Pub Date : 2017-01-01Epub Date: 2018-05-09DOI: 10.3233/JEM-180447
Sarah M Flood, José Pacas
The Annual Social and Economic Supplement (ASEC) is the most widely used type of Current Population Survey (CPS) data, but it is cumbersome to use the ASEC as part of a longitudinal CPS panel, especially linking to non-March months. In this paper, we detail the challenges associated with linking the ASEC to monthly CPS data, outline the creation of an identifier that links the ASEC and the March Basic Monthly data from 1989 through 2017, and provide substantive examples that illustrate the value of combining the ASEC with monthly data. The variable, MARBASECID, which we created to link ASEC and March monthly CPS data, represents a significant contribution to social and economic data infrastructure, saving individual researchers from having to duplicate the effort required to create linkages between ASEC and monthly CPS data.
{"title":"Using the Annual Social and Economic Supplement as Part of a Current Population Survey Panel.","authors":"Sarah M Flood, José Pacas","doi":"10.3233/JEM-180447","DOIUrl":"10.3233/JEM-180447","url":null,"abstract":"<p><p>The Annual Social and Economic Supplement (ASEC) is the most widely used type of Current Population Survey (CPS) data, but it is cumbersome to use the ASEC as part of a longitudinal CPS panel, especially linking to non-March months. In this paper, we detail the challenges associated with linking the ASEC to monthly CPS data, outline the creation of an identifier that links the ASEC and the March Basic Monthly data from 1989 through 2017, and provide substantive examples that illustrate the value of combining the ASEC with monthly data. The variable, MARBASECID, which we created to link ASEC and March monthly CPS data, represents a significant contribution to social and economic data infrastructure, saving individual researchers from having to duplicate the effort required to create linkages between ASEC and monthly CPS data.</p>","PeriodicalId":53705,"journal":{"name":"Journal of Economic and Social Measurement","volume":"42 3-4","pages":"225-248"},"PeriodicalIF":0.0,"publicationDate":"2017-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6010043/pdf/nihms964476.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"36252607","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Data on consumption expenditure of the household is essential in a wide array of economic research. This includes both topics in micro as well as macroeconomics. However, obtaining a consistent and precise measure of household consumption has proven notoriously difficult. This paper documents a method for computing a longitudinal consumption measure for Norwegian households from administrative records of income and wealth. Expenditure surveys tend to suffer from limited sample sizes and underrepresentation of high-income households. Administrative data does not have such limitations and offers a much larger sample with better coverage of all household types. This is particularly useful for improving the measurement of heterogeneity in consumption behavior.
{"title":"Imputing consumption from Norwegian income and wealth registry data","authors":"Å. Fagereng, Elin Halvorsen","doi":"10.3233/JEM-170438","DOIUrl":"https://doi.org/10.3233/JEM-170438","url":null,"abstract":"Data on consumption expenditure of the household is essential in a wide array of economic research. This includes both topics in micro as well as macroeconomics. However, obtaining a consistent and precise measure of household consumption has proven notoriously difficult. This paper documents a method for computing a longitudinal consumption measure for Norwegian households from administrative records of income and wealth. Expenditure surveys tend to suffer from limited sample sizes and underrepresentation of high-income households. Administrative data does not have such limitations and offers a much larger sample with better coverage of all household types. This is particularly useful for improving the measurement of heterogeneity in consumption behavior.","PeriodicalId":53705,"journal":{"name":"Journal of Economic and Social Measurement","volume":"42 1","pages":"67-100"},"PeriodicalIF":0.0,"publicationDate":"2017-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.3233/JEM-170438","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"70046077","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}
Pub Date : 2017-01-01Epub Date: 2017-11-14DOI: 10.3233/jem-170445
Marina Mileo Gorsuch, Kari Charlotte Wigness Williams
In demographic datasets, researchers frequently want to identify how members of a household are related. In this paper, we develop a new method of estimating parental and spousal relationships using data on fertility patterns and family interrelationships. The improved method includes cohabiting and same-sex couples and is comparable across all modern US IPUMS data projects. A detailed variable indicates how the relationship was inferred and the level of ambiguity around that inference. The new IPUMS family interrelationship variables are very accurate, matching self-reported spouse/partner for 99.99% and parent for over 99.00% of respondents. Among those identified as same-sex couples, we match self-reported spouse/partner for 100% of respondents, 87.57% of whom self-identify as lesbian, gay, or bisexual. We further demonstrate that the new family interrelationship variables closely track temporal variation in teenage fertility.
