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This chapter develops an asymptotic theory for a general transformation model with a time trend, stationary regressors, and unit root nonstationary regressors. This model extends that of Han (1987) to incorporate time trend and nonstationary regressors. When the transformation is specified as an identity function, the model reduces to the conventional cointegrating regression, possibly with a time trend and other stationary regressors, which has been studied in Phillips and Durlauf (1986) and Park and Phillips (1988, 1989). The limiting distributions of the extremum estimator of the transformation parameter and the plug-in estimators of other model parameters are found to critically depend upon the transformation function and the order of the time trend. Simulations demonstrate that the estimators perform well in finite samples.

This paper considers stationary regression models with near-collinear regressors. Limit theory is developed for regression estimates and test statistics in cases where the signal matrix is nearly singular in finite samples and is asymptotically degenerate. Examples include models that involve evaporating trends in the regressors that arise in conditions such as growth convergence. Structural equation models are also considered and limit theory is derived for the corresponding instrumental variable (IV) estimator, Wald test statistic, and overidentification test when the regressors are endogenous. It is shown that near-singular designs of the type considered here are not completely fatal to least squares inference, but do inevitably involve size distortion except in special Gaussian cases. In the endogenous case, IV estimation is inconsistent and both the block Wald test and Sargan overidentification test are conservative, biasing these tests in favor of the null.

The authors propose to estimate a varying coefficient panel data model with different smoothing variables and fixed effects using a two-step approach. The pilot step estimates the varying coefficients by a series method. We then use the pilot estimates to perform a one-step backfitting through local linear kernel smoothing, which is shown to be oracle efficient in the sense of being asymptotically equivalent to the estimate knowing the other components of the varying coefficients. In both steps, the authors remove the fixed effects through properly constructed weights. The authors obtain the asymptotic properties of both the pilot and efficient estimators. The Monte Carlo simulations show that the proposed estimator performs well. The authors illustrate their applicability by estimating a varying coefficient production frontier using a panel data, without assuming distributions of the efficiency and error terms.

The purpose of this study is to explore possible factors leading to a successful mediation in Chinese mediation shows. In China, media always play an indispensable role in information dissemination, morality advocacy and policy explanation.

This paper employed content analysis of 166 episodes of one representative mediation show, Gold Medal Mediation, and regression technique in data analysis.

Results of ordinal regression suggested that “secret talking”, rather than transparency, between disputants had significant influence on successful mediation. Function of mediators is limited in reaching full mediation. The effective factors leading to full mediation include compromise of rights, secret talking, attitude of the observer cohort. It suggests that the role of mediator is limited, rather than being over-exaggerated, in successful mediation. The successful mediation is largely dependent on disputants’ motivations. Additionally, “compromise of rights” by disputants is a key factor in solving disputes.

Findings of this study revealed the role of Chinese mediation shows in propagating mediation in contemporary Chinese society and supporting upheld morality values. Due to the nature of the chosen mediation show, some disputes take more than one episode to solve. However, this study looks at each episode without considering the integrity of the dispute. That is, if the disputes take two episodes, the coder codes the two episodes as two separate disputes instead of looking at it as one dispute.

By exploring various aspects of mediations shows, including the role of mediators, disputants and a cohort of observers, this study can both explicitly show predicted factors to successful mediations on the shows, and can implicitly examine the power and perceived justification of mediation in contemporary China via media.

Joon Y. Park is one of the pioneers in developing nonlinear cointegrating regression. Since his initial work with Phillips (Park & Phillips, 2001) in the area, the past two decades have witnessed a surge of interest in modeling nonlinear nonstationarity in macroeconomic and financial time series, including parametric, nonparametric and semiparametric specifications of such models. These developments have provided a framework of econometric estimation and inference for a wide class of nonlinear, nonstationary relationships. In honor of Joon Y. Park, this chapter contributes to this area by exploring nonparametric estimation of functional-coefficient cointegrating regression models where the structural equation errors are serially dependent and the regressor is endogenous. The self-normalized local kernel and local linear estimators are shown to be asymptotic normal and to be pivotal upon an estimation of co-variances. Our new results improve those of Cai et al. (2009) and open up inference by conventional nonparametric method to a wide class of potentially nonlinear cointegrated relations.

