Quantifying the impact of development of the transport sector in Pakistan.
Siddiqui, Rizwana
The paper quantifies the impact of tax-financed public investment
in infrastructure and services by mode of transportation, land, air, and
water, using the dynamic computable general equilibrium model. The model
includes resource cost, taxes, and cost of externalities such as
congestion, pollution, and accident, where congestion and accident are
incorporated for land transport only. The model measures benefits of an
investment programme by a change in prices not only in the transport
sector, but also in taking account of the advantages to other sectors of
the economy. The results show that tax-financed investment in transport
has reduced its share and cost of non-factor services in the total value
of commodities (first objective of NTC). It reduces transport cost of
movement of passengers. Improving safety and reliability of transport
operations can be concluded from a reduction in the environmental and
accident cost (2nd objective of NTC). Overall, the transport sector
development has a positive impact on macro aggregates too.
JEL classification: L9, R53, R41. O11, D62. C68
Keywords: Public Investment, Transport, Growth, Trade,
Externalities, CGE
1. INTRODUCTION
An efficient transport system is not only a pre-requisite for
economic development but is also important to achieve the objective of
economic integration in the world economy. Insufficient transport
infrastructure results in congestion, delay delivery time, fuel waste,
pollution and accident (1) which built inefficiencies in the economy and
costs the economy 4 to 6 percent of GDP each year [Shah (2006)and World
Bank (2007)], which can be saved by investing in transport services.
Realising its importance, the government of Pakistan has initiated
National Trade Corridor Improvement Programme (NTCIP) in 2005 to improve
logistic and transport infrastructure so that it can fulfill the demand
of economy more efficiently. This five years programme includes all
sectors that improve performance of corridor-high way namely, road
transport, railways, airports, and ships etc. The objective of the
programme is to reduce the cost of doing business and improve quality of
services. The study quantifies the efficiency of transport sector by
evaluating the impact of public investment to improve transport services
on the economy in general and on cost of land transportation in
particular; i.e., cost of freight and passenger movement and cost of
externalities such as congestion, air pollution and accident. The
outcome of the study depends on how improved facility is achieved, i.e.,
who bears the cost and who benefits etc. This paper assumes tax financed
public investment that not only change domestic price and demand, but
also welfare and poverty. The issue is analysed in computable general
equilibrium framework taking into account inter linkages of transport
sector with rest of the economy. First, a social accounting matrix (SAM)
is developed with a detailed transport module. Then, a dynamic CGE model
is developed around this SAM and simulations are conducted for short run
and long run analysis of public investment in trans port sector.
The Sections 2 and 3, respectively, presents review of the
transport sector of Pakistan and review of literature. Section 4
describes the main characteristics of standard CGE model and
modification made to it for the transport sector analysis. Section five
explains the data base. Section six evaluates the simulation results.
Final section concludes the paper with some policy implications.
2. TRANSPORT IN PAKISTAN
With 160 million of people, transport in Pakistan is one of the
rapidly growing sectors. With all basic modes of transportation--road,
railway, air, and water, it accounts for 12 percent of GDP higher than 6
percent in global economy. Road density is very low, 0.34 km/sq.km. In
2006, domestic transport (2) represents 1.29 percent of the final value
of the commodities against a targeted value of 0.8 percent to be
competitive at global level [Pakistan (2005)]. The detail of the
transport sector and its facilitating components such as construction of
roads, air ports and harbors and the stock of transport vehicles are
briefly discussed in the subsequent paragraphs.
2.1. Road Network
Road transport is the most popular mode of transportation in
Pakistan.
[FIGURE 1 OMITTED]
The government has initiated many projects to develop it. As a
result, total length of roads has approached to 260 thousand km in
2004-5 with an increase of high type road by 88 percent since 1990
(Table 1). Currently, the country has 19 national high ways including
motor ways of the length 9031 km under national high way authority
(NHA). It accounts for 3.5 percent of Pakistan entire road network
[Pakistan (2007)].
A cross country comparison shows that road density index can be
used as a symbol of prosperity and development. Pakistan has very low
road density, i.e., 0.3 compared 3.1 for Japan [Figure I. Source:
Pakistan (2006)]. Currently, Pakistan is endeavoring to gradually
increase this density from 0.32km/sq.km to 0.64 km/sq.km. During
1990-2005, rail services have declined in terms of passengers and
freight transport compared to road share due to priority changed by the
government towards road transport (Table 1). However, in 2004-05, a
positive trend in passenger traveling and freight traffic on rails have
been recorded due to railway development projects implemented to improve
in railway services. (3) In result, income of the Pakistan Railway has
increased from 10.6 billion to 13.2 billion during 2003-04 to 2004-5
[Pakistan (2005)].
2.2. Air Travel Service
The Pakistan International Air (PIA) Line since it established in
1956 provides transport services on both domestic and international
routes. The Civil Aviation Authority (CAA) manages and develops it.
Various measures have been taken to develop a strong air transport
infrastructure during the last fifteen years. (1) Installed a modern
aircraft power system at Quaid-e-Azam International airport, (2)
Renovation of existing terminal at Lahore, (3) Facilities at Nawabshah
airport, (4) Construction of Sukkur terminal, (5) up gradation of
Mohenjodaro Airport etc. Recently, an airport with joint private/public
efforts has been completed at Sialkot. However, the revenue passenger
kilometers (RPK) of PIA has not increased significantly despite increase
in number of planes and available seats (Table 2). Table 2 shows that
expenditure of PIA increase more than revenue over fifteen years.
2.3. Ports and Shipping
Pakistan has three deep sea ports. Karachi port is a premier port
of Pakistan and handles about 75 percent of the entire national trade.
The total volume of cargo handled at Karachi natural port was 19 million
tones including 15 million tones of imports and 4 million tones of
exports in 1989-90. The cargo handling has doubled over the years (Table
3).
Port Qasim is Pakistan's second deep sea port and meeting more
than 40 percent of shipping requirements of the country becomes busiest
port of the country. Currently a diverse range of commodities such as
furnace oil, chemicals, edible oil, coal, wheat, fertilisers etc. are
handled there. The cargo handling has significantly increased i.e., 43
percent during 2003-04 to 2004-05. Gwadar port is third deep sea port of
Pakistan situated on the Balochistan port and is currently under
construction.
Pakistan national Shipping Corporation is a group of companies
operates fleet of 14 vessels with a total dead weight carrying capacity of 570466 tons (DWT). They are serving not only national trade but also
participating in international trade.
