Over the past twenty years, imports to the U.S. from low-wage countries have increased dramatically. In this paper we examine how low-wage country import competition in the U.S. influences the probability of manufacturing establishment closure. Confidential data from the U.S. Bureau of the Census are used to track all manufacturing establishments between 1992 and 2007. These data are linked to measures of import competition built from individual trade transactions. Controlling for a variety of plant and firm covariates, we show that low-wage import competition has played a significant role in manufacturing plant exit. Analysis employs fixed effects panel models running across three periods: the first plant-level panels examining trade and exit for the U.S. economy. Our results appear robust to concerns regarding endogeneity.
{"title":"Plant Exit and U.S. Imports from Low-Wage Countries","authors":"Abigail M. Cooke, Thomas Kemney, D. Rigby","doi":"10.2139/ssrn.2714870","DOIUrl":"https://doi.org/10.2139/ssrn.2714870","url":null,"abstract":"Over the past twenty years, imports to the U.S. from low-wage countries have increased dramatically. In this paper we examine how low-wage country import competition in the U.S. influences the probability of manufacturing establishment closure. Confidential data from the U.S. Bureau of the Census are used to track all manufacturing establishments between 1992 and 2007. These data are linked to measures of import competition built from individual trade transactions. Controlling for a variety of plant and firm covariates, we show that low-wage import competition has played a significant role in manufacturing plant exit. Analysis employs fixed effects panel models running across three periods: the first plant-level panels examining trade and exit for the U.S. economy. Our results appear robust to concerns regarding endogeneity.","PeriodicalId":92154,"journal":{"name":"U.S. Census Bureau Center for Economic Studies research paper series","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2016-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88828170","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
L. Edlund, Cecilia Machado, María Micaela Sviatschi
In 1980, housing prices in the main US cities rose with distance to the city center. By 2010, that relationship had reversed. We propose that this development can be traced to greater labor supply of high-income households through reduced tolerance for commuting. In a tract-level data set covering the 27 largest US cities, years 1980-2010, we employ a city-level Bartik demand shifter for skilled labor and find support for our hypothesis: full-time skilled workers favor proximity to the city center and their increased presence can account for the observed price changes, notably the rising price premium commanded by centrality.
{"title":"Bright Minds, Big Rent: Gentrification and the Rising Returns to Skill","authors":"L. Edlund, Cecilia Machado, María Micaela Sviatschi","doi":"10.2139/ssrn.2823672","DOIUrl":"https://doi.org/10.2139/ssrn.2823672","url":null,"abstract":"In 1980, housing prices in the main US cities rose with distance to the city center. By 2010, that relationship had reversed. We propose that this development can be traced to greater labor supply of high-income households through reduced tolerance for commuting. In a tract-level data set covering the 27 largest US cities, years 1980-2010, we employ a city-level Bartik demand shifter for skilled labor and find support for our hypothesis: full-time skilled workers favor proximity to the city center and their increased presence can account for the observed price changes, notably the rising price premium commanded by centrality.","PeriodicalId":92154,"journal":{"name":"U.S. Census Bureau Center for Economic Studies research paper series","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2015-11-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82596915","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
In this paper we study the productivity-survival link in the U.S. poultry processing industry using the longitudinal data constructed from five Censuses of Manufactures between 1987 and 2007. First, we study the effects of physical productivity and demand-specific factors on plant survival and ownership change. Second, we analyze the determinants of the firm-level expansion. The results show that higher demand-specific factors decrease the probability of exit and increase the probability of ownership change. The effect of physical productivity on the probability of exit or ownership change is generally insignificant. Also, firms with higher demand-specific factors have higher probability to expand whereas the average firm-level physical productivity turns out to be an insignificant determinant of firm expansion.
