The article presents technical efficiency of the use of production resources for the research sample of the Polish FADN, representing the general population of agricultural holdings, representing over 90% of domestic commercial production. The impact of the size of activity measured by the utilised agricultural area and standard output (economic size), and of the production type on the efficiency was examined. In all cases, non-linear relationships were found, and the technical efficiency curve for grouping characteristics based on the size of the activity took the U shape. Therefore, deviations from the shape of these relations observed in numerous studies may result not only from the selection of the measurement method, but also from the lack of representativeness for the entire agrarian structure of researched farms. Assessing the impact of production orientation on technical efficiency without taking into account the diversity of groups in terms of the size of activity, especially with different assignments to different classes of economic size, in many cases may lead to erroneous conclusions.
{"title":"Technical Efficiency of Farms in Poland According to Their Sizes and Types","authors":"A. Kagan","doi":"10.30858/zer/115188","DOIUrl":"https://doi.org/10.30858/zer/115188","url":null,"abstract":"The article presents technical efficiency of the use of production resources for the research sample of the Polish FADN, representing the general population of agricultural holdings, representing over 90% of domestic commercial production. The impact of the size of activity measured by the utilised agricultural area and standard output (economic size), and of the production type on the efficiency was examined. In all cases, non-linear relationships were found, and the technical efficiency curve for grouping characteristics based on the size of the activity took the U shape. Therefore, deviations from the shape of these relations observed in numerous studies may result not only from the selection of the measurement method, but also from the lack of representativeness for the entire agrarian structure of researched farms. Assessing the impact of production orientation on technical efficiency without taking into account the diversity of groups in terms of the size of activity, especially with different assignments to different classes of economic size, in many cases may lead to erroneous conclusions.","PeriodicalId":105811,"journal":{"name":"Econometric Modeling: Agriculture","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-12-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123998740","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This paper identifies a mechanism through which trade restrictions and counter-restrictions affect the climate. A series of tariffs and retaliatory export taxes increases the level of global emissions if a country using export taxes obtains considerable real income gains from local air pollution reduction. As a related result, it is shown that under certain conditions, Home tariffs alone reduce global pollution emissions, whereas a combination of Home tariffs and Foreign production taxes increases these emissions. The results here have alarming implications. Second-best policies can provoke trade disputes and are harmful to the climate.
{"title":"Tariffs and Retaliation: A Climate Point of View","authors":"Takumi Haibara","doi":"10.2139/ssrn.3502615","DOIUrl":"https://doi.org/10.2139/ssrn.3502615","url":null,"abstract":"This paper identifies a mechanism through which trade restrictions and counter-restrictions affect the climate. A series of tariffs and retaliatory export taxes increases the level of global emissions if a country using export taxes obtains considerable real income gains from local air pollution reduction. As a related result, it is shown that under certain conditions, Home tariffs alone reduce global pollution emissions, whereas a combination of Home tariffs and Foreign production taxes increases these emissions. The results here have alarming implications. Second-best policies can provoke trade disputes and are harmful to the climate.","PeriodicalId":105811,"journal":{"name":"Econometric Modeling: Agriculture","volume":"79 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-12-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121800339","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Leora F. Klapper, Dorothe Singer, Saniya Ansar, Jake Hess
The ability to manage financial risk is especially important for people earning their living through agriculture. Many farmers only get paid once or twice a year, and households need to stretch their earnings across the year by saving or borrowing money. Moreover, agricultural production faces a variety of risks related to both production and markets because of their exposure to weather and disease shocks. Households engaged in agriculture may thus especially benefit from financial inclusion—access to and use of formal financial services. This paper explores the topic of financial risk management in agriculture—how adults who rely on growing crops or raising livestock as their household's main source of income manage financial risk and use financial services. The paper summarizes new data based on a nationally representative survey of about 15,000 adults in 15 lower-middle- and low-income Sub-Saharan African economies collected as part of the World Bank's Global Findex database. The majority of these adults reported suffering a bad harvest or significant livestock loss in the past five years, and most bear the entire financial risk of such a loss. Most adults in agricultural households lack the financial tools -- such as insurance, accounts, savings, and credit -- that could help them manage financial risks.
