Technology choice and efficiency on Australian dairy farms*

Deregulation of the Australian dairy industry, specifically the removal of price subsidies to ‘market milk’, as well as ongoing drought in many dairy regions, has placed considerable pressure on farm cash income and a search for ways in which dairy farms can be made to operate more efficiently. Using traditional farm survey data and a unique biannual data set on farm technology use, this paper estimates a stochastic production frontier and technical efficiency model for dairy farms in New South Wales and Victoria, determining the relative importance of each input in dairy production, the effects of key technology variables on farm efficiency, and overall farm profiles based on the efficiency rankings of dairy producers. Results show that production exhibits constant returns to scale and although feed concentration and the number of cows milked at peak season matter, the key determinants of differences in dairy farm efficiency are the type of dairy shed used and the proportion of irrigated farm area. Overall farm profiles indicate that those in the ‘high efficiency group’ largely employ either rotary or swing‐over dairy shed technology and have almost three times the proportional amount of land under irrigation.     

Feed use intensification and technical efficiency of dairy farms in New Zealand

In recent years, the traditionally pasture‐based dairy farms in New Zealand have become more intensive by using higher proportions of supplementary feed. This trend has been attributed to a range of factors, such as productivity enhancement, overcoming pasture deficits and the improvement of body condition scores. However, there is a lack of knowledge as to how feed use intensification affects the technical efficiency of dairy farms in New Zealand. This paper addresses the research gap by estimating the impact of feed use intensification on the technical efficiency of New Zealand dairy farms, using a fixed effects stochastic production frontier model and a balanced panel of 257 farms from 2010 to 2013. The empirical results show that technical efficiency on New Zealand dairy farms is positively and significantly influenced by feed use intensification, herd size and milking frequency.     

Technical efficiency,herd size,and exit intentions in U.S. dairy farms

The U.S. dairy industry has seen major restructuring in recent decades. A sharp decline in the number of U.S. dairy farms and an increase in average herd sizes have accompanied exits, which have been concentrated among smaller herds. Given that more productive farms are better positioned to increase operation size and to continue operation, we hypothesize that the more technically efficient farms are better able to expand and also have stronger incentives to continue production. Using data from the USDA's 2010 ARMS Phase III, Dairy Production Practices and Costs and Returns Report, we estimate technical efficiency using stochastic production frontier analysis with endogenous inputs. The efficiency estimate is then incorporated into the analysis of exit intention and herd size. The results confirm our hypotheses that smaller and less efficient farms are more likely to exit and that more efficient dairy farms tend to expand herd size. Moreover, farms without successors but with older and more educated operators are more likely to exit.     

The influence of management decisions and external factors on the dairy farmer's environmentally friendly farming objective: the Green Dairy experience

Ten dairy farms participated in an EU project that aimed to improve nitrogen use and assist with the adoption of more environmentally friendly farming practices. Nitrogen use and management decisions were monitored during 2003, 2004 and 2005. Nine farms improved nitrogen use (nitrogen output relative to input) in Year 2. Four farms maintained or further improved nitrogen use in Year 3. Management decisions and external factors that improved nitrogen use were increasing farm milk output, adopting best management practices for nitrogen use, growing forage crops that required less nitrogen than grass and favourable crop production conditions that rendered large quantities of good quality forage. Decisions that worsened nitrogen use were increasing cow numbers without sufficient management support, the late start of supplementary feeding when grass quality declined, setting the target yield too high, pursuing a higher milk price, less palatable silage and disease. Sufficient slurry storage is essential to improving nitrogen use. The savings from lower nitrogen input and the revenue from milk were in no proportion to the investments required for additional slurry storage, however. The farmers did adopt environmentally friendly practices, but only to the degree their businesses were able to sustain.     

Measuring financial performance on dairy farms

The motivation for this paper was to improve the information provided by the extension service for dairy farming. Databases as the Norwegian Dairy Financial Recording (NDFR) are commonly used for comparative analysis of farms. In the present paper, the problems related to these comparisons are discussed. Four different measures of financial performance are presented. The measures are; the gross margin, extended gross margin, and two different efficiency indexes based on use of data envelopment analysis (DEA). All four measures have advantages and disadvantages. The two gross margins are suitable for ranking farms when evaluating the impact of operative management variables, e.g., disease and miscellaneous welfare enhancing inputs on performance. However, efficiency indexes, which are estimated as ratios of actual and maximum output, given inputs, are more suitable when evaluating the impact of strategic management variables, e.g., concentrate or roughage per litre milk produced on performance.     

