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| 1 |
ID:
094946
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2010.
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| Summary/Abstract |
About ten years have passed since the deregulation of the U.S. retail electricity market, and it is now generally accepted that the available data is adequate to quantitatively assess and compare conditions before and after deregulation. This study, therefore, estimates the changes in price elasticity in the residential electricity market to examine the changes, if any, in household sensitivity (as a result of retail electricity market deregulation policies) to residential electricity rates. Specifically, six types of panel data are prepared, based on three cross-sections-all states (except for Alaska and Hawaii) and the District of Columbia, deregulated states, and non-deregulated states-and two time series-the period before deregulation and the period after deregulation. The panel empirical analysis techniques are used to determine whether or not the variables are stationary, and to estimate price elasticity. We find that there is no substantial difference in the price elasticity between deregulated and non-deregulated states for both periods-before deregulation and after deregulation. Thus, it can be said that the deregulation of the retail electricity market has not made consumers more sensitive to electricity rates and that retail deregulation policies are not the cause of price elasticity differences between deregulated and non-deregulated states.
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| 2 |
ID:
089548
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2009.
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| Summary/Abstract |
This paper examines economic returns to schooling in urban China using ordinary least square (OLS) and instrumental variable (IV) methodologies. First, we find that OLS estimates of the returns to education are lower in China than in other transition economies, whereas IV estimates are higher in China. Second, we find that OLS, a method for estimating the returns to education without control for endogeneity bias, may underestimate the true rates of return for men. In addition, if we do not control for endogeneity bias and the sample selection bias, we may further underestimate the true rates of return for women. Finally, we find that OLS estimates of the returns to education for men are slightly higher than for women. The IV estimates for women are higher than those for men, and this difference increases after correcting for selectivity biases.
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| 3 |
ID:
103330
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2011.
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| Summary/Abstract |
This paper constructs panel data from an 11-year data set on all 47 prefectures of Japan, covering the period 1996-2006 . We use this data set to analyze the factors affecting photovoltaic (PV) system diffusion. Our empirical results show that the regional government policy clearly helps to promote PV system adoption. It is also found that installation costs have a significant negative effect on PV system adoption, whereas housing investment and environmental awareness among residents have a positive effect. We believe that this finding has a significant implication for further PV system diffusion because it suggests the importance of regional diffusion policies reflecting the environmental awareness of regional residents.
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| 4 |
ID:
090109
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2009.
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| Summary/Abstract |
Since 2003, China's labor market has been facing two coexisting crises: a rural labor surplus and a severe shortage of migrant labor. Using data from the 2000 China Health and Nutrition Survey questionnaire, which covers 288 villages in 36 counties, this paper attempts to find a solution to this dilemma. Specifically, a multinomial logit model, a Mincer-type model and a probit model are applied to examine the effect of educational level on the employment choices for rural laborers, and on the wages and the employment status of migrants. Based on the results of our analysis, we propose the implementation of policy aimed at increasing the educational level of rural dwellers, in conjunction with other policies to eliminate all artificial barriers, to facilitate the migration of rural laborers.
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| 5 |
ID:
125789
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2013.
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| Summary/Abstract |
We apply the lag-augmented vector autoregression technique to test the Granger-causal relationships among wholesale electricity prices, natural gas prices, and crude oil prices. In addition, by adopting a cross-correlation function approach, we test not only the causality in mean but also the causality in variance between the variables. The results of tests using both techniques show that gas prices Granger-cause electricity prices in mean. We find no Granger-causality in variance among these variables.
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