Energy Demand Elasticities Research Articles

A comprehensive study to estimate income and price elasticities of household electricity consumption using Auto-metrics

This study focuses on understanding family electricity consumption behaviors in response to income and price changes from 1994 to 2022 across 12 prominent European countries. We employ a unique econometric approach, Auto-selection Models, to analyze the nuances of energy demand elasticity. Our methodology includes the use of saturation techniques, which are highly effective in identifying anomalies and discontinuities in the data, ensuring the reliability of our results. The Auto-metrics method streamlines the model selection process and enhances the accuracy of elasticity predictions. We use Error Correction Models (ECMs) for each country to examine the long-term equilibrium relationships among key variables such as energy consumption, household income, electricity prices, and weather patterns, taking into account any observed anomalies and significant structural changes. The findings reveal varying levels of income and price elasticity across the countries, reflecting their unique economic and climatic conditions. The study's results hold significant implications for policymaking. By recognizing and adapting to the varied characteristics of electricity demand elasticity, energy policies can be more accurately tailored at both the national and European Union levels.

Inflation and distributional impacts: Have mitigation policies been successful for vulnerable and energy poor households?

The aim of this paper is to assess the distributional impact of the 2021–23 price increase on Italian household expenditure and energy poverty. Using the microsimulation model developed by the Italian Parliamentary Budget Office, the analysis provides a comprehensive assessment of the uneven impact of inflation across the population and measures how mitigation policies have compensated for this impact. In particular, we focus on vulnerable households to examine whether energy poverty has been affected by the rise in energy prices and to what extent policies have succeeded in protecting these families. Our main findings show that in 2022, mitigation policies have stabilised the impact of inflation by compensating households for almost half of the effect of the price shock on their expenditure. Although not particularly well targeted at energy-poor households, the mitigation policies have protected households from a worsening of their energy vulnerability. However, the reduction of support measures adopted in 2023 is expected to increase the area of vulnerability, including households that are particularly sensitive to high energy costs. Finally, the behavioural response of households was also considered by estimating price elasticities of energy demand and measuring their impact on the simulated scenarios using a sensitivity approach.

Multi-time scale dynamic operation optimization method for industrial park electricity-heat-gas integrated energy system considering demand elasticity

This study proposes a multi-time scale dynamic optimization (MSDO) method for ultra-short-term scheduling in industrial electricity-heat-gas integrated energy systems. The aim is to enhance the feasibility of scheduling schemes and to utilize flexibility potential. The MSDO method considers equipment response differences and demand fulfillment time disparities. The dynamic aspect is reflected in the supply-demand matching within the scheduling time window. A single-layer model with unified temporal granularity is constructed based on lag parameter identification. The study proposes various forms of energy demand elasticity, including steam networks and cumulative demand, and investigates the optimal minimum temporal granularity for scheduling. Case results demonstrate that the MSDO method effectively characterizes the multi-energy time lag of equipment. Compared with methods disregarding lag parameters, the MSDO method enhances total profit by ¥ 120711.42 and improves operation stability by 2.96%. The MSDO method outperforms baseline methods in cost and stability, accommodating a 160% increase in renewable energy growth. Under different elasticity spaces, the profit of the cumulative demand method exceeds that of the average method. The time lag of different equipment impacts scheduling profits. An optimal choice exists for the minimum temporal granularity to strike a balance between computational efficiency, economy, and feasibility.

Price and Income Elasticities of Hungarian Household Energy Demand: Implications for Energy Policy in the Context of the Energy Crisis

The energy crisis that began in the second half of 2021, exacerbated by the Russian-Ukrainian war, created unexpected difficulty for European Union Member States in terms of shaping their energy policies. Hungary was one of the most vulnerable countries, whose economic development was fraught with severe risk due to the strong dependence on Russian energy sources and regulated energy prices for households, significantly slowing down the transition to green energy. The sharp change in energy prices due to the introduction of a price cap in 2013-2014 and the partial adjustment in 2022 draws attention to the situation of Hungarian energy demand. This study describes the absolute short-term price elasticities of Hungarian household natural gas and electricity demand and gas and electricity cross-price and income elasticities of the former for income deciles between 2010 and 2021 using the midpoint percentage method. The results show that electricity demand is more elastic than gas demand, implying that Hungarian household consumers are more responsive to changes in electricity prices than those of gas. In addition, low-income Hungarian households are more sensitive to changes in both of the latter than high-income households, while no consistent pattern is identified in the relationship between income and energy demand. Accordingly, the study recommends the implementation of a multi-tariff pricing strategy based on the energy burden of the income deciles. This should particularly target the first two deciles, which are the most vulnerable and sensitive to energy price changes.

