses as White in accordance with Federal guidance set by the U.S. Office of Management and Budget. Research that uses these edited public data relies on limited information on MENA people's racial identification. To address this limitation, we obtained unedited race responses in the nationally representative American Community Survey from 2005-2019 to better understand how people of MENA ancestry report their race. We also use these data to compare the demographic, cultural, socioeconomic, and contextual characteristics of MENA individuals who identify as White versus those who do not identify as White. We find that one in four MENA people do not select White alone as their racial identity, despite official guidance that defines 'White' as people having origins in any of the original peoples of Europe, the Middle East, or North Africa. A variety of individual and contextual factors are associated with this choice, and some of these factors operate differently for U.S.-born and foreign-born MENA people living in the United States.
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Who's Most Exposed to International Shocks? Estimating Differences in Import Price Sensitivity across U.S. Demographic Groups
March 2023
Working Paper Number:
CES-23-13R
Differences in consumption patterns across demographic groups mean that international price shocks differentially affect such groups. We construct import price indexes for U.S. households that vary by age, race, marital status, education, and urban status. Black households and urban households experienced significantly higher import price inflation from 1996-2018 compared to other groups, such as white households and rural households. Sensitivity to international price shocks varies widely, implying movements in exchange rates and foreign prices, both during our sample and during the Covid-19 pandemic, drove sizable differences in import price inflation ' and total inflation ' across households.
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Experimental Capture/recapture Estimation Using Census and Administrative Data
June 2026
Working Paper Number:
CES-26-38
This report expands upon the innovation of utilizing administrative records and third-party data implemented in the 2020 Census. The 2020 Census used administrative records and third-party data in address canvassing and nonresponse followup operations. The Census Bureau also has a long history of using administrative records of births, deaths, and other information to produce Demographic Analysis coverage estimates. Since 1980, the Census Bureau has produced capture-recapture coverage estimates by conducting an independent post-enumeration survey and utilizing dual system estimation approaches. This report presents the research results of attempting to see if administrative records and third-party data could be utilized to produce capture-recapture coverage estimates. This work uses an Expectation Maximization Log Linear Modeling approach previously researched by Statistics Netherlands and Statistics New Zealand. This report documents some of the experimental results from an evaluation that was part of the 2020 Census Program for Evaluation, Experiments, and Assessments.
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Research and/or Development? Financial Frictions and Innovation Investment
August 2023
Working Paper Number:
CES-23-39
U.S. firms have reduced their investment in scientific research ('R') compared to product development ('D'), raising questions about the returns to each type of investment, and about the reasons for this shift. We use Census data that disaggregates 'R' from 'D' to study how US firms adjust their innovation investments in response to an external increase in funding cost. Companies with greater demand for refinancing during the 2008 financial crisis, made larger cuts to R&D investment. This reduction in R&D is achieved almost entirely by reducing investment in research. Development remains essentially unchanged. If other firms patenting similar technologies must refinance, however, then Development investment declines. We interpret the latter result as evidence of technological competition: firms are reluctant to cut Development expenditures when that could place them at a disadvantage compared to potential rivals.
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Aggregating From Micro to Macro Patterns of Trade
February 2018
Working Paper Number:
CES-18-10
We develop a new framework for aggregating from micro to macro patterns of trade. We derive price indexes that determine comparative advantage across countries and sectors and the aggregate cost of living. If firms and products are imperfect substitutes, we show that these price indexes depend on variety, average demand/quality and the dispersion of demand/quality-adjusted prices, and are only weakly related to standard empirical measures of average prices, thereby providing insight for elasticity puzzles. Of the cross-section (time-series) variation in comparative advantage, 50 (90) percent is accounted for by variety and average demand/quality, with average prices contributing less than 10 percent.
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