贸易保护如何改变中国光伏出口目的国格局?

doi:10.11821/dlyj020180551

摘要/Abstract

摘要：

以欧美对中国光伏反倾销、反补贴（“双反”）事件为例,使用网络分析研究2009—2015年世界光伏贸易格局,以Logit模型探讨2009—2011年和2011—2013年中国210个地级市与175个目的国的光伏贸易演变。结果表明,“双反”后中国与欧美贸易量急剧下降,与非“双反”国家贸易量有所提升,主要目的国从德国、荷兰、意大利和美国转向日本、韩国、印度和新加坡。政策激励促进光伏出口,且“双反”后政策效力增强。出口关联显著提升正常贸易环境下出口增长,“双反”后则为负向作用。加工贸易比重高的区域受到贸易保护冲击更为严重。市场多元化不能缓冲“双反”冲击,目的国中心性高有利于建立稳健贸易联系。政策激励在光伏贸易中作用突出,减少直接补贴,增加创新奖励是政策优化方向。

关键词: 光伏, 反倾销, 反补贴, 网络分析, 加工贸易, 政策激励

Abstract:

In recent years, export-oriented development strategy in China is facing serious challenges under the prevailing trend of protectionism. Focusing on the anti-dumping and countervailing (AD) policy adopted by EU and US after 2011, this article tries to explain the dynamic of photovoltaic (PV) trade between China and other countries. We apply network analysis to investigate the pattern of PV trade during 2009 to 2015. And Logit model is utilized to find out the influencing factors that affect the pattern of PV destinations of prefectural cities in China in 2009-2011 and 2011-2013, respectively. The results show that, (1) the volume of trade between China and countries with AD policy dropped sharply after 2011, while the volume of export from China to countries beyond EU and US enjoys increase. The main destinations transferred from Germany, Netherlands, Italy and US to Japan, South Korea, India and Singapore. (2) Incentives can promote the export of PV products under marketization. Moreover, when some countries apply protectionism, appropriate policies play an important role in maintaining the pattern of trade and reducing the fluctuation of export. (3) Exporting relatedness of PV products can promote the growth of exports significantly in the first period. However, the effects of relatedness reversed after 2011, which indicates that export of Chinese prefecture-level cities are following new routines in front of trade protectionism. (4) Trade type of PV products only become significant in the second period, and the more processing trade a city has the worse its export situation would be. This results indicate that common trade is more robust than processing trade. (5) The diversification of market is not able to resist the negative effects of trade protection, which suggests that there is a threshold for market diversification to reduce the effect of protectionism. At the same time countries with high centrality are conducive to the growth of PV exports in prefectural cities. Based on the results we argue that, to guarantee the effect of diversification of market, it is necessary to establish export links with countries different from each other. Although trade protectionism leads to severe damage to Chinese PV industry, it also accelerates the transition from processing trade to common trade. After a short period of pain, it will be beneficial to the rise of Chinese PV industry. Appropriate policy cannot be underestimated in the rise of PV, especially in the context of trade protectionism.

Key words: photovoltaics, anti-dumping, countervailing, network analysis, processing trade, policy

朱向东, 贺灿飞, 朱晟君. 贸易保护如何改变中国光伏出口目的国格局?[J]. 地理研究, 2019, 38(11): 2565-2577.

ZHU Xiangdong, HE Canfei, ZHU Shengjun. How does protectionism change the pattern of the destinations of Chinese photovoltaic export?[J]. GEOGRAPHICAL RESEARCH, 2019, 38(11): 2565-2577.

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标准国家代码	国家名称	标准国家代码	国家名称	标准国家代码	国家名称	标准国家代码	国家名称
AUT	奥地利	ESP	西班牙	IRL	爱尔兰	POL	波兰
BEL	比利时	EST	爱沙尼亚	ITA	意大利	PRT	葡萄牙
BGR	保加利亚	FIN	芬兰	LTU	立陶宛	ROM	罗马尼亚
CYP	塞浦路斯	FRA	法国	LUX	卢森堡	SVK	斯洛伐克
CZE	捷克	GBR	英国	LVA	拉脱维亚	SVN	斯洛文尼亚
DEU	德国	GRC	希腊	MLT	马耳他	SWE	瑞典
DNK	丹麦	HUN	匈牙利	NLD	荷兰	USA	美国