Estimating energy demand elasticities for gas exporting countries: a dynamic panel data approach

Estimating energy demand elasticities for gas exporting countries: a dynamic panel data approach

The CO2 cost pass-through in nonlinear emission trading schemes

In this paper, we theoretically study the issues that how nonlinear structures of energy market affect CO2 costs of energy firms being passed through to energy prices in emission trading schemes. We set up oligopoly models to investigate CO2 cost pass-through under different emission right allocations, characterize analytic derivations of CO2 cost pass-through rates and then explore the connections between CO2 pass-through rates and nonlinear market structures. Our findings suggest that the CO2 cost pass-though rates are not only dependent on the elasticities of energy demand and supply, but largely determined by the convexity of demand curve and the competition intensity of energy market. More importantly, an economic curiosity (CO2 cost pass-through overshifting) is also observed in the emission trading schemes under suitable market conditions. The existence of CO2 cost pass-through overshifting provides regulators and policy makers important information that the emission trading schemes are at the risk of imperfect competition and may require further policy adjustments.

The Energy Demand Elasticity in Relation to Gross Domestic Product in Indonesia: Sectoral Approach

This paper aims at estimating the energy demand elasticity in relation to gross domestic product in Indonesia based on data from 1995 to 2018. The sectors examined are industry, trading, transportation, and housing sectors. The method of analysis is the Autoregressive Distributed Lag (ARDL). An interesting estimation result here is that the elasticity of the industry sector is negative both short and long term. The other three sectors show positive elasticity. This paper contributes to the discussion of the energy demand ARDL model to be used as a reference in developing countries.

Residential energy demand elasticity in Ghana: an application of the quadratic almost ideal demand systems (QUAIDS) model

Residential energy demand elasticity in Ghana: an application of the quadratic almost ideal demand systems (QUAIDS) model

The impact of information communication technology on energy demand: Some international evidence

This research considers an extended energy demand model with a finite mixture model that is incorporated to account for the heterogeneous nexus between information communication technology (ICT) and energy demand. We estimate this model by employing panel data for 34 OECD and 39 non-OECD countries covering the period from 2007 to 2017. The estimated results denote that a heterogeneous nexus exists between ICT and energy demand. Specifically speaking, ICT can not only exert a positive effect on energy demand, but also a negative impact on energy demand. Furthermore, financial development, government expenditure, and human capital can help ICT reduce energy demand, while foreign direct investment has the opposite effect. Nearly 14% of our sample countries experience switching between groups, whereas the large majority preserve the same group. Finally, compared to the extended energy demand model, the traditional energy demand model that ignores group heterogeneity cannot accurately estimate the price and income elasticities of energy demand.

A climate stress test on the financial vulnerability of Italian households and firms

This study presents a novel methodological framework for assessing the exposure of the Italian financial system to climate policy risks, using a micro-founded approach. By combining survey and administrative data with energy accounts and energy prices, we estimate the energy demand elasticity of Italian households and firms at the micro-level and we use this information to simulate the effects of four one-off carbon taxes (corresponding to €50, €100, €200 and €800 per ton of CO2) on their income and profits. To compute if (and how) carbon taxes might affect the share of financially vulnerable agents and the debt at risk, these estimates are employed as an input for the microsimulation models used to monitor financial stability at the Bank of Italy. According to our results, a level of carbon taxation within the range of €50−200 per ton does not have a sizeable effect on the share of financially vulnerable agents. The micro approach allows us to take into account the heterogeneous transmission channels of climate risks and indicates that the financial risks stemming from climate shocks are limited overall and specific to individual households and industries.

Green urbanization.

Large cities are more productive and generate more output per person. Using data from the UK on energy demand and waste generation, we show that they are also more energy-efficient. Large cities are therefore greener than small towns. The amount of energy demanded and waste generated per person is decreasing in total output produced, that is, energy demand and waste generation scale sublinearly with output. Our research provides the first direct evidence of green urbanization by calculating the rate at which per capita electricity use and waste decrease with city population. The energy demand elasticity with respect to city output is 83%: as the total output of a city increases by one percent, energy demand increases less than one percent, and the Urban Energy Premium is therefore 17%. The energy premium by source of energy demand is from households (13%), transport (20%), and industry (16%). Similarly, we find that the elasticity of waste generation with respect to city output is 90%. For one percent increase in total city output, there is a less than one percent increase in waste, with an Urban Waste Premium of 10%. Because large cities are energy-efficient ways of generating output, energy efficiency can be improved by encouraging urbanization and thus green living. We perform a counterfactual analysis in a spatial equilibrium model that makes income taxes contingent on city population, which attracts more people to big cities. We find that this pro-urbanization counterfactual not only increases economic output but also lowers energy consumption and waste production in the aggregate.

