IDEAS home Printed from https://ideas.repec.org/a/spr/jospat/v1y2020i1d10.1007_s43071-020-00005-w.html
   My bibliography  Save this article

Network dependence in multi-indexed data on international trade flows

Author

Listed:
  • Manfred M. Fischer

    (Vienna University of Economics and Business)

  • James P. LeSage

    (Texas State University)

Abstract

Faced with the problem that conventional multidimensional fixed effects models only focus on unobserved heterogeneity, but ignore any potential cross-sectional dependence due to network interactions, we introduce a model of trade flows between countries over time that allows for network dependence in flows, based on sociocultural connectivity structures. We show that conventional multidimensional fixed effects model specifications exhibit cross-sectional dependence between countries that should be modeled to avoid simultaneity bias. Given that the source of network interaction is unknown, we propose a panel gravity model that examines multiple network interaction structures, using Bayesian model probabilities to determine those most consistent with the sample data. This is accomplished with the use of computationally efficient Markov Chain Monte Carlo estimation methods that produce a Monte Carlo integration estimate of the log-marginal likelihood that can be used for model comparison. Application of the model to a panel of trade flows points to network spillover effects, suggesting the presence of network dependence and biased estimates from conventional trade flow specifications. The most important sources of network dependence were found to be membership in trade organizations, historical colonial ties, common currency, and spatial proximity of countries.

Suggested Citation

  • Manfred M. Fischer & James P. LeSage, 2020. "Network dependence in multi-indexed data on international trade flows," Journal of Spatial Econometrics, Springer, vol. 1(1), pages 1-26, December.
  • Handle: RePEc:spr:jospat:v:1:y:2020:i:1:d:10.1007_s43071-020-00005-w
    DOI: 10.1007/s43071-020-00005-w
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s43071-020-00005-w
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.

    File URL: https://libkey.io/10.1007/s43071-020-00005-w?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to look for a different version below or search for a different version of it.

    Other versions of this item:

