Laura Ravazzini, Ursina Kuhn, Gaël Brulé, C. Suter
Beyond income, wealth is one of most relevant components among national and international indicators of household finances. Three surveys that include Switzerland have recently integrated questions about wealth and its components. These surveys are the Swiss Household Panel -SHP- (2016), the Statistics on Income and Living Conditions -CH-SILC- (2015), and the Survey on Health, Ageing and Retirement in Europe -SHARE- (2015). Following three important criteria suggested by the Organisation for Economic Co-operation and Development (OECD), namely relevance, coherence and accuracy, this study systematically compares data on housing and financial wealth. The analysis addresses question wording, the comparison with national accounts and accuracy. Results suggest that SHARE is the most relevant survey in terms of financial wealth and total net worth. CH-SILC is a coherent survey that allows for additional analysis on subjective living conditions, while the SHP is an ecological survey in terms of the number of questions on wealth.
{"title":"Comparison of survey data on wealth in Switzerland","authors":"Laura Ravazzini, Ursina Kuhn, Gaël Brulé, C. Suter","doi":"10.3233/JEM-190461","DOIUrl":"https://doi.org/10.3233/JEM-190461","url":null,"abstract":"Beyond income, wealth is one of most relevant components among national and international indicators of household finances. Three surveys that include Switzerland have recently integrated questions about wealth and its components. These surveys are the Swiss Household Panel -SHP- (2016), the Statistics on Income and Living Conditions -CH-SILC- (2015), and the Survey on Health, Ageing and Retirement in Europe -SHARE- (2015). Following three important criteria suggested by the Organisation for Economic Co-operation and Development (OECD), namely relevance, coherence and accuracy, this study systematically compares data on housing and financial wealth. The analysis addresses question wording, the comparison with national accounts and accuracy. Results suggest that SHARE is the most relevant survey in terms of financial wealth and total net worth. CH-SILC is a coherent survey that allows for additional analysis on subjective living conditions, while the SHP is an ecological survey in terms of the number of questions on wealth.","PeriodicalId":53705,"journal":{"name":"Journal of Economic and Social Measurement","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-07-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.3233/JEM-190461","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46667128","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 journey between work and home plays an important role in daily time use, acting as both a fixed time cost of labor force participation and as a constraint on time for other activities. Data from the American Time Use Survey (ATUS) offer the opportunity to examine commuting behavior and its relationship to demographics, labor market characteristics, and the amount of time spent on other activities. Previous analyses have been complicated by the difficulties of obtaining commuting time measures from the ATUS. Travel information can be difficult to interpret in the ATUS, and many commuting trips are likely misclassified using stock measures of work-related travel. To address this shortcoming, I review the strategies of previous researchers to reclassify travel. After surveying possible methodologies, I focus on applying to the ATUS a methodology applied to the National Household Transportation Survey (NHTS). Detailed time information in the NHTS allows me to compare both aggregate commuting measures and the timing of commuting in the two surveys. I further extend the analysis to compare to journey-to-work information in another commonly used dataset, the American Community Survey. These comparisons and the methodology provided serve to enable and validate further analysis of commuting behavior using the ATUS, leveraging the advantages of this dataset.