The sectorally heterogeneous and time-varying price elasticities of energy demand in China

The price elasticities of energy demand are intrinsically sectorally heterogeneous and time-varying, which is crucial for policy assessment, yet little studied. Therefore, in this study, we apply a semiparametric model that allows the coefficients to vary with continuous and categorical attributes to explore the sector-specific and year-specific price elasticities. We take China as an example, covering 32 industrial sectors from 1999 to 2015. Two main results have been found: (a) yearly average elasticities increased during the sample period and experienced faster growth since the 11th Five-Year-Plan period; and (b) the price elasticities showed significant sectoral heterogeneity in their magnitude, range, and trend. Nonmetal products (e.g., cement), metals, and chemicals have the largest elasticities. The mining and equipment manufacturing sectors are close to the sample average value. The light industry sector has the largest heterogeneity. The weighted mean of our results is consistent with those in the existing literature but provides more sector-specific information.

Energy efficiency and rebound effects in German industry – evidence from macroeconometric modeling

Increases in energy efficiency are reduced by the rebound effect. Efficiency gains on the micro level do not lead to proportionate reductions of energy consumption on the macro level. The German energy-economy model PANTA RHEI is applied to better understand the rebound effect. To get more robust estimates micro data from a cost structure survey of the German manufacturing sector was used to derive price elasticities of energy demand. The mesoeconomic rebound effect of an autonomous increase in energy efficiency at the industry level in manufacturing is between 7% in 2021 and 12% in 2030. The macroeconomic rebound effect lies between 12% in 2021 and 18% in 2030. Inclusion of necessary investment and assumptions of higher elasticities of substitution increase the effects. Rebound effects limit the scope of technology-driven efficiency improvements and must be considered in the design of ambitious energy efficiency programs and climate policies.

Modeling primary energy and electricity demands in Bangladesh: An Autoregressive distributed lag approach

Bangladesh has been acknowledged as one of the fast-emerging global economies and its economy is expected to significantly grow in the years to come. As a result, the demand for energy in Bangladesh is likely to surge whereby meeting the rising energy demand would be a major policy concern for the government. Besides, the low per capita energy consumption levels have kept the nation's growth performances below par. Thus, identifying the macroeconomic factors that can elevate the energy consumption levels is pertinent for sustaining the economic growth rate of Bangladesh. Against this backdrop, this paper aims to model the macroeconomic determinants of both primary energy and electricity demands in Bangladesh between 1980 and 2018. The autoregressive distributed lag model, controlling for multiple structural breaks in the data, is used to ascertain the short- and long-run elasticities of energy demand while the Hacker and Hatemi-J causality analysis is applied to predict the causal relationships. The results from the econometric analysis, in a nutshell, reveal that the primary energy and electricity demands in Bangladesh are positively influenced by the higher levels of economic growth, household consumption expenditure, industrialization, energy imports, urbanization, and institutional quality. In contrast, higher prices of crude oil and greater incidences of income inequality are identified as the key factors that inhibit the overall energy demand in Bangladesh. Besides, energy demand is estimated to have bidirectional causal associations with economic growth, industrialization, and income inequality. Furthermore, unidirectional causations stemming from household consumption expenditure, energy imports, oil prices, and institutional quality are also witnessed. Hence, these findings impose several policy implications concerning sustainable management of energy demand in Bangladesh. It is recommended that the economic growth strategies should complement the energy sustainability objectives of the nation. Besides, it is also ideal for Bangladesh to reduce its imported energy-dependency to make use of the local energy resources. Furthermore, reducing income inequality and improving institutional quality is also recommended for enhancing the overall energy demand in Bangladesh.

Energy Demand Elasticity in Pakistan: An Inter-temporal Analysis from Household Survey Data of PIHS 2001-02 and PSLM 2010-11

This study analyses household consumption patterns of different forms of energy in Pakistan over two survey rounds (2001-02 and 2010-11), while comparison with an earlier study based on 1984-85 data extends the analysis over a 25 years horizon. Income elasticities of different types of fuels have been computed using the Extended Linear Expenditure System. The analysis shows a differential pattern of energy use across the urban and rural areas of the country as well as changes over time, with rural households spending proportionately more on fuels throughout this period.

A Micro-founded Climate Stress Test on the Financial Vulnerability of Italian Households and Firms

This study presents a novel methodological framework for assessing the exposure of the Italian financial system to climate policy risks, using a micro-founded approach. By combining survey and administrative data with energy accounts and energy prices, we estimate the energy demand elasticity of Italian households and firms at the micro-level and we use this information to simulate the effects of four one-off carbon taxes (corresponding to €50, €100, €200 and €800 per ton of CO2) on their income and profits. To compute if (and how) carbon taxes might affect the share of financially vulnerable agents and the debt at risk, these estimates are used as an input for the microsimulation models used to monitor financial stability at the Bank of Italy. According to our results, a level of carbon taxation within the range of €50-200 per ton does not have a sizeable effect on the share of financially vulnerable agents. The micro approach allows us to take into account the heterogeneous transmission channels of climate risks and indicates that the financial risks stemming from climate shocks are limited overall and specific to individual households and industries.

