Department of
MATHEMATICS






Syllabus for
Bachelor of Science (Economics, Mathematics)
Academic Year  (2023)

 
3 Semester - 2022 - Batch
Paper Code
Paper
Hours Per
Week
Credits
Marks
ECO331Y INTERMEDIATE MICROECONOMICS 3 3 100
ECO332Y INTERNATIONAL ECONOMICS 3 3 100
MAT331 REAL ANALYSIS 4 4 100
MAT332Y COMPLEX ANALYSIS 4 2 50
STA311Y R-PROGRAMMING 2 2 50
STA361Y STATISTICAL METHODS 3 3 100
4 Semester - 2022 - Batch
Paper Code
Paper
Hours Per
Week
Credits
Marks
ECO431Y INTERMEDIATE MACROECONOMICS 3 3 100
ECO432Y INTRODUCTION TO PUBLIC FINANCE 3 3 100
MAT431 ALGEBRA 4 4 100
MAT451Y DATA ANALYSIS USING PYTHON 2 2 50
MAT461Y FUNDAMENTALS OF ACTUARIAL SCIENCE 2 2 50
MAT462Y APPLIED MATHEMATICS FOR ECONOMICS 3 3 100

ECO331Y - INTERMEDIATE MICROECONOMICS (2022 Batch)

Total Teaching Hours for Semester:45
No of Lecture Hours/Week:3
Max Marks:100
Credits:3

Course Objectives/Course Description

 

Course Description

This course is designed to give a systematic introduction to mainstream approaches to the study of microeconomics. The course begins by introducing students to the theories and derivation of demand and supply. Then the course proceeds with a systematic introduction to the theories of production. With the understanding of laws of production, cost, revenue, and functioning of various markets are introduced. The course has been designed in such a way that it stimulates awareness on essential variables for the understanding of how consumers and firms derive various decisions.

 

Course Objectives

The course has been conceptualised in order to help students:

  • Develop an understanding of the conceptual foundations and analytical methods used in Microeconomics.
  • Familiarise with the basics of consumer behaviour and decision-making criteria.
  • Analyse and understand relationships and interactions in various forms of markets.

Learning Outcome

CO1: Understand and interpret the factors influencing consumer behaviour and derive market demand and supply.

CO2: Understand and evaluate the production function and various laws of production.

CO3: Distinguish between the various approaches on theories of cost.

CO4: Understand various concepts of revenue and analyse the dynamic interactions between demand and supply in various market structures.

Unit-1
Teaching Hours:15
Theory of Demand and Supply
 

Theory of Consumer Behaviour: The Cardinal Utility Theory, The Indifference Curves Theory, Derivation of demand curve; The Market Demand: Derivation of the Market Demand- Determinants of Demand -Elasticities of Demand; Market Supply: Individual supply- Derivation of the Market Supply- Determinants of Supply -Elasticities of Supply.

Unit-2
Teaching Hours:8
Theory of Production
 

Production Function; Laws of Production: The Law of Variable Proportions, Laws of Returns to Scale; Technological Progress and the Production Function.

Unit-3
Teaching Hours:8
Theory of Costs
 

The Traditional Theory: Short-Run Costs- Long-Run Costs, Economies and Diseconomies of scale, The 'Envelope Curve'; Modern Theory of Costs: Short-Run Costs, Long-Run Costs, The 'L-Shaped' Scale Curve.

Unit-4
Teaching Hours:14
Theory of the Firm
 

Concepts of Revenue: Total, Marginal and Average; Market structure: Perfect Competition - Output Determination; Monopoly - Price and Output Determination, Price Discrimination; Monopolistic Competition - Price and Output Determination; Oligopoly – Cournot Model, Cartel.

Text Books And Reference Books:

Koutsoyiannis, A. (1979). Modern Microeconomics. London: Macmillan Press.

Pindyck, R. S., & Rubinfeld, D. L. (2013). Microeconomics (8th ed.). New York: Pearson Education.

Essential Reading / Recommended Reading

Mankiw, N. G. (2017). Principles of Microeconomics (8th ed.). MA: Cengage Learning.

Salvatore, Dominick. (2017). Microeconomics Theory and Applications (5th ed.). Oxford: Oxford University Press.

Samuelson, P. A., & Nordhaus, W.D. (2010). Economics (19th ed.). New Delhi: McGraw-Hill Companies.

Evaluation Pattern

Evaluation Pattern

CIA1

MSE* (CIA2)

CIA3

ESE**

Attendance

Weightage

10

25

10

50

05

Mid Semester Exam      ** End Semester Exam

ECO332Y - INTERNATIONAL ECONOMICS (2022 Batch)

Total Teaching Hours for Semester:45
No of Lecture Hours/Week:3
Max Marks:100
Credits:3

Course Objectives/Course Description

 

This course provides the basics of international trade theory stems from classical to new trade theories, and international economic policies on domestic and world welfare. This course begins with an introduction to international trade. Then the neo classical trade theories and new trade theories are discussed. The course concludes with a discussion on trade policies and its controversies. The course uses the empirical evidences to explain the theories and models in international trade.

