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This paper provides one of the first and most detailed accounts of the large modern dairy farms that are emerging in the dairy sector in India. Qualitative interviews are used to understand how these farms differ from their traditional smallholder counterparts and how well integrated they are into the value chains.

Snowball sampling was used to identify large farmers. In total, 49 in-depth interviews were conducted with large commercial modern farms in Punjab. A detailed description of the main characteristics of these modern dairy farms is provided. Data from previous studies conducted in Punjab is used to compare the new farms with traditional smallholder farms.

The modern dairy farms are much more advanced in their use of technology compared to their traditional counterparts. These large commercial modern farms are very well integrated into the value chains. They often, but not exclusively, sell milk to formal supply chains, sometimes on a contractual basis.

Most of the literature on the Indian dairy sector focuses on smallholders. However, understanding and acknowledging the emergence of modern dairy farms is very important in understanding the development of value chains not only in the dairy sector in India, but in domestic food sectors in developing countries in general. This qualitative data analysis is a necessary first step if more large-scale representative information is to be collected in the future.

The purpose of this paper is to evaluate dairy farm financial performance over time utilizing farm financial ratios from three university business analysis programs. The evaluation includes measures of profitability, solvency, and liquidity by herd size.

Financial ratios to reflect profitability (rate of return on assets), solvency (debt to asset ratio), and liquidity (current ratio) were collected from Cornell University, Michigan State University, and the University of Wisconsin for dairy farms from 2000 to 2012. The distribution of farm financial performance using these ratios was examined over time and by herd size. Variance component methods are used to examine the percent of variation due to individual firm and industry aspects. A simple credit risk score is calculated to examine relative farm risk.

Dairy farm profitability performance is similar across herd sizes in poor years but larger herds realized significantly more profitability in good years. Findings were similar with respect to liquidity. Large herds consistently carried relatively more debt. Large herds’ financial performance was more uniform than across smaller herds. Larger herds had more financial risk as measured by credit risk scoring but recovered quickly to industry averages in profitable years.

The variation of dairy farm financial performance in an era of volatile milk and feed price is assessed. The results have important implications for farm financial management and benchmarking farm financial performance. In addition to helping to evaluate the efficacy of various price and income risk management tools, these results have important implications for understanding the benefits of the new federal Margin Protection Program for Dairy that is available to all US dairy farmers.

The purpose of this paper is to analyse the determinants of technical efficiency (TE) in dairy farms located in the South of Brazil, aiming for a better understanding of the topic for academics, dairy farmers and policymakers to improve the productivity and competitiveness of dairy farms.

This study was developed using a two-stage approach. Data envelopment analysis was used to estimate the TE level and regression models to understand the factors affecting TE in dairy farms. The sample size is 253 dairy farms in the South of Brazil.

The variation in the mean TE indexes reported in the literature can be explained by the attributes of the analysed studies, including the education of the farm operator, farm size (number of cows and milk), feed and labour costs, and use of services. Additionally, the results suggest that dairy farmers in the sample could increase milk output by 50.1 per cent (level of inefficiency) on average if they improve their TE.

This study makes three important contributions: first, it formulates hypotheses from the previous literature’s propositions on the estimation of TE in dairy farms; second, it tests the hypotheses in an empirical study to understand the main factors affecting the TE in dairy farms of the selected municipalities in the South of Brazil; and third, it compares previous findings on the determinants of TE in dairy farms serving different stakeholders, such as researchers, farmers and government representatives, to improve the productivity and competitiveness of dairy farms.

In the past decade, there has been a dramatic decline in agricultural employment in Bulgaria and several reports have pointed at supply chain modernisation and poor milk quality as the main reasons for the dramatic decline in the number of farms. However, to date the policy debate is been based on ad hoc claims, while there is relatively little micro-level evidence. The purpose of this paper is to analyse the determinants of structural change in the Bulgarian dairy sector in the period 2003-2009.

This paper analyses the determinants of structural change in the Bulgarian dairy sector in the period 2003-2009, using a unique panel survey of 296 farm households in the North and South Central Region of Bulgaria. In order to control for sample attrition bias, the authors use a two-step Heckman model of farm survival and growth model.

The data confirms the rapid outflow of agricultural labour from dairy farming activities: 55 per cent of the farm households supplying milk to a dairy company in 2003 stopped supplying in 2009. The main reasons for quitting are ageing of the household, health problems and an increase in off-farm employment alternatives and not supply chain modernisation and milk quality standards. The institutional innovations which are associated with integration in modern supply chains, such as the provision of farm assistance programmes, have a positive impact on small farms’ growth.

