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Purpose – This study explores the probability of expropriation of minority shareholders by controlling shareholders in the form of CEO compensation under an imperfect governance institution by using a novel Chinese dataset over 2001–2010.

Design/methodology/approach – We use a direct method to gauge controlling shareholders’ tunneling and expropriation of minority shareholders, and we present a simple model to link corporate governance and the degree of entrenchment by the largest shareholder. We use both Logit and Probit models to predict the likelihood of tunneling and use two-stage least square (2SLS) regression to address the endogeneity issues.

Findings – There are significant deterioration effects between controlling shareholder's tunneling and firm performance. Firms with more tunneling activities typically have larger controlling ownership, greater evidence of state control, less balance of power among large shareholders, and weaker board characteristics.

Research limitations/implications – The positive relationship between controlling shareholders’ tunneling and executive compensation implies that the controlling shareholder might divert personal benefits from the public firms at the expense of minority shareholders.

Originality/value – We focus on the effects of corporate governance restructuring on executive compensation and controlling shareholders’ tunneling in the Chinese context, and we also investigate whether these effects are stronger with the involvement of state ownership. We empirically address the issues between executive compensation and expropriation of minority shareholders.

This chapter examines China’s corporate governance and accounting environment that shapes the adoption of internationally acceptable principles and standards. Specifically, it examines international influences, including supranational organizations; foreign investors and international accounting firms; domestic institutional influences, including the political system, economic system, legal system, and cultural system; and accounting infrastructure. China’s convergence is driven by desired efficiency of the corporate sector and legitimacy of participating in the global market. Influenced heavily by international forces in the context of globalization, corporate governance and accounting practices are increasingly becoming in line with internationally acceptable standards and codes. While convergence assists China in obtaining legitimacy, improving efficiency is likely to be adversely affected given that corporate governance and accounting in China operate in an environment that differs considerably from those of Anglo-American countries. An examination of the corporate governance and accounting environment in China suggests heavy government involvement within underdeveloped institutions. While the Chinese government has made impressive progress in developing the corporate governance and accounting environment for the market economy, China’s unique institutional setting is likely to affect how the imported concepts are interpreted and implemented.

In view of the significant changes in the capital structure of China’s real estate industry and enterprises in recent years, this chapter employs financial indicators and the linear regression function to analyze the relationship between corporate debt ratio and the performance of 111 A-share listed real estate enterprises in China. This study finds that the corporate debt ratio of China’s real estate enterprises in the past decade has a significant negative impact on enterprises’ performance. The study also finds that among China’s real estate companies, the corporate debt ratio has a more significant negative impact on the performance of non-state-owned enterprises than state-owned enterprises. In addition, a high debt ratio has a more significant negative impact on return on equity (ROE) than on return on assets (ROA). However, when Tobin’s Q serves as a proxy for firm performance, the negative impact of the corporate debt ratio becomes insignificant in the presence of the firm size factor. The research results of this chapter can provide some reference for subsequent policy-making and investment decisions in the Chinese real estate market.

Special education in China has lagged behind regular education for many years, however, the past few decades, the government has made considerable efforts to develop and improve the special education system. While the citizens of China have had a generic moral interest in disability since ancient times, the development of special education schools did not occur until American and European missionaries started schools for the visually and hearing impaired in the 19th century. The next major influence in the development of the special education system occurred with China’s Cultural Revolution in 1978. Interestingly, there is not any exclusive legislation on special education but in the 1980s, the government started Learning in Regular Classrooms (LRC), which is China’s version of inclusion. LRC has progressed rapidly the past two decades; however, the quality of instruction is low due to a lack of specialists, a shortage of personnel, inadequate funding, and limited technology as well as other barriers that are delineated in the chapter. The chapter emphasizes the government’s recent efforts in in-service teacher training, the preparation of preservice teachers, working with families, developing community rehabilitation training programs, and implementing evidence-based practices. Special education in China today is at a good place but it has quite a way from the ideal situation.

Nonperforming assets in any banking system have stressed the economic health of nations. Resultantly, literature has given considerable impetus to predict failures and bankruptcy. Past studies have focused on the outcome of failures, while, there is a dearth of studies focusing on ongoing firms in bad shape. We plug this gap and attempt to identify underlying communication patterns for firms witnessing prolonged underperformance. Using text mining, we extract and analyze semantic, linguistic, emotional, and sentiment-based features in non-numeric communication channels of these poor-performing firms and their peers. These uncovered patterns highlight the use of vocabulary and tone of communication, in correspondence to their financial well-being. Furthermore, using such patterns, we deploy various Machine Learning algorithms to identify loser firm(s) way ahead in time. We observe promising accuracy over a time window of five years. Such early warning signals can be of critical importance to various stakeholders of a firm. Exploration of writing style-related features for any firm would help its investors, lending agencies to assess the likelihood of future underperformance. Firm management can use them to take suitable precautionary measures and preempt the future possibility of distress. While investors and lenders can be benefitted from this incremental information to identify the likelihood of future failures.