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This study aims to investigate the spatial distribution of housing prices and identify the affecting factors (independent variable) on the cost of residential units (dependent variable).

The method of the present study is descriptive-analytical and has an applied purpose. The used statistical population in this study is the residential units’ price in Tehran in 2021. For this purpose, the average per square meter of residential units in the city neighborhoods was entered in the geographical information system. Two techniques of ordinary least squares regression and geographically weighted regression have been used to analyze housing prices and modeling. Then, the results of the ordinary least squares regression and geographically weighted regression models were compared by using the housing price interpolation map predicted in each model and the accurate housing price interpolation map.

Based on the results, the ordinary least squares regression model has poorly modeled housing prices in the study area. The results of the geographically weighted regression model show that the variables (access rate to sports fields, distance from gas station and water station) have a direct and significant effect. Still, the variable (distance from fault) has a non-significant impact on increasing housing prices at a city level. In addition, to identify the affecting variables of housing prices, the results confirm the desirability of the geographically weighted regression technique in terms of accuracy compared to the ordinary least squares regression technique in explaining housing prices. The results of this study indicate that the housing prices in Tehran are affected by the access level to urban services and facilities.

Identifying factors affecting housing prices helps create sustainable housing in Tehran. Building sustainable housing represents spending less energy during the construction process together with the utilization phase, which ultimately provides housing at an acceptable price for all income deciles. In housing construction, the more you consider the sustainable housing principles, the more sustainable housing you provide and you take a step toward sustainable development. Therefore, sustainable housing is an important planning factor for local authorities and developers. As a result, it is necessary to institutionalize an integrated vision based on the concepts of sustainable development in the field of housing in the Tehran metropolis.

While much of the literature testing for shirking by professional athletes have used performance metrics, some works have quantified shirking in dollar terms by comparing salary to estimated marginal revenue product (MRP). However, Ordinary Least Squares (OLS) approaches to measuring shirking by comparing salary to MRP have an endogeneity problem, as salary and contract length are determined simultaneously. We test for shirking in Major League Baseball (MLB) using an MRP approach, addressing this potential endogeneity.

This paper uses instrumental variables regression to address potential endogeneity using MLB season-level player and team data from 2010 to 2017.

Using OLS regression, the impact of an additional year of guaranteed contract on shirking is estimated at approximately $1m in 2010 US dollars, and the impact of having a long-term contract is estimated at $5m, estimates comparable to those in the literature. Using instrumental variables regression, these impacts increase to $1.6m and over $9m in 2010 dollars.

Given large, causal shirking estimates, profit maximizing sports organizations should take caution when negotiating long-term contracts. These findings also have important implications for other labor market settings where workers feel job security.

To our knowledge, this is the first work testing for shirking in sports using an MRP approach which uses instrumental variables regression to address potential endogeneity.

This article investigates the determinants of cross-section variation of initial public offerings' (IPOs) first-day returns in a sample of 710 issues across seven emerging markets between 2013 and 2017.

Ordinary least squares regression (OLS) and the semi-parametric quantile regression (QR) technique are employed. QR enables to analyse beyond the explanatory variables' relative mean effect at various points in the endogenous variable distribution. Furthermore, parameter estimates under QR are robust to the existence of outliers and long tails in the data distribution.

Underpricing varies across countries with an average of 78%. According to the OLS results, independent variables explain 26% of the variation of IPOs' first-day returns. Findings show that employing QR is important, given the non-normality of the data and because each quantile is associated with a different effect of explanatory variables.

In addition to firm-specific, market-specific and issue-specific factors, the paper extends IPOs' underpricing literature through studying the impact of country-specific characteristics, largely neglected by literature, on IPO underpricing.

The purpose of this paper is to investigate whether banks’ environmental, social and governance (ESG) initiatives increase or decrease banks’ efficiency.

The sample used includes all listed banks in Saudi Arabia over the years 2016–2021. The authors performed different methods, including data envelopment analysis (DEA), ordinary least squares (OLS) and quantile regressions.

The OLS regression results show a negative linkage between ESG and banks’ efficiency. Further, the quantile regression analysis indicates that the ESG effect on banks' efficiency is negative across different quantiles. However, the DEA method shows that the DEA-generated scores for Banks’ efficiency are higher for ESG-adjusted scores in comparison to efficiency scores without incorporating ESG. Further, the comparison of the DEA-generated efficiency scores, over the sample period, of adjusted ESG banks still suffers from decreasing in their efficiency over the years. Concerning existing theory, the results are consistent with the stakeholders and the resource-based theories postulating that banks' ESG practices are ethical commitments and enable firms to gain competitive advantage and increase their reputation among stakeholders.

