Feasibility of constructing a dynamic price index to monitor essential commodity markets in Lusaka, Zambia

Abstract

Urban households in low-income developing economies are significantly susceptible to variations in the cost of vital goods, especially in environments marked by structural poverty, stark income disparity, and disjointed market systems. In Zambia, where a significant percentage of urban households dedicate a considerable portion of their income to food, electricity, and other essentials, even brief price surges might result in rapid welfare detriments. Notwithstanding this susceptibility, current price monitoring tools, particularly the Consumer Price Index (CPI), are primarily intended for macroeconomic inflation assessment and are constrained by monthly reporting intervals that mask intra-period price fluctuations. Consequently, swift price fluctuations in vital commodity markets frequently remain unnoticed in real time, limiting the ability of policymakers and families to respond promptly to affordability crises. This study evaluates the technological, economic, institutional, and welfare viability of developing a dynamic price index (DPI) specifically for vital commodity markets in Lusaka, Zambia. Anchored in a cohesive theoretical framework that merges signalling theory with the theory of income inequality, the research defines the DPI as both an informational infrastructure and a policy instrument attuned to distributional considerations. A mixed-methods sequential explanatory methodology is utilised, incorporating high-frequency market price data from both formal and informal markets, cross-sectional household survey data from various income groups, and a documentary study of current regulatory and statistical frameworks. Descriptive analysis indicates significant intra-period price volatility among staple commodities, characterised by weekly swings overlooked by standard monthly reporting methods. Econometric estimations, such as Ordinary Least Squares (OLS), Difference-in-Differences (DiD), and Vector Error Correction Models (VECM), reveal statistically significant correlations between dynamic price fluctuations and household affordability outcomes, as indicated by the Affordability of Essential Commodities (AEC) Index. Data from a pilot price information initiative suggests that enhanced access to high-frequency price signals improves household affordability and diminishes dependence on detrimental coping techniques, especially among economically vulnerable groups. An institutional assessment verifies the presence of essential capacities for dynamic monitoring within Zambia's statistics agencies, regulatory entities, and digital infrastructure, characterised by extensive mobile penetration and developed sector-specific pricing systems. Nonetheless, the heterogeneity of data governance and coordinating methods constitutes a significant operational issue. The results combined demonstrate that the establishment of a dynamic price index for Lusaka is technically feasible, econometrically sound, institutionally practical, and economically warranted. The study suggests that shifting from retroactive inflation assessment to prospective affordability monitoring will improve market transparency, increase policy responsiveness, and help mitigate inequalities in access to basic goods. It advocates for the implementation of a multi-source DPI platform with coordinated institutional supervision, integration with social protection systems, and the creation of a transparent dissemination strategy to optimise household welfare benefits.