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T.O. Ojo

Researcher at University of the Free State

Publications -  41
Citations -  556

T.O. Ojo is an academic researcher from University of the Free State. The author has contributed to research in topics: Agriculture & Food security. The author has an hindex of 7, co-authored 25 publications receiving 183 citations. Previous affiliations of T.O. Ojo include Obafemi Awolowo University & University of KwaZulu-Natal.

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Determinants of climate change adaptation strategies and its impact on the net farm income of rice farmers in south-west Nigeria

TL;DR: In this paper, a multivariate probit model was used to analyse the determinants of strategies adopted for adapting to climate change in a sample of smallholder rice farmers in south-west Nigeria.
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Understanding the adoption of climate change adaptation strategies among smallholder farmers: Evidence from land reform beneficiaries in South Africa

TL;DR: In this article, a zero-inflated double hurdle model was employed to estimate the factors influencing farmers' adoption of adaptation strategies and intensity of adoption at the household level in South Africa, and the authors concluded that farm-level policy efforts that aim to improve rural development should focus on farmers' education, on-farm demonstration and non-farm employment opportunities that seek to engage the farmers.
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Impact of Credit Demand on the Productivity of Rice Farmers in South West Nigeria

TL;DR: In this article, the impact of credit demand on the productivity of rice farmers in South West Nigeria was analyzed using an endogenous switching regression model (ESRM) that accounts for both heterogeneity and sample selection biases.
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Determinants of credit constraints and its impact on the adoption of climate change adaptation strategies among rice farmers in South-West Nigeria

TL;DR: In this article, the impact of credit constraints on climate change adaptation strategies among smallholder rice farmers in South-West Nigeria was analyzed using Generalized Method of Moments with Instrumental Variable (IV-GMM) and the seemingly unrelated regression (SUR) model.
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Understanding the determinants of climate change adaptation strategies among smallholder maize farmers in South-west, Nigeria

TL;DR: In this paper, a double-hurdle count data model was employed to estimate the factors influencing farmers' adoption of adaptation strategies while accounting for selection bias with the plugging of inverse mill ratio (IMR) as a regressor.