工作和家庭之间的旅程在日常时间使用中起着重要作用，既是劳动力参与的固定时间成本，也是对其他活动时间的限制。来自美国时间使用调查(ATUS)的数据为研究通勤行为及其与人口统计学、劳动力市场特征和花在其他活动上的时间的关系提供了机会。以前的分析由于难以从ATUS获得通勤时间指标而变得复杂。在ATUS中，旅行信息很难解释，许多通勤旅行可能被错误地分类为与工作相关的旅行。为了解决这个缺点，我回顾了以前的研究人员重新分类旅行的策略。在调查了可能的方法之后，我着重于将应用于国家家庭交通调查(NHTS)的方法应用于ATUS。NHTS中的详细时间信息使我能够比较两次调查中的总通勤措施和通勤时间。我进一步扩展了分析，将其与另一个常用数据集——美国社区调查(American Community Survey)中的通勤信息进行比较。这些比较和提供的方法有助于利用该数据集的优势，使用ATUS进一步分析通勤行为，并对其进行验证。
{"title":"Measuring commuting in the American Time Use Survey","authors":"Gray Kimbrough","doi":"10.3233/JEM-180459","DOIUrl":"https://doi.org/10.3233/JEM-180459","url":null,"abstract":"The journey between work and home plays an important role in daily time use, acting as both a fixed time cost of labor force participation and as a constraint on time for other activities. Data from the American Time Use Survey (ATUS) offer the opportunity to examine commuting behavior and its relationship to demographics, labor market characteristics, and the amount of time spent on other activities. Previous analyses have been complicated by the difficulties of obtaining commuting time measures from the ATUS. Travel information can be difficult to interpret in the ATUS, and many commuting trips are likely misclassified using stock measures of work-related travel. To address this shortcoming, I review the strategies of previous researchers to reclassify travel. After surveying possible methodologies, I focus on applying to the ATUS a methodology applied to the National Household Transportation Survey (NHTS). Detailed time information in the NHTS allows me to compare both aggregate commuting measures and the timing of commuting in the two surveys. I further extend the analysis to compare to journey-to-work information in another commonly used dataset, the American Community Survey. These comparisons and the methodology provided serve to enable and validate further analysis of commuting behavior using the ATUS, leveraging the advantages of this dataset.","PeriodicalId":53705,"journal":{"name":"Journal of Economic and Social Measurement","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-05-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.3233/JEM-180459","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42220571","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}
{"title":"The racial ‘digital divide’ in the predictive power of Google trends data for forecasting the unemployment rate","authors":"M. Dilmaghani","doi":"10.3233/JEM-180458","DOIUrl":"https://doi.org/10.3233/JEM-180458","url":null,"abstract":"","PeriodicalId":53705,"journal":{"name":"Journal of Economic and Social Measurement","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-04-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.3233/JEM-180458","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43733991","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}
{"title":"The creation of an experimental longitudinal database of business micro-data","authors":"A. Zeli","doi":"10.3233/JEM-180457","DOIUrl":"https://doi.org/10.3233/JEM-180457","url":null,"abstract":"","PeriodicalId":53705,"journal":{"name":"Journal of Economic and Social Measurement","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-04-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.3233/JEM-180457","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45121145","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}
Gary K. Taylor, Simon K. Medcalfe, M. Dugan, R. Ezell
{"title":"Estimating the implied discount rate: An application to multi-year nfl trades of draft picks","authors":"Gary K. Taylor, Simon K. Medcalfe, M. Dugan, R. Ezell","doi":"10.3233/JEM-180455","DOIUrl":"https://doi.org/10.3233/JEM-180455","url":null,"abstract":"","PeriodicalId":53705,"journal":{"name":"Journal of Economic and Social Measurement","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.3233/JEM-180455","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"70046123","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}
A recent one-time accounting “repatriation tax” charge against a leading cash flow series (e.g., Federal Reserve Economic Data series, Corporate Net Cash Flow with Inventory Valuation Adjustment) introduces a significant change in 4 Quarter, 2017 that is an accounting artifact. This note demonstrates the econometric impact of the charge and illustrates how to back it out resulting in a series consistent with economic activity. Without the proposed adjustment, the series has what is essentially a permanent outlier that is of such magnitude that it can distort regression coefficients and statistical models when the 4 Quarter, 2017 datapoint is included in analysis.
{"title":"The U.S. “2017 Tax Cuts & Jobs Act” introduces a significant data error in corporate net cash flow","authors":"Laurel J. Fish, Dennis Halcoussis, G. Phillips","doi":"10.3233/JEM-190460","DOIUrl":"https://doi.org/10.3233/JEM-190460","url":null,"abstract":"A recent one-time accounting “repatriation tax” charge against a leading cash flow series (e.g., Federal Reserve Economic Data series, Corporate Net Cash Flow with Inventory Valuation Adjustment) introduces a significant change in 4 Quarter, 2017 that is an accounting artifact. This note demonstrates the econometric impact of the charge and illustrates how to back it out resulting in a series consistent with economic activity. Without the proposed adjustment, the series has what is essentially a permanent outlier that is of such magnitude that it can distort regression coefficients and statistical models when the 4 Quarter, 2017 datapoint is included in analysis.","PeriodicalId":53705,"journal":{"name":"Journal of Economic and Social Measurement","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.3233/JEM-190460","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"70046140","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 : 2019-01-01Epub Date: 2020-01-03DOI: 10.3233/jem-190465
Michael D Hurd, Erik Meijer, Michael Moldoff, Susann Rohwedder
Survey measures of household wealth often incorporate measurement error. The resulting excess variability in the first difference in wealth makes meaningful statistical inference difficult on changes in household-level wealth. We study the effects of two methods intended to reduce this problem: Asset verification confronts respondents with large discrepancies between wealth reports from the current wave and from the previous wave. Cross-wave imputation uses adjacent wave information in the imputation procedures for missing data. In the U.S. Health and Retirement Study, the corrections from asset verification substantially reduced wave-to-wave changes in wealth. The cross-wave imputations also reduced variation, but to a lesser extent.
