Fixed Effects Panel Data Model Research Articles

Do the Islamic banks play a role in the monetary policy transmission in Pakistan? A comparative analysis with conventional banks using panel data analysis

In Pakistan, bank lending plays a critical role in economic activities due to the scarcity of stocks and bond options. Islamic banks face an extra layer of difficulty with limited open market instruments and lender of last resort facilities, as well as tough competition with conventional banks. This study analyzes the differences in bank lending by Islamic and conventional banks in transmitting monetary policy by modeling bank credit as a dependent variable while bank-specific assets, liquidity, capital and growth, inflation, and policy rates as explanatory variables. Polled OLS fixed effect panel data models are used to analyze annual data for 2009-2018. The study finds that Islamic bank credit is influenced significantly by policy rates, inflation, and growth, as well as capital and liquidity. Conventional bank credit is significantly affected by the policy rates, growth, and inflation but capital and liquidity are less correlated. This paper concluded that Islamic banks are significant in policy transmission. However, policy tools and differences in operations and contracts affect Islamic bank equity and liquidity which may suffer long-term economic participation.

The impact of digital finance development on vertical specialization: evidence from A-share listed companies in China

PurposeThis study intends to explore the relationship between digital finance and the vertical specialization of firms. The following questions are discussed: (1) As a representative new financial development model, what is the role of digital finance in the vertical specialization of firms? (2) If digital finance improves the level of vertical specialization of firms, what is the mechanism behind such improvement? (3) How does digital finance impact the vertical specialization of firms in different regions, industries, and firms?Design/methodology/approachA two-way fixed-effect model of panel data is proposed to verify the relationship between digital finance and the vertical specialization of firms. This model is constructed by matching the city-level data of digital finance with the data of China's A-share listed companies from 2011 to 2018. Meanwhile, the instrumental variable (IV) method and difference-in-difference (DID) method are adopted to deal with the endogeneity problem of the model.FindingsThe authors' study finds that digital finance has significantly improved the level of vertical specialization of firms. The result is robust under the endogeneity consideration and a series of robustness tests. After the dimensionality of the index is reduced, the depth of digital finance usage is more conducive to the improvement of the vertical specialization of firms compared with the width of digital finance coverage and the level of financial digitization. Digital finance mainly improves the level of vertical specialization of firms by reducing transaction costs and increasing the market thickness of the intermediate products. Moreover, digital finance has certain heterogeneity in promoting the vertical specialization of firms, an effect that is more significant in the eastern region, manufacturing industry and state-owned enterprises (SOEs).Research limitations/implicationsThe first limitation is the mechanism test. This research only analyzes the mechanism from transaction cost and the market thickness of the intermediate products. With the rapid development of information technology, digital finance will be further integrated into people's production and life. There will then be more mechanisms that should be explored between digital finance and the vertical specialization of firms. Another limitation is the data sample of this paper. The conclusions of this research are based only on the data of listed companies. However, in the authors' opinion, the specialization level of small and medium-sized enterprise (SMEs) should be higher. Therefore, the conclusions of this work are underestimated, which can be considered as the lower limit of digital finance for enterprise specialization.Social implicationsAs a favorable financing channel to supplement traditional financial service functions, digital finance plays a critical role in the operating efficiency of enterprises and the effective allocation of macro resources. The authors' research shows that digital finance has significantly improved the vertical specialization of firms. This conclusion provides guides to improve the production efficiency of enterprises and the quality of economic development.Originality/valueThis paper has three main contributions. (1) The relationship between financial development and the vertical specialization of firms is innovatively discussed from the perspective of digital finance, which implies that digital finance can effectively promote the level of vertical specialization of firms. (2) This paper provides new perspectives and ideas to reveal the impact mechanism of digital finance on the real economy by systematically analyzing the mechanism of digital finance on the vertical specialization of firms from the perspectives of transaction costs and financing constraints. (3) The regional differences in the development of digital finance, industry differences in the vertical specialization of firms and differences in the nature of enterprise property rights are all under consideration, which improves the effectiveness and pertinence of digital finance in promoting the vertical specialization of firms.