{"title":"The Effects of Productivity and Demand-Specific Factors on Plant Survival and Ownership Change in the U.S. Poultry Industry","authors":"Tengying Weng, T. Vukina, Xiaoyong Zheng","doi":"10.2139/ssrn.2636559","DOIUrl":"https://doi.org/10.2139/ssrn.2636559","url":null,"abstract":"In this paper we study the productivity-survival link in the U.S. poultry processing industry using the longitudinal data constructed from five Censuses of Manufactures between 1987 and 2007. First, we study the effects of physical productivity and demand-specific factors on plant survival and ownership change. Second, we analyze the determinants of the firm-level expansion. The results show that higher demand-specific factors decrease the probability of exit and increase the probability of ownership change. The effect of physical productivity on the probability of exit or ownership change is generally insignificant. Also, firms with higher demand-specific factors have higher probability to expand whereas the average firm-level physical productivity turns out to be an insignificant determinant of firm expansion.","PeriodicalId":92154,"journal":{"name":"U.S. Census Bureau Center for Economic Studies research paper series","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2015-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85303455","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Clifford A. Lipscomb, J. Youtie, S. Arora, Andy Krause, P. Shapira
This work examines the effects of receipt of business assistance services from the Manufacturing Extension Partnership (MEP) on manufacturing establishment performance. Several measures of performance are considered: (1) change in value-added per employee (a measure of productivity); (2) change in sales per worker; (3) change in employment; and (4) establishment survival. To analyze these relationships, we merged program records from the MEP’s client and project information files with administrative records from the Census of Manufacturers and other Census databases over the periods 1997–2002 and 2002–2007 to compare the outcomes and performance of “served” and “unserved” manufacturing establishments. The approach builds on, updates, and expands upon earlier studies comparing matched MEP client and non-client performance over time periods ending in 1992 and 2002. Our results generally indicate that MEP services had positive and significant impacts on establishment productivity and sales per worker for the 2002–2007 period with some exceptions based on employment size, industry, and type of service provided. MEP services also increased the probability of establishment survival for the 1997–2007 period. Regardless of econometric model specification, MEP clients with 1–19 employees have statistically significant and higher levels of labor productivity growth. We also observed significant productivity differences associated with MEP services by broad sector, with higher impacts over the 2002–2007 time period in the durable goods manufacturing sector. The study further finds that establishments receiving MEP assistance are more likely to survive than those that do not receive MEP assistance. Detailed findings of the study, as well as caveats and limitations, are discussed in the paper.
{"title":"Evaluating the Long-Term Effect of NIST MEP Services on Establishment Performance","authors":"Clifford A. Lipscomb, J. Youtie, S. Arora, Andy Krause, P. Shapira","doi":"10.2139/ssrn.2592023","DOIUrl":"https://doi.org/10.2139/ssrn.2592023","url":null,"abstract":"This work examines the effects of receipt of business assistance services from the Manufacturing Extension Partnership (MEP) on manufacturing establishment performance. Several measures of performance are considered: (1) change in value-added per employee (a measure of productivity); (2) change in sales per worker; (3) change in employment; and (4) establishment survival. To analyze these relationships, we merged program records from the MEP’s client and project information files with administrative records from the Census of Manufacturers and other Census databases over the periods 1997–2002 and 2002–2007 to compare the outcomes and performance of “served” and “unserved” manufacturing establishments. The approach builds on, updates, and expands upon earlier studies comparing matched MEP client and non-client performance over time periods ending in 1992 and 2002. Our results generally indicate that MEP services had positive and significant impacts on establishment productivity and sales per worker for the 2002–2007 period with some exceptions based on employment size, industry, and type of service provided. MEP services also increased the probability of establishment survival for the 1997–2007 period. Regardless of econometric model specification, MEP clients with 1–19 employees have statistically significant and higher levels of labor productivity growth. We also observed significant productivity differences associated with MEP services by broad sector, with higher impacts over the 2002–2007 time period in the durable goods manufacturing sector. The study further finds that establishments receiving MEP assistance are more likely to survive than those that do not receive MEP assistance. Detailed findings of the study, as well as caveats and limitations, are discussed in the paper.","PeriodicalId":92154,"journal":{"name":"U.S. Census Bureau Center for Economic Studies research paper series","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2015-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82700894","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Employment-related health coverage is the predominant form of health insurance in the nonelderly, US population. Developing sound policies regarding the tax treatment of employer-sponsored insurance requires detailed information on the insurance benefits offered by employers as well as detailed information on the characteristics of employees and their familes. Unfortunately, no nationally representative data set contains all of the necessary elements. This paper describes the development of the Employer-Sim model which models tax-based health policies by using data on workers from the Medical Expenditure Panel Survey Household Component (MEPS HC) to form synthetic workforces for each establishment in the Medical Expenditure Panel Survey Insurance Component (MEPS IC). This paper describes the application of Employer-Sim to estimating tax subsidies to employer-sponsored health insurance and presents estimates of the cost and indcidence of the subsidy for 2008. The paper concludes by discussing other potential applications of the Employer-Sim model.
