Panel Estimation Research Articles

The connection between disaggregate energy use and export sophistication: New insights from OECD with robust panel estimations

Numerous nations have demonstrated their commitment to achieve sustainable economic growth by enhancing export sophistication fueled by imperative energy utilization. This research examines the impact of renewable and non-renewable energy (RE and NRE) use on the improvement and diversification of export strategies among OECD economies using data from 1990 to 2022. This study contributes to the existing body of knowledge by introducing an export sophistication index as a dependent variable in the corresponding model. Pre-estimations followed by employing the CS-ARDL method findings revealed that disaggregated energy use plays a pivotal role in enhancing the intelligence of OECD economies, with the use of NRE energy exerting a more significant influence than REN use. While foreign direct investment, institutional quality and human capital also play essential roles in the complexity of exports within these economies. Applying the dynamic econometric technique, Wavelet coherence analysis substantiates these findings. Consequently, the study's results yield a range of policy recommendations.

Printed PZT Transducers Network for the Structural Health Monitoring of Foreign Object Damage Composite Panel

The work presented here focuses on the structural health monitoring (SHM) of a foreign object damage (FOD) composite panel equipped with an innovative printed piezoelectric transducer network. The 3D woven composite FOD panel measures approximately 800 mm x 320 mm, is curved with a cross-sectional thickness varying from approximately 2 mm to 12 mm, and a stainless-steel leading edge is bonded at one of its sides. The core idea explored here is to rely on an innovative screen-printing technology to print a full piezoelectric transducer allowing to successfully achieve SHM on such a complex composite structure. This work is being carried out within the European project MORPHO – H2020. After printing a 25 elements PZT network, a four points bending fatigue experimental campaign using the PZT network along with other sensor technologies (embedded optical fibres with FBG sensors and acoustic emission sensors) is carried out. This unique experimental campaign allows to generate data and will help to develop diagnostic and prognostic methodologies for remaining life estimation and SHM of the FOD panel. It is demonstrated here through impedance measurements that the printing process associated with the printed PZT transducers is highly repeatable thus validating its use at a larger industrial scale. Furthermore, the printed piezoelectric transducers electromechanical behaviour is characterized and they are shown to be able to detect foreign object impact and to size and localize resulting damage using Lamb waves signals collected at different locations of the network. This innovative printing technology for PZT transducers network is thus extremely promising. It is furthermore highly advantageous to use the printed transducers for SHM instead of regular ceramic ones as this technology is non-intrusive, add negligible weight, can be printed during the manufacturing process, and arrays of transducers ensure easy availability of another transducer in case of failure of one.

A Causal Analysis of Financial Development and Economic Growth

In terms of cause and effect, financial development and economic growth relationship has been a major empirical issue for researchers and policy makers. This study explores the causal linkages between financial development and economic growth catering for country specificity and structural shocks pertaining to different cross sections in SAARC and ASEAN countries by calling in the bootstrapping technique proposed by Konya (2006). We considered the panel estimation to allow for contemporaneous correlations and performed the Wald test for Granger Causality with country specific bootstrap critical values catering for structural breaks. Empirical investigation reveals the existence of both the demand and supply leading phenomena for the selected period of 1980-2019. The direction of causality is sensitive measures and proxies used for financial development.

A comparison of cryptocurrency volatility-benchmarking new and mature asset classes

The paper analyzes the cryptocurrency ecosystem at both the aggregate and individual levels to understand the factors that impact future volatility. The study uses high-frequency panel data from 2020 to 2022 to examine the relationship between several market volatility drivers, such as daily leverage, signed volatility and jumps. Several known autoregressive model specifications are estimated over different market regimes, and results are compared to equity data as a reference benchmark of a more mature asset class. The panel estimations show that the positive market returns at the high-frequency level increase price volatility, contrary to what is expected from the classical financial literature. We attributed this effect to the price dynamics over the last year of the dataset (2022) by repeating the estimation on different time spans. Moreover, the positive signed volatility and negative daily leverage positively impact the cryptocurrencies’ future volatility, unlike what emerges from the same study on a cross-section of stocks. This result signals a structural difference in a nascent cryptocurrency market that has to mature yet. Further individual-level analysis confirms the findings of the panel analysis and highlights that these effects are statistically significant and commonly shared among many components in the selected universe.

