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Pinelopi Koujianou Goldberg - One of the best experts on this subject based on the ideXlab platform.
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dealer price discrimination in new car purchases evidence from the Consumer Expenditure Survey
Journal of Political Economy, 1996Co-Authors: Pinelopi Koujianou GoldbergAbstract:This paper documents the variation in dealer discounts for new cars using transactions price data from the Consumer Expenditure Survey. Consumer-specific characteristics fail to explain dealer discounts, whereas model, market-specific, and purchase transaction variables (e.g., first-time purchase, trade-in, and financing through dealer) do explain them. The results contradict earlier findings of race and gender discrimination based on a controlled experiment. This contradiction is reconciled by examining the higher moments of the empirical discount distribution; while mean and median markups do not vary by race and gender, minority purchases are characterized by higher dispersion. This may rationalize the disparate treatment of minorities by dealers documented in the controlled experiment.
Dirk Krueger - One of the best experts on this subject based on the ideXlab platform.
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consumption over the life cycle facts from Consumer Expenditure Survey data
The Review of Economics and Statistics, 2007Co-Authors: Jesus Fernandezvillaverde, Dirk KruegerAbstract:This paper uses Consumer Expenditure Survey data and a seminonparametric statistical model to estimate life cycle profiles of consumption, controlling for demographics, cohort, and time effects. We construct age profiles for total and nondurable consumption as well as Expenditure patterns for Consumer durables. Special emphasis is placed on the comparison of different approaches to control for changes in demo- graphics over the life cycle. We find significant humps over the life cycle for total, nondurable, and durable Expenditures. Changes in household size account for roughly half of these humps. Bootstrap simulations suggest that our empirical estimates are tight in that standard errors are small.
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understanding consumption smoothing evidence from the u s Consumer Expenditure data
Journal of the European Economic Association, 2005Co-Authors: Dirk Krueger, Fabrizio PerriAbstract:Consumption models with endogenous debt constraints differ from standard incomplete markets models in their predictions about an individual household’s ability to smooth consumption across time and states of the world. In this paper we develop these differences, both theoretically and quantitatively. We then use data from the US Consumer Expenditure Survey (CE) to assess along which dimensions the predictions of these models are consistent with the empirical evidence. We find that both type models fail to fully account for the data and argue that a model that combines aspects of both might be more succesfull.
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consumption over the life cycle some facts from Consumer Expenditure Survey data
2004 Meeting Papers, 2004Co-Authors: Dirk Krueger, Jesus FernandezvillaverdeAbstract:This paper uses a seminonparametric model and Consumer Expenditure Survey data to estimate life cycle profiles of consumption, controlling for demographics, cohort and time effects. In addition to documenting profiles for total and nondurable consumption, we devote special attention to the age Expenditure pattern for Consumer durables. We find hump-shaped paths over the life cycle for total, for nondurable and for durable Expenditures. Changes in household size account for roughly half of these humps. The other half remains unaccounted for by the standard complete markets life cycle model. Our results imply that households do not smooth consumption over their lifetimes. This is especially the case for services from Consumer durables. Bootstrap simulations suggest that our empirical estimates are tight and sensitivity analysis indicates that the computed profiles are robust to a large number of different specifications.
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consumption over the life cycle some facts from Consumer Expenditure Survey data
National Bureau of Economic Research, 2002Co-Authors: Jesus Fernandezvillaverde, Dirk KruegerAbstract:This paper uses a seminonparametric model and Consumer Expenditure Survey data to estimate life cycle profiles of consumption, controlling for demographics, cohort and time effects. In addition to documenting profiles for total and nondurable consumption, we devote special attention to the age Expenditure pattern for Consumer durables. We find hump-shaped paths over the life cycle for total, for nondurable and for durable Expenditures. Changes in household size account for roughly half of these humps. The other half remains unaccounted for by the standard complete markets life cycle model. Our results imply that households do not smooth consumption over their lifetimes. This is especially true for services from Consumer durables. Bootstrap simulations suggest that our empirical estimates are tight and sensitivity analysis indicates that the computed profiles are robust to a large number of different specifications.
