基于聚类动态面板引力模型的国际贸易网络研究

王佳佳, 林明

系统工程理论与实践 ›› 2019, Vol. 39 ›› Issue (4) : 1042-1050.

PDF(656 KB)
中国科学院数学与系统科学研究院期刊网
PDF(656 KB)
系统工程理论与实践 ›› 2019, Vol. 39 ›› Issue (4) : 1042-1050. DOI: 10.12011/1000-6788-2018-1995-09
论文

基于聚类动态面板引力模型的国际贸易网络研究

    王佳佳1, 林明1,2,3
作者信息 +

Dynamic panel gravity model with latent clusters for the international trade network

    WANG Jiajia1, LIN Ming1,2,3
Author information +
文章历史 +

摘要

本文提出一种针对网络型数据的聚类动态面板引力模型，用于国际贸易流量网络的研究.该模型假设各贸易国分属于不同的潜在类别，各国间贸易流量对应的模型系数由出口国和进口国所属的类别决定.提出使用马尔可夫链蒙特卡罗方法对模型参数以及各贸易国所属的潜在类别进行贝叶斯估计.对2001-2015年60个国家间的贸易流量数据进行了实证分析.结果表明，所提出的模型能够对贸易国进行聚类，有效地提高贸易流量预测的精度.所提出的聚类动态面板引力模型可以被广泛的应用于其他动态网络型数据的研究.

Abstract

This paper proposes a dynamic panel gravity model with latent clusters (DPG-LC) to study the international trade network. In the model, the countries are divided into several latent groups. The model coefficients depend on the group labels of the exporting country and the importing country. The Markov chain Monte Carlo method (MCMC) is used to estimate the model under the Bayesian framework. The model is applied to the international trade data of 60 countries from 2001 to 2015. The results show that the DPG-LC model can effectively improve accuracy of predicting trading volumes. The proposed model can be widely applicable to study other dynamic network data.

关键词

动态面板引力模型 / 潜在聚类 / 贸易网络

Key words

dynamic panel gravity model / latent clusters / trade network

引用本文

EndNote

Ris (Procite)

Bibtex

导出引用
王佳佳 , 林明. 基于聚类动态面板引力模型的国际贸易网络研究. 系统工程理论与实践, 2019, 39(4): 1042-1050 https://doi.org/10.12011/1000-6788-2018-1995-09
WANG Jiajia , LIN Ming. Dynamic panel gravity model with latent clusters for the international trade network. Systems Engineering - Theory & Practice, 2019, 39(4): 1042-1050 https://doi.org/10.12011/1000-6788-2018-1995-09
中图分类号： F224.7   