{"title":"Financial Risk Management in Agriculture: Analyzing Data from a New Module of the Global Findex Database","authors":"Leora F. Klapper, Dorothe Singer, Saniya Ansar, Jake Hess","doi":"10.1596/1813-9450-9078","DOIUrl":"https://doi.org/10.1596/1813-9450-9078","url":null,"abstract":"The ability to manage financial risk is especially important for people earning their living through agriculture. Many farmers only get paid once or twice a year, and households need to stretch their earnings across the year by saving or borrowing money. Moreover, agricultural production faces a variety of risks related to both production and markets because of their exposure to weather and disease shocks. Households engaged in agriculture may thus especially benefit from financial inclusion—access to and use of formal financial services. This paper explores the topic of financial risk management in agriculture—how adults who rely on growing crops or raising livestock as their household's main source of income manage financial risk and use financial services. The paper summarizes new data based on a nationally representative survey of about 15,000 adults in 15 lower-middle- and low-income Sub-Saharan African economies collected as part of the World Bank's Global Findex database. The majority of these adults reported suffering a bad harvest or significant livestock loss in the past five years, and most bear the entire financial risk of such a loss. Most adults in agricultural households lack the financial tools -- such as insurance, accounts, savings, and credit -- that could help them manage financial risks.","PeriodicalId":105811,"journal":{"name":"Econometric Modeling: Agriculture","volume":"76 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-12-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132485270","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This paper outlines a method to forecast electricity generation (Gigawatt hours, GWh). The in-sample data set consists of yearly electricity generation (GWh) by OECD countries for the period 1999 to 2017. The out-sample period consists of electricity generation for the year 2018. Partial-Autocorrelation Function (PACF) tests reveal that the most appropriate Autoregressive model depends on the country concerned. For 72% of countries an AR(1) is applicable and is the focus of this research. A combination of AIC and Log-Likelihood criteria as well as a sigma squared measure are then applied to determine the countries that best fit the AR(1) model. The 31 countries selected using the PACF were sorted using the criteria. Applying the relevant AR(1) models to the out-sample data highlighted that there is some support for AIC, Log-Likelihood and sigma squared measures as accurate predictors of forecast accuracy for an AR(1) model when applied to electricity generation data for OECD countries. This result holds particularly for low model values (best fit) where forecast accuracy is greatest and after sorting the data into quartiles based on AIC measures for the forecast error measure as opposed to the mean percentage error measure.
{"title":"Forecasting Electricity Generation: An AR(1) Approach","authors":"D. Maroney","doi":"10.2139/ssrn.3495737","DOIUrl":"https://doi.org/10.2139/ssrn.3495737","url":null,"abstract":"This paper outlines a method to forecast electricity generation (Gigawatt hours, GWh). The in-sample data set consists of yearly electricity generation (GWh) by OECD countries for the period 1999 to 2017. The out-sample period consists of electricity generation for the year 2018. Partial-Autocorrelation Function (PACF) tests reveal that the most appropriate Autoregressive model depends on the country concerned. For 72% of countries an AR(1) is applicable and is the focus of this research. A combination of AIC and Log-Likelihood criteria as well as a sigma squared measure are then applied to determine the countries that best fit the AR(1) model. The 31 countries selected using the PACF were sorted using the criteria. Applying the relevant AR(1) models to the out-sample data highlighted that there is some support for AIC, Log-Likelihood and sigma squared measures as accurate predictors of forecast accuracy for an AR(1) model when applied to electricity generation data for OECD countries. This result holds particularly for low model values (best fit) where forecast accuracy is greatest and after sorting the data into quartiles based on AIC measures for the forecast error measure as opposed to the mean percentage error measure.","PeriodicalId":105811,"journal":{"name":"Econometric Modeling: Agriculture","volume":"80 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115746264","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Shutting down and/or upgrading existing productive assets are important economic decisions for the owners of those assets and are also the fundamental decisions that underlie the development of new, growing industries. This paper develops a dynamic structural econometric model of wind turbine owners' decisions about whether and when to add new turbines to a pre-existing stock, scrap an existing turbine, or replace old turbines with newer versions (i.e., upgrade). We apply our model to owner-level panel data for Denmark over the period 1980-2011 to estimate the underlying profit structure for wind producers and evaluate the impact of technology and government policy on wind industry development. Our structural econometric model explicitly takes into account the dynamics and interdependence of shutdown and upgrade decisions and generates parameter estimates with direct economic interpretations. Results from the model indicate that the growth and development of the Danish wind industry was primarily driven by government policies as opposed to technological improvements. The parameter estimates are used to simulate counterfactual policy scenarios in order to quantify the e ectiveness of the Danish feed-in-tari and replacement certificate programs. Results show that both of these policies significantly impacted the timing of shutdown and upgrade decisions made by turbine owners and accelerated the development of the wind industry in Denmark. We also find that when compared with the feed-in-tari ; a declining feed-in-tari ; and the replacement certificate program and the feed-in-tari combined, the replacement certificate program was the most cost-e ective policy both for increasing payo s to turbine owners and also for decreasing carbon emissions.
