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MPRA
Munich Personal RePEc Archive
Estimating the economic impacts of the
Padma bridge in Bangladesh
Selim Raihan and Bazlul Haque Khondker
South Asian Network on Economic Modeling (SANEM),
Department of Economics, University of Dhaka, Bangladesh
November 2010
Online at http://mpra.ub.uni-muenchen.de/37904/
MPRA Paper No. 37904, posted 7. April 2012 16:26 UTC
Estimating the Economic Impacts of the
Padma Bridge in Bangladesh
Selim Raihan
1
Bazlul Haque Khondker
2
November, 2010
1
Dr. Selim Raihan is Associate Professor, Department of Economics, University of Dhaka, Bangladesh.
selim.raihan@econdu.ac.bd
2
Dr. Bazlul Haque Khondker is Professor, Department of Economics, University of Dhaka, Bangladesh.
bazlul.khondker@gmail.com
Estimating the Economic Impacts of Padma Bridge in Bangladesh Raihan and Khondker (2010)
2
Content
EXECUTIVE SUMMARY
I. INTRODUCTION AND BACKGROUND
II. JAMUNA BRIDGE STUDY
III. TRAFFIC MODEL
IV. BANGLADESH SAM 2006/07
V. THE SAM MULTIPLIER MODULE
5.1. Derivation of the SAM Multiplier
5.2. Simulation Design: SAM-Based Model
5.3.1. Results of Simulation 1A
5.3.2. Results of Simulation 1B
5.3.3: Results of Simulation 2A
5.3.4. Results of Simulation 2B
5.3.5 Assessment of Annual Effects
5.3.6. Economic Cost-Benefit Analysis of Simulations 1A and 2A
VI. THE IMPACTS OF THE PADMA BRIDGE: A COMPUTABLE GENERAL EQUILIBRIUM ANALYSIS
6.1. The CGE Model for Bangladesh Economy
6.2. Simulation Design
6.3. Simulation Results
6.3.1. Macroeconomic Effects
6.3.2. Price Effects
6.3.3. Volume Effects
6.3.4. Factor Movements and Value-Added Effects
6.3.5. Welfare Effects
VII. POVERTY ESTIMATES UNDER DIFFERENT SIMULATIONS
VIII. CONCLUDING OBSERVATIONS
References
Annex 1: SAM Multiplier Modules
Annex 2: Mapping and Classification Scheme
Annex 3: Multipliers of the SAM Modules
Annex 4: Equations of the CGE Model
Estimating the Economic Impacts of Padma Bridge in Bangladesh Raihan and Khondker (2010)
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List of Tables
Table 1: Description of Simulations of the Jamuna Bridge Study
Table 2: Total and Annualized Economic Impacts of Simulations of the Jamuna Bridge Study
(Percentage Change from Base Values)
Table 3: Road User Benefit from the Traffic Model
Table 4: Disaggregation and Description of Bangladesh SAM Accounts
Table 5: Description of the Endogenous and Exogenous Accounts and Multiplier Affects
Table 6: Simulation 1A: Economic Wide Benefit of Intervention Using the National SAM Model-
Intermediate Classification (In million taka unless otherwise specified)
Table 7: Simulation 1A: Economy Wide Benefit of Intervention Using the National SAM Model-Final
Classification (In million taka unless otherwise specified)
Table 8: Simulation 1B: Economy Wide Benefit of Intervention Using the Regional SAM Model-
Intermediate Classification (In million taka unless otherwise specified)
Table 9: Simulation 1B: Economy Wide Benefit of Intervention Using the Regional SAM Model-Final
Classification (In million taka unless otherwise specified)
Table 10: Simulation 2A: Economy Wide Benefit of Intervention Using the National SAM Model-
Intermediate Classification (In million taka unless otherwise specified)
Table 11: Simulation 2A: Economy Wide Benefit of Intervention Using the National SAM Model-Final
Classification (In million taka unless otherwise specified)
Table 12: Simulation 2B: Economy Wide Benefit of Intervention Using the Regional SAM Model-
Intermediate Classification (In million taka unless otherwise specified)
Table 13: Simulation 2B: Economy Wide Benefit of Intervention Using the Regional SAM Model-Final
Classification (In million taka unless otherwise specified)
Table 14: Total and Annualized Economy Wide Benefit of Simulations (Percentage Change from Base
Values)
Table 15: Economic Evaluation Results Based on Simulation 1A (US$ million in 2009 prices, US$ 1 =
70 Taka)
Table 16: Economic Evaluation Results Based on Simulation 2A (US$ million in 2009 prices, US$ 1 =
70 Taka)
Table 17: Rates of Transport Margin by Sectors under Base and Simulation Scenarios
Table 18: Macroeconomic Effects (% change from base value)
Table 19: Sectoral Price Effects (Percentage change from base value)
Estimating the Economic Impacts of Padma Bridge in Bangladesh Raihan and Khondker (2010)
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Table 20: Price Impacts of Intervention Using the National Level 5 Activity Classification (Percentage
change from base value)
Table 21: Sectoral Effects of Simulation (Percentage change from base value)
Table 22: Volume Impacts of Intervention Using the National Level 5 Activity Classification
(Percentage change from base value)
Table 23: Effects on Value Added and Factor Movements (Percentage change from base value)
Table 24: Volume Impacts of Intervention Using the National Level 5 Activity Classification
(Percentage change from base value)
Table 25: Welfare effects (Percentage change from base value)
Table 26: Annualised Reduction in Aggregate Head-count Poverty Estimates under Different
Simulations (% change from base value)
Table 27: Annualised Impacts on Poverty Indices for different Household Groups under different
Simulations (% change from base value)
Estimating the Economic Impacts of Padma Bridge in Bangladesh Raihan and Khondker (2010)
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EXECUTIVE SUMMARY
Construction of Padma Bridge is expected to generate welfare to the people of Bangladesh
in general and the people of South West in particular. The benefits are expected to arise
from the greater integration of regional markets within the Bangladeshi national economy.
Moreover, given the interdependence of economic activities/sectors, the direct impacts of
the Padma Bridge on individual sectors and factor markets are likely to induce a chain of
changes in the rest of the sectors of the economy.
In this exercise, attempts have been made to quantify the economic as well as welfare
implication of Padma Bridge using four different types of methodologies. Although strict
comparisons of the outcomes of these models are not usually advocated, they have been
used in this exercise to examine the robustness of the project benefit outcomes
3
.
1. Although, it is customary to use ‘traffic’ models to estimate the benefits of transport
project (e.g. Padma Bridge), reliance only on the traffic model may underestimate full
benefits of the project since such model can only capture primary or direct benefits in
the form of efficiency gains arising out of cost and time saved.
2. The secondary benefits of a transportation project are also substantial. The secondary
effects may be generated due to multi-sectoral productivity gain through structural
change occurring in the economy from improved productivity made possible by the
bridge. The well known models for capturing secondary benefits are SAM based fixed
price and CGE models.
3. Hence in addition to adopting the traffic model, both SAM based fixed price and CGE
models are employed to estimate full benefits of the Padma Bridge project. In this
context the full benefits would thus compose of efficiency gains of traffic model and the
economy wide benefits of the SAM and CGE models.
4. Because of its location in the South West region of Bangladesh, Padma Bridge is
expected to have larger impacts on this regions compared to the other parts of
Bangladesh. A regional CGE model, although not an impossibility, has not been possible
because of lack of required region specific parameters and elasticity values. However a
regional SAM model was formulated to assess the impacts of Padma Bridge on the SW
region of Bangladesh.
Social Accounting Matrix (SAM) constructed for Bangladesh economy as well as for the
South West region served as the data bases for the above three economy wide models.
Following simulations were carried out to examine the benefits of the Padma Bridge. More
specifically, four simulations have been conducted for the SAM-Based Model. These are:
3
All these models are stand alone model and hence their outcomes should be considered independent of each
other. Strict comparison is not advocated in the literature. However, in this exercise road user benefit of the
traffic model is combined with the outcome of the SAM model (i.e. considering it as a measure of economy
wide secondary impacts due to the implementation of the project) to derive total benefit of the project.
Estimating the Economic Impacts of Padma Bridge in Bangladesh Raihan and Khondker (2010)
6
I. Simulation 1A (National): Total investment cost of building Padma Bridge will be around
$2.9 billion, out of which $2.1 billion will roughly be injected into the national
economy.The rest of the total cost will consist of imported inputs, interest charges etc.
$2.1 billion is expected to be injected into the economy in the following way:
Construction sector $1.4 billion, utility $0.1 billion, trade $0.1 billion, transport and
communication $0.15 billion, different kinds of services (professional, financial, public
administration, social etc) $0.3 billion and food $0.05 billion. This total injection figure
would exclude foreign imports, contingencies, IDC etc from the total cost of the bridge.
All other exogenous elements remain unaltered.
II. Simulation 1B (Regional): In order to simulate the impact of the Padma Bridge within the
Regional SW SAM model, we performed similar injection of $2.1 billion into the regional
economy. We did two alternative scenarios for the regional economy—one scenario
assumes that 100 percent of the investment stimulus will be felt in SW region and the
other scenario is that 70 percent of the stimulus will be operative in south-west region.
All other regional exogenous elements remain unaffected.
Operation of Jamuna Bridge suggests that additional demand may arise for consumer goods,
energy and utility services and as well as transport services. These demand effects are due
to bridge construction and associated services activities. Therefore, in line with the Jamuna
Bridge impact analysis exercise, further simulations were carried out (i.e. 2A and 2B) to
capture economic impacts of demand created by the investment stimulus of $2.1 billion.
The simulation set ups are explained below:
III. Simulation 2A (National): Increase in sectoral demand of other crops by 10 percent,
Fisheries by 10 percent, Utility by 5 percent and Transport by 20 percent at the national
level:
IV. Simulation 2B (Regional): Increase in sectoral demand of other crops by 20 percent,
Fisheries by 20 percent, Utility by 10 percent and Transport by 50 percent at the regional
level:
Construction of Padma Bridge likely to lessen time needed to move goods leading to
reduced transport margins. In line with the study on Jamuna Bridge a similar simulation is
conducted under the CGE framework where sectoral transport margins are reduced and its
impacts on resource re-allocation, sectoral output and consumption, poverty and income
distribution situation of the representative household groups are examined. The simulation
is as follow:
V. Simulation 3: In the CGE simulation base values of the sectoral transport margin rates
are reduced by 50 percent. The base values of all other parameters are retained.
Although outcomes of all types of models are positive, the results show variations due to
especially to size of shocks. The results are summarized below.
1. In the Traffic model, road users benefits are estimated based on the saving on vehicle
operation costs (VOC) and savings in travel time cost (TTC). Total road user benefit is
estimated to be about million 1,295,840 taka ($18,512 million) over the 31 year period.
Estimating the Economic Impacts of Padma Bridge in Bangladesh Raihan and Khondker (2010)
7
2. As for economy-wide (secondary) benefits, use of national SAM with injection of $2.1
billion into the economy (i.e. Simulation 1A) produced economy wide (secondary
benefits) in terms of value added of taka 453,670 million ($6481 million) over a period of
31 years, which represents 10.6 percent growth. This would give an annualized growth
rate of 0.33 percent of national base GDP. This is obtained by dividing the total economy
wide benefits by 31 to get an average annual incremental flow of value and dividing that
figure by base GDP figure, we get this (0.33 percent) annual figure. If the WEB figure is
added to with direct (traffic) benefits, the annual size of the benefits of the bridge, in
relation to GDP, would be larger, as noted later.
3. Compared to national GDP the average annual increase in SW regional base GDP because
of WEB alone will be 2.3 percent. This is on the assumption that a 100 percent of the
shock will occur within the regional economy. However, if we assume that only 70
percent of the shock would be operative in the region (and not full 100 percent), the
equivalent of annual rate of growth regional GDP would be roughly 1.66 percent. The
annual equivalent rate of growth was calculated keeping in view the 31 years as the time
taken to fully realize the impact of the bridge. If we took a shorter time horizon for fully
realizing the benefit of growth, then the annual equivalent rates could be larger. Given
that SAM based model assume excess capacity (which may be a reasonable assumption
in a country like Bangladesh with under-utilized resources), the size of impacts vary with
the size of injection or shock.
4. To sum up, using the Traffic model, road users benefit is found to be million 1,295,840
taka ($18512 million). We consider value added increase of million 453,670 taka ($6481
million) derived from the national SAM model (i.e. simulation 1A) as economy wide
benefits of the project. Thus, total project benefit is estimated to be 1,749,510 million
taka or $24993 million. The breakdown is: Total (1,749,510 million taka or $24993
million) = Road User Benefit (1,295,840 million taka or $18512 million) + WEB (453,670
million taka or $6481 million). This implies that total project benefit is 39 percent relative
to the base national income (i.e. 4,468,549 million taka or $63836 million). Assuming the
31 year full realization timeframe, total project benefits per year is then 1.26 percent
relative to the base national income. The base year GDP figure would not remain the
same over 31 years. Assuming 5 percent GDP growth over (as experienced in recent
years) the 31 period an alternative estimate of base year is arrived. The total project
benefit (i.e. 1,749,510 million taka or $24993 million) is only 0.56 percent relative to the
alternative base national income. Under certain assumptions, the relative size of annual
increase of output for the SW region would be 1.66 percent considering the WEB alone. If
the total benefits were taken into account, the relative size of annual flow of benefits in
comparison to regional GDP would, of course, be larger and, would depend on how much
of the traffic benefits would accrue to the south-west region.
5. Further assessment of the total project benefits (explained above) in terms of
conventional project appraisal measures suggests that the project is economically viable.
More specifically, the project is viable with:
Estimating the Economic Impacts of Padma Bridge in Bangladesh Raihan and Khondker (2010)
8
• a net present value of US$ 1234 million;
• a benefit-cost ratio (BCR) of 2.01; and
• an economic internal rate of return (EIRR) of 19 percent.
6. The application of constrained optimization model such as CGE model outcomes also
vindicates the findings of the traffic model and SAM based model. More specifically, 50
percent reduction in transport margins may lead to welfare increase by 0.78 percent
compared to the base value.
7. Under certain assumptions (Simulation 1A), the construction of the Padma Bridge would
lead to an annualised reduction in head-count poverty at the national level by 0.84
percent and at the regional level by 1.01 percent. Other simulations also indicated
reduction in poverty in different magnitudes.
Estimating the Economic Impacts of Padma Bridge in Bangladesh Raihan and Khondker (2010)
9
I. INTRODUCTION AND BACKGROUND
The Padma Bridge will be built to provide road and rail links between the relatively less-
developed Southwest region (SWR) of the country and the more-developed eastern half that
includes the capital of Dhaka and the port city of Chittagong. By facilitating transportation
across the river, the bridge is expected to lead to a greater integration of regional markets
within the Bangladeshi national economy. Given the interdependence of economic
activities/sectors, the direct impacts of the Padma Bridge on individual sectors and factor
markets are likely to induce a chain of changes in the rest of the sectors of the economy. This
in turn is expected to result in subsequent feedback effects. These indirect and induced
impacts can be estimated utilizing Social Accounting Matrix (SAM) and Computable General
Equilibrium (CGE) models. Moreover, we use the results of the model simulations and feed
them into the poverty module to estimate the impact of the bridge investment on national as
well as regional poverty levels. Furthermore, the simulated income affects are also be
included into the ‘cost-benefit’ analysis for a complete economic evaluation of the Padma
Bridge.
