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Acknowledgements My supervisor, Professor V. Seshamani, your guidance extends from academics to real life
experiences and am confident to succeed.
My fellow students of the Economic Policy Management 2011/2012 academic year cohort, your
support and competitiveness always made me strive to produce the best out of my capabilities.
2
Dedication
To my wife Viviane and daughter Thabo, your support and confidence in my efforts are the pillars of my inspiration.
3
Abstract The Railway Sector has shaped the development pattern of Zambia. Historically, Zambia was
positioned as a source of copper which was transported to the coast (Port of Durban) via railway
specifically constructed for this purpose. Today, most is not all of Zambia’s cities are developed
along the line of rail and most of them, including the capital city Lusaka, started as simple
railway sidings.
In the Sixth National Development Plan (SNDP) 2011-2015, the Government of the Republic of
Zambia (GRZ) has cogently raised concern on the status of transport infrastructure including the
deteriorated state of the main railway lines: Railway Systems of Zambia (RSZ) under a 20 year
concession from 2003 and the Tanzania Zambia Railways Authority (TAZARA). In this regard,
GRZ has proposed to rehabilitate and maintain the two main railway lines and also to develop
new railway spurs.
This report unveils the challenges and provides a justification for the case for railway transport
development in Zambia. It comprehensively analyzes GRZ economic policies and synergy with
Transport sector policies especially with a view to realize the lag in railway transport
infrastructure and how it can be improved. I show the importance of the railway industry to
Zambia in terms of Cost Benefit Analysis based on broad and specific appraisal guidelines being
applied universally and those specific to Zambia. Further, I advocate for policy reforms to
revitalize the railway sector by making them more relevant to the current economic scenario.
My arguments and analyses presented in this research are founded on empirical secondary data
and supplemented by primary data collected from the railway policy formulators, implementers
and operators. The Secondary data includes railway statutes, public policy and the international
norms of conducting the railway business. Overall, the report provokes Government to take up
its role in a liberalized economy: protecting strategic public infrastructure (and) services and also
provision of the desired public goods.
GRZ must have an inter-modal transport network which efficiently serves as a means to
economic development in light of the risen volumes of imports and exports and transiting goods
in Zambia. This is the rationale behind the proposed development of the National Transport
Infrastructure Master Plan as captured in the SNDP and the railway sector serves as one of the
main components of this plan.
My report endeavors to develop the most workable financing models for railway infrastructure
development.
4
Declaration This work is original and has not been submitted previously for any academic purpose.
All secondary sources are acknowledged.
Signed……………………………………………………………………………………
Date………………5th
October 2012……………………………………………
5
Certification
I declare that this thesis is from the student’s own work and efforts and where he has used
sources of information, all have been appropriately acknowledged.
This policy paper has been submitted with my approval
Supervisor: Professor V. Seshamani
Signature: …………………………………………………………….
Date: ……………………………………………………………..
6
Contents Acknowledgements ....................................................................................................................................... 1
Abstract ......................................................................................................................................................... 3
List of Acronyms ............................................................................................................................................ 7
List of Tables ................................................................................................................................................. 8
Annexure ....................................................................................................................................................... 9
List of Maps ................................................................................................................................................. 10
1.0 Introduction .................................................................................................................................... 11
1.1 Background ....................................................................................................................................... 11
1.2 Rationale for the Research ................................................................................................................ 11
1.3 Problem ............................................................................................................................................. 12
1.4 Objectives.......................................................................................................................................... 12
1.5 Research Question ............................................................................................................................ 12
1.6 Hypotheses ....................................................................................................................................... 12
2.0 Literature & Empirical Framework .................................................................................................. 12
3.0 Research Methodology ................................................................................................................... 25
3.1 Study Design................................................................................................................................ 25
3.2 Research Instruments ................................................................................................................. 26
3.3 Data Collection Procedure .......................................................................................................... 26
3.4 Data Analysis ............................................................................................................................... 27
4.0 Results ............................................................................................................................................. 28
5.0 Discussion ........................................................................................................................................ 47
6.0 Conclusion ....................................................................................................................................... 49
7.0 Recommendations .......................................................................................................................... 50
8.0 Bibliography ................................................................................................................................... 52
9.0 Annexure ......................................................................................................................................... 53
Annex 2: Annual Financial Data: ZRL & RSZ 1994-2011 .......................................................................... 55
Annex 2.b: Adjusted ZRL &RSZ Financial Data (1995-2010) ................................................................... 56
Annex3: Unit Root Test -Stationarity of regression variables ............................................................. 58
Annex 4: Regression results for using data in Annex 2b ......................................................................... 62
7
List of Acronyms
AoS Appraisal of Sustainability
ARU African Railway Union
CBA Cost Benefit Analysis
EU European Union
GRZ Government of the Republic of Zambia
JICA Japan International Cooperation Agency
ROADSIP Road Sector Investment Program
RSZ Railway Systems of Zambia
SNDP Sixth National Development Plan
TAZARA Tanzania Zambia Railways Limited
UK United Kingdom
8
List of Tables Table 1: List of prioritized SSA Corridors which transverse Zambia
Table 2: ROADSIP II cash inflows in US$ over a period of 10 years
Table 3: Organs of the Road Management Initiative
Table 4: Respondents: Institution, Designation, Age, experience in organization
Table 5: Respondent Institution; Transport focus; Railway Support
Table 6: Respondents Institution: Appraisal guidelines for railways, considerations for CBA
Table 7:Respondent Institution; How railway projects are appraised in Zambia; Are the GRZ
appraisal guidelines?
Table 8: Name of Institution: What is the value of railway efficiency to the Zambian economy?
Table 9: Respondent Institution; regional significance of Zambia railway network
Table 10: Respondents’ prioritized transport corridors
Table 11: Respondent Institution; Zambia railway policy sufficiency and relevance
Table 12: Respondent Institution; Strategic nature of the railway sector institutions in Zambia
Table 13: Respondent Institution; ownership of railway infrastructure in Zambia
Table 14: Pro-competitiveness of the railway policy
Table15: Goods fit for Railway Transportation
Table 16: Railway traffic regulatory policy in Zambia
Table 17: Respondent’s financial support to railways
Table 18: Options on how the railway sector can be revamped in Zambia
9
Annexure Annex 1: Questionnaire used in research
Annex 2a: Financial data on ZRL and RSZ 1994-2011
Annex 2b: Adjusted Financial data on ZRL and RSZ 1994-2011
Annex 3: Unit Root test of Stationarity for the dependent and explanatory regression variables
Annex 4: Regression results for using data in Annex 2b
10
List of Maps 1. Map 1: Proposed railway projects in Zambia
2. Map 2: Southern Africa Transport Corridors
11
1.0 Introduction
1.1 Background Transport is critical for development. Inappropriately designed transport strategies and
programmes result in networks and services that are not responsive to the needs of the users,
harm to the environment and exceed the available public finances. In the urban setting, the
quality of transport infrastructure and public transport service influence the location of firms and
individuals. The productivity of the labour market and the costs at which it is obtained are also
factors affected by quality transport infrastructure and service.
Railway transport infrastructure is ideally meant for bulk and heavy goods carriage. In this
respect, it is second to water transport in the context of the big vessels which ply the oceans and
seas transporting massive goods between continents. In Zambia, railway transport infrastructure
was traditionally built for transportation of copper being mined within the Copperbelt area to the
coasts of Africa for trade purposes.
Raballand and Whitworth (2011) recently attempted to find out if it is worthwhile for the
Government of Zambia to invest in the railways considering the shift in trade traffic from the
railways to the road. They argued that this shift in trade transport mode is because the road is
more competitive than the railways in terms of transit times, security, reliability, safety and even
offers better rates per ton kilometer. The shift from railway to road come about after the
privatization of the mines which saw GRZ ‘hand off’ policy on regulating which transport mode
to use for transport copper and related goods.
My research builds a case for railway transport development in Zambia. It is a pragmatic
positivist approach which comprehensively analyzes GRZ economic policies and synergy with
Transport sector policies. I essentially identify the lacunae in railway transport policy and
implementation strategy thereby proposing a Railway Sector Management Plan, the strategic
plan for development of the respective sector.
1.2 Rationale for the Research This research study has not been undertaken before in Zambia. However, a related study:
“Should Zambian Government Invest in Railways” (2011), was undertaken by Gael Raballand, a
Senior Economist with the World Bank, and Alan Whitworth, a Technical Advisor to the Zambia
Institute of Policy Analysis and Research. Their research was undertaken to critique GRZ
proposed railway investments. This is on the assumption that the road sector performance and
service delivery is too competitive for the railways to be revamped. (Road has replaced railway
as the transport mode for trade.) This is despite the current high cost of road maintenance &
rehabilitation.
This study builds on this knowledge and presents insight on the important role of policy review
and institutional setup for policy implementation. I also advocates for role of the state in a
dynamic and competitive liberalized economy with respect to transport infrastructure.
12
1.3 Problem There has not been any policy comparative study on surface transport modes in Zambia. Railway
Transport infrastructure is in a poor and redundant state relative to road transport infrastructure
despite their essential complementary role as surface transport modes for social and economic
development facilitation.
Transport policy and its implementation should not be an end in itself but a strategic means to an
end. As noted in the Zambia National Transport Policy (2003), there is need for an efficient
transport system to stimulate production and development by linking production to demand,
employment generation and income creation.
1.4 Objectives 4.01 To review the railway transport sector policy reforms and their impact on
operations, profitability and employment levels in the last 40 years; I have
considered
4.02 To investigate the institutional structures and/or strategies for policy
implementation in the railway transport sector in comparison to the road sector;
4.03 To establish the plausible financiers for transport infrastructure development.
1.5 Research Question What are the underlying reasons for poor performance of the railway sector in Zambia?
1.6 Hypotheses 1.61 The feasibility of Zambia railway sector development is not only at national level
but regional level as well;
1.62 Publicly owned railway infrastructure is key for viability and competitiveness in
operations of the railway sector; and
1.63 Deliberate or direct investment and institutional restructuring are relevant for
revamping the railway sector in Zambia.
2.0 Literature & Empirical Framework The Literature reviewed for this research builds a case for existence of the railway sector in
Zambia. I have reviewed recent railway sector developments from a global theoretical
perspective and then evaluated empirical research cases so as to benchmark my understanding
and analysis of the railway scenarios relative to the Zambian case. The following literature is
reviewed and serves as points of analytical reference.
2.1 Appraisal of Railway Performance Projects - A UK Approach (2005)
This document is strategically reviewed because it presents the analytical framework and
guidance used to appraise and select railway performance projects. It recognizes the fact
13
that projects compete for scarce resources hence the need for a business case to be raised
which usually involves a form of investment appraisal. For government funded projects
the most common appraisal technique is a cost-benefit analysis (CBA) (also called an
economic appraisal because it seeks to quantify, value and monetize unpriced economic
benefits)
Appraisal guidance establishes broad guidelines and introduces consistency in the
conduct of CBAs. It helps government to prioritize and select projects across a range of
industries. In the UK the Department of Transport adopted a multi-criteria analysis
framework for the appraisal of projects and policies. For the Railway Sector, in
particular, the UK has a Strategic Railway Authority which has also developed its own
guidance based on the broad appraisal framework and the Department of Transport
adopted guidance but is directly concerned with appraisal techniques in the railway
industry.
There is need to consider a number of appraisal guidance documents that exist in the
public sector, several of which impact directly on the investment appraisal of railway
projects and policies. There is also a need for specific appraisal guidance on valuing
railway benefits, e.g, in the UK generalized journey time and value of time are the two
most important economic concepts used to measure the non financial benefits of railway
performance improvements. What appropriate measurable factors can I similarly consider
for Zambia?
Comprehensive appraisal guidance on railway projects is developing with some speed
and sophistication in some countries like Australia and the Netherlands. Is it plausible for
Zambia?
According to this report, “An application of current appraisal guidance” as a
recommendation for railway infrastructure investment might change under past and
present appraisal guidance for two main reasons, namely:(i) Changes in policy and
Government objectives can lead to changes in appraisal practices which will, in turn, lead
to new appraisal guidance; and (ii) New appraisal guidance can also impact the appraisal
outcome and the recommendation that would be given to Ministers.
The implications of the UK case study which need to be considered in designing
appraisal guidance are as follows:
The simplicity and user-friendliness of the guidance (consistency within and between
guidance documents)
The risks of having formal guidance in place e.g. distortions will exist in the market
for public sector funds if some projects are assessed using the official guidelines
while other projects are appraised using other methods
The importance of establishing value for money based on consistent guidance
The costs of implementing the appraisal guidance e.g. will the railways be able to
perform the cost-benefit analysis without consultancy resources
14
The costs of compliance with the guidance e.g. will the Government be able to
enforce the guidance without performing ex-post evaluations or formal audits
My research probes the railway policies in Zambia and determines the prescribed
guidelines for infrastructure investment in reference to practice at international level.
