Master Of Economics
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Master Of Economics
The Master of Economics (MEcon or MEc) is a postgraduate master's degree in economics comprising training in economic theory, econometrics, and/or applied economics. The degree is also offered as an MS or MSc, MA or MCom in economics; variants are the Master in Economic Sciences (MEconSc), and the Master of Applied Economics. Structure The degree may be offered as a terminal degree or as additional preparation for doctoral study, and is sometimes offered as a professional degree, such as the emerging ''MPS in Applied Economics''. The program emphases and curricula will differ correspondingly. The course of study for the master's degree lasts from one to two years. A thesis is often required, particularly for terminal degrees. Many universities (in the United States) do not offer the master's degree directly; rather, the degree is routinely awarded as a master's degree "en route", after completion of a designated phase of the PhD program in economics. Typically, the c ...
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Postgraduate
Postgraduate or graduate education refers to academic or professional degrees, certificates, diplomas, or other qualifications pursued by post-secondary students who have earned an undergraduate ( bachelor's) degree. The organization and structure of postgraduate education varies in different countries, as well as in different institutions within countries. While the term "graduate school" or "grad school" is typically used in North America, "postgraduate" is often used in countries such as (Australia, Bangladesh, India, Ireland, New Zealand, Pakistan, South Africa, and the UK). Graduate degrees can include master's degrees, doctoral degrees, and other qualifications such as graduate certificates and professional degrees. A distinction is typically made between graduate schools (where courses of study vary in the degree to which they provide training for a particular profession) and professional schools, which can include medical school, law school, business schoo ...
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Complementary
A complement is something that completes something else. Complement may refer specifically to: The arts * Complement (music), an interval that, when added to another, spans an octave ** Aggregate complementation, the separation of pitch-class collections into complementary sets * Complementary color, in the visual arts Biology and medicine * Complement system (immunology), a cascade of proteins in the blood that form part of innate immunity *Complementary DNA, DNA reverse transcribed from a mature mRNA template *Complementarity (molecular biology), a property whereby double stranded nucleic acids pair with each other *Complementation (genetics), a test to determine if independent recessive mutant phenotypes are caused by mutations in the same gene or in different genes Grammar and linguistics * Complement (linguistics), a word or phrase having a particular syntactic role ** Subject complement, a word or phrase adding to a clause's subject after a linking verb * Phonetic c ...
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Computational Economics
Computational Economics is an interdisciplinary research discipline that involves computer science, economics, and management science.''Computational Economics''."About This Journal"an"Aims and Scope" This subject encompasses computational modeling of economic systems. Some of these areas are unique, while others established areas of economics by allowing robust data analytics and solutions of problems that would be arduous to research without computers and associated numerical methods.• Hans M. Amman, David A. Kendrick, and John Rust, ed., 1996. ''Handbook of Computational Economics'', v. 1, ElsevierDescription & chapter-previelinks.    • Kenneth L. Judd, 1998. ''Numerical Methods in Economics'', MIT Press. Links tdescription anchapter previews Computational methods have been applied in various fields of economics research, including but not limiting to:    Econometrics: Non-parametric approaches, Semi-parametric approaches, and Machine Learning. Dynamic Sys ...
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Game Theory
Game theory is the study of mathematical models of strategic interactions among rational agents. Myerson, Roger B. (1991). ''Game Theory: Analysis of Conflict,'' Harvard University Press, p.&nbs1 Chapter-preview links, ppvii–xi It has applications in all fields of social science, as well as in logic, systems science and computer science. Originally, it addressed two-person zero-sum games, in which each participant's gains or losses are exactly balanced by those of other participants. In the 21st century, game theory applies to a wide range of behavioral relations; it is now an umbrella term for the science of logical decision making in humans, animals, as well as computers. Modern game theory began with the idea of mixed-strategy equilibria in two-person zero-sum game and its proof by John von Neumann. Von Neumann's original proof used the Brouwer fixed-point theorem on continuous mappings into compact convex sets, which became a standard method in game theory and mathem ...
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Generalized Linear Model
In statistics, a generalized linear model (GLM) is a flexible generalization of ordinary linear regression. The GLM generalizes linear regression by allowing the linear model to be related to the response variable via a ''link function'' and by allowing the magnitude of the variance of each measurement to be a function of its predicted value. Generalized linear models were formulated by John Nelder and Robert Wedderburn as a way of unifying various other statistical models, including linear regression, logistic regression and Poisson regression. They proposed an iteratively reweighted least squares method for maximum likelihood estimation (MLE) of the model parameters. MLE remains popular and is the default method on many statistical computing packages. Other approaches, including Bayesian regression and least squares fitting to variance stabilized responses, have been developed. Intuition Ordinary linear regression predicts the expected value of a given unknown quanti ...
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Simultaneous Equation Methods (econometrics)
Simultaneous equations models are a type of statistical model in which the dependent variables are functions of other dependent variables, rather than just independent variables. This means some of the explanatory variables are jointly determined with the dependent variable, which in economics usually is the consequence of some underlying equilibrium mechanism. Take the typical supply and demand model: whilst typically one would determine the quantity supplied and demanded to be a function of the price set by the market, it is also possible for the reverse to be true, where producers observe the quantity that consumers demand ''and then'' set the price. Simultaneity poses challenges for the estimation of the statistical parameters of interest, because the Gauss–Markov assumption of strict exogeneity of the regressors is violated. And while it would be natural to estimate all simultaneous equations at once, this often leads to a computationally costly non-linear optimization p ...