{"title":"Family Matters: Development of new family interrelationship variables for US IPUMS data projects.","authors":"Marina Mileo Gorsuch, Kari Charlotte Wigness Williams","doi":"10.3233/jem-170445","DOIUrl":"https://doi.org/10.3233/jem-170445","url":null,"abstract":"<p><p>In demographic datasets, researchers frequently want to identify how members of a household are related. In this paper, we develop a new method of estimating parental and spousal relationships using data on fertility patterns and family interrelationships. The improved method includes cohabiting and same-sex couples and is comparable across all modern US IPUMS data projects. A detailed variable indicates how the relationship was inferred and the level of ambiguity around that inference. The new IPUMS family interrelationship variables are very accurate, matching self-reported spouse/partner for 99.99% and parent for over 99.00% of respondents. Among those identified as same-sex couples, we match self-reported spouse/partner for 100% of respondents, 87.57% of whom self-identify as lesbian, gay, or bisexual. We further demonstrate that the new family interrelationship variables closely track temporal variation in teenage fertility.</p>","PeriodicalId":53705,"journal":{"name":"Journal of Economic and Social Measurement","volume":"42 2","pages":"123-149"},"PeriodicalIF":0.0,"publicationDate":"2017-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.3233/jem-170445","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"39040872","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2017-01-01Epub Date: 2017-11-14DOI: 10.3233/JEM-170444
Brooke Helppie-McFall, Joanne W Hsu
This study leverages a randomized experimental design of a mixed-mode mail- and web-based survey to examine mode effects separately from sample selectivity issues. Using data from the Cognitive Economics Study, which contains some sensitive financial questions, we analyze two sets of questions: fixed-choice questions posed nearly identically across mode, and dollar-value questions that exploit features available only on web mode. Focusing on differences in item nonresponse and response distributions, our results indicate that, in contrast to mail mode, web mode surveys display lower item nonresponse for all questions. While respondents appear to prefer providing financial information in ranges, use of reminder screens on the web version yields greater use of exact values without large sacrifices in item response. Still, response distributions for all questions are similar across mode, suggesting that data on sensitive financial questions collected from the two modes can be pooled.
{"title":"A Test of Web and Mail Mode Effects in a Financially Sensitive Survey of Older Americans.","authors":"Brooke Helppie-McFall, Joanne W Hsu","doi":"10.3233/JEM-170444","DOIUrl":"10.3233/JEM-170444","url":null,"abstract":"<p><p>This study leverages a randomized experimental design of a mixed-mode mail- and web-based survey to examine mode effects separately from sample selectivity issues. Using data from the Cognitive Economics Study, which contains some sensitive financial questions, we analyze two sets of questions: fixed-choice questions posed nearly identically across mode, and dollar-value questions that exploit features available only on web mode. Focusing on differences in item nonresponse and response distributions, our results indicate that, in contrast to mail mode, web mode surveys display lower item nonresponse for all questions. While respondents appear to prefer providing financial information in ranges, use of reminder screens on the web version yields greater use of exact values without large sacrifices in item response. Still, response distributions for all questions are similar across mode, suggesting that data on sensitive financial questions collected from the two modes can be pooled.</p>","PeriodicalId":53705,"journal":{"name":"Journal of Economic and Social Measurement","volume":"42 2","pages":"151-169"},"PeriodicalIF":0.0,"publicationDate":"2017-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5976248/pdf/nihms967241.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"36188521","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The main Italian enterprise surveys are shifting from a simple traditional data collection approach to a more complex one. This new approach is based on survey database management involving the recasting of many data sources (including administrative data). The reasons for utilising administrative data are: improved timeliness, increased precision and a reduction in the statistical burden. In our paper we focus on the Italian SCI survey (Sistema dei Conti delle Imprese, i.e., Businesses accounts survey). A number of innovations have been introduced into this survey over the last few years and remain ongoing. Since 2005, final economic estimates are obtained combining various data sources, primarily administrative data. The integration procedure involves a number of methodological solutions. In this paper we deal with the problem of non-response, particularly unit non-response. At first methodological issues, research and applicative trends in the NSI (National Statistical Institute) are briefly reviewed. Afterwards alternative means of estimating business data using administrative records and integrating sources are applied to the SCI survey data. The integration procedure is presented and its impact on the improvement of final data quality is verified.