Location and uptake: integrated household and GIS analysis of technology adoption and land use, with application to smallholder dairy farms in Kenya

CIS‐derived measures of location and space have increasingly been used in models of land use and ecology. However, they have made few inroads into the literature on technology adoption in developing countries, which continues to rely mainly on survey‐derived information. Location, with all its dimensions of market access, demographics and agro‐climate, nevertheless remains key to understanding potential for technology use. The measures of location typically used in the adoption literature, such as locational dummy variables that proxy a range of locational factors, now appear relatively crude given the increased availability of more explicit GIs‐derived measures. This paper attempts to demonstrate the usefulness of integrating CIS‐measures into analysis of technology uptake, for better differentiating and understanding locational effects. A set of GIs‐derived measures of market access and agro‐climate are included in a standard household model of technology uptake, applied to smallholder dairy farms in Kenya, using a sample of 3330 geo‐referenced farm households. The three technologies examined are keeping of dairy cattle, planting of specialised fodder, and use of concentrate feed. Logit estimations are conducted that significantly differentiate effects of individual household characteristics from those related to location. The predicted values of the locational variables are then used to make spatial predictions of technology potential. Comparisons are made with estimations based only on survey data, which demonstrate that while overall explanatory power may not improve with CIS‐derived variables, the latter yield more practical interpretations, which is further demonstrated through predictions of technology uptake change with a shift in infrastructure policy. Although requiring large geo‐referenced data sets and high resolution GIS layers, the methodology demonstrates the potential to better unravel the multiple effects of location on farmer decisions on technology and land use.     

Estimating technical efficiency under unobserved heterogeneity with stochastic frontier models: application to northern German dairy farms

This article uses panel data estimation techniques to examinetechnical efficiency of individual dairy farms in northern Germany.To the extent that agricultural production is characterisedby heterogeneous production conditions, estimation techniquesthat do not account for unobserved heterogeneity produce biasedefficiency estimates. We therefore estimate a number of conventionalpanel data models and Greene's recently proposed ‘true’random-effects model, as well as an extension of the model toascertain the effects of different specification on the productionfunction and efficiency estimates. Our results appear to supporttheoretical expectations and previous findings according towhich a specification that is both time-variant and also controlscorrelations between unobserved heterogeneity and the explanatoryvariables avoids heterogeneity bias and thus ensures consistentefficiency estimates.     

Measuring technical efficiency of dairy farms with imprecise data: a fuzzy data envelopment analysis approach

This article integrates fuzzy set theory in the data envelopment analysis (DEA) framework to compute technical efficiency scores when input and output data are imprecise. The underlying assumption in conventional DEA is that input and output data are measured with precision. However, production agriculture takes place in an uncertain environment, and, in some situations, input and output data may be imprecise. We present an approach of measuring efficiency when data are known to lie within specified intervals and empirically illustrate this approach using a group of 29 dairy producers in Pennsylvania. Compared to the conventional DEA scores that are point estimates, the computed fuzzy efficiency scores are interval bound allowing the decision maker to trace the performance of a decision‐making unit at different possibility levels.     

The links between management's critical success factors and farm level economic performance on dairy farms in Sweden

Management's critical success factors (MCSFs) are used to indicate how farm profits develop, but their usefulness as profitability predictors has previously not been analyzed statistically. This paper explores the usefulness of some commonly used MCSFs in Swedish dairy farms, by investigating whether the MCSFs are significant predictors of economic efficiency. Further, the paper takes a comprehensive view of evaluating farm level efficiency, in that all major input and output efficiency scores are estimated. Previous literature has focused on only one score, or on only one perspective. Our results show that cost efficiency is the more problematic part of the profitability process. Especially the allocative part needs to be improved. Moreover, the results show that the MCSFs milk quality, herd fertility and involuntary culls ratio may not work as indicators of economic performance, whereas milk yield per cow and the mastitis ratio are significant indicators.     

Growth of milk production in German dairy farms: an empirical study based on event history analysis

This article investigates determinants of growth of milk production in German dairy farms with the use of event history analysis. This methodology enables the analysts to consider time as a proxy for not measurable effects on growth. The likelihood of a farm's moving from a nongrowth episode into a growth episode is estimated and the impact of various covariates on that likelihood is assessed. The analysis is based upon a balanced panel of annual farm accounts from 616 specialized dairy farms in Germany, covering the financial years 1995/1996–2008/2009. The results from event history analyses are presented for low and high growth rates. For both groups, it was found that the probability of entering a growth episode, defined as the event to be analyzed, increases over time, e.g., as a consequence of an increasing need to improve competitiveness. Moreover, several covariates, such as the share of subsidies in returns, farmer's age, and milk price, had a significant impact on growth in a farm's milk production. The analysis revealed, however, that the effect‐direction of some explanatory variables differed between the two groups.     

Economic analysis of the impact of adopting herd health control programs on smallholder dairy farms in Central Thailand

The economic impact of adopting herd health programs for mastitis and reproduction by small-scale dairy producers of Central Thailand was assessed using a policy analysis matrix (PAM). Following a reduction in the incidence of bovine disease on adopter farms, an increase in private net profits is observed. More importantly the social costs of supporting dairy farmers is reduced; the PAM effective protection coefficient was reduced by 35% for mastitis program adopters and by 44% for reproductive program adopters, indicating improved social efficiency of dairy policy. Other indicators of efficiency and policy implications are discussed.