Suchergebnisse

In panel structure models, individuals can be classified into different groups with the slope parameters being homogeneous within the same group but heterogeneous across groups, both the number of groups and each individual's group membership are unknown. This dissertation proposes some methods to identify the panel structure models under different specifications, namely, developing a Lasso-type Panel-CARDS method in the linear panel, constructing two sequential binary segmentation algorithms in the nonlinear panel, and using K-means algorithm in the spatial panel. Chapter 2 studies the estimation of a linear panel data model with latent structures. To identify the unknown group structure of vector parameters, we design an algorithm called Panel-CARDS which is a systematic extension of the CARDS procedure proposed by Ke, Fan, and Wu (2015) in a cross-sectional framework. We show that it can identify the true group structure asymptotically and estimate the model parameters consistently at the same time. Simulations evaluate performance and corroborate the asymptotic theory in several practical design settings. The empirical economic application considers the effect of income on democracy by using cross-country data over the period 1961-2000. It reveals the presence of latent groupings in this panel data. Chapter 3 proposes a procedure to identify latent group structures in nonlinear panel data models. To identify the group structures, we consider the order statistics for the preliminary unconstrained consistent estimators of the regression coefficients and translate the problem of classification into the problem of break detection. Then we extend the sequential binary segmentation algorithm of Bai (1997) for break detection from the time series setup to the panel data framework. We demonstrate that our method can identify the true latent group structures with probability approaching one and the post-classification estimators are oracle-efficient. The method has the advantage of more convenient implementation compared with some alternative methods, which is a desirable feature in nonlinear panel applications. To improve the finite sample performance, we also consider an alternative version based on the spectral decomposition of certain estimated matrix and link the group identification issue to the community detection problem in the network literature. Simulations show that our method has good finite sample performance. We apply this method to explore how individuals' portfolio choices respond to their financial status and other characteristics using the Netherlands household panel data from year 1993 to 2015, and find three latent groups. Chapter 4 considers the identification of latent group structures in dynamic spatial models with interactive fixed effects. The model treats three kinds of heterogeneity at the same time, namely, the spatial heterogeneity, individuals' heterogeneous responses to the same time factors, and heterogeneous slope coefficients. To identify the latent group structures, we adopt quasi-maximum likelihood estimation to get preliminary unconstrained estimators of the slope coefficients. Then we use the K-means algorithm on slope coefficients' consistent preliminary estimators to get the clusters. The asymptotic analysis shows that this method can identify the true group structure consistently. Therefore, the post-classification estimators have the oracle property. Monte Carlo simulations demonstrate that it has good finite sample performance.

This study provides a systematic analysis of the VIP-room contractual system of Macao's traditional casino industry. It examines the system's historical background, its organisational structure, and its operational mechanisms. The evolving and likely future changes in the VIP sector - as well as the mass market sector - caused by the liberalisation of Macao's gaming laws in 2001 are examined. The dynamics of the allocation of business between the VIP sector and mass market sector are examined in the context of underlying economic and cultural forces. A major conclusion of this analysis is that the VIP-room contractual system that evolved in Macao's casino industry from the 1980s until the current decade is already undergoing significant change in the new legal and competitive environment. There are already signs that it is being replaced by new systems consistent with competitive realities. However, Macao's VIP business will likely continue as an important component of the market in one form or another. (CIJ/GIGA)

This paper studies the estimation of a panel data model with latent structures where individuals can be classified into different groups with the slope parameters being homogeneous within the same group but heterogeneous across groups. To identify the unknown group structure of vector parameters, we design an algorithm called Panel-CARDS. We show that it can identify the true group structure asymptotically and estimate the model parameters consistently at the same time. Simulations evaluate the performance and corroborate the asymptotic theory in several practical design settings. The empirical application reveals the heterogeneous grouping effect of income on democracy.

