Household Poverty Levels Research Articles

Unveiling the influence of reproductive health on poverty: a cross-sectional study in Magwi County, South Sudan

Objective: To understand the relationship between household poverty and reproductive health characteristics in Magwi County, South Sudan. Background: Household poverty is a significant issue in many countries, including South Sudan. Poverty has been identified as a major obstacle to international development, affecting various aspects of development goals such as food security and health. Despite interventions by organizations like the World Bank, poverty rates in beneficiary countries like South Sudan have not seen significant reductions, suggesting the presence of predictors of poverty from behavioral, structural, and political origins. Methods: The study was conducted using an analytical cross-sectional survey design. The study targeted female and male spouses in households and employed a multistage sampling approach to select participants. Result: The results of the study revealed that the level of household poverty in Magwi County was 42%. The prevalence of household poverty was found to be influenced by reproductive health characteristics. The use of short-acting contraception by women was associated with a higher prevalence of poverty, whereas women who had ever aborted a pregnancy had a lower prevalence of poverty. Unintended pregnancy and inconsistent condom use by men were also associated with higher poverty rates, whereas men with only one sexual partner had lower poverty rates. Conclusion: This study provides valuable insights into the relationship between household reproductive health characteristics and poverty in Magwi County, South Sudan. It emphasizes the need for comprehensive approaches that address both behavioral and structural factors to effectively reduce poverty and improve development outcomes.

Analyzing Exchange Rate Effects on Trade: Empirical Evidence

In this study, we aimed to find a fair exchange rate for Egypt, exploring how exchange rate policies affect the country’s economic growth and food security. We also sought to answer an important question for Egyptian policymakers: “Do current exchange rate policies help reduce Egypt’s trade deficit?”. We used two methods in our research: First, we applied the purchasing power parity (PPP) method to determine the equilibrium real exchange rate (ERER). Then, we combined the computable general equilibrium model (CGE) with the ERER value from the PPP method to observe how different sectors interact with the overall economy and understand how household incomes and poverty levels are related. Our findings showed that the fair exchange rate is EGP 38.5 per US dollar, according to the PPP method. This new exchange rate may significantly impact the Egyptian economy. Some impacts are positive, such as better real GDP, more exports, and fewer imports; however, these are minor and not significant. On the downside, it may lead to higher inflation, increased prices for goods, and reduced consumption. Moreover, this study highlights the importance of having balanced exchange rate policies that consider Egypt’s unique economic situations, and challenges and align with other economic policies. Experience and reality have shown that exchange rates alone are not the only solution.

Abstract 26: Types of Adverse Childhood Experiences and Association With Sleep Duration in Children: Analysis of 2020-2021 National Survey of Children’s Health

Background: The number of adverse childhood experiences (ACEs) is associated with suboptimal sleep duration in children; however, the differential association of types of ACEs with sleep duration in youth is unknown. Given the known associations of both ACEs and sleep duration with cardiovascular health, such an investigation will provide insights for targeted clinical intervention. Objective: We investigated the most frequently reported ACE types and the association between each type of ACE and sleep duration among U.S. children aged 6-17 years. Methods: We used data from the 2020-2021 National Survey of Children’s Health, the most recent publicly available dataset. Parents or guardians were asked whether their child had ever experienced ten different types of ACEs. Multinomial logistic regression was used to assess the association of sleep duration with each of ACEs. We used the American Heart Association (AHA) Life Essential 8 scoring algorithm to calculate scores for sleep duration (range 0 [lowest] to 100 [highest]). Participants were categorized into three subgroups: (1) meeting age-appropriate optimal sleep duration; (2) ≥1-<2 hour below or ≥ 1 hour above optimal sleep duration; and (3) ≥ 2 hours below optimal sleep duration. Analyses controlled for child’s sex, age, race/ethnicity, household poverty level, regular bedtime, physical activity, and caregiver’s level of education. Results: Parental divorce was the most frequently reported ACE (28.1%) followed by financial hardship (12.9%) and drug abuse (10.1%) among U.S. children aged 6 to 17 years. Adjusting for covariates, 5 of 10 ACEs (parental divorce, parental imprisonment, domestic violence, living with someone who had a problem with alcohol or drugs, unfair treatment because of their sexual orientation or gender identity) were significantly associated with suboptimal sleep category 2. All 10 ACEs were significantly associated with suboptimal sleep category 3. Conclusions: These findings support that ACE type is differentially associated with suboptimal childhood sleep duration and suggests that certain traumatic events experienced during childhood could amplify the adverse effects of poor sleep on cardiovascular health. Healthcare providers should consider screening for ACE type concurrent with sleep duration to better understand aspects contributing to cardiovascular health in childhood.

