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As literatures argue that managers’ personalities will affect both corporate governance structures and corporate performance, the correlation between them is a mixed result. The purpose of this paper is to separate different routes leading to the mixed correlation, and name the separated routes as regime effect and signal effect.

By theoretical analysis, the authors list three routes leading to the correlation between corporate governance and corporate performance. Routes 1 and 2 show that governance can directly and indirectly change the performance; while route 3 shows that both the governance and performance are results of managers’ personalities, and the governance has no influence onto the performance, which means the correlation led by route 3 is fake. By design a new econometric methodology, this paper separates the mixed correlation between corporate governance and performance, and names the correlation led by routes 1 and 2 as the regime effect and the correlation led by route 3 as signal effect.

By an empirical research on Chinese listed corporates, the authors find that the correlations between Chinese listed corporates’ market value and main corporate governance factors can be separated into regime effects and signal effects; and the authors also find that some factors (Share of Institutional Investors, Share of Real Controller and the Squared, Dummy of Identical CEO and Chairman, Ownership Concentration) only show regime effects, some factors (Separating Extent of Ownership and Controlling Right, Dummy of Provincial State-Owned Firms) only show signal effects, and some factors (Dummy of Republic State-Owned Firms, Scale of Board) show both. What’s more, the authors find out an interesting result that the state-owning has no negative regime effect on China SOEs’ performance but very significantly negative signal effect; in this paper, the authors suggest that this means the key negative factors of Chinese SOEs is not state-owning ownership structure but the managers’ corruption.

As only the factors with regime effects can directly and indirectly affect corporates’ performance and the factors with signal effects show that there’re some managers’ personalities affecting both the governance and performance, the separation method in this paper can help shareholders knowing which governance factors will be helpful to improve the performance and which others will show managers’ hard-working or corruption intention.

Separate the regime effect and the signal effect from the correlation between corporate governance and performance.

Facing the aging workforce but older workers’ vulnerability in the labor market, this chapter empirically explores factors and policy implications to enhance older workers’ entered employment rates (EER) after exiting the national workforce program. After reviewing older workers’ attributes and the unique methods to train them, the chapter examines demographic, socioeconomic, and program attributions to older workers’ EER, controlling for cyclical changes in the labor market. The chapter relies on three sets of models including logistic regression, multi-level mixed-effect regression, and multilevel mixed effect logistic regression models, as well as longitudinal Workforce Investment Act Standardized Record Data and Bureau of Labor Statistics unemployment data. Older dislocated workers and older adults are examined separately. Some Workforce Innovation and Opportunity Act training and related service combinations are identified to contribute to older adults and older dislocated workers’ EER and to inform strategic decision-making about future allocations of funds and policy efforts to serve older workers.

The purpose of this paper is to investigate the relationship between tax avoidance, firm value and managerial ability in Tehran Stock Exchange and Over the Counter (OTC), according to the related theoretical foundations.

To calculate the managerial ability in this study, DEA is used based on the accounting data, company profile and industry and the hypotheses are estimated in a period of 12 years during 2004 to 2015 in TSE and OTC. Within the previous studies, to test the hypotheses, only the classical regression method is usually used and most of the times the effect of macroeconomic variables is not considered. In this study, in a new act for testing the hypotheses, three statistical methods are used, that is, classical regression models, mixed effects multilevel models and Bayesian multilevel models. Also in this study, the test of structural change is used to control the effects of macroeconomic variables, like inflation and other economic and political influence, on the results.

The results of these three methods show that the effect of income smoothing and earnings quality on the relationship between tax avoidance and firm value are significant.

Although several studies are conducted so far on the subject of the study, the current study is the first project which combined Bayesian econometrics. Therefore, the results are quite noble.

The purpose of this paper is to illustrate the value of extended time span coverage of state longitudinal education and workforce data system to inform and improve the effectiveness of future high impact expenditure decisions.

It used an analytical 29-year data file created by the author that links seven already-in-place education and workforce administrative record sources. Relying on the path dependency theory, multi-level mixed-effect logistic and multi-level mixed-effect linear regression models are used to test three hypotheses.

