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March 10, 20260 citationsOpen Access

Methodological Evaluation of Regional Monitoring Networks in Nigeria Using Time-Series Forecasting Models for Adoption Rate Measurement,Context

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CAChinenye Agbakora

Key Points

  • To assess how regional monitoring networks in Nigeria measure agricultural adoption rates using forecasting models.
  • Conducted a systematic literature review of monitoring networks across Nigeria.
  • Evaluated methodologies and time-series forecasting models used for measuring adoption rates.
  • Analyzed the prediction error margins and biases in the forecasting accuracy of different networks.
  • Average prediction error margin was ±5% during the study period.
  • Some networks showed high accuracy while others significantly underestimated trends.
  • Recommendations include improving data collection methods and expanding training for network operators.

Abstract

This review examines regional monitoring networks in Nigeria to evaluate their effectiveness in measuring adoption rates of agricultural practices. A systematic literature review was conducted, focusing on methodologies employed by monitoring networks across Nigeria. The analysis included a critical evaluation of time-series forecasting models used in measuring adoption rates. Regional monitoring networks showed significant variability in their ability to forecast adoption rates with an average prediction error margin of ±5% over the study period. While some networks demonstrated high accuracy, others had notable biases and underestimated trends due to data limitations and model assumptions. Networks should improve data collection methods and consider additional explanatory variables for more accurate forecasting. Enhanced training programmes are also recommended for network operators to reduce human error. The empirical specification follows Y=₀+^ X+, and inference is reported with uncertainty-aware statistical criteria.

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Cite This Study

Chinenye Agbakora (2010) studied this question.

synapsesocial.com/papers/69af95cf70916d39fea4dc64https://doi.org/10.5281/zenodo.18906361
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