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This thesis examines the drivers of demand and pricing of automobiles in the UK car market through three distinct chapters. Chapter 1 investigates the most likely characteristics of potential electric vehicle (EV) buyers, their preferred vehicle attributes, and the key barriers preventing a widespread EV adoption. Applying the adaptive Lasso, binomial and ordered logit regressions, I find that the likelihood of considering an EV purchase increases primarily with youth, education, being a student, and living in the south of UK. Additionally, purchase cost, performance and range represent the most important vehicle attributes, with high purchase cost and low maximum range being the key adoption barriers. Chapter 2 studies how vehicle characteristics, safety, and equipment influence conventional and alternative fuel vehicle prices. Furthermore, quality constant price indices are estimated, disentangling the growth of car prices into quality change and other factors. By manually constructing a brand-new dataset for the entire UK market 2008-2019, and applying the adaptive Lasso, weighted least squares, and quantile regressions to a hedonic model, I discover that the main drivers of price include vehicle performance and size/massiveness. The prices of alternative fuel vehicles are also more sensitive to any changes in vehicle characteristics. In addition, quality change is estimated to cause around 65% of the total increase in car prices. Chapter 3 examines the drivers of automobile demand, while taking into account price endogeneity, consumer heterogeneity, unobserved vehicle characteristics, and realistic substitution patterns. Combining the dataset of Chapter 2 with consumer demographics and applying the discrete-choice random-coefficient model of Berry, Levinsohn, and Pakes (BLP, 1995), we find that the key drivers of demand include fuel consumption, vehicle size, and price. Additionally, a ₤1000 increase in prices is estimated to cause a fall in demand by about 3%-5%, with 0.15% of consumers leaving the market.

This thesis investigates factors affecting demand for heat pumps in the residential sector in England and Wales. There are three objectives: to identify the macroeconomic and sociodemographic factors, environmental aspects, climatic conditions and policies that led to the mass deployment of heat pumps in other European countries; to assess the optimal level of heat pump adoption from a societal perspective taking account of environmental externalities; and to identify policies that could result in the mass-market deployment of heat pumps in the UK. Following reviews of studies on consumer preferences for heating systems, and markets and policies to promote heat pumps in eight European countries, two quantitative approaches are followed. The first is an econometric model based on panel data which estimates the impact of macroeconomic, sociodemographic and environmental factors on the demand for heat pumps in Austria, Finland, France, Germany, Sweden, Switzerland and the UK. The role played by three types of policies, financial/fiscal, informative and legislative, is investigated. These are found to have been significant factors in promoting heat pump take-up. A bottom-up techno-economic model simulating the choice of heating systems in the existing housing stock in England and Wales is then developed and is used to assess optimal heat pump take-up and policies that might promote their adoption. Capital cost subsidies, used in most European countries, are considered alongside the Renewable Heat Incentive approach adopted in the UK. The implications of adding the policy costs of support for renewable energy and energy efficiency to electricity prices, tilting the market against electric technologies, are also considered. The thesis concludes that financial incentives are needed to build heat pump markets, but they are not enough in themselves. Building supply chains, driving down costs and improving the performance of heat pumps are also essential.

The growing concern for security of energy supply and climate change has prompted this study. The thesis attempts to study the predictive power of global crude oil price on the natural gas price in the UK. Using quarterly price series of both energy commodities, the sample utilises data from 1988Q1-2015Q2 to accurately predict wholesale NBP gas price up to 7 - steps ahead. Using the most recent tools of comparing predictive ability of competing forecasting models, findings suggest that the benchmark price of Brent oil is able to predict natural gas price with minimum forecast error. Furthermore, the 4-model exogenous variable model is not encompassed by the bivariate 3-model forecast combination and offers gains in forecasting accuracy. The thesis also considers the residential demand for gas. Utilising microdata from the UK Living Costs and Food Survey 2013-2016, an attempt is made to estimate the household demand for gas and to determine the significance of government energy and climate change policies. Fitting the data to the model, a tobit censored regression model is employed to estimate residential gas demand. In addition to policy effects, seasonal, socioeconomic, dwelling type, tenure and heating equipment type effects are considered in the model. It is discovered that price elasticity ranges from -0.246 to -0.327 for the restricted model and -0.422 to -0.491 for the unrestricted model. The increase in consumer response to price changes can be attributed to government policy. Finally, it can be concluded that over the short to medium term gas prices are set to remain oil indexed and driven by shocks in the global oil market. Domestically, it is important to identify the different variations in seasonality, housing characteristics, family and income demographics that determine consumer behaviour to better understand the impact of government energy & climate change policies.