Thesia I. Garner - One of the best experts on this subject based on the ideXlab platform.
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Is the Consumer Expenditure Survey Representative by Income
2014Co-Authors: John Sabelhaus, David Johnson, Stephen Ash, David B. Swanson, Thesia I. Garner, John S. Greenlees, Steve HendersonAbstract:Aggregate under-reporting of household spending in the Consumer Expenditure Survey (CE) can result from two fundamental types of measurement errors: higher-income households (who presumably spend more than average) are under-represented in the CE estimation sample, or there is systematic under-reporting of spending by at least some CE Survey respondents. Using a new data set linking CE units to zip-code level average Adjusted Gross Income (AGI), we show that the very highest-income households are less likely to respond to the Survey when they are sampled, but unit non-response rates are not associated with income over most of the income distribution. Although increasing representation at the high end of the income distribution could in principle significantly raise aggregate CE spending, the low reported average propensity to spend for higher-income respondent households could account for at least as much of the aggregate shortfall in total spending.(This abstract was borrowed from another version of this item.)
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Is the Consumer Expenditure Survey Representative by Income
2013Co-Authors: John Sabelhaus, David Johnson, Stephen Ash, David B. Swanson, Thesia I. Garner, John S. Greenlees, Steve HendersonAbstract:Aggregate under-reporting of household spending in the Consumer Expenditure Survey (CE) can result from two fundamental types of measurement errors: higher-income households (who presumably spend more than average) are under-represented in the CE estimation sample, or there is systematic under-reporting of spending by at least some CE Survey respondents. Using a new data set linking CE units to zip-code level average Adjusted Gross Income (AGI), we show that the very highest-income households are less likely to respond to the Survey when they are sampled, but unit non-response rates are not associated with income over most of the income distribution. Although increasing representation at the high end of the income distribution could in principle significantly raise aggregate CE spending, the low reported average propensity to spend for higher-income respondent households could account for at least as much of the aggregate shortfall in total spending.
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reconciling user costs and rental equivalence evidence from the u s Consumer Expenditure Survey
2012Co-Authors: Thesia I. Garner, Randal J VerbruggeAbstract:Abstract Previous research [Verbrugge, Randal, 2008a. The puzzling divergence of aggregate rents and user costs, 1980–2004. The Review of Income and Wealth 54(4), 671–699] demonstrated that housing rents and ex ante user costs diverge markedly for extended periods of time, a finding with profound implications for income and inflation measurement. But the primary data sources in that study were various indexes, based upon largely disjoint data sources, constructed using different aggregation techniques, and each subject to various criticisms. This raised doubts about the quality of the comparison. The relationship between user costs and rents might well be much tighter at the micro level; after all, house prices and rents (and their growth rates) can vary dramatically within cities, and rents are notoriously sticky. Furthermore, the use of indexes precludes both cross-sectional and dollar cost comparisons. In this study, we use Consumer Expenditure Interview Survey (CE) data to examine the relationship between user costs and rents at the individual unit-level, in dollars, using unit-level information on house value, rent, taxes, and the like. This allows us to accurately estimate unit-specific user costs and to control for unobservables like structure and neighborhood quality. We also make the point that in theory, after-tax user costs should equal net rent, i.e., expected rental income, rather than gross rent. Our findings are striking. In keeping with most previous research, we find tremendous divergence between conventional measures of user costs and net rents, thus ruling out index construction errors as a possible explanation. This divergence does not result from a faulty rent measure: we find that reported rents are sensible, in that they move similarly to official rent indexes, and are not simply out-of-pocket expenses. Instead, and most perplexing, we find a surprisingly close correspondence between net rents and a particular estimate of user costs, one implicitly assuming zero transactions costs and constructed using an appreciation measure that is both theoretically suspect and empirically a poor predictor of actual appreciation.
