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Determinants of Primary school dropout in Chitwan and Nawalparasi
(Faculty of Statistics, 2012) Manandhar, Naresh
Nepal’s school education is structured as early childhood development (ECD)/ pre-primary level (PPC), primary level, lower secondary, secondary and higher secondary education.Primary level provides five years of education to the 5-9 years of school-going age children andconsists of five grades I-V.The primary school dropout is defined as “any student who leaves school for any reason before graduation or completion of a program of studies without transferring to another elementary or secondary school.” The objective of research is to find out the causes of dropout in primary schools of the study districts. The null hypotheses based on objectives are there is no significant difference between the primary school dropout children of boys and girls,at various grades andgovernment andprivate school. A cross-sectional tracer design study was conducted in 30 sampled schools of Chitwanand Nawalparasi districts.The pre-designed questionnaire was used for interview method tocollect information about dropout and studying children from one of the parent. The interviewed were taken from one of parents of 101 and 109 actual dropout children respectively from Chitwan and Nawalparasi districts.To fit the logistic regression model,250 parents of studying children were selected by using stratified random sampling and the interviews were taken. The highest actual dropout rate was found to be 6.69 percent in grade I and followed by5.24percent, 3.66 percent, 2.48 percent and 3.66 percent in grades II, III, IV and V respectively.The dropout rate for girl (4.04%) was less than boys (4.50%). The boys (52.6%) were more dropped out than girls (47.6%).The overall primary school dropout rate was found to be 4.26 percent in these study districts. The mean age of primary school dropout children is 8.74 years with standard deviation of 2.021 years.Dalit caste comprised of around 30.5 percent of dropped out children and they have higher chances of dropped out. The majority (73.3%) of dropout children were found to be Hindu by religion followed by Buddhist (21.4%) and Muslim and others (5.2%).The maximum (42.2%) of the actual dropout was due to illiteracy and negligenceof parents in the education of their children. Other causes of dropout were household work(38.5%) and poor economic status of parents (26.6%). Education status of the father plays animportant role in children education and if he is illiterate the chances of dropout is very high. Fromlogistic regression analysis of child related variables, grade, age and work at homewere found to be significant variable and among family related variables, parent’s apathy towards their children education, education status of father, education status of mother,occupation status of father and number of children in family were found to be significant. Government of Nepal should make the provision of automatic upgradation at primary grades so that any child will not dropout due to failure in examination or repetition. Decreasingthe dropout rate requires attraction for dropped out children,active participation of parents, local communities and government working in conjunction with one another.
The Impact of Socio-Economic and Demographic Variables on Maternal Health Behavior: A Statistical Approach
(Department of Statistics, 2014) Shrestha, Gauri
Available with full text
Impact of tourism in socio-economic development of nepal: A multivariate approach
(Faculty of Statistics, 2018) Dhakal, Basanta Kumar
Tourism being one of the major foreign exchange earnings and job providing sectors in local level is a growing service industry in Nepal. It significantly plays an important role in social and economic development of nation. Keeping in view of this reality, the objectives of this study are to examine the relationship between tourism benefits towards economic development process of the nation by using VEC model, to assess the residents’ attitudes towards economic impact of tourism in Nepal, and to assess the residents’ perceptions towards social impact of tourism in Nepal using EFA. This study is an attempt to apply different statistical methods/ models using two different sets of data namely secondary time series data and primary data. Vector error correction (VEC) model has been applied to analyze the secondary data from the period of 1990/91 to 2014/15 tourism data of Nepal provided by Ministry of Tourism and Civil Aviation for examining the relationship between tourism benefits towards economic development process of the nation. For analyzing the residents’ attitudes and perceptions towards economic and social impacts of tourism respectively, Exploratory Factor Analysis (EFA) has been used based on primary data through face to face