Exploring Oman’s International Tourism Determinants in a Gravity Modelling Framework

Abstract This research investigates Oman’s international tourism predictors within a coherent gravity modelling framework. International visitor arrival data for 2007 to 2015 involving Oman’s forty-eight main visitor origin countries are incorporated in the balanced panel estimation empirical phase that tests several gravity model specifications. The estimation procedure includes standard gravity variables and controls for several hypothesized influences. The findings provide strong evidence that the economic sizes of visitor recipient and origin countries, the distance between Oman and visitor origin countries, humidity, quality of accommodation, and common religion are statistically significant predictors. Surprisingly, while relevant, Oman’s cultural attractions (museums, forts, and castles) and the extent of human freedom are statistically insignificant. These findings are unique as they focus on the importance of factors determining Oman’s tourism within a cohesive and inclusive modelling framework. Policymakers can target the abovementioned variables to facilitate investments and propel tourism.

Renewable Adoption, Energy Reliance, and CO2 Emissions: A Comparison of Developed and Developing Economies

Emerging economies and ecosystems rely heavily on fossil fuels, and a country’s energy dependence is a strong indicator of its reliance on foreign suppliers. This study investigates the impact of energy dependence on energy intensity, CO2 emission intensity, and the exploitation of renewable resources in 35 developing and 20 developed nations. It also explores the correlation between renewable energy, GDP growth, and CO2 emissions. This study utilizes the Generalized Linear Model (GLM) and the Robust Least Squares (RLS) method to investigate the negative correlation between renewable energy and policymakers in established and emerging economies. It also employs distinctive linear panel estimation techniques spanning from 1970 to 2022. This study examines the impact of renewable energy on economic growth, energy consumption, and CO2 emissions across four continents. Developing countries see an increase in per capita CO2 emissions when their utilization of renewable energy exceeds their capacity. Even with the introduction of several proxies for renewable energy use using changed techniques, this discovery remains valid. Moreover, this is particularly crucial for industrialized nations with well-established institutions. Energy dependency has increased the energy and carbon intensity needed for expansion across all components, which is surprising. The regional study discovered a spillover impact in most regions, indicating that the consequences of energy reliance are similar in neighboring countries. Regional energy exchange unions play a vital role in reducing the adverse environmental and economic impacts of energy dependence, which is essential for the growth of the renewable energy sector and the decrease in greenhouse gas emissions. Undeveloped countries need to enhance their investment in research and development to advance technologically.

Indigenous representation and participation: The case of the Chilean Mapuche

According to the empowerment hypothesis, minority politicians encourage minority participation. The relationship between representation and participation has been extensively analyzed for several ethnic minorities and women, but there are no studies for indigenous populations in Latin America. This paper evaluates the link between descriptive representation and electoral registration of Mapuche, a deprived indigenous minority from the South of Chile that is as large as ten percent of the total population. We implement a panel estimation that controls district effects using a national dataset of more than three million new registrations in Chile for five municipal elections. We found that Mapuche mayors are significantly associated with higher Mapuche participation during the first year of the mayoral period. Since registration in Chile occurs throughout the representatives’ term, and we use registrations long before the next election, our evidence suggests that office-holding affects participation by channels other than electoral campaigning. To shed light on the channels, we describe the symbolic and substantive mechanisms used by Mapuche mayors to empower their communities.

Socio-economic issues and bank stability: The moderating role of competition

Bank stability has emerged as an area of colossal importance for economic and social well-being, especially in the aftermath of the global financial crisis of 2007–2008. Therefore, this paper examines the impact of socio-economic factors like corruption, political risk, and financial inclusion on the stability of banks. It also investigates whether bank competition interacts with socio-economic factors for the impact on bank stability. Through the use of a dynamic panel estimator and international bank data on country-level indicators spanning 139 nations from 2011 to 2021, our findings indicate that political risk and corruption impede bank stability while financial inclusion promotes it. Subsequent, investigation reveals that competition lessens the detrimental impact of corruption on bank stability while enhancing the stabilizing effects of financial inclusion and political risk. These findings have implications for regulators, government, and bank management in achieving social welfare and bank stability simultaneously.

