Using newly available administrative data from the IRS, this paper studies the distribution of employer-sponsored health insurance premiums. Previous estimates, in contrast, were almost exclusively from household surveys. After correcting for coverage limitations of IRS data, we find average premiums for employer-sponsored plans are roughly $1,000 higher in IRS records than in the Current Population Survey. The downward bias in the CPS results from underestimating premiums of married workers and topcoding of high premiums.
{"title":"How Much Does Health Insurance Cost? Comparison of Premiums in Administrative and Survey Data","authors":"Jeff Larrimore, David Splinter","doi":"10.17016/FEDS.2018.030","DOIUrl":"https://doi.org/10.17016/FEDS.2018.030","url":null,"abstract":"Using newly available administrative data from the IRS, this paper studies the distribution of employer-sponsored health insurance premiums. Previous estimates, in contrast, were almost exclusively from household surveys. After correcting for coverage limitations of IRS data, we find average premiums for employer-sponsored plans are roughly $1,000 higher in IRS records than in the Current Population Survey. The downward bias in the CPS results from underestimating premiums of married workers and topcoding of high premiums.","PeriodicalId":143058,"journal":{"name":"Econometric Modeling: Microeconometric Studies of Health","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131265966","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. Goodman, Michael Hurwitz, Jisung Park, Jonathan Smith
We demonstrate that heat inhibits learning and that school air conditioning may mitigate this effect. Student fixed effects models using students who retook the PSATs show that hotter school days in the years before the test was taken reduce scores, with extreme heat being particularly damaging. Weekend and summer temperatures have little impact, suggesting heat directly disrupts learning time. New nationwide, school-level measures of air conditioning penetration suggest patterns consistent with such infrastructure largely offsetting heat’s effects. Without air conditioning, a 1°F hotter school year reduces that year’s learning by 1 percent. Hot school days disproportionately impact minority students, accounting for roughly 5 percent of the racial achievement gap. (JEL I21, I24, J15, Q54)
{"title":"Heat and Learning","authors":"J. Goodman, Michael Hurwitz, Jisung Park, Jonathan Smith","doi":"10.2139/ssrn.3180724","DOIUrl":"https://doi.org/10.2139/ssrn.3180724","url":null,"abstract":"We demonstrate that heat inhibits learning and that school air conditioning may mitigate this effect. Student fixed effects models using students who retook the PSATs show that hotter school days in the years before the test was taken reduce scores, with extreme heat being particularly damaging. Weekend and summer temperatures have little impact, suggesting heat directly disrupts learning time. New nationwide, school-level measures of air conditioning penetration suggest patterns consistent with such infrastructure largely offsetting heat’s effects. Without air conditioning, a 1°F hotter school year reduces that year’s learning by 1 percent. Hot school days disproportionately impact minority students, accounting for roughly 5 percent of the racial achievement gap. (JEL I21, I24, J15, Q54)","PeriodicalId":143058,"journal":{"name":"Econometric Modeling: Microeconometric Studies of Health","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-04-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114222451","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, I study the role of changes in the wage structure and expectations about marriage in explaining the college gender gap reversal. With strongly diminishing marginal utility of wealth and in the presence of a gender wage gap, single women have a greater incentive than single men to invest in education. Marriage‐market distortions tend to depress the overall benefit of education for women relative to men. I develop a tractable two‐period model and parameterize it using US census data for the cohort born in 1950. I then show that it can generate a reversal and that the most important driving force for this is the decline in marriage rates.
{"title":"Wealth, Wages, and Wedlock: Explaining the College Gender Gap Reversal","authors":"L. Reijnders","doi":"10.1111/sjoe.12233","DOIUrl":"https://doi.org/10.1111/sjoe.12233","url":null,"abstract":"In this paper, I study the role of changes in the wage structure and expectations about marriage in explaining the college gender gap reversal. With strongly diminishing marginal utility of wealth and in the presence of a gender wage gap, single women have a greater incentive than single men to invest in education. Marriage‐market distortions tend to depress the overall benefit of education for women relative to men. I develop a tractable two‐period model and parameterize it using US census data for the cohort born in 1950. I then show that it can generate a reversal and that the most important driving force for this is the decline in marriage rates.","PeriodicalId":143058,"journal":{"name":"Econometric Modeling: Microeconometric Studies of Health","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122477544","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 rational addiction model is usually tested by estimating a linear second-order difference Euler equation, which may produce unreliable estimates. We show that a linear first-order difference equation is a better alternative. This empirical specification is appropriate under the reasonable assumption that people are uncertain about the time of their death, it is based on the same structural assumptions used in the literature, and it retains all policy implications of the deterministic rational addiction model. It is also empirically convenient because it is simple, it allows using efficient estimation strategies that do not require instrumental variables, and it is robust to the possible non-stationarity of the data. As an application we estimate the demand for smoking in the US from 1970 to 2016, and we show that it is consistent with the rational addiction model.