Spatial Analysis of Individuals Life Satisfaction in Turkey Within The Context of Socioeconomic Factors

Özet
 
 Amaç: İktisat biliminin temel argümanlarından biri, kaynakların kıt, ihtiyaçların ise sınırsız olmasıdır. Genel olarak bireylerin yaşamdan beklentilerinin yüksek olabileceği düşünülse de fizyolojik, güvenlik gibi en temel ihtiyaçlarının karşılanması dahi bireylerin yaşam memnuniyet düzeylerini arttırabilmektedir. Bir ülkede sınır komşusu olan bölgelerin sosyoekonomik yapısı benzerlik gösterdiğinden bir bölgede yaşam memnuniyet düzeyindeki değişme, bu bölgeye sınır komşusu olan bölgelerde aynı yönde değişme oluşturacaktır. Bu kapsamda çalışmada bireylerin yaşam memnuniyet düzeyinin Türkiye’nin 26 alt bölgesinin (ikinci düzey Türkiye İstatistiki Bölge Birimleri Sınıflandırması -İBBS-) sınır komşu olan bölgelerinde yayılım gösterip göstermediği ve bireylerin yaşam memnuniyetini etkileyen faktörlerin mekansal veri analiziyle belirlenmesi amaçlanmıştır. 
 
 Yöntem: Çalışmada Türkiye’nin 26 alt bölgesinde bireylerin yaşam memnuniyet düzeylerinin mekansal bağımlılığı, 2013 yılı için mekansal veri analiziyle araştırılmıştır. Türkiye İstatistik Kurumu (TÜİK) tarafından yayınlanan yaşam memnuniyeti anketi, il düzeyinde sadece 2013 yılında yapılmıştır. Bu nedenle analiz 2013 yılı için gerçekleştirilmiştir. Analizde yer alan değişkenler için 2013 yılı TÜİK ve Sosyal Güvenlik Kurumu (SGK) verileri kullanılmıştır. Analiz sonuçlarına göre mekansal regresyon modellerinden mekânsal otoregresif model çalışma için en uygun model olarak belirlenmiştir. 
 
 Bulgular: SAR model sonucuna göre bireylerin yaşam memnuniyet düzeyi sınır komşusu bölgeler arasında yayılım göstermektedir. Bireylerin yaşam memnuniyet düzeyini ortalama günlük kazanç ve bölgenin aldığı iç göç pozitif yönde etkilerken; işsizlik oranı, yüksekokul ve fakülte mezunları, malvarlığına karşı işlenen suçlar ve şiddet suçları negatif yönde etkilemektedir. Yine SAR model sonucuna göre, kişi başına gayri safi yurt içi hasıla ve tüketici fiyat endeksinin bireylerin yaşam memnuniyet düzeyine etkisi bulunmamaktadır. 
 
 Sonuç: Bir ülkede bireylerin yaşam memnuniyet düzeyinin yüksek olması, ülkenin sosyoekonomik yönden gelişmişliğinin bir göstergesi olduğu kabul edilebilir. Bu nedenle bireylerin yaşam memnuniyetini etkileyen sosyoekonomik faktörlerin belirlenmesi önem arz etmektedir. Bir ülkede bireylerin yaşam memnuniyet düzeyinin sınır komşu olan bölgelerde yayılım göstermesi ise, bölgeler arasında sosyoekonomik yönden farklılıkların giderilmesinin önemini ortaya koymaktadır. 
 
 Özgünlük: Konuyla ilgili yapılmış çalışmalarda analiz yöntemi olarak çoğunlukla lojit ve probit modeller ve sabit etkili panel veri modelleri kullanılmıştır. Mekansal veri analiz yöntemi uygulayan çalışmalara rastlanmamıştır. Yine analizde suç türleri ve bölgelerin aldığı göç oranına bağımsız değişkenler olarak yer veren Türkiye için yapılmış çalışmalara rastlanmamıştır. Bu nedenlerle çalışmanın özgünlük oluşturduğu düşünülmektedir.

