This paper discusses the benefits of investment in skills in China. We highlight the achievements China has made over time in human capital investments and the new challenges that have emerged as the country develops. To fuel China’s further economic growth and social developments, it is essential to take a more holistic view on skill investments. We suggest policies that promote both economic efficiency and social mobility.

Spatial autoregressive (SAR) models with varying coefficients are useful for capturing heterogeneous effects of the impacts of covariates as well as spatial interaction in empirical studies, and a wide range of popular models can be seen as its special cases, such as linear SAR models. In this study, we will propose a unified model selection method for the SAR model with varying coefficients to achieve two targets simultaneously: (1) variable selection (eliminate irrelevant covariates), and (2) identification of the covariates with constant effect among the relevant covariates. To do so, we follow the idea of group LASSO to incorporate two penalty functions to simultaneously do model selection and estimation. Monte Carlo experiments show that the proposed method performs well in finite samples. Finally, we illustrate the method with an application to the housing data of Chinese cities.

Over the last fifteen years, China rapidly expanded its outward foreign direct investment (OFDI) through remarkable economic growth and the “go global” policy. Chinese firms explored investment avenues especially in developing and emerging countries. As a result, China became the third largest contributor of OFDI. We examine the determinants of Chinese OFDI in 67 countries during the period lasting from 2006 to 2015 using the feasible generalized least square method. We find that the size of the economy, market opportunities, cost advantages due to low wage structure, ease of doing business, country risk, and geographical proximity are the prominent factors leading to changes in Chinese OFDI in developing and emerging economies. We find that China’s investments in different developing and emerging countries are driven by a different set of factors and the determinants of Chinese OFDI vary in low and high per capita income countries.

In this paper we design a compensation mechanism for the relocated households in the process of New-Type Urbanization in China. Based on the theories of dynamic rent spatial separation, bid-rent and non-renewable resource exploitation, we give a theretical look at how the current compensation mechanism shapes the welfare of relocated households. Firstly, land rent growth has a spatial difference and the growth rate of the marginal location rent is much higher than that of the mature site. Secondly, there is a demolition championship contest under the sole static money compensation, which can easily lead to land urbanization faster than population urbanization. Thirdly, in the long run the welfare loss of the household is mainly due to the absence of a dynamic compensation mechanism. Furthermore, we design a dynamic compensation mechanism based on the establishment of an asset securitization capital pool, which could be an alternative scheme in the process of New-Type Urbanization.

This paper focuses on the willingness to pay for green housing in China. First, we introduce green building related labels in China and briefly discuss the consumers’ incentives to buy this kind of building. Second, with the available transaction data in Shanghai, a hedonic regression model is applied to investigate whether or not a price premium in the residential market exists. Furthermore, we use the nonparametric matching model under a treatment framework to see the robustness of our results. The empirical result shows there exists a significant price premium in China. However, the premium does not increase with quality certification tiers. That may imply that homebuyers in China are not sensitive to the differences among green buildings although they are willing to pay a higher price for this newly emerging energy-saving building. And we also give the explanation why this has happened.

Sufficient evidence suggests that enterprises under strong government regulations suffer the economic effects of political connections, which not only leads to competitive disadvantages and loss of innovation, but also less willingness to take risks. This paper explores the relationship between political connections and corporate risk-taking behavior in corporate governance. Specifically, in 2008, the Chinese government announced new policies to regulate government officials concurrently holding the positions of independent directors in firms. We sample publicly listed firms in the Chinese A-share market over the period of 2005–2010 and investigate changes in risk-taking behavior due to the new policies. Our findings indicate that a reduction in politically connected independent directors may encourage risk-taking behavior subject to the factors of state ownership, industry regulations, local government control, and corporate characteristics.

This paper relaxes two assumptions on the traditional augmented Solow model: strict concavity of production functions and dual capital goods. It generalizes traditional conclusions of the Solow model by demonstrating that neoclassical properties of a production function are sufficient for the existence and global stability of the steady state in the augmented Solow model with multiple capital goods. Moreover, we prove necessity of essentiality of inputs for a neoclassical production function and generalize the golden rule of capital accumulation.