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NMIMS-Va Tech: Dual Degree Masters Program

Pamplin Hall

Focuses on the allocation of scarce resources in regard to the development and management of environmental and natural resources. Pre: ECON 2005.

Credit Hour(s): 3
Instruction Type(s): Lecture, Online Lecture

Use economic analysis to critically analyze government activities. Pre: ECON 3104.

Credit Hour(s): 3
Instruction Type(s): Lecture, Online Lecture

Use of economic analysis to critically analyze government activities related to revenue-generating, inefficiencies of taxes and social insurace programs. Pre: ECON 3104.

Credit Hour(s): 3
Instruction Type(s): Lecture, Online Lecture

Introduction of the use of theoretical and empirical analysis to build formal models to understand and explain the labor market and wage determination. Pre: ECON  2005 and 3254.

Credit Hour(s): 3
Instruction Type(s): Lecture, Online Lecture

Introduction to the theory of industrial organization and understanding firm behavior and competition. Pre: ECON 3104.

Credit Hour(s): 3
Instruction Type(s): Lecture, Online Lecture

Introduction to the economic definitions of the terms growth and development, the role of agriculture and industrialization, and the lives of the poor. Pre: ECON 2006 and 3104.

Credit Hour(s): 3
Instruction Type(s): Lecture, Online Lecture

Analysis of the Chinese economy with a focus on events since the creation of the Republic of China. Pre: ECON 3104.

Credit Hour(s): 3
Instruction Type(s): Lecture, Online Lecture

Economic analysis of the health care industry in terms of supply and demand of services, insurance, and government health policy. Pre: ECON 2005.

Credit Hour(s): 3
Instruction Type(s): Lecture, Online Lecture

Introduction of the use of mathematical and statistical concepts to analyze data in regards to various economic theories (probability, statistical) and models (bivariate regression, stochastic regressors). Pre: STAT 3005

Credit Hour(s): 3
Instruction Type(s): Lecture, Online Lecture

Analysis of the interaction between firms, consumers, and governments in regard to incentives when information is missed by managers and shareholders. Pre: ECON 3104 and MATH 1226 or 1026.

Credit Hour(s): 3
Instruction Type(s): Lecture, Online Lecture

Introduction to game theory and strategic behavior such as the Nash equilibrium and the Core. Pre: ECON 3104 and MATH 1226 or 1026.

Credit Hour(s): 3
Instruction Type(s): Lecture, Online Lecture

Introduction to the methodology for testing economic theories through familiarization of state-of-the-art research methodology by participating in and designing experiments. Pre: ECON 3104 and STAT 3005 or BIT 2406.

Credit Hour(s): 3
Instruction Type(s): Lecture, Online Lecture

Examination of the field of neuroeconomics using an interdisciplinary research approach that focuses on reward valuation in and by the brain. Pre: ECON 3104 or PSYC 2004 or NEUR 2025.

Credit Hour(s): 3
Instruction Type(s): Lecture, Online Lecture

Analysis of economic data with focus on understanding of decision-making in financial markets. Behavior of and optimal outcomes for individuals (consumption, savings, and investment), financial institutions (lending, borrowing, and risk management), regulators, and policymakers. Statistical tools and inference using recent data sets. Pre: 3254 or 4304. (3H, 3C)

Credit Hour(s): 3
Instruction Type(s): Lecture, Online Lecture

Intersection of advanced topics in philosophy, politics, and economics. Pre: PHIL/PSCI/ECON 2884

Credit Hour(s): 3
Instruction Type(s): Lecture, Online Lecture

Use of microeconomic principles to study the law, the effects laws have on citizens behavior and wellbeing, and the best laws for society. Use economic analysis to analyze goals of the legal system and effectiveness of laws. Pre: ECON 2005

Credit Hour(s): 3
Instruction Type(s): Lecture, Online Lecture

This sequence, which is part of the core curriculum in the Economics Ph.D. program, covers fundamental concepts at the foundation of modern microeconomic theory. The sequence relies heavily on calculus and other mathematical tools. 5005: noncooperative game theory, competitive and non-competitive markets, theory of the firm. 5006: consumer theory, general equilibrium and welfare economics, uncertainty and asymmetric information.

