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The Long Run Demand for Lighting: Elasticities and Rebound Effects in Different Phases of Economic Development

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In this paper, the authors provide a case study of the long run effects of socio-economic change and technological innovation on the consumption of energy services in the UK and suggest that understanding the evolution of demand for energy services and the factors that influence it contributes to a better understanding of future energy uses and associated greenhouse gas emissions.
Abstract
The provision of artificial light was revolutionised by a series of discontinuous innovations in lighting appliances, fuels, infrastructures and institutions during the nineteenth and twentieth centuries. In Britain, the real price of lighting fell dramatically (3,000-fold between 1800 and 2000) and quality rose. Along with rises in real income and population, these developments meant that total consumption of lighting was 40,000 times greater by 2000 than in 1800. The paper presents estimates of the income and price elasticities of demand for lighting services over the past three hundred years, and explores how they evolved. Income and price elasticities increased dramatically (to 3.5 and -1.7, respectively) between the 1840s and the 1890s and fell rapidly in the twentieth century. Even in the twentieth century and at the beginning of the twenty-first century, rebound effects in the lighting market still appear to be potentially important. This paper provides a first case study of the long run effects of socio-economic change and technological innovation on the consumption of energy services in the UK. We suggest that understanding the evolution of the demand for energy services and the factors that influence it contributes to a better understanding of future energy uses and associated greenhouse gas emissions.

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Statistical analysis of cointegration vectors

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Book

Likelihood-Based Inference in Cointegrated Vector Autoregressive Models

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Efficient Tests for an Autoregressive Unit Root

TL;DR: In this paper, a modified version of the Dickey-Fuller t test is proposed to improve the power when an unknown mean or trend is present, and a Monte Carlo experiment indicates that the modified test works well in small samples.
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Co-integration, Error Correction, and the Econometric Analysis of Non-Stationary Data

TL;DR: This book focuses on the exploration of relationships among integrated data series and the exploitation of these relationships in dynamic econometric modelling, and the asymptotic theory of integrated processes is described.
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Trending Questions (1)
How did the use of lighting evolve over time?

The use of lighting increased dramatically over time, with total consumption of lighting in Britain being 40,000 times greater in 2000 compared to 1800.