Source: UNIV OF CONNECTICUT submitted to
MANAGEMENT SYSTEMS TO IMPROVE THE ECONOMIC AND ENVIRONMENTAL SUSTAINABILITY OF DAIRY ENTERPRISES (REV. NC-1119)
Sponsoring Institution
National Institute of Food and Agriculture
Project Status
TERMINATED
Funding Source
Reporting Frequency
Annual
Accession No.
0219192
Grant No.
(N/A)
Project No.
CONS00854
Proposal No.
(N/A)
Multistate No.
NC-1042
Program Code
(N/A)
Project Start Date
May 27, 2009
Project End Date
Sep 30, 2013
Grant Year
(N/A)
Project Director
Bravo-Ureta, BO.
Recipient Organization
UNIV OF CONNECTICUT
(N/A)
STORRS,CT 06269
Performing Department
Agri & Resource Economics
Non Technical Summary
The dairy industry in New England is characterized by small and medium size operations. According to recent work by the Economic Research Service from the USDA, economies of size is a major feature of prevailing dairy farming technologies across the United States which puts small farms at a cost disadvantage. An implication of this technological feature is a positive association between farm size and profitability. Unfortunately, the data collected and used by the USDA to undertake this cost and profitability work only includes the state of Vermont within the New England region. Another important topic affecting the sustainability of dairy farms in urbanizing areas is the implementation of nutrient management practices (NMPs) designed to mitigate adverse environmental effects associated with dairy farm manure. Econometric models will be used to quantify the various components that affect output and productivity growth, and the competitiveness of dairy farms in Connecticut and New England. This type of analysis can have important implications concerning strategies and policy actions that might be needed to promote competitiveness and increased profitability. Econometric models will also be estimated, utilizing detailed data available for a few Connecticut dairy farms, at the individual field level and over a period of four to five years, to analyze the variables that affect a farmer's choice when implementing nutrient management plans. The results of these analyses will be helpful in formulating policy options designed to promote the adoption of NMPs which are consistent with farmer behavior and environmental quality.
Animal Health Component
(N/A)
Research Effort Categories
Basic
(N/A)
Applied
(N/A)
Developmental
(N/A)
Classification

Knowledge Area (KA)Subject of Investigation (SOI)Field of Science (FOS)Percent
60134503010100%
Knowledge Area
601 - Economics of Agricultural Production and Farm Management;

Subject Of Investigation
3450 - Milk;

Field Of Science
3010 - Economics;
Goals / Objectives
Main objective: To evaluate and develop sustainable management systems for dairy herds that address critical quality and variance control factors with implications to economic efficiencies and environmental impacts. a) To analyze management and nutrition strategies for replacement heifers as they pertain to production and profitability (heifers) b) To optimize lactating and dry cow decision-making as it relates to animal health, nutrient utilization, milk production, reproduction, and profitability (cows) c) To evaluate system components and integration of information into decision-support tools and whole farm analyses to improve efficiency, control variation, and enhance profitability, and environmental sustainability (whole farm)
Project Methods
1. Econometric procedures will be employed to estimate production and cost frontiers. The primary motivation to estimate production and cost frontiers is to decompose productivity growth into its major components: Technological Change (TC); Technical Efficiency (TEC); and Scale Efficiency Change (SEC). These various components are driven by different factors; thus, their magnitudes and evolution over time and across farm size imply different policy actions that might be required to address productivity improvements. 2. Econometric models will be estimated using Probit and Generalized Least Squares procedures. The results of these analyses will be helpful in formulating policy options designed to promote the adoption of NMPs which are consistent with farmer behavior and environmental quality.

Progress 05/27/09 to 09/30/13

Outputs
Target Audience: Dairy farmers, dairy extensionists, dairy researchers Changes/Problems: Nothing Reported What opportunities for training and professional development has the project provided? Researcher trained and mentored 3 graduate students during the duration of the project. How have the results been disseminated to communities of interest? The researchersattended several conferences and presented findings regarding technical and envrionmental efficiency associated with dairy production, and the implementation of NMP's by dairy farmers. Additional extension meetings have been held to disseminated the information regarding NMP's. What do you plan to do during the next reporting period to accomplish the goals? Nothing Reported

