This paper used binary logistic regression model to analyze factors that affect the choice of climate change adaptation strategies of farmers in Northern Ghana. Using semi-structured questionnaires, 155 farmers were randomly sampled from purposively selected three Northern Regions in Ghana. The empirical results of the binary logistic regression models revealed different effects of the factors on farmer's choice of adaptation strategies. Farming experience, farm income, access to phones, mixed farming, farmers' perception on reduction in rainfall amount and access to weather information significantly and positively affects the choice of at least five climate change adaptation strategies. Following the findings of this study, agricultural extension service should be intensified through organization of adult education programmes or field schools for farmers to educate them on some climate change adaptation strategies. Agro climatic information centers should be established at vantage points in farming communities to enable farmers seek for information to help them revise their climate change adaptation decisions for specific time and agricultural activity. Lastly, affordable climate change adaptation technologies should be designed and make available to poor farmers to adopt.

A lot of investment has been made in the agricultural sector of Ghana to increase agricultural production through the introduction of new technologies. However, it has been observed that despite efforts being made by the government through the introduction of new varieties of maize the productivity of maize farmers is generally low. This study sought to assess the efficiency of farmers in the Nkoranza area. The study employed the stochastic frontier model by using a onestage process in Frontier computer programme and using cross-sectional data of the 2008 major cropping season. Socioeconomic and management practices that influence technical efficiency were determined. Input elasticities as well as allocative efficiency of the farmers were also determined. A mean technical efficiency of 91 percent was obtained for maize farmers. There was a distinct variability in mean technical efficiency among farmers cultivating the improved variety and those cultivating the local variety. Variety of maize cultivated by the farmer, sex of the farmer, experience of maize farmer, distance of the farm from the farmers' residence and number of times a farmer gets extension visits were found to have significant effect on technical efficiency. Allocatively, maize farmers were found to be over utilizing labour but under utilizing fertilizer and seeds in the study area. The study recommended that more extension staff should be trained so that their services could be extended to more farmers.

Malnutrition is a matter of public concern worldwide, and remains the greatest challenge in Sub-Saharan Africa. The literature shows that, malnutrition is one of the major causes of childhood deaths and developmental problems around the globe. This study analyzed the factors affecting stunting and wasting in children 0-59 month's old in Northern Ghana using secondary data from Feed the Future Northern Ghana survey data. The study found that the prevalence rate of stunting was 37.14%, 35.79%, and 25.11% for the Northern, Upper East and Upper West regions respectively, while the prevalence of wasting was found to be 11.11%, 11.24%, and 7.31% for these regions. The study also found that the age of child, household total expenditure, region, age of the head of household and household access to safe drinking water were found to be significantly associated with both stunting and wasting. Furthermore, the gender of child, and household location in an urban area, were also found to be significantly associated with only stunting while household access to productive capital was also found to be significantly associated with only wasting. In conclusion, these factors identified should be taken into account when designing interventions on malnutrition in Northern Ghana.

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