Statistical Analysis of Poverty Trap Dynamics Among Rural Households in Benue State Using Panel Data

Poverty traps, defined as self-reinforcing mechanisms that prevent low-income households from escaping poverty, require panel data statistical analysis to distinguish transient poverty from chronic poverty states in rural Benue State, North Central Nigeria. This study analyses poverty trap dynamics among rural households in Benue State using a two-round panel dataset from the Benue State Agricultural Development Programme household survey (2018 and 2022) covering 420 households in Makurdi, Oju, and Ukum LGAs. Per capita household consumption expenditure deflated to 2018 prices was used to define poverty status. Markov transition matrices characterised poverty entry and exit probabilities. Random effects probit models estimated poverty persistence and the determinants of upward mobility. Bivariate probit estimated correlated poverty states across the two rounds. The poverty headcount was 58.3 percent in 2018 and 61.4 percent in 2022, indicating worsening poverty. Markov analysis showed a poverty persistence rate of 81 percent, meaning 81 percent of poor households in 2018 remained poor in 2022. Poverty exit probability was only 19 percent over the four-year period. Random effects probit identified non-farm income diversification (coefficient -0.48, p < 0.001), formal credit access (coefficient -0.39, p = 0.004), and household head secondary education (coefficient -0.31, p = 0.018) as significant poverty escape predictors. The study recommends targeted rural credit access, vocational training, and non-farm enterprise development to disrupt poverty trap mechanisms in Benue rural communities. Keywords: poverty trap, panel data, Markov transition, Benue State, poverty persistence