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Econometric connectedness as a measure of urban influence: evidence from Maine

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  • Thomas F. P. Wiesen

    (University of Maine School of Economics)

  • Todd Gabe

    (University of Maine School of Economics)

  • Lakshya Bharadwaj

    (University of Maine School of Economics)

Abstract

We propose a new indicator of urban influence, which builds from the concept of econometric connectedness that is commonly used to measure market integration in finance and macroeconomics. This metric, based upon a vector autoregression model, quantifies the fraction of the forecast error variance of a non-urban area’s economic activity that can be explained by the economic shocks of urban regions. As an illustration, we apply this metric to data on monthly total taxable sales for regions in the US state of Maine, with urban influence scores calculated relative to the state’s three largest cities. Additionally, we investigate how this measure of urban influence is related to a non-urban area’s population size, its distance to one of the state’s three largest cities, whether the region is coastal, and the importance of visitors to the area.

Suggested Citation

  • Thomas F. P. Wiesen & Todd Gabe & Lakshya Bharadwaj, 2023. "Econometric connectedness as a measure of urban influence: evidence from Maine," Letters in Spatial and Resource Sciences, Springer, vol. 16(1), pages 1-16, December.
    • Handle: RePEc:spr:lsprsc:v:16:y:2023:i:1:d:10.1007_s12076-023-00353-9
    DOI: 10.1007/s12076-023-00353-9
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    as
    1. Bouri, Elie & Cepni, Oguzhan & Gabauer, David & Gupta, Rangan, 2021. "Return connectedness across asset classes around the COVID-19 outbreak," International Review of Financial Analysis, Elsevier, vol. 73(C).
    2. Pukthuanthong, Kuntara & Roll, Richard, 2009. "Global market integration: An alternative measure and its application," Journal of Financial Economics, Elsevier, vol. 94(2), pages 214-232, November.
    3. Diebold, Francis X. & Yılmaz, Kamil, 2014. "On the network topology of variance decompositions: Measuring the connectedness of financial firms," Journal of Econometrics, Elsevier, vol. 182(1), pages 119-134.
    4. Mert Demirer & Francis X. Diebold & Laura Liu & Kamil Yilmaz, 2018. "Estimating global bank network connectedness," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 33(1), pages 1-15, January.
    5. Billio, Monica & Getmansky, Mila & Lo, Andrew W. & Pelizzon, Loriana, 2012. "Econometric measures of connectedness and systemic risk in the finance and insurance sectors," Journal of Financial Economics, Elsevier, vol. 104(3), pages 535-559.
    6. Nikolaos Antonakakis & Ioannis Chatziantoniou & David Gabauer, 2021. "A regional decomposition of US housing prices and volume: market dynamics and Portfolio diversification," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 66(2), pages 279-307, April.
    7. Yang, Jian & Yu, Ziliang & Deng, Yongheng, 2018. "Housing price spillovers in China: A high-dimensional generalized VAR approach," Regional Science and Urban Economics, Elsevier, vol. 68(C), pages 98-114.
    8. Brigitte Waldorf, 2009. "Is human capital accumulation a self-propelling process? Comparing educational attainment levels of movers and stayers," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 43(2), pages 323-344, June.
    9. Koop, Gary & Pesaran, M. Hashem & Potter, Simon M., 1996. "Impulse response analysis in nonlinear multivariate models," Journal of Econometrics, Elsevier, vol. 74(1), pages 119-147, September.
    10. Francis X. Diebold & Kamil Yilmaz, 2009. "Measuring Financial Asset Return and Volatility Spillovers, with Application to Global Equity Markets," Economic Journal, Royal Economic Society, vol. 119(534), pages 158-171, January.
    11. Belal Fallah & Mark Partridge, 2007. "The elusive inequality-economic growth relationship: are there differences between cities and the countryside?," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 41(2), pages 375-400, June.
    12. Pesaran, H. Hashem & Shin, Yongcheol, 1998. "Generalized impulse response analysis in linear multivariate models," Economics Letters, Elsevier, vol. 58(1), pages 17-29, January.
    13. Wiesen, Thomas F.P. & Beaumont, Paul M. & Norrbin, Stefan C. & Srivastava, Anuj, 2018. "Are generalized spillover indices overstating connectedness?," Economics Letters, Elsevier, vol. 173(C), pages 131-134.
