Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 16163

Search results for: logit model

16163 Assessing Effects of an Intervention on Bottle-Weaning and Reducing Daily Milk Intake from Bottles in Toddlers Using Two-Part Random Effects Models

Authors: Yungtai Lo

Abstract:

Two-part random effects models have been used to fit semi-continuous longitudinal data where the response variable has a point mass at 0 and a continuous right-skewed distribution for positive values. We review methods proposed in the literature for analyzing data with excess zeros. A two-part logit-log-normal random effects model, a two-part logit-truncated normal random effects model, a two-part logit-gamma random effects model, and a two-part logit-skew normal random effects model were used to examine effects of a bottle-weaning intervention on reducing bottle use and daily milk intake from bottles in toddlers aged 11 to 13 months in a randomized controlled trial. We show in all four two-part models that the intervention promoted bottle-weaning and reduced daily milk intake from bottles in toddlers drinking from a bottle. We also show that there are no differences in model fit using either the logit link function or the probit link function for modeling the probability of bottle-weaning in all four models. Furthermore, prediction accuracy of the logit or probit link function is not sensitive to the distribution assumption on daily milk intake from bottles in toddlers not off bottles.

Keywords: two-part model, semi-continuous variable, truncated normal, gamma regression, skew normal, Pearson residual, receiver operating characteristic curve

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16162 Poverty Dynamics in Thailand: Evidence from Household Panel Data

Authors: Nattabhorn Leamcharaskul

Abstract:

This study aims to examine determining factors of the dynamics of poverty in Thailand by using panel data of 3,567 households in 2007-2017. Four techniques of estimation are employed to analyze the situation of poverty across households and time periods: the multinomial logit model, the sequential logit model, the quantile regression model, and the difference in difference model. Households are categorized based on their experiences into 5 groups, namely chronically poor, falling into poverty, re-entering into poverty, exiting from poverty and never poor households. Estimation results emphasize the effects of demographic and socioeconomic factors as well as unexpected events on the economic status of a household. It is found that remittances have positive impact on household’s economic status in that they are likely to lower the probability of falling into poverty or trapping in poverty while they tend to increase the probability of exiting from poverty. In addition, not only receiving a secondary source of household income can raise the probability of being a never poor household, but it also significantly increases household income per capita of the chronically poor and falling into poverty households. Public work programs are recommended as an important tool to relieve household financial burden and uncertainty and thus consequently increase a chance for households to escape from poverty.

Keywords: difference in difference, dynamic, multinomial logit model, panel data, poverty, quantile regression, remittance, sequential logit model, Thailand, transfer

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16161 Economic Valuation of Forest Landscape Function Using a Conditional Logit Model

Authors: A. J. Julius, E. Imoagene, O. A. Ganiyu

Abstract:

The purpose of this study is to estimate the economic value of the services and functions rendered by the forest landscape using a conditional logit model. For this study, attributes and levels of forest landscape were chosen; specifically, attributes include topographical forest type, forest type, forest density, recreational factor (side trip, accessibility of valley), and willingness to participate (WTP). Based on these factors, 48 choices sets with balanced and orthogonal form using statistical analysis system (SAS) 9.1 was adopted. The efficiency of the questionnaire was 6.02 (D-Error. 0.1), and choice set and socio-economic variables were analyzed. To reduce the cognitive load of respondents, the 48 choice sets were divided into 4 types in the questionnaire, so that respondents could respond to 12 choice sets, respectively. The study populations were citizens from seven metropolitan cities including Ibadan, Ilorin, Osogbo, etc. and annual WTP per household was asked by using the interview questionnaire, a total of 267 copies were recovered. As a result, Oshogbo had 0.45, and the statistical similarities could not be found except for urban forests, forest density, recreational factor, and level of WTP. Average annual WTP per household for forest landscape was 104,758 Naira (Nigerian currency) based on the outcome from this model, total economic value of the services and functions enjoyed from Nigerian forest landscape has reached approximately 1.6 trillion Naira.

Keywords: economic valuation, urban cities, services, forest landscape, logit model, nigeria

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16160 A Discrete Logit Survival Model with a Smooth Baseline Hazard for Age at First Alcohol Intake among Students at Tertiary Institutions in Thohoyandou, South Africa

Authors: A. Bere, H. G. Sithuba, K. Kyei, C. Sigauke

Abstract:

We employ a discrete logit survival model to investigate the risk factors for early alcohol intake among students at two tertiary institutions in Thohoyandou, South Africa. Data were collected from a sample of 744 students using a self-administered questionnaire. Significant covariates were arrived at through a regularization algorithm implemented using the glmmLasso package. The tuning parameter was determined using a five-fold cross-validation algorithm. The baseline hazard was modelled as a smooth function of time through the use of spline functions. The results show that the hazard of initial alcohol intake peaks at the age of about 16 years and that at any given time, being of a male gender, prior use of other drugs, having drinking peers, having experienced negative life events and physical abuse are associated with a higher risk of alcohol intake debut.

