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1 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.

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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.

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Dedication

To my wife Viviane and daughter Thabo, your support and confidence in my efforts are the pillars of my inspiration.

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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.

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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……………………………………………

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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: ……………………………………………………………..

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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

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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

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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

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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

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List of Maps 1. Map 1: Proposed railway projects in Zambia

2. Map 2: Southern Africa Transport Corridors

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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.

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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

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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

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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.

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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

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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:

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(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 :

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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

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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

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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

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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.

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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.

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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

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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

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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.

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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

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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.

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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.

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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

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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

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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?

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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

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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

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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

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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

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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;

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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.

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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

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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

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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)

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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))

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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)

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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

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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.

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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)

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Map 2: Southern Africa Transport Corridors

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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

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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

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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)

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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

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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.

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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

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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

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Annex 1: Questionnaire used in research

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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

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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

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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

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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

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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

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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

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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

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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

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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