Submission of rfi 2016 final

SUBMISSION OF RFI

7/22/2016 THE PHYSICAL VERIFICATION OF LIQUOR OUTLETS IN GAUTENG

Green Lantern Consulting is a small, accounting and tax preparation ser-vice owned by Moss Movement Trading Enterprises (Pty) Ltd., a private company in Gauteng, Johannesburg. The firm offers tax accounting, man-agement accounting, and Sage Pastel set-up and training for small busi-ness clients.

Green Lantern Consulting

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SUBMISSION OF RFI T H E P H Y S I C A L V E R I F I C A T I O N O F L I Q U O R O U T L E T S I N G A U T E N G

Contents ABOUT GREEN LANTERN CONSULTING ............................................................................. 3 ACKNOWLEDGEMENTS ....................................................................................................... 6 ............................................................................................................................................. 6 PREFACE .............................................................................................................................. 7 RECENT HISTORY .............................................................................................................. 10

Legal cases ............................................................................................................................................. 10 SECTION ONE | 1 .............................................................................................................. 11

.................................................................................................................................................................. 11 Basic definitions and concepts ............................................................................................................. 12 Overview ................................................................................................................................................. 12 Presentation of data ............................................................................................................................. 12

SECTION TWO | 2 ............................................................................................................. 12 Gauteng Outlet Census (GOC) ........................................................................................................... 12

INTRODUCTION ................................................................................................................. 14 Overview ................................................................................................................................................. 15 How the count should be done ............................................................................................................ 15

Planning ................................................................................................................................................ 15 Pre-enumeration .................................................................................................................................. 15 Enumeration.......................................................................................................................................... 16 Data processing .................................................................................................................................. 16 Data editing and validation system ................................................................................................ 16 Independent monitoring and evaluation of census field activities ............................................ 17 Post enumeration survey (PES) ......................................................................................................... 18

Conclusion ................................................................................................................................................ 23 GEOGRAPHY OF GAUTENG .............................................................................................. 24

Provincial boundary changes 2001 – 2011 .................................................................................... 24 Local municipal boundary changes 2001 – 2011 .......................................................................... 26 Comparing the GOC with previous censuses ................................................................................... 28

PROPOSITIONS AND INTERPRETATIONS .......................................................................... 29 Demographic characteristics ................................................................................................................ 29

Introduction ........................................................................................................................................... 29 Population size .................................................................................................................................... 29 Population composition ...................................................................................................................... 33 License ratio ......................................................................................................................................... 33 Median age ......................................................................................................................................... 33 Population structure ............................................................................................................................ 33 Concluding remarks ............................................................................................................................ 33

The regulatory field .............................................................................................................................. 34 Informal economy sector status ........................................................................................................... 34

The informal market in South Africa ............................................................................................... 34 Conclusion ............................................................................................................................................. 35

Migration ................................................................................................................................................. 35 Informal settlements .............................................................................................................................. 38

Conclusion ............................................................................................................................................. 39 Expansion ................................................................................................................................................ 39

Conclusion ............................................................................................................................................. 41 PROJECT COSTS ................................................................................................................ 42 ........................................................................................................................................... 49

Proposed Budget ................................................................................................................................... 50 SAFETY MEASURES ............................................................................................................ 50 PAST PROJECT SAMPLE .................................................................................................... 51 ........................................................................................................................................... 52 ........................................................................................................................................... 53 DISCUSSION ...................................................................................................................... 54 RECOMMENDATIONS ........................................................................................................ 55 CONTACTS ........................................................................................................................ 56 REFERENCES ...................................................................................................................... 57

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ABOUT GREEN LANTERN CONSULTING Green Lantern Consulting was founded in 2013 and since that time has grown into the largest Bookkeeping and Business Consulting office in the area. We are an assertive office providing our clients a full range of services. Our offices are located in the Townships of South Africa because this is where we choose to live. However, we serve a wide variety of clients located throughout South Africa. Because our office is smaller than the national Business Consulting companies, we maintain close and open relationships with each of our clients. Our commitment is to provide the highest quality services while retaining a small-town/location atmosphere. Green Lantern Consulting is a member of the Private Companies Practice Section of the South African Institute of Professional Accountants (SAIPA) as well as a member of the Southern African Institute of Business Accountants (SAIBA) through its contracted consultants. It is active in the local provincial chamber of PAs. Professionalism Our office is one of the leading offices in the area. By combining our expertise, experience and the energy of our staff, each client receives close personal and professional attention. Our high standards, service and specialized staff spell the difference between our outstanding performance, and other offices. We make sure that every client is served by the expertise of our whole office. Responsiveness Our office is responsive. Companies who choose our office rely on competent advice and fast, accurate personnel. We provide total financial services to individuals, large and small businesses and other agencies.

To see a listing of our services, please take a moment and look at our services sub-heading. Because we get new business from the people who know us best, client referrals have fueled our growth in the recent years. Through hard work, we have earned the respect of the business and financial communities. This respect illustrates our diverse talents, dedication and ability to respond quickly. Quality A consulting office is known for the quality of its service. Our office's reputation reflects the high standards we demand of ourselves. Our primary goal as a trusted advisor is to be available to provide insightful advice to enable our clients to make informed financial decisions. We do not accept anything less from ourselves and this is what we deliver to you. We feel it is extremely important to continually professionally educate ourselves to improve our technical expertise, business and financial knowledge, and service to our clients. Our high service quality and "raving fan" clients are the result of our commitment to excellence. We will answer all of your questions, as they impact both your tax and financial situations. Services rendered Green Lantern Consulting mainly offers tax accounting, management accounting, and WaveApps set-up and training for small business clients. The business will expand its services to include bookkeeping services for small businesses. This will require an investment in marketing and staff to grow the business to contain this complementary line of business. We have developed a business plan which organizes the strategy and tactics for the business expansion and set objectives for growth over the next three years. The business will offer clients bookkeeping services with the oversight of a Professional Accountant (SA) at a price they can afford. To do this involves hiring undergraduate student bookkeepers and a graduate student manager, keeping fixed costs as low as possible, and continuing to define the expertise of Green Lantern through its website resources.

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Green Lantern Consulting seeks to provide a full suite of tax and management accounting services for small businesses in Johannesburg, Gauteng (SAB Egoli Region customers), allowing business own-ers to not only save money over in-house accounting and ensure their compliance with tax laws, but to make valuable management decisions from their numbers. We also seek to assist Shebeen/Tav-ern permit holders in acquiring Licenses to trade through lodging applications in compliance. The following are some of the key services provided to the client by Green Lantern: Payroll processing Accounts payable (entry, bill paying) Accounts receivable (entry, invoicing, deposits, collection) Sales tax processing Bank reconciliations Inventory management Financial statement preparation Other financial reporting Green Lantern intends to add the following License Application services for Shebeens, and to im-plement business development henceforth: Consent Letter from Municipality Notice of Intention Adverts to Government Gazette Notice of Application Documentation and provision of information on owner’s behalf Publication of notice of intention in two local newspapers Lodging of Application Sketching of Floor Plans Waste Management Solutions Provide double insulated Polyethylene portable toilet solutions (Suitability Certificate) License Renewals

ACKNOWLEDGEMENTS Green Lantern Consulting gratefully acknowledges the important contributions and guidance provided by the following members of its Technical Review Committee: Chair – Ipfi Madisha, Maintained data on topic-related research, and managed submission task • James Dickson, Coordination and administrative support for the submission task • Tshepiso Cwele, Reporting and consultation from field work • Joel Thakhuli, Member of KALTA Association (Liquor Traders Association) Without great support of KALTA liquor traders association it would be not possible to write this RFI proposal. KALTA has always been very responsive in providing necessary information, and without their generous sup-port this submission would lack in accurate information on current developments. In addition, Green Lantern Consulting would like to thank Nepo Pholo, Thabang Mashia, Beryl Mhlongo, Vusimuzi Dhlamini, for their expert contributions to this RFI proposal. The Author – Collin Mkhonza (CEO of Green Lantern Consulting)

(Reg No. 2011/113820/07) MOSS MOVEMENT TRADING ENTERPRISES (PTY) LTD

182 IBIS ESTATE, CAMWOOD STR. ESTHER PARK, EKURHULENI, 1619

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PREFACE In order to understand what it means to physically verify liquor outlets in Gauteng with a vision to phase in licensing, to enable transcendent regulations of the liquor trade as well as manage the informal market and thereby, ultimately, to transform the livelihoods of the general people, policy makers must develop both a foundation of an on-the-ground knowledge and an understanding of the key elements critical to achieving the project success. After a decade of unsuccessful efforts to migrate informal businesses to South Africa’s formal economy there remains little understanding of the dynamics in this sector, especially as regards micro-enter-prises. I developed this submission to provide a framework for acquiring the necessary dexterities in a way that emphasizes the uniqueness of each sector and each individual within the sector, pertaining to the transformation goals. Successful sector communication starts with strong relationships. This submission emphasizes the necessity in building and maintaining these relationships in order to make decisions and complete sector transformation undertakings and movements—that is the essence of socio-economic transformation work. When we look at the dynamics of sector communication, it is easy to see why it can be a challenging subject of thought to tackle. Experience in sectors is what policy makers need, yet this takes time. Until they get this experience, it is up to the consultants to provide them with the conceptual foundation and introduce them to the dexterities necessary for understanding and implementing successful sector communication. This submission will help with these commu-nication challenges. I had three main goals in developing this submission:

• Accuracy This submission is the result of many years of facilitating, researching, and coaching sector communication. It is important to impart to our policy makers artistries that are based in research from both the field of communication and other related disciplines. This document places a clear emphasis on communication dexterities first but also ensures that those dexterities are based on rigorous and current research. • Simulation of the sector experience To describe and explain sector communication concepts, this submission uses realistic examples to help policy makers get inside what sector work is really like. In addition to examples, I have provided dialogues of interacting sectors so policy makers can watch the sector process unfold. Both types of examples will help the GDED distinguish between effective and ineffective sector communication practices, as well as help them identify the practices they wish to adopt to improve their sector interaction. • A structured approach I have defined sector communication in terms of five key elements that can be used to evaluate policy effectiveness. These elements—sector size, interdependence of sec-tor members, group identity, sector goals, and sector structure—are introduced in Section 1 and integrated throughout the submission in the Tables and Figures feature. This framework allows policy makers to place new information and skills development into a larger context.