[FIGURE 2 OMITTED]
[FIGURE 3 OMITTED]
2.4. NTC--Programme of Pakistan [Pakistan (2007a)]
In the year 2005, Government of Pakistan has taken major
initiatives around the National Trade Corridor (NTC) to bring the
quality of transport services to international standards. The two
objectives among others are: (1) reduced share of domestic transport and
cost of non-factor services in the total value of commodities, (2)
Improved safety and reliability of transport operations etc. The focus
of the paper is on these two objectives of the NTC programme.
2.5. Investment in Transport Sector
Construction as a whole contributes to growth process through
higher multiplier effects with a number of backward and forward linkages. (4) The Figure 2 shows that private investment registered an
increase, but public sector investment has declined in transport
capital. Figure 6 shows that private and public investment in
construction has increased, which includes transport-infrastructure
also.
2.6. Externalities: Congestion, Pollution, and Accidents
Vehicles on the road have registered a sharp increase over the last
fifteen years from 2 million to 6 million (Table 1), which has resulted
in congestion i.e., vehicles per kilometer has increased from 12
vehicles/kin to 23 vehicles/kin. Air pollution is increasing function of
transportation facilities. During 1995 to 2002, carbon dioxide emission
has increased from 0.69 metric tons per capita to 0.75 metric tons per
capita with an increase in traffic load on the road (Table 1). In the
absence sufficient public transport infrastructure, tremendous increase
in vehicles on the road has deteriorated air quality.
[FIGURE 4 OMITTED]
Road traffic accidents are also deteriorating for both human and
physical loss. This is an important and preventable cause of death.
Downing (1985) shows that Punjab (the largest province of Pakistan) has
fatal accidents rate per million vehicles kilometers, 16 times higher
than the rate for UK (0.49 compared to 0.03) (Figure 4). Razzak and Luby
(1998) also shows that death rates for Karachi is much higher than
cities in developed countries i.e., 11.3 people die per 10000 vehicles
registered in Karachi, 1.4 die in Tokyo, and 2.8 die in UK (Manchester)
for a similar number of vehicles. Fatality index is extremely higher for
Pakistan i.e., 28 percent (4th highest of 29 countries). (5) The studies
in other countries suggest that low cost engineering improvements have
considerable potential for accident reduction.
3. LITERATURE REVIEW
A number of studies have evaluated transport sector development and
the issues related to transport such as congestion, pollution, and
accident using computable general equilibrium and partial equilibrium
models. The CGE models have advantage over partial equilibrium models as
they allow tracking of the changes in the economy not only in transport
sector but can also be linked with other sectors and welfare and
poverty. However, they do not allow for the same degree of modeling
details of the transport sector as partial equilibrium models. The
results of few studies are discussed below.
Conard and Heng (2006) develop a computable general equilibrium
model incorporating congestion cost and determine optimal tax financed
investment in road infrastructure. The results show that investment in
infrastructure reduces congestion cost. However, the study ignores
fundamental rule that a better infrastructure can generate additional
traffic. Mayeres and Proost (2004) discuss various principles of
transport pricing--average cost and marginal cost--with alternative ways
to finance the deficit, marginal labour tax rate or transfers in general
equilibrium frame work. The results show that welfare impact depends not
only on presence of budget constraint but also on the flexibility with
which that constraint is to be met, congestion and ratio of transport
revenue to financial costing in the base year. The results recommend
marginal cost pricing rule for welfare enhancing impact.
Ellis and Hine (1995) analyse transport sectors using participatory
mapping, historical time trend analysis, vehicle preference matrix, and
semi-structured questionnaires. The study found substantial difference
in transport tariff between Africa and Asia due to low vehicle diversity
in African countries, which is result of low income level, insufficient
support from the government, and poor back up services. To improve the
supply or quality of rural transport services, and/or reducing the cost
of their services should deregulate transport market. Government should
promote alternative modes.
The study conducted by Bank's Independent Evaluation Group (IEG) [World Bank (2007)] consists of review of the Bank's
assistance to the transport sector in developing countries over the last
ten years. The review suggests that developing countries have made
substantial improvement. They found that management is most important
for improved out come. Increase private sector participation along with
policies targeting to improved management especially in road transport
have enormous impact on transport efficiency. IEG [World Bank (2007)]
also pointed out that the cost of road accidents is a heavy burden on
developing countries i.e., more than 3000 deaths result daily from road
accidents. Low and middle-income countries account for 85 percent of
such deaths and 90 percent of injuries (1 to 2 percent of GDP, more than
the total development aid received by these countries.). WHO and World
Bank suggest that such injuries are a growing public health issue,
disproportionately affecting vulnerable groups of road users in
developing countries. World Bank (1994) shows that infrastructure
contribution to growth and poverty reduction could be significantly
increased by strengthening incentives to transport suppliers in three
ways: (1) more autonomous to management with accountability process. (2)
Restructuring sectors and regulations to promote effective competition
(3) giving users and the stakeholders more voice and responsibility in
planning and regulatory arrangements. Downing (1995) using data from
Pakistan indicate that low cost engineering improvement, particularly in
black spot can reduce accident in the country if backed with improvement
in training and enforcement. The study also shows that traffic police
can be used for maximum benefits.
4. COMPUTABLE GENERAL EQUILIBRIUM MODEL
First, main characteristics of CGE model, (6) which is static and
Walrasian in nature, are discussed. The model is extended with a
detailed module of land transport.
4.1. The Characteristics of a Standard CGE
The model is built around social accounting matrix (SAM) for the
year 2002 [Dorosh, et al. (2004)]. The SAM sectors, factors, and actors
are aggregated from original SAM and some sectors (transport and other
related sectors). The four types of economic agents are: two consumer
groups, eighteen production sectors, the government and the foreign
sector. Two primary factors are labour and capital. Two types of
households are included in the model representing two regions of
Pakistan--rural and urban. Consumers in different groups differ in their
productivity and income they receive, transfers from government, firms,
rest of the world and tastes. Households in the same groups are similar
in all respects. It was assumed that markets are perfectly competitive
and in the equilibrium all the factors and product markets are cleared.
In the production process, price dependent input coefficients are
used. Labour and capital together determines value added in each sector.
CES technology is assumed between labour and capital. Producers maximise
profits at the equilibrium--zero profit condition holds. The demands for
factors of production, labour and capital are fulfilled with fixed
supply-quantities. In factor market, all factors can move freely and
rental rates adjust to bring equilibrium in factor market.
The incomes from factors of production are distributed among
institutions in fixed shares in the base year. Households receive all
labour income, a part of capital income from production, transfer
payments from the government, and dividends from firms. They also
receive a certain amount of foreign exchange in terms of remittances that is used to finance the trade deficit. Household demand is specified
by linear expenditure system (LES)-maximising Stone-Geary utility
function subject to household's budget constraint. Their
expenditure includes tax payments to government, which are specified as
fixed shares of household income. Households' savings are specified
as fixed share of their income. The government collects taxes from
production and households and distribute (transfer payments) them among
households (indexed to the domestic price level), to production sectors
as subsidy payments and final consumption expenditure (of fixed
commodity quantities). Government savings is defined as the difference
between government revenues and expenditures. Enterprises income
originates from capital and paid to households as dividends and rest is
saved.
