中国稀土市场供需非均衡性分析与预警

doi:10.18402/resci.2019.05.04

摘要/Abstract

摘要：

供需非均衡问题是影响中国稀土市场良性运行的主要因素之一。本文通过延伸非瓦尔拉斯均衡理论及模型的应用领域,对中国稀土市场的有效供需开展非均衡性分析,并建立双曲线型聚合方程,使用2000—2016年中国稀土市场供需、工业企业和采矿业宏观基本面年度数据进行实证分析,探究了长期以来中国稀土市场供需不平衡状况的根本症结。研究表明,中国稀土市场具有的结构分散、买方垄断、价格偏低、黑稀土频现以及政策干预性强等特点,是其呈现非均衡性的重要成因。基于灰色关联诊断得出：稀土价格、生产技术、生产成本、企业收入、企业负债、宏观政策和工业发展状况等是影响稀土有效供需的敏感因素。从非均衡度测算值看,稀土市场供需的非均衡变化趋势大致为：从有效供给过剩转变为有效需求略旺。依据预警线设置,稀土市场较多年份呈现35%以上的供大于求重警状态。本文结论可为促进中国稀土市场均衡化发展提供一定的理论依据和决策支撑。

关键词: 稀土市场, 非均衡理论, 有效供给, 有效需求, 预警, 中国

Abstract:

China’s rare earth plays a mainstay role in the world, but there are few systematic studies on the non-equilibrium state of supply and demand in the market. This study extended the application of non-equilibrium theory and its model to analyze the non-equilibrium state between effective supply and effective demand of the rare earth resources market in China, establishing hyperbolic equations and conducting empirical analysis by using the 2000-2016 macro-level data on China’s rare earth market supply and demand, industrial enterprises and mining industry, and finally analyzing the crux of long-term imbalances between supply and demand. The results show that China’s rare earth market is characterized by decentralization, buyer monopoly, low prices, rampant smuggling, and strong policy intervention, which are important causes of its non-equilibrium condition. Based on grey relational analysis, rare earth price, production technology and cost, enterprise income and debt, macroeconomic policy, and industrial development are sensitive factors of rare earth’s effective supply and demand. Non-equilibrium degree calculation results indicate that the non-equilibrium trend of supply and demand in rare earth market is changing from oversupply to excessive demand. Based on the early-warning threshold values, in many years the market was in a serious warning state where supply exceeded demand by more than 35%. The conclusions may provide some basis for warning and decision support for promoting a balanced development of China’s rare earth market.

Key words: rare earth market, non-equilibrium theory, effective supply, effective demand, early warning, China

孙菁靖, 雷玉桃. 中国稀土市场供需非均衡性分析与预警[J]. 资源科学, 2019, 41(5): 860-871.

Jingjing SUN, Yutao LEI. Non-equilibrium and early warning research on the supply and demand of China’s rare earth market[J]. Resources Science, 2019, 41(5): 860-871.

图/表 12

图1

表1

稀土市场供需影响因素指标体系"

供需	影响因素指标	影响方向	影响机理说明
需求方面	稀土市场价格	–	其他条件一定下,提升稀土市场价格则稀土需求量减少。
	工业发展水平	+	稀土资源的应用领域大部分属于工业领域,所以国内工业化发展的进程决定了稀土应用企业的整体效益,效益好则稀土需求量大。
	工业企业收入	+	通常需求方的消费数量会随其收入水平的提高而增加,稀土资源也是稀土应用工业企业需要购买的生产要素,收益较好时,则会扩大采购量。
	工业企业债务	–	当稀土应用工业企业债务状况较重时,如果预期未来收益没有增加,为尽量保持盈亏平衡,就会减少产出,削减稀土的消费量。
供给方面	稀土市场价格	+	市场价格是稀土生产者供应产品的动力。其他条件一定,稀土价格越高,供应方就越有机会获得超额利润,愿意提供产品的数量就越多。
	供给成本	–	稀土供给成本相当于各种生产要素价格,如果其上涨,而稀土价格不变或上升幅度未超过成本增长的幅度,则必然会缩减稀土厂商利润,减少供给。
	工业发展水平	+	稀土企业属于工业企业的内部板块,整体工业发展水平提高也会带动它们进步。
	开采（生产）技术	+	技术进步是在稀土开采生产中,持续采用新技术、新方法以提高生产效率和生产要素质量的一个过程,因此,若投入与以往相同数量的生产要素,则能得到更多的产出。
	国外购买能力	+	国外稀土需求能力的加强,会刺激国内稀土厂商加大供应量。
	稀土出口政策	+	政府通常会依据国内外稀土市场运行的情况,出台必要的稀土生产、出口政策,这也是对稀土企业生产的约束和引导,进而控制稀土资源供给的数量和结构。
	固定资产投资	+	稀土资源方面的投资涵括了企业建设及购置固定资产,改、扩、新建等一系列经济活动,稀土供应很大程度上受限于这部分投入,因此加大固定资产投资,能够扩大稀土生产商的产出数量。