2.2 European Railway Research (2008)
The overall objectives of this research where to Develop “safer”, “greener” and
“smarter” transport systems for: respecting environment and natural resources the benefit
of citizens and society (2) Secure and develop the competitiveness of European industry
in the global market: By Dennis Schut, EU Research Manager
In this research I appreciate, in addition to environmental concerns, the encouraging and
increasing modal shift and decongesting of transport corridors through efficient interfaces
between transport modes; Ensuring sustainable urban mobility through new transport and
mobility concepts for passengers ensuring accessibility for all, Intelligent mobility
systems and multi-modal interfaces for transportation of passengers; Improving
integrated safety and security for surface transport systems by design; Strengthening
competitiveness in industrial processes through advanced and cost effective infrastructure
construction, maintenance and monitoring, competitive surface transport products and
services and competitive transport operations and innovative product concepts;
The research also highlights important cross-cutting activities including: Stimulating of
International Cooperation within Surface Transport Research; Stimulating International
Cooperation with Latin American countries in developing sustainable freight transport
systems, Shaping the new generation of sustainable surface transport mobility for Europe.
This research serves as a guide in considering the importance of regional and
international benefits of Zambian railway infrastructure developments and not only
national considerations.
2.3 Applied Transport Economics: Policy Management and Decision making (2005)
This is theoretical text on transport economics. I have used it to guide and inform my
arguments from a transport professional discipline perspective. The book advises on
policy management and decision making for transport sector. It considers (1) Transport
market dynamics including: market demand, elasticity of demand, the supply of transport,
pricing policy, cost levels and structure for railways, forecasting transport demand,
revenue & expenditure; (2) Public policy including: transport economic appraisal
techniques, economic appraisal valuation of elements, Public Private Partnership (PPP)
investments, funding an integrated transport policy, consideration between Regulation &
Competition; and (3) Transport and development which considers the linkage between
transport and economic activities.
15
2.4 India Railway Sector Investment Program (March 2009)
This is a report prepared by Scott Wilson PLC and it presents the Hospet - Tenaighat
Track Doubling Railway Investment Program approved for financing by the Asian
Development Bank. The relevance of this report is in the nature and purpose of the
Hospet – Tenaighat Track which was then being proposed for upgrading by doubling.
“This section primarily caters to the inland transport of Iron Ore and Iron and Steel for
export with Coal and Fertilisers imported through Mormugao Port on the west coast and
Cement traffic primarily from South Central Railway. Besides freight traffic, there are
also a substantial number of passenger trains on the project section. The bulk of traffic
moving across the project section is through traffic originating and terminating outside
Hospet to Tenaighat for/from Goa and other ports on the west coast, south of Goa. The
rail line is now carrying 14.25 million tones expected to reach 27 million tones in 2013-
14. It is therefore proposed to double the single line section between Hospet and
Tenaighat.” (Scott Wilson Railway Limited: 2009,10)
I have realized that that aims of this project (to enhance capacity and in doing so
increasing speed and operational efficiency of the project section whilst also ensuring that
the project impact positively on the local population and the environment) and the nature
and purpose of the railway line are akin to the railways in Zambia. The report emphasizes
the need for this proposal to be tune with the policies of the Government of India.
According to an extract from the website of the Department of Transport of the UK, the
Government’s role in the running of the railways is to provide strategic direction and to
procure rail services and projects that only it can specify. (http://www.dft.gov.uk/rail)
This Indian case is akin to the railway sector in Zambia. It has provoked my research to
query the strategic role of Government in railway infrastructure development and
performance. I ask the question: What are the primary government railway policies that
need to be in place for the sector’s sustainability?
2.5 Rail development in Africa: Stakes and prospects, objectives and missions of the
African Rail Union (2006)
This is a report by the specialized institution of the African Union responsible for rail
development in Africa. It aims at studying ways and means of unifying rail networks;
standardization of equipment and rolling stock; Interconnection of rail networks;
Coordination between railway and other means of transport; and improvement of rail
performances and quality services.
The African Railway Union (ARU) advocates that the importance of rail transport can be
gauged from the policies and programmes implemented by African governments,
Regional Economic Communities and Specialized institutions at regional and continental
level. As a member, Zambia – Kabwe Center, had been retained in 1976 within the
16
framework of at the Transport and Communications in Africa decade (1978-1988) for
railway human resource development.
“The politico-economic developments that occurred at the Southern African level with
Angola, Namibia, Zimbabwe gaining their independence and the eradication of the
apartheid system in South Africa brought new data in the choice of the center and the
need for obtaining an agreement on the site for the center between the various Southern
African networks. The Union proposes to launch a broad consultation with the networks
concerned in collaboration with the Southern African Railway Association (SARA).”
(Ibid 2006:10)
This report presents insight into the concerted efforts which Africa puts on the
revitalization and operations of the railway networks of the continent. Can the human
resource development projects and other initiatives that were under this organization be
reconsidered? What is the current continental opinion over railways? Is Kabwe still a
plausible centre of railway academic promulgation?
2.6 Preparatory Survey for Southern Africa Integrated Regional Transport Program
(March 2010)
This is a research undertaken by JICA, which perceives Africa as being at an economic
stage which Asia was 15 years ago. The study realizes the region’s abundance of natural
resources and its productive agricultural sector which is reported to have led to
exponentially increased trade with emerging market partners such as China, India, and
Brazil. However, while the region’s balance of trade is moving in a favorable direction,
inadequate transport (as well as energy and information and communications technology)
infrastructure poses a major bottleneck to the region’s achieving its full growth potential.
Of interest is the second of three research study objectives: To formulate a holistic view
of regional infrastructure creation, which is necessary to materialize the growth
scenarios, and clarify the issues to be addressed mainly from an assessment of the
regional transport sector.(Evaluation of the potential of Southern Africa regional
transport development corridors)
This study covered eight countries of the Southern African Region: Angola, Botswana,
Malawi, Mozambique, Namibia, South Africa, Zambia, and Zimbabwe; in addition, it
also covered the Democratic Republic of Congo and Tanzania, which play an important
role due to their direct linkages to the Southern African Region.
For the Railway sector, this report proposes an overall strategy of infrastructure
development following operational improvements and strengthening of international
competitiveness of products through reductions in transport costs.
The JICA Study Team analyzed the potential for integration of essential elements along
the 18 corridors of southern Africa in terms of:
17
(i) Contribution to growth scenarios: Corridor-based “contribution” to each of the three
growth scenarios: Referring to the condition of each corridor and the geographic
distribution of resources, evaluate each corridor based on its contribution to realizing
the growth scenarios. That is evaluation of Corridors on Contributions to Growth
Scenarios
(ii) Cost-benefit Analysis: Efficiency of corridor development: Referring to other
indicators such as traffic volumes and the cost of implementation, evaluate efficiency
of corridor development based on a benefit-cost analysis. Although this evaluation is
relative, after the standardization of the outcomes, corridors with higher efficiency
than average should be selected as prioritized corridors. Benefit/Cost Score = (Traffic
Score) ×(Benefit Score) ÷(Cost Score)
(iii)Socio-economic impact: Ease of corridor development implementation by analysis of
each country traversing the corridor by considering: Demographic Potential, Scale of
Economy, Governance and Business Environment in order to propose eight candidate
growth corridors.
In accordance with the Fourth Tokyo International Conference on African Development
(TICAD IV) held in May 2008 it is necessary to consider both internal and external
elements in order to realize the impact of a corridor development program in terms of
accelerating the growth of the region, with budgetary constraints however, it is necessary
to optimize resource allocation and prioritize corridor development programs in order to
maximize the effect on regional economic growth.
In this report, the following corridors were deemed as priority as ordered: Maputo
Corridor, North–South Corridor, Dar es Salaam Corridor, Beira Corridor, Nacala
Corridor, Trans-Caprivi Corridor, Trans-Kalahari Corridor, and Lobito Corridor. Of these
corridors Zambia is traversed four of them (North-South, Dar es Salaam, Nacala and
Lobito corridors)
Below is an extract from the report, which presents the details with respect to the
corridors on which Zambia is traversed and plays a significant role :
18
Table 1: List of prioritized SSA Corridors which transverse Zambia Corridor
Name
Potential
Resources
Countries
Traversed
Existing Condition / Bottlenecks
1. North-South
Corridor
Maize, Copper South Africa,
Zambia,
Zimbabwe,
Botswana ,
DRC
- The only missing road (bridge) link is currently at the
Kazungula border crossing.
- Long border crossing time (1–2 days) at Chirundu and
Beitbridge addressed by ongoing projects.
- Long border crossing times at Kasumbalesa, between
Zambia and the DRC
- Railway operated inefficiently due to issues related to
“hard” infrastructure and operations.
2. Dar- es
Salaam
Corridor
Cobalt,
Magnesium,
Copper, Seed,
Cotton,
Cassava,
Sugarcane,
Maize
Tanzania,
Malawi,
Zambia
- Nakonde/Tunduma border crossing busy with long border
crossing times (4-5 days).
- Deterioration of road conditions caused by heavy mineral
transport
- Decreasing rolling stock availability on the TAZARA
Line
- The long clearance time at the Port of Dar es Salaam
- Long dwell time at the container terminal (26 days)
3. Nacala
Corridor
Copper, Oil
bearing
plants, Seed
Cotton,
Cassava,
Sugarcane
Mozambique,
Malawi,
Zambia
-Trunk route to the port currently serves low traffic
volumes.
-Most road sections unpaved and/or have high roughness
levels.
-Low railway operation speed and capacity due to track
deterioration.
-Traffic at the port is expected to increase rapidly beyond
its current capacity.
4. Lobito
Corridor
Copper Angola,
DRC,
Zambia
- Rehabilitation required for Lobito rail link linking the
port with the DRC/Zambia Copperbelt.
- Repair and development of mines following the extended
conflict in the DRC has been hampered by the lack of
reliable transport to the sea.
The JICA Study Team identified potential programs for improving the prioritized corridors
specifically:
Road: Formulation of systems to prevent road deterioration; Improvement of the regional road
network
Railways: Infrastructure development following operational improvements; Strengthening of
international competitiveness of products through reductions in transport costs
Ports: Simplification of port procedures aiming at a single window approach; Development of
the capacity of container terminals
Border Posts: Development of legal framework and procedures for railway OSBPs;
Infrastructure and system improvements through OSBP implementation
Transport facilitation: Addressing non-physical barriers to cross-border transport
19
2.7 Road Sector Investment Program (ROADSIP) & Road Sector ACT of 2003
RoadSIP is a deliberate Investment Program which saw to the rehabilitation and,
restructuring of the Road Sector through policy reforms. It resulted into dismantling of
the Road Sector Institutions making them more specialized to specific function (Road
Development Agency, National Road Fund Agency, Road Transport and Safety Agency
and the National Council for Construction.)
The Road Sector is now evidently argued to be the most competitive mode of transport in
Zambia and the entire sub Saharan Africa. The mantra of the RoadSIP program includes
themes advocated for in most if not all African countries. Institutions like the Sub
Saharan Africa Transport Policy Program endeavor to realize the harmonious
implementation of this program in all these respective countries. It is a robust program
which not only includes policy reforms but institutional restructuring and finance
mobilization with guaranteed donor technical monitoring and evaluation at all times.
ROADSIP is a 15 year programme which, commenced in 1998 and will end in 2013 but
divided into two phases, namely ROADSIP I and II. Phase I started in March 1998 and
ended in 2003. The second phase started in 2004 and will end in 2013. The original
estimated budget for ROADSIP II was US$860 million but due to the large network, the
programme was extended to 10 years and costs also went up to US$1.6 billion.
ROADSIP II would first concentrate on roads that were identified in ROADSIP I, but had
no funding sources and as such, they could not be maintained.
GRZ is intends to implement ROADSIP II within the same economic, institutional and
legal framework as outlined in ROADSIP I. The objectives have been improved after
taking into account lessons learnt from ROADSIP I. ROADSIP II will address poverty in
rural areas and gender imbalance through the use of labour based methods and packaging
of contracts, maximum involvement of road users, transparency and accountability in
tenders and needs based management and budgets.
In view of the shortfalls in ROADSIP I, consultants were commissioned in 2003 to
finalize the ROADSIP II Bankable Document and Financial Strategy. Government and
Cooperating Partners approved these documents in 2003, below is the committed
financing framework for the program
20
Table 2: ROADSIP II cash inflows in US$ over a period of 10 years:
Internal Funding Total first
5 years
Total in 10 yrs
1. Government Funding 113,793,750 259,431,250
2. Fuel Levy 162,387,305 272,973,158
3. Donation of Excise Duty 5% 40,698,573 77,560,524
4. License Fees 186,473,335 272,686,669
5. Road Haulier tariff 53,104,238 77,656,238
6. International Transit charges 14,364,202 27,374,302
Subtotal 570,821,408 987,682,151
External Funding
1. World Bank 53,900,000 130,900,000
2. NORAD Funding 17,500,000 42,500,000
3. European Union 80,500,000 195,500,000
4. JICA 21,000,000 51,000,000
5. BADEA/Kuwait 17,500,000 42,500,000
6. KfW Germany 17,500,000 42,500,000
7. DANIDA 38,080,000 106,480,000
8. ADB 25,000,000 35,000,000
Subtotal 270,980,000 646,380,000
Grand total 841,801,402 1,634,062,141
Internal contribution 67.81% 60.44% Source: Government of the Republic of Zambia
The Road SIP II is management by the Road Management Initiative which operates
under for organs, guiding the operations of the implementing specialized road agencies:
The four organs being:
Table 4: Organs of the Road Management Initiative
Committee Members Meeting Schedule Committee of Ministers on RMI Chairman: Minister of MCT
Members Cabinet Ministers and
Deputy Ministers
Support Staff: Permanent Secretaries,
Officials and Other Staff
At least 4 times a year and
as and when necessary
(extra ordinary meetings)
Committee of Permanent Secretaries
on RMI
Chairperson: MCT PS
Members other PSs (from MoFNP,
MWS, MLGH, MTNR, MEW,
MACO, MoJ) and other support staff
Quarterly and as and when
necessary
Road Sector Investment Program
(ROADSIP) Steering Committee
Chairman MCT: Deputy Ministers
Members Component Managers and
other support staff.
