Cost Efficiency of Dairy Farming in New Zealand: A Stochastic Frontier Analysis

Jiang, Nan; Sharp, Basil

doi:10.1017/s1068280500005517

Cited by 17 publications

(22 citation statements)

References 21 publications

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“…Although increasing returns are preferred in regional analysis in the NZ dairy industry between 1980s till mid-2000s, it may not be the case in the NZ dairy industry in recent years. For example, by using a Cobb-Douglas production function, Jiang and Sharp (2014) found evidence of diminishing returns to scale regarding inputs expressed per cow in an empirical study of the NZ dairy industry from 1999 to 2005. Thus, we model the relationship between regional dairy yields and intensive inputs as well as other regional factors using a typical Cobb-Douglas production function.…”

Section: Model Specificationsmentioning

confidence: 99%

Spatial analysis of dairy yields response to intensive farming in New Zealand

Yang

Sharp

2018

CAER

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Purpose The New Zealand (NZ) dairy industry faces the challenge of increasing productivity and dealing with public concerns over nutrient pollution. The effective policy needs to address regional differences in productivity and fertilizer use. The purpose of this paper is to investigate how spatial effects influence the relationship between dairy yields and intensive farming practices across regions in NZ. Design/methodology/approach This paper employs spatial panel data models to establish whether unobserved spatial effects exist in the relationship between dairy yields and nutrient inputs regionally and nationally using 2002, 2007 and 2012 data from Statistics NZ and DairyNZ. Findings The results show positive spatial spillovers for most intensive inputs. The high level of effluent use and estimated negative yield response to nitrogen suggests that an opportunity exists for greater use of effluent as a substitute for nitrogenous fertilizer. Substitution has the potential to reduce dependence on fertilizer and contribute to a reduction in the nutrient pollution. Originality/value This paper is the first empirical application of spatial econometric methods to examine the spatial relevance of dairy yields and intensive farming in NZ. In particular, the spatial panel data model accounts for cross-sectional dependence and controls for heterogeneity. The results contribute to an understanding of how farmers can improve their management of intensive inputs and contribute to the formation of regional environmental policy that recognizes regional heterogeneity.

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Section: Model Specificationsmentioning

confidence: 99%

Spatial analysis of dairy yields response to intensive farming in New Zealand

Yang

Sharp

2018

CAER

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“…Variables included in the inefficiency model (i.e., z it as defined in equation 9) are selected based on a combination of evidence from the empirical literature (i.e., previous dairy efficiency studies) as well as data availability. Typical variables hypothesized to influence efficiency include farming intensity, livestock quality, age and education of farmer, and access to technology (e.g., Jiang and Sharp, 2014;Mosheim and Lovell, 2009;Weersink et al, 1990). For this study, the variables included in the model are herd size, milk yield, butterfat, years farming, proportion of paid labor, proportion of purchased feed, debt-to-asset ratio, a regional dummy for a farm located in North or South Alberta, linear and quadratic time trends, and proportion of forage in the diet.…”

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confidence: 99%

Greenhouse Gas Emissions and Technical Efficiency in Alberta Dairy Production: What Are the Trade-Offs?

Jeffrey

2019

J. Agric. Appl. Econ.

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The impact of greenhouse gas (GHG) reduction on the efficiency of Alberta's dairy industry is assessed through a technical efficiency analysis over the period 1996-2016, with and without emissions included as a "bad" output. Environmentally adjusted technical efficiency and technical efficiency estimates are highly correlated; thus, reducing GHG emissions may not result in decreased efficiency. Increased milk per cow, a southern Alberta location, and increased use of forage are associated with greater environmentally adjusted technical efficiency. The opportunity cost of foregone milk revenue associated with reduced emissions is Can$308.29 per metric ton of GHG. The results imply possible policy strategies to reduce emissions.

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“…Using the NZMFD, this paper contributes to the limited empirical literature employing crosssectional farm-level data in New Zealand (e.g. Anastasiadis & Kerr 2013;Jiang & Sharp 2014, 2015Soliman & Djanibekov 2018). In particular, it explores the efficacy of two mitigation options to reduce biological GHG emissions on farms: reducing the SR (number of cows per effective hectare of dairy land); and increase AP (measured by production of MS per cow).…”

Section: Resultsmentioning

confidence: 99%

“…Anastasiadis and Kerr (2013) explored the relationship between GHG emissions and production using a simpler version of the same dataset. Other empirical literature employing cross-sectional farm-level data in New Zealand is scarce but includes Jiang andSharp (2014, 2015) and Soliman and Djanibekov (2018), who also use the NZMFD dataset. This paper expands on this research, using richer data and having a stronger focus on economic outcomes of direct concern to policy.…”

Section: Introductionmentioning

confidence: 99%

Cows, Cash and Climate: Low Stocking Rates, High-Performing Cows, Emissions and Profitability across New Zealand Farms

2019

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Using the New Zealand Monitor Farm Data (NZMFD), this paper explores the cost-effectiveness of two mitigation options to reduce biological greenhouse gas (GHG) emissions on farms: reducing stocking rate (SR; the number of cows per effective hectare of dairy land); and increasing animal performance (AP; measured by production of milk solids (MS) per cow). These mitigation options have been defined as "no cost" because, if applied together, they could reduce the carbon footprint of farms while also maintaining or even improving profits (de Klein & Dynes, 2017). We evaluate the effect of these mitigation options on three main variables: milk profitability of the farm (cash operating surplus (COS)/ton of MS produced); emissions intensity (ton CO2eq/ton of MS produced); and the value of emissions (COS/ton CO2eq). The paper has two main findings: high-AP farms show significantly lower emissions intensities and higher milk profitability; and higher SRs on farms are significantly associated with lower emissions intensities while not being significantly associated with milk profitability or negatively associated with profit per hectare. These results imply that higher levels of AP reduce the GHG intensity of the farm and increase profit-a "no-cost" option-but unless either the SR or the area under dairy farming fall, an increase in AP will lead to an increase in absolute emissions. However, our results cast doubt on the idea that reducing SR is a no-cost way to achieve absolute emission reductions. The two options do seem to constitute a no-cost outcome when combined, but potentially the same mitigation could be achieved with lower loss of profit by reducing the area of dairy land while maintaining high SRs and increasing the performance of the animals.

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Cost Efficiency of Dairy Farming in New Zealand: A Stochastic Frontier Analysis

Cited by 17 publications

References 21 publications

Spatial analysis of dairy yields response to intensive farming in New Zealand

Spatial analysis of dairy yields response to intensive farming in New Zealand

Greenhouse Gas Emissions and Technical Efficiency in Alberta Dairy Production: What Are the Trade-Offs?

Cows, Cash and Climate: Low Stocking Rates, High-Performing Cows, Emissions and Profitability across New Zealand Farms

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