The study is one of the first to use panel data to analyse the impact of standards on the survival and growth of small farms in value chains. The authors analyse the determinants of farm survival and growth in the Bulgarian dairy sector in the period 2003-2009, using panel surveys of 296 dairy farm households in the North and South Central Region of Bulgaria and panel data from interviews with dairy companies. The findings are relevant beyond the Bulgarian dairy sector as supply chain modernisation and changes in quality regulations are taken place in many other transition and developing countries.

The purposes of this paper are to examine the actual conditions of the problems of poverty in rural areas in Inner Mongolia, to clarify the problems involved in the measure to fight poverty through promotion of dairy farming and to propose policies for future measures to fight poverty.

Both quantitative and qualitative analyses are employed, such as the estimation of production functions of agriculture in Inner Mongolia over the period 1998‐2004, the interview analysis and questionnaire survey for case studies. The different roles that three models play in poverty reduction such as the government assistant dairy farming, the enterprise entry dairy farming, and the multiple management dairy farming are discussed.

The paper confirms the growth of the corporate‐participating dairy farming contributes significantly to the development of the regions. It also clarifies the problem of the government‐aided dairy farming with its low profitability caused by insufficient input of fodder and the necessity to select management policies according to the natural conditions and resources available in individual regions, such as a shift toward recycling‐oriented beef cattle management in multiple dairy farming.

The paper adds insight into the promotion of dairy farming and poverty reduction in Inner Mongolia.

The study measures the technology gap and performance of the Norwegian dairy farms accounting for farm heterogeneity.

The analysis was based on a meta-frontier and unbalanced farm-level panel data for 1991–2014 from 417 Norwegian farms specialized in dairy production in five regions of Norway.

The result of the analysis provides empirical evidence of regional differences in technical efficiencies, technological gap ratios (TGRs) and input use. Consequently, the paper provides some insights into policies to increase the efficiency of dairy production in the country across all regions.

The author used a meta-frontier approach for modeling regional differences based on a single-output production function specification. This approach has commonly been used in the economics literature since Battese et al. (2004). To get more informative and useful results, it would be necessary to repeat the analysis within terms of multiple input-output frameworks using, for instance, the input distance function approach. Moreover, the author estimated the meta-frontier using the non-parametric approach, thus it is also a need for further analysis if the values are different by estimating using a parametric approach.

One implication for farmers (and their advisers) is that dairy farms in all regions used available technology in the area sub-optimally. Thus, those lagging the best-performing farms need to look at the way the best-performing farmers are operating. Policymakers might reduce the gap is through training, including sharing information about relevant technologies from one area to another, provided that the technologies being shared fit the working environment of the lagging area. Moreover, some of the dairy technologies they use may not fit other regions, suggesting that agricultural policies that aim to encourage efficient dairy production, such as innovation of improved technology (like breeding, bull selection and improved feed varieties) through research and development, need to account the environmental differences between regions.

For both taxpayers and consumers, one implication is that the contributions they pay that go to subsidize dairy farmers appear to bring some benefits in terms of more efficient milk production that, in turn, increases the supply of some foods so possibly making food prices more affordable.

The paper contributes to the literature in several ways. In contrast to Battese et al. (2004), the author accounts for farm-level performance differences by applying the model devised by Greene (2005), thus may serve as a model for future studies at more local levels or of other industries. Moreover, the author is fortunate to able to use a large level farm-level panel data from 1991 to 2014.

Dairy farms, along with livestock and specialty crop farms, face a tight labor supply and increasing labor costs. To overcome the challenging labor market, farm managers can increase labor-use efficiency through both human resource and capital investments. However, little is known about the relationship between such investments and farm profitability. The purpose of this paper is to examine the relationship between dairy farm financial performance and labor-use efficiency, as measured by labor productivity (milk sold per worker equivalent); labor costs (hired labor cost per unit of milk sold and hired labor cost per worker); and investment in labor-saving equipment.

Cluster analysis is applied to partition dairy farms into three performance categories (high/middle/low), based on farms’ rate of return on equity, asset turnover ratios and net dairy income per hundredweight of milk. Next, the annual financial rank is fitted into both random- and farm-level fixed-effects ordered logit and linear models to estimate the relationship between dairy farms’ financial performance and labor-use efficiency. This study also investigates the implications of using a single financial indicator as a measure of financial performance, which is the dominant approach in literature.

