Factors affecting farmers'choice to adopt risk management strategies:The application of multivariate and multinomial probit models

This study investigates the factors that impact farmers'adoption of risk management strategies(RMS)in Pakistan during times of uncertainty.The study examines farmers'adoption of RMS using both multinomial probit(MNP)and multivariate probit(MVP).Data were collected from 382 farmers sampled from four districts in KhyberPakhtunkhwa(KP)province of Pakistan via a multistage sampling technique.This study utilizes the MNP model,considering the assumption of Independence of Irrelevant Alternatives(IIA)and incorporating correlated error terms.The objective is to understand farmers'behavior in risky situations and determine if there is heterogeneity.Results are compared with the MVP model to assess robustness and gain deeper understanding of farmers'decisionmaking processes.The research findings reveal that our results are robust,and farmers behave homogeneously in various RMS scenarios.Farmers adopt RMS individually or in combination to mitigate the adverse effects of natural calamities on their livelihood.The risk-averse farmers,who perceive weather-related risks as a threat,access credits and information,and have farms close to a river are more likely to adopt RMS,irrespective of the format of the strategies available.Moreover,the predicted probabilities and correlation of the RMS and RM categories have strengthened our model estimation.These findings provide insights into the behavior of farmers in adopting RMS which are helpful for policymakers and stakeholders in developing strategies to mitigate the impacts of natural calamities on farmers.

SOME ASYMPTOTIC INFERENCE IN MULTINOMIAL NONLINEAR MODELS (A GEOMERIC APPROACH)

A geometric framework is proposed for multinomial nonlinear modelsbased on a modified version of the geometric structure presented by Bates & Watts[4]. We use this geometric framework to study some asymptotic inference in terms ofcurvatures for multinomial nonlinear models. Our previous results [15] for ordinarynonlinear regression models are extended to multinomial nonlinear models.

Modelling of Active and Latent Attributes Based on Traveler Perspectives: Case of Port City of Douala

A growing stream of study stresses the relevance of subjective elements in understanding the hierarchy of preferences that underpin individual travel behavior. The purpose of this study is to evaluate the impact of various factors on mode choice. To achieve this, a multinomial logit model (MNL) was used to analyze the relationships between mode choice and three classes of attributes;Combined Active and Latent, Active only and Latent only attributes. The data used are derived from surveys in the port city of Douala, Cameroon as a case study. Results stipulated that, the combined attributes model performed better than both active only attributes and latent only attributes models. Likewise, latent only attributes model performed better than active only attributes model. The advantage of modelling all three groups is for better selection of the most relevant attributes, and this is very relevant in understanding travel behavior of individuals and mode choice decisions.

Navigating Market Choices: Understanding Carrot Market Outlet Selection among Smallholder Farmers in Kenya

This research delves into the hurdles and strategies aimed at augmenting the market involvement of smallholder carrot farmers in Nakuru County, Kenya. Employing a Multinomial Logit (MNL) model, it scrutinizes the factors influencing the selection of marketing outlets among carrot farmers. The findings unveil that a significant majority (81%) of surveyed farmers actively participate in diverse market outlets, encompassing the farm gate, cleaning point, local market, external market, and export market. Notably, pivotal buyers include aggregators, brokers, wholesalers, retailers, and consumers, with transactions predominantly occurring at the farm level. Additionally, the analysis discerns substantial influences of socio-economic characteristics, experiential factors, and geographical proximity on farmers’ choices of market outlets. Specifically, gender, age, land size, farming experience, and distance to markets emerge as critical determinants. Moreover, the study delves into the examination of market margins along the carrot value chain, shedding light on the potential profitability of carrot farming in the region. Remarkably, higher average gross margins are identified in export and external markets, signaling lucrative prospects for farmers targeting these segments. However, disparities in profit distribution between farmers and traders underscore the necessity for interventions to ensure equitable value distribution throughout the value chain. These findings underscore the imperative for tailored interventions to tackle challenges and foster inclusive agricultural development. Strategies such as farmer organizations, contracting, and vertical integration are advocated to enhance market access and profitability for smallholder carrot farmers. Thus, this study enriches our comprehension of the dynamics within carrot value chains and provides valuable insights for policymakers and development practitioners aiming to uplift rural livelihoods and bolster food security.

