• Environmental and Resource Economics Review
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• v.23 no.3
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• pp.473-496
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• 2014

This paper intends to test the non-linear relationship between $CO_2$ emissions and income by employing cointegration model of the time-varying income elasticity. We select France, UK, Italy, Japan, US, China, India, Mexico and Korea and use non-parametric time series analysis on each country in order to estimate its own effect of income on $CO_2$ emission. The main results indicate that the $CO_2$ emission-income elasticities vary over time and the income elasticities of the Annex I countries tend to be higher in absolute terms than those of developing countries. In addition, we find that emission-income elasticities decrease for Annex I countries over time, whereas those for developing countries increase.

• Environmental and Resource Economics Review
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• v.26 no.4
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• pp.519-547
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• 2017

This paper explores whether it is better to forecast city gas demand in Korea using national level data directly or, alternatively, construct forecasts from regional demand models and then aggregate these regional forecasts. In the regional model, we consider gas demand for Seoul metropolitan and the other local areas. Our forecast evaluation exercise for 2013-2016 shows the regional forecast model generally outperforms the national forecasting model. This result comes from the fact that the dynamic properties of each region's gas demands can be better taken into account in the regional demand model. More specifically, the share of residential gas demand in the Seoul metropolitan area is above 50%, and subsequently this demand is heavily influenced by temperature fluctuations. Conversely, the dominant portion of regional gas demand is due to industrial gas consumption. Moreover, electricity is regarded as a substitute for city gas in the residential sector, and industrial gas competes with certain oil products. Our empirical results show that a regional demand forecast model can be an effective alternative to the demand model based on nation-wide gas consumption and that regional information about gas demand is also useful for analyzing sectoral gas consumption.