field survey of 601 respondents from three tourist destinations with response rate 91.76%. A set of questionnaire was developed to collect the data, and the respondents’ level of agreement has been measured by five point Likert scale. In order to investigate the long run relationship, VEC model has been used, and it indicated that the role of average length of stay towards increasing GDP is greater than number of international tourist arrival in Nepal. The results of Granger causality analysis have also illustrated that the increasing average length of stay of tourist plays positive role to increase GDP and vice versa (p value <0.001) and large number of international tourist plays the affirmative role to increase their average length of stay (p value <0.001). Similarly, in order to look into Nepal's foreign exchange earnings through tourism with an analysis of the international tourists’ arrival and the duration they spent in Nepal. The empirical result from the VEC model has concluded that the role of average length of stay towards increasing earnings from tourism is greater than number of international tourist. The findings from Granger causality analysis have also demonstrated the large number of international tourist and their average length of stay play positive role to increase foreign exchange earnings (p value <0.001). Similarly, the large number of international tourist plays the affirmative position to expand their average length of stay and vice versa (p value <0.001). Likewise, in order to explore long run relationship between number of international visitors and their length of stay towards their average expenditure in Nepal, the result of VEC model has indicated that the role of average length of stay towards increasing expenditure per tourist is greater than number of international tourists’ arrivals in Nepal. The results of Granger causality analysis have depicted that the increasing average length of stay of tourist takes part in affirmative position to increase expenditure of visitor and vice versa (p value <0.001). The large number of international tourist plays the positive role to increase their average length of stay (p value <0.001). In order to examine long run relationship of foreign exchange earnings from tourism and average expenditure of international tourists towards share of GDP of Nepalese tourism, the result of VEC model has shown that the role of average expenditure per visitor towards increasing GDP is greater than foreign exchange earnings from tourism. The results of Granger causality analysis have also depicted that increasing expenditure per visitor plays positive role to increase GDP and vice versa (p value <0.001). Similarly, foreign exchange earnings also facilitate the expansion of GDP (p value <0.001). The EFA found that 67.84% total variance has been explained by positive economic factors of tourism and 59.39% total variance has been explained by negative economic factors of tourism illustrating both positive and negative impacts of tourism from the respondents. Tourism, apart from being perceived as an economic factor, is also a social component and it prevails subjectively and intangibly in the community. It is found that 56.3% total variance has been explained by positive social factors of tourism and 60.4% total variance has been explained by negative social factors of tourism indicating the both negative and positive perceptions towards social impacts of tourism from respondents. It shows that tourism industries of Nepal are not still well planed and controlled but it has great potentiality for further development. So, effort should pay critical and sustained attention towards promoting cultural and natural resources, improving the infrastructure of tourism industry and employing the tourism marketing skills to optimize the economic benefits and social betterment for the quality of life of people through the tourism development.
Impacts of Pilgrimage Tourism for Sustainable Tourism Development: Special Focus on Lumbini
(Faculty of Statistics, 2013) Ghimire, Him Lal
The history of modern tourism is not as old as pilgrimage tourism- the oldest concept or original art of traveling. Pilgrimage to the sacred and holy sites induced modern tourism. The origin and evolution of the tirtha yatra(pilgrimage) tradition of Hindus seems to be as old as their civilizationor perhaps older than that. Nepal has become a decent destination for pilgrimage tourism with her large number of Hindu and Buddhist pilgrimage sites, shrines and temples. However, the stakeholders were not able to address the importance of Lumbini and develop in a professional ways. Today, Lumbini can be considered as a synonym of world peace center and a top class pilgrimage destination in the world. Lumbini Master Plan was a very ambitious plan for the overall development of Lumbini. However, the