The findings of this study offer important implications for regulators and bankers. Policymakers and bank regulators should make collective efforts to encourage financial institutions to adopt green finance initiatives to create an efficient financial system capable of counteracting risks from the external environment and stimulating economic growth. Banks’ managers should be aware that ESG initiatives serve society and the environment and offer a positive influence on banks’ efficiency.

To the best of the authors’ knowledge, this is the first study to explore the influence of ESG activities on banks' efficiency using DEA for banks in Saudi Arabia.

The study aims to examine how the information disclosed by the managers in the management discussion and analysis (MD&A) reports varies at the different levels of corporate performance.

To understand this quantile effect, first OLS technique was adopted and then, the quantile regression method was applied to explore the impact of MD&A disclosures on the firm performance across the lower and upper quantiles. The sample size for the study is 490 firms’ year observations for the period 2016–2022.

The results of the study demonstrate the negative but significant relationship between MD&A disclosures and corporate performance, supporting the two management strategies of “competitive disadvantage” in case of good performance and “management impression strategy” in case of poor performance. Furthermore, with other corporate governance variables, both the size of the board and the number of independent directors on the board are positively significant only in the case of the upper quantile indicating the heterogeneity in the relationship between the performance and the MD&A disclosures. Therefore, the overall findings of the study support that these results contradict the agency theory and the stakeholders’ theory as managers are not acting well as agents on behalf of the investors and work well only when they are controlled by the large board having more independent directors.

To the best of the authors’ knowledge, no study so far has incorporated quantile regression to assess the effect of MD&A disclosures on company performance at various levels of the firm performance, which gives more robust insights about the viewpoint of the managers on the different level of the firm performance. In other words, this study highlights the important information as to how the information provided in the MD&A reports varies as per the good or poor performance of the companies.

The purpose of this study is to investigate the impact of Shariah Advisory Board (SAB), Audit committee (AC) and board of directors (BD) characteristics on the performance of Islamic banks (IBs) in the MENA region.

The paper employs a quantitative approach, utilizing both ordinary least squares (OLS) regression and panel data analysis (random effects models) to examine the relationship between corporate governance variables and the performance of IBs. The sample consists of 50 IBs from 10 countries, spanning a seven-year period (2010–2016), with the exclusion of the Covid-19 pandemic period. To ensure the robustness of the results, various sensitivity tests were conducted, including pooled regression OLS and subsample analysis based on adhering to the Accounting and Auditing Organization for Islamic Financial Institutions (AAOIFI) standards.

The study's findings suggest that the size of the SAB and the membership of at least one member of the SAB on the AAOIFI have a notable adverse effect on the performance of IBs. On the other hand, the AC independence has a positive influence on bank performance. However, there was no significant impact observed for AC size, meeting frequency and BD characteristics on bank performance. The research also revealed nuanced relationships between governance variables and bank performance when analyzing the sample based on AAOIFI adoption. Among banks not adhering to AAOIFI standards, SAB size and CEO duality negatively affected return on assets, while AC independence positively impacted it. For AAOIFI-compliant banks, AC independence significantly improved bank performance, whereas AC meetings exhibited a negative effect. Furthermore, there were no significant relationships observed for return on equity among banks not adhering to AAOIFI standards, whereas AAOIFI-compliant banks experienced positive impacts from AC independence. These results offer valuable insights into the intricate connection between governance attributes and bank performance, particularly in the context of AAOIFI standards adoption.

The study's findings have important practical implications for various stakeholders in the Islamic banking industry. For bank practitioners and management, the study highlights the significance of enhancing the independence of AC to improve decision-making and risk management, leading to better bank performance. Moreover, careful selection of SAB members can mitigate potential negative effects on performance. Policymakers may consider promoting AAOIFI standards to shape the relationship between governance and bank performance. Investors can use the insights to make informed decisions, and banks with stronger governance may attract more investments.

Through quantitative analysis and AAOIFI-based sample division, this study adds to the growing literature on corporate governance and the performance of IBs by examining the impact of multiple corporate governance variables on the performance of IBs in the MENA region. To provide a theoretical basis for this relationship, three theories, namely agency, stewardship and stakeholder theories, are employed and discussed.

This study aims to examine the effect of board gender diversity on corporate litigation in China’s listed firms. The key questions this study addresses are: what are the effect of board gender diversity on corporate litigation in terms of both the frequency and severity of consequence, is there any heterogeneous effects of the relationships across firm performance?

