Panel Regression Method Research Articles

Cultural and creative industries and local economic growth: exploring the urban channel

ABSTRACT The role of cultural and creative industries (CCIs) in driving regional growth is a topic of ongoing debate, with conflicting empirical findings. This study investigates CCIs’ impact on regional dynamics from two angles. First, it recognises heterogeneity within CCIs, including technological, symbolic and artistic forms, as well as varying levels of creativity across space. Second, it considers the influence of urbanisation on the growth potential of CCIs. Using an original regional-level database on CCIs employment, the research analyses European regions’ growth patterns in relation to different forms of CCIs. Panel and spatial regression methods are employed, and endogeneity is addressed by an instrumental variable approach. The study uncovers effects of CCIs in different urban contexts, adding insightful elements for the design of regional policies.

Unveiling the drivers of green loan disclosures: a study of financial and governance determinants

PurposeThis study aims to investigate the factors influencing Indian banks’ choice of green loan disclosure practices. The study analyzes the effect of financial and governance variables to understand the sustainable reporting (through green lending) behavior of Indian banks.Design/methodology/approachThe data on green loan disclosure has been hand-collected from the annual reports using a content analysis approach. Using the data of 26 banks for 12 years (2012–2023), the study uses the panel regression method to control for cross-sectional heterogeneity and generalized methods of the moment to address potential endogeneity issues.FindingsThe empirical results depict that larger banks with sufficient risk capital and a strong corporate governance framework demonstrate greater disclosure of green loans. However, growth opportunities and higher market value impedes the reporting of green lending.Research limitations/implicationsThe findings of the study will enhance the extant literature on sustainability disclosure by integrating the financial sector companies in the context of an emerging economy. However, future research may include nonbanking finance companies as well.Social implicationsBanks use societal deposits to invest in productive avenues, and therefore, it is paramount to understand their social and environmental consciousness while evaluating a financing proposal. This research provides a thorough understanding of the sustainable reporting of banks through the lens of green lending.Originality/valueThis research provides unique evidence on the bank-specific determinants of green loan disclosure in an emerging economy context as against the extant literature which primarily focused on sustainable reporting of nonfinancial companies.

Area-level socioeconomic status impacts healthcare visit frequency by Australian inflammatory arthritis patients: results from the Australian Rheumatology Association Database.

Individuals with inflammatory arthritis (IA) require long-term rheumatologist care for optimal outcomes. We sought to determine if socioeconomic status (SES) influences general practitioner (GP) and specialist physician visit frequency and out of pocket (OOP) visit costs. We linked data from Australian Rheumatology Association Database (ARAD) participants with rheumatoid arthritis or psoriatic arthritis to the Pharmaceutical Benefits (PBS) and Medicare Benefits Schedule (MBS) from 2011-2018. Small-area SES was approximated as quintiles of the Index of Relative Socieconomic Advantage and Disadvantage. A comorbidity index (Rx-Risk) was determined from PBS data. Analysis was performed using panel regression methods. We included 1916 ARAD participants (76.3% rheumatoid arthritis, 71.1% women, mean [SD] age 54 [12] years and disease duration 6 [4] years). Participants averaged 9.0 (95% CI 8.6, 9.4) annual GP visits and 3.9 (3.8 to 4.1) annual specialist physician visits. After adjustment for sex, age, education, remoteness and comorbidity, there was an inverse relationship between annual GP visit frequency and higher SES quintile (-0.6 [-0.9, -0.3] visits/quintile) and a direct relationship between more frequent specialist visits and higher SES (linear slope 0.3 [0.2, 0.5] visits/quintile). Average OOP costs/visit were higher for specialist physician (AUD$38.43 [37.34, 39.53] versus GP visits (AUD$7.86 [7.42, 8.31], and higher SES was associated with greater OOP cost. Higher SES patients have relatively fewer GP visits and more specialist physician visits compared with lower SES patients, suggesting lower SES patients may receive suboptimal specialist physician care. OOP costs may be a contributing factor.

