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This study sets out to estimate the direct and total value of changes in soil quality due to agricultural practices of farmers in Central and Eastern Kenya. It goes further to assess the influence of compliance arrangement with regard to agri-food standards on the total economic value for soil quality elicited from the respondents.

Using a sample size of about five hundred farmers, the study applies the replacement cost and the contingent valuation method (CVM) approach to willingness to pay for valuing the direct economic costs and total economic costs (TEC) of changes in soil conditions respectively. The respondents are drawn from the counties of Kirinyaga (223), Machakos- Mbooni (142) and Mbuuri - Laikipia (137) with data from all of them having being analyzed in the CVM and only those from Kirinyaga had their soils sampled and analyzed in the application of the replacement cost methodology.

In the replacement cost approach, the study uses the non-French bean growing farmers as the baseline category against which the group and individually compliant farmers are evaluated. This is principally occasioned by the lack of a baseline data against which the three compliant arrangements can be evaluated. Using this approach, the direct economic costs of soil changes for the non-compliant and compliant farmers are estimated at approximately Kshs 29,423 and Kshs 23,553. Further, when the CVM is applied, the mean total economic costs for all the sampled respondents is estimated at Kshs 2,166 while for the non-growers, the non-compliant farmers and the compliant farmers, the mean TECs are estimated at Kshs 1,746, Kshs 1,953 and Kshs 2,523 respectively. Farmers from Machakos County are found to have the highest mean TEC estimate at Kshs 2,316 followed by those from Laikipia - Mbuuri at Kshs 2,253 and finally those from Kirinyaga have the least mean estimated TEC at Kshs 2,017.


In evaluating the driving factors behind the various WTP values elicited from the respondents, the double hurdle model is chosen owing to its superiority over the other regression approaches. Principally, this model allows the analyst to distinguish those factors that influence the decision to participate in the hypothetical market scenario posed to the respondents and those that influence the magnitude of payments to be made once the respondent has chosen to participate in such a market. The factors that are found to influence the participation decision are; the households land to labor ratio, the county of the respondent being Machakos, the compliance status of the household, membership of the household to a farming group, the households use of credit and the importance that the respondents attaches to the hypothetical market scenario posed. The second decision i.e. magnitude of payments to make is found to be influenced by; importance attached to the hypothetical market scenario, contact with extension agents, households distance from the nearest market centre, the households annual income category, the
compliance status of the household, respondents awareness of existence of soil testing laboratories and finally the county of the respondents being Machakos.


This study thus offer valuable policy relevant insights first with regard to the economic value of changes in soil quality due to various agricultural practices carried out in the study area. Secondly, the study provides insights into the effect of compliance with agri-food standards on environmental value. As such, it provides possible lessons to be learnt out of possible regulation in the use of agro-chemicals in Kenya's agricultural sector.