Corruption is a pervasive issue with profound global impact, undermining economic growth and exacerbating inequality (World Bank, 2021; Onyango, 2022). The United Nations Office on Drugs and Crime estimates that $1 trillion is paid in bribes and $2.6 trillion are stolen annually, representing over 5% of the global GDP. Factors like political instability, weak rule of law, and low civic participation contribute to its persistence (Sartor & Beamish, 2020). The World Bank advocates for a multifaceted approach to tackle corruption, including strengthening institutions and enforcing anti-corruption laws (World Bank, 2021). Various forms of corruption, including bribery and embezzlement, are especially rampant in the public sector, influencing political outcomes and undermining institutions. Transparency International's Corruption Perceptions Index (CPI) shows varying perceptions of corruption worldwide, with Denmark and New Zealand ranking as least corrupt and Syria, South Sudan, and Somalia as most corrupt (Allison, 2021).

Kopits and Craig (1998) provide foundational work, asserting that fiscal transparency is critical for combating corruption. They define fiscal transparency as public openness about governmental activities and finances. Wampler (2000) discusses the significance of participatory budgeting, emphasizing its role in citizen engagement and potentially reducing opportunities for corruption.

Building on these foundations, Dorotinsky & Pradhan (2007) highlight that a robust budget classification enhances fiscal transparency, aiding in reporting, control, and audit. Morgner (2013) elaborates on the risks of corruption in budgeting, stating that high discretion in fund allocation and opaque budgeting can lead to corruption. He argues that improved information management and budget preparation could reduce corruption. French (2013) agrees, suggesting that reforms in budget preparation can reduce grand corruption but cautions that technical reforms are not sufficient without political will.

Cimpoeru and Cimpoeru (2012) empirically examine the correlation between budget transparency and corruption control between 2006-2012. Their study finds that budget transparency and GDP per capita significantly affect the level of corruption control. These findings are consistent with the later work of Long (2019), who explores the positive correlation between transparency in budget preparation and lower perceived levels of corruption. OECD (2017) further supports this by discussing how participatory budgeting could deter and detect corruption.

More recent studies like Chen & Neshkova (2019) extend these arguments. They use data from the Open Budget Index and corruption indicators to strongly suggest that more fiscally transparent countries are perceived as less corrupt. Finally, Duri (2021) synthesizes various viewpoints and adds to the contemporary literature by arguing that the risk of corruption increases with discretionary fund allocation and opaque budgeting. He also cites a World Bank report and Cameron (2019) to emphasize the effectiveness of participatory budgeting in reducing corruption after the 2010 devolution of government to 46 counties

The study adopted a cross-sectional design and the use of quantitative data collection and analysis techniques based on a case study method. Amin (2005) points out that a cross- sectional approach helps the researcher to gather large amounts of data from a sample of cross-section/groups of people or units at a particular point in time. A cross-sectional study approach allows the researcher to collect information on the situation at a point in time. This is much easier, and more applicable to this study than a longitudinal approach which would require collection of information over a period of time (Bryman, 2006). The study was suited within the provisions of survey approach because the researcher gathered data and report the state in which things are without changing any variables.

In this study, a stratified sampling technique was employed to ensure a representative sample that could adequately reflect the diverse perspectives within Wakiso District's public finance management framework. Stratified sampling allowed for the division of the population into distinct subgroups or strata based on specific criteria—here, the technical and knowledgeable officers of the district. These strata were then sampled independently using both purposive and simple random sampling methods. Purposive sampling targeted individuals known for their expertise and roles relevant to the study’s focus, ensuring that the data collected was informed and accurate. Simple random sampling was used within these strata to mitigate selection bias and enhance the generalizability of the findings.

Following the guidelines of Morgan and Krejcie’s sample determination table, the study identified a suitable sample size of 113 participants from an estimated population of 160 officers. This sample size calculation was based on the premise that it would provide a statistically significant representation of the population, with a confidence level sufficient for analytical generalization.