Credit Hour(s): 3
Instruction Type(s): Lecture, Online Lecture
Prerequisite(s):

This sequence, which is part of the core curriculum in the Economics Ph.D. program, covers fundamental concepts at the foundation of modern microeconomic theory. The sequence relies heavily on calculus and other mathematical tools. 5005: noncooperative game theory, competitive and non-competitive markets, theory of the firm. 5006: consumer theory, general equilibrium and welfare economics, uncertainty and asymmetric information.

Credit Hour(s): 3
Instruction Type(s): Lecture, Online Lecture
Prerequisite(s): ECON 5005

Part of the core curriculum in the Econ PhD program provides an intensive treatment of modern macroeconomic and monetary theory. The course uses mathematical tools and analytic concepts. National income accounts; effective demand; neoclassical and Keynesian theories of capital and interest; supply and demand in money securities markets; introduction to macroeconomic dynamics; rational expectations.

Credit Hour(s): 3
Instruction Type(s): Lecture, Online Lecture

Part of core curriculum in the Econ PhD program providing an intensive treatment of modern macroeconomic and monetary theory. The course uses mathematical tools and analytic concepts. National income accounts; effective demand; neoclassical and Keynesian theories of capital and interest; supply and demand in money securities markets; introduction to macroeconomic dynamics; rational expectations.

Credit Hour(s): 3
Instruction Type(s): Lecture, Online Lecture
Prerequisite(s): ECON 5015

Extensive treatment of new techniques for economic modeling. Review of linear algebra and calculus; static optimization, with Lagrangian and Kuhn-Tucker methods; differential and difference equations; dynamic optimization, with calculus of variations, optimal control, and dynamic programming.

Credit Hour(s): 3
Instruction Type(s): Lecture, Online Lecture

Extensive treatment of new techniques for economic modeling. 5125: Probability and statistical inference, linear regression and related dynamic models, specification, estimation, misspecification, respecification, identification. 5126: Simultaneous equations, dynamic systems, time series, limited dependent variable models.

Credit Hour(s): 3
Instruction Type(s): Lecture, Online Lecture

Extensive treatment of new techniques for economic modeling. 5125: Probability and statistical inference, linear regression and related dynamic models, specification, estimation, misspecification, respecification, identification. 5126: Simultaneous equations, dynamic systems, time series, limited dependent variable models.

Credit Hour(s): 3
Instruction Type(s): Lecture, Online Lecture
Prerequisite(s): ECON 5125 (UG) OR ECON 5125

Markets and market structure. Methods for analyzing regulatory data. Antitrust law with a focus on U.S. institutions. Vertical and horizontal mergers. Anticompetitive behavior with a focus on collusion and monopolization. Regulation of price, entry, and the environment. Cost-benefit analysis, valuing nonmonetary benefits, and contingent valuation studies.

Credit Hour(s): 3
Instruction Type(s): Lecture, Online Lecture
Prerequisite(s): STAT 5054, STAT 5214G

Applications of price theory to applied problems at the graduate level. Utility maximization and demand, price indices, and short- and long-run demand. Discrete choice and product quality, location choice, and human capital. Profit maximization, cost minimization, factor demand, and industry model. Durable goods, capital accumulation, and value of a statistical life. Empirical analysis: formulating research questions, finding data from multiple sources, econometric analysis, and presenting findings to non-specialists. Students are assumed to have an understanding of principles-level microeconomics.

Credit Hour(s): 3
Instruction Type(s): Lecture, Online Lecture
Prerequisite(s): Graduate standing.  Principles-level microeconomics

Applied econometrics dealing with big data. Theoretical, computational, and statistical underpinnings of big data analysis. The use of econometric models and deep machine learning algorithms to analyze the high-dimensional data sets. Implications in research focusing on economic questions that arise from rapid changes in data availability and computational technology. Materials are hands-on tutorials that come with Python codes and real-world data sets. Pre: Graduate Standing. (3H, 3C).

