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Empirically Evaluating Grower Characteristics and Satisfaction with Organic Production

Author

Listed:
  • Govindasamy, Ramu
  • Italia, John
  • DeCongelio, Marc
  • Anderson, Karen
  • Barbour, Bruce

Abstract

Organic production has been practiced in the United States since the late 1940s. Since then, the organic industry has developed from small gardens to large farming operations. The government has proposed standards to establish what products may be classified as ‘organic.’ Organic products are those produced with no synthetic pesticides. Due to the laborious workload of producing products without synthetic pesticides, organic products are often sold at a premium. New Jersey, New York, and Pennsylvania have relatively more organic production than other states due to the higher value of land in the area and proximity to New York City and Philadelphia. This is because organic production commonly reaps higher profits per acre than conventional production does. The purpose of this study is to produce a profile of the typical organic farmer in these states, and to determine how satisfied they are with the current marketing channels that are open to them to market their organic produce. Specifically, the objectives are to determine producer characteristics such as: • The average acreage in organic production. • The variety of organic produce sold. • The different modes of advertising used in the sale of organic produce. • The marketing channels used, such as wholesale, retail and direct marketing. Additionally, three econometric models are formulated to estimate the following: • The characteristics of organic farmers that plan to extend their organic production over the next five years. • The characteristics of organic farmers that have had increases in gross sales per year over the last five years. • The characteristics of organic farmers that are satisfied with their returns from organic production. The logit framework is used for the regressions in this analysis because its asymptotic characteristic constrains the predicted probabilities to a range of zero to one. The v estimation method is the maximum likelihood estimation (MLE). Hence, given certain organic producer characteristics, the probability that the producer plans to expand their production is found. Similar explanations exist for the other two models. The three models are estimated using information obtained from the producers’ questionnaire located at the end of this report. These models identify the factors that significantly contribute to producers’ satisfaction with profits and the growth of the organic portion of their business. As expected, the average organic farm size of the sample was extremely small when compared to the mean farm size of each of the participating states. Furthermore, less than 18 percent of the respondents indicate that they are not satisfied with the profit margin they are able to generate from their organic production. Tomatoes were organically grown by more growers than any other crop was organically grown. However, producers reported the highest satisfaction with their returns from the three commodities grown by the fewest number of growers (apples, cattle and milk). Those organic producers who plan to extend their production in the next five years are likely to currently rent some of their land, to produce cattle but not milk, to grow herbs, to use Integrated Pest Management (IPM), to provide forms of agritourism such as hay rides and pick-your-own farms, to be younger farming operations, and to have had an increase in sales over the last five years. About two-thirds of the sample plans to increase production. Those organic producers that have had increases in gross sales per year over the last five years are likely to have at least 70% of their land in organic production, to grow vegetables but not herbs, to use labels to identify their products as certified organic, and to be younger farming operations. Again, about two-thirds of the sample has had increases in gross sales over the last five years. vi Those organic producers that are satisfied with their returns from organic production are more likely to be older farming operations, to have had an increase in sales over the last five years, to use labels to identify their products as certified organic, and to produce cattle. About two-fifths of the sample reported that they are satisfied with their returns from organic production. This report is phase one of a two phase report. Phase II will focus on the consumer characteristics of those who buy organic produce. The models in this report correctly predict the state of the dependent variable at least in 65% of the responses, while two of the models predict correctly 71% of the responses. This phase of the main report accomplishes finding the characteristics of organic producers that plan to expand their operations, that have had an increase in sales over the last five years, and that are satisfied with their organic production returns. This knowledge will be used in conjunction with Phase II to produce an over-all picture of the organic industry in the northeastern United States.

Suggested Citation

  • Govindasamy, Ramu & Italia, John & DeCongelio, Marc & Anderson, Karen & Barbour, Bruce, 2000. "Empirically Evaluating Grower Characteristics and Satisfaction with Organic Production," P Series 36738, Rutgers University, Department of Agricultural, Food and Resource Economics.
  • Handle: RePEc:ags:rutdps:36738
    DOI: 10.22004/ag.econ.36738
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    Cited by:

    1. Wang, Qingbin & Sun, Junjie, 2003. "Consumer Preference And Demand For Organic Food: Evidence From A Vermont Survey," 2003 Annual meeting, July 27-30, Montreal, Canada 22080, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    2. Govindasamy, Ramu & DeCongelio, Marc & Italia, John & Barbour, Bruce & Anderson, Karen, 2001. "Empirically Evaluating Consumer Characteristics and Satisfaction with Organic Products," P Series 36736, Rutgers University, Department of Agricultural, Food and Resource Economics.

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    Keywords

    Farm Management;

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