Cubic Spline Regression: An Application to Early Bipolar Disorder Dynamics

Owing to the fact that the major challenge of predicting the risk of having bipolar is the absence of a gold standard to distinguish between true cases and false positive;this study employed the extension of cubic spline function to the multinomial model to explore the risk tendency of unnoticed early bipolar across three different groups of mood disorder. The intermediate group was used to accommodate for false negative and false positive while mapping the true value of bipolar risk tendency across the three groups to a scale. Hence for all distributions of “yes” ticked in a mood disorder questionnaire, the study predicts the bipolar risk tendency while simultaneously accommodating for the patients response bias. The coefficients of the polynomial are obtained using the maximum likelihood method. The spline graph reveals how bipolar disorder build up slowly and lingers in the body for long without been noticed due to fluctuations in risk tendency of the mood scores.

Analysis of high-speed rail and airline transport cooperation in presence of non-purchase option

We study cooperation between the airline and high-speed rail(HSR) sectors by formulating their joint profit as a maximization problem using a multinomial logit choice model in a three-node setting. We allow the nonpurchase option as an outside option available to consumers. The demand for each choice is not only a function of the price but also the service quality, such as the total trip time, frequency of service, and ease of connecting from the hub to a nearby HSR station. As a result, the following findings are presented. First, regardless of the service quality of either sector and the non-purchase option,cooperation decreases the total volume of the domestic market of a country. Second, when the attractiveness of the outside option is high, the HSR and air sectors can prevent a large reduction in the total volume by cooperation in the connecting market. However, this is not the case in the domestic market. Third, if the non-purchase quality in the domestic market is high, then cooperation increases the social welfare of the whole market. If the non-purchase quality is low, then cooperation increases the welfare of the whole market only in cases where the number of potential customers in the connecting market is relatively large. We also show the effect of improving air–rail service quality on each market share and on the total profit.

GEOMETRIC METHOD OF SEQUENTIAL ESTIMATION RELATED TO MULTINOMIAL DISTRIBUTION MODELS

In 1980's, differential geometric methods are successfully used to study curved exponential families and normal nonlinear repression models. This paper presents a new geometric structure to study multinomial distributipn models which contain a set of nonlinear parameters. Based on this geometric structure, the authors study several asymptotic properties for sequential estimation. The bias, the variance and the information loss of the sequeatial estimates are given from geometric viewpoint, and a limit theorem connected with the obServed and expected Fisher information is obtained ill terms of curVature measures. The results show that the sequeotial estimation procedure has some better properties which are generally impossible for nonsequeotial estimation procedures.

Optimal model averaging estimator for multinomial logit models

In this paper,we study optimal model averaging estimators of regression coefficients in a multinomial logit model,which is commonly used in many scientific fields.A Kullback-Leibler(KL)loss-based weight choice criterion is developed to determine averaging weights.Under some regularity conditions,we prove that the resulting model averaging estimators are asymptotically optimal.When the true model is one of the candidate models,the averaged estimators are consistent.Simulation studies suggest the superiority of the proposed method over commonly used model selection criterions,model averaging methods,as well as some other related methods in terms of the KL loss and mean squared forecast error.Finally,the website phishing data is used to illustrate the proposed method.

Key factors contributing to crash severity at highway-rail grade crossings

The purpose of this paper is to develop and com- pare the preferred multinomial logit （MNL） and ordered logit （ORL） model in identifying factors that are important in making an injury severity difference and exploring the impact of such explanatory variables on three different severity levels of vehicle-related crashes at highway-rail grade crossings （HRGCs） in the United States. Vehicle-rail crash data on USDOT highway-rail crossing inventory and public crossing sites from 2005 to 2012 are used in this study. Preferred MNL and ORL models are developed and marginal effects are also calculated and compared. A majority of the variables have shown similar effects on the probability of the three different severity levels in both models. In addition, based on the Akaike information criterion, it is found that the MNL model is better than the ORL model in predicting the vehicle crash severity levels on HRGCs in this study. Therefore, the researchers recommend the use of MNL model in predicting severity levels of vehicle-rail crashes on HRGCs.