The Armington assumption is imposed--commodities produced locally
are assumed to be imperfect substitute for the imported commodities and
combined with CES technology. The economy is assumed to be a price-taker
on the import side. The imports are subjected to an import tariff. In
the market, the ratio between demands for products from these two
sources depends on relative prices. The allocation of domestic outputs
between domestic and foreign markets (Exports) is determined by the
relative prices received in domestic and foreign markets. Constant
elasticity of transformation is assumed between two types of goods.
Export demand is a function of the ratio of world export price to
domestic export price (fob) and base year export demand. The baseline
equilibrium is characterised by a trade deficit, which is financed by
foreign exchange to households (remittances).
Total supply in the domestic economy consists of domestic goods for
local consumption and imports. Demand side consists of households'
consumption, government consumption, intermediate input demands and
investment demand. Consumer prices (composite) are determined by demand
and supply equilibrium condition for each commodity. Total demand for
investment and government consumption in real terms are determined by
deflating with their respective price deflators.
The three blocks, savings-investment, government, and the rest of
the world are associated with the macro constraints of the model. The
total purchase of investment goods is financed by savings from the
domestic institutions and the rest of the world. (ii) The fiscal
balance--determined by the difference between government revenue and
spending; and (iii) the external trade balance implicitly equates the
supply and demand for foreign exchange. The difference between the two
is current account balance (CAB).
4.2. Transport Externalities in CGE
This module is developed for in depth analysis of land transport
system, which can be extended for other mode of transportation. The
basic structure of the CGE model mentioned above is extended to
incorporate congestion as in Conard and Heng (2006).7 Congestion reduces
the productivity of transport capital in the production sector and
dependent on the stock of infrastructure associated with transport,
roads, railways tracks, airports, and ports etc., which facilitates
transportation of goods and passengers. Similarly, transport capitals
(vehicles) such as cabs, buses, trucks, are included in the model
explicitly, which are important to determine congestion, pollution and
accidents. All these factors together determine the intermediate input
of transport services in each sector. Air pollution and accidents do not
affect consumer behaviour but indirectly affect domestic resources. The
change in accidents leads to change the loss of GDP.
First we assume that transport services are proportional to the
transport capital stock that can be improved by a better provision of
transport infrastructure (KI)-construction of roads.
KT = [KT.sup.0] EXP(-alpha_tr/KI) (1)
Where alpha_tr >0 and as KI [right arrow] [infinity], full
utilisation of the stock of transport equipment [KT.sup.0] is achieved.
In other words, transport services depend on congestion Z
(vehicales/kilometer) and elasticity ([[epsilon].sub.KT,] Z) of
effective transport capital wrt z (congestion), which is less than zero.
The equation is defined below
[TR.sup.e.sub.ser] = [KT.sup.0] * [Z.sup.[epsilon]XT,Z] (2)
The higher the Z, the less productive transport capital, which
effect cost of production--transport services used to move goods and
services from one place to other. Congestion index is defined below
[MATHEMATICAL EXPRESSION NOT REPRODUCIBLE IN ASCII] (3)
Where n+2 is number of sectors and 2 households, [KT.sup.0] is
actual transport capital used in transport services and [KT.sup.*] is
optimal capital stock. An extended network of the roads and better
connection between modes of transportation (increase stock of
transportation) improves the efficiency of the stock of transport
capital. Cost of transportation increases if Z>I. The stock of
transport infrastructure (KI) in Equation 1 reflects the direct effect
of KI on capacity utilisation which is defined below
CU(KI) = exp([alpha]/KI) < 1 (4)
Under optimal allocation Pc_cong (Price after including congestion
cost) is defined below
[PKT.sub.S] * [KT.sup.0] = [PKT.sup.1] * [KT.sup.0] +
C.sup.cong.sub.c] (5)
[KT.sup.0] is capital stock higher than the stock in the absence of
congestion, which can be saved if more infra structure is provided.
Congestion cost [C.sub.cong] is defined as
[MATHEMATICAL EXPRESSION NOT REPRODUCIBLE IN ASCII] (6)
[[beta].sub.i] is the size of externality (congestion) caused by
industry j.
Taking the elasticity ([[epsilon].sub.KT,Z] from Conard and Heng
(2006), we calibrate cost of congestion in the absence of congestion
data for Pakistan. To calculate congestion index Z we assume that actual
stock of transport capital is 20 percent higher than required given the
size of infra structure. If elasticity is high the congestion cost
externality for the economy is high and stocks of KT should be reduced.
In order to understand modeling of the direct and indirect effects of
investment in transport infrastructure see Figure 1 in Appendix I.
The level of other two externalities, pollution and accidents, (8)
are calculated with pre and post simulation data and do not affect
consumer behaviour. The marginal external cost of accidents (net output
losses in terms of transport capital goods, and medical costs) is
calculated assuming that relationship between accident risks and traffic
flow exists, which also depends on the investment in transport services
[Downing (1980)]. The relationship between accidental fatality rate and
per head transport capital is defined in Equation 7
[MATHEMATICAL EXPRESSION NOT REPRODUCIBLE IN ASCII] (7)
Where ACC = Accidental cost, [KT.sup.e] = total transport services
using transport capital (vehicles) and [KT.sup.e.sub.pc] is transport
services per capita. The value of [sigma] (-0.44) is taken from Downing
(1980) and alpha is calibrated using SAM values and population taken
from [Pakistan (2005)].
The model evaluates the transport-fuel related emissions cost
before and after simulations. Pollution creating input in transport in
the model is petroleum. The change in provision of transport services
lead to changes in demand for petroleum. As a result cost of emission
changes. The change in transport services determine the intermediate
input of petroleum which in turn determines the change in pollution cost
associated with this input in transport. An equation [modified version
of equation in Ryan, Miguel, and Miller (2002)] for emission associated
with petroleum is introduced to calculate cost of emission as follows.
[MATHEMATICAL EXPRESSION NOT REPRODUCIBLE IN ASCII] (8)
Where XSi is output of transport vi indicate share of emission of
co2 from transport services production. ICJ is intermediate consumption
of transport used by productive activities. Ctrh is households
consumption of transport services, and OF is other foreign services.
First environment cost associated with transport is calculated assuming
same relationship exists between emission and transport services as
total emission and output. Using emission data from World Development
Indicators (2006) environmental cost of transport sector is calculated.