A sample consists of 25,668 firm-year observations from over 3,340 firms is examined using logistic regression analysis and negative binomial regression analysis. The authors also use event study method and ordinary least square (OLS) regression to explore female directors’ effects on reducing the negative consequences of litigation. The logistic regression and OLS regression are reestimated with interaction terms when examining the firm performance heterogeneity.

The authors document that firms with greater female representation on their boards experience fewer and less severe corporate litigations. Moreover, in high-performing firms, board gender diversity plays a more potent role in reducing the frequency and consequences of corporate litigation than low-performing firms.

This study is among the first to examine the relationship between board gender diversity and the comprehensive corporate litigations under Chinese context. It sheds new light on China’s boardroom dynamics, offering valuable empirical implication to Chinese corporate policymakers on the role of female directors.

Public-private partnership (PPP) highway projects in India are undertaken at both state and national levels, such that differences exist in how the procuring authorities manage project risk during the development and construction phase under different institutional frameworks. This study assesses the performance implication of the different administrative positionings of the procuring authority.

A data set of 516 PPP highway projects implemented in India formed the basis of this study. Means comparison, ordinary least squares (OLS) regression and seemingly unrelated regression were used to assess the impact of procuring authority on schedule performance.

The findings suggest that the state and the national highway projects were no different in achieving financial closure. However, the administrative positioning of the procuring authorities had a significant impact on other schedule performance variables. The construction of the state highway projects started quickly after the financial closure compared to the national highway projects. Moreover, the state highway projects were not only planned to be implemented at a faster rate but they were actually implemented at a faster rate and had a lower time overrun.

Procuring authorities under the state governments, being closer to the project, are better placed to manage project risk than those under the national government.

The administrative distance of the procuring authority from the PPP project and its implication on performance has never been studied.

The purpose of this paper is to fill the momentous gap by explicitly investigating the asymmetric effects of monetary policy (MP) on non-bank financial intermediation (NBFI) assets.

The authors utilized panel data from 29 countries for the period of 2012–2020 and used the quantile regression estimation. In addition to simultaneous quantile regression (SQR), the authors also employ quantile regression with clustered data (Parente and Silva, 2016) and the generalized quantile regression (GQR) method (Powell, 2020).

The empirical results show a significant heterogeneous impact of MP. While there is a positive relationship between MP and NBFI assets (“waterbed effect”) at lower quantiles of NBFI assets, at middle and higher quantiles, MP has a negative impact on NBFI assets (“search for yield” effect). The authors further find that negative impact strengthens as the quantile levels of NBFI assets rise from mid to high. Findings also reveal that “procyclicality” (except higher quantile) and “institutional demand” hypotheses hold. However, regarding “regulatory arbitrage,” mixed results are observed indicating the impact of Basel III requirements.

Previous empirical studies have concentrated on either the Dynamic Stochastic General Equilibrium (DSGE) framework or conditional mean regression approaches and delivered mixed findings of the MP effects on NBFI. The current paper takes a step toward dealing with this issue by deploying quantile regression methodology, which shows the impact of MP on NBFI at different conditional distributions (quantiles) of NBFI assets instead of just NBFI's conditional mean distribution.

Sustainability represents innovative elements in determining the profitability of real estate investments, among other factors, including the green component in real estate. Evidence from the literature has pointed out that incorporating green features into residential buildings can reduce operational costs and increase the building’s value. Although green real estate is considered the future trend of choice, it is still being determined whether prospective buyers are willing to accept the extra cost of green residential investment. Therefore, this study aims to investigate the effect of housing attributes and green certification on residential real estate prices.

The impact of the housing attribute and green certification in the residential sectors was assessed using a transaction data set comprising approximately 861 residential units sold in Selangor, Malaysia, between 2014 and 2022. Linear and quantile regression were used in this study by using SPSS software for a robust result.

The findings indicate that the market price of residential properties in Malaysia is influenced by housing attributes, transaction types and Green Building Index certification. The empirical evidence from this study suggests that green certification significantly affects the sales price of residential properties in Malaysia. The findings of this research will help investors identify measurable factors that affect the transaction prices of green-certified residential real estate. These identifications will facilitate the development of strategic plans aimed at achieving sustainable rates of return in the sustainable residential real estate market.

Specifically, this research will contribute to achieving area 4 of the 11th Malaysia Plan, which pertains to pursuing green growth for sustainability and resilience. This will be achieved by enhancing awareness among investors and homebuyers regarding the importance of green residential buildings in contributing to the environment, the economy and society.

The regression model for housing attributes and green certification on house price developed in this study could offer valuable benefits to support and advance Malaysia in realising its medium and long-term goals for green technology.