Fixed Effects Panel Data Model Research Articles

Does eco-innovation foster or hinder environmental performance? Recent evidence from Europe

ABSTRACT This study investigates the impact of country-level eco-innovation policies on the environmental performance of European firms. As different industries are expected to produce more pollution, the study then explores the impact on the firms operating in sensitive industries. We use fixed effects panel data models to examine 1,098 firms listed in 22 European countries from 2010–2018. Our results indicate that country-level eco-innovative policies provide an encouraging environment for European firms to adopt environment-friendly practices. Eco-innovation policies help firms achieve CO2 targets and mitigate climate change which supports the product stewardship theory. Our results also suggest that larger, more profitable, and low debt-financed European firms have better environmental performances. We also find a moderating impact of industry sensitivity and make an intriguing discovery that country-level eco-innovation policies hinder the environmental efforts of the firms operating in sensitive European industries. These results are robust to different proxies of eco-innovation and endogeneity issues due to reverse causality.

Spatial–Temporal Characteristics and Driving Mechanisms of Rural Industrial Integration in China

The scientific evaluation of the development of rural industrial integration is of great significance to understanding the changes occurring in the industrial structure of China’s agricultural sector. Combined with the practical problems related to the development of China’s rural industrial integration on the basis of four dimensions, i.e., agricultural industrial chain extension, agricultural multifunctionality, agricultural service industry integration development and the economic effect of rural industrial integration, the level of China’s rural industrial integration development is calculated for the period from 2008 to 2020 by means of the entropy method, and its spatial–temporal evolution characteristics and the regional heterogeneity of its driving factors are discussed on the basis of kernel density estimation, hotspot analysis and a fixed effect panel data model. The results showed the following: (1) From 2008 to 2020, the level of rural industrial integration development in 31 provinces in China improved to varying degrees. The growth rate of agricultural service industry integration was the highest, while the economic effect of rural industrial integration was second; the growth rate of the agricultural industrial chain extension was the lowest, and agricultural multifunctionality exhibited a fluctuating upward trend, peaking in 2017. In terms of spatial distribution, the representative provinces and cities with high and low levels of each dimension were different. (2) Rural industrial integration development in China was characterized by a regional imbalance, with polarization in the central and western regions. In terms of spatial distribution, an “east–middle–west” ladder pattern was obvious. The hotspots were mainly concentrated in the southeast region, and they showed a gradually expanding trend, while the coldspots were mainly concentrated in the northwest region, and they showed a trend of gradually decreasing size. (3) In terms of driving factors, the urbanization level, rural human capital, rural transportation facilities, rural ecological environment, intensity of financial support for agriculture and rural digitalization had significantly positive effects, while the degree of industrial upgrade had a significantly negative effect. Each driving factor had different effects on the rural industrial integration development in the eastern, central and western regions.

Research on the Coupling of Financial Technology to Green Venture Capital Driving and the Development of Two Systems

In view of the drive of financial technology to green venture capital and the coupling of the development of the two systems, first, based on the data of 31 provinces (cities) in China from 2014 to 2019, a fixed effect panel data model is built to empirically analyze the relationship between financial technology and green venture capital, and then a coordination model of the coupling degree of the two systems is built to analyze from a macro perspective. The results show that the advantages of financial science and technology are consistent with the bottleneck of green venture capital. The development of green policy, education level and innovation atmosphere will help to provide a good environment for the development of green venture capital; Industrial development has crowding out effect on green venture capital; China's financial technology and green venture capital have been in an antagonistic coupling state for a long time, and the long-term lagging development of financial technology is an important factor restricting the improvement of the coupling degree of the two systems; The coupling degree of the three regions and two systems in China is increasing year by year, but the coupling degree difference between regions is increasing. Therefore, it is proposed to optimize the development environment of green venture capital from various aspects, improve the development level of financial science and technology in a multi-pronged manner, and promote the coordinated and high-quality development of the two systems.

Beijing Blue: Impact of the 2008 Olympic Games and 2014 APEC Summit on Air Quality.

This paper examines the effects of interventions to reduce air pollution during two international events on air quality in Beijing and its neighbor cities. Air quality data were gathered from China's Ministry of Environmental Protection, meteorological data from the China Meteorological Administration and economic data from the China Statistical Yearbook. The paper uses fixed-effect panel data models to empirically evaluate air quality improvement in Beijing and other affected cities before, during, and after the 2008 Olympic Games and the 2014 Asia-Pacific Economic Cooperation summit. Results show substantial improvement in air quality in Beijing and neighboring cities during the two events. However, some of the air quality improvement achieved reverted within a year after the games and within a week after the summit. Furthermore, the improvement achieved during the summit completely reverted and air quality deteriorated severely five days after the summit. It is also found that air quality in China, at least in the cities included in this study, gradually improved over the past 15 years or so. The findings suggest that sustainable interventions and incentive-based programs to reduce emissions from industry production and traffic are the key to maintaining the air pollution reduction achieved during the events.