{"title":"Employer-Sim Microsimulation Model: Model Development and Application to Estimation of Tax Subsidies to Health Insurance","authors":"E. Miller, T. Selden, J. Banthin","doi":"10.2139/SSRN.2573132","DOIUrl":"https://doi.org/10.2139/SSRN.2573132","url":null,"abstract":"Employment-related health coverage is the predominant form of health insurance in the nonelderly, US population. Developing sound policies regarding the tax treatment of employer-sponsored insurance requires detailed information on the insurance benefits offered by employers as well as detailed information on the characteristics of employees and their familes. Unfortunately, no nationally representative data set contains all of the necessary elements. This paper describes the development of the Employer-Sim model which models tax-based health policies by using data on workers from the Medical Expenditure Panel Survey Household Component (MEPS HC) to form synthetic workforces for each establishment in the Medical Expenditure Panel Survey Insurance Component (MEPS IC). This paper describes the application of Employer-Sim to estimating tax subsidies to employer-sponsored health insurance and presents estimates of the cost and indcidence of the subsidy for 2008. The paper concludes by discussing other potential applications of the Employer-Sim model.","PeriodicalId":92154,"journal":{"name":"U.S. Census Bureau Center for Economic Studies research paper series","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2014-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80886648","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Using confidential U.S. customs data on trade transactions between U.S. importers and Bangladeshi exporters between 2002 and 2009, and information on the geographic location of Bangladeshi exporters, we show that the presence of neighboring exporters that previously transacted with a U.S. importer is associated with a greater likelihood of matching with the same U.S. importer for the first time. This suggests a role for business networks among trading firms in generating exporter-importer matches. Our research design also allows us to isolate potential gains from neighborhood exporter presence that are partner-specific, from overall gains previously documented in the literature.
{"title":"Buyer-Seller Relationships in International Trade: Do Your Neighbors Matter?","authors":"Fariha Kamal, A. Sundaram","doi":"10.2139/ssrn.2573121","DOIUrl":"https://doi.org/10.2139/ssrn.2573121","url":null,"abstract":"Using confidential U.S. customs data on trade transactions between U.S. importers and Bangladeshi exporters between 2002 and 2009, and information on the geographic location of Bangladeshi exporters, we show that the presence of neighboring exporters that previously transacted with a U.S. importer is associated with a greater likelihood of matching with the same U.S. importer for the first time. This suggests a role for business networks among trading firms in generating exporter-importer matches. Our research design also allows us to isolate potential gains from neighborhood exporter presence that are partner-specific, from overall gains previously documented in the literature.","PeriodicalId":92154,"journal":{"name":"U.S. Census Bureau Center for Economic Studies research paper series","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2014-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90306458","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
I quantify the contribution of sectoral shocks to business cycle fluctuations in aggregate output. I develop a multi-industry general equilibrium model in which each industry employs the material and capital goods produced by other sectors, and then estimate this model using data on U.S. industries sales, output prices, and input choices. Maximum likelihood estimates indicate that industry-specific shocks account for nearly two-thirds of the volatility of aggregate output, substantially larger than previously assessed. Identification of the relative importance of industry-specific shocks comes primarily from data on industries intermediate input purchases, data that earlier estimations of multi-industry models have ignored.
{"title":"How Important are Sectoral Shocks?","authors":"Enghin Atalay","doi":"10.2139/ssrn.2523424","DOIUrl":"https://doi.org/10.2139/ssrn.2523424","url":null,"abstract":"I quantify the contribution of sectoral shocks to business cycle fluctuations in aggregate output. I develop a multi-industry general equilibrium model in which each industry employs the material and capital goods produced by other sectors, and then estimate this model using data on U.S. industries sales, output prices, and input choices. Maximum likelihood estimates indicate that industry-specific shocks account for nearly two-thirds of the volatility of aggregate output, substantially larger than previously assessed. Identification of the relative importance of industry-specific shocks comes primarily from data on industries intermediate input purchases, data that earlier estimations of multi-industry models have ignored.","PeriodicalId":92154,"journal":{"name":"U.S. Census Bureau Center for Economic Studies research paper series","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2014-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81603021","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The Longitudinal Employer-Household Dynamics (LEHD) Program at the U.S. Census Bureau, with the support of several national research agencies, maintains a set of infrastructure files using administrative data provided by state agencies, enhanced with information from other administrative data sources, demographic and economic (business) surveys and censuses. The LEHD Infrastructure Files provide a detailed and comprehensive picture of workers, employers, and their interaction in the U.S. economy. This document describes the structure and content of the 2011 Snapshot of the LEHD Infrastructure files as they are made available in the Census Bureaus secure and restricted-access Research Data Center network. The document attempts to provide a comprehensive description of all researcher-accessible files, of their creation, and of any modifcations made to the files to facilitate researcher access.
