您的位置:山东大学 -> 科技期刊社 -> 《山东大学学报(理学版)》

《山东大学学报(理学版)》 ›› 2019, Vol. 54 ›› Issue (5): 61-67,76.doi: 10.6040/j.issn.1671-9352.0.2018.531

•   • 上一篇    下一篇

投入产出网络中的关键产业

巩金秋(),徐进*(),胡发胜   

  1. 山东大学数学学院, 山东 济南 250100
  • 收稿日期:2018-09-23 出版日期:2019-05-20 发布日期:2019-05-09
  • 通讯作者: 徐进 E-mail:gongjinqiu@mail.sdu.edu.cn;jinxu@sdu.edu.cn
  • 作者简介:巩金秋(1994—),女,硕士研究生,研究方向为运筹与经济分析. E-mail: gongjinqiu@mail.sdu.edu.cn
  • 基金资助:
    国家自然科学基金资助项目(11471193);国家自然科学基金资助项目(11271006);国家自然科学基金资助项目(11631014)

Key sectors in input-output network

Jin-qiu GONG(),Jin XU*(),Fa-sheng HU   

  1. School of Mathematics, Shandong University, Jinan 250100, Shandong, China
  • Received:2018-09-23 Online:2019-05-20 Published:2019-05-09
  • Contact: Jin XU E-mail:gongjinqiu@mail.sdu.edu.cn;jinxu@sdu.edu.cn
  • Supported by:
    国家自然科学基金资助项目(11471193);国家自然科学基金资助项目(11271006);国家自然科学基金资助项目(11631014)

摘要:

随着经济协作日益密切,产业网络关联程度的加深,部门的生产变化会波及其上游和下游部门的生产,直接或间接地影响其他部门,进而对整体经济产生影响。从部门间投入产出网络的角度,衡量每个产业部门对于总产出波动的影响。通过直接消耗系数矩阵构建投入产出网络,研究部门冲击对总产出波动的影响。在构建的投入产出网络基础上,从对总产出波动影响大小的角度,刻画关键产业,其生产冲击对整个网络的产出波动影响最大。用我国2012年投入产出数据实证分析,发现批发、零售业和农产品业通过网络关联对总产出波动影响最大,可作为关键产业。

关键词: 投入产出网络, 总产出波动, 关键产业

Abstract:

As economic cooperation becomes closer and industrial network becomes more connected, changes in sector production will affect the output of its upstream and downstream sectors, directly or indirectly affecting other sectors, and thereby affecting the overall economy. From the perspective of intersectoral input-output network, the influence of each sector on the aggregate volatility is measured. The input-output network is constructed by direct consumption coefficient matrix to study the role of sectoral shocks in the aggregate volatility. On the basis of the established input-output network, the key sectors are depicted from the perspective of the impact on the aggregate volatility, whose productivity shock has the greatest impact on the output volatility of the entire network. The empirical analysis of China's 2012 input and output data shows that the wholesale and retail, agricultural product sectors have the greatest impact on the aggregate volatility through network linkages, which can be regarded as key sectors.

Key words: input-output network, aggregate volatility, key sectors

中图分类号: 

  • F223

图1

4个部门投入产出网络简图"

表1

我国2012年网络关联影响系数排序(前十位)"

