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.