Exploring drivers of unsafe disposal of child stool in India using hierarchical regression model.

Disposal of children's stools is often neglected in Indian sanitation programs, putting them at higher risk of diseases transmitted through the fecal-oral route. Therefore, the current study aims to identify the socioeconomic and demographic factors associated with the unsafe disposal of child stool in India and to estimate the geographical variation in unsafe disposal. The study used 78,074 births under two years from the fifth round of the National Family Health Survey (2019-21). Descriptive statistics, bivariate analysis with the chi-square test, and a four-level hierarchical logistic regression model were applied to accomplish the study objectives. Findings revealed a 61.3% prevalence of unsafe stool disposal nationwide, significantly varying between rural (45%) and urban (67%) areas. Multilevel logistic regression highlighted that mother's education, wealth quintile, and sanitation facility were significant predictors of unsafe disposal of child stools. Random intercept statistics revealed a substantial geographical unit-level variance in unsafe stool practice in India. The study emphasizes the widespread unsafe disposal of child stool among Indian mothers with young children below two years, and the study underscores a range of contributing factors, including education, media exposure, prosperity, water availability, and sanitation. It also accentuates the significance of the geographical variance in the unsafe disposal of child stool in India, particularly at the household level, followed by the community level. Hence, the findings underscore the importance of focused interventions, including targeted household-level poverty alleviation programs, initiatives to enhance sanitation and water facilities, and community-level public health awareness programs.

Female-headed household characteristics and poverty levels in Namibia: An ordinal probit analysis of the 2015/16 Namibia Household Income and Expenditure Survey

Poverty incidence in Namibia is higher amongst female-headed households (46%) compared to male-headed households (41%). However, this situation is further worsened by females in households increasingly being forced to play multiple, conflicting roles after losing their spouses, and to work in marginal, part-time, informal and low-income jobs due to their lack of access to high-paying jobs, while having to take care of children, siblings and sometimes parents with no form(s) of assistance. In this study, a cross-sectional quantitative study design of the 2015/16 NHIES and an ordinal probit model was used to examine the household characteristics that contribute to poverty among female-headed households in Namibia, as well as their effects on the households’ poverty levels. Results from this study showed that characteristics such as region (p<0.001), main language spoken at home (p<0.001), main source of income (p=0.009), location (p=0.016), and highest level of education (p=0.005) had significant associations with the household poverty levels. Additionally, female-headed households in the urban areas in the Hardap, Otjozondjupa and Zambezi regions, whose main languages spoken were English, German, Zambezi and other languages, with tertiary education and main source of income from commercial farming and other sources were less likely to be severely poor and more likely to be not-poor. Therefore, it is recommended that the Namibian government and policymakers further improve the livelihood of women, especially those heading households in other regions, in terms of a comprehensive social development strategy that covers the immediate needs for short-term and long-term needs of these women.

Understanding 24-hour movement guideline adherence and links to school achievement, social-behavioural problems, and emotional functioning among children and adolescents with learning disabilities

ABSTRACTThis cross-sectional study examined the associations between adherence to 24-hour movement behaviour (24-HMB) guidelines and indicators of school achievement, social-behavioural problems, and emotional functioning among a nationally representative sample of US children and adolescents with learning disabilities (LD). Data were retrieved from the 2020–2021 National Survey of Children's Health (NSCH), including 4999 children and adolescents (aged between 6 and 17 years) with LD. Multivariate logistic regressions were conducted to estimate odds ratios (OR) with 95% confidence intervals (95%CI), adherence to 24-HMB guidelines was considered as independent variables (Model 1: continuous variable; Model 2: categorical variable), and indicators of school achievement, social-behavioural problems, and emotional functioning as dependent variables. Covariates included age, sex, race, overweight status, the severity of learning disability, educational intervention, parental education, and household poverty level. Overall, 2156 participants (41.47%) met one of the three 24-HMB recommendations, 1289 (26.04%) met two 24-HMB recommendations, and 336 participants (6.62%) met all three 24-HMB recommendations. Positive associations between adherence to 24-HMB guidelines and most of the assessed outcomes were observed. Those who adhered to at least two of the three 24-HMB guidelines (PA + SL, PA + ST, SL + ST, and PA + SL + ST) had better school achievement and fewer social-behavioural problems. Additionally, adherence to PA + SL or SL + ST guidelines was linked with improved emotional functioning. This study provides evidence that adherence to 24-HMB guidelines is associated with superior school achievement, social-behavioural problems, and emotional function, and thus suggests future public health efforts should promote adequate levels of PA, limited ST, and sufficient SL among children and adolescents with LD.