Impacts
What was accomplished under these goals? Studies werecompleted on nutrient management based on data from four CT dairy farms over 5 years for individual fields. One such study evaluatedthe implementation of nutrient management plans (NMPs) by comparing farmers’ reported practices with recommended manure and fertilizer management, and the feasibility of using soil and corn tissue tests to document improvements in such management (Tao et al., 2010). A second study estimated changes in costs of manure handling, costs of the fertilizer replacement value of manure, and expected changes in net revenues associated with the implementation of NMPs. New-England dairy farm data for 1980-2011, collected and summarized by the Farm Credit Bureau, wasassembled. Njuki et al. (2011b, 2012a, 2012b)estimated a directional distance function model to measure the amount of pollution originating from these dairy farms. The pollution emanating from methane (CH4), nitrous oxide (N2O), carbon dioxide (CO2) and particulate matter was then converted to a carbon dioxide equivalent (CO2e) and aggregated in order to obtain the corresponding undesirable output. Then, in a desirable output-undesirable output framework, we evaluated technical and environmental efficiency of these dairy farms using estimates of shadow prices, technical efficiency, and the Morishima elasticity of substitution.

Publications


    Progress 01/01/12 to 12/31/12

    Outputs
    OUTPUTS: The work undertaken by UConn under NC1042 contributes to objective 3 focusing on the analysis and application of farm records, and on farm strategies for environmental enhancement and profitability. The followings are UConn's achievements in 2011-12: New-England dairy farm data for 1980-2011, collected and summarized by the Farm Credit Bureau, has been assembled. Njuki et al. (2011b, 2012a, 2012b) have estimated a directional distance function model to measure the amount of pollution originating from these dairy farms. The pollution emanating from methane (CH4), nitrous oxide (N2O), carbon dioxide (CO2) and particulate matter was then converted to a carbon dioxide equivalent (CO2e) and aggregated in order to obtain the corresponding undesirable output. Then, in a desirable output-undesirable output framework, we evaluated technical and environmental efficiency of these dairy farms using estimates of shadow prices, technical efficiency, and the Morishima elasticity of substitution. The rationale for this work is to determine the environmental performance of these farms, and hence their environmental sustainability. We have established that large dairy farms face lower shadow prices and even lower marginal costs of abatement than smaller farms. The implication is that in the presence of regulatory policies to reduce pollution, smaller farms would face higher compliance costs. The results of this study are being prepared to be submitted to a peer-reviewed journal for publication. PARTICIPANTS: B. Bravo-Ureta, PI. Graduate student Deep Mukherjee. TARGET AUDIENCES: Research scientist, dairy farms, policy makers PROJECT MODIFICATIONS: Nothing significant to report during this reporting period.

    Impacts
    B. Bravo-Ureta and collaborators are conducting additional dairy research with funding from two different USDA NIFA projects. Another graduate student involved in this research, Deep Mukherjee, recently completed his dissertation. The results from Dr. Mukherjee's first essay indicate that heat stress has a significant non-linear negative effect on milk production, and that the omission of heat stress in the production frontier leads to a misspecification error. In addition, an increase in the temperature and humidity index (THI) in the hot summer and fall months has a significant negative effect on milk production. Results from the second essay suggest that a warmer environment can hamper future productivity growth in dairy farming; thus, research that facilitates farmer adaptation to reduce the impact of heat stress is warranted.

    Publications

    • Njuki, E., B. E. Bravo-Ureta, and D. Mukherjee. 2011. Measuring Environmental Efficiency: A Comparison of Input and Output Based Approaches Using Bayesian Distance Frontiers. Selected Paper, Southern Economic Association- Association of Environmental and Resource Economists Conference, Washington D. C, November 19 -21, 2011.
    • Njuki, E., B. E. Bravo-Ureta, and D. Mukherjee. 2012. Measuring Technical and Environmental Efficiency Using Shadow Values: A Bayesian Approach. Selected Paper, Asia-Pacific Productivity Conference (APPC), Bangkok, Thailand, July 25, 2012.
    • Mukherjee, Deep. 2012. Economic Dynamics and Sustainability of Agriculture in the Face of Climate Change. Ph. D. dissertation, University of Connecticut, 2012.
    • Mukherjee, D., B. E. Bravo-Ureta and A. De Vries. 2012. Dairy Productivity and Climatic Conditions: Econometric Evidence from Southeastern United State. Australian Journal of Agricultural and Resource Economics 57(2012): 123-140
    • Tao, H., T. F. Morris, B. Bravo-Ureta, R. Meinert and J. Neafsey. 2012. Nutrient Applications Reported by Farmers Compared with Performance-Based Nutrient Management Plans. Agronomy Journal 104 (2012): 437-447.
    • Njuki, E., B. E. Bravo-Ureta, and D. Mukherjee. 2012. The Good and the Bad: Measuring Environmental Efficiency in Dairy Farming. October 2012, (in press)


