1. Protected areas are vital for biodiversity conservation although some have been criticized for not providing adequate socio-economic benefits to local people. However, empirical studies on socio-economic impacts of protected areas that control for confounding factors are rare.
2. Here, we assessed the potential impacts of Maasai Mara National Reserve in South-Western Kenya on welfare (indicated by levels of income, consumption, and assets) of, and poverty incidence among 423 randomly selected local households. We used descriptive statistics to summarize demographic and socio-economic statuses of the households. Then, we estimated effects of the protected area on welfare of the households using ordinary least - squares regression model and entropy balancing.
3. The protected area did not have any significant effect on welfare of, and poverty levels among the households. Households that lived within a 5 km radius of the protected area boundary incurred significantly higher crop destruction and livestock depredation losses than households that lived 5 - 25 km from the boundary. Nevertheless, majority of the households held positive views about the protected area due to direct and indirect benefits that they had already gained or expected to gain from it in the future.
4. These results suggest that interventions are needed to reduce losses caused by wildlife in the protected area and improve its social and economic benefits to the local households.

We used questionnaire surveys to collect data from households that lived adjacent to the protected area (i.e. within a 5 km radius of the boundary) and distant households (i.e. lived 5 to 25 km from the boundary) in six wards (Naikarra, Angata Barikoi, Mara, Lolgorian, Siana and Kimintet ) that covered a total of 72 villages. Questionnaire for the interviews contained both sets of closed-and open-ended questions to enable a comprehensive understanding of interviewees’ perceptions of benefits and losses attributable to the protected area from multiple perspectives. We used descriptive statistics to summarize demographic and socio-economic statuses of the households. Then to assess impact of the protected area on welfare of the households, we did an empirical analysis in two steps. First, we estimated effect of the protected area on welfare using ordinary least - squares regression model and entropy balancing. Second, we determined a relationship between the protected area and poverty within the households using poverty indicators.