排序部门名称bi/biifi网络关联影响系数
1批发和零售11.457 58.300 687.853 8
2农产品11.243 08.191 087.002 1
3货币金融和其他金融服务11.521 47.407 375.724 8
4精炼石油和核燃料加工品11.310 92.142 872.160 5
5电力、热力生产和供应11.137 74.449 268.871 3
6石油和天然气开采产品10.489 36.779 166.416 3
7基础化学原料8.674 52.007 254.855 2
8煤炭采选产品7.998 24.850 544.530 8
9有色金属及其合金和铸件7.930 71.897 841.636 5
10商务服务7.243 62.560 639.124 7
1 RASMUSSEN P N . Studies in inter-sectoral relations[M]. Amsterdam: North-Holland Publishing Co, 1956.
2 AUGUSTINOVICS M . Methods of international and intertemporal comparison of structure[J]. Contributions to Input-output Analysis, 1970, 1: 249- 269.
3 JONES L P . The measurement of hirschmanian linkages[J]. The Quarterly Journal of Economics, 1976, 90 (2): 323.
doi: 10.2307/1884635
4 刘起运. 关于投入产出系数结构分析方法的研究[J]. 统计研究, 2002, 19 (2): 40- 42.
doi: 10.3969/j.issn.1002-4565.2002.02.010
LIU Qiyun . The research on the method of structural analyses regarding the input-output coefficients[J]. Statistical Research, 2002, 19 (2): 40- 42.
doi: 10.3969/j.issn.1002-4565.2002.02.010
5 杨灿, 郑正喜. 产业关联效应测度理论辨析[J]. 统计研究, 2014, 31 (12): 11- 19.
doi: 10.3969/j.issn.1002-4565.2014.12.002
YANG Can , ZHENG Zhengxi . Analysis of the theoretical issues on the measurement of industrial linkage[J]. Statistical Research, 2014, 31 (12): 11- 19.
doi: 10.3969/j.issn.1002-4565.2014.12.002
6 沈利生. 重新审视传统的影响力系数公式:评影响力系数公式的两个缺陷[J]. 数量经济技术经济研究, 2010, 27 (2): 133- 141.
SHEN Lisheng . Revaluating traditional formula of influence power coefficient[J]. The Journal of Quantitative & Technical Economics, 2010, 27 (2): 133- 141.
7 贾传亮, 胡发胜, 孙颖. 主成分分析法在产业关联度研究中的应用[J]. 运筹与管理, 2006, 15 (2): 73- 76.
doi: 10.3969/j.issn.1007-3221.2006.02.017
JIA Chuanliang , HU Fasheng , SUN Ying . Application of principal component analysis to research of industrial relevancy[J]. Operations Research and Management Science, 2006, 15 (2): 73- 76.
doi: 10.3969/j.issn.1007-3221.2006.02.017
8 魏勇强, 乔彦芸. 资源型地区主导产业选择研究:以山西省为例[J]. 改革与战略, 2018, 34 (5): 80- 86.
WEI Yongqiang , QIAO Yanyun . The choice of leading industry for resource rich region: from the perspective of Shanxi province[J]. Reformation and Strategy, 2018, 34 (5): 80- 86.
9 GUO J , ZHANG Y J , ZHANG K B . The key sectors for energy conservation and carbon emissions reduction in China: evidence from the input-output method[J]. Journal of Cleaner Production, 2018, 179: 180- 190.
doi: 10.1016/j.jclepro.2018.01.080
10 OWEN A , SCOTT K , BARRETT J . Identifying critical supply chains and final products: an input-output approach to exploring the energy-water-food nexus[J]. Applied Energy, 2018, 210: 632- 642.
doi: 10.1016/j.apenergy.2017.09.069
11 SCHULTZ S . Approaches to identifying key sectors empirically by means of input-output analysis[J]. The Journal of Development Studies, 1977, 14 (1): 77- 96.
doi: 10.1080/00220387708421663
12 黄素心, 王春雷. 产业部门重要性测算:基于假设抽取法的实证[J]. 统计与决策, 2011, 333 (9): 4- 6.
HUANG Suxin , WANG Chunlei . Measurement of industrial sector importance: empirical study based on hypothetical extraction method[J]. Statistics and Decision, 2011, 333 (9): 4- 6.
13 陈效珍, 赵炳新. 基于虚拟消去法(HEM)的产业关联修正影响系数研究[J]. 管理评论, 2014, 26 (6): 23- 32.
CHEN Xiaozhen , ZHAO Bingxin . Research on industry linkage correction influence coefficients based on hypothetical extraction method[J]. Management Review, 2014, 26 (6): 23- 32.
14 朱为华, 刘凯, 闫小勇, 等. 识别流网络关键节点的虚拟外界投入产出分析法[J]. 电子科技大学学报, 2018, 47 (2): 292- 297.
doi: 10.3969/j.issn.1001-0548.2018.02.021
ZHU Weihua , LIU Kai , YAN Xiaoyong , et al. Identification of critical nodes in flow network by a virtual external input-output analysis[J]. Journal of University of Electronic Science and Technology of China, 2018, 47 (2): 292- 297.
doi: 10.3969/j.issn.1001-0548.2018.02.021
15 ACEMOGLU D , CARVALHO V M , OZDAGLAR A , et al. The network origins of aggregate fluctuations[J]. Econometrica, 2012, 80 (5): 1977- 2016.
doi: 10.3982/ECTA9623
16 LUCAS R E Jr . Understanding business cycles[J]. Carnegie-Rochester Conference Series on Public Policy, 1977, 5: 7- 29.
doi: 10.1016/0167-2231(77)90002-1
17 李乔. 矩阵论八讲[M]. 上海: 上海科学技术出版社, 1988: 71- 105.
LI Qiao . Eight lectures on matrix theory[M]. Shanghai: Shanghai Scientific and Technical Publishers, 1988: 71- 105.
18 BALLESTER C , CALVÓ-ARMENGOL A , ZENOU Y . Who's who in networks-wanted: the key player[J]. Econometrica, 2006, 74 (5): 1403- 1417.
doi: 10.1111/ecta.2006.74.issue-5
[1] 董兴林,齐欣. 基于时滞效应的青岛市两阶段科技投入与产出互动关系[J]. 山东大学学报(理学版), 2018, 53(5): 80-87.
Viewed
Full text