Keywords: cross-validation, discrete hazard model, LASSO, smooth baseline hazard

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16159 Modeling the Risk Perception of Pedestrians Using a Nested Logit Structure

Authors: Babak Mirbaha, Mahmoud Saffarzadeh, Atieh Asgari Toorzani

Abstract:

Pedestrians are the most vulnerable road users since they do not have a protective shell. One of the most common collisions for them is pedestrian-vehicle at intersections. In order to develop appropriate countermeasures to improve safety for them, researches have to be conducted to identify the factors that affect the risk of getting involved in such collisions. More specifically, this study investigates factors such as the influence of walking alone or having a baby while crossing the street, the observable age of pedestrian, the speed of pedestrians and the speed of approaching vehicles on risk perception of pedestrians. A nested logit model was used for modeling the behavioral structure of pedestrians. The results show that the presence of more lanes at intersections and not being alone especially having a baby while crossing, decrease the probability of taking a risk among pedestrians. Also, it seems that teenagers show more risky behaviors in crossing the street in comparison to other age groups. Also, the speed of approaching vehicles was considered significant. The probability of risk taking among pedestrians decreases by increasing the speed of approaching vehicle in both the first and the second lanes of crossings.

Keywords: pedestrians, intersection, nested logit, risk

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16158 Analysis of Effect of Microfinance on the Profit Level of Small and Medium Scale Enterprises in Lagos State, Nigeria

Authors: Saheed Olakunle Sanusi, Israel Ajibade Adedeji

Abstract:

The study analysed the effect of microfinance on the profit level of small and medium scale enterprises in Lagos. The data for the study were obtained by simple random sampling, and total of one hundred and fifty (150) small and medium scale enterprises (SMEs) were sampled for the study. Seventy-five (75) each are microfinance users and non-users. Data were analysed using descriptive statistics, logit model, t-test and ordinary least square (OLS) regression. The mean profit of the enterprises using microfinance is ₦16.8m, while for the non-users of microfinance is ₦5.9m. The mean profit of microfinance users is statistically different from the non-users. The result of the logit model specified for the determinant of access to microfinance showed that three of specified variables- educational status of the enterprise head, credit utilisation and volume of business investment are significant at P < 0.01. Enterprises with many years of experience, highly educated enterprise heads and high volume of business investment have more potential access to microfinance. The OLS regression model indicated that three parameters namely number of school years, the volume of business investment and (dummy) participation in microfinance were found to be significant at P < 0.05. These variables are therefore significant determinants of impacts of microfinance on profit level in the study area. The study, therefore, concludes and recommends that to improve the status of small and medium scale enterprises for an increase in profit, the full benefit of access to microfinance can be enhanced through investment in social infrastructure and human capital development. Also, concerted efforts should be made to encouraged non-users of microfinance among SMEs to use it in order to boost their profit.

Keywords: credit utilisation, logit model, microfinance, small and medium enterprises

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16157 Evaluation of Neighbourhood Characteristics and Active Transport Mode Choice

Authors: Tayebeh Saghapour, Sara Moridpour, Russell George Thompson

Abstract:

One of the common aims of transport policy makers is to switch people’s travel to active transport. For this purpose, a variety of transport goals and investments should be programmed to increase the propensity towards active transport mode choice. This paper aims to investigate whether built environment features in neighbourhoods could enhance the odds of active transportation. The present study introduces an index measuring public transport accessibility (PTAI), and a walkability index along with socioeconomic variables to investigate mode choice behaviour. Using travel behaviour data, an ordered logit regression model is applied to examine the impacts of explanatory variables on walking trips. The findings indicated that high rates of active travel are consistently associated with higher levels of walking and public transport accessibility.

Keywords: active transport, public transport accessibility, walkability, ordered logit model

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16156 Introduction of Mass Rapid Transit System and Its Impact on Para-Transit

Authors: Khalil Ahmad Kakar

Abstract:

In developing countries increasing the automobile and low capacity public transport (para-transit) which are creating congestion, pollution, noise, and traffic accident are the most critical quandary. These issues are under the analysis of assessors to break down the puzzle and propose sustainable urban public transport system. Kabul city is one of those urban areas that the inhabitants are suffering from lack of tolerable and friendly public transport system. The city is the most-populous and overcrowded with around 4.5 million population. The para-transit is the only dominant public transit system with a very poor level of services and low capacity vehicles (6-20 passengers). Therefore, this study after detailed investigations suggests bus rapid transit (BRT) system in Kabul City. It is aimed to mitigate the role of informal transport and decreases congestion. The research covers three parts. In the first part, aggregated travel demand modelling (four-step) is applied to determine the number of users for para-transit and assesses BRT network based on higher passenger demand for public transport mode. In the second part, state preference (SP) survey and binary logit model are exerted to figure out the utility of existing para-transit mode and planned BRT system. Finally, the impact of predicted BRT system on para-transit is evaluated. The extracted outcome based on high travel demand suggests 10 km network for the proposed BRT system, which is originated from the district tenth and it is ended at Kabul International Airport. As well as, the result from the disaggregate travel mode-choice model, based on SP and logit model indicates that the predicted mass rapid transit system has higher utility with the significant impact regarding the reduction of para-transit.