{"title":"Testing Rational Addiction: When Lifetime is Uncertain, One Lag is Enough","authors":"D. Dragone, Davide Raggi","doi":"10.2139/ssrn.3155099","DOIUrl":"https://doi.org/10.2139/ssrn.3155099","url":null,"abstract":"The rational addiction model is usually tested by estimating a linear second-order difference Euler equation, which may produce unreliable estimates. We show that a linear first-order difference equation is a better alternative. This empirical specification is appropriate under the reasonable assumption that people are uncertain about the time of their death, it is based on the same structural assumptions used in the literature, and it retains all policy implications of the deterministic rational addiction model. It is also empirically convenient because it is simple, it allows using efficient estimation strategies that do not require instrumental variables, and it is robust to the possible non-stationarity of the data. As an application we estimate the demand for smoking in the US from 1970 to 2016, and we show that it is consistent with the rational addiction model.","PeriodicalId":143058,"journal":{"name":"Econometric Modeling: Microeconometric Studies of Health","volume":"273 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-03-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134103823","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 'secondary effects' legal doctrine allows municipalities to zone, or otherwise regulate, sexually oriented businesses. Negative 'secondary effects' (economic externalities) justify limiting First Amendment protection of speech conducted inside strip clubs. One example of a secondary effect, cited in no fewer than four United States Supreme Court rulings, is the negative effect of strip clubs on the quality of the surrounding neighborhood. Little empirical evidence that strip clubs do, in fact, have a negative effect on the surrounding neighborhood exists. To the extent that changes in neighborhood quality are reflected by changes in property prices, property prices should decrease when a strip club opens up nearby. We estimate an augmented repeat sales regression model of housing prices to estimate the effect of strip clubs on nearby residential property prices. Using real estate transactions from King County, Washington, we test the hypothesis that strip clubs have a negative effect on surrounding residential property prices. We exploit the unique and unexpected termination of a 17 year moratorium on new strip club openings in order to generate exogenous variation in the operation of strip clubs. We find no statistical evidence that strip clubs have 'secondary effects' on nearby residential property prices.
{"title":"Strip Clubs, “Secondary Effects” and Residential Property Prices","authors":"T. Brooks, B. Humphreys, Adam D. Nowak","doi":"10.1111/1540-6229.12236","DOIUrl":"https://doi.org/10.1111/1540-6229.12236","url":null,"abstract":"The 'secondary effects' legal doctrine allows municipalities to zone, or otherwise regulate, sexually oriented businesses. Negative 'secondary effects' (economic externalities) justify limiting First Amendment protection of speech conducted inside strip clubs. One example of a secondary effect, cited in no fewer than four United States Supreme Court rulings, is the negative effect of strip clubs on the quality of the surrounding neighborhood. Little empirical evidence that strip clubs do, in fact, have a negative effect on the surrounding neighborhood exists. To the extent that changes in neighborhood quality are reflected by changes in property prices, property prices should decrease when a strip club opens up nearby. We estimate an augmented repeat sales regression model of housing prices to estimate the effect of strip clubs on nearby residential property prices. Using real estate transactions from King County, Washington, we test the hypothesis that strip clubs have a negative effect on surrounding residential property prices. We exploit the unique and unexpected termination of a 17 year moratorium on new strip club openings in order to generate exogenous variation in the operation of strip clubs. We find no statistical evidence that strip clubs have 'secondary effects' on nearby residential property prices.","PeriodicalId":143058,"journal":{"name":"Econometric Modeling: Microeconometric Studies of Health","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-03-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116869384","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 general purpose of a dynamic factor model (DFM) is to summarize a large number of time series into a few common factors. Here we explore a number of DFM specifications applied to 80 granular, non-overlapping indexes of commercial property prices in the US, quarterly from 2001 to 2017. We examine the nature and the structure of the factors and the index forecasts that can be produced using the DFMs. We consider specifications of 1, 2, 3 and 4 common factor trends. As a major motivation for the use of DFMs is their ability to improve out-of-sample forecasting of systems of numerous related series, we apply the DFM estimated factor returns in an Autoregressive Distributed Lag (ARDL) model to forecast the individual real estate price series. We compare the forecasted residuals to a conventional Autoregressive (AR) forecast model as a "benchmark" for two markets: Boston apartments and Dallas commercial. The results show that the ARDL model predicts the crisis and subsequent recovery really well, whereas the "benchmark" model typically follows the previous price trend. We find that the DFM forecasts are most precise with only one or two factors. The two prominent factors may reflect general economic conditions and the rental housing market, respectively.
