Syllabus for
Master of Science (Economics and Analytics)
Academic Year  (2023)

The Department of Economics, CHRIST (Deemed to be University) Delhi NCR Campus, formed in 2019 consists of a faculty pool with rich experience in teaching, research and consultancy. The Department has five full-time faculty members with specialisation in Development Economics, Rural and Health Economics, Quantitative Economics, Agricultural Economics, Resource Economics, involving in advanced research.

Vision

Establish an identity as a department of high standard in teaching and research in Economics.

 Mission

Equip students with advanced knowledge and skill sets to address real world economic problems and undertake cutting edge research on contemporary economic issues.

The Master of Science in Economics and Analytics is an intensive program that will guide students through economic modelling and theory to computational practice and cutting-edge tools, providing a thorough training in descriptive, predictive and prescriptive analytics. Students will be equipped with a solid knowledge of econometric and machine learning methods, optimization and computing. These big-data skills, combined with knowledge of economic modelling, will enable them to identify, assess and seize the opportunity for data-driven value creation in the private and public sectors. Students will be trained to contribute significantly to empirical and applied work in the upcoming field of Economics. 

CIA - 70% 

ESE - 30% 

This paper aims at strengthening the knowledge of important macroeconomic variables and their role in determining the equilibrium level of output and employment and provides insights into the factors influencing the capital inflows and outflows in an open economy model. It helps the students to understand the theoretical foundation of macroeconomics and the contribution of different schools of thought to the further development of macroeconomics. 

The principles of data science deals with the econometric scientific methods of analyzing data. Today, we live in a big data world, where the amount of data generated

everyday is very huge, therefore we need methods to clearly transform and analyze data. Therefore, machine learning, which is included in this syllabus, does the job.

Also, the students here are introduced into different scenarios and methodologies to get results out of data.

Linear Algebra plays a fundamental role in the theory of Data Analytics. This course aims at introducing the basic notions of vector spaces, Linear Algebra and the use of Linear Algebra in applications to Data Analytics.  

This course enables the students to

●      Understand the importance of research in creating and extending the knowledge base of their subject area;

●   Distinguish between the strengths and limitations of different research approaches regarding their subject/research area

●      Know the range of qualitative and quantitative research methods potentially available to them;

●      Differentiate between the role of practitioners and the role of researchers;

●      Understand and analyze critically reflect upon issues of ethics and role of the researcher; 

●    Independently work, to plan and to carry out a small-scale research project.

The objective of this course is to provide comprehensive knowledge of Python programming paradigms required for Data Science.

 This Course aims at strengthening the knowledge of important macroeconomic variables and their role in determining the equilibrium level of output and employment and provides insights into factors influencing the capital inflows and outflows in an open economy model. It helps the students to understand the theoretical foundation of macroeconomics and the contribution of different schools of thought to the further development of macroeconomics. Upon successful completion of this course, the students will be able to: critically evaluate the consequences of basic macroeconomic policy options under differing economic conditions within a business cycle.

On completion of the course students should be able to:

●      Understanding of simple and multiple linear regression, its assumptions, and the impact of violations of its assumptions.

●      Developing their proficiency with the econometric software like EViews and Stata required to model economic data in practice.

●      Formulating, estimating, testing, and interpreting suitable models for the empirical study of economic events.

*    Ability to evaluate the performance of alternative econometric models through the appropriate use of tests.

The main objectives of the course are to train the students to grasp the use of mathematical techniques and operations to analyse economic problems and to introduce students to various economic concepts which are amenable to mathematical treatment.

The course is designed to train and equip the students to carry out research. The course enables the students to 

• Gain knowledge of core research techniques which forms a basis for understanding and critical analysis of the published work in economics. 
• Develop the analytical skills required to conduct research in the economics discipline. 

The Course enables students to

• Introduce the historical development of statistics, presentation of data, descriptive measures and fitting mathematical curves for the data.
• Introduce the measurement of the relationship of quantitative and qualitative data and the concept of probability.
• Understand and apply the descriptive measures and probability for data analysis.

The course enables the students to

● Familiarize students with the financial system and its components viz. financial instruments, financial institutions, financial markets and financial regulations.

● Acquaint them with contemporary theories about the workings of different financial markets including money market, capital markets (bonds, stocks and hybrids) and derivative markets.

● Introduce them with the policy and regulatory framework within which financial institutions are required to function.

The course provides a deep understanding about the broad principles and theories, which tend to govern the flow of trade in goods, services and capital — both short-term and longterm — at the global level. The contents of the course help them to examine the impact of the trade policies followed both at the national and international levels as also their welfare implications at macro level and the distribution of gains from trade to North and South with particular reference to India, also the likely consequences on income, employment and social standards and possible policy solutions

The course discusses fundamental models used to analyze theoretical and empirical issues in economic growth and development. The main objective of the course is to familiarize students with the problem of development in underdeveloped and developing economies. In addition, this course also discusses the major theoretical developments in areas of Growth economics and policy discourses.

To provide the students with an in-depth understanding of the work done by some of these scholars and practitioners, and make them an expert at understanding, diagnosing, and designing behavioural change interventions that help people make better decisions and achieve policy or social welfare outcomes.

This course enables students to

● Understand the differences between supervised and unsupervised machine learning models

● Optimize the models and understand the effect of algorithm parameters’ modification

● Combine various models and create strategies to overcome commonly faced challenges in machine learning algorithm implementation

● Implement machine learning models in various economics-related applications 

The course enables students to,

●        Create an Interactive dashboard from different datasets. 

●        Illustrate importing data from different data sources and then learn to clean data with tool.  

●        Visualize data using graphs and plots. The graphs so build can give you the overall information of the data. 

The course is designed to provide a real-world project development and deployment environment

for the students.

The Vision of Christ University is “Excellence and Service” and this can be achieved through the holistic development of individuals enabling effective contribution to society. Christ University provides the nurturing ground for all stakeholders to realize academic, personal, interpersonal and societal growth and upliftment. Industry internship focuses on learning by doing and making students more responsible and dynamic so that they can harness their hidden potential and get ready to take up tasks and challenges of the industry with confidence and motivation. Industry Internship provides students with exposure to life beyond academics enabling them to solve real-life problems. It provides students with practical knowledge of the application of Economics and Analytics in the industry and also the importance of discipline, hard work and dedication. This internship aims to widen the horizons of the students to make informed decisions regarding their future and career. The students shall learn new skills and make good professional interpersonal relationships. The skills learned during the Industry Internship will also have a bearing on students’ placements and career planning. 

Internship Report:

The student shall work with the organization as an intern for a period of 4 months and submit an internship report of 2000 words in consultation with the allotted faculty guide. The student shall ensure regular weekly contact with the faculty guide during the entire period of the internship. The student will report to the faculty guide every week and apprise him/her of the weekly progress of the internship. In addition to the submission of the internship report, the student will also present his internship report before a panel of examiners followed by a Question and Answer session.

Research Publication enables students to raise their intellectual abilities and contribute to the existing literature through research. It also enables them to dive deeper into researchable problems and come up with novel ideas and bring them to the forefront by publishing them as a research article/paper in esteemed research journals.

The student will be allotted a faculty guide to supervising the research work. The students are expected to undertake quality research in consultation with the faculty guide. The student will be in regular contact with the faculty guide and try to complete the research work in the stipulated time. The faculty guide will guide the student in all matters related to the finalization of the topic, writing of the research article/paper, analysis of data, selection of the journal and communications with the journal.