Borella, Margherita; (2002) Time series analyses of consumption grouped data. Doctoral thesis (Ph.D), UCL (University College London).

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Abstract

The general framework for this thesis is the analysis of the time series properties of grouped data. The first chapter focuses on the dynamic properties of durable expenditure. Consumers make durable purchases infrequently and usually in large amounts. Aggregating among agents can lead to very complicated dynamics in aggregate demand, as fluctuations will be driven both by fluctuations in the number of consumers making the purchase and by fluctuations in the size of the purchase. A dynamic index model is estimated using a long time series of cross section data drawn from the UK Family Expenditure Survey. The methodology used is well suited to analyse the dynamic response of durable expenditure to economy-wide shocks at different aggregation levels. The second chapter aims at characterising the time series properties of individual consumption; data are drawn from the UK Family Expenditure Survey. The methodology consists in estimating multivariate moving average systems for grouped variables: this approach has the advantage of allowing to explicitly take into account the measurement error present in the individual measures of consumption and income. A panel data technique is used in the third chapter to evaluate different models of the individual earnings process. The analysis is based on the Bank of Italy Survey of Household Income and Saving; the analysis is carried out exploiting the panel component of the Survey. This analysis permits to undertake a study of pension earnings distribution in Italy: the final chapter analyses how effective is redistribution of pensioners' income under different Social Security systems.

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