Marginal Effects and Significance Testing with Heckman’s Sample Selection Model: A Methodological Note

This paper illustrates two techniques for calculating the statistical significance of the marginal effects derived from Heckman’s sample selection model,an increasingly common econometric specification in political science. The discussion draws on an analysis by Sweeney (2003) of the incidence and intensity of interstate disputes. After replicating his results, the paper presents the delta method and the nonparametric bootstrap as alternative techniques for obtaining standard errors of the marginal effects, which themselves are calculated from a transformation of the model parameters.The analysis reveals two variables for which misleading inferences are drawn with respect to the precision of the estimated coefficients in the original study, suggesting that significance testing of the derived marginal effects is warranted.Heckman model, statistical significance, delta method; nonparametric bootstrap, dispute severity

Re-Identifying the Rebound – What About Asymmetry?

Rebound eff ects measure the behaviorally induced off set in the reduction of energy consumption following effi ciency improvements. Using panel estimation methods and household travel diary data collected in Germany between 1997 and 2009, this study identifi es the rebound eff ect in private transport by allowing for the possibility that fuel price elasticities – from which rebound eff ects can be derived – are asymmetric. This approach rests on evidence that has emerged from the empirical literature suggesting that the response in individual travel demand to price increases is stronger than to decreases. Such an asymmetric response would necessitate reference to the fuel price elasticity derived from price decreases in order to identify the rebound eff ect, as the rebound occurs in response to a decrease in unit cost for car travel due to improved fuel effi ciency. While we fail to reject the hypothesis that the magnitude of the response to a price increase is equal to that of a price decrease, our rebound eff ect estimate for single-vehicle households of 58% is in line with a recent German study by Frondel, Peters, and Vance (2008).Automobile travel; panel estimation models

A Count Data Analysis of Ridership in Germany’s Public Transport

Focusing on adult members of German households, this paper investigates the determinants of public transit ridership with the aim of quantifying the effects of fuel prices, fares, person-level attributes, and characteristics of the transit system on transport counts over a five-day week. The reliance on individual data raises several conceptual and empirical issues, the most fundamental of which is the large proportion of zero values in transit counts. To accommodate this feature of the data, we employ modeling procedures referred to as zero-inflated models (ZIMs), which order observations into two latent regimes defined by whether the individual never uses public transport. Our estimates reveal fuel prices to have a positive and substantial influence on transit ridership, though there is no evidence for a statistically significant impact of the fare.Transit Ridership, Pricing Policy, Zero-Inflated Models, Household Data.

On the Link between Urban Form and Automobile Use - Evidence from German Survey Data

This study investigates the influence of urban form on automobile travel using travel-diary data from Germany. Two dimensions of car use are considered: the discrete decision to own a car and the continuous decision of distance traveled. Because these decisions are likely to be influenced by factors unobservable to the researcher, we apply censored regression models to evaluate the role of biases emerging from sample selectivity. Unlike much of the literature, we find that urban form variables are a significant determinant of both automobile ownership and use, a finding that holds even after using instrumental variables to control for endogeneity.urban form, non-work automobile travel, sample selectivity, instrumental variables

Cities and Satellites: Spatial Effects and Unobserved Heterogeneity in the Modeling of Urban Growth

The confluence of factors driving urban growth is highly complex, resulting from a combination of ecological and social determinants that co-evolve over time and space. Identifying these factors and quantifying their impact necessitates models that capture both why urbanization happens as well as where and when it happens. Using a database that links five satellite images spanning 1976–2001 to a suite of socioeconomic, ecological and GIS created explanatory variables, this study develops a spatial-temporal model of the determinants of built-up area across a 25,900 square kilometer swath across central North Carolina. Extensive conversion of forest and agricultural land over the last decades is modeled using the complementary log-log derivation of the proportional hazards model, thereby affording a means for modeling continuous- time landscape change using discrete-time satellite data. To control for unobserved heterogeneity, the model specification includes an error component that is Gamma distributed. Results confirm the hypothesis that the landscape pattern surrounding a pixel has a major influence on the likelihood of its conversion and, moreover, that the omission of external spatial effects can lead to biased inferences regarding the influence of other covariates, such as proximity to road. Cartographic and nonparametric validation exercises illustrate the utility of the model for policy simulation.Urban growth, landscape pattern, satellite imagery, hazard model,North Carolina