Technological innovations and preexisting markets: The interaction between Airbnb and New York’s hotel and housing markets

AbstractThis paper analyzes the interaction between Airbnb and two traditional markets in New York City, long‐term rentals and hotels, to investigate whether Airbnb is a substitute to either one. Using data from InsideAirbnb, the American Community Survey (ACS), Zillow Research, and the City Planning Primary Land Use Tax Lot Output (PLUTO), we estimate three different models: (i) a fixed effect panel data model relating the number of listings to the number of hotels and socioeconomic variables; (ii) hedonic price regressions relating long‐term rents to the number of Airbnb host listings and prices; and (iii) a simultaneous equation model of supply and demand for long‐term rentals where rental supply and demand are functions of Airbnb nightly rates. We find that: (i) the numbers of host listings and guest reviews are higher in neighborhoods with higher concentration of hotels; (ii) there is a positive relationship between long‐term rents and both the number of Airbnb listings and Airbnb rates; (iii) the supply‐and‐demand simultaneous equations model shows a negative relation between the supply of properties for rent and Airbnb nightly rates; and (iv) the supply‐and‐demand simultaneous equations model shows a positive relationship between the demand for rentals and Airbnb nightly rates. These results are consistent with Airbnb being a substitute to both hotels and long‐term housing rentals.

Investor attention and the COVID-19 concept stocks in China's stock market

PurposeThis paper investigates the impact of investor attention on the COVID-19 concept stocks in China's stock market from the perspectives of the macroeconomy, the stock market and the COVID-19 pandemic.Design/methodology/approachOn the basis of controlling the time effects and individual fixed effects, this paper studies the impact of investor attention on the COVID-19 concept stocks in China's stock market through a set of fixed effect panel data models. Among them, investor attention focuses on macroeconomy, stock market and the COVID-19 pandemic, respectively, while stock indicators cover return, volatility and turnover. In addition, this paper also examines the heterogeneity influence of investor attention on the COVID-19 concept stocks from the perspective of time and stock classification.FindingsFindings indicate that the attention to macroeconomy does not have a statistically significant effect on the return, unlike the attention to stock market and COVID-19 incident. Three types of investor attention have significant positive effects on the volatility and turnover rate. During the outbreak of the domestic epidemic, the impact of investor attention was significantly higher than that during the outbreak of the epidemic overseas. A finer-grained analysis shows that the attention to stock market has significantly increased the return of preventive type and treatment type stocks, while diagnostic-related stocks have been most affected by the attention to COVID-19 incident.Research limitations/implicationsThe major limitation of this work is the construction of investor attention. Although Baidu index is widely used, investor attention can be assessed more accurately based on more unstructured data. In addition, the effect of the COVID-19 can also be investigated in a longer time domain. Further research can be combined with the dynamics of the COVID-19 pandemic to more comprehensively evaluate its impact on the stock market.Originality/valueThe research proves that investor attention plays an important role in stock pricing and provides empirical evidence on the behavioral foundations of the conceptual sector of the stock market under uncertainty. It also has practical implications for regulators and investors interested in conducting accurate asset allocation and risk assessment.

Regional differences and influencing factors of the carbon emission efficiency from public buildings in China

