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Megersa Debela Daksa

Researcher at Haramaya University

Publications -  5
Citations -  55

Megersa Debela Daksa is an academic researcher from Haramaya University. The author has contributed to research in topics: Heckman correction & Multivariate probit model. The author has an hindex of 3, co-authored 5 publications receiving 28 citations. Previous affiliations of Megersa Debela Daksa include Western Michigan University.

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Enterprise innovation in developing countries: An evidence from Ethiopia

TL;DR: In this paper, the authors used survey data to analyze the determinants of enterprise innovation in Ethiopia using a multivariate probit (MVP) model and found that engagement in R&D, on-the-job training, and website ownership significantly determine enterprise innovation.
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Does energy-environmental Kuznets curve hold for Ethiopia? The relationship between energy intensity and economic growth

TL;DR: In this paper, the authors investigated drivers of energy intensity in Ethiopia over the period of 1974-2014 using ARDL bounds test approach to cointegration and FMOLS-based Hansen parameter instability test methods to examine the long-run relationship among the variables.
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Risk Adjusted Production Efficiency of Maize Farmers in Ethiopia: Implication for Improved Maize Varieties Adoption

TL;DR: In this article, the authors analyzed the technical efficiency and production risk of 862 maize farmers in major maize producing regions of Ethiopia using the stochastic frontier approach to estimate the level of technical efficiencies of stallholder farmers.
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Determinants of deforestation in Western Oromia region of Ethiopia: The case of Komto Forest

TL;DR: In this article, a study was conducted to analyse the determinants of deforestation in Ethiopia, Western Oromia, the case of Komto Forest in East Wollega Zone, employing primary cross-sectional data on sampled households.
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Adoption Spells of Improved Potato Varieties by Smallholder Farmers in Eastern Ethiopia: The Duration Approach

TL;DR: In this article, the authors used Weibull regression to analyze the data gathered from 365 sample farmers and found that timely availability of seed, access to labor and irrigation water, land size, and adaptation strategy by farmers are among the factors curtailing the timeframe to adopt improved potato varieties.