This article introduces a new Hopenhayn-Melitz-type model of heterogeneous producers with endogenous technology choice. Different from previous trade models, it describes smallholder producers in rural areas of developing countries in the context of environment and development economics. Shocks (climate change) and various policies affect the producers’ endogenous choice between market entry or exit and between simple or advanced technology. This adds new margins of adjustment to models used in this context. Based on these mechanisms, the theoretical analysis identifies a novel type of the rebound effect via market entry. The numerical application to coffee production in rural Vietnam shows that secondary effects of the shocks, such as changes in the number of producers, can be larger than the original impact. Technology-supporting policies can have unintended detrimental side effects on less productive producers.
{"title":"Economic Policy and Technology Choice of Heterogeneous Producers","authors":"Michael Hübler, G. Schwerhoff","doi":"10.1086/724517","DOIUrl":"https://doi.org/10.1086/724517","url":null,"abstract":"This article introduces a new Hopenhayn-Melitz-type model of heterogeneous producers with endogenous technology choice. Different from previous trade models, it describes smallholder producers in rural areas of developing countries in the context of environment and development economics. Shocks (climate change) and various policies affect the producers’ endogenous choice between market entry or exit and between simple or advanced technology. This adds new margins of adjustment to models used in this context. Based on these mechanisms, the theoretical analysis identifies a novel type of the rebound effect via market entry. The numerical application to coffee production in rural Vietnam shows that secondary effects of the shocks, such as changes in the number of producers, can be larger than the original impact. Technology-supporting policies can have unintended detrimental side effects on less productive producers.","PeriodicalId":47114,"journal":{"name":"Journal of the Association of Environmental and Resource Economists","volume":"10 1","pages":"1369 - 1404"},"PeriodicalIF":3.6,"publicationDate":"2023-02-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43685809","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This study uses data from an ongoing, open-cohort, longitudinal China Health and Nutrition Survey to examine how the environmental regulation aimed at abating sulfur dioxide (SO2) alters income distribution. We find that this regulation induces a 14%–27% decrease in income inequality, depending on the measurement method. An improvement in income inequality is achieved by lowering the wages of high-income groups while keeping the wages of low-income groups (especially blue-collar workers) unchanged. This change in the labor market can be attributed to a policy that primarily targets emissions from power plants while leaving the manufacturing sector unaffected. As a result, the manufacturing sector continues to create jobs and absorb the blue-collar workers dismissed from other sectors, mitigating the widening income gap. Our study sheds new light on the role of environmental policy in reshaping the labor market and its implications for income distribution.
{"title":"Does Environmental Regulation Matter for Income Inequality? New Evidence from Chinese Communities","authors":"Bihong Huang, Ying Yao","doi":"10.1086/724519","DOIUrl":"https://doi.org/10.1086/724519","url":null,"abstract":"This study uses data from an ongoing, open-cohort, longitudinal China Health and Nutrition Survey to examine how the environmental regulation aimed at abating sulfur dioxide (SO2) alters income distribution. We find that this regulation induces a 14%–27% decrease in income inequality, depending on the measurement method. An improvement in income inequality is achieved by lowering the wages of high-income groups while keeping the wages of low-income groups (especially blue-collar workers) unchanged. This change in the labor market can be attributed to a policy that primarily targets emissions from power plants while leaving the manufacturing sector unaffected. As a result, the manufacturing sector continues to create jobs and absorb the blue-collar workers dismissed from other sectors, mitigating the widening income gap. Our study sheds new light on the role of environmental policy in reshaping the labor market and its implications for income distribution.","PeriodicalId":47114,"journal":{"name":"Journal of the Association of Environmental and Resource Economists","volume":"10 1","pages":"1309 - 1334"},"PeriodicalIF":3.6,"publicationDate":"2023-02-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41986256","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
We investigate how successfully machine-learning (ML) prediction algorithms can be used to estimate causal treatment effects in electricity demand applications with nonexperimental data. We use three prediction algorithms—XGBoost, random forests, and LASSO—to generate counterfactuals using observational data. Using those counterfactuals, we estimate nonexperimental treatment effects and compare them to experimental treatment effects from a randomized experiment for electricity customers who faced critical-peak pricing and information treatments. Our results show that nonexperimental treatment effects based on each algorithm replicate the true treatment effects, even when only using data from treated households. Additionally, when using both treatment households and nonexperimental comparison households, standard two-way fixed effects regressions replicate the experimental benchmark, suggesting little benefit from ML approaches over standard program evaluation methods in that setting.
