ANALYSIS OF REVENUES IN PUBLIC SECTOR ENTITIES

Аннотация

This study examines the methodological and institutional aspects of revenue analysis in public sector entities, emphasizing its role in strengthening fiscal transparency, improving budget credibility, and informing strategic decision-making. Drawing on international standards, particularly IPSAS, and comparative scholarly perspectives, the paper highlights current challenges in developing economies and proposes pathways for integrating analytical tools into public financial management. Keywords: Public sector revenue, revenue analysis, IPSAS, fiscal governance, accrual accounting, budget forecasting, financial transparency. Revenues serve as the primary source of financing for the activities of public sector entities and represent the fiscal foundation of governmental functions. The accuracy and quality of revenue analysis directly affect a government’s ability to plan expenditures, manage deficits, and ensure the long- term sustainability of its operations. In an era of increasing fiscal pressure and demand for transparency, conducting comprehensive and methodologically sound analysis of public revenues has become an essential component of public financial management. The relevance of revenue analysis lies in its ability to identify trends, evaluate compliance with fiscal forecasts, detect inefficiencies in revenue collection, and guide policy decisions. In developing countries such as Uzbekistan, the role of systematic revenue analysis is growing due to economic reforms aimed at increasing budgetary efficiency and harmonizing public sector practices with international standards. However, many public sector institutions still face methodological and institutional challenges in conducting accurate and timely analysis of revenues. The analysis of revenues in public sector entities is a critical component of modern public financial management and has been the subject of considerable scholarly and institutional attention. As public revenue structures have grown more complex, encompassing a broad array of tax and non-tax sources, the theoretical and methodological underpinnings of revenue analysis have evolved in parallel to meet the needs of auditors, and financial managers. 196 CURRENT APPROACHES AND NEW RESEARCH IN MODERN SCIENCES International scientific-online conference At the core of revenue analysis lies the classification and recognition of revenue streams, which is foundational for ensuring comparability, consistency, and reliability of financial data. According to the International Public Sector Accounting Standards (IPSAS), revenues are broadly categorized into exchange transactions (e.g., sales of goods and services) and non-exchange transactions (e.g., taxes, grants, and transfers), each governed by distinct recognition criteria under the accrual basis of accounting [1]. The adoption of accrual-based accounting is widely recognized as a turning point in public sector financial reporting, enabling the recognition of revenues when economic benefits are received or receivable, rather than when cash is collected. Several scholars have explored the implications of this shift. For example, Lüder and Jones [2] argue that accrual accounting enhances the depth and precision of revenue analysis by allowing for the timely capture of all economic events affecting an entity’s financial position. In contrast, the traditional cash basis—still prevalent in many developing countries—limits the analytical capacity of public sector entities by excluding receivables, accrued revenues, and revenue commitments from financial reports. This deficiency hampers both horizontal (inter-entity) and vertical (intra-entity) comparisons across fiscal periods. Chan [3] contributes to the debate by emphasizing that while accrual accounting theoretically improves transparency and decision-usefulness of financial information, its effectiveness depends on institutional context and the availability of reliable data systems. Indeed, in many developing countries, including those in Central Asia, the lack of robust information infrastructure and the persistence of fragmented revenue collection mechanisms present major challenges to the practical utility of advanced analytical tools. From a methodological standpoint, literature highlights a range of techniques for revenue analysis, including trend analysis, elasticity and buoyancy measurement, scenario analysis, and variance decomposition. Elasticity analysis, for example, assesses how responsive revenue streams are to changes in macroeconomic variables such as GDP or inflation, providing a powerful tool for medium-term revenue forecasting [4]. However, the reliability of such analysis is contingent on data quality and model specification. Bird and Zolt [5] note that in low-income countries, revenue elasticity tends to be low due to administrative inefficiencies and narrow tax bases, underscoring the need to combine analytical work with institutional reform. 197 CURRENT APPROACHES AND NEW