A logic system for the choice of risk levels in hypothesis testing

We have examined current, traditional practice of establishing risk levels, favoring use of small α and implicitly accepting correspondingly larger β errors. There are both loses and gains associated with this approach. In particular, small a minimizes the probability of erroneously rejecting H_o, but it also increases the chances that a new model, representing a real improvement, may be discarded. There is no overwhelming logic that one type of error is always more important than the other, since relative costs vary with the conditions surrounding the research investigation.     

A Laboratory Science Approach to Teaching in the Agricultural Economics Curriculum

We argue that economic laboratory experiments can facilitate active learning of theory in the agricultural economics curriculum by placing students in decision-making roles. Three types of experimental protocols are described, along with a discussion of the costs and benefits of experiments. The Double Auction Experiment provides a platform for demonstrating concepts of equilibrium, price discovery, externalities, excess supply, surplus, and speculation. The Monopoly Experiment is a platform for demonstrating concepts of advance production, inventory carryover, monopoly pricing, and search strategies. The Oligopoly Experiment is a platform for demonstrating concepts of thin markets, coordination, and imperfectly competitive equilibria.     

Adoption of organic farming in Germany and Austria: an integrative dynamic investment perspective

Farm‐level adaptation to changing economic environments is often slower than expected. Technological innovations, for instance, are frequently adopted at a later date than the net present value of investment suggests. This can be explained by a model of “investment under uncertainty,” which consistently accounts for uncertainty, sunk costs, and the flexibility of investment timing. Its essential conclusion is that, due to temporal opportunity costs, critical incremental cash flows that trigger investments might be higher than those needed for simple cost recovery. This accounts for an ostensible reluctance to invest (economic hysteresis). In this article, we demonstrate how slow conversion to organic farming in general, and the different rates of conversion in Germany and Austria in particular, can be explained by the new investment theory.     

Comparing Inference Methods for Non‐probability Samples

Social and economic scientists are tempted to use emerging data sources like big data to compile information about finite populations as an alternative for traditional survey samples. These data sources generally cover an unknown part of the population of interest. Simply assuming that analyses made on these data are applicable to larger populations is wrong. The mere volume of data provides no guarantee for valid inference. Tackling this problem with methods originally developed for probability sampling is possible but shown here to be limited. A wider range of model‐based predictive inference methods proposed in the literature are reviewed and evaluated in a simulation study using real‐world data on annual mileages by vehicles. We propose to extend this predictive inference framework with machine learning methods for inference from samples that are generated through mechanisms other than random sampling from a target population. Describing economies and societies using sensor data, internet search data, social media and voluntary opt‐in panels is cost‐effective and timely compared with traditional surveys but requires an extended inference framework as proposed in this article.