Keywords: BRT, para-transit, travel demand modelling, Kabul City, logit model

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16155 National Directorate of Employment Training and Agricultural-Small and Medium Enterprises Performance in Nigeria

Authors: Festus M. Epetimehin

Abstract:

This study was conducted to identify the effect of National Directorate of Employment (NDE) training on the profit of Agricultural-Small and Medium Enterprises (SMEs) and to evaluate the factors that influenced farmers' participation in NDE training, as well as the type and frequency of training farmers and other agro-allied entrepreneurs in Nigeria. Using a multi-stage sampling procedure, a total of 384 respondents were sampled, including 192 beneficiaries and 192 non-beneficiaries in Oyo and Lagos States, respectively. Data were analysed using Binary Logit regression and Propensity Score Matching techniques. According to the binary logit analysis, respondents’ gender, availability to extension services, and the location of respondent’s operation were determinant factors influencing NDE training enrolment. All identified factors are related to the probability of respondents’ involvement in a positive way. Propensity score matching revealed that Agricultural-SMEs who participated in the NDE program boosted their profit by N341,072.18. The positive outcome of the effect implies that NDE training enhances Agri-SME performance in Nigeria. The study concluded that greater funding should be provided for the NDE for performance-enhancing training of the Agri-SMEs.

Keywords: PSM, binary logit model, Agri-SME

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16154 Characteristics and Item Parameters Fitness on Chemistry Teacher-Made Test Instrument

Authors: Rizki Nor Amelia, Farida A. Setiawati

Abstract:

This study aimed to: (1) describe the characteristics of teacher-made test instrument used to measure the ability of students’chemistry, and (2) identify the presence of the compability difficulty level set by teachers to difficulty level by empirical results. Based on these objectives, this study was a descriptive research. The analysis in this study used the Rasch model and Chi-square statistics. Analysis using Rasch Model was based on the response patterns of high school students to the teacher-made test instrument on chemistry subject Academic Year 2015/2016 in the Yogyakarta. The sample of this research were 358 students taken by cluster random sampling technique. The analysis showed that: (1) a teacher-made tests instrument has a medium on the mean difficulty level. This instrument is capable to measure the ability on the interval of -0,259 ≤ θ ≤ 0,659 logit. Maximum Test Information Function obtained at 18.187 on the ability +0,2 logit; (2) 100% items categorized either as easy or difficult by rasch model is match with the teachers’ judgment; while 37 items are categorized according to rasch model which 8.10% and 10.81% categorized as easy and difficult items respectively according to the teachers, the others are medium categorized. Overall, the distribution of the level of difficulty formulated by the teachers has the distinction (not match) to the level of difficulty based on the empirical results.

Keywords: chemistry, items parameter fitness, Rasch model, teacher-made test

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16153 Early Warning System of Financial Distress Based On Credit Cycle Index

Authors: Bi-Huei Tsai

Abstract:

Previous studies on financial distress prediction choose the conventional failing and non-failing dichotomy; however, the distressed extent differs substantially among different financial distress events. To solve the problem, “non-distressed”, “slightly-distressed” and “reorganization and bankruptcy” are used in our article to approximate the continuum of corporate financial health. This paper explains different financial distress events using the two-stage method. First, this investigation adopts firm-specific financial ratios, corporate governance and market factors to measure the probability of various financial distress events based on multinomial logit models. Specifically, the bootstrapping simulation is performed to examine the difference of estimated misclassifying cost (EMC). Second, this work further applies macroeconomic factors to establish the credit cycle index and determines the distressed cut-off indicator of the two-stage models using such index. Two different models, one-stage and two-stage prediction models, are developed to forecast financial distress, and the results acquired from different models are compared with each other, and with the collected data. The findings show that the two-stage model incorporating financial ratios, corporate governance and market factors has the lowest misclassification error rate. The two-stage model is more accurate than the one-stage model as its distressed cut-off indicators are adjusted according to the macroeconomic-based credit cycle index.

