The demand for M3 and inflation forecasts: An empirical analysis for Switzerland

The Demand for M3 and Inflation Forecasts: An Empirical Analysis for Switzerland. — This paper argues that money should continue to play an important role in monetary policy even if a central bank pursues a strategy based on inflation forecasts. Within the context of an error correction model, the paper delivers empirical evidence that both the growth rate of the monetary aggregate M3 and the size of excess M3 incorporate useful information with regard to future inflation in Switzerland. This evidence strongly suggests that money should remain an important indicator for monetary policy.     

Optimal design of experiments to identify latent behavioral types

Bayesian optimal experiments that maximize the information gained from collected data are critical to efficiently identify behavioral models. We extend a seminal method for designing Bayesian optimal experiments by introducing two computational improvements that make the procedure tractable: (1) a search algorithm from artificial intelligence that efficiently explores the space of possible design parameters, and (2) a sampling procedure which evaluates each design parameter combination more efficiently. We apply our procedure to a game of imperfect information to evaluate and quantify the computational improvements. We then collect data across five different experimental designs to compare the ability of the optimal experimental design to discriminate among competing behavioral models against the experimental designs chosen by a “wisdom of experts” prediction experiment. We find that data from the experiment suggested by the optimal design approach requires significantly less data to distinguish behavioral models (i.e., test hypotheses) than data from the experiment suggested by experts. Substantively, we find that reinforcement learning best explains human decision-making in the imperfect information game and that behavior is not adequately described by the Bayesian Nash equilibrium. Our procedure is general and computationally efficient and can be applied to dynamically optimize online experiments.

     

What Drives ETF Flows?

The value of exchange traded fund (ETF) assets has increased from $66 billion in 2000 to almost a trillion dollars in 2010. We use this massive expansion in ETF assets to study what drives ETF flows. Using a data set of over 500 ETFs from 2001 to 2010, we show that ETF investors chase returns in the same way as mutual fund investors. While there is an active debate about whether return chasing by mutual fund investors represents the pursuit of superior talent, the existence of return chasing in this passively managed environment should not represent a search for skilled managers. We also show that ETF flows increase following high volume, small spreads, and high price/net asset value ratios. Finally, we find little evidence of superior market timing in ETF flows. Our results suggest that return chasing in both mutual funds and ETFs is more likely the result of naïve extrapolation bias on the part of investors that has contributed to the growth of the ETF industry.     

What factors influence auditors' use of computer-assisted audit techniques?

To meet the challenges of rapid advances in client technology, audit standards urge auditors to use computer-assisted audit tools and techniques (CAATs). However, recent research suggests that CAAT use is fairly low. This paper uses the Unified Theory of Acceptance and Use of Technology (UTAUT) to identify and then examines factors potentially influencing auditors' use or non-use of CAATs. Examining auditor use of CAATs is important because CAATs hold out the promise of improving audit efficiency and effectiveness. Data was obtained from 181 auditors from Big 4, national, regional, and local firms. Results indicate that outcome expectations, the extent of organizational pressures and technical infrastructure support influence the likelihood that auditors will use CAATs.     

Price and yield effects of spill-overs in international agricultural research: evidence from ICRISAT and Australia

International agricultural research aimed at improving productivity in developing countries also has spill-over effects on developed countries. Research that affects the supply of commodities is also likely to affect the world price of tradeable commodities. In this paper, the effects of spill-overs to Australia from successful cost-reducing research into sorghum and chickpeas at die International Crops Research Institute for the Semi-Arid Tropics (ICRISAT) aimed at developing countries are assessed. Genetic materials developed and distributed through ICRISAT are used in Australia to increase productivity. The price-reducing effects of successful research are incorporated into the analysis of spill-over impacts on productivity. The net effects on welfare for producers and consumers of sorghum and chickpeas in Australia and the Rest of the World (ROW) are identified. The consequences of the impacts are discussed and the implications for further funding of international agricultural research are also discussed.     

A Common Nomenclature for Stated Preference Elicitation Approaches

It is often difficult to determine what actually was done in work involving data collected with stated preference surveys because the terms used to describe various procedures have ambiguous and sometimes conflicting meanings. Further, terms used to describe data collection procedures often are confounded with terms used to describe statistical techniques. We call for the use of a common nomenclature to describe what was done in a data collection effort for stated preference studies, and take a first step at setting out such nomenclature. We only seek to improve clarity in the communication of research results and take no position here on appropriateness of particular procedures.     

Context Effects in a Negatively Framed Social Dilemma Experiment

A number of studies of the positively-framed voluntary contribution mechanism (VCM) public goods game have examined the role of context on participant behavior. Relatively little attention, however, has been given to the effects of context in negatively-framed VCM games even though this setting is relevant to a wide array of real world challenges, such as common pool resource use and pollution externalities. This study uses a carefully-controlled laboratory experiment to investigate the degree to which the context in which decisions are made influences decision making in a negatively-framed VCM laboratory experiment. The context treatments that we evaluate vary communication, voting, and the status quo of the initial endowment. Results indicate that providing groups the opportunity to communicate and vote significantly reduces choices that impose external costs. Importantly, the pro-social effects of communication and voting are strongest when the status quo endowment is the private account, which generates costs on other participants. This result suggests that the effect of the status quo endowment is a function of whether the social dilemma is framed positively or negatively when communication between participants is allowed.     

Innovation in the medical device sector: an open business model approach for high-tech small firms

Innovation in the medical device industry is progressing rapidly with many technologies heralded as major breakthroughs. The public are often well informed about these matters, which results in a patient pull for innovations that are years from market. HTSFs operating in this environment face huge challenges in terms of realising the latent economic potential from new innovations. Open innovation offers the prospect of lower costs for innovation, faster times to market, and the chance to share risks. By developing open business models medical device companies can capture the multifaceted ideas of scientists, engineers, clinicians and indeed patients; thus allowing beneficial technologies to reach the market more quickly in a way that is evidence focused. This study uses a qualitative approach to investigate the explicit and implicit business models within HTSFs in the health care sector and provides a useful contribution to understand the challenges and identify solutions in this multi-stakeholder environment.