incompletion of the plan on time has been a great problem to develop tourism in Lumbini. Tourist arrivals in Lumbini has been fluctuated and affected by several reasons. Mega events in Lumbini have been helping to attract more tourists and enhance the Lumbini's status in the international market. Majority of the tourist visit Lumbini in a group. However, usually larger group of tourists/pilgrims make very short visit in Lumbini when they come via India. They are same day visitors and if Nepal can stop them at least for one day, it will have great impact in economy and employment. Beside pilgrimage purpose, Lumbini can be the attractive destination for the extra- religious activities such as sightseeing, cultural, historical. Nepal's share was very negligible with(0.06%) in tourist arrival in the world total in 2010.It is crucial to obtain accurate estimates of the uncertainty surrounding monthly international tourist arrivals based on time series data. The data series were analyzed in terms of the number of tourist arrivals, the corresponding logarithms, annual differences and log-differences in this research. It was argued that the preferred series to model the monthly tourist arrivals was one which has a distribution closer to a normal distribution. The monthly tourist arrivals levels depictedvery high coefficient of variation (CV) for the 11 tourist source countries. Likewise, monthly tourist arrivals to Nepal showed very strong seasonal patterns. Estimates of the conditional mean for the GARCH(1, 1) model for the level, logarithm, annual difference and log difference were obtained through a modeling procedure in which only significant variables were included until a parsimonious specification is achieved. The ten years armed conflict of Nepal (1997-2006)made clear that the devastatingimpacts such as loss of lives,damage of infrastructure, loss of livelihoods and an uncertainfuture in Nepal.After 2006 movement and peace process also did not solve the problem of continuous instability, and poor security situation of the country which has been affecting tourism badly. 10 th national plan for tourism development had expected US $ 60 per touristper day income from tourists in 2006 where as the data shows US $ 55.0 per tourist per day in reality in 2006. The datashows that income per tourist per day is US$ 43.2, gross foreign currency earning in convertible currency is US$ 329.98 millions and length of stay is 12.67 days. Increase in per day income and length of stay can contribute significantly in economy and employment. This research demonstrates that Lumbini is the world top class destination, its development and sustainability can worth a lot economically for the country like Nepal. In a time of increasing competition and uncertainty in the tourism, stakeholders should explore many different avenues for sustainability within the sector.
Nutritional Status among Under Five Children and Their Mothers with Gender Perspective
(Central Department of Statistics, 2012) Pradhan, Amita
Survey results since 1975 in Nepal do not ascertain favorable situation of nutrition among children under five years of age as indicated by the percent of children with stunting, wasting and underweight. National Family Health Survey (NFHS), 1996 revealed that 54.8% were stunted, 12.7% were wasted and 54.2% were underweight. Nepal Micronutrient Status Survey, 1998 displayed that 54% of children in Nepal were stunted and 47% underweight. The first national nutritional survey in 1975 also exhibited similar findings of 48.1% stunted, 2.8% wasted and 50% underweight. The data suggest that there is no enhancement in the nutritional status in the country during this time span. Nepal Demographic and Health Survey 2001 revealed the percent prevalence for underweight and wasted children of under five years of age as 48.3% and 9.6% and about 50% of these children showed stunting. Similarly, NDHS 2006 reveals that the percent prevalence for underweight and wasted children of under five years of age are 39% and 13%. Forty nine percent of the children under five years of age are stunted. To overcome the problem of malnutrition, the factors associated with nutrition needs to be studied. Many studies show that wealth status of household, size of the child at the birth, educational status of mothers and mother’s autonomy are related with her own and her child’s nutrition. This study was intended to determine percent prevalence of nutritional status as indicated by percent of normal children and percent of underweight, stunted and wasted children as well as percent of mothers with normal and low body mass index. This study also tried to explore the factors associated with nutrition among children under five years of age and the mothers. There are many indicators of gender status and while analyzing the data, some of the variables related to status of