Approach The title of this document, Submission of RFI: Physical Verification of Liquor Outlets throughout The Gauteng Province, speaks to two fundamental components of sector interaction: building relationships and sector perfor-mance. In this submission, policy makers will discover the unique dynamics of sector communication, the essential artistries that lead to transformation success, and the GDED roles, tasks, and processes that pave the way for effective sector work. By examining sectors from each of these viewpoints, policy makers come to understand

the dynamic capacity of each sector and learn to treat each sector as a unique communication opportunity. To be competent in sector communication, as this submission emphasizes, policy makers must learn to identify each sector situation as unique, assess what skills are needed, and effectively apply the appropriate skills and pro-cedures. In essence, the goal of this text is to provide a toolbox from which planners can draw in any group situation—whether planning a function with an Association at a location or participating in a task-oriented sector project in a business or political context. To start this process, policy makers must first become aware of their own communication in departments and the ways in which it can be improved to enhance sector dynamics. The emphasis here is on critical thinking, skills assessment, and practice. Features Pertaining to the recruitment and placement of 500 young people within the province, the element of group work in respect to the project is eminent. We have thus devised a system of coaching for the students which will enable them to be able to work together in groups, in order to ensure the successful verification strategy as proposed by this submission. These features form part of the verification strategy. This submission contains a number of proposed features to enhance recruited young peoples' learning when implemented:

• Putting the Pieces Together boxes The five core elements in defining a group are used as a structure for evaluating group effectiveness. The five elements are group size, interdependence of members, group identity, group goals, and group structure. These elements are to be introduced and integrated in every phase of the project as a special feature so that students become more aware of how communication inhibits or facilitates group success. • Skills grounded in a solid research base The best advice for communicating in groups is drawn from group research and theory, which has identified the most effective processes and results for group interaction. Thus the skills presented and suggested in the text are research based. An exam-ple is the characteristics of bona fide groups to situate a group within its larger context. The sub-mission introduces the influence of participation, time, diversity, and technology on task activity, information drawn from current research in small group communication. Functional theory is to be used as a framework to evaluate decision-making procedures. And situational leadership is used to help students identify and compare leadership styles and choose the most effective style for a particular group situation. • Extensive use of realistic examples In addition to describing what is happening in groups through the use of extensive examples, this submission proposes the development of transcripts of group dialogues so students can see the communication process unfold. Group dialogues also pro-vide an opportunity to suggest and test different communication approaches. Using the dialogue examples in this way can help students analyze how the group’s conversation might have proceeded differently if alternative communication strategies were employed. • A wide range of group types The proposed project scope speaks to students’ experiences by providing information about a wide variety of groups, including family and social groups, work teams and high-performance task groups, civic and community groups, and discussion and decision-making groups. Whether students’ experiences are with groups that are formal or informal, personal or professional, task oriented or relationally oriented, they need communication skills to build and maintain relationships that support effective problem solving and decision making. • Two types of pedagogical boxes emphasizing skills development

• Mastering Groups Skills: This boxed feature provides students with the opportunity to use an assessment technique to determine the influence of their own communication style on the

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eventual success or failure of the group. This feature ought to be designed to help students understand their stake in and responsibility for group effectiveness.

• Skill Builder: Integrated throughout the project, these boxes give students an opportunity to test, develop, and practice their group communication skills through exercises and activities.

• Other in-project learning aids • Group skills previews: At the beginning of each day, there is an overview for students about

which skills they will be learning and practicing in the day. • End-of-day summaries and discussion questions and exercises. • Glossary sheets. • Extensive list of references for further study.

Organization To provide a foundation, Days 1–5 will see facilitators describe basic communication concepts as they apply to groups or teams. By increasing their abilities to effectively send and receive messages—which, in turn, create the group’s structure—students accomplish the first step in achieving more effective group participation. Days 6–10 address building relationships, decision making, problem solving, conflict management, and leadership—both as interaction opportunities and interaction problems that are a regular and dynamic aspect of group interaction. Increasing students’ skills in these areas will help them maximize their group interaction efforts. Despite the extensive research on group interaction, there is no blueprint for group success. What works in one group situation may fail in another. Thus Days 11–12 cover meeting management, facilitation skills, and tech-niques for providing feedback to the group. Whether in the role of leader or member, students should be able to facilitate their group’s interaction to help the group stay or get back on track. Armed with specific principles, procedures, and feedback techniques, students can make more informed choices about how to help their group. Facilitators’ Resources To assist in proffering with this submission, I have formulated a Facilitator’s Manual. This manual includes the consulting philosophy that was a foundation for this submission, syllabus examples for the group communication daily-course as should be created for the recruited youths, methods of obtaining feedback from students about the course and their learning experiences and expectations which will usher-in and enhance a skills development program moving forward, day-by-day consulting resources, a day-by-day research bank with both objective and essay questions, and suggestions for year-long group projects pertaining to the informal liquor retail ("she-been") sector. The companion website (www.greenlanternsa.co.za/shebeens/) has additional information for both project facilitators and students. Facilitators can access PowerPoint presentations and the Facilitator’s Man-ual, review recent contributions to group communication literature, and find links to other resources for teaching the course. The student section of the website contains learning objectives, practice tests, flashcards, and a glossary review. Students will also find links to groups portrayed in the media, as well as to the type of groups in which they regularly participate. The website is regularly updated with new features and content.

RECENT HISTORY 1International literature discusses ‘exit’ and ‘exclusion’, holding that poor law enforcement is the reason for the persistence and growth of the informal economy. Through examining the informal liquor retail (“shebeen”) sector, we demonstrate that enforcement actually produces informality in this sector. Illustrated with examples from one of our sites in Orlando, Soweto, the submission describes key aspects of shebeen business practice, including the responses to greater law enforcement. Notably, instead of closing shop or facing the hurdles of compliance, the great majority of shebeens continue to evade the law by downscaling their activities. This finding has implica-tions, not just for liquor policy in South Africa, but for understanding both theories of formalisation and theories of the informal economy. It has been estimated there are between 190,000-265,000 informal liquor retailers, or shebeens, in South Africa (Devey et al. 2003 – Labour Force Survey data; Charman 2006; Petersen & Charman 2010). Notably, the great majority of products sold in South African shebeens are legally manufactured by formal, regulated businesses (A&T Consulting, 2005). However as the vast majority of shebeens operate without a state license and almost always in violation of various municipal zoning regulations and by-laws, they are both informal and illegal enterprises. Indeed, recently the Gauteng provincial government passed new liquor legislation that sets tough new criteria for the formalisation of alcohol retailing in the province, not least due a concern for the health and social impacts of alcohol abuse. Gauteng has experienced intensified policing around liquor retail in eco-nomically poor residential areas where the great majority of these enterprises are located (Charman, Petersen & Piper forthcoming). Consequently, the policy implementation around shebeens offers a unique opportunity to gain insight into state enforcement around informal businesses and its impact on the South African economy. Indeed since the legislation has taken effect, not only have few shebeeners migrated into the formal system, but the vast majority have remained informal enterprises, rather improving and developing new coping strategies to better evade law enforcement. In this context, the net result has been to criminalise a key livelihood, and worsen relations between police and shebeeners through ongoing raiding, confiscation and harassment. It has also created an environment conducive to corruption. In addition to offering new insights into a prominent enterprise, an important contribition given the ‘paucity of research on those enterprises that do exist’ (Neves & Du Toit 2012: 132), our submission seeks to shed light on recent theories of formalisation. We wish to show how, contrary to Kanbur (2009, 2012), the enforcement of new laws does not necessarily lead to formalisation or avoidance, but can lead to even more wide-scale and pernicious forms of evasion. In our view this is because of the failure of government to understand the cost-benefit analysis that shebeeners have undertaken to continue operating their businesses despite the new legislative environment. In this regard, we would also disagree with Gelb et al (2009), that the barrier of skills shortages serve as key reasons for the failure of business formalisation in South Africa – at least in respect of shebeens. Legal cases To understand the dynamics and excessive sprouting of shabeens in the country, a situation which threatens to undermine their successful verification, it is advisable to refer to events such as the published case – Case CCT 57/05 – heard on 2 March and 3 May 2006, and decided on 2 June 2006 – where the applicants pursued the confirmation of an order of constitutional invalidity made by the Pretoria High Court in respect of the definition of “shebeen” contained in section 1 of the Gauteng Liquor Act, 2 of 2003 (“the Act”).

1 Charman, A., Petersen, L. & Piper, L. (2013). Enforced Informalisation: the case of liquor retailers in South Africa. DEVELOP-MENT SOUTHERN AFRICA, 30(4–5): 580–595

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SECTION ONE | 1 Collecting data about a population flowchart:

Collecting Data about a Population Flowchart: Census and Sample

Collecting Data About A Population

What is a Population?