Economic theory suggests that profits of firms in industries with higher competition are less persistent and more volatile than in industries with lower competition (Stigler, 1963; Mueller, 1977). Extending this reasoning, I hypothesize that accounting-based fundamentals are more effective in predicting performance in industries with lower competition. I find that a measure of fundamentals (Piotroski’s F-score) has greater ability to identify potentially mispriced securities in industries with lower competition. The results are robust to using a variety of competition measures and imply that industry competition is an important consideration in the application of fundamental analysis.

The purpose of this paper is to suggest that the information ethics (IE) of students appear to improve more through adoption of the technology mediated learning (TML) platform rather than face-to-face (FTF) approach. In addition, it shows the pattern changes in each scenario resulting from the ethics training and analyses them from the Confucian ethics perspective, indicating that researchers should consider this aspect in future models.

This study employed non-parametric methods to test the outcome of the “information ethics course” of two kinds of training platforms. FTF training: 193 students; TML training: 185 students.

The TML platform produces a more significant improvement in the students’ respect for rules, privacy, accessibility, and intellectual property (IP) cognition, rather than the FTF method. Based on the findings, two propositions (eight sub-propositions) are formulated and revised two sub-propositions.

However, this study has a few limitations that can be enhanced by further research in the future: first, the data were only collected from one university (National Pingtung University), thus, the external validity is not satisfactory for all Chinese context students. Second, it is necessary to collect both of scenario-based and qualitative data from different cultural context students (such as Mainland China, the USA, Europe, Arabia, etc.) and then compare their results, thereby making further contributions to the current study. Third, the study was intentionally used as the measure of progress in ethical understanding without highlighting the difference between intentionality and actual behavior.

Teachers should draw upon the principles of Ren, Yi, and Li, from the Confucian ethics perspective to encourage students to respect the IE for Chinese context students. In addition, emphasis should be placed on the ability of students to build their information ethics cognition through the cognitive information processing learning methods, which can enhance the “accessibility,” “accuracy,” “privacy,” and “IP” cognition of Chinese students in both the FTF and TML platform learning process. This will help to reduce students’ unethical behavior as they advance in their future careers.

We study the events that motivate CEOs to underinvest in R&D long-term projects (CEO myopia). Based on the existing literature in earnings management and agency theory, myopia is likely to become more problematic under five circumstances: when the CEO nears retirement (the CEO horizon problem), R&D projects have very long time horizons (the project horizon problem), the firm’s financial health is deteriorating (the cover-up problem), ownership structure is heavily weighted toward insider owners (minority owner oppression problem), and when the threat of hostile takeover increases (the entrenchment problem). We setup a dynamic simulation model in which rational CEOs maximize the total value of their bonus compensation over their tenure. Our findings related to the five circumstances are consistent with the extant literature. However, we found an unexpected stable, nonlinear (inverted U-shaped) relationship between CEO tenure and R&D investment. We discuss the theoretical implications of our model and offer suggestions for future research.

This study provides new evidence on the effect of compulsory schooling laws on educational attainment and earnings. First, we re-examine the effect of compulsory schooling laws for cohorts born between 1900 and 1964 (“older cohorts”) using newly available data that match administrative earnings records with the survey data. Second, we provide among the first evidence on cohorts born between 1977 and 1996 (“younger cohorts”). Our findings suggest that compulsory schooling laws increased the educational attainment of older cohorts, but had no economically significant effect on the educational attainment of younger cohorts. We are unable to find consistent evidence that compulsory schooling laws increased the earnings of older cohorts – a finding which adds to growing evidence that compulsory schooling laws are less beneficial than earlier studies suggest.

We consider the Bayes estimation of a multivariate sample selection model with p pairs of selection and outcome variables. Each of the variables may be discrete or continuous with a parametric marginal distribution, and their dependence structure is modeled through a Gaussian copula function. Markov chain Monte Carlo methods are used to simulate from the posterior distribution of interest. The methods are illustrated in a simulation study and an application from transportation economics.