表1

图2

表2

表3

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表5

图3

表6

图4

图5

表7

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变量名称	符号及单位	均值	标准差	最大值	最小值
稀土交易量	REQ_t /t	62 356.824	27 576.911	99 500	19 200
稀土价格^4）(4）稀土价格为中国稀土氧化物产品的出口均价,即UN Comtrade中HS编码为284610和284690这两类产品的出口价格均值。)	REP_t /（美元/t）	16 797.353	29 732.191	123 705	2 805
稀土进口量	IM_t /t	3 994.647	3 973.368	16 440	709
稀土出口量^5）(5）这里的稀土出口量数据来源于国外网站,其中还包含了黑稀土出口这部分。)	EX_t /t	40 357.059	15 647.016	61 900	13 509
稀土专利数^6）(6）稀土专利数来源网址：http://www.soopat.com/;全部专利包括发明、实用新型、外观、发明授权。)	TECH_t /t	7 543.647	6 067.949	19 955	1 088
稀土出口配额量^7）(7）从2015年开始,中国取消稀土出口配额制度,因此2015年和2016年的稀土出口配额量为0。)	QUOTA_t /t	41 424.235	20 107.299	65 609	0
工业生产总值	VALUE_t /亿元	136 146.177	75 860.043	247 860	40 260
采矿业职工工资总额	WAGE_t /亿元	1 992.529	1 244.507	3 833	496
采矿业固定资产投资	INVEST_t /亿元	7 485.824	5 065.761	14 651	1 109
工业企业负债	DEBT_t /亿元	28 9291.294	1.903	606 642	76 744
工业企业成本	COST_t /亿元	472 546.941	3.413	984 668	68 654
工业企业收入	INCOME_t /亿元	559 186.059	4.008	1 158 999	84 152

变量	REP_t	IM_t	TECH_t	VALUE_t	INCOME_t	DEBT_t
REQ_t	0.700	0.544	0.555	0.639	0.588	0.629
变量	EX_t	QUOTA_t	INVEST_t	WAGE_t	COST_t	综合
REQ_t	0.571	0.602	0.627	0.579	0.588	0.602

需求方程	IM_t	VALUE_t	DEBT_t			R²	Adjusted R²
	0.133*** （0.037）	2.379*** （0.288）	-1.408*** （0.261）			0.923	0.912
供给方程	REP_t	TECH_t	QUOTA_t	INVEST_t	WAGE_t	R²	Adjusted R²
	0.078*** （0.017）	0.490*** （0.068）	1.798*** （0.178）	1.042*** （0.165）	-2.266*** （0.406）	0.953	0.937

需求方程	IM_t	VALUE_t	DEBT_t
	0.110** （0.041）	2.434*** （0.197）	-1.374*** （0.168）
供给方程	REP_t	TECH_t	QUOTA_t	INVEST_t	WAGE_t
	0.167*** （0.036）	1.268*** （0.287）	6.826*** （1.799）	4.153*** （1.244）	-9.314*** （2.751）

年份	有效需求（RED_t）	有效供给（RES_t）	交易量（REQ_t）	非均衡度（REZ_t）
2000	116.953	310.025	116.953	-1.651
2001	131.334	231.447	131.334	-0.762
2002	161.539	114.583	114.583	0.410
2003	171.101	477.023	171.101	-1.788
2004	217.514	575.769	217.514	-1.647
2005	241.597	788.369	241.597	-2.263
2006	317.785	778.473	317.785	-1.450
2007	360.940	858.806	360.940	-1.379
2008	380.411	969.164	380.411	-1.548
2009	364.416	1 014.456	364.416	-1.784
2010	431.487	919.252	431.487	-1.130
2011	492.522	432.863	432.863	0.138
2012	480.485	337.483	337.483	0.424
2013	477.746	442.708	442.708	0.079
2014	471.285	675.117	471.285	-0.433
2015	505.784	737.935	505.784	-0.459
2016	587.266	518.229	518.229	0.133