{"title":"Wind Turbine Shutdowns and Upgrades in Denmark: Timing Decisions and the Impact of Government Policy","authors":"Jonathan A Cook, C.-Y. Cynthia Lin Lawell","doi":"10.2139/ssrn.3336341","DOIUrl":"https://doi.org/10.2139/ssrn.3336341","url":null,"abstract":"Shutting down and/or upgrading existing productive assets are important economic decisions for the owners of those assets and are also the fundamental decisions that underlie the development of new, growing industries. This paper develops a dynamic structural econometric model of wind turbine owners' decisions about whether and when to add new turbines to a pre-existing stock, scrap an existing turbine, or replace old turbines with newer versions (i.e., upgrade). We apply our model to owner-level panel data for Denmark over the period 1980-2011 to estimate the underlying profit structure for wind producers and evaluate the impact of technology and government policy on wind industry development. Our structural econometric model explicitly takes into account the dynamics and interdependence of shutdown and upgrade decisions and generates parameter estimates with direct economic interpretations. Results from the model indicate that the growth and development of the Danish wind industry was primarily driven by government policies as opposed to technological improvements. The parameter estimates are used to simulate counterfactual policy scenarios in order to quantify the e ectiveness of the Danish feed-in-tari and replacement certificate programs. Results show that both of these policies significantly impacted the timing of shutdown and upgrade decisions made by turbine owners and accelerated the development of the wind industry in Denmark. We also find that when compared with the feed-in-tari ; a declining feed-in-tari ; and the replacement certificate program and the feed-in-tari combined, the replacement certificate program was the most cost-e ective policy both for increasing payo s to turbine owners and also for decreasing carbon emissions.","PeriodicalId":105811,"journal":{"name":"Econometric Modeling: Agriculture","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131106115","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
C. Fischer, L. Reins, D. Burtraw, D. Langlet, Åsa Löfgren, M. Mehling, Stefan E. Weishaar, L. Zetterberg, Harro van Asselt, K. Kulovesi
When it was launched in 2005, the European Union emissions trading system (EU ETS) was projected to have prices of around €30/ton CO2 and to be a cornerstone of the EU’s climate policy. The reality was a cascade of falling prices, a ballooning privately held emissions bank, and a decade of low prices providing inadequate incentive to drive investment in the technologies and innovation necessary to achieve long-term climate goals. The European Commission responded with administrative measures, including postponing the introduction of allowances (backloading) and using a quantity-based criterion for regulating future allowance sales (the market stability reserve); although prices are beginning to recover, it is far from clear whether these measures will adequately support the price into the future. In the meantime, governments have been turning away from carbon pricing and adopting overlapping regulatory measures that reinforce low prices and further undermine the confidence in market-based approaches to addressing climate change. The solution in other carbon markets has been the introduction of a reserve price that would set a minimum price in allowance auctions. Opponents of an auction reserve price in the EU ETS have expressed concern that a minimum auction price would interfere with economic operations in the market or would be tantamount to a tax, which would trigger a decision rule requiring unanimity among EU Member States. This Article reviews the economic and legal arguments for and against an auction reserve price. Our economic analysis concludes that an auction reserve price is necessary to accommodate overlapping policies and for the allowance market to operate efficiently. Our legal analysis concludes that an auction reserve price is not a “provision primarily of a fiscal nature,” nor would it “significantly affect a Member State’s choice between different energy sources.” We describe pathways through which a reserve price could be introduced.
