Crude oil prices do play significant role in the global economy and are a key input into option pricing formulas, portfolio allocation, and risk measurement. In this paper, a hybrid model integrating wavelet and multiple linear regressions (MLR) is proposed for crude oil price forecasting. In this model, Mallat wavelet transform is first selected to decompose an original time series into several subseries with different scale. Then, the principal component analysis (PCA) is used in processing subseries data in MLR for crude oil price forecasting. The particle swarm optimization (PSO) is used to adopt the optimal parameters of the MLR model. To assess the effectiveness of this model, daily crude oil market, West Texas Intermediate (WTI), has been used as the case study. Time series prediction capability performance of the WMLR model is compared with the MLR, ARIMA, and GARCH models using various statistics measures. The experimental results show that the proposed model outperforms the individual models in forecasting of the crude oil prices series.
This study investigates whether financial development dampens the negative impact of oil resource abundance on economic growth. Because of substantial cross-sectional dependence in our data, which contain a core sample of 63 oil-producing countries from 1980 through 2010, we use the common correlated effect mean group (CCEMG) estimator to account for the high degree of heterogeneity and drop the outlier countries. The empirical results reveal that oil resource abundance affects the growth rate in output contingent on the degree of development in financial markets. More developed financial markets can channel the revenues from oil into more productive activities and thus offset the negative effects of oil resource abundance on economic growth. Thus, better financial development can reverse resource curse or enhance resource blessing in oil-rich economies.
Globally, around three billion people depend upon solid fuels such as firewood, dry animal dung, crop residues, or coal, and use traditional stoves for cooking and heating purposes. This solid fuel combustion causes indoor air pollution (IAP) and severely impairs health and the environment, especially in developing countries like Pakistan. A number of alternative household energy strategies can be adopted to mitigate IAP, such as using liquefied petroleum gas (LPG), natural gas, biogas, electric stoves, or improved cook stoves (ICS). In this study, we estimate the benefit-cost ratios and net present value of these interventions over a ten-year period in Pakistan. Annual costs include both fixed and operating costs, whereas benefits cover health, productivity gains, time savings, and fuel savings. We find that LPG has the highest benefit-cost ratio, followed by natural gas, while ICS has the lowest benefit-cost ratio. Electric stoves and biogas have moderate benefit-cost ratios that nevertheless exceed one. To maximize the return on cleaner burning technology, the government of Pakistan should consider encouraging the adoption of LPG, piped natural gas, and electric stoves as means to reduce IAP and adopt clean technologies.