INDIAN STATISTICAL INSTITUTE
STUDENTS' BROCHURE


MASTER OF SCIENCE IN QUANTITATIVE ECONOMICS (MS(QE))



 

1. ELIGIBILITY FOR ADMISSION:

Three-year Bachelor's degree with Economics  and  Mathematics  as full subjects. Holders of the B.Stat. degree of the Institute are eligible only if they have taken all the four elective papers  in Economics in the B.Stat. course. The  details  of  admission
are available in the prospectus.

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2. STIPENDS AND OTHER FINANCIAL SUPPORTS:

The students admitted to this course will be  given  initially  a stipend at par with that of M.Stat. students which is at  present
Rs.800/- only per  month  and  an  annual  contingency  grant  of  Rs.1250/- only. Students should be warned  at  the  end  of  each semester if the performance is unsatisfactory and in  which  case his/her stipend may  be  withdrawn  fully  or  partially.  If  the stipend of a student  is  withdrawn  fully  or  partially  at  the beginning  of  any  particular  semester,  but  his/her  academic
performance in that semester turns out to be good  then  the  full  amount of the stipend for  that  semester  may  be  restored  with retrospective effect. A student will  deserve  this  provided  the requirements for continuation of the programme are  satisfied  and the course composite score in that semester is at least 60% and no more than one composite score in that semester is less  than  45%. Stipend should be given after the end of  each  month  for  eleven months in each academic year.

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3. METHOD OF EXAMINATION AND AWARD OF DEGREE:

For  each  course  there  should  be  periodical   and   semestral  examinations; the scores in these would be  combined  in  suitable ratios to be decided  by  the  teachers'  committee  to  obtain  a composite score in the course. A student will be allowed to take a semestral examination if  he/she  attends  at  least  75%  of  all classes in the semester and  his/her  character  and  conduct  are satisfactory. A student would  be  declared  to  have  passed  the first/second year of the course if he/she
a) does not obtain a composite score of less  than  25%  in  any course,
b) does not obtain a composite score of less than  45%  in  more than three courses, and
c) secures at least 45 in an  overall  percentage  of  composite scores in the course.

If the composite score of a  student  falls  short  of  45%  in  a course, the student may take a back paper  examination.  At  most four back paper examinations will be allowed in a  year  for  each student. Maximum possible score in the back paper  examination  is 45. Only one back paper is allowed in each course. A maximum of  6 back paper examinations will be allowed in two years. If a student fails  to  appear  in  periodical/semestral  examinations  due  to illness or extreme family emergency, and this is promptly reported to the Dean of Studies in writing, the teachers' committee, at its discretion,  may  allow  the   student   to   take   supplementary examinations.

If the student fails in the first year  examinations,  even  after appearing for supplementary/back paper examinations referred to in the preceding  paragraph,  then  he/she  has  to  discontinue  the course. However, if he/she fails in the second  year  examinations even after supplementary/back  paper  examinations,  then  at  the discretion of the teachers' committee, he/she may  be  allowed  to repeat the second year of the course without stipend. If a student fails to meet  the  attendance  requirements  due  to  illness  or extreme family emergency, which is promptly reported to  the  Dean of Studies in writing, the teachers' committee, at its discretion, may waive the attendance requirements. A student who successfully completes the first and the second year of the course  will  be  declared  to  have  passed  the  M.S.  in  Quantitative Economics degree examination and placed in the
i) First Class with Distinction if  he/she  secures  an  overall average percentage score of at least 75 in the twenty courses,

ii) First  Class  if  the  student  secures  an  overall  average percentage score of at least 60  but  less  than  75  in  the
     twenty courses,
iii) Second Class if the student fails to secure First Class with Distinction or First Class.

A student passing the M.S.(Q.E) degree examination will be given a certificate of M.S.(Q.E) degree and a marks sheet mentioning

i)  the twenty courses taken and the composite percentage   score  in each course, and

ii) the class in which the student is placed.

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4. COURSE  STRUCTURE :

The programme comprises fourteen compulsory courses  (including  a dissertation) and six optional courses distributed  as  follows  :

(a)  five compulsory courses each in  semesters  I  and  II  (first     year), two in semester III and  one  in  semester  IV (second year);
(b) six optional courses and the dissertation in semesters III and  IV (second year).

The student will have to  opt  for  one  of  the  following  three packages in the second year.
 

Package (i)      : three optional courses in each  of  semesters  III and IV and a dissertation in semester III;
Package (ii)     : three optional courses in each  of  semesters  III and IV and a dissertation in semester IV;
Package (iii)    : two  optional  courses  and  a   dissertation   in semester III and four optional courses in semester IV.
 

Semester I of the course will be taught in Delhi, semesters II and III will be taught in Kolkata and semester IV will be taught both in Delhi and Bangalore. However, any particular student will  have to take the course for semester IV either in Delhi or in Bangalore depending upon his optional subjects. The semesterwise distribution of compulsory courses apart from the
Dissertation is given below :

Semester I :

(a) Microeconomic Theory I,
(b) Macroeconomic  Theory I,
(c) Statistics I (for students without  statistics  background)
     or
     Advanced Mathematics (for students with statistics background),
(d) Economic  Development  I,
(e) Mathematical  Methods  in Economics
     or
     Optimisation   Techniques   (for   students   with mathematical background).

Semester II :

(a)  Microeconomic  Theory  II,
(b)  Macroeconomic Theory II,
(c) Statistics  II  (for  students  without  statistics background)
     or
     Advanced Statistics (for students  with  statistics background),
(d) Statistics  III,   Computer   Programming   and Applications   (for   students   without   computer   programming
      background)
      or
      Advanced Computer Programming  (for  students  with computer programming background),
(e) Econometric Methods I.

Semester III :

(a) Econometric Applications  I
(b) Planning Techniques.

Semester IV :

(a) Economic Development II.