Learning Outcome

CO1 : demonstrate a strong foundation in the theories of international economics

CO2: examine the trade policies and practices adopted globally

CO3: analyse the effects of economic integration on the economy

Unit-1
Teaching Hours:5
Unit I: Introduction to International Trade
 

Introduction: What is international economics about? An overview of world trade. Stylized facts about international trade, Components of Balance of Payments: Current account and Capital account.

Unit-2
Teaching Hours:16
Unit II: Theories of International Trade
 

Smith’s absolute advantage theory of trade, Ricardo’s comparative advantage theory of trade, concepts of offer curve and terms of trade; Heckscher-Ohlin theory, Rybczinski and Stolper-Samuelson theorems; factor price equalisation theorem; Leontief Paradox; Krugman’s New Trade Theory.

Unit-3
Teaching Hours:15
Unit III: Trade policies
 

Instruments of trade policy; tariffs, quotas, export subsidies, voluntary export restraints, Global value Chain (GVC’s).

Unit-4
Teaching Hours:9
Unit IV: Contemporary issues in international trade
 

Political economy of trade policies, Controversies of trade policies, Free trade agreements

Text Books And Reference Books:

Dominick Salvatore. (2021). International Economics, 13th ed. Wiley

Francis Cherunilam. (2020). International Economics, 6th ed. McGraw Hill

Feenstra, R., Taylor, A. (2014). International Economics, 3rd ed. Worth Publishers.

Krugman, P., Obstfeld, M., Melitz, M. (2018). International Economics - Theory and Policy, 11th ed. Pearson Education

Pugel, T. (2015). International Economics, 16th ed. McGraw-Hill.

Soderstein, B and Geoffrey Reed (1999). International Economics, 3rd ed. Palgrave Macmillan

Dominick Salvatore. (2021). International Economics, 13th ed. Wiley

Essential Reading / Recommended Reading

 Bagwell, Kyle, and Robert W. Staiger. The Economics of the World Trading System. MIT Press, 2004. ISBN: 9780262524346

Antweiler, Werner and David Trefler. “Increasing Returns and All That: A View from Trade.” American Economic Review 92 no. 1 (2002): 93–119.

Bernhofen, Daniel M, and Brown. “Testing the General Validity Of the Heckscher-Ohlin Theorem: The Natural Experiment of Japan.” (PDF) University of Nottingham Working Paper, 2009.

Bowen, Harry P, Leamer, et al. “Multicountry, Multifactor Tests of the Factor Abundance Theory.” (PDF - 2.43MB) American Economic Review 77, no. 5 (1987): 791–809.

Dornbusch, R., S. Fischer, et al. “Comparative Advantage, Trade, and Payments in a Ricardian Model with a Continuum of Goods.” American Economic Review 67, no. 5 (1977): 823–39.

Eaton, J., and S. Kortum. “Technology, Geography and Trade.” Econometrica 70, no. 5 (2002): 1741–79.

Broda, Christian, Nuno Limão, and David E. Weinstein. “Optimal Tariffs and Market Power: The Evidence.” American Economic Review 98, no. 5 (2008): 2032-2065.

Limao, Nuno. “Preferential Trade Agreements as Stumbling Blocks for Multilateral Trade Liberalization: Evidence for the United States.” American Economic Review 96, no. 3 (2006): 896–914.

Rose, Andrew K. “Do We Really Know That the WTO Increases Trade?” American Economic Review 94, no. 1 (2004): 98–114.

Evaluation Pattern

 

Evaluation Pattern

CIA1

MSE (CIA2)

CIA3

ESE

Attendance

Weightage

10

25

10

50

05

MAT331 - REAL ANALYSIS (2022 Batch)

Total Teaching Hours for Semester:60
No of Lecture Hours/Week:4
Max Marks:100
Credits:4

Course Objectives/Course Description

 

Course description : This course enables the students to understand the basic techniques and theories of real Analysis.

 

Course objectives : This course will help the learner to

COBJ1. examine the convergence or divergence of sequences and series.

COBJ2. understand the different types of convergence and their properties.

 

Learning Outcome

CO1: understand the concepts of limits, infimum, supremum, and boundedness of sequences.

CO2: examine the convergence of series using various tests.

CO3: distinguish between different types of convergence of sequence and series.

CO4: identify the region of convergence for sequence and series of functions.

Unit-1
Teaching Hours:20
Sets and Sequences
 

Open sets, closed sets, closure of a set, countable and uncountable sets, topology of real line. Sequences: Definition of Sequences, limit of a sequence, algebra of limits of a sequence, convergent, divergent, and oscillatory sequences, problems thereon. Bounded sequences, Monotonic sequences and their properties, Cauchy sequence.

Unit-2
Teaching Hours:20
Infinite Series
 

Infinite series, Cauchy convergence criterion for series, geometric series, comparison test, convergence of p-series, D'Alembert's Ratio test, Raabe's test, Cauchy's Root test, alternating series, Leibnitz’s test. Definition and examples of absolute and conditional convergence.