Implication Of Environmental Related Cost On Performance Of Oil And Gas Companies In Nigeria

The study examined the implication of environmental cost on performance of oil and gas companies in Nigeria. The objectives of the study are to examine whether environmental cost affects return on capital employed and market value added of oil and gas companies in Nigeria. Data for this study were retrieved from reports of the companies from 2013-2017 financial years and values for the qualitative data such as environmental regulatory cost (ERC) and environmental health and safety cost (EHSC) were measured using dichotomy procedures. Values were assigned from 0-5 based on the level of disclosure using global reporting index (GRI). Having examine the content of the financial report of the companies, the analytical technique used for this study was the panel regression method. The research results indicate that there exists a relationship between environmental cost and profitability of oil and gas companies in Nigeria. The study therefore recommended amongst others that Oil and gas companies should focus reasonable attention to addressing relevant environmental issues and cost involvement disclosed in their financial report for the purpose of profit measurement.

The Impact of African Swine Fever on the Efficiency of China’s Pig Farming Industry

African Swine Fever (ASF) is a severe viral disease that has significantly impacted the pig farming industry in China. It first broke out in China in 2018 and quickly spread to multiple provinces, significantly affecting the production efficiency of the pig farming industry. This study utilized pig production data from 17 provinces in China from 2010 to 2022 and applied the Malmquist production efficiency index and panel regression methods to assess the impact of the ASF epidemic on the efficiency of the pig farming industry. The results indicated that the outbreak of ASF significantly reduced overall production efficiency, which magnified the vulnerabilities of the production system. Although there was a general decline in technological change and pure technical efficiency, the increase in scale efficiency suggested effective resource optimization by farmers under resource-constrained conditions. In light of these findings, it is recommended to strengthen biosecurity education and epidemic prevention measures in the pig farming industry and to enhance technological innovation and the application of smart technologies to improve production efficiency and disease response capabilities. Additionally, timely adjustments in farming scale and resource optimization will be key to addressing future challenges. Through these strategies, the pig farming industry can maintain stable production efficiency during future epidemics and push towards a more efficient and refined production model.

BREAKING BARRIERS: FEMALE DIRECTORS, EARNINGS MANAGEMENT, AND THE INFLUENCE OF EDUCATION AND SUSTAINABILITY REPORTING

<p><strong>Background</strong>: The role of women directors in corporate governance has received increasing attention, especially regarding their impact on earnings management. Recognizing this role is critical as companies need to increase transparency and accountability in their financial practices, while recognizing the role of sustainability.</p><p><strong>Objective</strong>: These studies aim to find out, whether female participation in the board of directors can reduce earnings management practices, by adopting different types of measurements for the female variable.</p><p><strong>Research Method</strong>: The applied methods are purposive sampling where 49 samples collected from Indonesia Stock Exchange (IDX) that consistently publishing financial and sustainability report with a timeframe of 2018-2022. Implementing data panel regression method using Stata application.</p><p><strong>Result</strong>: The result indicate that, three female director can reduce earnings management, while independent commissioner and GRI disclosure are positively related to earnings management.</p><p><strong>Originality/Novelty of Research:</strong> This studies use different kind of measurements towards female director variables, to proving applied theory are still relevant and to resolve the limitation of previous studies to find the critical effect of female directors participation to decreasing earnings management in Indonesia.</p><p> </p>

Financial inclusion and financial crisis: Arguments, stylized facts and evidence

AbstractThe literature has examined the relationship between financial inclusion and financial stability, but no studies have examined the relationship between financial inclusion and financial crisis. This study examines the effect of financial inclusion on financial crisis using data from 28 countries from 2006 to 2017. Three stylised facts were established based on real‐world observation. One, the level of financial inclusion, in terms of number of bank depositors, decreases during domestic financial crisis. Two, the level of financial inclusion, in terms of ATM penetration, does not decrease during global and domestic financial crises. Three, the level of financial inclusion, in terms of number of bank branch, decreases during global and domestic financial crises and the contraction is stronger during a domestic financial crisis. Using the panel regression, logit and probit regression estimation methods, the empirical results show that low levels of financial inclusion, measured by fewer bank depositors and fewer bank branches, increase the likelihood that a financial crisis will occur. Low levels of financial inclusion, measured by fewer bank depositors, increase the likelihood that a financial crisis will occur in low financial‐inclusion countries. In contrast, greater ATM penetration increases the likelihood that a financial crisis will occur in low financial‐inclusion countries. The interaction analyses show that all indices of financial inclusion have a joint positive impact on financial crisis, implying that high levels of financial inclusion increases the likelihood that a financial crisis will occur.