Data Sources

Census and Sample

Who or what is the target population?

Will the data be collected from all or part of the population?

How will the data be sourced?

Census Complete enumeration (all)

Sample

Partial enumeration (part)

Population Define target population

Direct data collection Primary data

Indirect data collection

Secondary data

Survey Includes questionnaires, interviews, focus groups and observations

Administrative data source Exist as by product of administrative processes

Basic definitions and concepts Sample Method: A sample survey is a study that obtains data from a subset of a population, in order to estimate population attributes. Census Method: A census is a study that obtains data from every member of a population. In most studies, a census is not practical, because of the cost and/or time required. Overview Location models continue to be recognised as valuable tools for providing insights to decision makers regarding the impacts and relative attributes of potential planning alternatives. An important area of current location modelling research has been devoted to issues associated with siting of undesirable facilities. A number of approaches for addressing equity and community impact in locating these facilities are reviewed and devel-oped in this submission. Application results for the planning models presented in this submission demonstrate their relative benefits and solution characteristics. Presentation of data With Gauteng currently facilitating radical socio-economic transformation and seeking to achieve a fully regu-lated alcohol distribution and trade system, this submission uses a spatial analytical approach to examine, verify and enumerate the number and spatial distribution of alcohol outlets in the province, formal and informal, over a three year horizon.

SECTION TWO | 2 Gauteng Outlet Census (GOC) Green Lantern Consulting has identified a Census to be the most suitable and practical way of carrying out the physical verification of liquor outlets in the Gauteng province. We have termed this the Gauteng Outlet Census (GOC). However it is important to delineate the limitations of the census method of study, as is done here below: A Census method refers to the complete enumeration of a universe. A universe may be a place, a group of people or a specific locality through which we collect the data. The census method is necessary in cases such as population enumeration or animal enumeration etc. for gaining vast knowledge about the particular universe. But in contrary, this method is not applicable or needed pertaining some social problems because it is costly and time consuming. It is difficult to study the whole universe as financial aid is a prerequisite to complete the study. For this reason we use a Sampling method to pick out a sample from the whole universe. The census method is perplex and takes more time in performing data collection. The census method is suitable only in the following cases:

1. Where the universe is not vast; 2. Where there is enough time to collect data; 3. Where a higher degree of accuracy is required and; 4. Where there are enough funds available.

Following are the advantages and disadvantages of the census method:

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A D V A N T A G E S O F T H E C E N S U S M E T H O D Following are the merits of census data collection: INTENSIVE STUDY Data collection through the census method gives opportunity to the investigator to have an intensive study about a problem. The investigator gathers a lot of knowledge through this method. HIGHER DEGREE OF ACCURACY In this method there would be a higher degree of accuracy in the data. No other method is as accurate as the census method in a situation where the universe is small. SUITABLE FOR HETEROGENEOUS UNITS This method is also suitable for units having heterogeneity or nonconformity. INDISPENSABLE IN SOME CASES In certain cases this method is very important and is suitable to be used for data collection. Without this method the study of a universe remains uncompleted. D I S A D V A N T A G E S O F C E N S U S D A T A C O L L E C T I O N Following are the demerits of census data collection: INCONVENIENT This method is inconvenient because it takes too much time, money and a sometimes set of industrial organisations. POSSIBLE IN FEW CASES This method is possible only in few cases of data collection. POSSIBLE IN DEFINED CIRCUMSTANCES This method is possible only in a limited universe, it requires not a vast area of study. TIME AND LABOUR CONSUMING It is much time and labour consuming. It requires a lot of personnel to be involved in the data collection. FATED STATISTICAL ERRORS Data collected through this method will have more statistical errors. Thus we can see that the census method of data collection is helpful only in an area where inquiry is limited, where there is ample time and financial resources available, and in situation in which the data required should be of a high degree of accuracy; otherwise not.

INTRODUCTION While it is beyond the scope of this submission to engage systematically with this wide range of theories, our findings do speak to the notion of the intimate economic linkages between informal and formal business, given that the vast majority of products sold in shebeens are drawn from the formal economy. In addition, notions of rational cost-benefit analysis clearly inform the behaviour and self-understanding of shebeeners. The spatiali-sation of order with different rules applying to different parts of the city, and the over-regulation of the shebeen sector are all evident too. While it is not possible to generalise from the case of shebeens to other microenter-prises in poor areas, and certainly not the informal economy more widely, there is a profound sense in which the existence and nature of the shebeen sector in South Africa is a consequence of politics and policy rather than economic marginalization or market-driven logics. At the end of the day it is instructive to remember that what remains in contention is not the nature of the products that are sold in shebeens (legally manufactured liquor), but rather by whom it is sold, and in what space. This point brings us to the issue of formalisation – that is the process by which informal and sometimes illegal enterprises and activities can be brought into the formal system. The apparent persistence of informality in South Africa gained heightened political attention when, in the late 1990s, former President Thabo Mbeki referred to the notion of a second economy and the state responded in policies and programmes which sought to ‘migrate’ informal businesses across the formal frontier (Devey et al. 2006). After a decade, this migration has largely failed, with recent evidence suggesting that the informal economy has actually continued expanding (Wills 2009). How are we to understand this failure? Writing on the case of employment law in India, Kanbur (2009, 2012) proposes that the persistence of informality can be explained by the non-enforcement of regulations, especially in the case of enterprises that are non-compliant, evade the law and operate illegally. He argues that the challenge is largely one of enforcement. Assuming a context of informality, Kanbur conceptualises four possible positions as regards the standing of enterprises: A) compliant enterprises, B) enterprises that evade compliance, for example ignoring the law, C) enterprises that avoid compliance through adjustment so that the law does not apply to them, and D) enterprises that fall outside the regulatory framework. Kanbur’s argument is that enforcement of informality compels those enterprises positioned in B to either become compliant (A) or to adjust their operations to avoid regulatory controls, in other words move to C position. However, in the case of shebeens in South Africa, the enthusiastic application of law in all our research sites caused very little migration of evasive shebeeners to compliance. It has also not resulted in avoidance, as this is not possible. Instead shebeeners have found increasingly covert ways to evade enforcement, including building the costs of stock confiscation and bribery into the running of the business. The reasoning is straightforward. As compliance is practically impossible for all but a handful of enterprises (primarily due to municipal land use regulations), most shebeeners choose to manage intensified law enforcement impacts on their business rather than go out of businesses altogether and lose their livelihood. The point for Kanbur, is that his model only works, when the policy enforcement aligns with real-world incentives. This is not the case with shebeens and the law in South Africa. Lastly, the diversity of shebeens reminds us that the notion of the ‘informal’ is a residual conceptual category, and that there are potentially significant divisions between those how who could be seen as successful business people or entrepreneurs and those who operate in a more ‘survivalist’ or marginal way. This suggests that a policy framework and practice is possible that distinguishes the ‘entrepreneur’ from the ‘survivalist’ and looks to include the former in the formal system while allowing the survivalist to avoid criminalisation. If correct, this analysis suggests that informality in the shebeen sector is, in significant part, a political and policy issue, and that even if these policy issues were addressed, around at least half of the shebeener population would likely remain operating in survivalist mode in the absence of more meaningful opportunities, and continue trying to run a their small businesses under the state’s radar. To put the point more bluntly, you cannot solve the ‘shebeen problem’ through a policy approach based on law enforcement.

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Overview The Gauteng Outlet Census (GOC) is a principal means of collecting basic population and outlet statistics re-quired for social and economic development, policy interventions and implementations, their (informal liquor retailers) transformation and evaluation. Green Lantern has conducted three similar enumerations (2012, 2013 and 2016). The Green Lantern Outlet Population Tally 2016 was the third enumeration to be conducted since the proceedings before The Pretoria High Court in 2006 and a number of population and outlet attributes were measured and a variety of indicators generated. This part of the submission provides profiled results on all previous Green Lantern Outlet Population Tallies as a precursor to the new and proposed Gauteng Outlet Census which is to cover all related physical verification topics; demographics, migration, evasion of laws, the regulatory field, informal economy sector status, informal settlements, and expansion. How the count should be done The Gauteng Outlet Census (GOC) should be conducted over a long time horizon. It is suited by Green Lantern Consulting for the GOC to be done over a two year period, at first phase, and a post-enumeration and finali-sation of results to be conducted over a year. This means the entire GOC will be done over a three year period. This section focuses on the various activities that Green Lantern proposes should be carried out prior to the finalisation of the results. They can be summarised as follows: Planning, Pre-enumeration, Enumeration, Pro-cessing and Editing. As a precursor to the GOC, a Location Survey should be conducted. The Location Survey (LS) is a large-scale household survey conducted to bridge the gap between the GOC. The purpose of the location Survey is to collect information on the trends and level on demographic and socio-economic data; the extent of poor households; access to facilities and services; levels of employment/unemployment; in order to assist in the planning, evaluation and monitoring of programmes of the GOC. It will be conducted only through a Sampling method as defined earlier in this text under the Basic Definitions and Concepts sub-heading. Ap-proximately 300 households province-wide should be enumerated. Planning This process involves the development of the overall strategy, the structure for the project, component plans and budget. These processes are to be started as soon as feasible and should then be subsequently reviewed after 6 months, after the completion of a Location Survey (LS), three months before. Methodologies and procedures are thereafter developed and tested in a form of mini tests and pilot projects in informal settlements and townships respectively. The findings from these tests will help to refine the plans and methods for the final test called the “Dress Rehearsal”. The latter is expected to be a replica of how the actual count is to be conducted in the GOC, and therefore the timing has to be the same month as the main Census, i.e. on Commencement Month. Pre-enumeration The pre-enumeration phase mainly involves the final preparatory work before the actual count. It starts with mass production of the Gauteng Outlet Census instruments like questionnaires, manuals, field gear etc. The phase also involves acquisition of satellite offices required in the districts, recruitment of the 1st level of field manage-ment staff (District Census Coordinators - 13 DCCs) and Field work Co-ordinators – 6 00 FWCs. These groups of people are then to be given intense training based on their key performance areas. At the same time the province should be sub-divided into small pockets called enumeration areas (EAs); the underlying principle for this sub-division is that an EA should be within reach of a Fieldworker and all outlets in that EA can be covered within the allocated number of days. This process should yield approximately 270 EAs. The other benefit for this sub-division is the finalisation of the distribution plan of all materials required in the province and its districts.

