1、firms operating in the US, the elasticity of substitution across material inputs was estimated to be only 0.2 in the short run. Most of the existing literature on natural disasters focuses on how GVCs transmit shocks, domestically (Carvalho et al., 2016) or internationally (Boehm et al., 2019).3 In
2、this paper, we study instead the longer- 2 For an analysis of the long-term evolution of global value chains, see Constantinescu et al. (2020) and World Bank (2020). 3 An exception is Zhu et al. (2016) which uses Japanese firm-level data from 2010-2013, to show that the earthquake increased manufact
3、uring offshoring from Japan among firms in the prefectures most affected by the disaster. 3 term impact of the 2011 earthquake in Japan on trade patterns. We focus on the automobile and electronics industries, for which Japan is a key supplier, especially of parts and components. For instance, as th
4、e shock severely affected production of Japanese automotive equipment, it had cascading effects on global auto producers such as Honda, Opel, Nissan, and General Motors which froze production lines in several factories worldwide (Automotive News, 2011). In electronics, the problems were similar, as
5、many specialized inputs such as connectors, microphones, and sensors were produced in Japan and had few or no substitutes (World Bank, 2020). To motivate the analysis, we identify certain patterns in the data. We examine imports of auto and electronics in the 15 largest auto producing countries as o
6、f 2010 and in the 15 largest exporters of final electronics products to gauge the longer term effect of the earthquake on suppliers.4 The left panel of Figure 1 shows the average shares of products imported from Japan for importers where Japan is not a prominent supplier (less than 15 percent of tot
7、al imports of that product by the country). The right panel focuses on importers largely dependent on Japanese suppliers (more than 15 percent of total imports in a product line). The figure shows that reliance on Japan dropped sharply following the 2011 earthquake for the countries most dependent o
8、n Japan. The drop was more than 10 percentage points for the auto industry, while in the case of electronics the earthquake appeared to accelerate pre-existing declining trends. This is prima facie evidence that large shocks do lead to a partial reconfiguration of supply chains: while less exposed i
9、mporters return to near pre-crisis operations after the shock, it is the more dependent producers that tend to change production structures. 4 See Table A1 in the Appendix for the list of countries. While we have data for automobile production by countries, we do not have similar data for electronic
10、s and therefore rely on export data. 4 Figure 1: Country share of imports from Japan in auto and electronics (average) Source: 6-digit HS 1988/92 import data from United Nations Comtrade. Notes: The figures plot Japans average market share for auto and electronics for country-products in which Japan
11、 had an average market share below 15 percent (left panel “Low Share”) and in country-products in which Japan had an average market share greater than 15 percent (right panel “High Share”) calculated over the 2004-2010 period. The sample for auto is restricted to the 15 largest auto producers and fo
12、r electronics to the 15 largest exporters of final electronics; in both cases Japan is excluded. The analysis relies on a simple identification strategy. We use detailed international trade data for automobile and electronics components and final goods to study whether in the aftermath of the 2011 e
