Does the Swiss Car Market Reward Fuel Efficient Cars? Evidence from Hedonic Pricing Regressions, Matching and a Regression Discontinuity Design

To correct market failures due to the presence of negative externalities associated with energy consumption, governments have adopted a variety of policies, including taxes, subsidies, regulations and standards, and information-based policies. For example, labels that clearly convey energy consumption rates, associated costs, and emissions of conventional pollutants and CO2, have been devised and used in the last two decades in several countries. In 2003, Switzerland introduced a system of fuel economy labels, based on grades ranging from A to G, where is A best and G is worst, to assist consumers in making decisions that improve the fleet s fuel economy and lower emissions. We use a dataset documenting all passenger cars approved for sale in Switzerland each year from 2000 to 2011 to answer three key research questions. First, what is the willingness to pay for fuel economy? Second, do Swiss drivers - or Swiss auto importers on their behalf - appear to do a one-to-one tradeoff between car purchase price and savings on fuel costs over the lifetime of the car? Third, does the label have an additional effect on price, all else the same, above and beyond that of fuel efficiency alone? Hedonic pricing regressions that exploit the variation in fuel economy across make-models, and over time within make-models, suggest that there is a (modest) capitalization of fuel economy into car prices. The diesel premium, however, exceeds the future fuel cost savings made possible by diesel cars, even at zero discount rates. An alternate calculation suggests that the fuel economy premium is consistent with a very low discount rate (2.5%). We use a sharp regression discontinuity design (RDD) based on the mechanism used by the Swiss Federal Office of Energy to assign cars to the fuel economy label to see if the label has an independent effect on price, above and beyond that of the fuel economy. The RDD approach estimates the effect to be 6-11%. To broaden the fuel economy range over which we assess the effect of the A label, we also deploy matching estimators, and find that the effect of an A label on car price is approximately 5%

Some empirical issues in the estimation of market values of environmental amenities

This study presents consistent, and more efficient estimates compared with OLS and IV, for market values of amenities. The gain in efficiency is based on the use of a number of different indicators for the same amenity. The theory is derived from on a Lancasterian model that forces the functional form to be linear in characteristics. The empirical structure based on latent variables is applied to a model on property values of residential housing using different indicators for neighborhood quality. The dependent variable (property market value) is also treated as a latent variable for which two measures are available. The model is estimated using data from the U.S. American Housing Survey. The effect of quality of neighborhood on property values consistently estimated, is positive and significant. Variances of errors of measurement, and variances of the latent structures arepositive and significant without imposing nonnegativity restrictions

Some empirical issues in the estimation of market values of environmental amenities

This study presents consistent, and more efficient estimates compared with OLS and IV, for market values of amenities. The gain in efficiency is based on the use of a number of different indicators for the same amenity. The theory is derived from on a Lancasterian model that forces the functional form to be linear in characteristics. The empirical structure based on latent variables is applied to a model on property values of residential housing using different indicators for neighborhood quality. The dependent variable (property market value) is also treated as a latent variable for which two measures are available. The model is estimated using data from the U.S. American Housing Survey. The effect of quality of neighborhood on property values consistently estimated, is positive and significant. Variances of errors of measurement, and variances of the latent structures arepositive and significant without imposing nonnegativity restrictions.Este estudio presenta estimaciones consistentes, y más eficientes comparadas con MeO y VI, de valores de mercado de bienes ambientales (amenities). La ganancia en eficiencia está basada en el uso de varios indicadores para el mismo bien. La teoría se deriva de un modelo Lancasteriano, que impone la linealidad en características de la forma de 'la ecuación de precio. La estructura empírica basada en variables latentes es aplicada a un modelo sobre valores de propiedad residencial usando diferentes indicadores de calidad de vecindario. La variable dependiente (valor de mercado de la propiedad) está tratada también como una variable latente para la cual se utilizan dos mediciones. El modelo se estima con datos provenientes de la encuesta de hogares en EE.UU. (U.S. American Housing Survey). El efecto de calidad de vecindario sobre el valor de la propiedad estimado en fonna consistente, es positivo y significativo. La varianza de los errores de medida, y las varianzas de las estructuras latentes son positivas y significativas sin imponer ninguna restricción de no negatividad.Fac. de Ciencias Económicas y EmpresarialesInstituto Complutense de Análisis Económico (ICAE)TRUEpu

Neural Network Analysis of the Employee Classification Problem for Tax Purposes

Since 1987 the U.S. Internal Revenue Service has relied on twenty common law factors for guidance in determining whether a worker is an emplyoee or an independent contractor. This study presents new evidence on the task of simplifying that complex classification problem. Neural network methodology is used to classify workers using data obtained from Private Letter Rulings issued by the Internal Revenue Service from 1988 through a portion of 1993, a data set not previously used for this purpose. The model is highly accurate in correctly classifying workers as either employees or independent contractors. The overall prediction success rate using sample data was 97.2 percent and drops to 91.4 percent when a holdout sample was used. These findings are robust for each of the years in the study. For comparison purposes, classification results using logistic regression are also included. Results from both methodologies are identical

An estimation of technical efficiency for Florida public elementary schools

We use a frontier production function estimation technique to analyze whether elementary schools in Florida are operating at an efficient level and to explain any inefficiencies. A motivation for this analysis comes from recent state and federal level educational initiatives designed to improve school accountability and reduce class sizes. Results presented here indicate that while Florida elementary schools are not operating at efficient levels (with regional mean inefficiency estimates in the 4.1-5.1% range), they compare favorably to published results for other states. One factor associated with higher inefficiency is student promotion rates--something which does lie within the purview of school administrators and may have important policy implications. However, other factors associated with higher inefficiency (percent free-lunch eligible, higher crime and violence, higher suspension rates and not having a parent-teacher organization) are indicators of conditions that lie largely beyond the direct control of public schools, casting doubt on the effectiveness of recent accountability measures to improve efficiency.Technical efficiency Economics of education Efficiency Productivity Frontier production function Florida elementary schools

Estimating consumer preferences using market data - an application to us automobile demand

This paper explores the possibility of using market data to identify consumer preferences. A utility function composed of `homogeneous' characteristics and goods-specific effects is used as a basic link between the goods space and the characteristics space. The functional form for the hedonic price equation, the data requirements and issues of measurement errors for estimating demand and supply of characteristics are discussed. We illustrate the methodology by considering the US automobile demand using 1969-86 data compiled from Consumer Reports and Ward's Automotive Yearbook