Updated Surveillance Metrics and History of the COVID-19 Pandemic (2020-2023) in the Middle East and North Africa: Longitudinal Trend Analysis.

This study updates the COVID-19 pandemic surveillance in the Middle East and North Africa (MENA) we first conducted in 2020 with 2 additional years of data for the region. The objective of this study is to determine whether the MENA region meets the criteria for moving from a pandemic to endemic. In doing so, this study considers pandemic trends, dynamic and genomic surveillance methods, and region-specific historical context for the pandemic. These considerations continue through the World Health Organization (WHO) declaration of the end of the public health emergency for the COVID-19 pandemic on May 5, 2023. In addition to updates to traditional surveillance data and dynamic panel estimates from the original study by Post et al, this study used data on sequenced SARS-CoV-2 variants from the Global Initiative on Sharing All Influenza Data (GISAID) to identify the appearance and duration of variants of concern. We used Nextclade nomenclature to collect clade designations from sequences and Pangolin nomenclature for lineage designations of SARS-CoV-2. Finally, we conducted a 1-sided t test to determine whether regional weekly speed of COVID-19 spread was greater than an outbreak threshold of 10. We ran the test iteratively with 6 months of data from September 4, 2020, to May 12, 2023. The speed of COVID-19 spread for the region had remained below the outbreak threshold for 7 continuous months by the time of the WHO declaration. Acceleration and jerk were also low and stable. Although the 1- and 7-day persistence coefficients remained statistically significant and positive, the weekly shift parameters suggested the coefficients had most recently turned negative, meaning the clustering effect of new COVID-19 cases became even smaller in the 2 weeks around the WHO declaration. From December 2021 onward, Omicron was the predominant variant of concern in sequenced viral samples. The rolling t test of the speed of spread equal to 10 became entirely insignificant from October 2022 onward. The COVID-19 pandemic had far-reaching effects on MENA, impacting health care systems, economies, and social well-being. Although COVID-19 continues to circulate in the MENA region, the rate of transmission remained well below the threshold of an outbreak for over 1 year ahead of the WHO declaration. COVID-19 is endemic in the region and no longer reaches the threshold of the pandemic definition. Both standard and enhanced surveillance metrics confirm that the pandemic had transitioned to endemic by the time of the WHO declaration.

Pharmaceutical consumption, economic growth and life expectancy in the OECD: the application of a new causal direction from dependency algorithm and a DeepNet process

PurposeThe objective of this study is to reevaluate the correlation among pharmaceutical consumption, per capita income, and life expectancy across different age groups (at birth, middle age, and advanced age) within the OECD countries between 1998 and 2018.Design/methodology/approachWe employ a two-step methodology, utilizing two independent approaches. Firstly, we con-duct the Dumitrescu-Hurlin pairwise panel causality test, followed by Machine Learning (ML) experiments employing the Causal Direction from Dependency (D2C) Prediction algorithm and a DeepNet process, thought to deliver robust inferences with respect to the nature, sign, direction, and significance of the causal relationships revealed in the econometric procedure.FindingsOur findings reveal a two-way positive bidirectional causal relationship between GDP and total pharmaceutical sales per capita. This contradicts the conventional notion that health expenditures decrease with economic development due to general health improvements. Furthermore, we observe that GDP per capita positively correlates with life expectancy at birth, 40, and 60, consistently generating positive and statistically significant predictive values. Nonetheless, the value generated by the input life expectancy at 60 on the target income per capita is negative (−61.89%), shedding light on the asymmetric and nonlinear nature of this nexus. Finally, pharmaceutical sales per capita improve life expectancy at birth, 40, and 60, with higher magnitudes compared to those generated by the income input.Practical implicationsThese results offer valuable insights into the intricate dynamics between economic development, pharmaceutical consumption, and life expectancy, providing important implications for health policy formulation.Originality/valueVery few studies shed light on the nature and the direction of the causal relationships that operate among these indicators. Exiting from the standard procedures of cross-country regressions and panel estimations, the present manuscript strives to promote the relevance of using causality tests and Machine Learning (ML) methods on this topic. Therefore, this paper seeks to contribute to the literature in three important ways. First, this is the first study analyzing the long-run interactions among pharmaceutical consumption, per capita income, and life expectancy for the Organization for Economic Co-operation and Development (OECD) area. Second, this research contrasts with previous ones as it employs a complete causality testing framework able to depict causality flows among multiple variables (Dumitrescu-Hurlin causality tests). Third, this study displays a last competitive edge as the panel data procedures are complemented with an advanced data testing method derived from AI. Indeed, using an ML experiment (i.e. Causal Direction from Dependency, D2C and algorithm) it is believed to deliver robust inferences regarding the nature and the direction of the causality. All in all, the present paper is believed to represent a fruitful methodological research orientation. Coupled with accurate data, this seeks to complement the literature with novel evidence and inclusive knowledge on this topic. Finally, to bring accurate results, data cover the most recent and available period for 22 OECD countries: from 1998 to 2018.