13、arthquake, importers more dependent on Japan before the earthquake behaved differently from importers less dependent on Japan. Apart from the change in imports from Japan, we also investigate whether the 2011 earthquake led to a diversification of imports away from Japan and to reshoring or nearshor
14、ing of production by more dependent importers. We find that the earthquake led to a sharp decline in imports from Japan of auto parts and finished vehicles of countries more dependent on Japan before the shock. Electronics shows a similar pattern to the auto industry, but the decline was less pronou
15、nced. For both auto and electronics, intermediate imports were less affected than final imports. Using a continuous measure of dependence, we find that 5 the decline in imports for both auto and electronics is more severe the higher the importers dependence on Japanese suppliers in the period preced
16、ing the earthquake. We find, somewhat surprisingly, that importers more exposed to Japan before the 2011 earthquake did not increase import diversification in either auto or electronics. There is also no evidence that countries re-shored production. In fact, importers more exposed to Japan before th
17、e 2011 earthquake increased total imports, which is consistent with an intensification of offshoring rather than reshoring. An important question relates to which countries picked up the slack as supply chains reorganized in the aftermath of the 2011 earthquake. We perform a difference-in-difference
18、s analysis, comparing shifts in trade patterns of high Japan-dependent products with other products while controlling for importer and product specific time-varying shocks. We find that in the years following the shock, production relocation decisions were largely driven by fundamentals rather than
19、policy. Developing countries, rather than top exporters, were the primary beneficiaries and production tended to relocate in larger countries. There is no evidence that supply chains were increasingly regionalized or that importers sought nearby suppliers, except for final autos where transport cost
20、s are especially high. The rest of the paper is organized as follows. Section 2 provides a simple framework to think of the effects of natural disasters and the reshaping of supply chains. Section 3 studies the impact of the Japanese earthquake on the reconfiguration of supply chains. Section 4 take
21、s a closer look at where production moved after the shock. Section 5 concludes. 2. Natural disasters and supply chain reconfiguration To guide the empirical analysis, we propose a simple framework to think of the impact of natural disasters on the reconfiguration of supply chains. To begin with, con
22、sider the choice from the perspective of a multinational firm that imports from a subsidiary located in Japan.5 A disaster that destroys fixed assets like factories will accelerate the reallocation of production to production hubs where average costs are lower. Note that in normal circumstances, a f
23、irm would move to another location if the sum of the cost and insurance savings in the new location were larger than the fixed costs of relocation. Specifically, we 5 As noted in the introduction, Boehm et al. (2019) found that Japanese multinationals abroad lost access to auto intermediates and exp