The optional courses are to be chosen from the following list :

 1. Econometric Methods II
 2. Econometric Applications II
 3. Time Series Analysis and Forecasting
 4. Sample Survey : Theory and Practice
 5. Bayesian Econometrics
 6. Intertemporal Economics
 7. Game Theory and Economic Analysis
 8. Theory of Planning
 9. Industrial Organization
10. Social Accounting
11. Agricultural Economics
12. Public Economics
13. Regional Planning
14. International Economics I
15. International Economics II
16. Mathematical Programming with Applications to Economics
17. Monetary Economics
18. History of Economic Thought.
19. Macro Dynamics.
20. Social Choice and Political Economy.
21. Incentives and Organization.
22. Privatization and Regulations.
23. Environmental and Resource Economics.
24. Theory of Finance I.
25. Theory of Finance II.
26. Political Economy and Comparative System.
 

The list of optional courses may be revised from time to time  and the courses to be actually offered announced at appropriate  time.

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5. DISSERTATION:

A student is required to submit a dissertation paper  on  a  topic assigned/approved by the teachers' committee  and  prepared under the supervision of a faculty member. The work should be started at the beginning of the third semester by the students taking package (i) of the course and the fourth semester by other students and be completed along with the courses of the respective semesters.  The dissertation should be submitted within two weeks of completion of all examination for the courses in the semester. The work for  the dissertation should relate to some important problem in an area of  Economics, conometrics, Quantitative Economics or related  topics and would be  graded  as  one  full  course  in  a  semester.  The dissertation will be evaluated by the supervisor and a copy of it, along with the grade/score awarded by the supervisor, be submitted to the Dean of  studies  sufficiently  prior  to  the  meeting  of teachers' committee for finalising the result.

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6.SYLLABI OF THE COURSES:

The Compulsory Courses would be as follows :

1. Microeconomic Theory I
2. Macroeconomic Theory I
3(a). Statistics I, or
3(b). Advanced Mathematics (for students with a statistics background)
4. Economic Development I
5(a). Mathematical Methods in Economics, or
5(b). Optimization Techniques
6. Microeconomic Theory II
7. Macroeconomic Theory II
8(a). Statistics II, or
8(b). Advanced Statistics (for students with a statistics background)
9(a). Statistics III, Computer Programming and Applications, or
9(b). Advanced Computer Programming (for students with a computerprogramming background)
10. Econometric Methods I
11. Econometric Applications I
12. Planning Techniques and Plan Models
13. Economic Development II
14. Dissertation

The Optional Courses would be as follows:

1. Econometric Methods II
2. Econometric Applications II
3. Time Series Analysis and Forecasting
4. Sample Survey: Theory and Practice
5. Bayesian Econometrics
6. Intertemporal Economics
7. Game Theory and Economic Analysis
8. Theory of Planning
9. Industrial Organization
10. Social Accounting
11. Agricultural Economics
12. Public Economics
13. Regional Planning
14. International Economics I
15. International Economics II
16. Mathematical Programming with Applications to Economics
17. Monetary Economics
18. History of Economic Thought
19. Macrodynamics
20. Social Choice and Political Economy
21. Incentives and Organizations
22. Privatisation and Regulations
23. Environmental and Resource Economics
24. Theory of Finance I
25. Theory of Finance II
26. Political Economy and Comparative Systems

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(A) SYLLABI FOR COMPULSORY COURSES:

Compulsory Course 1: Microeconomic  Theory

1.  Theory of consumer Behaviour under Certainty, Preference  orderings,  utility  functions,  budget  sets,  demand
     theory, duality theory. Theory of revealed preference. Aggregation  of  individual  demand curves. Applications.
2.  Theory of the Firm Production sets, cost minimization,  profit  maximization,  supply curves. Duality theory, Aggregation of
     individual  supply  curves, theory of monopoly, Applications.
3.  Demand-Supply Equilibrium in a Single Market Equilibrium  in  a   single   market.   Stability   :   Walrasian, Marshallian,
     and cobweb models, Methods  of  comparative  statics, Applications to capital an labour markets.
4.  Decision-Making under Uncertainty Preference  over  lotteries.   Von   Neumann-Morgenstern   utility functions. Risk
     aversion and measures thereof.  Partial  orderings of risky projects. Applications.
5.  Market Structure with Imperfect Competition Monopolistic Competitions. Oligopoly Theory.

Compulsory Course 2: Macroeconomic Theory I

1.  Review of National Income and Product Accounts.
2.  Keynesian Macroeconomics: effective demand and the multiplier - IS-LM  model  -  aggregate  demand  and  supply  curves  -  simple macroeconomics of the open economy.
3.  Structuralist Macroeconomics : Structural rigidities in a  less developed economy- demand, supply and credit constraints.
4.  The Supply of Money: monetary and financial institutions.
5.  Introduction to Growth Theory.