Epidemiology of Current Asthma in Children Under 18: A Two-Decade Overview Using National Center for Health Statistics (NCHS) Data.

This study conducted a comprehensive two-decade analysis of current asthma among children under 18 in the United States using National Center for Health Statistics (NCHS) data. The primary objective was to assess the prevalence of current asthma, evaluate temporal trends, and identify disparities based on gender, age, insurance status, household poverty levels, and race/ethnicity. Data spanning 2003-2019 from NCHS were analyzed, focusing on current asthma prevalence among children under 18. Age-adjusted prevalence rates were calculated and stratified by various factors, including gender, age groups, health insurance status, poverty levels, and race/ethnicity. The study revealed substantial disparities in current asthma prevalence. Over the two-decade period, the overall prevalence of current asthma fluctuated. It increased from 2003 (8.5%) to 2009 (9.6%) and then decreased by 2019 (7.0%). Gender disparities were evident, with males (9.9%) consistently reporting a higher prevalence than females (7.5%). Older children aged between 10-17 years (10.4%) consistently had a higher prevalence of asthma than younger children aged 0-4 (5.3%) and 5-9 years (9.5%). Children with Medicaid insurance (11.2%) had the highest prevalence, followed by insured (8.9%), privately insured (7.7%), and uninsured children (6.1%). Children living below the federal poverty level (FPL) consistently reported the highest prevalence (11.3%), while children above 400% of the FPL (7.1%) had the lowest prevalence. Racial disparities were observed, with Black children (14.3%) having higher asthma prevalence, followed by White (7.6%) and Asian children (5.4%). The study highlights significant disparities in current asthma prevalence over the two-decade period analyzed. While the overall prevalence showed fluctuations, it generally increased from 2003 to 2009 and then decreased by 2019. Gender disparities were evident, with males consistently reporting a higher prevalence compared to females. Older children in the 10-17 age group consistently had a higher asthma prevalence than younger age groups. Moreover, disparities based on insurance status and income levels were also apparent, with children on Medicaid and those living below the FPL reporting higher asthma prevalence. Racial disparities were observed, with Black children having the highest prevalence, followed by White and Asian children. These findings emphasize the importance of addressing these disparities and tailoring interventions to improve asthma management and prevention across different demographic groups.

The impact of livelihood diversification as a climate change adaptation strategy on poverty level of pastoral households in southeastern and southern Ethiopia

The impact of livelihood diversification as a climate change adaptation strategy on poverty level of pastoral households in southeastern and southern Ethiopia

Microfinance Impact on Household Poverty Levels

Purpose: The aim of the study was to investigate Microfinance Impact on Household Poverty Levels
 Methodology: This study adopted a desk methodology. A desk study research design is commonly known as secondary data collection. This is basically collecting data from existing resources preferably because of its low cost advantage as compared to a field research. Our current study looked into already published studies and reports as the data was easily accessed through online journals and libraries.
 Findings: The study's findings highlighted that microfinance has a mixed impact on household poverty levels. While treated households experienced increased income, consumption, and investment, overall poverty reduction remained modest. Notably, the positive effects were more pronounced for households with pre-existing entrepreneurial skills. The relationship between microfinance and women's empowerment was complex, as these programs had varying impacts on income generation and decision-making among women. Furthermore, group-based microcredit programs led to improved household welfare for both genders, with females experiencing more significant poverty reductions.
 Unique Contribution to Theory, Practice and Policy: Financial Inclusion Theory and Social Capital Theory may be used to anchor future studies on Microfinance impact on household poverty levels. Offer financial literacy training and business development support to borrowers. Enforce policies that protect borrowers from predatory lending practices, ensuring transparency in loan terms and preventing coercive debt collection tactics

Socioeconomic Barriers to Care for Pediatric Airways Utilizing Geographic Information Systems.

