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AbstractRenewable Portfolio Standards (RPS) are U.S. state mandates that utilities produce some of their electricity using renewable energy sources in an effort to reduce greenhouse gas emissions. While advocates highlight the potential long‐term benefits of RPS, critics argue that RPS will increase electricity prices due to the higher costs of renewable energy generation. However, to date, there are no published empirical studies of the effect of RPS on electricity prices. Using state‐level panel data from 1990 to 2011 and the difference‐in‐differences method, I find that implementation increases electricity prices when the RPS policy first becomes binding.

AbstractIn this paper, we advance the empirical literature on US state and local fiscal policymaking by using the synthetic control method (SCM) to create pairwise matches for states in subsequent regression analysis of the relationships between state and local fiscal policies and several state economic outcomes. Additional contributions include the use of principal component analysis to construct broader narratives of state economic performance and to reduce the dimensionality of the characteristics used in SCM matching, while the regressions also include variables to control for post‐matching economic shocks. Compared to conventional regression analysis, the SCM matching‐regression approach better addresses potential endogeneity, reduces interpolation bias, and creates fiscal policy measures that better reflect policy differences. The SCM‐matched regressions produce more statistically significant relationships between state and local fiscal variables and economic outcomes than do the conventional unmatched regressions, suggesting improved identification of state and local fiscal policy effects on economic outcomes. Robust relationships found include negative economic effects of the own‐source revenue burden and property taxes. Consistent with the existing literature, the estimated fiscal policy effects are quantitatively small and unlikely to drive differences in state economic performance.

Using the 3‐year microdata sample of the American Community Survey for 2009–2011, we examine the effect of state‐level public school teacher salaries relative to those of other college graduates in the state not employed in education on the decision to teach. We find that relative teacher salaries in the state positively affect the share of education majors that are employed as public school teachers at the time of the survey. The effect for males majoring in math, science, and computer education is largest among all estimated effects. A statistically significant effect is also found among females majoring in elementary education. (JEL H75, I20, R23)

Purpose: Electric vehicles industry has gotten a rapid development in the world, especially in the developed countries, but still has a gap among different countries or regions. The advanced industrialization experiences of the EVs in the developed countries will have a great helpful for the development of EVs industrialization in the developing countries. This paper seeks to research the industrialization path & prospect of American EVs by forecasting electric vehicles demand and its proportion to the whole car sales based on the historical 37 EVs monthly sales and Cars monthly sales spanning from Dec. 2010 to Dec. 2013, and find out the key measurements to help Chinese government and automobile enterprises to promote Chinese EVs industrialization. Design/methodology: Compared with Single Exponential Smoothing method and Double Exponential Smoothing method, Triple exponential smoothing method is improved and applied in this study. Findings: The research results show that: American EVs industry will keep a sustained growth in the next 3 months. Price of the EVs, price of fossil oil, number of charging station, EVs technology and the government market & taxation polices have a different influence to EVs sales. So EVs manufacturers and policy-makers can adjust or reformulate some technology tactics and market measurements according to the forecast results. China can learn from American EVs polices and measurements to develop Chinese EVs industry. Originality/value: The main contribution of this paper is to use the triple exponential smoothing method to forecast the electric vehicles demand and its proportion to the whole automobile sales, and analyze the industrial development of Chinese electric vehicles by American EVs industry. ; Peer Reviewed

Purpose: Electric vehicles industry has gotten a rapid development in the world, especially in the developed countries, but still has a gap among different countries or regions. The advanced industrialization experiences of the EVs in the developed countries will have a great helpful for the development of EVs industrialization in the developing countries. This paper seeks to research the industrialization path & prospect of American EVs by forecasting electric vehicles demand and its proportion to the whole car sales based on the historical 37 EVs monthly sales and Cars monthly sales spanning from Dec. 2010 to Dec. 2013, and find out the key measurements to help Chinese government and automobile enterprises to promote Chinese EVs industrialization. Design/methodology/approach: Compared with Single Exponential Smoothing method and Double Exponential Smoothing method, Triple exponential smoothing method is improved and applied in this study. Findings: The research results show that: (1) American EVs industry will keep a sustained growth in the next 3 months. (2) Price of the EVs, price of fossil oil, number of charging station, EVs technology and the government market & taxation polices have a different influence to EVs sales. So EVs manufacturers and policy-makers can adjust or reformulatesome technology tactics and market measurements according to the forecast results. And (3) China can learn from American EVs polices and measurements to develop Chinese EVs industry. Originality/value: The main contribution of this paper is to use the triple exponential smoothing method to forecast the electric vehicles demand and its proportion to the whole automobile sales, and analyze the industrial development of Chinese electric vehicles by American EVs industry.