The rapid development of the tertiary industry has made the energy consumption of public buildings grow too fast during the operation stage, which has become a key area of energy conservation and emission reduction in China’s construction industry. This study uses the Minimum Distance to Strong effective Frontier function (MinDS) and Malmquist-Luenberger (ML) index analysis methods to measure the public building carbon emission efficiency (PBCEE) of 30 provincial-level units in China’s eight economic regions from 2010 to 2019, and analyze regional differences and evolution. Then, the influencing factors of PBCEE in different regions were analyzed using the fixed-effect panel data model. The results show that: 1) China’s PBCEE is generally low, with an average efficiency value of only 0.74, and there are great differences among regions, showing the spatial characteristics of “high in the east and low in the west.” 2) Relying on the positive impact of technological progress, the PBCEE in the eight regions increased year by year, with an annual growth rate of 1.82%. 3) The influence results and degrees of various factors on PBCEE are different in different economic zones, but increasing the proportion of electricity consumption has a certain positive effect on improving PBCEE. The same influencing factor has obvious threshold characteristics for PBCEE in different regions, so the government needs to consider the actual situation of the region when formulating carbon emission reduction policies for public buildings.

Investor psychology in the stock market: An empirical study of the impact of overconfidence on firm valuation

Behavioral theories suggest that overconfident investors overestimate the quality of their information and underestimate risk. They have a high demand for risky assets and require a lower risk premium, causing asset prices to rise and leading to overvaluation. We investigate how overconfidence affects firm valuation in Saudi Arabia's emerging stock market. We used 4004 firm-quarter observations. To ensure that our results are robust to unobserved firm-specific heterogeneity and endogeneity issues, we used the fixed-effects panel data model and the dynamic panel data model. The findings show that overconfidence positively and significantly affects firm valuation. Results remain robust when using various overconfidence proxies and when replacing the different econometric models. This study has important implications for academics, investors, and regulators. Hopefully, it will make investors more aware of the impact of their psychology on asset pricing; thus, increasing the rationality of their stock market decision making for improved market efficiency.

City spatial structure and smart city innovation: the case of China

PurposeThis study aims to analyze the relevance of the city spatial structure for smart city innovation from the perspective of agglomeration externalities, and discusses whether there is heterogeneity in innovation across different geographical areas and population scales of cities.Design/methodology/approachThe authors construct the centralization and concentration indexes to conceptualize the city spatial structure of 286 cities (prefecture-level) in China based on the LandScan Global Population Dataset from 2001 to 2016. A fixed-effects panel data model is employed to analyze the relationship between the spatial structure and the innovation ability of smart cities; the results were validated through robustness tests and heterogeneity analyses.FindingsThe study found that the more concentrated and more evenly the distribution of urban population, namely the more city spatial structure tends to be weak-monocentricity, the higher the level of innovation in smart cities. The relevance of the weak-monocentricity structure and smart city innovation varies significantly depending on their geographical location and the size of the city. This result is more applicable to cities in the eastern and central regions, as well as to cities with smaller populations.Originality/valueThe adjustment and optimization of the city spatial structure is important for enhancing smart city construction. Unlike previous studies, which mostly use a single dimension of “the proportion of population in sub-centres to the population of all central areas” to measure city spatial structure, the authors employed the spatial centralization and spatial concentration. It is hoped that this study can guide smart city construction from the perspective of the development model of city spatial structure.

Does climate help modeling COVID-19 risk and to what extent?

A growing number of studies suggest that climate may impact the spread of COVID-19. This hypothesis is supported by data from similar viral contagions, such as SARS and the 1918 Flu Pandemic, and corroborated by US influenza data. However, the extent to which climate may affect COVID-19 transmission rates and help modeling COVID-19 risk is still not well understood. This study demonstrates that such an understanding is attainable through the development of regression models that verify how climate contributes to modeling COVID-19 transmission, and the use of feature importance techniques that assess the relative weight of meteorological variables compared to epidemiological, socioeconomic, environmental, and global health factors. The ensuing results show that meteorological factors play a key role in regression models of COVID-19 risk, with ultraviolet radiation (UV) as the main driver. These results are corroborated by statistical correlation analyses and a panel data fixed-effect model confirming that UV radiation coefficients are significantly negatively correlated with COVID-19 transmission rates.

Do Globalization, Technology Adoption and Economic Development Influence Income Inequality in Developing Asian Nations?