24、erienced severe reductions in production of final goods. The case of arms length trade is also considered below. 6 define the cost of relocation, C = F + S, as the sum of the cost of building a factory, F, and the cost of establishing new relationships in the new production location, S. The benefit
25、of relocation, B = (c + i) q, depends on the scale of production, q (assumed for simplicity to be the same in the two locations), the per-unit cost difference, c, and the per unit insurance premium difference, i, in the new location. For parsimony, we use a static example, in a dynamic setting the c
26、ost savings would compound overtime, without changing the qualitative results. A firm would relocate if (c + i) q F + S. Before a natural disaster, small differences in unit costs would not induce a relocation the sunk costs in the existing location create inertia. The event has two implications for
27、 the decision to relocate production. First, if the factory is destroyed as a consequence of the disaster, the cost of building a new factory, F, is no longer relevant because it is truly sunk. It disappears from the inequality because it must now be paid in both the old and new locations. Although
28、the cost of building new relationships, S, must still be incurred in the new location, firms will now be more sensitive to cost differences between the old and new locations than if the factory were intact. If the same factors that affect production cost also affect cost of building a new factory (f
29、or example, exchange rate undervaluation), that will enhance this effect. Second, the natural disaster may affect the differential on the insurance premium between locations. As the old location is riskier, relocating to a new low-risk location becomes more attractive. Figure 2 provides an illustrat
30、ion of the forces at play. Note that finding new production locations in the aftermath of a natural disaster has larger benefits the higher the dependence on production and hence imports from the exporting country (Japan). To see why, note that the expected costs of exposure to a specific source for
31、 imports are related to the relative importance and riskiness of that source. The larger the imports, the greater the disruption caused by a cut off in production in that source. The benefits of relocating production can be seen as the inverse of the expected costs from the disruption associated wit
32、h a natural disaster. Accordingly, in Figure 2, BPRE = (c + i) q shows the benefits of switching away from the risky source before the realization of the event as increasing in exposure (i.e. quantity imported from Japan). This benefit must be compared with the costs which depend on the costs of rel
33、ocating production and the costs of investing in a new relationship, captured by the schedule CPRE = F + S. Before the realization of the natural disaster, country-sectors with exposure higher than q*(PRE) would have switched away from Japan. 7 A first question that this framework helps to address i
34、s whether to continue sourcing from a country that experiences a natural disaster. Following the recent empirical literature on behavioral economicssee Bourdeau-Brien and Kryzanowski (2020) for the US and Cameron and Shah (2015) for Indonesiawe assume that for any given level of dependence, an incre
35、ase in the perceived riskiness of the source increases the expected loss and, hence, the benefit from switching away from it. The schedule BPOST = (c + iPOST) q depicts the upward shift in benefits due to the upward revision in perceived riskiness, and hence the insurance premium differential, after
