Studies in Microeconomics

Studies in Microeconomics seeks high quality theoretical as well as applied (or empirical) research in all areas of microeconomics (broadly defined to include other avenues of decision science such as psychology, political science and organizational behavior). In particular, we encourage submissions in new areas of Microeconomics such as in the fields of Experimental economics and Behavioral Economics. All manuscripts will be subjected to a peer-review process. The intended audience of the journal are professional economists and young researchers with an interest and expertise in microeconomics and above.

In addition to full-length articles MIC is interested in publishing and promoting shorter refereed articles (letters and notes) that are pertinent to the specialist in the field of Microeconomics (broadly defined).

MIC will periodically publish special issues with themes of particular interest, including articles solicited from leading scholars as well as authoritative survey articles and meta-analysis on the themed topic.

We will also publish book reviews related to microeconomics, and MIC encourages publishing articles from policy practitioners dealing with microeconomic issues that have policy relevance under the section Policy Analysis and Debate.

TOPICS: Topics include (but are by no means restricted to): rational choice and individual decision making, consumer choice, producer choice, choice under uncertainty, game theory (cooperative, non-cooperative, static and dynamic), market equilibrium, market failure (imperfect competition, public goods and externalities), information economics, general equilibrium , social choice, welfare economics and mechanism design, as well as theoretical or empirical research in industrial organization and public economics that uses a microeconomic framework. Additionally, we are interested in promoting research involving laboratory and field methods to address important economic as well as policy relevant questions that are difficult to examine using the more traditional naturally occurring data.