Measuring time preferences

We review research that measures time preferences—i.e., preferences over intertemporal tradeoffs. We distinguish between studies using financial flows, which we call “money earlier or later” (MEL) decisions and studies that use time-dated consumption/effort. Under different structural models, we show how to translate what MEL experiments directly measure (required rates of return for financial flows) into a discount function over utils. We summarize empirical regularities found in MEL studies and the predictive power of those studies. We explain why MEL choices are driven in part by some factors that are distinct from underlying time preferences.National Institutes of Health (NIA R01AG021650 and P01AG005842) and the Pershing Square Fund for Research in the Foundations of Human Behavior

Asset liability management using stochastic programming

This chapter sets out to explain an important financial planning model called asset liability management (ALM); in particular, it discusses why in practice, optimum planning models are used. The ability to build an integrated approach that combines liability models with that of asset allocation decisions has proved to be desirable and more efficient in that it can lead to better ALM decisions. The role of uncertainty and quantification of risk in these planning models is considered

Anomalies in Economics and Finance

The term “anomaly” played a crucial role in Thomas Kuhn’s characterization of scientific progress. For Kuhn, an anomaly is a puzzle which challenges an accepted paradigm. Puzzles only achieve anomalous status once an alternative paradigm becomes available which allows explanation of the puzzle. Anomalies were introduced into the finance literature by Michael Jensen but more as resolvable puzzles than Kuhnian anomalies. They entered economics via Richard Thaler who saw behavioural economics as the alternative to the neoclassical paradigm. Both authors use the term anomaly in a deliberately Kuhnian manner. Kuhn formulated his ideas by looking back across the history of physics. By contrast, behavioural economists use Kuhn’s concepts in a forward-looking manner as a marketing tool for their ideas.anomaly, behavioural, effects.

Agent-based modeling: a systematic assessment of use cases and requirements for enhancing pharmaceutical research and development productivity.

A crisis continues to brew within the pharmaceutical research and development (R&D) enterprise: productivity continues declining as costs rise, despite ongoing, often dramatic scientific and technical advances. To reverse this trend, we offer various suggestions for both the expansion and broader adoption of modeling and simulation (M&S) methods. We suggest strategies and scenarios intended to enable new M&S use cases that directly engage R&D knowledge generation and build actionable mechanistic insight, thereby opening the door to enhanced productivity. What M&S requirements must be satisfied to access and open the door, and begin reversing the productivity decline? Can current methods and tools fulfill the requirements, or are new methods necessary? We draw on the relevant, recent literature to provide and explore answers. In so doing, we identify essential, key roles for agent-based and other methods. We assemble a list of requirements necessary for M&S to meet the diverse needs distilled from a collection of research, review, and opinion articles. We argue that to realize its full potential, M&S should be actualized within a larger information technology framework--a dynamic knowledge repository--wherein models of various types execute, evolve, and increase in accuracy over time. We offer some details of the issues that must be addressed for such a repository to accrue the capabilities needed to reverse the productivity decline

Contested modelling

We suggest that the role and function of expert computational modelling in real-world decision-making needs scrutiny and practices need to change. We discuss some empirical and theory-based improvements to the coupling of the modelling process and the real world, including social and behavioural processes, which we have expressed as a set of questions that we believe need to be answered by all projects engaged in such modelling.  These are based on a systems analysis of four research initiatives, covering different scales and timeframes, and addressing the complexity of intervention in a sustainability context. Our proposed improvements require new approaches for analysing the relationship between a project’s models and its publics.  They reflect what we believe is a necessary and beneficial dialogue between the realms of expert scientific modelling and systems thinking.  This paper is an attempt to start that process, itself reflecting a robust dialogue between two practitioners sat within differing traditions, puzzling how to integrate perspectives and achieve wider participation in researching this problem space.&nbsp

Safety management theory and the military expeditionary organization: A critical theoretical reflection

Management of safety within organizations has become a key topic within safety science. Theorizing on this subject covers a diverse pallet of concepts such as “resilience” and “safety management systems”. Recent studies indicate that safety management theory has deficiencies. Our interpretation of these deficiencies is that much confusion originates from the issue that crucial meta-theoretical assumptions are mostly implicit or applied inconsistently. In particular, we argue that these meta-theoretical assumptions are of a systems theoretical nature. Therefore, we provide a framework that will be able to explicate and reflect on systems theoretical assumptions. With this framework, we analyze the ability of two frequently used safety management theories to tackle the problem of managing safety of Dutch military expeditionary organizations. This paper will show that inconsistent and implicit application of systems theoretical assumptions in these safety management theories results in problems to tackle such a practical problem adequately. We conclude with a reflection on the pros and cons of our framework. Also, we suggest particular meta-theoretical aspects that seem to be essential for applying safety management theory to organizations