women such as woman’s educational status, employment status, working hour per day, decision making ability, contraceptive use and media exposure etc. were tried to link with nutrition of children and women themselves. This was an observational study carried out in Kathmandu district. This study also used the secondary data of Nepal Demographic and Health Survey, 2006 for the enrichment of the scope of the study to whole Nepal. The primary data were collected from Kathmandu district. The proportional allocation of households from different VDCs and municipalities was insured. The households were selected by spinning a bottle at different junctions in survey area. The sample size calculated was 454 children. The primary data was collected by interviewing the mothers. The anthropometry for under-5 years and their mothers were collected by using weighing machine, Sakir’s tape and measuring tape. STATA 9, PHSTAT2, Growth analyzer 3.5, Epi Info 2000, Microsoft Excel 2007, SPSS 13 and SPSS 17 were used for analysis. Necessary tables, chi square test (exact test where applicable),z test for proportion, Kruskal Wallis test, ANOVA, ordinal regression, MANCOVA, LMS method for smoothing growth centile curve and chi square test of goodness of fit were used in the process of data analysis. The percent of children with stunting, underweight and wasting was found as 58.8%, 34.4% and 14.6% respectively as per present study. Ordinal regression came out as suitable method for nutrition data. Wherever required assumption for ordinal regression failed, partial proportional odds model was a good substitute. Alternative gamma parameterization results were observed in line to partial proportional odds model. MANOVA analysis could not hold required assumption in this data set. Household wealth, area of residence, size at birth, education of mothers was found to impact the nutrition of children. Moreover, employment status of the mothers showed effects on child’s height. Furthermore, mothers’ exposure to mass media emerged as significant predictor for underweight. Female children showed substantial risk of being underweight. Likewise, exclusive breastfeeding resulted into better MUAC facet. Media exposure showed positive blow on nutrition of women and higher number of children to the woman indicated negative agreement with her BMI. The growth charts did not resemble marked gender differences in its mold. The fiftieth centile comparison with CDC 2000 charts indicated lower height for age assessment for NDHS and Kathmandu data. Overlapping fiftieth centiles of Kathmandu with CDC 2000 charts which were elevated than NDHS were observed for weight for age. Looking at these insights, it could be concluded that at one hand wealth status of the household was important in defining the nutrition of the children and at the other hand size of the child at birth and education of the mothers, employment status of the mothers played effective role. Here the important notion is that size at birth is linked with mother’s nutrition during pregnancy. Employment and education may contribute to gain autonomy among the mothers which would be reflecting in household resource allocation resulting into more allocation in nutritious food. Key words: BMI, Nutrition, Height for Age, Weight for Age, Weight for Height
Optimizing multiple regression model for rice production forecasting in Nepal
(Institute of Science and Technology, Statistics, 2015) Dhakal, Chuda Prasad
This research, testing the possibility of use of probable predictors, has optimized multiple regression model to be used for rice production forecasting in Nepal. Fifty years (1961-2010) time series data were divided into training sample (a sample which is used to build the model) (n=35), and test sample size of 15 through which the built model was cross validated for its reliability in forecasting. This research has explored and used all the underlying principles of linear regression model building and its application in forecasting the production, mainly crop production such as rice. The model sustained with the three principle predictors: harvested area, rural population and price at harvest whereas these variables could explain 93% variation in production; the forecast variable. The model as such was parsimonious and as well the good fit with minimal (5%) mean absolute percentage error in its forecast. It therefore, for this fit, was concluded that multiple regression model could be scientifically used in forecasting, and the concerned stakeholders could thus be benefited from the this model especially for the enhanced ease, and efficiency for rice production forecasting to be used for planning purpose at national level. Future work might consider to increase the precision of the model in any aspects like making it more parsimonious and reliable than which have been purposed in this study.
