Forests, biomass use and poverty in Malawi

Malawi is one of the poorest countries in Africa and has faced significant deforestation over the years. This paper seeks to examine the nature of the relationship between poverty and forests in Malawi. We try to answer three sets of questions: a) what is the extent of biomass available for meeting the energy needs of the poor in Malawi and how is this distributed? b) To what extent does fuelwood scarcity affect the welfare of the poor? And c) do households spend more time in fuelwood collection in response to scarcity? We answer these questions by matching household surveys with remote-sensing data.Our analyses suggest that biomass scarcity is associated with small but significantly lower household welfare, particularly for the rural poor. At current high levels of scarcity, 80% of rural poor households are likely to benefit from an increase in biomass in the community. Rural women spend more time on fuelwood collection where biomass is scarce. The small decrease in welfare associated with biomass scarcity suggests that households cope with scarcity in a variety of ways. Any effort to reduce degradation and deforestation in Malawi has to build on a clear understanding of household adaptation to fuelwood scarcity.     

Estimating Households' Preferences for Environmental Amenities Using Equilibrium Models of Local Jurisdictions

Much research has focused on the development of equilibrium models of local jurisdictions to analyze the formation of social structures and community characteristics. These models, however, have been subjected to little empirical testing. In a recent paper, Epple and Sieg (1999) developed a new method for estimating equilibrium models of local jurisdictions, but they did not include environmental amenities in their empirical application. In this paper, we extend and apply this new method to estimate households’ preferences for alternative environmental amenities in the Portland Oregon metropolitan area. We show that estimated structural parameters would be biased if environmental amenities are ignored. By including amenities into the structural models of local jurisdictions, households’ preferences for alternative environmental amenities and public goods are estimated. Parameter values underlying households’ residential choices are uncovered. Many of the empirical regularities observed in the data are replicated (JEL R1, R2, Q2).     

The effectiveness of home energy audits: A case study of Jackson,Wyoming

This study examines the factors that influence households to adopt modifications recommended by home energy audits and whether these audits lead to significant reductions in electricity use. Household decisions after the audits are recorded along with the corresponding recommended modifications and the offers for co-funding. A discrete choice model of the household decision after the audit is estimated. The results indicate that the potential improvement in heating efficiency from the proposed modifications increase the probability of implementing conservation measures. Co-funding offers also significantly raise the odds of accepting the modifications but are relatively less important than anticipated efficiency improvements. Several approaches are used to determine whether and how much energy is saved after the audits. Electricity demand models are estimated using data two years before and after each household audit. For households who decide to modify their houses after the audit, monthly average electricity use per square foot decreases 7%. While there is an estimated 2% reduction in electricity use attributed to the audit by households who decided not to adopt the proposed modifications, this reduction is not statistically significant, casting doubt on the presence of modifications in behavior from the audit information itself. For all households audited, the results from the electricity demand models suggest that the LVE home energy audit program reduced household electricity use 4.7%. In contrast, a differences-in-differences approach using synthetic control groups based upon a smaller but still sizeable sample of 2000 observations finds that home energy audits reduce household electricity use by more than 10%. Overall, these findings suggest that home audits result in modest but significant reductions in energy use and that co-funding encourages investments that otherwise may not be privately optimal.     

基于面板数据的中国能源强度演变区域影响因素研究

本文基于我国29个省市自治区1990年到2008年的区域面板数据,对影响我国能源强度变化的主要指标进行了回归分析,在区域层面探究了各个因素对我国能源强度变化的影响机理及结果。研究结果发现燃料价格与能源强度变化呈负相关关系,热度日和冷度日的影响效果只有在南部地区显著,人均收入、投资资本比率等因素在不同阶段对能源强度有着不同的影响。本文更进一步的解释了我国能源强度变化的内在影响因素,有助于系统深入的分析我国能源利用中存在的问题。研究结论对节能减排政策的制订具有一定的实践指导意义。     

Energy efficiency and heating technology investments: Manipulating financial information in a discrete choice experiment

We elicit homeowners’ willingness to pay (WTP) for energy efficiency and low-carbon technologies in the context of heating appliance replacement. We employ a within-between subject design that involves manipulating information in a two-stage discrete choice experiment (DCE) and use WTP space estimation to identify the role of financial information in reducing fossil fuel use. We find that homeowners’ average valuation of energy efficiency exceeds associated heating cost savings, suggesting that they also consider non-monetary benefits when evaluating this type of investment, whereas information about private and pro-social benefits of investments only has a limited impact on WTP. Evidence also suggests that homeowners have a strong preference for the existing technology. Consequently, fossil fuel users’ WTP for switching to low-carbon technologies does not cover respective investment cost differentials, and we derive evidence on how combined subsidies and information can induce these users to opt out of fossil technologies.     

