What the study found
Dynamic price monitoring (DPM) improved forecasts of household affordability for essential commodities in Lusaka, Zambia. The study reports that models including the dynamic price index (DPI) reduced prediction error and gave earlier warning of affordability stress than models without DPI.
Why the authors say this matters
The authors conclude that adding predictive econometric modeling can turn DPM from a descriptive tool into a proactive welfare governance tool. They also say this is important for predicting affordability shocks before they occur in a setting where commodity costs are linked to poverty and inequality.
What the researchers tested
The researchers used a quantitative, longitudinal design combining household survey data from 384 participants in Woodlands, Chalala, and Zingalume with 30 quarters of secondary price data from Q3 2017 to Q4 2024. They tested econometric forecasting models using descriptive statistics, stationarity and cointegration tests, Vector Autoregression (VAR), and Vector Error-Correction Modeling (VECM).
What worked and what didn't
The results showed strong long-term correlations among the variables. A 1-unit rise in DPI was linked to a 0.45-unit rise in affordability of essential commodities (AEC), while a 1-unit rise in volatility was linked to a 0.32-unit drop in AEC; the error-correction term was -0.38 (p<0.01), indicating a tendency to return to long-run equilibrium.
What to keep in mind
The abstract does not describe detailed limitations beyond the scope of the data and models used. The findings are specific to Lusaka, the sampled households, and the time period studied.
Key points
- Models including the dynamic price index reduced prediction error by 33.7%.
- The models gave an average early warning of affordability stress 1.5 quarters sooner.
- A 1-unit rise in DPI was linked to a 0.45-unit rise in affordability of essential commodities.
- A 1-unit rise in volatility was linked to a 0.32-unit drop in affordability of essential commodities.
- The study used survey data from 384 participants and 30 quarters of price data.
Disclosure
- Research title:
- Dynamic price monitoring improved affordability forecasting in Lusaka
- Authors:
- Ikabongo Mwiya, Austin Mwange, Sylvia Manjeri Aarakit
- Institutions:
- University of Zambia, Makerere University
- Publication date:
- 2026-03-08
- OpenAlex record:
- View
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