JAMES TAYLOR
I am a Lecturer in Economics at the Australian National University, working out of the Research School of Economics. I enjoy economic theory, hiking, and casual mathematics.
RESEARCH
My research focus is in Microeconomic Theory, with a particular emphasis on Behavioural Decision Theory. My thesis includes works on common knowledge, knowledge aggregation in general, imprecise probabilities, and the common prior assumption. Titles and abstracts of thesis papers are below, and working papers can be provided on request.
Given a group of agents, each with heterogeneous information, there are many forms of combining agents' information. This paper introduces some language for investigating different methods of aggregating information within groups, where the knowledge of each agent takes the general operator form. A number of specific aggregation formulations are considered in detail, including what `somebody knows', what `everybody know', common knowledge, and distributed knowledge. Distributed knowledge is what can be determined by cooperating agents, given their information, under direct communication. Regularity and preservation properties of aggregators are investigated and applied to the specific aggregators listed.
COMMON KNOWLEDGE FOR RATIONAL AND BEHAVIOURAL AGENTS
An implicit idea in the classic concept of common knowledge is that all agents possess perfect information processing; this occurs when agents have partitional knowledge. This paper discusses some of the shortcomings of the classic definition of common knowledge. When agents have non-partitional knowledge, the classic common knowledge operator may not satisfy positive introspection. It also does not properly consider many reasonable knowledge questions that one would expect to see in a common knowledge operator. We propose an alternative definition of common knowledge which solves these problems, and reduces to the classic definition when all agents have partitional knowledge. We discuss further alternative definitions of common knowledge.
IMPRECISE PROBABILITIES UNDER GENERAL INFORMATION STRUCTURES
This work proposes a new model for imprecise probabilities based around the use of a general information structure for each agent, called the Behavioural Imprecise Probability. A strict separation of Knightian risk and uncertainty is used, where risk is described using a standard probability measure, and uncertainty is captured by the information structure of the agent. This model is appropriate when the agent knows the underlying probability of a given state of the world, but faces incomplete information about the true state of the world. An agent views an event as at least as likely as the probability they know the event happens, and at most as likely as the probability they think the event is possible. The results of Tversky and Kahneman (\textit{Phychological Review}, 1983) are explained using behavioral imprecise probabilities.
CYCLES AND COMMON PRIORS WITHOUT FULL SUPPORT (NOTE)
When analyzing the possibility of common prior existence, most of the literature focuses only on common priors with full support. This paper extends the cycles approach (Rodrigues-Neto, J Econ Theory 2009 and J Math Econ 2012) used for checking common prior existence to the case of posteriors and common priors without full support, characterizes the models where a common prior (with any support) exists, and computes the maximal support for a common prior. Checking all cycle equations remains a sufficient condition for the existence of a common prior even when priors and posteriors of some states may be zero, however this is no longer a necessary condition. Properties of the common prior arising from connected and disconnected graphs are considered, with an emphasis on models with full support posteriors.
ATOMIC CYCLES AND COMMON PRIOR EXISTENCE (NOTE)
Harsanyi's Consistency Problem (Management Science, 1967-8) asks whether a given set of posteriors is consistent with a common prior. Rodrigues-Neto (J Econ Theory, 2009) proposes a solution to this problem using a multigraph built from the agents' information partitions called a meet-join diagram. A common prior exists if and only if for all cycles of the meet-join diagram an equation called the cycle equation is consistent. This work shows that a common prior exists if and only if the cycle equations for atomic cycles are consistent. It is therefore necessary and sufficient to check cycles of length 2d+1 where d is the diameter of the meet-join diagram, or length 2d in the two agent case. This generalizes the result of Hellwig (Economics Letters, 2013) in the two agent case.
TEACHING
My lecturing experience at the Australian National University has focused on core Microeconomics, Mathematical Economics, and Econometric Forecasting. Course sizes have ranged from 25 to 550 students, covering core and elective subjects for both undergraduate and masters students.
MICROECONOMICS 1
This is a standard Microeconomics 1 course, covering Supply and Demand, Market Structures, Public Goods and Externalities, and International Trade. Game Theory and Behavioural Economics are discussed briefly.
Lecture Slides Forthcoming
MICROECONOMICS 3
This is an advanced course in Microeconomic Theory, following Varian. The course covers consumer and producer theory, market structures, price controls, and a range of topics in microeconomic theory.
FORECASTING FOR BUSINESS AND ECONOMICS
This is a standard Forecasting Course combining theory and practical elements. Theory is driven mainly by matrix calculus to maximise likelihood functions. Practical work is done using Matlab, and focuses on building forecasting tools from the ground up.
Lecture Slides forthcoming.
MATHEMATICAL TECHNIQUES FOR ECONOMIC ANALYSIS
This course covers required mathematical techniques for standard economic analysis at the upper undergraduate and graduate levels. Topics covered include Calculus and Optimisation, Linear Algebra, Probability, and Proof Methods.
Due to the nature of the material, the course was taught by hand, so detailed lecture slides are not available.
MATHEMATICAL TECHNIQUES FOR ADVANCED ECONOMIC ANALYISIS
This course is an intensive, non-credit summer course taught with 4 hour lecture, 4 days a week, for 4 weeks. The material is similar to that of Mathematical Techniques for Economic Analysis, but generally taught at a slightly higher level.
BUSINESS ECONOMICS
This is a Masters-level service course providing an introduction to Microeconomics and Macroeconomics for masters students in related disciplines; principally Finance and Accounting students.
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ACADEMIC BACKGROUND
PhD - Australian National University (2019)
PhB (Mathematics) - Australian National University (2010)
LECTURING
Microeconomics 1 (2021, 2020, 2019, 2018)
Business and Economic Forecasting (2021, 2020, 2019, 2018, 2016)
Business Economics (2021, 2020, 2019)
Microeconomics 3 (2021)
Mathematical Techniques for Advanced Economic Analysis (2018, 2017, 2015, 2014)
Mathematical Techniques for Economic Analysis (2016)
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CONFERENCE PRESENTATIONS
Australasian Economic Theory Workshop (2020, 2019, 2017)
Econometric Society European Meeting (2019)
Asian Meeting of the Econometric Society (2019)
Society for the Advancement of Economic Theory Conference (2018, 2016)
Center for Mathematical Social Science (2015)
