Local infrastructure governance in Peru:a systems thinking appraisal

Ensuring the through-life quality of infrastructure systems is a fundamental instrument in providing economic development and enhancing quality of life. The complexity of infrastructure networks themselves, the operations of the public entities which manage them and the governance systems which oversee them make this a challenging activity. This research uses the city of Arequipa in Peru as a case study to bridge the knowledge gap on the behaviour of such municipalities regarding the management of infrastructure systems. It employs qualitative Systems Dynamics Modelling through a methodology based on the V-Model, with its emphasis on validation and verification, and framed in the systems thinking approach. First, 67 variables characterising the management of infrastructure systems in Arequipa are identified from literature and semi-structured interviews with key actors. Second, a model of the system is constructed using Causal Loop Diagrams. Within this model, 33 feedback loops are identified, formed from the causal influences between variables. Third, a diagnosis is carried out that unequivocally illuminates the municipalities’ failure patterns. Fourth, by identifying leverage points, a paradigm shifting intervention is proposed along with tools that municipalities can implement to improve their performance. Finally, these proposals are validated with key actors through a focus group

Overconfident Investors, Predictable Returns, and Excessive Trading

The last several decades have witnessed a shift away from a fully rational paradigm of financial markets toward one in which investor behavior is influenced by psychological biases. Two principal factors have contributed to this evolution: a body of evidence showing how psychological bias affects the behavior of economic actors; and an accumulation of evidence that is hard to reconcile with fully rational models of security market trading volumes and returns. In particular, asset markets exhibit trading volumes that are high, with individuals and asset managers trading aggressively, even when such trading results in high risk and low net returns. Moreover, asset prices display patterns of predictability that are difficult to reconcile with rational-expectations–based theories of price formation. In this paper, we discuss the role of overconfidence as an explanation for these patterns