Uncovering the factors that affect earthquake insurance uptake using supervised machine learning.

The escalating threat of natural disasters to public safety worldwide underlines the crucial role of effective environmental risk management tools, such as insurance. This is particularly evident in the case of earthquakes that occurred in Oklahoma between 2011 and 2020, which were linked to wastewater injection, underscoring the need for earthquake insurance. In this regard, from a survey of 812 respondents in Oklahoma, USA, we used supervised machine learning techniques (i.

Disaggregated impacts of off-farm work participation on household vulnerability to food poverty in Ghana.

This study examines disaggregated impacts of participation in off-farm employment on household vulnerability to food poverty in Ghana. We use household-level data collected from smallholder farmers in Ghana. This study employs the multinomial endogenous switching regression model to account for selection bias due to both observed and unobserved heterogeneity.

Food Poverty, Vulnerability, and Food Consumption Inequality Among Smallholder Households in Ghana: A Gender-Based Perspective.

We examined gender-based household welfare differences in Ghana among smallholder households. We measured disparities in welfare outcomes (food poverty, vulnerability, and food consumption inequality) across male and female household heads and identified the set of covariates influencing them. The study utilizes a dataset from a farm household survey undertaken in Northern Ghana from October to December 2018.