Sachintha Fernando

About

Hi! I am Sachintha, a PhD candidate at the Martin Luther University Halle-Wittenberg (MLU), at the Chair of Econometrics and Empirical Economic Research. I am also an associated doctoral researcher at the Economics of Connected Natural Commons (ECO-N), University of Leipzig, and a Joachim Herz Stiftung Fellow since 2024.

I am an empirical economist specializing in the evaluation of environmental and climate policy. My research uses quasi-experimental methods to analyze large spatio-temporal datasets, such as gridded emissions inventories, traffic count data, and flood exposure, as well as survey data on well-being. I investigate whether climate policies deliver the environmental benefits they promise, and how environmental events and exposure affect the well-being of the people who live through them.

Before starting my PhD, I worked as an Economist at Verité Research, an independent think tank in Sri Lanka, where I led the Economics unit. My work there covered youth unemployment, female labor force participation, social welfare policy and agricultural policy. I collaborated with organisations including UNICEF, UNDP, the World Bank, the European Union, CIPE and the Sri Lankan Government. I remain affiliated with Verité Research.

I am always happy to collaborate or chat about research. Please feel free to get in touch!

Publications

Zero Fare, Cleaner Air? The Causal Effect of Luxembourg’s Free Public Transportation Policy on Transport Emissions

Environmental and Resource Economics, Vol. 89, Art. 45, 2026 · with Tobias Eibinger

Paper DOI

In March 2020, Luxembourg became the first country to make public transport free. We use this unique setting to evaluate the policy’s impact on transport emissions using a synthetic difference-in-differences framework. We use spatial emissions data to construct a panel of NUTS 2 regions in the EU from 2016 to 2022. We estimate an average reduction of 5.9% in road transport CO2 and overall road transport GHG emissions, with larger effects for NOx. These findings are robust against confounding shifts in working from home and commuting patterns, vehicle fleet electrification, and the localized effects of the COVID-19 pandemic. Complementary event-study evidence from automatic traffic counters and air quality stations through 2023 corroborates our findings and suggests larger effects on weekends.

Rising Waters, Falling Wellbeing: The Effects of the 2013 East German Flood on Subjective Well-Being

Accepted, Environmental and Resource Economics · with Katharina Kolb and Christoph Wunder

Paper

This paper employs a panel event study design to examine the causal effects of the 2013 flood disaster in East Germany on subjective well-being. We merge geo-spatial flood data with longitudinal data from the Socio-Economic Panel (SOEP) to identify individuals in affected municipalities. Our results show that those affected by the flood report a significant life satisfaction drop of 0.17 points on an 11-point scale, which is equivalent to a 2.5% fall from pre-flood levels, in the year after the flood. The effect is more severe in peripheral areas than in central areas, and for low-income individuals than for high-income individuals. However, the effect dissipates by 2015. Additionally, we observe a notable initial decrease in health satisfaction, followed by recovery, while financial satisfaction was largely unaffected.

Working Papers

Macro-level Worries in the Energy Transition: Insights from Germany's Coal Phase-out Regions

with Yasmine Bakr and Christoph Wunder · Draft available upon request

This paper studies how a major decarbonization policy affects macro-level worries about society. We examine Germany’s 2020 coal phase-out and its effects on worries about social cohesion, economic development, and climate change among residents of Eastern German lignite regions. Using longitudinal data from the German Socio-Economic Panel (2015-2023) and a panel eventstudy difference-in-differences design, we compare individuals in treated coal regions with residents of unaffected Eastern German districts before and after the legislation. We find substantial regional heterogeneity. In the Central German lignite region, the coal phase-out has little lasting effect on macro-level worries, with at most a temporary decline in economic worries. In Lusatia, by contrast, worries about social cohesion rise persistently after the policy, while economic worries show an immediate but unstable increase. Worries about climate change remain unchanged in both regions. The results show that decarbonization policies can reshape perceptions of society even when material compensation accompanies transition support.

Are the Effects of Finland's Carbon Tax on Transport Emissions Robust to Donor Pool Composition?

Solo-authored · Draft available upon request

This paper replicates Mideksa (2024), which applies the synthetic control method to estimate the effect of Finland's 1990 carbon tax introduction on per capita transport sector carbon emissions. I successfully replicate the main findings: the synthetic counterfactual closely tracks Finnish emissions in the pre-treatment period, with a substantial post-1990 divergence consistent with the original study. However, I show that this result is entirely driven by the inclusion of a single donor unit, Luxembourg, which is a structural outlier yet receives a positive weight in the optimization. Including Luxembourg is unusual in the literature: Luxembourg is a well-documented structural outlier, as its comparatively low fuel prices attract fuel tourism from neighboring countries, inflating its recorded transport emissions relative to actual domestic transport activity. Excluding Luxembourg deteriorates the pre-treatment fit and attenuates the estimated treatment effect, which falls to roughly a third of the original estimate and becomes indistinguishable from the placebo distribution. A donor pool resampling exercise confirms that the large treatment effect reported in the original study is systematically concentrated in subsamples containing Luxembourg. These findings highlight the sensitivity of synthetic control estimates to donor pool composition and provide an empirical illustration of interpolation bias in action.