Economic measurement and modelling with large datasets: theory, application and policy implications

Abstract

In this thesis I debate the merits of using large disaggregated datasets to drive economic theory, and its implications for economic policy making. In chapter 2 we use a previously unexplored dataset of 1/4 million photo-interpreted points to measure the supply of residential land across Europe. Using this dataset, we estimate the reduced-form parameters of a Pigovian externality model for land controls. We interpret the results of these estimates as evidence that across Europe the supply of residential land use is detrimentally restricted to below the social optimum. In chapter 3 the underlying dynamics of the UK consumer price in inflation are explored from 27:5 million underlying price quotes in the Consumer Price Index. We find evidence of secular trends in the pricing mechanism of firms in the UK, as well as support for the theory of state dependent pricing. Further, our results indicate that neither the Bank of England nor professional forecasters are taking into account the information embedded in a flexibility index which could improve their inflation forecasts. Lastly, in chapter 4 I explore a framework for decomposing the inflation rate into missing observations, product replacements and regular matched inflation rates. Using this framework I explore a potential source of bias in the inflation measurement of a particular narrow category of good, "Women's top, long sleeved, not blouse", due to uncaptured quality change. The results are preliminary, and difficult to interpret as the bias found could be explained by fashion cycles rather than being a measurement error. Finally, in chapter 5 I provide my concluding remarks, finding that there is indeed a benefit to exploring large disaggregated datasets, as they can uncover features of economic fundamentals that are not readily observable in aggregated data