Poverty and resource dependence in rural India

Previous studies of rural households in developing countries have tended to find that the dependence of these households on common-pool resources declines with income. Our study of households in Jhabua, India, finds a more complex relationship. Using the share of resource income in total long-run or “permanent” income as our dependence measure—which we argue is more appropriate than the short-run income-based measure commonly used in the literature—we find that for households that collect any resources at all, dependence exhibits a U-shaped relationship with income. That is, the poorest and richest households depend more on resources than households with intermediate incomes. The poorest and richest households are also found to be least likely to collect, however, indicating that resource use at the income extremes is bimodal—either zero or above average. Moreover, the observed trends for resources as a whole are not mirrored in those for individual resources. Dependence on fuelwood and dung declines with income, for example, while dependence on fodder and construction wood increases. These findings suggest that common-pool resources are a productive source of income not just for the poor but also for the rich, and that improvements in the stocks of these resources can potentially form the basis of poverty reduction efforts in these economies.     

A pseudo-panel data model of household electricity demand

We study the dynamic behaviour of household electricity consumption on the basis of four large independent surveys conducted in the province of Québec from 1989 to 2002. The latter region displays some rather unique features such as the very extensive use of electricity for space heating in a cold climate and the wide range of energy sources used to meet space heating requirements. We adopt Deaton (1985) approach to create 25 cohorts of households that form a pseudo-panel. The cohorts have on average 131 households. The model error terms allow for group heteroskedasticity and serial correlation. Short-run and long-run own and cross-price elasticities are statistically significant. Electricity and natural gas are estimated to be substitutes while electricity and fuel oil are complements, as it may occur in the Quebec context. The estimate of the income elasticity is not significant. Comparisons with related studies are provided.     

Subjective probabilistic expectations,household air pollution,and health: Evidence from cooking fuel use patterns in West Bengal,India

An increasing number of empirical studies have investigated the determinants of cooking fuel choice in developing countries, where health risks from household air pollution are one of the most important issues. We contribute to this stream of literature by examining individuals’ subjective probabilistic expectations about health risks when using different types of fuel and their role in cooking fuel usage patterns. We also explore how these patterns, in turn, are associated with health status. Using data collected from 557 rural Indian households, we find that subjective probabilistic expectations of becoming sick from dirty fuel usage are negatively and significantly associated with the fraction of days of dirty fuel usage in households. Concurrently, dirty fuel usage and self-reported health status of the individual being sick are also significantly correlated. We then conduct a policy simulation of information provision regarding the health risks of dirty fuel usage. Our simulation demonstrates that although the provision of information results in statistically significant changes in households’ cooking fuel usage patterns and in individuals’ health status, these changes may be small in size.     

关中地区清洁能源供暖方案的经济环境效益研究

使用清洁能源进行供暖,对关中地区治污减霾、改善能源结构具有积极的意义,但关于关中地区清洁能源供暖经济效益的研究鲜有报道。根据关中地区的供暖需求,论文制定了煤改电、煤改气和浅层地热能三种清洁能源供暖方案,构建了办公建筑、商业建筑和居住建筑三类典型模型,计算了这三类模型使用煤改电、煤改气和浅层地热能方案的投资、成本、净现值、内部收益率及投资回收期。浅层地热能方案净现值最大,盈利总量最大,其次为煤改电方案,最后为煤改气方案。煤改电方案内部收益率最高,煤改气方案最低,但对比差额投资内部收益率,浅层地热能供暖方案优于煤改电方案,煤改电方案优于煤改气方案。根据模型参数,评价了不同方案的污染物排放量和节能性,浅层地热能方案节能性最优,煤改电次之,煤改气较差。论文旨在为推动陕西省清洁能源事业的科学、有序发展提供理论依据。     

Investigating household choice for health and life insurance

The objective of this article is to investigate the joint determination of household choice for health and life insurance. Using the 2008–2009 Consumer Expenditure Survey data, we model household choice for health and life insurance assuming households consider purchasing them to manage financial risks in their life, after accounting for household characteristics, insurance characteristics, health status, and disability status. The model allows assessing the impact of health insurance choice on the choice of life insurance and the correlation between these two choices. The result suggests that health insurance choice positively affects the choice of life insurance and these two choices are positively correlated indicating complementary nature of these insurances in the basket of households’ risk minimising goods.     