      Showing the category, sample and sampling method

            Source: Wakiso District Local Government (2023)

To determine the sample size for each category, the following formula was used:

                                                  x total sample size

Linear Regression of Budget Preparation on Corruption

a. Dependent Variable: Corruption

b. Predictors: (Constant), Budget Preparation

a. Dependent Variable: Corruption

a. Dependent Variable: Corruption

Source: Field Data (2024)

Analyzing the influence of budget preparation on corruption in Wakiso District, Uganda, the hypothesis posits no significant association between the two variables. The regression analysis presents a strong positive correlation (R = .786), indicating a robust relationship, the model explains 78.6% of the variance in corruption, suggesting a substantial effect of budget preparation on corruption levels.

The ANOVA results show a highly significant F-statistic (F = 160.063, p < .001), indicating that the regression model is statistically significant and the variable of budget preparation is a predictor of corruption levels.

Examining the coefficients, we see that the unstandardized B for budget preparation is .935, and the standardized beta coefficient is .786. The t-test for the budget preparation coefficient is extremely significant (t = 12.652, p < .001), offering strong evidence against the null hypothesis. The constant (B = .126, p = .670) is not significant, suggesting that when budget preparation scores are zero, the predicted level of corruption does not differ significantly from the mean of corruption.

The analysis suggests that improved budget preparation is associated with a decrease in corruption. This may reflect the literature on PFM reforms, such as those discussed by Bräutigam, Fjeldstad, and Moore (2008), who emphasize the role of thorough budget processes in enhancing transparency and reducing opportunities for corruption.

In conclusion, the statistical evidence from the analysis leads to the rejection of the null hypothesis, indicating that budget preparation has a significant negative association with the incidence of corruption in Wakiso District. The strength of the relationship, as indicated by the high R Square and the significant F-statistic, underscores the importance of meticulous budget preparation as a strategy against corruption. The findings advocate for rigorous budget planning as a key component in combating corruption in public finance management.

The study reveals a profound influence of budget formulation practices on the levels of corruption within Wakiso District, Uganda. The substantial negative correlation of -0.786 between these practices and corruption instances, underscored by its statistical significance, illustrates that well-structured and transparent budget formulation can drastically curtail corrupt activities. The statistically significant negative correlation between these variables highlights that enhancing the clarity and inclusiveness of budget processes directly contributes to minimizing corrupt activities. This relationship is reinforced by the robust explanatory power of budget formulation in predicting corruption levels, as evidenced by the regression analysis. These findings are aligned with theoretical expectations and existing literature which advocate for the strengthening of budgetary procedures to ensure fiscal discipline and integrity.

The study shows a moderate negative correlation between improved revenue management practices and the occurrence of corruption, signifying that more rigorous and efficient revenue management could serve as a deterrent to corrupt activities.

The study reveals that budget execution practices within Wakiso Districts a significant negative correlation with corruption, confirming the critical role that adherence to budgetary procedures plays in curbing corrupt activities

The findings on the impact of accounting and reporting practices on corruption in Wakiso District establish a clear negative correlation, underscoring the significant role that enhanced financial transparency and adherence to international standards play in curbing corrupt practices. Improved accounting and reporting not only make it more challenging for corruption to go unnoticed but also enhance external scrutiny and accountability, reinforcing the integrity of financial management within the district

Wakiso District Local Government should implement mandatory public consultations and enhance disclosures during the budget preparation phase. These steps will ensure a higher degree of transparency and stakeholder engagement, crucial for minimizing discretionary powers that often pave the way for corruption.

Wakiso District Local Government should bolster the capacity of budgetary oversight bodies to conduct regular, detailed reviews of budget proposals and executions. This enhancement should include specialized training for officials in advanced fiscal analysis to proactively detect and address potential inconsistencies and irregularities, thus preventing corrupt practices.

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