{"title":"The Legal and Economic Case for an Auction Reserve Price in the EU Emissions Trading System","authors":"C. Fischer, L. Reins, D. Burtraw, D. Langlet, Åsa Löfgren, M. Mehling, Stefan E. Weishaar, L. Zetterberg, Harro van Asselt, K. Kulovesi","doi":"10.2139/ssrn.3477716","DOIUrl":"https://doi.org/10.2139/ssrn.3477716","url":null,"abstract":"When it was launched in 2005, the European Union emissions trading system (EU ETS) was projected to have prices of around €30/ton CO2 and to be a cornerstone of the EU’s climate policy. The reality was a cascade of falling prices, a ballooning privately held emissions bank, and a decade of low prices providing inadequate incentive to drive investment in the technologies and innovation necessary to achieve long-term climate goals. The European Commission responded with administrative measures, including postponing the introduction of allowances (backloading) and using a quantity-based criterion for regulating future allowance sales (the market stability reserve); although prices are beginning to recover, it is far from clear whether these measures will adequately support the price into the future. In the meantime, governments have been turning away from carbon pricing and adopting overlapping regulatory measures that reinforce low prices and further undermine the confidence in market-based approaches to addressing climate change. The solution in other carbon markets has been the introduction of a reserve price that would set a minimum price in allowance auctions. Opponents of an auction reserve price in the EU ETS have expressed concern that a minimum auction price would interfere with economic operations in the market or would be tantamount to a tax, which would trigger a decision rule requiring unanimity among EU Member States. This Article reviews the economic and legal arguments for and against an auction reserve price. Our economic analysis concludes that an auction reserve price is necessary to accommodate overlapping policies and for the allowance market to operate efficiently. Our legal analysis concludes that an auction reserve price is not a “provision primarily of a fiscal nature,” nor would it “significantly affect a Member State’s choice between different energy sources.” We describe pathways through which a reserve price could be introduced.","PeriodicalId":105811,"journal":{"name":"Econometric Modeling: Agriculture","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129553150","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Abstract This paper documents the effect of primary forest cover loss on increased incidence of malaria. The evidence is consistent with an ecological response. I show that land use change, anti-malarial programs or migration cannot explain the effect of primary forest cover loss on increased malarial incidence. Falsification tests reveal that the effect is specific to malaria, with forest cover having no discernible effect on other diseases with a disease ecology different from that of malaria. Back-of-the-envelope calculations indicate that the morbidity-related malaria-reducing local benefits of primary forests are at least $1-$2 per hectare.
{"title":"Ecosystems and Human Health: The Local Benefits of Forest Cover in Indonesia","authors":"Teevrat Garg","doi":"10.2139/ssrn.3010785","DOIUrl":"https://doi.org/10.2139/ssrn.3010785","url":null,"abstract":"Abstract This paper documents the effect of primary forest cover loss on increased incidence of malaria. The evidence is consistent with an ecological response. I show that land use change, anti-malarial programs or migration cannot explain the effect of primary forest cover loss on increased malarial incidence. Falsification tests reveal that the effect is specific to malaria, with forest cover having no discernible effect on other diseases with a disease ecology different from that of malaria. Back-of-the-envelope calculations indicate that the morbidity-related malaria-reducing local benefits of primary forests are at least $1-$2 per hectare.","PeriodicalId":105811,"journal":{"name":"Econometric Modeling: Agriculture","volume":"43 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124862896","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
In theory, regulators concerned about inequality will deviate from efficient two-part tariffs, charging lower-than-efficient fixed monthly fees and higher-than-efficient per-kilowatt-hour prices. To quantify that relationship, we develop a measure of the redistributive extent of utility tariffs: the “electric Gini.” Utilities with higher electric Ginis shift more costs from households using relatively little electricity to households using more. In practice, US utilities whose ratepayers have more unequal incomes have higher electric Ginis. But electricity demand is only loosely correlated with income, which means that electricity prices are an indirect and ineffective policy for countering income inequality. (JEL D31, L11, L94, L98)
