Multinomial Logistic Regression on Markov Chains for Crop Rotation Modelling

Paton, Lewis William; Troffaes, Matthias C. M.; Boatman, N. D.; Hussein, Mohamud; Hart, Andy

doi:10.1007/978-3-319-08852-5_49

Cited by 10 publications

(10 citation statements)

References 10 publications

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“…The MNL model estimates the likelihood of adoption of non-reference categories against a reference (base) category in terms of relative risk ratio (RRR) [27]. The other reason for choosing this model is that this has been more commonly used in recent studies [27][28][29][30]. Having three farming practices in place, farmers can choose the one they prefer the most from the three alternatives.…”

Section: Analytical Modelmentioning

confidence: 99%

Who Adopts Agroforestry in a Subsistence Economy?

Dhakal¹,

Kumar²

2020

Preprint

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Land degradation is a critical issue globally putting our future generations at risk. The decrease in farm productivity over the years is evidence of land degradation severity in Nepal. Among the many strategies in place, agroforestry, which is an integrated tree-based farming, is widely recommended to address this productivity issue. This paper thoroughly examines what influences the choice of agroforestry adoption by farmers and what discourages the adoption. For this, a total of 288 households were surveyed using a structured questionnaire. Two agroforestry practices were compared with conventional agriculture with the help of the Multinomial Logistic Regression (MNL) model. The likelihood of adoption was found to be influenced by gender; the male-headed households were more likely to adopt the tree-based farming practice. Having a source of off-farm income was positively associated with the adoption decision of farmers. Area of farmland was found being the major constraint to agroforestry adoption for smallholder farmers. Some other variables that affected positively included livestock herd size, provision of extension service, home-to-forest distance, farmers' group membership and awareness of farmers about environmental benefits of agroforestry. Irrigation was another adoption constraint that the study area farmers were faced with. The households with means of transport and with larger family (household) size were found to be reluctant towards agroforestry adoption. A collective farming practice could be a strategy to engage the smallholder farmers in agroforestry.

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Section: Analytical Modelmentioning

confidence: 99%

Who Adopts Agroforestry in a Subsistence Economy?

Dhakal¹,

Kumar²

2020

Preprint

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“…Carrión-Flores, Flores-Lagunes and Guci [23] use the MNL model by incorporating spatial dependence in Medina County, Ohio, for the determinants of land-use choices. Paton, et al [27] investigate the impact of rainfall and crop profit margin on crop choice by using MNL regression to generate the crop choice transition probabilities.…”

Section: Literature Reviewmentioning

confidence: 99%

“…The Markov chain approach has been widely used in land use studies [34][35][36][37][38][39] as well as agricultural-related studies especially for studying the crop rotation behavior [27,28,[40][41][42][43]. Based on Taylor and Karlin [44] and Savage [38], a Markov process {X t } given the value of X t is a stochastic process with the property that the values of X u for u < t do not affect the values of X s for s > t. In other words, knowledge of past behavior is predictive of the probability of any specific future behavior if the current state is known.…”

Section: Markov Chain Approachmentioning

confidence: 99%

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

et al. 2020

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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.

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“…The logistic regression and decision tree techniques can be used to predict frost occurrences. Those techniques have been used for various fields including agronomy [9,10], meteorology [11], and medicine [12]. However, to the best of our knowledge, few studies have been conducted on frost prediction using those techniques.…”

Section: Introductionmentioning

confidence: 99%

Prediction of Frost Occurrences Using Statistical Modeling Approaches

Lee

Chun

Han³

et al. 2016

Advances in Meteorology

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We developed the frost prediction models in spring in Korea using logistic regression and decision tree techniques. Hit Rate (HR), Probability of Detection (POD), and False Alarm Rate (FAR) from both models were calculated and compared. Threshold values for the logistic regression models were selected to maximize HR and POD and minimize FAR for each station, and the split for the decision tree models was stopped when change in entropy was relatively small. Average HR values were 0.92 and 0.91 for logistic regression and decision tree techniques, respectively, average POD values were 0.78 and 0.80 for logistic regression and decision tree techniques, respectively, and average FAR values were 0.22 and 0.28 for logistic regression and decision tree techniques, respectively. The average numbers of selected explanatory variables were 5.7 and 2.3 for logistic regression and decision tree techniques, respectively. Fewer explanatory variables can be more appropriate for operational activities to provide a timely warning for the prevention of the frost damages to agricultural crops. We concluded that the decision tree model can be more useful for the timely warning system. It is recommended that the models should be improved to reflect local topological features.

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Multinomial Logistic Regression on Markov Chains for Crop Rotation Modelling

Cited by 10 publications

References 10 publications

Who Adopts Agroforestry in a Subsistence Economy?

Who Adopts Agroforestry in a Subsistence Economy?

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

Prediction of Frost Occurrences Using Statistical Modeling Approaches

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