参考文献

[1] Tinbergen J. Shaping the world economy:Suggestions for an international economic policy[M]. New York:The Twentieth Century Fund, 1962.
[2] Anderson J E. A theoretical foundation for the gravity equation[J]. The American Economic Review, 1979, 69(1):106-116.
[3] Bergstrand J H. The gravity equation in international trade:Some microeconomic foundations and empirical evidence[J]. The Review of Economics and Statistics, 1985, 67(3):474-481.
[4] Anderson J E, Wincoop E. Gravity with gravitas:A solution to the border puzzle[J]. The American Economic Review, 2003, 93(1):170-192.
[5] Bergstrand J H. The generalized gravity equation, monopolistic competition, and the factor-proportions theory in international trade[J]. The Review of Economics and Statistics, 1989, 71(1):143-153.
[6] Hummels D, Levinsohn J. Monopolistic competition and international trade:Reconsidering the evidence[J]. The Quarterly Journal of Economics, 1995, 110(3):799-836.
[7] Evenett S J, Keller W. On theories explaining the success of the gravity equation[J]. Journal of Political Economy, 2002, 110(2):281-316.
[8] Rose A K, Wincoop E. National money as a barrier to international trade:The real case for currency union[J]. The American Economic Review, 2001, 91(2):386-390.
[9] Rose A K. Do we really know that the WTO increases trade[J]. The American Economic Review, 2004, 94(1):98-114.
[10] 郝景芳, 马弘. 引力模型的新进展及对中国对外贸易的检验[J]. 数量经济技术经济研究, 2012(10):52-68. Hao J F, Ma H. Gravity equation:A literature review and applications to China's foreign trade[J]. The Journal of Quantitative & Technical Economics, 2012(10):52-68.
[11] 罗来军, 罗雨泽, 刘畅, 等. 基于引力模型重新推导的双边国际贸易检验[J]. 世界经济, 2014(12):67-94.
[12] Olivero M P, Yotov Y V. Dynamic gravity:Endogenous country size and asset accumulation[J]. Canadian Journal of Economics, 2012, 45(1):64-92.
[13] Nuroǧlu E, Kunst R M. Competing specifications of the gravity equation:A three-way model, bilateral interaction effects, or a dynamic gravity model with time-varying country effects[J]. Empirical Economics, 2014, 46(2):733-741.
[14] Chen H, Mirestean A, Tsangarides C G. Bayesian model averaging for dynamic panels with an application to a trade gravity model[J]. Econometric Reviews, 2016, 37(7):777-805.
[15] 何慎远, 李斌, 庞淑娟, 等. 我国出口信用保险对出口促进作用的实证研究[J]. 系统工程理论与实践, 2011, 31(5):792-798. He S Y, Li B, Pang S J, et al. Empirical study on exports promoting effect of China's export credit insurance[J]. Systems Engineering-Theory & Practice, 2011, 31(5):792-798.
[16] Head K, Mayer T. Gravity equations:Workhorse, toolkit, and cookbook[M]. Handbook of International Economics, 2014, 4:131-195.
[17] Stack M. Regional integration and trade:Controlling for varying degrees of heterogeneity in the gravity model[J]. The World Economy, 2009, 32(5):772-789.
[18] Mátyás L. Proper econometric specification of the gravity model[J]. The World Economy, 1997, 20(3):363-368.
[19] Glick R, Rose A K. Does a currency union affect trade? The time-series evidence[J]. European Economic Review, 2002, 46:1125-1151.
[20] Melitz J, Toubal F. Native language, spoken language, translation and trade[J]. Journal of International Economics, 2014, 93(2):351-363.
[21] Berthelon M, Freund C. On the conservation of distance in international trade[J]. Journal of International Economics, 2008, 75(2):310-320.
[22] Kalirajan K. Stochastic varying coefficients gravity model:An application in trade analysis[J]. Journal of Applied Statistics, 1999, 26(2):185-193.
[23] Tzouvelekas V. Accounting for pairwise heterogeneity in bilateral trade flows:A stochastic varying coefficient gravity model[J]. Applied Economics Letters, 2007, 14(12):927-930.
[24] Egger P, Prǔša J. The determinants of trade costs:A random coefficient approach[J]. Empirical Economics, 2016, 50(1):51-58.
[25] Fratianni M, Kang H. Heterogeneous distance-elasticities in trade gravity models[J]. Economics Letters, 2006, 90(1):68-71.
[26] Narayan S, Nguyen T. Does the trade gravity model depend on trading partners? Some evidence from Vietnam and her 54 trading partners[J]. International Review of Economics and Finance, 2016, 41:220-237.
[27] Lin C, Ng S. Estimation of panel data models with parameter heterogeneity when group membership is unknown[J]. Journal of Econometric Methods, 2012, 1(1):42-55.
[28] Bonhomme S, Manresa E. Grouped patterns of heterogeneity in panel data[J]. Econometrica, 2015, 83(3):1147-1184.
[29] Su L, Shi Z, Phillips P. Identifying latent structures in panel data[J]. Econometrica, 2016, 84(6):2215-2264.
[30] 田巍, 姚洋, 余淼杰, 等. 人口结构与国际贸易[J]. 经济研究, 2013(11):87-99. Tian W, Yao Y, Yu M J, et al. Demography and international trade[J]. Economic Research Journal, 2013(11):87-99.
[31] Goldstein J L, Rivers D, Tomz M. Institutions in international relations:Understanding the effects of the GATT and the WTO on world trade[J]. International Organization, 2007, 61(1):37-67.
[32] Felbermayr G J, Toubal F. Cultural proximity and trade[J]. European Economic Review, 2010, 54(2):279-293.
[33] 张晓旭, 梁小珍, 胡毅, 等. 港珠澳大桥建成对香港经济的影响研究[J]. 系统工程理论与实践, 2016, 36(12):3026-3033. Zhang X X, Liang X Z, Hu Y, et al. Analysis of the impact on Hong Kong's economy due to the establishment of Hong Kong-Zhuhai-Macao bridge[J]. Systems Engineering-Theory & Practice, 2016, 36(12):3026-3033.
[34] Keck A, Raubold A, Truppia A. Forecasting international trade:A time series approach[J]. OECD Journal:Journal of Business Cycle Measurement and Analysis, 2009, 2:157-176.
[35] 盛斌, 廖明中. 中国的贸易流量与出口潜力:引力模型的研究[J]. 世界经济, 2004(2):3-12.
[36] Zellner A, Hong C, Min C. Forecasting turning points in international output growth rates using Bayesian exponentially weighted autoregression, time-varying parameter and pooling techniques[J]. Journal of Econometrics, 1991, 49(1-2):275-304.
[37] Sewell D K, Chen Y. Latent space models for dynamic networks[J]. Journal of the American Statistical Association, 2015, 110(512):1646-1657.
[38] Sewell D K, Chen Y. Latent space models for dynamic networks with weighted edges[J]. Social Networks, 2016, 44:105-116.

基金

国家自然科学基金（11101341，71631004，71131008）
PDF(656 KB)

Accesses

Citation

Detail
段落导航
相关文章

/

〈 〉