For the air and water transport, passenger and freight traffic are
defined on the basis of input-output table. No other module for
transport equipment or larger activities on airport and harbour has been
included in the paper. For these two sectors, we discuss results with
reference to change in transport services only.
4.3. Dynamic Features of the Model
For the long run analysis model is run for ten years. The capital
stock is defined on the basis of an average capital output ratio (ACOR).
One of the channels, suggested by new growth theory, by which trade
enhances growth is that a country can obtain advanced technology from
its trading partners through trade. The model incorporates it through
change in factor productivity. Growth in labour force and total factor
productivity (or technological progress) increases at an exogenous rate
of two percent and one percent respectively. All other exogenous
variables also increase with exogenous growth rate of two percent. The
investment demand equation by target determines the pattern of
reallocation of new investment among different sectors of the economy
after the shock. The model is solved for each year.
The calibration of the model consists of the selection of
parameters such that the behaviour of the economic agents around the
bench mark equilibrium and their valuation of the transport
externalities correspond with values given in the literature. Here,
congestion is assumed to occur only on the road network.
5. CONSTRUCTION OF SOCIAL ACCOUNTING MATRIX
The starting point is SAM constructed by [Dorosh, et al. (2004)],
which depict the situation in Pakistan in 2002 and represents the bench
mark equilibrium. First, the production sectors are aggregated into 11
sectors from 34 sectors--agriculture, mining, manufacturing (food,
textile, cement, wood, petroleum, and other manufacturing),
construction, transport and other services. These sectors buy primary
inputs from households and using them in the production process
generates value added. In exchange of supplying factor services,
households receive income as wages and returns to capital.
The main focus of the paper is to analyse the impact of development
of transport infrastructure to improve transportation in the country.
The SAM 2002 has four sectors which contain data to analyse the issue
under focus--transport. 1. Construction, 2. Transport services. 3.
Transport equipment (which includes transport vehicles). 4. Energy
(Petroleum). Here, for the purpose of detailed analysis, construction
and transport services are disaggregated by mode of
transportation--land, air and water using information from various
sources. Keeping all agriculture sectors together, industry and services
sectors are disaggregated for the detailed analysis of transport
services. Industrial sector includes transport related sectors; cement,
wood (construction goods), transport goods (petroleum, transport
equipment, and other manufacturing) and non transport sectors--food and
textile. Construction and transport services have been disaggregated by
mode of transportation; road, air, water. All other transportation
activities are aggregated into one (9). Rest of the services other than
transport is aggregated into one.
Different types of construction activities are identified. The
construction (10) activities differ in both nature of output and input
structure, the output originating from construction sector flows to the
ownership of dwellings and rest to investment. The construction sector
covers all repairs, addition, alteration and demolishing activities
carried out in the economy by households, private bodies, public
institutions and the general government is considered as intermediate
construction in each sector. The investment goods are determined by
targeted sectors and disaggregated into private and public sector (Table
5). The table shows that transport services are energy (petroleum)
intensive. Land, air and water transport use 57.5 percent, 45.1 percent
and 46.6 percent of petroleum (Table 5).
The principal source of, data on GFCF in building and
infrastructure is from national accounts. The construction is associated
with mode of transportation, the government is the principal agents. A
distinction is made between passenger and freight transport services.
Freight transport is considered as intermediate consumption, whereas
final consumption expenditure of household on transport is considered as
movement of passengers. The structure of cost of production is presented
by mode of transportation in Table 6 shows that on average transport
cost is 3.7 percent in production activity. It is relatively high for
mining products and transport equipment, 10.1 percent and 8.2 percent
respectively and very low in construction activities. The construction
is activity which is produced at the place it is needed.
Land transport services are largely demanded by urban households
(Table 7). Both urban and rural households with thirty and seventy
percent of population uses 50 percent each of total land transport
services. Air and Water transport are largely used by urban households
in the domestic economy. Any improvement in this sector will benefit
more to urban households. The unique feature is that the production of
it is not storable and highly time and route specific.
6. SIMULATION EXPERIMENTS
The above model--with externalities--is subjected to assess the
impacts of development of transport sector through tax financed public
investment in transport infrastructure and transport services. These
projects are costly and there is need to pay special attention to find
financial resources. They can be financed through domestic resources or
through multinational assistance. Domestic resources can be raised
through increasing saving, cut in government expenditure, or raising
government revenue through taxes, which can have different impact on
macro aggregates and welfare and poverty. In this exercise we use tax
financed investment. Following simulations are conducted for the short
run and long run analysis. One year and ten years, respectively, are the
time frame for short run and long run analysis.
* Business as usual (BaU) growth path.
* Tax-financed investment in transport sector.
The discussion of results focuses on the change in cost of
production, demand for transport services and externalities. The
performance of the transport is measured by change in transport cost,
demand for transport capital, congestion, the emission and the accidents
etc. The comparison of the results for short run and long run reveals
how the conclusions change between the two periods.
The general equilibrium model presented in the earlier section
treats, labour supply, government consumption in real term, CAB,
exchange rate, public investment by target, remittance income,
government transfers to households, transport capital, as exogenous
variables. The model solves for local production, imports, exports,
income levels, congestion, demand for transport capital, household
income and expenditure, government revenue etc. All exogenous variables
grow by 2 percent over the years.
In these experiments, public investment in transport infrastructure
and transport services is increased by 20 percent. This type of
government decisions require policy makers to have a good idea of the
extra costs caused by the activity, Here, it is assumed that public
investment is tax financed. The benefit/losses in the presence of market
imperfections are measured by the variation in the cost of production
which leads to change in prices not only of transport services but also
in the prices of other goods and services produced in the economy and
the change in returns to factors of production. The change in cost of
production is the profit/loss of the producer. The users completely pay
for resource cost. The change in this cost shows the benefit or loss to
the users (consumers). Congestion is determined endogenously associated
with demand for transport capital with given stock of infrastructure
(transport capital/km). The cost associated with fuel emission and
accidents are estimated before and after the policy shock exogenously
based on values of transport services determined with in the model.
The development of transport infrastructure lowers the price of
transport and the cost of production as well. On the other hand increase
tax rate lead to increase in prices. The net change in prices determines
the impact on macro aggregates. The exports of construction material
(cement, wood, and other manufactured commodities) decline as domestic
demand increases due to development of infrastructure, etc. The increase
stock of infrastructure of road reduces congestion which lower demand
for transport capital by firms and households. This lowers environmental
cost also. Similarly improved transport services reduce accidental cost.