Compulsory Course 3(a): Statistics I

1. Type of investigation and collection of data : Complete  enumeration,  sample  survey,  controlled   experiments,
    observational studies, retrospective and prospective studies.
2. Types of observations : Classification and tabulation of univariate data. Summarisation of  univariate data-Histogram,  mean,
    variance,  skewness,  kurtosis, ogive, percentiles, Interpretation.
3.  Notions of statistical inference:
    (a) Estimation of  population  mean  -  Use  of  random  sampling, simulation study.
    (b) Randomized allocation - Valid comparisons-simulation study.
    (c) Elementary concepts of design of experiments - Local  control, randomization and replication - through examples and
         simulation.
4. Probability Theory: Sample  space,  events.  combinatorics.  classical  and  axiomatic definition  of  probability;simple  consequences.  Equally  likely probability  model.  Conditional  probability  and   independence. Bayes' formula.
Random   variables,   distribution   function,   discrete   random variables,  Binomial,  Poisson,  Geometric,   Negative   Binomial, Hypergeometric  -  illustration  through  data,  genesis.  Poisson approximation  to  Binomial.   Continuous   random   variables   - introduction,  illustration  by   simulation,   Uniform,   Normal, Exponential,  Beta,   Gamma,   Logistic,   Pareto,   Lognormal   - illustration  trough  data,  genesis.  Normal   approximation   to Binomial. Distribution of function  of  a  random  variable.  Expectation  - definition, mean, variance and moments in general. Illustration.
5. Bivariate data : Discrete and continuous type. Scatter diagram. Bivariate frequency distribution-arrays and marginals. Correlation -  computation  and interpretation.   Linear   regression   -    regression    effect, least-squares computation, residuals, RMS  errors  for  regression and its use,  outliers,  (graphically),  check  on  linearity  and homoscedasticity (graphically) Curvilinear regression, correlation ratio, intraclass correlation, Rank  Correlation.  Association  of  attributes.
6. Bivariate probability distribution : Marginal and  conditional.  Conditional  expectation.  Regression, Correlation. Bivariate normal distribution.

Compulsory Course 3(b): Advanced Mathematics : Real Analysis

1. Elements of point-set topology in Rn  : Open sets in Rn, structure  of  open  sets  in Rn,  closed  sets,
Accumulation   points,   Bolzano-Weierstrass    Theorem,    Cantor inter-section  theorem,  Lindelof  covering  theorem.  Heine-Borel Theorem, Compactness in Rn. Metric space,  point-sot  topology  in metric space, Boundary of a set.
2. Limits and continuity in metric space: Convergent sequences  in a metric space. Cauchy sequence. Complete metric spaces, Limit  of  a function. Continuous function, Continuity and inverse images  of  open and  closed  sets,  Functions  continuous  on  compact  sets, Topological mappings. Bolzano's theorem, connectedness.
3. Discontinuities of real-valued functions: Monotonic  functions. Functions of bounded variation. Total variation.

Compulsory Course 4: Economic Development I

1.  Introduction
2.  Technological Dualism
3.  Financial Dualism
4.  Contractual Relations in Agriculture:
5.  Industrial Development
6.  Growth. Distribution and Employment
7.  Inequality and Poverty
8.  International Economy and Economic Development

Compulsory Course 5(a): Mathematical Methods in Economics

A. Linear Algebra

Vector in Rn. Simple operations. Vector  spaces  in Rn.  Spanning set.   Linear   dependence    and    independence.    Basis    and finite-dimensional vector space, Dimension  of  finite-dimensional vector space. Extension of a linear  independent set  to  a  basis, subspace and its dimension. Norm and inner product. Orthogonality. GramSchmidt process. Orthogonal basis. Projection of a vector  on a sub-space. Matrix. Row-space and  column-space.  Nullity.  Rank. Singular  and  nonsingular  matrices.  Inversion  of   a   matrix. Idempotent  Matrix.  Orthogonal  Projection.  Numerical  solution. Linear equations: homogeneous and non-homogeneous.

B. Advanced Calculus: Functions of Several Variables
 

1. Sequences and convergence. Closed and open sets. Limit points.
2. Functions of several independent variables. Geometry.
3. Continuity
4. Partial derivatives; change in the order of differentiation.
5. Differential and its geometric meaning.
6. Mean-Value Theorem and Taylor's Theorem.
7. Integrals of a function depending on a parameter continuity and differentiability. Interchange of Integrals.

C. OPTIMIZATION

Lagrange method of multiplies. Maxima and Minima of several variables. Elements of linear programming.

Compulsory Course 5(b): Optimization Techniques.

1. Convex sets; Separation theorems for convex sets.
2. Lagrange method of multipliers. Maxima and minima of  functions of several  variables.
3. Elements of linear  programming.  Convex  programming.  Dynamic programming. Applications.
4. Partial derivatives; change in the order of differentiation.
5. Differential and its geometric meaning.
6. Mean-value theorem and Taylor's Theorem.
7. Integrals of a function depending on  a  parameter-  continuity and differentiability. Interchange of integrals.

Compulsory Course 6: Microeconomic Theory II

1. Equilibrium with Many Commodities and Agents Equilibrium of exchange : the working of the model; relatedness of
goods;   complementality   and    substitutability-stability  on comparative statics vs dynamic stability  and  the  correspondence
principle.

Equilibrium with production : relatedness of  goods  and  factors; stability and comparative statistics with production.
Process of factors and goods in general equilibrium under constant returns to scale : the non-substitution  theorem  and  the  factor price equalization theorem: the production frontier.
2. Existence of a General Equilibrium Pure exchange model. The model with production.
3. General Equilibrium and Welfare. Welfare functions. Social choice  and  aggregation  of  individual objectives. The Pareto ranking  and  the  fundamental  theorem  of  welfare economics. Theory  of  the  core  of  an  economy.  Market  failures.
4. General Equilibrium with Public Goods External effects. Collective consumption. Lindahl equilibrium.
5. Introduction to non-Walrasian Equilibrium Dreze   equilibrium.   Benassy    equilibrium.    Malinvaud-Yonnes
equilibrium.  Equivalences  between   the   different   types   of  non-Walrasian equilibria. Efficiency of non-Walrasian equilibrium.

Compulsory Course 7: Macroeconomic Theory II

1. Microeconomic foundations of Macroeconomics - contributions of  the disequilibrium theorists :
The  Hicks  Patinkin  theory:  full  employment  and   involuntary unemployment in Patinkin'smodel. Clower's critique of  the  Hicks- Patinkin   theory:   notional   demand,   effective   demand   and non-Walrasian equilibrium - Classical and  Keynesian  unemployment in a non-Walrasian framework.  Asymmetric  price  flexibility  and effectiveness  of  employment  policies.  Role  of  money  in  the disequilibrium framework.
2. Microeconomic foundations of macroeconomics - contributions  of  the non classical school. The basic market clearing model,  Money, inflation and interest rates in the  market  clearing  model.  The labour  market,  investment  and   economic   growth.   Government behaviour - taxes,  transfers  and  the  public  debt,  Money  and business fluctuations - the market clearing model with  incomplete information.  rational  expectation  and  the  new   approach   to stabilization policy.
3. Special Topics Overlapping generations model and money, contract theory of price rigidity and unemployment, theory  of  government  policy,  recent developments  in  the  analysis  of  the  problem  of  balance  of  payments, inflation and unemployment.