Currently, income inequality has become an international issue that needs to be overcome and also requires the attention of researchers and policymakers. Hence, this study is an attempt to explore the impact of globalization, technology adoption, and economic development on income inequality. For this purpose, 20 years of large-scale panel data over the period from 2001 to 2020 for ten emerging Asian nations (Iran, Jordan, Iraq, Laos, Pakistan, Bangladesh, Sri Lanka, Thailand, Indonesia, and the Philippines) is mined from the World Bank database and KOF globalization index. In order to inspect the empirical relationship among the selected variables, the panel data fixed effects model (FEM) along with the robust standard error is employed. The results indicate that globalization, technology adoption, and economic development have a negative linkage with income inequality, which means these factors play a significant role in removing the income inequality in developing countries. This study provides insight for policymakers while developing policies regarding income inequality elimination in the country.

Investment in roads and traffic safety: linked to economic development? A European comparison

This study analyzes how economic resources invested in roads may affect mortality, depending on the level of economic development of a country. To this end, 23 European countries were classified into two groups—high-income countries and low-income countries—according to their average Gross Domestic Product (GDP) per capita over the period 1998–2016. The economic resources are considered through the investment in construction and the maintenance expenditure. Further variables are included to control for several factors related to the infrastructure, socioeconomics, legislation, and meteorology. Fixed-effects panel data models were built separately for the interurban road network of each group of countries. These models also capture the international inequalities within each group and the country-specific national trend for the study period. The main results indicate a reduction effect on the fatality rate of road maintenance expenditure (in both groups), and of the investment in construction (in the low-income countries). Other variables—such as proportion of motorways, motorization rate, unemployment rate, GDP per capita, alcohol consumption, Demerit Point System, and mean annual precipitation—showed statistically significant results as well. Finally, the country-specific fixed effects and the country-specific trend were mapped geographically, to better reflect national conditions for achieving lower fatality rates in the high-income countries, and greater progress in reducing fatalities in the low-income countries. In the end, this study provides evidence to policy-makers that can help to achieve a safer and more sustainable transport system, namely, how to tackle an ongoing major problem—traffic-related deaths—when attending and allocating the economic resources that road infrastructure needs.

Research on the interactive response relationship between thermal power carbon emission and industrial structure in Western China.

The thermal power industry takes the important social responsibility of energy conservation and environmental protection. The carbon emissions made by the thermal power industry are affected by the industrial structure. In this paper, the carbon emission of thermal power generation is divided into three links: energy combustion, desulfurization process, and power transportation. The total carbon emission of thermal power in 11 provinces in western China from 2000 to 2017 is calculated. Combined with industrial reform, this paper constructs a panel data fixed effect model to systematically analyze the interactive response relationship between thermal power carbon emission and industrial structure in the western region. The research shows that due to the continuous expansion of hydropower, wind power, and other new energy power generation scale and the improvement of energy efficiency in the western region, the growth trend of thermal power carbon emission has slowed down since 2010. The industrial development pattern is the main driving force of regional economic development, and the secondary industry in the western region is the main driving factor of thermal power carbon emission. High quality economic development in the western region can be promoted through technological upgrading, new energy development, and industrial multi-mode operation.

Do Cities Improve Our Health Status? A State-Level Analysis in India

While several cross-country level studies suggest urbanization increases health outcomes; national-level studies are missing. On the other hand, India is experiencing a very low level of urbanization due to policy failures. In this context, this study assesses the impact of urbanization on health outcomes in Indian states from the period of 1991 to 2011. Urbanization is measured by the total urban population and percentage of urban population as different states are having a different level of urbanization. Health outcomes are measured by total fertility rate, infant mortality rate, and life expectancy at birth. The static panel data models such as fixed-effect and random-effect panel data models suggest that the total urban population and the percentage of the urban population have a positive effect on life expectancy at birth and have a negative effect on the infant mortality rate and total fertility rate. Among the control variables, the percentage of urban households having access to electricity, urban monthly per capita consumption expenditure, and per capita net state domestic product has also had a similar effect on the health outcomes. Other important variables such as rural to urban migration, literacy rate, poverty rate, access to safe drinking water, labor force participation rate, and the extent of inequality also play an important role in increasing health outcomes. We also checked the robustness of our results by using the instrumental variable generalized method of moments. Our results support the Theory of Demographic Transition and suggest that Indian policymakers must support increasing the urbanization rate for achieving higher health outcomes. However, proper management of urbanization by providing basic services to urban dwellers is also very important in this regard.

