This paper considers whether the U.S. needs a new national survey to measure time use. The paper begins by discussing the ways that time use is measured within the U.S; as a part of that discussion, the pros and cons of the different methods are highlighted. Next, the paper highlights why time use data is essential to addressing many questions in social sciences. The paper then turns to outlining the current gaps in our measurement of household time use. Finally, the paper discusses whether a new national dataset is needed to address these gaps. The paper concludes that a new national survey is not needed to fill the gaps - however, some guidance is provided as to how existing surveys can be modified to improve time use measurement.
{"title":"Measuring time use in household surveys","authors":"Erik Hurst","doi":"10.3233/JEM-150414","DOIUrl":"https://doi.org/10.3233/JEM-150414","url":null,"abstract":"This paper considers whether the U.S. needs a new national survey to measure time use. The paper begins by discussing the ways that time use is measured within the U.S; as a part of that discussion, the pros and cons of the different methods are highlighted. Next, the paper highlights why time use data is essential to addressing many questions in social sciences. The paper then turns to outlining the current gaps in our measurement of household time use. Finally, the paper discusses whether a new national dataset is needed to address these gaps. The paper concludes that a new national survey is not needed to fill the gaps - however, some guidance is provided as to how existing surveys can be modified to improve time use measurement.","PeriodicalId":53705,"journal":{"name":"Journal of Economic and Social Measurement","volume":"40 1","pages":"177-196"},"PeriodicalIF":0.0,"publicationDate":"2015-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.3233/JEM-150414","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"70045478","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}
K. Phillips, Raul Hernandez, Benjamin R. M. Scheiner
In this paper we take a closer look at a potential flaw in the measurement of Texas Real Gross Domestic Product (RGDP) – value added in the oil and gas industry. BEA estimates of Texas RGDP in oil and gas extraction have a negative correlation with factors of production and units of output. In this paper we use several different approximations of RGDP in oil and gas extraction to see which seems to be a good substitute for the BEA estimates. We find that a measure based on changes in Texas physical production of oil and gas results in an estimate of total state RGDP that is more highly correlated with Texas job growth and closer to the correlation of these measures nationally. This adjusted measure of Texas RGDP should be a better measure of Texas economic performance.
{"title":"A closer look at potential distortions in state real gross domestic product: The case of the Texas energy sector","authors":"K. Phillips, Raul Hernandez, Benjamin R. M. Scheiner","doi":"10.3233/JEM-140384","DOIUrl":"https://doi.org/10.3233/JEM-140384","url":null,"abstract":"In this paper we take a closer look at a potential flaw in the measurement of Texas Real Gross Domestic Product (RGDP) – value added in the oil and gas industry. BEA estimates of Texas RGDP in oil and gas extraction have a negative correlation with factors of production and units of output. In this paper we use several different approximations of RGDP in oil and gas extraction to see which seems to be a good substitute for the BEA estimates. We find that a measure based on changes in Texas physical production of oil and gas results in an estimate of total state RGDP that is more highly correlated with Texas job growth and closer to the correlation of these measures nationally. This adjusted measure of Texas RGDP should be a better measure of Texas economic performance.","PeriodicalId":53705,"journal":{"name":"Journal of Economic and Social Measurement","volume":"39 1","pages":"105-119"},"PeriodicalIF":0.0,"publicationDate":"2014-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.3233/JEM-140384","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"70043136","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}
Most data sets used by economists are collected with after-the-fact surveys and the time aggregation is done by the survey respondents who produce, for example, monthly aggregates not actual transactions. 21st century digital transaction technologies will increasingly allow the collection of actual transactions, which will create an important new set of opportunities for forming time aggregates. This paper uses a transaction-by-transaction data set on purchases of diesel fuel by over-the-road truckers to form amonthly diesel volume index from 1999 to 2012 purged of weekday, holiday and calendar effects. These high-frequency data allow new and more accurate ways to correct for (1) the variability in the weekday composition of months and (2) the drift of holiday effects between months. These corrections have substantial effects on month-to-month comparisons.