Empirical evidence on digitization enabling the transition to a green economy in China.

In the context of the new normal, enhancing digitalization to empower the transition to a green economy is a critical instrument to promote China's economic transition from virtual to real sectors. It is also a necessary approach to realize the high-quality economic development in China. Based on panel data of 282 prefecture-level and above cities in China from 2011 to 2020, the study employs panel regression, spatial metrics, and other methods to explore the impact of urban digitization on the transition to a green economy from the dimensions of direct and indirect transmission mechanism, as well as heterogeneous effects. The findings reveal that digitalization not only exerts a positive effect on the green transition but also generates significant spatial spillover effects. The influence of digitization level on green economic transition exhibits notable regional heterogeneity. Advancement in digitization can foster green economic transition by catalyzing green technological innovation. While digitalization contributes to the green transition by optimizing the structure of energy consumption, its mediating effect is relatively modest. Therefore, it is essential to fortify the supply of digital innovative technology and strengthen digitalization and green technology innovation to jointly facilitate the transition to a green economy. This necessitates the implementation of differentiated development paths for digitization-enabled green economic transition in various regions.

Pengaruh Financial Distress dan Opinion Shopping terhadap Penerimaan Opini Audit Going Concern: Studi Empiris pada Perusahaan Sektor Pertambangan Terdaftar di Bursa Efek Indonesia tahun 2018-2022

This study aims to examine the effect of financial distress, and opinion shopping on going concern audit opinion acceptance. The population in this study were all mining sector companies listed on the Indonesia Stock Exchange in 2018-2022. The sampling technique used is purposive sampling. The number of samples used in this study were 75 samples. Hypothesis testing is done by analyzing using data panel regression methods. The results showed that financial distress has a positive effect on going concern audit opinion acceptance, and opinion shopping has no effect on going concern audit opinion acceptance in mining sector companies listed on the Indonesia Stock Exchange in 2018- 2022.

The Impact of Disclosing Digitalization Information on Corporate Financial Performance

The purpose of the present study is to assess the relationship between digitalization disclosure indicators and market capitalization in the Russian market, including during the COVID-19 pandemic. The research methodology includes text analysis to evaluate various components of digital transformation (business model transformation, process transformation, domain transformation, organization transformation) and digitalization. The model was assessed using panel regression and machine learning methods. The empirical basis of the study included financial indicators of 70 Russian companies and annual reports for 2017–2021. The main results are: 1) wider disclosure of information about digitalization in the annual reports of Russian companies increased company market capitalization; 2) the transformation of processes and organizationswas highly significant for Russian companies; 3) the COVID-19 pandemic accelerated digitalization and led to a partial catch-up in the level of digitalization among less advanced companies. The results of this study can be used by investors and company management to develop more competent and comprehensive digital policies.

Geographically Weighted Panel Regression (GWPR) and Geographically and Temporally Weighted Regression (GTWR) Methods in the Influence of Factors Affecting the Minimum Wage of Each Province in Indonesia

The study compares the Geographically Weighted Panel Regression (GWPR) method and the Geographically Temporal Weighted Regression (GTWR) method using a spatial and temporal approach in the data. Both of these methods are developments by one of the Geographically Weighted Regression (GWR) methods. GWPR, which is a combination of the GWR model with panel data regression to analyze spatial variations between regions on the influence of the provincial minimum wage determination factor in Indonesia. Meanwhile, GTWR is used to analyze the presence of non-stationarity in its data if there is spatial and temporal simultaneously. In this study, both methods, namely GWPR and GTWR, will show variations in the influence of variables in each location by showing their local parameters with kernel weighting. In selecting the optimum bandwidth of the kernel weight function using cross validation (CV) with the minimum value to be used. After that, when measuring the best model of the two methods, which is GWPR and GTWR, it will be shown by the largest R2 value, RMSE and, AIC with the smallest value. From the results of the study between GWPR and GTWR, namely the GTWR method has an R2 value (93.73%) and the GWPR method has an R2 value (67.32%). Therefore, the R2 value of the GTWR method is greater than the GWPR method. The results of the study indicate that the GTWR method is a better method in handling spatial-temporal.