Connection between corruption and homicide rate: an empirical evaluationfrom Latin America

This article investigates the impacts of corruption on total homicide rates and considers random-effect, fixed-effect, and pooled panel data models. The approach shows the impact of the Corruption Perception Index (CPI) proposed by the website “Transparency International” on homicide rates in Latin American countries in the period 2010-2018. In this context, the contribution of this research is to evaluate the impact of corruption on homicide rates, as it is an approach little explored in the literature. Based on different empirical models, the results support the hypothesis that acts of corruption affect homicide rates, even controlling the results for other variables associated with socioeconomic aspects. In a way, there is empirical evidence that the greater the presence of corruption in society, the higher the homicide rate.

Investigation on Heterogeneous Influence of Government Subsidies on Pollution Reduction of Power Companies and Its Influencing Mechanism

This study aims to investigate whether the subsidies promote pollution reduction or not by taking the power companies in China as a case study. So, we built a fixed-effects panel data model first, which is then used to verify the influence of government subsidies on pollution reduction in power companies. Additionally, how the subsidy influencing mechanism would work is also investigated. Results find that subsidies can significantly reduce power companies’ pollution, especially sulfur dioxide emissions and soot. At the same time, the result also showed that the government subsidies could encourage power companies to cut emissions by taking measures like end-of-pipe control and green innovation. Also, from the perspective of heterogeneity, government subsidies have a better effect on the regions with stronger environmental regulations, less economically developed regions, big-scale companies, and companies with low slack.

ANALYSIS OF INFLATION CONVERGENCE IN THE ECONOMIC COMMUNITY OF WEST AFRICAN STATES (ECOWAS) ZONE (1987-2021)

This study examines the convergence of inflation (country annual average inflation rate) through it determinants vis-?-vis the set convergence criteria in the Economic Community of West African States during the period 1987-2020. The study adopted ex-post factor design in order to answer the research questions. The study undertook unit root test employing Levin, Lin, and Chu (LLC) panel unit root method to check the stationarity of the variables, Auto Regressive Distributed Lag (ARDL) model and Error Correction Model (ECM) to determine whether or not they are co-integrated and a dynamic fixed effect panel data model covering 15 countries over the period under review. The study found that while West African Economic Monetary Union (WAEMU) countries inflation rates fall below the threshold, West African Monetary Zone (WAMZ) inflation rates are beyond the ECOWAS inflation convergence rate of less than or equal to 5 percent, that cross?country differences in inflation rates are attributed to the variation of the output gap, the increase in liquidity, the variation of exchange and interest rates, and the persistent increase in the price level. In the view of targeting the five percent (5 %) percent convergence criterion, the study recommended that Changes of traditional country monetary approaches to a supra-national monetary authority that compels compliance to a regional monetary and inflation targets, stimulation of economic growth, lowering of interest rates as well as adoption of a strong and efficient exchange rate mechanism becomes imperative for the ECOWAS member states

World Heritage Site inscription and city tourism attractiveness on national holidays: new evidence with migration big data from China

ABSTRACT World Heritage Site (WHS) inscription has been considered as a certification of tourism quality since it is designated to properties with outstanding universal value. While it is hypothesised that the title can raise tourism attractiveness through signalling tourism quality, empirical evidence remains highly mixed. This paper tries to identify the causal effect by using unique daily city-pair tourist flow intensities from Tencent migration big data on two Chinese national holidays between 2015 and 2019 and constructing multi-dimensional fixed effects panel data models. We find that the WHS inscription does raise city tourism attractiveness. One WHS increases tourist inflow intensity by at least 6.7% up to around 10%. The tourism-enhancing effect is consistent under many robustness checks and displays some notable heterogeneity effects in terms of holiday types, days within each holiday and high-speed rail connections. These results suggest that WHS inscription could be a valid tourism quality signal used by tourism administrations to enhance city tourism attractiveness.