The study finds that greater labor productivity and cost efficiency (as measured by hired labor cost per unit of milk sold) are associated with better farm financial performance. No statistically significant relationship is found between farm financial performance and both hired labor cost per worker and advance milking systems (a proxy of capital investment in labor-saving technology). Future studies would benefit from better measurements of labor-saving technology. This study also demonstrates inconsistency in regression results when individual financial variables are used as a measure of financial performance. The greater labor-use efficiency on high-performing farms may be a combination of hiring more-skilled workers and managerial strategies of reducing unnecessary labor activities. The results emphasize the importance of managerial strategies that improve overall labor-use efficiency, instead of simply minimizing total labor expenses or labor cost per worker.

This study examines the importance of labor productivity and labor cost efficiency for dairy farm management. It also develops a novel approach which brings a more comprehensive financial performance evaluation into regression models. Furthermore, this study explicitly demonstrates the potential for inconsistent results when using individual financial variable as a measure of financial performance, which is the dominant measurement of financial performance in farm management studies.

The purpose of this paper is to identify the structural problem in the Chinese dairy sector. There exists a large number of low‐efficiency, small‐scale farms, and productivity inequality between small and large farms keeps increasing, which is a possible driving force behind the Melamine scandal in 2008.

Using the stochastic frontier production function, this paper estimates and compares the changes in technology and technical efficiency between backyard, small‐scale, medium‐scale and large‐scale dairy farms in China over the period between 2004 and 2008.

There are compensating effects between technology and technical efficiency. However, low yield for backyard farms is mainly caused by traditional low‐yield varieties, even though the technical efficiency is very high, which cannot compensate for the low technology.

The author put the assumption of constant return to scale mainly due to the data availability. Such an assumption implies that there are no scale‐effects between the different scales in productivity, and the productivity difference is explained by technology and technical efficiency.

In order to solve the structural problems, Chinese governments should help small‐scale farmers to adopt new high‐yield varieties, to subsidize small‐scale farmers, and to train farmers to master the complicated skills for raising high‐yield varieties.

The paper gives another possible explanation for the Melamine scandal of milk powder in 2008. If the structural problem cannot be solved, similar food safety scandals could happen once again.

The purpose of this paper is to examine the rise in crossbred cow numbers in the US dairy herd. Methods used look at well managed herds to see if crossbreeding provides a management tool that producers are using to maintain profitability.

The authors estimate a Translog stochastic production frontier (SPF) for US dairy farms to examine the competitiveness of crossbred and non-crossbred dairy herds by system and region.

The bottom-line conclusion is that WM or highly efficient crossbred herds solidly compete on a financial basis with larger WM Western Holstein herds, the most technically efficient managed group, based on the SPF results in the authors’ study. The study finds that net return on assets for crossbred herds are not different from Western Holstein herds and that there is no significant difference in amount of milk per cow produced annually.

Because of a need to unmask the advantages of crossbreeding as a technology it was necessary to separate WM herds from poorly managed herds. That was done by frontier estimates that robustly ranked operation and corrected for endogeneity, tested for selectivity bias, and incorporated the NASS survey design.

For the first time, the 2010 Dairy Cost and Returns questionnaire version of the Agricultural Resource Management Survey (Dairy CAR) design allows researchers to expand survey observations to represent the vast majority of the US dairy farm population and to sort dairy farms into crossbred/non-crossbred herds.

The purpose of this paper is to investigate the potential of eco-labels to help dairy farm viability as one partial solution to a complex problem. Specifically, it aims to understand which attributes are most likely to increase consumption and garner price premiums.

This paper uses key informant interviews and a convenience sample (n=203) of supermarket shoppers in Vermont. It uses Likert-type scales to measure the likelihood of increased purchase and paying price premiums based on a series attributes including animal welfare, fair labor standards, family farms and environmental stewardship. It calculates and compares mean ratings of each attribute and use an ordinal regression to measure the effect of demographic attributes on each attribute’s rating.

Interviewed stakeholders named low milk prices and evolving industry structure as harming dairy farm viability. They list supply control and improved promotion as potential solutions. Survey respondents say attributes supporting animal welfare, farm workers, family farms and healthy soil are most likely to garner increased consumption and price premiums.

The authors use a convenience sample, so generalization to larger populations is not advisable.

Promotion around animal welfare, farm workers, family farms and healthy soil is most likely to be effective, based on the results of this study. The survey responses are very highly correlated, suggesting that a multi-attribute eco-label may garner the most support.

This work can inform efforts to promote dairy farm viability, an important sector of the agricultural economy in Vermont and elsewhere in the USA.

This research provides the ranking of attributes which may appear on eco-labels by current consumers of dairy products in a state with an important dairy heritage and industry.