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Defining Areas: Linking Geographic Data in New Zealand

Author

Listed:
  • Arthur Grimes

    (Motu Economic and Public Policy Research)

  • David C. Maré

    (Motu Economic and Public Policy Research)

  • Melanie Morten

    (Motu Economic and Public Policy Research)

Abstract

This paper develops a match quality statistic to quantify the trade-off between 'specificity' and 'completeness' when aggregating one regional aggregation to another. We apply this statistic to calculate the degree of mismatch between various regional aggregations for New Zealand using 1991 and 2001 Census Data. A program to calculate mismatch statistics is included as an appendix, as a Stata(r) ado file.

Suggested Citation

  • Arthur Grimes & David C. Maré & Melanie Morten, 2006. "Defining Areas: Linking Geographic Data in New Zealand," Working Papers 06_07, Motu Economic and Public Policy Research.
    • Handle: RePEc:mtu:wpaper:06_07
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    File URL: https://motu-www.motu.org.nz/wpapers/06_07.pdf
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    Cited by:

    1. Arthur Grimes & David C. Maré & Melanie Morten, 2007. "Adjustment in Local Labour and Housing Markets," Working Papers 07_10, Motu Economic and Public Policy Research.
    2. Richard Fabling & David C. Maré, 2012. "Cyclical Labour Market Adjustment in New Zealand: The Response of Firms to the Global Financial Crisis and its Implications for Workers," Working Papers 12_04, Motu Economic and Public Policy Research.
    3. Arthur Grimes & Sean Hyland, 2013. "Passing the Buck: Impacts of Commodity Price Shocks on Local Outcomes," Working Papers 13_10, Motu Economic and Public Policy Research.

    More about this item

    Keywords

    Match quality; Geographic Aggregation;

    JEL classification:

    • R1 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General Regional Economics
    • C80 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - General

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