Socio-Economic and Institutional Constraints to Accessing Credit among Smallholder Farmers in Nyandarua District, Kenya

Amongst the challenges faced by smallholder farmers in production is inaccessibility to credit. This study sought to identify household socio-economic and institutional constraints influencing access to credit among smallholder farmers in Nyandarua District. The study used a Logit model. Both quantitative and qualitative data were acquired from primary and secondary sources. Primary data was collected using questionnaires through a survey design. A sample of 164 smallholder farmers was selected using stratified, multi-stage random sampling techniques. Data was analyzed using descriptive statistics and maximum likelihood method using Statistical Package for Social Sciences (SPSS). The study established that socio-economic constraints such as age, gender, household size, farm income, collateral and awareness are critical determinants of access to credit. The study also established that institutional requirements such as costs involved in operating / maintaining bank accounts, loan requirements and transaction costs involved in the credit process influenced access to credit. The study concludes that household socio-economic characteristics and institutional requirements influence access to credit. Key recommendations made include the need by government to deal with bureaucracies involved in land registration to benefit majority of smallholder farmers who remain insecure in the land they use without proof of ownership and also to make easier the registration of lease certificates for those who do not own land and use land on leasehold tenure system. Financial institutions should also put in place less stringent credit requirements and reduce credit costs especially interest rates to make credit more affordable. Keywords: socio-economic and institutional constraints, credit access, smallholder farmers, logit model

Assessment of Farmers’ Adaptation to the Effects of Climate Change in Kenya: the Case of Kyuso District

The study was carried out to assess how farmers in Kyuso District have adapted to the effects of climate change. Survey data was collected from 246 farmers from six locations that were sampled out through a multistage and simple random sampling procedure. The probit regression model was fitted into the data in order to assess factors influencing farmers’ adaptation to the effects of climate change. The analysis revealed that 85% of the farmers had adapted in various ways to the effects of climate change. In this regard, the age of the farmer, gender, education, farming experience, farm income, access to climate information, household size, local agro-ecology, distance to input/output market, access to credit, access to water for irrigation, precipitation and temperature were found to have significant influence on the probability of farmers to adapt to climate change. The study suggests that more policy efforts should thus be geared towards helping all the farmers in the district to adapt to climate change. Key words: climate change, adaptation, probit regression model, Kyuso District

Analysis of Farmers’ Perceptions of the Effects of Climate Change in Kenya: the Case of Kyuso District

A cross-sectional analysis was carried out to evaluate how farmers in Kyuso District have perceived climate change. Data was collected from 246 farmers from six locations sampled out through a multistage and simple random sampling procedure. The logistic regression analysis was carried out to assess factors influencing farmers’ perceptions of climate change. The analysis revealed that 94% of farmers in Kyuso District had a perception that climate was changing.  In this regard, age of the household head, gender, education, farming experience, household size, distance to the nearest input/output market, access to irrigation water, local agro-ecology, access to information on climate change, access to extension services, off farm income and change in temperature and precipitation were found to have significant influence on the probability of farmers to perceive climate change. Since the level of perception to climate change revealed by the study was found to be high (94%), the study suggests that more policy efforts should thus be geared towards helping farmers to adapt to climate change. Key words: Climate change, Perceptions, Logistic regression, Kyuso District

Is Agricultural Extension a Determinant of Farm Diversification - Evidence from Kenya

Farm diversification is a common coping strategy among smallholder farmers, especially in the developing countries. As a result, understanding the determinants of farm diversity is paramount. Access to extension has been found to be an important determinant of farm diversity through the technology adoption pathway. Despite farmers access to several extension services, no evidence exists on the effect of different extension services on farm diversity. This study evaluates the effect of extension services on farm diversity in Kenya. It uses a truncated Poisson model on a sample of 743 households who were selected using a multi stage sampling technique. The findings show that there are significant differences between the least and the most diversified farms. Furthermore, access to government, private and NGO extension services, alongside farmer demographic characteristics, increases farm diversity. This study therefore recommends for hiring, training and facilitating extension officers. In addition, the different extension services should be used as compliments and targeted to where their impact is highest. Acknowledgement : This research was financially supported by the German Federal Ministry of Food and Agriculture (BMEL) based on the decision of the Parliament of the Federal Republic of Germany (grant number 2813FSNu01)

An assessment of the factors influencing household willingness to pay for non-marketed benefit of cattle in the agro-pastoral systems of Mozambique

This study used Probit model to analyze factors influencing probability of household willingness to pay for non-marketed benefits (NBS) of cattle in Mozambique. The primary data from 184 agro-pastoralist households were collected using a structured questionnaire. Data collected comprised information relating to household demographic, household livelihoods and non-marketed benefits of cattle. The result showed that the probability of household willingness to pay (WTP) was influenced by both animal and household related characteristics. Animal related characteristics that had a significant influence on the probability of households WTP for NMB’s of cattle included: Animal age (ANAGE), herd size (HERDSIZE) and cattle breeds (INDBRED). Household related characteristics that had significant (p<0.05) influence on probability of household WTP for NMB’s of cattle, comprised: Dependant ratio (DEPRAT), household size (HHS), off-farm income (OFFINC) and distance to the market (DISTMK). As expected, however, the OFFINC had a negative influence on probability of household WTP for NMB’s of cattle. The study concluded that non-marketed benefits of cattle were highly valued among agro-pastoralist in Mabalane district and thus were willing to pay for them

Analysis of Farmers’ Perceptions of the Effects of Climate Change in Kenya: The Case of Kyuso District

A cross-sectional analysis was carried out to evaluate how farmers in Kyuso District have perceived climate change. Data was collected from 246 farmers from six locations sampled out through a multistage and simple random sampling procedure. The logistic regression analysis was carried out to assess factors influencing farmers’ perceptions of climate change. The analysis revealed that 94% of farmers in Kyuso District had a perception that climate was changing. In this regard, age of the household head, gender, education, farming experience, household size, distance to the nearest input/output market, access to irrigation water, local agro-ecology, access to information on climate change, access to extension services, off farm income and change in temperature and precipitation were found to have significant influence on the probability of farmers to perceive climate change. Since the level of perception to climate change revealed by the study was found to be high (94%), the study suggests that more policy efforts should thus be geared towards helping farmers to adapt to climate change