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A Growing Problem: Exploring Livestock Farm Resilience to Droughts in Unit Record Data

Author

Listed:
  • Levente Timar

    (Motu Economic and Public Policy Research)

  • Eyal Apatov

    (Oranga Tamariki, Ministry for Children)

Abstract

Climate models indicate that New Zealand’s farms will be increasingly exposed to adverse climate events in the future. In this study, we empirically investigate drought impacts on farm enterprises by linking financial, agricultural and productivity data from Statistics New Zealand’s Longitudinal Business Database (LBD) with historical weather data from NIWA. Our sample consists of an unbalanced panel of over 67,000 observations of livestock farm enterprises between 2002 and 2012. We run a set of panel regressions with time and farm fixed effects to estimate the effect of changes in drought intensity on gross output, profit per hectare, current loans and intermediate expenditure of dairy and sheep-beef farms. To explore factors of resilience to droughts, we also examine how the estimates change with different farm characteristics. Most (but not all) of the estimated drought effects are significant, consistent across various specifications and of the expected sign. However, we have limited success in conclusively identifying farm characteristics that affect drought outcomes in our data.

Suggested Citation

  • Levente Timar & Eyal Apatov, 2020. "A Growing Problem: Exploring Livestock Farm Resilience to Droughts in Unit Record Data," Working Papers 20_14, Motu Economic and Public Policy Research.
    • Handle: RePEc:mtu:wpaper:20_14
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    References listed on IDEAS

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    1. Richard Fabling, 2009. "A Rough Guide to New Zealand's Longitudinal Business Database," Global COE Hi-Stat Discussion Paper Series gd09-103, Institute of Economic Research, Hitotsubashi University.
    2. Peck, Dannele E. & Adams, Richard M., 2010. "Farm-level impacts of prolonged drought: is a multiyear event more than the sum of its parts?," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 54(01), pages 1-18.
    3. Apatov, Eyal & Fabling, Richard & Jaffe, Adam & Morris, Michele & Thirkettle, Matt, 2015. "Agricultural Productivity in New Zealand: Estimating Production Functions using the Longitudinal Business Database," 2015 Conference (59th), February 10-13, 2015, Rotorua, New Zealand 202516, Australian Agricultural and Resource Economics Society.
    4. Richard Fabling, 2011. "Keeping it Together: Tracking Firms on New Zealand’s Longitudinal Business Database," Working Papers 11_01, Motu Economic and Public Policy Research.
    5. Arthur Grimes & Andrew Aitken, 2008. "Water, Water Somewhere: The Value of Water in a Drought-Prone Farming Region," Working Papers 08_10, Motu Economic and Public Policy Research.
    6. Lawes, R.A. & Kingwell, R.S., 2012. "A longitudinal examination of business performance indicators for drought-affected farms," Agricultural Systems, Elsevier, vol. 106(1), pages 94-101.
    7. Dannele E. Peck & Richard M. Adams, 2010. "Farm-level impacts of prolonged drought: is a multiyear event more than the sum of its parts?," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 54(1), pages 43-60, January.
    8. Richard Fabling & Lynda Sanderson, 2016. "A Rough Guide to New Zealand's Longitudinal Business Database (2nd edition)," Working Papers 16_03, Motu Economic and Public Policy Research.
    9. Güneş Kamber & Chris McDonald & Gael Price, 2013. "Drying out: Investigating the economic effects of drought in New Zealand," Reserve Bank of New Zealand Analytical Notes series AN2013/02, Reserve Bank of New Zealand.
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    More about this item

    Keywords

    Drought; farm enterprise; resilience; panel data; fixed effects;
    All these keywords.

    JEL classification:

    • Q12 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Agriculture - - - Micro Analysis of Farm Firms, Farm Households, and Farm Input Markets
    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models

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