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supplemental poverty measure thresholds imputing noncash benefits to the Consumer Expenditure Survey using current population Survey parts i and ii
2011Co-Authors: Thesia I. Garner, Charles HokayemAbstract:In March 2010 an Interagency Technical Working Group (ITWG) released guidelines on thresholds and resources for a Supplemental Poverty Measure (SPM), recommending that thresholds include in-kind benefits that are accounted for in resources; however, only limited in-kind benefit information is available in the Consumer Expenditure Survey (CE), the data source upon which the thresholds are based. Garner (2010a,b,c) imputed in-kind rates and benefits for the National School Lunch Program (NSLP) and Women, Infants, and Children Program (WIC) using eligibility guidelines (CE Eligibility Method). To better reflect reported rates of participation, data from the Current Population Survey (CPS), the basis of the SPM resource measure, are used to model imputations to the CE for participation in NSLP and WIC (CPS Program Participation Method). Thresholds based on the CPS Program Participation Method are produced for 2009 and compared to thresholds based on the CE Eligibility Method. Preliminary results reveal that the two sets of thresholds defined for owners with mortgages, owners without mortgages, and renters are not statistically significantly different from each other. In contrast, when housing tenure thresholds are compared to each other within each method group, statistically significant differences arise.
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estimation of the misreporting models using micro data sets derived from the Consumer Expenditure Survey the gap between macro and micro economic statistics on Consumer durables
2010Co-Authors: Atsushi Maki, Thesia I. Garner, Massachusetts AvenueAbstract:In many countries, a gap between macroeconomic and microeconomic statistics is observed. To explain the gap, the present paper tests the misreporting hypothesis originally proposed by Deaton and Irish [4]. The data used for estimation involves ten clusters of Consumer durables from the Consumer Expenditure Survey in the US. Misreporting takes place, if a household purchased goods but did not report the amount (type 1 misreporting), or it purchased goods but reported the amount incorrectly (type 2 misreporting). The variance of the measurement error in type 2 misreporting is small and is not statistically
Yihua Liao - One of the best experts on this subject based on the ideXlab platform.
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transportation Expenditures and ability to pay evidence from Consumer Expenditure Survey
Transportation Research Record, 2006Co-Authors: Piyushimita Thakuriah, Yihua LiaoAbstract:Data at several levels of aggregation and spatial resolution show that mobility (measured by different outcomes such as vehicle miles traveled and automobile ownership) increases with income. It is equally likely that, in turn, investments in mobility (purchase and operation of private automobiles, consumption of public transportation services) allow greater quality of life in general and the ability to increase one's income. This possibly circular relationship is explored by using the Consumer Expenditure Survey (CEX) data set. Single-equation Tobit models of annual household transportation Expenditures are posited with, in the first case, annual before-tax income and, in the second case, annual total household-level Expenditures as a proxy for permanent income. With a variety of demographic, community and spatial, economic, family, and life-cycle conditions of the household controlled, it is found that permanent incomes explain mobility investments better than annual incomes. However, mobility investmen...
Fuad Hasanov - One of the best experts on this subject based on the ideXlab platform.
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Housing, Household Portfolio, and Intertemporal Elasticity of Substitution: Evidence from the Consumer Expenditure Survey
Social Science Research Network, 2005Co-Authors: Fuad HasanovAbstract:This paper investigates whether the inclusion of housing in a household portfolio is important to the household’s intertemporal decision making. Households hold portfolios of assets rather than a Treasury bill and/or a stock index and make their spending decisions based on expected total returns of an array of assets. The total returns account for capital gains, taxes, and inflation. In addition to financial assets such as stocks and bonds, we incorporate a real asset, residential housing, into a household portfolio. In particular, we estimate the intertemporal elasticity of substitution (IES), that is, how a change in asset or portfolio return affects household’s consumption growth, using a sample of households from the Consumer Expenditure Survey. Since changes in housing return can affect consumption of households over time, we investigate whether the inclusion of housing in the household portfolio provides different IES estimates. Moreover, utilizing a household-level data set, we estimate IES parameters for different groups of assetholders. Our results indicate that the housing return positively affects consumption growth, and housing is an important asset to account for in the household portfolio.