Do High Oil Prices Matter? – Evidence on the Mobility Behavior of German Households

Focusing on travel survey data from Germany, this paper investigates the determinants of automobile travel, with the specific aim of quantifying the effects of fuel prices and fuel economy. The analysis is predicated on the notion that car mileage is a two-stage decision process, comprising the discrete choice of whether to own a car and the continuous choice of distance traveled. To capture this process, we employ censored regression models consisting of Probit and OLS estimators, which allows us to gauge the extent to which sample selectivity may bias the results. Our elasticity estimates indicate a significant positive association between increased fuel economy and increased driving, and a significantly negative fuel-price elasticity, which ranges between –35% and –41%.Taken together, these results suggest that fuel taxes are likely to be a more effective policy measure in reducing emissions than fuelefficiency standards.Automobile travel, rebound effect, two-part model

Rural Electrification and Fertility – Evidence from Côte d’Ivoire

Using household-level survey data from Côte d’Ivoire, this paper investigates the determinants of fertility with a particular focus on the effect of electrification. Based on count data regression models, our analysis suggests a highly significant relationship between fertility and electricity, but one that is only revealed when the model distinguishes between rural and urban areas. Specifically, we find a positive association between electricity and fertility for urban households, contrasted by a negative relationship for rural households. This dichotomy is suggested to reflect the influences of electricity in facilitating child care, off set by its modernizing impacts through the provision of information.Rural development; energy access; demography; count data

Driving for Fun? – A Comparison of Weekdays and Weekend Travel

Focusing on individual motorists in car-owning households in Germany, this paper econometrically investigates the determinants of automobile travel with the specific aim of quantifying the effects of fuel prices and person-level attributes on travel conducted over a five-day week and weekend. Our analysis is predicated on the notion that car use is an individual decision, albeit one that is dependent on intra-household allocation processes, thereby building on a growing body of literature that has identified the importance of socioeconomic factors such as employment status, gender, and the presence of children in determining both access to the car and distance driven. To capture this two-stage decision process, we employ the Two-Part Model, which consists of Probit and OLS estimators, and derive elasticity estimates that incorporate both the discrete and continuous choices pertaining to car use.With fuel price elasticity estimates ranging between –0.42 and –0.48, our results suggest raising prices via fuel taxes to be a promising energy conservation and climate protection measure.Automobile travel, Two-Part Model, interaction effects

On Marginal and Interaction Effects: The Case of Heckit and Two-Part Models

Interaction effects capture the impact of one explanatory variable x1 on the marginal effect of another explanatory variable x2. To explore interaction effects, so-called interaction terms x1x2 are typically included in estimation specifications. While in linear models the effect of a marginal change in the interaction term is equal to the interaction effect, this equality generally does not hold in non-linear specifications (AI, NORTON, 2003). This paper provides for a general derivation of marginal and interaction effects in both linear and non-linear models and calculates the formulae of the marginal and interaction effects resulting from HECKMAN's sample selection model as well as the Two-Part Model, two commonly employed censored regression models. Drawing on a survey of automobile use from Germany, we argue that while it is important to test for the significance of interaction effects, their size conveys limited substantive content. More meaningful, and also more easy to grasp, are the conditional marginal effects pertaining to two variables that are assumed to interact.Censored regression models, interaction terms

Future Pain at the Diesel Pump? Potential Eff ects of the European Commission’s Energy Taxation Proposal

The Energy Tax Directive recently proposed by the European Commission envisages to tax fuels based on their energy content. By raising prices for diesel to a level higher than that of petrol, this proposal would eliminate the price advantage currently enjoyed by diesel in most EU Member States. To explore the implications of such a tax regime for automobile travel, the present analysis undertakes a comparative analysis of price elasticities for both fuel types. Drawing on household panel data from Germany, we fail to reject the hypothesis that the fuel price elasticities for petrol and diesel are equal. With our uniform fuel price elasticity estimates being on the order of -0.5 to -0.42, the typical fi nding from the empirical literature that the elasticities gleaned from household-level data are generally larger than those from aggregate time-series data is reconfirmed.Fuel taxation; fuel price elasticities; household data; automobile travel; panel