Unit-3
Teaching Hours:20
Sequence and Series of functions
 

Sequences and series of functions, Pointwise and uniform convergence. Mn - test, M-test, Statements of the results about uniform convergence. Power series and radius of convergence.

Text Books And Reference Books:

S.C.Malik and Savita Arora, Mathematical Analysis , Second Edition, New Delhi, India: New Age international (P) Ltd., 2005.

Essential Reading / Recommended Reading
  1. R.G. Bartle and D. R Sherbert, Introduction to Real Analysis, John Wiley and Sons (Asia) P. Ltd., 2000.
  2. E. Fischer, Intermediate Real Analysis ,1 st ed.(Reprint), Springer Verlag, 2012.
  3. K.A. Ross, Elementary Analysis- The Theory of Calculus Series- Undergraduate Texts in Mathematics, Springer Verlag, 2003.
  4. S Narayana and M.D. Raisinghania, Elements of Real Analysis, Revised ed., S. Chand & Company Ltd, 2011.
  5. T. M. Apostol, Calculus (Vol. I), John Wiley and Sons (Asia) P. Ltd., 2002.
Evaluation Pattern

 

Component

Mode of Assessment

Parameters

Points

CIA I

MCQ,

Written Assignment,

Reference work, etc.,

Mastery of the core concepts

Problem solving skills

 

10

CIA II

Mid-semester Examination

Basic, conceptual and analytical knowledge of the subject

25

CIA III

Written Assignment, Project

Problem solving skills

10

Attendance

Attendance

Regularity and Punctuality

05

ESE

 

Basic, conceptual and analytical knowledge of the subject

50

Total

100

MAT332Y - COMPLEX ANALYSIS (2022 Batch)

Total Teaching Hours for Semester:60
No of Lecture Hours/Week:4
Max Marks:50
Credits:2

Course Objectives/Course Description

 

Course Description: This course enables the students to understand the basic theory and principles of complex analysis.

Course Objectives​: This course will help the learner to

COBJ1. Understand the theory and geometry of complex numbers.

COBJ2. Evaluate derivatives and integrals of functions of complex variables.

COBJ3. Examine the transformation of functions of complex variables. 

Learning Outcome

CO1: Understand the concepts of limit, continuity, differentiability of complex functions

CO2: Evaluate the integrals of complex functions using Cauchy?s Integral Theorem/Formula and related results

CO3: Examine various types of transformation of functions of complex variables.

CO4: Apply the concepts of complex analysis to analyze and address real world problems.

Unit-1
Teaching Hours:15
Analytic Functions
 

Properties of complex numbers, regions in the complex plane, functions of complex variable, limits, limits involving the point at infinity, continuity and differentiability of functions of complex variable. Analytic functions, necessary and sufficient conditions for a function to be analytic. 

Unit-2
Teaching Hours:15
Complex Integration and Conformal Mappings
 

Definite integrals of functions, contour integrals and its examples, Cauchy’s integral theorem, Cauchy integral formula, Liouville’s theorem and the fundamental theorem of algebra, elementary transformations, conformal mappings, bilinear transformations.

Text Books And Reference Books:

Dennis G. Zill and Patrick D. Shanahan, A first course in Complex Analysis with Applications, 2nd Ed, Jones & Barlett Publishers, 2011. 

Essential Reading / Recommended Reading

1.  J. W. Brown and R. V. Churchill, Complex Variables and Applications, 8th ed., McGraw – Hill International Edition, 2009.

2.  J. Bak and D. J. Newman, Complex analysis, 2nd ed., Undergraduate Texts in Mathematics, Springer-Verlag New York, Inc., New York, 2000.

3.  A. Jeffrey, Complex Analysis and Applications, 2nd ed., CRC Press, Boca Raton 2013.

4.  L. V. Ahlfors, Complex Analysis, 3rd ed., McGraw-Hill Education, 2017.

5. S. Ponnusamy, Foundations of Complex Analysis, 2nd ed., Narosa Publishing House, Reprint 2021.

Evaluation Pattern

 

Component

Mode of Assessment

Parameters

Points

CIA I

Written assignment and Test

Mastery of the core concepts and Problem solving skills

5

CIA II

Mid-Semester Examination

Basic, Conceptual and analytical knowledge of the subject

10

CIA III

Problem solving assignment and Test

Problem solving skills

5

 

Attendance

Regularity and Punctuality

5

ESE

 

Basic, Conceptual and analytical knowledge of the subject

25

Total

50

STA311Y - R-PROGRAMMING (2022 Batch)

Total Teaching Hours for Semester:30
No of Lecture Hours/Week:2
Max Marks:50
Credits:2

Course Objectives/Course Description

 

Course Description:

This course provides an introduction to R, statistical language, and an environment that provides more flexible graph capabilities than other popular statistical packages. The course also covers the basics of R for statistical computation and exploratory analysis.

Course Objectives:

This course is to equip the students to visualize and analyse the data using R and to communicate statistical results in correct manner. 

Learning Outcome

CO1: Understand R and R studio and create reports using R markdown.

