Quantitative Modelling-Part-1 by Tarun Das

8/14/2019 Quantitative Modelling-Part-1 by Tarun Das

1/14

Quantitative Modeling

Presented byDr Tarun Das


2/14

2

1.1 Purpose of Quantitative Modeling

Policy planning versus physical planning

Indicative planning versus target setting

Optimizing versus consistency approach

Partial/sectoral versus economy wide model

Selective versus all purpose modelLearning versus blue print approach

Consultancy versus dirigist approach

Monitoring trends versus forecasting future

Sound public investment versus overallinvestment planning


3/14

3

1.2 Dimensions of Quantitative Models

Macro models (National level)

Meso (Middle level)Spatial (over space)Regional (over regions)

Sectoral (over industries/ sectors)Micro (at unit levels)Inter temporal (over time)

Intergenerational (over generations)


4/14

4

1.3 Types of Models

Static or dynamic models

Short, medium, long term model Consistency or Behaviouristic or

Optimizing or Econometric models

Closed or open economy model Economy wide or sectoral model

Selective or All purpose model

Comprehensive or partial model Deterministic or indeterminate


5/14

5

1.4 Desirable characteristicsof an Ideal Model

Internal consistency Comprehensiveness with two-way feed backs

Dynamic to take care of change over time

Unique and stable solutions

Easy testing and calibration of the model withthe help of available data, computer capacitiesand algorithms, statistical techniques

Model should be continually tested, reviewed,

Calibrated, monitored, updated, simulated andimproved to make it more realistic


6/14

6

1.5 Advantage of Econometric Modeling

An Econometric Model helps: to formalize the system,

to establish inter-relations

among major policy variables thatcan be specified, calibrated,tested, monitored, updated,simulated and predicted withcertain degree of confidence, and to identify trade-off amongalternative policy options.


7/14

7

2.1 Steps in Econometric Modeling

Specify objectives and purpose

Have a sound theoretical basis Identification of potential variables Specification of equations Identification of equations

Calibration of parameters Testing- Various goodness of fitstatistics- R-sq, -sq, Theil index etc. Simulation and policy planning

Monitoring and updatingPrediction and Projection.


8/14

8

2.2 Econometric Modeling

Types of Data

Time series

Cross section

Panel - Combination of time series and

cross section data Pooled- Combination of sectors/ regions


9/14

9

2.3 Types of variables.3 Types of variables Endogenous variables (determined

within the model) Ct,Yt Exogenous/ predetermined variable Wt

Parameters , , , , Lagged variable Ct-1 Instrumental variable Wt Dummy (binary, categorical, indicator,

qualitative, dichotomous) variable Dt

Omitted variables Catch all variable (could be time trend)

Ct = + Yt +Wt + Ct-1 + Dt

Dt = 1 if t is 1991 to 2003, 0 otherwise


10/14

10

2.4 Types of EquationsTechnical such as production function

Behavioral such as consumption function Definitional such as capital/output ratio

Identities such as Y = C + I + G

Structural form

Ct = 1 + 1Yt + Ut It =2 +2Yt + 3Yt-1 + Vt

Yt = Ct + It + Gt

Reduced form

Yt = 3 + 4Yt-1 + 5 Gt + Wt3 = (1 + 2 )/6,4 =3 /6,5=1/6,6 =1 -1 -2

3 1 G l Di t b


11/14

11

3.1 General Disagreements byModelers

Let all the flowers flourish

General purpose versus single purpose model

Normative versus descriptive model

Policy oriented versus general understanding

Short run versus long run model

Large versus small model

Top down versus bottom up model

To guess or leave out crucial missing data

How to deal with future economic agents,technology change, prices and population?

Whom should we address?


12/14

12

3.2 General Agreements by Modelers- 1

State your biases and intuitive arguments

Computer models of social systems should not beexpected to produce precise results.

Qualitative judgements from econometric modelsare useful for policy formulation.

Models should be selected to fit problems.

Social environment and political economymay betreated as given in the model.

Models should be tested rigorously for the realworld with full range of policies.

Substantial portion of resources should be usedfor full documentation of the model.


13/14

13

3.3 General Agreements by Modelers-2

Part of the model documentation should be

technically complete so that any other group cantest, calibrate and run the model.

Part of the documentation should be clear and freefrom jargons for general understanding by the non-technical audience.

Modelers should specify data sources and sharetheir data.

Users and policy makers should be involved in themodeling process.

It is necessary to continually review, monitor,update, upgrade, and simulate the model.


14/14

14

Thank you

Have a Good Day

Quantitative Modelling-Part-1 by Tarun Das

Documents

Transcript of Quantitative Modelling-Part-1 by Tarun Das