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Publication Success factors of farm investments : the example of Swiss dairy farms(2021) Kramer, Benedikt; Doluschitz, ReinerThis scientific analysis aims to identify success factors of farm investments, which are supported by interest free loans. The data basis consists of data from the Farm Accountancy Data Network (FADN) from 2003 through 2014 from Switzerland, which is matched to data from the Meliorations- und Agrarkredit-Projekt-Informations-System (MAPIS), where all supported dairy barn investments in Switzerland are registered. In addition, a Gini coefficient on the level of municipality is added, calculated from agricultural census data (AGIS). One of the main variables analysed is calculated profit. Another important variable, analysed in this work, is herd size. As a first step, the development of calculated profit and herd size change after investment are analysed by two separate fixed-effects panel regression models. The results show, that calculated profit is significantly and positively influenced by the amount of agricultural land of the farm and significantly reduced for the first three years after investment. From the fourth year onwards, no coefficients are significant anymore, which might either be caused by a divergent development of individual farms or by the diminishing number of observations. Herd size change is positive and significantly influenced by the amount of agricultural land. Also the period of quota phasing out affected herd size change positively. Dairy herds probably grew in the year before investment already and kept growing till five years after investment. Both dependent variables indicate that farms undergo an adjustment phase after investment. For the analysis of investment probability, the data sample is extended by including observations of all dairy farms and combined dairy/arable crop farms in the valley and hill region. Observations after investment are excluded. A logit regression model of the pooled data reveals that among the financial variables, only equity and farm income have a small positive and significant effect on investment probability. Social characteristics show a larger effect. The investment probability increases with age, farm household size and the presence of a partner. In order to analyse influencing factors of successful investments, investments that enable the farm to achieve the same or higher calculated profit as before, are considered successful. The year before investment is used as the basis and a Cox Proportional-Hazard-model is used to investigate those influencing factors. The model reveals that for farm having a higher calculated profit before investment, it is more difficult to restore that level after investment. Off-farm income and expenses for purchase of additional animals affect recovery of calculated profit significantly negative. The largest significant negative impact comes with more family labour. The results suggest that family labour which is likely to be freed up by productivity gains, is not reallocated to off-farm income. Additional indicators for land competition on the level of municipality are used. Agricultural income per family working unit is analysed as financial measure. This is a precursor for calculated profit and reflects financial efficiency of the input of family labor. In addition, growth of the dairy herd is analyzed. A random effects model is used for both variables. For dairy herd growth, utilized agricultural area and milk quota abolishment have a positive effect. More subsidized projects within a municipality and a higher concentration of acreage have a negative effect. For agricultural income per family working unit, utilised agricultural area, number of subsidized projects within a municipality, valley region and equity have a positive effect while milk quota abolishment has a negative effect. Off-farm income, which has been used as off-farm income per full-time working unit, showed no statistically significant effect. Neighboring effects appear to be more important for dairy herd growth than for agricultural income. Based on the derived definitions, success factors are identified. An adjustment phase is confirmed, while the productivity of family labour seems to be the most important influencing factor for recovering calculated profits of the pre-investment situation. Structural influences seem most important for herd size growth. With regard to the negative effect of off-farm labour, off-farm labour might be seen as enabling farms with off-farm labour to accept a lower level of labour productivity. In general, the social characteristics of farms seem to have a larger impact on dairy farm investments than financial variables. For investment support, the results imply not only to put emphasis on financial characteristics. In addition, the adjustment phase must be considered with investment plans. With such long lasting investments like dairy barns, strategic decisions by the farmer combined with family characteristics might be more important than financial indicators.