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We compare the finite sample power of short- and long-horizon tests in nonlinear predictive regression models of regime switching between bull and bear markets, allowing for time varying transition probabilities. As a point of reference, we also provide a similar comparison in a linear predictive regression model without regime switching. Overall, our results do not support the contention of higher power in longer horizon tests in either the linear or nonlinear regime switching models. Nonetheless, it is possible that other plausible nonlinear models provide stronger justification for long-horizon tests.

I review the burgeoning literature on applications of Markov regime switching models in empirical finance. In particular, distinct attention is devoted to the ability of Markov Switching models to fit the data, filter unknown regimes and states on the basis of the data, to allow a powerful tool to test hypotheses formulated in light of financial theories, and to their forecasting performance with reference to both point and density predictions. The review covers papers concerning a multiplicity of sub-fields in financial economics, ranging from empirical analyses of stock returns, the term structure of default-free interest rates, the dynamics of exchange rates, as well as the joint process of stock and bond returns.

Urbanisation, environmental sustainability and property markets are intertwined. Consequently, studies on any of these three topics need to take the other two topics into consideration. By critically reviewing 33 hedonic pricing studies in 16 key journals in the urban studies and environmental policies areas, we summarise quantitative evidence on the price of environmental externalities resulting from China's urbanisation process. We find that Chinese residents are willing to pay more for the access to green space and waterbody as well as the treatment of urban pollution. The cost and benefit of these amenities and disamenities have already been capitalised in house prices. The central and local government in China can leverage market force to encourage, support and facilitate sustainable urban development and environmental protection, instead of directly intervening in the property market by using public resources. Meanwhile, the estimated hedonic price of Urban Green, Urban Blue and Urban Grey helps policymakers to understand the cost and benefit of their urban development decisions. Our review of the papers on Urban Green, Urban Blue and Urban Grey suggests that there have been promising and encouraging development in studies on all three topics in the last decade. The quality and quantity of hedonic price research has been improving notably. However, it is also clear that there is virtually no empirical evidence from the second- or third-tier cities, particularly, regarding Urban Green and Urban Blue investigations. The small number of existing hedonic studies is far from sufficient to draw reliable conclusions about the costs of environmental externality for cities that have not been studied. What works in first-tier cities may not hold elsewhere in China due to the large geographical variation in natural endowment, economic development status and local customs. There are many pieces that are missing from this big picture. More hedonic price studies are needed.

This chapter discusses and investigates the sustainability reporting across different sectors. The first section discusses and investigates the relationship between sustainability reporting and primary sector's performance (Agriculture and Food Industries Sector and Energy Sector). The second section discusses and investigates the relationship between sustainability reporting and secondary sector's performance (Manufacturing Sector). The final section discusses and investigates the relationship between sustainability reporting and tertiary sector's performance (Banks and Financial Services Sector, Retail Sector, Telecommunication and Information Technology Sector, and Tourism Sector).

Applied econometric analysis is often performed using data collected from large-scale surveys. These surveys use complex sampling plans in order to reduce costs and increase the estimation efficiency for subgroups of the population. These sampling plans result in unequal inclusion probabilities across units in the population. The purpose of this paper is to derive the asymptotic properties of a design-based nonparametric regression estimator under a combined inference framework. The nonparametric regression estimator considered is the local constant estimator. This work contributes to the literature in two ways. First, it derives the asymptotic properties for the multivariate mixed-data case, including the asymptotic normality of the estimator. Second, I use least squares cross-validation for selecting the bandwidths for both continuous and discrete variables. I run Monte Carlo simulations designed to assess the finite-sample performance of the design-based local constant estimator versus the traditional local constant estimator for three sampling methods, namely, simple random sampling, exogenous stratification and endogenous stratification. Simulation results show that the estimator is consistent and that efficiency gains can be achieved by weighting observations by the inverse of their inclusion probabilities if the sampling is endogenous.

In this paper, we explore an extensive panel data set covering more than 4,000 listed firms in 16 European countries to study the effects of shareholder protection on ownership structure and firm performance. We document a negative firm-level correlation between shareholder protection and ownership concentration. Differentiating between shareholder types, we find that this pattern is mainly driven by strategic investors. In contrast, we find a positive correlation between shareholder protection and block ownership of institutional investors, in particular when we restrict the analysis to independent institutional investors. Finally, we find that independent institutional investors are positively associated with firm valuation as measured by Tobin’s Q. The opposite applies for strategic investors. Overall, our results are consistent with the view that (i) high shareholder protection and (ii) limited ownership by strategic investors make small investors and investors interested in security returns more confident in their investments.

The authors measure the impact of culture on Sharia; Social and Financial Disclosure (SSFD) of Islamic Banks (IBs) around the world.

Content analysis is used to measure levels of disclosure for a sample of 136 IBs of 25 countries for years 2013 and 2014. Different cultural measures are used. These include secrecy/transparency as suggested by Gray (1988) and Hofstede (1980, 1983, 2001, 2010)’s culture dimensions which include: Power Distance; Individualism; Masculinity; Uncertainty Avoidance; Long-Term Ordination and Indulgence. Ordinary least square (OLS) regression is used to test the research hypotheses.

After controlling bank-specific, corporate governance and country characteristics, the authors found that Hofstede’s culture dimensions have a significant impact on SSFD. They also found that Gray's transparency dimension positively influence levels of sharia, social and aggregated disclosure. Therefore, they conclude that culture influences levels of disclosure in IBs.

This study has policy implications for managers and regulators of Islamic banking industry.

This study is the first to use both Gray and Hofstede models in the context of IBs around the world. It also the first to explore the impact of culture on three different disclosure levels for IBs.

We reformulate regression modeling so that ideas often associated with field theory and social network analysis can be brought to bear at every stage in the computation and interpretation of regression coefficients in studies of organizations. Rather than “transcending” general linear reality, we seek to get more out of it. We formulate a dual to regression modeling based on using the variables to learn about the cases. We illustrate our ideas by applying the new approach to a database of hundreds of violent extremist organizations, focusing on understanding which groups use or pursue unconventional weapons (chemical, biological, radiological, nuclear).