 

Credit Hour(s): 3
Instruction Type(s): Lecture, Online Lecture

An intensive coverage of the most important techniques of econometric estimation and hypothesis testing, addressing the use of both cross-section and time series data. A core sequence in the MA program in both locations. Prerequisite to the research-thesis seminar in Northern Virginia.

Credit Hour(s): 3
Instruction Type(s): Lecture, Online Lecture
Prerequisite(s): ECON 2115 (UG) OR ECON 2116 (UG) OR ECON 2005 (UG) OR ECON 2006 (UG) OR ECON 2125 (UG) OR ECON 2126 (UG) OR ECON 2025H (UG) OR ECON 2026H (UG) OR ECON 2115 OR ECON 2116 OR ECON 2005 OR ECON 2006 OR ECON 2125 OR ECON 2126 OR ECON 2025H OR ECON 2026H

An intensive coverage of the most important techniques of econometric estimation and hypothesis testing, addressing the use of both cross-section and time series data. A core sequence in the MA program in both locations. Prerequisite to the research-thesis seminar in Northern Virginia.

Credit Hour(s): 3
Instruction Type(s): Lecture, Online Lecture
Prerequisite(s): AAEC 5126 OR ECON 5126

Laboratory techniques are valuable for answering research questions which defy traditional empirical analysis due to lack of field data. Examples include proposed regulations, new market designs and tests of theory. The goal of this course is two-fold: to develop skills in experimental methods appropriate for economics and related fields and to familiarize students with the results of experimental tests of economic theory. Requirement: Graduate or honors undergraduate, major standing, and permission of the departmental director of graduate study or course instructor.

Credit Hour(s): 3
Instruction Type(s): Lecture, Online Lecture

Emphasizes strategic behavior in the presence of multiple decision makers. Game theory deals with strategic interaction and provides the formal framework to describe and analyze situations with conflicting interests--as well as situations with both common and conflicting interests. Proof of applicability is provided by means of numerical examples and real life cases, e.g., bargaining, contract theory, economic policy games, and voting.

Credit Hour(s): 3
Instruction Type(s): Lecture, Online Lecture
Prerequisite(s): (ECON 5005 (UG), ECON 5006 (UG)) OR (ECON 5005, ECON 5006)

Psychological, social, and cognitive factors in economic decisions. Topics include risk and ambiguity, intertemporal choice and self-control, bounded rationality, heuristics, emotions, social norms, social preferences, learning, attention, and inference. Applications include contracting, bargaining, labor, development, industrial organization, finance, and macroeconomics.

Credit Hour(s): 3
Instruction Type(s): Lecture, Online Lecture
Prerequisite(s): ECON 5006

This course assumes a basic understanding of multiple regression and simultaneous equations modeling and introduces students to advanced econometric techniques commonly used in empirical work. These techniques include linear time series modeling in the time domain, discrete choice models, and panel data methods.

Credit Hour(s): 3
Instruction Type(s): Lecture, Online Lecture
Prerequisite(s): ECON 5126

A modern approach to economics of growth and development for graduate students in economics and related disciplines. Topics include sources of growth; neo-classical, endogenous, and dualistic theories of growth; households economics and human capital accumulation; economics of population; and consequences of imperfect market for land, labor and capital.

Credit Hour(s): 3
Instruction Type(s): Lecture, Online Lecture
Prerequisite(s): (ECON 3104 (UG), ECON 3204 (UG)) OR (ECON 3104, ECON 3204)

Labor demand and supply, investment in human capital, discrimination in the labor market, and the theory of equalizing wage differentials; search and unemployment, unions, and income distribution.