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Multivariate Time Series
In mathematics, a time series is a series of data points indexed (or listed or graphed) in time order. Most commonly, a time series is a sequence taken at successive equally spaced points in time. Thus it is a sequence of discrete-time data. Examples of time series are heights of ocean tides, counts of sunspots, and the daily closing value of the Dow Jones Industrial Average. A time series is very frequently plotted via a run chart (which is a temporal line chart). Time series are used in statistics, signal processing, pattern recognition, econometrics, mathematical finance, weather forecasting, earthquake prediction, electroencephalography, control engineering, astronomy, communications engineering, and largely in any domain of applied science and engineering which involves temporal measurements. Time series ''analysis'' comprises methods for analyzing time series data in order to extract meaningful statistics and other characteristics of the data. Time series ''forecast ...
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Multiple Linear Regression
In statistics, linear regression is a linear approach for modelling the relationship between a scalar response and one or more explanatory variables (also known as dependent and independent variables). The case of one explanatory variable is called ''simple linear regression''; for more than one, the process is called multiple linear regression. This term is distinct from multivariate linear regression, where multiple correlated dependent variables are predicted, rather than a single scalar variable. In linear regression, the relationships are modeled using linear predictor functions whose unknown model parameters are estimated from the data. Such models are called linear models. Most commonly, the conditional mean of the response given the values of the explanatory variables (or predictors) is assumed to be an affine function of those values; less commonly, the conditional median or some other quantile is used. Like all forms of regression analysis, linear regression focuses on ...
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Heterodox Economics
Heterodox economics is any economic thought or theory that contrasts with orthodox schools of economic thought, or that may be beyond neoclassical economics.Frederic S. Lee, 2008. "heterodox economics," '' The New Palgrave Dictionary of Economics'', 2nd Edition, v. 4, pp. 2–65 Abstract. These include institutional, evolutionary, feminist, social, post-Keynesian (not to be confused with New Keynesian), ecological, Austrian, complexity, Marxian, socialist, and anarchist economics. Economics may be called '' orthodox'' or ''conventional'' economics by its critics.C. Barry, 1998. ''Political-economy: A comparative approach''. Westport, CT: Praeger. Alternatively, mainstream economics deals with the "rationality–individualism–equilibrium nexus" and heterodox economics is more "radical" in dealing with the "institutions–history–social structure nexus". A 2008 review documented several prominent groups of heterodox economists since at least the 1990s as working tog ...
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Representative Agent
Economists use the term representative agent to refer to the typical decision-maker of a certain type (for example, the typical consumer, or the typical firm). More technically, an economic model is said to have a representative agent if all agents of the same type are identical. Also, economists sometimes say a model has a representative agent when agents differ, but act in such a way that the sum of their choices is mathematically equivalent to the decision of one individual or many identical individuals. This occurs, for example, when preferences are Gorman aggregable. A model that contains many different agents whose choices cannot be aggregated in this way is called a heterogeneous agent model. The notion of the representative agent can be traced back to the late 19th century. Francis Edgeworth (1881) used the term "representative particular", while Alfred Marshall (1890) introduced a "representative firm" in his ''Principles of Economics''. However, after Robert Lucas, J ...
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Heterogeneity In Economics
In economic theory and econometrics, the term heterogeneity refers to differences across the units being studied. For example, a macroeconomic model in which consumers are assumed to differ from one another is said to have heterogeneous agents. Unobserved heterogeneity in econometrics In econometrics, statistical inferences may be erroneous if, in addition to the observed variables under study, there exist other relevant variables that are unobserved, but correlated with the observed variables; dependent and independent variables .M. Arellano (2003), Panel Data Econometrics', Chapter 2, 'Unobserved heterogeneity', pp. 7-31. Oxford University Press. Methods for obtaining valid statistical inferences in the presence of unobserved heterogeneity include the instrumental variables method; multilevel models, including fixed effects and random effects models; and the Heckman correction for selection bias. Economic models with heterogeneous agents {{Further, Agent-based computational ...
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Dynamic Stochastic General Equilibrium
Dynamic stochastic general equilibrium modeling (abbreviated as DSGE, or DGE, or sometimes SDGE) is a macroeconomic method which is often employed by monetary and fiscal authorities for policy analysis, explaining historical time-series data, as well as future forecasting purposes. DSGE econometric modelling applies general equilibrium theory and microeconomic principles in a tractable manner to postulate economic phenomena, such as economic growth and business cycles, as well as policy effects and market shocks. Terminology As a practical matter, people often use the term "DSGE models" to refer to a particular class of econometric, quantitative models of business cycles or economic growth called real business cycle (RBC) models.Christiano (2018) Considered to be classically quantitative, DSGE models were initially proposed by Kydland & Prescott, and Long & Plosser;Long & Plosser (1983) whereby Charles Plosser described RBC models as a precursor for DSGE modeling. As mentione ...
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