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The Horizontal Distribution of Carbon Emissions in Türkiye

This paper extends the literature on the distributional impacts of carbon pricing in Türkiye by examining both vertical (income-based) and horizontal (non-income-based) inequalities in household carbon emissions. Using the ARIA (Analytical Routine for Inequality Assessment) microsimulation framework with data from the 2019 Turkish Household Budget Survey, we simulate direct and indirect carbon emissions linked to household expenditures. Consistent with prior findings, emissions rise with income but decline as a share of income, indicating regressivity. However, horizontal inequality in emissions exceeds vertical inequality. By analyzing emissions relative to personal characteristics, we find that older individuals and car owners exhibit higher carbon intensity, while larger households and those with children show lower intensity. These insights underscore the importance of incorporating diverse personal traits into climate policy design.

Behavioural, Nutritional, and Health Effects of Food Carbon Taxes: Evidence from a QUAIDS Demand System for Pakistan

Food pricing policies are increasingly discussed as instruments to internalise environmental externalities and improve diets. The motivation is clear: animal-based foods account for a disproportionate share of food-system greenhouse gas (GHG) emissions (Clark et al., 2019; Poore & Nemecek, 2018), while dietary patterns high in red and processed meat are strongly associated with cardiovascular disease (CVD) risks (Afshin et al., 2019; Willett et al., 2019). Yet the case for food carbon taxes cannot be made on emissions alone. In low- and middle-income countries, food expenditure shares are high and nutritional adequacy is often fragile, so price shocks can have first-order welfare and nutrition consequences (FAO, 2022). Whether carbon pricing in food delivers health co-benefits, or instead worsens diet quality for vulnerable households, is fundamentally an empirical question about substitution behaviour. This paper develops a behavioural microsimulation framework that links food carbon taxation → prices → consumption substitution → protein intake → predicted CVD risk. The core behavioural engine is a Quadratic Almost Ideal Demand System (QUAIDS), estimated on household microdata from Pakistan. QUAIDS is well-suited here because it accommodates flexible Engel-curve shapes and non-linear expenditure effects (Banks et al., 1997), which matter in settings with substantial heterogeneity in food budgets and diet composition. The demand system follows the standard AIDS/QUAIDS tradition (Deaton & Muellbauer, 1980) and is estimated with demographic controls and survey weights. Food is grouped into nine aggregates that reflect both emissions and nutrition channels: cereals; red meat; poultry; fish; dairy; fruit and vegetables; beverages; processed foods; and plant-based protein (legumes/peas/beans). Prices are constructed from unit values and total expenditure is equivalised using a square-root scale. From the estimated parameters, we recover own- and cross-price elasticities and propagate policy-induced price changes through predicted budget shares and implied quantities. Nutritional outcomes focus on protein (given its policy relevance for affordability and adequacy), derived from group-specific nutrient coefficients. Health outcomes are evaluated using comparative risk assessment logic by mapping dietary changes into shifts in cardiovascular disease (CVD) risk factors, drawing on established evidence on diet–disease relationships from large-scale comparative risk assessments (Lim et al., 2012; Micha et al., 2017) and widely used dietary benchmarks for healthy and sustainable diets (Springmann et al., 2016; Tilman & Clark, 2014). We simulate three carbon-tax scenarios applied to all food: no revenue recycling, full revenue recycling via an equal per-capita lump-sum transfer, and targeted partial recycling, where 20% of revenues subsidise plant-based protein (legumes/peas/beans). The tax is calibrated at €5 per tCO₂e, consistent with low-end carbon prices observed across many existing instruments, particularly in low- and middle-income settings (World Bank, 2023). This design captures a key tension: while carbon pricing can reduce diet-related emissions, substitution toward cheaper calories or processed foods may dilute nutritional and health co-benefits (Smed et al., 2016). The partial-recycling scenario tests whether modest earmarking can redirect substitution toward lower-emission, nutritionally favourable foods relative to the pure-tax and lump-sum benchmarks. Methodologically, the paper embeds a demand system within a fiscal microsimulation framework to jointly evaluate climate, nutrition, and health outcomes, and shows how recycling design governs whether behavioural responses translate into co-benefits.

Incorporating the Prebound Effect in Retrofit Policy Analysis: Distributional Results for Belgium

This paper compares the distributional incidence of three decarbonization instruments in the Belgian residential sector: EPC‑based minimum standards, carbon pricing with an equal per‑household dividend, and renovation subsidies financed by a uniform lump‑sum tax. Using Woonsurvey 2018 and a dwelling‑level microsimulation model that evaluates renovation profitability on observed energy use, we quantify household monetary impacts, renovation take‑up, and equity (across and within income groups) for budget neutral policies calibrated to common C02 targets. Three results stand out. First, EPC standards concentrate burdens on low‑income and low‑use households and generate high dispersion because they compel renovations where realized savings are small. Second, universal subsidies are costly on average and distribute benefits unevenly, with sizable transfers to infra‑marginal projects. Third, carbon pricing with revenue recycling yields the lowest and most evenly distributed household burdens, largely because it triggers heat‑pump adoption in dwellings with the highest energy consumption. We further show that combining a modest carbon price with targeted heat‑pump support can meet the same emissions target at lower cost and with a smaller variance of household impacts than under the carbon dividend. Results are robust to rebound, landlord–tenant limits, and reasonable variations in discounting, horizons, and costs.

