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Persistence, Randomization, and Spatial Noise

Author

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  • Morgan Kelly

Abstract

Historical persistence studies and other regressions using spatial data commonly have severely inflated t statistics, and different standard error adjustments to correct for this return markedly different estimates. This paper proposes a simple randomization inference procedure where the significance level of an explanatory variable is measured by its ability to outperform synthetic noise with the same estimated spatial structure. Spatial noise, in other words, acts as a treatment randomization in an artificial experiment based on correlated observational data. Combined with Müller and Watson (2021), randomization gives a way to estimate credible confidence intervals for spatial regressions. The performance of twenty persistence studies relative to spatial noise is examined.

Suggested Citation

  • Morgan Kelly, 2021. "Persistence, Randomization, and Spatial Noise," Working Papers 202124, School of Economics, University College Dublin.
    • Handle: RePEc:ucn:wpaper:202124
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    File URL: http://hdl.handle.net/10197/12565
    File Function: First version, 2021
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    Citations

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    Cited by:

    1. Cinnirella, Francesco & Hornung, Eric & Koschnick, Julius, 2022. "Flow of Ideas : Economic Societies and the Rise of Useful Knowledge," CAGE Online Working Paper Series 632, Competitive Advantage in the Global Economy (CAGE).
    2. Neha Deopa & Daniele Rinaldo, 2023. "Sacred Ecology: The Environmental Impact of African Traditional Religions," Papers 2401.13673, arXiv.org.
    3. Dalgaard, Carl-Johan & Kaarsen, Nicolai & Olsson, Ola & Selaya, Pablo, 2022. "Roman roads to prosperity: Persistence and non-persistence of public infrastructure," Journal of Comparative Economics, Elsevier, vol. 50(4), pages 896-916.
    4. Martina Cioni & Giovanni Federico & Michelangelo Vasta, 2022. "Persistence studies: a new kind of economic history?," Review of Regional Research: Jahrbuch für Regionalwissenschaft, Springer;Gesellschaft für Regionalforschung (GfR), vol. 42(3), pages 227-248, December.
    5. Kevin Hjortshøj O’Rourke, 2022. "Globalization," Working Papers 20220075, New York University Abu Dhabi, Department of Social Science, revised Jan 2022.
    6. Adhikari, Tamanna & Whelan, Karl, 2023. "Did raising doing business scores boost GDP?," Journal of Comparative Economics, Elsevier, vol. 51(3), pages 1011-1030.

    More about this item

    Keywords

    Historical persistence; Spatial data; Randomization inference; Spatial noise;
    All these keywords.

    JEL classification:

    • N0 - Economic History - - General

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