Papers Containing Keywords(s): 'estimator'
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John M. Abowd - 3
Viewing papers 1 through 10 of 32
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Working PaperIncorporating Administrative Data in Survey Weights for the Basic Monthly Current Population Survey
January 2024
Working Paper Number:
CES-24-02
Response rates to the Current Population Survey (CPS) have declined over time, raising the potential for nonresponse bias in key population statistics. A potential solution is to leverage administrative data from government agencies and third-party data providers when constructing survey weights. In this paper, we take two approaches. First, we use administrative data to build a non-parametric nonresponse adjustment step while leaving the calibration to population estimates unchanged. Second, we use administratively linked data in the calibration process, matching income data from the Internal Return Service and state agencies, demographic data from the Social Security Administration and the decennial census, and industry data from the Census Bureau's Business Register to both responding and nonresponding households. We use the matched data in the household nonresponse adjustment of the CPS weighting algorithm, which changes the weights of respondents to account for differential nonresponse rates among subpopulations. After running the experimental weighting algorithm, we compare estimates of the unemployment rate and labor force participation rate between the experimental weights and the production weights. Before March 2020, estimates of the labor force participation rates using the experimental weights are 0.2 percentage points higher than the original estimates, with minimal effect on unemployment rate. After March 2020, the new labor force participation rates are similar, but the unemployment rate is about 0.2 percentage points higher in some months during the height of COVID-related interviewing restrictions. These results are suggestive that if there is any nonresponse bias present in the CPS, the magnitude is comparable to the typical margin of error of the unemployment rate estimate. Additionally, the results are overall similar across demographic groups and states, as well as using alternative weighting methodology. Finally, we discuss how our estimates compare to those from earlier papers that calculate estimates of bias in key CPS labor force statistics. This paper is for research purposes only. No changes to production are being implemented at this time.View Full Paper PDF
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Working PaperThe 2010 Census Confidentiality Protections Failed, Here's How and Why
December 2023
Working Paper Number:
CES-23-63
Using only 34 published tables, we reconstruct five variables (census block, sex, age, race, and ethnicity) in the confidential 2010 Census person records. Using the 38-bin age variable tabulated at the census block level, at most 20.1% of reconstructed records can differ from their confidential source on even a single value for these five variables. Using only published data, an attacker can verify that all records in 70% of all census blocks (97 million people) are perfectly reconstructed. The tabular publications in Summary File 1 thus have prohibited disclosure risk similar to the unreleased confidential microdata. Reidentification studies confirm that an attacker can, within blocks with perfect reconstruction accuracy, correctly infer the actual census response on race and ethnicity for 3.4 million vulnerable population uniques (persons with nonmodal characteristics) with 95% accuracy, the same precision as the confidential data achieve and far greater than statistical baselines. The flaw in the 2010 Census framework was the assumption that aggregation prevented accurate microdata reconstruction, justifying weaker disclosure limitation methods than were applied to 2010 Census public microdata. The framework used for 2020 Census publications defends against attacks that are based on reconstruction, as we also demonstrate here. Finally, we show that alternatives to the 2020 Census Disclosure Avoidance System with similar accuracy (enhanced swapping) also fail to protect confidentiality, and those that partially defend against reconstruction attacks (incomplete suppression implementations) destroy the primary statutory use case: data for redistricting all legislatures in the country in compliance with the 1965 Voting Rights Act.View Full Paper PDF
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Working PaperMixed-Effects Methods For Search and Matching Research
September 2023
Working Paper Number:
CES-23-43
We study mixed-effects methods for estimating equations containing person and firm effects. In economics such models are usually estimated using fixed-effects methods. Recent enhancements to those fixed-effects methods include corrections to the bias in estimating the covariance matrix of the person and firm effects, which we also consider.View Full Paper PDF
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Working PaperImproving Estimates of Neighborhood Change with Constant Tract Boundaries
May 2022
Working Paper Number:
CES-22-16
Social scientists routinely rely on methods of interpolation to adjust available data to their research needs. This study calls attention to the potential for substantial error in efforts to harmonize data to constant boundaries using standard approaches to areal and population interpolation. We compare estimates from a standard source (the Longitudinal Tract Data Base) to true values calculated by re-aggregating original 2000 census microdata to 2010 tract areas. We then demonstrate an alternative approach that allows the re-aggregated values to be publicly disclosed, using 'differential privacy' (DP) methods to inject random noise to protect confidentiality of the raw data. The DP estimates are considerably more accurate than the interpolated estimates. We also examine conditions under which interpolation is more susceptible to error. This study reveals cause for greater caution in the use of interpolated estimates from any source. Until and unless DP estimates can be publicly disclosed for a wide range of variables and years, research on neighborhood change should routinely examine data for signs of estimation error that may be substantial in a large share of tracts that experienced complex boundary changes.View Full Paper PDF
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Working PaperMisallocation or Mismeasurement?
