Evaluation of the green technology innovation efficiency of China's manufacturing industries: DEA window analysis with ideal window width

Data Envelopment Analysis (DEA) window analysis with ideal window width is applied to evaluate the green technology innovation efficiency of 28 manufacturing industries in China during 2006–2014. The obtained results are compared with those calculated using the traditional DEA model, and convergence analysis of the efficiency is conducted. Five years is the obtained ideal window width and DEA window analysis with ideal window produces results closer to reality for China's manufacturing industry. The overall efficiency of the green technology innovation in the manufacturing sector is low following a wave-shaped curve – first decreasing, then increasing and decreasing again, with large inter-industrial differences. There are 8 high-, 14 medium- and 6 low-efficiency industries. A convergence trend in the green technology innovation efficiency within the 28 manufacturing industries exists, implying a catch-up effect between them.     

Supply‐ versus Demand‐Side Policies in the Presence of Carbon Leakage and the Green Paradox

We consider a climate coalition that seeks to reduce global emissions in the presence of carbon leakage and resource exhaustibility. We show that a credible announcement of future unilateral supply‐side policies delays foreign emissions, and we derive the optimal combination of consumer taxes and producer taxes when we consider leakages from free riders, both within periods and across periods. The tax shares generally differ over time. A decline in the present value of the social cost of carbon over time supports a time path where the consumers’ tax share of the total carbon tax also declines over time. We illustrate our findings with a numerical model.     

Can Industrial Restructuring Significantly Reduce Energy Consumption? Evidence from China

This article uses China’s input–output (I-O) tables in 2002, 2007, and 2012 to estimate the real energy consumption of each sector after the I-O adjustment. The relationship between the sectors is further analyzed using the utility analysis method based on ecological network analysis. The empirical results show that although the traditional energy-intensive industries are the major energy-consuming sectors from a direct energy consumption perspective, large energy consumption by energy-intensive industries is transferred to downstream industries through intermediate products after the I-O adjustment. Specifically, the building industry and service sector are the sectors with the highest real energy consumption. With the upgrading and optimization of the industrial structure, the proportion of energy-intensive sectors in China is declining. However, the development of the service sector and infrastructure construction still requires large intermediate inputs. Thus, industrial restructuring cannot significantly reduce China’s total energy consumption.     

Do country risk and financial uncertainty matter for energy commodity futures?

Using an instrumental variable quantile regression technique, this paper assesses whether country risk and financial uncertainty exert an impact on energy commodity futures prices under different commodity conditional return distributions over the period from January 1994 to July 2017. We also discuss whether the correlations change with different dimensions of country risk, that is economic, financial, and political. The results reveal that country risk and financial stress do have a significant impact on energy commodity returns of futures contracts with different maturities, but their direction, intensity, and significance differ, caused by the distinct market situations and divergent channels of country risk.     

Determinants of energy use in the informal food sector

Although enterprises in the informal food sector require energy to transform, cook and process food, energy-use patterns in this sector are not well understood by policymakers and the local-level authorities who regulate their trading activities. This paper reviews relevant literature and presents empirical data collected in Rwanda, Senegal and South Africa on the use of traditional and modern energy sources by informal food sector operators. Our sample includes male- and female-operated enterprises in the urban centres of three African countries where the informal food sector is important, not only for providing the convenience of affordable and readily prepared meals, but also as a source of income for women and men in developing countries. Multiple fuel-use and energy-stacking strategies are common among informal food enterprises and policy needs to acknowledge this if it is to intervene in ways that will benefit both enterprises and regulators.     

Then and Now: Examining Older People's Engagement in Outdoor Recreation Across the Life Course

Outdoor recreation provides a range of health and wellbeing benefits and facilitates engagement with natural environments. We explore older people's participation in outdoor recreation throughout their lives to examine how past experiences shape engagement later in life. A qualitative life history approach, consisting of semi-structured interviews and a focus group in three place-specific (urban, rural, and small town coastal) case studies in Scotland, was adopted. Thematic analysis revealed ways in which childhood experiences shaped adult engagement and highlighted life course transitions where behaviour change was most pronounced. Place and gender were considered as factors which may affect responses. Participants identified the points of getting married, becoming a parent, children entering adolescence, retirement, the onset of disabilities or ill health, and the death of others as “moments of change” in the extent and/or form of their outdoor recreation. The findings highlight potential for targeted interventions to promote outdoor recreation throughout life.     

Probabilistic access forecasting for improved offshore operations

Improving access is a priority in the offshore wind sector, driven by the opportunity to increase revenues, reduce costs, and improve safety at operational wind farms. This paper describes a novel method for producing probabilistic forecasts of safety-critical access conditions during crew transfers. Methods of generating density forecasts of significant wave height and peak wave period are developed and evaluated. It is found that boosted semi-parametric models outperform those estimated via maximum likelihood, as well as a non-parametric approach. Scenario forecasts of sea-state variables are generated and used as inputs to a data-driven vessel motion model, based on telemetry recorded during 700 crew transfers. This enables the production of probabilistic access forecasts of vessel motion during crew transfer up to 5 days ahead. The above methodology is implemented on a case study at a wind farm off the east coast of the UK.     

Is it still economic to build a new coal-fired power plant in the U.S.? A real option analysis

In the U.S., virtually no new coal-fired power plants have been built in recent years. Both industry experts and academics seem to believe that no rational firm will build a new coal-fired plant. Will such a trend continue in the future? To provide insights into this question, we investigate the optimal decision of an electricity company with an irreversible and deferrable opportunity to build either a new coal-fired or natural gas-fired power plant as its new base-load resource. According to our real option analysis, the optimal decision depends on the location. In the case of the eastern U.S., it is optimal to choose a natural gas plant if a firm is given a choice among a new natural gas plant, a new coal plant and deferring the investment. However, contrary to the common sentiment in the industry and academia, building a new coal plant in the western U.S. is still more economical than building a new natural gas plant in the absence of emission pricing. Furthermore, introducing carbon pricing to western U.S. states, as California did, can substantially increase the probability that a firm will optimally choose a natural gas plant over a coal plant.     

Peer effects in the diffusion of water‐saving agricultural technologies

We investigate the role of peer effects in the diffusion of an important water‐saving irrigation technology: low energy precise application (LEPA). Using detailed irrigation behavior data for growers in the High Plains Aquifer region of Kansas covering 1990–2014, we find clear evidence of peer influence in adoption of LEPA, net of environmental factors. Specifically, an additional neighboring LEPA installation within 1 km increases the probability of adoption by about 0.3 percentage points, on average, and this effect diminishes with distance. Our empirical estimates indicate that in the absence of peer effects, LEPA adoption would have been about 10% lower (1,000–1,600 fewer installations) per year. In addition, we find that growers install LEPA in response to higher energy prices.     

Why invest in green technologies? Sustainability engagement among small businesses

This study examines the links between sustainability engagement and green technology investments. Using data on 139 Finnish small businesses, the results show a positive relationship between the two. The sustainability engagement of small businesses affects their interest in investing in green technology. However, engagement in environmental sustainability does not seem to be the main motivator behind green technology investments. The results of the mediation analysis show that when investing in green technologies, companies do not consider environmental sustainability as a main value but as a way of achieving social and economic value.