Improved drinking water, healthier children? Evidence from Pakistan

Purpose One of the United Nations’ sustainable development goals is to ensure the availability of improved drinking water for everyone. In this study, we examine the association between access to improved drinking water at the district level and child nutritional outcomes in Pakistan.Design/methodology/approach We employ district-level unbalanced panel data from Pakistan from various rounds of Pakistan Social and Living Standards Measurement Surveys and Multiple Indicators Cluster Surveys compiled by the Data4Pakistan, Pakistan District Development Portal. We examine the impact of the percentage of the population in a given district with access to clean drinking water on the percentage of stunted, underweight and wasted children in the district. The analysis proceeds in two steps. In the first step, we explore the spatial distribution of improved drinking water coverage and child development outcomes across districts. In the second step, we study their relationship by employing standard panel estimation methods and controlling for district characteristics.Findings The spatial analysis reveals the large disparity among districts and provinces in terms of improved drinking water coverage and child nutrition. The estimation results indicate that there is a significant association between the accessibility of improved drinking water and child development outcomes. The effect is significant for child stunting and underweight but not for child wasting. The impact appears to be stronger in rural districts. These findings are robust to alternate empirical strategies.Originality/value This is the first such study to examine the provision of improved drinking water at the district level in relation to child developmental outcomes in a developing country context.Peer reviewThe peer review history for this article is available at: https://publons.com/publon/10.1108/IJSE-09-2023-0739

Natural resource rents and financial inclusion nexus: Evidence from Africa

A significant gap in total natural resources wealth and financial inclusion studies on the African continent stems from their impact and variation. To address these deficiencies, this study investigates the effect of total natural resource rents on financial inclusion, employing data from 27 African economies from 2004 to 2019. This study uses the most recent panel estimators, causality test and variance decomposition analysis for accuracy and reliability. Findings reveal that total natural resources wealth and economic progress significantly reduces financial inclusion, while fossil and renewable energy promote financial inclusion. Moreover, financial globalization had an insignificant outcome on financial inclusion. The causality test revealed bi-directional causation between financial inclusion in renewable energy and financial inclusion in economic progress. Again uni-directional causation from financial inclusion to fossil energy and financial inclusion to natural resources wealth. At the same time, a neutral causal effect was found from financial inclusion to financial globalization. Regarding variations, financial inclusion had the highest effect on natural resource rents. Our findings grasp new insight into financial inclusion in Africa, and policymakers are advised to support natural resources rent by directing its impact into the economy's real sector.

Changes in the cost-effectiveness of pneumococcal vaccination and of programs to increase its uptake in U.S. older adults.