It is expected that the Padma Bridge will have the most significant economic and poverty
impacts in Khulna and Barisal Divisions – the southwest region of Bangladesh. Therefore, it is
also imperative to conduct simulation of the Bridge’s impact at the regional level utilizing an
input-output table for the Southwest and a restructured SAM model that takes into account
region-specific households (i.e. Southwest regional SAM based model). Incorporation of
region-specific households within a SAM framework would surely provide additional avenues
for a more comprehensive assessment of the impacts of the Bridge on sectors, household
income-consumption and, hence, on the poverty situation at the regional level.
In order to assess the impacts of the Padma Bridge, a SAM based-fixed price model and a
CGE based-flex price model are used in conjunction with the traffic model. Models based on
regional SAM are not readily available and thus these models have been built to simulate
the impacts at the regional level. The 2007 SAM for Bangladesh has been modified to
incorporate regional dimension both in production and institutional accounts. The 2007
Estimating the Economic Impacts of Padma Bridge in Bangladesh Raihan and Khondker (2010)
10
SAM is transformed
4
into a fixed price demand driven model to assess the impacts of
additional demand (i.e. presumed to generate due to Padma Bridge) on the regional as well
as on the national economy of Bangladesh. Also, a CGE model for the Bangladesh economy
is used to explore the impact of reduction in transport margin.
Although, it is customary to use ‘traffic’ models to estimate the benefits of transport project
(e.g. Padma Bridge), reliance only on the traffic model may underestimate full benefits of
the project since such model can only capture primary or direct benefits in the form of
efficiency gains arising out of cost and time saved. However, the secondary benefits of a
transportation project are also substantial. The secondary effects may be generated due to
multi-sectoral productivity gain through structural change occurring in the economy from
improved productivity made possible by the bridge. The well known models for capturing
secondary benefits are SAM based fixed price and CGE models. Hence in addition to using
the traffic model, both SAM based fixed price and CGE models are employed to estimate full
benefits of the Padma Bridge project.
A SAM is a square matrix with columns for expenditure and rows covering income accounts.
It combines input-output data with national accounts data to reflect the circular flow of
income at a particular point in time. In this context, its key use is to assess the economy
wide effects of a particular exogenous impact (such as the completion of the Padma Bridge)
that leads to different expenditure patterns. Two limitations of the SAM model are (i) fixed
price ruling out reallocation of resources due to price changes and (ii) excess capacity
ensuring supply due to demand increase. As a result of these limitations, a SAM may
overestimate the impact of investment shocks, especially in a full-employment economy.
On the other hand, CGE analysis, allows for the assessment of the impacts of exogenous
shocks (such as the completion of the Padma Bridge) within a constrained optimization
framework (i.e. changes in quantity are restricted). At the core of the CGE model is a set of
equations describing the behavior of various economic agents (such as firms and
4
A Social Accounting Matrix is a macroeconomic data set consists of accounts such as activity; commodity;
factors; households etc. SAM data set is transformed into a model by assigning some of the SAM accounts as
endogenous and exogenous.
Estimating the Economic Impacts of Padma Bridge in Bangladesh Raihan and Khondker (2010)
11
households) when faced with changes in relative prices. Furthermore, CGE models which
invoke fully flexible prices and supply-side constraints usually underestimate the effect of
investment or policy shocks. In order to examine these bounds, both SAM and CGE models
are employed in this exercise.
5
Furthermore, because of its location in the South West region of Bangladesh, Padma Bridge
is expected to have larger impacts on this regions compared to the other parts of
Bangladesh. A regional CGE model, although is not an impossibility, could not be used due
to lack of required region specific parameters and elasticity values. So a regional SAM model
was preferred over a regional CGE model to assess the impacts of Padma Bridge on the SW
region of Bangladesh. A South West region SAM model was also used to assess Padma
Bridge impact on the SW of Bangladesh.
II. JAMUNA BRIDGE STUDY
6
Similar SAM based and CGE models were also used to estimate the economy wide benefits
of the Jamuna Bridge (JB). The economy wide effects were estimated by applying
conventional macroeconomic tools, making use of an improved version of Bangladesh’s
Social Accounting Matrix (SAM) model and a standard Computable General Equilibrium
(CGE) model. Working with a national level SAM, however, restricts this type of analysis, in
spite of the inclusion of region-specific household groups. This is because the size of change
observed in any activity pertaining to a region is normally scaled down so that the size of the
effect is small. The effect at the household level is further underestimated since the
estimated total change through a national SAM is distributed across households in all
regions. A second exercise was, therefore, carried out to supplement the findings of the first
exercise by estimating changes at the regional level by using a regional SAM. A regional SAM
was thus constructed to capture region-specific outcomes.
5
These models are comparative static models showing before and after shock and are not projections showing
growth paths. Only the traffic model used to estimate the direct benefit does the projection of only the traffic
growth.
6
For details please see Jamuna Bridge Impact Study, Final Report, prepared on behalf of: Asian Development
Bank (TA No. BAN 3681), The Louis Berger Group, Inc. February 2003
Estimating the Economic Impacts of Padma Bridge in Bangladesh Raihan and Khondker (2010)
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In the SAM approach, the impact of the JB was demonstrated through enhancing the demand of
other crops, electricity and transport services.
Three simulations were carried out for SAM
model are described below:
Table 1: Description of Simulations of the Jamuna Bridge Study
Application of SAM Increase in demand
Simulation
National
Other crops—5%
Utility (Electricity) —5%
Transport—16%
Simulation 1 Regional
Other crops—20%
Utility (Electricity) —10%
Transport—50%
Simulation 2 Regional
Other crops—20%
Utility (Electricity) —10%
Transport
—
100%
The outcomes of the SAM models for the Jamuna study are presented below. Since there is no
capacity constraints, matching outputs are always supplied (as a result of demand interventions),
which resulted in higher factorial incomes and household consumption expenditure.
Table 2: Total and Annualized Economic Impacts of Simulations of the Jamuna Bridge Study
(Percentage Change from Base Values)
National SAM Based Regional SAM: Simulation 1 Regional SAM: Simulation 2
Increase in: Total Annualized Total Annualized Total Annualized
Output 29.73 1.19 37.2 1.49 45.65 1.83
Factor Income 28.97 1.16 35.23 1.41 44.29 1.77
Household Income
28.03
1.12
35.72
1.43
44.15
1.77
Poverty Reduction 30.17 1.21 39.92 1.60 47.47 1.90
Note: Poverty reduction rate is reported to have been 1.1 percent per year during 1991-2000.
On the other hand, in the CGE case the simulation was performed by reducing the transport margin
rates. The base values of the sectoral transport margin rates are halved (i.e., reduced by 50 percent)
to examine their implication on variables both at sectoral and macro levels
7
. The base values of all
other parameters are retained.
The changes in transport rates alter the relative price situation in the economy, which then led to
the reallocation of existing resources to various producing activities. The gains are obtained by
reducing existing distortions and hence they are small. Since supplies of primary factors were fixed
there is no scope of generating extra income by employing additional factors (as was the case in the
SAM approach).
7
The sectoral transport rates are derived as proportions of sectoral total domestic sales values.
Estimating the Economic Impacts of Padma Bridge in Bangladesh Raihan and Khondker (2010)
13
Aggregate consumption expenditure, domestic sales, exports and imports are found to be enhanced
by 1.05, 1.10, 1.37 and 0.89 percent compared to their base values. However as expected the most
impressive gains have been found for the general price index which declined by 3.4 percent. The
positive growth of the economy and moderate fall of general price index led to the enhancement of
national welfare by 0.51 percent of base value of household income.
III. TRAFFIC MODEL
8
Road users benefits, estimated based on the saving on vehicle operation costs (VOC) and
savings in travel time cost (TTC). Vehicle operating cost (VOC) is used to provide economic
value in distance savings covering various factors such as fuel, tiers and maintenance etc.
For economic valuation unit VOC was derived from the “Road Users Cost Report, 2004-05”,
RHD. Total VOC was disaggregated into fuel and non-fuel components, which were then
escalated to 2009 values by the increase in average petroleum spot price (IMF, 2009b) and
Consumer Price Index (BBS, 2009a). A measure of Value of Time (VOT) is used to convert
travel time savings into a monetary value. Savings in travel time costs account for 23% of
total benefits estimated by Design Consultant. Unit travel time costs for passengers and
crew were sourced from RHD (2005) and for freight in transit from STUP (2007). These were
then escalated to 2009 using prices by estimated increase in General Wage Rate Index from
BBS (2008) and ADB (2009). These constitute a major part of the quantifiable benefits. Total
road user benefit is estimated to be about million 1,295,840 taka over the 31 year period.
Table 3: Road User Benefit from the Traffic Model
Year
End June
VOC
TTC
Sub
-
total
2011
0
2012
0
2013
0
2014
0
2015
19
31
50
2016
37
50
88
2017
61
75
137
2018
74
87
161
2019
84
97
182
2020
93
106
199
2021
111
124
235
2022
131
145
276
2023
153
168
321
2024
176
193
369
2025
202
221
423
8
The traffic benefits were estimated by Design Consultants and revised by the World Bank team.
Estimating the Economic Impacts of Padma Bridge in Bangladesh Raihan and Khondker (2010)
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Year
End June
VOC
TTC
Sub
-
total
2026
231
243
473
2027
260
266
526
2028
290
291
581
2029
322
316
637
2030
354
342
696
2031
370
351
721
2032
386
360
746
2033
401
370
771
2034
417
378
795
2035
431
388
820
2036
447
397
844
2037
462
407
869
2038
477
417
895
2039
493
427
919
2040
508
437
945
2041
513
438
951
2042
518
439
957
2043
521
440
962
2044
525
441
966
2045
542
455
997
Total (Mill USD)
9609
8900
18512
Total (Mill Taka)
672630
623000
1295840
IV. BANGLADESH SAM 2006/07
In a narrower sense, a SAM is a systematic database and an organized, consistent
classification system. As a data framework, the SAM is a snapshot, which explicitly
incorporates various crucial transaction links among variables, such as the mapping of
factorial income distribution from the structure of production and the mapping of the
household income distribution from the factorial income distribution, among others. In a
broader sense, in addition to providing a consistent classification scheme, it can be
conceived as a modular analytical framework for a set of interconnected subsystems which
specifies the major relationships among variables within and among these systems (see
Pyatt and Thorbecke, 1976).
For the purpose of this exercise, a SAM for 2006/07 for Bangladesh has been constructed.
SAM 2006/07 is composed of 109 accounts. The distributions of 109 accounts are: (i) 41
activities; (ii) 41 commodities; (iii) 4 factors of production; (iv) 11 current institutions; and (v)
2 capital institutions. Data on various components of the demand side have been collected
from Bangladesh Bureau of Statistics (BBS). In particular, data on public consumption by 41
commodities, gross fixed capital formation by 41 commodities, and private consumption by
41 commodities have been obtained from BBS. The vector of private consumption data is
Estimating the Economic Impacts of Padma Bridge in Bangladesh Raihan and Khondker (2010)
15
further distributed among the eight representative household groups using the unit record
data of Household Income and Expenditure Survey (HIES) of 2005. Data on exports of goods
and services are collected from the Export Promotion Bureau and Bangladesh Bank (i.e. the
central bank of Bangladesh). Supply side composed of value added and imports of goods
and services. We used disaggregated BBS data to derive the value added vector for the 41
activities. Data on imports of goods and services are collected from Bangladesh Bank and
National Board of Revenue. Information on direct and indirect taxes and subsidies has been
collected from National Board of Revenue and the Finance division, Ministry of Finance.
Input-output flow matrix for 2006/07 has been derived by using newly conducted surveys
for few selected activities and updating the previous technology vectors using secondary
information. More specifically, out of the 41 activities, technology vectors of five important
activities such as paddy, livestock, poultry, pharmaceuticals and information technology
(ICT) have been derived using the field survey data. The technology vectors of the remaining
36 activities are updated using secondary information.
Due to data limitation, constructing a Southwest specific regional was a difficult task.
Several data sources and information have been consulted to derive the SW regional SAM.
Information of IFPRI regional SAM for Bangladesh for 2005 has been used in addition to the
information/data collected from the secondary sources to derive a SW regional SAM. More
specifically, following data sets have been used along with the information contained in
IFPRI regional SAM to generate the value added vector:
• Provisional Estimates of Gross Regional Product 1995-96 to 1999-2000, published by
the Bangladesh Bureau of Statistics (BBS) in May 2002.
• Employment data from the 2005 Labor Force Survey published by the Bangladesh
Bureau of Statistics (BBS) in 2006.
• Output shares of major sub-sectors within manufacturing from the 2005-06 Report
on Bangladesh’s Survey of Manufacturing Industries (SMI).
Furthermore, input-output coefficients for the Southwest region have been based on the
input-output coefficients used in the IFRPI SAM for the Southwest region. After adjusting
Estimating the Economic Impacts of Padma Bridge in Bangladesh Raihan and Khondker (2010)
16
the I-O coefficients for the 41 activities and commodities, the regional SAM was
appropriately balanced so that the base scenario reflected the current situation (i.e. 2007) in
Khulna and Barisal divisions as closely as possible
9
.
The 2006/07 SAM identifies the economic relations through four types of accounts: (i)
production activity and commodity accounts for 41 sectors; (ii) 4 factors of productions with
2 different types of labour and 2 types of capital; (iii) current account transactions between
4 main institutional agents; household-members and unincorporated capital, corporation,
government and the rest of the world; and (iv) two consolidated capital accounts
distinguished by public and private origins to capture the flows of savings and investment.
The disaggregation of activities, commodities, factors and institutions in the SAM is given in
Table 4.
Table 4: Disaggregation and Description of Bangladesh SAM Accounts
Accounts Description of Elements
Activities (41)
Agriculture (12) Paddy Cultivation, Grains, Jute Cultivation, Sugarcane Cultivation, Vegetables,
Commercial Crops, Other Crop Cultivation, Livestock Rearing, Poultry Rearing, Shrimp
Farming, Fishing, and Forestry
Manufacturing (20) Rice Milling, Grain Milling, Fish Process, Oil Industry, Sweetener Industry, Food,
Leather, Jute, Clothing, RMG, Tobacco, Wood, Chemical, Fertilizer, Petroleum, Clay
Products, Cement, Steel, Machinery, and Miscellaneous
Construction (1) Construction
Services (8) Utility, Trade, Transport, Social Services, Financial services, Public Administration and
Defense, Professional Services, and Other Services
Commodities (41)
Agriculture (12) Paddy Cultivation, Grains, Jute Cultivation, Sugarcane Cultivation, Vegetables,
Commercial Crops, Other Crop Cultivation, Livestock Rearing, Poultry Rearing, Shrimp
Farming, Fishing, and Forestry
Manufacturing (20) Rice Milling, Grain Milling, Fish Process, Oil Industry, Sweetener Industry, Food,
Leather, Jute, Clothing, RMG, Tobacco, Wood, Chemical, Fertilizer, Petroleum, Clay
Products, Cement, Steel, Machinery, and Miscellaneous
Construction (1) Construction
Services (8) Utility, Trade, Transport, Social Services, Financial services, Public Administration and
Defense, Professional Services, and Other Services
9
Detailed National and Regional SAMs are available in Excel.
Estimating the Economic Impacts of Padma Bridge in Bangladesh Raihan and Khondker (2010)
17
Accounts Description of Elements
Factors of Production (4)
Labour (2) Labour Unskilled, and Labour Skilled
Capital (2) Capital and Land
Current Institutions (11)
Households (8) Rural: landless, Agricultural marginal, Agricultural small, Agricultural large, Non-farm
poor and Non-farm non poor
Urban: Households with low educated heads, and households with high educated
heads
Others (3) Government, Corporation and Rest of the World
Capital Institutions (2)
Public Capital Public Capital
Private Capital Private Capital
In that context the Bangladesh SAM 06/07 captures:
• The sources of income and expenditure destination of all accounts.