For air and water transport the focus is on transportation cost only
(11) not the pollution or any other externality. The changes in factor
prices and government revenue determine equilibrium household income
levels. The impacts on poverty depend on not only on income levels but
also on price levels. The higher incomes and lower prices generate lower
poverty incidences. Even with higher prices, poverty reduces if income
increase is higher than price increase. The urban households are the
main user of transport services so a reduction in transport prices would
have positive impacts on urban households indicating that urban
households get the advantage of lower prices due to investment in
transport infrastructure than the rural households. However, they are
also major contributor to domestic saving and if savings adjust to
finance investment they bear larger negative effect in terms of
consumption and welfare even in the presence of lower prices. Thus
results are subject to the adjustment mechanism--closure. The following
sections discuss the results of the simulations.
Simulation 1: BaU path
A dynamic CGE allows economy to grow in the absence of any policy
change.
First, a business as usual (BaU) path is depicted for one year and
ten years which is used as a reference scenario for short run and long
run analysis, respectively. This exercise takes into account efficiency
effect as well as accumulation effects in the absence of any policy
change. The results indicate growth path for 2003 to 20012 in the
absence of any policy change. In this exercise output grows by 9.5
percent over ten years with value added growth 4 percent per annum on
average. This shows decline in intermediate input mainly transport
services. Exports expand by 9 percent over ten years. The results of
simulations for short run and long run are compared to get an idea for
future policy framework.
Simulation 2: Tax Financed Public Investment in Transport
Infrastructure and Transport Services. (Short run vs. Long run Effects)
In this exercise public investment is used as instrument which
entered the model as exogenous variables. Simultaneous increase in
public investment in transport infrastructure and transport services by
twenty percent for each of the three transport modes, land, air, water
is fed into the model. Additional tax on consumption is imposed to raise
resources to finance this investment. The results of this tax financed
extension of transport infrastructure and transport services are
presented in Tables 8 to 11.
The first impact of increase in tax financed investment is that
stock of transport infrastructure--road, ports and harbors--have
increased. The price of land transport does not change in the short run
but decline by (-3.1) percent in the long run. As a result, demand for
land transport services (intermediate input) for freight movement rise
by 0.24 percent in the short but decline significantly in the long run,
by -7.8 percent. The households' demand for land transport
(expenditure on travel) follows the same pattern in the rural area. But
expenditure on land transport by urban households decline in the short
run as well as in the long run, they are the major user of land
transport. On the other hand, price of air transport and water transport
rise in the short run by 0.9 and 1.03 percent, but significantly decline
in the long run; -1.3 and -13.2 percent, respectively. This indicates
public investment in the short run do not generate enough supply of
infrastructure, which results in reduction in prices to compensate for
the price hike due to tax raise. In the short run, demand for air
transport and water transport decline by the producers for the freight
movement and by households for passenger movement in the urban area. In
the long urn air transport cost reduces in productive activities as well
as expenditure by both types of households. The expenditure on water
transport by all the three users increases with significant decline in
prices. This proves the argument made by Down that better infrastructure
provision generate additional demand [Conrad and Heng (2006)]. Though
this statement is made for land transport, but this can be applied to
other mode of transportations.
In the short run, taxes rise more than decline in prices. As a
result price level in the country (GDP-deflator) rise by 1 percent.
Though improved supply of infrastructure has negative effect on prices,
but this effect is not enough to compensate for rise in taxes. The
relative prices for all other commodities decline or remain unchanged
leaving consumer price index unchanged in the short run. Wile in the
long run consumer prices decline for majority of commodities due to
significant decline in cost of transport services (freight cost and
passenger cost). This indicates that development of transport services
renders benefits in the long run. Consumer prices rise for transport
equipment and petroleum (major input in transport services) by 1.4 and 2
percent, respectively (Appendix II, Table 1). The effect of rise in tax
cancelled out by the decline in transportation cost of the users. As a
result consumer price index (CPI) has declined by (-0.75 percent) in the
long run over BaU value.
The effects on macro aggregates presented in Table 8 show that
output has risen in the short run by (0.04) percent due to increase in
cost of intermediate inputs which has risen by 0.07 percent. In the long
run, value added increase over BaU value by 0.02 percent and output
decline by 0.04 percent due to decline in cost of intermediate inputs by
0.1 percent. Intermediate cost associated with freight transport has
declined in the long run significantly for land transport and air
transport, whereas water transport rises which is mainly used for export
purposes. However, this needs to be analysed further by extending the
model.
Exports increase in the short run as well as in the long run by
0.11 and 0.06 percent over their respective BaU values. The demand for
investment goods; cement, wood, and other manufacturing rises in the
long run by (2.7, 11.4, and 1.1 percent) respectively (Table 9).
Improved infrastructure provision reduces the demand for transport
capital by (-0.04) percent over BaU value (Table 9). In result demand
for petroleum fell by 1.7 percent.
The benefit of improved infrastructure provision includes the
variation in prices of all goods and services, including land and
labour. The change in other variables such as exports, imports, labour
demand also reveals benefit or losses to the economy etc. Table 1 in
Appendix II shows the impacts on volumes of goods produced, exported and
imported in detail. A rise in export of all commodities can be observed
except food and textile, which decline marginally. (12) Imports of
mining commodities (a major input in petroleum sector) and petroleum
(major input in transport services) increases significantly in the long
run (Table 1 in Appendix II).
An increase/decline in labour demand can be observed in transport
and other related sectors (Table 1 in Appendix II). An increase in
production of construction and sectors related to transport and other
sectors such as mining, cement, wood, other manufacturing have drawn
resources from agriculture, food and textile. The changes in production
activities, which ultimately have changed factor demand lead to
significant decline in wage rate and capital rental rates by (-8.4 and
-9.4) percent (Table 8), respectively, in the long run,
Congestion Cost
Congestion reduces transport services provided by transport capital
in the presence of insufficient transport infrastructure.
The results show that tax financed development of transport
infrastructure and services increase congestion cost marginally in the
short run (0.10 percent) but significantly reduce congestion cost by
(-3.5 percent) over BaU values in the long run. The results also show
that increase stock of road reduces demand for transport capital by
(-0.04) percent (Table 9). The reduction in congestion due to increase
stock of transport infrastructure has led to firms lower transport
capital (Table 9).
Environmental Benefits/Loss. This is measured by the net difference
in environmental costs between the Ball values and the simulated values.
We assume that this difference does not influence the demand or the
supply since these costs are not perceived by users or by producers and
doest not feed back into the model. This effect is calculated
exogenously in the model on the basis of change in transport services,
which are endogenously determined in the model. The results show that
reduction in demand for transport services and transport capital reduces
air pollution by (-2.05) percent (Table 10), which would affect health
status of the individuals positively. However, health indicators have
not been included in the present model to measure change in health
status.