Geographic information systems (GIS) provide a unique set of tools to spatially analyze health care and identify patterns of health outcomes to help optimize delivery. Our goal is to create maps of pediatric tracheostomy patients using GIS to assess socioeconomic and other factors that impact postoperative care after discharge to home. A retrospective study was performed on patients (≤21 years old) who underwent tracheostomy at a tertiary care pediatric hospital from January 1, 2015 to December 31, 2020. Using GIS, we geocoded patient addresses and conducted spatial analyses of the relationship between patients and access to health care providers as well as vulnerable population factors including poverty, educational attainment, and single-parent households. A total of 156 patients were included. Patients initially discharged to transitional care (108/156, 69.2%) had significantly higher likelihood of presenting to the ED regardless of socioeconomic status (OR: 2.28, 95% CI: 1.03-5.05; p = 0.042). There was no relationship between ED visit rate and median household income, poverty level, and percentage of uneducated adults (p = 0.490; p = 0.424; p = 0.752). Median distance to the tertiary care pediatric hospital was significantly longer for patients with no ED visit (median = 61.28 miles; SD = 50.90) compared with those with an ED visit (median = 37.75 miles; SD = 35.92) (p = 0.002). The application of GIS could provide geo-localized data to better understand the healthcare barriers to access for children with tracheostomies. This study uniquely integrates medical record data with socioeconomic factors and social determinants of health. 4 Laryngoscope, 134:1919-1925, 2024.

24-Hour movement behaviors among visually impaired US children and adolescents

Background24-h movement behavior (24-HMB) guidelines suggest that children and adolescents should limit screen time (ST), get an adequate amount of sleep (SL), and engage in a sufficient amount of physical activity (PA) to ensure optimal health. However, it is not fully understood how adherence to these 24-HMB guidelines apply specifically to visually impaired children and adolescents. To address this gap in the literature, a cross-sectional study was conducted to investigate potential associations between adherence to the 24-HMB guidelines and academic, social, and emotional outcomes among a national sample of visually impaired children and adolescents. MethodsData on movement behaviors (physical activity, screen time, and sleep duration) and specific outcome variables (academic performance, social function, and emotional function) were collected through caregiver-proxy reports (questionnaires completed by the caregivers of the visually impaired children and adolescents aged between 6 and 17 years). Logistic regressions were performed to examine the associations between the adherence to 24-HMB guidelines and academic, social, and emotional outcomes adjusting for covariates (e.g., age, sex, race, weight, birth status, household poverty level, and the caregiver's education level) and calculate the odds ratio with 95% confidence interval (CI). ResultsAmong 907 visually impaired children and adolescents, only a small proportion adhered to all three 24-HMB guidelines (6.12%). The prevalence of adhering to the SL (33.16%) was higher than those participants meeting PA (3.68%) and ST guidelines (10.28%). As compared to participants who did not meet any of the three 24-HMB guidelines, adhering to: (1) PA + ST guidelines were linked to better academic performance; (2) PA + ST guidelines were linked to less social difficulties, and (3) SL + ST guidelines were linked to better emotional functioning. ConclusionLess than one-third of the visually impaired children and adolescents did meet one or more guidelines of the 24-HMB recommendations. Adhering to the 24-HMB guidelines, both alone and in an integrated manner, was linked to better academic performance, social relationships, and emotional functioning while visually impaired children and adolescents who adhered to PA + ST guidelines benefited the most. Our results suggest that the promotion of the 24-HMB guidelines among visually impaired children and adolescents might be an effective intervention strategy to promote academic, social, and emotional development among this unique group, although further research is necessary to empirically buttress this assumption.