意大利主要的企业调查正在从简单的传统数据收集方式转向更为复杂的方式。这种新方法基于调查数据库管理,涉及许多数据源(包括管理数据)的重铸。利用行政数据的理由是:提高时效性、提高准确性和减少统计负担。在我们的论文中,我们关注意大利SCI调查(Sistema dei Conti delle impression,即企业账户调查)。在过去的几年里,许多创新被引入到这项调查中,并仍在进行中。自2005年以来,最终的经济估计是结合各种数据来源获得的,主要是行政数据。集成过程涉及许多方法上的解决方案。本文主要研究无响应问题,特别是单元无响应问题。首先简要回顾了国家统计研究所的方法问题、研究和应用趋势。随后,利用行政记录和综合资源估算商业数据的替代方法被应用于SCI调查数据。给出了集成过程,并验证了其对提高最终数据质量的影响。
{"title":"Combining survey and administrative data in Italian business surveys","authors":"S. Biffignandi, L. Nascia, A. Zeli","doi":"10.3233/JEM-150420","DOIUrl":"https://doi.org/10.3233/JEM-150420","url":null,"abstract":"The main Italian enterprise surveys are shifting from a simple traditional data collection approach to a more complex one. This new approach is based on survey database management involving the recasting of many data sources (including administrative data). The reasons for utilising administrative data are: improved timeliness, increased precision and a reduction in the statistical burden. In our paper we focus on the Italian SCI survey (Sistema dei Conti delle Imprese, i.e., Businesses accounts survey). A number of innovations have been introduced into this survey over the last few years and remain ongoing. Since 2005, final economic estimates are obtained combining various data sources, primarily administrative data. The integration procedure involves a number of methodological solutions. In this paper we deal with the problem of non-response, particularly unit non-response. At first methodological issues, research and applicative trends in the NSI (National Statistical Institute) are briefly reviewed. Afterwards alternative means of estimating business data using administrative records and integrating sources are applied to the SCI survey data. The integration procedure is presented and its impact on the improvement of final data quality is verified.","PeriodicalId":53705,"journal":{"name":"Journal of Economic and Social Measurement","volume":"41 1","pages":"67-83"},"PeriodicalIF":0.0,"publicationDate":"2016-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.3233/JEM-150420","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"70045944","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}
Pub Date : 2016-01-01Epub Date: 2016-06-21DOI: 10.3233/JEM-160421
Fabian T Pfeffer, Robert F Schoeni, Arthur Kennickell, Patricia Andreski
Household wealth and its distribution are topics of broad public debate and increasing scholarly interest. We compare the relative strength of two of the main data sources used in research on the wealth holdings of U.S. households, the Survey of Consumer Finances (SCF) and the Panel Study of Income Dynamics (PSID), by providing a description and explanation of differences in the level and distribution of wealth captured in these two surveys. We identify the factors that account for differences in average net worth but also show that estimates of net worth are similar throughout most of the distribution. Median net worth in the SCF is 6% higher than in the PSID and the largest differences between the two surveys are concentrated in the 1-2 percent wealthiest households, leading to a different view of wealth concentration at the very top but similar results for wealth inequality across most of the distribution.
{"title":"Measuring Wealth and Wealth Inequality: Comparing Two U.S. Surveys.","authors":"Fabian T Pfeffer, Robert F Schoeni, Arthur Kennickell, Patricia Andreski","doi":"10.3233/JEM-160421","DOIUrl":"10.3233/JEM-160421","url":null,"abstract":"<p><p>Household wealth and its distribution are topics of broad public debate and increasing scholarly interest. We compare the relative strength of two of the main data sources used in research on the wealth holdings of U.S. households, the Survey of Consumer Finances (SCF) and the Panel Study of Income Dynamics (PSID), by providing a description and explanation of differences in the level and distribution of wealth captured in these two surveys. We identify the factors that account for differences in average net worth but also show that estimates of net worth are similar throughout most of the distribution. Median net worth in the SCF is 6% higher than in the PSID and the largest differences between the two surveys are concentrated in the 1-2 percent wealthiest households, leading to a different view of wealth concentration at the very top but similar results for wealth inequality across most of the distribution.</p>","PeriodicalId":53705,"journal":{"name":"Journal of Economic and Social Measurement","volume":"41 2 1","pages":"103-120"},"PeriodicalIF":0.0,"publicationDate":"2016-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.3233/JEM-160421","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"70045995","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The linking of detailed information on health, medical care, and insurance to economic outcomes is a central feature of data collection efforts in the economics of aging. In this paper, I use newly available linked panel data from a unique supplement to the Health and Retirement Study (HRS) known as the Prescription Drug Study (PDS) to examine the impact of insurance coverage on prescription drug utilization for those 65 and older. Fixed-effect estimates suggest that gaining coverage resulted in a 15% increase in utilization. Gaining coverage also was associated with a 20-50% reduction in the incidence of cost-related non-adherence. However, even among the uninsured, only a relatively small proportion of drugs (12%) were associated with episodes of cost-related non-adherence.