排名	2009年		2011年		2013年		2015年
排名	目的国	出口额	目的国	出口额	目的国	出口额	目的国	出口额
1	德国	37.30	德国	56.60	日本	47.00	日本	52.11
2	荷兰	15.60	荷兰	54.50	美国	19.90	韩国	27.54
3	意大利	8.43	意大利	38.80	荷兰	15.90	美国	19.60
4	比利时	5.53	美国	28.20	印度	8.36	印度	14.72
5	美国	4.13	比利时	17.30	德国	6.10	荷兰	9.80
6	西班牙	3.35	澳大利亚	11.00	澳大利亚	5.41	新加坡	6.19
7	法国	2.71	法国	5.90	南非	5.28	菲律宾	5.97
8	韩国	2.34	印度	4.93	韩国	4.64	泰国	5.89
9	日本	2.24	日本	4.32	比利时	3.91	英国	5.81
10	澳大利亚	2.08	西班牙	3.87	英国	3.86	智利	4.46

变量类型	变量	变量名称	变量解释
被解释变量	ENEX	出口额变化	城市i在t1年对国家j光伏出口额高于t0年记为1,反之为0
解释变量	AD	目的国“双反”	目的国j对中国实施“双反”政策记为1,反之为0
	Sub	光伏补贴收入	城市i光伏企业所获补贴金额
	Type	出口类型	城市i光伏出口中加工贸易所占比重
	Relate	出口关联	城市i光伏与其他出口产品的关联度
	Diver	出口多元化	城市i光伏出口额大于1万美元的目的国数目
	Degree	目的国中心性	目的国j在世界光伏贸易网络中的度中心性
控制变量	GDPPC	城市人均GDP	城市i的人均GDP
	Import	城市光伏进口	城市i从国家j进口光伏产品记为1,否则为0
	Exp_c	目的国光伏出口	目的国j光伏出口总额
	Struc_c	目的国产业结构	目的国j工业产值占GDP比重
	Distance	地理距离	目的国j人口重心与中国人口重心的距离

变量（单位,数据源）	2011年被解释变量与2009年解释变量						2013年被解释变量与2011年解释变量
变量（单位,数据源）	样本数	均值	标准差	最小值	最大值		样本数	均值	标准差	最小值	最大值
被解释变量
ENEX （-,贸易库）	2873	0.620	0.485	0	1.000	3916		0.559	0.497	0	1.000
解释变量
AD（-,-）	2873	0.284	0.451	0	1.000	3916		0.284	0.451	0	1.000
Sub（万元,企业库）	2873	885	1670	0	31941	3916		1720	5462	0	429075
Type（%,贸易库）	2873	22.900	38.200	0.0	100.000	3916		25.500	39.900	0	100.000
Relate（-,贸易库）	2873	0.262	0.116	0.009	0.458	3916		0.286	0.102	0.023	0.467
Diver（个,UN Comtrade）	2873	23.800	25.300	0	91.000	3916		30.400	32.000	0	118.000
Degree（-,UN Comtrade）	2873	38.200	36.000	1.000	146.000	3916		41.900	36.700	1.000	153.000
控制变量
GDPPC（万元,中国城市统计年鉴）	2873	4.270	2.120	0.449	10.200	3916		5.830	2.650	0.646	13.100
Import（-,贸易库）	2873	0.126	0.332	0	1.000	3916		0.149	0.356	0	1.000
Exp_c（亿美元,UN Comtrade）	2873	4.120	9.850	0	46.700	3916		6.914	15.800	0	73.800
Struc_c（%,世界银行）	2873	26.800	10.700	5.000	96.600	3916		27.500	11.600	4.200	95.400
Distance（km,CEPII）	2873	8165	3984	1124	19110	3916		8165	3984	1124	19110

变量	2009—2011年			2011—2013年
变量	模型（1）	模型（2）	模型（3）	模型（4）	模型（5）	模型（6）
解释变量
Sub	0.195**		0.159*	0.122***		0.135***
Type	-0.094		-0.067	-0.838***		-0.840***
Relate	5.944***		5.245***	-1.236		0.363
AD		0.106	0.380		-0.680***	-1.293***
Diver		0.0019**	0.0144**		-0.0357*	-0.0055**
Degree		0.0019***	0.0157***		0.0079**	0.0200***
控制变量
GDPPC	0.117e-04*	0.120e-04***	0.125e-04*	0.201e-04***	0.115e-04***	0.263e-04***
Import	0.446**	0.124	0.341	0.852***	0.113	0.596**
Exp_c	33.200e-08***	8.650e-08	3.300e-08**	3.510e-08	4.430e-08	10.100e-08
Struc_c	-3.219***	-1.240***	-1.766*	1.002	1.120	0.728
Distance	0.048	-0.269**	-0.168	-0.409*	0.070	-0.389
Constant	-3.054***	0.100	-4.193***	-2.645***	0.841***	-3.723***
Observations	2873	2873	2873	3916	3916	3916
LR chi2	162.400	117.900	613.100	191.400	155.900	50.600
Prob>chi2	0.000	0.000	0.000	0.000	0.000	0.000