IDEAS home Printed from https://ideas.repec.org/a/spr/apjors/v8y2024i4d10.1007_s41685-024-00352-8.html
   My bibliography  Save this article

Spatial regression analysis of political gender gap in Japan

Author

Listed:
  • Kenichi Kuromiya

    (Nagoya University)

Abstract

Internationally, it has been repeatedly pointed out that the proportion of female members in the Diet and the local assemblies is extremely low in Japan. This is called a political gender gap. We analyzed the relationships between socioeconomic indicators and this political gender gap, and underlying causes using several spatial regression models. Prefectures are geographically connected; so, they can influence each other. Therefore, we incorporated geographical relationships between prefectures into the model. We found that a high proportion of women in a particular prefectural assembly was associated with a low proportion of women in adjacent prefectural assemblies. Thus, competition and repulsion exist between the adjacent prefectural assemblies. Furthermore, several series of analyses using spatial regression models showed that the impact of the political gender gap in a particular prefecture spread to adjacent prefectures, but not further. We found that considering prefectural spatial autocorrelations was important while examining the political gender gap, and previous studies that did not consider spatial autocorrelation might have been biased. However, here we were able to better explain the background of real-world phenomena occurring in the real world by applying spatial regression models.

Suggested Citation

  • Kenichi Kuromiya, 2024. "Spatial regression analysis of political gender gap in Japan," Asia-Pacific Journal of Regional Science, Springer, vol. 8(4), pages 1163-1184, December.
    • Handle: RePEc:spr:apjors:v:8:y:2024:i:4:d:10.1007_s41685-024-00352-8
    DOI: 10.1007/s41685-024-00352-8
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s41685-024-00352-8
    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/s41685-024-00352-8?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 search for a different version of it.

    References listed on IDEAS

    as
    1. James P. LeSage, 2014. "What Regional Scientists Need to Know about Spatial Econometrics," The Review of Regional Studies, Southern Regional Science Association, vol. 44(1), pages 13-32, Spring.
    2. Burridge, Peter, 2011. "A research agenda on general-to-specific spatial model search," INVESTIGACIONES REGIONALES - Journal of REGIONAL RESEARCH, Asociación Española de Ciencia Regional, issue 21, pages 71-90.
    3. James P. LeSage & R. Kelley Pace, 2018. "Spatial econometric Monte Carlo studies: raising the bar," Empirical Economics, Springer, vol. 55(1), pages 17-34, August.
    4. J. Elhorst, 2010. "Applied Spatial Econometrics: Raising the Bar," Spatial Economic Analysis, Taylor & Francis Journals, vol. 5(1), pages 9-28.
    5. Lung-fei Lee & Xiaodong Liu & Xu Lin, 2010. "Specification and estimation of social interaction models with network structures," Econometrics Journal, Royal Economic Society, vol. 13(2), pages 145-176, July.
    Full references (including those not matched with items on IDEAS)

