International Journal of u- and e- Service, Science and Technology Vol.9, No. 12 (2016), pp.281-290 http://dx.doi.org/10.14257/ijunesst.2016.9.12.25 ISSN: 2005-4246 IJUNESST Copyright ⓒ 2016 SERSC Shadow Price of the Oil Industry LIU XiMei; WANG ChangFeng; Shahid Rasheed and Muhammad Nawaz Tunio School of Economics and Management, Beijing University of Posts and Telecommunications, Beijing 1000876, China 1092457487@qq.com;wangcf@bupt.edu.cn;shahidrasheed@outlook.com; mntunio2014@hotmail.com Abstract Oil, hailed as modern industrial blood, is of greater significance to a state, and is closely related to people's lives. Shadow price of the oil industry is a key evaluation parameter for the business of an economy. In this paper, the application of input-output method and linear programming theory has been sought to establish an optimization model for the oil industry and the shadow price of the oil industry has been calculated according to the 2007 China input-output table. The analysis concludes that among the agriculture, the industry, and the tertiary industry, the prices of oil industry products bear maximum influence on the prices of agricultural products. Key words: input-output model; linear programming; shadow price; oil industry 1. Introduction In today’s world, oil is recognized as the "blood" of a national economy. It is not only an imperative strategic resource for energy but is also an important chemical raw material. A lot of studies have been dedicated to evaluate the social benefits of oil industry and various useful conclusions are also drawn. Shadow price in operations research is defined as the optimal solution to the dual problem [1]. In year 2002, Yu Bo, Chi Chunjie, and Su Guofu used input-output model analysis to calculate the impact of oil price fluctuations on China's economy [2]. Similarly, in 2004, Han Dongyan and Chen Rui analyzed the influence of petroleum price on national economy equilibrium and the impact of oil price fluctuations on rest of the industry, and put forward certain countermeasures and Suggestions [3]. In 2007, Liu Weiguo, Xu Wenxin, and Li Xiaoliang used logit function to monitor the degree to which the changes in oil prices impact the economy [4]. Likewise, in 2008, Li Yunling conducted an empirical analysis by applying the input and output method to work out the effect of oil industry on the other industry in China. He suggested some policy recommendations for China’s petroleum import and export trade and energy consumption [5]. In year 2010, Li Xiaoyan used grey correlation to establish three models for quantitative analysis of correlation between energy consumption and economic growth. Based on his findings, he advanced the implementation of energy saving measures in order to improve the efficiency of energy utilization [6]. More recently in year 2015, Song Bo and Mu Yueying proposed a new method to deduce the shadow price of carbon emission based on the parameterized environmental directional distance function [7]. Also in year 2015, Tian Shiqiang , Shi Guangming, and Xiong Hui analyzed the shadow price of sulfur dioxide and nitrogen oxide by using the pollutant emission data of 23 thermal power plants in Hunan province [8]. Since the mentioned studies rarely dealt with the shadow price of petroleum industry, they can hardly be used directly for evaluation of oil industry’s impact on the national economy. The development of market economy in China, the strengthening of macro-control, and the declining oil prices in Chinese industry make it increasingly