Applied economics

Applied economics is the study as regards the application of economic theory and econometrics in specific settings. As one of the two sets of fields of economics (the other set being the core), it is typically characterized by the application of the core, i.e. economic theory and econometrics to address practical issues in a range of fields including demographic economics, labour economics, business economics, industrial organization, agricultural economics, development economics, education economics, engineering economics, financial economics, health economics, monetary economics, public economics, and economic history. From the perspective of economic development, the purpose of applied economics is to enhance the quality of business practices and national policy making. The process often involves a reduction in the level of abstraction of this core theory. There are a variety of approaches including not only empirical estimation using econometrics, input-output analysis or simulations but also case studies, historical analogy and so-called common sense or the "vernacular". This range of approaches is indicative of what Roger Backhouse and Jeff Biddle argue is the ambiguous nature of the concept of applied economics. It is a concept with multiple meanings. Among broad methodological distinctions, one source places it in neither positive nor normative economics but the art of economics, glossed as "what most economists do". The origin and meanings of applied economics have a long history going back to the writing of Say and Mill. Say wrote about "applying" the "general principles of political economy" to "ascertain the rule of action of any combination of circumstances presented to us". The full title of Mill's (1848) work is Principles of Political Economy with Some of Their Applications to Social Philosophy. John Neville Keynes was perhaps the first to use the phrase "applied economics".

Reward timing matters in motor learning

One-shot learning and eligibility traces in sequential decision making

One-shot learning and eligibility traces in sequential decision making

Reward timing matters in motor learning