Monthly
21
2.8 Zambia National Transport Policy (2003)
This is the main transport policy document in Zambia. For the railway sector, the Policy
states:
“ In order to address the problems of rail transport the Government shall focus on the
following issues:-
(a) streamlining of the railway organization, reforming management and upgrading
essential railway labour to improve labour productivity;
(b) encouraging private sector involvement in rail management through concessioning in
order to improve railway efficiency;
(c) ensuring that the bulk of cargo transportation is carried by rail in order to reduce
pressure on the road network;
(d) ensuring the preservation of investment and the continuous improvement of rail
infrastructure;
(e) expanding and strengthening of government capacity to develop supportive
regulatory and investor-friendly legislation, monitor compliance with policies and
legislation; and
(f) standardizing practices and procedures in line with SADC member states to provide
seamless and predictable service throughout the region.
For this purpose the goals, policy objectives and strategies of rail transport are detailed
below:
Goal: To provide a competitive, cost- effective, commercial, efficient and market-driven
railway transport system.
Policy Objectives: In order to meet the above stated goal, the policy objective shall be to:
(a) maximize railway capacity;
(b) reduce railway deficits and government funding burdens;
(c) encourage the functioning of railways as a market-sensitive commercial enterprise;
(d) enhance inter-modal transport competition; and
(e) ensure private sector participation.
Out of the planned strategies to achieve the above objectives four of them are most
critical for our evaluation, though not ignoring the rest: (f) review the regulatory structure
to facilitate appropriate concessioning of railways; (g) develop an integrated railway
transport system, which will support competition among the various modes of transport;
(h) foster inter-modal co-operation between road and rail, especially for the movement of
international freight and passengers; and (i) promote co-operation with regional railways
in order to ensure undisrupted movement of cargo at interchange points, through- running
of locomotives, as well as other rolling stock and other measures to improve customer
satisfaction.
22
2.9 Sixth National Development Plan (2011).
A GRZ national development plan towards the country’s long term ‘Vision 2030’
The Government of Zambia (GRZ) has declared its intention to rehabilitate and maintain
its main railway lines (TAZARA and RSZ) and also build new railway spurs to support
the existing infrastructure for trade facilitation. This is being proposed as part of a
National Transport Infrastructure Master Plan (to be developed). (Republic of Zambia
2011)
There are essentially five (5) new proposed railway spurs to be developed in Zambia.
These include:
Map 1: Proposed railway projects in Zambia
Source: Government of the Republic of Zambia
(i) Chingola-Solwezi-Jimbe (Angola): to link Zambia railway network to the Angolan
network through to Port Lobito
(ii) Nseluka-Muplungu Railway: to link TAZARA to the Great lakes region of East
Africa via Lake Tanganyika
(iii) Chipata- TAZARA-Mpika: to enhance trade via the Nacala Corridor by facilitating
freight through Port Nacala and ease congestion at Dar es Salaam
(iv) Kafue-Lion’s Den (Zimbabwe): to link the Zambia railway network to Port Beira of
Mozambique via Zimbabwe
(v) Livingstone-Katima Mulilo via Kazungula: to enhance trade links amongst Zambia,
Botswana and Namibia by utilizing Walvis Bay Port. This is hoped to encourage
trade even with South America especially Brazil.
23
2.10 Railway Legislation in Zambia
This include: The Railways Act; The Tanzania Zambia Railway Act; The Railways
(Deviation) Act; Nkana-Nchanga Branch Railways Act; Rhodesia Railways Act;
Mashona Railway Company Limited Act; Roan Antelope Branch Railway Act; Mufulira
Mokambo Railway Act; Railway Transfer of Statutory Powers Act; The Rhodesia
Railway Act, 1949
The railway legislation above are operational policy documents and statutes which
oversee the administration of the railway lines in Zambia. They serve as key policy and
statutory references for my research. I reviewed these policies, where necessary to
determine their relevance in today’s economy.
2.11 2003 GRZ/RSZ Concession
This is a railway concession signed between the GRZ and NLPI (RSZ) for exclusive
rights to the operation and management of the Zambian main railway line between
Livingstone and Chingola, including the inter-mine network and passenger service
provision.
“…the concessionaire took over operations on 3rd
December 2003. The initial target was
to concession the railway by September 2001. There were three main reasons for the
delay: (i) the MCT at one point constituted a committee of eight cabinet ministers to
oversee the process and the committee took a long time to convey approvals for the
concession design and eventually the committee was scrapped; (ii) the second-ranked
bidder made a representation to the Government and dealing with that also delayed the
approval of the concession by the Attorney General; and (iii) The negotiations between
the preferred bidder and the Government-appointed negotiating team took an inordinately
long time.” (Zambia Railways Restructuring Project Report, 2005, P8)
In view of the 2003 GRZ/RSZ Concession, the World Bank undertook a railway
restructuring project ( costing US$27 million) producing an Implementation completion
Report December 20, 2005. The objective of this project was to enable Zambia Railways
(ZR) through restructuring and privatization to: (i) increase operating efficiency; (ii)
reduce cost of operations; and (iii) make freight services and tariffs competitive, and,
consequently, increase the railways’ share of the local, international, and transit freight
traffic. These objectives were to be met through implementation of 8 strategic project
components. Two of these, cited for the purpose of my research, are component (e) ZRL
restructuring(US$0.5 million, 2% of total project cost); (f) regulatory and legal
framework (US$0.8 million, 3% of total project cost; and (g) MCT strengthening
(US$0.5 million, 2% of total project cost).
It was reported that component (e) rated satisfactory in that ZRL downsized to 25 staff
and its role redefined to manage the railway concession instead of being a railway
operator. Component (g) was rated moderately satisfactory in that MCT through a
24
consulting firm produced a report for Review of the regulation and legal framework for
the railway industry in 2005. It includes:
- An outline of the existing legal framework;
- A draft of an enabling new railway legislation to reflect the changed railway structure
and a liberalized business environment;
- An overview of the agencies currently and potentially involved in railway regulation;
- A discussion on the need for railway specific economic regulations and the
application of environmental regulations; and
- Specific proposals for licensing of railway operators and institutional structure for
railway safety regulations.
However it is reported not to have been implemented because “the way forward was not
all clear-and experience in other countries did not point to an obvious answer. The need
for economic regulation for the railways was questionable as there is reasonable
completion from road transport services and the Concessionaire is free to set freight
tariffs and select the freight it wants to carry…The moderately satisfactory rating reflects
the fact that the amendment need not have been delayed to this extent.” (Page 11,World
Bank Report No:32520, 2005)
2.12 Should Zambian Government Invest in Railways? (2011).
This is a study conducted by Gael Raballand, a Senior Economist with the World Bank,
and Alan Whitworth, a technical advisor of the Zambia Institute of Policy Analysis and
Research. The study assesses the Zambian railway sector’s survival in the presence of a
competitive road sector. It criticizes GRZ proposals to invest in the Railway Sector.
The study argues that he railway sector was constructed for copper transportation.
However, despite rekindled increase in copper production, it is unlikely that the railway
sector can regain it transport market share from the road because of relatively lower road
operating cost and higher efficiency. However, the road sector is not blameless. It has
increased road maintenance cost, traffic congestion, road safety concerns and despite
being privately driven, it is argued that it pays insufficient road user charges to meet full
cost of these market failures. It is also deduced that railways consume about 30% less
fuel than road transport.
Events in the 1990s changed the railway transport economic environment in Zambia. The
main explanatory variables of this adverse change being: Economic liberalization of
Zambia; Independence of South Africa and the resulting proliferation of the trucking
industry along the North South Corridor to facilitate trade between Zambia and South
Africa; deteriorated railway infrastructure due to deferred maintenance and lack of its
recapitalization; and, competitiveness from the trucks due lower rates per tone-kilometer,
reliability and reduced transit times.
The railway sector was constructed for copper transportation. However, despite rekindled
increase in copper production, it is unlikely that the railway sector can regain it transport
25
market share from the road because of relatively lower road operating cost and higher
efficiency. However, the road sector is not blameless. It has increased road maintenance
cost, traffic congestion, road safety concerns and despite being privately driven, it is
argued that it pays insufficient road user charges to meet full cost of these market
failures. It is also deduced that railways consume about 30% less fuel than road transport.
The study proposes that Government’s investment in railway lines is highly risky to
undertake. First, Government would have to choose between rehabilitating TAZARA or
RSZ line before developing new lines as these would serve as tributaries to the two main
lines. Further, exploitation of the Congo DRC mining opportunities would require prior
strategic market planning to commit and guarantee traffic for the railways. Considering
scarcity of funds, Government could be more prudent by improving road sector
management and consider the railways as a sunk cost.
I envisage that the review of the above carefully selected literature will enrich my
theoretical concepts and help us to clarify my hypotheses, models and distinguish the
relevant variables for my research. In addition, they will inform my development of the
data collection tool.
3.0 Research Methodology
3.1 Study Design In this research, we used a mixed method approach involving primary and secondary
data. The Primary data was essentially qualitative where as the secondary data was
quantitative. The primary data was collected from a purposively sampled group of
respondents who comprise the key transport sector holders in Zambia including:
3.1.1 Government Ministries: Ministry of Finance and National Planning,
Ministry of Transport Works Supply and Communications and the
Ministry of Commerce Trade and Industry
3.1.2 Railway operators: Railway Systems of Zambia (RSZ) and Tanzania
Zambia Railways Authority (TAZARA)
3.1.3 Railway asset holding company in Zambia: Zambia Railways limited
(ZRL)
3.1.4 Infrastructure construction regulatory institution: National Council for
Construction (NCC)
3.1.5 Transport training institute: Chartered Institute of logistics and Transport
(CILT)
3.1.6 Foreign missions to Zambia: Danish Embassy, Embassy of the People’s
Republic of China, Embassy of Japan and the German Embassy
3.1.7 Transport donor agencies/organizations: European Union (EU), World
Bank (WB), African Development Bank (AfDB), Japanese International
Cooperation Agency (JICA), Danish International Development
Assistance (DANIDA) and Kfw Germany.
26
3.1.8 Regional economic communities: Common Market for Eastern ans
Southern Africa (COMESA) and the Southern Africa Development
Community (SADC)
Ideally, the questionnaire was also supposed to be administered to the main railway
customers vis; the copper and other mining companies, cement producers (Lafarge
Zambia), Nakambala Sugar Company Plc, Ndola Lime and bulk exporters of agricultural
products. However, due to the time limitation with this research, this was not done.
Secondly, I endeavored to understand the political and economic policy influence on
railway development and operational efficiency of the main railway line under
concession. The significance of the role of government in transport infrastructure
development was analyzed over regulatory and competitive economic policy realms. This
entailed application of economic theories, mathematics and statistical inference to
analyze the variables influencing revenues of the railway sector. In essence I investigate
the structural stability of the operations considering government interventions and
privatization railway (RSZ concession) between1994-2011. In this regard, I used the
ordinary least squares method to determine the relationship below:
Railway Returns = Passenger numbers + Freight (cargo) volumes - Number of
Employees + capital Investment + Regulatory policy
In the proposed regression equation above I expected railway revenues to be positively
influenced by passenger numbers, freight (cargo) volumes, capital investment, and
negatively to the number of employees and, I want to realize the effect of regulatory
policy. The qualitative analysis of the data collected was also supplement by quantitative
methods on a case study basis. This will be used to evaluate essential key qualitative
variables like types of government systems and the political influence on infrastructure
development.
3.2 Research Instruments I main used one research instrument: A structured questionnaire which was composed of
four parts. This tool was essentially used to collect the primary data which as we shall
realize, supplements the secondary data that was analyzed. The Questionnaire is attached
hereto as Annex: 1
3.3 Data Collection Procedure There we 3 forms of data collection procedures.
3.3.1 For the literature reviewed, data was mainly collected from the national
libraries, University of Zambia (main campus) library, the key transport
sector stakeholders identified above (3.1.1) and other documents were
downloaded from the worldwide web.
3.3.2 The qualitative primary data was collected using the structure
questionnaire attached as Annex 1. In some instances, the questionnaire
was administered via one-one interviews with the respondents, while
27
others were sent and responded to via e-mail. Some responses were mailed
back with additional information whereas other (2) respondents just
remitted their own structured response.
3.3.3 The secondary financial data and employment numbers used in the Chow
Test for structural stability was obtained from the Zambia Railways
headquarters found in Kabwe town of the Central Province.
3.4 Data Analysis
Data analysis conducted in this research was distinctly done in respect of the three forms
of data collection procedures above.
3.4.1 With respect to the literature review data, the data was skimmed through
for the most relevant information. This involved identification of
information with respect to Railway projects appraisal guideline, Cost
benefit analysis for railways, policy relevant information, legal and
statutory obligations for the railway sector, transport institutional
frameworks, and transport theoretical authorities so as to rationally guide
our arguments and analysis. This was mainly desk review of data.
3.4.2 The qualitative information generated from the questionnaire data
involved questionnaire coding, data entry into computer software
application-Microsoft Excel, data analysis and interpretation - Statistical
package for Social Scientists-SPSS and reporting-Microsoft Word)
3.4.3 For the primary financial data collected from ZRL, I applied
econometrics: Chow Test of Structural Stability using the E-vies statistical
package after extracting this data from the Microsoft excel where I had
initially entered it.
