School of Statistics and Planning (SSP) Collection
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ItemDeterminants of childhood stunting among children below five years in Uganda: UDHS 2016 Data analysis(Makerere University, 2026)Background: Childhood stunting remains a critical public health and developmental challenge in Uganda, reflecting chronic undernutrition and systemic environmental inequalities. This study investigated the socio-demographic, health, and environmental determinants of stunting among children under five years in Uganda. Methods: The study utilized cross-sectional data from the child dataset of the Uganda Demographic and Health Survey (UDHS). Data analysis was performed using SPSS version 27. Univariate analysis described sample baseline characteristics. Bivariate analysis was executed using Pearson's Chi-Square tests and independent samples t-tests. Multivariate analysis employed both binary logistic and probit regression models to evaluate robust independent predictors of child stunting while checking model specification consistency. Results: Preliminary univariate results showed a substantial burden of chronic malnutrition, with [Insert Stunting %] of the children classified as stunted. Bivariate assessments revealed significant differences in stunting prevalence across geographical residences, maternal education levels, and household wealth quintiles (p < 0.05). Children from rural households and mothers with no formal education exhibited higher stunting rates. Environmental variables, including safe drinking water source and improved sanitation facility access, as well as child health status (history of recent diarrhea), were strongly associated with child nutritional outcomes. The mean child dietary diversity score was significantly lower among stunted children compared to nonstunted peers. Conclusion: Addressing child stunting in Uganda demands comprehensive, multi-sectoral interventions targeting maternal education, improvements in household environmental sanitation infrastructure, rural health delivery, and targeted young child feeding strategies to enhance dietary diversity.
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ItemEffects of the central bankrate, inflation and commercial bank lending rate on GDP in Uganda. A quarterly timeseries analysis (2017-2025)(Makerere University, 2026)This study examined the effect of the Central Bank Rate (CBR), inflation and commercial bank lending rate on Gross Domestic Product (GDP) in Uganda using quarterly time-series data covering the period from 2017 to 2025. The study was motivated by the need to understand the effectiveness of monetary policy transmission and its influence on economic growth in Uganda. Secondary data were obtained from the Bank of Uganda (BOU), Uganda Bureau of Statistics (UBOS), International Monetary Fund (IMF), and the World Bank. The study employed the Autoregressive Distributed Lag (ARDL) bounds testing approach because the variables exhibited mixed orders of integration, I(0) and I(1). Descriptive statistics, correlation analysis, Augmented Dickey-Fuller (ADF) unit root tests, ARDL bounds testing for cointegration and diagnostic tests were conducted using Stata 17. The findings revealed the existence of a long-run equilibrium relationship among GDP, the Central Bank Rate, inflation and commercial bank lending rate. The ARDL bounds test produced an F-statistic of 5.237 which exceeded the upper critical bound at the 5 percent significance level, confirming cointegration among the variables. The long-run estimates showed that the Central Bank Rate had a negative effect on GDP (β = -0.1124), inflation had a negative effect on GDP (β = -0.0821), and the commercial bank lending rate had the strongest negative effect on GDP (β = -0.6247). The commercial bank lending rate emerged as the most influential monetary variable affecting economic growth in Uganda. The study concludes that increases in interest rates and inflation reduce economic growth in the long run, with commercial bank lending rates exerting the greatest impact on GDP. The study recommends policies aimed at reducing commercial bank lending rate spreads, strengthening monetary policy transmission mechanisms and enhancing coordination between monetary and fiscal policy to promote sustainable economic growth in Uganda.
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ItemTime series analysis of the relationship between active mobile cellular subscriptions and economic growth in Uganda.(Makerere University, 2026)This study investigates the dynamic relationship between active mobile cellular subscriptions and economic growth in both the short and long-run for Uganda. It uses an Auto Regressive Distributed Lag (ARDL) model to carry out a time-series analysis of the variables for the period from 2001 to 2024, modeling Gross Domestic Product (GDP) as a function of active mobile cellular subscriptions, Gross Fixed Investment and total labor force(Natural Log of variables is used). The model satisfies classical diagnostic assumptions, showing no evidence of serial correlation or heteroskedasticity. The finitesample bounds test confirms the existence of a stable, long-run level relationship at 5% significance. The Error Correction Term reveals a rapid adjustment, with 79.35% of short run economic disequilibrium correcting back to the steady state trend annually. The sample yields statistically insignificant coefficients in the long-run but has a significant, delayed active mobile cellular subscriptions return in the short-run, which is a 1% increase in active mobile cellular subscriptions in the previous year leading to a 0.56% increase in economic growth in the current year. These findings suggest that active mobile cellular subscriptions do not yield instantaneous returns but require a one-year gestation period to generate economic returns.
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ItemDeterminants of low insurance uptake among Ugandan households(Makerere University, 2026)Despite modest growth in gross written premiums over the past decade, insurance penetration in Uganda remains below 1% of GDP, reflecting persistently low household uptake and a limited understanding of the demographic, socioeconomic and attitudinal factors that shape enrolment decisions. This study examined the determinants of low insurance uptake among Ugandan households, with specific objectives to assess the effects of demographic factors (age, place of residence and level of education), socioeconomic factors (income level and employment status) and attitudinal factors (insurance literacy and perceived trust) on insurance uptake. The study adopted a quantitative, cross-sectional design using secondary data from the nationally representative FinScope Uganda 2023 Survey. Data were analysed in three stages using STATA: univariate analysis to describe sample characteristics, bivariate analysis using a simple complementary log-log regression to test unadjusted associations between each independent variable and insurance uptake, and multivariate analysis using a multivariable complementary log-log model to test the study’s hypotheses while controlling for other covariates. Only 2.61% of respondents held insurance. At the bivariate level, age, place of residence, education, employment status and income were all significantly associated with uptake. After adjustment, age lost significance, while place of residence, level of education, employment status (for paid employment and NPISH) and income level remained significant predictors, with income level and education emerging as the strongest and most consistent determinants. Insurance literacy and perceived trust could not be empirically tested because the available measures were observed only among the small number of respondents who already held a policy and had filed a claim. The study concludes that low insurance uptake among Ugandan households is primarily a demographic and socioeconomic phenomenon, driven mainly by affordability, education, place of residence and access to formal employment rather than age, and recommends affordability-focused product design, simplified consumer education, expanded rural distribution channels and workplace-linked group schemes for informal workers, alongside further research using data able to independently measure insurance literacy and trust.
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ItemEffect of disaggregated inflation components on the Central Bank Rate in Uganda: an ARDL approach(Makerere University, 2026)This study examined the effect of disaggregated inflation components on the Central Bank Rate (CBR) in Uganda using monthly data from August 2017 to January 2026. Specifically, the study investigated the influence of core inflation, food crops inflation, and energy, fuel and utilities (EFU) inflation within an Autoregressive Distributed Lag (ARDL) framework. The analysis included descriptive statistics, correlation analysis, unit root tests, ARDL estimation, diagnostic tests, and a robust Unrestricted Error Correction Model (UECM). The findings indicate that none of the three inflation components had a statistically significant independent long-run effect on the CBR. However, the COVID-19 structural shock significantly influenced short-run monetary policy decisions, while the negative and significant error correction term confirmed a stable longrun relationship and an adjustment speed of approximately 10% per month. The study concludes that the Bank of Uganda responds more to broad macroeconomic conditions and major structural shocks than to individual inflation components, and recommends a more holistic approach to monetary policy formulation.