This paper studies estimation of a panel data model with latent structures where individuals can be classified into different groups where slope parameters are homogeneous within the same group but heterogeneous across groups. To identify the unknown group structure of vector parameters, we design an algorithm called Panel-CARDS which is a systematic extension of the CARDS procedure proposed by Ke, Fan, and Wu (2015) in a cross section framework. The extension addresses the problem of comparing vector coefficients in a panel model for homogeneity and introduces a new concept of controlled classification of multidimensional quantities called the segmentation net. We show that the Panel-CARDS method identifies group structure asymptotically and consistently estimates model parameters at the same time. External information on the minimum number of elements within each group is not required but can be used to improve the accuracy of classification and estimation in finite samples. Simulations evaluate performance and corroborate the asymptotic theory in several practical design settings. Two empirical economic applications are considered: one explores the effect of income on democracy by using cross-country data over the period 1961-2000; the other examines the effect of minimum wage legislation on unemployment in 50 states of the United States over the period 1988-2014. Both applications reveal the presence of latent groupings in these panel data.

The phenomenon of 'cancer villages' has emerged in many parts of rural China, drawing media attention and becoming a fact of social life. However, the relationship between pollution and disease is often hard to discern. Through sociological analysis of several villages with different social and economic structures, the authors offer a comprehensive, historically grounded analysis of the coexistence between the incidence of cancer, environmental pollution and villagers' lifestyles, as well as the perceptions, claims and responses of different actors. They situate the appearance of 'cancer villages' in the context of social, economic and cultural change in China, tracing the evolution of the issue over two decades, and providing deep insights into the complex interactions and trade-offs between economic growth, environmental change and public health.

Due to rapid urbanization, industrialization and motorization, a large number of Chinese cities are affected by heavy air pollution. In order to explore progress, remaining challenges, and sustainability of air pollution control in the Beijing-Tianjin-Hebei (BTH) region after 2013, a mixed method analysis was undertaken. The quantitative analysis comprised an overview of air quality management in the BTH region. Semi-structured expert interviews were conducted with 12 stakeholders from various levels of government and research institutions who played substantial roles either in decision-making or in research and advising on air pollution control in the BTH region. The results indicated that with the stringent air pollution control policies, the air quality in BTH meets the targets of the Air Pollution Prevention and Control Action Plan. However, improvements vary across the region and for different pollutants. Although implementation has been decisive and was at least in parts effectively enforced, significant challenges remained with regard to industrial and traffic emission control, and national air quality limits continued to be significantly exceeded and competing development interests remained mainly unsolved. There were also concerns about the sustainability of the current air pollution control measures especially for industries due to the top-down enforcement, and the associated large burden of social cost including unemployment and social inequity resulting industrial restructuring. Better mechanisms for ensuring cross-sectoral coordination and for improved central-local government communication were suggested. Further suggestions were provided to improve the conceptual design and effective implementation of respective air pollution control strategies in BTH. Our study highlights some of the major hurdles that need to be addressed to succeed with a comprehensive air pollution control management for the Chinese mega-urban agglomerations.

Due to rapid urbanization, industrialization and motorization, a large number of Chinese cities are affected by heavy air pollution. In order to explore progress, remaining challenges, and sustainability of air pollution control in the Beijing-Tianjin-Hebei (BTH) region after 2013, a mixed method analysis was undertaken. The quantitative analysis comprised an overview of air quality management in the BTH region. Semi-structured expert interviews were conducted with 12 stakeholders from various levels of government and research institutions who played substantial roles either in decision-making or in research and advising on air pollution control in the BTH region. The results indicated that with the stringent air pollution control policies, the air quality in BTH meets the targets of the Air Pollution Prevention and Control Action Plan. However, improvements vary across the region and for different pollutants. Although implementation has been decisive and was at least in parts effectively enforced, significant challenges remained with regard to industrial and traffic emission control, and national air quality limits continued to be significantly exceeded and competing development interests remained mainly unsolved. There were also concerns about the sustainability of the current air pollution control measures especially for industries due to the top-down enforcement, and the associated large burden of social cost including unemployment and social inequity resulting industrial restructuring. Better mechanisms for ensuring cross-sectoral coordination and for improved central-local government communication were suggested. Further suggestions were provided to improve the conceptual design and effective implementation of respective air pollution control strategies in BTH. Our study highlights some of the major hurdles that need to be addressed to succeed with a comprehensive air pollution control management for the Chinese mega-urban agglomerations.