Estimating the effect of a gasoline tax on carbon emissions

Recently the proposal has been made to raise gasoline taxes in the United States to curb carbon emissions. The existing literature on the sensitivity of gasoline consumption to changes in price may not be appropriate for evaluating the effectiveness of such a tax. First, most of these studies fail to address the endogeneity of gasoline prices. Second, the responsiveness of gasoline consumption to a change in tax may differ from the responsiveness of consumption to an average change in price. We address these challenges using a variety of methods including traditional single‐equation regression models, estimated by least squares or instrumental variables methods, and structural vector autoregressions. Our preferred approach exploits the historical variation in US federal and state gasoline taxes. Our most credible estimates imply that a 10‐cent per gallon increase in the gasoline tax would reduce carbon emissions from vehicles in the United States by about 1.5%. Copyright © 2010 John Wiley & Sons, Ltd.     

成交量、持仓量对我国大豆类期货价差波动影响的实证分析

采用GARCH(1,1)模型就成交量、持仓量对大豆类期货价差波动率的影响进行实证分析,结果显示：当期成交量、持仓量对大豆期货价差波动的整体影响是显著的;滞后成交量、持仓量对大豆期货价差波动的整体影响也是显著的;当成交量、持仓量同时进入条件方差方程时,它们对大豆类期货价差波动的影响整体上也是显著的。这一结论揭示了我国大豆期货市场信息传递过程,验证了我国大豆期货市场的信息非有效性,对期货市场投资者以及期货市场监管者具有一定的借鉴意义。     

The demand for gasoline: a two stage approach

The demand for gasoline has typically been estimated using a reduced-form equation model. The simplicity of the approach is attractive, but has proven to be costly in terms of the insights lost as to the nature of the processes governing the interdependence between fuel efficiency and the overall demand for gasoline. On the other hand, disaggregating the overall demand for gasoline into all of its components produces an enormous amount of detail and many insights, but increases commensurately the complexity of the system and reduces its usefulness in forecasting.A two stage simple demand equation is used which first involves an estimation of the level of fuel efficiency of the fleet stock in terms of price induced technical change. In the second stage, the first equation is coupled with other typical demand variables to determine the overall demand for gasoline. The procedure provides an excellent forecasting equation of both the short-and long-term demand for gasoline.     

Gasoline prices,transport costs,and the U.S. business cycles

The effects of gasoline prices on the U.S. business cycles are investigated. In order to distinguish between gasoline supply and gasoline demand shocks, the price of gasoline is endogenously determined through a transportation sector that uses gasoline as an input of production. The model is estimated for the U.S. economy using five macroeconomic time series, including data on transport costs and gasoline prices. The results show that although standard shocks in the literature (e.g., technology shocks, monetary policy shocks) have significant effects on the U.S. business cycles in the long run, gasoline supply and demand shocks play an important role in the short run.     

Calendar synchronization of gasoline price increases

In many retail gasoline markets with Edgeworth price cycles, large and regular price increases occur on the same day of the week every week, that is, they are calendar synchronized. In this article, I test whether calendar synchronization leads to higher or lower consumer expenditures on gasoline compared to a world with cycles but without calendar synchronization. On one hand, firms may attempt to trigger price increases just prior to periods of normally high demand. On the other, consumers may be better able to predict and shift purchases to low price days of the cycle. Using high‐frequency gasoline volume data and matching it to high‐frequency price data, I find that the latter effect dominates. All else equal, consumer expenditures on gasoline fall with calendar synchronization in the study markets. I also calculate intertemporal price elasticities and find them to be high.     

Increasing the price variation in a repeated cross section

Insufficient price variation seriously hampers many applications of consumer demand models. This paper examines the empirical performance of a potential remedy for this problem that was suggested by [Lewbel, A., 1989. Identification and estimation of equivalence scales under weak separability. Review of Economic Studies 56, 311–316], the construction of individual specific price indices for bundles of goods. These individual specific price indices allow for a population with heterogeneity in preferences for goods within a given bundle of goods. We confine ourselves to heterogeneous Cobb Douglas within bundle preferences, while between bundles, we allow for several parametric and even general nonparametric specifications. In a variety of settings, we show that such prices produce superior empirical results than the ones obtained through the traditional practice of using aggregate price indices. Our empirical analysis is based on the British Family Expenditure Survey data, and uses several categories of food. Both in parametric as well as nonparametric models, we obtain higher precision of estimates for parameters or functions, as well as economically more plausible results.     

Pain at the pump: Gasoline prices and subjective well-being

In recent years, there has been growing interest in the health implications of rising gasoline prices. This paper considers the impact of gasoline prices on subjective well-being, as captured by survey questions on happiness and life satisfaction. Using rich data from the DDB Worldwide Communications Life Style™ survey, we document a negative relationship between gasoline prices and self-reported life satisfaction over the period 1985–2005. The estimated reduction in well-being, moreover, is found to be nearly twice as large among groups of likely car owners. Interestingly, although rising gasoline prices lead to an immediate deterioration in subjective well-being, analyses of lagged prices suggest that well-being almost fully rebounds 1 year later and changes very little each year thereafter. Our contemporaneous estimates imply that rising gasoline prices generate well-being losses comparable to faltering labor market conditions, and likely offset some of the physical health benefits found in previous research.     

