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Estimating Income Elasticity of Household Energy Using the Quantile Regression Method

Tahavori, Mohammad Sajad | 2021

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  1. Type of Document: M.Sc. Thesis
  2. Language: Farsi
  3. Document No: 54800 (44)
  4. University: Sharif University of Technology
  5. Department: Management and Economics
  6. Advisor(s): Madanizadeh, Ali
  7. Abstract:
  8. Abstract In this study, by using panel instrumental variable quantile regression method (IVQP) and household budget data during the years 2011-2018, income elasticity of Housing energy has been estimated at different levels of energy expenditure. This method helps to study the whole energy expenditure distribution instead of focusing on the average effects. The study results show that income elasticity has a downward trend with increasing energy consumption quantiles. In other words, households with higher consumption have less income elasticity, so that the income elasticity is estimated for 10, 90 percentage, 0.47, and 0.32 quantiles, respectively. Also, in another part of the research, the average income elasticity for different income deciles is estimated, and the results show that the income elasticity for the first and tenth deciles are 0.57 and 0.32, respectively. Thus, the income elasticity of high-income deciles is higher than that of low-income groups.Research Aim: Income elasticity of Housing energy estimation Research method: Panel instrumental variable quantile regression method Findings: The study results show that income elasticity has a downward trend with increasing energy consumption quantiles. In other words, households with higher consumption have less income elasticity, so that the income elasticity is estimated for 10, 90 percentage, 0.47, and 0.32 quantiles, respectively. Also, in another part of the research, the average income elasticity for different income deciles is estimated, and the results show that the income elasticity for the first and tenth deciles are 0.57 and 0.32, respectively.Conclusion: The income elasticity of high-income deciles is higher than that of low-income groups
  9. Keywords:
  10. Income Elasticity ; Quantile Regression ; Energy Consumption ; Housing Energy Estimation ; Energy Consumption Optimization ; Energy Demand

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