Multiple factors, such as less complex U.S. adult pneumococcal recommendations that could increase vaccination rates, childhood pneumococcal vaccination indirect effects that decrease adult vaccination impact, and increased vaccine hesitancy (particularly in underserved minorities), could diminish the cost-effectiveness of programs to increase pneumococcal vaccination in older adults. Prior analyses supported the economic favorability of these programs. A Markov model compared no vaccination and current recommendations (either 20-valent pneumococcal conjugate vaccine [PCV20] alone or 15-valent pneumococcal conjugate vaccine plus the 23-valent pneumococcal polysaccharide vaccine [PCV15/PPSV23]) without or with programs to increase vaccine uptake in Black and non-Black 65-year-old cohorts. Pre-pandemic population- and serotype-specific pneumococcal disease risk and illness/vaccine costs came from U.S. Program costs were $2.19 per vaccine-eligible person and increased absolute vaccination likelihood by 7.5%. Delphi panel estimates and trial data informed vaccine effectiveness values. Analyses took a healthcare perspective, discounting at 3%/year over a lifetime time horizon. Uptake programs decreased pneumococcal disease overall. In Black cohorts, PCV20 without program cost $216,805 per quality-adjusted life year (QALY) gained compared with no vaccination; incremental cost-effectiveness was $245,546/QALY for PCV20 with program and $425,264/QALY for PCV15/PPSV23 with program. In non-Black cohorts, all strategies cost >$200,000/QALY gained. When considering the potential indirect effects from childhood vaccination, all strategies became less economically attractive. Increased vaccination with less complex strategies had negligible effects. In probabilistic sensitivity analyses, current recommendations with or without programs were unlikely to be favored at thresholds <$200,000/QALY gained. Current U.S. pneumococcal vaccination recommendations for older adults were unlikely to be economically reasonable with or without programs to increase vaccine uptake. Alternatives to current pneumococcal vaccines that include pneumococcal serotypes associated with adult disease should be considered.

Deep Learning-Based Detection and Segmentation of Damage in Solar Panels

Renewable energy can lead to a sustainable future and solar energy is one the primary sources of renewable energy. Solar energy is harvested mainly by photovoltaic plants. Though there are a large number of solar panels, the economic efficiency of solar panels is not that high in comparison to energy production from coal or nuclear matter. The main risk involved in solar plants is the high maintenance cost involved in maintaining the plants. To help reduce this issue, automated solutions using Unmanned Aerial Vehicles (UAVs) and satellite imagery are proposed. In this research work, we propose a novel deep learning architecture for the segmentation of solar plant aerial images, which not only helps in automated solar plant maintenance, but can also be used for the area estimation and extraction of solar panels from an image. Along with this, we also propose a transfer learning-based model for the efficient classification of solar panel damage. Solar panel damage classification has a lot of applications. It can be integrated into monitoring systems, raising alerts when there is severe damage or damage of a certain type. The adaptive UNet model with Atrous Spatial Pyramid Pooling (ASPP) module that performed the dilated convolutions that we proposed achieved an overall accuracy of 98% with a Mean Intersection-Over-Union (IoU) Score of 95% and took under a second to process an image. Our classification model using Visual Geometry Group 19 (VGG19) as the backbone for feature extraction has achieved a classification accuracy of 98% with an F1 score of 99%, thus detecting the five classes of damage, including undamaged solar panels, in an efficient manner.

Do surging house prices discourage fertility? Global evidence, 1870–2012

This paper examines the relationship between house prices and fertility rates during the global fertility transition. We establish an analytical framework that considers the complementary nature of children and housing, leading to the hypothesis of a negative effect of house prices on fertility when they are highly complementary. We utilize a newly published house prices dataset spanning 1870 to 2012, covering multiple countries, and employ fixed effect and dynamic panel estimations to address identification challenges including unobserved heterogeneity and dynamic effects. Results show that surging house prices discourage fertility, with a ten percent increase in real house prices associated with a reduction of 0.01 to 0.03 births per woman. These effects are comparable to the impact of increased female education. Our findings offer insights into the evolving patterns of global fertility trends, underscoring the role of increased housing costs in shaping demographic changes.