Compulsory Course 8(a): Statistics II

1. Multivariate data: Covariance   matrix.   Multiple   linear   regression.    partial correlation. Multiple correlation.
2. Multivariate distributions : Continuous and discrete conditional  and  marginal.  Independence, Expectation and  conditional  expectation,  Moments,  Regressions. Partial   and   multiple   correlations.    Multivariate    normal distribution  -  description  and  properties.  Joint  probability distribution of random variables.  Order  Statistics.  Chebyshev's inequality, WLLN,CLT.
3. Random sampling : Techniques of drawing  random  sampling;  Theory  and  methods  of stratified  sampling,  systematic  sampling,  varying  probability sampling,  multistage  sampling  and  ratio  estimation   methods; related sampling distribution by simulation.
4. Point Estimation Finite population : Estimation of mean  and  proportion.  Standard error.   Estimation   of   parameters   in   standard   univariate distribution. Statistic, estimator, MSE, uniasedness, consistency, Sufficiency.  Method   of   moments,   LSE,   MLE,   Computations. Illustrations, Comparison of estimators, Cramer-Rao inequality.
5. Interval Estimation : Introduction. Illustrations with standard  distribution.  Criteria for  goodness  -  Simulation.  Confidence  interval  for   median. Large-sample approximation.

Compulsory Course 8(b): Advanced Statistics

Time-series    Analysis:    Discrete-parameter    stochastic processes; strong and week stationarity; autocovariance  and
autocorrelation. Moving average (MA),  autoregressive  (AR), autoregressive  moving  average  (ARMA)  and  autoregressive
integrated  moving  average(ARIMA)  processes.   Box-Jenkins models.  Estimation  of  the  parameters  in  ARIMA  models;
forecasting.  Residuals  and  diagnostic  checking.  Use  of  computer packages. Spectral analysis  of  weakly  stationary
processes.  Periodogram  and  correlogram   analysis;   fast Fourier transforms

Compulsory Course 9(a): Statistics III, Computer Programming and Applications

Computer Programming - (First half of the semester)

1. Computer Organisation : Hardware : Memory; control unit; arithmetic logic unit; input  and output devices; number system; internal representation of  numbers and  characters;  machine  language.  Software  :   Higher   level language: compiler; assembler; operating system; editor.
2. Programming in a high level language (FORTRAN/C etc.) : Flow charts: constants and variables; arithmetic operators; string
operators; logical operators; relational operators; arithmetic and logical  expressions,;   input   and   output   statements,   type
specification and storage location allocation control  statements;
subprogramme, files.
3. Numerical/Statistical applications, random number generation
4. Numerical/Econometric/Statistical packages :

Statistics III (second half of the semester)

1. Tests of Statistical Hypotheses: Statistical Hypotheses, Type I and Type II errors, level and size, p-value,  randomized  test,  power.  Illustration  with   binomial distribution. Sign test.
Normal distribution - one-population and two-population  problems. One way classified  data.  F-Test.  Unbiasedness.  Computation  of  Power. Distribution of X-bar and S2. Tests for correlation. Tests for regression coefficients. Tests for parameters in N2.
2. Large-sample tests for means, proportions etc. Chi-Square  test of goodness of fit. Test of homogeneity. Test for independence.

Compulsory Course 9(b): Advanced Computer Programming

1. Programming in PASCAL/C Concept of data,  program  heading,  label  declaration,  constant definition, type definition, variable declaration,  procedure  and function declaration. Assignment statement, compound  statement,  repetitive  statement,
conditional statement, unconditional jump statement, Data types  - scaler and subrange, structured types - array, record,  set  file. pointer.
2. Procedures and function : Input and Output Statements.
3. Data structures : (The course will consist of 5 hours on the terminal per  week  and 50 lecture hours)

Compulsory Course 10: Econometric Theory I

1. Estimation of parameters of  multivariate  normal  distribution and principal components analysis.
2(a)  The Nature of Econometrics.
2(b)  Review of classical Least Squares Regression  Analysis:  point and  interval  estimation  and  tests  of   hypotheses   involving regression  coefficients; R2  and adjusted R2 ;  prediction  :  non-linear relationships;  Use  of  dummy  variables;   multicollinearity   - consequences and  use  of  extraneous  information;  specification errors : ML estimation and asymptotic results.
2(c)  Generalized   LS   Theory:   Detection   and   handling   of heteroscedasticity (Glesjer test  and  Goldfeld-Quandt  test)  and autocorrelation of disturbances (AR(1), error  process  only):  DW statistic and Von Neuman ratio (BLUS and recursive residuals  )  ; properties of OLS  estimators  under  non-spherical  disturbances; prediction.
2(d)  Stochastic Regressors; (i) case where X and epsilon are  fully independent; (ii)case where X and  epsilon  are  contemporaneously uncorrelated; uses of lagged  independent  variables;  distributed lags;   use   of   lagged   dependent    variables    with/without autocorrelated disturbances; time series methods; (iii) case where X and epsilon are contemporaneously correlated: (a) The errors  in variables problems, IV estimation and grouping  methods;  (b)  The problem of simultaneous equation systems - structural and  reduced forms. Least squares bias, the problem of identification, rank and
order conditions  for  identifiability,  use  of  restrictions  on variances and covariances of disturbances; indirect least squares,
recursive systems and OLS, two-stage LS,  K-class  estimators.  IV estimation, LIML/Least Variance Ratio estimation.  Three-stage  LS and FIML methods. Comparative merits  of  different  estimators  - asymptotic results, Monte Carlo studies. Prediction from estimated structural models.