Price and Output Elasticities of Energy Demand for Industrial Sectors in OECD Countries

The price and output elasticities of energy demand continue to be of interest to academia and policy institutions, having been estimated in previous studies. However, the estimated results show some inconsistencies, especially at the sectoral level, across countries. Based on our conjecture that those inconsistencies are mainly due to the effect of contingent energy intensities and partially to different units of analysis, we narrowed the analysis to the industry level and classified 16 industries into energy-intensive and less energy-intensive groups. The effects of price and output on energy demand were then compared between these two groups using 274 industry panel data across 20 Organization for Economic Cooperation and Development (OECD) countries from 1978 to 2013. The results showed that the price elasticity of energy demand was consistently lower in the energy-intensive group than in the less energy-intensive group, whereas the output elasticity of energy demand was higher in the energy-intensive group than in the less energy-intensive group. Using panel differences and system generalized method of moments estimations, the dynamic elasticities of energy demand were also estimated. Energy demand in reaction to both price and output changes appeared to be more elastic in the long term than in the short term for both energy-intensive and less energy-intensive groups. These findings could be a useful reference for policy makers to deploy separate energy policies for different industries aiming for different temporal effects.

Dynamic multilevel modelling of industrial energy demand in Europe

Previous studies of industry level energy demand have not accounted for the hierarchical nesting of industries within a system that also adequately allows for country specific determinants of energy demand. The principal contribution of this paper is therefore to analyse energy demand for European industries over the period 1995–2009 using a dynamic multilevel model that accounts for this hierarchical data structure. Among other things, we find, firstly, that our dynamic multilevel model suggests that if industry income and the industry energy price increase by 10%, long run energy demand will increase by 8.1% and fall by 6.8%, respectively. Secondly, we find that the corresponding long run income and price elasticities are substantially larger in a standard dynamic model of industry level energy demand which does not account for the hierarchical data structure. Our results therefore suggest that not accounting for the hierarchical data structure results in unreliable estimates of energy demand elasticities. From a policy perspective we argue that it is imperative that future industry level energy demand studies account for the hierarchical structure of the data. This is to prevent energy policy making being based on industry level evidence that substantially inflates the responsiveness of long run energy demand to income and price changes.

Energy demand elasticities and weather worldwide

The purpose of this paper is to empirically estimate a model of aggregate residential and commercial energy demand elasticities, taking into account capital stock and climatic effects. We model a theoretically founded non-linear energy demand system, the generalized almost ideal, for the most important 117 countries in the world, which represent around 95% of the world population and 97% of the primary residential energy consumption, for the period 1978–2012. To this end, we assume a multi-stage utility maximization process, which models energy demand within a comprehensive theoretical framework. This paper offers three new contributions to research. First, we model energy aggregate demand response with a flexible and theoretically plausible simultaneous system. Second, we empirically measure the complete structure of price and expenditure elasticities of energy demand worldwide. Third, we explicitly estimate the impact of climate conditions on energy demand, with a newly constructed measure of weather impact based on geo-located heating and cooling degree-days. Econometric estimation reveals quantitative evidence of different income and price elasticities across countries and highlights the weather and capital stock impact on energy demand, inducing energy efficiency. Electricity tends to be a luxury good in advanced economies. Our results have welfare-improving policy implications, because appropriate policy strategies can help public decision-makers promote production efficiency and consumer welfare.

Modelling UK sub-sector industrial energy demand

The importance of considering homogenous economic agents when estimating energy demand functions is recognized in the literature, but so far data availability problems have explained the prevalence of empirical analyses only at an aggregate level. Motivated by the goal of developing the new industrial module to be adopted by the UK government Department of Business, Energy and Industrial Strategy (BEIS) for their econometric Energy Demand Model, we propose the first cointegration analysis that provides evidence on energy demand elasticities with respect to economic activity and energy price at a disaggregated industrial level. While the average of our estimates are comparable to those of the existing literature on the industrial sector as a whole, we find that there is considerable heterogeneity in relation to the long-run impact of economic activity and energy price on energy consumption, as well as to the speed with which firms re-adjust their equilibrium demand of energy in response to economic shocks. Finally, we learn that long-run disequilibria are tackled through altering the level of energy consumption rather than economic activity, a conclusion that has important implications for policy analysis.