{"title":"The Electric Gini: Income Redistribution Through Energy Prices","authors":"Arik Levinson, Emilson Delfino Silva","doi":"10.3386/w26385","DOIUrl":"https://doi.org/10.3386/w26385","url":null,"abstract":"In theory, regulators concerned about inequality will deviate from efficient two-part tariffs, charging lower-than-efficient fixed monthly fees and higher-than-efficient per-kilowatt-hour prices. To quantify that relationship, we develop a measure of the redistributive extent of utility tariffs: the “electric Gini.” Utilities with higher electric Ginis shift more costs from households using relatively little electricity to households using more. In practice, US utilities whose ratepayers have more unequal incomes have higher electric Ginis. But electricity demand is only loosely correlated with income, which means that electricity prices are an indirect and ineffective policy for countering income inequality. (JEL D31, L11, L94, L98)","PeriodicalId":105811,"journal":{"name":"Econometric Modeling: Agriculture","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115608768","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Whether the agricultural insurance has positive impacts on the primary industry has been debated for decades of years. This paper studies this question based on the policy-based agricultural insurance implementation in 2007 in China. We conduct difference in difference analysis and event study estimation. We find that the premium subsidy policy has significantly positive effects on the primary industry. This policy increases the primary industry production by 1310 yuan per person in the pilot provinces, compared to the non-pilot provinces. Among four sub-industries in the primary industry, the policy mainly affects the agriculture, especially the crops production.
{"title":"Does Agricultural Insurance Premium Subsidy Benefit the Primary Industry?","authors":"Yugang Ding, Chengjiu Sun","doi":"10.2139/ssrn.3468412","DOIUrl":"https://doi.org/10.2139/ssrn.3468412","url":null,"abstract":"Whether the agricultural insurance has positive impacts on the primary industry has been debated for decades of years. This paper studies this question based on the policy-based agricultural insurance implementation in 2007 in China. We conduct difference in difference analysis and event study estimation. We find that the premium subsidy policy has significantly positive effects on the primary industry. This policy increases the primary industry production by 1310 yuan per person in the pilot provinces, compared to the non-pilot provinces. Among four sub-industries in the primary industry, the policy mainly affects the agriculture, especially the crops production.","PeriodicalId":105811,"journal":{"name":"Econometric Modeling: Agriculture","volume":"91 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122187388","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This study applies the recently developed autoregressive distributed lag bounds testing approach to investigate demands for gasoline and diesel in the ground transportation sectors of 10 Asian countries from 1983 to 2013. Results reveal an inelastic fuel demand with respect to price, except in Hong Kong. This relation implies that the government is unable to limit fuel consumption by controlling price. Moreover, fuel demand with respect to income is generally greater than price elasticity. In other words, if the growth of the national income is faster than that of fuel price, fuel consumption will continually increase. Long‐term income elasticity is greater than unity in half of the examined countries. The demand for transportation fuel in these countries is expected to grow at a rate faster than the growth of GDP over a wide range of economies in Asia, with the implication that the concern regarding the scarcity of fossil fuel is not misplaced.
{"title":"Demand for Ground Transportation Fuels in 10 Asian Countries: An Application of the Autoregressive Distributed Lag Bounds Testing Approach","authors":"Wenhua Liu, Ka Lin","doi":"10.1111/1468-0106.12245","DOIUrl":"https://doi.org/10.1111/1468-0106.12245","url":null,"abstract":"This study applies the recently developed autoregressive distributed lag bounds testing approach to investigate demands for gasoline and diesel in the ground transportation sectors of 10 Asian countries from 1983 to 2013. Results reveal an inelastic fuel demand with respect to price, except in Hong Kong. This relation implies that the government is unable to limit fuel consumption by controlling price. Moreover, fuel demand with respect to income is generally greater than price elasticity. In other words, if the growth of the national income is faster than that of fuel price, fuel consumption will continually increase. Long‐term income elasticity is greater than unity in half of the examined countries. The demand for transportation fuel in these countries is expected to grow at a rate faster than the growth of GDP over a wide range of economies in Asia, with the implication that the concern regarding the scarcity of fossil fuel is not misplaced.","PeriodicalId":105811,"journal":{"name":"Econometric Modeling: Agriculture","volume":"55 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131488604","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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