Keywords: Multinomial logit model, corporate governance, company failure, reorganization, bankruptcy

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16152 The Role of Temporary Migration as Coping Mechanism of Weather Shock: Evidence from Selected Semi-Arid Tropic Villages in India

Authors: Kalandi Charan Pradhan

Abstract:

In this study, we investigate does weather variation determine temporary labour migration using 210 sample households from six Semi-Arid Tropic (SAT) villages for the period of 2005-2014 in India. The study has made an attempt to examine how households use temporary labour migration as a coping mechanism to minimise the risk rather than maximize the utility of the households. The study employs panel Logit regression model to predict the probability of household having at least one temporary labour migrant. As per as econometrics result, it is found that along with demographic and socioeconomic factors; weather variation plays an important role to determine the decision of migration at household level. In order to capture the weather variation, the study uses mean crop yield deviation over the study periods. Based on the random effect logit regression result, the study found that there is a concave relationship between weather variation and decision of temporary labour migration. This argument supports the theory of New Economics of Labour Migration (NELM), which highlights the decision of labour migration not only maximise the households’ utility but it helps to minimise the risks.

Keywords: temporary migration, socioeconomic factors, weather variation, crop yield, logit estimation

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16151 Heavy Vehicles Crash Injury Severity at T-Intersections

Authors: Sivanandan Balakrishnan, Sara Moridpour, Richard Tay

Abstract:

Heavy vehicles make a significant contribution to many developed economies, including Australia, because they are a major means of transporting goods within these countries. With the increase in road freight, there will be an increase in the heavy vehicle traffic proportion, and consequently, an increase in the possibility of collisions involving heavy vehicles. Crashes involving heavy vehicles are a major road safety concern because of the higher likelihood of fatal and serious injury, especially to any small vehicle occupant involved. The primary objective of this research is to identify the factors influencing injury severity to occupants in vehicle collisions involving heavy vehicle at T- intersection using a binary logit model in Victoria, Australia. Our results show that the factors influencing injury severity include occupants' gender, age and restraint use. Also, vehicles' type, movement, point-of-impact and damage, time-of-day, day-of-week and season, higher percentage of trucks in traffic volume, hit pedestrians, number of occupants involved and type of collisions are associated with severe injury.

Keywords: binary logit model, heavy vehicle, injury severity, T-intersections

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16150 On the Determinants of Women’s Intrahousehold Decision-Making Power and the Impact of Diverging from Community Standards: A Generalised Ordered Logit Approach

Authors: Alma Sobrevilla

Abstract:

Using panel data from Mexico, this paper studies the determinants of women’s intrahousehold decision-making power using a generalised ordered logit model. Fixed effects estimations are also carried out to solve potential endogeneity coming from unobservable time-invariant factors. Finally, the paper analyses quadratic and community divergence effects of education on power. Results show heterogeneity in the effect of each of the determinants across different levels of decision-making power and suggest the presence of a significant quadratic effect of education. Having more education than the community average has a negative effect on power, supporting the notion that women tend to compensate their success outside the household with submissive attitudes at home.

Keywords: women, decision-making power, intrahousehold, Mexico

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16149 Discrete Choice Modeling in Education: Evaluating Early Childhood Educators’ Practices

Authors: Michalis Linardakis, Vasilis Grammatikopoulos, Athanasios Gregoriadis, Kalliopi Trouli

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Discrete choice models belong to the family of Conjoint analysis that are applied on the preferences of the respondents towards a set of scenarios that describe alternative choices. The scenarios have been pre-designed to cover all the attributes of the alternatives that may affect the choices. In this study, we examine how preschool educators integrate physical activities into their everyday teaching practices through the use of discrete choice models. One of the advantages of discrete choice models compared to other more traditional data collection methods (e.g. questionnaires and interviews that use ratings) is that the respondent is called to select among competitive and realistic alternatives, rather than objectively rate each attribute that the alternatives may have. We present the effort to construct and choose representative attributes that would cover all possible choices of the respondents, and the scenarios that have arisen. For the purposes of the study, we used a sample of 50 preschool educators in Greece that responded to 4 scenarios (from the total of 16 scenarios that the orthogonal design resulted), with each scenario having three alternative teaching practices. Seven attributes of the alternatives were used in the scenarios. For the analysis of the data, we used multinomial logit model with random effects, multinomial probit model and generalized mixed logit model. The conclusions drawn from the estimated parameters of the models are discussed.

Keywords: conjoint analysis, discrete choice models, educational data, multivariate statistical analysis

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16148 Fruits and Vegetable Consumers' Behaviour towards Organised Retailers: Evidence from India

Authors: K. B. Ramappa, A. V. Manjunatha

Abstract:

Consumerism in India is witnessing unprecedented growth driven by favourable demographics, rising young and working population, rising income levels, urbanization and growing brand orientation. In addition, the increasing level of awareness on health, hygiene and quality has made the consumers to think on the fairly traded goods and brands. This has made retailing extremely important to everyone because without retailers’ consumers would not have access to day-to-day products. The increased competition among different retailers has contributed significantly towards rising consumer awareness on quality products and brand loyalty. Many existing empirical studies have mainly focused on net saving of consumers at organised retail via-a-vis unorganised retail shops. In this article, authors have analysed the Bangalore consumers' attitudes towards buying of fruits and vegetables and their choice of retail outlets. The primary data was collected from 100 consumers belonging to the Bangalore City during October 2014. Sample consumers buying at supermarkets, convenience stores and hypermarkets were purposively selected. The collected data was analyzed using descriptive statistics and multinomial logit model. It was found that among all variables, quality and prices were major accountable factors for buying fruits and vegetables at organized retail shops. The empirical result of multinomial logit model reveals that annual net income was positively associated with the Big Bazar and Food World consumers and negatively associated with the Reliance Fresh, More and Niligiris consumers, as compared with the HOPCOMS consumers. Per month expenditure on fruits and vegetables was positively and age of the consumer was negatively related to the consumers’ choice of buying at modern retail markets. Consumers were willing to buy at modern retail outlets irrespective of the distance.