Coopetition Between TTA and OTA Based on Multinomial Logit Choice Model

This paper proposes a framework to analyse the impact of online travel agency(OTA)when it steps into an original market of a traditional travel agency(TTA).Based on the multinomial logit choice model,the demand model and the profit model are presented.Then,the demand squeeze,the total demand increase and the cooperation range of wholesale price are analysed.From the analysis,the results indicate that:(1)OTA can increase the demand of the whole market while it squeezes the demand of TTA;(2)The demand squeeze,total demand increase and the range of cooperation wholesale price are all positive with the perceived value from OTA and negative with the perceived value from TTA.(3)The more immature the market is the more necessary for TTA to cooperate with OTA.In addition,numerical example and sensitivity analysis of perceived value and price are presented to illustrate the demand squeeze,demand increase and cooperation range of wholesale price.

Studying on equilibriums between price and QoS in multi-provider overlay access networks

From the viewpoint of game theory, this paper proposes a model that combines QoS index with price factor in overlay access networks, and uses the multinomial logit （MNL） to model the choice behaviour of users. Each service class is considered an independent and competitive entity offered by each provider, which aims at maximizing its own utility. Based on noncooperative game, we prove the existence and uniqueness of equilibriums between QoS levels and prices among various service classes, and demonstrate the properties of equilibriums. Finally, these results are verified via ntunerieal analysis.

Factors Explaining the Dynamics of Agricultural Technological Innovations Adoption: Evidence from Senegal’s Rain Maize Farmer

This paper analyzes the adoption dynamics of improved rainfed maize seeds disseminated in Senegal in 2013 by the West African Agricultural Productivity Program (WAAPP). We group maize producers into five groups (non-adopters, laggards/abandoners, late adopters, followers and pioneers/innovators) and take into account the heterogeneity of unobservable characteristics of the producers. In the pioneers/innovators group, the availability of labour, household size, shocks, and frequency of access to advice positively influence adoption, whereas financial constraints and high numbers of plots reduce the probability of adoption. Producers in the followers’ category tend to be older and more educated than those in the other categories. However, food insecurity and shocks such as diseases hamper adoption. For the group of late adopters, household size and available storage infrastructures explain adoption. However, the number of plots and shocks reduces their probability of adoption. Laggards tend to face shocks and food insecurity. The authors recommend to consider the dynamics of the adoption of technological innovations and heterogeneity of the characteristics of adopters groups in future research. They also recommend farmers to increase their adoption rate of the “Early Thai” and “Suwan 1” seed varieties thanks to their higher yields compared to traditional varieties. Also, a higher adoption rate would positively impact the food security of maize farmers in Eastern Senegal and High Casamance, especially in terms of availability. Other studies measuring the number of years needed for large-scale adoption of improved seed varieties should be conducted.

Contraceptive Method Choice Among Newly Married Couples and Influential Factors in Shanghai Municipality

A follow-up study with 7,826 representative newly married couples for fifteen months after their weddings in Shanghai Municipality showed that among the 3, 412 couples who actually adopted contraceptive method, rhythm was the main choice; the proportion for couples taking the contraceptive pill was much higher among sexually active couples before their weddings. The proportions of adopting rhythm or condom or the both, however, increased afterwards.About 86% of couples who had ever planned adopting the rhythm at registration actually used it. In fact, 16% of those who had ever planned to take pills eventually made this choice, because of their worry about any adverse side effects on mother's and fetus' health. Their knowledge about contraception,especially the pills, was incomprehensiue. APProximately 62% of condom users had not been given any instruction regarding its use when they got this contracoptive device one year later. Half of the pill and spermicide users learnt these respective methods from their friends or relatives. The proportion of delivering contraceptiues alter marriage by;F.P.P. was rather low. By fitting the multinomial logistic regression model, it is indicated that couple's evaluation on contraceptiue methods and contraceptiue goal were the main factors determining newlyweds' method of choice. Wife's knowledge on contraception and the accessibility of contraceptives and devices also influenced the method choice to some extent.