28
4.0 Results The results to be presented are threefold:
4.1 Responses to the questionnaire:
The questionnaire was submitted to a total of 21 purposively sampled respondents of
which thirteen responded.
The questionnaire was structure in four parts. Below are the results for each part.
Part A: This section was probing for preliminary information of the respondents
including: Name of institution, Designation of respondent, sex, age and type of institution
they work for. The following are the results:
Table 4: Respondents: Institution, Designation, Age, experience in organization
Name of Institution * Designation? * What type of institution do you work for? Age*Experience
What type of institution do you work for?
Name of Institution Designation Age
Years in org
1 GOVERNMENT MINISTRY MCTI ECONOMIST 28 2
MOFNP CHIEF ECONOMIST1 41 4
MOFNP CHIEF ECONOMIST2 40 5
MTWSC DIRECTOR PLANNING 47 5
MTWSC GOVERNMENT INSPECTOR OF RAILWAYS 54 9
NCC CEO 49 13
2 EMBASSY DANIDA
ROAD SECTOR PROGRAMME COORDINATOR 45 7
3 INTERNATIONAL COOPERATION AGENCY AFDB TRANSPORT INFRASTRUCTURE SPECIAL 50 3.5
EU ENGINEERING ADVISOR 36 8
JICA PROGRAM OFFICER- INFRASTRUCTURE 29 0.75
WB SENIOR TRANSPORT SPECIALIST 50 8
5 TRANSPORT OPERATOR TAZARA MANAGING DIRECTOR 64
6 PROFESSIONAL BODY CILT TRANSPORT EXPERT 57 33
TOTAL 13 13
All the respondents were male.
Part B: This part was essentially to confirm if the respondents consider the transport
sector in their work and the main area of responsibility in respective to transport. The part
also probes if railways are an area of support for the respondents’ institutions and it
concludes with an investigation of whether the respondents’ institution have any
appraisal guidelines for railways and what the main considerations for cost benefit
analysis for railways. From the table below we note that all respondents focus on the
transport sector and only four out of the thirteen institutions do not support railways in
Zambia.
29
Table 5: Frequency of Respondents support; Transport focus; Railway Support
Name of Institution * Is the transport sector an area of focus for your institution? * Does your institution support the railway sector in Zambia? Crosstabulation
Does your institution support the railway sector in Zambia?
No. of Respondents Is the transport sector an area of focus for your institution?
1.00 YES 2.00 NO
1.00 YES Total
1.00 YES 9 9 9
2.00 NO 4 4 4
Total 13 13
For the institutions who currently supporting railways,: 3 respondent said that their main
type of support is Finance and resource mobilization, whilst 1 said they advocate for the
railway sector development. Another alluded to their transport service provision whilst 2
embraced all the reasons given by the other respondents and added that it is their mandate
to support and develop the railway sector.
Type of support to Railway development sector
Support to railways development sector
Type of Support offered Frequency Percent
MINISTRY MANDATE 1 7.7
FINANCE 3 23.1
ADVOCACY 1 7.7
RESOURCE MOBILIZATION 1 7.7
TRANSPORT SERVICE 1 7.7
ALL ABOVE 1 7.7
Total (99) 8 61.5
Missing 5 38.5
Total 13 100
0
20
40
60
80
Frequency Percent
9.00
69.23
4
31
Institutional Support for railway sector development
YES
NO
30
Table 6: Respondents Institution: Appraisal guidelines for railways, CBA considerations
Does your institution have an appraisal guidance for
railway projects?
No. of Institutions
1.00 YES 2.00 NO What are the main considerations for cost benefit analysis for railways?
1 1
CBA is done but not necessarily for economic/financial viability but over national development tool
3
3 No idea
1 1
economic activities through the link areas - volume of expected traffic existing alternative transport and cost effectiveness comparison
2
2 economic impact to the nation
1 1
Return of investment and cost benefit
1 1 Development, rehabilitation, maintenance and operational costs; time savings, user cost savings, environmental and social benefits where possible
1
1 Impact on poverty reduction; economic rate of return; sustainability
1 1 rail moves more tonnage per litre of diesel, cost of rail maintenance per km is cheaper than road, more traffic by rail results into less road maintenance costs
1
1 Covering operational costs and meeting demand for railway services
1
1 It is cheap yet carries bulky cargo
TOTAL 4 9
Cost benefit Considerations in railway projects
Does your institution have appraisal guidance for railway projects?
Frequency Percent
YES 4 30.8
NO 9 69.2
Total 13 100.0
Does your institution hav…
0%
YES 31%
NO 69%
Existing appraisal guidance for railway projects
31
Part C: This part of the questionnaire assesses the respondents’ insight on how railway
projects are appraised in Zambia, the value of their efficiency, and their relevance to the
southern region and entire African continent. This is also compounded by an
investigation on whether the railway sector institutional setup attunes with the railway
policy. The results are presented below:
Of the 13 respondents, 4 said that GRZ intentions to develop the railway sector are not
based on any appraisal guides, 2 said they are, 3 said they don’t know whilst the rest did
not respond to this question. It was also revealed by 6 respondents feel that railway
projects in Zambia are developed on political directives whilst only 1 respondent said that
they are based on standard appraisal guidance for transport infrastructure development
and cost benefit analysis, respectively. 2 respondents said they did not know the basis
whilst the rest reserved their opinions.
The specific responses are shown in Table 7 below.
Table 7:Name of Institution * How are railway projects appraised in Zambia? * Are the GRZ
intentions to develop the railway sector based on any appraisal guidelines?
Are the GRZ intentions to develop the railway sector based on any appraisal guidelines?
No. of Institution
How are railway projects appraised in Zambia?
Total
1.00 SAG FOR TRANSPORT INFRASTRUCTURE DEVELOPMENT
3.00 COST BEST ANALYSIS
4.00 POLITICAL DIRECTION
5.00 OTHER
1.00 YES 2
1 1
1 1
2.00 NO 4 4 4
9.00 DON’T KNOW
3
1 1
1 1
1 1
Missing 4 4
TOTAL 13 13
YES 30%
NO 50%
DON’T KNOW 20%
Are GRZ intentions to develop the railway sector based on any appraisal guidelines?
32
With respect to value of railway efficiency to the Zambian economy: 2 respondents felt
that this is in terms of freight carriage for trade; 3 considered regional trade facilitation; 2
said freight carriage and passenger transportation; 2 said freight carriage and regional
trade facilitation; and 4 said freight, passenger and trade facilitation.
Table 8: Name of Institution * What is the value of railway efficiency to the Zambian economy?
What is the value of railway efficiency to the Zambian economy?
Total 1.00 FREIGHT
CARRIAGE FOR TRADE
3.00 REGIONAL TRADE FACILITATION
4.00 FREIGHT CARRIAGE & PASSENGER TRANSPORTATION
5.00 FREIGHT CARRIAGE & REGIONAL TRADE FACILITATION
7.00 FREIGHT, PASSENGER & TRADE FACILITATION
Frequency 2 3 2 2 4 13
I also considered the responses to the consideration of regional and/or African market in
appraising railway developments.
Table 9: Respondent Institution; regional significance of Zambia railway network
Number of Institutions * Are there benefits to Zambia if railways are developed with view to capture the regional and not
only national traffic demand. * If YES to (14) above, please explain
If YES to (14) above, please explain
No. of
Institution
Are there benefits to Zambia if railways are
developed with view to capture the regional and
not only national traffic demand.
Total 1.00 YES
MONOPOLIZE DRC TRANSIT TRAFFIC 1 1 1
MINING SECTOR TRADE FACILITATION 1 1 1
REDUCE DAMAGE & CONGESTION OF ROADS 1 1 1
CHEAPER BULK CARGO TRANSPORT 2 2 2
REGIONAL TRADE & GROWTH OF EXTERNAL SECTOR 1 1 1
ALL ABOVE 1 1 1
8.00 REVENUE & SERVICE PROVISION 2 2 2
77%
15%
Is the Zambian railway network important to the African continent?
YES
NO
Missing
33
The respondents prioritized the following transport corridors, for Zambia’s development. We
note the frequency of appearance of North South and Dar es Salaam corridors. The scalar in
these responses is one stakeholder who does not understand what transport corridors are.
Table 10: Respondents’ prioritized transport corridors
Which transport sector corridors should be prioritized for railway developments in Zambia? According to priority.
Name of Institution
Lobito-WalvisBay-Great lakes 1
Railway-Road-Air 1
Currently None 1
NorthSouth-Nacala 2
NorthSouth 1
NorthSouth-DaresSalaam-Nacala 1
DaresSalaam-WalvisBay-NorthSouth 1
NorthSouth-DaresSalaam-WalvisBay 1
Lobito-Beira-Great Lakes 1
All Corridors 1
This can only be answered after a careful analysis 2
It is interesting to note that only 1 respondent said the current railway policy was
sufficient for the sector. The other respondents to this question qualified their responses
as shown below:
Table 11: Number of Institution * Is the current railway policy framework sufficient and relevant for the sector’s development?If NO to (16) above explain. *
Is the current railway policy framework sufficient and relevant for the sector’s development?
No. of Institutions
If NO to (16) above explain.
Total
1.00 PRIVATE SECTOR LED DEVELOPMENT NOT WORKING
2.00 DOESN'T PROVIDE FOR MODERN COMPETITIVE WAYS OF DOING BUSINESS
4.00 NO CLEAR DIVISION FOR RESPONSIBILITIES OF STAKEHOLDERS
6.00 PRIVATE SECTOR LED DEVELOPMENT NOT WORKING & NO FINANCIAL FRAMEWORK
9.00 ALL ABOVE
1.00 YES 1 1 1
2.00 NO
1 1 1
1 1 1
1 1 1
2 1 1 2
1 1 1
3.00 Missing 6 6
Total 13 2 1 2 1 13
34
Further, it is advisable that every policy gets to have its respective strategic implementation
framework. In this regard, I queried the sampled respondents on whether or not the institutional
setup in the railway sector was structured in line with the railway policy. Table 12 below
presents their responses:
Table 12: Respondent Institution: Strategic nature of the railway sector institutions in Zambia
Validate your response to question
No. of
Institutions
Is the railway sector institutional setup
structured in line with the railway policy?
Total 1.00 YES 2.00 NO 9.00 DON’T KNOW
Zambia Railways Limited (ZRL) needs to be restructured to
take up new role of railway asset investment company; Need to
re-align functions between MTWSC and ZRL
1 1
1
The institutional setup to support railway policy implementation
is not sufficient
1 1 1
There is no specific and detailed policy in place for the railway
sector
1 1 1
The current Railway Act Cap 453 does not allow Zambia
Railways assets to be placed under a privately owned
company and the safety regulation of railway operators needs
to be detached from the ministry for it to be effective
1 1 1
The institutional setup is according to legislation (TAZARA
ACT) which is an integral part of railway policy. However, it
may need change to enhance inter territorial rail service
integration
1 1 1
Not Sure
4 1 1
3 3
Missing 4 4
TOTAL 13 13
35
Part D: In the last part of the questionnaire we begin with an inquest of who owns and maintains
railway infrastructure. Secondly, we drift to check if the railway policy promotes
competitiveness for the operators. This is meant to prelude our investigation on the perceived
ideal goods for railway transportation and to what extent, if any, the government influences or
ensures that such goods are transported by railways, and the probable repercussions thereof.
Table 13: Name of Institution * Who maintains the railway infrastructure in Zambia? * Who owns the railway
infrastructure in Zambia?
Who owns the railway infrastructure in Zambia?
Response Frequency Percent
Valid GOVERNMENT 10 76.9
PRIVATE SECTOR 1 7.7
Total 11 84.6
No response 2 15.4
Total 13 100.0
Maintenance of railway infrastructure
10 out of 11 respondents who answered this question said railway infrastructure are
owned by government whilst 1 said they are privately owned. Of the 10 who are said
Government owns the infrastructure, 5 said government maintains the infrastructure, 4
said the infrastructure maintained under PPP and 1 said it is maintained by the private
sector. The respondent who said railway infrastructure is privately owned is of the
opinion that it is maintained under PPP.
As regards policy provisions to promote competition among operations, the following
were the responses:
0 10 20 30 40 50 60 70 80 90
Frequency
Percent
36
Table 14: Number of Institutions * Does the railway policy promote competition for railway operators? If YES
explain how? *
Does the railway policy promote
competition for railway operators?
If YES explain how?
Total
Current policy not
clear but the
revised bill does
provide for
competition
The current
railway policy
gives a monopoly
to the main
railway operator
who can impose
any charges on
any would-be
operator
It should in any
case promote
cooperation
rather than
competition
Not Sure
YES No. of Institution 1 1 1
NO No. of Institution 9
7 7
1 1
1 1
Total 1 1 7 9
From the table we see that only one respondent said that the railway policy promotes
competition, and he argues that the current policy is not clear but the revised bill does
provide for competition. The other nine respondents to this said the policy is not
precompetitive for operators. Of these respondents one argues that the current railway
policy gives a monopoly to the main railway operator who can impose any charges on
any would-be operator; another said it should in any case promote cooperation rather than
competition. The rest said they were not sure or did not provide any reason.
According to the respondents, the following were their prioritized goods which are
suitable for railway transportation in Zambia.