    References listed on IDEAS

    as
    1. Badi H. Baltagi & Esfandiar Maasoumi, 2013. "An Overview of Dependence in Cross-Section, Time-Series, and Panel Data," Econometric Reviews, Taylor & Francis Journals, vol. 32(5-6), pages 543-546, August.
    2. James E. Anderson & Eric van Wincoop, 2004. "Trade Costs," Journal of Economic Literature, American Economic Association, vol. 42(3), pages 691-751, September.
    3. Kristian Behrens & Cem Ertur & Wilfried Koch, 2012. "‘Dual’ Gravity: Using Spatial Econometrics To Control For Multilateral Resistance," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 27(5), pages 773-794, August.
    4. Laszlo Balazsi & Laszlo Matyas & Tom Wansbeek, 2018. "The estimation of multidimensional fixed effects panel data models," Econometric Reviews, Taylor & Francis Journals, vol. 37(3), pages 212-227, March.
    5. James E. Anderson & Eric van Wincoop, 2003. "Gravity with Gravitas: A Solution to the Border Puzzle," American Economic Review, American Economic Association, vol. 93(1), pages 170-192, March.
    6. L W Hepple, 1995. "Bayesian Techniques in Spatial and Network Econometrics: 2. Computational Methods and Algorithms," Environment and Planning A, , vol. 27(4), pages 615-644, April.
    7. James P. LeSage & Manfred M. Fischer, 2016. "Spatial Regression-Based Model Specifications for Exogenous and Endogenous Spatial Interaction," Advances in Spatial Science, in: Roberto Patuelli & Giuseppe Arbia (ed.), Spatial Econometric Interaction Modelling, chapter 0, pages 15-36, Springer.
    8. Vasilis Sarafidis & Tom Wansbeek, 2012. "Cross-Sectional Dependence in Panel Data Analysis," Econometric Reviews, Taylor & Francis Journals, vol. 31(5), pages 483-531, September.
    9. Peter Egger & Michael Pfaffermayr, 2003. "The proper panel econometric specification of the gravity equation: A three-way model with bilateral interaction effects," Empirical Economics, Springer, vol. 28(3), pages 571-580, July.
    10. Ranjan, Priya & Tobias, Justin, 2007. "Bayesian Inference in the Gravity Model," Staff General Research Papers Archive 12721, Iowa State University, Department of Economics.
    11. LeSage, James P. & Chih, Yao-Yu & Vance, Colin, 2019. "Markov Chain Monte Carlo estimation of spatial dynamic panel models for large samples," Computational Statistics & Data Analysis, Elsevier, vol. 138(C), pages 107-125.
    12. Wilfried Koch & James P. LeSage, 2015. "Latent Multilateral Trade Resistance Indices: Theory and Evidence," Scottish Journal of Political Economy, Scottish Economic Society, vol. 62(3), pages 264-290, July.
    13. James P. LeSage & Christine Thomas-Agnan, 2015. "Interpreting Spatial Econometric Origin-Destination Flow Models," Journal of Regional Science, Wiley Blackwell, vol. 55(2), pages 188-208, March.
    14. Robert C. Feenstra, 2002. "Border Effects and the Gravity Equation: Consistent Methods for Estimation," Scottish Journal of Political Economy, Scottish Economic Society, vol. 49(5), pages 491-506, November.
    15. World Bank, 2002. "World Development Indicators 2002," World Bank Publications - Books, The World Bank Group, number 13921.
    16. Lung-fei Lee & Jihai Yu, 2012. "QML Estimation of Spatial Dynamic Panel Data Models with Time Varying Spatial Weights Matrices," Spatial Economic Analysis, Taylor & Francis Journals, vol. 7(1), pages 31-74, March.
    17. Debarsy, Nicolas & LeSage, James, 2018. "Flexible dependence modeling using convex combinations of different types of connectivity structures," Regional Science and Urban Economics, Elsevier, vol. 69(C), pages 48-68.
    18. James P. LeSage & R. Kelley Pace, 2008. "Spatial Econometric Modeling Of Origin‐Destination Flows," Journal of Regional Science, Wiley Blackwell, vol. 48(5), pages 941-967, December.
    19. Baltagi, Badi H., 2015. "The Oxford Handbook of Panel Data," OUP Catalogue, Oxford University Press, number 9780199940042.
    20. Debarsy, Nicolas & LeSage, James, 2018. "Flexible dependence modeling using convex combinations of different types of connectivity structures," Regional Science and Urban Economics, Elsevier, vol. 69(C), pages 48-68.
    21. James Paul LeSage, 2020. "Fast MCMC estimation of multiple W-matrix spatial regression models and Metropolis–Hastings Monte Carlo log-marginal likelihoods," Journal of Geographical Systems, Springer, vol. 22(1), pages 47-75, January.
    22. Priya Ranjan & Justin L. Tobias, 2007. "Bayesian inference for the gravity model," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 22(4), pages 817-838.
    23. James Paul LeSage & Manfred M. Fischer, 2020. "Cross-sectional dependence model specifications in a static trade panel data setting," Journal of Geographical Systems, Springer, vol. 22(1), pages 5-46, January.
    24. Tamás Krisztin & Manfred M. Fischer, 2015. "The Gravity Model for International Trade: Specification and Estimation Issues," Spatial Economic Analysis, Taylor & Francis Journals, vol. 10(4), pages 451-470, December.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Dargel, Lukas & Thomas-Agnan, Christine, 2022. "A generalized framework for estimating spatial econometric interaction models," TSE Working Papers 22-1312, Toulouse School of Economics (TSE).
    2. Thomas-Agnan, Christine & Dargel, Lukas, 2023. "Efficient Estimation of Spatial Econometric Interaction Models for Sparse OD Matrices," TSE Working Papers 23-1409, Toulouse School of Economics (TSE).
    3. Sucharita Gopal & Manfred M. Fischer, 2023. "Opioid mortality in the US: quantifying the direct and indirect impact of sociodemographic and socioeconomic factors," Letters in Spatial and Resource Sciences, Springer, vol. 16(1), pages 1-17, December.
    4. Dargel, Lukas, 2021. "Revisiting Estimation Methods for Spatial Econometric Interaction Models," TSE Working Papers 21-1192, Toulouse School of Economics (TSE).
    5. Yufei Lin & Yingxia Pu & Xinyi Zhao & Guangqing Chi & Cui Ye, 2023. "The Spatiotemporal Elasticity of Age Structure in China’s Interprovincial Migration System," Sustainability, MDPI, vol. 15(10), pages 1-18, May.
