The webinar takes place on Tuesday at 16:00 CET on Zoom and has a duration of 60 minutes, with questions at the end. In order to attend the webinar, registration is mandatory. Please use the following link to access the registration form.

  • October 13th

Nicolas Treich (Toulouse School of Economics, INRAE, Université Toulouse Capitole)

An economic model of the meat paradox

with Nina Hestermann and Yves Le Yaouanq.

Abstract :

How can individuals care about animals and, at the same time, eat meat? We design a survey study to explore this "meat paradox". Survey participants (N = 3054) underestimate farm animal suffering, and underestimate it more (i.e., are less realistic) when they eat more meat. Building on the literature on cognitive dissonance, we develop a model in which individuals form self-serving beliefs in order to reduce the moral guilt associated with meat consumption. The model characterizes how individuals' beliefs about animal welfare and their attitude towards information are affected by the economic environment (e.g., price of meat, salience of animal welfare), and by individuals' preferences (e.g., taste for meat, moral cost of guilt). Several empirical observations are consistent with our model.

  • Read the paper (PDF)

  • Slides of the presentation (PDF)

  • October 27th

Sébastien Houde (Grenoble Ecole de Management)

"Consumer Myopia in Vehicle Purchases: Evidence from a Natural Experiment"

with Kenneth Gillingham and Arthur A. van Benthem


A central question in the analysis of fuel-economy policy is whether consumers are myopic with regards to future fuel costs. We provide the first evidence on consumer valuation of fuel economy from a natural experiment that provides exogenous variation in fuel-economy ratings. We examine the short-run equilibrium effects of a restatement of fuel-economy ratings that affected 1.6 million vehicles. Using the implied changes in willingness-to-pay, we find that consumers act myopically: consumers are indifferent between $1 in discounted fuel costs and 16-39 cents in the purchase price when discounting at 4%. This undervaluation persists under a wide range of assumptions.

  • Read the paper (PDF)

  • November 24th

Rainald Borck (University of Postdam)

"Urban pollution: A global perspective"

with Philipp Schrauth.


We analyze urban air pollution worldwide using satellite data for over fifteen years. We document basic facts about the distribution of pollution in space and the evolution over time. We find that 70 percent of the population worldwide and 80 percent of city dwellers are exposed to PM2.5-levels exceeding WHO thresholds. We also study how urban pollution is affected by urban population density in contrast to the size of urban agglomerations. Using OLS, within country fixed effects and instrumental variables, we find that the absolute size of an agglomeration is more important than population density for air quality in cities. We study the heterogeneity of this relationship by continents and country-specific income levels, and find that agglomeration size has the strongest effect in Asia and in high income countries.

  • December 8th

Ben Groom (University of Exeter)

" REDD+ as an area based policy: Evidence from the 2011Indonesian Moratorium on Palm Oil, logging and Timber Concessions"

with Charles Palmer and Lorenzo Sileci.

  • January 5th

Marco Percoco (Università Bocconi)

"New Car Taxation and its Unintended Environmental Consequences"

with Angela Bergantino and Mario Intini.


In Italy, in 2011 the Superbollo tax was introduced for newly registered cars exceeding 185 kW. Although the aim of the tax was not to reduce CO2 emission as it was actually aimed at increasing government revenues during the economic crisis, we show that it had significant and unexpected impacts on buyers’ behavior. Using data related to the universe of vehicles registered between 2008 and 2017 and by using a difference-in- difference framework, we find that the Superbollo had a significant role in reducing CO2 emissions and in increasing the car share with low CO2 emissions. In particular, we show that the introduction of the Superbollo shifted consumers towards greener cars, not necessarily ecological (e.g. electric), with a subsequent reduction in the emission of CO2 per kilometer traveled of an order of magnitude of 5 to 7%.

  • January 19th

Beat Hintermann (Universität Basel)

"Mobility Pricing in Switzerland"


We report the results from a large-scale randomized control trial in Switzerland that simulated the effect of mobility pricing that varies across time, space and mode of transport. Providing a monetary incentive reduced the overall external costs of transport generated by the study participants. This reduction is a consequence of mode substitution and a shift of departure times. Providing information about the external costs of transport in the absence of pricing also changes behaviour, but this effect is smaller and statistically significant only for subgroups. We do not detect a pronounced heterogeneity of the pricing effect. The average elasticity of external costs with respect to pricing is -0.33.

  • February 2nd

Romain Crastes (University of Leeds)

"Using shifted lognormal distributions in order to avoid “exploding” willingness-to-pay distributions in mixed logit models"


Discrete choice experiments (also known as stated preference surveys or conjoint analysis) are a popular method for analysing preferences and measuring Willingness-To-Pay for different attributes of a policy or an environmental good. The literature on model specification mainly proposes two approaches for accounting for unobserved taste heterogeneity: (1) the preference space approach, where the distribution of WTP is derived from the distribution of coefficients specified by the analyst in the utility function and (2) the WTP space approach, where the analyst directly specifies the distribution of WTP, from which the distributions of coefficients can be derived. It is generally found that models in preference space fit the data better but models in WTP space provide more reasonable WTP distributions. Train and Weeks (2005) in a seminal paper suggest that further work is needed to identify distributions that either yield better fit in WTP space or deliver more reasonable WTP distributions in preference space.