It also gives a better estimate of the number of field staff to recruit for the count. The pre-enumeration phase will involve approximately over 2000 staff. Enumeration The enumeration phase, starts with the training of supervisors as listers. Each person has to list all dwellings within an EA and has a minimum of 2 EAs to cover. These areas are to be called supervisory units. As they are listing, they are also to be expected to publicise the activities of the GOC within their supervisory units. Upon completion of listing, final adjustments of workload and number of enumerators required are finalised. Training of enumerators starts in earnest, and it mainly covers how to complete the questionnaire and to read a map. The latter is to aid them to identify the boundaries of their assigned areas. An enumerator is also given a few days before the start of the count to update their orientation book with any developments that might have happened since listing, as well as introduce themselves to the communities they are to work with, through posters bearing their photos and special identification cards. On the night of the Commencement Month the actual count starts with informal settlements and special areas (new housing developments) given special attention. The enu-meration phase is to be undertaken by an army of field staff in excess of 2 113, inclusive of management. Data processing The processing of over 4 million questionnaires commences in the first month of Year Three of the GOC, imme-diately after the completion of the reverse logistics in the last month of Year Two of the GOC. Each box and its contents are to be assigned a store location in the processing centre via a store management system. Each time a box is required for any process it is called through this system. The processing phase is sub-divided in the following processes: primary preparation - where all completed questionnaires are grouped into clusters of 34 and the spine of the questionnaire cut off. Secondary preparation - where questionnaires are finally prepared for scanning, by removing foreign materials in between pages and ensure that all pages are loose. Scanning - questionnaires are put through a scanner to create an electronic image. Final Tilling and completion - where any unrecognized reading/ badly-read image by the scanner has to be verified by a data capturer. This process will take approximately 8 months. Over 700 data processors working 3 shifts per day are to be employed for this phase to ensure that 11, 7 million single pages are accounted for. Data editing and validation system The execution of each phase of the Gauteng Outlet Census operations introduces some form of errors in Census data. Despite quality assurance methodologies embedded in all the phases; data collection, data capturing (both manual and automated), coding, and editing, a number of errors will creep in and distort the collected information. To promote consistency and improve on data quality, editing is a paramount phase in identifying and minimising errors such as invalid values, inconsistent entries or unknown/missing values. The editing process for the Gauteng Outlet Census must be based on defined rules (specifications). The editing of the GOC data should thus involve a number of sequential processes: selection of members of the editing team, review of the National Census 2016 and 2016 Community Survey editing specifications, development of editing specifications for the GOC pre-tests (informal settlements and townships Pilot Projects and Dress Rehearsal), development of firewall editing specifications and finalisation of specifications for the main Gauteng Outlet Census. EDITING TEAM The Gauteng Outlet Census editing team must be drawn from various divisions of the organisation based on skills and experience in data editing. The team must thus be composed of subject matter specialists (demogra-phers and programmers), managers as well as data processors. This feature lends itself to skills development. A program may be created which will ensure that various skills pertaining to data editing to be transferred to the recruited youths.

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ROLE OF THE TEAM Among other Census activities, editing team roles and responsibilities include:

Establishment of editing plan/schedule Formulation and application of clear and concise editing specifications Validation of Census data using other data sources Ensuring of consistency of editing rules between Censuses (benchmarking) where applicable Provision of imputation flags and rates Identification of errors and provide corrections where possible Review and refinement of the edit specifications based on edit trail evaluations, cross tabulations,

and comparison of Census data with other datasets Testing the specifications before confirming and applying them

Editing specification process commences with activities relating to review of existing editing specifications guide-lines. Census 2001 specifications as well as Community Survey 2007 survey specifications and UN handbook on Census editing may be reviewed to form the basis of the specifications. EDITING STRATEGY FOR GAUTENG OUTLET CENSUS The Gauteng Outlet Census questionnaire should not be very complex, characterised by many sections, yet may have interlinked questions and skipping instructions. Editing of complex, interlinked data items requires appli-cation of a combination of editing techniques. Errors relating to structure are resolved using structural query language (SQL) in Oracle dataset. CSPro software may be used to resolve content related errors. The strategy to be used for the GOC data editing may be implementation of automated error detection and correction with minimal changes. Combinations of logical and dynamic imputation/editing may be used. Logical imputations are preferred, and in many cases as such that may arise substantial effort must be undertaken to deduce a consistent value based on the rest of the outlet’s information. To profile the extent of changes in the dataset and assess the effects of imputation, a set of imputation flags are included in the edited dataset. Imputation flags values include the following: 0 – No imputation was performed; raw data were preserved 1 – Logical editing was performed, raw data were blank 2 – Logical editing was performed, raw data were not blank 3 – Hot-deck imputation was performed, raw data were blank 4 – Hot-deck imputation was performed, raw data were not blank Independent monitoring and evaluation of census field activities Independent monitoring of the GOC field activities are to be carried out by a team of 15 professionals and 100 Monitoring and Evaluation Monitors from Monitoring and Evaluation division. These include field training, publicity, listing and enumeration. This is to make sure that the activities are implemented according to the plans and have independent reports on the same. They also conduct Gauteng Outlet Census and the Post Enumeration Survey (PES) Verification studies to identify the out-of-scope cases within GOC (a sample of 135 EAs) and the PES sample (270 EAs) – which should also be reported in Gauteng Outlet Census PES EA Summary Books.

Post enumeration survey (PES) A post-enumeration survey (PES) is an independent sample survey that is conducted immediately after the com-pletion of Census enumeration in order to evaluate the coverage and content errors of the Census. The PES for the GOC must be undertaken shortly after the completion of GOC enumeration, for a period of about a month, in approximately 270 enumeration areas (EAs) (which later may be increased to 278 due to subdivision of large EAs). The main goal of the PES will be to collect high quality data that would be compared with GOC data in order to determine how many people were missed in the GOC and how many were counted more than once. An Outlet Census is a massive exercise, and while every effort will be made to collect information on all individual outlets in the province, including the implementation of quality assurance measures, it is inevitable that some outlets will be missed and some will be counted more than once. A PES assists in identifying the following types of errors:

• Coverage error: this includes both erroneous omissions (e.g. an outlet that was not enumerated) and erroneous inclusions (e.g. an outlet that moved into the enumeration area (EA) after Census but was still enumerated, or an outlet that was enumerated more than once).

• Content error: this refers to the errors on the reported characteristics of the outlets enumerated during Census.

• The errors may emanate from the following reasons: • Failure to account for all inhabited areas in the EA frame; • EA boundary problems; Incomplete listing of structures and failure to identify all

dwellings within an EA; • Failure to enumerate/visit all listed dwellings within an EA; • Failure to identify all households within a dwelling unit in instances whereby a dwell-

ing unit has more than one household; • Failure to enumerate households (complete questionnaires) for all households due to

refusals, unreturned questionnaires for self-enumeration, inability to contact house-holds, etc.);

• Failure to include all individuals within households; • Failure to observe the inclusion rule based on a person’s presence on Census night

(i.e. failure to apply the de facto rule accurately); and • Lost questionnaires or damaged questionnaires that could not be processed

It is important to note that with the Census Method, usually more people are missed during a Census, and thus the Census count of the population is lower than the true population. This difference is called net undercount. A good example is with the National Census where rates of net undercount can vary significantly for different population groups depending on factors such as sex, age and geographic location. Stats SA obtains estimates of the net undercount, including the type and extent of content errors (reported characteristics of persons and households enumerated in the Census) using information collected through the PES. PREPARATIONS FOR THE PES Planning involves the development of documents outlining the goal and objectives of the PES, timelines of the project, identification of resources (financial, human and otherwise) required for implementing the project, and the development of methodology documents. Timelines for the PES should be synchronised with those of the GOC to ensure the relevance of the project, and adhered to international best practice for maintaining a closed population between GOC and PES data collection, i.e. it should be carried out within a few months, preferably within six (6) months, after the completion of GOC fieldwork to ensure that the impact of natural population changes, such as new establishments, closing-downs as a result of deaths or other, migration, as well as lapses in respondent recall do not complicate the exercise. Activities of the PES include the following:

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• Sampling: sample design and selection; • Development of data collection methodologies: methods and procedures for data collection (pub-

licity, listing and enumeration), including quality control measures applied during data collection; • Development of matching and reconciliation procedures and systems: guidelines for matching, in-

cluding rules for determining the match status of outlets and individuals, as well as computer-based system for capturing outlet and owner records for matching purposes;

• Questionnaire development: selection of data items which allow measurement of coverage and content, including layout design and printing of questionnaire;

• Data collection: publicity, listing and enumeration of outlets in selected enumeration areas (EAs); • Matching and reconciliation: office matching (comparison) of GOC and PES outlet and owner rec-

ords, and revisits to outlets in order to confirm or get more information that might assist in matching unresolved cases; and

• Analysis and reporting: compilation of tables and report on PES results.