Compulsory Course 11: Econometric Applications I

1.  Analysis  of  Income  and  Allied  Size  Distributions  Pareto distribution, graphical test and fitting, universality of Pareto's
Law.  Lognormal  distribution-properties,   graphical   test   and fitting, law of proportionate effect. Income inequality  -  notion
of economic inequality,  Lorenz  curve,  Lorenz  ratio  and  their properties, other common measures of inequality; poverty - concept and measurement.
2. Demand Analysis Demand  function  and  elasticities   of   demand;   Engel   curve specification  and  estimation  from  budget  data,  treatment  of demographic factors in Engel curve  analysis.  Demand  function  - specification and estimation from time-series data, methodological problems in estimation, dynamic factors in the analysis of  demand for a single commodity.
3. Production Analysis: Production  function  -  theoretical  properties,  elasticity   of substitution: problems of estimation  of  a  production  function; Cobb-Douglas  production  function  -  methods  and  problems   of estimation.

Compulsory Course 12: Planning Techniques and Plan models

1. Introduction Concept of economic planning, planning techniques and plan models.
2. Linear Programming (LP) (i) Examples of LP problems; dual problems; some duality theorems. (ii) A review of  relevant  results  in  linear  algebra,  Simplex method and related theoretical results. Exercises, (iii) Use of LP model to solve resource allocation problem-decentralized planning, an outline of the  Dantzig  Wolfe  algorithm  as  a  decentralized planning technique.
3. Input-Output (IO) Analysis :(i) The Structure, (ii) The problem of viability, (iii) Uses of I/O  model,  (iv)  Extensions  of  I/O
models - (a)  Introduction  of  primary  factors  and  feasibility approach, (b) Leontief model, (c) Introduction of  joint  products in an activity and also alternative  activities  for  producing  a given good.
4. Cost-Benefit Analysis(CBA) (i) Objectives of CBA : (ii)  Identification  and  measurement  of  costs and  benefits  ,  (iii)  Rate  of  interest  for  CBA;  time preference for individual and for society: methods of discounting. Exercises on CBA.
5. Plan Models (i) Methodology of plan models. (ii) Macroeconomic  growth  models and their uses in planning: (a) the Harrod-Domar model -investment and growth; (b) investment capacity  "the  Feldman  -  Mahalanobis model.(iii) Multi-sector models: (a)  general  structure  of  such models, (b) selected multisector planning models.

Compulsory Course 13: Economic Development II (Indian Economics)

A. MACROISSUES

1. Development of the Indian Economy - an Overview
2. Unemployment, Urbanisation and Industrialization
3. Constraints on Growth
4. Level of Living and Poverty
5. Planning in a Mixed Economy
6. Economic Policies
7. Resource Mobilization
8. Balance of Payments
9. Monetary Policy

B. MICROISSUES

1. Agricultural Development
2. Industrial Development
3. Regional Disparities and Urbanization

Compulsory Course 14: Dissertation

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(B) SYLLABI FOR OPTIONAL COURSES:

Optional Course 1: Econometric Methods II

1.  Inference  in  Linear  Regression  Model  with   Non-spherical Disturbances;  Detection  of  Presence  of herteroscedasticity  in disturbances - Breusch Pagan -  test.  Ramsey's  test,  Szroeter's class  of  tests,  White's  test;  estimation  under  alternatives specifications of heteroscedasticity:  detection  of  presence  of serial correlation in disturbances - Breush  -  Godfrey  test  and gereralization of the Durbin-Watson  test:  estimation  of  models with MA(1) and ARMA(1,1) error processes.
2.  Qualitative  and  Limited  Dependent   Variable Models; Linear probability  model;  probit  and  logit  analysis;  censored   and truncated  models;   Heckman's   and   Amemiya's   approaches   to estimation of such models.
3.  Specification  Analysis: Types  of  misspecification  and  their consequences: Criteria for selection of a set of regressors R2  and adjusted R2, Mallow's Cp Criterion, Amemiya's prediction criterion, Akaike's information   criterion   and   Sawa's   information    criterion;non-linearity, transformation of variables and related econometric problems, estimation of  models  with  Box-Cox  transformation  of variables, Hausman's general test of misspecification;  tests  for non-nested models.
4. Analysis of Panel Data: Alternative model specifications - models with varying intercepts  and  constant  slope  coefficient,  dummy variable model and the error components model, the SUR models; and Swamy's random coefficient  model;  stimation  of  these  models; Hildreth-Houck  random  coefficient  models  switching  regression model and adaptive regression model.
5. Decision Theoretic and Other  Types  of  Inferences  in  Linear Models: Alternative  approaches  to  inference;  decision-theoretic estimators; models with prior  information  -  pretest  estimator, James-Stein  estimation  ridge  and  adaptive  ridge   estimators; Boot-strap  and  Jacknife  -  resampling  procedures   and   their applications in regression analysis.
6. Inferences in Nonlinear Statistical Models Introduction: estimation methods. computational methods - gradient methods, method of steepest descent; Newton-Raphson methods etc.
7. Introduction to Bayesian Econometrics Bayes'  Theorem,  prior  probability  density   functions.   point estimates of parameters, Bayesian intervals for parameters,  point prediction, some large sample  properties  of  Bayesian  posterior
probability density functions.

