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".
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In economics, dynamic inconsistency or time inconsistency is a situation in which a decision-maker's preferences change over time in such a way that a preference can become inconsistent at another point in time. This can be thought of as there being many different "selves" within decision makers, with each "self" representing the decision-maker at a different point in time; the inconsistency occurs when not all preferences are aligned.
In statistics, and particularly in econometrics, the reduced form of a system of equations is the result of solving the system for the endogenous variables. This gives the latter as functions of the exogenous variables, if any. In econometrics, the equations of a structural form model are estimated in their theoretically given form, while an alternative approach to estimation is to first solve the theoretical equations for the endogenous variables to obtain reduced form equations, and then to estimate the reduced form equations.
Innovation economics is new, and growing field of economic theory and applied/experimental economics that emphasizes innovation and entrepreneurship. It comprises both the application of any type of innovations, especially technological, but not only, into economic use. In classical economics this is the application of customer new technology into economic use; but also it could refer to the field of innovation and experimental economics that refers the new economic science developments that may be considered innovative.
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Covers inter-temporal calculations, landowner's arbitrage, and profitability evaluation in real estate economics.
Explores investment choice analysis, covering discounting, risk assessment, and financial evaluation methods like net present value and payback periods.
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In statistical modeling, regression analysis is a set of statistical processes for estimating the relationships between a dependent variable (often called the 'outcome' or 'response' variable, or a 'label' in machine learning parlance) and one or more independent variables (often called 'predictors', 'covariates', 'explanatory variables' or 'features'). The most common form of regression analysis is linear regression, in which one finds the line (or a more complex linear combination) that most closely fits the data according to a specific mathematical criterion.
Discount is the difference between the face value of a bond and its present value. We propose an arbitrage-free dynamic framework for discount models, which provides an alternative to the Heath-Jarrow-Morton framework for forward rates. We derive general c ...
Heidelberg2023
When humans or animals perform an action that led to a desired outcome, they show a tendency to repeat it. The mechanisms underlying learning from past experience and adapting future behavior are still not fully understood. In this thesis, I study how huma ...
Reward timing, that is, the delay after which reward is delivered following an action is known to strongly influence reinforcement learning. Here, we asked if reward timing could also modulate how people learn and consolidate new motor skills. In 60 health ...