{"title":"RCTs against the Machine: Can Machine Learning Prediction Methods Recover Experimental Treatment Effects?","authors":"Brian C. Prest, Casey J. Wichman, K. Palmer","doi":"10.1086/724518","DOIUrl":"https://doi.org/10.1086/724518","url":null,"abstract":"We investigate how successfully machine-learning (ML) prediction algorithms can be used to estimate causal treatment effects in electricity demand applications with nonexperimental data. We use three prediction algorithms—XGBoost, random forests, and LASSO—to generate counterfactuals using observational data. Using those counterfactuals, we estimate nonexperimental treatment effects and compare them to experimental treatment effects from a randomized experiment for electricity customers who faced critical-peak pricing and information treatments. Our results show that nonexperimental treatment effects based on each algorithm replicate the true treatment effects, even when only using data from treated households. Additionally, when using both treatment households and nonexperimental comparison households, standard two-way fixed effects regressions replicate the experimental benchmark, suggesting little benefit from ML approaches over standard program evaluation methods in that setting.","PeriodicalId":47114,"journal":{"name":"Journal of the Association of Environmental and Resource Economists","volume":"10 1","pages":"1231 - 1264"},"PeriodicalIF":3.6,"publicationDate":"2023-02-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42460100","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
In two-sided markets with multidimensional contracting, what are the costs and benefits of market concentration? I study this question using data that describe drilling firm negotiations with private landowners for access to mineral rights. Firms benefit from signing geographically proximate contracts through economies of density. Using newly collected data, I model bilateral negotiations as a one-to-many match between firms and landowners and extend the framework to allow complementary preferences among firms for geographically proximate leases. The model estimates imply substantial market concentration in leasing activity that benefits drilling firms and is costly to private landowners through fewer legal protections. Counterfactual experiments that require more landowner concessions in leasing agreements suggest that landowners’ gains outweigh firms’ costs, increasing total welfare by at least 10%. Moreover, firms do not appear to respond to higher leasing costs by signing many fewer leases, suggesting that firms would have likely continued drilling in Tarrant County.
{"title":"One-to-Many Matching with Complementary Preferences: An Empirical Study of Market Concentration in Natural Gas Leasing","authors":"Ashley Vissing","doi":"10.1086/724498","DOIUrl":"https://doi.org/10.1086/724498","url":null,"abstract":"In two-sided markets with multidimensional contracting, what are the costs and benefits of market concentration? I study this question using data that describe drilling firm negotiations with private landowners for access to mineral rights. Firms benefit from signing geographically proximate contracts through economies of density. Using newly collected data, I model bilateral negotiations as a one-to-many match between firms and landowners and extend the framework to allow complementary preferences among firms for geographically proximate leases. The model estimates imply substantial market concentration in leasing activity that benefits drilling firms and is costly to private landowners through fewer legal protections. Counterfactual experiments that require more landowner concessions in leasing agreements suggest that landowners’ gains outweigh firms’ costs, increasing total welfare by at least 10%. Moreover, firms do not appear to respond to higher leasing costs by signing many fewer leases, suggesting that firms would have likely continued drilling in Tarrant County.","PeriodicalId":47114,"journal":{"name":"Journal of the Association of Environmental and Resource Economists","volume":"10 1","pages":"1179 - 1229"},"PeriodicalIF":3.6,"publicationDate":"2023-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49561833","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
We examine self-selection in polychotomous choice models that construct attribute values for each alternative conditioned on observed choices. Using observations made only when the alternative was chosen ignores private information which was a basis for the decision, biasing resulting estimates. We suggest a full-information maximum likelihood procedure that performs well at the extremes of the choice set in our sample, and use an “identification at infinity” weighting to identify levels. We apply the model to understanding fishing location choice in the economically significant Bering Sea pollock fishery, where expected catches at each location are constructed from harvests observed when that location is chosen.