Environmental Engel Curves over four decades – The case of the Republic of Ireland

The relationship between income and carbon dioxide (CO₂) emissions has been debated in the environmental economics literature, primarily through two complementary but conceptually distinct frameworks. At the macro level, the Environmental Kuznets Curve (EKC) hypothesis posits a non-linear relationship between economic development and emissions, whereby emissions initially increase with income growth before stabilising or declining at higher income levels. At the micro level, Environmental Engel Curves (EECs) describe how household-level emissions vary with income within a given country, reflecting differences in consumption patterns, energy use, and access to carbon-intensive goods and services. These two literatures typically developed separately, leaving a gap: we have limited evidence on how the within-country income-emissions relationship evolves as an economy moves along its development path. To our knowledge, only one study examine temporal changes in the distribution of household CO₂ emissions within a single country, notably Sager (2019) for the United States. This paper studies the evolution of Environmental Engel Curves over time using six waves of the Irish Household Budget Survey (HBS) from the early 1980s to 2015, a period during which Ireland experienced exceptionally rapid income growth and major changes in consumption opportunities and energy use. We estimate income-emissions relationship for multiple points along Ireland’s development trajectory and ask: How does the shape of the EEC change as a country transitions from lower- to higher-income status? In doing so, we explicitly separate two mechanisms that are easily confounded in cross-sectional work: (i) changes in the carbon content of given consumption categories (i.e. carbon intensity of heating) and (ii) changes in the prevalence of carbon-intensive durables (i.e. personal vehicles) across the income distribution (extensive margin). We focus, in particular, on direct household energy use, focusing on residential heating fuels and private transport (vehicle ownership), which are plausible channels through which development alters EEC shape. These categories are where diffusion, infrastructure constraints, and policy-induced technology change are most likely to generate non-linearities. By documenting how EECs shift and re-shape across three decades of development within a single country, the paper complements cross-country evidence on heterogeneous distributional incidence (Dorband et al., 2019) and time-series evidence for the United States (Sager, 2019). We show that the EKC can be understood as the outcome of changing Environmental Engel Curves over the development process, driven by the diffusion and saturation of carbon-intensive household technologies. References Dorband, I. I., Jakob, M., Kalkuhl, M., & Steckel, J. C. (2019). Poverty and distributional effects of carbon pricing in low- and middle-income countries – A global comparative analysis. World Development, 115, 246–257. https://doi.org/10.1016/j.worlddev.2018.11.015 Sager, L. (2019). Income inequality and carbon consumption: Evidence from Environmental Engel curves. Energy Economics, 84, 104507. https://doi.org/10.1016/j.eneco.2019.104507

Distributional Effects of Distance-Based Road Pricing: A Behavioral Microsimulation Study for the Brussels-Capital Region

At the intersection of transport economics and public finance, this research contributes to the empirical literature on transport pricing as a policy tool for addressing the externalities of vehicle use. In line with recent technological developments and ongoing policy debates, it provides an ex-ante evaluation of a distance-based road pricing scheme that varies by time (peak and off-peak), location (congested and non-congested zones), and vehicle characteristics. While such systems are widely recognized as efficient, as they better align driving costs with externalities, their implementation in passenger transport remains limited. This absence is largely driven by concerns about distributional effects, highlighting the need for robust empirical evidence on equity implications as a key input for policy feasibility.

Household Demand Responses to Carbon Pricing by Energy Poverty Status: Evidence from Belgium

This paper develops a behavioral microsimulation framework to analyse how carbon pricing affects energy vulnerable households in Belgium. We focus on two groups: energy poor (EP) households, who devote a large share of their income to energy, and hidden energy poor (hEP) households, who spend little on energy as they severely restrict their consumption. Using eleven cross-sections of the Belgian Household Budget Survey (2003–2016), we first document structural differences between EP and hEP households with logistic regressions. We then estimate a demographically specified Quadratic Almost Ideal Demand System (Banks et al., 1997) and develop a two-stage residual inclusion procedure to address the endogeneity of energy poverty statuses. The resulting price and income elasticities by vulnerability profiles are used to simulate responses and welfare impacts of a carbon price on heating and transport fuels, consistent with the forthcoming EU ETS 2. Behavioral adjustments are highly heterogeneous: lower-income and energy vulnerable households show higher fuel price elasticities than wealthier groups, with hEP households responding most strongly to price increases. Consequently, EP households face substantial carbon costs but comparatively smaller welfare losses, whereas hEP households suffer disproportionately large welfare losses despite their low expenditure exposure. These results reveal horizontal equity concerns that are invisible in income-based metrics alone and highlight the need to integrate detailed energy vulnerability profiles into carbon pricing design.