Environmental Economics Literature Research Articles

A new look at the finance–environment nexus: How yield spread affects environmental quality in the United States

AbstractEnhancing environmental quality is currently a key focus for policymakers. Furthermore, researchers are also prioritizing the investigation of novel variables that can influence environmental quality. The yield spread is commonly used as a leading indicator for business cycles in the macro‐finance literature, providing information about future expectations regarding business cycles. The yield spread also presents information about the borrowing costs of firms. None of the existing studies in the environmental economics literature has tested the impact of the yield spread on environmental quality, implying the level of the yield spread has not been considered a variable that can influence environmental quality. This study aims to fill this gap by providing evidence on the effect of yield spread (between 2‐ and 10‐year government bonds) on environmental quality in the United States from June 1976 to September 2023. The results indicate that an increase in the yield spread leads to a rise in environmental destruction. These results suggest two considerable consequences. First, optimistic expectations today lead to the overuse of resources and environmental destruction. Second, firms' higher borrowing costs may be forcing them to use less environmentally friendly production methods to offset more expensive financing costs and increase their profits. This study asserts that companies should enhance their environmental sensitivity, and policymakers should adopt a more proactive stance, based on the results of this study and other research that demonstrates the detrimental impacts of environmental regulation violations and poor environmental performances on companies' stock prices and financial performances.

Shaping the Future of Environmental Economics: A Bibliometric Review of Current Trends and Future Directions

Environmental economics is increasingly pivotal in addressing global environmental challenges. This study aims to elucidate the research landscape in this field, focusing on prevalent themes such as climate change, carbon emissions, sustainable development, and environmental policy. Employing a bibliometric analysis, we analyzed a substantial corpus of literature from Scopus. We applied Lotka's Law to assess author productivity and distribution and conducted institutional and country-level analyses to map the geographical spread and institutional affiliations in environmental economics research. Our analysis highlights a significant growth in the environmental economics literature, with a notable focus on climate change and sustainability. A concentration of publications among a few authors was observed, indicating influential researchers and potential for increased collaboration. The rise in publications, particularly in China and leading journals like 'The Journal of Cleaner Production,' reflects a global upsurge in environmental economics research. Distinct clusters were identified, covering diverse topics from climate change economics to environmental policy. The study acknowledges limitations due to exclusive reliance on Scopus data, suggesting future research to include other databases like the Web of Science for a more comprehensive analysis. Considering the evolving nature of environmental challenges, we advocate for interdisciplinary approaches and continual updates in research to address emergent trends in this critical field.

How Sustainable is Environmental Economics? A Review of Research Trends and Implications

Embarking on a comprehensive review of the Environmental Economics literature, we employed a bibliometric approach to gather 6,118 articles published between 1993 and 2023 from Scopus-indexed journals. Leveraging various software tools, including RStudio, VOSviewer, and Excel, we analyzed the data to identify the most active scientific contributors in terms of countries, institutions, sources, documents, and authors. Our examination revealed a notable upward trend in publication starting from 2017, underscoring the increasingly diverse applications of Environmental Economics across domains such as Sustainability, Environmental Footprints, Carbon Emissions, Climate Impact, Navigating Environmental Governance, Policies for Sustainable Futures, Economic Approaches, and Environmental Sustainability. Notably, China, the United States, and the United Kingdom emerged as the top three contributors to the literature. The findings of our study offer valuable insights for market participants, particularly in understanding how Environmental Economics can inform their decision-making processes.

Does negative interest rate policy impact carbon emissions? Evidence from a quasi-natural experiment

Financial policy is an essential tool for achieving sustainable economic development and has been extensively studied in the environmental economics literature. This study employs panel data of 45 countries from 2007 to 2019 and a multi-period difference-in-differences (DID) method to investigate the mechanism and transmission path of negative interest rate policy on carbon dioxide emissions. The results indicate that the implementation of negative interest rate policy can significantly reduce CO2 emissions, and various robustness tests substantiate this result. Mechanism tests show that when the interest rate breaks the zero lower bound constraint, CO2 emissions can be reduced through the exchange rate channel, while the credit channel is blocked. Furthermore, the mitigation effect of negative interest rate policy varies with country heterogeneity, and countries with low comprehensive development, high economic growth, and high investment levels have more potential to control environmental degradation. The study evaluates the effects of negative interest rate policy from an environmental perspective, providing useful policy insights for monetary authorities to formulate effective policies to promote coordinated economic and environmental development.

