Education, as an investment in human capital, is regarded as an important determinant of sustainable economic growth [¹,²]. The purpose of this study is to explore the cointegration and causality between the investment in education and sustainable economic growth in Guangdong province by using the panel data of 21 cities from 2000 to 2016. We construct a variable intercept panel data model with an individual fixed effect based on the Cobb-Douglas production function, estimating the contribution of the investment in education to economic growth by introducing lags. The findings show the existence of the feedback causality between education and sustainable economic growth. Also, the results reveal that the local financial investment in education plays a positive and statistically significant role in promoting sustainable economic growth. However, the contribution of the local financial investment in education to economic growth varies in different areas. The investment in education in the Pearl River Delta region have the most obvious pull effects on its regional economy, whereas the Western region takes the second place. Meanwhile, the local financial investment in education for its role in promoting economic growth obviously has a two-year hysteresis effect. These findings have important implications for Guangdong’s solution to the imbalance between regional educational investment and sustainable economic growth.

This study develops a biennial Malmquist–Luenberger productivity index that is used to measure the sources of economic growth by utilizing data envelopment analysis and the directional distance function. Taking restrictions on resources and the environment into account based on the green growth accounting framework; we split economic growth into seven components: technical efficiency change, technological change, labor effect, capital effect, energy effect, output structure effect and environmental regulation effect. Further, we apply the Silverman test and Li-Fan-Ullah nonparametric test in combination with kernel distribution to test for the counterfactual contributions at the provincial level in China from 1998 to 2012. The empirical results show that: (1) technological progress and TFP make positive contributions to economic growth in China, while technical efficiency drags it down; (2) the effect of output structure and CO₂ emissions with environmental regulation restrain economic growth in some provinces; and (3) overall, physical capital accumulation is the most important driving force for economic take-off, irrespective of whether the government adopts environmental regulations.

By adjusting direction vectors, we are able to measure technical efficiency incorporating risk preference of individual banks using non-parametric and parametric approaches. Furthermore, we explore categories of commercial banks by comparing their risk preferences to the risk preference that optimizes technical efficiency. Three results emerged. First, technical efficiency scores of joint stock and city commercial banks surpassed those of state-owned commercial banks under the optimal risk preference, and technical efficiency generally improved over time. Second, the preference for risk balance was optimal for achieving technical efficiency. Third, a larger proportion of state-owned and joint stock commercial banks fall into the preference for risk neutral category than city commercial banks.

By adopting an energy-input based directional distance function, we calculated the shadow price of four types of energy (i.e., coal, oil, gas and electricity) among 30 areas in China from 1998 to 2012. Moreover, a macro-energy efficiency index in China was estimated and divided into intra-provincial technical efficiency, allocation efficiency of energy input structure and inter-provincial energy allocation efficiency. It shows that total energy efficiency has decreased in recent years, where intra-provincial energy technical efficiency drops markedly and extensive mode of energy consumption rises. However, energy structure and allocation improves slowly. Meanwhile, lacking an integrated energy market leads to the loss of energy efficiency. Further improvement of market allocation and structure adjustment play a pivotal role in the increase of energy efficiency.