A simplified homogeneous approach for non-linear analysis of masonry infill panels under in-plane loads

This paper aims to create a unified model that effectively combines continuous 2-dimensional elements and discrete components to capture the nonlinear characteristics and failure mechanisms of solid and perforated masonry infill panels. Given that masonry infill behavior is primarily influenced by shear deformations, an equivalent model is developed by using multiple small square panels arranged diagonally and interconnected by two-component springs, encompassing axial and shear behavior at their intersections. For the sake of simplicity, the divided panels are assumed to behave elastically, with plasticity concentrated only in the axial component of the connector springs. Plastic behavior in the boundary elements was considered to involve both flexural and shear plastic hinges to provide an accurate estimation of the entire infill panel's behavior. To validate this approach, the simplified model is benchmarked against eight experimental masonry infill panels surrounded by steel or reinforced concrete frames and with or without openings. The results including global behavior and crack pattern were compared with available numerical predictions based on finite element method from the literature in addition to experimental outcomes. Ultimately, this comparison demonstrated that the homogeneous model could effectively predict the non-linear lateral behavior of the panels and accurately forecast crack patterns. Additionally, the use of unidirectional non-linear springs and the appropriate arrangement of elastic panels significantly reduced both pre-processing and analysis time.

Unlocking Desire: Exploring the Impact of Seductive Forces of Political Risk, Financial Inclusion, and Competition on Bank Stability in Emerging Markets

This research inquiry overlaps financial services inclusion and a national government's risk of political instability, competition, and banking system stability. It is the analysis of 22 emerging market countries from 2016 to 2021. The research is going to be based on GMM-System dynamic data panel estimate method and the aim is to illuminate the interplay of these factors and to detect their impact on the banking industry sustainability. The point estimates derived from the GMM-System estimation reveal that several of the main conclusions have been reached. The main point to note is that, in general, the more inclusive financial system, the more stable banking sector there will be in the world. What this finding stresses is the necessity of an inclusive financial system to strengthen banks by being a part of the ever-growing body of evidence on how financial inclusion can foster economic growth and stability. Not only does the evidence support the assumption that political unrest and financial markets have a strong relationship, but also the numbers show that this relationship is highly likely. In the case of a country where political instability is reduced, the financial sector turns out to be more viable, the study reveals. Political risk is of a great significance for financial markets and banking systems, and therefore call for political stability as a fundamental for the reliable banking system. Taken together, the finding of the study will be very useful for not only government officials but also the banking sector. The output reaffirms the fact that financial inclusion, competition and political risks are the key components for the sector stability increase. Such factors have a very important influence on the policy, regulation, and strategic decision of banking. These findings show the imperativeness of political and corporate leaders to make progress in increasing financial accessibility, allowing fair competition, and safeguarding political stability so that banking sectors may be reinforced and thus, the world's banking systems may become more resilient.Keywords: Political Risk, Financial Inclusion, Bank Stability, Emerging Economies, Competition.

Updated Surveillance Metrics and History of the COVID-19 Pandemic (2020-2023) in Latin America and the Caribbean: Longitudinal Trend Analysis.