{"title":"Reducing cross-wave variability in survey measures of household wealth.","authors":"Michael D Hurd, Erik Meijer, Michael Moldoff, Susann Rohwedder","doi":"10.3233/jem-190465","DOIUrl":"https://doi.org/10.3233/jem-190465","url":null,"abstract":"<p><p>Survey measures of household wealth often incorporate measurement error. The resulting excess variability in the first difference in wealth makes meaningful statistical inference difficult on changes in household-level wealth. We study the effects of two methods intended to reduce this problem: <i>Asset verification</i> confronts respondents with large discrepancies between wealth reports from the current wave and from the previous wave. <i>Cross-wave imputation</i> uses adjacent wave information in the imputation procedures for missing data. In the U.S. Health and Retirement Study, the corrections from asset verification substantially reduced wave-to-wave changes in wealth. The cross-wave imputations also reduced variation, but to a lesser extent.</p>","PeriodicalId":53705,"journal":{"name":"Journal of Economic and Social Measurement","volume":"44 2-3","pages":"117-139"},"PeriodicalIF":0.0,"publicationDate":"2019-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.3233/jem-190465","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"38917937","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}
{"title":"Demographic correlates of the onset of work limiting health conditions","authors":"K. Couch, P. Yu","doi":"10.3233/JEM-180451","DOIUrl":"https://doi.org/10.3233/JEM-180451","url":null,"abstract":"","PeriodicalId":53705,"journal":{"name":"Journal of Economic and Social Measurement","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2018-07-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.3233/JEM-180451","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46647137","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}
{"title":"Maximum likelihood estimation of the Markov chain model with macro data and the Ecological inference model","authors":"A. ten Cate","doi":"10.3233/jem-180452","DOIUrl":"https://doi.org/10.3233/jem-180452","url":null,"abstract":"","PeriodicalId":53705,"journal":{"name":"Journal of Economic and Social Measurement","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2018-07-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.3233/jem-180452","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49636372","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}
Economic data collection from commodities producers in the United States typically consists of revenues and quantities. While the data collected in some sectors such as fisheries are a census of the population, features of the population such as prices, must be calculated. Unit values are widely used as a price measure to impose a single price in place of dispersed ratios of revenue to quantity from individual producers but alternatives exist. In this paper, different linear aggregation procedures are used to calculate price measures, such as ratio-based calculations (e.g., ratio-of-means, mean-of-ratios), or estimation by ordinary least squares. There are non-trivial differences in the prices calculated depending on the procedure. This paper proposes a unified framework, including Bayesian estimation, for considering the tradeoffs inherent in the different methods commonly employed.
{"title":"A unified framework for calculating aggregate commodity prices from a census dataset","authors":"Michaela Dalton, B. Fissel","doi":"10.3233/JEM-180453","DOIUrl":"https://doi.org/10.3233/JEM-180453","url":null,"abstract":"Economic data collection from commodities producers in the United States typically consists of revenues and quantities. While the data collected in some sectors such as fisheries are a census of the population, features of the population such as prices, must be calculated. Unit values are widely used as a price measure to impose a single price in place of dispersed ratios of revenue to quantity from individual producers but alternatives exist. In this paper, different linear aggregation procedures are used to calculate price measures, such as ratio-based calculations (e.g., ratio-of-means, mean-of-ratios), or estimation by ordinary least squares. There are non-trivial differences in the prices calculated depending on the procedure. This paper proposes a unified framework, including Bayesian estimation, for considering the tradeoffs inherent in the different methods commonly employed.","PeriodicalId":53705,"journal":{"name":"Journal of Economic and Social Measurement","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2018-07-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.3233/JEM-180453","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42183510","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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