Table15: Goods fit for Railway Transportation
Name of Institution Priority good for railway transportation
DANIDA Copper concentrates & cathodes; Heavy construction machinery; Industrial
chemicals
MTWSC DIRP Copper ore; manganese, cement; fertilizer; crude oil; motor vehicles; heavy
machinery & equipment
AfDB Mineral(e.g. Copper); Cement; Agric produce; steel; other construction materials
MoFNP1 Bulk commodities (Copper; Cobalt; Maize; Coal; Fertilizer; Fuel
MoFNP2 Mineral cargo(copper, cobalt, zinc); Abnormal cargo(mining equipment);
Dangerous cargo(acids & inflammables);Maize; Miscellaneous bulk cargo
CILT Metals; Grains; Fertilizers; Machinery; Petroleum products
NCC Heavy goods (Copper); Heavy machinery
WB Mining products & inputs; agricultural inputs; construction industry material;
37
hyrdro-carbons; non perishable agricultural goods
EU Fuel; Mining products;Heavy equipment for mines & construction; agricultural
products; car imported
MTWSC GIR Copper cathodes; copper concentrates; fuel; coal; acids
JICA Metal Cathodes(Copper); Cement
TAZARA Large volumes; heavy weight; continuation rather than one-off; bulk; long
distance
MCTI Copper; crude; fertilizers/chemicals; mine materials/machinery
The respondents’ position on whether or not there is government regulation on goods to be
transported by railways if presented below:
Table 16: Railway traffic regulatory policy in Zambia
Number of Institutions * Does the Government have any deliberate policy to ensure that such goods are transported by
railway? * If NO what is the impact of this non state regulation?
If NO what is the impact of this non state regulation?
No. of
Institution
Does the Government have any
deliberate policy to ensure that such
goods are transported by railway?
Total 1.00 YES 2.00 NO
9.00 DON’T
KNOW
1 Government has intentions, but cannot at the moment legislate due to
supply side constraints; Impact: Higher cost of road rehabilitation and
maintenance; high transportation cost to business community
1 1 1
2 The deterioration and damage to the existing road network; Lack of
investment and incentive for railway investment
5 4 4
1 1
4 More bulk and heavy cargo moving by road instead of by rail 2 2 2
5 Railway sector is not competitive versus road sector meaning that roads
are overused with major impact on the road condition network (+ safety and
environmental issues)
1 1 1
6 By intention based on practicality of capacity to transport 1 1 1
7 Don't Know
Name of Institution
2 1 1
1 1
Out of 12 respondents to these two questions, 3 said that the Government does have
deliberate policy to ensure that such goods are transported by railway, 8 said no and feel
that this causes deterioration and damage to the existing road network, Lack of
investment and incentive for railway investment plus bulk and heavy cargo gets to be
moved by road. 1 respondent said they do not know.
38
On the question: Has your institution financed any railway projects in Zambia? YES/NO
Explain, the following table presents the responses:
Table 17: Respondent’s financial support to railways
Name of Institution * Does your institution support railway sector development? * Has your institution financed
any railway projects in Zambia?
Has your institution financed any railway projects in Zambia?
No. of
Institution
Does your institution support
railway sector development?
Total 1.00 YES 2.00 NO
1 YES:CMRL & Mulobezi Railway Line 3 1 1
2 2
2 YES: Planning to support railway sector based of GRZ selected
priorities
2 1 0 1
0 1 1
3 YES: Advocacy for more resources to be allocated to railways 1 1 1
4 YES: Financed the ZRL restructuring project 2000-2005 1 1 1
5 NO: not part of our mandate 3 0 1 1
1 0 1
1 0 1
6 NO: Absence of realistic specific policy and related investment plan;
impact on poverty reduction not demonstrated; Economic rate of return
not calculated or too low to justify investment; weak institutional capacity
1 1 1
39
As regards the questions to do with availability of railway experts in the responding
institutions, the responses were as follows:
Do you have any railway experts in your institution?
Frequency Percent
YES 6 46.2
NO 5 38.5
No response 2 15.4
Total 13 100.0
I concluded the questionnaire with a request for 3 options on how the railway sector can
be developed. The table below presents the responses.
Table 18: Options on how the railway sector can be revamped in Zambia
How can the performance of the railway sector be improved in Zambia? Briefly propose at least 3
precise interventions.
No. of
Institutions
1 It is difficult to reasonably justify any investments in railways under the current economic levels of
trade and requirement for fast and more efficient movements of goods and services
1
10 Not certain and would not want to make unfounded suggestions 1
11 coming up with good transport policy; opening up new areas with economic activity; cheap
financial access to banks
3
2 Policy shift on transport infrastructure development- focus and balance for surface transport;
increase funding to railway sector; legislate against movement of bulk freight on roads
1
3 define the policy in railway development; balance railway and road transportation benefit analysis;
provide incentives for railways investment and transportation
1
4 Government recapitalization 3
5 Implement policy reforms aimed at enhancing competition and better regulation; More targeted
financing to the railways sector; More capacity building of railways experts 1
6 Investment to upgrade infrastructure, introduce open concessions, create railway fund for
development of infrastructure
1
7 Its role clearly articulated in the Transport Policy; Increased oversight at policy level (ministry
responsible); capacity building within parastals involved in the railway management 1
8 Establishment of a national Transport master plan taking into account regional context,
establishment of a specific national sector policy and investment plan coherent with 1
9 To separate railway infrastructure from operations, and Government to invest in the railways as it
does for the roads, To recapitalize Zambia Railways Limited and allow it to operate on commercial
lines with an independent board of Directors;
1
46.2%
38.5%
15.4%
Do you have railway experts
YES
NO
No response
40
4.2 Regression analysis results
The results were generated to assess the performance of the railway sector under
government control (1994-2003) verses under private sector management Concession
(2004-2011). Data was obtained from Zambia Railways Limited and Ministry of
Finance and National Planning. The data used is attached as Annex 2.
Since the number of observation were few i.e., 17 (1994-2011), I applied the Lisman
Sandee Matrix to the data so as to transform it into quarterly data, hence increasing the
number of observations for a more meaningful analysis.
Lisman and Sandee Matrix:
0.0729 0.1982 -0.0211
-0.0103 0.3018 -0.0415
-0.0415 0.3018 -0.0103
-0.0211 0.1982 0.0729
Secondly, considering that the data used is time series data, I applied the unit test root of
stationarity using E-views application and made the data set stationary. The results for
this process are attached as Annex 3
The results of the regression were as follows (also attached as Annex 4):
RESULT 1: Assuming no structural break
1. Period 1995-2010 Government and RSZ combined operation assessment Estimation Command: ===================== LS (REV(-1)) C (PSNGERS(-1)) (CARGO(-1)) (CAPITAL(-1)) (EMPLYEE(-1),2) (GDP(-1)) Estimation Equation: ===================== REV(-1) = C(1) + C(2)*PSNGERS(-1) + C(3)*CARGO(-1) + C(4)*CAPITAL(-1) + C(5)*EMPLYEE(-1) + C(6)*GDP(-1) Substituted Coefficients: ===================== REV(-1) = 2989.7736 + 2.670481383*PSNGERS(-1) + 0.7237714377*CARGO(-1) + 0.2549622512*CAPITAL(-1) - 0.4238110695*EMPLYEE(-1) + 0.000123625037*GDP(-1)
41
Dependent Variable: REV(-1) Method: Least Squares Date: 09/13/12 Time: 17:45 Sample(adjusted): 1995:2 2010:4 Included observations: 63 after adjusting endpoints
Variable Coefficient Std. Error t-Statistic Prob.
C 2989.774 3903.515 0.765918 0.4469 PSNGERS(-1) 2.670481 1.122918 2.378162 0.0208
CARGO(-1) 0.723771 0.128620 5.627201 0.0000 CAPITAL(-1) 0.254962 0.029782 8.560910 0.0000 EMPLYEE(-1) -0.423811 1.318892 -0.321339 0.7491
GDP(-1) 0.000124 0.007196 0.017179 0.9864
R-squared 0.965773 Mean dependent var 28415.60 Adjusted R-squared 0.962771 S.D. dependent var 12845.97 S.E. of regression 2478.602 Akaike info criterion 18.55917 Sum squared resid 3.50E+08 Schwarz criterion 18.76328 Log likelihood -578.6139 F-statistic 321.6750 Durbin-Watson stat 0.276746 Prob(F-statistic) 0.000000
Where: REV= Railway Revenue; PSNGERS= revenues from passenger service;
CARGO= Revenues from Cargo transported; CAPTIAL= Amount of capital invested,
EMPLYEE= Number of employees; and GDP= Gross Domestic Product
From the given results, we interpreted as follows:
Revenue for the railway sector is significantly influenced by cargo transported and the
amounted of capital invested at 1% confidence level. For every K1,000,000 worth of
cargo transported, the revenue increases by K700,000, where as for every K1,000,000
invested in capital, the revenue increases by K250,000.
The variables in this regression explain 96% of the variation in railway revenue. From the
F-statistic given, we conclude that overall, the model is good.
Regression 1 assumes that there is no difference between the two time periods and
therefore estimates the relationship between Revenues and passenger returns, cargo
returns, capital invested, number of employees and the GDP for the entire time period
consisting of 63 observations after adjusting points.
Regressions (2) and (3) below assume that the regressions in the two time periods: (i) Period
1995-2003 Government Control 9 years before concession and (ii) Period 2004-2010
Under Concession (Private Sector) for 7 years; are different; that is, the intercept and the
slope coefficients are different.
RESULT 2: Railway performance under Government Control 1994-2003
2. Period 1995-2003 Government Control 9 years before concession Estimation Command: ===================== LS (REV(-1)) C (PSNGERS(-1)) (CARGO(-1)) (CAPITAL(-1)) (EMPLYEE(-1),2) (GDP(-1))
42
Estimation Equation: ===================== REV(-1) = C(1) + C(2)*PSNGERS(-1) + C(3)*CARGO(-1) + C(4)*CAPITAL(-1) + C(5)*EMPLYEE(-1) + C(6)*GDP(-1) Substituted Coefficients: ===================== REV(-1) = -111914.4105 + 0.9541018346*PSNGERS(-1) + 0.35740554*CARGO(-1) - 0.2150118214*CAPITAL(-1) - 8.758467961*EMPLYEE(-1) + 0.2255638798*GDP(-1) Dependent Variable: REV(-1) Method: Least Squares Date: 09/22/12 Time: 16:15 Sample(adjusted): 1995:2 2003:4 Included observations: 35 after adjusting endpoints
Variable Coefficient Std. Error t-Statistic Prob.
C -111914.4 7551.069 -14.82100 0.0000 PSNGERS(-1) 0.954102 0.729894 1.307179 0.2014
CARGO(-1) 0.357406 0.091071 3.924490 0.0005 CAPITAL(-1) -0.215012 0.031988 -6.721627 0.0000 EMPLYEE(-1) -8.758468 0.792265 -11.05498 0.0000
GDP(-1) 0.225564 0.014813 15.22740 0.0000
R-squared 0.994001 Mean dependent var 20888.94 Adjusted R-squared 0.992966 S.D. dependent var 11839.39 S.E. of regression 992.9280 Akaike info criterion 16.79400 Sum squared resid 28591275 Schwarz criterion 17.06063 Log likelihood -287.8950 F-statistic 960.9891 Durbin-Watson stat 1.168160 Prob(F-statistic) 0.000000
Interpretation:
- The explanatory variables in the model explain 99% of the variation in the railway
revenue.
- All the variables significantly influence revenue at below 1 percent confidence level
except for passenger revenues
- There is a significant negative relationship between Railway revenues and number of
employees and Capital invested.
RESULT 3: Railway performance under Concession (RSZ) 2004-2011
3. Period 2004-2010 Under Concession (Private Sector) for 7 years Estimation Command: ===================== LS (REV(-1)) C (PSNGERS(-1)) (CARGO(-1)) (CAPITAL(-1)) (EMPLYEE(-1),2) (GDP(-1)) Estimation Equation: ===================== REV(-1) = C(1) + C(2)*PSNGERS(-1) + C(3)*CARGO(-1) + C(4)*CAPITAL(-1) + C(5)*EMPLYEE(-1) + C(6)*GDP(-1) Substituted Coefficients: ===================== REV(-1) = -5741.272333 + 2.582371932*PSNGERS(-1) + 0.6971907831*CARGO(-1) + 0.2255404181*CAPITAL(-1) + 22.39085802*EMPLYEE(-1) + 0.005545400925*GDP(-1)
43
Interpretation:
- The explanatory variables explain 98% of the variation in the railway revenues
- Passenger service revenues, Cargo revenues, capital invested and number of
employees significantly influence railway revenues at 5% confidence level.
- GDP influences the railway revenues at 10% confidence level of consideration
A look at the estimated regressions suggests that the relationship between Revenue and
the explanatory variables is not the same in the two sub-periods. The slopes in the
preceding regressions seem different. In the period 1950–2003 the Revenue generated is
significantly influenced by amount of capital investment, number of employees and GDP,
with Capital invested having a negative influence, whereas in the period 2004–2010
Revenues generated were significantly influenced by returns from passenger services,
cargo freight, capital invested, employee numbers and GDP. From the regression
parameters generated we can see that the GDP had more influence in the Government
operations period (i.e.0.225564) than during the concession period (0.005545). Capital
invested during the concession period had a positive significant influence on Revenues.
