Post Graduate Program in Economics

The purpose of these courses is to prepare students for the Core Courses that will follow. Since not all students accepted into the program will have a rigorous quantitative training essential for an economics program, the Foundations Courses will introduce them to the essential elements of mathematical and statistical tools. For students who do join the program with some quantitative training, the Foundations Course will serve to review concepts in a practical and applied manner.

Learning Outcomes & Skills

• Rigorous understanding of mathematical and statistical concepts
• Ability to apply mathematical and statistical tools to economics
• Preparedness for the Core Courses

Foundation course will cover two subjects:

1) Mathematics

In this course students will learn:

• Counting – Permutations and Combinations and Binomial Coefficients/Theorem
• Introduction to Functions – Graph of Common Functions, Composite, Inverse, Continuity
• Functions – Limits, Continuity, Asymptotes
• Introduction to the Concept of Derivatives – Simple rules and examples
• Derivatives – Product, Chain, Implicit
• Maxima and Minima – Convexity, Concavity, Inflection
• Partial Derivatives
• Applications of Derivatives
• Constrained Optimization, Lagrangian
• Introduction to Integration as Limit of a Sum – Introduction to Anti-Derivatives, FTC to connect the dots
• Common Integration Techniques, Solving Problems
• Definite Integrals, Area Under the Curve, Producer-Consumer Surplus and Other Problems
• Linear Algebra (separate module for Data Science students, with the option to audit for Economics students)

Learning outcomes of this course:

• Familiarize students with undergraduate to postgraduate mathematics
• Learn how mathematics is useful in analytics.
• Ability to solve mathematical problems
• Preparedness for the Core Course

2) Statistics

Data Scientists work with data drawn from the real world, and students are required to become proficient with the basic tools of data analysis. In this course students will learn:

• What a random variable is, and how to describe it using the concept of probability
• How to work with common probability distribution functions such as the Binomial, Poisson and Normal distributions
• How to compute the expected value and variance of a random variable
• How to work with jointly distributed random variables
• How to formulate a statistical hypothesis, and how to test it
• How to compute confidence intervals
• Markov Chain methods.

Learning outcomes of this course::

• To familiarize students with undergrad to post-graduate statistics.
• Applications of statistics into business and data analytics, economics and finance, and variance fields of studies.

After developing a solid quantitative foundation, all students are required to take a set of four Core Courses:

1. Applied Microeconomics
2. Advanced Macroeconomics
3. Econometrics
4. Data Management & programming

Each of these courses lead the students into an in-depth exploration of topics that every economist is expected to be proficient in. These courses will also prepare students for the Elective Courses, which provide training in more specialized sub-disciplines of finance, public policy and data analytics.

Learning Outcomes & Skills

• Rigorous understanding of markets and how they function
• Ability to solve problems in microeconomics and macroeconomics
• Ability to structure and analyze economic data with R programming
• Knowledge of real-world markets, economies and policies
• Ability to critically evaluate news articles about ongoing economic developments in India and abroad
• Ability to critically evaluate academic and policy research in economics
• Ability to write short- and long-form pieces on real-world economics issues
• Ability to prepare and understand simple financial accounts
• Preparedness for stream specialization in the Elective Courses

Applied Microeconomics

Course objectives: Applied Microeconomics course provides theoretical analysis of different types of markets along with real life reflections including insights into reasons for failure of the competitive market and government interventions through public policies. Microeconomics is a study of isolated and collective interaction of small, individual units that make up the economy, namely, consumers, producers and markets.  It studies behavior of economic agents in resolving trade-offs and achieve constrained and unconstrained optimization with the help of mathematical framework.

Course contents: Thrust areas are consumers’, producers’ decision – making mechanism, market equilibrium and competitive goods and factor markets, choices under uncertainty and risks, market failure and role of government and markets with asymmetric information. Mathematical interpretation of the theory will be an integral part of the course. Application of theory to the real world situations and current issues will be an important facet of this course.

Learning Outcomes: 

• Comprehensive understanding of the domain knowledge
• Ability to apply mathematical reasoning to the theory and make estimates regarding competitive market outcomes, equilibriums, and optimal solutions
• Ability to develop independent critical thinking to understand limitations of competitive markets in real life
• Ability to analytically evaluate efficacies of public policies.

Advanced Macroeconomics

Course objectives: The objectives of this course are to understand the principles and practice of macroeconomics and that economics and politics are intertwined. The course will help students make sense of the present-day macroeconomic context globally and in India.

Select topics: Basics of Macroeconomics such as the Solow Growth model and IS-LM, Macroeconomic and national income concepts, monetary and fiscal policies, money, credit and banking, exchange rate concepts and exchange rate regimes, financialization and the global financial crisis of 2008.

