IDEAS home Printed from https://ideas.repec.org/p/ags/aaea16/235576.html
   My bibliography  Save this paper

Local and regional spatial interactions of Norwegian farm growth

Author

Listed:
  • Storm, Hugo
  • Heckelei, Thomas

Abstract

A major challenge in the analysis of micro level spatial interaction is to distinguish actual interactions from the effects of spatially correlated omitted variables. We approach this problem by considering a spatially lagged explanatory model (SLX) employing two spatial weighting matrices differentiating between local and regional neighbourhoods. We empirically analyse spatial interaction between individual farms in Norway and additionally perform Monte Carlo simulations exploring the model’s performance under different data settings. Results show that including two spatial weighting matrices can indeed reduce the bias resulting from omitted variables. In the empirical application, it allows identifying different significant interaction effects.

Suggested Citation

  • Storm, Hugo & Heckelei, Thomas, 2016. "Local and regional spatial interactions of Norwegian farm growth," 2016 Annual Meeting, July 31-August 2, Boston, Massachusetts 235576, Agricultural and Applied Economics Association.
    • Handle: RePEc:ags:aaea16:235576
    DOI: 10.22004/ag.econ.235576
    as

    Download full text from publisher

    File URL: https://ageconsearch.umn.edu/record/235576/files/AAEA_StormHeckelei.pdf
    Download Restriction: no

    References listed on IDEAS

    as
    1. Stephen Gibbons & Henry G. Overman, 2012. "Mostly Pointless Spatial Econometrics?," Journal of Regional Science, Wiley Blackwell, vol. 52(2), pages 172-191, May.
    2. Andrea Zimmermann & Thomas Heckelei, 2012. "Structural Change of European Dairy Farms – A Cross-Regional Analysis," Journal of Agricultural Economics, Wiley Blackwell, vol. 63(3), pages 576-603, September.
    3. Hugo Storm & Klaus Mittenzwei & Thomas Heckelei, 2015. "Direct Payments, Spatial Competition, and Farm Survival in Norway," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 97(4), pages 1192-1205.
    4. Berger, Thomas, 2001. "Agent-based spatial models applied to agriculture: a simulation tool for technology diffusion, resource use changes and policy analysis," Agricultural Economics, Blackwell, vol. 25(2-3), pages 245-260, September.
    5. Gunnar Breustedt & Hendrik Habermann, 2011. "The Incidence of EU Per‐Hectare Payments on Farmland Rental Rates: A Spatial Econometric Analysis of German Farm‐Level Data," Journal of Agricultural Economics, Wiley Blackwell, vol. 62(1), pages 225-243, February.
    6. Mikaël Akimowicz & Marie-Benoît Magrini & Aude Ridier & Jacques-Eric Bergez & Denis Requier-Desjardins, 2013. "What Influences Farm Size Growth? An Illustration in Southwestern France," Applied Economic Perspectives and Policy, Agricultural and Applied Economics Association, vol. 35(2), pages 242-269.
    7. David J. Lewis & Bradford L. Barham & Brian Robinson, 2011. "Are There Spatial Spillovers in the Adoption of Clean Technology? The Case of Organic Dairy Farming," Land Economics, University of Wisconsin Press, vol. 87(2), pages 250-267.
    8. LeSage, James P. & Pace, Robert Kelley, 2011. "Pitfalls in Higher Order Model Extensions of Basic Spatial Regression Methodology," The Review of Regional Studies, Southern Regional Science Association, vol. 41(1), pages 13-26, Summer.
    9. Christoph R. Weiss, 1999. "Farm Growth and Survival: Econometric Evidence for Individual Farms in Upper Austria," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 81(1), pages 103-116.
    10. Guastella, Gianni & Moro, Daniele & Sckokai, Paolo & Veneziani, Mario, 2014. "The Capitalisation of Fixed per hectare Payment into Land Rental Prices: a Spatial Econometric Analysis of Regions in EU," 2014 Third Congress, June 25-27, 2014, Alghero, Italy 173093, Italian Association of Agricultural and Applied Economics (AIEAA).
    11. Feichtinger, Paul & Salhofer, Klaus, 2014. "The common agricultural policy of the EU and agricultural land prices - a spatial econometric approach for Bavaria," 2014 International Congress, August 26-29, 2014, Ljubljana, Slovenia 182751, European Association of Agricultural Economists.
    12. Arne Hallam, 1991. "Economies of Size and Scale in Agriculture: An Interpretive Review of Empirical Measurement," Review of Agricultural Economics, Agricultural and Applied Economics Association, vol. 13(1), pages 155-172.
    13. Solmaria Halleck Vega & J. Paul Elhorst, 2015. "The Slx Model," Journal of Regional Science, Wiley Blackwell, vol. 55(3), pages 339-363, June.
    14. Mosnier, Claire & Wieck, Christine, 2010. "Determinants of spatial dynamics of dairy production: a review," Discussion Papers 162896, University of Bonn, Institute for Food and Resource Economics.
    15. Eva Schmidtner & Christian Lippert & Barbara Engler & Anna Maria Häring & Jaochim Aurbacher & Stephan Dabbert, 2012. "Spatial distribution of organic farming in Germany: does neighbourhood matter?," European Review of Agricultural Economics, Foundation for the European Review of Agricultural Economics, vol. 39(4), pages 661-683, September.
    16. Case, Anne, 1992. "Neighborhood influence and technological change," Regional Science and Urban Economics, Elsevier, vol. 22(3), pages 491-508, September.
    17. Doris Läpple & Hugh Kelley, 2015. "Spatial dependence in the adoption of organic drystock farming in Ireland," European Review of Agricultural Economics, Foundation for the European Review of Agricultural Economics, vol. 42(2), pages 315-337.
    18. Schmidtner, Eva & Lippert, Christian & Dabbert, Stephan, 2015. "Does Spatial Dependence Depend on Spatial Resolution? – An Empirical Analysis of Organic Farming in Southern Germany," German Journal of Agricultural Economics, Humboldt-Universitaet zu Berlin, Department for Agricultural Economics, vol. 64(03), September.
    19. Holloway, Garth & Shankar, Bhavani & Rahman, Sanzidur, 2002. "Bayesian spatial probit estimation: a primer and an application to HYV rice adoption," Agricultural Economics, Blackwell, vol. 27(3), pages 383-402, November.
    Full references (including those not matched with items on IDEAS)

    More about this item

    Keywords

    Agricultural and Food Policy; Land Economics/Use; Research Methods/ Statistical Methods;

    NEP fields

    This paper has been announced in the following NEP Reports:

    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:ags:aaea16:235576. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (AgEcon Search). General contact details of provider: http://edirc.repec.org/data/aaeaaea.html .

    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 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.

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.