The Effect of Current Accounts, Savings and Time Deposits on Banking Credit: A Case Study of Regional Development Banks (RDB) in Indonesia

This study aims to examine the effect of Current Accounts, Savings, and Time Deposits on Banking Credit of Regional Development Banks (BPD) in Indonesia. The data in this study are in the form of quarterly reports from Regional Development Banks (BPD) in Indonesia. Current Accounts, Savings, and Time Deposits on Banking Credit of Regional Development Banks (BPD) in Indonesia is expected to be evident in 2019–2022. The research method used is the panel regression method. The outcomes show that current accounts, savings and time deposits influences the credit of bank BPD. R Settled 0.994461 current accounts, savings and time deposits factors influence bank credit. The Adjusted R Squared value of 0.994461 indicates that the independent variables can explain the dependent variable 99.44% of the time, while other factors not included in the model have an impact on the remaining 0.5539%. This means that 99.44% of the variable Savings and Time Deposits can predict bank credit, while the remaining 0.5539 percent is impacted by other factors not investigated in this study. This result serves as a warning to BPD banks in each province to be careful in extending credit to customers, because when credit increases, current accounts, savings and time deposits also increase. And if credit decreases, it's the other way around. This means that the higher the credit given to customers, the banking income will also increase with the help of increased current accounts, savings and time deposits. The significance and implications of the results of this research can provide an illustration that although regional banks (BPD) still have an impact on the Indonesian economy even though they only provide samples in the form of savings products.

ESG scores and stock returns during COVID-19: an empirical analysis of an emerging market

PurposeThe COVID-19 pandemic resulted in a dramatic downturn in the global stock markets. Investors look for safe stocks that can provide better risk-adjusted returns. Stocks with higher Environmental, Social, and Governance (ESG) scores can be good choices for investors. This study focuses on this argument by examining the relationship between ESG indicators and stock returns while considering financial and macroeconomic variables.Design/methodology/approachIn this study, 39 non-financial firms listed in Nifty-50, for which data is available, have been included. Panel data from 2018 to 2021 is collected to examine this relationship in the presence of COVID-19. Additionally, the panel regression method is used.FindingsThe empirical findings indicate a positive relationship between ESG scores and stock returns. This relationship holds even when the control variables like Return on Assets (ROA), Gross Domestic Product (GDP), Return on Equity (ROE), age, size, leverage of the firm, inflation, and crisis period are used in the model.Originality/valueThis study contributes by examining the linkage between ESG indicators and stock return while controlling the impact of the financial and macroeconomic variables in Indian markets, which has not been undertaken so far. Moreover, this is the first study to use the ESG score data of S&P Global, which gives more weight to the material factors of a firm.Peer reviewThe peer review history for this article is available at: https://publons.com/publon/10.1108/IJSE-10-2023-0819.

Assessing the Impact of COVID-19 on Banks’ Profitability: The Role of Size in an Emerging Economy

This work investigates the impact of the COVID-19 crisis on Brazilian banks’ profitability, and if the impact was stronger for smaller banks. Brazil was highly affected by COVID-19 crisis, has a highly concentrated banking sector, and is well known for the high technology of its financial market. We collected information from 42 banks on the quarterly financial statements available in Brazilian Central Banks during the period between January/2016 and March/2021. We ran Arellano–Bond generalized method of moments dynamic panel regression and our results confirm that the COVID-19 crisis negatively impacted the profitability of the Brazilian banks and that large banks were the most affected. Brazilian government adopted anti-crisis measures that relaxed regulations in order to decrease credit spreads. This may have alleviated the impact of the crises on small banks and also encouraged the appearance of fintech companies, which competed directly with banks.