    14. Ghelfi, Linda M. & Parker, Timothy S., 1997. "A County-Level Measure of Urban Influence," Staff Reports 278818, United States Department of Agriculture, Economic Research Service.
    15. Antonakakis, Nikolaos, 2012. "Exchange return co-movements and volatility spillovers before and after the introduction of euro," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 22(5), pages 1091-1109.
    16. repec:wsr:wpaper:y:2012:i:080 is not listed on IDEAS
    17. Mitch Renkow, 2003. "Employment Growth, Worker Mobility, and Rural Economic Development," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 85(2), pages 503-513.
    18. McGranahan, David A., 1999. "Natural Amenities Drive Rural Population Change," Agricultural Economic Reports 33955, United States Department of Agriculture, Economic Research Service.
    19. Liu, Yuntong & Wei, Yu & Wang, Qian & Liu, Yi, 2022. "International stock market risk contagion during the COVID-19 pandemic," Finance Research Letters, Elsevier, vol. 45(C).
    20. Parker, Timothy S. & Ghelfi, Linda M., 2004. "Using the 2003 Urban Influence Codes to Understand Rural America," Amber Waves:The Economics of Food, Farming, Natural Resources, and Rural America, United States Department of Agriculture, Economic Research Service, pages 1-2, April.
    21. Sims, Christopher A, 1980. "Macroeconomics and Reality," Econometrica, Econometric Society, vol. 48(1), pages 1-48, January.
    22. Waldorf, Brigitte S., 2006. "A Continuous Multi-dimensional Measure of Rurality: Moving Beyond Threshold Measures," 2006 Annual meeting, July 23-26, Long Beach, CA 21383, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    23. Gordon Mulligan & Mark Partridge & John Carruthers, 2012. "Central place theory and its reemergence in regional science," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 48(2), pages 405-431, April.
    24. Gordon F. Mulligan, 1984. "Agglomeration and Central Place Theory: A Review of the Literature," International Regional Science Review, , vol. 9(1), pages 1-42, September.
    25. Diebold, Francis X. & Yilmaz, Kamil, 2012. "Better to give than to receive: Predictive directional measurement of volatility spillovers," International Journal of Forecasting, Elsevier, vol. 28(1), pages 57-66.
    26. Narayan, Paresh Kumar, 2022. "Understanding exchange rate shocks during COVID-19," Finance Research Letters, Elsevier, vol. 45(C).
    27. Cronin, David, 2014. "The interaction between money and asset markets: A spillover index approach," Journal of Macroeconomics, Elsevier, vol. 39(PA), pages 185-202.
    28. Anufriev, Mikhail & Panchenko, Valentyn, 2015. "Connecting the dots: Econometric methods for uncovering networks with an application to the Australian financial institutions," Journal of Banking & Finance, Elsevier, vol. 61(S2), pages 241-255.
    29. Yi, Shuyue & Xu, Zishuang & Wang, Gang-Jin, 2018. "Volatility connectedness in the cryptocurrency market: Is Bitcoin a dominant cryptocurrency?," International Review of Financial Analysis, Elsevier, vol. 60(C), pages 98-114.
    30. David A. McGranahan & Timothy R. Wojan & Dayton M. Lambert, 2011. "The rural growth trifecta: outdoor amenities, creative class and entrepreneurial context -super-§," Journal of Economic Geography, Oxford University Press, vol. 11(3), pages 529-557, May.
    31. Miller, Kathleen K. & Weber, Bruce A., 2003. "Persistent Poverty Across The Rural-Urban Continuum," Working Papers 18910, Oregon State University, Rural Poverty Research Center (RPRC).
    32. Ghelfi, Linda M. & Parker, Timothy S., 1997. "A County-Level Measure of Urban Influence," Rural America/ Rural Development Perspectives, United States Department of Agriculture, Economic Research Service, vol. 12(2), February.
    Full references (including those not matched with items on IDEAS)

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    More about this item

    Keywords

    Connectedness; Market integration; Rurality; Variance decomposition; Urban influence;
    All these keywords.

    JEL classification:

    • R12 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General Regional Economics - - - Size and Spatial Distributions of Regional Economic Activity; Interregional Trade (economic geography)
    • C4 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics
    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models

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