{"title":"Prescription drug coverage and drug utilization: New evidence from the HRS prescription drug study","authors":"Gary V. Engelhardt","doi":"10.3233/JEM-150418","DOIUrl":"https://doi.org/10.3233/JEM-150418","url":null,"abstract":"The linking of detailed information on health, medical care, and insurance to economic outcomes is a central feature of data collection efforts in the economics of aging. In this paper, I use newly available linked panel data from a unique supplement to the Health and Retirement Study (HRS) known as the Prescription Drug Study (PDS) to examine the impact of insurance coverage on prescription drug utilization for those 65 and older. Fixed-effect estimates suggest that gaining coverage resulted in a 15% increase in utilization. Gaining coverage also was associated with a 20-50% reduction in the incidence of cost-related non-adherence. However, even among the uninsured, only a relatively small proportion of drugs (12%) were associated with episodes of cost-related non-adherence.","PeriodicalId":53705,"journal":{"name":"Journal of Economic and Social Measurement","volume":"41 1","pages":"49-65"},"PeriodicalIF":0.0,"publicationDate":"2016-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.3233/JEM-150418","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"70045525","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 Supplemental Poverty Measure (SPM) was recently introduced by the U.S. Census Bureau as an alternative measure of poverty that addresses many shortcomings of the official poverty measure (OPM) to better reflect the resources households have available to meet their basic needs. The Census SPM is available only in the Current Population Survey (CPS). This paper describes a method for constructing SPM poverty estimates in the Panel Study of Income Dynamics (PSID), for the biennial years 1998 through 2010. A public-use dataset of individual-level SPM status produced in this analysis will be available for download on the PSID website. Annual SPM poverty estimates from the PSID are presented for the years 1998, 2000, 2002, 2004, 2006, 2008, and 2010 and compared to SPM estimates for the same years derived from CPS data by the Census Bureau and independent researchers. We find that SPM poverty rates in the PSID are somewhat lower than those found in the CPS, though trends over time and impact of specific SPM components are similar across the two datasets.
{"title":"Measuring poverty using the Supplemental Poverty Measure in the Panel Study of Income Dynamics, 1998 to 2010","authors":"Sara E. Kimberlin, H. L. Shaefer, Jiyoon Kim","doi":"10.3233/JEM-160425","DOIUrl":"https://doi.org/10.3233/JEM-160425","url":null,"abstract":"The Supplemental Poverty Measure (SPM) was recently introduced by the U.S. Census Bureau as an alternative measure of poverty that addresses many shortcomings of the official poverty measure (OPM) to better reflect the resources households have available to meet their basic needs. The Census SPM is available only in the Current Population Survey (CPS). This paper describes a method for constructing SPM poverty estimates in the Panel Study of Income Dynamics (PSID), for the biennial years 1998 through 2010. A public-use dataset of individual-level SPM status produced in this analysis will be available for download on the PSID website. Annual SPM poverty estimates from the PSID are presented for the years 1998, 2000, 2002, 2004, 2006, 2008, and 2010 and compared to SPM estimates for the same years derived from CPS data by the Census Bureau and independent researchers. We find that SPM poverty rates in the PSID are somewhat lower than those found in the CPS, though trends over time and impact of specific SPM components are similar across the two datasets.","PeriodicalId":53705,"journal":{"name":"Journal of Economic and Social Measurement","volume":"41 1","pages":"17-47"},"PeriodicalIF":0.0,"publicationDate":"2016-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.3233/JEM-160425","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"70045959","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}
While the majority of inequality research focuses on income metrics to measure changes in inequality, a growing number of scholars argue that consumption is a better metric for measuring disparities in an individual's contemporaneous well-being. This study adds to a growing literature on consumption inequality by testing how consumption inequality varies across consumption categories and changes overtime. We find that overall consumption inequality declined since the mid-2000s before a recent uptick, which can be mostly explained by decreasing gaps in transportation expenditures on vehicle purchases. At the same time, the recent decline in overall consumption inequality disguises growing inequalities in health and education expenditures (human capital investments). The rising inequality in human capital investments is of particular concern as it can predict future increases in inequality.
