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Dive into the research topics where Swagata “Ban” Banerjee is active.

Publication


Featured researches published by Swagata “Ban” Banerjee.


Journal of Agricultural and Applied Economics | 2008

A Binary Logit Estimation of Factors Affecting Adoption of GPS Guidance Systems by Cotton Producers

Swagata “Ban” Banerjee; Steven W. Martin; Roland K. Roberts; Sherry L. Larkin; James A. Larson; Kenneth W. Paxton; Burton C. English; Michele C. Marra; Jeanne M. Reeves

Binary logit analysis was used to identify the factors influencing adoption of Global Positioning System (GPS) guidance systems by cotton farmers in 11 Mid-south and Southeastern states. Results indicate that adoption was more likely by those who had already adopted other precision-farming practices and had used computers for farm management. In addition, younger and more affluent farmers were more likely to adopt. Farmers with larger farms and with relatively high yields were also more likely to adopt. Education was not a significant factor in a farmer’s decision to adopt GPS guidance systems.


Journal of Agricultural and Applied Economics | 2007

Effects of Seed and Farm Characteristics on Cottonseed Choice: A Choice-Based Conjoint Experiment in the Mississippi Delta

Swagata “Ban” Banerjee; Darren Hudson; Steven W. Martin

Producers’ preferences for cottonseed with respect to price, seed type, yield, and fiber quality are examined by a willingness-to-pay approach via mail surveys. Results indicate a positive willingness to pay (WTP) for technology relative to conventional cottonseed, and WTP increases with the level of technology. Yield and quality also show a positive WTP. Larger farms have a higher WTP for technology, and farms with more farm labor have a lower WTP for technology. These results suggest economies of size in technology adoption (biotechnology is not size-neutral) and that labor and biotechnology are direct substitutes.


Crop Management | 2005

Estimating Total Costs and Possible Returns from Precision Farming Practices

Steven W. Martin; James E. Hanks; Aubrey Harris; Gene D. Wills; Swagata “Ban” Banerjee

Precision farming technologies are becoming increasingly popular. However, few studies have addressed the whole-farm and per-acre expense of these technologies. A 33-acre farm example is used to establish baseline cost estimates of these technologies. Findings suggest that per-acre expense is relatively small (


Journal of Agricultural and Applied Economics | 2007

Forecasting Irrigation Water Demand: A Case Study on the Flint River Basin in Georgia

Swagata “Ban” Banerjee; Irfan Y. Tareen; Lewell F. Gunter; Jimmy Bramblett; Michael E. Wetzstein

8.00 to


Journal of Agricultural and Applied Economics | 2013

Econometric Forecasting of Irrigation Water Demand Conserves a Valuable Natural Resource

Swagata “Ban” Banerjee; Babatunde A. Obembe

12.00/acre) if sufficient acres are available and may be smaller than conventional wisdom would suggest. Average annual input savings in the study amounted to approximately


AgBioForum | 2009

Adoption of conservation-tillage practices and herbicide-resistant seed in cotton production.

Swagata “Ban” Banerjee; Steven W. Martin; Roland K. Roberts; James A. Larson; Robert J. Hogan; Jason L. Johnson; Kenneth W. Paxton; Jeanne M. Reeves; G. B. Frisvold; P. D. Mitchell; T. M. Hurley

2.00/acre. Possible yield increases may more than cover the cost of implementing a whole-farm precision farming system even on minimum-size farms.


Crop Protection | 2008

An estimation of producer returns from Bt cotton with varying refuge sizes

Swagata “Ban” Banerjee; Steven W. Martin

Southeast drought conditions have accentuated the demand for irrigation in the face of restricted water supply. For allocating this supply, Georgia held an auction for withdrawing irrigated acreage. This auction withdrew 33,000 acres from irrigation, resulting in a physical estimate of a 399 acre-feet daily increase in water flow. The actual reduction is driven by crop distributional changes on the basis of economic substitution and expansion effects. In contrast to the physical estimates, an econometric model that considers these effects is developed. The differences between the physical and econometric models result in an increase in the estimate of water savings of around 19% to 24%.


2007 Annual Meeting, February 4-7, 2007, Mobile, Alabama | 2007

Adoption of Conservation-Tillage Practices in Cotton Production

Swagata “Ban” Banerjee; Steven W. Martin; Roland K. Roberts; James A. Larson; Robert J. Hogan; Jason L. Johnson; Kenneth W. Paxton; Jeanne M. Reeves

Natural causes (such as droughts), non-natural causes (such as competing uses), and government policies limit the supply of water for agriculture in general and irrigating crops in particular. Under such reduced water supply scenarios, existing physical models reduce irrigation proportionally among crops in the farmer’s portfolio, disregarding temporal changes in economic and/or institutional conditions. Hence, changes in crop mix resulting from expectations about risks and returns are ignored. A method is developed that considers those changes and accounts for economic substitution and expansion effects. Forecasting studies based on this method with surface water in Georgia and Alabama demonstrate the relative strength of econometric modeling vis-a`-vis physical methods. Results from a study using this method for ground water in Mississippi verify the robustness of those findings. Results from policy induced simulation scenarios indicate water savings of 12% to 27% using the innovative method developed. Although better irrigation water demand forecasting in crop production was the key objective of this pilot project, conservation of a valuable natural resource (water) has turned out to be a key consequence.


2005 Annual Meeting, February 5-9, 2005, Little Rock, Arkansas | 2005

Farm Profits from Stochastic and On-Farm Yields of Bt and Non-Bt Cotton in the Mississippi Delta

Swagata “Ban” Banerjee; Steven W. Martin; Michael E. Wetzstein


2008 Annual Meeting, February 2-6, 2008, Dallas, Texas | 2008

A Binary Logit Analysis of Factors Impacting Adoption of Genetically Modified Cotton

Swagata “Ban” Banerjee; Steven W. Martin

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Steven W. Martin

Mississippi State University

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Kenneth W. Paxton

Louisiana State University

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Jimmy Bramblett

United States Department of Agriculture

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