    Progress 01/01/11 to 12/31/11

    Outputs
    OUTPUTS: (1) Average technical efficiency (TE) for Florida and Georgia (FL-GA) dairy farms has been estimated, with and without controlling for climatic conditions. (2) Farm level data to carry out a similar study on the economics of milk production and heat stress in Kentucky (KY) has been prepared for analysis. (3) To disseminate the research findings from FL-GA, a presentation has been delivered at one international conference, and an article is currently under review with an academic journal. (4) The team has just started to analyze the data set from KY. Another conference paper abstract has been submitted, focusing on KY data set, and decision is pending. PARTICIPANTS: Boris Bravo-Ureta, Professor, Dept. of Ag. & Resource Econ, University of Connecticut Allbert DeVries, Associate Professor, Dept. of Animal Science, University of Florida Lane Ely, Emeritus Professor, Dept. of Dairy Science, University of Georgia Victor Cabrera, Assistant Professor, Department of Dairy Science, University of Wisconsin Deep Mukherjee, Ph.D. candidate, Dept. of Ag. & Resource Econ, University of Connecticut Eric Njuki, Ph.D. candidate, Dept. of Ag. & Resource Econ, University of Connecticut Jeremy Jelliffe, M.S. candidate, Dept. of Ag. & Resource Econ, University of Connecticut TARGET AUDIENCES: Agricultural Economists, Policy makers PROJECT MODIFICATIONS: Nothing significant to report during this reporting period.

    Impacts
    Florida and Georgia dairy farm data for 1995-2008 has been assembled and used to explore: (1) the relationship between farm level TE and climatic conditions; (2) the rate of technological progress; and (3) effectiveness of combined use of fans and sprinkler system to reduce the heat stress impact on milk production. Conventional dairy productivity and efficiency studies do not consider the environmental condition in which a dairy farmer operates. Sometimes, inefficiency in resource utilization can be attributed to climatic conditions which are beyond human control. Controlling for heat stress in a dairy production frontier absorbs a significant portion in the deficit in milk production which could have otherwise been attributed to inefficiency which would be misleading. The TE scores are higher compared to the ones obtained following conventional model specification. Average TE score is around 90% while the rate of technological progress is around 1% over the study period (1995-2008). Another salient outcome of our model, which has policy implications, is the relative effectiveness of a combined fan-sprinkling cooling mechanism in order to reduce the impact of heat stress. For the benchmark scenario, the average farm has an annual milk production per cow equal to 18,689 lbs. In contrast, a farmer can gain of 963 lbs (5%) per cow per year, if he employs the fan-sprinkling system. Given a milk price of $16.29/cwt (average price received by farmers in the US in 2010), the annual increase in gross revenues for an average farm using the cooling system is approximately $106,830. In light of this result, it is somewhat surprising that about half of the farms in the sample analyzed have not adopted this cooling strategy. So, this calls for extension activities to provide information on the economic feasibility of this adaptation strategy to farmers.

    Publications

    • Mukherjee, D., B. E. Bravo-Ureta, and A. DeVries. Assessing the linkage between dairy productivity and climatic conditions: Evidence from South-eastern United States. Australian Journal of Agricultural & Resource Economics, First round review completed, revision in progress. 2011
    • Mukherjee, D., Dey, D., B.E. Bravo-Ureta, and A. DeVries. Modeling the Impact of Climate Risk on Dairy Production: A Case Study of Florida and Georgia. Presented at the EWEPA Conference, Verona, Italy, June 2011.


    Progress 01/01/10 to 12/31/10

    Outputs
    OUTPUTS: Collaboration is underway with dairy scientists from the University of Florida, the University of Georgia, and the University of Wisconsin to analyze the farm level data that have been collected over the past several years by these universities. Research results were presented at an international economics conference and also shared with scientists at the NC 1042 annual meeting in Idaho. PARTICIPANTS: Boris Bravo-Ureta, Professor, Dept. of Ag. & Resource Econ., University of Connecticut Albert De Vries, Associate Professor, Dept. of Animal Science, University of Florida Lane Ely, Emeritus Professor, Dept. of Dairy Science, University of Georgia Victor Cabrera, Assistant Professor, Department of Dairy Science, University of Wisconsin Deep Mukherjee, Ph.D. candidate, Dept. of Ag. & Resource Econ., University of Connecticut TARGET AUDIENCES: Nothing significant to report during this reporting period. PROJECT MODIFICATIONS: Nothing significant to report during this reporting period.