Passenger Choice Behavior between Direct and Transit Flights——A Case Study on Passengers Using Hub Airports in the Northeast Asian Region

This study analyzes air passenger route choice behavior for long-haul inter-continental travel. It employs the SP （state preference） technique and logit modeling to investigate the impact of route development via neighboring countries in the region. With the Japanese government pursuing an increase in international routes at Haneda International Airport, and the Chinese government planning to construct Beijing Capital Second International Airport by 2019, the competition among airports to serve as hubs in Northeast Asia will increase significantly. Korean passengers will have a greater number of route choices when traveling to North America or Europe, utilizing not only direct flights from Incheon International Airport but also flights via Tokyo or Beijing area airports including Haneda International Airport, Narita International Airport, Beijing Capital International Airport and Beijing Capital Second International Airport. Accordingly, passengers will choose among the alternatives by considering fares and flight times. As such, it is essential for airports to offer flights with competitive prices for transit passengers to become successful competitive airports in the region. Therefore, it will become more important for market decision makers to strive toward more attractive ticket prices and better route network quality.

Models and estimators linking individual-based and sample-based rarefaction, extrapolation and comparison of assemblages

Aims In ecology and conservation biology,the number of species counted in a biodiversity study is a key metric but is usually a biased underestimate of total species richness because many rare species are not detected.Moreover,comparing species richness among sites or samples is a statistical challenge because the observed number of species is sensitive to the number of individuals counted or the area sampled.For individual-based data,we treat a single,empirical sample of species abundances from an investigator-defined species assemblage or community as a reference point for two estimation objectives under two sampling models:estimating the expected number of species(and its unconditional variance)in a random sample of(i)a smaller number of individuals(multinomial model)or a smaller area sampled(Poisson model)and(ii)a larger number of individuals or a larger area sampled.For sample-based incidence(presence–absence)data,under a Bernoulli product model,we treat a single set of species incidence frequencies as the reference point to estimate richness for smaller and larger numbers of sampling units.Methods The first objective is a problem in interpolation that we address with classical rarefaction(multinomial model)and Coleman rarefaction(Poisson model)for individual-based data and with sample-based rarefaction(Bernoulli product model)for incidence frequencies.The second is a problem in extrapolation that we address with sampling-theoretic predictors for the number of species in a larger sample(multinomial model),a larger area(Poisson model)or a larger number of sampling units(Bernoulli product model),based on an estimate of asymptotic species richness.Although published methods exist for many of these objectives,we bring them together here with some new estimators under a unified statistical and notational framework.This novel integration of mathematically distinct approaches allowed us to link interpolated(rarefaction)curves and extrapolated curves to plot a unified species accumulation curve for empirical examples.We provide new,unconditional variance estimators for classical,individual-based rarefaction and for Coleman rarefaction,long missing from the toolkit of biodiversity measurement.We illustrate these methods with datasets for tropical beetles,tropical trees and tropical ants.Important Findings Surprisingly,for all datasets we examined,the interpolation(rarefaction)curve and the extrapolation curve meet smoothly at the reference sample,yielding a single curve.Moreover,curves representing 95%confidence intervals for interpolated and extrapolated richness estimates also meet smoothly,allowing rigorous statistical comparison of samples not only for rarefaction but also for extrapolated richness values.The confidence intervals widen as the extrapolation moves further beyond the reference sample,but the method gives reasonable results for extrapolations up to about double or triple the original abundance or area of the reference sample.We found that the multinomial and Poisson models produced indistinguishable results,in units of estimated species,for all estimators and datasets.For sample-based abundance data,which allows the comparison of all three models,the Bernoulli product model generally yields lower richness estimates for rarefied data than either the multinomial or the Poisson models because of the ubiquity of non-random spatial distributions in nature.