METHODOLOGY The PES is an independent survey that replicates the Gauteng Outlet Census in sampled enumeration areas (EAs). The major assumption used in the PES is that the GOC and the PES are independent, the estimate of the percentage missed by the PES but found by the GOC, and the percentage missed by the GOC but found by the PES, can be used to construct estimates of the percentage missed by both PES and GOC. The PES seeks to estimate the total number of owners and outlets in housing units on the night of Commencement Month (GOC night). The units of observation are the persons who spent the GOC night and/or the PES night in these living quarters. SAMPLING The sampling frame for the PES is the complete list of GOC EAs, amounting to 270 EAs as estimated. This phase introduces the Primary Sampling Units. The primary sampling units (PSUs) are the GOC EAs. The principle for selecting the PES sample is that the EA boundaries for sampled EAs should have well defined boundaries, and these boundaries should correspond with those of GOC EAs to allow for item-by-item comparison between the GOC and PES records. Stratification hence follows. The stratification and sampling process followed will allow for the provision of estimates at provincial, district, municipal (geography type = urban) and non-municipal (geography type = informal and squatter-camp) levels, but estimates will only be reliable at provincial and district levels. The sample of 270 EAs is thus selected and allocated to the districts based on expected standard errors which are to be based on those obtained through benchmarking. Outlets in institutions (other than Work-ers’ Hostels), floating outlets are excluded from the PES sample. QUESTIONNAIRE DEVELOPMENT The approach to questionnaire design focused on capturing the main elements for measuring coverage and content errors. Only a few elements from the GOC questionnaire which are not likely to change within a short period (that is between the GOC and the PES reference nights) are to be retained. The questionnaire must allow for the classification of each listed trader/person as ‘non-mover’, ‘in-mover’, ‘out-mover’, or ‘out-of-scope’, with regard to their household presence status on GOC night (Commencement Month). The data items for the PES questionnaire must include first name and surname, date of birth, age, sex, population group and presence of person in dwelling unit on GOC and/or PES night.

FIELDWORK METHODOLOGY The PES replicates the GOC in the sampled EAs, which means that all methodologies and procedures for data collection are based on GOC methodologies and procedures. PES fieldwork is thus split into the following three (3) phases; publicity and listing, enumeration and mop-up operations.

• Publicity and listing are conducted at the same time. Publicity focuses on informing and educating respondents and relevant stakeholders about the purpose of the PES to ensure successful coverage of all dwelling units (DUs) in selected EAs. Listing involves the recording of all structures (including all DUs, number of outlets in DUs and number of persons in households) in the sampled EAs in the EA Summary Books.

• Enumeration involves interviewing respondents and recording responses in the fields provided in the PES questionnaire. Self-enumeration for the PES is discouraged, but is used in instances where the respondent insists on self-enumeration.

• Mop-up operations are to be conducted in the form of follow-up visits by senior field staff to outlets that could not be contacted during the enumeration period.

MATCHING AND RECONCILIATION METHODOLOGY The matching exercise involves the comparison of outlet and owner records in GOC data and PES data. A two-way case-by-case matching must be conducted using the two sources: PES questionnaires and GOC question-naires. Reconciliation visits must then be conducted in order to confirm or get more information that would assist in matching unresolved cases, i.e. outlets or owners enumerated in the GOC that did not correspond with outlets or owners enumerated in the PES. Guidelines for matching, including rules for determining the match status of outlets and owners, are to be developed. A computer-assisted manual matching system is then developed for the capturing of data for matching purposes. PES DATA COLLECTION PES data collection commences immediately after the completion of GOC fieldwork. The PES is a much smaller scale operation (and hence easier to control) than the GOC. These features enable the PES to deliver a more accurate estimate of the percentage of owners and outlets missed by the GOC. PES data collection (field operations) should be independent from GOC operations and the following measures must be taken to maintain the operational independence of the PES:

• independent listing of enumeration areas (EAs) in the PES sample; • using separate/independent office staff in the PES and GOC where possible; • ensuring the PES interviewers are not employed as GOC field staff in the same area, and vice

versa; and • maintaining the confidentiality of the PES sample so that GOC field and office staff are not aware

which areas are included in the PES. Temporary personnel (Fieldworkers and Fieldwork Supervisors) are to be recruited from the EAs/districts in which they would be working and undergo rigorous training on fieldwork procedures to ensure that they deliver work of high quality at the end of the fieldwork phase. Experienced permanent staff from Local Surveys (based in provincial offices) are to be seconded to the project for the duration of data collection in supervisory positions to ensure high quality data and minimise costs. The PES follows the integrated approach towards fieldwork; whereby 1 Fieldworker conducts publicity, listing and enumeration in 1 EA. A total of 547 Fieldworkers and Fieldwork Supervisors are to be appointed for the collection of data in the 278 EAs (initially 270, but may be increased to 278 due to split EAs). A ratio of 1 Fieldwork Supervisor for four (2) Fieldworkers may applied, but due to the spread of the sample in various districts, this ratio may not always be applied.

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MATCHING AND RECONCILIATION The matching process involves the comparison of outlet and owner records in GOC data and PES data. The main phases in the matching process are to be:

• Initial matching which involves searching through the GOC records in order to find the corresponding cases from the PES enumeration records, and vice-versa (a two-way match);

• Capturing which involves the capturing of PES and GOC information on a capturing tool which forms part of the computer-assisted manual matching system. Information for non-matched outlets and owners is also captured;

• Computer-assisted matching which is the automated assigning of an initial match status for the outlets and owners, and owners moving status. This process must be done concurrently with the capturing process. Classifications from initial matching are as follows:

1. Matched 2. Possible match In PES not in GOC: 3. in PES not in GOC - definite non-match 4. in PES not in GOC - insufficient or unclear information 5. in-mover 6. established after GOC 7. in GOC not in PES;

• Reconciliation visits are follow-up visits to outlets in the PES sampled EAs. The purpose of reconcili-

ation visits is to collect relevant information in order to determine the final match status of unresolved cases identified during initial matching. Cases of ‘possible match’, ‘in PES not in GOC - insufficient or unclear information’, and ‘in GOC not in PES’ are considered unresolved and are then sent to the field for reconciliation; and

• Final matching which involves the use of the results obtained from the reconciliation visits and initial

matching phases to assign a definite match status to each case. The table below illustrates the pos-sible outcomes from final matching.

Table 1.1: The table below illustrates the possible outcomes from final matching

ESTIMATION AND TABULATION Coverage measures must be calculated only for cases belonging to the PES universe. The initial estimates – weighted estimates of total from the sample must include the following:

a) Estimated number of non-movers; b) Estimated number of out-movers; c) Estimated number of matched non-movers; d) Estimated number of matched out-movers; e) Estimated number on in-movers; f) Estimated number of erroneous inclusions in the GOC; and g) Estimated number of correctly enumerated persons missed in the PES

Dual system estimation must be used to arrive at the true population of the outlets in the province. This means that two independent sources or ‘systems’ are to be used to arrive at the estimate of the true population: the GOC and the PES. Both estimates contribute to the dual-system estimate, which is more complete than either the GOC or the PES estimate alone. In the end, this true population is compared with the GOC-enumerated popu-lation and the difference is the net undercount (or overcount). The following table is an example which indicates the undercount rates as estimated by a PES.

1. matched In PES not in GOC: 2. missed in GOC 3. PES erroneous inclusion - cases in PES not in GOC that were outside the EA boundaries

or otherwise erroneously included in PES 4. PES insufficient information - cases in PES not in GOC for which a final match status

cannot be assigned due to insufficient information 5. in-mover 6. established after GOC In GOC not in PES: 7. correctly enumerated in GOC, missed in PES 8. GOC erroneous inclusion 9. GOC insufficient information – cases in GOC not in PES for which a final match status

cannot be assigned due to insufficient information

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Table 1.2 Illustration of undercount rates as estimated by a PES

Net Census Coverage Error: Total and Rate by Province

Province Omission rate for persons Omission rate for households

Western Cape 18,6 17,8

Eastern Cape 12,9 10,3

Northern Cape 13,4 14,8

Free State 10,1 9,4

KwaZulu-Natal 16,7 16,5

North West 14,9 17,0

Gauteng 14,7 15,2

Mpumalanga 15,5 14,4

Limpopo 10,0 9,6 The adjustment procedure must consist of creating homogeneous adjustment classes with similar coverage rates and calculating a common undercount rate, adjustment factor and adjustment figure for each class separately. The adjusted figure for the total population is obtained by summing across the adjustment classes. In addition, only the population of outlets receive adjustment classes. The totals for the balance of the population, namely owners living in collective quarters and the homeless on backyards or farms, are not adjusted. Conclusion The Gauteng Outlet Census project will have its own challenges and successes, like any other massive project. Be that as it may, the following are worth mentioning; the GOC fieldworkers who will traverse the province to collect information from households, respondents who will open their doors and lock their dogs to aid the field staff to do their work, the processors who will work 24hrs/7days a week to ensure that the data can be released within a year of enumeration, the proposed GOC management team who will meet daily for two years to steer the project forward; It is only through such concerted efforts that as a province we can and will continuously improve on our endeavours. That is the true meaning of "Ntirhisano."