36、 a shock. These benefits are compared with the costs, now captured by CPOST = S. The model indicates that (a) an increase in perceived riskiness and the destruction of physical capital lower the threshold at which firms would choose to switch suppliers (from q*(PRE) to q*(POST) in Figure 2); and (b)
37、 importers that are more dependent on the source (i.e. those with imports higher than q*(POST) are more likely to switch to a different supplier. Note that sectors where the fixed 型 矿石量 （万吨） 金属氧化物资源储量（t） 平均品位（%） Ta2O5 Nb2O5 Rb2O Cs2O Li2O Ta2O5 Nb2O5 Rb2O Cs2O Li2O 行业周报 | 有色金属 10 | 请务必仔细阅读报告尾部的重要声明
38、西部证券西部证券 2021 年年 09 月月 25 日日 Ta-1 121b 456.24 645.28 405.19 20778.94 2882.41 41415.08 0.01 0.01 0.29 0.04 0.57 122b 135.34 167.45 98.91 0.01 0.01 333 134.08 169.75 111.55 0.01 0.01 查明矿产 资源量 725.66 982.48 615.65 0.01 0.01 其余钽铌矿体 8323.35 7491.015 6658.68 191437.05 30796.395 358736.39 0.01 0.01 0.23 0.
39、04 0.43 低品位铷矿体 130.05 78.03 78.03 4811.85 559.215 7542.9 0.01 0.01 0.37 0.04 0.58 总计总计 9179.06 9534.005 7968.01 217027.84 34238.02 407694.37 0.01 0.01 0.24 0.04 0.44 资料来源：加布斯盐湖环评报告，西部证券研发中心 表 7：蒙金矿业旗下加不斯矿区铌钽矿产能情况 产能 产率（%） 精矿品位（%） 回收率 （%） 年精矿产量（t/a） 含金属量（t） 一 钽铌精矿 0.02025 40 45 121.50 Ta2O5 29.16t, N
40、b2O5 19.44t 二 锂精矿 12.86 2.3 58 77160 Li2O 1774.68t、Rb2O 578.70t CS2O 92.59t 小计 77281.5 三 破碎逸散粉尘 / 35.7 四 尾矿 87.11 522647.1 主要为长石， 全部外售 合计合计 600000 资料来源：加布斯盐湖环评报告，西部证券研发中心 【盛新锂能【盛新锂能】2021.09.24:关于全资子公司盛威致远国际有限公司收购资产的公告关于全资子公司盛威致远国际有限公司收购资产的公告 2021年9月22日 ， 公 司 与 全 资 香 港 子 公 司 盛 威 国 际 、 华 友 国 际 、 SALTA
41、EXPLORACIONESS . A. （一家根据阿根廷共和国法律注册成立和存续的公司， 以下简称“SESA”或“目标公司”）签署了股权及债权转让协议，盛威国际拟购买 华友国际在交割日持有的 SESA100%股权及华友国际对 SESA 的股东借款债权，交易价 格为 37,668,868.91 美元。SESA 和 POTASIO Y LITIO DE ARGENTINA S.A.（一家根据 阿根廷共和国法律设立和存续的公司，以下简称“PLASA”）在 2016 年 5 月 6 日根据阿 根廷共和国法律签订了公司联合体合同（以下简称“UT 协议”）并组建了 UT 联合 体；根据UT 协议，SESA
42、 和 PLASA 各持有 UT 联合体 50%的权益份额，SESA 为 UT 联合体的运营方， UT 联合体经营阿根廷 SDLA 项目/ Diablillos 盐湖 （以下简称 “SDLA 项目”）。华友国际与 Hanaq ArgentinaS.A.（以下简称“Hanaq”）签署债权和股权 转让以及不可撤销的减资合同，通过该减资合同，Hanaq 向华友国际转让其持有目标公 司 30%股权以及债权，减资合同履行完毕后，华友国际将持有目标公司 100%股权。本次 盛威国际收购目标公司股权及债权需在上述减资合同履行完毕后进行交割。 本次收购完成 后，盛威国际将持有 SESA 100%股权，并通过 S
43、ESA 拥有对 UT 联合体的运营权， UT 联合体经营阿根廷 SDLA 项目。 表 8：SDLA 项目概况 锂 钾 金属量（吨） 探明+控制 307535 3393647 推测 77464 811472 资源量：Li2CO3 当量（万吨） 探明+控制 163.61 推测 41.48 总计：Li2CO3 当量（万吨） 205.09 行业周报 | 有色金属 11 | 请务必仔细阅读报告尾部的重要声明 西部证券西部证券 2021 年年 09 月月 25 日日 产能：Li2CO3 当量（吨） 2500 资料来源：公司公告，西部证券研发中心 【神火股份】【神火股份】2021.09.24：河南神火煤电股
44、份有限公司关于收购上海神火铝箔有限公司：河南神火煤电股份有限公司关于收购上海神火铝箔有限公司 25%股权涉及关联交易的公告股权涉及关联交易的公告 为进一步推进铝加工板块整合，提升铝加工板块的业务协同能力，加强对子公司的管理， 优化股权结构和法人治理结构，提升运营决策效率，神火股份决定以协议转让方式收购申 美国际所持上海铝箔 25%股权， 收购价格为北京亚太联华出具的 神火股份拟进行股权收 购所涉及的上海铝箔股东全部权益价值资产评估报告（亚评报字【2021】314 号，以下 简称“资产评估报告”）确认的净资产值 37,327.93 万元*25%=9,331.9825 万元。申 美国际为普天工贸全
45、资子公司；截至目前，普天工贸持有公司 8.91%的股权，公司以现金 方式收购申美国际所持上海铝箔 25%股权事项构成关联交易， 但不构成 上市公司重大资 产重组管理办法规定的重大资产重组，也不构成重组上市。 【盛屯矿业【盛屯矿业】2021.09.24:对外投资公告对外投资公告 为进一步聚焦镍、铜、钴能源金属，贯彻公司上控资源，下拓材料的经营战略，盛屯矿业 于 2021 年 9 月 23 日召开第十届董事会第三十二次会议，审议通过在贵州省黔南州福泉 市投资建设年产 30 万吨电池级硫酸镍、 30 万吨电池级磷酸铁及 1 万金属吨电池级钴产品 新能源材料项目，投资主体为公司全资孙公司盛屯能源金属化
46、学（贵州）有限公司，最终 以市场监督管理部门核定的名称为准），总投资金额 619,329 万元。本投资事经第十届董 事会第三十二次会议审议通过，董事会审议通过后需经股东大会审议批准。本项目尚需经 过政府有关部门的批准。本次投资不属于关联交易，不属于重大资产重组事项。 【东方锆业【东方锆业】2021.09.23:关于公司产品价格调整的公告关于公司产品价格调整的公告 鉴于各种生产原辅材料价格持续上涨且供应紧张，公司自 2021 年 9 月 24 日起在原价格 基础上上调相关锆产品销售价格：氯氧化锆产品（包含母液料）上调 2000 元/吨；二氧化 锆产品上调 6000 元/吨。同时，公司其他锆系列产品价格将同步进行调整。本次上调产品 销售价格将对公司经营业绩产生积极的影响。同时公司董事会提醒投资者注意，本次提价 对销售量的影响尚具有不确定性，新销售价格持续时间也不能确定，存在产品价格继续波 动的风险。 行业周报 | 有色金属 12