{"title":"Forecasting US Commercial Property Price Indexes Using Dynamic Factor Models","authors":"Alex M. van de Minne, Marc K. Francke, D. Geltner","doi":"10.2139/ssrn.3148680","DOIUrl":"https://doi.org/10.2139/ssrn.3148680","url":null,"abstract":"The general purpose of a dynamic factor model (DFM) is to summarize a large number of time series into a few common factors. Here we explore a number of DFM specifications applied to 80 granular, non-overlapping indexes of commercial property prices in the US, quarterly from 2001 to 2017. We examine the nature and the structure of the factors and the index forecasts that can be produced using the DFMs. We consider specifications of 1, 2, 3 and 4 common factor trends. As a major motivation for the use of DFMs is their ability to improve out-of-sample forecasting of systems of numerous related series, we apply the DFM estimated factor returns in an Autoregressive Distributed Lag (ARDL) model to forecast the individual real estate price series. We compare the forecasted residuals to a conventional Autoregressive (AR) forecast model as a \"benchmark\" for two markets: Boston apartments and Dallas commercial. The results show that the ARDL model predicts the crisis and subsequent recovery really well, whereas the \"benchmark\" model typically follows the previous price trend. We find that the DFM forecasts are most precise with only one or two factors. The two prominent factors may reflect general economic conditions and the rental housing market, respectively.","PeriodicalId":143058,"journal":{"name":"Econometric Modeling: Microeconometric Studies of Health","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-03-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132407909","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 examine the effects of house prices on public school finances including tax revenue and expenditures. We find an elasticity of school district revenue with respect to house price growth of 0.2 and a similar elasticity for expenditures. Elasticities for expenditures, however, are much more volatile and correlated with the business cycle. During the Great Recession, the Federal Government acted as a social safety net for local schools. Our results also indicate that there are positive and statistically significant elasticities for teacher salaries with respect to house prices. These elasticities were largest during the Great Recession and the elasticities are even larger for teacher benefits. Findings further suggest that elasticities for school administrator salaries are similar to (and not statistically different from) elasticities for teacher salaries. Elasticities for administrator salaries are smaller (and thus less responsive) than elasticities for teacher benefits.
{"title":"House Prices and School Finances","authors":"Chandler Lutz","doi":"10.2139/ssrn.3228073","DOIUrl":"https://doi.org/10.2139/ssrn.3228073","url":null,"abstract":"In this paper, we examine the effects of house prices on public school finances including tax revenue and expenditures. We find an elasticity of school district revenue with respect to house price growth of 0.2 and a similar elasticity for expenditures. Elasticities for expenditures, however, are much more volatile and correlated with the business cycle. During the Great Recession, the Federal Government acted as a social safety net for local schools. Our results also indicate that there are positive and statistically significant elasticities for teacher salaries with respect to house prices. These elasticities were largest during the Great Recession and the elasticities are even larger for teacher benefits. Findings further suggest that elasticities for school administrator salaries are similar to (and not statistically different from) elasticities for teacher salaries. Elasticities for administrator salaries are smaller (and thus less responsive) than elasticities for teacher benefits.","PeriodicalId":143058,"journal":{"name":"Econometric Modeling: Microeconometric Studies of Health","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-03-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128749219","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}
Zoning regulations provide benefits, but they also restrict housing supply and hence raise prices. This paper quantifies their importance by comparing prices to the marginal costs of supply at different points in time. For detached houses, marginal costs comprise the dwelling structure and the land that other home owners need to forego. Relative to our estimates of these costs, we find that, as of 2016, zoning raised detached house prices 73 per cent above marginal costs in Sydney, 69 per cent in Melbourne, 42 per cent in Brisbane and 54 per cent in Perth. Zoning has also raised the price of apartments well above the marginal cost of supply, especially in Sydney. We emphasise that this is not the amount that housing prices would fall in the absence of zoning. The effect of zoning has increased dramatically over the past two decades, likely due to existing restrictions binding more tightly as demand has risen.