February 2020
Working Paper Number:
CES-20-07
The ratio of revenue to inputs differs greatly across plants within countries such as the U.S. and India. Such gaps may reflect misallocation which hinders aggregate productivity. But differences in measured average products need not reflect differences in true marginal products. We propose a way to estimate the gaps in true marginal products in the presence of measurement error. Our method exploits how revenue growth is less sensitive to input growth when a plant's average products are overstated by measurement error. For Indian manufacturing from 1985'2013, our correction lowers potential gains from reallocation by 20%. For the U.S. the effect is even more dramatic, reducing potential gains by 60% and eliminating 2/3 of a severe downward trend in allocative efficiency over 1978'2013.View Full Paper PDF
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Working PaperMANAGING TRADE: EVIDENCE FROM CHINA AND THE US
May 2019
Working Paper Number:
CES-19-15
We present a heterogeneous-firm model in which management ability increases both production efficiency and product quality. Combining six micro-datasets on management practices, production and trade in Chinese and American firms, we find broad support for the model's predictions. First, better managed firms are more likely to export, sell more products to more destination countries, and earn higher export revenues and profits. Second, better managed exporters have higher prices, higher quality, and lower quality-adjusted prices. Finally, they also use a wider range of inputs, higher quality and more expensive inputs, and imported inputs from more advanced countries. The structural estimates indicate that management is important for improving production efficiency and product quality in both countries, but it matters more in China than in the US, especially for product quality. Panel analysis for the US and a randomized control trial in India suggest that management exerts causal effects on product quality, production efficiency, and exports. Poor management practices may thus hinder trade and growth, especially in developing countries.View Full Paper PDF
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Working PaperThe Distributional Effects of Minimum Wages: Evidence from Linked Survey and Administrative Data
March 2018
Working Paper Number:
carra-2018-02
States and localities are increasingly experimenting with higher minimum wages in response to rising income inequality and stagnant economic mobility, but commonly used public datasets offer limited opportunities to evaluate the extent to which such changes affect earnings growth. We use administrative earnings data from the Social Security Administration linked to the Current Population Survey to overcome important limitations of public data and estimate effects of the minimum wage on growth incidence curves and income mobility profiles, providing insight into how cross-sectional effects of the minimum wage on earnings persist over time. Under both approaches, we find that raising the minimum wage increases earnings growth at the bottom of the distribution, and those effects persist and indeed grow in magnitude over several years. This finding is robust to a variety of specifications, including alternatives commonly used in the literature on employment effects of the minimum wage. Instrumental variables and subsample analyses indicate that geographic mobility likely contributes to the effects we identify. Extrapolating from our estimates suggests that a minimum wage increase comparable in magnitude to the increase experienced in Seattle between 2013 and 2016 would have blunted some, but not nearly all, of the worst income losses suffered at the bottom of the income distribution during the Great Recession.View Full Paper PDF
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Working PaperConsidering the Use of Stock and Flow Outcomes in Empirical Analyses: An Examination of Marriage Data
January 2017
Working Paper Number:
CES-17-64
This paper fills an important void assessing how the use of stock outcomes as compared to flow outcomes may yield disparate results in empirical analyses, despite often being used interchangeably. We compare analyses using a stock outcome, marital status, to those using a flow outcome, entry into marriage, from the same dataset, the American Community Survey. This paper considers two different questions and econometric approaches using these alternative measures: the effect of the Affordable Care Act young adult provision on marriage using a difference-indifferences approach and the relationship between aggregate unemployment rates and marriage rates using a simpler ordinary least squares regression approach. Results from both analyses show stock and flow data yield divergent results in terms of sign and significance. Additional analyses suggest prior-period temporary shocks and migration may contribute to this discrepancy. These results suggest using caution when conducting analyses using stock data as they may produce false negative results or spurious false positive results, which could in turn give rise to misleading policy implications.View Full Paper PDF
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Working PaperIndustrial Investments in Energy Efficiency: A Good Idea?
January 2017
Working Paper Number:
CES-17-05
Yes, from an energy-saving perspective. No, once we factor in the negative output and productivity adoption effects. These are the main conclusions we reach by conducting the first large-scale study on cogeneration technology adoption ' a prominent form of energy-saving investments ' in the U.S. manufacturing sector, using a sample that runs from 1982 to 2010 and drawing on multiple data sources from the U.S. Census Bureau and the U.S. Energy Information Administration. We first show through a series of event studies that no differential trends exist in energy consumption nor production activities between adopters and never-adopters prior to the adoption event. We then compute a distribution of realized returns to energy savings, using accounting methods and regression methods, based on our difference-in-difference estimator. We find that (1) significant heterogeneity exists in returns; (2) unlike previous studies in the residential sector, the realized and projected returns to energy savings are roughly consistent in the industrial sector, for both private and social returns; (3) however, cogeneration adoption decreases manufacturing output and productivity persistently for at least the next 7-10 years, relative to the control group. Our IV strategies also show sizable decline in TFP post adoption.View Full Paper PDF
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Working PaperData in Action: Data-Driven Decision Making in U.S. Manufacturing
January 2016
Working Paper Number:
CES-16-06
Manufacturing in America has become significantly more data-intensive. We investigate the adoption, performance effects and organizational complementarities of data-driven decision making (DDD) in the U.S. Using data collected by the Census Bureau for 2005 and 2010, we observe the extent to which manufacturing firms track and use data to guide decision making, as well as their investments in information technology (IT) and the use of other structured management practices. Examining a representative sample of over 18,000 plans, we find that adoption of DDD is earlier and more prevalent among larger, older plants belonging to multi-unit firms. Smaller single-establishment firms adopt later but have a higher correlation with performance than similar non-adopters. Using a fixed-effects estimator, we find the average value-added for later DDD adopters to be 3% greater than non-adopters, controlling for other inputs to production. This effect is distinct from that associated with IT and other structured management practices and is concentrated among single-unit firms. Performance improves after plants adopt DDD, but not before ' consistent with a causal relationship. However, DDD-related performance differentials decrease over time for early and late adopters, consistent with firm learning and development of organizational complementarities. Formal complementarity tests suggest that DDD and high levels of IT capital reinforce each other, as do DDD and skilled workers. For some industries, the benefits of DDD adoption appear to be greater for plants that delegate some decision making to frontline workers.View Full Paper PDF