Optional Course 2: Econometric Applications II

1. Income and  Allied  Size  Distributions  Stochastic  models  of income  distribution-  forms  of  income  distribution  and  their properties.  Measurement  of  economic  inequality-  positive  and normative  measures  of  relative  inequality,  Aitkinson-Kohm-Sen measure, significance of Lorenz curve  in  inequality  comparison; problems of  measurement  and  comparison  of  income  inequality; Indian studies on income  distribution,  inequality  and  absolute poverty.
2. Demand Analysis Theoretical frame for demand analysis  based  on  complete  demand systems:  alternative  approaches  to  specification  of  complete static demand system: models of complete static demand systems and their properties - linear expenditure  system.  Rotterdam  models. models based on generalized  Gorman  Polar  form  cost  functions; method and  problems  of  estimation  of  complete  static  demand system; dynamic demand models - sources of  dynamism  in  consumer
behaviour; alternative  approaches  to  specification  of  dynamic functions - Chow's  model,  Stone  Rowe  model,  state  adjustment model, properties and estimation methods for these models.
3. Production Analysis Review  of  production  theory  with  special  reference  to   the alternative approaches to representation of production  technology and  the  properties  of  a  production  function  including   the elasticity of substitution:  Cobb-Douglas  production  function  - properties,   specification,   problem   of   identification   and alternative  estimation   techniques;   constant   elasticity   of substitution (CES) production function - properties and estimation techniques;  treatment  of  technical   progress   in   production analysis; aggregate  production  functions:  general  problems  of production analysis with particular reference to the  problems  of choice of form, choice of variables, problem  of  aggregation  and measurement of variables and interpretation.
4. Application of  Econometrics  to  Macro-economic  ProblemsMacro econometric models - econometric issues in the  specification  and estimation: illustrative  application;  uses  in  forecasting  and policy evaluation.

Optional Course 3: Time Series Analysis and Forecasting

Time series as a realization of stochastic  process.  Stationarity and  strict  stationarity.  White  noise,  test   of   randomness.
Estimation and  elimination  of  trend  and  seasonal  components. Autocovariance function and their estimation. AR,  MA  and  ARMA  processes their  properties,   conditions   for stationarity, invertibility, Autocovariance function  and  partial
autocovariance  function  ,   ARIMA   processes.   Identification, estimation and diagnostic checks; order selection; Seasonal  ARIMA processes. Prediction -Minimum  MSE  forecasts,  including  standard  errors. stepwise autoregression. Exponential smoothing and  its  variants. Optimality of exponential  smoothing.  Combination  of  forecasts. Comparative merits of different techniques. Transfer  function  models  -  construction  and  use.  Asymptotic properties of maximum likelihood  and  least  squares  estimators. confidence intervals. Multivariate time series  models.  Threshold models, Elements of spectral analysis - estimation and use. Use of computer packages for time series analysis.

Optional Course 4: Sample Survey: Theory ad Practice

1. Introductions: Need of sample surveys. Sampling versus complete enumeration. Merit of random sampling. Random sampling number. and their uses for random sampling. pps selection by  Lahiri's  method and using map frames.
2. Sampling Techniques Simple random sampling with/without  replacement  estimation  with s.e.'s  of  population/domain   totals/means,   proportions   etc. stratified  srs  allocation  of   sample   size,   gain   due   to stratification,  construction  of  strata.  linear  and   circular systematic sampling. pps  and  pps  systematic  sampling.  Cluster sampling. Multi-stage sampling two-stage simple  random  sampling, choice of sample sizes. Composite    sampling     designs;     self-weighting     designs:
interpenetrating  sub-samples.  Ratio  estimators-bias.  use  etc. Regression estimators, Double  sampling:  sampling  on  successive occasions.
3. Planning and Conduct of Sample Surveys Statement of objectives: choice  of  method  of  data  collection; questionnaire designing: choice of reference period  and  handling of seasonality; choice of  sampling  frame  and  sampling  design:
pilot  surveys:  cost  and  variance  functions;  field  work  and supervision; data editing and processing.
4. Non-sampling Errors: Measurement and control: coverage errors; nonresponse and response errors:  Post-enumeration  surveys  and   reinterviews:   external (record)  checks;  consistency  checks;  use  of  interpenetrating samples etc.
5. Experience of Indian Surveys on Selected Topics

Optional Course 5: Bayesian Econometrics

1. Principles of Bayesian Analysis
2. The Simple Univariate Normal Linear Regression Model
3. Analysis of Single Equation Nonlinear Models
4. Multivariate Regression Models
5. Comparison and Testing of Hypothesis
6. Simultaneous Equations Econometric Models

Optional Course 6: Intertemporal Economics

1. A Model of Intertemporal Accumulation The General multisector  growth  model,  drawn  from  Von-Neumann.Malinvaud, Feasible programmes, Properties of the set of  feasible programmes.
2. Efficient Consumption Programs Characterizations of efficiency in aggregative  and  multisectoral models, efficiency and present value maximization.
3. Optional Consumption Programs Optimality  criteria  in  discounted  and   undiscounted   models, Existence of optimal programs.
4. Selected Topics Exhaust  resources,  Consistent  planning   and   dynamic   games, Irreversible investment, Overlapping generations models, Temporary equilibria.

Optional Course 7: Game Theory and Applications

1. Noncooperative Games Games in normal form.  Nash  equilibrium  and  standard  concepts, Applications of static games  to  economics,  Games  in  extensive form.  A  refinement  of  Nash  equilibrium:  subgame  perfection.Applications of extensive games. Other  refinements.  Applications to economic situations with incomplete information. Repeated games
and applications.
2. Cooperative Games Games in characteristic function form. Various solution  concepts: core,  bargaining  set,  Shapley  value,   etc.   Application   to economics.

Optional Course 8: Theory of Planning

1. Political Economy of the State, Alternative Viewpoints
2. Modelling Government Behaviour Rational choice  models,  median  voter  model,  legislatures  and special interest groups; bureaucracy models.
3. Planning Models Centralized  planning:  informationally   decentralized   planning processes: Lange-Lerner, MDP procedures: Team Theory.
4. Incentives within the Public Sector Performance Incentives for managers, decentralized organisation of production,  multidivisional  firms,  cost  centres   and   profit centres, cost allocation transfer pricing, labour policies: Soviet and East European firms.
5. Cost-Benefit Analysis
6. Pricing Public Sector Outputs Marginal  cost  and  average  cost  pricing,  peak  load  pricing, priority pricing.