In May 2020, the World Health Organization (WHO) declared Latin America and the Caribbean (LAC) the epicenter of the COVID-19 pandemic, with over 40% of worldwide COVID-19-related deaths at the time. This high disease burden was a result of the unique circumstances in LAC. This study aimed to (1) measure whether the pandemic was expanding or contracting in LAC when the WHO declared the end of COVID-19 as a public health emergency of international concern on May 5, 2023; (2) use dynamic and genomic surveillance methods to describe the history of the pandemic in the region and situate the window of the WHO declaration within the broader history; and (3) provide, with a focus on prevention policies, a historical context for the course of the pandemic in the region. In addition to updates of traditional surveillance data and dynamic panel estimates from the original study, we used data on sequenced SARS-CoV-2 variants from the Global Initiative on Sharing All Influenza Data (GISAID) to identify the appearance and duration of variants of concern (VOCs). We used Nextclade nomenclature to collect clade designations from sequences and Pangolin nomenclature for lineage designations of SARS-CoV-2. Additionally, we conducted a 1-sided t test for whether the regional weekly speed (rate of novel COVID-19 transmission) was greater than an outbreak threshold of 10. We ran the test iteratively with 6 months of data across the period from August 2020 to May 2023. The speed of pandemic spread for the region had remained below the outbreak threshold for 6 months by the time of the WHO declaration. Acceleration and jerk were also low and stable. Although the 1- and 7-day persistence coefficients remained statistically significant for the 120-day period ending on the week of May 5, 2023, the coefficients were relatively modest in magnitude (0.457 and 0.491, respectively). Furthermore, the shift parameters for either of the 2 most recent weeks around May 5, 2023, did not indicate any change in this clustering effect of cases on future cases. From December 2021 onward, Omicron was the predominant VOC in sequenced viral samples. The rolling t test of speed=10 became entirely insignificant from January 2023 onward. Although COVID-19 continues to circulate in LAC, surveillance data suggest COVID-19 is endemic in the region and no longer reaches the threshold of the pandemic definition. However, the region experienced a high COVID-19 burden in the early stages of the pandemic, and prevention policies should be an immediate focus in future pandemics. Ahead of vaccination development, these policies can include widespread testing of individuals and an epidemiological task force with a contact-tracing system.

The impact of ESG profile on Firm's valuation in emerging markets

Environmental, Social and Governance (ESG) factors are a critical input in emerging markets for managing risks, attracting capital, being competitive, and complying with evolving regulations. The firms prioritizing ESG are likely to drive innovation and enhance long-term value creation, making them more resilient in these dynamic markets. Therefore, a plausible link should exist between ESG and firm valuation. In this paper, we attempt to validate this link by evaluating the impact of ESG scores and ESG controversies on Tobin's Q and enterprise value to sales (EV/S). Our assessment is based on a comprehensive sample of non-financial firms across sixteen emerging markets for eleven years. Based on fixed effects panel estimations we demonstrate, in general, a positive relationship between firm value and ESG profiles. The fundamental valuation (Tobin's Q) is influenced by the lagged ESG score, while for the multiplier (EV/S), we find the current ESG score to be relevant. For the RepRisk index, we observe that ESG controversies negatively impact firm value for both fundamental and multiplier proxies. Our findings hold considerable implications for the evolving landscape of ESG compliance, particularly for firms and investors in emerging markets, as well as for the broader financial system.

The impact of cleaner energy sources, advanced technology firms, and economic expansion on ecological footprints is critical in sustainable development

The environmental degradation accompanying economic growth, despite the potential mitigating effects of technological advancements and cleaner energy sources. This study examines the critical impact of cleaner energy sources, advanced technology firms, and economic expansion on ecological footprints within the context of sustainable development, focusing on the period between 2010 and 2022. By comparing the E7 (emerging seven) and G7 (Group of Seven) economies, the research aims to delineate how these factors collectively influence environmental sustainability in both developing and developed nations. Utilizing a robust panel estimation technique, the study systematically explores the relationship between the adoption of renewable energy technologies, the growth of high-tech industries, and macroeconomic expansion, alongside their respective effects on the ecological footprint, a key indicator of environmental impact. Our statistical analysis reveals significant differences between the E7 and G7 countries. For the G7, investments in cleaner energy and technology sectors have shown a more pronounced effect in reducing ecological footprints, attributed to higher efficiency standards and greater public awareness. In contrast, the E7 countries exhibit a delayed response, owing to varying stages of economic development and technological adoption, although promising trends are emerging. Notably, the G7 demonstrates a more pronounced inclination towards financial imperialism (0.043), while the E7 is significantly influenced by green energy sources (0.258). Policy implications drawn from the findings suggest that targeted investments in green technologies and renewable energy sources, coupled with robust policies supporting economic expansion in a sustainable manner, are crucial for both groups of countries. For the E7, accelerating technology transfer and adopting stricter environmental regulations are key, while the G7 should focus on innovation and the continuous improvement of energy efficiency standards. This dual approach is essential for mitigating the environmental impacts of economic growth and steering the global economy towards a more sustainable trajectory.