In the causal analysis of observational data, the positivity assumption requires that all
treatments of interest be observed in every patient subgroup. Violations of this assumption …

This study estimates the impacts of the adoption of different mechanized farming strategies
(ie no-mechanized farming, semi-mechanized farming, and full-mechanized farming) on …

A relatively large body of literature has documented the welfare effects of smallholder
farmers' participation in single-commodity output markets. However, limited empirical …

This study analyzes the impact of the adoption of agricultural mechanization and its intensity
on the non-farm employment of rural women using the 2016 China Labor-force Dynamics …

Recently there has been an increasing concern about plastic mulch film pollution from
agricultural production in China. Given the knowledge of plastic mulch film is information …

This study examines the association between police facial recognition technology (FRT)
deployment and racial differences in arrests across 1136 US cities in 2016. We estimated …

This paper examines the impacts of cooking fuel choices on individuals' subjective well-
being, measured by happiness and life satisfaction, using open-access data from the 2016 …

There is a dearth of robust methods to estimate the causal effects of multiple treatments
when the outcome is binary. This paper uses two unique sets of simulations to propose and …

In finding effects of a binary treatment, practitioners use mostly either propensity score
matching (PSM) or inverse probability weighting (IPW). However, many new treatment effect …

Rationale, aims and objectives Interventions with multivalued treatments are common in
medical and health research; examples include comparing the efficacy of competing …