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Hot and Cold Spot Analysis Using Stata

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  • KONDO Keisuke

Abstract

Spatial analysis is attracting more attention from Stata users with the increasing availability of regional data. This article presents an implementation of hot and cold spot analysis using Stata. For this purpose, I introduce the new command getisord, which calculates the Getis-Ord Gi* (d) statistic in Stata. To implement this command, the only additionally required information is the latitude and longitude of regions. In combination with shape files, results obtained from the getisord command can be visually displayed in Stata. In this article, I offer an interesting illustration to explain how the getisord command works in Stata.

Suggested Citation

  • KONDO Keisuke, 2015. "Hot and Cold Spot Analysis Using Stata," Discussion papers 15901, Research Institute of Economy, Trade and Industry (RIETI).
    • Handle: RePEc:eti:dpaper:15901
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    1. Sascha O. Becker, Sascha O & Voth, Hans-Joachim, 2023. "From the Death of God to the Rise of Hitler," The Warwick Economics Research Paper Series (TWERPS) 1478, University of Warwick, Department of Economics.
    2. Luigi Aldieri & Concetto Paolo Vinci, 2017. "Theoretical and Empirical Foundations of Energy Production Efficiency Activity," International Business Research, Canadian Center of Science and Education, vol. 10(9), pages 39-49, September.
    3. Becker, Sascha O. & Voth, Hans-Joachim, 2023. "From the Death of God to the Rise of Hitler," CAGE Online Working Paper Series 688, Competitive Advantage in the Global Economy (CAGE).
    4. Obschonka, Martin & Lee, Neil & Rodríguez-Pose, Andrés & Eichstaedt, johannes Christopher & Ebert, Tobias, 2018. "Big Data, artificial intelligence and the geography of entrepreneurship in the United States," OSF Preprints c62tn, Center for Open Science.
    5. Nielsen, Hana, 2021. "Coal and Sugar: The Black and White Gold of Czech Industrialization (1841-1863)," Lund Papers in Economic History 229, Lund University, Department of Economic History.
    6. repec:ags:aaea22:336001 is not listed on IDEAS
    7. Martin Obschonka & Neil Lee & Andrés Rodríguez-Pose & Johannes C. Eichstaedt & Tobias Ebert, 2020. "Big data methods, social media, and the psychology of entrepreneurial regions: capturing cross-county personality traits and their impact on entrepreneurship in the USA," Small Business Economics, Springer, vol. 55(3), pages 567-588, October.
    8. Luigi Aldieri & Concetto Paolo Vinci, 2018. "An assessment of energy production efficiency activity: a spatial analysis," Letters in Spatial and Resource Sciences, Springer, vol. 11(3), pages 233-243, October.
    9. Andreas Ferrara & Price Fishback, 2024. "Discrimination, Migration, and Economic Outcomes: Evidence from World War I," The Review of Economics and Statistics, MIT Press, vol. 106(5), pages 1201-1219, September.
    10. Yu, Yantuan & Peng, Chong & Li, Yushuang, 2019. "Do neighboring prefectures matter in promoting eco-efficiency? Empirical evidence from China," Technological Forecasting and Social Change, Elsevier, vol. 144(C), pages 456-465.
    11. Hooijen, Inge & Bijlsma, Ineke & Cörvers, Frank & Poulissen, Davey, 2020. "The geographical psychology of recent graduates in the Netherlands: Relating environmental factors and personality traits to location choice," ROA Research Memorandum 001, Maastricht University, Research Centre for Education and the Labour Market (ROA).

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