M.Sc. in Economics and Data Science

M.Sc. in Economics and Data Science program is an interdisciplinary graduate degree designed to equip students with advanced knowledge of economic theory and cutting-edge data science techniques. The program emphasizes integrating quantitative methods, programming skills, and analytical tools to address real-world economic and policy challenges. Graduates will be prepared for careers in academia, industry, or government, where they can leverage data-driven insights to inform decision-making and innovate in the digital economy.

As a flagship initiative of our university, this master’s program will serve as the cornerstone for establishing the Central Asia School of Economics (CASE), further solidifying our commitment to advancing economic research and policy analysis in Uzbekistan. CASE will be based on three pillars: MEDS, GEAR (The Greater Eurasia Research Center), and YESU (Young Economists Society of Uzbekistan) and we envision an emergence of vibrant and community of young economists, who will make a decisive contribution to the nation’s economic growth and prosperity.

Course Structure

The program consists of ECTS 126 credits distributed over two year full-time.

Classes are expected to be held four times a week in the morning and afternoon. Please note that the schedule is subject to change.

First Year
Semester	Course Code	Course	Course Type	ECTS Credits
Semester 1	ECON650	Macroeconomic Theory 1	Core	8
	ECON640	English for Academic Purposes	Core	8
	ECON612	Math for Economics	Core	4
	ECON611	Probability Theory and Statistics	Core	4
	ECON690	Econometrics 1	Core	4
	ECON610	Microeconomics 1	Core	4
Semester 2	ECON670	Macroeconomic Theory 2	Core	8
	ECON680	Foundations of Data Science	Core	8
	ECON620	Microeconomics 2	Core	4
	ECON630	Microeconomics 3	Core	4
	ECON660	Game theory	Core	4
	ECON695	Econometrics 2	Core	4
Total Credits				64

Second Year
Semester	Course Code	Course	Course Type	ECTS Credits
Semester 3	GRAD601	Research Methods in Humanities, Natural & Social Sciences	Core	8
	ECON720	Data science and machine learning	Core	8
	ECONEC	Graduate ECON Elective Course	Elective	4
	ECONEC	Graduate ECON Elective Course	Elective	4
	ECONEC	Graduate ECON Elective Course	Elective	4
	ECONEC	Graduate ECON Elective Course	Elective	4
Semester 4	ECON790	Capstone project/Master Thesis	Core	24
Total Credits				56

Program's Total Credits

120

Elective Course Options
Course Code	Course	ECTS Credits
ECONEC	Graduate ECON Elective Course	4
ECONEC	Graduate ECON Elective Course	4
ECONEC	Graduate ECON Elective Course	4
ECONEC	Graduate ECON Elective Course	4

Note: The structure of the course is subject to change.