GEOGRAPHY OF GAUTENG Provincial boundary changes 2001 – 2011 A number of changes occurred in terms of provincial and municipal boundaries during the period between Censuses 2001 and 2011. Of the nine provinces, only two provinces (Western Cape and Free State) were not affected by changes. The provincial boundary changes were mostly as a result of eight cross boundary munici-palities which were absorbed in full into respective provinces. Gauteng's southern border is the Vaal River, which separates it from the Free State. It also borders on North West to the west, Limpopo to the north, and Mpuma-langa to the east. Table 2.1: Geographical land area changes since 2001 Province name Provincial code Land area in square

kilometers _2001 Land area in square kilometers 2011

Western Cape 1 129 462 129 449 Eastern Cape 2 168 966 169 954 Northern Cape 3 372 889 362 599 Free State 4 129 825 129 824 KwaZulu-Natal 5 94 361 92 305 North West 6 104 882 116 231 Gauteng 7 18 178 16 936 Mpumalanga 8 76 495 79 487 Limpopo 9 125 754 122 816 Total 1 220 813 1 219 602

The shift of the national boundary over the Indian Ocean in the North East corner of KwaZulu-Natal to cater for the Isimangaliso Wetland Park led to the increase in South Africa's land area. Boundary changes speak to the increase of land-space. This results in more immigration rates and "settling opportunities", the result thereof, pertaining to our study, is an increase of the informal sector which is widely dominated by the informal liquor retailers (shebeens) as a means of survival. Such situations pose difficulty in the enumeration and verification of these outlets, as the "ground" is forever changing, with owners consistently on the move and operating under "survivalist" mode – meaning they may trade at any given time and then abruptly stop trading, only to continue again after a while, as and when their economic situation dictates.

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Map 2.1: Provincial boundary changes since 2001

Provincial boundary changes mostly affected North West (land size decreased to 11348,9 square kilometres). Most of this was absorbed by Northern Cape. The second largest decrease in land size was for Mpum- langa which decreased by 2991,9 square kilometres with Limpopo being the main recipient of this land area. It should be noted that the increased extent of KwaZulu-Natal is not mainly based on the exchange of Umzikulu (formerly in the Eastern Cape Province) and Matatiele (formerly in KwaZulu-Natal), but due to the shift of the national boundary over the Indian Ocean in the north east corner of the province to cater for the iSimangaliso Wetland Park. In terms of which areas moved to which province, which affects the Gauteng Province, a detailed outline is provided for below.

North West and Gauteng

• Merafong City municipality (2001) was a cross boundary local municipality between North West and Gauteng and was allocated to the Gauteng province based on the current provincial bounda-ries. West Rand (DMA) municipality (2001) was not aligned to the then provincial boundary and was absorbed into Mogale City municipality in full based on the current provincial boundaries.

• City of Tshwane Metropolitan Municipality was a cross boundary municipality between Gauteng

and North West provinces. The portions adjacent to Moretele and Madibeng municipalities were allocated to Gauteng in full based on the current provincial boundaries.

North West and Limpopo:

• Limpopo lost a portion of the Bela Bela municipality to North West’s Moretele municipality. In turn North West lost a portion of the Moretele Municipality to Limpopo’s Bela Bela municipality based on the current provincial boundaries.

Gauteng and Mpumalanga: • A portion of Delmas municipality (2001) now called Victor Kanye was allocated to the City of

Tshwane in Gauteng based on the current provincial boundaries. • Kungwini municipality, now incorporated into the City of Tshwane, was a cross boundary municipality

and is now fully allocated to Gauteng, based on the current provincial boundaries.

Local municipal boundary changes 2001 – 2011 In 2001, the Geographical Frame consisted of 262 local municipalities. This total has been reduced to 234 local municipalities in the 2011 geographical frame. The difference of 28 municipalities is explained as follows: In total, 25 District Management Areas (DMAs) were absorbed into the existing provinces.

• The City of Tshwane absorbed a further two municipalities (Nokeng Tsa Taemane and Kungwini). • A new municipality (Kagisano Molopo – NW379) was established by merging NW391 (Kagisano)

and NW395 (Molopo).

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Map 2.2: Municipal boundary changes in 2001

For municipalities, 107 municipalities decreased in geographical area while 155 municipalities had an in-crease in geographical area.

Figure 2.1: Population density in Gauteng Province

Comparing the GOC with previous censuses Comparison of Gauteng Outlet Census with previous Censuses (2011 and 2016) will require alignment of data for the two Censuses to 2016 municipal boundaries. This is because the country’s provincial demarcations underwent a number of changes at provincial and municipal boundaries as outlined in the section above. In order to maintain a high degree of accuracy, such scrutiny must be made.

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PROPOSITIONS AND INTERPRETATIONS The Gauteng Outlet Census ought to be comprehensive, with a number of topics: demographics, the regulatory field, immigration, informal settlements, expansion and the informal economy sector status. This chapter pre-sents key interpretations and propositions from each of the outlined topics. Demographic characteristics Introduction A Census is the basic source of demographic information at all levels of geography in a given area at a de-fined time. This part provides hypothesized information on size, composition and structure of the population of outlets in Gauteng from 2016–2022. This serves as an example of the type of data capturing which will be required for the continuing implementation of the GOC for control and enhancement purposes. Population size Table 3.1: Total outlet population by district, Gauteng Outlet Censuses 2016, 2019 and 2022 District GOC 2016 GOC 2019 GOC 2022

City of Johannesburg Metropolitan Municipality

6 875 8 335 10 734

Ekurhuleni Metropolitan Municipality

4 244 5 651 9 053

City of Tshwane Metropolitan Municipality

5 864 7 919 9 861

Sedibeng District Municipality

3 504 4 775 5 590

Metsweding District Municipality

2 302 4 129 6 300

West Rand District Municipality

7 223 8 098 9 953

Gauteng 30 012 98 907 51491 Censuses 2016 and 2019 have been aligned to 2022 municipal boundaries

Table 3.1 indicates that the population size of Outlets in Gauteng has increased noticeably from 30 thousand in 2016 to 51 thousand in 2022. Johannesburg, followed by West Rand, which has the majority of the popula-tion in both in Censuses 2016 and 2019, but was overtaken by Tshwane in Location Survey 2015 and GOC 2016, leaving Tshwane to take second place. (Example scenario) Figure 3.1: Percentage distribution of outlet-population by district, 2016–2022 (exemplar)

58,3

22,5

53,5

44,5

44,2

53,657,

4

34,4

41,8

52,8

32,3

53,3

22

33

55

44

22

55,3

54,2

43,7 44,5

23,5

54,3

J M E M T M S D M D W R

Census 2016 Census 2019 LS 2015 Census 2011

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Table 3.2: Exemplar Population and percentage change by district: Censuses 2016, 2019 and 2022, and LS 2018 Districts Census

2016 Census 2019

2016-2019 % change

CS 2018 2017-2018 % change

Census 2022

2019-2022 % change

JM 3 956 875 4 524 335 14,3 5 278 585 16,7 5 822 734 10,3

EM 6 147 244 6 278 651 2,1 6 527 747 4,0 6 562 053 0,5

TM 1 011 864 991 919 -2,0 1 058 060 6,7 1 145 861 8,3

SD 2 633 504 2 706 775 2,8 27 73 058 2,5 2 745 590 -1,0

MD 8 572 302 9 584 129 11,8 10 259 229

7,0 10 267 300

0,1

WR 2 727 223 2 984 098 9.4 3 056 083 2,4 3 509 953 14,9

South Af-rica

40 583 573

44 819 778

10,4 48 502 059

8,2 51 770 560

6,7

Table 3.2 provides the district percentage share of the total population for the three periods: 2016–2019, 2017– 2018 and 2019 to 2022.

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Table 3.3: Percentage distribution of the population by population group and district, 2016–2022(Exemplar)

Black African Coloured Indian/Asian White Other

District 2016 2017 2018 2022 2016 2017 2018 2022 2016 2017 2018 2022 2016 2017 2018 2022 2022

JM 21,6 26,7 30,1 32,9 56,0 53,9 50,2 48,8 1,1 1,0 1,3 1,0 21,4 18,4 18,4 15,7 1,6

EM 86,6 87, 87,6 86,3 7,7 7,7 7,5 8,3 0,3 0,3 0,3 0,3 0,3 0,3 0,3 0,3 0,3

TM 44,9 46,5 39,8 50,4 43,7 42,9 50,0 40,3 3 0,2 0,2 3 0,2 0,2 0,7 11,2 10,3 10,0 1,6

SD 45,8 45,5 46,6 369,6 12,6 85,5 596, 66,5 44, 66,5 88,5 24,6 46,5 98.5 58.5 79.5 75.1

MD 16. 35.2 .13 13.2 13.2 15.2 46.5 489. 47.2 75. 645.5 72.5 456.5 51 510.5 6.6 6512.