Keywords: organized retailers, consumers' attitude, consumers' preference, fruits, vegetables, multinomial logit, Bangalore

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16147 Method of Parameter Calibration for Error Term in Stochastic User Equilibrium Traffic Assignment Model

Authors: Xiang Zhang, David Rey, S. Travis Waller

Abstract:

Stochastic User Equilibrium (SUE) model is a widely used traffic assignment model in transportation planning, which is regarded more advanced than Deterministic User Equilibrium (DUE) model. However, a problem exists that the performance of the SUE model depends on its error term parameter. The objective of this paper is to propose a systematic method of determining the appropriate error term parameter value for the SUE model. First, the significance of the parameter is explored through a numerical example. Second, the parameter calibration method is developed based on the Logit-based route choice model. The calibration process is realized through multiple nonlinear regression, using sequential quadratic programming combined with least square method. Finally, case analysis is conducted to demonstrate the application of the calibration process and validate the better performance of the SUE model calibrated by the proposed method compared to the SUE models under other parameter values and the DUE model.

Keywords: parameter calibration, sequential quadratic programming, stochastic user equilibrium, traffic assignment, transportation planning

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16146 A Monte Carlo Fuzzy Logistic Regression Framework against Imbalance and Separation

Authors: Georgios Charizanos, Haydar Demirhan, Duygu Icen

Abstract:

Two of the most impactful issues in classical logistic regression are class imbalance and complete separation. These can result in model predictions heavily leaning towards the imbalanced class on the binary response variable or over-fitting issues. Fuzzy methodology offers key solutions for handling these problems. However, most studies propose the transformation of the binary responses into a continuous format limited within [0,1]. This is called the possibilistic approach within fuzzy logistic regression. Following this approach is more aligned with straightforward regression since a logit-link function is not utilized, and fuzzy probabilities are not generated. In contrast, we propose a method of fuzzifying binary response variables that allows for the use of the logit-link function; hence, a probabilistic fuzzy logistic regression model with the Monte Carlo method. The fuzzy probabilities are then classified by selecting a fuzzy threshold. Different combinations of fuzzy and crisp input, output, and coefficients are explored, aiming to understand which of these perform better under different conditions of imbalance and separation. We conduct numerical experiments using both synthetic and real datasets to demonstrate the performance of the fuzzy logistic regression framework against seven crisp machine learning methods. The proposed framework shows better performance irrespective of the degree of imbalance and presence of separation in the data, while the considered machine learning methods are significantly impacted.

Keywords: fuzzy logistic regression, fuzzy, logistic, machine learning

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16145 The Impact of the Parking Spot’ Surroundings on Charging Decision: A Data-Driven Approach

Authors: Xizhen Zhou, Yanjie Ji

Abstract:

The charging behavior of drivers provides a reference for the planning and management of charging facilities. Based on the real trajectory data of electric vehicles, this study explored the influence of the surrounding environments of the parking spot on charging decisions. The built environment, the condition of vehicles, and the nearest charging station were all considered. And the mixed binary logit model was used to capture the impact of unobserved heterogeneity. The results show that the number of fast chargers in the charging station, parking price, dwell time, and shopping services all significantly impact the charging decision, while the leisure services, scenic spots, and mileage since the last charging are opposite. Besides, factors related to unobserved heterogeneity include the number of fast chargers, parking and charging prices, residential areas, etc. The interaction effects of random parameters further illustrate the complexity of charging choice behavior. The results provide insights for planning and managing charging facilities.

Keywords: charging decision, trajectory, electric vehicle, infrastructure, mixed logit

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16144 A Study of Mode Choice Model Improvement Considering Age Grouping

Authors: Young-Hyun Seo, Hyunwoo Park, Dong-Kyu Kim, Seung-Young Kho

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The purpose of this study is providing an improved mode choice model considering parameters including age grouping of prime-aged and old age. In this study, 2010 Household Travel Survey data were used and improper samples were removed through the analysis. Chosen alternative, date of birth, mode, origin code, destination code, departure time, and arrival time are considered from Household Travel Survey. By preprocessing data, travel time, travel cost, mode, and ratio of people aged 45 to 55 years, 55 to 65 years and over 65 years were calculated. After the manipulation, the mode choice model was constructed using LIMDEP by maximum likelihood estimation. A significance test was conducted for nine parameters, three age groups for three modes. Then the test was conducted again for the mode choice model with significant parameters, travel cost variable and travel time variable. As a result of the model estimation, as the age increases, the preference for the car decreases and the preference for the bus increases. This study is meaningful in that the individual and households characteristics are applied to the aggregate model.