• Breakdown of sectoral GDP (value addition) by labour and capital factors.
• Income generation and distribution of the institutions in general and household groups
in particular.
• Patterns of expenditure by institutions including Household groups.
• The inter-dependence between activities and institutions with respect to income
generation and final demand creation.
• Inter-dependence among institutions regarding transfer receipts and transfer payments.
• Role of institutions in capital formation.
• Relationship of the domestic economy with the Rest of the World or external sector.
V. THE SAM MULTIPLIER MODULE
5.1. Derivation of the SAM Multiplier
10
The move from a SAM data framework to a SAM model or multiplier framework requires
decomposing the SAM accounts into “exogenous” and “endogenous” as well as to introduce
10
Detailed analysis is provided in Annex 1.
Estimating the Economic Impacts of Padma Bridge in Bangladesh Raihan and Khondker (2010)
18
a set of assumptions pertaining to the Generalized Leontief Model
11
. Generally accounts
intended to be used as policy instruments (e.g. government expenditure, investment,
exports) are made exogenous and accounts a priory specified as objectives or targets must
be made endogenous (e.g. activity, commodity demand, factor return and household
income).
For any given injection into the exogenous accounts (i.e. instruments) of the SAM, influence
is transmitted through the interdependent SAM system among the endogenous accounts.
The interwoven nature of the system implies that the incomes of factors, households and
production are all derived from exogenous injections into the economy via a multiplier
process. The multiplier process is developed here on the assumption that when an
endogenous income account receives an exogenous expenditure injection, it spends it in the
same proportions as shown in the matrix of average propensities to spend (APS). The
elements of the APS matrix is calculated by dividing each cell by its corresponding column
sum totals.
The multiplier analysis using the SAM framework helps to understand the linkages between
the different sectors and the institutional agents at work within the economy. Accounting
multipliers have been calculated according to the standard formula for accounting (impact)
multipliers, as follows:
Y = A Y + X = (I – A)
–1
X = M
a
X
Where:
Y is a vector of incomes of endogenous variables
X is a vector of expenditures of exogenous variables
A is the matrix of average expenditure propensities for endogenous accounts
M
a
= (I – A)
–1
is a matrix of aggregate accounting multipliers (generalized Leontief
inverse).
11
ALARCON, J.V. (2002): Social Accounting Matrix-Based Modelling: Extension to Wellbeing and
Environment and Computable General Equilibrium Models: Applications using the 1975 and 1980 Ecuador and
Bolivian 1989 and 1997 SAMs, Institute of Social Studies, The Hague, The Netherlands, pp. 13-15.
Estimating the Economic Impacts of Padma Bridge in Bangladesh Raihan and Khondker (2010)
19
Variations in any one of the exogenous account (i.e. in this case ΔX) will produce total
impacts (ΔY) of endogenous entries via the multipliers. More specifically they are expressed
as:
ΔY =
M
a
x ΔX.
The economy wide effect is thus equal to ΔY =
M
a
x ΔX. Thus ΔY captures the economy wide
impacts on the four endogenous accounts namely: (i) gross output; (ii) commodity demand;
(iii) factor returns and (iv) household. Table 5 provides the description of the endogenous
and exogenous accounts and multiplier effects.
Table 5: Description of the Endogenous and Exogenous Accounts and Multiplier Affects
Endogenous (y) Exogenous (x)
The activity (gross output multipliers), indicates the total effect on
the sectoral gross output of a unit-income increase in a given
account i in the SAM, and is obtained via the association with the
commodity production activity account i.
The consumption commodity multipliers, which indicates the total
effect on the sectoral commodity output of a unit-income increase in
a given account i in the SAM, is obtained by adding the associated
commodity elements in the matrix along the column for account i.
Intervention into through activities (x
= i + g + e), where i= GFC + ST (GFCF)
Exports (e)
Government Expenditure (g)
Investment Demand (i)
Inventory Demand (i)
The value added or GDP multiplier, giving the total increase in GDP
resulting from the same unit-income injection, is derived by
summing up the factor-payment elements along account i’s column.
Household income multiplier shows the total effect on household
and enterprise income, and is obtained by adding the elements for
the household groups along the account i column.
Intervention via households
(x = r + gt + ct), where
Remittance ( r)
Government Transfers (gt)
Corporation Transfers (ct)
The economy-wide impacts of the Padma Bridge are examined by changing the total
exogenous injection vector, especially Government Expenditure (g), and Investment
demand (investment in construction, infrastructure, machinery and equipment). More
Estimating the Economic Impacts of Padma Bridge in Bangladesh Raihan and Khondker (2010)
20
specifically, the total exogenous account is manipulated to estimate their effects on output
(through an output multiplier), value-added or GDP (through the GDP multiplier), and
household income (through household income multiplier) and commodity demand (via
commodity multipliers). The calculated multipliers are provided in Annex 3.
5.2. Simulation Design: SAM-Based Model
Simulation 1A (National): Total investment cost of building Padma Bridge will be around
$2.9 billion, out of which $2.1 billion is estimated as the amount that will be injected into
the economy. It is further assumed that $2.1 would be injected into the economy in the
following way: Construction sector $1.4 billion, utility $0.1 billion, trade $0.1 billion,
transport and communication $0.15 billion, different kinds of services (professional,
financial, public administration, social etc) $0.3 billion and food $0.05 billion. This total
injection excludes foreign imports, contingencies, IDC etc from total cost. All other
exogenous elements remain unaltered.
Simulation 1B (Regional): In order to simulate the impact of the Padma Bridge within the
Regional SW SAM model, we performed similar injection of $2.1 billion into the regional
economy. All other regional exogenous elements remain unaffected. In tracing the impact
on the regional economy, two alternatives were reviewed. First, it was assumed that the
entire injection would accrue to the region. Second, it was assumed that 70 percent of
injection would accrue to the region.
Operation of Jamuna Bridge suggests that additional demand may arise for consumer goods,
energy and utility services and as well as transport services. These demand effects are in
addition to impacts generated due to bridge construction and associated services activities.
Therefore, in line with the Jamuna Bridge impact analysis exercise, further simulations were
carried out (i.e. 2A and 2B) to capture economic impacts of demand. The simulation set ups
are explained below:
Estimating the Economic Impacts of Padma Bridge in Bangladesh Raihan and Khondker (2010)
21
Simulation 2A (National): Increase in sectoral demand at the national level: Other crops by
10 percent, Fisheries by 10 percent, Utility by 5 percent and Transport by 20 percent.
Simulation 2B (Regional): Increase in sectoral demand at the regional level: Other crops by
20 percent, Fisheries by 20 percent, Utility by 10 percent and Transport by 50 percent.
5.3. SAM Based Simulation Results
Impacts simulations using the ‘National’ and the ‘Regional’ SAM models are reported in
terms of gross output, commodity demand, value added by factors and household
consumption. Moreover, output and commodity demand outcomes are reported using
intermediate classifications of activity (i.e. 17 activities aggregated from the 41 activities),
commodity (i.e. 17 activities aggregated from the 41 commodities), value-added (i.e. 4
factors of production) and household groups (i.e. 8 representative households) as well
according to final classification (i.e. Activity-5, commodity-5, value-added-3 and household
groups-3). The mapping is shown in Annex 2.
5.3.1. Results of Simulation 1A
Simulated outcomes by four endogenous accounts according to the national level
‘intermediate classification’ are reported in Table 6. As a result of the $2.1 billion injection,
the gross output of the economy would increase by 10.56 percent compared to the base
year value. The largest increase of 29 percent has been reported for the construction
activity (i.e. due to increase in construction commodity demand) followed by linked
activities such as forestry (19 percent), utility (17 percent), other industries (14 percent) and
machinery (13.5 percent). The effects on other sectors are determined by the sectoral
interlinkages as can be understood from the estimates of the SAM multipliers reported in
Annex 3.
Estimating the Economic Impacts of Padma Bridge in Bangladesh Raihan and Khondker (2010)
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Table 6: Simulation 1A: Economic Wide Benefit of Intervention
Using the National SAM Model-Intermediate Classification
(In million taka unless otherwise specified)
Endogenous SAM Accounts (Intermediate Classification)
Base Value
Simulation
% Change over Base
1
Cereal Crops
614209
55060
8.97
2 Commercial Crops 199811 13050 6.53
3
Livestock
-
Poultry
-
fishing
764211
62889
8.23
4
Forestry
210295
40473
19.24
5 Other Agriculture 159683 14046 8.80
6
Other Food
1156780
103912
8.98
7
Leather Products
64680
2574
3.97
8
Cloth
274245
12582
4.58
9
Readymade Garments
734635
7323
0.99
10 Chemical-Fertilizer 96050 10558 11.00
11
Machinery
338400
45821
13.54
12
Petroleum Products
45849
4312
9.41
13 Other Industries 318938 44561 13.98
14
Construction
895119
260071
29.06
15
Transport
556137
46726
8.40
16 Utility 200010 34176 17.08
17
Other Services
2746118
231270
8.43
Gross Output
9375170
989400
10.56
1 Cereal Crops 647473 58089 8.97
2
Commercial Crops
281463
18706
6.64
3 Livestock-Poultry-fishing 769744 63383 8.23
4
Forestry
210295
40473
19.24
5
Other Agriculture
178805
15733
8.80
6 Other Food 1302387 116817 8.97
7
Leather Products
65167
2594
3.97
8
Cloth
357348
16784
4.70
9 Readymade Garments 748044 7456 0.99
10
Chemical
-
Fertilizer
220509
23653
10.73
11
Machinery
676932
71475
10.56
12
Petroleum Products
247631
23289
9.41
13
Other Industries
539253
64169
11.90
14 Construction 895119 260071 29.06
15
Transport
654329
54976
8.40
16
Utility
208034
35547
17.08
17 Other Services 2790890 234088 8.39
Total Commodity Demand
10793425
1107304
10.26
18
VA Labour Unskilled
1107767
116069
10.47
19 VA Labour Skilled 1130936 97308 8.60
20
VA Capital
1941427
216344
11.14
21
VA Land
288419
23950
8.30
Value
added
4468549
453670
10.16
Estimating the Economic Impacts of Padma Bridge in Bangladesh Raihan and Khondker (2010)
23
Endogenous SAM Accounts (Intermediate Classification)
Base Value
Simulation
% Change over Base
22 Rural Landless 300256 27482 9.15
23
Rural Marginal Farmers
283097
25634
9.05
24
Rural Small Farmers
549961
47406
8.63
25 Rural Large Farmers 341538 28974 8.49
26
Rural Non Farm Poor
433473
35822
8.26
27
Rural Non Farm Non Poor
1156862
114049
9.86
28 Urban Low Education 490267 42807 8.73
29
Urban High Education
1168683
101617
8.70
Household
income
4724136
423793
8.97
National
(Output + Commodity + Factor + Household)
29361280
2974168
10.13
Note: Gross output = intermediate use + factor payments; Total commodity demand = commodity demanded
by households; Value added = factor payments; Household income = Incomes of different household
categories
Value-added or gross domestic product of the Bangladesh is expected to increase by more
than 10 percent compared to the base case implying that annual addition to GDP over 31
years between 2014 and 2044
12
is 0.33 percent. Largest return would accrue to the capital
factor (11.14 percent) followed closely by unskilled labour (10.47 percent).
As mentioned above, economy wide benefit is added to the road users benefits of the traffic
model to derive the total project benefit
13
. Road users benefit is estimated to be million
1,295,840 taka. We consider value added increase of million 453,670 taka as economy wide
benefits of the project. Thus, total project benefit is estimated to be 1,749,510 million taka
[i.e. Total (1,749,510) = Road User Benefit (=1,295,840) + WEB (=453,670)]. This implies that
total project benefit is 39 percent relative to the base national income (i.e. 4,468,549 million
taka). Assuming the 31 year full realization timeframe, total project benefits per year is then
1.26 percent relative to the base national income. Alternatively, assuming 5 percent GDP
growth over the 31 period an alternative estimate of base year is arrived. The total project
benefit (i.e. 1,749,510 million taka) is only 0.6 percent relative to the alternative base
national income.
Due to leakages of different types (e.g. savings and direct taxes), increase in household
consumption is 1.19 percent less than the increase in value-added or GDP. More specifically,
12
The 31 years time period is selected to maintain consistency with the reference period used in the Traffic
Model.
13
It should be noted that, outcomes of these three models independently suggest that the project is economically
viable.
Estimating the Economic Impacts of Padma Bridge in Bangladesh Raihan and Khondker (2010)
24
total household consumption would increase by 8.97 percent compared to the base case
over the 31 years between 2014 and 2044. Among the household groups, largest increase is
found for the non-farm non poor household group (9.86 percent) followed by landless (9.15
percent) and marginal farmers (9.05 percent).
Simulated outcomes are further aggregated following the classification involving 5 activities,
5 commodities, 3 factors and 3 household groups. Simulated outcomes according to the
final classification are reported in Table 7.
Table 7: Simulation 1A: Economy Wide Benefit of Intervention
Using the National SAM Model-Final Classification
(In million taka unless otherwise specified)
Endogenous SAM Accounts (Final Classification)
Base Value
Simulation
% Change over Base
1
Agriculture
1948209
185517
9.52
2 Manufacturing 3229588 265816 8.23
3
Construction
895119
260071
29.06
4 Transport 556137 46726 8.40
5
Services
2746118
231270
8.43
Gross Output
9375170
989400
10.56
1 Agriculture 2087781 196384 9.41
2
Manufacturing
4365306
361785
8.29
3
Construction
895119
260071
29.06
4 Transport 654329 54976 8.40
5
Services
2790890
234088
8.39
Total Commodity Demand
10793425
1107304
10.26
1 Labour 2238703 213377 9.54
2
Capital
1941427
216344
11.14
3
Land
288419
23950
8.30
Value added
4468549
453670
10.16
1
Rural Land Based
1474851
129498
8.78
2 Rural Non-farm 1590335 149871 9.42
3
Urban
1658950
144425
8.71
Household Income
4724136
423793
8.97
National (Output + Commodity + Factor + Household) 29361280 2974168 10.13
Note: Gross output = intermediate use + factor payments; Total commodity demand = commodity demanded
by households; Value added = factor payments; Household income = Incomes of different household
categories
Estimating the Economic Impacts of Padma Bridge in Bangladesh Raihan and Khondker (2010)
25
As mentioned above, due to the intervention gross output would increase by 10.56 percent
compared to the base case. Among the 5 activities, largest increase of 29.06 percent is
found for the construction activity followed by agriculture (9.52 percent) since forestry is
included in broad agriculture activity classification. Increases in output of the other three
activities would be more than 8 percent.
Income generation has been reported by three types of factors-labour, capital and land.
Largest increase of 11.14 percent is found for the capital factor followed by labour factor
(9.54 percent). Lowest income generation has been reported for land factor (i.e. 8.30
percent).
Among three categories of household groups, largest gain is reported for the rural
household engaged in non-farm activities (9.42 percent) followed almost equally by rural
land based household (8.71 percent) and urban household (8.78 percent).
5.3.2. Results of Simulation 1B
As mentioned in previous sections, the Padma Bridge is expected to have large impact on
the economy and poverty situation of Khulna and Barisal Divisions, since the Bridge links this
region to the generally more prosperous markets of the eastern part of Bangladesh.
However, the previous simulation exercise fails to capture the benefits that may potentially
accrue to the people (households) in the Southwest. There may be two reasons for this.