NW 56.3 63. 6126 6526 .56 15 89 4564 654 464 154 16 498 89 59 5 9

WR 45 98 66 55 66 45 42 525 121 22 121 55 33 44 66 146 546

SA 16 48 55 36 114 61 49 15 65 366 364 41 13 13 1233 13 133

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Population composition Figure 3.3 would present the percentage distribution of the population by sex in the three Censuses and LS 2018. Overall; the results would indicate whether the population is predominantly female. On average, based on current research, the population consists of 48,2% of the male population and 51,7% of the female popu-lation License ratio License ratio is one of the key measures of outlet composition. It would give the number of males for every 100 females who operate licensed outlets. If it is above 100, it then would show the predominance of males over females, conversely when it is lower than 100, the reverse would be true. Generally permit ratios at establish-ment of new outlets are high and decrease gradually as business increases due to applications for licenses. The sharpest evidence for such a contrast is that 75% of the high volume outlets based on current research have obtained liquor licenses, yet only 20% of medium volume outlets have licenses. Indeed only 50% per cent of the mid volume outlets even apply for licenses. This would indicate that enterprise size is relevant to formalisa-tion, and that the incentives to formalise become more real when a business is doing more than 66 creates a week and when, for example, direct deliveries would then improve efficiency. However, at least half of the identified high and medium volume businesses whose turnover is sufficient to warrant formalisation chose to remain informal and unlicensed. Median age Generally median age gives an indication of whether the population is young, old or intermediate. Shryock et al1. (1976) described a population as being young when it has a median of less than 20 and those with medians of 30 and above as being old. Those with median ages between 20 and 29 are referred to as populations of intermediate age. Population structure Knowledge about the age-sex distribution of a population is valuable information on demographics and socio-economic concerns. Amongst its importance, it can be used to evaluate, adjust the completeness and accuracy of Census counts. Nationally, the figures will show that there is a fairly large proportion of females than males in all age groups except for younger age groups where the proportion of males is higher than females. However many factors could contribute to a decrease of this enumeration section. Further analysis would therefore be scheduled to be done to ascertain the key drivers to such an occurrence. Concluding remarks Age-sex distribution indicate a marked increase or decline for both males and females at various ages. The provincial share of the population indicates the status of the population in Gauteng. Among the population groups, it can be determined which population constituted more than which during the census periods. Functional age group patterns show age group differences for both males and females whilst projecting the status of those of the economically active population over time. For this study it is worth noting that the majority of outlet owners are women, as dictated in the simple terms of the economy, they are the primary care givers of any household.

The regulatory field Introduction The notion of the informality, in its early articulation, focused on the presence of economic activities outside state regulatory frameworks. Hart (1973), for instance, characterised the informal sector (economy) as “unregulated economic enterprises or activities”. It is important to note that this submission focuses only on one form of micro-enterprise, and while these are central to the informal economy, this is only one of many different kinds. In respect of the definition of micro-enterprises it should be noted that the National Small Business Act 1996, and Amendment Act (26 of 2003) considers such to refer to businesses employing less than five people, have a turnover of less than R 200 000 and assets less than R 100 000. Informal micro-enterprises are ‘businesses that are not registered in any way… small in nature… and operated from homes, street pavements and other informal arrangements” (Statistics South Africa Labour Force Survey: March 2007). Small in size and relatively poor in business assets, informal micro-enterprises are characterised by their reliance on extended family net-works to provide access to capital and labour often on terms that usually cannot be matched in the formal economy (Collins et al 2009). Attendance to requirements The regulation of shebeens presents a paradox. Their inclusion within the regulatory framework would allow for the enforcement of trading conditions, including restrictions on under-age drinking and poor employment conditions. Yet their regulation would require the acceptance of their spatial location, as most are situated in the heart of residential areas of economically marginalised communities, where land use is deemed residential and commercial activities are commonly not permitted. It would also acknowledge acceptability of businesses that some interest groups question, given their religious, ideological, or personal aversion to alcohol. The issue of the regulation of shebeens has been debated in the context of a moral panic, where access to alcohol has been presented as a harbinger of crime, violence and social conflict (Parry & Dewing 2006). It is not surprising, therefore, that all provincial governments have, with varying degrees of intention, all chosen to exclude she-beens from the regulatory framework, restricting licences to formal business. The result is then the evasion of laws by outlet owners. Informal economy sector status The informal market in South Africa INTRODUCTION The source of ‘official’ labour market statistics in the country is the Quarterly Labour Force Survey (QLFS). Census 2011 also included labour market questions; however, the results may be different from those obtained from the QLFS completed in the fourth quarter of 2011 (QLFS_Q4:2011) for two main reasons. The reference period for employment in Census 2011 was fixed (the week before the Census night – 9 October 2011). In contrast, the QLFS used a moving reference period (the week prior to the date of the interview) over a three-month period. The QLFS therefore included persons who were employed during the course of every month in the October–December quarter while in principle, the Census only included those employed in the first week of October. In addition, Census 2011 results are based on the de facto measure of the population while the QLFS is based on the de jure measure. As a result, the household questionnaire used in Census 2011 to collect labour market information was not intended for persons who either spent Census night in institutions or were transients. To the extent that these groups included employed persons, their labour market status would not be known, since they were only required to complete a shorter questionnaire which excluded labour market questions.

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The Gauteng Outlet Census should thus adopt a de jure system of measurement, as such the dynamics of the informal sector population are forever shifting. This then also changes the outlet landscape, and will make it more difficult to keep count. Key informal market rates by population group The provincial informal market rates often mask large variations by district. This reflects differences in urbani-sation as well as differences in the economic structure of the districts. Key informal market rates by sex and population group This section analyses the results of previous census (Census 2011) by population group. The black African pop-ulation group accounts for 78,2% of the working age population while the white population accounts for 9,3%, the coloured population for 9,1% and the Indian/Asian population for 2,8% - according to Census 2011. This distribution affects many of the informal market outcomes analysed in this section. Key informal market rates by age group The analysis in this section will show that people in the youngest age groups face particular challenges in the South African labour market. Conclusion The specialised labour market surveys were introduced by Stats SA in the 1990s specifically for collecting ‘Official’ labour market information regarding persons who are employed, those who are unemployed and those who are not economically active. Although it is proposed that GOC also includes labour market questions, the results will differ from those in the QLFS for two main reasons. Firstly, the reference period for employment in GOC as proposed is one week while in the QLFS it covers a three-month period. Compared with GOC, the QLFS is therefore more likely to capture individuals who work on a casual/part-time basis. Secondly, the GOC uses not a de facto measure of the population but should follow the QLFS which uses a de jure measure. As a result, employed persons who are not in private households on GOC night (e.g. persons who are in hotels or guest houses) are otherwise required to complete a shorter questionnaire which does not include labour market questions. When comparing Census 2011 national results with those of the QLFS_Q4:2011 the reading suggests that the patterns of key labour market indicators based on population group, age, and sex are similar although the levels may sometimes be different. The Census 2011 results show that among the black African population, the unemployment rate (official and expanded) is higher than among the other groups, while among the white population group the unemployment rate is lowest. Census 2011 results also show that the unemployment rate among black African women is 41,2% based on the official definition and 52,9% based on the expanded definition. In contrast, the unemployment rate among white women is 6,9% based on the official definition and 12,5% based on the expanded definition. With regard to the situation of young people in the South African labour market, the Census 2011 results show that the unemployment rate among youth aged 15-24 years is higher than in the older age groups. Migration Introduction Migration can be defined as a change in a person’s permanent or usual place of residence. Along with fertility and mortality, migration is one of the components of population change. Information on previous and usual province of residence refers to migration between the 2001 and 2011 Censuses. Lifetime migration on the other hand deals with movements based on where the person was born and where they currently reside. This section

provides information on internal migration as well as immigration. Information regarding emigration is not part of the analysis. Patterns of migration between censuses Such is based on the question "Has (name) been living in this place since 'specified date?' The latest provincial boundaries may be used for this analysis. Respondents are asked to report on the month and year they moved to the place where the enumeration takes place and data therefore only reflect the last movement. Although a person might have moved several times before the last move, it is unfortunately not possible to ask about all these movements in a Census. The movements of people from a certain province to another, the in-and out-migration and net migration are to be recorded. Turnover figures obtainable as the summation of in- and out-migration, provide an indication of total movements.

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Table 3.4: Province of previous residence by province of usual residence (Exemplar) Black African Coloured Indian/Asian White Other

Province 1996 2001 2007 2011 1996 2001 2007 2011 1996 2001 2007 2011 1996 2001 2007 2011 2011 WC 21,6 26,7 30,1 32,9 56,0 53,9 50,2 48,8 1,1 1,0 1,3 1,0 21,4 18,4 18,4 15,7 1,6

EC 86,6 87, 87,6 86,3 7,7 7,7 7,5 8,3 0,3 0,3 0,3 0,3 0,3 0,3 0,3 0,3 0,3 NC 44,9 46,5 39,8 50,4 43,7 42,9 50,0 40,3 3 0,2 0,2 3 0,2 0,2 0,7 11,2 10,3 10,0 1,6 FS 45,8 45,5 46,6 369,6 12,6 85,5 596, 66,5 44, 66,5 88,5 24,6 46,5 98.5 58.5 79.5 75.1

KZN 161, 35,9 .83,5 71,2 13,2 15,2 46.5 48,5. 47.2 75. 645.5 72.5 456.5 51 510.5 6.6 6512. NW 56,3 63,8 6126 65,6 .56,2 15 89 45,4 654 464 154 16 498 89 59 5 9 GP 45,7 98 66 55,1 66 45 42 52,5 121 22 121 55 33 44 66 146 546 MP 11,5 11 133 56,9 46,6 465 56 42,6 95 4 6114 615 465 146 14 1464 154 LP 41,4 15 1546 62,3 44,5 579 494 464 116 16 6 46 64 146 146 146 6 SA 16,8 48,6 55,4 36,1 114 61 49 15 65 366 364 41 13 13 1233 13 133

It can be seen from Table 3.4 that Eastern Cape, Northern Cape, Free State, KwaZulu-Natal and Limpopo experienced a net out-flow of people during the 10-year period (between the 2001 and 2011 Censuses). Western Cape and Gauteng showed the highest in-flow figures. Surprisingly, North West and Mpumalanga also showed high net in-flow. Focusing on the North West province, it seems that the highest migration interaction was with Gauteng and that North West gained less people from Gauteng than it lost to it (75 260 against 103 550). It is also worth noting that the highest inflow to the North West came from outside South Africa (about 28% of all inflow). The turnover data also revealed some interesting figures. Some provinces with a low net migration showed relative high turnover numbers. KwaZulu-Natal for example has a net migration loss of 30 684, but the turnover is just over half a million. This is also the case with the Free State and North West.