Keywords: age grouping, aging, mode choice model, multinomial logit model

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16143 Analysis of Awareness and Climate Change Impact in Energy Efficiency of Household Appliances

Authors: Meltem Ucal

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It is obvious that with limited resources and increasing of energy consumption from day to day, increase in amount of greenhouse gases in the atmosphere will increase risk of climate change. The objective of “Raising Awareness in Energy Efficiency of Household Appliances and Climate Change” paper is to make the connection between climate change and energy saving to be understood. First of all, research and evaluation aiming improvement of women’s behaviors of purchasing and using household appliances and also educate next generations who will be faced risks of climate change, with their mothers will be done.

Keywords: energy efficiency, climate change, wareness, household appliences, econometrics model, logit model

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16142 Predicting the Lack of GDP Growth: A Logit Model for 40 Advanced and Developing Countries

Authors: Hamidou Diallo, Marianne Guille

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This paper identifies leading triggers of deficient episodes in terms of GDP growth based on a sample of countries at different stages of development over 1994-2017. Using logit models, we build early warning systems (EWS), and our results show important differences between developing countries (DCs) and advanced economies (AEs). For AEs, the main predictors of the probability of entering in a GDP growth deficient episode are the deterioration of external imbalances and the vulnerability of fiscal position while DCs face different challenges that need to be considered. The key indicators for them are first, the low ability to pay their debts, and second, their belonging or not to a common currency area. We also build homogeneous pools of countries inside AEs and DCs. The evolution of the proportion of AE countries in the riskiest pool is marked first, by three distinct peaks just after the high-tech bubble burst, the global financial crisis, and the European sovereign debt crisis, and second by a very low minimum level in 2006 and 2007. In contrast, the situation of DCs is characterized first by the relative stability of this proportion and then by an upward trend from 2006, that can be explained by a more unfavorable socio-political environment leading to shortcomings in the fiscal consolidation.

Keywords: currency area, early warning system, external imbalances, fiscal vulnerability, GDP growth, public debt

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16141 Factors Affecting At-Grade Railway Level Crossing Accidents in Bangladesh

Authors: Armana Huq

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Railway networks have a significant role in the economy of any country. Similar to other transportation modes, many lives suffer from fatalities or injuries caused by accidents related to the railway. Railway accidents are not as common as roadway accidents yet they are more devastating and damaging than other roadway accidents. Despite that, issues related to railway accidents are not taken into consideration with significant attention as a major threat because of their less frequency compared to other accident categories perhaps. However, the Federal Railroad Administration reported nearly twelve thousand train accidents related to the railroad in the year 2014, resulting in more than eight hundred fatalities and thousands of injuries in the United States alone of which nearly one third fatalities resulted from railway crossing accidents. From an analysis of railway accident data of six years (2005-2010), it has been revealed that 344 numbers of the collision were occurred resulting 200 people dead and 443 people injured in Bangladesh. This paper includes a comprehensive overview of the railway safety situation in Bangladesh from 1998 to 2015. Each year on average, eight fatalities are reported in at-grade level crossings due to railway accidents in Bangladesh. In this paper, the number of railway accidents that occurred in Bangladesh has been presented and a fatality rate of 58.62% has been estimated as the percentage of total at-grade railway level crossing accidents. For this study, analysis of railway accidents in Bangladesh for the period 1998 to 2015 was obtained from the police reported accident database using MAAP (Microcomputer Accident Analysis Package). Investigation of the major contributing factors to the railway accidents has been performed using the Multinomial Logit model. Furthermore, hotspot analysis has been conducted using ArcGIS. Eventually, some suggestions have been provided to mitigate those accidents.

Keywords: safety, human factors, multinomial logit model, railway

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16140 Examining the Cognitive Abilities and Financial Literacy Among Street Entrepreneurs: Evidence From North-East, India

Authors: Aayushi Lyngwa, Bimal Kishore Sahoo

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The study discusses the relationship between cognitive ability and the level of education attained by the tribal street entrepreneurs on their financial literacy. It is driven by the objective of examining the effect of cognitive ability on financial ability on the one hand and determining the effect of the same on financial literacy on the other. A field experiment was conducted on 203 tribal street vendors in the north-eastern Indian state of Mizoram. This experiment's calculations are conditioned by providing each question scores like math score (cognitive ability), financial score and debt score (financial ability). After that, categories for each of the variables, like math category (math score), financial category (financial score) and debt category (debt score), are generated to run the regression model. Since the dependent variable is ordinal, an ordered logit regression model was applied. The study shows that street vendors' cognitive and financial abilities are highly correlated. It, therefore, confirms that cognitive ability positively affects the financial literacy of street vendors through the increase in attainment of educational levels. It is also found that concerning the type of street vendors, regular street vendors are more likely to have better cognitive abilities than temporary street vendors. Additionally, street vendors with more cognitive and financial abilities gained better monthly profits and performed habits of bookkeeping. The study attempts to draw a particular focus on a set-up which is economically and socially marginalized in the Indian economy. Its finding contributes to understanding financial literacy in an understudied area and provides policy implications through inclusive financial systems solutions in an economy limited to tribal street vendors.