Learning outcomes:

• have a good understanding of macro-economic theories and their ability to explain the real world
• be prepared and equipped to undertake further higher studies in economics.
• be able to interpret economic data and make sense of them
• be able to connect the dots of politics, economics, history and society and understand which of them is the more important force and in what circumstances
• be able to opine on and make futuristic statements on the direction of the macroeconomy with awareness of the limitations of such statements
• be equipped to work in areas related to economic policy and analysis in government and in the private sector

Econometrics

Course objectives: The objective of this course is to introduce students to the fundamental ideas and tools in Econometrics in an applied and intuitive way.

Select topics: Bi-variate and multivariate linear regression, assumptions under the linear regression model and their failure, extensions to the linear regression framework- log-log models, quadratic models,etc., logistic and probabilistic regression models.

Learning outcomes: By the end of this course, students will have a good theoretical and practical understanding of the fundamental econometric models and be well equipped to apply them on real-world data using tools such as R.

Data Management and Programming

Course objective: The primary objective of this course is to provide a firm foundation in the application of data science principles to various fields of study, especially, Economics and Finance. The course will be exclusively taught on Python and particularly caters to programming novices.

Select topics:

Installation; IDEs (IDLE, Jupyter Notebook); a programmer’s logic view of a computer; basic data types int, float, string, boolean; variables; the None type; print and input functions, escape sequences; operators – arithmetic, assignment,  relational, Boolean and identity operators; the format function; the sys.argv object; string functions; iterability, subscripting and indexing of objects; Unicode strings; the list data type, list functions, list comprehension; list operators, the tuple data type; the class type; the range class; the for loop; the while loop; nested loops; the enumerate function; the zip function; introduction to itertools; python in-built functions; the if, elif, else statements; mandatory code indentation in Python;  user-defined functions – declaration, arguments, body, return, variable number of arguments, named arguments; lambda functions; nested functions; generator functions; the dictionary data type; items, keys, values of a dictionary, dictionary methods; list of dictionaries; sorting a list of dictionaries; mutable and immutable data types; the numpy package; ndarrays; numpy methods; the pandas package; the dataframe type; the series type; the groupby type; dataframe indexing – iloc and loc; dataframe operations; filtering a dataframe using a boolean array; pandas functions; dataframe columns and index; multi-index; pivot tables; dataframe apply method; pandas merge; sorting of sortable types; the set data type.

Learning Outcomes: At the end of this course students would have grasped the essentials of core Python concepts and be extremely comfortable processing data on Python.

There are 10 elective courses on offer, of which, students will choose 4 for credit (and are allowed to audit one or more of the remaining 6). Of the 10, 9 are divided into 3 streams of 3 courses each. A student is not required to, but may wish to, specialize in one of the 3 streams, and if he/she decides to do so, then he/she must take all 3 courses in that stream, and 1 additional course to complete the 4 for-credit courses.

1. Finance
2. Public Policy
3. Data Analytics

Data Analytics
Machine Learning–

Course objective: The purpose of this course is to familiarize the students with modern machine learning models. Most of the courses in this area either focus on the concept or application of machine learning algorithms. This is an introductory course for theoretical machine learning. Furthermore, in this course, most models will be explained with great details such as problem statements, solutions, algorithms, implementation, and solving real-world problems with actual data.

Select topics:

• Statistical Learning
• Data Prepossessing / Cleaning
• Linear Regression
• Classification
• Resampling Methods
• Linear Model Selection and Regularization
• Non-Linear Regression
• Tree-Based Methods
• Support Vector Machines
• Unsupervised Learning

Learning outcome: By the end of this course, students will be able to formulate real-world problems and their solutions using mathematics and move on to advance machine learning techniques. The course will also prepare students with advanced skills for programming with machine learning models.

Time Series Econometrics

Course objective: This course is designed to familiarize students with the econometric tools used in time series analysis and implement those tools on real-world economic and financial data.

Select topics:

• Random walk
• Unit root process
• Seasonality
• ARMA and ARIMA models
• Box-Jenkins methodology
• ARCH-GARCH models

Learning outcomes: By the end of this course, students will be familiar with the theoretical underpinnings of time series analysis, be able to build models with time-series data, run them and interpret the results on R.

Advanced Econometrics for policy analysis–

Course Objectives: This course will equip students with advanced tools in Econometrics, used in evaluating public policy outcomes and beyond.

Select topics:

• Instrumental Variables
• Two-Stage Least Squares,
• Propensity Score Matching,
• Regression Discontinuity Design,
• Difference-in-Difference and Quantile Regressions

Learning outcomes:

By the end of this course, students will be able to assess the different contexts in which these econometrics techniques can be applied and how to apply them on real-world data. This course will benefit students interested in applied econometrics, data analytics and public policy evaluation.