CO2: Demonstrate data handling using statistical tool R.

CO3: Demonstrate the usage of R for introductory Statistics.

Unit-1
Teaching Hours:6
Introduction to R and R Studio
 

Getting started with R - installing R and R studio - getting help - installing and loading packages - R–markdown-simple arithmetic calculations - Numbers and Vectors - Objects- modes and attributes - Ordered and unordered Factors - Arrays and Matrices.

Unit-2
Teaching Hours:6
Lists and Data Frames
 

Constructing and modifying lists - Making Data frames - attach () and detach () - Working with data frame - Reading data from files using read. table () – scan ()

Unit-3
Teaching Hours:6
Grouping Conditional Execution and Loops
 

Grouping - Conditional execution: if statements - Repetitive execution: for loops - repeat and while loops - Functions.

Unit-4
Teaching Hours:6
Exploratory Data Analysis
 

Introduction to Statistics - probability and data with R. Visualizing numerical data - graphing systems available in R

Unit-5
Teaching Hours:6
Descriptive Statistics
 

Descriptive Statistics - measures of central tendency and dispersion – correlation - transforming data - exploring categorical variables. 

Text Books And Reference Books:

Grolemund G.,  Hands-on programming with R: write your own functions and simulations, O' Reilly Media Inc., 2014. 

W. N. Venables, D. M. Smith,  An Introduction to R, R Core Team, version 4.0.3, 2020. 

Essential Reading / Recommended Reading

Peng R. D,  Exploratory data analysis with R, Lulu.Com, 2012. 

Crawley M. J.,  The R book, John Wiley & Sons, 2012 

Seema Acharya,  Data Analytics Using R, CRC Press, Taylor & Francis Group, 2018

Evaluation Pattern

CIA : 50%

ESE: 50%

STA361Y - STATISTICAL METHODS (2022 Batch)

Total Teaching Hours for Semester:45
No of Lecture Hours/Week:3
Max Marks:100
Credits:3

Course Objectives/Course Description

 

Course Description:

This course is designed to teach the basic concepts of random variables, generation functions, and an introduction to inferential statistics. It also gives a brief idea about standard probability distributions, sampling, and how they are applied in real time situations.

Course Objective:

Develop an understanding of random variables, probability distributions, and two-dimensional random variables, as well as sampling distributions, and inferential statistics.

Learning Outcome

CO1: Demonstrate the random variables and its functions.

CO2: Compute the expectations for random variable functions and generating functions.

CO3: Demonstrate various discrete and continuous distributions and their usage.

CO4: Formulate hypotheses, test using statistics, interpret results with p-values for a research question.

Unit-1
Teaching Hours:9
Random variables
 

Definition - Discrete and continuous random variables - Probability Mass function and Probability density function - Distribution function and its properties - Two dimension random variables: Discrete and continuous type - Joint Density function

Unit-2
Teaching Hours:9
Mathematical Expectation and Generating functions
 

Expectation of single and bivariate random variables and its properties - Conditional expectations - Moments and Cumulants - Moment Generating Function - conditional probability – conditional expectation - independence of variables with illustration.

Unit-3
Teaching Hours:9
Discrete Probability distributions
 

Uniform - Bernoulli - Binomial - Poisson – geometric distributions along with their properties and applications

Unit-4
Teaching Hours:9
Continuous Probability distributions
 

Uniform - Normal – Exponential distributions along with their properties and real-life applications. Population and sample - Parameter and statistic – sampling distributions: chi-square, t, F (only definition and statement of applications)

Unit-5
Teaching Hours:9
Introduction to statistical Inference
 

Point Estimators – hypothesis - testing of hypothesis problem -Setting of Hypothesis -Null and alternative hypotheses - Test statistics - Types of errors in hypothesis testing - level of significance – Critical region and p-value - Decision making.

Text Books And Reference Books:

Gupta S.C and Kapoor V.K,  Fundamentals of Mathematical Statistics, 12th edition, Sultan Chand & Sons, New Delhi, 2020.

Essential Reading / Recommended Reading

Mukhopadhyay P,  Mathematical Statistics, Books and Allied (P) Ltd, Kolkata, 2015.

Rohatgi V.K and Saleh E,  An Introduction to Probability and Statistics, 3rd edition, John Wiley & Sons Inc., New Jersey, 2015.

Montgomery D.C and Runger G.C,  Applied Statistics and Probability for Engineers, Wiley India, New Delhi, 2018.

Mood A.M, Graybill F.A, and Boes D.C,  Introduction to the Theory of Statistics, 3rd edition, McGraw Hill, New Delhi, 2017.

Evaluation Pattern

Component

Mode of Assessment

Parameters

Points

CIA I

MCQ,

Written Assignment,

Reference work, etc.,

Mastery of the core concepts

Problem solving skills.