Optional Course 9: Industrial Organisation

1. Structure-Conduct Performance Paradigm
2. Static Oligopoly Models Homogeneous  goods-Cournot  and  Bertrand  models:  differentiated products - horizontal and vertical  differentiation:  models  with free entry contestable markets. Cournot and price  setting  models with free entry.
3. Dynamic Oligopoly models Entry deterrence, limit pricing, attrition and reputation  models, collusion and cartels.
4. R & D and Adaption of Technology Private vs. social incentives  for  R  &  D  models  of  adoption. diffusion and transfer of technology.
5. Mergers and Takeovers Firm size and vertical integration, corporate finance.
6. Regulation of Monopolies Rate of  return  regulation,  regulation  of  firms  with  unknown costs/demands.
7. Multinational Firms

Optional Course 10: Social Accounting

1. The Economic Process and Various Concepts
2.  System of Scocial/National Accounts
3. National Accounts and Various Estimates
4. 'Real' Gross Domestic Product/'real' National Income
5. Estimation of National Income in India
6. Preparation of an Input-output (IO) Table,

Optional Course 11: Agricultural Economics

Part I : Theory

1. Price  and  income  elasticities  of  demand  for  agricultural commodities,   factors   affecting   demand    for    agricultural
commodities with particular reference to developing economies.
2.  Characteristics  of  the  supply  function  for   agricultural commodities - output response in periods of rising prices -  lags
in adjustment and the cobweb model -price responsiveness of market supply.
3. Agricultural price policies: aims of price policy  -  types  of price policy - theoretical  analysis  of  price  support  and  its
applicability.

Part II Issues in Indian Agriculture

1. Growth & fluctuations in Indian agriculture since  independence.
2. Farm efficiency.
3. The New Agricultural Techonology.
4. Behabiour of marketed/marketable surplus of foodgrains.
5. Rural employment.
6. Relations of production.

Optional Course 12: Public Economics

1. Welfare  Objectives  of  the  State  :  Interpersonal   utility comparisons;   incentives   and   mechanism   design;   Gibbard
   Satterthwaite theorem. Groves scheme for public goods.
2. Consumer Surplus & Deadweight Loss, Tax incidence. (Harberger)
3. Optimal Taxation and Public Production
4. Dynamics : incidence and efficiency analysis of taxes.
5. Tax Evasion
6. Imperfect Competition and Optimal Fiscal Policies.
7. Controlling  Externalities:  second-best  theory  and  optimal taxes.
8. Procurement Policies : incentive contracts and auction theory.

Optional Course 13: Regional Economics

1. Introduction to Regional Planning
2. Review of the Indian Situation
3. Concepts and Techniques Used in Regional Planning
4. Regional Decisionmaking and Regional Balances
5. Functioonal Spatial Configuration and Regional Synthesis

Optional Course 14: International Economics I

1. The Basic Exchange Model: Stability and comparative statics - immeserizing growth,  transfer problem.
2. Ricardian Trade Theory - comparative advantage with many  goods and many countries - neo-Ricardian trade theory.
3. Neo-classical Models  of  Trade  -  The  Heckscher  -  Ohlin  - Samuelson model and the specific factor model.
4. Theory of Commercial Policy - tariffs, taxes  and  quantitative restrictions.
5. Imperfect Competition and International Trade
6. International Trade and Economic Development

Optional Course 15: International Economics II

1. Introduction to balance of payments
2. Different approaches to the  problem  of  balance  of  payments adjustments.
3. Exchange Rate Regimes - fixed exchange rate. flexible  exchange rate.
4. Forward  Markets.  spot  markets  and  the  efficient   market hypothesis of exchange rate determination.
5. Selected Topics - The Quershooting  hypothesis,  components  of the  current  account  and  the   exchange   rate.  international transmission of economic disturbances.
Optional Course 16: Mathematical Programming with Applications to Economics

1. Static Problems Quadratic Programming - Wolfe's algorithm,  optimization  problems with large variance in returns.
Nonlinear  Programming  Methods  -  Frank-Wolfe  method,  gradient method, resource allocation problems.Stochastic Linear programming
2. Dynamic Problems Calculus of Variations - Euler Equation, first  and  second  order conditions for fixed and end  point  problems,  free  horizon  and transversity condition. Optimal  Control   Theory-The   Ponntryagin   Maximal   Principle,
applications  to  production  planning,  growth  and   investment. Dynamic  Programming-  Principle  of  optimality,  application  of optimal  growth  problems,  Stochastic   Dynamic   Programming   - Application to asset price, investment under uncertainty.

Optional Course 17: Monetary Economics

Transaction, Precautionary  and  speculative  demands  for  money, Money in a  overlappling  generation  model,  General  equilibrium Baumol-Tobin Model, Cash-in-advance  model,  Currency  and  Credit with long lived agents in overlapping generations, Monetary policy (non-)neutrality, Money,  inflation  and  stability,  Money  vs. interest rate targetting.

Optional Course 18: History of Economic Thought

Part I. Overview of the Subject and Time-frame of Reference "Beginning" of the subject in the concept  of  "circular  flow"  -
idea of "social accounting"; the mercantilist background -  common and  distinct  analytical  features  of  the  "reaction"   against
mercantilism in Adam Smith and Quesnay ; theoretical structure  of classical economics - division of labour and exchange, wage,  rent and profit, the Ricardian system;  Marx-  the  wider  perspective, surplus value; abandonment of classical framework of the  "turning point" in the history of economic thought -  common  and  distinct analytical features of the "reaction" against classical  economics in Jevons, Menger and Walras, the second generation  marginalists, birth   of   "welfare    economics","perfect"    and    "imperfect competition",  "effective  demand";  review  of  the   theoretical structure of contemporary economics -  micro  and  macroeconomics; short vs long run; economic theory and econometrics.

