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Innovation ability has become one of the core elements in the pursuit of China’s green growth, and high-tech industries are playing a leading role in technological innovation in China. With the rapid development of China’s high-tech industries, their innovation efficiency has attracted widespread attention. This article aims to illustrate a shared inputs two-stage network Data Envelopment Analysis (DEA), to measure the innovation efficiency of high-tech industries in China’s 29 provinces from 1999 to 2018. The results indicate that there are obvious differences in the innovation efficiency of the provinces. The technology development efficiency, the technical transformation efficiency, and the overall innovation efficiency of the developed east coast provinces are generally higher than those of the backward central and western provinces. This article further applies the spatial econometrics model to analyze the factors influencing the innovation efficiency of high-tech industries. We have found that government support, R&D input intensity, industries aggregation, economic extroversion, and the level of development of the modern service industries cause varying degrees of impact on innovation efficiency.

AbstractThere is close relationship between science & technology inputs and economic growth. Based on the data of science & technology input and economic growth, the paper makes the econometric models analysis on the economic growth and science & technology input of the three major coastal economic regions of China. The paper analyzes and compares the contribution rate of science & technology inputs to economic growth of the three major economic regions.

This article presents a model of development, civil war and climate change. There are multiple interactions. Economic growth reduces the probability of civil war and the vulnerability to climate change. Climate change increases the probability of civil war. The impacts of climate change, civil war and civil war in the neighbouring countries reduce economic growth. The model has two potential poverty traps – one is climate-change-induced and one is civil-war-induced – and the two poverty traps may reinforce one another. The model is calibrated to sub-Saharan Africa and a double Monte Carlo analysis is conducted in order to account for both parameter uncertainty and stochasticity. Although the IPCC Special Report on Emission Scenarios (SRES) is used as the baseline, thus assuming rapid economic growth in Africa and convergence of African living standards to the rest of the world, the impacts of civil war and climate change (ignored in SRES) are sufficiently strong to keep a number of countries in Africa in deep poverty with a high probability.

Consumer interest in farmers’ markets (FMs) has dramatically increased during the past decade. The number of FMs in the United States has grown from 1755 in 1994 to 8140 in 2019 (USDA, 2019). To evaluate the economic impacts (EIs) of FMs in the Washington, DC metropolitan area, we collected FMs’ consumer data and used IMPLAN-based social accounting matrices to evaluate the direct, indirect, and induced economic impacts of FMs. The empirical results from IMPLAN provide the direct gross sales, income figures, and an estimate of the number of jobs in the study region. The results show the average total output of USD 36,181,059, total employment of 663 people, total value-added creation of USD 19,019,226, and total labor income created of USD 8,653,350 in the region. The FM average income multiplier is 1.51, which indicates that a USD 1 increase in personal income (PI) for an FM translates into USD 1.51 in PI across the economy of the region. We also highlight the impact of FMs as an important component of the circular economy (CE). To this end, we present a qualitative approach examining the potential of a CE as applied to the farmers’ markets in the Washington, DC metropolitan area using qualitative data from focus groups. The goal of the circular economy is to provide more sustainability in the local economy.

With rapid progress in the corporate social responsibility (CSR) theories and the up-gradation of the global market information disclosure system, enterprises have increased their attention toward relevant stakeholders and social responsibility. CSR exerts a substantial impact on the sustainable development of enterprises and markets in the economic and social fields. On the one hand, the increasingly perfect supporting facilities promote the financial growth of the entire society. While on the other hand, the profit-seeking trend of capital is also on the rise. The incongruity between the rapid progress of enterprises and the lack of social responsibility limits the benign development of the market. This study discusses the antecedents of CSR from the variable combination perspective using the fuzzy-set qualitative comparative analysis. It also investigates which combination of characteristics has better CSR performance. After the configuration analysis, it is identified that four paths lead to high CSR performance. These include the market-developed type, political link type, financial performance type, and state-owned enterprise subsidy type, and the level of each type is explained in-depth. Finally, this study provides management inspiration for the government and enterprises to formulate a sound social responsibility strategy and improve CSR performance by optimizing the matching of CSR activities and business objectives.

Our paper analyzes the sources of labor productivity variation in U.S. bituminous coal surface mining from 1960 to 1976. The coal mining industry was among the first to experience a prolonged decline in labor productivity in the post-World War II period. In surface mining nationally, labor productivity in 1977 was 26.6 tons per worker-day, or 28 percent less than the peak of 36.7 tons per worker-day achieved in 1973. Moreover, in several major coal-producing states, the decline began much earlier and was more dramatic. For example, in West Virginia (the first state to experience declining productivity) the loss in productivity between 1965, the year in which productivity in the state peaked, and 1976 was nearly 52 percent. Eastern Kentucky experienced an even larger drop of 56 percent between 1967 and 1976. It was only the expansion of surface mining to western states in the 1970s that delayed the appearance of a national decline in productivity until the early 1970s. The industry has thus foreshadowed the labor productivity declines that subsequently occurred in other industries.

The upsurge in higher education is considered a key determinant for enhancing green growth. Moreover, ICT development is also the main catalyst of green growth. This research explores the role of higher education and ICT on green growth for China from 1995 to 2020. The study employs auto-regressive distributive lag (ARDL) approach for short-run and long-run estimates of green growth. The effect of higher education and ICT on green growth is significantly positive in the long run and short run. The outcomes of the empirical models reveal that financial inclusion is positively associated with green growth in both long run and short run. Moreover, renewable energy consumption is found to have a positive impact on green growth. The findings thus point to the need for policies that promote human capital and ICT infrastructure as a way of accelerating green growth.

Were the large investments in energy and transportation infrastructure effective in fostering economic growth? Or did economic growth trigger these infrastructure developments? To answer these questions, we develop a simple model of production capacity constraints and use China’s Western Development Strategy (WDS) as an example to investigate how the relationships among energy investment, transportation infrastructure expansion and economic growth differ in the pre- and post-WDS periods. Our Granger causality analysis uses a panel data sample for China’s 30 provinces in the Western and non-Western regions for the period of 1991-2012. We find Granger causality only in the post-WDS period from transportation infrastructure expansion to economic growth and from economic growth to energy investment. These results suggest energy and transportation capacity constraints in the post-WDS period but not the pre-WDS period. Their policy implication is that China should continue its energy and transportation infrastructure investments with improved coordination.