 

10

CIA II

Mid-semester Examination

Basic, conceptual, and analytical knowledge of the subject

25

CIA III

Written Assignment, Project

Problem solving skills

10

Attendance

Attendance

Regularity and Punctuality

05

ESE

 

Basic, conceptual, and analytical knowledge of the subject

50

Total

100

ECO431Y - INTERMEDIATE MACROECONOMICS (2022 Batch)

Total Teaching Hours for Semester:45
No of Lecture Hours/Week:3
Max Marks:100
Credits:3

Course Objectives/Course Description

 

Course Description

This course is in continuation to the Introductory Macroeconomics course offered in the second semester. The course first introduces students to the mathematical framework for Keynesian economics – ISLM. Then the links between output, inflation, and unemployment and the effectiveness of policies are discussed from the Keynesian and the Monetarist perspectives. The third unit then introduces students to the open economy framework, and the course concludes with a discussion on the contemporary debates in the field of macroeconomic theory and policies.

Course Objectives

The course aims to:

  • enhance the understanding of the learners regarding the macroeconomic dynamics in the short-run closed as well as open economy.
  • understand and analyse the nexus between output, inflation and unemployment in both the short-run and in the long-run.
  • understand and critically evaluate contemporary macroeconomic policies, create reports and deliver presentations

Learning Outcome

CO1: Upon completion of the course, the students will be able to explain the macroeconomic dynamics in the short-run closed economy as well as open economy.

CO2: Upon completion of the course, the students will be able to test and discover the nexus between output, inflation, and unemployment in both the short run and the long run.

CO3: Upon completion of the course, the students will be able to evaluate the pros and cons of various macroeconomic policies in the real-world context, create reports following APA guidelines; and deliver presentations before peers.

Unit-1
Teaching Hours:15
The Closed Economy in the Short Run
 

The goods market and derivation of IS curve; real influences and Shift in IS schedule; the money market and derivation of LM curve; monetary influences and the shift in LM curve; determination of equilibrium income and interest rates; the relative efficacy of fiscal and monetary policy under IS-LM framework; Critiques of IS-LM.

Unit-2
Teaching Hours:9
Output, Inflation and Unemployment
 

Links between output and unemployment: Okun’s law; Estimates of potential GDP and their limitations; Natural rate of unemployment; Factors affecting natural rate of unemployment; Links between inflation and unemployment: Phillips curve; Friedman-Phelps expectations augmented Phillips curve; Output-inflation trade-off: Keynesian vs. Monetarists view.

Unit-3
Teaching Hours:15
Open Economy Models
 

The Mundell-Fleming model: assumptions; determining equilibrium output and exchange rate in a small open economy; the monetary and fiscal policy under floating and fixed exchange rates regimes.

Unit-4
Teaching Hours:6
Recent debates in Macroeconomic Policy
 

Economic Stabilization-Monetary vs. Fiscal Policy; Handling Recession- Higher Spending vs. Tax Cuts; Monetary Policy-Rule vs. Discretion Based; Central Bank Goal: Zero vs. non-zero Inflation; Government Budget - Balanced vs. Unbalanced; Tax Laws for Savings – Reformed vs. Not Reformed.

Text Books And Reference Books:

Dornbusch, R., Fischer, S., & Startz, R. (2015). Macroeconomics (11th ed.). New Delhi: Tata McGraw.

Froyen, R. (2014). Macroeconomics: Theories and Policies (10th ed.). Pearson Education.

Mankiw, N. G. (2014). Principles of Macroeconomics (7th ed.). Cengage Learning.

Mankiw, N. G. (2015). Macroeconomics (9th ed.). USA: Worth Publishers.

Essential Reading / Recommended Reading

Abel, A. B. & Bernanke, B. S. (2011). Macroeconomics (7th ed.) New Delhi: Pearson Education.

Blanchard, O. (2009). Macroeconomics (5th ed.). New Delhi: Pearson Education.

Heijdra, B. J. & Ploeg, F. V. (2001). Foundations of Modern Macroeconomics. Oxford: Oxford University Press.

McConnell, C. R., & Brue, S. L. (2011). Macroeconomics, Principles, Problems, and Policies.  New York: McGraw Hill Inc.

Moorthy, V. (2017). Applied Macroeconomics. New Delhi: I. K. International Publishing House.

Thomas, A. M. (2021). Macroeconomics: An Introduction. Cambridge: Cambridge University Press.

Evaluation Pattern

Evaluation Pattern

CIA1

MSE* (CIA2)

CIA3

ESE**

Attendance

Weightage

10

25

10

50

05

* Mid Semester Exam      ** End Semester Exam

ECO432Y - INTRODUCTION TO PUBLIC FINANCE (2022 Batch)

Total Teaching Hours for Semester:45
No of Lecture Hours/Week:3
Max Marks:100
Credits:3

Course Objectives/Course Description

 

Public Economics is the study of government policy from the point of view of economic efficiency and equity. This course introduces students to allocation,distribution, stabilisation and regulatory functions of government. The course discusses about concept of public goods, club goods, and merit goods, andanalyses causes of externalities and market failures. It then does a systematic analysis of sources of government revenue, expenditure, public debt which is inclusive of theories on taxation, public expenditure and Economist views on public debts to provide students a broader perspective to analyse such issues. Last unit, provides a thorough understanding on fiscal institutions with a careful analysis of the issues pertaining to budgetary policies in general and Indian experience in particular.