Determinants of farmers’ adoption of land management practices in Gelana subwatershed of Northern highlands of Ethiopia

Introduction:Soil erosion is the major environmental problem in Ethiopia.In response to this problem,the country has been in continuous struggle to adopt land management practices.Therefore,the objective of this study was to investigate the determinants of farmers’adoption of land management practice in the Gelana sub-watershed,Northern highlands of Ethiopia.Methods:The data was collected from 176 randomly selected farming households using a survey questionnaire and was analyzed using multinomial logit model(MNL).Results:The results showed that education,family size,slope of the plot,tenure security,training,access to farm credit and extension service positively and significantly affect adoption of land management practices while age has a negative and significant influence on adoption.Conclusions:The findings suggest that improving farmers’education status and increase the availability of credit to reduce poverty and increase income would enhance the adoption of land management practices.

Random-parameters analysis of highway characteristics on crash frequency and injury severity

Factors that affect highway-related crash frequency and injury severity vary across observations. Using a methodology that does not account nor correct for heterogeneity in observed and unobserved crash factors across highway segments may lead to biased and inconsistent estimated coefficients, thus resulting in erroneous inferences. The present paper demonstrates the use of random-parameters models to facilitate and enhance how crash factors affect crash frequency and injury severity along a highway segment. The results indicate that a unit increase in the presence of stop sign along a highway segment reduces crash frequency by 2.471 for 87.24% of the roadway segments. For the remaining 12.76% of the roadway segments, crash frequency is increased by the same margin. Using the random-parameters multinomial logit model, the result indicates that, for 90.89% of the observations, the presence of a stop sign on a highway segment increases the probability of the injury outcome. For 9.11% of the observations, the presence of a stop sign on a highway segment reduces the probability of the injury outcome, and the marginal effect value across observations is 0.0017. Vertical grades greater than 5% increase crash frequency for 58.46% of the highway segments, and decrease for 41.54% of the highway segments by 0.121 for one unit increase in vertical grades.

Association of self-reported health with alcohol consumption: a study conducted among Chinese and Canadian middle-aged and older adults

There has been lack of studies that examine the relationship between self-rated health(SRH)and alcohol consumption,particularly in middle-aged and older adult populations.This study aims to investigate association of SRH status with alcohol consumption in middle-aged and older adult populations.The study is a cross-sec-tional study design that was based on the China Health and Retired Longitudinal study(CHARLS)and the Canadian Alcohol and Drug Monitoring Survey(CAD-UMS)and the Canadian Alcohol,Tobacco and Drug Survey(CTADS).Measure of health is SRH status and self-reported alcohol use.Multinomial logistic regres-sion was performed to model the data and the odds ratio of self-reported excel-lent,very good,good and fair(versus poor)for current and former drinkers versus nondrinkers and current drinkers versus former drinkers was estimated in models after adjusting for covariates.This study found that in both Chinese and Canadian adult populations,current drinkers reported better health status than former drink-ers;lifetime nondrinkers reported better health status than former drinkers.Current drinkers reported better health status than nondrinkers.Canadian moderate drinkers(1.3-44 g per day)tended to report better health compared with occasional drinkers and Chinese heavy drinkers(45+grams per day)reported better health status com-pared with occasional drinkers in both populations.This study found current drink-ers tended to have better health status than former drinker and lifetime nondrinkers in adult populations.Nondrinkers tended to report better health status than former drinkers.Low and medium drinkers reported better health status.

Cleaning the energy sources for water heating among Nanjing households： barriers and opportunities for solar and natural gas

Energy for water heating accounts for an increasing part in residential energy demand in China. An extensive survey was conducted to analyze the determinants of household energy choices for water heaters among residents in Nanjing, China. Two sets of variables were examined as potential influences： building features and household socio-economic characteristics. Results suggest that building features such as gas availability and building structures, and household characteristics such as household head＇s education degree and energy-conserving sense are crucial determinants in choosing natural gas as water heater energy. Installation permission for solar water heater, building stories, and residential location serve as determining factors in choosing solar water heaters. Based on these, barriers and opportunities are discussed for transitions toward cleaner water heating energies, and suggestions are given for local governments to promote cleaner energy replacement in China.