First, it is necessary to adjust downward the magnitude of the regional impacts of the Bridge
within the national models that was utilized to account for the fractional share of the
Southwest in the whole of Bangladesh. Second, all benefits resulting from the simulations
are distributed to households across all regions so that the pie received by the people in the
southwest is likely to be underestimated. Thus, we also conducted simulations of the
Bridge’s impact at the regional level utilizing a SW regional SAM model that takes into
account region-specific households.
Simulated outcomes of injection of $2.1 billion using the ‘Regional’ SAM model is reported
in this section again in terms of output supply, commodity demand, value added by factors
Estimating the Economic Impacts of Padma Bridge in Bangladesh Raihan and Khondker (2010)
26
and household consumption. The outcomes are reported following the ‘intermediate’ and
‘final’ endogenous account classification.
Table 8: Simulation 1B: Economy Wide Benefit of Intervention
Using the Regional SAM Model-Intermediate Classification
(In million taka unless otherwise specified)
Endogenous SAM Accounts (Intermediate Classification)
Base Value
Simulation
% Change
1
Cereal Crops
82010
49316
60.13
2 Commercial Crops 43145 23194 53.76
3
Livestock
-
Poultry
-
fishing
193480
68146
35.22
4
Forestry
36272
38976
107.45
5 Other Agriculture 26570 16262 61.21
6
Other Food
165149
105160
63.68
7 Leather Products 3129 1785 57.03
8
Cloth
20522
14198
69.19
9
Readymade Garments
14024
8976
64.01
10 Chemical-Fertilizer 23363 9678 41.43
11
Machinery
76982
69954
90.87
12
Petroleum Products
6613
6536
98.83
13 Other Industries 62503 85623 136.98
14
Construction
87508
139738
159.69
15
Transport
78228
56557
72.29
16 Utility 27155 27751 102.19
17
Other Services
386929
257047
66.43
Gross Output 1333583 978900 73.40
1
Cereal Crops
82119
49384
60.13
2
Commercial Crops
44943
24290
54.05
3 Livestock-Poultry-fishing 193508 68165 35.23
4
Forestry
36272
38976
107.45
5
Other Agriculture
26786
16393
61.20
6 Other Food 165628 105478 63.68
7
Leather Products
3130
1785
57.03
8
Cloth
20943
14503
69.24
9 Readymade Garments 14282 9141 64.01
10
Chemical
-
Fertilizer
23424
9704
41.43
11 Machinery 80617 71807 89.07
12
Petroleum Products
6626
6548
98.83
13
Other Industries
63590
86446
135.95
14 Construction 87508 139738 159.69
15
Transport
78382
56667
72.29
16
Utility
27206
27804
102.19
17 Other Services 387554 257368 66.41
Total Commodity Demand
1342515
984197
73.32
18
VA Labour Unskilled
132408
98133
74.11
Estimating the Economic Impacts of Padma Bridge in Bangladesh Raihan and Khondker (2010)
27
Endogenous SAM Accounts (Intermediate Classification)
Base Value
Simulation
% Change
19 VA Labour Skilled 152721 105493 69.07
20
VA Capital
293265
216977
73.98
21
VA Land
64424
37961
58.93
Value added 642818 458562 71.34
22
Rural Landless
41451
28922
69.78
23
Rural Marginal Farmers
41598
27468
66.04
24 Rural Small Farmers 75323 50692 67.30
25
Rural Large Farmers
96441
65962
68.39
26
Rural Non Farm Poor
62621
42482
67.84
27
Rural Non Farm
Non Poor
204405
140637
68.80
28
Urban Low Education
56472
39021
69.10
29 Urban High Education 61593 40813 66.26
Household
Income
639904
435997
68.14
South West Bangladesh
(Output + Commodity + Factor + Household)
3958820.9
2857658
72.18
Note: Gross output = intermediate use + factor payments; Total commodity demand = commodity demanded
by households; Value added = factor payments; Household income = Incomes of different household
categories
Injection impacts on four endogenous accounts of the Regional SAM (i.e. activity,
commodity, factor and household) have been reported in Table 6. As mentioned above,
injection of $2.1 billion into the ‘Southwest’ (SW) Bangladesh would translate 159.69
percent increase in construction demand compared to the regional base value. It is
important to note that the estimated increase of 159.69 percent of construction demand is
almost 5.5 times larger than the estimated increase of 29 percent at the national Level
14
l.
Due to this large injection, the impacts on the four endogenous accounts are also large
compared to the impacts found under the National SAM model.
The gross output of the regional SW economy would increase by 73.4 percent compared to
the base regional gross output. As expected the largest increase of 159.69 percent has been
reported for the construction activity (i.e. due to increase in construction commodity
demand) followed by linked activities such as other industries (135.95 percent), forestry
(107.45 percent), utility (102.19), and machinery (90.87 percent).
14
According to 2007 estimates, regional SW GDP is around 15 percent of national income.
Estimating the Economic Impacts of Padma Bridge in Bangladesh Raihan and Khondker (2010)
28
Value-added or gross domestic product of the SW Bangladesh is expected to increase by
more than 71 percent compared to the base GDP of SW Bangladesh implying that annual
addition to SW GDP over 31 years between 2014 and 2044 would be around 2.3 percent.
Unlike the national case, the largest return would accrue to unskilled labour (74.11 percent)
followed closely by the capital factor (73.98 percent) reflecting regional structure of
production, factorial income generation and their ultimate distribution among the region
specific representative household groups.
Total consumption of the household of SW Bangladesh would increase by 68.14 percent
compared to the their base consumption envisaging that annual addition to household
consumption over 31 years between 2014 and 2044 would be around 2.2 percent. Among
the household groups, the largest increase is found for the landless (69.78 percent),
followed by urban low educated household group (69.1 percent) and non-farm non-poor
household groups (68.8 percent).
Simulated outcomes are further aggregated following the final classification involving 5
activities, 5 commodities, 3 factors and 3 household groups. Simulated outcomes according
to the final classification are reported in Table 9.
Table 9: Simulation 1B: Economy Wide Benefit of Intervention
Using the Regional SAM Model-Final Classification
(In million taka unless otherwise specified)
Endogenous SAM Accounts (Final Classification)
Base Value
Simulation
% Change
1
Agriculture
381477
195896
51.35
2 Manufacturing 399441 329662 82.52
3
Construction
87508
139738
159.69
4
Transport
78228
56557
72.29
5 Services 386929 257047 66.43
Gross Output
1333583
978900
73.40
1
Agriculture
383628
197209
51.41
2 Manufacturing 405444 333214 82.18
3
Construction
87508
139738
159.69
4
Transport
78382
56667
72.29
5
Services
387554
257368
66.41
Total
Commodity Demand
1342515
984197
73.32
1 Labour 285129 203625 71.41
Estimating the Economic Impacts of Padma Bridge in Bangladesh Raihan and Khondker (2010)
29
Endogenous SAM Accounts (Final Classification)
Base Value
Simulation
% Change
2 Capital 293265 216977 73.98
3
Land
64424
37960
58.93
Value added
642818
458562
71.34
1 Rural Land Based 254814 173044 67.91
2
Rural Non
-
farm
267026
183120
68.58
3
Urban
118065
79834
67.61
Household Income 639904 435997 68.14
South West Bangladesh (Output + Commodity + Factor + Household)
3958820.9
2857658
72.18
Note: Gross output = intermediate use + factor payments; Total commodity demand = commodity demanded
by households; Value added = factor payments; Household income = Incomes of different household
categories
As mentioned above, due to the intervention regional gross output would increase by 73.4
percent compared to the base case. Among the 5 activities, the largest increase of 159.69
percent is found for the construction activity followed by manufacturing (82.52 percent) and
Transport (72.29 percent).
Income generation has been reported by three types of factors-labour, capital and land. The
largest increase of around 74 percent is found for the capital factor followed by labour
factor (71.41 percent). Lowest income generation has been reported for land factor (i.e.
58.93 percent).
Among three categories of household groups, largest gain is reported for the rural
household engaged in non-farm activities (68.58 percent) followed almost equally by rural
land based household (67.91 percent) and urban household (67.61 percent).
5.3.3: Results of Simulation 2A
The impacts of the rise in sectoral demand on the national economy using the national SAM-
intermediate classification are presented in Table 10. The gross output increases by 9.2
percent. The largest rise is for the transport sector (27.45 percent) followed by livestock-
poultry-fishing (18.23 percent), utility (16.68 percent), other agriculture (14.78 percent) and
other food (11.02 percent). The total commodity demand increases by 9.08 percent and
value-added by 8.99 percent. The largest rise is for the capital (9.92 percent). Household
Estimating the Economic Impacts of Padma Bridge in Bangladesh Raihan and Khondker (2010)
30
consumption increases by 8.06 percent, and the largest rise is observed for the rural non-
farm non poor household.
Table 10: Simulation 2A: Economy Wide Benefit of Intervention
Using the National SAM Model-Intermediate Classification
(In million taka unless otherwise specified)
Endogenous SAM Accounts (Intermediate Classification)
Base Value
Simulation
% Change over Base
1
Cereal Crops
614209
49260
8.02
2 Commercial Crops 199811 28973 14.5
3
Livestock
-
Poultry
-
fishing
764211
139316
18.23
4
Forestry
210295
19389
9.22
5 Other Agriculture 159683 23601 14.78
6
Other Food
1156780
127477
11.02
7 Leather Products 64680 3247 5.02
8
Cloth
274245
11902
4.34
9
Readymade Garments
734635
6832
0.93
10 Chemical-Fertilizer 96050 7895 8.22
11
Machinery
338400
12013
3.55
12
Petroleum Products
45849
3838
8.37
13 Other Industries 318938 15819 4.96
14
Construction
895119
23989
2.68
15
Transport
556137
152660
27.45
16 Utility 200010 33362 16.68
17
Other Services
2746118
202664
7.38
Gross Output 9375170 862236 9.20
1
Cereal Crops
647473
51927
8.02
2
Commercial Crops
281463
40812
14.50
3 Livestock-Poultry-fishing 769744 138043 17.93
4
Forestry
210295
19389
9.22
5
Other Agriculture
178805
26427
14.78
6 Other Food 1302387 143523 11.02
7
Leather Products
65167
3271
5.02
8
Cloth
357348
15509
4.34
9 Readymade Garments 748044 6957 0.93
10
Chemical
-
Fertilizer
220509
18126
8.22
11 Machinery 676932 24031 3.55
12
Petroleum Products
247631
20727
8.37
13
Other Industries
539253
26747
4.96
14 Construction 895119 23989 2.68
15
Transport
654329
179613
27.45
16
Utility
208034
34700
16.68
17 Other Services 2790890 205968 7.38
Total Commodity Demand
10793425
979760
9.08
18
VA Labour Unskilled
1107767
92659
8.37
Estimating the Economic Impacts of Padma Bridge in Bangladesh Raihan and Khondker (2010)
31
Endogenous SAM Accounts (Intermediate Classification)
Base Value
Simulation
% Change over Base
19 VA Labour Skilled 1130936 95604 8.37
20
VA Capital
1941427
192510
9.92
21
VA Land
288419
23560
8.06
Value added 4468549 404333 8.99
22
Rural Landless
300256
23994
8.06
23
Rural Marginal Farmers
283097
22506
8.06
24 Rural Small Farmers 549961 41881 7.75
25
Rural Large Farmers
341538
25947
7.75
26
Rural Non Farm Poor
433473
31403
7.44
27
Rural Non Farm Non Poor
1156862
101122
8.68
28
Urban Low Education
490267
35836
7.44
29 Urban High Education 1168683 95015 8.06
Household
Income
4724136
377766
8.06
National (Output + Commodity + Factor + Household)
29361280
2542155
8.68
Note: Gross output = intermediate use + factor payments; Total commodity demand = commodity demanded
by households; Value added = factor payments; Household income = Incomes of different household
categories
Simulated outcomes are further aggregated following the classification involving 5 activities,
5 commodities, 3 factors and 3 household groups. Simulated outcomes according to the
final classification are reported in Table 11.
Table 11: Simulation 2A: Economy Wide Benefit of Intervention
Using the National SAM Model-Final Classification
(In million taka unless otherwise specified)
Endogenous SAM Accounts (Final Classification) Base Value Simulation % Change over Base
1
Agriculture
1948209
260538
13.37
2
Manufacturing
3229588
222385
6.89
3 Construction 895119 23989 2.68
4
Transport
556137
152660
27.45
5
Services
2746118
202664
7.38
Gross Output
9375170
862236
9.20
1
Agriculture
2087781
276599
13.25
2 Manufacturing 4365306 293591 6.73
3
Construction
895119
23989
2.68
4
Transport
654329
179613
27.45
5 Services 2790890 205968 7.38
Total
Commodity Demand
10793425
979760
9.08
1
Labour
2238703
188263
8.41
2 Capital 1941427 192510 9.92
3
Land
288419
23560
8.17
Value added
4468549
404333
8.99
Estimating the Economic Impacts of Padma Bridge in Bangladesh Raihan and Khondker (2010)
32
1
Rural Land Based
1474851
114328
7.75
2 Rural Non-farm 1590335 132525 8.33
3
Urban
1658950
130851
7.89
Household
Income
4724136
377766
8.06
National (Output + Commodity + Factor + Household) 29361280 2542155 8.68
Note: Gross output = intermediate use + factor payments; Total commodity demand = commodity demanded
by households; Value added = factor payments; Household income = Incomes of different household
categories
5.3.4. Results of Simulation 2B
The economic impacts on the Southwest region due to rise in sectoral demand are
presented in Table 12 based on the regional SAM-intermediate classification.
Table 12: Simulation 2B: Economy Wide Benefit of Intervention
Using the Regional SAM Model-Intermediate Classification
(In million taka unless otherwise specified)
Endogenous SAM Accounts (Intermediate Classification) Base Value Simulation % Change over Base
1
Cereal Crops
82010
44117
8.02
2
Commercial Crops
43145
41963
97.26
3 Livestock-Poultry-fishing 193480 236587 122.28
4
Forestry
36272
22432
61.84
5
Other Agriculture
26570
26341
99.14
6 Other Food 165149 122075 73.92
7
Leather Products
3129
1054
33.67
8
Cloth
20522
5974
29.11
9 Readymade Garments 14024 875 6.24
10
Chemical
-
Fertilizer
23363
12882
55.14
11 Machinery 76982 18331 23.81
12
Petroleum Products
6613
3713
56.14
13
Other Industries
62503
20795
33.27
14 Construction 87508 15731 17.98
15
Transport
78228
144036
184.12
16
Utility
27155
30382
111.88
17 Other Services 386929 191538 49.50
Gross Output
1333583
938825
70.40
1
Cereal Crops
82119
6586
8.02
2
Commercial
Crops
44943
43712
97.26
3
Livestock
-
Poultry
-
fishing
193508
236621
122.28
4 Forestry 36272 22432 61.84
5
Other Agriculture
26786
26555
99.14
Estimating the Economic Impacts of Padma Bridge in Bangladesh Raihan and Khondker (2010)
33
Endogenous SAM Accounts
(Intermediate Classification)
Base Value
Simulation
% Change over Base
6 Other Food 165628 122429 73.92
7
Leather Products
3130
1054
33.67
8
Cloth
20943
6097
29.11
9 Readymade Garments 14282 891 6.24
10
Chemical
-
Fertilizer
23424
12915
55.14
11
Machinery
80617
19197
23.81
12 Petroleum Products 6626 3720 56.14
13
Other Industries
63590
21156
33.27
14
Construction
87508
2345
2.68
15
Transport
78382
144320
184.12
16
Utility
27206
30439
111.88
17 Other Services 387554 191848 49.50
Total Commodity Demand
1342515
892316
66.47
18
VA Labour Unskilled
132408
92659
63.24
19 VA Labour Skilled 152721 95604 65.41
20
VA Capital
293265
192510
62
21
VA Land
64424
23560
51.77
Value added 642818 404333 62
22
Rural Landless
41451
23994
60.76
23
Rural Marginal Farmers
41598
22506
57.04
24
Rural Small Farmers
75323
41881
58.28
25
Rural Large Farmers
96441
25947
58.59
26 Rural Non Farm Poor 62621 31403 60.14
27
Rural Non Farm Non Poor
204405
101122
59.83
28
Urban Low Education
56472
35836
60.14
29 Urban High Education 61593 95015 59.21
Household
Income
639904
377766
59.52
South West Bangladesh (Output + Commodity + Factor + Household)
3958820.9
2542155
61.07
Note: Gross output = intermediate use + factor payments; Total commodity demand = commodity demanded
by households; Value added = factor payments; Household income = Incomes of different household
categories
Simulated outcomes are further aggregated following the classification involving 5 activities,
5 commodities, 3 factors and 3 household groups. Simulated outcomes according to the
final classification are reported in Table 13.