Course Descriptions

Course Code	Course	ECTS Credits	Description
ECON610	Microeconomics 1	4	Is devoted to consumers’ behavior; covers classical consumer theory in a deterministic setup, including utility maximization and demand analysis. Then introduces the theory of choice under uncertainty, focusing on decision-making with risk and expected utility.
ECON620	Microeconomics 2	4	Is devoted to producer’s behavior in various market configurations (monopolistic, oligopolistic, and competitive markets). Two most common producer’s problems – cost minimization and profit maximization – will be considered. Optimal behavior of a firm for various market configurations will be derived. After adding the demand side, equilibrium outcomes at monopolistic, oligopolistic, and competitive markets, will be required.
ECON630	Microeconomics 3	4	Consists of two blocks. First is devoted to general equilibrium theory, which studies market clearing prices and quantities in perfectly competitive markets, in a setup that minimizes exogenous variables. Topics include the existence and efficiency of competitive equilibria, Walrasian equilibrium, and the fundamental theorems of welfare economics. It covers basic theory and extends to equilibrium under uncertainty, market failures (such as externalities), and the role of market completeness. Second is an introduction to information economics. The topics include problems of adverse selection and moral hazard, models of signaling and screening and a brief introduction to mechanism design.
ECON650	Macroeconomic theory 1	8	This course introduces basic concepts of macroeconomics such as national income, employment, the price level, interest rates, and the exchange rate. Reviews basic models that describe how these variables are determined in the long-run. Introduces IS-LM, aggregate demand and supply, and the Phillips curve analytical apparatus. Then it provides an introduction into theories of economic growth. Such models as Solow growth model, growth models with microeconomic foundations and endogenous growth theories are discussed.
ECON670	Macroeconomic theory 2	8	This course consists of two parts. The first part covers issues in the theory of consumption, investment and asset prices. Baseline models are studied: life cycle/permanent income hypothesis for consumption, Tobin’s q-theory for investment and CAPM/CCAPM theory for asset pricing, as well as extensions and modifications of the baseline models. The second part is an introduction into theories of business cycles. Alternative business cycle models such as Real Business Cycle and New Keynesian are introduced. Effects of fiscal and monetary policy are discussed.
ECON612	Math for Economics	4	Equips students with core mathematical tools for analyzing advanced economic models. Topics include constrained and unconstrained optimization, convex analysis, fixed-point theorems, and dynamic programming.
ECON611	Probability theory and statistics	4	Introduction to probability theory and statistics. Students master mathematical foundations of probability theory and basic methods of statistical analysis of data. Topics include basic concepts of probability theory, random variables and probability distributions, central limit theorems, hypothesis testing, confidence intervals.
ECON690	Econometrics 1	4	The course familiarizes students with basic concepts of econometric analysis. Students learn how to apply basic econometric models to cross-sectional data. The topics include: introduction to single-equation regression estimation; ordinary least-squares estimation, confidence intervals, and significance testing. Students also familiarize themselves with a regression software package.
ECON695	Econometrics 2	4	This course is the second part of the introductory econometrics sequence, designed to familiarize students with core econometric methods. Topics covered include models for time-series data, panel data, censored data, non-linear models and Generalized Method of Moments (GMM).
ECON660	Game theory	4	Introduces basic concepts and results of non-cooperative game theory. Core concepts such as dominance, Nash equilibrium, mixed strategies, and subgame perfection are presented in both static and dynamic settings.
ECON680	Foundations of Data Science	8	This course provides students with a practical introduction to the foundations of data science, combining programming, data handling, visualization, and modeling. The emphasis is on hands-on learning, with students developing projects throughout the entire course. The acquired skills will be applied to real-world cases drawn from economics and business.
ECON720	Data science and machine learning	8	Building on the foundational data science course, this class introduces advanced methods for economic data analysis and prediction using modern machine learning techniques. Students will work with supervised and unsupervised learning methods, including regularization, tree-based models, ensemble learning, clustering, and dimensionality reduction, with applications to real-world economic and financial data.
ECON623	English for academic purposes	8	This course is designed to help graduate students develop the academic writing skills necessary for success in coursework, research, and professional communication. It focuses on the conventions of academic English, including clarity, coherence, argumentation, and appropriate use of sources. Students will learn how to plan, draft, and revise a range of academic texts, such as essays, literature reviews, research papers, and reports.
ECON700	Research methods in Economics	6	This course introduces students to the principles and practices of economic research, preparing them to design and carry out independent research projects. Students will explore key areas of economic inquiry, review examples of empirical and theoretical studies, and learn about data sources, methodological approaches, and analytical tools commonly used in economics. A major focus is on formulating research questions, conducting literature reviews, and selecting appropriate research designs.
ECON690	Capstone project	24	The project allows students to apply their knowledge and skills to conduct an independent research project under the guidance of a faculty mentor, integrating concepts from various economics courses.
ECON710	Advanced game theory	4	This course builds on the foundations of non-cooperative game theory to explore advanced models and analytical techniques used in modern economic research. Topics include Bayesian games, mechanism design, repeated games, evolutionary game theory, bargaining models, and cooperative game theory.
ECON705	Development economics	4	Explores the key theories, empirical methods, and policy debates in development economics. It examines the causes and consequences of poverty, inequality, and underdevelopment, with a focus on market failures, institutions, and interventions in low- and middle-income countries.
ECON701	Energy & Environmental economics	4	Explores the economic dimensions of environmental issues, including pollution, natural resource depletion, climate change, sustainability, and policy approaches to address environmental challenges.
ECON713	Labour economics	4	Introduces the field of labor economics with a special focus on Central Asia. Covers theoretical models of labor supply and demand. Also, important concepts like human capital and discrimination are introduced. Institutional bases of labor market functioning are discussed.
ECON702	Transition economics	4	Covers various aspects of transition from central planning to a market-oriented system and the role of institutions in the economy in general. Analyses functioning of the traditional centrally planned economic system. Discusses key components of market-oriented reforms including price liberalization, privatization, and reform of government institutions.
ECON622	Growth theory and economic policy	4	Examines the theoretical foundations and empirical evidence of long-run economic growth and explores their implications for economic policy. It covers classical and modern growth models, including the Solow model, endogenous growth theories, and models with human capital, technology, and institutions.
ECON714	Applied policy analysis	4	This course trains students in the practical tools, frameworks, and methods used in real-world policy analysis. It bridges theory and practice, focusing on how evidence, data, and economic reasoning inform the design, implementation, and evaluation of public policies.
ECON709	Behavioral Economics	4	This course explores how insights from psychology and other behavioral sciences can enrich standard economic models of decision-making. It examines systematic departures from rational choice theory and analyzes how these deviations affect consumer behavior, savings, labor supply, health decisions, and public policy.
ECON629	Microeconometrics	4	Provides a thorough training in applied econometrics. Discusses both technical aspects of modern econometric approaches as well as application of these approaches in various fields of applied economic research. Topics may include quasi-experimental approaches to estimating causal effects (difference-in-difference, regression discontinuity, instrumental variables) or heterogeneous treatment effects.
ECON703	Topics in Macroeconomics	4	This course explores advanced and current research areas in macroeconomics, building on the analytical foundations developed in previous macroeconomics courses.
ECON625	International trade	4	This course examines the theories, empirical evidence, and policy issues surrounding international trade. It covers classical and modern trade theories (comparative advantage, Heckscher–Ohlin, etc.) and trade policy tools such as tariffs, quotas, and trade agreements.
ECON665	Public finance	4	This course examines the role of government in the economy, focusing on the theory and practice of taxation, public expenditure, and fiscal policy. It explores the efficiency and equity implications of different tax systems, public goods, externalities, social insurance, and intergovernmental fiscal relations.
ECON704	Principles of finance	4	This introductory course in financial management covers the key decisions made by an organization’s finance department: financial statements, time value of money, risk and return, investments, and corporate finance.
ECON667	Corporate finance/financial markets	4	This course provides an integrated view of corporate finance decisions and the functioning of financial markets. Topics include capital structure, corporate valuation, investment and financing decisions, dividend policy, risk management, asset pricing, and market efficiency.
ECON708	Financial econometrics	4	The course gives an introduction to the mathematical statistical and econometric analysis of time series data with emphasis on financial time series data (risk management, forecasting, derivatives pricing).
ECON675	Economic consultancy monitoring and evaluation	4	This course introduces students to the tools and practices used in economic consultancy and the design, monitoring, and evaluation of public policies, development programs, and business projects. Students will learn cost-benefit analysis, experimental and quasi-experimental methods, indicator development, and reporting.
ECON711	Industrial organization	4	This course examines the structure, conduct, and performance of firms and markets, focusing on market power, strategic interactions, and regulatory policies. Topics include game-theoretic models of imperfect competition, pricing strategies, entry/exit, product differentiation, innovation, R&D, and vertical relationships.
ECON706	Agricultural and natural resource economics	4	This course explores the economic principles and policy issues related to agriculture, natural resources, and the environment. Topics include production and consumption in agriculture, commodity markets, land and water resource management, sustainable resource use, government policies, climate change, and globalization.

