Syllabus for
Master of Science (Economics and Analytics)
Academic Year  (2021)

The Department of Economics at the Delhi NCR campus is functioning under the School of Social Sciences in CHRIST (Deemed to be University). Established in the year 2019 with the commencement of the new Campus at Delhi NCR, the department has representation of faculty from all cultures and regions in India and with qualifications from the top institutions in the country and abroad. Together with rich experience in teaching, research and consultancy, they specialises in Monetary and Financial Economics, Environmental Economics, Behavioural Economics, Industrial Economics, Informal Economy and so on, involving in advanced research.

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.

TheMasterofScienceinEconomicsandAnalyticsisanintensiveprogramthatwill guidestudentsthrougheconomicmodellingandtheorytocomputationalpracticeand cutting-edge tools, providing a thorough training in descriptive, predictive and prescriptive analytics. Students will be equipped with a solid knowledge of econometricandmachinelearningmethods,optimizationandcomputing.Thesebig- dataskills,combinedwithknowledgeofeconomicmodelling,willenablethemto identify,assessandseizetheopportunityfordata-drivenvaluecreationintheprivate andpublicsectors.Studentswillbetrainedtocontributesignificantlytoempiricaland appliedworkintheupcomingfieldofEconomics.

Examination and Assessment

 The evaluation is divided in to two components: Continuous Internal Assessment (CIA) including Mid Semester Examination (MSE), and the End Semester Examination (ESE).

 Assessment Pattern

 The Continuous Internal Assessment (CIA) will be assessed for seventy per cent weightage and the End Semester Examination (ESE) for thirty per cent weightage. The practical courses and the common core courses will be assessed out of hundred marks in various components including attendance. The Mid Semester and End Semester written examination question pattern consists of questions divided into two or three sections with short answers, short essays and long essays.

Course Objectives This course aims at analyzing the Economic behavior of the firms and markets. It is mainly concerned with the objective of equipping the students in a comprehensive manner with various aspects of consumer behavior and demand analysis, Production theory and behavior of cost, equilibrium of firm and various forms of market.

Course Outcomes

Upon successful completion of this course, the students will be able to:

• Demonstrate the analytical and critical skills relevant to economics thinking,

• Demonstrate the rigorous quantitative training that analytical economics requires,

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.

This course proposes to familiarize students with Introduction to Mathematical Economics, is designed with the intention to understand Areas under curve-Definite and indefinite Integration, Application- Consumer Surplus and Producer Surplus, the focus is on Concavity, Convexity, Quasi concavity, Quasi convexity Optimization of functions. This course intend to discuss about the Constrained Optimization Problems two variables, one constraint-Lagrange-multiplier method-First order conditions-Second order conditions, aims to discuss the Difference and Differential Equations and Economic Applications. 

Course Objectives

The main aim of the course is to provide knowledge about mathematical techniques in advanced forms and their applications.

The main objectives of the paper are to train the students to grasp the use of mathematical techniques and operations to analyze economic problems and to initiate students into various economic concepts which are amenable to mathematical treatment

The course aims to explain the basic concepts of python programming. The course aims to enable the students to do python programming using conditionals, loops, functions, various data structures and to implement file handling

A good grasp of microeconomics is vital for managerial decision making, for designing and understanding public policy. The course is intended to provide a good understanding and base to the students in applying the concepts and methods of microeconomics in the practical field. This course will equip the students to understand the various aspects of the traditional Microeconomic theory as well as the latest developments in this field and the applications of theories in analyzing current economic problems and to develop the ability to synthesize knowledge.

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. 

The course is designed to impart the learning of principles of econometric methods and tools.  This is expected to improve student’s ability to understand econometrics in the study of economics. This course is intended to provide a thorough and sound understanding of the essential theoretical base, an introduction to the important and useful techniques of modeling and also an understanding of the broad applications of econometrics.

This course is planned to give the students the basic knowledge in R programming  language and to make them familiar with the flexible graphical capabilities of R. It also  covers the Statistical computational features of R and exploratory analysis and  modeling using R 

The course is designed to train and equip the students to carryout 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 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., enables students to understand and apply the descriptive measures and probability for data analysis. Students will be able to evaluate the relationship between quantitative and qualitative data and the concept of probability. 

• Introduce the main concepts that describe the institutional structure of the society
• Provide an overview of the recent developments in the field of institutional  economics 
• Help the students to understand the role of institutional environment in economic  theory and in business practice
• Enable to use the concepts and methods of institutional economics in the analysis of  institutions of the society 

Predictive analytical tools are increasingly used in business decision making. The course will introduce the participants to business problems where models that involve prediction, classification, clustering and association can be applied. The course is designed as a hands on exercises using data available in the public domain. The course requires that the  participants are familiar with basic working in R and have sufficient understanding of basic statistics. At the end of the course participants will be able to classify predictive models and distinguish which models are suitable for a particular problem. The course will also emphasize on performance and accuracy problems of predictive models as and when they arise and be able to fix them