Estimating the Economic Impacts of Padma Bridge in Bangladesh Raihan and Khondker (2010)
34
Table 13: Simulation 2B: Economy Wide Benefit of Intervention
Using the Regional SAM Model-Final Classification
(In million taka unless otherwise specified)
Endogenous SAM Accounts (Final Classification)
Base Value
Simulation
% Change over Base
1
Agriculture
1948209
371440
97.37
2 Manufacturing 3229588 216079 54.10
3
Construction
895119
15731
17.98
4
Transport
556137
144036
184.12
5 Services 2746118 191538 49.50
Gross Output
9375170
938825
70.40
1
Agriculture
2087781
335906
87.56
2
Manufacturing
4365306
217897
53.74
3
Construction
895119
2345
2.68
4 Transport 654329 144320 184.12
5
Services
2790890
191848
49.50
Total Commodity Demand
10793425
892316
66.47
1 Labour 2238703 183675 64.42
2
Capital
1941427
182001
62.06
3
Land
288419
33263
51.63
Value added 4468549 404333 62
1
Rural
Land Based
1474851
149513
58.68
2
Rural Non
-
farm
1590335
160084
59.95
3 Urban 1658950 70463 59.68
Household Income
4724136
377766
59.52
South West Bangladesh (Output + Commodity + Factor + Household) 3958820.9 2542155 61.07
Note: Gross output = intermediate use + factor payments; Total commodity demand = commodity demanded
by households; Value added = factor payments; Household income = Incomes of different household
categories
5.3.5 Assessment of Annual Effects
The pace at which the Padma Bridge is expected to impact upon output, income and
subsequent reduction in poverty level, would depend mainly on the extent to which the
bridge’s capacity will be used. In line with traffic model estimation, one may assume that it
will take roughly 31 years for full realization of the estimated simulation results from SAM
analysis. Accordingly, the total effects are converted into annual effects and the estimates
are presented in Table 14. It is important to note that the simulation exercises were meant
to trace the impacts of a particular intervention, assuming that all other things remained
constant.
Estimating the Economic Impacts of Padma Bridge in Bangladesh Raihan and Khondker (2010)
35
Table 14: Total and Annualized Economy Wide Benefit of Simulations
(Percentage Change from Base Values)
Simulation 1A:
National SAM Based
Simulation 1B:
Regional SAM Based
Simulation 2A:
National SAM Based
Simulation 2B:
Regional SAM Based
Increase in:
Total
(1)
Annualized
(2)
Total
(3)
Annualized
(4)
Total
*
(5)
Annualized
(6)
Total
(7)
Annualized
(8)
Total
(9)
Annualized
(10)
Gross Output 10.56 0.34 73.40 2.37 51.4 1.66 9.20 0.30 70.40 2.27
Commodity
10.26
0.33
73.32
2.37
51.3
1.66
9.08
0.29
66.47
2.14
Factor Return
10.16
0.33
71.34
2.30
49.9
1.61
8.99
0.29
62.00
2.00
Household
Income 8.97 0.29 68.14 2.20 47.7 1.54 8.06 0.26 59.52 1.92
Note: *Annual equivalent rates of growth were calculated keeping in view the 31 years as the time taken to
fully realize the impact of the bridge. If we took a shorter time horizon for fully realizing the benefit of growth,
then the annual equivalent rates could be larger. The annualized equivalent rate would be 0.33 percent for
national GDP (compared to the national base GDP) and 2.3 percent for SW region (compared to the SW base
GDP) assuming 100 percent confinement of shock to the regional economy. If we assume that if 70 percent of
the shock would be operative in the region, the equivalent of annual rate of growth regional GDP would be
roughly 1.66 percent (please see column 5 and 6 respectively for revised WEB under 70 percent injections.
Given that SAM based model assume excess capacity (which may be a reasonable assumption in a country like
Bangladesh with under-utilized resources), the size of impacts vary with the size of injection or shock.
5.3.6. Economic Cost-Benefit Analysis of Simulations 1A and 2A
The quantifiable cost and benefits of the Padma Bridge carried out by AECOM New Zealand
Limited in their study “Padma Multipurpose Bridge Design Project: Detailed Economic and
Financial Analysis”, has been modified to reassess the economic viability of the Padma
Bridge. The major features of the cost-benefit analysis are:
1. The values of the project costs are obtained from the AECOM report.
2. Instead of using the road users benefits based on additional traffic, road users’ benefits
are based on existing traffic. The benefit estimates are taken from AECOM report.
3. Non-road users’ benefits are derived from the simulated outcome of the National SAM
model exercise.
4. The cost-benefit analysis was undertaken over a thirty one -year period following
opening of the bridge. A real discount rate of 12% was used, reflecting the economic
opportunity cost of capital in Bangladesh. All costs and benefits were expressed in 2009
Estimating the Economic Impacts of Padma Bridge in Bangladesh Raihan and Khondker (2010)
36
prices, and 2009/10 was adopted as the discount year. Residual value was allowed for in
the last year of the evaluation period (2045).
The estimated outcomes of cost-benefit analysis for the Simulations 1A and 2A in terms of
Net Present Value (NPV), Benefit-Cost Ratio (BCR), and Internal Economic Rate of Return
(IERR) are provided in Tables 15 and 16 respectively.
Table 15 shows that, based on the quantified benefits of Simulation 1A, the project is
economically viable, with a net present value of US$ 1234 million, a benefit-cost ratio (BCR)
of 2.01 and an economic internal rate of return (EIRR) of 19 percent. Also, from Table 16 it
appears that based on the benefits of Simulation 2A, the project’s net present value is US$
1184, the benefit-cost ratio is 1.97 and the economic internal rate of return (EIRR) is 18
percent. The EIRRs from these two simulations are well in excess of the economic
opportunity cost of capital of 12 percent.
Table 15: Economic Evaluation Results Based on Simulation 1A
(US$ million in 2009 prices, US$ 1 = 70 Taka)
Cost
Project Benefits
Net
Economic
Benefits
Year
End June
Capital
Cost
O&M Total
Cost
Road User Benefits Non Road User Benefits Total
Benefits
VOC
TTC
Sub
-
total
Ferry
Land
Utilities
WEB
2011
60
60
0
0
-
60
2012 500 500 0 0 -500
2013
500
500
0
0
-
500
2014
500
500
0
0
-
500
2015 324 0 324 19 31 50 0 384 271 0 705 381
2016
13
13
37
50
88
0
0
87
74
2017 25 25 61 75 137 0 23 161 136
2018
25
25
74
87
161
0
36
197
172
2019
25
25
84
97
182
0
57
242
217
2020 25 25 93 106 199 0 73 272 247
2021
25
25
111
124
235
0
87
322
297
2022
25
25
131
145
276
0
0
102
378
353
2023 15 15 153 168 321 0 0 117 438 423
2024
15
15
176
193
369
0
134
503
488
2025
15
15
202
221
423
0
162
585
570
2026 15 15 231 243 473 0 190 717 702
2027
15
15
260
266
526
0
218
744
729
2028 15 15 290 291 581 0 250 831 816
Estimating the Economic Impacts of Padma Bridge in Bangladesh Raihan and Khondker (2010)
37
Cost
Project Benefits
Net
Economic
Benefits
Year
End June
Capital
Cost
O&M Total
Cost
Road User Benefits Non Road User Benefits Total
Benefits
VOC
TTC
Sub
-
total
Ferry
Land
Utilities
WEB
2029
15
15
322
316
637
0
296
957
942
2030 15 15 354 342 696 0 296 992 977
2031
15
15
370
351
721
0
296
1017
1002
2032
15
15
386
360
746
0
296
1042
1027
2033 15 15 401 370 771 0 296 1067 1052
2034
15
15
417
378
795
0
296
1091
1076
2035
15
15
431
388
820
0
296
1206
1191
2036
15
15
447
397
844
0
296
1140
1125
2037
15
15
462
407
869
0
296
1165
1150
2038 15 15 477 417 895 0 296 1281 1266
2039
15
15
493
427
919
0
296
1307
1292
2040
15
15
508
437
945
0
296
1241
1226
2041 15 15 513 438 951 0 296 1247 1232
2042
15
15
518
439
957
0
296
1253
1238
2043
15
15
521
440
962
0
296
1348
1333
2044 15 15 525 441 966 0 296 1262 1247
2045
15
15
542
455
997
0
296
1293
1278
Total
1,884
508
2392
9609
8900
18512
0
384
271
6481
26091
23699
NPV
(12%)
$1,310
$139
$1,398
$1,291
$1,321
$1,660
$0
$343
$242
$902
$2,632
$1,234
ERR
19%
NPV $1,234
B/C
2.01
Table 16: Economic Evaluation Results Based on Simulation 2A
(US$ million in 2009 prices, US$ 1 = 70 Taka)
Cost Project Benefits Net
Economic
Benefits
Year
End June
Capital
Cost
O&M
Total
Cost
Road User Benefits
Non Road User Benefits
Total
Benefits
VOC
TTC
Sub
-
total
Ferry
Land
Utilities
WEB
2011 60 60 0 0 -60
2012
500
500
0
0
-
500
2013 500 500 0 0 -500
2014
500
500
0
0
-
500
2015
324
0
324
19
31
50
0
384
271
0
705
381
2016 13 13 37 50 88 0 0 87 74
2017
25
25
61
75
137
0
20
161
136
2018
25
25
74
87
161
0
32
193
168
2019 25 25 84 97 182 0 50 242 217
2020
25
25
93
106
199
0
64
263
238
2021
25
25
111
124
235
0
77
312
287
2022 25 25 131 145 276 0 0 90 366 341
Estimating the Economic Impacts of Padma Bridge in Bangladesh Raihan and Khondker (2010)
38
Cost
Project Benefits
Net
Economic
Benefits
Year
End June
Capital
Cost
O&M Total
Cost
Road User Benefits Non Road User Benefits Total
Benefits
VOC
TTC
Sub
-
total
Ferry
Land
Utilities
WEB
2023
15
15
153
168
321
0
0
103
424
409
2024 15 15 176 193 369 0 118 487 472
2025
15
15
202
221
423
0
143
566
551
2026
15
15
231
243
473
0
168
717
702
2027 15 15 260 266 526 0 192 718 703
2028
15
15
290
291
581
0
221
801
786
2029
15
15
322
316
637
0
261
957
942
2030
15
15
354
342
696
0
261
957
942
2031
15
15
370
351
721
0
261
982
967
2032 15 15 386 360 746 0 261 1007 992
2033
15
15
401
370
771
0
261
1032
1017
2034
15
15
417
378
795
0
261
1056
1041
2035 15 15 431 388 820 0 261 1206 1191
2036
15
15
447
397
844
0
261
1105
1090
2037
15
15
462
407
869
0
261
1130
1115
2038 15 15 477 417 895 0 261 1281 1266
2039
15
15
493
427
919
0
261
1307
1292
2040
15
15
508
437
945
0
261
1206
1191
2041
15
15
513
438
951
0
261
1213
1198
2042
15
15
518
439
957
0
261
1218
1203
2043 15 15 521 440 962 0 261 1348 1333
2044
15
15
525
441
966
0
261
1227
1212
2045
15
15
542
455
997
0
261
1258
1243
Total 1,884 508 2392 9609 8900 18512 0 384 271 5715 25532 23140
NPV
(12%)
$1,310
$139
$1,398
$1,291
$1,321
$1,660
$0
$343
$242
$796
$2,582
$1,184
ERR
18%
NPV $1,184
B/C
1.97
Estimating the Economic Impacts of Padma Bridge in Bangladesh Raihan and Khondker (2010)
39
VI. THE IMPACTS OF THE PADMA BRIDGE: A COMPUTABLE GENERAL EQUILIBRIUM
ANALYSIS
So far, we have analysed the indirect impacts of the Padma Bridge using the SAM-model,
which is a fixed-price demand driven approach. As understood from the study on Jamuna
Bridge, one of the major effects of the construction of Padma Bridge would be the reduction
in the transport margin across the sectors. In line with the study on Jamuna Bridge this
study also undertakes a simulation exercise considering a cut in the transport margins. An
alternative method of undertaking this exercise is to run this simulation in a Computable
General Equilibrium (CGE) framework, whose advantage is that it traces the price effects of
the exogenous shock. In an increasingly market oriented economy, the variations in prices
may be the most important sources of re-allocation of resources among competing activities
which then may alter the factorial income and hence personal income distribution. Changes
in personal income distribution of household groups and consumer price indices may have
different implications on the welfare and poverty situations of the distinct household
groups. Application of computable general equilibrium analysis allows us to assess the
impacts of exogenous shocks primarily through changing prices. A SAM prepared for the
year 2006-07 serves as the consistent and comprehensive database for the above-
mentioned exercises.
The variations in the sectoral prices will reallocate resources across the producing activities,
thereby altering factoral income generation. As a consequence, the personal income of the
household group will also be altered. Implied price, income and consumption effects will
have implications for the household welfare situation and poverty incidence. Welfare
situation is measured by the well-known equivalent variation.
6.1. The CGE Model for Bangladesh Economy
A CGE model examines the consequences of policy reforms within a constrained
optimization framework. Computable general equilibrium models capture the detailed
accounts of the circular flows of receipts and outlays in an economy. It satisfies general
Estimating the Economic Impacts of Padma Bridge in Bangladesh Raihan and Khondker (2010)
40
equilibrium conditions in various markets simultaneously. Such models are useful to analyse
associations between various agents of the economy.
In line with most of CGE models, the model has been solved in comparative static mode and
provides an instrument for controlled policy simulations and experiments. Solution of each
simulation presents complete sets of socio-economic, meso and macro level indicators such
as activity/commodity prices, household incomes and expenditures, factor demand and
supplies, gross domestic products, exports and imports, and household poverty situation.
The model is calibrated to the SAM to exactly reproduce the base year values
15
. The
equations of the CGE model are presented in Annex 4.
Activities
On the production side it is assumed that in each sector there is a representative firm that
generates value added by combining labour and capital. A nested structure for production is
adopted. Sectoral output is a Leontief function of value added and total intermediate
consumption. Value added is in turn represented by a CES function of capital and composite
labour. The latter is also represented by a CES function of two labour categories: skilled
labour and unskilled labour. Both labour categories are assumed to be fully mobile in the
model. In the different production activities we assume that a representative firm
remunerates factors of production and pays dividends to households.
Households
Households earn their income from production factors: labour, land and capital. They also
receive dividends, government transfers and remittances. They pay direct income tax to the
government. Household savings are a fixed proportion of total disposable income.
Household demand is derived from a Cobb-Douglas (C-D) utility function.