Keywords: financial literacy, education, street entrepreneurs, tribals, cognitive ability, financial ability, ordered logit regression.

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16139 Household's Willingness to Pay for Safe Non-Timber Forest Products at Morikouali-Ye Community Forest in Cameroon

Authors: Eke Balla Sophie Michelle

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Forest provides a wide range of environmental goods and services among which, biodiversity or consumption goods and constitute public goods. Despite the importance of non-timber forest products (NTFPs) in sustaining livelihood and poverty smoothening in rural communities, they are highly depleted and poorly conserved. Yokadouma is a town where NTFPs is a renewable resource in active exploitation. It has been found that such exploitation is done in the same conditions as other localities that have experienced a rapid depletion of their NTFPs in destination to cities across Cameroon, Central Africa, and overseas. Given these realities, it is necessary to access the consequences of this overexploitation through negative effects on both the population and the environment. Therefore, to enhance participatory conservation initiatives, this study determines the household’s willingness to pay in community forest (CF) of Morikouali-ye, eastern region of Cameroon, for sustainable exploitation of NTFPs using contingent valuation method (CVM) through two approaches, one parametric (Logit model) and the other non-parametric (estimator of the Turnbull lower bound). The results indicate that five species are the most collected in the study area: Irvingia gabonensis, the Ricinodendron heudelotii, Gnetum, the Jujube and bark, their sale contributes significantly to 41 % of total household income. The average willingness to pay through the Logit model and the Turnbull estimator is 6845.2861 FCFA and 4940 FCFA respectively per household per year with a social cost of degradation estimated at 3237820.3253 FCFA years. The probability to pay increases with income, gender, number of women in the household, age, the commercial activity of NTFPs and decreases with the concept of sustainable development.

Keywords: non timber forest product, contingent valuation method, willingness to pay, sustainable development

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16138 Determinant Factor of Farm Household Fruit Tree Planting: The Case of Habru Woreda, North Wollo

Authors: Getamesay Kassaye Dimru

Abstract:

The cultivation of fruit tree in degraded areas has two-fold importance. Firstly, it improves food availability and income, and secondly, it promotes the conservation of soil and water improving, in turn, the productivity of the land. The main objectives of this study are to identify the determinant of farmer's fruit trees plantation decision and to major fruit production challenges and opportunities of the study area. The analysis was made using primary data collected from 60 sample household selected randomly from the study area in 2016. The primary data was supplemented by data collected from a key informant. In addition to the descriptive statistics and statistical tests (Chi-square test and t-test), a logit model was employed to identify the determinant of fruit tree plantation decision. Drought, pest incidence, land degradation, lack of input, lack of capital and irrigation schemes maintenance, lack of misuse of irrigation water and limited agricultural personnel are the major production constraints identified. The opportunities that need to further exploited are better access to irrigation, main road access, endowment of preferred guava variety, experience of farmers, and proximity of the study area to research center. The result of logit model shows that from different factors hypothesized to determine fruit tree plantation decision, age of the household head accesses to market and perception of farmers about fruits' disease and pest resistance are found to be significant. The result has revealed important implications for the promotion of fruit production for both land degradation control and rehabilitation and increasing the livelihood of farming households.

Keywords: degradation, fruit, irrigation, pest

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16137 Smallholder Participation in Organized Retail Markets: Evidence from India

Authors: Kedar Vishnu, Parmod Kumar

Abstract:

India is becoming most favored retail destination in the world. The organized retail has presented many opportunities to farmers to increase income by shifting cropping pattern from food grains to commercial crops. Previous research revealed potential benefits for farmers by supplying fruits and vegetables to organized retail channels. However the supply of fruits and vegetables from small and marginal farmers remain low than expected. The main objective of this paper is to identify the factors determining market participation of smallholder farmers in modern organized retail chains. Attempt is also made to find out factors influencing the choice of participation in particular organized retail collection centers as compared to other organized retail. The paper was based on primary survey of 40 Beans and Tomato farmers who supply to organized retail collection centers from Karnataka, India. Multiple regression technique is used to identify the factors determining quantity sold at collection centers. The regression result, show that area under vegetables, yield, and price from modern collection center and having access to technical help were found significantly affecting quantity sold into modern organized retail channels. On the opposite, increased rejection rates and vegetable prices at APMC were found influencing farmers decision into the reverse side. Empirical result of the multinomial logit model show that Reliance fresh has tendency to prefer large farmers who can supply more quality and better quantity compared with TESCO and More collection centers. The negative sign of area, having access to technical help, transportation cost, and number of bore wells led to higher probability of farmers to participate in Reliance Fresh collection centers as compared with More and TESCO.

