Energy intensity, growth and technical change

Shanker, Akshay; Stern, David I.

doi:10.2139/ssrn.3256574

Cited by 4 publications

(3 citation statements)

References 38 publications

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“…Second, GDP shocks tend to increase GDP by much more than they increase energy use, which is strongly supported by Figure 3. In a simple aggregate model of the economy, as in Shanker and Stern (2018) or Saunders (2008), if the price of energy is constant then labor-augmenting technical change cannot change energy intensity because the marginal product of energy is a function of energy intensity alone. However, we see that GDP shocks increase the price of energy as well and this is what allows energy intensity to decline.…”

Section: Conclusion and Discussionmentioning

confidence: 99%

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Estimating the economy-wide rebound effect using empirically identified structural vector autoregressions

2021

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The size of the economy-wide rebound effect is crucial for estimating the contribution that energy efficiency improvements can make to reducing greenhouse gas emissions and for understanding the drivers of energy use. Existing estimates, which vary widely, are based on computable general equilibrium models or partial equilibrium econometric estimates. The former depend on many a priori assumptions and the parameter values adopted, and the latter do not include all mechanisms that might increase or reduce the rebound and mostly do not credibly identify the rebound effect. Using a structural vector autoregressive (SVAR) model, we identify the dynamic causal impact of structural shocks, including an energy efficiency shock, applying identification methods developed in machine learning. In this manner, we are able to estimate the rebound effect with a minimum of a priori assumptions. We apply the SVAR to U.S. monthly and quarterly data, finding that after four years rebound is around 100%. This implies that policies to encourage cost-reducing energy efficiency innovation are not likely to significantly reduce energy use and greenhouse gas emissions in the long run.

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Section: Conclusion and Discussionmentioning

confidence: 99%

“…Rather the level of price affects the rate of innovation (Acemoglu, 2002). If the elasticity of substitution between energy and other inputs is less than unity, then an increase in the price of energy relative to other inputs will increase the rate of energy-augmenting technical change (Shanker and Stern, 2018).…”

Section: Theoretical Backgroundmentioning

confidence: 99%

Estimating the economy-wide rebound effect using empirically identified structural vector autoregressions

2021

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“…Energy helps to utilize capital more efficiently by using advanced technology. 19 Diaz and Puch 18 argue that capital investment return relies on energy prices and other exogenous factors such as technology and knowledge. Following this argument, we advocate that the incremental capital-output ratio (ICOR) can be considered an essential indicator for measuring EI or energy efficiency because it shows how efficiently capital has been used as firms gradually become technically efficient.…”

Section: Introductionmentioning

confidence: 99%

Nexus between energy intensity and capital-output ratio: A holistic approach

Amin

Taghizadeh–Hesary

Kabir

et al. 2022

Energy & Environment

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The incremental capital-output ratio indicates the extent of capital efficiency as firms gradually become technically efficient. Therefore, we aim to empirically assess the linkage between energy intensity and incremental capital-output ratio from a holistic point of view, the first of its kind, by analyzing data from select South Asian countries, lower- and middle-income, and high-income countries. We use standard and robust cross-sectional augmented econometric methodologies for the empirical analysis using data from 1990 to 2018. We reveal unidirectional causation from the incremental capital-output ratio to energy intensity in five South Asian countries and 52 high-income countries. However, bidirectional causality is found between the incremental capital-output ratio and energy intensity for the 34 lower- and middle-income countries. The elasticity of the incremental capital-output ratio to energy intensity for South Asian countries is 0.15 in the long-run. By contrast, the same elasticities for lower- and middle-income and high-income countries are 0.11 and 0.003, respectively. The effect of the incremental capital-output ratio on energy intensity is significantly lower in high-income countries than in the other two groups due to technical inefficiency. Our results are expected to guide the policymakers in developing and emerging economies in adopting optimal policies to achieve efficient and sustainable production and consumption.

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