Accident Cost
Accident cost is determined from the pre and post simulation values
of land transport service using equation 7 given in the model. The
results show that increase investment in transport sector (13) reduce
accidental cost by 1.2 percent over the BaU value in the long run and by
1.08 percentage points over the short run impact (Table 10).
Households Income and Poverty Incidence
Table 11 shows the impacts on income and household's consumer
price indices for the representative households. The income earned and
CPI faced by each representative household reduces at different degrees
depending on their base values of income and consumption.
The impacts on income poverty are positive in the short run as
income of both households increase, whereas CPI for rural households
remains constant but reduces for urban households. In the long run, the
negative on poverty incidence can be deduced as income decline more than
CPIs for both representative households (Table 10). But this will be
thoroughly analysed at the later stage.
7. CONCLUSION
It has been widely recognised that economies with better road and
communications network are more competitive and successful. A good
transport system should be comprehensive and sustainable--economically,
environmentally and socially. In view of this, government has started
NTC improvement programme. The aim of the NTC program is to improve
transport services, reduce costs of transportation which ultimately
concerned with reduction in the costs of doing business. In this paper,
the two objectives of the programs, have been focused; (1) Reduce share
of domestic transport and cost of non-factor services in the total value
of commodities. (2) Improve safety and reliability of transport
operations etc.
These objectives largely depend on public investment. However, this
type of government decisions requires policy makers to have a good idea
of the extra costs caused by the activity and how it should be
generated. This analysis include not only resource cost, but also the
cost associated with externalities such as congestion cost, accident
cost, (14) and the environmental COSTS. (15 )The transport users
completely pay for resource cost. But fuel emission and accident cost is
not perceived by the consumers and do not affect demand and supply of
services. But it has detrimental affects on human life. These effects
are estimated before and after the exogenous shock.
The results show that development of transport sector brings multi
dimension benefits and help to achieve the two key objectives of NTC
programme. Tax financed investment has reduced share of domestic
transport and cost of non-factor services in the total value of
commodities (first objective of NTC). It reduces transport cost
associated with passenger movement too. It has improved safety and
reliability of transport operations etc. by reducing environmental and
accident cost (second objective). It has positive impact on growth and
exports. The results show that tax financed public investment in
transport and related sectors renders benefits in the long run, whereas
in the short run it produces negative effect.
The reduction in cost associated with externalities shows that
development of this sector bring about not only economic benefits but
may also be helpful in reducing human poverty. However, this needs to be
modeled explicitly. The main policies comes out of this study is that
government should develop transport infrastructure for larger economic
benefits in the long run. Taxes can be used to overcome the problem of
resource constraint. The alternative way to finance the investment will
be the focus of the future work to find optimal policy to generate
financial resources. Government investment in transport services can
help to avoid output losses.
In reality air pollution and accident risks also affect consumption
choices. Such feed back effects--discussed in Mayeres and Regemorter
(2003)--will increase the usefulness of the model. The air and water
transport, are defined on the basis of input output table. No other
module for these two modes is incorporated for detailed analysis. Other
poverty targeted interventions such as schools, clinic nutrition
programmes and even credit extension depend on transport in one way or
the other. For instance, in developing countries, 40 to 60 percent of
people live more than 8 miles away from health facilities. Development
of transport infrastructure would also increase the benefit in terms of
human capital development. Thus this sector has huge benefits. Further
work is needed to unveil the total benefits of development of this
sector.
APPENDIX I
[FIGURE 1 OMITTED]
APPENDIX II
Table 1
Effects of Tax Financed Public Investment to Develop Transport
Services
Consumer Exports of Goods
Prices and Services
Short Long Short Long
Variables Run Run Run Run
Agriculture 0.00 -3.70 -0.23 3.60
Mining -0.88 1.89 -1.11 12.57
Food Manufactured -0.92 2.03 0.13 -0.91
Text and Leather 0.00 3.91 0.55 -2.17
Wood 0.00 0.75 0.00 3.58
Cement 0.00 -3.57 -0.12 10.96
Petroleum 0.00 3.80 -0.14 9.24
Transport Equipment 0.00 1.40 -0.01 2.11
Other Manufactured 0.00 1.97 0.00 0.00
Land-construction -1.01 0.00 0.00 0.00
Air-construction -1.01 -1.59 0.00 0.00
Water-construction 0.00 -1.59 0.00 0.00
Other-construction 0.00 -3.25 0.00 0.00
Transport-Land 0.00 -3.08 0.00 0.00
Transport-Air 0.94 -1.26 -1.45 0.74
Transport-Water 1.03 -13.16 -0.74 15.00
Transport-Other 1.02 -5.30 -0.34 5.32
Other Services 1.02 -3.94 0.00 0.00
Total 0.00 -0.75 0.11 0.06
Imports of Goods of Value-
Services added
Short Long Short Long
Variables Run Run Run Run
Agriculture 0.42 -8.61 -1.3 0.01
Mining -1.56 8.45 15.7 -1.69
Food Manufactured -0.03 -3.94 -2.2 0.11
Text and Leather -0.32 -1.58 -2.5 0.42
Wood 0.21 -0.55 3.1 0.09
Cement -0.28 -0.78 11.4 0.20
Petroleum 0.36 6.95 -2.7 -0.07
Transport Equipment 0.14 0.46 12.5 0.06
Other Manufactured 0.00 0.00 2.1 0.05
Land-construction 0.00 0.00 15.5 0.35
Air-construction 0.00 0.00 16.6 0.34
Water-construction 0.00 0.00 16.3 0.20
Other-construction 0.00 0.00 11.4 0.08
Transport-Land 0.00 0.00 -3.0 -0.06
Transport-Air 0.00 0.00 -0.6 -1.30
Transport-Water 0.00 0.00 14.1 -0.71
Transport-Other 0.00 0.00 -1.2 -0.07
Other Services 0.56 -10.94 -0.6 -0.06
Total 0.02 0.00 0.0 0.00
Labour
Demand
Short Long
Variables Run Run
Agriculture 0.0 -1.71
Mining -1.7 15.35
Food Manufactured 0.1 -2.59
Text and Leather 0.4 -2.86
Wood 0.1 3.73
Cement 0.2 10.93
Petroleum 0.0 -3.60
Transport Equipment 0.1 12.19
Other Manufactured 0.1 1.72
Land-construction 0.4 15.23
Air-construction 0.4 16.44
Water-construction 0.2 16.14
Other-construction 0.1 11.30
Transport-Land 0.0 -3.42
Transport-Air -1.3 -0.88
Transport-Water -0.7 13.91
Transport-Other 0.0 -1.75
Other Services 0.0 -0.92
Total 0.0 0.00
REFERENCES
Conrad, Klaus and Stefan Heng (2006) Financing Road Infrastructure
by Savings in Congestion Costs: A CGE Analysis. Mannheim University,
Department of Economics, Seminargebaude, Mannheim.
