Quantitative Modelling-Part-2 by Tarun Das

8/14/2019 Quantitative Modelling-Part-2 by Tarun Das

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Quantitative Modeling Part-2

A Multiregionalmultisectoral Transport

Model for IndiaPresented by

Dr Tarun Das

Professor, IILM, Lodhi Inst.Area

Formerly Economic Adviser,Plannin Commission and Min of


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CONTENTS

1. Macroeconomic and Transport Model

2. Surveys of Traffic Flows and ModalCosts

3. Model Results

4. Conclusions


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1.1 A Multisectoral MultiregionalTransport Model for India

Macro Model and Sub-models:1. Macroeconomic and input-output model

2. Regional Allocation and Traffic Generation

3. Traffic Distribution

4. Optimal modal split5. Network assignments

6. Investment and physical planning

7. Economic Evaluation

8. Systems feedback


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1.2 Macroeconomic and Input OutputModel in Leontief Framework

Xit = aij Xjt +FitFit = Cit + Git + Iit + STit + EXit - IMPit

Cit estimated by Engel curvesLinear C = + YLoglinear Log C = + Log Y

Semi log Log C = + Y

Log Inverse Log C = + / Y

Log Log Inverse Log C = + 1 Log Y+ 2 / Y

Iit is estimated by investment sub model within a framework of adistributed lag mode.

Git is estimated by minimum needs program and other public distributionand welfare programs.

STit by fixed coefficients.

EXit are exogenous.

IMPit =mjt xjt + ki Cit + bi Git + hi Iitl


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1.3 Regional Allocation andTraffic Generation

Regional demarcation: India is divided 420zones (broadly coinciding with districts) and20 regions.

Commodity aggregation: by rail trafficclassifications.

1. Regional allocation of supply- Shift and share

technique2. Regional allocation of demand- Regional

input-output model in Leontief framework

3. Surveys on transport cost by rail, road, air,

inland water and coastal shippingTransport cost = User cost + Operator cost


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1.4 Traffic ForecastingModels

1. Time trend method2. Elasticity approach3. Traffic intensity method4. Transport coefficient method5. Multiple regression model6. Input-output model

7. Material balance approach8. Linear programming model9. Gravity model


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1.5 Traffic Distribution

1. Gravity model for heterogeneous goodsTrs = Ar Bs Xr Ds exp (- Crs) for each commodity i Xr = Trs over s= 1 to 20 Ds =Trs over r=1 to 20

X =Xr +Ds

2. Linear Programming Model forhomogeneous goods

3. Calibration of the model fordetermination of commodity specificparameter

4. Test of the model


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1.6 Modal Split andOther Sub-models

1. Modal split by least cost mode2. Network assignment by successive

shortest path with capacity constraints

3. Investment requirement of each mode

and region is estimated in terms ofinfrastructure and vehicular needs giventhe age profile and life span of existingstock.

4. System is evaluated for resourceconstrains in terms of time, money,energy and foreign exchange needs.


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2.1 Survey on traffic flowsand modal costs

1. Comprehensive All India Survey conducted byRITES with the help of state govts.

2. Computerized Railway data for the year 1986-87-O-D matrix for commodities for 7000 railwaystations

3. Survey for roads and ports4. Computerized Air passenger data by Indian airlines

for all origins and destination

5. Economic cost= Operator cost+ user cost

6. Shadow price for labour and energy


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2.2 Traffic of Bulk Goods in1986-87

Items Mln

ton

Bln

TKM

Rail

Lead

Road

Lead

Total

Km

1.Foodgrains 46 34 1146 386 748

2.Coal 120 82 717 469 482

3.Iron ore 22 7 325 373 327

4.POL 30 13 504 271 429

5.Iron-steel 20 16 1191 487 308

6.Cement 31 16 673 276 524

7.Fertilisers 24 17 939 292 706

2 3 C dit i h


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2.3 Commodity-wise shares(%)

Goods Rail

Ton

Road

Ton

Total

Ton

Rail

tkm

Road

tkm

Total

tkmFoodgrains 8.5 10.7 9.5 12.5 10.2 11.8

Coal 40.7 7.4 25.1 37.8 8.3 28.4

Iron ore 8.2 0.4 4.6 3.4 0.4 2.5

POL 8.1 4.4 6.4 5.3 2.9 4.5

Iron & steel 3.6 4.9 4.2 3.5 5.9 5.6Cement 7.6 5.3 6.5 6.6 3.6 5.7

Fertilizers 5.5 4.3 4.9 7.0 3.1 5.7


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. o a ares- a anRoad

Goods Rail Ton Road Ton Rail TKM Road tkm

Foodgrains 48 52 73 27

Coal 86 14 91 9

Iron ore 96 4 95 5

POL 68 32 80 20

Iron-steel 46 54 67 33

Cement 62 38 80 20

Fertilisers 59 41 83 17

All goods 53 47 69 31

2 5 B k i t f d


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2.5 Break-even points for road(kms)

Goods Road

Lead km

1976-77

price

1986-87

price

% shift

Foodgrains 386 247 280 +13.4

Coal 469 201 232 +15.4

Iron ore 373 241 324 +34.4

POL 271 60 67 +10.1

Iron-steel 487 311 220 -29.3

Cement 276 222 193 -13.1

Fertilisers 292 200 184 -8.0

All goods 406 200 210 +5.0


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3.1 Model results

1. Traffic forecast for 1990-91 and 1995-96

2. Modal split by least cost mode

2. Network assignment and identification

of high density corridors by rail androad

3. Investment requirements of each mode

4. Recommendations regardingrationalisation of passenger fares andfreight rates


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4. Concluding Remarks

1. Rail transport is least expensive for long andmedium distance and bulk traffic

2. Rail transport is least energy intensive, moreenvironment friendly and less accident prone.

3. Road transport is cheapest mode for short distance

and consumer friendly for door to door service. Italso generates more employment and helps inenhancing rural connectivity.

4. However, road transport is more energy intensiveand leads to pollution problems and traffic hazard.


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Thank you

Have a Good Day

Quantitative Modelling-Part-2 by Tarun Das

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