Keywords: fruits, vegetables, organized retail markets, multinomial logit model

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16136 Accessibility of Institutional Credit and Its Impact on Agricultural Output: A Case Study

Authors: Showkat Ahmad Bhat, M. S. Bhatt

Abstract:

The study evaluates the ex-post impact of institutional credit on agricultural output. It first examines the key factors that influence the accessibility of institutional credit by farm households. For quantitative analysis both program participant and non-participant respondents were drawn and cross-sectional survey data were collected from 412 households in Pulwama District of Jammu & Kashmir (India). Propensity Score Matching Method was employed to analyze the impact of the institutional credit on agricultural output. Results show that institutional credit has a positive and significant impact on the agricultural output measured in terms of farm income and crop productivity. To estimate the accessibility of credit, an examination of both demand side and supply side factors were carried out. The demand for credit was measured with respect to respondents who applied for credit. Supply side credit allocation measured in terms of the proportion of ‘credit amount’ farmers obtained. Logit and Two-limit Tobit Regression Models were used to investigate the determinants that influence the accessibility of formal credit for Demand for and supply of credit respectively. The estimated results suggested that the demand for credit is positively and significantly affected by the factors such as: age of the household head, formal education, membership, cash crop grown, farm size and saving account. All the variables were found significantly increasing the household’s likelihood to demand for and supply of credit from banks. However, the impact of these factors varies considerably across the credit markets. Factors which were found negatively and significantly influencing the accessibility of credit were: ‘square of the age’, household assets and rate of interest. The credit constraints analysis suggested that square of the age; household assets and rate of interest were the three most important factors that increased the probability of being constrained. The study finally discusses these results in detail and draws some recommendations.

Keywords: institutional credit, agriculture, propensity score matching logit model, Tobit model

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16135 Modeling Default Probabilities of the Chosen Czech Banks in the Time of the Financial Crisis

Authors: Petr Gurný

Abstract:

One of the most important tasks in the risk management is the correct determination of probability of default (PD) of particular financial subjects. In this paper a possibility of determination of financial institution’s PD according to the credit-scoring models is discussed. The paper is divided into the two parts. The first part is devoted to the estimation of the three different models (based on the linear discriminant analysis, logit regression and probit regression) from the sample of almost three hundred US commercial banks. Afterwards these models are compared and verified on the control sample with the view to choose the best one. The second part of the paper is aimed at the application of the chosen model on the portfolio of three key Czech banks to estimate their present financial stability. However, it is not less important to be able to estimate the evolution of PD in the future. For this reason, the second task in this paper is to estimate the probability distribution of the future PD for the Czech banks. So, there are sampled randomly the values of particular indicators and estimated the PDs’ distribution, while it’s assumed that the indicators are distributed according to the multidimensional subordinated Lévy model (Variance Gamma model and Normal Inverse Gaussian model, particularly). Although the obtained results show that all banks are relatively healthy, there is still high chance that “a financial crisis” will occur, at least in terms of probability. This is indicated by estimation of the various quantiles in the estimated distributions. Finally, it should be noted that the applicability of the estimated model (with respect to the used data) is limited to the recessionary phase of the financial market.

Keywords: credit-scoring models, multidimensional subordinated Lévy model, probability of default

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16134 E-Consumers’ Attribute Non-Attendance Switching Behavior: Effect of Providing Information on Attributes

Authors: Leonard Maaya, Michel Meulders, Martina Vandebroek

Abstract:

Discrete Choice Experiments (DCE) are used to investigate how product attributes affect decision-makers’ choices. In DCEs, choice situations consisting of several alternatives are presented from which choice-makers select the preferred alternative. Standard multinomial logit models based on random utility theory can be used to estimate the utilities for the attributes. The overarching principle in these models is that respondents understand and use all the attributes when making choices. However, studies suggest that respondents sometimes ignore some attributes (commonly referred to as Attribute Non-Attendance/ANA). The choice modeling literature presents ANA as a static process, i.e., respondents’ ANA behavior does not change throughout the experiment. However, respondents may ignore attributes due to changing factors like availability of information on attributes, learning/fatigue in experiments, etc. We develop a dynamic mixture latent Markov model to model changes in ANA when information on attributes is provided. The model is illustrated on e-consumers’ webshop choices. The results indicate that the dynamic ANA model describes the behavioral changes better than modeling the impact of information using changes in parameters. Further, we find that providing information on attributes leads to an increase in the attendance probabilities for the investigated attributes.

Keywords: choice models, discrete choice experiments, dynamic models, e-commerce, statistical modeling

Procedia PDF Downloads 97