How Does Environmental Data from ESG Concept Affect Stock Returns: Case of the European Union and US Capital Markets

This article examines the environmental, social, and governance (ESG) performance of firms, with a focus on the environmental pillar of the ESG concept. It is believed that the price of equities as well as sector-specific characteristics may be affected by ESG data. It also contributes to the argument that environmental performance and governance quality are related. The purpose of this paper is to statistically validate the separated environmental data from the ESG concept and investigate its impact on the equity price in the EU and the United States. Using simple linear regressions and a fixed effect panel data model, the association between environmental score and governance score, as well as equity price and environmental score, was estimated. This study examines the 500 largest US corporations comprising the S&P 500 index (S&P) and the 600 largest EU companies comprising the STOXX Europe 600 index (STOXX) (SXXP). This article analyzes ESG statistics for the period 2015–2020. The results indicate that a higher government score has a favorable effect on environmental pledges and that changes in stock price depend in part on environmental data. The novel contribution of this paper is that the results suggest a sector-specific contribution to the model, and it would be fascinating to analyze sector disparities and their ESG-related policies in greater detail. Doi: 10.28991/ESJ-2023-07-02-08 Full Text: PDF

Linking inventory management and financial performance of manufacturing industry companies

Purpose- Investments in inventories have a significant role in manufacturing companies’ operating cycles. The rapid conversion of inventories into sales and eventually the creation of profits lead to financial performance. In the study, we examine the effect of various types of inventories held by the manufacturing companies on profitability. Methodology- We use the real sector statistics published by the Central Bank of the Republic of Turkey. In this context, we analyse the data set of 86 sub-sectors for the period from 2009 to 2021 by using the fixed effects panel data model. While gross, operating and net profit margins are dependent variables in order to examine the effect of inventory management in various levels, types of inventories relative to sales are used as independent variables in the models. Other than inventories, fixed assets turnover and manufacturing industry growth rates are included as control variables in the models. Findings- We find that there is not a statistically significant relationship between operating profit margin and inventories other than raw materials. However, finished goods and merhandise inventories are negatively related to net profit margin. None of the inventory types are statistically related to gross profit margin. We obtain a negative relationship between profitability ratios and manufacturing industry growth rate as a control variable. Conclusion- We conclude that the rapid conversion of finished goods and merchandise inventories into sales contributes to net profits of the manufacturing industry companies. However, holding periods of raw materials and work-in-process inventories do not have significant relationships with net profitability. Furthermore, we result that inventories are related to profit margin not at the level of gross or operating profit, rather at the level of net profitability. Accordingly, manufacturing companies should be more cautious about the holding periods of finished goods and merchandise inventories rather than of raw materials and work-in-process inventories. Findings indicate that profit margins of manufacturing companies decrease –probably due to competition– during economic upturns. Keywords: inventory management, manufacturing industry, profitability, working capital JEL Codes: G30, G32

Governmental anti-pandemic policies, vaccination, population mobility, Twitter narratives, and the spread of COVID-19: Evidence from the European Union countries.

We provide large-scale empirical evidence on the effects of multiple governmental regulatory and health policies, vaccination, population mobility, and COVID-19-related Twitter narratives on the spread of a new coronavirus infection. Using multiple-level fixed effects panel data model with weekly data for 27 European Union countries in the period of March 2020-June 2021, we show that governmental response policies were effective both in reducing the number of COVID-19 infection cases and deaths from it, particularly, in the countries with higher level of rule of law. Vaccination expectedly helped to decrease the number of virus cases. Reductions in population mobility in public places and workplaces were also powerful in fighting the pandemic. Next, we identify four core pandemic-related Twitter narratives: governmental response policies, people's sad feelings during the pandemic, vaccination, and pandemic-related international politics. We find that sad feelings' narrative helped to combat the virus spread in EU countries. Our findings also reveal that while in countries with high rule of law international politics' narrative helped to reduce the virus spread, in countries with low rule of law the effect was strictly the opposite. The latter finding suggests that trust in politicians played an important role in confronting the pandemic.