{"title":"LEHD Data Documentation Lehd-Overview-S2011: LEHD Infrastructure Files in the Census RDC – Overview","authors":"L. Vilhuber, Kevin McKinney","doi":"10.2139/SSRN.2448301","DOIUrl":"https://doi.org/10.2139/SSRN.2448301","url":null,"abstract":"The Longitudinal Employer-Household Dynamics (LEHD) Program at the U.S. Census Bureau, with the support of several national research agencies, maintains a set of infrastructure files using administrative data provided by state agencies, enhanced with information from other administrative data sources, demographic and economic (business) surveys and censuses. The LEHD Infrastructure Files provide a detailed and comprehensive picture of workers, employers, and their interaction in the U.S. economy. This document describes the structure and content of the 2011 Snapshot of the LEHD Infrastructure files as they are made available in the Census Bureaus secure and restricted-access Research Data Center network. The document attempts to provide a comprehensive description of all researcher-accessible files, of their creation, and of any modifcations made to the files to facilitate researcher access.","PeriodicalId":92154,"journal":{"name":"U.S. Census Bureau Center for Economic Studies research paper series","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2014-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85036274","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
J. Haltiwanger, Henry R. Hyatt, Erika McEntarfer, L. Sousa, Stephen R. Tibbets
The Census Bureau’s Quarterly Workforce Dynamics (QWI) and OnTheMap now provide detailed workforce statistics by employer age and size. These data allow a first look at the demographics of workers at small and young businesses as well as detailed analysis of how hiring, turnover, job creation/destruction vary throughout a firm’s lifespan. Both the QWI and OnTheMap are tabulated from the Longitudinal Employer-Household Dynamics (LEHD) linked employer-employee data. Firm age and size information was added to the LEHD data through integration of Business Dynamics Statistics (BDS) microdata into the LEHD jobs frame. This paper describes how these two new firm characteristics were added to the microdata and how they are tabulated in QWI and OnTheMap
{"title":"Firm Age and Size in the Longitudinal Employer-Household Dynamics Data","authors":"J. Haltiwanger, Henry R. Hyatt, Erika McEntarfer, L. Sousa, Stephen R. Tibbets","doi":"10.2139/ssrn.2423452","DOIUrl":"https://doi.org/10.2139/ssrn.2423452","url":null,"abstract":"The Census Bureau’s Quarterly Workforce Dynamics (QWI) and OnTheMap now provide detailed workforce statistics by employer age and size. These data allow a first look at the demographics of workers at small and young businesses as well as detailed analysis of how hiring, turnover, job creation/destruction vary throughout a firm’s lifespan. Both the QWI and OnTheMap are tabulated from the Longitudinal Employer-Household Dynamics (LEHD) linked employer-employee data. Firm age and size information was added to the LEHD data through integration of Business Dynamics Statistics (BDS) microdata into the LEHD jobs frame. This paper describes how these two new firm characteristics were added to the microdata and how they are tabulated in QWI and OnTheMap","PeriodicalId":92154,"journal":{"name":"U.S. Census Bureau Center for Economic Studies research paper series","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2014-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88358990","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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.
{"title":"Expanding the Role of Synthetic Data at the U.S. Census Bureau","authors":"Ron S. Jarmin, T. Louis, Javier Miranda","doi":"10.2139/ssrn.2408030","DOIUrl":"https://doi.org/10.2139/ssrn.2408030","url":null,"abstract":"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.","PeriodicalId":92154,"journal":{"name":"U.S. Census Bureau Center for Economic Studies research paper series","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2014-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"91419956","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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