Large but temporary price increases are sometimes deployed on days when the demand for electricity is extremely high due to exceptionally warm or cold weather. But what happens when the extreme price changes are permanent? Between January 2013 and April 2016, natural gas and electricity prices in Ukraine increased dramatically (up to 300% of the initial rates). We exploit variation in tariffs over time and across customers to estimate the price elasticity of electricity demand using a panel dataset with monthly meter readings from households in the city of Uzhhorod in Ukraine. We ask three research questions. First, what is the price elasticity of consumption implicit in the response (if any) to these large electricity price changes? Second, is there evidence of heterogeneity in the price elasticity of electricity demand driven by dwelling or household characteristics, or by consumer understanding of block pricing and/or own consumption levels? Third, how quickly do household adjust their consumption after a price change?
Despite its importance for policy purposes (including climate policy and the energy transition), evidence about the price elasticity of natural gas demand in the residential sector is very limited and based on inference from situations with modest variation in prices. We focus on a locale and time when price changes were extreme and presumably salient to consumers, namely Ukraine between 2013 and 2017. We exploit the tariff reforms and detailed micro-level household consumption records to estimate the price elasticity of the demand for natural gas. To isolate behavior, attention is restricted to those households that made no structural energy-efficiency upgrades to their homes, and thus kept the stock of gas-using capital fixed. We further examine the short-run elasticity by restricting the sample to a few months before and after the tariff changes. Our results suggest that under extreme price changes, households are capable of reducing consumption, even without installing insulation or making any other structural modifications to their homes. The price elasticity is about -0.16. Wealthier households, people living in multifamily buildings, and heavy users have more inelastic demands. Households reduced consumption even when they received “subsidies,†namely lump-sum government assistance, suggesting that when the price signal is sufficiently strong, lump-sum transfers have only a minimal effect on consumption. We also find some evidence that the stronger the salience, the stronger the responsiveness to price, although this effect is modest and may partly overlap with that of income or baseline consumption. Our data also suggest that the consumers with the lowest uptake of energy efficiency improvements might be those who—by necessity or through skills—are the most productive at reducing energy use through behaviors.
Despite its importance for policy purposes (including climate policy and the energy transition), the literature on the price elasticity of natural gas demand in the residential sector is very limited and based on inference from situations with modest variation in prices. We focus on a locale and time when price changes were extreme and presumably salient to consumers, namely Ukraine between 2013 and 2017. We exploit the tariff reforms and detailed micro-level household consumption records to estimate the price elasticity of the demand for natural gas. To isolate behavior, attention is restricted to those households that made no structural energy-efficiency upgrades to their homes, and thus kept the stock of gas-using capital fixed. We further examine the short-run elasticity by restricting the sample to a few months before and after the tariff changes. Our results suggest that in the face of extreme tariff changes, households were able to reduce their natural gas consumption, even without installing insulation or making any other energy efficiency investments. We find that the elasticity is about -0.16. Wealthier households, people living in multifamily buildings, and heavy users have more inelastic demands. Households reduced consumption even when they received “subsidies,” namely lump-sum government assistance, suggesting that when the price signal is sufficiently strong, lump-sum transfers have only a minimal effect on consumption. We also find some evidence that the stronger the salience, the stronger the responsiveness to price, although this effect is modest and may partly overlap with that of income or baseline consumption. Our data also suggest that the consumers with the lowest uptake of energy efficiency improvements might be those who — by necessity or through skills — are the most productive at reducing energy use through behaviors.
Large but temporary price increases are sometimes deployed on days when the demand for electricity is extremely high due to exceptionally warm or cold weather. But what happens when the extreme price changes are permanent? Between January 2013 and April 2016, natural gas and electricity prices in Ukraine increased dramatically (up to 300% of the initial rates). We exploit variation in tariffs over time and across customers to estimate the price elasticity of electricity demand using a panel dataset with monthly meter readings from households in Uzhhorod in Ukraine. The price elasticity of electricity demand is -0.2 to -0.5, with the bulk of our estimates around -0.3. The elasticity becomes up to 50% more pronounced over the first three months since prices change. We find only limited evidence that persons who are attentive about their consumption levels, their bills, or the tariffs are more responsive to the price changes.
Large but temporary price increases are sometimes deployed on days when the demand for electricity is extremely high due to exceptionally warm or cold weather. But what happens when the extreme price changes are permanent? Between January 2013 and April 2016, natural gas and electricity prices in Ukraine increased dramatically (up to 300% of the initial rates). We exploit variation in tariffs over time and across customers to estimate the price elasticity of electricity demand using a panel dataset with monthly meter readings from households in the city of Uzhhorod in Ukraine. We ask three research questions. First, what is the price elasticity of consumption implicit in the response (if any) to these large electricity price changes? Second, is there evidence of heterogeneity in the price elasticity of electricity demand driven by dwelling or household characteristics, or by consumer understanding of block pricing and/or own consumption levels? Third, how quickly do household adjust their consumption after a price change?