Environmental Kuznets curve (EKC) hypothesis: A bibliometric review of the last three decades

The environmental Kuznets curve (EKC) is a widely tested hypothesis in the environmental economics literature. It explains the dynamics between economic growth and environmental degradation. This study conducts a bibliometric analysis for the past three decades (1994–2021) that contributes to the intellectual structure and knowledge progress of the EKC hypothesis using descriptive analysis and networking analysis. The descriptive analysis comprises publication trends, language, publishers, Web of Science category and research areas, and citation analysis. Meanwhile, networking analysis includes keyword co-occurrence analysis, co-authorship analysis and co-citation analysis. The findings of the descriptive analysis reveal that the number of publications in the EKC hypothesis has gradually increased over the years. The most productive publishers are Elsevier and Springer Nature. Researchers from China and Turkey tend to be the most prolific authors, with the highest number of citations, co-authorships and co-citations. According to the network analysis, the main keywords appearing in the EKC studies are economic growth, CO2 emissions, energy consumption, China, renewable energy and financial development, which is also supported by the most frequently used keyword plus and its clusters. Based on our findings, we have proposed several policy recommendations from the keyword analysis that could foster economic development and improve environmental quality simultaneously. From the emerging trends of EKC, new directions for future research are also proposed.

Exploring the Impact of Economic Growth on the Environment: An Overview of Trends and Developments

In our modern world, energy keeps the global economy running, and economic growth concerns are profoundly interrelated with environmental quality issues. Interestingly, scientists engage with empirical research to identify the impacts and causalities at the interface of economic activities, energy supply, and demand. The importance of the present study lies in a discussion of all contemporary research efforts bridging two strands of empirical literature in environmental economics: developments in energy growth nexus discussion and the environmental Kuznets curve. Furthermore, it highlights the inclusion of untested explanatory variables and the impacts on environmental degradation levels. In the context of the EKC hypothesis, the most popular indicators are greenhouse gas emissions (GHGs) and carbon dioxide emissions in conceptualizing environmental degradation. A review of relevant empirical studies disclosed additional research opportunities that can consider currently untested and less visible proxies of economic growth. For both strands in the literature, results differ based on the group of countries investigated, the econometric models adopted, the format of data, e.g., time series or panel analyses, the time frames due to data availability, and the proxies used to conceptualize energy, environmental degradation, and economic growth. Practical implications indicate that environmental degradation can be avoided or significantly limited within sustainable economic growth to reduce carbon dioxide emissions and increase the use of renewables in the energy mix. Furthermore, one particular implication is the concept of energy efficiency to reduce relevant demand to produce the same outcome or task.

Natural resource endowments and growth dynamics in Africa: evidence from panel cointegrating regression