Abstract

Cited

  Shared   
  Discussed   
[1] 杨军. 金属基纳米材料表征和纳米结构调控[J]. 山东大学学报(理学版), 2013, 48(1): 1 -22 .
[2] 何海伦, 陈秀兰*. 变性剂和缓冲系统对适冷蛋白酶MCP-01和中温蛋白酶BP-01构象影响的圆二色光谱分析何海伦, 陈秀兰*[J]. 山东大学学报(理学版), 2013, 48(1): 23 -29 .
[3] 赵君1,赵晶2,樊廷俊1*,袁文鹏1,3,张铮1,丛日山1. 水溶性海星皂苷的分离纯化及其抗肿瘤活性研究[J]. J4, 2013, 48(1): 30 -35 .
[4] 孙小婷1,靳岚2*. DOSY在寡糖混合物分析中的应用[J]. J4, 2013, 48(1): 43 -45 .
[5] 罗斯特,卢丽倩,崔若飞,周伟伟,李增勇*. Monte-Carlo仿真酒精特征波长光子在皮肤中的传输规律及光纤探头设计[J]. J4, 2013, 48(1): 46 -50 .
[6] 冒爱琴1, 2, 杨明君2, 3, 俞海云2, 张品1, 潘仁明1*. 五氟乙烷灭火剂高温热解机理研究[J]. J4, 2013, 48(1): 51 -55 .
[7] 杨莹,江龙*,索新丽. 容度空间上保费泛函的Choquet积分表示及相关性质[J]. J4, 2013, 48(1): 78 -82 .
[8] 李永明1, 丁立旺2. PA误差下半参数回归模型估计的r-阶矩相合[J]. J4, 2013, 48(1): 83 -88 .
[9] 唐风琴1,白建明2. 一类带有广义负上限相依索赔额的风险过程大偏差[J]. J4, 2013, 48(1): 100 -106 .
[10] 廖明哲. 哥德巴赫的两个猜想[J]. J4, 2013, 48(2): 1 -14 .