How do oil price shocks affect the output volatility of the U.S. energy mining industry? The roles of structural oil price shocks Yong Jiang a , Zhongbao Zhou b, ⁎, Qing Liu b , Ling Lin c , Helu Xiao d a School of Finance, Nanjing Audit University, Nanjing 211815, China b School of Business Administration, Hunan University, Changsha 410082, China c School of Economics, Hunan Agricultural University, 410128 Changsha, China d Business School, Hunan Normal University, Changsha 410081, China abstract article info Article history: Received 28 October 2017 Received in revised form 29 February 2020 Accepted 2 March 2020 Available online 13 March 2020 Keywords: Crude oil price shocks Output volatility Energy mining industry Structural VAR model JEL classification: C22 E44 G12 Q43 This paper focuses on how explicit structural shocks that characterize the endogenous character of international oil price change affect the output volatility of the U.S. crude oil and natural gas mining industries. To this end, we employ a modified structural vector autoregressive model (SVAR) to decompose real oil-price changes into four components: U.S. supply shocks, non-U.S. supply shocks, aggregate demand shocks, and oil-specific demand shocks mainly driven by precautionary demand. The results indicate that output volatility of the U.S. crude oil and natural gas mining industry has significantly negative responses to U.S. supply shocks, aggregate demand shocks, and oil-specific demand shocks, while lacks significant response to non-U.S. supply shocks. Variance de- composition and historical decomposition confirm that U.S. supply shocks occupy most explaining variations in output volatility among the four structural oil shocks. Moreover, the oil-specific demand shocks explain more variation than that of aggregate demand shocks for the crude oil mining industry, but the opposite is true for the natural gas mining industry. © 2020 Elsevier B.V. All rights reserved. 1. Introduction This paper mainly investigates the responses of the output volatility of the U.S. energy mining industry (which includes the mining indus- tries of crude oil and natural gas) to structural crude oil price shocks by employing a new modified SVAR model that is based on the frame- work of Kilian and Park (2009). As the world's largest economy, the U.S. has always been the largest consumer of crude oil. According to British Petroleum (BP), the U.S. consumed 19.88 million barrels per day in 2017, which accounted for 20.2% of the world's total. This huge demand for oil is met by both domestic and foreign markets. In 2017, the U.S. imported 10.08 million barrels per day on average, which is 14.9% of the global crude oil imports. More important is domestic pro- duction. Due mainly to the shale oil revolution, the domestic production of crude oil in the U.S. has experienced a high rate of growth in recent decades. From 2006 to 2016, its crude oil production grew by an annual average rate of 6.0%. In 2017, crude oil production in the U.S. reached 13.06 million barrels per day, which represents an increase of 5.4% from the previous year, and the U.S., for the first time, became the world's largest oil producer, with 14.1% of the total world production. The surging domestic production not only substantially reduces its de- pendence on imports, which have fallen from a historic peak of 60% in 2005 to 42.74% in 2016 but also promotes exports. From 2006 to 2016, the average growth rate of oil exports of the U.S. reached 14.0%, which is far higher than that of the second-place country, namely, Canada, which had a rate of only 5.3%. In 2017, the U.S. growth rate reached 13.7%, and its average daily export was 5.54 million barrels, which accounted for 8.2% of the world's oil export. The boom of the en- ergy mining industry in the U.S. not only emancipates the U.S. from an over-reliance on oil imports but also packs a powerful punch in the in- ternational energy market. Therefore, the detection of the dynamics of the U.S. energy mining industry output has become significant, which has already attracted widespread attention from governments, international organizations and the academic community (Bataa and Park, 2017; Kang et al., 2017a; Kang et al., 2016; Kilian, 2016). However, the extant literature leaves several problems unsolved. First, the growing dependence of Energy Economics 87 (2020) 104737 ⁎ Corresponding author. E-mail address: z.b.zhou@hnu.edu.cn (Z. Zhou). https://doi.org/10.1016/j.eneco.2020.104737 0140-9883/© 2020 Elsevier B.V. All rights reserved. Contents lists available at ScienceDirect Energy Economics journal homepage: www.elsevier.com/locate/eneeco