Foreign Trade
It is assumed that foreign and domestic goods are imperfect substitutes. This geographical
differentiation is introduced by the standard Armington assumption with a constant
15
In calibration procedure, most of the model parameters are estimated endogenously keeping the various
elasticity values fixed.
Estimating the Economic Impacts of Padma Bridge in Bangladesh Raihan and Khondker (2010)
41
elasticity of substitution function (CES) between imports and domestic goods. On the supply
side, producers make an optimal distribution of their production between exports and
domestic sales according to a constant elasticity of transformation (CET) function.
Furthermore, a finite elasticity export demand function is assumed. Even if it is assumed
that the international terms of trade are given, the small country assumption for Bangladesh
is rejected, and assumed that foreign demand for Bangladeshi exports is less than infinite. In
order to increase their exports, local producers must decrease their free on board (FOB)
prices.
Government
The government receives direct tax revenue from households and firms and indirect tax
revenue on domestic and imported goods. Its expenditure is allocated between the
consumption of goods and services (including public wages) and transfers. The model
accounts for indirect or direct tax compensation in the case of a tariff cut.
System Constraints and Equilibrium Conditions
There are four constraints in the system. The real constraint refers to domestic commodity
and factor market; the nominal constraint represents two macro balances: the current
account balance of the rest of the world and the savings-investment balance.
Sectoral supply is a composite of imports and output sold in the domestic market.
Composite demand, on the other hand, includes final demands (i.e. private and public
consumption expenditure and investment) and intermediate input demand. Variations in
the sectoral prices assure equilibrium between sectoral supply and demand.
In the case of factor market, it is assumed that total quantities of factors supply are fixed.
This specification also implies full mobility of labour factors across producing activities and
variations in their returns (e.g. wages) assures equilibrium in the factor market.
The inflows (transfers to and from domestic institutions) are fixed but imports and exports
are determined endogenously in the model. Foreign savings is fixed in this model and
nominal exchange rate acts as numeraire.
Estimating the Economic Impacts of Padma Bridge in Bangladesh Raihan and Khondker (2010)
42
Finally, for the savings-investment equilibrium, the model treats the investment decision as
given and hence savings has to adjust to ensure the equality to the fixed value of
investment. The basic approach is to allow the savings propensity of one of the domestic
institution to vary.
6.2. Simulation Design
In CGE models since demands (which are usually assumed exogenous in SAM models) are
endogenous along with supply, injection via demand variations are ruled out in CGE models.
Since construction of Padma Bridge likely to lessen time needed to move goods leading to
reduced transport margins, in CGE exercise one simulation is conducted where sectoral
transport margins are reduced and its impacts on resource re-allocation, sectoral output
and consumption, poverty and income distribution situation of the representative
household groups are examined. Following simulation is conducted:
Simulation 3: In this simulation base values of the sectoral transport margin rates are
reduced by 50 percent
16
. The base values of all other parameters are retained.
6.3. Simulation Results
In order to capture the effects of changes in transport margins on sectoral prices and
volumes of output, as well as on the household’s welfare and poverty situation, the
transport margins paid by each of the producing activities are deducted from their
transaction values valued at purchaser prices. The derived sectoral transport margins are
then added as a component in the formation of the domestic sales price. Variations in the
transport margins affect the domestic sales price first and subsequently the changed
domestic sales price will influence all other prices due to their interdependence. The base
and simulation values of transport margin rates are presented in Table 17.
16
The sectoral transport rates are derived as proportions of sectoral total domestic sales values.
Estimating the Economic Impacts of Padma Bridge in Bangladesh Raihan and Khondker (2010)
43
Table 17: Rates of Transport Margin by Sectors under Base and Simulation Scenarios
Sectors
Base rate
New rate under
simulation 3
1 Paddy Cultivation 3.69 1.85
2
Grains
4.16
2.08
3
Jute Cultivation
4.71
2.36
4 Sugarcane Cultivation 3.74 1.87
5
Vegetables
4.93
2.47
6
Commercial Crops
3.07
1.54
7 Other Crop Cultivation 1.22 0.61
8
Livestock Rearing
1.14
0.57
9 Poultry Rearing 1.12 0.56
10
Shrimp Farming
1.33
0.66
11
Fishing
1.18
0.59
12 Forestry 1.03 0.52
13
Rice Milling
1.25
0.62
14
Grain Milling
1.46
0.73
15 Fish Process 1.49 0.75
16
Oil Industry
1.13
0.57
17
Sweetener Industry
1.40
0.70
6.3.1. Macroeconomic Effects
The macro impacts of the fall in transport margins on major macro variables are reported in
Table 18. It is observed that the effects of the transport margin rate reduction on macro
variables are positive. Under Simulation 3, real GDP rises by 1.14 percent. The general price
index falls by 2.85 percent. Both exports and imports rise by 1.89 and 1.66 percent
respectively. Domestic sales and consumption expenditure also rise by 2.05 percent and
1.95 percent respectively. The positive growth of the economy and moderate fall of general
price index led to the enhancement of national welfare by 0.78 percent of base value of
household income.
Estimating the Economic Impacts of Padma Bridge in Bangladesh Raihan and Khondker (2010)
44
Table 18: Macroeconomic Effects (% change from base value)
Macro variables Simulation 3
Real Gross Domestic Product 1.14
General Price Index -2.85
Imports 1.89
Exports 1.66
Domestic Goods 2.05
Consumption Expenditure 0.95
Equivalent Variation 0.78
The reasons for obtaining different outcome magnitudes under the SAM and CGE
approaches lie in the fact that the impact of the Padma Bridge intervention is explained
differently under the two approaches. In the SAM approach, the impact was demonstrated
via enhancing the sectoral demand. Since there is no capacity constraints, matching outputs
are always supplied, which resulted in higher factorial incomes and household consumption
expenditure. In the CGE case, the simulation was performed by reducing the transport
margin rates. The changes in transport rates alter the relative price situation in the
economy, which then led to the reallocation of existing resources to various producing
activities. The gains are obtained by reducing existing distortions and hence they are small.
Since supplies of primary factors were fixed there is no scope of generating extra income by
employing additional factors (as was the case in the SAM approach)
17
.
6.3.2. Price Effects
The fall of transport margin rates affects the sectoral domestic sales price first. The changes
in domestic sales prices then influence other prices, allocation of resources, incomes and
consumption expenditures. The price effects of reduction in transport margin rate for 41
sectors are presented in Table 19.
17
The CGE results under Padma exercise are largely similar to those under the Jamuna exercise. However, the
differences between SAM and CGE outcomes under the Padma exercise are wider than that found for the
Jamuna exercise. The probable reasons mat include: (i) changed inter-industry structure reflecting larger
multipliers; and (ii) relatively larger size of the demand intervention.
Estimating the Economic Impacts of Padma Bridge in Bangladesh Raihan and Khondker (2010)
45
Under Simulation 3, the fall in prices of domestic sales in general is higher for the
agricultural sectors compared to the manufacturing and services sector. Since the base of
rates of transport margins for agriculture are higher than manufacturing and services, these
sectors would experience the larger price fall. The fall in the price of domestic sales is the
highest for forestry sector. The fall in consumer and producer prices help reduce the general
price index. The fall in FOB export prices results in rise in the competitiveness of the sectors.
As a result of the fall in domestic sales prices (which dominates the consumer price
formation), the prices faced by final consumers are also reduced. The reduction in the
domestic price of manufacturing product imports led to a further decline of consumer prices
of manufacturing commodities. Due to the interdependence of price formation, imports-
exports and producer prices have also been affected by the fall of domestic sales prices.
Table 19: Sectoral Price Effects (Percentage change from base value)
Simulation 3
Sectors Domestic
Sales
Consumer Producer Export_
FOB
1
Cereal Crops
-
2.38
-
2.28
-
2.24
0.00
2 Commercial Crops -2.78 -2.74 -2.65 -1.76
3
Livestock
-
Poultry
-
fishing
-
2.44
-
2.26
-
2.50
-
2.71
4
Forestry
-
2.92
-
2.62
-
2.49
0.00
5 Other Agriculture -2.46 -2.27 -2.17 -2.01
6
Other
Food
-
2.34
-
2.31
-
2.19
-
1.42
7
Leather Products
-
0.95
-
0.92
-
0.87
-
0.79
8 Cloth -1.41 -1.35 -1.24 -1.04
9
Readymade Garments
-
1.26
-
1.25
-
1.24
-
1.23
10
Chemical
-
Fertilizer
-
1.50
-
1.35
-
1.24
-
1.23
11
Machinery
-
1.42
-
1.69
-
1.60
-
1.63
12
Petroleum
Products
-
1.48
-
1.31
-
1.17
-
1.02
13 Other Industries -1.45 -1.41 -1.42 -1.21
14
Construction
-
1.67
-
1.29
-
1.92
0.00
15
Transport
-
1.34
-
1.27
-
1.20
-
1.07
16 Utility -1.09 -1.76 -1.46 0.00
17
Other Services
-
1.24
-
1.12
-
1.66
-
1.33
Simulated outcomes for 5 aggregated sectors are reported in Table 20. The fall of prices of
domestic sales is reported to be the highest for agriculture, followed by manufacturing and
construction activities.
Estimating the Economic Impacts of Padma Bridge in Bangladesh Raihan and Khondker (2010)
46
Table 20: Price Impacts of Intervention Using the National Level 5 Activity Classification
(Percentage change from base value)
Simulation 3
Sectors
Domestic
Sales
Consumer
Producer
Export_FOB
1
Agriculture
-
2.55
-
2.42
-
2.48
-
2.30
2
Manufacturing
-
1.52
-
1.50
-
1.48
-
1.29
3 Construction -1.67 -1.29 -1.92
4
Transport
-
1.34
-
1.27
-
1.20
-
1.07
5
Services
-
1.27
-
1.25
-
1.54
-
1.50
6.3.3. Volume Effects
Under Simulation 3, the decline in sectoral prices leads to rise in sectoral domestic sales,
consumption, imports, exports and outputs. Consistent with the price decline pattern, the
gains are found to be the highest for agricultural sectors. Fishing sector would experience
the largest rise in output. Export from sectors like other crop, vegetables, poultry, rice and
food rise by more than 5 percent.
Table 21: Sectoral Effects of Simulation
(Percentage change from base value)
Sectors
Simulation 3
Output
Imports
Exports
Domestic
Sales
Consum
-
ption
1
Cereal Crops
2.58
1.89
0.00
2.45
0.00
2
Commercial Crops
3.56
2.04
2.08
3.17
1.53
3 Livestock-Poultry-fishing 4.44 2.28 3.34 4.23 1.90
4
Forestry
3.52
0.00
0.00
3.76
1.48
5
Other Agriculture
4.62
2.49
5.28
4.38
1.91
6 Other Food 3.85 2.21 3.36 3.48 1.59
7
Leather Products
1.84
0.99
2.38
1.69
0.76
8
Cloth
2.47
1.47
0.10
2.50
1.13
9 Readymade Garments 0.54 0.29 0.60 0.46 0.21
10
Chemical
-
Fertilizer
3.06
2.96
4.32
3.56
1.52
11 Machinery 2.75 1.14 1.85 2.37 0.77
12
Petroleum Products
4.65
2.51
3.64
3.42
1.94
13
Other Industries
3.83
2.05
3.73
4.63
1.57
14 Construction 3.38 0.00 0.00 3.66 1.14
15
Transport
3.53
2.44
3.03
3.16
1.37
16
Utility
2.91
2.27
0.00
2.27
1.31
17 Other Services 4.19 1.75 1.41 3.74 1.58
Estimating the Economic Impacts of Padma Bridge in Bangladesh Raihan and Khondker (2010)
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Simulated outcomes for 5 aggregated sectors are reported in Table 22. Output in the
agricultural sector as a whole rises by 3.84 percent, which is the highest among the five
broad sectors. Also, exports and domestic sales in agriculture experience the largest rise.
Table 22: Volume Impacts of Intervention Using the National Level 5 Activity Classification
(Percentage change from base value)
Sectors
Simulation 3
Output Imports Exports Domestic
Sales
Consum-
ption
1
Agriculture
3.84
2.30
4.39
3.60
1.55
2
Manufacturing
3.22
2.10
3.38
3.12
1.41
3 Construction 3.38 0.00 0.00 3.66 1.14
4
Transport
3.53
2.44
3.03
3.16
1.37
5 Services 3.54 2.20 3.15 3.14 1.43
6.3.4. Factor Movements and Value-Added Effects
Under a general equilibrium framework, any shock into the system would lead to
reallocation of resources from existing less productive sectors to relatively more productive
sectors. The resultant primary factor movements and changes in value added are reported
in Table 23. Under Simulation 3, in general, resources move out of some manufacturing and
services activities and are absorbed in the agricultural and some manufacturing leading to
the positive value added growth of agriculture and manufacturing activities. On the other
hand, reduced availability of primary factors manifested in negative value added growth for
many services activities.
Table 23: Effects on Value Added and Factor Movements (Percentage change from base value)
Sectors
Simulation 3
Value
-
Added Labour unskilled Labor skilled
Capital
Land
1 Cereal Crops 1.03 0.87 0.84 0.00 1.07
2
Commercial Crops
1.41
1.12
1.09
0.00
1.49
3
Livestock
-
Poultry
-
fishing
1.78
1.52
1.48
1.95
0.00
Estimating the Economic Impacts of Padma Bridge in Bangladesh Raihan and Khondker (2010)
48
Sectors
Simulation 3
Value-
Added Labour unskilled Labor skilled
Capital Land
4
Forestry
1.41
1.20
1.15
1.55
0.00
5
Other Agriculture
1.85
1.57
1.51
0.00
1.91
6 Other Food 1.51 1.59 1.62 1.43 0.00
7
Leather Products
0.74
0.76
0.77
0.66
0.00
8 Cloth 0.98 1.03 1.05 0.93 0.00
9
Readymade Garments
0.22
0.22
0.23
0.19
0.00
10
Chemical
-
Fertilizer
-
0.99
-
1.11
-
1.14
-
0.86
0.00
11 Machinery -0.35 -0.30 -0.30 -0.36 0.00
12
Petroleum Products
-
1.86
-
1.99
-
2.03
-
1.67
0.00
13
Other Industries
-
0.72
-
0.90
-
0.92
-
0.56
0.00
14 Construction 1.75 1.52 1.55 1.58 0.00
15
Transport
0.91
0.86
0.88
0.82
0.00
16
Utility
-
0.76
-
0.66
-
0.68
-
0.69
0.00
17 Other Services 0.57 -0.23 0.27 0.84 0.00
Simulated outcomes for 5 aggregated sectors are reported in Table 24. Under Simulation 3,
value-added in the agricultural sector would rise by 1.54 percent while that of
manufacturing would rise by only 0.34 percent. Construction and transport sector would
experience positive gain in value added while the value added in the services sector decline
by 0.43 percent.
Table 24: Volume Impacts of Intervention Using the National Level 5 Activity Classification
(Percentage change from base value)
Sectors
Simulation 3
Value-Added Labour unskilled Labor skilled
Capital Land
1
Agriculture
1.54
1.31
1.26
0.75
0.88
2 Manufacturing 0.34 0.36 0.37 0.31 -
3
Construction
1.75
1.52
1.55
1.58
-
4
Transport
0.91
0.86
0.88
0.82
-
5 Services -0.43 -0.40 -0.40 -0.38 -
6.3.5. Welfare Effects
Most CGE modellers use these models to assess the impacts of given shocks or policies on a
specific economy. While it is quite straightforward to measure impacts on aggregate
Estimating the Economic Impacts of Padma Bridge in Bangladesh Raihan and Khondker (2010)
49
nominal production and consumption levels, relative prices, nominal income and savings, it
is less obvious to quantitatively evaluate how much better or worse off the households are.