PurposeWith heterogeneous findings dominating the growth and natural resources relations, there is a need to explain the variances in Africa's growth process as induced by robust measures of factor endowments. This study used a comprehensive set of data from the updated database of the World Bank to capture the heterogeneous dimensions of natural resource endowments on growth with a particular focus on establishing complementary evidence on the resource curse hypothesis in energy and environmental economics literature in Africa. These comprehensive data on oil rent, coal rent and forest rent could provide new and insightful evidence on obscure relations on the subject matter.Design/methodology/approachThis paper considers the panel vector error correction model (PVECM) procedure to explain changes in economic growth outcomes as induced by oil rent, coal rent and forest rent. The consideration of the PVECM was premised on the panel unit root process that returns series that were cointegrated at the first-order differentials.FindingsThe paper found positive relations between oil rent, coal rent and economic development in Africa. Forest rent, on the other hand, is inversely related to economic growth in Africa. Trade and human capital are positively related to economic growth in Africa, while population growth is negatively associated with economic growth in Africa.Research limitations/implicationsShort-run policies should be tailored towards the stability of fiscal expenditure such that the objective of fiscal policy, which is to maintain the condition of full employment and economic stability and stabilise the rate of growth, can be optimised and sustained. By this, the resource curse will be averted and productive capacity will increase, leading to sustainable growth and development in Africa, where conditions for growth and development remain inadequately met.Originality/valueThe originality of this paper can be viewed from the strength of its arguments and methods adopted to address the questions raised in this paper. This study further illuminated age-long obscure relations in the literature of natural resource endowment and economic growth by taking a disaggregated approach to the component-by-component analysis of natural resources factors (the oil rent, coal rent and forest rent) and their corresponding influence on economic growth in Africa. This pattern remains underexplored mainly in previous literature on the subject. Many African countries are blessed with an abundance of these different natural resources in varying proportions. The misuse and mismanagement of these resources along various dimensions have been the core of the inclination towards the resource curse hypothesis in Africa. Knowing how growth conditions respond to changes in the depth of forest resources, oil resources and coal resources could be useful pointers in Africa's overall energy use and management. This study contributed to the literature on natural resource-induced growth dynamics by offering a generalisable conclusion as to why natural resource-abundance economies are prone to poor economic performance. This study further asks if mineral deposits are a source or reflection of ill growth and underdevelopment in African countries.

Do green innovation, I.C.T., and economic complexity matter for sustainable development of B.R.I. economies: moderating role of higher education.

The research intends to enlarge the environmental economics literature by displaying the probable mechanisms between green innovation, higher education, and sustainable development. In the context of a new era, sustainability faces challenging obstacles. Many studies have looked at fundamental factors affecting CO2 emissions, while the impact of green innovation and higher education is essential but mostly ignored. This study looked at 60 Belt and Road Initiative (B.R.I.) economies to see how factors, including green innovation, economic complexity index, I.C.T., and higher education, affect carbon emissions in the presence of sustainable development using annual data from 2000-2020. In order to calculate the persistence of the connection between the factors, this research uses the CS-ARDL. The results' robustness and reliability were examined using PMG estimation. The results indicate that the economic complexity index and urbanization positively impact carbon emission (CO2). Higher education (E.D.U.) has a significant positive impact in the short run and a negative effect in the long run-on carbon emissions. Similarly, information and communication technology (I.C.T.) and green innovation have a negative impact on carbon emission (CO2). Moreover, the results indicate that the moderate effect of green innovation with economic complexity index, information and communication technology, and higher education has a negative impact on carbon emission. The estimated coefficients also provide significant policy implications for the chosen and the other developing markets in designing an adequate route ahead to a sustainable environment.

Enhancing environmental quality in the United States by linking biomass energy consumption and load capacity factor

This study analyzes the impact of biomass energy, financial development, and economic growth on environmental quality using the novel Fourier autoregressive distributed lag (ARDL) approach on annual data for the period 1965–2018 in the United States (USA). The study analyzes the impact of related variables on the load capacity factor (LCF) as well as on indicators of environmental degradation such as carbon dioxide emissions and ecological footprint. The LCF is one of the most comprehensive environmental indicators to date, encompassing both biocapacity and ecological footprint. In this regard, this study contributes to the environmental economics literature by examining, for the first time, the impact of biomass energy on the LCF. The results of the cointegration test show that there is only a long-run relationship between the LCF and the independent variables. According to the Fourier ARDL results, biomass energy improves the environmental quality, while financial development has no effect on the LCF. Moreover, the increase in per capita income reduces the LCF. Furthermore, since the income elasticity is larger in the long run than in the short-run, the environmental Kuznets curve is validated. Therefore, the United States government should encourage the use of biomass and investment in this form of energy.