An empirical analysis of effects of gasoline price change on transportation behavior in Japan,with consideration of regional differences

This empirically analyzes the effect of gasoline price change on various aspects of surface transport behavior comprehensively, with consideration of regional differences as to whether or not the region includes a major metropolitan agglomeration area (hereafter, “megalopolis”), by means of carefully arranging yearly time-series data from fiscal 1987 to fiscal 2008 in Japan. The aim is to look at common as well as different effects among regions and to draw policy implications relating to fuel price, as well as to fuel tax, towards developing a low-carbon transport system, which are applicable to other countries including emerging countries where a demographic disparity between megalopolis areas and rural areas might be increasing. The methodology includes the multiple regression models complemented by the 1st order auto-regressive models of error terms, where the elasticities of gasoline price and those of income regarding usage of personal automobiles, of public transport and of passenger railways with or without periodic tickets, and fuel consumption on cars, as well as ownership of various types of cars, are estimated for individual gross-regions. In both gross-regions, higher gasoline prices are commonly shown to be related to lower ownership of larger private passenger cars, higher ownership of light cars, lower ownership of the total private passenger cars, lower passenger-km per capita in cars, lower fuel consumption on cars and higher transit ridership. The result suggests general automobile-fuel-price policy implications, the extent of which is differentiated by spatial characteristics, and estimates the adverse effect of the possible abolition of the provisional gasoline tax rate on the emissions in both gross-regions. The application of result is also tried in exploring effect of other policy measures such as expressway tolls.     

A Bayesian mixed logit–probit model for multinomial choice

In this paper, we introduce a new flexible mixed model for multinomial discrete choice where the key individual- and alternative-specific parameters of interest are allowed to follow an assumption-free nonparametric density specification, while other alternative-specific coefficients are assumed to be drawn from a multivariate Normal distribution, which eliminates the independence of irrelevant alternatives assumption at the individual level. A hierarchical specification of our model allows us to break down a complex data structure into a set of submodels with the desired features that are naturally assembled in the original system. We estimate the model, using a Bayesian Markov Chain Monte Carlo technique with a multivariate Dirichlet Process (DP) prior on the coefficients with nonparametrically estimated density. We employ a “latent class” sampling algorithm, which is applicable to a general class of models, including non-conjugate DP base priors. The model is applied to supermarket choices of a panel of Houston households whose shopping behavior was observed over a 24-month period in years 2004–2005. We estimate the nonparametric density of two key variables of interest: the price of a basket of goods based on scanner data, and driving distance to the supermarket based on their respective locations. Our semi-parametric approach allows us to identify a complex multi-modal preference distribution, which distinguishes between inframarginal consumers and consumers who strongly value either lower prices or shopping convenience.     

Time reversibility of stationary regular finite-state Markov chains

We propose an alternate parameterization of stationary regular finite-state Markov chains, and a decomposition of the parameter into time reversible and time irreversible parts. We demonstrate some useful properties of the decomposition, and propose an index for a certain type of time irreversibility, applicable to chains whose states are naturally ordered. Two empirical examples illustrate the use of the proposed parameter, decomposition and index. One, on gasoline price mark-ups, involves observed states. The other, on U.S. investment growth, features latent states.     

Inferring Policy Objectives from Economic Outcomes*

Estimated policy rules are reduced‐form equations that are silent on many important policy questions. However, a structural understanding of monetary policy can be obtained by estimating a policymaker's objective function. The paper derives conditions under which the parameters in a policymaker's policy objective function can be identified and estimated. We apply these conditions to a New Keynesian sticky‐price model of the US economy. The results show that the implicit inflation target and the relative weight placed on interest rate smoothing both declined when Paul Volcker was appointed Federal Reserve chairman.     

Effects of the 1979 gasoline shortages on Philadelphia housing prices

Conventional theory predicts that transportation cost to a big-city central business district is an important determinant of housing prices. If this is true, the sudden rise in gasoline price following the Iranian revolution in 1979 could have caused a relative housing-price shift in central and peripheral neighborhoods. This paper looks for such an effect by fitting hedonic price functions in selected neighborhoods at varying distances from downtown Philadelphia, and testing for a relative shift at the time of the gasoline shortage. The results suggest that the energy shortage's effects may have been focused disproportionately on a few already revitalizing neighborhoods.     

Quantile Autoregressive Distributed Lag Model with an Application to House Price Returns*

This article studies quantile regression in an autoregressive dynamic framework with exogenous stationary covariates. We demonstrate the potential of the quantile autoregressive distributed lag model with an application to house price returns in the United Kingdom. The results show that house price returns present a heterogeneous autoregressive behaviour across the quantiles. Real GDP growth and interest rates also have an asymmetric impact on house prices variations.     