A Geodemographic Analysis of Travel Time to Uveitis Specialists in the United States

ABSTRACT Purpose Travel time to a patient’s medical provider represents a significant component of access to care. We examined travel time to the nearest uveitis specialist for the American population and characterize its impact on access to uveitis care. Design Observational studies using the American Community Survey and American Census Bureau population estimates. Methods Addresses of fellowship-trained uveitis specialists were collected from the American Uveitis Society (AUS) and the Ocular Immunology and Uveitis Foundation (OIUF) websites and geocoded using ArcGIS Pro 2.9. Service areas were defined as all locations within a 60-min drive time from each specialist’s location. Demographic and population data for total population, racial groups, household poverty levels, population in dependent groups (younger than 18, older than 65), and health insurance status were overlaid. Data were aggregated for census tracts within and outside service areas and compared using chi-square analysis. Main Outcome Measures: Differences in population demographics for people within and outside service area coverage. Results 223 uveitis specialist addresses were geocoded into ArcGIS. Of specialist locations, 94% were found in urban areas. Of the total United States population, 63.3% were found to be within service areas. Of these, 55.9% were White and 14.7% were African American, whereas 70% of the people outside service areas were White and 10.1% were African American (p < 0.0001) (Table 1). Only 8.3% of the people within service area coverage had no health insurance compared with 9.5% outside service areas (p < 0.0001). Within coverage areas, 12.7% of the households had a total income below the federal poverty level versus 15.1% of the households outside service area coverage (p < 0.0001). Within service area coverage, 37.4% of the people were in a dependent age group compared with 40.4.% outside service area coverage (p < 0.0001). Conclusions Our analysis shows a significant travel burden to the nearest uveitis specialist for a large proportion of Americans. More providers are needed in rural areas, as patients there are more likely to live under the poverty line, be uninsured, or belong to a dependent age group.

Abstract 33: Using the AHA's Life Essential 8 Criteria to Assess Sleep Duration and Its Association With Social Determinants of Health in U.S. Children

Introduction: In 2010, the American Heart Association (AHA) began using 7 indicators to measure cardiovascular health, known collectively as Life’s Simple 7. In June 2022, the AHA added an 8 th indicator: sleep duration. Although earlier studies have examined whether/how the indicators in Life’s Simple 7 might be impacted by social determinants of health (SDoH), few epidemiological studies have examined how SDoH influence the 8 th indicator in U.S. children. Purpose: We used the AHA Life Essential 8 scoring criteria to assess sleep duration among U.S. children and whether certain SDoH were associated with sleep duration. Methods: We utilized data from the 2019-2020 National Survey of Children’s Health. For all children, we calculated the score for sleep duration (range 0 [lowest] to 100 [highest]). Based on the AHA scoring algorithm and the distribution of sleep duration, participants were divided into three mutually exclusive subgroups: (1) those who met age-appropriate optimal sleep duration; (2) those who had 1-&lt;2 hour below or ≥ 1 hour above optimal sleep duration; and (3) those who had ≥ 2 hours below optimal sleep duration. Multinomial logistic regressions were used to assess the association of sleep duration with 4 SDoH factors (adverse childhood experiences [ACEs], received preventive care during past 12 months, food insufficiency, and living in unsafe neighborhoods). We controlled for child’s sex, age, race/ethnicity, and household poverty level. Results: Among children aged 6 to 17 years (n=49,821), the mean sleep duration score was 77.1 (95% CI 76.4 to 77.7) and 65.5% of the children had age-appropriate optimal sleep scores. Three SDoH factors were associated with higher likelihood of suboptimal sleep duration. Adjusting for covariates, for each point increase in number of ACEs the likelihood of having suboptimal sleep duration was increased (relative risk ratios [RR]:1.05 [95% CI 1.02 to 1.09]; 1.21 [95% CI 1.15 to 1.27]). The likelihood of having suboptimal sleep duration was also increased for those who reported food insufficiency at home (RR:1.19 [95% CI 1.06 to 1.33]; 1.67 [95% CI 1.40 to 1.98]) as well as for those who reported living in an unsafe neighborhood (RR: 1.34 [95% CI 1.04 to 1.71]; 1.63 [95% CI 1.19 to 2.23]). Conclusions: Our findings show that using the AHA’s Life Essential 8 scoring criteria, one third of U.S. children do not meet optimal sleep duration standards. These findings highlight the need for greater attention to social and systemic influences on children's sleep health. It is critical for healthcare providers to recognize that suboptimal sleep duration is a risk factor for poor cardiovascular health, and that certain SDoH are associated with suboptimal sleep duration.

