中美产业部门全要素生产率比较——基于环境友好全球价值链视角

doi:10.18402/resci.2022.03.11

摘要/Abstract

摘要：

中间品贸易隐含能源要素与碳排放所带来的产业发展影响问题已开始引起重视。本文从环境友好全球价值链视角出发,将增加值核算方法与SupSBM模型相结合,分别测算出2000—2014年中国和美国两个贸易强国产业部门整体及三次产业的全要素生产率、要素投入效率及碳排放效率。研究发现：①美国整体产业部门的全要素生产率高于中国,但是这种差距逐渐变小。主要归因于中国第一产业、第三产业国内劳动投入效率的提升。②按年平均统计,中国整体产业部门国内劳动投入效率高于美国,而其他要素投入效率均低于美国。③按年平均统计,与美国相比,中国第三产业发展向环境友好方向演变,但第一、第二产业环境友好发展不显著,有待进一步提高。因此,以政策为引导,补齐产业部门投入产出效率短板,扩大产业链间效率溢出效应,是实现中国产业部门环境友好全球价值链视角下全要素生产率提升的关键。

关键词: 环境友好型, 全球价值链, 全要素生产率, 产业部门, 中国, 美国

Abstract:

The impact of industrial development brought about by the energy factors and carbon emissions embodied in intermediate trade has begun to attract attention. From the perspective of environmentally friendly global value chain, this paper combines the value-added accounting method with the SupSBM (slacks-based measure) model to calculate the total factor productivity, factor input efficiency and carbon emission efficiency of the overall industrial sector and the three industries of the two major trading powers China and the United States in 2000-2014. The results show that: (1) The total factor productivity of the overall industrial sector in the United States is higher than that in China, but the gap is gradually narrowing. This is mainly attributable to the improvement of domestic labor input efficiency in China's primary and tertiary industries. (2)According to the annual average statistics, the domestic labor input efficiency of China's overall industrial sector is higher than that of the United States, while the input efficiency of other factors is lower than that of the United States. (3) According to the annual average statistics, compared to the United States, the development of China's tertiary industry is becoming environmentally friendly, but the environmentally friendly development of the primary and secondary industries is not significant and needs to be further improved. Therefore, under the guidance of policies, making up for the shortcomings of input-output efficiency in industrial sectors and expanding the efficiency spillover effect between industrial chains are the keys to realizing the improvement of total factor productivity from the perspective of environmentally friendly global value chains in China's industrial sectors.

Key words: environmentally friendly, global value chain, total factor productivity, industrial sectors, China, the United States

桑丹丹, 王元月, 丁黎黎. 中美产业部门全要素生产率比较——基于环境友好全球价值链视角[J]. 资源科学, 2022, 44(3): 570-582.

SANG Dandan, WANG Yuanyue, DING Lili. Comparison of total factor productivity between industrial sectors in China and the United States: From the perspective of environmentally friendly global value chains[J]. Resources Science, 2022, 44(3): 570-582.

图/表 6

图1

表1

按产业平均统计的中国和美国整体产业部门的全要素生产率、要素投入效率、碳排放效率

行业	全要素生产率		要素投入效率		碳排放效率		行业	全要素生产率		要素投入效率		碳排放效率
行业	CHNE	USAE	CHN_X	USA_X	CHN_b	USA_b	行业	CHNE	USAE	CHN_X	USA_X	CHN_b	USA_b
r1	0.166	0.174	0.245	0.270	0.235	0.168	r27	0.215	0.958	0.338	0.968	0.133	0.950
r3	0.198	0.240	0.278	0.343	0.313	0.353	r29	0.409	1.054	0.529	1.067	0.451	1.009
r4	0.268	0.898	0.394	0.938	0.240	0.854	r30	0.401	0.694	0.520	0.798	0.449	0.706
r5	0.201	0.222	0.296	0.344	0.262	0.180	r31	0.255	0.185	0.374	0.289	0.299	0.161
r6	0.173	0.182	0.267	0.283	0.187	0.170	r32	0.202	0.204	0.308	0.325	0.207	0.110
r7	0.164	0.187	0.252	0.291	0.188	0.168	r33	0.181	0.177	0.280	0.282	0.172	0.106
r8	0.161	0.196	0.251	0.311	0.158	0.120	r34	0.183	0.303	0.278	0.433	0.213	0.349
r9	0.186	0.220	0.282	0.336	0.212	0.205	r35	0.267	0.275	0.389	0.398	0.310	0.324
r10	0.791	1.098	0.818	1.125	0.780	1.000	r36	0.248	0.291	0.356	0.423	0.304	0.318
r11	0.181	0.986	0.283	1.004	0.132	0.967	r39	0.360	0.904	0.490	0.937	0.452	0.920
r12	0.216	1.017	0.323	1.022	0.253	1.000	r40	0.276	0.546	0.395	0.673	0.345	0.605
r13	0.154	0.205	0.241	0.322	0.140	0.138	r41	1.374	1.113	1.460	1.140	1.072	1.041
r15	0.176	0.192	0.279	0.310	0.117	0.079	r42	0.590	1.747	0.692	1.918	0.583	1.148
r16	0.177	0.217	0.280	0.340	0.134	0.147	r44	1.551	1.237	1.677	1.302	1.110	1.010
r17	0.369	0.773	0.459	0.829	0.352	0.789	r45	0.230	0.626	0.339	0.742	0.283	0.701
r18	0.190	0.239	0.297	0.370	0.149	0.169	r47	0.248	0.479	0.371	0.627	0.254	0.525
r19	0.222	0.230	0.342	0.356	0.177	0.172	r49	0.409	0.479	0.522	0.627	0.448	0.525
r20	0.239	0.380	0.366	0.506	0.197	0.329	r50	0.283	0.430	0.414	0.566	0.304	0.514
r21	0.277	0.444	0.392	0.562	0.232	0.412	r51	0.465	0.249	0.605	0.361	0.444	0.324
r22	0.197	0.244	0.302	0.369	0.196	0.223	r52	0.249	0.316	0.365	0.455	0.268	0.335
r24	0.545	0.482	0.623	0.681	0.496	0.351	r53	0.281	0.351	0.413	0.490	0.262	0.404
r25	0.290	0.543	0.410	0.715	0.239	0.437	r54	0.128	0.373	0.197	0.510	0.188	0.442

表1

图2

图3

图4

图5

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