Voluntary Disclosures and their Drivers: A Study of MDA Reports in India

The aim of this study is to examine the impact of corporate characteristics on voluntary disclosures of management discussion and analysis (MD&A) reports in India. Using a formal tone, the data was extracted from the annual reports of the top 100 listed firms available on the CMIE Prowess database for seven years (2016–2022). After excluding 23 companies from the financial and insurance sector, a panel regression method with the assistance of Gretl software was employed to investigate the relationship between the Management Discussion and Analysis Disclosure Index (MDADI) for voluntary aspects and various corporate attributes, with a total of 490 firm years of balanced observations. In India, firms follow the mandatory compliance of the MD&A reports, but voluntary disclosures are somehow those which are not much emphasized but are a good indication of firm performance and their accountability towards their stakeholders (Mayew et al., 2015). Our empirical findings reveal that profitability as a proxy to firm performance has a significant positive relationship with MD&A voluntary disclosures. Further, an insignificant association between VDS (Voluntary Disclosure Score) and the board size, presence of independent directors and firm size was found. This indicates that firm performance plays a significant role in adding more voluntary disclosures in MD&A reports. The possible reason for this could be the use of “Management Impression Strategy” in the MD&A reports, which means managers disclose more only when the firm has earned more and use impressive language to attract stakeholders. The outcomes of this research offer valuable insights for regulators, policymakers, and listed companies in India, aiding in the enhancement of MD&A reporting quality. Additionally, this study provides a roadmap for future research on MD&A reporting quality and corporate attributes in other emerging countries that have similar regulatory frameworks. This paper makes a timely and pertinent contribution to the scholarly discourse by shedding light on the relationship between MD&A disclosures and firm attributes. Its findings provide valuable insights for both academia and industry.

Impact of Health and Non-health Inputs on Health Outcomes: A Comparative Study of South Asia, Southeast Asia, BRICS and ASEAN Regions

This study assessed the impact of health and non-health factors on crude death rate, infant mortality rate and life expectancy at birth across 21 developing and emerging countries. Utilising panel regression and Z-score methods, it identified two country clusters based on the relationship between health input augmenting factors and health outcomes. Findings revealed variations in health outcomes among emerging countries like the Russian Federation, Brazil, China, and India compared to some developing countries. The study emphasised the significant role of health input augmenting factors and noted varied influences of socio-economic, environmental and health factors on health outcomes. Additionally, a notably stronger elasticity of health outcomes was observed concerning non-health determinants. JEL: I12; I13; I15

The impacts of the Ethiopian developmental state model on the competition, efficiency and profitability of banks

PurposeThis study examines the impacts of the Ethiopian developmental state model on the competition, efficiency and profitability of banks.Design/methodology/approachThe competition, efficiency and profitability of the Ethiopian bank are measured using Panzar Rose, data envelopment analysis and financial ratio. Fixed-effect panel regression methods are applied to test the direction and strength of association between the Ethiopian developmental state model and the competition, efficiency and profitability of the country's banks while controlling bank-specific market structure and macroeconomic factors.FindingsThe Ethiopian developmental state model embeds the state-directed financial system, which affects the banking industry using a range of credit allocation instruments. Of which, directed credit schemes, interest rate control and the lack of financial freedom reduce the competition and efficiency of banks. The National Bank of Ethiopia (NBE) advances to the government and the sale of Treasury bills to a captive market enhances banking competition while negatively affecting banking efficiency. Interest rate control and the lack of financial freedom lower banking profitability. Unexpectedly, directed credit schemes improve banking profitability.Research limitations/implicationsAs with any study, this one has limitations. The intra-period comparison of efficiency is based on balanced data. Future studies can use methods that can measure the efficiency of banks using unbalanced data. The computation of the yearly H-statistic is constrained by the small sample size. The use of high-frequency data for measuring competition can provide us with better insights into banking competition in Ethiopia. Furthermore, there are a number of methods for measuring banking competition, efficiency and profitability with different assumptions. Approaching the subject of this study by applying different methods will offer different insights.Practical implicationsThe contributions of this study to practice are at two levels. First, at the policy level, it enhances our understanding of the impacts of developmental state model policies, as implemented in Ethiopia, on the banking industry and therefore provides suggestions to policymakers to reform the sector's policies. Second, it offers input to the management of banks regarding the factors that impact the industry.Originality/valueThe banking industry is often studied in the context of financial liberalisation. The originality of this study lies in investigating how the competition, efficiency and profitability of banks are affected when operating in the context of significant state interventions in the industry.