    Impacts
    The climatic elements of humidity and temperature jointly influence milk production as dairy cows suffer from heat stress. It is very likely that global warming will result in more heat stress events in near future, calling for more research to evaluate the potential economic impact on dairy farming. The likely direct effect of global warming on dairy production is evaluated for the farmers in Florida and Georgia. Climatic conditions are incorporated in two ways: 1) using a dummy variable to control for drought years; and 2) incorporating a heat stress index (popularly known as THI) computed from historical weather data. In this research we econometrically examine the impact of climatic conditions on milk production and dairy farm efficiency. Stochastic frontier analysis is used to measure technical efficiency and technological progress for an unbalanced panel of Florida dairy producers that includes 77 farmers from 1995 to 2008. The negative impact of heat stress conditions and drought on annual milk output from dairy cows is found to be statistically significant in estimation of the stochastic frontier. A salient result of the Florida analysis is that inclusion of weather data absorbs a considerable share of what otherwise would be attributed to inefficiency. Mean technical efficiency from the final model is as high as 90%. The rate of technological change estimated from different models is moderate and the farms in the sample exhibit increasing returns to scale. Sensitivity analysis has been carried out to find that the marginal effect of heat stress on milk production can be as high as 189 lb/cow/year. Work is underway to expand the analysis of climatic conditions on dairy farm productivity in two dimensions. One dimension is geographical were the Florida model will be reestimated adding data from Georgia. In addition, Wisconsin data will be analyzed. Technological gap, if any, will be tested, too. A second dimension is methodological where we will investigate alternatives ways of modeling climatic variation.

    Publications

    • Moreira, V. H. and B. E. Bravo-Ureta. Technical Efficiency and Technological Gap Ratios for Dairy Farms in Three Southern Cone Countries: A Stochastic Meta-Frontier Model. Journal of Productivity Analysis 33(2010): 33-45.
    • Mukherjee, D., B. E. Bravo-Ureta, and A. DeVries. Assessing the Linkage between Dairy Productivity Growth and Weather Patterns: A Case Study of Florida. Paper Presented at the Asia Pacific Productivity Conference, Taipei, Taiwan, July 2010.


    Progress 01/01/09 to 12/31/09

    Outputs
    OUTPUTS: Although the work by the UConn team (Dr. Boris Bravo-Ureta and Deep Mukherjee, graduate student) started in Fall'09, significant progress has been made as follows: Progress has been made in the electronic organization of the dairy farm financial summary and input-output records for New England that will be used for the productivity studies. The team already collected annual reports ("Northeast Dairy Farm Summary", prepared by the First Pioneer Farm Credit) for the years 1980-93, 1996-2002, 2005, 2007 and 2008. We established necessary contacts to obtain the missing reports in order to develop a complete dataset for 1980-2009. These data are aggregated at the regional levels - northern New England, southern New England and New York. Research collaboration agreement has been made with Prof. Albert De Vries, Department of Animal Sciences, University of Florida and Prof. Lane Ely, Department of Animal & Dairy Science, University of Georgia to use farm level data collected by a dairy program run by these universities. We are currently studying the dataset and plan to use this data for productivity analysis. As locational references are available we plan to test the impact of local weather on dairy productivity. Finally, contacts have been established with Prof. Victor Cabrera, Department of Dairy Science, University of Wisconsin to explore possibilities of finding similar data for Wisconsin dairy farms. PARTICIPANTS: Deep Mukherjee, Graduate student, Agricultural & Resource Economics, University of Connecticut. Dr. Albert De Vries, Asst. Professor, Dept. of Dairy Science, University of Florida. Dr. Lane Ely, Professor, Dept. of Dairy & Animal Science, University of Georgia. TARGET AUDIENCES: Dairy Farmers, Dairy Extensionists, Dairy Researchers PROJECT MODIFICATIONS: Nothing significant to report during this reporting period.

    Impacts
    The project just started. There are no outcomes/impacts yet.

    Publications

    • Moreira, V.H., Bravo-Ureta, B.E. 2009. A Study of Dairy Farm Technical Efficiency Using Meta-Regression: An International Perspective. Chilean Journal of Agricultural Research 69-2:214-223