Credit Hour(s): 4
Instruction Type(s): Lecture, Online Lecture
Prerequisite(s): ECON 5005

This course describes the theory of government expenditures, stressing market failure as the rationale for government activity. The course describes the normative outcome achieved by a benevolent government, and the positive outcome achieved under rules of collective choice. Tax policy for different levels of government and selected topics in state and local public finance are also addressed.

Credit Hour(s): 3
Instruction Type(s): Lecture, Online Lecture
Prerequisite(s): (ECON 5005 (UG), ECON 5006 (UG) OR (ECON 5005, ECON 5006)

Effects of industry structure on price and non-price behavior of firms, on market equilibrium, and on economic welfare. Problems of oligopolistic industries and analysis of government policies (regulation, anti-trust).

Credit Hour(s): 3
Instruction Type(s): Lecture, Online Lecture
Prerequisite(s): ECON 5005 (UG) OR ECON 5005

Introduction to major panel data techniques and modeling ideas currently employed (e.g., dynamic panel, panel for discrete choice model, treatment effect and program evaluations etc.), including both statistical theory derivations and practical applications.

Credit Hour(s): 3
Instruction Type(s): Lecture, Online Lecture
Prerequisite(s): (AAEC 5125 OR ECON 5125), AAEC 5126

Bayesian estimation of economic models, with focus on Gibbs sampling, hierarchical modeling, data augmentation, and model search. Strong emphasis on programming and computational implementation.

Credit Hour(s): 3
Instruction Type(s): Lecture, Online Lecture
Prerequisite(s): AAEC 5126 OR ECON 5126 OR STAT 5304 OR STAT 5444

Specification and estimation of static, dynamic oligopoly models, application of these models to the study of entry and market structure, vertical relationships, and collusion. Empirical application of auction models to economic development and to public finance.

Credit Hour(s): 3
Instruction Type(s): Lecture, Online Lecture
Prerequisite(s): ECON 5005

The philosophical and methodological problems underlying econometric modeling and inference. Topics include the distinction between statistical and substantive significance, the proper interpretation of inference p-values, data mining, and other issues related to reliable inference and learning from data.

Credit Hour(s): 3
Instruction Type(s): Lecture, Online Lecture
Prerequisite(s): ECON 5125

Theoretical frameworks for real business cycle models, New Keynesian models, and monetary policy. Applying network theory and information theory to macroeconomics. Dynamic modeling, programming, and empirical macroeconomics.

Credit Hour(s): 3
Instruction Type(s): Lecture, Online Lecture
Prerequisite(s): ECON 5006, ECON 5016

Review and discussion of current research in economics by students, faculty members, and guest speakers. This course may be repeated for a maximum of 6 credits. Students are required to have Doctoral Standing in Economics.

Credit Hour(s): 1
Instruction Type(s): Lecture, Online Lecture

The M.A. program in Economics has the distinction of being housed in the College of Science at Virginia Tech.. The program aims to integrate economic theory with modern data techniques to prepare students for the new-age economy.  The students will earn a portfolio of skills to learn about how economists in various fields use mathematical models and interpret statistical evidence to think about problems in the context of business, policy circles, and academia.  Apart from learning about the standard theory and modeling toolkit in economics, the students in this program will be trained in modern data techniques.  This combination of skills is highly valued in the new-age economy.  Students interested in pursuing a Ph.D. in Economics will also be able to take a wide range of electives from our doctoral courses while enrolled in the M.A. program.


The primary goal of this program is to integrate modern data techniques with economic theory to teach students how to apply economic theory and quantitative methods to address questions relevant to the context of industries, academia, and policy institutions.  The economics graduate curriculum at Virginia Tech. is known to meet the need of the modern sectors, which is evidenced by the most recent placements from our STEM-certified Ph.D. program in companies such as Geiko, Capital One, Discover Financials, GM Financials, and Activision Blizzard.  The M.A. program is designed to prepare students equally well for careers in banking and finance, market research, government, and consulting. The program will also prepare students interested in pursuing a Ph.D. in Economics.