Apr 17, 2020
How beneficial is basic energy access — typically lighting and mobile charging — for rural households? Despite research on the economic impacts of basic energy access, few studies have investigated how it changes household behavior. Here we report results from a randomized controlled trial in rural Uttar Pradesh, India, which identifies the behavioral impacts of providing solar lanterns to households that normally rely on kerosene as their primary source of lighting. Eighty-nine of the 184 households participating in the study were given a free, high-quality solar lantern. Comparing changes in responses from the baseline questionnaire and an endline questionnaire administered six months later, we find that the lanterns reduced energy expenditures, improved lighting, improved satisfaction with lighting, more use of lighting for domestic activities (e.g., reading), and improved satisfaction with lighting for domestic activities. Overall, our results show that basic energy access can offer substantial benefits within the households, even if broader rural economic transformation is not plausible.
Apr 9, 2020
International carbon markets are an appealing and increasingly popular tool to regulate carbon emissions. By putting a price on carbon, carbon markets reshape incentives faced by firms and reduce the value of emissions. How effective are carbon markets? Observers have tended to infer their effectiveness from market prices. The general belief is that a carbon market needs a high price in order to reduce emissions. As a result, many observers remain skeptical of initiatives such as the European Union Emissions Trading System (EU ETS), whose price remained low (compared to the social cost of carbon). In this paper, we assess whether the EU ETS reduced CO2 emissions despite low prices. We motivate our study by documenting that a carbon market can be effective if it is a credible institution that can plausibly become more stringent in the future. In such a case, firms might cut emissions even though market prices are low. In fact, low prices can be a signal that the demand for carbon permits weakens. Thus, low prices are compatible with successful carbon markets. To assess whether the EU ETS reduced carbon emissions even as permits were cheap, we estimate counterfactual carbon emissions using an original sectoral emissions dataset. We find that the EU ETS saved about 1.2 billion tons of CO2 between 2008 and 2016 (3.8%) relative to a world without carbon markets, or almost half of what EU governments promised to reduce under their Kyoto Protocol commitments. Emission reductions in sectors covered under the EU ETS were higher.
Apr 4, 2020
To ensure climate stability, the decarbonization of the global economy is necessary. Coal-fired power generation is both the most carbon-intensive form of electricity supply and associated with adverse health effects. Thus, retiring coal-fired power plants is essential for achieving the goals of the Paris agreement on climate change. Here we introduce a retirement index that ranks coal-fired power plants based on their age, carbon emissions, and potential for air pollution. Based on the index, the top plants identified for retirement are located in China, India and South Korea. This contrasts with the general approach in the current policy discourse, where older plants in developed countries are prioritized rather than younger plants in developing countries. China and India remain consistently the top countries with most capacity in need of retirement across several sensitivity checks.
Feb 13, 2020
We examine unequal outcomes in the implementation of India’s national rural electrification program in Uttar Pradesh. We ask two questions: (1) to what extent did Dalits, the lowest group in India’s caste hierarchy, receive less attention when the state electrified rural communities? (2) Was BSP, the state’s Dalit party, able to reduce this inequality? Using data from a hundred thousand villages, we provide robust evidence for unequal outcomes. Villages inhabited solely by Dalits were 20 percentage points less likely to be covered by the program than villages without any Dalits. Moreover, a regression discontinuity analysis shows that the electoral success of BSP failed to reduce such differences. These results highlight the magnitude and persistence of caste inequality in the implementation of democratic public policy, despite political representation.
Feb 10, 2020
How can demand for electricity be estimated without fine-grained usage data? Employing an original and large dataset, we develop a novel method for determining drivers of demand without electricity meter data. We first segment Indian consumers by their willingness to pay for electricity service, their level of usage, and their satisfaction with lighting, and then use cluster membership as a dependent variable in order to determine which household-level factors predict electricity usage. Our approach employs machine-learning and more traditional regression techniques to determine the optimal number of segments, generate the segments, and determine the predictors of segment membership. The dataset consists of more than 10,000 households in more than 200 villages in the states of Bihar, Odisha, Rajasthan, and Uttar Pradesh. We find that the rural Indian electricity market can be segmented into three clusters based on households’ willingness to pay, satisfaction with lighting, and appliance wattage. The clusters consist of potential customers, low-demand customers, and high-use customers. We then determine the predictors of membership in these clusters. We show that different types of consumers can be identified along easily observable measures. Moreover, we show that there are clear groups of consumers that vary along their satisfaction, willingness to pay, and existing appliance usage.