The Impact of Extreme Temperature Shocks on the Health Status of the Elderly in China

With the accelerating process of climate change, long-term exposure to extreme temperatures could threaten individuals' physical health, especially for the vulnerable population. This paper aims to investigate the long-term effects of extreme temperature exposure on the health of the elderly in the context of climate change and aging. Different from most of the existing literature in environmental economics, we define the relative extreme temperature exposure based on the local temperature pattern. By combining a large national household survey and nationwide meteorologic historical data, this study provides empirical evidence that heat exposure days and cold exposure days during the past year both significantly affect the physical health of middle-aged and elderly groups, controlling for city, year, and individual fixed effects. The effect on individual physical health has certain seasonal characteristics and is heterogeneous across populations. Additionally, cooling and heating equipment are effective in alleviating the reverse impact of heat and cold exposure. The estimation is robust and consistent across a variety of temperature measurements and model modifications. Our findings provide evidence of the long-term and accumulative cost of extreme temperature to middle-aged and elderly human capital, contributing to helping the public to better understand the full impact of climate change.

A machine learning process for examining the linkage among disaggregated energy consumption, economic growth, and environmental degradation

Improving environmental quality is at the heart of the Saudi Vision 2030. Within this context, this study seeks to extend previous environmental economics literature by examining the relationship between disaggregated energy use, economic growth, and environmental quality in Saudi Arabia using machine learning (ML) techniques. Using data from 1980 to 2020, we found that reducing CO2 emissions cannot be done in Saudi Arabia without a complete transition from fossil to renewable resources and a more viable road to sustainability. ML-based regression and prediction shows that CO2 emissions will continue to grow until 2024. Beginning in 2025 and beyond, the emissions decrease (i.e., reducing CO2 emissions) must be accompanied by an increment use of renewable energies to guarantee stable economic growth.

On the potential use of the Ecosystem Services Valuation Database for valuation in the System of Environmental Economic Accounting

The System of Environmental Economic Accounting - Ecosystem Accounting (SEEA EA) provides a framework for quantifying and valuing ecosystem services that is consistent with the System of National Accounts (SNA). As such, monetary estimates for ecosystem services are required to be measured as exchange values. The environmental economics literature on the value of ecosystem services has expanded consideralby over the past two decades and the Ecosystem Services Valuation Database (ESVD) currently provides the most comprehensive collection and synthesis of this information. The primary valuation studies included in the ESVD, however, measure a variety of value concepts including welfare values, exchange values and others. This raises a challenge for using existing value data as input to SEEA EA applications. This paper explores potential approaches to using the ESVD for value transfers that are consistent with SEEA EA, specifically for the estimation of meta-analytic value functions that can be used to reflect spatial variation in supply and demand of ecosystem services and proxy exchange values. It identifies avenues for future research and development of the ESVD to operationalise and test this approach.

Role of environmental regulations and eco-innovation in energy structure transition for green growth: Evidence from OECD

How to effectively tackle the gigantic issue of climate change with policy instruments like environmental regulations is a highly relevant and complicated question. The constant performance monitoring of said policy instruments is much essential to formulate effective green growth strategies. Therefore, this study empirically explore the nexus between environmental regulations and green growth while considering green patents, eco-taxations, human capital index, renewable energy consumption, and economic growth with extended proxies of pollution emissions. Advance panel data estimation techniques are employed to produce robust results by solving the issues of endogeneity, heteroskedasticity, serial correlation, and cross-sectional dependency for selected OECD countries covering the time horizon from 1994 to 2020. The empirical findings confirm the positive role of environmental regulations to push for eco-innovations and pull for green growth while endorsing the double divided (DD) hypothesis. The findings contribute to environmental economics literature that such ecotaxes not only promote eco-friendly innovations with economic benefits but promote sustainability practices among individuals and corporations, recommend that OECD countries should focus to promote ecotaxes and eco-innovations as an efficient and effective policy instrument and share with less developed countries as a social responsibility. Besides this other important strategic policy recommendations were suggested to policymakers for the promulgation of sustainable development.

Is there a trade-off between financing current account deficits and environmental deterioration in developing countries? An empirical investigation for the validity of the pollution haven hypothesis.