{"title":"Consumption inequality in the Great Recession","authors":"Hyojung Lee, Gary D. Painter","doi":"10.3233/JEM-160424","DOIUrl":"https://doi.org/10.3233/JEM-160424","url":null,"abstract":"While the majority of inequality research focuses on income metrics to measure changes in inequality, a growing number of scholars argue that consumption is a better metric for measuring disparities in an individual's contemporaneous well-being. This study adds to a growing literature on consumption inequality by testing how consumption inequality varies across consumption categories and changes overtime. We find that overall consumption inequality declined since the mid-2000s before a recent uptick, which can be mostly explained by decreasing gaps in transportation expenditures on vehicle purchases. At the same time, the recent decline in overall consumption inequality disguises growing inequalities in health and education expenditures (human capital investments). The rising inequality in human capital investments is of particular concern as it can predict future increases in inequality.","PeriodicalId":53705,"journal":{"name":"Journal of Economic and Social Measurement","volume":"41 1","pages":"145-166"},"PeriodicalIF":0.0,"publicationDate":"2016-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.3233/JEM-160424","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"70045867","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}
Laura B. Nolan, I. Garfinkel, Neeraj Kaushal, Jaehyun Nam, J. Waldfogel, Christopher Wimer
The U.S. Census Bureau and the Bureau of Labor Statistics recently developed a substantially improved measure of poverty, the Supplemental Poverty Measure (SPM). The SPM has only been released since 2009, and prior efforts by researchers to construct a historical SPM time series have not taken into account an essential element of the new measure - geographical differences in the cost of living - which is necessary for accurately describing poverty trends in important demographic and regional subgroups. We build the first historical SPM time series from 1967-2014 that adjusts poverty thresholds for cost of living. We do so bringing together a constellation of data sources - the Current Population Survey, the Decennial Census, the Department of Housing and Urban Development's Fair Market Rents, and others. We find that geographically adjusting thresholds increases poverty rates in metro areas, the Western states, and among Latinos, but decreases poverty rates in non-metro areas and in the South. The geographic adjustment of poverty thresholds is an impactful component of the SPM.
{"title":"A new method for measuring historical poverty trends: Incorporating geographic differences in the cost of living using the Supplemental Poverty Measure","authors":"Laura B. Nolan, I. Garfinkel, Neeraj Kaushal, Jaehyun Nam, J. Waldfogel, Christopher Wimer","doi":"10.3233/JEM-160433","DOIUrl":"https://doi.org/10.3233/JEM-160433","url":null,"abstract":"The U.S. Census Bureau and the Bureau of Labor Statistics recently developed a substantially improved measure of poverty, the Supplemental Poverty Measure (SPM). The SPM has only been released since 2009, and prior efforts by researchers to construct a historical SPM time series have not taken into account an essential element of the new measure - geographical differences in the cost of living - which is necessary for accurately describing poverty trends in important demographic and regional subgroups. We build the first historical SPM time series from 1967-2014 that adjusts poverty thresholds for cost of living. We do so bringing together a constellation of data sources - the Current Population Survey, the Decennial Census, the Department of Housing and Urban Development's Fair Market Rents, and others. We find that geographically adjusting thresholds increases poverty rates in metro areas, the Western states, and among Latinos, but decreases poverty rates in non-metro areas and in the South. The geographic adjustment of poverty thresholds is an impactful component of the SPM.","PeriodicalId":53705,"journal":{"name":"Journal of Economic and Social Measurement","volume":"41 1","pages":"237-264"},"PeriodicalIF":0.0,"publicationDate":"2016-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.3233/JEM-160433","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"70046058","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}