Untapped improvements in energy efficiency in the residential sector may deliver large savings in energy use and the CO2 associated emissions. Yet empirical assessments have been difficult and controversial. We collect monthly natural gas meter readings from a sample of homes in Transcarpathia, in Western Ukraine, an early adopter of the country's trend away from district heating, from January 2013 to April 2017, a period over which the residential natural gas tariffs rose by over 700%. We combine the monthly meter readings with documentation about each household's heating-related energy efficiency upgrades to the home (wall, attic or basement insulation; new windows; boiler replacement, and insulation around pipes) to form a panel dataset. We estimate the effect of the energy efficiency renovations on natural gas consumption, controlling for weather, income and government energy assistance. The decision to do the renovations and natural gas consumption are likely endogenous (people do the renovations because they hope to consume less), so we instrument for the renovations by creating a cross-validation instrument based on a supply-side argument. Even for a given type of energy efficiency upgrades, the estimated effect of the renovations varies dramatically in magnitude, depending on whether the renovations are instrumented for and on how detailed the fixed effects are. The coefficients on the renovations are almost always negative in our regressions, but practically and statistically significant only when we instrument for the renovations. This is in agreement with our respondents' difficulty assessing whether the renovations had saved them gas or money. The IV estimates indicate that insulation delivers 13-24% reductions in natural gas usage, and up to a 5% internal rate of return (IRR) to the investment over 20 years. Judicious use of an existing government program can yield positive IRRs and make energy efficiency upgrades a good investment in a generally poor-performing housing market.
Untapped improvements in energy efficiency in the residential sector may deliver large savings in energy use and the CO2 associated emissions. Yet empirical assessments have been difficult and controversial. We collect monthly natural gas meter readings from a sample of homes in Transcarpathia, in Western Ukraine, an early adopter of the country’s trend away from district heating, from January 2013 to April 2017, a period over which the residential natural gas tariffs rose by over 700%. We combine the monthly meter readings with documentation about each household’s heating-related energy efficiency upgrades to the home (wall, attic or basement insulation; new windows; boiler replacement, and insulation around pipes) to form a panel dataset. We estimate the effect of the energy efficiency renovations on natural gas consumption, controlling for weather, income and government energy assistance. The decision to do the renovations and natural gas consumption are likely endogenous (people do the renovations because they hope to consume less), so we instrument for the renovations by creating a cross-validation instrument based on a supply-side argument. Even for a given type of energy efficiency upgrades, the estimated effect of the renovations varies dramatically in magnitude, depending on whether the renovations are instrumented for and on how detailed the fixed effects are. The coefficients on the renovations are almost always negative in our regressions, but practically and statistically significant only when we instrument for the renovations. This is in agreement with our respondents’ difficulty assessing whether the renovations had saved them gas or money. The IV estimates indicate that insulation delivers 13-24% reductions in natural gas usage, and up to a 5% internal rate of return (IRR) to the investment over 20 years. Judicious use of an existing government program can yield positive IRRs and make energy efficiency upgrades a good investment in a generally poor-performing housing market.
Large but temporary price increases are sometimes deployed on days when the demand for electricity is extremely high due to exceptionally warm or cold weather. But what happens when the extreme price changes are permanent? Between January 2013 and April 2016, natural gas and electricity prices in Ukraine increased dramatically (up to 300% of the initial rates). We exploit variation in tariffs over time and across customers to estimate the price elasticity of electricity demand using a panel dataset with monthly meter readings from households in the city of Uzhhorod in Ukraine. We ask three research questions. First, what is the price elasticity of consumption implicit in the response (if any) to these large electricity price changes? Second, is there evidence of heterogeneity in the price elasticity of electricity demand driven by dwelling or household characteristics, or by consumer understanding of block pricing and/or own consumption levels? Third, how quickly do household adjust their consumption after a price change? Histograms of the monthly usage records suggest that our Ukrainian consumers were aware of the increasing block pricing system and responded to marginal prices, with bunching observed at the then-current as well as future block cutoffs. The price elasticity of electricity demand is approximately -0.2 to -0.5, with the bulk of our estimates around -0.3. The elasticity becomes up to 50% more pronounced over the first three months since prices change. We find only limited evidence that persons who are attentive about their consumption levels, their bills, or the tariffs are more responsive to the price changes. The tariff increases do help reduce CO2 emissions, but at a high cost per ton.
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