{"title":"Workday, holiday and calendar adjustment: Monthly aggregates from daily diesel fuel purchases","authors":"Edward Leamer","doi":"10.3233/JEM-140386","DOIUrl":"https://doi.org/10.3233/JEM-140386","url":null,"abstract":"Most data sets used by economists are collected with after-the-fact surveys and the time aggregation is done by the survey respondents who produce, for example, monthly aggregates not actual transactions. 21st century digital transaction technologies will increasingly allow the collection of actual transactions, which will create an important new set of opportunities for forming time aggregates. This paper uses a transaction-by-transaction data set on purchases of diesel fuel by over-the-road truckers to form amonthly diesel volume index from 1999 to 2012 purged of weekday, holiday and calendar effects. These high-frequency data allow new and more accurate ways to correct for (1) the variability in the weekday composition of months and (2) the drift of holiday effects between months. These corrections have substantial effects on month-to-month comparisons.","PeriodicalId":53705,"journal":{"name":"Journal of Economic and Social Measurement","volume":"39 1","pages":"1-29"},"PeriodicalIF":0.0,"publicationDate":"2014-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.3233/JEM-140386","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"70043229","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}
Lifestyle data are rarely used in multivariate economic and social studies because the data describe the probability of having a categorical attribute. We propose a novel conversion of lifestyle data into metric scale values. Examining the 2001 referendum on the Allianz-Arena in Munich, our analysis demonstrates that refined indicators of value and strata orientation outperform the typical oriented indicators of economic wealth, in terms of capturing the spatial distribution of support and opposition to the project.
{"title":"Measuring and quantifying lifestyles and their impact on public choices: The case of professional football in Munich","authors":"Gabriel M. Ahlfeldt, W. Maennig, M. Ölschläger","doi":"10.3233/JEM-140387","DOIUrl":"https://doi.org/10.3233/JEM-140387","url":null,"abstract":"Lifestyle data are rarely used in multivariate economic and social studies because the data describe the probability of having a categorical attribute. We propose a novel conversion of lifestyle data into metric scale values. Examining the 2001 referendum on the Allianz-Arena in Munich, our analysis demonstrates that refined indicators of value and strata orientation outperform the typical oriented indicators of economic wealth, in terms of capturing the spatial distribution of support and opposition to the project.","PeriodicalId":53705,"journal":{"name":"Journal of Economic and Social Measurement","volume":"39 1","pages":"59-86"},"PeriodicalIF":0.0,"publicationDate":"2014-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.3233/JEM-140387","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"70043528","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}
Disparity in an outcome between two groups is often measured via the coefficient of a dummy variable in a regression that pools both groups. The dummy is interpreted as the disparity. A casual search of the literature in economics and other social sciences reviews far too many examples of this method to catalog. Unfortunately, if the impact of one (or more) of the control variables differs between the two groups, the measured disparity (i.e., the coefficient on the group dummy) will be biased. We illustrate and derive this bias. Given the bias, we believe that one is better running separate regressions for each group and then implementing decomposition methods or predicting adjusted gaps in outcome (i.e., predicting the but-for world that would exist if the two groups had identical characteristics).
{"title":"The bias in measuring disparity in outcomes via a dummy variable: A note","authors":"Shawn W. Ulrick","doi":"10.3233/JEM-140390","DOIUrl":"https://doi.org/10.3233/JEM-140390","url":null,"abstract":"Disparity in an outcome between two groups is often measured via the coefficient of a dummy variable in a regression that pools both groups. The dummy is interpreted as the disparity. A casual search of the literature in economics and other social sciences reviews far too many examples of this method to catalog. Unfortunately, if the impact of one (or more) of the control variables differs between the two groups, the measured disparity (i.e., the coefficient on the group dummy) will be biased. We illustrate and derive this bias. Given the bias, we believe that one is better running separate regressions for each group and then implementing decomposition methods or predicting adjusted gaps in outcome (i.e., predicting the but-for world that would exist if the two groups had identical characteristics).","PeriodicalId":53705,"journal":{"name":"Journal of Economic and Social Measurement","volume":"39 1","pages":"153-161"},"PeriodicalIF":0.0,"publicationDate":"2014-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.3233/JEM-140390","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"70043648","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}
Julia A Rivera Drew, Sarah Flood, John Robert Warren
Data from the Current Population Survey (CPS) are rarely analyzed in a way that takes advantage of the CPS's longitudinal design. This is mainly because of the technical difficulties associated with linking CPS files across months. In this paper, we describe the method we are using to create unique identifiers for all CPS person and household records from 1989 onward. These identifiers-available along with CPS basic and supplemental data as part of the on-line Integrated Public Use Microdata Series (IPUMS)-make it dramatically easier to use CPS data for longitudinal research across any number of substantive domains. To facilitate the use of these new longitudinal IPUMS-CPS data, we also outline seven different ways that researchers may choose to link CPS person records across months, and we describe the sample sizes and sample retention rates associated with these seven designs. Finally, we discuss a number of unique methodological challenges that researchers will confront when analyzing data from linked CPS files.