As direct and indirect utility functions are purely ordinal in nature, we can only analyse the
direction of change. An interesting alternative is provided by using the money metric
utility function, which measures the nominal income the consumer needs at one set of
prices in order to be as well of at an alternative set of prices and nominal income. As such,
it can be used to obtain monetary measures of the welfare effects of different policy
scenarios. The most common of these measures is equivalent variations (EV).
Table 25 presets the change in consumer price index, income and EV of the eight
representative households in the model. Under both the scenarios, all the households
experience fall in CPIs and rise in income which leads to rise in real consumption and
welfare of the households. The largest rise in EV is for the small and marginal farmers. In
general the rural households experience larger rise in real consumption and welfare.
Table 25: Welfare effects (Percentage change from base value)
Simulation 3
Households
CPI
Income
EV
Landless
-
2.65
1.19
0.86
Marginal farmers -2.68 1.45 0.89
Small farmers
-
2.58
1.67
0.89
Large farmers
-
2.56
1.14
0.76
Rural non-farm poor -2.52 1.26 0.72
Rural non
-
farm non poor
-
2.22
1.14
0.68
Urban low education
-
2.48
1.20
0.78
Urban high education
-
2.36
1.11
0.65
VII. POVERTY ESTIMATES UNDER DIFFERENT SIMULATIONS
It can be mentioned that under the SAM model, which is a fixed price model, the changes in
household incomes are judged against a pre-determined poverty line income. However,
under the CGE framework, there is an initial distribution of income for different
representative household groups. Now, for any policy shock, the incomes of different
household groups change. Also, the poverty line income is adjusted for the change in
Estimating the Economic Impacts of Padma Bridge in Bangladesh Raihan and Khondker (2010)
50
consumer price index. Now, the simulated income of the household is compared with the
new adjusted poverty line income. If the income is above the poverty line income, the
household is non-poor and if it is below the household is poor. The annualised headcount
poverty impacts under different scenarios are presented in Table 26.
Table 26: Annualised Reduction in Aggregate Head-count Poverty Estimates under different Simulations
(% change from base value)
Type of Model
Simulation 1
A
(National)
Simulation 1B
(Regional)
Simulation 2
A
(National)
Simulation 2B
(Regional)
Simulation 3
(National)
SAM Multiplier Model
-
0.
8
4
-
1.
01
-
0.
6
3
-
0.
8
1
X
CGE Model
X
X
X
X
-
0.
08
Note: The annualised figures are derived by dividing the total effects by 31 years
It appears from Table 26 that under the SAM multiplier model, Simulation 1A would
generate the highest reduction in annualised head-count poverty at the national level (-0.84
percent) and Simulation 1B would generate the highest fall in head-count poverty at the
regional level (-1.01 percent). The annual fall in head-count poverty under Simulation 3 (CGE
framework) would be 0.08 percent.
Now, using the Foster-Greer-Thorbecke (FGT) class of poverty measures (Foster, et al, 1984)
we can also derive other two measures of poverty: poverty gap index and squared poverty
gap index for different household categories under different simulations. The poverty gap
index, measures the depth of poverty, and it estimates the average distance separating the
income of the poor from the poverty line as a proportion of the income indicated by the
line. The squared poverty gap index, also measures the severity of poverty, quantifies the
aversion of the society towards poverty. Table 27 provides the annualised estimates of
impact on poverty indices for different household groups under the three national
simulations. It appears that the poorer household groups are likely to experience higher
reduction in poverty indices compared to their non-poor counterparts under all those three
simulations.
Estimating the Economic Impacts of Padma Bridge in Bangladesh Raihan and Khondker (2010)
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Table 27: Annualised Impacts on Poverty Indices for different Household Groups under different Simulations
(% change from base value)
Simulation 1A
Simulation 2A
Simulation 3
Households
Head
-
count
(P0)
Poverty
gap
(P1)
Squared
poverty
gap
(P2)
Head
-
count
(P0)
Poverty
gap
(P1)
Squared
poverty
gap
(P2)
Head
-
count
(P0)
Poverty
gap
(P1)
Squared
poverty
gap
(P2)
Landless
-
0.99
-
1.21
-
1.38
-
0.74
-
0.95
-
1.19
-
0.09
-
0.12
-
0.15
Marginal farmers
-
0.86
-
1.13
-
1.19
-
0.64
-
0.89
-
1.03
-
0.08
-
0.11
-
0.13
Small farmers
-
1.06
-
1.33
-
1.38
-
0.80
-
1.04
-
1.19
-
0.10
-
0.13
-
0.15
Large farmers
-
0.54
-
0.70
-
0.83
-
0.40
-
0.55
-
0.71
-
0.05
-
0.07
-
0.09
Rural non-farm poor -0.43 -0.51 -0.64 -0.32 -0.40 -0.55 -0.04 -0.05 -0.07
Rural non
-
farm non
-
poor
-
0.32
-
0.40
-
0.46
-
0.24
-
0.32
-
0.40
-
0.03
-
0.04
-
0.05
Urban low education
-
0.95
-
1.22
-
1.38
-
0.72
-
0.96
-
1.19
-
0.09
-
0.12
-
0.15
Urban high education -0.66 -0.91 -0.73 -0.49 -0.72 -0.63 -0.06 -0.09 -0.08
National
-
0.84
-
0.99
-
1.10
-
0.63
-
0.78
-
0.95
-
0.
08
-
0.10
-
0.12
Note: The annualised figures are derived by dividing the total effects by 31 years
VIII. CONCLUDING OBSERVATIONS
By facilitating transportation across the river, the Padma Bridge is expected lead to the
greater integration of regional markets within the Bangladeshi national economy. On the
basis of their suitability of capture primary and secondary economic impacts of construction
project, three different types of economy wide models are employed in addition to
traditional traffic model to capture the total and economy wide impacts of Padma Bridge.
Although outcomes of all types of models are positive, the results show variations due to
especially to size of shocks. The results are summarized below.
1. In the Traffic model, road users benefits are estimated based on the saving on vehicle
operation costs (VOC) and savings in travel time cost (TTC). Total road user benefit is
estimated to be about million 1,295,840 taka over the 31 year period.
2. Out of the total cost of the project ($2.9 billion), it was estimated that about $2.1 billion
would be injected into the economy and the rest consists of imports, IDC etc. Injection of
$2.1 billion into the economy using national SAM model envisaged value added increase
of 453,670 million taka. This increase implies that annualized equivalent rate for national
GDP would be 0.33 percent compared to the national base GDP (i.e. 4,468,549 million
Estimating the Economic Impacts of Padma Bridge in Bangladesh Raihan and Khondker (2010)
52
taka). Annual equivalent rates of growth were calculated keeping in view the 31 years as
the time taken to fully realize the impact of the bridge. If we took a shorter time horizon
for fully realizing the benefit of growth, then the annual equivalent rates could be larger.
3. On the other hand, injection of $2.1 billion into the regional economy using the regional
SAM model envisaged that annualized equivalent rate for regional GDP would be 2.3
percent compared to the regional base GDP. However, if it assumed that only 70 percent
of the shock would be operative in the region (against full 100 percent or $2.1 billion),
the annualized equivalent rate for regional GDP would be roughly 1.66 percent of the
regional base GDP. Given that the SAM model assume excess capacity (which may be a
reasonable assumption in a country like Bangladesh with under-utilized resources), the
size of impacts vary with the size of injection or shock.
4. Using the Traffic mode, road users benefit is found to be million 1,295,840 taka. We
consider value added increase of million 453,670 taka derived from the national SAM
model (i.e. simulation 1A) as economy wide benefits of the project. Thus, total project
benefit is estimated to be 1,749,510 million taka (i.e. Total (1,749,510) = Road User
Benefit (=1,295,840) + WEB (=453,670). This implies that total project benefit is 39
percent relative to the base national income (i.e. 4,468,549). Assuming the 31 year full
realization timeframe, total project benefits per year is then 1.26 percent relative to the
base national income. The base GDP figure would change over 31 years. Assuming 5
percent GDP growth over the 31 period an alternative estimate of base year is arrived.
The total project benefit (i.e. 1,749,510) is only 0.56 percent relative to the alternative
base national income (average GDP during that period).
5. Further assessment of the total project benefits (explained above) in terms of
conventional project appraisal measures suggests that the project is economically viable.
More specifically, the project is viable with:
• a net present value of US$ 1234 million;
• a benefit-cost ratio (BCR) of 2.01; and
• an economic internal rate of return (EIRR) of 19 percent.
Estimating the Economic Impacts of Padma Bridge in Bangladesh Raihan and Khondker (2010)
53
6. The application of constrained optimization model such as CGE model outcomes also
vindicates the findings of the traffic model and SAM based model. More specifically, 50
percent reduction in transport margins may lead to welfare increase by 0.78 percent
compared to the base value.
7. Under certain assumptions (Simulation 1A), the construction of the Padma Bridge would
lead to an annualised reduction in head-count poverty at the national level by 0.84
percent and at the regional level by 1.01 percent. Other simulations also indicated
reduction in poverty in different magnitudes.
Estimating the Economic Impacts of Padma Bridge in Bangladesh Raihan and Khondker (2010)
54
References
AECOM New Zealand Limited “Padma Multipurpose Bridge Design Project: Detailed
Economic and Financial Analysis- Revision 1”
Alarcon, J.V. (2002): Social Accounting Matrix-Based Modelling: Extension to Wellbeing and
Environment and Computable General Equilibrium Models: Applications using the
1975 and 1980 Ecuador and Bolivian 1989 and 1997 SAMs, Institute of Social Studies,
The Hague, The Netherlands, pp. 13-15.
Foster, J.E., J. Greer and E. Thorbecke (1984), ‘A Class of Decomposable Poverty Measures’,
Econometrica, 52, pp: 761-776.
Household Income and Expenditure Survey (HIES) of 2005, Bangladesh Bureau of Statistics
(BBS), Dhaka
Labor Force Survey (2006), Bangladesh Bureau of Statistics (BBS), Dhaka
Pyatt G. and E. Thorbecke (1976) Planning Techniques for a Better Future, ILO, Geneva.
Survey of Manufacturing Industries (SMI), Bangladesh Bureau of Statistics (BBS), Dhaka
Estimating the Economic Impacts of Padma Bridge in Bangladesh Raihan and Khondker (2010)
55
Annex 1
:
SAM Multiplier Modules
The shift from a ‘data’ SAM structure to a SAM Multiplier Module requires the introduction of
assumptions and the separation of the SAM accounts into ‘exogenous’ and ‘endogenous’
components
18
.
Table A1: General SAM Modular Structure
1a-PA 1b-CM 2-FP 3a-HH-OI 4-KHH-OI 5-ROW TDD
1a PA T
1a, 1b
0 Y
1a
1b CM T
1b, 1a
T
1b, 3
T
1b, 4
T
1b, 5
Y
1b
2 FP T
2, 1a
T
2, 5
Y
2
3 HH-IO T
3, 1a
T
3, 1b
T
3, 2
T
3, 3
T
3, 5
Y
3
4 KHH-OI T
4, 1a
T
4, 3a
T
4, 5
Y
4
5 ROW T
5, 1b
T
5 2
T
5, 3
0 0 Y
5
TSS E
1a
E
1b
E
2
E
3
E
4
E
5
Where: by definition Y
i
= E
j
and 1 Production (1a PA = Production Activities and 1b CM = Commodities); 2 FP =
Factors of Production; 3 HH-IO = Households and Other Institutions (incl. Government); 4 KHH-OI = Capital
Account Households and Other Institutions (incl. government); 5 ROW = Rest of the World (Current and capital
account). Blank entries indicate that there are no transactions by definition.
The separation is needed to gain entry into the system, allowing some variables within the SAM
structure to be manipulated exogenously (via injection instruments) to assess the subsequent
impacts on the endogenous accounts as well as on the exogenous accounts.
Generally, accounts intended to be used as policy instruments are classified as exogenous and
accounts specified a priory as objectives (or targets) are classified as endogenous.
Three accounts are designated as endogenous accounts: (1) Production (Production Activities and
Commodities) account, (2) Factors of Production account, (3a) Households and Other Institutions
(excl. the Government).
The exogenous accounts comprises 3a Government (expenditure, transfer, remittances); 4 Capital
account of institutions (savings and demand for houses, investment demand, infrastructure and
18
The methodology and symbology follows Pyatt, G. and Jeffrey Round, (1977) Pyatt, G. and Jeffrey Round,
(1979) and Pyatt, G. and Roe, A. (1987) (eds), while the lay out follows Alarcón, J. V., E. Delabastida and R. Vos,
(1984), Alarcon, J. V., S. Keuning, J. van Heemst, W. de Ruyter and R. Vos, (1991).
Estimating the Economic Impacts of Padma Bridge in Bangladesh Raihan and Khondker (2010)
56
machinery and equipment); and 5 ROW transfers, remittances, export demand and capital. The SAM
Flows and the categorization into endogenous and exogenous accounts are shown below.
Table A2: Endogenous and Exogenous Accounts
1a-PA 1b-CM 2-FP 3a-HH-OI 3b-Gov 4-KHH-OI
5-ROW
TDD
1a PA T
1a, 1b
0 Y
1a
1b CM T
1b, 1a
T
1b, 3a
T
1b, 3b
T
1b, 4
T
1b,5
Y
1b
2 FP T
2, 1a
T
2, 5
Y
2
3a HH-OI T
3a, 2
T
3a, 3a
T
3a, 3b
T
2, 5
Y
3
3b Gov T
3b, 1a
T
3b, 1b
T
3b, 3a
T
3b, 3b
T
3a, 5
4 KHH-OI T
4, 1a
T
4, 3
T
4, 5
Y
4
5 ROW T
5, 1b
T
5, 2
T
5, 3a
T
5, 3b
T
5, 4
0 Y
5
TSS E
1a
E
1b
E
2
E
3a
E
3b
E
4
E
5
Where Endogenous: 1 Production (1a PA = Production Activities and 1b CM = Commodities); 2 FP = Factors of
Production; 3a HH = Households and Other Institutions (excl. Government); Where Exogenous: 3b
Government; 4 KHH-OI = Capital Account of Households and of Other Institutions (incl. government); 5 ROW =
Rest of the World (Current and capital account). Blank entries indicate that there are no transactions by
definition.
Table A3: Endogenous and Components of Exogenous Accounts
PA CM FP 3a HH&OI EXO INCOME
Exogenous Accounts (EXO) used as
injections Column Vectors
1a PA T
1a 1b
0 X
1a
Y
1a
X
1a
= 0
1b CM T
1b 1a
T
1b 3a
X
1b
Y
1b
X
1b
= Government Consumption
Subsidies -Taxes + Exports + Gov.
Investment (capital formation in
infrastructure and machinery and
equipment) + Gross Capital Stock
formation
2 FP T
2 1a
X
2
Y
2
X
2
=Factor Remittances from ROW
3a HH&OI T
3a 2
T
3a 3a
X
3a
Y
3a
X
3a
= Factor Remittances from ROW
3b-5
Leaks
L
1a
L
1b
L
2
L
3a
L
3b-5
= X
3b-
5
Y
3b-5
3b =Aid to Government from ROW
EXPN E
1a
E
1b
E
2
E
3a
E
3b-5
Where E
i =
Y
j
L
1a
= Activity Tax L
3a
= Income Tax + Household Savings + Corporate Savings
Estimating the Economic Impacts of Padma Bridge in Bangladesh Raihan and Khondker (2010)
57
L
1b
= Commodity Tax + Import Duty + Imports L
3b-5
X
3b-5
and Y
3b-5
falls out of the model
L
2
= Factor Remittances to ROW
Blank entries indicate that there are no transactions by
definition.
