Conference Agenda

Many policies and programs, especially complex ones and those administered to vulnerable groups, rely for their implementation on frontline staff. We contribute to an emerging literature in economics that opens the ‘black box’ of how the characteristics and attitudes of frontline staff impact on public program performance. Matching survey data collected from over one hundred energy advisors that staff a nation-wide energy efficiency assistance program in Germany with data from around 16,300 energy efficiency consultations in the homes of low-income households, we find significant heterogeneity in performance between staff. Advisors' economic preferences and their own energy efficiency investment choices contribute to our understanding of the impact of frontline staff on adviser-determined audit outcomes as well as households' investment decisions. While advisors' socio-demographic characteristics do not predict audit outcomes, socio-demographics matter in combination with household demographics via peer effects.

In recent years, there has been a noticeable uptick in prices across various energy sources, stemming from either supply conditions or the imposition of higher CO$_2$ prices as part of efforts to drive decarbonization in economies. These developments, however, have sparked concerns about how the resulting expenditures are distributed across income levels. This paper addresses this concern by delving into the degree of regressivity of household energy expenditures.

Using data from the European Household Budget Survey, we examine the distribution of household energy expenditures in 19 European countries during the years 2010, 2015, and 2020. We gauge the level of inequality through concentration indices of energy expenditures and Kakwani indices and decompose the concentration indices in various components to screen out the determinants of this inequality. In 2020, the proportion of equivalent disposable income allocated to energy expenses for the lowest income quintile ranges from 7.5\% in Luxembourg to a staggering 30.1\% in Croatia. Notably, all countries exhibit regressive energy expenditures, as the cumulative share of energy expenditure surpasses the cumulative share of household income.

Nevertheless, significant variations exist in the degree of regressivity among countries. Estonia stands out with the highest regressivity at -0.24, while Bulgaria experiences the least regressivity in total household energy expenditures, registering a value of -0.13. This underscores the importance of not solely focusing on the fraction of income spent on energy, as the countries with the highest or lowest shares may differ from those with the highest or lowest degrees of regressivity. In examining energy expenditure inequality, we analyze the distinct impact of various socio-demographic factors. Taking Germany as a case study, our findings reveal that the predominant factor contributing to energy expenditure inequality is income, accounting for nearly 60\% of the concentration index. The remaining socio-demographic variables, including socio-economic status, household size, age of the household head, and household type collectively explain the remaining 40\% of the concentration index.

In India, dependence on highly polluting traditional cooking technologies that run on biomass fuels imposes a great risk to health, as they emit high levels of health-damaging air pollutants. In particular, women are the most vulnerable risk group exposed to high concentrations of these pollutants, as they spend more time in the cooking area. This study quantifies the impacts of different types of cooking technologies on individual health levels and assesses future health outcomes of scenarios that aim to provide universal access to modern cooking energy services by 2030.

Carbon pricing is of central importance for an efficient climate policy, but also entails the risk of impairing the affordability of basic goods such as residential heating for private households. This study analyses the impact of carbon pricing on residential heating affordability in a microeconomic model which endogenizes the choice of a renewable heating technology. We compare the effectiveness of a renewable heating subsidy and a lump-sum transfer, both of equal amount, as potential compensation policies. Our findings indicate that carbon pricing can increase the household’s heating cost burden due to the higher up-front fixed costs associated with a renewable heating technology. Subsidizing the renewable heating technology emerges as the most effective policy to reduce the household’s burden in this case. If the renewable technology is not the household’s optimal choice, the relative effectiveness of the two compensation policies in particular depends on whether their introduction changes the household’s optimal technology choice. Overall, our results highlight the importance of considering the technological adjustment when evaluating the impacts of carbon pricing on the affordability of residential heating.