The findings are consistent with the hypotheses: inclusion of the multiple steps along a post-secondary education pathway and prior job histories are both critical to understanding workforce outcomes mechanisms; it takes time for the employment outcome effect to be evident and strong following education attainment.

The study concludes with research limitations and implications for decision makers to call for retaining and investing in administrative records with extended time span coverage, particularly for the already-in-place historical administrative records.

The paper is one of the first to demonstrate the value of extended time span coverage in a longitudinal state integrated data system through econometric modeling, using longitudinally integrated data linking seven administrative records covering continuously for 29 years. No matter for prior education or employment pathway, it is only through extended time span coverage that employment outcomes can be well measured and the rich nuances interpreting the mechanisms of education return on investment can be revealed.

Two of the primary growth strategies for Major League Soccer (MLS) have been team expansion and the construction of soccer-specific stadiums. Therefore, the purpose of this paper is to determine the relationship between these factors and game-specific MLS spectator attendance.

Two multiple regression models, one using multi-level mixed effects linear regression and another using interval regression, were developed to explain the variation in attendance utilizing the two factors of interest along with other control factors that have been identified as attendance determinants in previous literature. Game-specific data were collected for five MLS seasons, 2007-2011.

The two regression models explained approximately 40 percent of the variation in spectator attendance and the results showed that expansion teams and soccer-specific stadiums were significantly related to attendance. However, the effect of soccer-specific stadiums was minimized due to the extreme success of the Seattle Sounders in drawing about twice as many fans as the next highest drawing franchise, yet playing in an American football stadium.

While many of the standard factors such as the presence of holidays and novelty players, competition from other professional teams, and day of week, competition from other professional teams; team quality failed to show significance. Expansion teams drew better than incumbent teams and the impact from soccer-specific stadia is weak given the success of the Seattle franchise (and possibly negative when excluding Seattle). Censoring of the dependent variable had a discernible impact on many of the attendance factors.

These findings may be useful to managers of MLS and their teams along with other professional teams and/or leagues that are investigating the use of either team expansion or the construction of new facilities to increase spectator attendance.

This is the first study to investigate the relationship between expansion and new stadium construction in MLS over multiple years. The results indicate that MLS’s decision to use team expansion and the construction of soccer-specific stadiums has been beneficial with respect to spectator attendance.

The purpose of this paper is to investigate the accuracy and volatility of different methods for estimating and updating hedonic valuation models.

The authors apply six estimation methods (linear least squares, robust regression, mixed-effects regression, random forests, gradient boosting and neural networks) and two updating methods (moving and extending windows). They use a large and rich data set consisting of over 123,000 single-family houses sold in Switzerland between 2005 and 2017.

The gradient boosting method yields the greatest accuracy, while the robust method provides the least volatile predictions. There is a clear trade-off across methods depending on whether the goal is to improve accuracy or avoid volatility. The choice between moving and extending windows has only a modest effect on the results.

This paper compares a range of linear and machine learning techniques in the context of moving or extending window scenarios that are used in practice but which have not been considered in prior research. The techniques include robust regression, which has not previously been used in this context. The data updating allows for analysis of the volatility in addition to the accuracy of predictions. The results should prove useful in improving hedonic models used by property tax assessors, mortgage underwriters, valuation firms and regulatory authorities.

The purpose of this study is to estimate the effects of gender composition in the workplace on employee job satisfaction and commitment.

The data were collected on both the organizational and employee levels at three different points in time in organizations with more than 70 employees. Multi-level mixed-effects ordered logistics regressions were used to account for the multi-level nature of the data and the ordered nature of the dependent variables.

Employees in gender-balanced workplaces show higher levels of job satisfaction and commitment than those in female-dominated or male-dominated workplaces. The relationship is also based on the gender of the individual, as men show a significantly lower level of both job satisfaction and commitment when working in male-dominated workplaces than others, while for women, the effect is only significant for commitment.

Aiming for a balance in the gender composition of the workplace may improve employee attitudes, especially for men. The results also indicate that further research is warranted into why job satisfaction and commitment are significantly lower among men in male-dominated workplaces.

