Papers Containing Keywords(s): 'sample'
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Viewing papers 11 through 16 of 16
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Working PaperMatching Addresses between Household Surveys and Commercial Data
July 2015
Working Paper Number:
carra-2015-04
Matching third-party data sources to household surveys can benefit household surveys in a number of ways, but the utility of these new data sources depends critically on our ability to link units between data sets. To understand this better, this report discusses potential modifications to the existing match process that could potentially improve our matches. While many changes to the matching procedure produce marginal improvements in match rates, substantial increases in match rates can only be achieved by relaxing the definition of a successful match. In the end, the results show that the most important factor determining the success of matching procedures is the quality and composition of the data sets being matched.View Full Paper PDF
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Working PaperUSING IMPUTATION TECHNIQUES TO EVALUATE STOPPING RULES IN ADAPTIVE SURVEY DESIGN
October 2014
Working Paper Number:
CES-14-40
Adaptive Design methods for social surveys utilize the information from the data as it is collected to make decisions about the sampling design. In some cases, the decision is either to continue or stop the data collection. We evaluate this decision by proposing measures to compare the collected data with follow-up samples. The options are assessed by imputation of the nonrespondents under different missingness scenarios, including Missing Not at Random. The variation in the utility measures is compared to the cost induced by the follow-up sample sizes. We apply the proposed method to the 2007 U.S. Census of Manufacturers.View Full Paper PDF
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Working PaperEvaluation of Commercial School and Teacher Lists to Enhance Survey Frames
July 2014
Working Paper Number:
carra-2014-07
This report summarizes the potential for teacher lists obtained from commercial vendors for enhancing sampling frames for the National Teacher and Principal Survey (NTPS). We investigate three separate vendor lists, and compare coverage rates across a range of school and teacher characteristics. Across all vendors, coverage rates are higher for regular, non-charter schools. Vendor A stands out as having higher coverage rates than the other two, and we recommend further evaluating Vendor A's teacher lists during the upcoming 2014-2015 NTPS Field Test.View Full Paper PDF
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Working PaperEXPANDING THE ROLE OF SYNTHETIC DATA AT THE U.S. CENSUS BUREAU
February 2014
Working Paper Number:
CES-14-10
National Statistical offices (NSOs) create official statistics from data collected from survey respondents, government administrative records and other sources. The raw source data is usually considered to be confidential. In the case of the U.S. Census Bureau, confidentiality of survey and administrative records microdata is mandated by statute, and this mandate to protect confidentiality is often at odds with the needs of users to extract as much information from the data as possible. Traditional disclosure protection techniques result in official data products that do not fully utilize the information content of the underlying microdata. Typically, these products take the form of simple aggregate tabulations. In a few cases anonymized public- use micro samples are made available, but these face a growing risk of re-identification by the increasing amounts of information about individuals and firms available in the public domain. One approach for overcoming these risks is to release products based on synthetic data where values are simulated from statistical models designed to mimic the (joint) distributions of the underlying microdata. We discuss re- cent Census Bureau work to develop and deploy such products. We discuss the benefits and challenges involved with extending the scope of synthetic data products in official statistics.View Full Paper PDF
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Working PaperMeasuring Productivity Dynamics with Endogenous Choice of Technology and Capacity Utilization: An Application to Automobile Assembly
December 2000
Working Paper Number:
CES-00-16
During the 1980s, all Japanese automobile producers opened assembly plants in North America. Industry analysts and previous research claim that these transplants are more productive than incumbent plants and that they produce with a substantially different production process. We compare the two production processes by estimating a model that allows for heterogeneity in technology and productivity. We treat both types of heterogeneity as intrinsically unobservable. In the model, plants choose technology before production starts. They condition subsequent input decisions on this choice. Maximum likelihood estimation is used to estimate the unconditional distribution of the technology choice, output, and inputs. The model is applied to a sample of automobile assembly plants. We control for capacity utilization, unobserved productivity differences, and price effects. The results indicate that there exist two distinct technologies. In particular, the more recent technology uses labor less intensively and it has a higher elasticity of substitution between labor and capital. Hicks-neutral productivity growth is estimated to be lower, while capital-biased (labor-saving) productivity growth is estimated significantly higher, for the new technology. Using the estimation results, we decompose industry-wide productivity growth in plant-level changes and composition effects, for both technologies separately. Plant-level productivity growth is further decomposed to reveal the importance of capital-biased productivity growth, increase in capital-labor ratio, and returns to scale.View Full Paper PDF
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Working PaperAn Economist's Primer on Survey Samples
September 2000
Working Paper Number:
CES-00-15
Survey data underlie most empirical work in economics, yet economists typically have little familiarity with survey sample design and its effects on inference. This paper describes how sample designs depart from the simple random sampling model implicit in most econometrics textbooks, points out where the effects of this departure are likely to be greatest, and describes the relationship between design-based estimators developed by survey statisticians and related econometric methods for regression. Its intent is to provide empirical economists with enough background in survey methods to make informed use of design-based estimators. It emphasizes surveys of households (the source of most public-use files), but also considers how surveys of businesses differ. Examples from the National Longitudinal Survey of Youth of 1979 and the Current Population Survey illustrate practical aspects of design-based estimation.View Full Paper PDF
