This thesis is concerned with the econometric modelling of gasoline prices in US. The intention is to characterize the market process in this crucial and significant industry. Overall we have been seeking to identify a mechanism to signal and measure market failure and consequently improve market performance. Firstly we examine the time series properties of gasoline prices using the criteria for perfect arbitrage to test market efficiency from the stationarity of price proportions. This is done by considering market efficiency across in different regions of the US, by applying a range of different stationary tests. In this analysis we collected a comprehensive data set of gasoline prices for all regions of the US mainland for the longest period available. Forni (2004), outlined reasons why the analysis of price proportions may be advantageous; especially when the sample is limited. Stationarity corresponds to a broad market, it is found here that the US gasoline market is on average broad. Except for the Gulf Coast and Lower Atlantic, which may be seen as economically and/or geographically separated, market structure in the rest of the US would not appear to be a problem Next we investigate possible long-run price leadership in the US gasoline market and the inter-relatedness of price behaviour relevant to a competitive market. Following Hunter & Burke (2007) and Kurita (2008) market definition is tested. This is done on an extended regional data set to Kurita and following the analysis in Hunter and Burke on a set of company data for the US.We analysed long-run price leadership through the cointegrated vector auto-regression (VAR) to identify key characteristics of long-run structure in the gasoline market. The analysis of the system of regional prices confirms problems with the Gulf Coast and Lower Atlantic, but also based on the finding that the cointegrating rank is less than N-1 using both types of data ( regional price data and company price data) and the findings on weak exogenity it is suggested that competition across the whole of the US is further limited. We applied further tests to company data on prices and quantity data to investigate further the need to regulate for potential anomalies and to capture more directly consumer harm. The variance screening method applied to recent weekly data indicates that there is too little variation in gasoline prices and this would seem to support the cointegration study. Furthermore we applied a dynamic disequilibrium analysis to attempt to identify long-run demand and supply in the gasoline market. Finding significant variables using the Phillips-Hansen fully modified estimation of the switching regression is necessary to distinguish two long-run equations (S&D). Moreover a comparison is made with a Markov Switching Model (MSM) of prices and this suggests a similar pattern of regime to the quantity information analysed in by our disequilibrium model.