Learning Outcome

CO1: Develop an understanding about the various functions of government.

CO2: Understand the sources of market failure and the need for government intervention and its possible outcomes.

CO3: Develop a critical understanding of the key theories of public economics.

CO4: Explain the various component of government budget and its wider impact on the economy.

CO5: Examine the role of government institutions in centre-state financial relationship.

Unit-1
Teaching Hours:9
Unit I: Role of Government in an Organised society
 

The nature, scope and significance of public economics – Principle of Maximum Social advantage: Approaches and Limitations- Functions of Government - Economic functions - allocation, distribution and stabilization; Regulatory functions of the Government and its economic significance

Unit-2
Teaching Hours:9
Unit II: Public Goods and Market failure
 

Concept of public goods - characteristics of public goods, national vs. local public goods; Externality - concept of social versus private costs and benefits, merit goods, club goods; Provision versus production of public goods - Market failure and public Provision.

Unit-3
Teaching Hours:9
Unit III: Taxation
 

Concept of tax, types, canons of taxation-Incidence of taxes; Taxable capacity; Approaches to the principle of Equity in taxation -Ability to Pay principle, Benefit Approach; Sources of Public Revenue; VAT, Goods and Services Tax.

Unit-4
Teaching Hours:9
Unit IV: Public Expenditure and Public Debt
 

Structure and growth of public expenditure; Wagner’s Law of increasing state activities; Wiseman-Peacock hypothesis Different approaches to public debt; concepts of public debt; sources and effects of public debt; Methods of debt redemption- Trends of Public expenditure, Public debt and subsidies in India.

Unit-5
Teaching Hours:9
Unit V Government Budget and Policy
 

Government budget and its structure – Receipts and expenditure - concepts of current and capital account, balanced, surplus, and deficit budgets, concept of budget deficit vs. fiscal deficit- FRBM Act. Federal Finance: Different layers of the government; Inter governmental Transfer; horizontal vs. vertical equity; Principle of federal finance; Theory of Grants; Finance Commission.

Text Books And Reference Books:

Rosen. S., Harvey & Ted Gayer. (2008). Public Finance, Mc- Graw Hill Companies: New York

Bhatia A.K. (2018). Public Economics, Wisdom Press, New Delhi.  Chapter -1.

Musgrave, R.A. and P.B Musgrave (1989). Public Finance in Theory and Practice, Tata McGraw-Hill, New Delhi.

Jha, R (2010). Modern Public Economics, Rutledge, London.

Essential Reading / Recommended Reading

Rosen. S., Harvey & Ted Gayer. (2008). Public Finance, Mc- Graw Hill Companies: New York.

Cullis, John G. & Jones, Philip R. (2009). Public finance and public choice: analytical perspectives.  Oxford ; New York :  Oxford University Press

Tyagi B.P., Public Finance, Jai Prakash Nath Pub. Meerut (UP).

Government of India Budget Report, various issues

Citizen Report, various issues

Srivastava, D. K (2000). Fiscal Federalism in India, New Delhi, Har-Anand Publication Ltd.

Finance Commission Reports.

Economic Survey, Government of India, various issues.

State Finances: A Study of Budgets, Reserve Bank of India, various issues.

Evaluation Pattern

Evaluation Pattern

CIA1

MSE* (CIA2)

CIA3

ESE**

Attendance

Weightage

10

25

10

50

05

MAT431 - ALGEBRA (2022 Batch)

Total Teaching Hours for Semester:60
No of Lecture Hours/Week:4
Max Marks:100
Credits:4

Course Objectives/Course Description

 

Course description : This course aims at developing the ability to write the mathematical proofs.  It helps the students to understand and appreciate the beauty of the abstract nature of mathematics and also to develop a solid foundation of theoretical mathematics.

Course objectives : This course will help the learner to

COBJ1. Understand the fundamentals of groups and its theories.

COBJ2. Relate abstract algebraic constructs to more familiar sets and operators

COBJ3. Know about the subgroups and group homomorphisms

COBJ4. Get familiar with the theories on rings, integral domains and fields.

Learning Outcome

CO1: Describe and generate groups, rings and fields.

CO2: Identify and differentiate different structures and understand how changing properties give rise to new structures.

CO3: Demonstrate the knowledge of concepts of rings and fields.

Unit-1
Teaching Hours:15
Groups
 

Definition and examples of groups, examples of abelian and non-abelian groups, the group Zn of integers under addition modulo n and the group U(n) of units under multiplication modulo n, complex roots of unity, groups of symmetries: Equilateral triangle.

Unit-2
Teaching Hours:25
Subgroups and Group Homomorphisms
 

Subgroups, the concept of a subgroup generated by a subset and the commutator subgroup of group, examples of subgroups including the center of a group. order of an element, cyclic subgroups, Cosets, Index of subgroup, Lagrange’s theorem, consequences of Lagrange’s theorem, Normal subgroups: their definition, examples, and characterizations, Quotient groups, permutation groups and Symmetric groups – Homomorphism of groups – Kernel of group homomorphisms and theorems thereon – Fundamental theorem of homomorphism of group.

