The p-Value Debate and Statistical (Mal)practice - Implications for the Agricultural and Food Economics Community

A vivid debate is ongoing in the scientific community about statistical malpractice and the related publication bias. No general consensus exists on the consequences and this is reflected in heterogeneous rules defined by scientific journals on the use and reporting of statistical inference. This paper aims at providing an overview on the debate, discussing how it is perceived by the agricultural economics community, and deriving implications for our roles as researchers, contributors to the scientific publication process, and teachers. Following a 'Mixed Methods Review', we start by summarizing the current state of the p-value debate in the context of the replication crisis and commonly applied statistical practices in our community. This is followed by motivation, design, results and discussion of an explorative and descriptive survey on statistical knowledge and practice among the researchers in the agricultural economics community in Austria, Germany and Switzerland. Instead of providing specific guidelines or rules, we derive implications for our roles in the scientific process to support a needed long-term cultural change regarding empirical scientific practices. Acceptance of scientific work should largely be based on the theoretical and methodological rigor and where the perceived relevance arises from the questions asked, the methodology employed, and the data used but not from the results generated. Revised and clear journal guidelines, the creation of resources for teaching and research, and public recognition of good practice are suggested measures to move forward.