Program degree requirements

To graduate from the Master of Science in Economics and Data Science program, students must meet the following academic, research and administrative requirements

Academic coursework
Completion of required credits: successfully complete a total of 120 ECTS credits as defined by the curriculum.
Capstone project: Master’s thesis
Conduct original research in economics and data science under faculty supervision. Submit a written thesis that meets academic standards and defend it successfully before a committee. The thesis should demonstrate the ability to apply data science methods to economic problems and contribute new insights to the field.
Internship (Optional for Applied economics track)
Applied Economics track requires an internship at a relevant role.
Attendance and participation
Meet the program’s attendance requirements, including participation in lectures, seminars, workshops, or other required academic activities.

Eshchanov Baxtiyor Ruzumbayevich

Head of Department

b.eshchanov@newuu.uz

Shapoval Aleksander Borisovich

Professor

a.shapoval@newuu.uz

Hannum Christopher Michael

Associate Professor

ch.hannum@newuu.uz

Chernina Evgeniia Markovna

Assistant professor

e.chernina@newuu.uz

Lehmann Hartmut Friedrich Hans

Professor

h.lehmann@newuu.uz

Program learning outcomes

Graduates of the M.Sc. in Economics and Data Science will possess:

Advanced Economic Knowledge: Master economic theories, models, and methodologies to analyze complex issues.
Proficiency in Data Science Tools and Techniques: Evaluate policies and market trends, applying evidence-based solutions using Python, R, or similar for data analysis and computational modeling.
Research Competence: Conduct independent research and communicate findings effectively. Develop and apply advanced mathematical and statistical methods to analyze economic phenomena and large datasets. Conduct independent and collaborative research using cutting-edge methods in economics and data science.
Global Perspective: Analyze economic issues from a global and multicultural perspective.
Ethical Decision-Making: Address ethical considerations in economic analysis and policy.
Global Perspective: Analyze economic issues from a global and multicultural viewpoint.
Leadership and Communication: Demonstrate leadership, teamwork, and clear communication of economic concepts.
Lifelong Learning: Commit to continuous learning and adaptability in evolving economic contexts.

