Carbon pricing is considered the most efficient policy to reduce greenhouse gas emissions but it has also been conjectured that other policies need to be implemented first to remove certain economic and political barriers to stringent climate policy. Here, we examine empirical evidence on the the sequence of policy adoption and climate policy portfolios of G20 economies and other major emitters that eventually implemented a national carbon price. We find that all countries adopted carbon pricing late in their instrument sequence after the adoption of (almost) all other instrument types. Furthermore, we find that countries that adopted carbon pricing in a given year had significantly larger climate policy portfolios than those that did not. In the last part of the paper, we examine heterogeneity among countries that eventually adopted a carbon price. We find large variation in the size of policy portfolios of adopters of carbon pricing, with more recent adopters appearing to have introduced carbon pricing with smaller portfolios. Furthermore, countries that adopted carbon pricing with larger policy portfolios tended to implement a higher carbon price. Overall, our results thus suggest that policy sequencing played an important role in climate policy, specifically the adoption of carbon pricing over the last two decades.
Seasonal temperature variability and economic cycles [under review]
Published working paper: GRI Working Paper No. 374
Most recent version: here
In this paper, I examine to what extent temperature variability can explain seasonal economic cycles. To this aim, I first construct a novel dataset of seasonal temperature and seasonal economic production for a sample of 98 countries. This dataset reveals a much larger diversity of seasonal economic cycles around the world than previously reported. Furthermore, the data suggests that previously identified stylised facts, including a peak of production around Christmas and a trough around mid-year, can only be found in about half of all countries. I then attribute these economic cycles to variation in temperature. For identification, I propose and apply a novel econometric approach based on seasonal differences that accounts for expectations. The results suggest that seasonal temperature has a statistically significantly positive effect on seasonal production. Using data on GVA for different industry groups I can attribute this effect to industries that are relatively more exposed to ambient temperature. Furthermore, the results suggest that economic development makes countries more resilient to temperature fluctuations. Overall, the effect of temperature on seasonal economic cycles appears large, as in many countries the effect of temperature is strong enough to explain almost all of the observed seasonal economic cycle. Regarding future anthropogenic climate change, the results suggest that changes to seasonal temperatures will lead to a reallocation of economic activity from one season to another of up to several percentage points of annual GDP, pointing to yet another channel through which climate change will affect economic production that has so far been overlooked.
Weather, mobility, and COVID-19 infections: results from panel data analysis and an epidemiological model [under review]
with Ana De Menezes-Silva and James Rising
Most recent version: available upon request
The debate over the influence of weather on COVID-19 epidemiological dynamics remains unsettled as multiple factors are conflated, including vi- ral biology, transmission through social interaction, and the probability of disease detection. Here we disentangle these dynamics with a multi-method approach combining econometric techniques with epidemiological models to analyze data for over 4000 geographic units. We show distinct and signifi- cant effects of temperature, thermal comfort, solar radiation, and precipitation on the growth of infections. We find that weather affects the rates of both disease transmission and detection, and we isolate transmission effects to understand the potential for seasonal shifts. The instantaneous effects of weather are small, with R0 about 0.007 higher in winter than summer. However, these effects compound over time, so that a region with a 5 C drop over three months in winter is expected to have 190% more confirmed cases at the end of that 90 days period, relative to constant temperature. We also find that the contribution of weather produces the largest effects in 1high-latitude countries. As the COVID-19 pandemic continues to evolve and risks becoming endemic, these seasonal dynamics may play a crucial role for health policy.
Temperature variability and long-run economic development [under review]
Published working paper: LSE Geography and Environment Discussion Paper Series 26
Most recent version: here
This study estimates causal effects of temperature variability on long-run economic development, which are not accounted for in most estimates of the costs of future climate change. For identification I use a novel research design based on spatial first-differences. Economic activity is proxied by nightlights. Informed by the underlying physical mechanisms, I distinguish between day-to-day, seasonal, and interannual variability. The results suggest an economically large and statistically significant negative effect of day-to-day variability on economic activity. Regarding seasonal variability, I find a smaller but also negative effect. The estimated effect of interannual variability is positive at low and negative at high temperatures. These effects are robust, they can be identified in urban and rural areas, and they cannot be explained with the spatial distribution of agriculture. The results suggest that temperature variability will add to the costs of anthropogenic climate change, especially in relatively warm and currently relatively poor regions.
Some Like It Cold: The Persistent Cost of Higher Temperatures in European Economic Sectors [under review]
with Ben Groom and Sefi Roth
Most recent version: available upon request
The international diffusion of policies for climate change mitigation [under review]
with Adil Mohommad and Gregor Schwerhoff
Published working paper: IMF Working Paper No. 2022/115
In this paper, we study the international diffusion of carbon pricing policies. In the first part, we empirically examine to what extent the adoption of carbon pricing in a given country can explain the subsequent adoption of the same policy in other countries. In the second part, we quantify the global benefits of policy diffusion in terms of greenhouse gas emission reductions elsewhere. To do so, we combine a large international dataset on carbon pricing with several other datasets. For causal identification, we estimate semi-parametric Cox proportional hazard models. We find robust and statistically significant evidence for policy diffusion. The magnitude of the estimated effects is substantial. For two neighbouring countries, policy adoption in one country increases the probability of subsequent adoption in the other country on average by several percentage points. Motivated by this result, we use Monte Carlo simulations based on our empirical estimates to quantify both direct domestic and indirect foreign emission reductions of policy adoption and subsequent diffusion. The results based on our central empirical estimates suggest that for most countries indirect emission reductions of carbon pricing can exceed direct emission reductions. Overall, our results provide additional support for the adoption of stringent climate policies, especially in countries where climate change mitigation policies might so far have been considered as being of relatively little importance because of a relatively small domestic economy.
Trade liberalisation and adaptation to sea-level rise
Political preferences and the consumer incidence of carbon pricing
The economic benefits of accurate weather forecasts