Primal Analytical Foundations of Dynamic Production Analysis

This chapter develops dynamic production analysis within the context of the adjustment cost model of the firm, where adjustment costs are associated with changes in the level of the quasi-fixed factors, also known as internal adjustment costs. The chapter characterizes axiomatically several primal representations of the adjustment cost production technology. The axiomatic approach is a cornerstone to model production technology both in theoretical and empirical work. The existence of several representations of the adjustment cost production technology is essential in the analysis of the firm’s decisions and its adjustment path that are conditioned by the technology. Three set representations of the adjustment cost production technology are discussed and characterized axiomatically. Two functional representations of the technology are also addressed using an axiomatic approach.

The Role of DRD1 and DRD2 Receptors for Response Selection Under Varying Complexity Levels: Implications for Metacontrol Processes

Background Highly complex tasks generally benefit from increases in cognitive control, which has been linked to dopamine. Yet, the same amount of control may actually be detrimental in tasks with low complexity so that the task-dependent allocation of cognitive control resources (also known as “metacontrol”) is key to expedient and adaptive behavior in various contexts. Methods Given that dopamine D1 and D2 receptors have been suggested to exert opposing effects on cognitive control, we investigated the impact of 2 single nucleotide polymorphisms in the DRD1 (rs4532) and DRD2 (rs6277) genes on metacontrol in 195 healthy young adults. Subjects performed 2 consecutive tasks that differed in their demand for control (starting with the less complex task and then performing a more complex task rule). Results We found carriers of the DRD1 rs4532 G allele to outperform noncarriers in case of high control requirements (i.e., reveal a better response accuracy), but not in case of low control requirements. This was confirmed by Bayesian analyses. No effects of DRD2 rs6277 genotype on either task were evident, again confirmed by Bayesian analyses. Conclusions Our findings suggest that higher DRD1 receptor efficiency improves performance during high, but not low, control requirements, probably by promoting a “D1 state,” which is characterized by highly stable task set representations. The null findings for DRD2 signaling might be explained by the fact that the “D2 state” is thought to enhance flexible switching between task set representations when our task only featured 1 task set at any given time.

An Introduction to CORA 2015

The philosophy, architecture, and capabilities of the COntinuous Reachability Analyzer (CORA) are presented. CORA is a toolbox that integrates various vector and matrix set representations and operations on them as well as reachability algorithms of various dynamic system classes. The software is designed such that set representations can be exchanged without having to modify the code for reachability analysis. CORA has a modular design, making it possible to use the capabilities of the various set representations for other purposes besides reachability analysis. The toolbox is designed using the object oriented paradigm, such that users can safely use methods without concerning themselves with detailed information hidden inside the object. Since the toolbox is written in MATLAB, the installation and use is platform independent.