In a financial market where all investors have valuable private information, full rationality requires that investors have an unlimited ability of figuring out the equilibrium model. Instead, I assume that due to a lack of knowledge or experience, some investors do not know the equilibrium model and use only their private information in forming their demand. By investigating the investment behavior of these “boundedly rational” investors and contrasting it with that of the rational ones, I find that in a market where the two kinds of investors coexist, it is the boundedly rational investors who contribute to price stability. The welfare implication is that, although each investor benefits from conditioning his asset demand on the information transmitted by the equilibrium price, it can happen that all investors lose by doing so because the equilibrium price becomes too volatile.

We use disaggregated data by country and industry to empirically analyze the host country determinants of Chinese outward foreign direct investment (FDI) for the years 2003 to 2011. Our results suggest that the host-country determinants of Chinese FDI differ between high- and low-income countries. While all Chinese FDI is invariably market seeking, other motivations stand out for differing sectors in specific country groups. The resource seeking motivation is relevant for manufacturing FDI to high-income countries with relatively high fuel abundance, and to low-income countries with primary resource abundance (other than fuels). Differently, the strategic-asset seeking motivation, measured by the level of R&D spending on GDP, only positively and significantly affects Chinese manufacturing and service FDI to OECD countries, while higher education levels are an attraction factor for all investing firms. Natural resource is an important attraction factor for Chinese FDI, not only in resource-related sectors, but also in manufacturing and service sectors. Finally, Chinese FDI tends to follow exports (rather than foster them), especially in service sectors.

This paper studies a general equilibrium model of rural-urban migration in which manufacturing firms engage in oligopolistic competition and choose increasing returns technologies to maximize profits. Urban residents incur commuting costs to work in the Central Business District. Surprisingly a change in the size of the population or an increase in the exogenously given wage rate will not affect a manufacturing firm’s choice of technology. This helps to explain why firms in developing countries may not adopt labor intensive technologies even under abundant labor supply. An increase in the number of manufacturing firms increases both the employment rate and the level of employment in the manufacturing sector. However, manufacturing firms choose less advanced technologies. Capital accumulation leads manufacturing firms to choose more advanced technologies, but may not increase employment in the manufacturing sector.

In addition to the direct productivity effect, public capital also has an indirect effect on private capital stock and labor input. This paper offers an evaluation of both the direct and indirect effects of Chinese public capital by applying a trans-log aggregate production function including public capital stock to a panel of regional data from 1986–2009. Moreover, we calculate the impact of public capital on regional total factor productivity (TFP) performance by introducing a system GMM estimation. The results show that the output elasticity of Chinese public capital stock is significantly positive, but decreasing year on year, and public capital is found to be a substitute for labor but complementary to private capital input. Finally, public capital has a significant positive effect on regional TFP performance.

A small-scale, but highly-stylized dynamic stochastic general equilibrium model is estimated by the maximum likelihood method using Chinese quarterly data. Model specifications and parameter equalities between various competing model variants are addressed by formal statistical hypothesis tests, while implications for business cycle fluctuations are evaluated via a variance decomposition experiment, second-moments matching, and some out-of-sample forecast exercises. It is highlighted that the monetary authority takes an aggressive stance to the current inflation pressure (there is a significant lagged response), while leaving less attention to changes in aggregate output. Variance decomposition reveals that large percentages of variations in real and nominal variables are explained by the highly volatile preference and potential output shock, respectively. When nominal and real frictions as well as additional shocks are included, overall our estimated model can successfully reproduce the stylized facts from actual data of Chinese business cycles and frequently can even outperform those forecasts from an unconstrained VAR.

Based on the World Bank Investment Climate Survey, this paper investigates the openness effects on the efficiency of firms in China’s manufacturing industry using a two-step data envelopment analysis (DEA) approach. In the first step, the aggregate efficiency of open firms and non-open firms is compared in each sub-industry using a group-wise heterogeneous bootstrap procedure. The results show, at a 90% confidence level, that open firms are more efficient than non-open firms in four out of five sub-industries. Furthermore, in the second step, we employ the two-stage bootstrap DEA approach to more specifically evaluate the effects of openness on the efficiency of firms. The regression results show that three openness indicators (foreign capital, import and export) have strong positive effects on firms’ efficiency in China’s manufacturing industry. In addition, the results also suggest that a larger state share, larger firm size, and more capital stock are negatively related to the efficiencies of firms, while a firms’ learning and absorptive capacity is positively related to its efficiency.

Based on China Household Finance Survey (CHFS) data, China’s Gini Coefficient stood at 0.61 in 2010, above the global average of 0.44, according to the World Bank. The high Gini Coefficient represents a large income disparity of the country. It is understandable that a high Gini is common in fast-growing economies and can be reduced through government’s transfer payments given the experience of OECD countries. This paper illustrates the breakdown of China’s Gini, regional, rural and urban differences in household income. Specifically, it is found that poor health, insufficient social welfare and low education level are the main reasons for poverty of rural households. This paper also provides solutions to reduce the Gini coefficient. In the short term, China government can invest more on social insurance and implement large-scale transfer payments. The figure shows that China government has sufficient financial sources to strengthen secondary distribution to subsidize the low-income group. In the long term, government can increase overall educational level and reduce the opportunity inequality to narrow the income gap.