Global Economics - Junior

COURSE #: ECON 3003

Course description

Econometrics II is an advanced quantitative methods course which builds on the skills and knowledge acquired in Econometrics I. This course has four separate parts and introduces binary choice, time-series and panel data models. In the first part, students will revise and extend their knowledge of limited dependent variables with specific regression models needed to analyze binary, ordinal and count data of the type that is often found in analysis of survey data. The second part covers time-series regression analyses with special attention to issues of stationarity and seasonality, applicable in assessing the timing of effects and forecasting. In the third part, students will study the analysis of panel data using different regression models. In particular, the course will discuss pooled OLS, fixed and random effect models, The fourth part covers how to conduct field experiments and generate the resulting data using natural or quasi-experimental research designs.

Course Learning outcomes

At the end of this course students are expected to be able to:

• Interpret coefficients, odds ratios and marginal effects of linear and logistic regression models, as well as multinomial and ordered logistic regressions.
• Recognize and define Poisson distributed, truncated and censored numeric and categorical dependent variables
• Analyze time series with different patterns of autocorrelation, trend and seasonal fluctuations, detect structural breaks for use in forecasting
• Interpret short and long run impacts of shocks using vector autoregression and vector error correction models.
• Analyze cross-section time series, panel and dynamic panel data using pooled ordinary least squares regressions, fixed and random effect regressions, and the Arellano-Bond estimator
• Perform natural and quasi-experiments in order to estimate treatment and causal effects

Course Assessment and Grading

COURSE #: ECON 3004

Course Description

The International Economics: Trade, Theory and Policy course offers a comprehensive overview of the so called "real" or trade part of international economics. The course examines the causes and consequences of international trade, as well as provides an analysis of trade policy. Questions addressed include, but are not limited to: Why do nations trade? Who gains and who loses from trade? Is free trade optimal, or should it be restricted in some cases? Should countries intervene to influence the structure of their international trade? This course extensively uses tools from Microeconomics and Macroeconomics although set in a different and sometimes unfamiliar context. The course is not limited to theoretical models, though, and each topic is backed by the empirical evidence including examples from Central Asia economies. The course allows students to understand how theoretical models can be applied in real life.

Course Learning Outcomes

The expected learning outcomes for the students who will successfully complete the course are:

• define the driving forces of International trade
• identify gains and losses from free international trade for different categories of people
• recognize the interconnectedness between international economics and regional economic issues
• adopt formal models and analytical tools to real life economic problems
• identify important issues in contemporary international trade agenda and appreciate connections with the reality in Central Asia

Course Assessments and Grading

COURSE #: ECON 3006

Course Description

Natural Resource Economics applies microeconomic concepts and tools to such issues that arise from the growth, use, depletion and degradation of natural systems and their components, including land, energy, air, water, and biodiversity. It also looks for solutions that exploit economic facets of human behavior to address these issues in ways that get the most done at minimum cost. You will learn that economic objectives do not necessarily conflict with sustainability and environmental goals, and that markets can be harnessed to improve environmental quality and preservation of natural resource. We will also discuss the limitations of economic analysis to provide policy guidance on Natural Resource issues. The course begins with a review of microeconomic concepts related to the function (or dysfunction) of markets. We will look at standard (neoclassical) ways of understanding Natural Resource issues that arise when markets fail to deliver optimal/desirable outcomes with regard to natural resources, environmental quality, and the human benefits that derive from them. We will then learn about market-based, regulatory, and community-based approaches to achieving economic efficiency and/or sustainability within these systems. We will evaluate economic (and other) approaches to real-world problems in terms of efficient allocation, sustainable scale and just distribution.

Course Learning Outcomes

• Describe the economic aspects of natural resource issues
• Apply analytical tools (rhetorical, graphical, and mathematical) to describe the extent to which these issues constitute the failure of market systems
• Explain the difficulties arising in using economic analysis in natural resource policy design
• Recognize a number of real-world environmental policy problems, particularly those in the context of mountainous regions of Central Asia and evaluate in depth solutions to such problems using economic analysis.

Course Assessment and Grading

COURSE #: ECON 3008

Course Description

This course focuses on processes of economic development within the context of low and middle-income countries, emphasizing the implications for development strategies and policies. Key issues include the level and nature of inter-relationships between rural and urban development, the processes of economic transformation, and the role of institutions and policies in development. The analytical approach and many of the issues discussed are drawn from development economics, although these will be positioned within the broader geographical, social and political context of Central Asia. The course employs theories and skills learnt in other economics courses and applies them in a less abstract way through collection and analysis of data from various sources. By the end of the course, the students should be able to identify relevant problems constraining the economic (rural and urban) development of the individual Central Asian republics and approach these problems in a rigorous and critical way.

Course Learning Outcomes

By the end of this course the students will be able to:

• Discuss economic theories that have shaped growth and development
• Explain the causes and consequences of underdevelopment, poverty and income inequality
• Apply the tools of economic analysis to problems of rural and urban development
• Analyze policy initiatives undertaken to spur economic growth and their economic, social and environmental impact
• Employ theory and data to conduct basic economic analyses on issues specific to economic development
• Evaluate empirical work in development.

Course Assessment and Grading

COURSE #: ECON 4037

Course Description

Electricity plays a crucial role in our life, allowing us to perform our daily routines and to undertake economic, social and developmental activities. Economics of Electricity is an interdisciplinary economics course which covers both a detailed description of the technologies and institutions of the consumption, production and transportation sides of electricity markets.  A variety of core microeconomic concepts are introduced for non-economists, in order to better understand the behavior of firms, consumers and regulators in electricity markets. The course emphasizes issues related to both the local and the global electricity sectors, with an eye towards pricing, regulation and access. In particular, the tools learned in the course will set the foundations to conduct energy research, making use of quantitative data, write policy case studies, produce market forecasts and manage energy-related firms and investments. 

Course Learning Outcomes

At the end of the course in energy economics students are expected to be able to:

• Apply microeconomic modeling techniques to understand the functioning of a variety of energy markets and the impact of government actions in them;
• Discuss the special characteristics of wholesale and retail electricity markets, electricity pricing and electric grids;
• Model investment and other financial decisions for a variety of energy firms;
• Assess the effects of energy price volatility on energy importers and other sources of systemic risk;
• To explain the determinants of energy access and link between energy access and economic development;
• To evaluate programs for improving energy efficiency;

Course Assessment and Grading

COURSE #: ECON 4308

Course description

Data Science III: Automated statistical analysis of the terabytes of data that are produced every minute in text form is one of the frontiers of data analysis. It allows the integration of new data types in standard statistical analysis as well as new insights into the properties and significance of texts. Text Analysis is an advanced quantitative methods course which builds on the skills and knowledge acquired in Econometrics I & II. Students learn the tools required for statistical analysis of text, including working with character encodings, regular expressions and string functions.  The course progresses to construction of datasets from text, analysis of texts based on their similarity, sophistication and sentiment as well as classification of texts, descriptive statistics and data visualization for text data and description of texts based on topic.

Learning outcomes

At the end of this course students are expected to be able to:

• Classify texts based on characteristics using unsupervised learning algorithms
• Utilize regular expressions to write code for pattern matching in text strings
• Create variables from text strings and apply these in categorization of texts and analysis of text sentiment
• Extract sentiment information and other variables from text for application in traditional regression analysis
• Analyze the similarity and sophistication of texts for use in comparison between and identification of authors
• Perform Latent Dirichlet Analysis to determine the topics found in bodies of text

Course Assessment and Grading