Farmers’ characteristics’ and the propensity to reduce debt: The case for New Zealand (NZ) primary producers

2019 
Purpose - The purpose of this paper is to investigate a farm manager’s personal characteristics (personality, age, education, objectives, experience, etc.) as drivers of debt payback success and rates. Traditionally bankers have used historic business statistics, and equity levels, to assess loans and credit worthiness. It is hypothesised that a managers’ personal characteristics are likely to be a better predictor of future debt payback performance. Design/methodology/approach - The literature was searched to isolate the managers’ personal variables likely to determine debt payback. The information led to defining a quantitative model based on the theory of planned behaviour (TPB) which was hypothesised as determining payback rates where a choice was available. A postal random stratified survey of NZ owner operator farm managers provided the data to test the model and define its parameters using regressions, structural equation modelling and statistical comparisons. Findings - The modelling results make it clear a manager’s personal characteristics are highly correlated with debt payback and, logically, are very likely to be the drivers. Four random effects equations and a comparison of high- and low-debt payback managers led to this conclusion. Practical implications - Bankers should use the managers’ personal characteristics, as defined in the regressions, alongside traditional measures when assessing farm business loan requests. This approach is opposite to the traditional methods using mainly historic data. Originality/value - The use of the TPB in assessing debt payback is a new and novel approach showing how enduring personal characteristics can be used in assessing proposals, and particularly, entrepreneurs’ adventurist investments in situations where historic data are not available.
    • Correction
    • Source
    • Cite
    • Save
    • Machine Reading By IdeaReader
    64
    References
    3
    Citations
    NaN
    KQI
    []