Finance
Financial Statements Analysis–

Course Objectives:

The key objective of this course is to equip students with a solid understanding of financial statements and its application with real world examples. The course will focus on analyzing and interpreting financial statements with the aim of performing a fundamental analysis of the company and forming a view on its overall prospects. This course will provide Economics students the financial acumen which they can apply to not just in economics based roles, but also to core finance and risk roles offered in the industry.

Select Topics:

• Introduction to financial markets and understanding of company and industry lifecycles.
• Understanding structure and concepts of financial statements and be able to interpret them in the context of the business environment
• Understand various accounting terms and key accounting concepts – including terms used under GAAP/IND-AS.
• Create financial spreads in excel, interpret key ratios and make an initial assessment
• Understand applications of FSA – close look at the Fundamental Analysis process. Understand how an Equity investor views a company vis-à-vis its lenders or Bondholders – walkthrough actual Equity Research reports and Credit Rating Rationales.
• Bank Analysis – compare and contrast the business models of a typical corporate to that of a Bank. Overview of financial statements & CRAMEL framework for analyzing Banking entities
• Hands on practice with live examples to deepen the knowledge and tune into real life cases.

Learning Outcomes:

• Ability to easily interpret the financial statements and understand their linkages.
• Be able read a live Annual Report and use various analytical tools to assess a company.
• Know about various ancillary sources of information available and apply it to perform a comprehensive assessment of a company.
• Ability to easily understand Credit Rating Rationales and Equity Research reports.

Corporate Finance

Course Objectives:

Corporate finance is concerned with understanding what financial managers should do to increase company value. This course is designed to introduce essential aspects of financial decision-making in businesses. The primary objective is to provide the framework, concepts, and tools for analyzing financial decisions based on fundamental principles of modern financial theory. We will work with live examples to study the application of these concepts. This course will provide Economics students the financial acumen which they can apply to not just for economics based roles, but also to core finance and risk roles offered in the industry.

Select Topics:

• We will build on the concept of time value of money and understand how this concept can be used for capital budgeting decisions.
• Financial statement analysis, key ratios and free cashflow concepts
• Understand Risk and return, Cost of Capital and Capital Asset Pricing Model (CAPM)
• Why is capital structure important? Does Debt matter and how much should a corporation borrow?
• Payout policy – can dividend decisions impact corporate value? How does a firm decide its Dividend policy?
• Understand how companies are valued? How to security analysts and credit analysts assess companies? Relative and intrinsic valuation techniques (DCF model)
• Why do companies resort to Mergers and Acquisitions – understand the basics of Merger mechanics

Learning Outcomes:

• This course will help in understanding the financial aspects of managerial decisions which create value for the business.
• Key learning outcomes will be to apply skills in evaluating capital budgeting decisions by using different project evaluation criteria; perform time-value calculations by using financial mathematics; understand capital structure and dividend decisions and application of various valuation techniques to value businesses.

Measuring Risk in Equity & Fixed Income Markets–

Risk Management forms a very important function for any organization. It is closely linked with the strategic goals of any organization. A risk-managed business is appealing to investors, lenders, suppliers etc. and this helps in overall growth of an Enterprise in both the short run as well as the long run.

Course objectives:

1. Begin with the basics of capital markets and products, this course builds on to further concepts like derivatives, risk analytics etc.
2. The portion is designed to help candidates build a sound and in depth understanding of financial and risk concepts. Concepts covered are used frequently in the industry.

Select Topics:

• Capital Market Ecosystem
• Understanding of Debt markets – bond pricing, credit spreads, spot rates etc.
• Understanding of equity markets – Index, Beta, etc..
• Understanding of Derivatives markets – Linear (Forwards, Futures, FRA etc.) and non-Linear products (Options, Interest rate options etc.)
• Option Pricing models- Binomial , Black Scholes Merton, Black’s model
• Options trading strategies for risk management
• Risk Management – Market Risk, Credit Risk analytics, Risk mgmt in banks
• Capital and Regulatory – Organizational policies, regulatory guidelines etc.

Learning Outcomes:

1. Candidates will build expertise and confidence in key areas of finance and risk management
2. Course will provide Economics candidates the financial acumen which they can apply to not just for economist roles but also to core finance and risk roles offered in the industry
3. Candidates will get a flavour of some hands-on modelling activities during the course which will help them connect theory with practice

Public Policy –
Public Policy of Development– This course will provide an understanding of how economics can be used to understand development policies in the real world. Students will learn to analyze complex public policy issues in development as well as evaluate the impact of different policy approaches to a particular problem. In this course students will learn:

1. What determines the decisions of poor households in developing countries?
2. What are the different types of risks faced by poor households and how can we mitigate them?
3. How do we make schools work better for poor citizens?
4. How do we make poor citizens healthy?
5. How do we analyze the effectiveness of microfinance on economic and social development?
6. What is the scope for policy interventions in India and what policies have been tried out?
7. How to evaluate the impact of public programs using modern empirical methods in economics, such as Randomized Control Trials (RCTs).