Dorosh. P, M. K. Niazi, and H. Nazli (2004) A Social Accounting
Matrix for Pakistan, 2001-02: Methodology and Results. A Background
Research Paper for the Pakistan Rural Factor Markets Study.
Downing, A. J. (1985) Road Accidents in Pakistan and the Need for
Improvements in Driver Training and Traffic Law Enforcement. In PTRC Summer Annual meeting, University of Sussex, 15-18 July 1985, Proc of
Seminar H. London PTRC Education and Research Services, 77-92. Overseas
Unit Transport and Road Research Laboratory, Crow Thorne Berkshire
United Kingdom.
Eachenique, Marcial and Marco Ponti (2005) Transport Investment and
Economic Assessment, University of Cambridge Department of Architecture,
EPRSC. Solutions, Sustainability of Land Use and Transport in outer
Neighbour hoods
Ellis, S. and J. L. Hine (1995) The Transition from Non-motorised
to Motorised Modes of Transport. ODA, Overseas Centre, Transport
Research Laboratory, Crowthorne Berkshire United Kingdom.
Mayeres, I. and K. Van Dender (2003) Modelling the Health Related
Benefits of Environmental Policies--A CGE Analysis for the EU Countries
with GEM-E3. (ETE Discussion Paper 2003 10). www.econ, kuleuven, ac.
Be/ew / academic / energmil / publications.
Mayeres, Inge and Proost Stef (2004) Testing Alternative Transport
Pricing Strategies: A CGE Analysis for Belgium. Paper Presented at the
conference on "Input-Output and General Equilibrium: Data,
Modelling and Policy Analysis", Brussel, Belgium.
Pakistan, Government of (2005) Economic Survey. Economic Advisor
Wing, Finance Division, Islamabad.
Pakistan, Government of (2007) Economic Survey. Economic Advisor
Wing, Finance Division, Islamabad.
Pakistan, Government of (2007) Pakistan: National Trade Corridor
Programme. SAR Regional Strategy Update.
Pakistan, Government of (Various Issues) Economic Survey. Economic
Advisor Wing, Finance Division, Islamabad.
Razzak, A. Junaid and Stephen P. Luby (1998) Estimating Deaths and
Injuries Due to Road Traffic Accidents in Karachi Pakistan, through the
Capture-recapture Method. International Epidemiological Association, UK.
27, 866-870.
Shah, Asad (2006) National Trade Corridor. Presented in Pakistan
Development Forum.
Siddiqui, Rizwana (2007a) Dividends of Liberalisation of
Agriculture Trade Trickle Down to Poor in Pakistan.
Siddiqui, Rizwana and Abdur-Razzaque Kemal (2006) Remittances,
Trade Liberalisation, and Poverty in Pakistan: The Role of Excluded
Variables in Poverty Change Analysis. The Pakistan Development Review
45:3.
Siddiqui, Rizwana, Abdur-Razzaque Kemal, and Rehana Siddiqui (2006)
Veronique Robichaud and Mohammad Ali Kemal "Trade Liberalisation,
Fiscal Adjustment, and Poverty in Pakistan: A CGE Based Analyses."
Unpublished paper, MIMAP-PhaseII, IDRC-Canada.
Siddiqui. Rizwana (2007b) Welfare and Poverty Implications of
Global Rice and Agricultural Trade Liberalisation for Pakistan. Chapter
5 in forthcoming book.
World Bank (2007) A Decade of Action in Transport--An Evaluation of
World Bank Assistance to the Transport Sector, 1995-2005. World Bank,
Washington, DC. http://www.worldbank.ord/ieg.
Comments
(1) The CGE model, like other mathematical models, has its inherent
limitations.
Most of the results are already built into the assumptions.
Therefore, the assumptions should be realistic.
(2) Assumptions like "air pollution is an increasing function
of transport facility" are not taking into account the costs of
congestion. (3) Many of the policy outcomes generated by the model is
more obvious.
(4) The analytical model is not exactly the dynamic CGE model. Some
revisions in the presentation may be necessary before publication.
Krishna Prasad Pant
NARDF, Kathmandu, Nepal.
(1) Accident problems cost about 2 percent of GDP [World Bank
(2007)]. WHO points out that road safety is very important that can be
reduced by investing in signs, training programme for drivers and
improving the logistic. It smooth traffic flow, reduce frequency of
accident, break down of vehicles and non-predictable situation.
(2) On average, it is composed of 18 products.
(3) An amount of Rs 9.28 has been allocated for the railways during
2004-05 [Pakistan (2005)]. The development of railway includes
manufacturing of 16 diesel electric engines, manufacturing of 66
coaches.
(4) The country has about 40 building material industries, which
support investment and growth environment.
(5) The reason may be inadequacy of emergency health facilities.
(6) For detail see Siddiqui (2007a, 2007b), Siddiqui and Kemal
(2006), Siddiqui, et al. (2006).
(7) For a detailed discussion on this module, see Conard and Heng
(2006).
(8) It is predicted that by 2020 road accidents will be the third
largest contributor to the global burden of mortality and injury.
(9) The storage include, oil and gas pipelines, transport handling,
and services establishments and communication services rendered by
Pakistan post office, Telecom, FFV, Radio etc.
(10) The construction sector covers all repairs, addition,
alteration and demolishing activities carried out in the economy by
households, private bodies, public institutions and the general
government. New construction work and repair and maintenance of
buildings and civil engineering work.
(11) Majority of these services are used for export services, which
need to be modeled in further detail.
(12) The demand for these goods fell because of decline in
households' consumption that indicates that welfare deteriorates.
This can be explored further by changing the closure of the model.
(13) Traffic lights, yellow marks on the road etc.
(14) It is predicted that by 2020 road accidents will be the third
largest contributor to the global burden of mortality and injury.
(15) Accident and the time cost have double dimension cost born by
the users and the cost born by the other users on the road. At the time
being it is not explicitly broken down into these components.
Rizwana Siddiqui <rizwana_599@hotmail.com> is Research
Economist at the Pakistan Institute of Development Economics, Islamabad.
Table 1
Land Transport in Pakistan
Road
Road Vehicles Traffic
(l) (2) Congestion=
col 2/col 1
000 km No. in Mln
Year
1989-90 162.4 2 12
1994-95 207.7 3 14
1999-00 248.3 4 16
2004-05 260.0 6 23
Year 1995 1996 1997
C02 * Emission
Metric Tons per
Capita 0.69 0.75 0.73
Railways
Route Passen- Freight Freight Loco- Freight
gers Carried Tonne motives Wagon in
'000'nos
000 km million Million Km Mln Nos. Nos.
