Migrant remittance behavior in Uganda: A household analysis
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Background: World over, development of nations is directly linked to migration since one in seven people in the world is a migrant and a quarter of them, international migrants (Ratha, 2005). The economic importance of international migrants has been demonstrated by international remittances that are sent to families in the migrants’ home countries. According to World Bank, 2015, remittance flows to developing countries were expected to reach $414 billion in 2013 (up 6.3 percent over 2012), and $540 billion by 2016. Worldwide, remittance flows may reach $550 billion in 2013 and over $700 billion by 2016. Despite an increased interest in the role of international remittances at the international level, sparse information that exists in Uganda reveals that little or no attention has been put on examining whether remittances are invested in development or non- development ventures at household level (Wamala, 2010). This research gap warrants a need for studies on understanding the role of international remittances. Exploring the role of remittances and how it offers ingredients to enhance the development potential for citizens is important. This will be a contribution to the development in Uganda given that during the global financial crisis remittances proved resilient by falling with a minimal margin compared to the foreign direct investment; private debt and portfolio equity flows. Data Sources: Data from the survey on personal transfers by Ugandans living abroad during the year 2010 is used. This survey was the fourth in a series of annual surveys jointly conducted by Bank of Uganda and the Uganda Bureau of Statistics.Methods: Complementary log-log regression model was used because of the small numbers of households in the categories of interest (asymmetrically distributed). Survey weights were applied to data in order to account for the complex survey design including clustering and stratification. Results: Remittance receipt status was determined by region of the household, number of rooms in the house, household main source of lighting fuel. Using remittances for development was determined by sex of the household head, household regional location, house ownership status sex, marital status and senders’ residence. Conclusion: Results show that a household that had a member abroad also had higher chances of receiving remittances compared to the household with no member abroad. Results on the contrary found household and household head characteristics significantly associated with remittance receipt status of a household. Use of international remittances for development of households was significantly determined by sex of the household head, regional location of the household, house ownership status and number of rooms in the house. It is therefore recommended that government should leverage migration opportunities for women and also expand migration opportunities across all regions of the country since it augments development for households with migrants
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it