International Political Economy– International Political Economy studies the intricate relationships between markets and states, between money and power, and between economics and politics, and is essential for students hoping to find employment in public policy roles in today’s global context. In this course students will learn:

1. Why policymakers must pay attention to the interplay between economics and politics in designing effective policy
2. What the main economic theories of trade are, and why these theories prescribe that countries should liberalize trade
3. Why countries often choose not to liberalize trade, and what forms trade cooperation has in fact taken in the last 100 years
4. What the main economic theories of FDI are
5. How countries compete to attract multinational corporations
6. Why China’s accession to the WTO in 2001 is a significant event in the history of multilateral trade liberalization
7. What the Trans-Pacific Partnership means for its signatories and for those who have chosen not to sign the TPP
8. What the political-economic considerations for liberalizing international finance are (with particular reference to the Euro project and its apparent failure)
9. The fundamental principles of exchange rate economics, and why global financial stability requires the intervention and oversight of multilateral institutions such as the IMF

Behavioural and Experimental Economics: This course introduces the major insights of behavioral and experimental economics to individual choice, social choice, and public policy. The course will first establish fundamental principles in behavioural and experimental economics. The last module of the course will explore the cutting-edge research in behavioral and experimental economics and its implications for public policy. In this course students will learn

1. How to critically assess existing theories in economics using experimental data and understand behavioural basis for the same.
2. How to explore theories in behavioural economics and assess their applicability.
3. How to use behavioral insights to inform individual, household, and social decision-making.
4. How to review complex public policy problems through the lens of principles of behavioural economics.
5. How to analyze data from experiments to evaluate and fine tune policies that could not be easily tested with naturally occurring data.

Crises– The 2008 Global Financial Crisis highlights the importance of understanding the myriad ways in which financial and macroeconomic systems are susceptible to episodic collapse. This course will teach students:

1. A brief history of financial crises during the last 100 years
2. How, in most of those cases, crises were precipitated by macroeconomic mismanagement leading to the buildup of speculative asset price bubbles
3. How speculative asset price bubbles form (via a classroom experiment designed to simulate bubble formation)
4. The specific features of the 2008 Global Financial Crises, especially the role of structured finance, the malfunctioning of debt markets, and the over-leveraging of financial institutions
5. How a financial crisis causes economic activity to collapse, with specific reference to the examples of Japan after 1991, and the US and Europe after 2008
6. How a financial crisis causes economic activity to collapse, with specific reference to the examples of Japan after 1991, and the US and Europe after 2008
7. What kinds of preemptive policies can prevent the buildup of speculative asset price bubbles
8. What kinds of post-crisis policies can prevent the collapse of economic activity
9. How to analyze the current world economic scenario where a new crisis originating in China or some other emerging market may erupt

The 10th course, Crises, does not fit neatly within any one stream, but students who specialize in the Finance or Public Policy streams may consider it as their 4th for-credit elective course since the course has elements of both finance and public policy. Alongside the three courses in each stream, students will also be offered Workshops/Econ Labs. These are not required for credit, but students specializing in a stream are strongly advised to attend the Workshops/Econ Labs being offered in that stream, as these will illustrate some of the principles taught in that stream and also offer additional training that is often required for jobs in the arena of that stream.

DISSERTATION

Writing a Dissertation is an integral part of the courses offered at MDAE because it initiates the students to the process of research which is the means to stimulate curiosity as well as satisfy it in a scientific manner. It opens minds to new possibilities and explore further on subjects and widens the knowledge base.

At MDAE, students work on a research topic in their interest for three months and are mentored by the faculty, industry experts, and the members of its Academic Board. The students are assisted by their supervisors in various ways including search for literature, data collection, data entry, and manuscript development.

The top four dissertations are read by the Chairman of the Academic Board, Lord Meghnad Desai and he selects the best paper from among them. These four papers are compiled as an e-book.

Assessment

The program adheres to a philosophy of continuous assessment throughout the academic year to ensure that students effectively master the course materials and get enough opportunities to test their mastery. To this end, the students will be graded on the following:

• End-of-course examination and project
• Periodic problem sets
• Writing assignments/Programming assignments
• Contribution to classroom discussion and presentation
• Classroom Attendance

The precise breakup of the final course grade into these diverse components, and also the precise form that these components will assume in each course, will remain at the discretion of the course instructor, and will be communicated to students via the course syllabus that the instructor will hand out prior to the course.