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An econometric estimation of gross margin volatility: a case of ox production in Namibia

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  • Bach, H. J. Sartorius von
  • Kalundu, K. M.

Abstract

Cattle production in Namibia has been widely analysed. However, farm business performance is still partially understood. This paper provides a scenario of volatility in gross margin in the cattle farming enterprise, as a result of weather cycles. The impact of drought on biomass cattle production augmented by other factors are compound to the hypothesis for profit maximisation. The paper follows a stepwise approach to test the causality of variables affecting production decision-making during periods of volatility, such as drought or floods Testing the OLS results for robustness, if was found that the inclusion of dynamic estimations such as ARDL and ARCH/GARCH approaches were required. Findings show that effective rainfall is the main determinant for livestock farming in the Namibian arid areas, much more than stocking rates or other variables suggested in earlier literature. Advanced analysis shows that the inclusion of known rainfall cycles in production decision making can improve the farm gross margin by 15.9%, which reduces volatility. The findings call for extension services to avail early warning systems that will enable livestock farmers to cushion the impact of gross margin volatility. Cushioning the cattle industry against gross margin volatility will provide positive impact on the national economy.

Suggested Citation

  • Bach, H. J. Sartorius von & Kalundu, K. M., 2020. "An econometric estimation of gross margin volatility: a case of ox production in Namibia," Agrekon, Agricultural Economics Association of South Africa (AEASA), vol. 59(4), October.
    • Handle: RePEc:ags:agreko:347989
    DOI: 10.22004/ag.econ.347989
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    References listed on IDEAS

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    1. Bollerslev, Tim, 1986. "Generalized autoregressive conditional heteroskedasticity," Journal of Econometrics, Elsevier, vol. 31(3), pages 307-327, April.
    2. Eduardo Fernández-Huerga, 2008. "The Economic Behavior of Human Beings: The Institutional/Post-Keynesian Model," Journal of Economic Issues, Taylor & Francis Journals, vol. 42(3), pages 709-726, September.
    3. Engle, Robert F, 1982. "Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation," Econometrica, Econometric Society, vol. 50(4), pages 987-1007, July.
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