Asymmetric Price Adjustment and Consumer Search: An Examination of the Retail Gasoline Market

This article proposes a new explanation for why retail prices respond more quickly to cost increases than cost decreases. I develop a search model that assumes consumers’ expectations of prices are based on prices observed during previous purchases. This model predicts that consumers search less when prices are falling, which results in higher profit margins and a slower price response to cost changes. I then empirically examine patterns of retail gasoline price response and price dispersion to show that this model predicts observed price behavior better than previously suggested explanations.     

Estimating the distribution of welfare effects using quantiles

This paper proposes a framework to model welfare effects that are associated with a price change in a population of heterogeneous consumers. The framework is similar to that of Hausman and Newey (Econometrica, 1995, 63, 1445–1476), but allows for more general forms of heterogeneity. Individual demands are characterized by a general model that is nonparametric in the regressors, as well as monotonic in unobserved heterogeneity, allowing us to identify the distribution of welfare effects. We first argue why a decision maker should care about this distribution. Then we establish constructive identification, propose a sample counterparts estimator, and analyze its large‐sample properties. Finally, we apply all concepts to measuring the heterogeneous effect of a change of gasoline price using US consumer data and find very substantial differences in individual effects across quantiles.     

Monetary policy and stock prices in small open economies: Empirical evidence for the new EU member states

This study presents evidence on the effect of domestic and Euro Area monetary policy on stock prices in four new EU member states of Central Europe and the main determinants of stock price volatility, estimating structural vector autoregressive models identified with short-run restrictions. We find that stock prices in the considered new EU member states are more sensitive to changes in the Euro Area interest rate than to the domestic one. Moreover, the bulk of stock price volatility in these countries is due to shocks related to exchange rate and Euro Area monetary policy. Overall, we find that local stock markets are more sensitive to external shocks than to domestic ones.     

Inside the Crystal Ball: New Approaches to Predicting the Gasoline Price at the Pump

Appropriate real‐time forecasting models for the US retail price of gasoline yield substantial reductions in the mean‐squared prediction error (MSPE) at horizons up to 2 years as well as substantial increases in directional accuracy. Even greater MSPE reductions are possible by constructing a pooled forecast that assigns equal weight to five of the most successful forecasting models. Pooled forecasts have lower MSPE than the US Energy Information Administration gasoline price forecasts and the gasoline price expectations in the Michigan Survey of Consumers. We also show that as much as 39% of the decline in gas prices between June and December 2014 was predictable. Copyright © 2016 John Wiley & Sons, Ltd.     

Anticipation,Tax Avoidance,and the Price Elasticity of Gasoline Demand

Least‐squares estimates of the response of gasoline consumption to a change in the gasoline price are biased toward zero, given the endogeneity of gasoline prices. A seemingly natural solution to this problem is to instrument for gasoline prices using gasoline taxes, but this approach tends to yield implausibly large price elasticities. We demonstrate that anticipatory behavior provides an important explanation for this result. Gasoline buyers increase purchases before tax increases and delay purchases before tax decreases, rendering the tax instrument endogenous. Including suitable leads and lags in the regression restores the validity of the IV estimator, resulting in much lower elasticity estimates. Copyright © 2016 John Wiley & Sons, Ltd.     

Inference with non-Gaussian Ornstein–Uhlenbeck processes for stochastic volatility

Continuous-time stochastic volatility models are becoming an increasingly popular way to describe moderate and high-frequency financial data. Barndorff-Nielsen and Shephard (2001a) proposed a class of models where the volatility behaves according to an Ornstein–Uhlenbeck (OU) process, driven by a positive Lévy process without Gaussian component. These models introduce discontinuities, or jumps, into the volatility process. They also consider superpositions of such processes and we extend that to the inclusion of a jump component in the returns. In addition, we allow for leverage effects and we introduce separate risk pricing for the volatility components. We design and implement practically relevant inference methods for such models, within the Bayesian paradigm. The algorithm is based on Markov chain Monte Carlo (MCMC) methods and we use a series representation of Lévy processes. MCMC methods for such models are complicated by the fact that parameter changes will often induce a change in the distribution of the representation of the process and the associated problem of overconditioning. We avoid this problem by dependent thinning methods. An application to stock price data shows the models perform very well, even in the face of data with rapid changes, especially if a superposition of processes with different risk premiums and a leverage effect is used.     

货币和税收政策对我国住房价格的影响——基于VAR模型的实证研究

基于我国1999-2010年房地产市场季度数据,本文建立向量自回归模型(VAR)和向量误差修正模型(VEC),将住房供给和需求同时纳入模型,分析我国利率政策、信贷政策和税收政策对住房价格的影响。结果显示,贷款利率在短期内对住房供给有负效应,但长期效应不明显;贷款规模对住房价格的短期冲击明显,二者之间存在正相关关系;针对保有环节征税可以通过影响住房供给,从而有效抑制住房价格上升。根据我国住房供求特点,应优先选择税收工具,通过促进住房供给实现控制房价的政策目标。