Note on Injection: For any given injection into the exogenous accounts X
i
(i.e. instruments) of the SAM,
influence is transmitted through the interdependent SAM system among the endogenous accounts. The
interwoven nature of the system implies that the incomes of factors, institutions and production are all
derived from exogenous injections into the economy via a multiplier process. Multiplier models may also be
built on the input-output frameworks. The main shortcoming of the IO model is that the feedback between
factor income generation (value added) and demand by private institutions (households) does not exist. In this
case the circular economic flow is truncated. The problem can be partly tackled by endogenising household
consumption within the I-O framework; this is typically referred to as a ‘closed I-O model’. In this case, the
circular economic flow is only partially truncated. A better solution is to extend the I-O to a SAM framework
which captures the full circular economic flow.
SAM coefficient (Aij) are derived from payments flows by endogenous accounts to themselves (Tij)
and other endogenous accounts as to the corresponding outlays (Ei = Yj); similarly, the leak
coefficients (Bij) derived from flows reflecting payments from endogenous accounts to exogenous
accounts. They are derived below.
Table A4: Coefficient Matrices and Vectors of the SAM Model
Account 1a - PA 1b – CM 2 – FP
3a -
HH&OI
3b … 5 EXO Income
1a – PA
A
1a,1b
= T
1a,1b
/ Y
1b
X
1a
Y
1a
1b – CM
A
1b,1a
= T
1b,1a
/ Y
1a
A
1b,3a
= T
1b,3a
/ Y
3a
X
1b
Y
1b
2 – FP
A
2,1a
= T
2,1a
/ Y
1a
X
2
Y
2
3a - HH&OI
A
3a,2
= T
3a,2
/ Y
2
A
3a,3a
= T
3a,3a
/ Y
3a
X
3a
Y
3a
3b … 5 Leaks
B
1a
= L
1a
/ Y
1a
B
1b
= L
1b
/ Y
1b
B
2
= L
2
/ Y
2
B
3a
= L
3a
/ Y
3a
Expenditure E
1a
= Y
1a
E
1b
= Y
1b
E
2
= Y
2
E
3
= Y
3a
The multiplier analysis using the SAM framework helps to understand the linkages between the
different sectors and the institutional agents at work within the economy. Accounting multipliers
Estimating the Economic Impacts of Padma Bridge in Bangladesh Raihan and Khondker (2010)
58
have been calculated according to the standard formula for accounting (impact) multipliers, as
follows:
Y = A Y + X = (I – A)
–1
X = M
a
X
Where:
Y is a vector of incomes of endogenous variables
X is a vector of expenditures of exogenous variables
A is the matrix of average expenditure propensities for endogenous accounts
M
a
= (I – A)
–1
is a matrix of aggregate accounting multipliers (generalized Leontief inverse).
Variations in any one of the exogenous account (i.e. in this case ΔX) will produce total impacts (ΔY)
of endogenous entries via the multipliers. The total impact will be decomposed by direct and
induced impacts for capturing the strengths of the transmission channel.
Table A6: Description of the Endogenous and Exogenous Accounts and Multiplier Affects
Endogenous (y) Exogenous (x)
The activity (gross output multipliers), indicates the total effect on
the sectoral gross output of a unit-income increase in a given
account i in the SAM, and is obtained via the association with the
commodity production activity account i.
The consumption commodity multipliers, which indicates the total
effect on the sectoral commodity output of a unit-income increase in
a given account i in the SAM, is obtained by adding the associated
commodity elements in the matrix along the column for account i.
Intervention into through activities (x
= i + g + e), where i= GFC + ST (GFCF)
Exports (e)
Government Expenditure (g)
Investment Demand (i)
Inventory Demand (i)
The value added or GDP multiplier, giving the total increase in GDP
resulting from the same unit-income injection, is derived by
summing up the factor-payment elements along account i’s column.
Factor Income Remittances from RoW.
Household income shows the total effect on household and
enterprise income, and is obtained by adding the elements for the
household groups along the account i column.
Intervention via households
(x = r + gt + ct), where
Remittance ( r)
Government Transfers (gt)
Corporation Transfers (ct)
Estimating the Economic Impacts of Padma Bridge in Bangladesh Raihan and Khondker (2010)
59
The economy-wide impacts of infrastructure investments are examined by changing the total
exogenous injection vector (especially Government Expenditure (g), Government Investment
(expenditures on infrastructure, machinery and equipment) and Investment Demand (i). More
specifically, the total exogenous account is manipulated to estimate their effects on output (through
an output multiplier), value-added or GDP, (through the GDP multiplier), and household income
(through household income multiplier).
Estimating the Economic Impacts of Padma Bridge in Bangladesh Raihan and Khondker (2010)
60
Annex 2
:
Mapping and Classification Scheme
Table A7: Mapping
Activity-Commodity 17 Activity-Commodity 41
1. Cereal Crops Paddy Cultivation and Grains Cultivation
2. Commercial Crops Jute cultivation, Sugarcane Cultivation and Commercial Crops
3. Livestock-Poultry-fishing Livestock Rearing, Poultry Rearing, Shrimp Farming and Fishing
4. Forestry Forestry
5. Other Agriculture Vegetable and Other Crop Cultivation
6. Other Food Rice Milling, Grain Milling, Fish Process, Oil Industry, Sweetener Industry and Food
7. Leather Products Leather
8. Cloth Jute and Clothing
9. Readymade Garments Ready Made Garment
10. Chemical-Fertilizer Chemical and Fertilizer
11. Machinery Steel and Machinery
12. Petroleum Products Petroleum Products
13. Other Industries Wood, Tobacco, Clay Products, Cement, and Miscellaneous
14. Construction Construction
15. Transport Transportation
16. Utility Utility
17. Other Services Trade, Social Services, Financial Services, Public Administration-Defense, Professional
Services and Other Services
Activity-Commodity 5 Activity-Commodity 17
a.
Agriculture
Cereal Crop, Commercial Crop, Livestock
-
Poultry
-
fishing, Forestry and Other Agriculture
b. Manufacturing Other Food, Leather Products, Cloth, Readymade Garments, Chemical-Fertilizer,
Machinery, Petroleum Products and Other Industries
c. Construction Construction
d. Transport Transport
e.
Services
Other Services
Labour Factor 1 Labour Factor 2
•
Labour
Labour Skilled and Labour Unskilled
Household
3
Household 8
•
Rural Land Based
Landless, Marginal, Small, Large
•
Rural Non-farm
Rural Non Farm Poor, and Rural Non Farm Non Poor
•
Urban
Low Education and High Education
Estimating the Economic Impacts of Padma Bridge in Bangladesh Raihan and Khondker (2010)
61
Annex 3
:
Multipliers of the SAM Modules
The multipliers derived using the National and Regional SAMs are reported here.
Table A8: Multipliers of the National and Regional SAMs
National SAM Regional SAM SW
1 a_Paddy Cultivation 11.66 11.33
2 a_Grains 9.55 11.85
3 a_Jute Cultivation 11.57 10.89
4
a_Sugarcane
Cultivation
11.31
11.65
5 a_Vegetables 11.13 11.00
6 a_Commercial Crops 10.84 10.85
7 a_Other Crop Cultivation 11.82 11.98
8
a_Livestock Rearing
11.29
11.67
9 a_Poultry Rearing 10.92 13.95
10 a_Shrimp Farming 12.85 12.21
11 a_Fishing 11.08 10.79
12
a_Forestry
11.37
11.35
13 a_Rice Millling 12.53 11.96
14 a_Grain Milling 9.56 11.71
15 a_Fish Process 13.53 12.70
16
a_Oil Industry
8.56
11.27
17 a_Sweetener Industry 11.72 11.43
18 a_Food 9.88 11.53
19 a_Leather 12.02 11.77
20
a_Jute
12.53
11.45
21 a_Clothing 10.91 11.00
22 a_RMG 10.67 10.68
23 a_Tobacco 6.50 10.95
24
a_Wood
10.75
11.49
25 a_Chemical 9.07 11.01
26 a_Fertilizer 10.79 10.25
27 a_Petroleum 4.09 12.63
28
a_Clay Products
10.44
10.65
29 a_Cement 10.60 11.80
30 a_Steel 10.36 11.27
31 a_Machinery 9.98 10.39
32
a_Miscellaneous
10.38
10.27
33 a_Construction 10.50 11.12
34 a_Utility 10.11 9.99
35 a_Trade 9.93 9.27
Estimating the Economic Impacts of Padma Bridge in Bangladesh Raihan and Khondker (2010)
62
National SAM Regional SAM SW
36
a_Transport
10.20
9.58
37 a_Social Servcies 10.22 9.12
38 a_Financial servcies 10.29 9.20
39 a_Public Administration and Defense 10.47 9.36
40 a_Professional Servcies 9.15 8.92
41 a_Other Services 10.80 10.50
42 c_Paddy 12.66 12.33
43 c_Grains 6.08 12.62
44 c_Jute 12.57 11.89
45 c_Sugarcane 12.31 12.65
46 c_Vegetables 10.83 11.87
47 c_Commercial Crops 8.08 11.13
48 c_Other Crop 12.11 12.96
49 c_Livestock Rearing 11.99 12.65
50 c_Poultry Rearing 11.87 14.94
51 c_Shrimp Farming 13.85 13.21
52 c_Fishing 12.08 11.79
53 c_Forestry 12.37 12.35
54 c_Rice 13.34 12.92
55 c_Grain 10.46 12.71
56 c_Fish Process 14.19 13.70
57 c_Oil Industry 4.86 11.88
58 c_Sweetener Industry 5.93 12.25
59 c_Food 10.30 12.50
60 c_Leather 12.93 12.77
61 c_Jute 13.43 12.45
62 c_Clothing 9.17 11.62
63 c_RMG 11.48 11.60
64 c_Tobacco 7.49 11.95
65 c_Wood 9.35 12.44
66 c_Chemical 5.23 11.60
67 c_Fertilizer 3.47 11.14
68 c_Petroleum 1.76 13.32
69 c_Clay Products 10.79 11.64
70 c_Cement 9.12 12.75
71 c_Steel 8.25 11.95
72 c_Machinery 4.56 10.02
73 c_Miscellaneous 4.43 10.22
74 c_Construction 11.50 12.12
75
c_Utility
10.72
10.92
Estimating the Economic Impacts of Padma Bridge in Bangladesh Raihan and Khondker (2010)
63
National SAM Regional SAM SW
76
c_Trade
10.93
10.27
77 c_Transport 9.67 9.58
78 c_Social Servcies 11.22 10.12
79 c_Financial servcies 10.30 10.09
80 c_Public Administration and Defense 10.57 10.19
81 c_Professional Servcies 9.28 9.80
82 c_Other Services 11.80 11.50
83 VA Labour Unskilled 10.62 9.68
84 VA Labour Skilled 8.82 6.46
85 VA Capital 8.97 7.26
86 VA Land 9.75 9.25
87 Landless 11.34 8.81
88 Marginal 10.15 9.82
89 Small 9.92 9.17
90 Large 7.29 8.85
91 Rural Non Farm Poor 8.63 6.22
92 Rural Non Farm Non Poor 10.80 9.05
93 Low Education 9.60 9.44
94 High Education 5.98 2.44
Total 100.0 100.0
Estimating the Economic Impacts of Padma Bridge in Bangladesh Raihan and Khondker (2010)
64
Annex 4
:
Equations of the CGE Model
Equations Description
1.
Price Block
2.
)1(
iiii
tvtmERPWMPM ++⋅⋅=
Import Price
3.
_ /(1 )
i i
PE PE FOB ER te
= ⋅ +
Export Price
4.
iiiiii
MPMDPDQP ⋅+⋅=⋅
Composite Price
5.
iiiiiiii
EPEDtvtdPDXPX ⋅+⋅−−⋅=⋅ )1(
Activity Price
6.
∑
⋅
=
j
jjii
PPN
τ
Input price
7.
iiiiii
INTPNXPXVPV ⋅−⋅=⋅
Value added price
8.
j
j
iji
PPK
⋅
=
∑
κ
Capital Price
Production and Supply Block
9.
i
i
i
i
i
i
iii
NVAXX
φ
φφ
ηη
/1
])1([
−
−−
⋅−+⋅⋅=
Gross Output (CES
aggregate of value-
added and
intermediate input)
10.
i
ii
ii
ii
PV
PN
VN
φ
η
η
+
⋅
−⋅
⋅=
1
1
]
)1(
Composite
Intermediate
11.
i
i
if
f
ifii
FDAVV
µ
µ
α
1
][
−
−
⋅⋅=
∑
Value added
function
12.
i
i
iff
i
iif
iif
WAV
PV
VFD
µ
µ
ϖ
α
+
⋅⋅
⋅
⋅=
1
1
Factor Demand
13.
ifif
i
ff
FDWFY
⋅
⋅
=
∑
ϖ
Factor Income
14.
i
ii
i
i
i
iii
DMAQQ
ρ
ρρ
δδ
/1
])1([
−
−−
⋅−+⋅⋅=
Composite Supply
(Armington
Function)
15.
i
ii
ii
ii
PM
PD
DM
σ
δ
δ
+
−⋅
⋅
⋅=
1
1
]
)1(
[
Import-Domestic
Demand Ratio
16.
iii
DMQ +=
Composite
commodity
aggregation for
perfect substitutes
17.
ii
DQ =
Composite supply for
Non-imported
commodities
18.
ii
MQ =
Composite supply for
Non-produced
imports
19.
i
ii
i
i
i
iii
DEATX
φ
φφ
γγ
/1
])1([
−−
⋅−+⋅⋅=
Composite supply
function
Estimating the Economic Impacts of Padma Bridge in Bangladesh Raihan and Khondker (2010)
65
Equations Description
20.
i
ii
ii
ii
tdPD
PE
DE
ϕ
γ
]
)1(
)1(
[
−⋅
−
⋅
⋅=
Export Supply
21.
0
_
i
e
i
i i
i
PWE
E E
PE FOB
= ⋅
Export Demand
Institutional Income
22.
f
f
fhh
FYYF ⋅=
∑
,
ε
Household Factor
Income
23.
[
]
)1(
hhhhh
sthRMYFY −−⋅+=
Household Income
24.
∑∑∑
⋅⋅+⋅⋅⋅+⋅=
i
iiiii
i
ih
h
h
PDXtdERMPWMtmYthYG
Government Income
25.
hihiih
YPCD ⋅=⋅
β
Consumption
Demand
26.
GTOTGD
g
i
i
⋅=
β
Government
Demand
27.
IDKPK
iii
⋅=⋅
ξ
Investment by
Destination
28.
j
j
iji
DKID
⋅
=
∑
κ
Investment by Origin
29.
∑
⋅
=
j
jiji
NINT
τ
Intermediate
Demand
Equilibrium
Condition
30.
SFSGSHS
h
h
++=
∑
Total Savings by
Institutions
31.
i
h
iihii
IDGDCDINTQ +++=
∑
Product Market
Balance: Supply
equals Demand
32.
if f
i
FD FS
=
∑
Factor Market
Balance:
Demand plus
unemployed factor
equals Supply.
(capital is fully
employed, but
labour is not)
33.
0
=−−⋅−⋅
∑∑∑
SFRMEPWEMPWM
h
hi
i
ii
i
i
Current Account
Balance: Receipts
equal to Outlays
34.
SFSGSHSI
h
h
++==
∑
Macro Balance:
Investment equals
Savings