Unit-3
Teaching Hours:20
Rings, Integral Domain and Fields
 

Definition and examples of rings, examples of commutative and non-commutative rings: rings from number systems, Zn the ring of integers modulo n, ring of real quaternions, rings of matrices, polynomial rings, and rings of continuous functions. Subrings and ideals, Integral domains and fields, examples of fields: Zp, Q, R, and C. Field of rational functions.

Text Books And Reference Books:
  1. I. N. Herstein, Topics in Algebra, Second Edition. Wiley India (P) Ltd. New Delhi, India Vikas Publishing House Pvt. Ltd, 2006.
Essential Reading / Recommended Reading
  1. M. Artin, Abstract Algebra, 2nd Ed., Pearson, 2011.
  2. S. R. Nagpaul and S.K.Jain, Topics in Applied Abstract Algebra, Universities Press, 2010.
  3. Joseph A Gallian, Contemporary Abstract Algebra, 4th Ed., Narosa, 2000.
  4. Pinter, Charles C. A Book of Abstract Algebra, New York: McGraw-Hill, 1990.
  5. J. B. Fraleigh, A First Course in Abstract Algebra, 7th Ed., Pearson, 2002.
Evaluation Pattern

 

Component

Mode of Assessment

Parameters

Points

CIA I

MCQ,

Written Assignment,

Reference work, etc.,

Mastery of the core concepts

Problem solving skills

 

10

CIA II

Mid-semester Examination

Basic, conceptual and analytical knowledge of the subject

25

CIA III

Written Assignment, Project

Problem solving skills

10

Attendance

Attendance

Regularity and Punctuality

05

ESE

 

Basic, conceptual and analytical knowledge of the subject

50

Total

100

MAT451Y - DATA ANALYSIS USING PYTHON (2022 Batch)

Total Teaching Hours for Semester:30
No of Lecture Hours/Week:2
Max Marks:50
Credits:2

Course Objectives/Course Description

 

Course Description:

This course is aimed at enabling the students to appreciate and understand the concepts of mathematics and statistics with the help of Python programming language. Students will learn to use the tools, libraries and packages useful for data analysis.

Course Objectives:

This course will help the learner to:

  • gain proficiency in using Python for programming. 
  • acquire skills in usage of suitable functions/packages of Python for data analysis.
  • acquaint with Numpy and Pandas packages for data manipulating and visualization.
  • illustrates use statistics methods to handle data effectively.

Learning Outcome

CO1: The students will acquire proficiency in using tools, libraries, packages of Python for data analysis.

CO2: The students shall demonstrate the use of Python tools for visualizing data.

CO3: The students will be familiar with the statistical methods for describing data.

Unit-1
Teaching Hours:10
Analysing data with NumPy and Pandas
 

Arrays in NumPy, Creating, Indexing, Slicing, Algebraic operations on array, Python Data structures: List, Tuple, Dictionaries. Data series and Data frames, Using Pandas library to read and write data from a CSV file and Excel file.

Unit-2
Teaching Hours:10
Data Visualization
 

Plotting data in Python using Matplotlib: 2D plots, bar graph, histogram, box plot, pie chart. Plotting data using Seaborn: Line Plot, Scatter Plot, Box plot, Point plot, Count plot, Violin plot, Swarm plot, Bar plot.

Unit-3
Teaching Hours:10
Describing Data with Statistics
 

Mean, Median, Mode, Creating a frequency table, Dispersion, Variance, and standard deviation, Correlation between two data sets- Correlation Coefficient, Regression, GroupBy in Python, foundations of predictive analysis.

Text Books And Reference Books:

Stefanie Molin and Ken Jee, Hands-On Data Analysis with Pandas: A Python data science handbook for data collection, wrangling, analysis, and data analysis, 2nd Edition.

Essential Reading / Recommended Reading

Wes McKinney, Python for Data Analysis

Jake VanderPlas, Python Data Science Handbook: Essential Tools for Working with Data, 2nd Edition.

 

Evaluation Pattern

Component

Parameter

Mode of Assessment

Maximum

Points

CIA I

Mastery of the concepts

Lab Assignments

20

CIA II

Conceptual clarity and analytical skills

Lab Exam - I

10

Lab Record

Systematic documentation of the lab sessions.

e-Record work

07

Attendance

Regularity and Punctuality

Lab attendance

03

95-100% : 3

90-94%   : 2

85-89%   : 1

CIA III

Proficiency in executing the commands appropriately.

Lab Exam - II

10

Total

50

MAT461Y - FUNDAMENTALS OF ACTUARIAL SCIENCE (2022 Batch)

Total Teaching Hours for Semester:30
No of Lecture Hours/Week:2
Max Marks:50
Credits:2

Course Objectives/Course Description

 

This course is designed to prepare students to pursue careers in Actuarial Science. The aim of this course is to provide grounding in Actuarial Mathematics and their applications. Topics covered include the economics of insurance, survival distributions, life tables, and different types of life insurance.