Influence of Economic and Financial Openness in Urban Agglomerations of Major Bay Areas

ABSTRACT This paper examines how four indicators of economic/financial openness, namely, trade openness, actual tariff rate, financial openness, and investment openness have shaped the world’s four major bay area’s urban agglomerations. The study considers four key bay areas, New York, Tokyo, San Francisco and Guangdong-Hong Kong-Macao, over the period 2005–2018. Using the panel data fixed effect model analysis, our study finds that: the interaction of comprehensive openness, investment openness, trade openness and comprehensive openness plays a positive role in economic growth, while the actual tariff rate and financial openness play a negative role. In the long run, each bay area should expand their opening-up to the outside world and promote economic growth.

Relationship between the Cost of Capital and Environmental, Social, and Governance Scores: Evidence from Latin America

Environmental, social, and governance (ESG) scores play a pivotal role in the strategic design of firms. The literature has demonstrated the importance of sustainability issues in the financial performance of firms around the world. In particular, understanding the relationship between sustainability and the cost of capital is crucial for determining financial strategy and decision making. We identify an opportunity in the literature to analyze this relationship within Latin America (LatAm) firms. Thus, this study analyzes the relationship between ESG scores with the cost of capital of firms with headquarters in LatAm using a data set that includes 606 observations corresponding to information about 202 firms from 2017 to 2019. To conduct our analysis, two fixed effects panel data models were estimated. We model this relationship by taking ESG scores and each of its ESG Pillar scores—i.e., Environmental, Social, and Governance pillar scores—as independent variables and analyzing how they affect the cost of capital. According to the results, there is an inverse effect relationship between ESG scores and the cost of capital. Additionally, we did not find a relationship between the Social Pillar score and the Environmental Pillar score with the cost of capital. By contrast, the Governance Pillar score shows a negative relationship with the cost of capital. This indicates that the increase in transparency about internal processes and governance entities can be an essential driver of value creation for firms and higher financing confidence in LatAm firms. This study represents a breakthrough in explaining the impact of ESG scores on the cost of capital in LatAm. Ultimately, the current study presents the potential for further research in this field.

Exploring the effect of the primary care health workers number on infectious diarrhea morbidity and where the health resources should go

We aimed to explore the association between the number of primary healthcare workers and infectious diarrhea morbidity at community levels and to provide evidence-based implications for optimizing primary healthcare manpower resource allocations. We collected annual infectious diarrhea morbidity and relevant data of 4321 communities in Sichuan Province, China, from 2017 to 2019. Global and local Moran’s I were calculated to detect the spatial clustering of infectious diarrhea morbidity and to identify areas where increased primary healthcare manpower resources should be allocated. The spatial lag fixed effects panel data model was adopted to explore the association between the number of primary healthcare workers per 1000 residents and infectious diarrhea morbidity. Significantly high–high and low–low clusters of infectious diarrhea cases were found to be mainly distributed in underdeveloped and developed areas during the studied period years, respectively. The infectious diarrhea morbidity was found to be statistically negatively associated with the number of primary healthcare workers per 1000 residents with a coefficient of − 0.172, indicating that a 0.172 reduction of infectious diarrhea morbidity (1/10,000) was associated with doubled amounts of primary healthcare workers per 1000 residents. Our findings highlighted the role of primary healthcare in the process of infectious diarrhea prevention and control, and implied that constant efforts should be addressed to facilitate infectious diarrhea prevention and control, especially in the underdeveloped areas.