EFFECT OF LIVELIHOOD DIVERSIFICATION ON THE POVERTY LEVELS OF RURAL FARMING HOUSEHOLDS IN SOUTHWEST NIGERIA

The purpose of this study was to examine the effects of livelihood diversification on the poverty levels of rural farming households in Southwest Nigeria. A multistage sampling technique was employed to select a total of 300 respondents in the study area. Primary data were collected on rural farming household’s socio-economic characteristics, indicators of poverty such as food and non-food expenditure with the aid of a well-structured questionnaire. Data obtained were analyzed using descriptive statistics, Foster Greer and Thorbecke model, and Tobit regression. Tobit regression estimates revealed that sex of the household heads, marital status, years of formal education, household size, farm size, farming experience, dependent ratio and household assets and livelihood diversification affects the poverty levels of farming households. Hence, livelihood diversification opportunities should be strengthened by exposing farming households to training on what they can venture into to boost their income.

Model selection and optimization for poverty prediction on household data from Cambodia

Addressing global poverty requires understanding of the most poverty-stricken regions. One approach towards achieving this is through poverty prediction, a task that entails classifying poverty levels of households using available data. While machine learning (ML) has been applied in numerous fields with considerable success, its application in poverty prediction using exclusively household survey data is yet to be thoroughly explored. Household survey data offers a detailed view into the living conditions, lifestyle, and socio-economic factors affecting households. Hence, we aim explore the use of this data type in predicting poverty levels. Our study primarily focuses on three ML models: softmax classification, random forest classification, and multilayer perceptron (MLP). We chose Cambodia for this study due to its unique socio-economic landscape and as a representative of developing nations struggling with poverty. This analysis will serve as the foundation for applying this approach to other nations. The analysis was based on a dataset consisting of 15,825 household samples and 1,873 features obtained through the Demographic and Health Surveys (DHS) program in Cambodia. The study's aim was to validate the effectiveness of ML in poverty prediction using household data and identify the best performing model among the selected three. We hypothesized that the MLP, due to its advanced neural network structure, would provide superior results compared to the softmax classification and random forest models. As anticipated, the multilayer perceptron outperformed the other models, achieving an accuracy of 87% against the 81% and 80% accuracy of the random forest and softmax classification models respectively.

The involvement of Non-Governmental Organizations activities in Household Poverty reduction in Oyam District, Uganda

Purpose: This study examined the contribution of NGO activities on poverty reduction in Oyam District-Northern Uganda and recommends strategies for improving wellbeing of people of the region and entirely Uganda as a Country. This was based on account that, Oyam District was estimated with the lowest annual GDP per capita of 223 USD compared to the neighbouring Districts of Apac and Kole with the annual GDP per capita of 228 USD and 230 USD respectively&#x0D; Methodology: The study used a correlational design with correlational and regression methods of analysis. It was conducted among beneficiaries of selected NGOs comprising a sample of 290 from a population of 860.&#x0D; Findings: This study reveals a significant and positive contribution of NGO activities to poverty reduction in Oyam District and that NGO activities has a moderate relationship with household poverty level in Oyam District. The results further show that the financial support provided by NGOs significantly contributes to poverty reduction while the food security support provided does not.&#x0D; Conclusion and recommendations: It is established that NGO activities contribute significantly to poverty reduction in Oyam District. This study recommends that the food security support be backed with the provision of market for the agricultural products of the NGO beneficiaries and in order to create income for them. The study further recommends for the NGO support to agricultural product market search for their beneficiaries as well as forming the beneficiaries in different groups and train them on financial literacy for better management of finances.&#x0D; Unique contributions to policy and/or practice: This study contributes positively to the understanding of non-state actors and the role they play in reducing poverty among communities that are recovering from decades of civil war in Uganda.

The Effects of the Transmigration Programme on Poverty Reduction in Indonesia’s Gorontalo Province: A Multidimensional Approach

The transmigration program in Gorontalo Province plays an important role in poverty reduction. The districts of Gorontalo and Boalemo, as a part of Gorontalo Province, were purposefully selected as research locations. A total of 240 respondents of transmigrant and local households were interviewed using a questionnaire containing a list of questions with a 5-Likert scale. The objectives of this research are: (1) to measure the multidimensional poverty level of transmigrant and local households, (2) to determine the impact of the transmigration program on poverty reduction and (3) to identify the factors that influence poverty status of transmigrant and local households. The results show that the poverty level of transmigrant households tends to be lower than local households. The longer the placement of transmigration, the more likely it is to reduce regional poverty levels. The health dimension has a high contribution to the cause of poverty of transmigrants, while the education dimension contributes to the highest cause of poverty of local households. The results of the analysis also show that farmers who are more educated, participate in skills training and have a side business have more opportunity to reduce poverty. The study confirms that the transmigration program has a significant impact on poverty reduction in the region.

