Agropastoralists’ Climate Change Adaptation Strategy Modeling: Software and Coding Method Accuracies for Best-Worst Scaling Data

Abstract

AbstractInvestigating software and coding method accuracies are still a challenge when dealing with best-worst scaling data. Comparing various climate change policy estimates and their relative importance across different statistical packages has received little attention. In this chapter, we use best-worst scaling approach to determine agropastoralist preferences for 13 climate change adaptation policies across two popular statistical packages (R and SAS). While data were collected from 271 agropastoralists, mixed logit was used to analyze data. Results reveal that mean and standard deviation estimates for 13 climate change adaptation policies from R are higher and statistically significant than SAS estimates. Based on R estimates, prolific animal selection, vaccination, settlement, strategic mobility, and strategic destocking are the most popular climate change adaptation policies, and more than two-third of respondents are in favor of these policies.