    6. Lukas Dargel, 2021. "Revisiting estimation methods for spatial econometric interaction models," Journal of Spatial Econometrics, Springer, vol. 2(1), pages 1-41, December.
    7. Albert Millogo & Ines Trojette, 2020. "Pro-trade effects of MENA immigrants in France: does governance matter?," Economics Bulletin, AccessEcon, vol. 40(4), pages 3219-3230.
    8. Peter Nijkamp & Waldemar Ratajczak, 2021. "Gravitational Analysis in Regional Science and Spatial Economics: A Vector Gradient Approach to Trade," International Regional Science Review, , vol. 44(3-4), pages 400-431, May.
    9. Yuxue Sheng & James Paul LeSage, 2021. "Interpreting spatial regression models with multiplicative interaction explanatory variables," Journal of Geographical Systems, Springer, vol. 23(3), pages 333-360, July.
    10. Jeong, Hanbat & Lee, Lung-fei, 2024. "Maximum likelihood estimation of a spatial autoregressive model for origin–destination flow variables," Journal of Econometrics, Elsevier, vol. 242(1).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. James Paul LeSage & Manfred M. Fischer, 2020. "Cross-sectional dependence model specifications in a static trade panel data setting," Journal of Geographical Systems, Springer, vol. 22(1), pages 5-46, January.
    2. Wilfried Koch & James P. LeSage, 2015. "Latent Multilateral Trade Resistance Indices: Theory and Evidence," Scottish Journal of Political Economy, Scottish Economic Society, vol. 62(3), pages 264-290, July.
    3. Rodolfo Metulini & Roberto Patuelli & Daniel A. Griffith, 2018. "A Spatial-Filtering Zero-Inflated Approach to the Estimation of the Gravity Model of Trade," Econometrics, MDPI, vol. 6(1), pages 1-15, February.
    4. Rodolfo Metulini & Paolo Sgrignoli & Stefano Schiavo & Massimo Riccaboni, 2018. "The network of migrants and international trade," Economia Politica: Journal of Analytical and Institutional Economics, Springer;Fondazione Edison, vol. 35(3), pages 763-787, December.
    5. Carlos Llano-Verduras & Santiago Pérez-Balsalobre & Ana Rincón-Aznar, 2021. "Market fragmentation and the rise of sub-national regulation," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 67(3), pages 765-797, December.
    6. Maria Cipollina & Luca De Benedictis & Luca Salvatici & Claudio Vicarelli, 2016. "Policy Measurement And Multilateral Resistance In Gravity Models," Working Papers LuissLab 16130, Dipartimento di Economia e Finanza, LUISS Guido Carli.
    7. Pamela Smith & Xiangwen Kong, 2022. "Intellectual property rights and trade: The exceptional case of GMOs," The World Economy, Wiley Blackwell, vol. 45(3), pages 763-811, March.
    8. Lukas Dargel, 2021. "Revisiting estimation methods for spatial econometric interaction models," Journal of Spatial Econometrics, Springer, vol. 2(1), pages 1-41, December.
    9. Peter Egger & Michael Pfaffermayr, 2016. "A generalized spatial error components model for gravity equations," Empirical Economics, Springer, vol. 50(1), pages 177-195, February.
    10. Moura, Ticiana Grecco Zanon & Chen, Zhangliang & Garcia-Alonso, Lorena, 2019. "Spatial interaction effects on inland distribution of maritime flows," Transportation Research Part A: Policy and Practice, Elsevier, vol. 128(C), pages 1-10.
    11. Kristian Behrens & Cem Ertur & Wilfried Koch, 2012. "‘Dual’ Gravity: Using Spatial Econometrics To Control For Multilateral Resistance," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 27(5), pages 773-794, August.
    12. Fischer, Manfred M. & LeSage, James P., 2018. "The role of socio-cultural factors in static trade panel models," Working Papers in Regional Science 2018/04, WU Vienna University of Economics and Business.
    13. Andrew J. Cassey & Katherine N. Schmeiser & Andreas Waldkirch, 2016. "Exporting Spatial Externalities," Open Economies Review, Springer, vol. 27(4), pages 697-720, September.
    14. J.A. Bikker, 2009. "An extended gravity model with substitution applied to international trade," Working Papers 09-17, Utrecht School of Economics.
    15. Vollrath, Thomas L. & Hallahan, Charles B., 2009. "Economic costs and payoffs of bilateral/regional trade agreements," 2009 Annual Meeting, July 26-28, 2009, Milwaukee, Wisconsin 49375, Agricultural and Applied Economics Association.
    16. repec:dau:papers:123456789/7446 is not listed on IDEAS
    17. Nicolas Péridy, 2006. "La nouvelle politique de voisinage de l'Union européenne. Une estimation des potentiels de commerce," Revue économique, Presses de Sciences-Po, vol. 57(4), pages 727-746.
    18. Oxana Babecká Kucharčuková & Jan Babecký & Martin Raiser, 2012. "Gravity Approach for Modelling International Trade in South-Eastern Europe and the Commonwealth of Independent States: The Role of Geography, Policy and Institutions," Open Economies Review, Springer, vol. 23(2), pages 277-301, April.
    19. repec:dau:papers:123456789/7448 is not listed on IDEAS
    20. James P. LeSage & Christine Thomas-Agnan, 2015. "Interpreting Spatial Econometric Origin-Destination Flow Models," Journal of Regional Science, Wiley Blackwell, vol. 55(2), pages 188-208, March.
    21. Marie Daumal & Soledad Zignago, 2010. "Measure and determinants of border effects of Brazilian states," Papers in Regional Science, Wiley Blackwell, vol. 89(4), pages 735-758, November.
    22. Bo Xiong & Sixia Chen, 2014. "Estimating gravity equation models in the presence of sample selection and heteroscedasticity," Applied Economics, Taylor & Francis Journals, vol. 46(24), pages 2993-3003, August.

    More about this item

    Keywords

    Origin-destination panel data flows; Cross-sectional dependence; MCMC estimation; Log-marginal likelihood; Gravity models of trade; Sociocultural distance;
    All these keywords.

    JEL classification:

    • C18 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Methodolical Issues: General
    • C33 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Models with Panel Data; Spatio-temporal Models
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:jospat:v:1:y:2020:i:1:d:10.1007_s43071-020-00005-w. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.