Recovering Forecast Distributions of Crop Composition: Method and Application to Kentucky Agriculture

Recovering Forecast Distributions of Crop Composition: Method and Application to Kentucky Agriculture

This paper proposes a novel application of the multinomial logit (MNL) model using Cropland Data Layer and field-level boundaries to estimate crop transition probabilities, which are used to generate forecast distributions of total acreage for five major crops produced in the state of Kentucky. Thes...

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Main Authors: GwanSeon Kim, Mehdi Nemati, Steven Buck, Nicholas Pates, Tyler Mark
Format: Article
Language:English
Published: MDPI AG 2020-04-01
Series:Sustainability
Subjects:
forecast distribution
multinomial logit model
simulation
transition probability
Online Access:https://www.mdpi.com/2071-1050/12/7/2917
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spelling doaj-4594e86b7f894e13bf48077a0eef18982020-11-25T02:33:57ZengMDPI AGSustainability2071-10502020-04-01122917291710.3390/su12072917Recovering Forecast Distributions of Crop Composition: Method and Application to Kentucky AgricultureGwanSeon Kim0Mehdi Nemati1Steven Buck2Nicholas Pates3Tyler Mark4College of Agriculture, Arkansas State University, Jonesboro, AR 72467, USASchool of Public Policy, University of California, Riverside, CA 92521, USADepartment of Agricultural Economics, University of Kentucky, Lexington, KY 40546, USADepartment of Agricultural Economics, University of Kentucky, Lexington, KY 40546, USADepartment of Agricultural Economics, University of Kentucky, Lexington, KY 40546, USAThis paper proposes a novel application of the multinomial logit (MNL) model using Cropland Data Layer and field-level boundaries to estimate crop transition probabilities, which are used to generate forecast distributions of total acreage for five major crops produced in the state of Kentucky. These forecasts distributions have a wide range of applications that, besides providing interim acreage estimates ahead of the June Acreage Survey, can inform the ability of producers to incorporate new crops in the land-use rotation, investments in location-specific capital and input distribution as well informing the likelihood of adverse water quality events from nutrient run-off.https://www.mdpi.com/2071-1050/12/7/2917forecast distributionmultinomial logit modelsimulationtransition probability
collection DOAJ
language English
format Article
sources DOAJ
author GwanSeon Kim
Mehdi Nemati
Steven Buck
Nicholas Pates
Tyler Mark
spellingShingle GwanSeon Kim
Mehdi Nemati
Steven Buck
Nicholas Pates
Tyler Mark
Recovering Forecast Distributions of Crop Composition: Method and Application to Kentucky Agriculture
Sustainability
forecast distribution
multinomial logit model
simulation
transition probability
author_facet GwanSeon Kim
Mehdi Nemati
Steven Buck
Nicholas Pates
Tyler Mark
author_sort GwanSeon Kim
title Recovering Forecast Distributions of Crop Composition: Method and Application to Kentucky Agriculture
title_short Recovering Forecast Distributions of Crop Composition: Method and Application to Kentucky Agriculture
title_full Recovering Forecast Distributions of Crop Composition: Method and Application to Kentucky Agriculture
title_fullStr Recovering Forecast Distributions of Crop Composition: Method and Application to Kentucky Agriculture
title_full_unstemmed Recovering Forecast Distributions of Crop Composition: Method and Application to Kentucky Agriculture
title_sort recovering forecast distributions of crop composition: method and application to kentucky agriculture
publisher MDPI AG
series Sustainability
issn 2071-1050
publishDate 2020-04-01
description This paper proposes a novel application of the multinomial logit (MNL) model using Cropland Data Layer and field-level boundaries to estimate crop transition probabilities, which are used to generate forecast distributions of total acreage for five major crops produced in the state of Kentucky. These forecasts distributions have a wide range of applications that, besides providing interim acreage estimates ahead of the June Acreage Survey, can inform the ability of producers to incorporate new crops in the land-use rotation, investments in location-specific capital and input distribution as well informing the likelihood of adverse water quality events from nutrient run-off.
topic forecast distribution
multinomial logit model
simulation
transition probability
url https://www.mdpi.com/2071-1050/12/7/2917
work_keys_str_mv AT gwanseonkim recoveringforecastdistributionsofcropcompositionmethodandapplicationtokentuckyagriculture
AT mehdinemati recoveringforecastdistributionsofcropcompositionmethodandapplicationtokentuckyagriculture
AT stevenbuck recoveringforecastdistributionsofcropcompositionmethodandapplicationtokentuckyagriculture
AT nicholaspates recoveringforecastdistributionsofcropcompositionmethodandapplicationtokentuckyagriculture
AT tylermark recoveringforecastdistributionsofcropcompositionmethodandapplicationtokentuckyagriculture
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