Dichotomization of quantitative variables in poverty analysis

It has been proposed four schemes of dichotomization for the four household level quantitative variables – area of land holding, geographic accessibility to the nearest market centre, number of children under 15 and number of literate members of working-age – with justification in the selection of threshold value for each variable to dichotomize into disadvantaged and advantaged group of households using the Nepal Living Standard Survey 2010/11 data with 5988 households and 28,670 of their household members. Association of each dichotomized variable with household level poverty status (poor/non-poor) was found highly significant. Finally, the proposed schemes of dichotomization have tested empirically for their ability to differentiate the poor people into two categories - ‘more vulnerable’ and ‘less vulnerable’ - by fist estimating the three measures of poverty – head count index, poverty gap index and squared poverty gap index - of each group of population and comparing the estimated measures between the disadvantaged and advantaged group of populations. Statistical analysis has been performed by using IBM SPSS version 20. To a large extent the proposed schemes of dichotomization have found to differentiate the poor people into two groups; for example, the head count index of the disadvantaged group of the number of children under 15 is 3.1 times higher than that of the advantaged group. The results of this paper are expected to be useful to the policy makers and development planners of Nepal for focusing their poverty reduction program towards the more vulnerable group of population as well as academician. BIBECHANA 19 (2022) 142-149

Causal inference for time-varying treatments in latent Markov models: An application to the effects of remittances on poverty dynamics

To assess the effectiveness of remittances on the poverty level of recipient households, we propose a causal inference approach that may be applied with longitudinal data and time-varying treatments. The method relies on the integration of a propensity score based technique, the inverse propensity weighting, with a general latent Markov (LM) framework. It is particularly useful when the outcome of interest is a characteristic that is not directly observable, and the analysis is focused on: (i) clustering units in a finite number of classes according to this latent characteristic and (ii) modelling the evolution of this characteristic across time depending on the received treatment. Parameter estimation is based on a two-step procedure. First, individual propensity score weights are computed accounting for predetermined covariates. Then, a weighted version of the standard LM model likelihood, based on such weights, is maximised by means of an expectation-maximisation algorithm or, alternatively, adopting a stepwise procedure. Finite-sample properties of the proposed estimators are studied by simulation. The application is focused on the effect of remittances on the poverty status of Ugandan households, based on a longitudinal survey spanning the period 2009–2014, and where manifest variables are indicators of deprivation. We find that remittances reduce the probability of falling into poverty, whereas they exert no impact on the probability of moving out of poverty.

PENDAPATAN DAN KESEJAHTERAAN RUMAH TANGGA AGROINDUSTRI TAHU PADA SENTRA INDUSTRI TAHU DI PEKON GADINGREJO KECAMATAN GADINGREJO KABUPATEN PRINGSEWU

This study intends to interprete the income, the level of household welfare of tofu agroindustry owners and to know the factors related to the level of household welfare of tofu agroindustry owners at the tofu industry center, Gadingrejo District, Pringsewu Regency. The research location is in Pekon Gadingrejo, Gadingrejo District, Pringsewu Regency using a census method. There are 15 respondents who own tofu agroindustry in Pekon Gadingrejo. Data analysis uses a descriptive quantitative analysis that includes the level of welfare according to Sajogyo, BPS, World Bank, and ADB as well as Spearman Rank analysis to determine the related factors. The results showed that the household income of tofu agroindustry owners in Pekon Gadingrejo was before the pandemic of IDR32,214,381.20 per month with a percentage of 97,41% of tofu agroindustry businesses, and income from other businesses of 2,59%. Household income during the pandemic was IDR23,273,759.10 per month with a percentage of 96,63% of tofu agroindustry businesses and income from other businesses of 3,37%. The welfare and poverty level of tofu agroindustry households in Pekon Gadingrejo based on Sajogyo's criteria, most of the group is sufficient, based on the standard of BPS, which is 40 % in the poor category, based on the criteria of the World Bank and ADB, which is a poverty rate of 0 %. The factors related to the level of household welfare of the tofu agroindustry are the level of household income and household expenditure. Key words: household, income, tofu, welfare