This course will focus on game theory and its applications to various microeconomic issues. Topics covered
will include decision-making under uncertainty, strategic and extensive form games with complete information, Bayesian games, extensive form games with incomplete information. This course will also serve as a pre-requisite for Microeconomics 2 and concepts developed here will be extensively used for the economic analysis undertaken there.
How are economic allocations determined? This is perhaps the most central question in all of economics. This course will serve as a rigorous introduction to the theoretical body of work that economists use to address this question. The major focus will be on general equilibrium theory and the general competitive model, including its extensions to incorporate financial markets. Issues of asymmetric information in the context of the competitive model will also be covered. Besides this, the course will focus on some key theories in the areas of auctions, bargaining, money and banking, search and matching as they pertain to the central question of the course.
This course is an introduction to neoclassical growth, setting the theoretical foundations of modern macroeconomics. It will cover the theories of economic growth and long-run economic development and discuss how different factors such as human capital, physical capital, technology, trade, to name a few, contribute to economic growth. It will also deliberate over the empirical patterns which explain why different countries grow along different paths. The course aims to equip student with tools and ideas behind dynamic economic analysis.
This course will provide an in-depth treatment of recursive methods that are employed in modern macroeconomics. To that end, students will be introduced to the theory of dynamic programming as well as its application to growth models, models of investment, of consumption and savings, self-insurance, asset pricing, unemployment and unemployment insurance. The programming languages of Matlab and Python will be used to offer a rigorous introduction to quantitative methods in macroeconomics
This course is designed to equip students to learn statistical tools for analyzing real life data, related to economics in particular and social sciences in general. It will equip students both with theoretical knowledge as well as the know-how of how to implement theory through software applications like Stata. The main thrust of the course will be on cross-sectional data analysis. The course will also serve as a pre-requisite for Econometrics 2.
This course is on applied econometrics and will focus on introducing students to empirical methods used for policy evaluation in applied microeconomics research (such as labour, health, public, urban, education, environment and development economics). The course will cover topics such as causal inference, treatment effects, randomized controlled trials, differencing methods, instrumental variables, regression discontinuity design and matching methods. This course will involve surveying the existing literature on these empirical methods as well as learning to apply these techniques using cross-sectional and panel datasets.
Quantitative Methods in Economics :
This course will focus on developing the mathematical tools that are used extensively in microeconomics, macroeconomics, and econometrics. The course will cover the basics of real analysis, optimization, dynamic programming, and linear algebra.
Development Economics :
The course introduces students to analytical approaches to the study of development economics. It will develop basic concepts, theories and applied empirical evidence to provide an understanding of the main issues underpinning development economics. Topics covered include the economies of less developed countries, poverty traps, human capital investment in health and education, the changes in poverty, demography, the roles of individuals, families, institutions and policies. The course also aims to equip students with an understanding of a range of empirical methods in development. It will illustrate how economic models can provide insights into understanding behaviour and how the empirical implications of models can be assessed with appropriate choice of research design and econometric methods.