    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. Kenichi Kuromiya, 2022. "Econometric analysis of the employment of persons with disabilities in prefectural boards of education," International Journal of Economic Policy Studies, Springer, vol. 16(2), pages 423-441, August.
    2. Süleyman Taşpınar & Osman DoĞan & Jiyoung Chae & Anil K. Bera, 2021. "Bayesian Inference in Spatial Stochastic Volatility Models: An Application to House Price Returns in Chicago," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 83(5), pages 1243-1272, October.
    3. Ariane Amin & Johanna Choumert, 2015. "Development and biodiversity conservation in Sub-Saharan Africa: A spatial analysis," Economics Bulletin, AccessEcon, vol. 35(1), pages 729-744.
    4. Azémar, Céline & Desbordes, Rodolphe & Wooton, Ian, 2020. "Is international tax competition only about taxes? A market-based perspective," Journal of Comparative Economics, Elsevier, vol. 48(4), pages 891-912.
    5. Haller, Peter & Heuermann, Daniel F., 2016. "Job search and hiring in local labor markets: Spillovers in regional matching functions," Regional Science and Urban Economics, Elsevier, vol. 60(C), pages 125-138.
    6. Shishir Shakya & Alicia Plemmons & Juan Tomas Sayago-Gomez, 2022. "Spatial spillovers and the productivity-compensation gap in the United States," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 68(3), pages 669-689, June.
    7. Kadam, Parag & Magnan, Nicholas & Dwivedi, Puneet, 2023. "A spatial dependence approach to assessing the impacts of Sustainable Forestry Initiative’s Fiber Sourcing certification on forestry Best Management Practices in Georgia, United States," Forest Policy and Economics, Elsevier, vol. 157(C).
    8. Simon K. C. Cheung & Tommy K. Y. Cheung, 2022. "Mixed membership nearest neighbor model with feature difference," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(8), pages 1578-1594, December.
    9. Morton, Craig & Anable, Jillian & Yeboah, Godwin & Cottrill, Caitlin, 2018. "The spatial pattern of demand in the early market for electric vehicles: Evidence from the United Kingdom," Journal of Transport Geography, Elsevier, vol. 72(C), pages 119-130.
    10. Baltagi, Badi H. & Rokicki, Bartlomiej, 2014. "The spatial Polish wage curve with gender effects: Evidence from the Polish Labor Survey," Regional Science and Urban Economics, Elsevier, vol. 49(C), pages 36-47.
    11. Matteo Lippi Bruni & Irene Mammi, 2017. "Spatial effects in hospital expenditures: A district level analysis," Health Economics, John Wiley & Sons, Ltd., vol. 26(S2), pages 63-77, September.
    12. Amin, A. & Choumert-Nkolo, J. & Combes, J.-L. & Combes Motel, P. & Kéré, E.N. & Ongono-Olinga, J.-G. & Schwartz, S., 2019. "Neighborhood effects in the Brazilian Amazônia: Protected areas and deforestation," Journal of Environmental Economics and Management, Elsevier, vol. 93(C), pages 272-288.
    13. Peter Burridge & J. Paul Elhorst & Katarina Zigova, 2016. "Group Interaction in Research and the Use of General Nesting Spatial Models," Advances in Econometrics, in: Spatial Econometrics: Qualitative and Limited Dependent Variables, volume 37, pages 223-258, Emerald Group Publishing Limited.
    14. Cassandra Johnson Gaither & Sadia Afrin & Fernando Garcia-Menendez & M. Talat Odman & Ran Huang & Scott Goodrick & Alan Ricardo da Silva, 2019. "African American Exposure to Prescribed Fire Smoke in Georgia, USA," IJERPH, MDPI, vol. 16(17), pages 1-15, August.
    15. 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.
    16. Roger Bivand & Giovanni Millo & Gianfranco Piras, 2021. "A Review of Software for Spatial Econometrics in R," Mathematics, MDPI, vol. 9(11), pages 1-40, June.
    17. Carlos Carreira & Luís Lopes, 2020. "How are the potential gains from economic activity transmitted to the labour factor: more employment or more wages? Evidence from the Portuguese context," Regional Science Policy & Practice, Wiley Blackwell, vol. 12(2), pages 319-348, April.
    18. Ludwik Wicki & Robert Pietrzykowski & Dariusz Kusz, 2022. "Factors Determining the Development of Prosumer Photovoltaic Installations in Poland," Energies, MDPI, vol. 15(16), pages 1-19, August.
    19. Zhang, Jianhua & Ballas, Dimitris & Liu, Xiaolong, 2023. "Neighbourhood-level spatial determinants of residential solar photovoltaic adoption in the Netherlands," Renewable Energy, Elsevier, vol. 206(C), pages 1239-1248.
    20. Guilherme Cemin Paula & André M. Marques, 2022. "Brazilian Wage Curve: Further Evidence Based on Spatial Interactions in Times of Recession, 2012–2019," The Indian Journal of Labour Economics, Springer;The Indian Society of Labour Economics (ISLE), vol. 65(3), pages 689-708, September.

    More about this item

    Keywords

    Political gender gap; Socioeconomic characteristics; Spatial regression model; Maximum likelihood; Spillover effect;
    All these keywords.

    JEL classification:

    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
    • H44 - Public Economics - - Publicly Provided Goods - - - Publicly Provided Goods: Mixed Markets
    • H73 - Public Economics - - State and Local Government; Intergovernmental Relations - - - Interjurisdictional Differentials and Their Effects

    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:apjors:v:8:y:2024:i:4:d:10.1007_s41685-024-00352-8. 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.