Returns from passenger services had significant influence on Revenue in the Concession
period as seen from the P-values at 10% confidence level. Whether this change was due
to the economic policies or the change from state controlled to private control of the main
railway system under a concession; is hard to say. This further suggests that the pooled
regression (1)—that is, the one that pools all the 63 adjusted observations and runs a
common regression, disregarding possible differences in the two sub-periods may not be
appropriate.
Of course, the preceding statements need to be supported by appropriate statistical test(s).
Now the possible differences, that is, structural changes, may be caused by differences in
the intercept or the slope coefficient or both.
Dependent Variable: REV(-1) Method: Least Squares Date: 09/14/12 Time: 06:07 Sample(adjusted): 2004:2 2010:4 Included observations: 27 after adjusting endpoints
Variable Coefficient Std. Error t-Statistic Prob.
C -5741.272 3762.516 -1.525913 0.1420 PSNGERS(-1) 2.582372 0.505512 5.108431 0.0000
CARGO(-1) 0.697191 0.064984 10.72861 0.0000 CAPITAL(-1) 0.225540 0.045677 4.937777 0.0001 EMPLYEE(-1) 22.39086 8.481345 2.640013 0.0153
GDP(-1) 0.005545 0.003275 1.693140 0.1052
R-squared 0.988229 Mean dependent var 37779.67 Adjusted R-squared 0.985426 S.D. dependent var 6209.928 S.E. of regression 749.6794 Akaike info criterion 16.27030 Sum squared resid 11802404 Schwarz criterion 16.55826 Log likelihood -213.6490 F-statistic 352.6003 Durbin-Watson stat 0.411369 Prob(F-statistic) 0.000000
44
We thus apply a formal test, the Chow test to achieve this. This test assumes that:
1. That is, the error terms in the sub-period regressions are normally distributed with the
same (homoscedastic) variance σ2.
2. The two error terms for regression 2 and regression 3 are independently distributed.
The mechanics of the Chow test are as follows:
1. Estimate regression (1), which is appropriate if there is no parameter instability, and
obtain RSS3 with df = (n2 + n3 – k), where k is the number of parameters estimated,
6 in the present case. For our regression RSS1 =350,000,000 with df = 56. We call
RSS1 the restricted residual sum of squares (RSSR) because it is obtained by
imposing the restrictions that the sub-period regressions are not different.
2. Estimate (2) and obtain its residual sum of squares, RSS2, with df = (35 − 6). In our
regression, RSS2 = 28,591,275 and df = 29.
3. Estimate (3) and obtain its residual sum of squares, RSS3, with df = (27 − 6). In our
regression RSS3= 11,802,404 with df = 21.
4. Since the two sets of samples are deemed independent, we can add RSS2 and RSS3 to
obtain what may be called the unrestricted residual sum of squares (RSSUR), that is,
obtain:
RSSUR = RSS2 + RSS3 with df = (n2 + n3 − 2k)
In the present case, RSSUR = (28,591,275+ 11,802,404) = 40,393,679, with df = 40
5. Now the idea behind the Chow test is that if in fact there is no structural change [i.e.,
regressions (2) and (3) are essentially the same], then the RSSR and RSSUR should not
be statistically different. Therefore, if we form the following ratio:
F = (RSSR − RSSUR)/k
(RSSUR)/(n2 + n3 − 2k) ~F[k,(n2+n3−2k)]
Therefore we are testing the hypothesis:
- Null Hypothesis, Ho: Regression 2= Regression 3 (i.e. No structural change or break)
Alternative Hypothesis, H1: Regression 2 is not equal to Regression 3. (there is a
structural break)
- Test statistic: We use the F-statistic as shown above, with 6 parameters and 40
degrees of freedom. Critical values = 1.37, 2.0, 2.45 and 3.51
We undertake our test considering 25%, 10%, 5% and 1% significant level
respectively.
Therefore, we do not reject the null hypothesis of parameter stability (i.e., no structural
change) if the computed F value in an application does not exceed the critical F value
obtained from the F table at the chosen level of significance (or the p value). In this case
we may be justified in using the pooled (restricted?) regression (1). Contrarily, if the
computed F value exceeds the critical F value, we reject the hypothesis of parameter
stability and conclude that the regressions (2) and (3) are different, in which case the
pooled regression (1) is of doubtful or uncertain value, to say the least.
45
Computing our F-statistic from the F ratio given above, we get
F = (350000000 − 40393679)/6
(40393679)/(40) ~F(6,40)
= 51.09815
Conclusion and Decision: The computed F-statistic (51.09815) is higher than the critical
values at all considered significant levels: 25%, 10%, 5% and 1%.
We thus reject the Null Hypothesis and conclude that statistically, there is a structural
break. That is to say, the economic policies and the concessioning of the main railway
line to a private operator, caused significant changes on the performance of the railways
in terms of revenues that were being generated as influenced by differences in: returns
from passenger train services; cargo freight; capital invested; number of employees; and
the economic performance of the country as represented by Gross Domestic Product,
between the two respective periods.
4.3 Other structured responses for RSZ and JICA
These responses were in terms of written submissions from the respondents
(Including Railway Systems of Zambia and the Embassy of Japan)
1. Railway Systems of Zambia, in their submission argue that:
“ ..before major investments are injected to the industry, there is a need to address
some concerns and develop a proper mechanism to maximize utilization of the
existing infrastructure. Once this is done, a significant improvement will be seen
without the need for any Government expense; the Dar es Salaam corridor and the
North-South Corridor will be able to increase volumes drastically with almost
immediate effect.” (Benjamin Even, RSZ, 2012)
2. The Japanese Embassy submitted that:
In an excerpt from a recent speech read on behalf of the Ambassador, it was said that, “
In the past 20 years, Japan has supported 126 km of roads in Lusaka alone. And another
15km will be added with Ring Road” (Embassy of Japan, 27 July 2012)
46
Map 2: Southern Africa Transport Corridors
47
5.0 Discussion 5.1 Research Challenges
The main challenge faced with this research was the lack of time for effective one to one
interview administration of the questionnaires. I was in most instances inclined to e-
mailing and/or submitting the questionnaires to the offices of the respective respondents
for them to attend to them at their convenience and revert back once completed
preferably on or before the 24th
of August 2012. Other hurdles were in terms of non
responses due to confidentiality or other undisclosed reasons; financial constraints for me
to travel to the Copperbelt Province to meet with the main railway customers- the mines;
and the time demand from the EPM program taught courses which were running in
parallel to this research exercise.
As regards, the financial data collected from ZRL headquarters, the only data available
was from 1994 to 2011. Other data prior to 1994 would have been very useful and could
have avoided me from transforming the annual data into quarterly data using the Lisman
and Sandee Matrix.
In the initial work plan (attached the detailed work plan Annex 7), there was a scheduled
validation workshop for the draft report. This was not undertaken due to time constraint
realizing that responses to the questionnaire were submitted later than the required dates.
This in turn affected the time schedule for data entry and analysis.
5.2 Discussion of results
Despite the above challenges, the research yielded great insight into the key stakeholder’s
perceptions of the railway sector in terms of its Policy framework, implementation
structures and development prospects.
Initially it is interesting to note that the Transport Infrastructure sector is dominated my
male employees. In fact, for all our respondents were male with ages ranging from 28- 64
years. Apart from the Ministry responsible for transport and the railway transport
operator, other stakeholders do not have specific training in railway transport but
essentially have an opportunity to consult their technical railway experts though not
stationed in Zambia (especially the cooperating partners)
All the purposively sampled respondents confirmed their support of the transport sector
but not all of them currently support the railway sector in particular. Judging from the
research results, there is lack of confidence in the sufficiency and implementation
structure of the railway policy. In certain instances, the policy is not even recognized as a
representative policy to guide such a strategic transport sector which mainly serves the
primary economic contributor of the country-mines. There is no deliberate financing
framework and no directed stakeholder responsibility for the railway policy. This
suggests an ambiguity in the conduct of business in the sector. As such, even the
operations of the private sector are deemed to be inefficient. Further, the railway policy is
specifically identified as not having an institutional implementation framework. This
48
challenge is also attributed to the non appraisal nor revision of the relevant railway
policies and statutes.
Appraisal guidelines are important is not a pre-requisite for any infrastructure
development. Railway infrastructure development is not an exception to this standard.
Cost Benefit analysis is the usual government tool employed for this purpose. Drawing
from the research results, there is varied understanding of the considerations for cost
benefit analysis. In the extreme cases, I tend appreciate some respondents who simply
admitted to not having an idea as to what the CBA considerations are for railway sector
development in Zambia. Most respondents opted to speculate on their perceived ideal
considerations which did not necessary tally though could be used as elements of a
comprehensive railway CBA tool for railway infrastructure development. The absence of
standard railway appraisal guidelines probably induced the perception that most if not all
railway developments are politically motivated.
However, from the responses given, common is the attributed value to freight carriage
and regional trade facilitation. Over 70% of the respondents realize railway efficiency in
these two areas.
In addition, it is interesting to note that as prioritized in the JICA study (2010), the
respondents consistently prioritized, in most instances, the North South Corridor, Dar es
Salaam Corridor and the Lobito Corridor. But, it was alarming to note that some
stakeholders should very little knowledge on the development corridor initiatives, none
was actually able to acknowledge and appreciate the JICA study of 2010.
Ownership of any property has significance on its maintenance. It is very important to
clarify on the responsibilities and obligations of stakeholders and/or shareholders to any
ownership agreement. I realize that there has been uncertainty with regard to who must
maintain the existing railway network, under concession, in Zambia. Realizing the
magnitude of the required resources for this task, all the parties have resorted to taking
advantage of the ownership ambiguity and given limited attention to maintenance and
rehabilitation of the railway infrastructure. This is evidenced by the current poor state of
the railways.
Engagement of the private sector into the operations of the railways in Zambia was not
only meant to bring efficiency but competitiveness. However, there are lacunae in the
guiding policy to achieve this. In as much as the private sector was engaged policy was
not reviewed to guide their operations, this resulted in enabling the private operator to
monopolize the industry whilst optimizing on the redundancies of the orthodox archaic
policies and statutes guiding the sector.
As noted in the study by Whitworth and Raballand (2011) our researcher confirms that
stakeholders in the transport sector blame the large annual road sector maintenance costs
on the diverted transportation of bulk and heavy cargo from the railways to the roads. The
government has even permitted transportation of relatively abnormal loads on roads
49
instead of them being carried via railways. This attests to the non regulation of what type
of goods should be transported by railways.
We note from the responses with respect to railway sector support and financing that the
plausible financiers have a challenge of putting their money where there is no bankable
document. However, their willingness to finance the sector is undoubted as they have
financed railway sector reviews, RoadSIP, and recently an independent review of the
performance of the RSZ/ZRL Concession. What they require is an affirmed railway
sector development agenda, with clear targets and commitment from Government. This
as evidenced by the lack of confidence and uncertainty in the current railway policy and,
lack of an policy institutional implementation frame. Worse still, there is no evidence of a
railway sector financing framework for investors to buy in.
From our regression results we concluded that there is a structural break in the
performance of the railway under concession and before concession, due to the economic
policies and the concessioning of the main railway line to a private operator.
Comparing the performance pre and post concession periods capital investment under
concession had significantly improved performance of the railways even impacting
passenger service delivery as seen in the significance of the passenger revenues under
concession period unlike prior to the concession. However, the value of railways in
Zambia is dependent on the freight cargo and this is the major sector revenue contributor.
Overall economic performance as measure my GDP was more influential on the railway
sector before the concession, we may loosely be inclined to state this was as a result of
government ensuring that most mining products and other bulk cargo and dangerous
substances (acids and fuel) were transported by railway.
A regional perspective of the impetus of Zambian railway network exacerbates the above
arguments. Zambia has more to gain if it consolidates its infrastructure plans attune to the
COMESA and SADC infrastructure development plans.
6.0 Conclusion
Before my completion of this report, it was interesting to realize that the GRZ has terminated the
concession agreement with RSZ and restored ZRL as the interim operator and manager of the
main Zambia railway line.
My arguments and carefully selected literature therefore now serve as the vital instrument to
precise the strategic planning for the revitalization of not only former RSZ railway but the entire
railway sector in the country.
Ethically, it is not enough to argue that it depends on the context (i.e. what is wrong in one
context may be right in the other). Account should be taken of the larger/more unifying moral
principles (what is the most professional way to manage the railway sector, a proactive railway
policy must be sector sensitive and dynamic to promote efficient and competitive operations)
50
Railway sector development has a strong case but it needs Government realization of its roles
and responsibilities and most importantly stakeholder ‘invitation to treat’ on an informed railway
sector strategic plan and bankable document.
7.0 Recommendations As per research proposal prospects my research recommends the following road map for the
railway infrastructure and sector performance development:
NO. RECOMMENDATION RATIONALE
PART A: Railway Sector focus
1 Establish clear role of Government Mandate of government towards railways
2. Enhance stakeholder commitment and
participation in the sector
Advocate for deliberate development of the
sector with informed bankable documents &
deliverables
PART B: Strategic Level
1. Revise railway policy and respective acts To be relevant and guide railway sector
development
2. Identification of railway stakeholder profile
in revised policy
Stakeholders should know their
responsibilities and what is expected from
them
3. Re-structure the Railway Sector
Institutional structures attune to revised
policy and acts
To have an affirmed policy implementation
strategy with accountable implementers/
institutions
4. Railway Sector Human resource audit at
policy, strategic & implementation levels
To identify the required human resource to
implement the revised railway policy
5. Develop pre-requisite training curriculum
for specific staff
A railway authority to ensure that the railway
sector is managed by competent staff (ZRL &
NCC to ponder on this)
PART C: Implementation Level
1. Consider performance contracts for ZRL,
TAZARA and other operators as may be
applicable
To encourage competition under a government
enabled environment.