The impact of foreign direct investment (FDI) on environmental quality has been discussed in the environmental economics literature over the last decades. Within this scope, the pollution haven hypothesis (PHH) postulates that FDI inflows can cause environmental degradation in developing countries. Using data over the period 1993-2018 for 10 developing countries with current account deficits, this paper aims to test the validity of the PHH. Therefore, the paper examines whether or not developing countries face off a trade-off between financing current account deficits and environmental deterioration. The paper employs panel data methods that consider cross-sectional dependence. The empirical findings show that foreign direct investment inflows have no impact on environment, meaning the PHH does not dominate for these countries. Hence, the findings indicate that there is no trade-off between financing current account deficits and environmental deterioration.

Regulation versus taxation: Efficiency of zoning and tax instruments as anti-congestion policies

The following two types of instruments may be used to combat the congestion of road and nonroad infrastructure: first, zoning as quantity regulation favored by planners; and second, congestion charges as tax instruments favored by economists. In contrast to the instrument choice literature in environmental economics, urban economics and planning studies seldom analyze these types of instruments together. We analyze these instruments in a general equilibrium spatial model with spatial heterogeneity. We examine their working mechanisms and efficiencies and extend the instrument choice approach to the externalities caused by infrastructure congestion. When the instrument design is optimal, zoning can be more efficient than, as efficient as, or less efficient than, congestion charges, depending on the relative strength of road and nonroad congestion. However, when, for whatever reason, there are deviations from the optimal instrument level, zoning not only becomes inferior to congestion charges, but is also likely to reduce welfare.

Determinants of CO2 emissions in the BRICS economies: The role of partnerships investment in energy and economic complexity

The anthropogenic implications of energy consumption, real income level, and natural resources abundance have been well documented in the environmental economics literature. However, given the uniqueness of many economies i.e., partnerships investment in energy and economic complexity around the globe, it is imperative to investigate the nexus between the outlined variables in a carbon-income framework. To this end, we leverage on second- generational panel methods for its superiority over first-generation model over annual frequency data from 1990 to 2018 for the case of BRICS countries. Empirical findings show that positive changes in trade openness and economic complexity stimulate environmental quality. On the contrary, economic growth, natural resources and public-private partnership contribute to environmental degradation. Based on these results, new insights are obtained for the policymakers, and policies are recommended to develop the environmental quality in BRICS economies.

A case for measuring negative willingness to pay for consumer goods

Negative willingness to pay (WTP) has received significant attention in the environmental economics literature but generally has been ignored by economists interested in measuring consumer preferences for food and beverages. Most consumer preference studies have focused solely on WTP measures and, in most cases, have treated negative consumer responses to a product as equivalent to consumers simply not wanting to purchase it since both sentiments have a WTP estimate of $0.However, for some goods such as bottled water, this approach can be an oversimplification that fails to reveal consumers’ true sentiments, a problem that is relevant in policy contexts. To test this question, we conduct a randomized controlled study involving 1384 adult consumers that tests how three unconventional elicitation approaches affect estimates of consumer preferences for nearly identical goods: bottled water and tap water. We find that stated values for both types of water differ by treatment and that ignoring negative WTP values upwardly biases the premium consumers are willing to pay for bottled water. Our findings show that allowing negative values of WTP provides more-accurate valuations and measures of differences in valuations for two goods, something that is particularly important for policymaking since consumer valuations can reflect their support for efforts to address externalities associated with consumer goods or may reflect other consumer sentiments, such as food safety concerns.

Research effort devoted to regulating and supporting ecosystem services by environmental scientists and economists.