WTP distributions in preference space are derived by dividing the coefficient of a given non-monetary attribute by the price coefficient. Unreasonable WTP distributions are often found when the price attribute is assumed to be (negative) lognormal or loguniform. This is because the lognormal and loguniform distributions have a point-mass near zero, leading to the issue known as the “exploding implicit price” problem (Giergiczny et al., 2002). At the same time, specifying the price attribute as being lognormal or loguniform in preference space often leads to specifications which outperform their counterparts in WTP space in terms of goodness-of-fit. This is especially true when most of the non-monetary attributes are assumed to be normally distributed.

In this paper, we propose to use a new distribution for the cost attribute, which we call the mu-shifted lognormal distribution, in order to provide more reasonable WTP distributions in preference space. The mu-shifted distribution is inspired from the three-parameter lognormal distribution originally suggested by Cohen and Whitten (1980). The three-parameter distribution features an additional shift parameter which can contribute to move the point mass of the (negative) lognormal distribution away from zero. The mu-shifted distribution simply consists in replacing the shift parameter by the logarithm of the mean of the negative lognormal distribution, which provides two desirable features:

i. It prevents the shift parameter from being positive, which is both behaviourally implausible and leads to WTP distributions with no existing moments given that the distribution of the price spans on both sides of zero

ii. It leads to a model which is more parsimonious in parameters

We test the proposed distribution on 10 datasets and compare it to seven other specifications including WTP space, a lognormal cost, a loguniform cost and a multinomial logit model, leading to a total of 80 models and 414 WTP distributions. The mu-shifted lognormal distribution is found to yield similar results than the lognormal distribution for the cost in terms of goodness-of-fit but provides much more reasonable WTP distributions. More precisely, we find that the WTP estimates derived from lognormal models are between 4.6 and 23 times higher than the WTP estimates derived from WTP space models, while the mu-shifted lognormal models yield WTP estimates which are only between 0.08 and 1.32 times higher than those derived from WTP space models. At the same time, we find no significant differences in terms of goodness-of-fit between the mu-shifted lognormal models and the lognormal models. Both distributional assumptions lead to reductions of the Bayesian Information Criterion comprised between 12% and 0.5% compared to WTP space models.

  • Read the paper (PDF)

  • February 16th

Simone Borghesi (FSR Climate - European University Institute)

"Leave or remain? An evolutionary approach to carbon leakage in Emission Trading Systems"

with Angelo Antoci, Gianluca Iannucci and Mauro Sodini


Emissions trading is gaining increasing importance around the world as a suitable instrument to address climate change. In the absence of a global carbon market, however, unilateral carbon policies may end up causing carbon leakage effects, the more so if carbon prices are to increase in the future to achieve more ambitious emissions abatement targets. This paper intends to explore the possible delocalization effects of an Emissions Trading System (ETS) by proposing an evolutionary theoretical model in which regulated firms decide whether to stay (keep their production activities in the domestic country) or leave (move production abroad where no ETS is in place) imitating what other firms do. We investigate how this decision is affected by some key ETS design features, such as the emissions cap, the number of allowances granted for free to ETS firms, the level of a floor price for allowances. Numerical simulations show that the firms' decision on whether to stay or relocate abroad, and on how many allowances to purchase (and/or emissions to abate) for those that stay, are more sensitive to policies that reduce the cost of green technologies than to changes in specific features of the ETS design such as the emissions cap, the floor price and the number of permits granted for free.

  • March 2nd

Joseph Shapiro (UC Berkeley)

"Regulating Untaxable Externalities: Are Vehicle Air Pollution Standards Effective and Efficient?"


What is a feasible and efficient policy to regulate air pollution from vehicles? A Pigouvian tax is technologically infeasible. Most countries instead rely heavily on exhaust standards that limit air pollution emissions per mile for new vehicles. These standards differ substantially from fuel economy regulations. We assess the effectiveness and efficiency of these standards and counterfactual policies. We show that the emissions rate of new US vehicles has fallen by more than 99 percent since standards began in 1967. Several research designs applied to a half century of data suggest that exhaust standards have caused a majority of this decline. Yet exhaust standards are not cost-effective in part because they give no incentive to scrap old vehicles, which account for a large share of emissions. To study counterfactual policies, we develop analytical and quantitative models of the new and used vehicle fleets. We find that making ownership fees increase with the mean emissions of a vehicle type would decrease emissions and increase welfare. By contrast, current actual registration and vehicle property taxes (perversely) decrease with a vehicle's emissions.