An investigation of the increasing prevalence of nonpurchase of meat by British households

The purpose of the analysis has been to investigate the determinants of the household's decisions regarding the purchase of meat in Great Britain. The approach, using a Box-Cox generalization of the ‘double hurdle’ model, has depicted the household making two choices, namely whether or not to purchase the product (the participation decision) and then, for those households which do purchase, how much to buy (the expenditure decision). The determinants considered are socioeconomic variables, such as the total expenditure of the household, market prices, characteristics of the householder (age, gender, education, type of employment) and characteristics of the household (location, presence of children, etc.). By conducting the analysis over several years of survey data (1975–1993) it is possible to investigate whether the influence of these variables has changed over time. The bulk of the empirical analysis has concerned single adult households (with or without children).     

Carbon mitigation costs for the commercial building sector: Discrete–continuous choice analysis of multifuel energy demand

We estimate a carbon mitigation cost curve for the U.S. commercial sector based on econometric estimation of the responsiveness of fuel demand and equipment choices to energy price changes. The model econometrically estimates fuel demand conditional on fuel choice, which is characterized by a multinomial logit model. Separate estimation of end uses (e.g., heating, cooking) using the U.S. Commercial Buildings Energy Consumption Survey allows for exceptionally detailed estimation of price responsiveness disaggregated by end use and fuel type. We then construct aggregate long-run elasticities, by fuel type, through a series of simulations; own-price elasticities range from −0.9 for district heat services to −2.9 for fuel oil. The simulations form the basis of a marginal cost curve for carbon mitigation, which suggests that a price of $20 per ton of carbon would result in an 8% reduction in commercial carbon emissions, and a price of $100 per ton would result in a 28% reduction.     

Greenhouse Gas Abatement Cost Curves of the Residential Heating Market: A Microeconomic Approach

In this paper, we develop a microeconomic approach to deduce greenhouse gas abatement cost curves of the residential heating sector. Our research is based on a system dynamics microsimulation of private households’ investment decisions for heating systems to the year 2030. By accounting for household-specific characteristics, we investigate the welfare costs of different abatement policies in terms of the compensating variation and the excess burden. We investigate two policies: (i) a carbon tax and (ii) subsidies on heating system investments. We deduce abatement cost curves for both policies by simulating welfare costs and greenhouse gas emissions to the year 2030. We find that (i) welfare-based abatement costs are generally higher than pure technical equipment costs; (ii) given utility maximizing households a carbon tax is the most welfare-efficient policy and; (iii) if households are not utility maximizing, a subsidy on investments may have lower marginal greenhouse gas abatement costs than a carbon tax.     

On the power of indicators: how the choice of fuel poverty indicator affects the identification of the target population

In light of the creation of the EU Energy Poverty Observatory (EPOV) in January 2018 and the increase in debates on how fuel poverty is measured, we propose a critical analysis of fuel poverty indicators and demonstrate that choosing a given indicator is central to the identification of the fuel-poorpopulation.

First, we conducted an inter-indicator analysis to show how profiles of fuel-poor households vary depending on the indicator selected. We designed a multidimensional approach based on a multiple correspondence analysis and a hierarchical and partitioning clustering analysis to study characteristics of fuel-poor households. We highlight the difficulty of identifying a fuel-poor ‘typical profile’ and show that the composition of the population depends on the choice of the indicator.

Second, we applied an intra-indicator analysis using two objective expenditure-based indicators with thresholds. In particular, we conducted a sensitivity analysis based on a logit model including variables describing household and dwelling characteristics. We show that the profiles of fuel-poor households as well as the drivers of fuel poverty vary considerably with the chosen threshold level.Given these findings, we stress the need to review how we currently rely on conventional fuel poverty indicators to identify target groups and give some recommendations.     