Satellite-based soybean yield prediction in Argentina: A comparison between panel regression and deep learning methods

The accurate prediction of soybean yield is vital for global food market stabilization and food security. Recent advancements in remote sensing technology have significantly amplified interest in leveraging satellite-based methods for predicting crop yield. These methods offer in-season yield estimates. By utilizing this timely information, decision-makers can formulate strategic, well-informed choices that preemptively mitigate potential food price hikes, ultimately bolstering food security. While simple regression models have been widely utilized for satellite-based yield prediction, researchers have recently begun to explore the use of deep learning algorithms. This study compares the performance of panel regression and deep learning models for in-season soybean yield prediction at the Department (county-equivalent) level in Argentina. Data sources include the latest soybean land use products and MODIS bi-weekly vegetation index products. Results indicate that deep learning models significantly outperform panel regression. Deep learning Long Short-Term Memory (LSTM) models, which incorporate attention mechanism and a series of peak NDVI images, generate more accurate and time-sensitive predictions. Among competing LSTM models, the one with attention mechanism applied to the entire growing season's NDVI data yields the highest prediction accuracy, with a Root Mean Square Error (RMSE) of 505.78 kg/ha and Normalized Root Mean Square Error (NRMSE) of 0.0726. The LSTM model with attention on the three highest NDVI images attains a satisfactory prediction accuracy (RMSE = 627.28 kg/ha, NRMSE = 0.089) six weeks prior to harvest. This study presents a robust model for predicting crop yields, promoting sustainable production of soybeans and facilitating knowledgeable choices among farmers and policymakers.

Mediating Role of the Human Development Index in the Relationship between Transfer Funds on Unemployment and Income Inequality in Aceh Province, Indonesia

The transfer of funds from the central government to Aceh Province tends to increase from 2013 to 2022. However, the high transfer funds have led to a lack of regional independence in Aceh, and problems such as unemployment and income inequality still need to be fully resolved. This study aims to investigate the effect of transfer funds on unemployment and income inequality with HDI as a mediator in Aceh Province. This study uses panel data from 23 districts/cities of Aceh Province from 2011-2022. The data were processed using panel regression and path analysis methods. The findings show that transfer funds have a positive and significant effect on HDI and income inequality and a significant negative effect on unemployment. Transfer funds indirectly affect the unemployment rate and income inequality through the human development index. The Aceh Provincial Government is advised to conduct more intensive policies to reduce the unemployment rate and income inequality in Aceh Province, especially through transfer funds.

The role of debt maturity in stock price crash risk: a comparison of developing and developed Asian economies

PurposeThis study examines the impact of debt maturity structure on stock price crash risk (SPCR) in Asian economies and the moderating effect of firm age on this relationship.Design/methodology/approachThe study utilized annual data from 432 nonfinancial firms publicly listed in six Asian countries: China, Hong Kong, Japan, Singapore, Pakistan and India. The observation period covers 14 years, from 2007 to 2020. The sample was categorized into three groups: the entire sample and one group each for developing and developed Asian economies. A generalized least squares panel regression method was employed to test the research hypotheses.FindingsThe results suggest that long-term debt has a significant negative influence on SPCR in Asian economies, indicating that firms with high long-term debt experience lower future SPCR. Moreover, firm age negatively moderates this relationship, implying that older firms may experience a more pronounced reduction in SPCR due to high long-term debt. Finally, firms in developed Asian economies with high long-term debt are more effective in mitigating the risk of a significant drop in their stock prices than firms in developing Asian economies.Originality/valueThis study contributes to the literature in several ways. To the best of the researcher’s knowledge, this is the first of such efforts to investigate the relationship between debt maturity structure and crash risk in Asia. Additionally, it reveals that long-term debt influences SPCR directly and indirectly in Asia through the moderating role of firm age. Lastly, it is likely one of the first studies by a research team in Asia to compare the nonfinancial markets of developed and developing Asian countries.