{"title":"The Effect of Zoning on Housing Prices","authors":"Ross Kendall, P. Tulip","doi":"10.2139/ssrn.3149272","DOIUrl":"https://doi.org/10.2139/ssrn.3149272","url":null,"abstract":"Zoning regulations provide benefits, but they also restrict housing supply and hence raise prices. This paper quantifies their importance by comparing prices to the marginal costs of supply at different points in time. For detached houses, marginal costs comprise the dwelling structure and the land that other home owners need to forego. Relative to our estimates of these costs, we find that, as of 2016, zoning raised detached house prices 73 per cent above marginal costs in Sydney, 69 per cent in Melbourne, 42 per cent in Brisbane and 54 per cent in Perth. Zoning has also raised the price of apartments well above the marginal cost of supply, especially in Sydney. We emphasise that this is not the amount that housing prices would fall in the absence of zoning. The effect of zoning has increased dramatically over the past two decades, likely due to existing restrictions binding more tightly as demand has risen.","PeriodicalId":143058,"journal":{"name":"Econometric Modeling: Microeconometric Studies of Health","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-03-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124679379","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. Cardoso, Paulo Guimarães, P. Portugal, Hugo Reis
We bring together the strands of literature on the returns to education, its spillovers, and the role of the employer shaping the wage distribution. The aim is to analyze the labor market returns to education taking into account who the worker is (worker unobserved ability), what he does (the job title), with whom (the coworkers) and, also crucially, for whom (the employer). We combine data of remarkable quality – exhaustive longitudinal linked employer-employee data on Portugal – with innovative empirical methods, to address the homophily or reflection problem, selection issues, and common measurement errors and confounding factors. Our methodology combines the estimation of wage regressions in the spirit of Abowd, Kramarz, and Margolis (1999), Gelbach's (2016) unambiguous conditional decomposition of the impact of various omitted covariates on an estimated coefficient, and Arcidiacono et al.'s (2012) procedure to identify the impact of peer quality. We first uncover that peer effects are quite sizeable. A one standard deviation increase in the measure of peer quality leads to a wage increase of 2.1 log points. Next, we show that education grants access to better-paying firms and job titles: one fourth of the overall return to education operates through the firm channel and a third operates through the job-title channel, while the remainder is associated exclusively with the individual worker. Finally, we unveil that an additional year of average education of coworkers yields a 0.5 log points increase in a worker's wage, after we net out a 2.0 log points return due to homophily (similarity of own and peers' characteristics), and 3.3 log points associated with worker sorting across firms and job titles.
{"title":"The Returns to Schooling Unveiled","authors":"A. Cardoso, Paulo Guimarães, P. Portugal, Hugo Reis","doi":"10.2139/ssrn.3153383","DOIUrl":"https://doi.org/10.2139/ssrn.3153383","url":null,"abstract":"We bring together the strands of literature on the returns to education, its spillovers, and the role of the employer shaping the wage distribution. The aim is to analyze the labor market returns to education taking into account who the worker is (worker unobserved ability), what he does (the job title), with whom (the coworkers) and, also crucially, for whom (the employer). We combine data of remarkable quality – exhaustive longitudinal linked employer-employee data on Portugal – with innovative empirical methods, to address the homophily or reflection problem, selection issues, and common measurement errors and confounding factors. Our methodology combines the estimation of wage regressions in the spirit of Abowd, Kramarz, and Margolis (1999), Gelbach's (2016) unambiguous conditional decomposition of the impact of various omitted covariates on an estimated coefficient, and Arcidiacono et al.'s (2012) procedure to identify the impact of peer quality. We first uncover that peer effects are quite sizeable. A one standard deviation increase in the measure of peer quality leads to a wage increase of 2.1 log points. Next, we show that education grants access to better-paying firms and job titles: one fourth of the overall return to education operates through the firm channel and a third operates through the job-title channel, while the remainder is associated exclusively with the individual worker. Finally, we unveil that an additional year of average education of coworkers yields a 0.5 log points increase in a worker's wage, after we net out a 2.0 log points return due to homophily (similarity of own and peers' characteristics), and 3.3 log points associated with worker sorting across firms and job titles.","PeriodicalId":143058,"journal":{"name":"Econometric Modeling: Microeconometric Studies of Health","volume":"146 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132559874","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}
We study the effect of early life exposure to above average levels of rainfall on adult mental health. While we find no effect from pre-natal exposure, post-natal positive rainfall shocks decrease average Center for Epidemiological Studies Depression (CESD) mental health scores by 15 percent and increase the likelihood of depression by 5 percent, a more than 20 percent increase relative to the mean. These effects are limited to females. We rule out prenatal stress and income shocks as pathways and find evidence suggestive of increased exposure to disease.
{"title":"Positive Early Life Rainfall Shocks and Adult Mental Health","authors":"M. Pasha, Marc Rockmore, Chih Ming Tan","doi":"10.2139/ssrn.3129776","DOIUrl":"https://doi.org/10.2139/ssrn.3129776","url":null,"abstract":"We study the effect of early life exposure to above average levels of rainfall on adult mental health. While we find no effect from pre-natal exposure, post-natal positive rainfall shocks decrease average Center for Epidemiological Studies Depression (CESD) mental health scores by 15 percent and increase the likelihood of depression by 5 percent, a more than 20 percent increase relative to the mean. These effects are limited to females. We rule out prenatal stress and income shocks as pathways and find evidence suggestive of increased exposure to disease.","PeriodicalId":143058,"journal":{"name":"Econometric Modeling: Microeconometric Studies of Health","volume":"60 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-02-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126757257","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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