Measuring the contribution of unpaid overtime in the gross value added of UK industries:an assessment using data envelopment analysis and statistical methods

Abstract

This dissertation attempts to measure the contribution of unpaid overtime in relation to UK industries (SIC codes)’ economic output (Gross Value Added) for the period 2002-2012, based on data from the Labour Force Survey (LFS) and the Office for National Statistics (ONS). The study provides the different theoretical approaches of unpaid labour’s definition, and more specifically those of mainstream economic approaches (eg. neoclassical) in comparison to the Marxist categories. Acknowledging that it is not always possible to construct Marxist variables with orthodox datasets, the dissertation uses the Marxist theory to attempt to explain the movement in the orthodox statistics. Unpaid overtime’s effect on the UK industries’ product (GVA) is not examined by wage-based approaches as the mainstream scholars and practitioners tend to do, but by an output-based one, using working-time as the measure of industries’ contribution. In this attempt, both parametric (Statistical regression methods) and non-parametric approaches (Data Envelopment Analysis) are used in order to account for unpaid overtime’s contribution to the UK industries product (GVA) as it is estimated by the orthodox statistics of Britain