Risk Factors Affecting Poverty in Nepal: Statistical Modeling Approach
(Institute of Science & Technology, 2023-07) Acharya, Krishna Prasad
Poverty is one of the main problems of developing countries, like Nepal and its reduction is a central issue. The identification of its determinants to reduce the monetary poverty is one of the key issues. According to previous studies, log-binomial regression model (LBRM) is a good option to logistic regression model (LRM) for common outcomes, mostly used in the analysis of clinical and epidemiological data. However, the use of LBRM and the comparison with LRM for data on poverty has not been discussed yet. The objectives of this study are to identify the important risk factors, to compare the LRM and LBRM in identifying the risk factors and estimating their effects on poverty in Nepal, and to assess the stability of the model through bootstrapping method. The data used for the analysis is the cross-sectional household level data (n = 5988) of Nepal Living Standard Survey 2010/11. All the data required for this study are not available in the provided household level data file of 5,988 households but are available in the individual level data file of 28,670 individuals. The individual level data are converted into household level data in order to generate the data on a number of variables, and merged into the main data file. With the support of rigorous review of literature and the availability of the variables in the dataset, seven possible independent variables have been considered for both the LRM and LBRM. They are: sex of household head (female / male), literacy status of household head (illiterate / literate), status of remittance recipient of household (no / yes), status of land ownership (no / yes), household with access to nearest market center (poor / better), number of children under 15 years (more than two / at most two), and number of literate members of working age population (WAP) (none / at least one). The response variable is household poverty (poor / non-poor). Implementing the stepwise forward and backward selection procedure with all these seven variables for the development of each final multiple regression model, only six variables except sex of household head has come out statistically significant at 5% level of significance. The LRM has yielded the odds ratio (OR) and LBRM has yielded risk ratio (RR) with 95% confidence interval estimate (CIE) for each covariate. Diagnostics of the model, the goodness of fit test, a risk assessment based on the presence of variables, and the stability of each model has been carried out. The classification and discrimination of the LRM has been also assessed. LRM and LBRM have been compared with respect to different criteria such as selection of covariates, effect size and its precision. The model's good fit test using and test of model's diagnostics criteria has also been compared. Further, the comparisons have also been made in risk assessment on the bais of factors present in the model, stability of the model and convergence failure problem. The effect size in terms of OR and in RR of six factors in each final model namely illiterate household head (OR: 2.20, 95% CIE: 1.86 – 2.61, p < 0.001; RR: 1.68, 95% CIE: 1.49 – 1.89, p < 0.001), remittance non recipient household (OR: 1.90, 95% CIE: 1.64 – 2.20, p < 0.001; RR: 1.45, 95% CIE: 1.33 – 1.59, p < 0.001), household with no land holdings (OR: 1.53, 95% CIE: 1.31 – 1.78, p < 0.001; RR: 1.22, 95% CIE: 1.11 – 1.34, p < 0.001), household with poor access to market center (OR: 1.77, 95% CIE: 1.52 – 2.07, p < 0.001; RR: 1.51, 95% CIE: 1.34 – 1.69, p < 0.001), household having > 2 children aged under 15 (OR: 4.69, 95% CIE: 4.06 – 5.42, p < 0.001; RR: 2.96, 95% CIE: 2.66 – 3.28, p < 0.001) and household not having literate members of WAP (OR: 1.29, 95% CIE: 1.07 – 1.56, p < 0.001; RR: 1.16, 95% CIE: 1.05 – 1.29, p < 0.001) are significantly associated with the likelihood of poverty. For each covariate, the OR is overestimated than that of RR. There is narrower 95% CIE of RR than that of OR for each covariate. It shows that RR is more precise than OR. Greater elevation in risk in LRM compared to LBRM varies from 13% to 173%. In each model, there is no convergence issues have been countered, where both the models are equally stable as assessed by bootstrapping procedure. Almost all variables are repeated 100% times among 1000 times repetition. The visual assessments of diagnostics of each model are reasonably satisfactory. There is considerable acceptable discrimination of LRM (AUC: 0.78) and model correct classification values of 67.15%. The good fit of the model is satisfied by LRM [ with 8 d.f.= 6.05, p = 0.53] but not satisfied by LBRM [ with 8 d.f.= 28.60, p = 0.0004]. Since the LRM satisfied the majority of requirements of model performance instead of some limitations, this model seems to be better than the LBRM for this data set. Nevertheless, the LBRM is an option for the LRM since it has better accuracy and avoids overestimating effect size. The findings of this study are expected to be useful for researchers and policy makers in the relevant field.

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