 

Course Objectives​:

This course will help the learner to acquire fundamental knowledge of  Economics of insurance, Life Tables,Survival Distributions and Life Insurance.

Learning Outcome

CO1: Understand the principles of Actuarial modeling and cash flow models and apply them to real-world problems

CO2: Apply the financial mathematics concepts like the time value of money, calculation of present values, and accumulated value of cash flows, annuities, project appraisals, NPV, loan schedules, etc.

CO3: Apply the life insurance concepts in introducing various life insurance products and their use.

Unit-1
Teaching Hours:7
The Economics of Insurance
 

Utility Theory, Insurance and Utility, Elements of Insurance, Optimal Insurance, Models for Individual Claim Random variables, Sums of independent random variables, Approximations for the distribution of sums, Applications to insurance

Unit-2
Teaching Hours:13
Survival Distributions and Life Tables
 

Probability for the Age-at-Death: The Survival function, Time-until-Death for a Person Age x, Curtate-Future-LifeTime, Force of Mortality. Life Tables: Relation of Life Table Functions to the Survival Function, Life table example, The Deterministic Survivorship Group, Other Life-Table Characteristics, Assumptions for Fractional Ages

Unit-3
Teaching Hours:10
Life Insurance
 

Insurances Payable at the Moment of Death, Level Benefit Insurance, Endowment Insurance, Deferred Insurance, Varying benefit Insurance, Insurances Payable at the end of the year of death, Relationships between Insurances Payable at the moment of Death and the End of the Year of Death, Differential equations for Insurances Payable at the Moment of Death

Text Books And Reference Books:

N.L.Bowers, H.U.Gerber, J.C. Hickman, D.A. Jones and C.J. Nesbitt, Actuarial Mathematics, The Society of Actuaries, 1997.

Essential Reading / Recommended Reading

1. David C. M. Dickson, Mary R. Hardy, Howard R. Waters, Actuarial Mathematics for life contingent risk. Cambridge University Press, 2009

2. Steven Roman, Introduction to the Mathematics of Finance: From risk management to options pricing. Springer, 2004.

Evaluation Pattern

 

Component

Mode of Assessment

Parameters

Points

CIA I

MCQ,

Written Assignment,

Reference work, etc.,

Mastery of the core concepts 

Problem solving skills.

 

10

CIA II

Mid-semester Examination

Basic, conceptual, and analytical knowledge of the subject

25

CIA III

Written Assignment, Project

Problem solving skills

10

Attendance

Attendance

Regularity and Punctuality

05

MAT462Y - APPLIED MATHEMATICS FOR ECONOMICS (2022 Batch)

Total Teaching Hours for Semester:45
No of Lecture Hours/Week:3
Max Marks:100
Credits:3

Course Objectives/Course Description

 

This course is designed to help students to apply Calculus in solving Problems in Economics with the aid of FOSS tools.

Course Objective :

         COBJ 1:  Apply optimization techniques of calculus in Economics.

         COBJ 2:  Be familiar with the theory of integral calculus to understand concepts such as  Consumer/ Producer surplus,  Ramsey pricing, etc.

         COBJ 3:Use differential equations in conceptualising simple mathematical models in Economics.

Learning Outcome

CO1: Apply methods in calculus to solve optimization problems in Economics

CO2: Use integral calculus for various applications in Economics

CO3: Solve the mathematical models in Economics using differential equations

CO4: Use appropriate FOSS tools for mathematical computations

Unit-1
Teaching Hours:15
Optimization
 

Functions of one variable: Profit maximisation - Concavity and optimization - free rider problem - Comparative statics - elasticity, demand and profit maximisation - Taxation and monopoly - Taxation incidence and supply and demand - Ramsey pricing - Case studies with the help of FOSS tools.

Unit-2
Teaching Hours:15
Integration
 

Common integrals and rules of integration - Consumer surplus - Producer surplus - Consumer surplus and welfare - Average and marginal cost - Taxation and consumer surplus - present value - inequality measures - Ramsey pricing - Welfare measures - Case studies with the help of FOSS tools.

Unit-3
Teaching Hours:15
Differential Equations
 

First order differential equations - logistic model - The Bernoulli equation - Systems of differential equations - Stability- Case study with the help of FOSS tools.

Text Books And Reference Books:

J Bergin, Mathematics for Economists with Applications, 1st ed, Routledge, 2015.

Essential Reading / Recommended Reading

A J Mabbett, Workout Mathematics for Economists, Macmillan master series, 1986.

Evaluation Pattern

 

Component

Mode of Assessment

Parameters

Points

CIA I

MCQ,

Written Assignment,

Reference work, etc.,

Mastery of the core concepts 

Problem solving skills.

 

10

CIA II

Mid-semester Examination

Basic, conceptual, and analytical knowledge of the subject

25

CIA III

Written Assignment, Project

Problem solving skills

10

Attendance

Attendance

Regularity and Punctuality

05

Final Submission

 

Basic, conceptual, and analytical knowledge of the subject

50

Total

100