-Cheng Kuo

In Search of Causal Relationship between FDI, GDP, and Energy Consumption - Evidence from China

The balance between economic growth and environmental protection has been the core concern of policy makers in developing countries for the past two decades. This study is one of the few studies to empirically inspect the relationship between economic growth, FDI, and energy consumption over the period 1978-2010 in China. The results reveal that there is a unidirectional Granger causality running from GDP to energy consumption. This suggests that increase of GDP will consume more energy and implementing of the energy conservation policies and energy demand management policies in China may not have negative impact on economic growth. Besides, a bi-directional Granger causality has been found between energy consumption and FDI. This implies that Chinese government should cautiously evaluate the positive and negative effects of FDI inflows and put efforts into making more effective control policies on environmental protection.

The Causal Relationship between Gross Domestic Product, Exports, Energy Consumption, and CO2 in Thailand

This study examines the Granger causality relationship between gross domestic product (GDP), exports, energy consumption (EC) and CO2 emissions in Thailand for the period of 1965 to 2010. The results show six bidirectional causality relationships between GDP and exports, GDP and EC, GDP and CO2 emissions, exports and EC, exports and CO2 emissions, as well as EC and CO2 emissions. The finding of this research has powerful policy implication for Thailand. The policy makers are under pressure from the environmental representatives to reduce CO2 emissions although the state still faces enormous challenge to improve its economy. Therefore, GDP, exports and CO2 emissions are associated with EC. Also, energy consumption, exports or GDP will cause to CO2 emissions then policy makers in Thailand encounter a main dilemma as the environmental degradation through CO2 emissions would worsen the life in the long-run. The policy makers should pay higher attention to invest energy infrastructure, encourage using less polluting or renewable energy sources, educate public awareness, upgrade energy efficiency, or offer tax credit to meet the increasing energy demands but can promote economic growth and exports at the same time.

Energy Consumption, GDP, and Foreign Direct Investment in Germany

This research studies the causal relationship between energy consumption, gross domestic product (GDP), and foreign direct investment (FDI) in Germany for a period of 1971-2010. The empirical results reveal that there is a unidirectional causality running from GDP to energy consumption and from GDP running to FDI in Germany. This is due to the highly rising trends of economic activities in the country which can lead to the expansion in energy consumption. As there is an increase in economic activities within the country, then the growth rate will be in the rising path. As a result, the foreign investors will see the promising future and then invest in the host country. The conservative energy policy is recommended to support the energy saving because it will have little or no adverse effect on GDP. The energy efficiency should be applied by encouraging the use of renewable energy sources in economic activities as an alternative to stimulate the economic growth of the country. Also, the public expenditure should be expanded to increase the country’s economy and attract foreign investors. In addition, the government should support for the service industry such as insurance, finance and banking, and tourism because this type of industry does not consume as much energy as the manufacturing industry does in the overall manufacturing processes. Besides, the government should provide tax credit for the manufacturers who can fulfill the energy efficiency for their operation.

Energy Consumption Forecasting in Hong Kong Using ARIMA and Artificial Neural Networks Models

There have been considerable efforts contributed to the development of effective energy demand forecast models due to its critical role for economic development and environmental protection. This study focused on the adoption of artificial neural network (ANN) and autoregressive integrated moving average (ARIMA) models for energy consumption forecasting in Hong Kong over the period of 1975-2010. Four predictors were considered, including population, GDP, exports, and total visitor arrivals. The results show most ANN models demonstrate acceptable forecast accuracy when single predictor is considered. The best single input model is the case with GDP as predictor. Population and exports are the next proper single inputs. The model with total visitor arrivals as sole predictor does not perform satisfactorily. This indicates that tourism development demonstrates a different pattern from that of energy consumption. In addition, the forecast accuracy of ANN does not improve considerably as the number of predictors increase. Findings imply that with the ANN approach, choosing appropriate predictors is more important than increasing the number of predictors. On the other hand, ARIMA generates forecasts as accurate as some good cases by ANN. Results suggest that ARIMA is not only a parsimonious but effective approach for energy consumption forecasting in Hong Kong.

Deploying Arima and Artificial Neural Networks Models to Predict Energy Consumption in Taiwan

With the aim of predicting Taiwan’s energy consumption for the short term (1 year), the medium term (3 years), the medium-long term (5 years), and the long term (10 years), this study applies autoregressive integrated moving average (ARIMA) models and artificial neural networks (ANNs) models and the mean absolute percentage error (MAPE) approach is employed to measure prediction accuracy. Based on data extracted from over the period 1965–2010, the results indicate that the single variable ARIMA models illustrate superior performance than that of ANNs1. As to multivariable models, ANNs8 model including variables of energy consumption and exports show the most accurate prediction in short term and medium-long term, while ANNs6 model comprising energy consumption, GDP, and exports has the highest accuracy for medium term prediction. Meanwhile, ANNs5 model consisting of energy consumption and population shows the best accuracy for the long term prediction. Overall, it may conclude that exports and population are two essential variables to predict Taiwan’s energy consumption for the short, medium, medium-long, and long term periods. The results support the assumption that parsimonious set of variables incorporated in research models may not sacrifice prediction accuracy. This concludes the contributions of this study.

Effect of Tourism Development on Energy Consumption, CO2 and Economic Growth in China

This study examines the effect of tourism development on energy consumption, CO2 and economic growth in China over the period from 1981 to 2010. An extension of ARIMA model was performed to investigate the relationship between variables. Two principle test results emerge from this study. First, increases on visitors may largely give rise to GDP. On the other hand, increase on tourism receipts may result in greater energy consumption and CO2 emission to some extent as compared to number of visitors. However, the amount of effects from either tourism receipts or number of visitors to energy consumption and CO2 emission are limited. From an energy conservation and economic growth point of view, the results support the hypothesis of tourism-led economic growth in the China economy with relatively limited increase of energy consumption and CO2 emission.

Economic Growth, Energy Consumption and Tourism Development in Taiwan: A Granger Causality Approach

This study examines the causal relationship among economic growth, energy consumption and tourism development in Taiwan over the period from 1965 to 2010. Three Principle test results emerge from this study. First, test results indicate a long-run equilibrium relationship and a bi-direction of causality between energy consumption and tourism development with one proxy, number of visitors, being more significant than the other, visitor expenditures. Second, a bi-directional causality between energy consumption and economic growth is observed. Third, test results indicate no reciprocal causal relationship between tourism development and economic growth. From an energy conservation and sustainable tourism point of view, it is suggested policy makers and industry leaders develop high value, high profit tourism products that aim on attracting more visitor expenditures rather than numbers of visitor.