Part II. Major Thematic Developments Social Accounting: Physiocracy - breaking  through  the  "circular flow", the concept of "product net", the physiocratic system as  a whole;  classical  economics  -   departures   from   physiocracy, distinguishing the "physical" and the "value"  approaches  to  the problem, developments in each approach, the problem of "services" - contribution  of  Mill  and  Senior;  neoclassical  economics  - subjectivist redefinition of the concept of  production,  national
income accounting and related systems. Price formation: Classical (Smith)  -  natural  vs  market  price,  the  problem  of  "rent"; neoclassical (Marshall) - "firm theory", market morphology and the bench mark of "perfect competition", short vs long run  and  fixed vs variable costs, further developments - doctrines  of  imperfect competition; modern (Kalecki and others) -  theories  of  producer pricing.Macro  Modelling  :  Quesnay  :  Tableau  Economique;  Ricardo   : Distribution through time; Marx  :  Theories  of  crises;  Keynes, Kalecki and genesis and morphology  of  macro-models  of  business cycles/ growth/ distribution/ development. Welfare Economics  :  Origin  and  evolution  of  the  concept  of "utility"; Marshall and the Cambridge tradition; Paretian  welfare economics; Social welfare function. General equilibrium : Walras; the problem of " existence" and  the development   of   mathematical   economics;   tatonnement,   non- tatonnement and the problem of "stability"; feedback from "general equilibrium" to "macro modelling"  -  multisector  models  of  von Neuman, Leontief and Sraffa. Developments in Money- Banking, Public Finance  and  International Trade.

Optional Course 19: Macrodynamics

Traditional Growth Models : Bounds  on  long  term  growth  rates, technological progress and unbounded growth,  predictive  contents of the models. The Convergence Question and The Need for an Endogenous Theory  of Growth : Early results on endogenous growth - market failures, new growth theory models and alternatives  channels  for  endogenizing growth - technology (physical capital, product  innovation,  human capital),  population  growth  (fertility),   government   policy.
Growth in an Open Economy.

Optional Course 20: Social Choice and Political Economy

1. Classical Aggregation Theory: Arrow's  theorem,  Harsanyi's  theorem,  aggregation   with   rich informational structures.
2. Classical Voting Theory : The  Gibbard  -  Satterthwaite  theorem,  results  on  restricted domains, the median voter result,  stochastic  outcome  functions. The  Theory  of  Implementation   in   Complete   and   Incomplete Information Settings.
The Theory of Elections, Legislatures and Agenda Control.
3. The Theory of Interest Groups : Lobbying, bureaucracies, endogenous coalition  formation.  Models of Corruption.

Optional Course 21: Incentives and Organizations

1. Theory of Incentives : Adverse  selection,  moral  hazard,  multiple   agents,   contract dynamics.
2. Organization Theory : Team theory, message space  size,  costly  information  processing models.
3. Incentive-based Approaches : Supervision, managerial slack, limited commitment.
4. Applications to the Theory of the Firm : Decentralisation,  hierarchies,  transfer   pricing,   managerial compensation, cost allocation.

Optional Course 22: Privatization and Regulation

Regulation of competition; externalities and  natural  monopolies; vertical integration; mergers  and  takeovers;  bureaucracies  and corruption.  Public  Sector  Performance  in   India   and   Other Developing Countries. Privatisation : Theory and experiences.

Optional Course 23: Environmental and Resource Economics

Externalities;  model  of  resource  depletion;  exhaustible   and renewable  resources;  irreversibility  and  uncertainty;   common property;  the  charges  and  standard  approach  in   environment regulation; direct control and  taxes;  contingent  valuation  and other approaches to non-market valuation.

Optional Course 24: Theory of Finance I

Preference Representation Under Uncertainty. Stochastic Dominance. Measures of Risk. Portfolio Frontier. Value aximisation  and  the Seperation  Theorem.  CAPM.  Valuation  of  Security.   Asymmetric Information and Efficiency.

Optional Course 25: Theory of Finance II

Modigliani-Miller Theorem. Agency Costs and  Management.  Debt  vs Equity.   Corporate   Law   and   Governance.Takeovers,   Mergers, Acquisitions  and  Their  Disciplinary  Impact  on   Opportunistic Behaviour. Value  of  Large  vs  Small  Share  Holders.  Financial Institutions and the Market for Corporate Control.

Optional Course 26: Political Economy and Comparative System

1. Classical Political Economy : Crystallisation of  the  concept  of  "social  structure"  in  the concept of "class"- class  division  and  boundary  of  production ("productive"  vs  "unproductive"  class/labour)  in  Quesnay  and Smith, the systems of social accounting, policy aspects - reaction against  "mercantilism";  theoretical   structure   of   classical
political economy- value,  distribution  and  accumualations,  the Ricardian  system,  the  post  Ricardian  scene  :  emergence   of "socialist" doctrines.
2. Marxian Political Economy : The  boarder  perspectives  and  view  of  history  -  "modes   of production" (feudalism, capitalism and socialism);  the  political economy of capitalism - surplus value, theories of crises.
3. Further Developments in the Political Economy of Capitalism :
Developments within a "class"  framework  -  Kalecki's  theory  of effective demand  and  business  cycles;  abandoning  the  "class" framework or the turning point in the history of economic  thought - birth of  "welfare  economics",  "competition"  and  "monopoly", Keynes' theory of effective demand and its link up with the theory of growth.
4. Political Economy of Socialism : Doctrines and experiences.
5. Political Economy of LDCs : The intrinsic heterogeneity and amorphousness of LDCs, the  "goal" of development and role of "governments" -  the  "mixed"  economy, economic development in a historical perspective - the concept  of "dual economy", global perspectives.

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