2. Develop appraisal guidelines for railway
infrastructure development (CBA, NPV,
SMB, e.t.c.)
Structure cost benefit analysis considerations for
Zambian railways relative to regional and
international respective benchmarks so as to
inform plausible financiers
3. Establish a technical steering committee
of key stakeholders (including donors)
To advise the sector on interests of all
stakeholders and their expectations with regard
to policy relevance, institutional structures and
implementation, service provision
4. Railway Sector Communication policy
development
To comprehensively sensitize all stakeholders
and the general public on the railway sector:
Structures, responsibilities, operations &
services
51
There is need for a cost benefit analysis to be objectively undertaken on all proposes railway
sector projects so as to inform government and the plausible sector financiers. The financing
framework for the railway sector needs to be presented by government and should based on a
clear road map and desired deliverable as proposed by the one given above. The willingness of
cooperating partners to finance the railway sector will then actualized.
Government has taken the bold step of terminating the main railway concession agreement, this
move needs strategic and objective ensuing measures, as proposed above to rekindle railway
performance in Zambia.
Time is of the essence, an integrated transport master plan needs to be developed. The African
Development Bank have explicitly declared their full support for this initiative and the other
cooperating partners have not negated it, the onus is on Government present its case in a
consistent and logical manner. Accessibility and demand infrastructure, transport as may be
defined, serves to facilitate development of the economic and social sectors of this country. The
time to realize this is not tomorrow.
52
8.0 Bibliography African Railway Union Rail development in Africa: Stakes and prospects, objectives and
missions of the African Rail Union
ARU General Secretariat Kinshasa, Congo DR, 2006
Anna Chau & Angèle Galea Appraisal of Railway Performance Projects - A UK Approach Delft
University of Technology, Netherlands, 2005
Benjamin Even General on Railways in SADC , RSZ 2012
Dennis Schut European Railway Research
Union Internationale de Chemins de fer Brussels, 2008
Gaël Raballand Should Zambian Government Invest in Railways? (2011)
and Alan Whitworth Zambia Institute of Policy Analysis & Research, Lusaka, 2010
Jim Hunter, Derek Holden India Railway Sector Investment Program
Scott Wilson Railways Ltd, United Kingdom, 2009
Kazunori OSHIYAMA Preparatory Survey for Southern Africa Integrated Regional Transport
Program
JICA PADECO Co., Ltd.Mitsubishi UFJ Research and Consulting Co.,
Ltd., Lusaka, Zambia 2010
Republic of Zambia Road Sector Investment Program (ROADSIP) & Road Sector ACT
Government Printers, Lusaka, Zambia, 2003
Republic of Zambia Zambia National Transport Policy
Government Printers, Lusaka, Zambia, 2003
Republic of Zambia Sixth National Development Plan
Government Printers, Lusaka, Zambia, 2011
Republic of Zambia Mashona Railway Company Limited Act 1965
Republic of Zambia Mufulira Mokambo Railway Act 1965
Republic of Zambia Nkana-Nchanga Branch Railways Act 1965
Republic of Zambia Railway Transfer of Statutory PoIrs Act 1964
Republic of Zambia The Railways Act 1982
Republic of Zambia The Railways (Deviation) Act 1965
Republic of Zambia Rhodesia Railways Act 1965
Republic of Zambia The Rhodesia Railway Act, 1949
Republic of Zambia Roan Antelope Branch Railway Act 1965
Republic of Zambia The Tanzania Zambia Railway Act 1993
Republic of Zambia 2003 GRZ/RSZ Concession 2003
Stuart Cole Applied Transport Economics: Policy Management and Decision making
3rd
Edition
Kogan Page Limited, London, United Kingdom, 2005
World Bank Zambia Railways Restructuring Project
Report No. 32520 December 20, 2005
53
9.0 Annexure
Annex 1: Questionnaire used in research
Annex 2a: Financial data on ZRL and RSZ 1994-2011
Annex 2b: Adjusted Financial data on ZRL and RSZ 1994-2011
Annex 3: Unit Root test of Stationarity for the dependent and explanatory regression variables
Annex 4: Regression results for using data in Annex 2b
54
Annex 1: Questionnaire used in research
55
Annex 2: Annual Financial Data: ZRL & RSZ 1994-2011 (In millions except employee numbers)
YEAR REV PRFTLOS PSNGERS CARGO EMPLYEE CAPITAL STAF COST dGRZREG GDP
1994 26580 -158028 1806 19095 2585 10259 1162 0 2240129
1995 23148 -5981 1307 16629 3087 12254 1387 0 2176903
1996 30375 41758 1715 21821 5514 21885 2478 0 2328057
1997 52657 3690 2973 37829 6533 25930 2936 0 2404904
1998 49183 -6346 3343 39397 5041 20008 1682 0 2360203
1999 90946 -5288 4883 60236 3308 17678 1870 0 2412729
2000 97090 -7949 4907 66002 3162 94835 2554 0 2497554
2001 120085 -96867 4382 84702 1775 190431 2049 0 2619796
2002 143659 -6000 2677 109021 1538 213146 1793 0 2706706
2003 162989 8400 2550 95133 1538 208314 1399 0 2845492
2004 133688 14777 7445 126243 856 57800 4770 1 2999252
2005 127632 912 7200 119106 1018 44183 3953 1 3159453
2006 138548 7328 3049 132821 1039 94877 25238 1 3356135
2007 131701 -208 4241 120494 914 71397 34531 1 3563998
2008 176884 -2504 6469 161863 974 112342 36643 1 3766490
2009 163813 3863 5506 150942 893 125943 34037 1 4007660
2010 196841 -992 4592 185937 886 155360 38736 1 4313050
2011 185166 175 4410 172432 927 200877 41120 1 4591873
56
Annex 2.b: Adjusted ZRL &RSZ Financial Data (1995-2010) to quarterly level using Lisman and Sandee Matrix
YEAR REV PRFTLOS PSNGERS CARGO EMPLYEE CAPITAL STAFCOST dGRZREG GDP
95Q1 5884.703 -13586.8 354.5183 4227.47 683.9445 2714.85 307.3274 0 545645.6
Q2 5451.73 -1910.33 304.6783 3916.382 676.2001 2684.362 303.791 0 537301.6
Q3 5570.134 4322.989 301.8391 4001.433 767.5849 3047.093 344.8502 0 540045
Q4 6241.433 5193.115 345.9643 4483.714 959.2705 3807.694 431.0314 0 553910.8
96Q1 6596.752 7762.562 372.463 4738.984 1180.071 4683.801 530.3023 0 569373.7
Q2 6743.485 12511.03 380.7454 4844.396 1361.21 5402.582 611.7303 0 580382
Q3 7664.166 12812.77 432.7246 5505.836 1468.725 5829.273 660.0591 0 587495.6
Q4 9370.598 8671.636 529.067 6731.784 1503.995 5969.345 675.9083 0 590805.7
97Q1 11613.19 3909.417 643.7348 8257.182 1590.446 6312.574 727.0712 0 596567
Q2 13537.93 946.8936 740.8524 9557.06 1705.664 6769.927 790.7584 0 603872.6
Q3 14124.74 -553.951 791.646 10105.43 1690.906 6711.364 765.9232 0 604875.6
Q4 13381.15 -612.359 796.7668 9909.326 1545.984 6136.136 652.2472 0 599588.8
98Q1 11667.81 -877.199 776.283 9295.24 1405.583 5482.877 507.9498 0 592201.2
Q2 10526.8 -1733.78 775.651 9000.582 1316.802 5037.698 399.7818 0 587410.5
Q3 11721.42 -2013.89 835.243 9699.68 1216.182 4780.236 366.5226 0 587654.6
Q4 15266.97 -1721.13 955.823 11401.5 1102.433 4707.189 407.7458 0 592936.7
99Q1 19562.34 -1342.98 1107.978 13418.17 956.4163 2961.344 439.3624 0 597563.3
Q2 22911.68 -1200.67 1235.616 15034.35 815.2091 1193.486 441.0504 0 600203
Q3 24406.38 -1250.68 1284.413 15864.43 756.5843 3528.088 468.2568 0 604488.4
Q4 24065.6 -1493.66 1254.994 15919.04 779.7903 9995.082 521.3304 0 610474.3
00Q1 23339.41 82.9067 1236.078 15685.59 830.4091 16066.93 599.2919 0 615625.5
Q2 23381.49 1675.439 1248.785 15783.84 846.5567 20536.23 666.5027 0 620189.2
Q3 24290.63 -1181.83 1233.154 16547.18 798.7271 25926.13 672.0875 0 626649.6
Q4 26078.47 -8525.52 1188.984 17985.39 686.3071 32305.71 616.1179 0 635089.7
01Q1 27847.5 -19651.9 1169.748 19299.14 549.863 40159.52 554.4661 0 644203.8
Q2 29279.78 -28903.6 1160.85 20358.87 439.2994 47649.72 517.6725 0 652601.3
Q3 30732.73 -28842.8 1091.274 21701.06 388.6306 51341.02 493.9293 0 659126.9
Q4 32224.99 -19468.7 960.128 23342.93 397.207 51280.75 482.9321 0 663864
02Q1 33788.34 -8428.04 796.2242 25775.43 401.7773 51732.53 475.2258 0 667412.4
Q2 35355.37 -1161.67 656.959 28082.09 382.0589 53720.99 461.9642 0 671812.1
Q3 36693.97 2122.661 599.8006 28407.53 374.6645 54278.94 441.6842 0 678853.8
Q4 37821.32 1467.054 624.0162 26755.95 379.4993 53413.53 414.1258 0 688627.8
03Q1 39956.34 915.6853 543.4738 24139.26 398.8902 55606.6 307.3445 1 698011.2
Q2 42162.34 1983.675 433.0494 22349.14 412.803 58275.06 205.7953 1 706421.5
Q3 41851.25 2631.917 581.811 22886.47 391.5246 53428.27 298.6777 1 715548.9
Q4 39019.07 2868.723 991.6658 25758.13 334.7822 41004.07 587.1825 1 725510.5
04Q1 35685.82 3521.918 1509.574 29443.42 260.2996 25709.79 963.9928 1 735223.7
Q2 33371.52 4335.331 1921.836 32177.37 200.2524 13464.81 1261.127 1 744748.4
57
Q3 32268.39 4101.705 2066.916 32925.33 184.0284 8343.924 1340.812 1 754544
Q4 32362.27 2818.046 1946.674 31696.88 211.4196 10281.48 1204.069 1 764736
05Q1 32119.15 1103.381 1905.447 30007.4 242.2471 10968.79 598.6958 1 774034.6
Q2 31392.61 -181.074 1969.743 29133.82 255.2971 8801.694 96.5074 1 783351
Q3 31544.24 -413.482 1832.588 29339.05 261.0067 9958.496 735.109 1 794485.8
Q4 32575.99 403.1749 1492.223 30625.73 259.4491 14454.02 2522.688 1 807581.6
06Q1 33985.7 1523.283 1039.707 32465.53 260.8566 20519.09 4561.741 1 820309.7
Q2 35033.59 2210.829 670.0267 33858.09 265.1538 25215.82 6143.076 1 832433.3
Q3 35160.54 2175.885 577.7059 33901.39 261.909 26064.9 7097.11 1 845055.1
Q4 34368.18 1418.003 761.5607 32596 251.0806 23077.2 7436.073 1 858337
07Q1 32471.04 545.82 926.3424 30149.25 236.3465 18697 7910.727 1 871573.7
Q2 30979.63 -34.3368 980.0656 28279.72 224.7225 15908.19 8640.82 1 884737.1
Q3 32175.71 -341.095 1086.77 29185.83 222.6945 16453.1 8996.656 1 897540.1
Q4 36074.62 -378.388 1247.822 32879.2 230.2365 20338.71 8982.797 1 910147.1
08Q1 41202.96 -592.965 1475.148 37680.38 240.8351 24813.63 9061.772 1 921772.1
Q2 45228.83 -913.879 1680.163 41345.07 247.4795 27942.79 9290.653 1 933699.6
Q3 46230.73 -786.864 1719.631 42295.05 246.8243 29644.63 9275.24 1 947541.9
Q4 44221.49 -210.291 1594.058 40542.5 238.8611 29940.95 9015.336 1 963476.4
09Q1 41209.24 604.0362 1465.988 37793.25 229.3026 29873.54 8600.079 1 977890
Q2 39447.96 1232.813 1404.512 36170.72 222.7062 30405.03 8287.4 1 991725.4
Q3 40070.62 1279.987 1345.95 36921.83 219.9606 31747.2 8352.701 1 1008778
Q4 43085.19 746.1642 1289.55 40056.2 221.0306 33917.23 8796.821 1 1029267
10Q1 47048.85 81.3058 1218.471 44218.07 221.1452 35735.09 9291.141 1 1050116
Q2 50034.95 -346.437 1146.139 47405.16 219.7264 37254.04 9633.464 1 1069837
Q3 50701.16 -461.503 1111.944 48075.64 220.7872 39591.98 9854.453 1 1088064
Q4 49056.03 -265.366 1115.447 46238.13 224.3412 42778.89 9956.943 1 1105032
58
Annex3: Unit Root Test -Stationarity of regression variables 1. REVENUE
ADF Test Statistic -10.97109 1% Critical Value* -3.5398 5% Critical Value -2.9092 10% Critical Value -2.5919
*MacKinnon critical values for rejection of hypothesis of a unit root.