{"title":"Full-Information Selection Bias Correction for Discrete Choice Models with Observation-Conditional Regressors","authors":"Y. A. Chen, A. Haynie, Christopher M. Anderson","doi":"10.1086/719794","DOIUrl":"https://doi.org/10.1086/719794","url":null,"abstract":"We examine self-selection in polychotomous choice models that construct attribute values for each alternative conditioned on observed choices. Using observations made only when the alternative was chosen ignores private information which was a basis for the decision, biasing resulting estimates. We suggest a full-information maximum likelihood procedure that performs well at the extremes of the choice set in our sample, and use an “identification at infinity” weighting to identify levels. We apply the model to understanding fishing location choice in the economically significant Bering Sea pollock fishery, where expected catches at each location are constructed from harvests observed when that location is chosen.","PeriodicalId":47114,"journal":{"name":"Journal of the Association of Environmental and Resource Economists","volume":"10 1","pages":"231 - 261"},"PeriodicalIF":3.6,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43552345","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
: Land policy has major implications for human health and economic development via its in fl uence on outcomes like water pollution, food security, real estate development, and climate change. My research focuses on land use policy in the context of public good provision, valuation of externalities and ecosystem services, and estimating regulatory costs and bene fi ts — often utiliz-ing satellite products to fi ll data gaps to help answer policy-relevant questions. The fi rst chapter of my dissertation investigates the impact of pesticides on human health and welfare using cicada emergence as an ecologically-driven natural experiment to explore the social cost of pesticides use in agriculture. The second chapter analyzes the relationship between irrigation and climate change, showing how adaptive measures can create negative externalities like aquifer drawdown and salinization. The third chapter provides an estimate of the value of wetlands for fl ood mitigation, an important topic in relation to the Clean Water Act and future climate change. Overall, these chapters explore both how humans affect the land and the reverse feedback of how land use decisions affect human welfare.
{"title":"Wallace E. Oates Outstanding Doctoral Dissertation Award","authors":"Charles A. Taylor","doi":"10.1086/723734","DOIUrl":"https://doi.org/10.1086/723734","url":null,"abstract":": Land policy has major implications for human health and economic development via its in fl uence on outcomes like water pollution, food security, real estate development, and climate change. My research focuses on land use policy in the context of public good provision, valuation of externalities and ecosystem services, and estimating regulatory costs and bene fi ts — often utiliz-ing satellite products to fi ll data gaps to help answer policy-relevant questions. The fi rst chapter of my dissertation investigates the impact of pesticides on human health and welfare using cicada emergence as an ecologically-driven natural experiment to explore the social cost of pesticides use in agriculture. The second chapter analyzes the relationship between irrigation and climate change, showing how adaptive measures can create negative externalities like aquifer drawdown and salinization. The third chapter provides an estimate of the value of wetlands for fl ood mitigation, an important topic in relation to the Clean Water Act and future climate change. Overall, these chapters explore both how humans affect the land and the reverse feedback of how land use decisions affect human welfare.","PeriodicalId":47114,"journal":{"name":"Journal of the Association of Environmental and Resource Economists","volume":"10 1","pages":"iii - iii"},"PeriodicalIF":3.6,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47285622","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Research relying on remotely sensed data on land use and deforestation has exploded in recent years. While satellite-based measures have clear advantages in terms of coverage, the presence of measurement error within these products is often overlooked. Here, we detail the econometric implications of these errors when analyzing the determinants of binary measures of deforestation or forest cover. We then discuss estimators that exploit knowledge of the remote-sensing process to obtain consistent estimates. Finally, we assess our estimators via simulation and an impact evaluation of a conservation program in Mexico. We find that both geography and characteristics of the raw data can lead to systematic underreporting of deforestation. However, accounting for these sources of error, which are common across many satellite-based metrics, can limit the bias from misclassification.