The relationship between gender and job satisfaction and commitment is well established, but less is known about the effects of gender composition on job satisfaction and commitment. Previous papers have focused on job satisfaction. This paper extends prior studies by estimating the effects of gender composition on both job satisfaction and commitment using multi-level regressions on a rich dataset.

Based on institutional theory, this study aims to analyze the influencing mechanisms of the institutional environment in the digital context on technology entrepreneurship.

Using data from the Global Entrepreneurship Monitor, World Bank and World Economic Forum, this study builds a multilevel database covering 79 countries and 97,146 individuals from 2013 to 2017. A mixed-effects logistic regression model with the fixed part and random part was chosen to test the hypotheses in this study. The mixed-effects logistic regression model used in this study includes a random intercept with random effects at the country level, while the robustness test considers a more complex two-level model with a random intercept plus random slope.

The findings indicate that different dimensions of the institutional environment in the digital context have different effects on individual technology entrepreneurship. The analysis shows that exposure to digital networks and innovative culture positively influences technology entrepreneurship. However, intellectual property rights protection has a negative impact on technology entrepreneurship. Furthermore, the government digitalization has different effects on above relationships. When a government digitalization is higher, there will be a weaker positive relationship between exposure to digital networks and technology entrepreneurship. When a government digitalization is higher, there will be a stronger positive relationship between innovative culture and technology entrepreneurship. When a government digitalization is higher, there will be a weaker negative relationship between Intellectual property rights protection and technology entrepreneurship. Finally, the effect of innovative culture on technology entrepreneurship in the digital context is stronger for females than for males.

The aforementioned findings contribute to a better understanding of the theoretical logic underlying digital factors affecting the institutional environment and technology entrepreneurship and act as a reference for the country in terms of raising its scientific and technological levels and promoting economic structure transformation in the digital era.

The purpose of this paper is to analyze the relationship between social capital and subjective ranking of household economic well-being in transition countries. The current study tests whether the performance of formal institutions moderates this link.

The analyses are based on the data from the second wave of the Life in Transition Survey. The measures “generosity of welfare policy (social safety nets)” and “ability of formal institutions to control inflation” were provided by the Bertelsmann Transformation Index Project. The study uses four measures of social capital: trust in family, trust in friends and acquaintances, trust in most people and the number of support sources. To test the hypotheses, the study employs mixed-effects regression models.

The study indicates a significant positive effect of social capital on subjective household well-being. Formal institutions do not have a significant effect on subjective ranking of household well-being. The evidence on institutions as moderators rejects the substitution effect between formal institutions and social capital. Higher generosity of welfare policy institutions and higher ability of formal institutions to control inflation strengthen the positive effect of particular trust (trust in family and trust in friends and acquaintances) on subjective ranking on the ladder of social standing (subjective ranking of household well-being), which is in line with the “crowding in” theory.

The paper adds on the limited research on transition countries. The paper contributes to the discussion on “crowding in” and “crowding out” effects of formal institutions on social capital.

The purpose of this paper is to investigate the effect of managerial ability on tax avoidance in Tehran Stock Exchange (TSE) and OTC by classifying the income smoother and non-income smoother companies based on the theoretical approaches.

To measure the managerial ability the data envelopment analysis is applied based on the accounting data, company and industry characteristics. In this research, hypotheses are tested for the first time by three statistical methods, namely classical regression models, mixed effect multilevel models, and Bayesian multilevel models, which have never been addressed in Persian accounting research studies. The hypotheses are estimated during a 12-year period from 2004 to 2015 in TSE and OTC. In this research, according to Lucas’s critique, structural change test is used in order to control macroeconomic and political variables affecting the results of the study.

The results of hypothesis testing by employing three statistical methods suggest that only one hypothesis of this investigation is significant, which shows the significant association of type of market’s impact (exchange of OTC) on the relationship between managerial ability and tax avoidance.

Each company’s performance is affected by various factors. The study intends to mention that the performance of listed companies in the stock market depends heavily on its financial reports. And investors with perceived perception by the reports, can indirectly squeeze their stock indexes with their sudden sale of stocks, and question the company’s performance with losses to the company.