The Impact of Foreign Direct Investment on Income Convergence in China - A Spatial Panel Data Analysis

After taking into account the spatial dependence effects in the panel data consisting of all 31 provinces, direct-controlled municipalities, and autonomous regions in China between the years 1998 and 2017, it found significant spatial autocorrelation effects in both traditional absolute and conditional β income convergence models. At the national level, using the spatial econometric models (Spatial Error Model for absolute convergence and Spatial Durbin Model for conditional convergence), the analysis shows that in the past 19 years from 1999 to 2017, there is no absolute β income convergence. However, there is conditional β income convergence after controlling for all growth factors, while the positive effect of fixed asset investment on regional economic growth is significant, and the effect of population growth is significantly negative. The other growth factors such as FDI inflow, export, and higher education enrollment were surprisingly found no statistically significant effects on regional economic growth. From regional level (Spatial Durbin Model and Spatial Lag Model), there is no conditional β income convergence within each four economic regions. Nonetheless, the northeast region showed an income divergence trend, where only the fixed asset investment is positively significant. This study results imply that China should continue to improve fixed asset investment and control population growth to stimulate regional economic growth and income convergence.

High-speed railways and local economic performance: evidence from China’s prefecture-level cities

Purpose The purpose of this paper is to identify the causal effect of high-speed railways (HSRs) and investigate the affecting channels; the second purpose is to examine how HSRs change the distribution of economic activity across cities and sectors. Design/methodology/approach A difference-in-difference strategy is implemented to estimate the impact of recently built HSRs on local economic performance in China, exploiting the geography and time variations in HSR operations. Findings Using panel data from China’s City Statistical Yearbook 2001–2019, the authors find that HSRs lead to a significant increase in cities’ gross domestic product (GDP) and GDP per capita, but the authors do not find any significant change in GDP growth. This conclusion still holds true after the authors address the endogeneity problems. A mechanism analysis shows that HSRs improve local economic performance mainly by increasing fixed asset investment. The authors also find that the HSR investment is a policy that favors metropolitan areas due to the larger increase in the GDP for larger cities and with HSRs, the industrial and service sectors will further agglomerate in larger cities. Originality/value The authors contribute to the literature in several ways. First, this paper improves the estimation strategy in identifying the HSR impact on the local economic performance. Second, this paper investigates the affecting channels of HSRs. This paper proves that HSRs in China promote the cities’ economic performance mainly by increasing the fixed asset investment. Third, this study provides evidence for the new economic geography models pioneered by Krugman (1991).

Influencing Factors and Decoupling Analysis of Carbon Emissions in China's Manufacturing Industry

The manufacturing industry directly reflects national productivity, and it is also an industry with serious carbon emissions, which has attracted wide attention. This study decomposes the influential factors on carbon emissions in China’s manufacturing industry from 1995 to 2018 into industry value added (IVA), energy consumption (E), fixed asset investment (FAI), carbon productivity (CP), energy structure (EC), energy intensity (EI), investment carbon intensity (ICI) and investment efficiency (IE) by Generalized Divisia Index Model (GDIM). The decoupling analysis is carried out to investigate the decoupling states of the manufacturing industry under the pressure of "low carbon" and "economy.” Considering the technological heterogeneity, we study the influential factors and decoupling status of the light industry and the heavy industry. The results show that: (1) Carbon emissions of the manufacturing industry present an upward trend, and the heavy industry is the main contributor. (2) Fixed asset investment (FAI), industry value added (IVA) are the driving forces of carbon emissions. Investment carbon intensity (ICI), carbon productivity (CP), investment efficiency (IE), and energy intensity (EI) have inhibitory effects. The impact of the energy consumption (E) and energy structure (EC) are fluctuating. (3) The decoupling state of the manufacturing industry has improved. Fixed asset investment (FAI), industry value added (IVA) hinder the decoupling; carbon productivity (CP), investment carbon intensity (ICI), investment efficiency (IE), and energy intensity (EI) promote the decoupling.

Education Investment, Fixed Asset Investment and Regional Economic Development Differences——Empirical analysis based on Chinese

In this article, it discusses the differences in economic development between urban and rural areas and regions in our country from the perspective of education investment and fixed asset investment. Based on the provincial data of 31 provinces from 1999 to 2017 released by National Bureau of Statistics, it expends the Cobb-Douglas model and Lucas model, and analyses the data with multiple linear regression models. From the study, it finds that compared with investment in fixed assets, investment in education has a larger role in promoting economic development, which is more obvious in the underdeveloped central and western regions and rural areas. However, at the same time it needs to note that the positive effects of education investment will be restricted by the economic structure and policy environment, and education expenditure policies should also be implemented in accordance with time and local conditions.

Forecast China’s monthly urban fixed asset investment based on the ARIMA model

In recent years, as China’s urbanization level has risen, China’s urban fixed asset investment has also been rising. Judging from monthly data, China’s urban fixed asset investment has shown a volatile upward trend, with an obvious 11-month cycle. And in each cycle, the fluctuation range of the investment amount is getting larger. This paper uses an ARIMA model with an additive seasonal effect to fit the monthly urban fixed asset investment sequence and predict the future investment. In the end, this paper established a fitting model for China’s urban fixed asset investment, and obtained a good forecasting effect.

Accelerated Depreciation Tax Credit and Corporate Financialization Based on the PSM-DID Model

In this paper, we use the data of China’s manufacturing listed companies from 2009 to 2018, adopt the method of propensity score matching and double difference (PSM-DID) to solve the sample’s selective bias, and select the accelerated depreciation policy of fixed assets issued by China in 2014 as a quasi-natural experiment to verify the robustness of the empirical results, which will affect the R&D investment of manufacturing enterprises and the structural tax reduction of China. This paper makes an empirical study on the effect of fixed asset investment to restrain the financialization of manufacturing enterprises. The results show that (1) accelerated depreciation policy of fixed assets significantly promotes the R&D investment and fixed asset investment of enterprises and reduces the level of enterprise financialization; (2) accelerated depreciation of fixed asset local tax policy, through guiding the R&D investment, fixed asset investment, and deferred income tax acquisition of enterprises. It guides the investment of enterprises to the real economic field, thus reducing the financial assets of enterprises. The investment has restrained the financial trend of real enterprises. The conclusion of this paper is of practical significance to support the formulation and implementation of the national structural tax reduction policy and to clarify the regulatory role and mechanism of the structural tax reduction policy.