Essays in Environmental and Energy Economics

This dissertation contributes developments in modeling and policy analysis in environmental and energy economics. All three chapters are useful to ongoing debates in climate change policy and the regulation of greenhouse gas emissions. My first chapter develops a model of consumer decision-making in an analysis of the electricity retail choice market in Texas. This project explores (1) the limitations of consumer decision-making in a setting with large choice sets and (2) the relationship between competition and product variety after deregulation. I find strong evidence of inattention and search costs as explanations for consumers\u27 widespread failure to choose cost-minimizing contracts. These findings suggest that policymakers could improve welfare with interventions that reduce search costs and inattention, such as removing the legal obstacles to concierge services or introducing a web-based tool to find consumers\u27 cost-minimizing contract based on their consumption history. My findings also suggest that these interventions could lead to higher adoption of time-varying rates, which could lead to more efficient allocation of grid resources and lower emissions levels. My other main finding is that consumers are constrained in the monopoly setting from expressing their heterogeneous preferences for contract variety. This insight may guide regulators in monopoly settings to consider increasing variety. Of course, the possible benefits of increased variety face a trade-off with the costs of search and inattention. My second chapter is co-authored with Robert Mendelsohn and Paula Pereda. We propose a model to estimate the economic damages from weather shocks and climate change. We contrast our model with the models used in previous literature, and we show that our model estimates substantially different effects than this earlier work, a finding the emphasizes the importance of model selection and careful consideration of the implicit assumptions. We demonstrate our method in the contexts of both agricultural profits and GDP, but this model could be easily transported to a variety of other settings and sectors in the climate change damages literature. My final chapter is co-authored with Kenneth Gillingham and James Stock. We compare several time series models to estimate the price elasticity of new vehicle sales, addressing the classic challenges of price and sales endogeneity and simultaneity in time series analysis with aggregate data. Correctly identifying the price elasticity of new vehicle sales is especially important for estimating the impacts of fuel economy standards because changing fuel economy stringency is assumed to cause a shock to new vehicle prices. The resulting effect on new vehicle sales has broad implications beyond the immediate impact on the vehicle industry. In particular, new vehicles generally have the best safety features and pollution controls, so reducing replacement of used vehicles has consequences for public safety and pollution levels. This project is also a novel application of a structural vector autoregression with instrumental variables (SVAR-IV), a relatively new methodology borrowed from the monetary policy literature. We compare the SVAR-IV with other time series approaches, some of which have been considered in policymaking for fuel economy standards

Fuel prices and road deaths in Australia

After years of general progress in reducing Australia’s road death toll, road deaths increased in 2015 and 2016, reaching 1293 per annum. These were also years of relatively cheap fuel following the dramatic decline in the world oil price in late 2014. This study uses monthly data to model the number of road deaths in Australia. Our estimates suggest that low fuel prices have contributed to knocking Australia off track for meeting its 2020 road safety target. The paper also provides a discussion of other factors that may have contributed to the rise in Australia’s road death toll.Australian Research Council (DE160100750

Modelling renewal price elasticity : an application to the motor portfolio of Ocidental

Mestrado em Ciências ActuariaisO aumento da competitividade no mercado segurador automóvel em Portugal tem levado as seguradoras a considerar uma abordagem de tarifação mais assente na procura, como um complemento à tradicional abordagem baseada no risco. As companhias de seguros querem actualmente saber mais sobre como evitar a saída dos seus clientes, durante o período de renovação de apólice, sem prejudicar a rentabilidade. Este relatório é o resultado de um estágio curricular que teve lugar junto da Ocidental Seguros, tendo como principais objectivos modelar a taxa de anulação na renovação do seguro automóvel da companhia e analisar como diversas variáveis influenciam as renovações. Considerámos a regressão logística, um caso particular dos Modelos Lineares Generalizados, para modelar a variável de resposta binária renovação/anulação. Modelando a variável de resposta como uma função da variação do prémio e de outras variáveis explicativas, é possível estimar a probabilidade de anulação por valor da alteração do prémio para cada cliente. Como a variação do prémio é a única variável que a companhia pode controlar directamente, obter tal informação sobre a elasticidade preço de cada cliente permitirá à seguradora tomar melhores decisões, com o objectivo de aperfeiçoar o equilíbrio entre o grau de satisfação dos clientes e a rentabilidade. A capacidade do modelo em prever que clientes irão anular as suas apólices foi também examinada. Para converter as probabilidades obtidas pelo modelo em classificações binárias, foram comparados vários critérios de optimização de ponto de corte, de modo a encontrar o valor que resulta na melhor capacidade discriminatória global.The increase in competition in the Portuguese Motor insurance market has lead insurers to consider a more demand-based approach to ratemaking, as a complement to the usual risk-based approach. Insurance companies now want to have a better understanding of how to prevent their clients from leaving the company, during the policy renewal period, while maintaining profitability. This report is the result of a curricular internship that took place at Ocidental Seguros, with the main goals of modelling the company's Motor insurance lapse rate during the renewal period and studying how different covariates influence renewals. We considered logistic regression, a special case of Generalized Linear Models, to model the binary response variable renewal/lapse. By modelling the response as a function of premium change and other covariates, the lapse probability for each client per amount of premium variation can then be estimated. As premium change is the only covariate the company has direct control over, obtaining such knowledge on each client's price elasticity will allow the insurer to make better decisions, so that a finer balance between customer satisfaction and profitability can be achieved. The model's capacity to predict which clients will cancel their policy was also analysed. In order to transform the output probabilities into binary classifications, several threshold optimisation criteria were compared, to find the threshold generating the best overall discriminatory performance.N/