Augmented Dickey-Fuller Test Equation Dependent Variable: D(REV,2) Method: Least Squares Date: 09/13/12 Time: 10:42 Sample(adjusted): 1995:4 2010:4 Included observations: 61 after adjusting endpoints
Variable Coefficient Std. Error t-Statistic Prob.
D(REV(-1)) -0.490359 0.044696 -10.97109 0.0000 D(REV(-1),2) 0.908748 0.062131 14.62625 0.0000
C 318.4596 84.18002 3.783078 0.0004
R-squared 0.812966 Mean dependent var -28.91041 Adjusted R-squared 0.806516 S.D. dependent var 1376.757 S.E. of regression 605.5914 Akaike info criterion 15.69822 Sum squared resid 21270976 Schwarz criterion 15.80203 Log likelihood -475.7956 F-statistic 126.0518 Durbin-Watson stat 1.096467 Prob(F-statistic) 0.000000
2. PROFIT/LOSS ADF Test Statistic -5.343723 1% Critical Value* -3.5380
5% Critical Value -2.9084 10% Critical Value -2.5915
*MacKinnon critical values for rejection of hypothesis of a unit root.
Augmented Dickey-Fuller Test Equation Dependent Variable: D(PRFTLOS) Method: Least Squares Date: 09/13/12 Time: 10:44 Sample(adjusted): 1995:3 2010:4 Included observations: 62 after adjusting endpoints
Variable Coefficient Std. Error t-Statistic Prob.
PRFTLOS(-1) -0.183575 0.034353 -5.343723 0.0000 D(PRFTLOS(-1)) 0.744329 0.067876 10.96600 0.0000
C -242.2366 243.4386 -0.995062 0.3238
R-squared 0.688588 Mean dependent var 26.53175 Adjusted R-squared 0.678032 S.D. dependent var 3356.412 S.E. of regression 1904.503 Akaike info criterion 17.98901 Sum squared resid 2.14E+08 Schwarz criterion 18.09193 Log likelihood -554.6592 F-statistic 65.22991 Durbin-Watson stat 0.889428 Prob(F-statistic) 0.000000
59
3. PASSENGERS ADF Test Statistic -4.724712 1% Critical Value* -3.5380
5% Critical Value -2.9084 10% Critical Value -2.5915
*MacKinnon critical values for rejection of hypothesis of a unit root.
Augmented Dickey-Fuller Test Equation Dependent Variable: D(PSNGERS) Method: Least Squares Date: 09/13/12 Time: 10:48 Sample(adjusted): 1995:3 2010:4 Included observations: 62 after adjusting endpoints
Variable Coefficient Std. Error t-Statistic Prob.
PSNGERS(-1) -0.117552 0.024880 -4.724712 0.0000 D(PSNGERS(-1)) 0.810068 0.071170 11.38222 0.0000
C 127.8788 28.63545 4.465751 0.0000
R-squared 0.704852 Mean dependent var 13.07691 Adjusted R-squared 0.694847 S.D. dependent var 161.4080 S.E. of regression 89.16285 Akaike info criterion 11.86598 Sum squared resid 469050.8 Schwarz criterion 11.96891 Log likelihood -364.8455 F-statistic 70.44985 Durbin-Watson stat 1.074979 Prob(F-statistic) 0.000000
4. CARGO ADF Test Statistic -20.32655 1% Critical Value* -3.5398
5% Critical Value -2.9092 10% Critical Value -2.5919
*MacKinnon critical values for rejection of hypothesis of a unit root.
Augmented Dickey-Fuller Test Equation Dependent Variable: D(CARGO,2) Method: Least Squares Date: 09/13/12 Time: 10:50 Sample(adjusted): 1995:4 2010:4 Included observations: 61 after adjusting endpoints
Variable Coefficient Std. Error t-Statistic Prob.
D(CARGO(-1)) -0.567658 0.027927 -20.32655 0.0000 D(CARGO(-1),2) 0.993705 0.036912 26.92117 0.0000
C 363.4330 48.43053 7.504213 0.0000
R-squared 0.935904 Mean dependent var -31.51746 Adjusted R-squared 0.933694 S.D. dependent var 1337.815 S.E. of regression 344.4869 Akaike info criterion 14.56992 Sum squared resid 6882930. Schwarz criterion 14.67373 Log likelihood -441.3825 F-statistic 423.4472 Durbin-Watson stat 1.204037 Prob(F-statistic) 0.000000
60
5. CAPITAL ADF Test Statistic -5.211015 1% Critical Value* -3.5398
5% Critical Value -2.9092 10% Critical Value -2.5919
*MacKinnon critical values for rejection of hypothesis of a unit root.
Augmented Dickey-Fuller Test Equation Dependent Variable: D(CAPITAL,2) Method: Least Squares Date: 09/13/12 Time: 10:52 Sample(adjusted): 1995:4 2010:4 Included observations: 61 after adjusting endpoints
Variable Coefficient Std. Error t-Statistic Prob.
D(CAPITAL(-1)) -0.320748 0.061552 -5.211015 0.0000 D(CAPITAL(-1),2) 0.662949 0.098808 6.709442 0.0000
C 214.6240 249.6900 0.859562 0.3936
R-squared 0.490012 Mean dependent var 46.29797 Adjusted R-squared 0.472426 S.D. dependent var 2656.476 S.E. of regression 1929.511 Akaike info criterion 18.01585 Sum squared resid 2.16E+08 Schwarz criterion 18.11966 Log likelihood -546.4835 F-statistic 27.86411 Durbin-Watson stat 1.296867 Prob(F-statistic) 0.000000
6. STAFF COST ADF Test Statistic -5.769077 1% Critical Value* -3.5398
5% Critical Value -2.9092 10% Critical Value -2.5919
*MacKinnon critical values for rejection of hypothesis of a unit root.
Augmented Dickey-Fuller Test Equation Dependent Variable: D(STAFCOST,2) Method: Least Squares Date: 09/13/12 Time: 10:54 Sample(adjusted): 1995:4 2010:4 Included observations: 61 after adjusting endpoints
Variable Coefficient Std. Error t-Statistic Prob.
D(STAFCOST(-1)) -0.334978 0.058064 -5.769077 0.0000 D(STAFCOST(-1),2) 0.708371 0.092768 7.635942 0.0000
C 50.84667 26.80789 1.896706 0.0629
R-squared 0.550493 Mean dependent var 1.007049 Adjusted R-squared 0.534993 S.D. dependent var 289.2603 S.E. of regression 197.2508 Akaike info criterion 13.45476 Sum squared resid 2256656. Schwarz criterion 13.55857 Log likelihood -407.3701 F-statistic 35.51514 Durbin-Watson stat 1.235884 Prob(F-statistic) 0.000000
61
7. EMPLOYEES ADF Test Statistic -4.969188 1% Critical Value* -3.5398
5% Critical Value -2.9092 10% Critical Value -2.5919
*MacKinnon critical values for rejection of hypothesis of a unit root.
Augmented Dickey-Fuller Test Equation Dependent Variable: D(EMPLYEE,2) Method: Least Squares Date: 09/13/12 Time: 15:38 Sample(adjusted): 1995:4 2010:4 Included observations: 61 after adjusting endpoints
Variable Coefficient Std. Error t-Statistic Prob.
D(EMPLYEE(-1)) -0.273078 0.054954 -4.969188 0.0000 D(EMPLYEE(-1),2) 0.621649 0.094663 6.566998 0.0000
C -3.568325 3.959953 -0.901103 0.3713
R-squared 0.479185 Mean dependent var -1.439849 Adjusted R-squared 0.461225 S.D. dependent var 41.90440 S.E. of regression 30.75836 Akaike info criterion 9.738130 Sum squared resid 54872.45 Schwarz criterion 9.841944 Log likelihood -294.0130 F-statistic 26.68191 Durbin-Watson stat 1.407855 Prob(F-statistic) 0.000000
8. GDP ADF Test Statistic -10.66458 1% Critical Value* -3.5417
5% Critical Value -2.9101 10% Critical Value -2.5923
*MacKinnon critical values for rejection of hypothesis of a unit root.
Augmented Dickey-Fuller Test Equation Dependent Variable: D(GDP,3) Method: Least Squares Date: 09/13/12 Time: 10:57 Sample(adjusted): 1996:1 2010:4 Included observations: 60 after adjusting endpoints
Variable Coefficient Std. Error t-Statistic Prob.
D(GDP(-1),2) -0.854808 0.080154 -10.66458 0.0000 D(GDP(-1),3) 0.559727 0.079783 7.015637 0.0000
C 131.5945 198.1118 0.664244 0.5092
R-squared 0.686434 Mean dependent var -206.3633 Adjusted R-squared 0.675432 S.D. dependent var 2660.368 S.E. of regression 1515.635 Akaike info criterion 17.53376 Sum squared resid 1.31E+08 Schwarz criterion 17.63848 Log likelihood -523.0129 F-statistic 62.38999 Durbin-Watson stat 1.798878 Prob(F-statistic) 0.000000
62
Annex 4: Regression results for using data in Annex 2b Revenue= Passenger rev + Cargo rev + Capital Inv + Employee No. + GDP
Result 1: Assuming no structural break 1994-2011
Result 2: Assuming structural break 1995-2003 Under Government control & regulation
Result 3: Assuming structural break 2004-2010 Under Concession (RSZ) RESULT 1 (REV(-1)) C (PSNGERS(-1)) (CARGO(-1)) (CAPITAL(-1)) (EMPLYEE(-1),2) (GDP(-1)) 1995-2010 Dependent Variable: REV(-1) Method: Least Squares Date: 09/13/12 Time: 17:45 Sample(adjusted): 1995:2 2010:4 Included observations: 63 after adjusting endpoints
Variable Coefficient Std. Error t-Statistic Prob.
C 2989.774 3903.515 0.765918 0.4469 PSNGERS(-1) 2.670481 1.122918 2.378162 0.0208
CARGO(-1) 0.723771 0.128620 5.627201 0.0000 CAPITAL(-1) 0.254962 0.029782 8.560910 0.0000 EMPLYEE(-1) -0.423811 1.318892 -0.321339 0.7491
GDP(-1) 0.000124 0.007196 0.017179 0.9864
R-squared 0.965773 Mean dependent var 28415.60 Adjusted R-squared 0.962771 S.D. dependent var 12845.97 S.E. of regression 2478.602 Akaike info criterion 18.55917 Sum squared resid 3.50E+08 Schwarz criterion 18.76328 Log likelihood -578.6139 F-statistic 321.6750 Durbin-Watson stat 0.276746 Prob(F-statistic) 0.000000
RESULT 2: (REV(-1)) C (PSNGERS(-1)) (CARGO(-1)) (CAPITAL(-1)) (EMPLYEE(-1),2) (GDP(-1)) 1995-2003 Dependent Variable: REV(-1) Method: Least Squares Date: 09/22/12 Time: 16:15 Sample(adjusted): 1995:2 2003:4 Included observations: 35 after adjusting endpoints
Variable Coefficient Std. Error t-Statistic Prob.
C -111914.4 7551.069 -14.82100 0.0000 PSNGERS(-1) 0.954102 0.729894 1.307179 0.2014
CARGO(-1) 0.357406 0.091071 3.924490 0.0005 CAPITAL(-1) -0.215012 0.031988 -6.721627 0.0000 EMPLYEE(-1) -8.758468 0.792265 -11.05498 0.0000
GDP(-1) 0.225564 0.014813 15.22740 0.0000
R-squared 0.994001 Mean dependent var 20888.94 Adjusted R-squared 0.992966 S.D. dependent var 11839.39 S.E. of regression 992.9280 Akaike info criterion 16.79400 Sum squared resid 28591275 Schwarz criterion 17.06063 Log likelihood -287.8950 F-statistic 960.9891 Durbin-Watson stat 1.168160 Prob(F-statistic) 0.000000
63
RESULT 3: (REV(-1)) C (PSNGERS(-1)) (CARGO(-1)) (CAPITAL(-1)) (EMPLYEE(-1),2) (GDP(-1)) 2004-2010 Dependent Variable: REV(-1) Method: Least Squares Date: 09/14/12 Time: 06:07 Sample(adjusted): 2004:2 2010:4 Included observations: 27 after adjusting endpoints
Variable Coefficient Std. Error t-Statistic Prob.
C -5741.272 3762.516 -1.525913 0.1420 PSNGERS(-1) 2.582372 0.505512 5.108431 0.0000
CARGO(-1) 0.697191 0.064984 10.72861 0.0000 CAPITAL(-1) 0.225540 0.045677 4.937777 0.0001 EMPLYEE(-1) 22.39086 8.481345 2.640013 0.0153
GDP(-1) 0.005545 0.003275 1.693140 0.1052
R-squared 0.988229 Mean dependent var 37779.67 Adjusted R-squared 0.985426 S.D. dependent var 6209.928 S.E. of regression 749.6794 Akaike info criterion 16.27030 Sum squared resid 11802404 Schwarz criterion 16.55826 Log likelihood -213.6490 F-statistic 352.6003 Durbin-Watson stat 0.411369 Prob(F-statistic) 0.000000