4 research outputs found

    LEADING INDICATORS FOR REGIONAL COTTON RESPONSE: STRUCTURAL AND TIME SERIES MODELING RESULTS

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    Resurging southeastern cotton production compels better cotton acreage forecasts for planning seed, chemical, and other input requirements. Structural models describe leading acreage response indicators, and forecasts are compared time-series models. Cotton price, loan rate, deficiency payments, lagged corn acreage, the PIK program, and previous cotton yield significantly influence response.Crop Production/Industries,

    LEADING INDICATORS OF REGIONAL COTTON ACREAGE RESPONSE: STRUCTURAL AND TIME SERIES MODELING RESULTS

    Get PDF
    Resurgent cotton production compels better acreage forecasts for planning seed, chemical, and other input requirements. Structural models describe leading acreage response indicators, and forecasts are compared to time-series models. Cotton price, loan rate, deficiency payments, lagged corn acreage, the PIK program, and previous cotton yield significantly influence cotton acreage response.resurgent cotton production, cotton acreage, Crop Production/Industries,

    LEADING INDICATORS FOR REGIONAL COTTON RESPONSE: STRUCTURAL AND TIME SERIES MODELING RESULTS

    No full text
    Resurging southeastern cotton production compels better cotton acreage forecasts for planning seed, chemical, and other input requirements. Structural models describe leading acreage response indicators, and forecasts are compared time-series models. Cotton price, loan rate, deficiency payments, lagged corn acreage, the PIK program, and previous cotton yield significantly influence response

    LEADING INDICATORS OF REGIONAL COTTON ACREAGE RESPONSE: STRUCTURAL AND TIME SERIES MODELING RESULTS

    No full text
    Resurgent cotton production compels better acreage forecasts for planning seed, chemical, and other input requirements. Structural models describe leading acreage response indicators, and forecasts are compared to time-series models. Cotton price, loan rate, deficiency payments, lagged corn acreage, the PIK program, and previous cotton yield significantly influence cotton acreage response
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