Household-level analysis of the impacts of electricity consumption on welfare and the environment in Cambodia: Empirical evidence and policy implications

Cambodia’s biomass consumption is the most dominant energy source at residential sector, and its use is mainly for cooking and heating which could affect health due to indoor air pollution. The biomass is mainly sourced from wood cutting and forest-encroachment that could impact the environment due to reduction of forest at considerable scale. By using the data 2015 of Cambodia Socio-Economic Survey, the study investigates the impacts of electricity consumption on household welfare, such as earnings and the school performance of children in the households, and further to investigate its impacts on the environment. The study found that household’s access to electricity with ability to spend on electricity consumption contributes to the positive household welfare effects and environment via a reduction of biomass consumption, and the more household spends on biomass, the more they are prone to sickness of lung problem. The study also confirmed the important role of human capital formation for the positive impact on the welfare and the environment. These findings lead to policy implications that would improve affordable access to electricity to ensure that all households can use electricity for their basic needs and productivity, and also to reduce the negative effects on environment.     

Heterogeneous firms,corporate taxes and export behavior: A firm-level investigation for Italy

This paper analyses the effect of home corporate taxes on a firm’s decision to expand the scale of its activity through exports using a rich dataset on Italian firms. Starting out from the observation that firms’ export activity vary greatly among them and tend to be systematically related to firm’s characteristics, we relate differences in firms’ export choices to firm level incidence of corporate taxes. Our results suggest that (i) corporate taxes matter at both the extensive and the intensive margin and (ii) higher corporate taxes may increase the probability of new firms’ entry in the foreign market while they decrease the export intensity of incumbent exporters.     

Estimating and communicating food system impacts: A case study in Montreal, Quebec

Modern food systems are characterized by a range of resource use, environmental, and socioeconomic impacts, resulting from choices made by various actors, including the public, who are “distanced” from these impacts, with important implications for sustainability. In order to make ecologically responsible food choices, the public will need information that is reliable, easily comprehensible, and that allows them to discriminate between these choices in terms of the range of impacts, and their trade-offs with factors such as market price.We illustrate, by means of a case study involving nine variations of two meals of similar nutritional energy content, some challenges and issues associated with estimating and integrating the diverse impacts of food systems, and explore the implications of our results for communicating these impacts in a manner that balances epistemic adequacy with heuristic usefulness in enabling ecologically responsible food choices.     

Are children an incentive or a disincentive for migration? Evidence from Vietnam

This study analyzes the influence of children on household migration decisions using data on current internal movement in Vietnam a country that has experienced significant rural–urban migration in the recent years. Families with children usually have three migration choices: move together, stay together or send only one parent to work afar. Using an instrumental variable approach, we show that having an additional child reduces the probability of household migration by 0.0115, while it increases the likelihood of fathers’ migration by 0.0121. These effects suggest that households with more children may be less mobile but may have a greater economic need for migration.     

Examining energy poverty in Chinese households: An Engel curve approach

This article is first to model energy poverty in Chinese households using an Engel curve approach. To analyse the determinants of energy poverty and energy expenditures across households, we avail the 2015 wave of the Chinese General Social Survey (CGSS). Possible presence of endogeneity is accounted for in the model specification as well as by using the Lewbel heteroscedasticity identified endogenous variables estimator. In addition, we are the first to scrutinise disparity and discrimination by conducting the Blinder–Oaxaca decomposition of energy poverty model by gender, ethnicity, region (Eastern vs. non-Eastern provinces), and urbanisation status (rural vs. urban residents). Our analysis shows: (i) education is the key determinant of various energy poverty measures and energy expenditure shares across Chinese households; (ii) other determinants including fossil fuel mix and electricity price discrimination are found to worsen energy poverty, on average. However, fossil fuel mix is found to increase expenditure share of total energy, electricity, and coal and decrease that of biomass; and (iii) the Blinder–Oaxaca decomposition analyses show no statistically significant gender or ethnic discrimination in energy poverty rates. However, there is substantial divide between Eastern and non-Eastern provinces and between rural and urban households—with these groups also discriminated against when accessing clean cooking fuels and technologies. The Blinder–Oaxaca results also generally support the logistic and the Lewbel energy poverty model findings.