Entry requirements

Bachelor degree from an accredited institution (minimum 180 ECTS credits) or a higher academic qualification (degree course format should be full-time or part-time)
A pass in Entrance Exam.

Applicants with a GRE/GMAT (10th or Focus edition) certificate may be exempt from the entrance exam. Their exam results will be based on their score in the GRE/GMAT Math (Quantitative) section.

To check how GRE/GMAT Math (Quantitative) score compares to the exam score, please use the equivalency table below.

If applicants prefer, they may still take the exam. In case of a difference between the score granted from the GRE/GMAT Math (Quantitative) section and the exam score, the higher score will be considered.

Equivalency table

GMAT 10th Edition
GMAT Score	Entrance Exam Score (in percentage)
50-51	100
48-49	95
46-47	90
44-45	85
42-43	80
40-41	75
38-39	70
36-37	65
34-35	60
32-33	55
30-31	50
28-29	45

GMAT Focus Edition
GMAT Score	Entrance Exam Score (in percentage)
89-90	100
87-88	95
85-86	90
83-84	85
81-82	80
79-80	75
77-78	70
75-76	65
73-74	60
71-72	55
69-70	50
67-68	45

GRE
GMAT Score	Entrance Exam Score (in percentage)
169-170	100
167-168	95
165-166	90
163-164	85
161-162	80
159-160	75
157-158	70
155-156	65
153-154	60
151-152	55
149-150	50
147-148	45

English language requirements

Proficiency in the English language as evidenced by one of the below:

IELTS 6.0 or higher
TOEFL iBT 60 or higher

Note: We accept only the TOEFL iBT taken at approved test centers. We do not accept the TOEFL iBT Home Edition.

CEFR B2 (56-60)

Applicants who have completed their bachelor’s degree entirely in English do not need to provide any additional proof of language proficiency.

Exam Format

Total Duration: 90 minutes

Total Number of Questions: 8

Total Marks: 70

Mark Per Correct Answer:
Section A - 8
Section B - 10

The following topics will be covered:

Linear algebra

Vectors, matrices, and operations with them. Linear dependence of a system of vectors. Basis of a linear space. Scalar product.
Determinant of a square matrix. Calculation of determinants. Expansion of a determinant along a row and a column.
Transposed matrix. Inverse matrix. Rank of a matrix. Special types of matrices.
Systems of linear equations. Cramer's method. Gaussian elimination method. Fundamental system of solutions.
Eigenvalues and eigenvectors of a matrix. Diagonalization and computing the powers of a matrix.

Mathematical analysis

Functions of one variable. Limit of a function. Derivatives. Taylor series expansion. Function analysis and graphing.
Functions of multiple variables. Partial derivatives. Total differential.
Gradient of a function. Directional derivative. Hessian matrix. Unconstrained extrema of multivariable functions. Necessary and sufficient conditions for extrema.
Basic integration. Definite and indefinite integrals.

Differential Equations

Equations with separable variables. Equations in total differentials. Change of variables method. Bernoulli equation.
First-order linear differential equations. Method of variation of constants.
Homogeneous linear differential equations with constant coefficients. Characteristic equation. Solution stability.

Probability Theory

Basic concepts of probability theory. Random events and random variables. Probability density function. Joint distribution of multiple random variables. Conditional distributions.
Characteristics of random variable distributions (expectation, variance, covariance). Properties of expectation, variance, and covariance. Conditional expectation.

Recommended Literature:

Gilbert Strang - Introduction to Linear Algebra
James Stewart - Calculus: Early Transcendentals
Dennis G. Zill - A First Course in Differential Equations with Modeling Applications
Sheldon Ross - A First Course in Probability

Exam Date and Deadline for Registration

Exam Date	Deadline for Registration
26th April	18th April
14th June	6th June
23rd August	15th August

Fees and Funding

Tuition Fee for 2025/2026 Academic Year
Local students	27 500 000 UZS per academic year
International students	$ 3 250 USD per academic year

Career Perspectives

M.Sc. in Economics and Data Science program emphasizes integrating quantitative methods, programming skills, and analytical tools to address real-world economic and policy challenges. Graduates will be prepared for careers in academia, industry, or government, where they can leverage data-driven insights to inform decision-making and innovate in the digital economy.

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M.Sc. in Economics and Data Science