{"title":"Remotely Incorrect? Accounting for Nonclassical Measurement Error in Satellite Data on Deforestation","authors":"J. Alix-Garcia, Daniel L. Millimet","doi":"10.1086/723723","DOIUrl":"https://doi.org/10.1086/723723","url":null,"abstract":"Research relying on remotely sensed data on land use and deforestation has exploded in recent years. While satellite-based measures have clear advantages in terms of coverage, the presence of measurement error within these products is often overlooked. Here, we detail the econometric implications of these errors when analyzing the determinants of binary measures of deforestation or forest cover. We then discuss estimators that exploit knowledge of the remote-sensing process to obtain consistent estimates. Finally, we assess our estimators via simulation and an impact evaluation of a conservation program in Mexico. We find that both geography and characteristics of the raw data can lead to systematic underreporting of deforestation. However, accounting for these sources of error, which are common across many satellite-based metrics, can limit the bias from misclassification.","PeriodicalId":47114,"journal":{"name":"Journal of the Association of Environmental and Resource Economists","volume":"10 1","pages":"1335 - 1367"},"PeriodicalIF":3.6,"publicationDate":"2022-12-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46818742","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
In a resource extraction model that features imperfect substitution and endogenous market power, we analytically characterize the effect of anticipated future demand shocks on the resource extraction path. We show that the resource owner’s market share and reserves-to-extraction ratio are sufficient to calculate the supply response under constant elasticity of substitution between alternative energy resources. The analytical characterization of the extraction response allows us to conduct scenario analyses based on available oil market data. Applying data on OPEC, we find a relatively small increase in current extraction due to an anticipated decrease in the price of alternative energy resources, which implies that endogenous markup adjustments of OPEC countries largely reduce the adverse consequences of anticipated climate policies due to intertemporal carbon leakage.
{"title":"Climate Policy and Resource Extraction with Variable Markups and Imperfect Substitutes","authors":"M. Curuk, Suphi Şen","doi":"10.1086/723704","DOIUrl":"https://doi.org/10.1086/723704","url":null,"abstract":"In a resource extraction model that features imperfect substitution and endogenous market power, we analytically characterize the effect of anticipated future demand shocks on the resource extraction path. We show that the resource owner’s market share and reserves-to-extraction ratio are sufficient to calculate the supply response under constant elasticity of substitution between alternative energy resources. The analytical characterization of the extraction response allows us to conduct scenario analyses based on available oil market data. Applying data on OPEC, we find a relatively small increase in current extraction due to an anticipated decrease in the price of alternative energy resources, which implies that endogenous markup adjustments of OPEC countries largely reduce the adverse consequences of anticipated climate policies due to intertemporal carbon leakage.","PeriodicalId":47114,"journal":{"name":"Journal of the Association of Environmental and Resource Economists","volume":"10 1","pages":"1091 - 1120"},"PeriodicalIF":3.6,"publicationDate":"2022-12-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45826697","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Protected areas (PAs) are the leading policy to lower deforestation. Yet resistance by land users leads PAs to be created in remote sites, lowering impact. Resistance continues after PA creation, with both illegal deforestation and advocacy for PADDD, that is, reducing PA status (downgrading) or PA size (partial or full erasure, downsizing or degazettement). For the Brazilian Amazon, we estimate 2010–15 forest impacts of 2009–12 PA erasures, on average and for distinct states. Before panel-DID regression, to find similar controls we matched using static characteristics and 8–10 years of pretreatment deforestation. PA erasures should raise deforestation if erased PAs faced and blocked pressures. Consistent with this, three conditions for “environmental selection” yielded little short-run impact from PADDD: low pressures, unblocked higher pressures, and pressures blocked less by those PAs selected for erasures. Yet for “development selection,” with PA erasures in sites with pressures plus enforcement, PADDD yielded increased deforestation.
