Enhancing the competitiveness of Finnish organic production in the changing policy environment

Tiivistelmä

Common Agricultural Policy is changing affecting payments in member states after 2020. Furthermore, many governments are planning to cut back subsidies for organic farms in 2018. They see growing organic markets as the solution, not government subsidies. However, some warning signs have been reported in the Netherlands and Great-Britain as a result of decreased subsidies for organic farms; in Great-Britain organic land area has decreased almost 30 % during 2010-2015. In Finland, the current debate is focused on justification of higher subsidies for organic farms in the future, while statistics show that organic farms are already more profitable than conventional farms. At this time when organic production is facing decreasing subsidies, there is also an objective set by the government to increase the organic land area from the current 12 % to 20 % by 2020. It is not known how organic farming will be affected, facing these conflicting demands.

To answer these questions, this study aims to compare the economic performance of organic farms and conventional farms. Further, technical efficiency analysis is applied to answers the question if it is possible to improve economic performance of organic farming under the lower subsidies scenario by making production processes more productive and efficient. In this non-parametric Data Envelopment Analysis (DEA) -based approach, productivity and efficiency scores are estimated for each farm. Low efficiency farms are benchmarked against best performing technically efficient farms, and their use of inputs is compared against efficient organic farms. At the second stage, linear regression models are fitted to explain factors affecting the efficiency of organic farms.

In the third analysis, focus is on the health indicators and occupational health on organic farms. This study is based on two data. First one is interview data collected by the Finnish Institute of Occupational Health. The data contain agricultural production, work exposure and health outcome information for full-time farmers. A de-identified subset is requested, containing relevant variables for analysis. Data will be analysed using multivariable logistic regression modelling. The association of selected health indicator and organic production (vs. not) is examined while controlling for personal demographic and agricultural production variables. The hypothesis is that health indicators are better among organic producers while controlling for potential confounding factors. The second data is farm survey data. This analysis analysis e.g. health factors and financial reasons affecting farmer´s interest to convert to organic production.

Organic production is often considered and mentioned as a strategic choice of a farm as such. However, there is great variation among organic farms, too. There are big farms that are specialised on few crops and utilizing newest production technology and on the other hand smaller farms marketing their products directly from the farm. In this study, farmers´ attitudes towards management are recognized and different development paths are compared to all farms. The results of the study help to further develop farmers’ training, education and advisory services for farmers’ in organic production. This study is based on the same interview data as third analysis.