The economic valuation of ecosystem services in part reflects the desire to use conventional economic tools (markets and economic instruments) to conserve ecosystem services. However, for regulating and supporting ecosystem services that depend on ecosystem structure and function, estimation of economic value requires estimates of the current level of underlying ecological functions first. This primary step is in principle, the job of environmental scientists, not economists. Here, we provide a coarse-level quantitative assessment of the relationship between the research effort expended by environmental scientists (on the biophysical values) and economists (on the monetary values) on 15 different regulating and supporting services in 32 ecosystem types using peer-reviewed article hits retrieved from bibliographic databases as a measure of research effort. We find a positive, moderately strong (r = 0.69) correlation between research efforts in the two domains, a result that, while encouraging, is likely to reflect serendipity rather than the deliberate design of integrated environmental science-economics research programs. Our results suggest that compared to environmental science research effort economic valuation is devoted to a smaller, less diverse set of ecosystem services but a broader, more diverse, set of ecosystem types. The two domains differed more with respect to the ecosystem services that are the major focus of research effort than they did with respect to the ecosystem types of principal research interest. For example, carbon sequestration, erosion regulation, and nutrient cycling receive more relative research effort in the environmental sciences; air quality regulation in economic valuations. For both domains, cultivated areas, wetlands, and urban/semi-urban ecosystem types received relatively large research effort, while arctic and mountain tundra, cave and subterranean, cryosphere, intertidal/littoral zone, and kelp forest ecosystem types received negligible research effort. We suggest ways and means by which the field of sustainability science may be improved by the design and implementation of a searchable database of environmental science and economic valuation literature as well as a global ecosystem service research network and repository that explicitly links research on the estimation and prediction of biophysical ecosystem functions with that of the social sciences and other knowledge systems. These suggestions would, at least in principle, facilitate a more efficient research agenda between economists and environmental scientists and aid management, regulatory and judicial decision-makers.

Estimating different order polynomial logarithmic environmental Kuznets curves

This paper contributes to the environmental literature by (i) demonstrating that the estimated coefficients and the statistical significance of the non-leading terms in quadratic, cubic, and quartic logarithmic environmental Kuznets curve (EKC) specifications are arbitrary and should therefore not be used to choose the preferred specification and (ii) detailing a proposed general-to-specific type methodology for choosing the appropriate specifications when attempting to estimate higher-order polynomials such as cubic and quartic logarithmic EKC relationships. Testing for the existence and shape of the well-known EKC phenomenon is a hot topic in the environmental economics literature. The conventional approach widely employs quadratic and cubic specifications and more recently also the quartic specification, where the variables are in logarithmic form. However, it is important that researchers understand whether the estimated EKC coefficients, turning points, and elasticities are statistically acceptable, economically interpretable, and comparable. In addition, it is vital that researchers have a clear structured non-arbitrary methodology for determining the preferred specification and hence shape of the estimated EKC. We therefore show mathematically and empirically the arbitrary nature of estimated non-leading coefficients in quadratic, cubic, and quartic logarithmic EKC specifications, being dependent upon the units of measurement chosen for the independent variables (e.g. dependent upon a rescaling of the variables such as moving from $m to $bn). Consequently, the practice followed in many previously papers, whereby the estimates of the non-leading terms are used in the decision to choose the preferred specification of an estimated EKC relationship, is incorrect and should not be followed since it potentially could lead to misleading conclusions. Instead, it should be based upon the sign and statistical significance of the estimated coefficients of the leading terms, the location of turning point(s), and the sign and statistical significance of the estimated elasticities. Furthermore, we suggest that researchers should follow a proposed general-to-specific type methodology for choosing the appropriate order of polynomials when attempting to estimate higher-order polynomial logarithmic EKCs.

A Machine Learning Analysis of the Recent Environmental and Resource Economics Literature

We use topic modeling to study research articles in environmental and resource economics journals in the period 2000–2019. Topic modeling based on machine learning allows us to identify and track latent topics in the literature over time and across journals, and further to study the role of different journals in different topics and the changing emphasis on topics in different journals. The most prevalent topics in environmental and resource economics research in this period are growth and sustainable development and theory and methodology. Topics on climate change and energy economics have emerged with the strongest upward trends. When we look at our results across journals, we see that journals have different topical profiles and that many topics mainly appear in one or a few selected journals. Further investigation reveal latent semantic structures across research themes that only the insider would be aware.