{"title":"Does the Selective Erasure of Protected Areas Raise Deforestation in the Brazilian Amazon?","authors":"D. Keleş, A. Pfaff, Michael B. Mascia","doi":"10.1086/723543","DOIUrl":"https://doi.org/10.1086/723543","url":null,"abstract":"Protected areas (PAs) are the leading policy to lower deforestation. Yet resistance by land users leads PAs to be created in remote sites, lowering impact. Resistance continues after PA creation, with both illegal deforestation and advocacy for PADDD, that is, reducing PA status (downgrading) or PA size (partial or full erasure, downsizing or degazettement). For the Brazilian Amazon, we estimate 2010–15 forest impacts of 2009–12 PA erasures, on average and for distinct states. Before panel-DID regression, to find similar controls we matched using static characteristics and 8–10 years of pretreatment deforestation. PA erasures should raise deforestation if erased PAs faced and blocked pressures. Consistent with this, three conditions for “environmental selection” yielded little short-run impact from PADDD: low pressures, unblocked higher pressures, and pressures blocked less by those PAs selected for erasures. Yet for “development selection,” with PA erasures in sites with pressures plus enforcement, PADDD yielded increased deforestation.","PeriodicalId":47114,"journal":{"name":"Journal of the Association of Environmental and Resource Economists","volume":"10 1","pages":"1121 - 1147"},"PeriodicalIF":3.6,"publicationDate":"2022-11-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47034143","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Both electric cars and residential solar panels are environmentally friendly durable goods that are often subsidized. The relationship between the two in demand will affect the efficiency of a range of green policies. This study explores the complementarity between the two goods, taking an instrumental variables approach. Using global horizontal irradiance as an instrument, I find that each existing solar adoption leads to approximately 0.184 additional electric car sales, including 0.121 battery electric vehicles and 0.063 plug-in hybrid electric vehicles. Utilizing availability of high occupancy vehicle lanes and gasoline prices as instruments, I find that each electric vehicle ownership leads to roughly 0.26 additional solar installations. The complementarity mainly comes from lack of charging stations and insufficient compensation for excess solar energy sold back to the grid. The findings imply substantial spillovers from policies affecting either choice, changing the cost-benefit calculus for a range of green policies.
{"title":"Are Electric Cars and Solar Panels Complements?","authors":"Xueying Lyu","doi":"10.1086/723494","DOIUrl":"https://doi.org/10.1086/723494","url":null,"abstract":"Both electric cars and residential solar panels are environmentally friendly durable goods that are often subsidized. The relationship between the two in demand will affect the efficiency of a range of green policies. This study explores the complementarity between the two goods, taking an instrumental variables approach. Using global horizontal irradiance as an instrument, I find that each existing solar adoption leads to approximately 0.184 additional electric car sales, including 0.121 battery electric vehicles and 0.063 plug-in hybrid electric vehicles. Utilizing availability of high occupancy vehicle lanes and gasoline prices as instruments, I find that each electric vehicle ownership leads to roughly 0.26 additional solar installations. The complementarity mainly comes from lack of charging stations and insufficient compensation for excess solar energy sold back to the grid. The findings imply substantial spillovers from policies affecting either choice, changing the cost-benefit calculus for a range of green policies.","PeriodicalId":47114,"journal":{"name":"Journal of the Association of Environmental and Resource Economists","volume":"10 1","pages":"1019 - 1057"},"PeriodicalIF":3.6,"publicationDate":"2022-11-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44477417","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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