  • March 16th

Erica Myers (University of Illinois at Urbana-Champaign)

"Decomposing the Wedge Between Projected and Realized Returns in Energy Efficiency Programs"


Evaluations of energy efficiency programs reveal that realized savings consistently fall short of projections. We decompose this `performance wedge' using data from the Illinois Home Weatherization Assistance Program (IHWAP) and a machine learning-based event study research design. We find that bias in engineering models can account for up to 41% of the wedge, primarily from overestimated savings in wall insulation. Heterogeneity in workmanship can also account for a large fraction (43%) of the wedge, while the rebound effect can explain only 6%. We find substantial heterogeneity in energy-related benefits from IHWAP projects, suggesting opportunities for better targeting of investments.

  • Read the paper (PDF)

  • March 30th

M. Tivadar et Y. Schaeffer (Univ. Grenoble Alpes)



The environmental inequalities rise from the fact that social groups are differently distributed in space relatively to an environmental variable (natural amenities or environmental hazards). Intuitively, when members of two groups have similar spatial distributions, the environmental inequality should be inexistent. Thus, spatial segregation and environmental inequalities are phenomena linked by a key variable: space. Despite this strong connection, the number of studies interested on the association between spatial segregation and environmental inequality is small and a formal demonstration of the links between these phenomena is missing.

In a previous contribution (Schaeffer and Tivadar, 2019), we adapted existing segregation indices to measure environmental inequalities. We developed two types of measures, based on spatial dissimilarity for the analysis of areal-level environmental data (such as vegetation cover or pollution loads in census blocks) and on relative centralization for the analysis of multiple points environmental data (such as geocoded hazardous sites or urban parks). We also proposed adjusted indices that take into account the impacts of local interactions across spatial units’ boundaries and of the distance to amenities/disamenities selected for analysis. For all these indices, we adapted resampling techniques to test their statistical significance (Monte Carlo permutations tests) and to identify the spatial units that play a significant impact on the index value (outliers’ identification with jackknife techniques). As a complement, we developed the SegEnvIneq R package (Tivadar and Schaeffer, 2020) that provides the functions necessary to compute the different versions of the indices and to make appropriate resampling tests.

In this further work, we demonstrate mathematically that environmental inequality level is bounded by the spatial segregation level. Put differently, spatial segregation is a necessary but insufficient condition for environmental inequality. Finally, we explore this result with an empirical analysis of the relationship between the two phenomena in French urban areas.

  • April 13th

Martino Pelli (Université de Sherbrooke)

"Childhood Exposure to Storms and Long-Term Educational Attainments in India"


This paper examines how exposure to storms over the course of compulsory schooling affects educational attainments and the type of activity performed by individuals in young adulthood. We construct a unique continuous measure of childhood exposure to storms that varies by birth-year cohort and district for young adults in rural and urban India. We find that storms have substantial disruptive impacts on education. In the districts exposed to the most powerful winds, the estimates imply that children are 9% more likely to accumulate an educational delay and 6.5% less likely to obtain higher levels of education (beyond secondary school). In the long run, these delays have an impact on the type of labor market activity that these individuals perform. Using childhood exposure to storms as an instrument, we find that a one-year educational delay leads to a 42.6% drop in the probability of accessing regular salaried jobs. We determine that the impact of storms on education works through a permanent negative income shock.

  • Read the paper (PDF)

  • April 27th

Helene Bouscasse (CR INRAE, CESAER) et Rim Rejeb (GAEL).

"What role does the health impact of transport modes play in our transport choices?"

Abstract :

The high modal share of the private car has important environmental and health consequences. With the deterioration of air quality, we see an increase of cardiovascular diseases, pulmonary diseases, cancers, etc. Thus, reducing the car's place in our mobility practices would contribute to reducing these health risks. However, this solution is not simple to implement since we are dealing with a complex behaviour that is a result of a combination of “objective” determinants (eg. Cost, infrastructure, etc.) and more “personal” determinants (eg. Perceptions, norms, habits, etc.). As part of the interdisciplinary project Mobil’Air, two studies try to contribute to a better understanding for these determinants. First, InterMob, a two-year long field controlled intervention aimed at changing durably transportation modes toward more active transport, by including both “hard” and “soft” levers. Second, an online Stated Preference survey focusing on health determinants, which are more difficult to access on the field. In this second study, we evaluate the extent to which information about the impacts of mode choice on public or individual health influences our mobility choices to more active and less polluting modes. Participants made choices in different hypothetical scenarios varying depending on the mode (car, public transport, walking and cycling), travel time, cost and associated individual and public cardiovascular risks.

  • May 11th

Alejandro Capparos (CSIC, Spain)

  • May 25th

Philippe Quirion (CIRED)

  • June 8th

Gino Baudry (Imperial College)

  • June 22nd