{"title":"Making Full Use of the Longitudinal Design of the Current Population Survey: Methods for Linking Records Across 16 Months.","authors":"Julia A Rivera Drew, Sarah Flood, John Robert Warren","doi":"10.3233/JEM-140388","DOIUrl":"https://doi.org/10.3233/JEM-140388","url":null,"abstract":"<p><p>Data from the Current Population Survey (CPS) are rarely analyzed in a way that takes advantage of the CPS's longitudinal design. This is mainly because of the technical difficulties associated with linking CPS files across months. In this paper, we describe the method we are using to create unique identifiers for all CPS person and household records from 1989 onward. These identifiers-available along with CPS basic and supplemental data as part of the on-line Integrated Public Use Microdata Series (IPUMS)-make it dramatically easier to use CPS data for longitudinal research across any number of substantive domains. To facilitate the use of these new longitudinal IPUMS-CPS data, we also outline seven different ways that researchers may choose to link CPS person records across months, and we describe the sample sizes and sample retention rates associated with these seven designs. Finally, we discuss a number of unique methodological challenges that researchers will confront when analyzing data from linked CPS files.</p>","PeriodicalId":53705,"journal":{"name":"Journal of Economic and Social Measurement","volume":"39 3","pages":"121-144"},"PeriodicalIF":0.0,"publicationDate":"2014-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.3233/JEM-140388","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"33422692","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}
This paper examines the potential sources behind statistically significant seasonal patterns in the state level seasonally adjusted Local Area Unemployment Statistics (LAUS) released by the U.S. Bureau of Labor Statistics (BLS). We find that these seasonal patterns are likely spurious and may be due to the pro-rata factors used in benchmarking the states to census regions and national totals. In addition we find that the Henderson 13 filter used by the BLS to smooth the seasonally adjusted state data often makes the data inconsistent with national labor market data. We conclude that the BLS should use seasonally adjusted data when estimating the pro-rata factors used to benchmark states to regional and national totals.
{"title":"A note on spurious seasonal patterns and other distortions in the BLS local area unemployment statistics","authors":"K. Phillips, Jianguo Wang","doi":"10.3233/JEM-140389","DOIUrl":"https://doi.org/10.3233/JEM-140389","url":null,"abstract":"This paper examines the potential sources behind statistically significant seasonal patterns in the state level seasonally adjusted Local Area Unemployment Statistics (LAUS) released by the U.S. Bureau of Labor Statistics (BLS). We find that these seasonal patterns are likely spurious and may be due to the pro-rata factors used in benchmarking the states to census regions and national totals. In addition we find that the Henderson 13 filter used by the BLS to smooth the seasonally adjusted state data often makes the data inconsistent with national labor market data. We conclude that the BLS should use seasonally adjusted data when estimating the pro-rata factors used to benchmark states to regional and national totals.","PeriodicalId":53705,"journal":{"name":"Journal of Economic and Social Measurement","volume":"39 1","pages":"145-152"},"PeriodicalIF":0.0,"publicationDate":"2014-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.3233/JEM-140389","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"70043542","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 Database of Global Economic Indicators (DGEI) from the Federal Reserve Bank of Dallas aims to standardize and disseminate economic indicators for policy analysis and scholarly work on the role of globalization. Its main purpose is to offer a broad perspective on a number of global factors affecting the U.S. economy. DGEI indicators are based on a core sample of 40 countries with aggregates for the rest of the world (ex. the U.S.) and by level of development attainment and openness to trade. DGEI indicators currently include real GDP, industrial production (IP), Purchasing Managers Index (PMI), merchandise exports and imports, headline CPI, core CPI (ex. food and energy), PPI/WPI inflation, nominal and real exchange rates, and short-term interest rates. Here we describe our methodology to transform and combine different time series, for temporal and cross-country aggregation, and to highlight the importance of using representative data in international macroeconomics research. Our paper makes a related contribution to the literature by providing a formal assessment of conventional interpolation methods used to adjust the data frequency. A selection of the DGEI-derived global indicators – to be updated monthly – can be accessed at the following URL: http://www.dallasfed.org/institute/dgei/index.cfm.