Purpose: Electric vehicles industry has gotten a rapid development in the world, especially in the developed countries, but still has a gap among different countries or regions. The advanced industrialization experiences of the EVs in the developed countries will have a great helpful for the development of EVs industrialization in the developing countries. This paper seeks to research the industrialization path & prospect of American EVs by forecasting electric vehicles demand and its proportion to the whole car sales based on the historical 37 EVs monthly sales and Cars monthly sales spanning from Dec. 2010 to Dec. 2013, and find out the key measurements to help Chinese government and automobile enterprises to promote Chinese EVs industrialization. Design/methodology: Compared with Single Exponential Smoothing method and Double Exponential Smoothing method, Triple exponential smoothing method is improved and applied in this study. Findings: The research results show that: American EVs industry will keep a sustained growth in the next 3 months. Price of the EVs, price of fossil oil, number of charging station, EVs technology and the government market & taxation polices have a different influence to EVs sales. So EVs manufacturers and policy-makers can adjust or reformulate some technology tactics and market measurements according to the forecast results. China can learn from American EVs polices and measurements to develop Chinese EVs industry. Originality/value: The main contribution of this paper is to use the triple exponential smoothing method to forecast the electric vehicles demand and its proportion to the whole automobile sales, and analyze the industrial development of Chinese electric vehicles by American EVs industry. ; Peer Reviewed

The paper presents the position and load reference generation for a motor stand simulating a mechatronic chain, in this case a three degree of freedom robot leg. The task is accomplished using three PLC controlled motors in position as the robot joint actuators coupled with three controlled in torque, simulating the load at each simulation time-step. The paper briefly discusses the mathematical model and presents the visual interface used in the simulation, which is then to be further integrated into a virtual environment robot control application.

"Available online 12 January 2018" ; Several polyesters were synthesized from ethylene glycol, glycerol and adipate, succinate dimethyl esters. Immobilized Candida antarctica lipase B was used as catalyst for 6hours under vacuum at 70°C without any further solvents. The highest conversion rate of 88.5% occurred for the polymerization of poly (ethylene adipate), evaluated by 1H NMR. MALDI-TOF analysis indicated that most of the oligomers formed were dimers or trimers. After successfully synthesize the polyesters we set-up the optimal conditions for their in-situ coating onto cotton substrates with a soluble lipase from Thermomyces lanuginosus. This work presents a novel bio-approach to impart hydrophobic properties to coated cotton-based fiber materials. ; This work was supported by Chinese government scholarship under the State Scholarship Fund (grant number 201706790049), Jiangsu Province Scientific Research Innovation Project for Academic Graduate Students (grant number KYLX16_0788), Training Fund for Excellent Doctoral Student in Jiangnan University, Key Projects of governmental cooperation in international scientific and technological innovation (grant number 2016 YFE0115700) and the National Key R & D Program of China (grant number 2017 YFB0309100). This work was also supported by the Portuguese Foundation for Science and Technology (FCT) under the scope of the strategic funding of UID/BIO/04469/2013 unit and COMPETE 2020 (grant number POCI-01-0145-FEDER-006684) and under the Project RECI/BBB-EBI/0179/2012 (grant number FCOMP01-0124-FEDER-027462). This study was also supported by BioTecNorte operation (grant number NORTE-01-0145-FEDER000004) funded by the European Regional Development Fund under the scope of Norte2020 – Programa Operacional Regional do Norte. This work was also supported by the National Natural Science Foundation of China (grant number 31470509 and 31201134), the Industry-Academic Joint Technological Prospective Fund Project of Jiangsu Province (grant number BY2013015-24 and ...