TRENDS IN ENERGY CONSUMPTION AND EMISSIONS IN BRICS: ANALYZING THE DATA AND THE FACTORS AFFECTING ENERGY EFFICIENCY

There has been growing awareness about global warming and sustainable development, especially because of the dependence on non-renewable energy resources and its effect on emissions. This paper analyses the trends in energy consumption and CO2 emissions in BRICS nations for the period 2000-2020. Data shows that though there has been a rise in both energy consumption and emissions, the inter-country trends are quite different after population differences have been included. Therefore per capita trends are equally important because countries with large population need more energy resources to meet the growing needs of people. Analysis of trends in energy intensity and emission intensity shows both to be declining, thereby indicating a move towards greater energy efficiency. A panel data fixed effects model is used to estimate the effect of various factors on the energy and emission intensities. Results show that GCF has a negative relation with both intensities, while the effect of population is positive. Paris Agreement dummy variable shows that average intensities were lower after the implementation of the Paris Climate Accord.

Investigating The Determinants of Islamic Bank’s Profitability: A Cross Countries Analysis

The measurement of bank profitability has an essential role in the banking sector’s success and is an indicator for predicting financial distress. This study aims to look at the determinants of the profitability of Islamic banks by including the bank’s internal and macroeconomic variables. The study focuses on Islamic banking in 10 countries with the most prominent Islamic finance sector during the 4th quarterly data period from 2016 to the 4th quarter of 2021. The data analysis method in this study uses panel data fixed effect model analysis. The results showed that the bank’s internal variables, namely bank size, capital adequacy, liquidity, and banking stability, are important factors that affect profitability. Interesting findings show that increased financial inclusion variables and labor productivity can encourage high profitability growth. Meanwhile, GDP and inflation also affect banking performance from the macro sector. The study implies that Islamic bank needs to manage the internal financial condition properly to achieve and maintain the performance. In addition, to increase the performance the bank needs to heighten the human resources capacity while the financial authorities are required to issue the policies to support the development of Islamic banks.

Does Agricultural Credit Input Promote Agricultural Green Total Factor Productivity? Evidence from Spatial Panel Data of 30 Provinces in China.

Improving agricultural green total factor productivity is crucial to promoting high-quality agricultural development. This paper selects the panel data of 30 provinces in China from 2009 to 2020 and uses the super-efficiency SBM model with undesirable outputs to measure the agricultural green total factor productivity of all regions in China. On this basis, this paper uses the panel data fixed-effect model and spatial Durbin model to empirically discuss the impact of agricultural credit input on agricultural green total factor productivity and its spatial spillover effect. The main conclusions are as follows: First, from 2009 to 2020, the average values of agricultural green total factor productivity in national, eastern, central, and western regions are 0.8909, 0.9977, 0.9231, and 0.8068, respectively, and the agricultural green total factor productivity needs to be further improved. Second, the agricultural green total factor productivity presents a significant and positive spatial correlation, and the spatial distribution of agricultural green total factor productivity is not random and irregular. Third, agricultural credit input can significantly promote agricultural green total factor productivity in the local region, but it hinders the improvement of agricultural green total factor productivity in the adjacent regions. Fourth, the impact of agricultural credit input on the agricultural green total factor productivity and its spillover effect has a significant regional heterogeneity. This paper believes that paying attention to the spatial spillover effect of agricultural total factor productivity, optimizing the structure and scale of agricultural credit input, and formulating reasonable agricultural credit policies can improve agricultural green total factor productivity.

Homogenous or heterogeneous? Demand effect of reviewer similarity in online video website

PurposeNowadays, online platforms which provide products or services try to implement their homegrown communities to facilitate users' social interactions. Reviewers' activities in these communities can reflect their interests. Based on the theory of homophily, the authors aim to explore the impacts of the reviewer preference similarity and opinion similarity on the rate of product diffusion.Design/methodology/approachFirst, the authors construct reviewer similarity network based on their common interests and propose typical network metrics to measure reviewer preference similarity. Second, the authors measure reviewer opinion similarity with natural language processing. Finally, based on a panel data from an online video platform in China, both the fixed-effect and random-effect panel data models are constructed.FindingsThe authors find that reviewer preference similarity has a positive effect on the product diffusion, whereas reviewer opinion similarity has a negative effect on the diffusion. Furthermore, temporal distance moderates the relationship between reviewer similarity and the product diffusion. As a double-edged sword, review preference similarity hinders product diffusion in the initial phase, whereas benefits it in the later phase. Reviewer opinion similarity is always detrimental to product diffusion, especially in the initial phase.Originality/valueThis paper extends the understanding of homophily from the micro peer level to the group level by constructing reviewers' similarity network and highlights the important role of reviewer preference similarity and opinion similarity in product diffusion. The results also provide important insights for managers to design and implement diversity strategies for better product adoption in the community context.

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.