{"title":"A New Database of Global Economic Indicators","authors":"Valerie Grossman, Adrienne Mack, Enrique Martínez-García","doi":"10.3233/JEM-140391","DOIUrl":"https://doi.org/10.3233/JEM-140391","url":null,"abstract":"The Database of Global Economic Indicators (DGEI) from the Federal Reserve Bank of Dallas aims to standardize and disseminate economic indicators for policy analysis and scholarly work on the role of globalization. Its main purpose is to offer a broad perspective on a number of global factors affecting the U.S. economy. DGEI indicators are based on a core sample of 40 countries with aggregates for the rest of the world (ex. the U.S.) and by level of development attainment and openness to trade. DGEI indicators currently include real GDP, industrial production (IP), Purchasing Managers Index (PMI), merchandise exports and imports, headline CPI, core CPI (ex. food and energy), PPI/WPI inflation, nominal and real exchange rates, and short-term interest rates. Here we describe our methodology to transform and combine different time series, for temporal and cross-country aggregation, and to highlight the importance of using representative data in international macroeconomics research. Our paper makes a related contribution to the literature by providing a formal assessment of conventional interpolation methods used to adjust the data frequency. A selection of the DGEI-derived global indicators – to be updated monthly – can be accessed at the following URL: http://www.dallasfed.org/institute/dgei/index.cfm.","PeriodicalId":53705,"journal":{"name":"Journal of Economic and Social Measurement","volume":"39 1","pages":"163-197"},"PeriodicalIF":0.0,"publicationDate":"2014-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.3233/JEM-140391","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"70043656","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}
Individual attitudes and opinions may visibly impact upon an individual's decisions on how and when to use health care services and associated decisions with respect to medical expenditures. These health care preferences also serve as important inputs in helping to predict health insurance coverage take-up decisions. This paper considers the degree of concordance over time in health care attitudes regarding the need and value of health insurance coverage based on national data from the Medical Expenditure Panel Survey. It demonstrates that individuals who consistently indicated they were healthy and did not need coverage were substantially less likely to have a medical expense in both years, relative to their counterparts who consistently disagreed with that classification. The paper also finds that adults under the age of 65 who consistently indicated that health insurance was not worth the cost were at nearly three times as likely to be continuously uninsured relative to those who consistently disagreed.
{"title":"The influence of health care preferences on insurance enrollment and medical expenditure behaviors","authors":"S. Cohen","doi":"10.3233/JEM-140381","DOIUrl":"https://doi.org/10.3233/JEM-140381","url":null,"abstract":"Individual attitudes and opinions may visibly impact upon an individual's decisions on how and when to use health care services and associated decisions with respect to medical expenditures. These health care preferences also serve as important inputs in helping to predict health insurance coverage take-up decisions. This paper considers the degree of concordance over time in health care attitudes regarding the need and value of health insurance coverage based on national data from the Medical Expenditure Panel Survey. It demonstrates that individuals who consistently indicated they were healthy and did not need coverage were substantially less likely to have a medical expense in both years, relative to their counterparts who consistently disagreed with that classification. The paper also finds that adults under the age of 65 who consistently indicated that health insurance was not worth the cost were at nearly three times as likely to be continuously uninsured relative to those who consistently disagreed.","PeriodicalId":53705,"journal":{"name":"Journal of Economic and Social Measurement","volume":"38 1","pages":"325-345"},"PeriodicalIF":0.0,"publicationDate":"2013-11-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.3233/JEM-140381","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"70043447","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}
Endogenous growth models consider the stock of R&D (or knowledge) both as a paid input and as an indicator of technical progress. It is shown in this paper that this is inconsistent with core economic theory. In addition, growth eventually stalls in these models unless one assumes increasing returns to scale in all inputs or allows for some exogenous technical progress to occur. This paper shows that neither of these assumptions are necessary to obtain sustained endogenous growth when inputs are properly defined and when a new input is introduced that we call thinking.
{"title":"Thinking and growing: Towards a reconciliation of exogenous and endogenous growth theories","authors":"René Durand","doi":"10.3233/JEM-130375","DOIUrl":"https://doi.org/10.3233/JEM-130375","url":null,"abstract":"Endogenous growth models consider the stock of R&D (or knowledge) both as a paid input and as an indicator of technical progress. It is shown in this paper that this is inconsistent with core economic theory. In addition, growth eventually stalls in these models unless one assumes increasing returns to scale in all inputs or allows for some exogenous technical progress to occur. This paper shows that neither of these assumptions are necessary to obtain sustained endogenous growth when inputs are properly defined and when a new input is introduced that we call thinking.","PeriodicalId":53705,"journal":{"name":"Journal of Economic and Social Measurement","volume":"38 1","pages":"187-200"},"PeriodicalIF":0.0,"publicationDate":"2013-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.3233/JEM-130375","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"70043149","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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