Year Tonne
1989-90 8.8 84.9 7.7 5.7 753
1994-95 8.8 67.7 8.1 6.7 678 30.1
1999-00 7.8 68.0 4.8 3.6 597 23.9
2004-05 7.8 75.7 6.1 4.8 592 21.6
Year 1998 1999 2000 2001 2002 2003
C02 * Emission
Metric Tons per
Capita 0.74 0.75 0.76 0.78 0.75
Source: Pakistan (Various Issues).
* World Development Indicators (2006).
Table 2
Pakistan International Airlines Corporation
Revenue Revenue Revenue
Km flown Hours Passengers Available
000 Flown Carried 000 Seats
Year (Mln) 000 Mln Bln Km
1989-90 62.6 120.9 5.1 14247.
1994-95 72.5 134.7 5.5 15848.
1999-00 75.9 134.6 5.1 18265.
2004-05 80.7 131.3 5.3 20348
Operating
(in Million of Rs)
Year Revenue Expenditure No. of Planes
1989-90 16412 15728 43
1994-95 25417 24199 47
1999-00 36860 39214 46
2004-05 61308 61175 42
Source: Pakistan (Various Issues).
Table 3
Transportation of Goods and Services (Million of Tones)
Cargo at Karachi Port
Year Total Import Export No. of Shipping Vessels
1989-90 19.1 15.0 4.1 28
1994-95 23.1 17.5 5.6 15
1999-00 23.8 18.1 5.6 15
2004-OS 28.6 22.1 6.5 14
Source: Pakistan (Various Issues).
Table 4
Structure of SAM
Sectors in Original SAM Disaggregation Data Sources
1. Transport l. 1. Land 2. Air, Supply and Use Table
3. Water, 4. Other for 1990.
2. Petroleum 2. 5. Petroleum SAM 1974-75 SAM
1984-85
3. Construction 3. 1. Land National Account of
infrastructure [Road Pakistan, Pakistan
and Rail tracks], 2. Integrated Household
Ports, 3. Air ports, Survey(PIHS)
4. All other
construction
4. Other Manufacturing 6. Transport
equipment, 7. Other
manufacturing
Table 5
The Cost Structure of Transport Services
Sectors Land Transport
(Road and Air Water Other
Railway) Transport Transport Transport
Agriculture 0.11 0.00 0.00 0.00
Mining 0.04 2.73 5.39 5.32
Food Manufactured 0.00 0.45 0.00 0.01
Text and Leather 0.14 0.27 0.16 0.33
Wood 1.86 0.23 0.04 0.01
Cement 0.01 0.01 0.02 0.06
Petroleum 57.54 45.11 46.56 1.52
Transport Equipment 6.29 0.09 2.22 7.96
Other Manufactured 16.24 37.57 0.53 57.26
Land-construction 2.19 0.00 0.00 0.00
Air-construction 0.00 0.83 0.00 0.00
Water-construction 0.00 0.00 1.48 0.00
Other-construction 0.00 0.00 0.00 6.94
Transport-Land 0.01 0.02 0.05 0.74
Transport-Air 0.02 3.36 0.15 0.52
Transport-Water 0.00 0.00 0.00 0.19
Transport-Other 0.06 1.29 0.91 1.04
Other Services 15.48 8.03 42.50 18.10
Total 100 100 100 100
Capital 39.2 58.4 82.0 30.2
Labour 60.8 41.6 18.0 69.8
Total 100 100 100 100
Table 6
Cost Structure of Production Activities
Transport Other Value-
Sectors Services Inputs added Total
Agriculture 3.50 39.06 57.43 100
Mining 10.11 15.31 74.58 100
Food Manufactured 2.26 71.15 26.59 100
Text and Leather 3.82 74.78 21.40 100
Wood 4.25 59.46 36.29 100
Cement 3.25 41.78 54.96 100
Petroleum 3.02 77.62 19.36 100
Transport Equipment 8.24 37.51 54.25 100
Other Manufactured 4.69 59.62 35.69 100
Land-construction 2.77 59.97 37.26 100
Air-construction 0.00 61.68 38.32 100
Water-construction 0.00 61.72 38.28 100
Other-construction 0.02 46.86 53.13 100
Transport-Land 0.04 44.26 55.70 100
Transport-Air 4.26 86.87 8.88 100
Transport-Water 0.27 24.38 75.35 100
Transport-Other 0.46 18.17 81.37 100
Other Services 5.42 27.18 67.39 100
Total 3.74 46.55 49.70 100
Agriculture 3.74 46.55 49.70 100
Table 7
Demand for Transport Services (%)
Rural Urban Rest of the
Households Households World Total
Transport-Land 50.26 49.74 0.00 100
Transport-Air 5.50 15.58 78.92 100
Transport-Water 4.59 4.80 90.61 100
Table 8
Macro Effects of Higher Public Investment in Transport
(Variation Over BaU)
20 Percent Increase in Public Investment in Transport Infrastructure
Financed by Consumption Taxes
Variables Short Run Long Run
Out Put 0.04 -0.04
Value Added 0.00 0.02
Consumer Price 0.00 -0.75
GDP Deflator 1.02 -8.46
Intermediate Demand 0.07 -0.10
Freight Transport Cost
Transport-Land 0.24 -7.77
Transport-Air -0.001 -3.24
Transport-Water -0.16 0.29
Passenger Transport Cost
Rural 0.05 -5.74
Transport-Land
Transport-Air 0.11 -7.74
Transport-Water -0.67 1.90
Urban -0.18 -3.2
Transport-Land
Transport-Air -0.32 -4.93
Transport-Water -1.07 4.55
Trade
Export 0.11 0.06
Imports 0.02 0.00
Wage Rate 1.02 -8.4
Returns to Capital 0.00 -9.4
Table 9
Cost of Infrastructure Development-Variation over BaU Path
Demand for Construction Goods
Variables Short-run Long-run
Wood 0.10 2.74
Cement 0.20 11.36
Petroleum -0.20 -1.74
Transport Equipment 0.24 9.17
Other Manufacturing 0.11 1.12
Transport Capital (Optimal) 1.7 -0.04
Table 10
Externalities
Externalities Short Run Long Run
Congestion Cost 0.10 -3.50
Pollution Cost -0.12 -2.05
Accident Cost -0.07 -1.15
Table 11
Households Income and Welfare Indicators
Short Run Income CPI Poverty
Rural Households 1 0 Reduce
Urban Households 1 -1 Reduces
Long Run
Rural Households -8.2 -1.5 Increase
Urban Households -7.9 -1.5 Increase