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Lifetime migration patterns Migration patterns discussed prior are based on the usual residence and previous residence information. For the analysis in this section the birth province will replace previous residence to give life-time migration patterns. Patterns however become clearer if we calculate net migration and turnover numbers. Life-time migrants to Gauteng are high as expected. 23% of our countries population are born in Gauteng. Informal settlements In terms of the HDA Act No. 23, 2008, the Housing Development Agency (HDA), is mandated to assist organs of State with the upgrading of informal settlements. The HDA therefore commissioned a study to investigate the availability of data and to analyse this data relating to the profile, status and trends in informal settle-ments in South Africa, nationally and provincially as well as for some of the larger municipalities. This section summarises available data for the province of Gauteng. HOUSEHOLDS HOUSING Housing is one of the basic human needs and has both direct and indirect implications on lives of households including health, welfare and social status in communities. A number of questions were included in Census 2011

258 958 (9% of GA Households)

EA: Informal Settlement 339 497

(12% of GA Households)

Main Dwelling: Informal

Dwelling/Shack not in backyard

448 383 (16% of GA Households)

76% of households who live in EAs classified as Informal Settlements, live in shacks not in backyards 58% of households who live in shacks not in backyards, live in EAs classified as Informal Settlements

CROSS-OVER TYPE OF DWELLING AND ENUMERATION AREA: GAUTENG Total households who live in an informal settlements OR in a Shack not in a backyard: 528 992

Source: Census 2001

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Essentials This section aimed to highlight Census findings relating to types of main dwellings and basic services which have important policy implications. The government has a responsibility to improve sanitation to its people. The proportion of households having pit toilets with ventilation, households having access to pit toilets without ventilation, the proportion of households using the bucket toilet system, and the percentage of households that are without toilets are depicted. This allows for the aggregating of other factors relating to informal liquor trading and policy making as regards to informal settlements. Conclusion It is evident that in general there is improvement in the access to basic services over time. Such improvements provide direct benefits to households in terms of better living conditions, environmental and health standards. Municipal analysis shows significant disparities between urban and rural municipalities. Expansion Introduction With the increase of the population, it is almost inevitable that there will be an increase in the number of informal settlements in the province. This in turn results in the expansion of the informal retailor sector (shebeens). It is thus important to keep track of the population growth as an informative to the outlet population dynamics.

EXPANSION OF SETTLEMENTS A final consideration relates to the underlying unit of analysis. Survey and census data sources characterise individuals or households rather than individual settlements. These data sources provide estimates of the popu-lation who live in informal settlements as well as indications of their living conditions. The data as it is released cannot provide an overview of the size, growth or conditions at a settlement level2 although it is possible to explore household-level data at provincial and municipal level depending on the data source and sample size. The definition of a household is critical in understanding household level data. By and large household surveys define a household as a group of people who share a dwelling and financial resources. According to Statistics SA ‘A household consists of a single person or a group of people who live together for at least four nights a week, who eat from the same pot and who share resources’. Using this definition, it is clear that a household count may not necessarily correspond to a dwelling count; there may be more than one household living in a dwelling. Likewise a household may occupy more than one dwelling structure. From the perspective of household members themselves the dwelling-based household unit may be incomplete. Household members who share financial resources and who regard the dwelling unit as ‘home’ may reside elsewhere. In addition, those who live in a dwelling and share resources may not do so out of choice. Household formation is shaped by many factors, including housing availability. If alternative housing options were available the household might reconstitute itself into more than one household. Thus, while the survey definition of a house-hold may accurately describe the interactions between people who share a dwelling and share financial re-sources for some or even most households, in other cases it may not. The surveys themselves do not enable an interrogation of this directly. The City of Johannesburg has a detailed database comprising 180 informal settlements across all regions of the City. The latest available dataset was published in May 2010. In many cases maps and aerial photographs are available over time. Settlement data includes:

• Informal settlement name • Township name • Region and Ward • GPS co-ordinates • Number of shacks • Services (Water, Sanitation, Refuse) • Land ownership (Gauteng province, City of Johannesburg, Council, Parastatal, Public, Private, Com-

bination, etc.) • Year established • Settlement status (applications approved, in situ upgrading, planning phase, eviction, relocation,

etc.) This information is vital and should be considered when performing the Gauteng Outlet Census.

2 It may be possible for Statistics South Africa to match EA level data from the 2001 Census to settlements to provide an over-view of specific settlements. Given that the Census data is more than ten years old, and that conditions in informal settlements are likely to have changed significantly since then, the feasibility of this analysis was not established.

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INCREASE IN INFORMAL TRADERS

Conclusion It is evident from the table that there has been an increase in the population of the province. This has a knock on effect on the economy of the province and thus imposes some level of difficulty in maintaining an accurate enumeration of outlets throughout the years as is proposes by the Gauteng Outlet Census (GOC) with this submission. However, such systems of tracking are an imperative to ensure timely and successful planning.

SAMPLE SIZES IN THE DIFFERENT SURVEYS – TRACKING PREPOSITION FOR THE GAUTENG OUTLET CENSUS

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PROJECT COSTS The total GOC Project will cost about R 64 million. The Gauteng Outlet Census has been identified by Green Lantern Consulting as the most suitable and most effective means of carrying out the physical verification of liquor outlets in the province. There are three main components of census costs, and are as adapted for the GOC Census need to be more cost-effective. But they will remain costly despite the use of modern, relatively low-cost, computer technology. There is a fine balance between keeping census costs to a minimum and preserving the unique advantages of a census. Unless sufficient resources are available at each stage of the census, the quality and value of the entire census can be jeopardized. Three activities tend to take-up the bulk of census operation costs. First, census maps. Accurate maps provide the basis for a variety of census operations, including setting enu-merator assignments, ensuring completeness of coverage, estimating travel time and costs, and establishing field offices. They also provide the basis for producing thematic maps for spatial analysis of the census. The use of GIS, with ground-truthing, can lead to significant cost savings in the determination of enumeration areas. Further, the continuous and multiple use of maps by and across different government departments can help spread cartographic costs. Second, population enumeration. This is the most expensive census operation. Each person and every living quarter in a country must be enumerated within a short period of time. Enumeration costs depend upon factors such as method of enumeration; the source of supply of enumerators, the geography and topography of the country and the number of questions asked in the census questionnaire. Sampling can reduce census enumeration and processing costs, and improve the quality of information. Sampling at enumeration reduces field-training and processing costs in the main census, and enhances data quality for difficult topics and provides additional information from selected households. However, considerable care needs to be taken in sample selection and implementation to avoid biases in the results. Third, data capture, processing, analysis, preparation of reports and dissemination. Continued advances in computer systems technology, such as electronic scanning of marks and characters, have greatly increased the speed and reliability in producing and disseminating tabulations, increasing the extent to which automation can be applied as the standard method of processing. However, modern high-level data processing technology, and the skills to handle it, are frequently in short supply in developing countries. And it is by no means self-evident that, in labor surplus situations advanced technologies, such as sophisticated scanning devices, should necessarily be chosen to replace more labor-intensive methods. Although avoiding human transcription errors, such as data misreading or mispunching, the technology may have limited application in the years following a census. By contrast, a large number of stand-alone personal computers and related equipment items bought to facilitate census data processing may help permanently upgrade institutional capacity.

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BUDGET ESTIMATE FOR HIRING OF PROFESSIONALS FOR THE LOCATION SURVEY (LS-GOC)

Project Team of Profes-sionals Rate (Daily)

01-Jun 08-Jun 15-Jun 22-Jun 29-Jun 06-Jul 13-Jul 20-Jul 27-Jul 03-Aug 10-Aug 17-Aug 24-Aug 31-Aug 07-Sep 14-Sep 21-Sep 28-Sep Cost

John C R 1 200,00 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 R 108 000,00 Richard Mogale R 800,00 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 R 72 000,00 Neel Wale R 800,00 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 R 72 000,00 Sheen John R 750,00 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 R 67 500,00 Rachel Zulu R 850,00 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 R 76 500,00 Thabo Roy R 850,00 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 R 76 500,00 Tracy Mikels R 950,00 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 R 85 500,00 John Temper R 650,00 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 R 58 500,00

R 34 250,00

R 34 250,00

R 34 250,00

R 34 250,00

R 34 250,00

R 34 250,00

R 34 250,00

R 34 250,00

R 34 250,00

R 34 250,00

R 34 250,00

R 34 250,00

R 34 250,00

R 34 250,00

R 34 250,00

R 34 250,00

R 34 250,00

R 34 250,00 R 616 500,00

Other Re-sources Rate (Daily)

01-Jun 08-Jun 15-Jun 22-Jun 29-Jun 06-Jul 13-Jul 20-Jul 27-Jul 03-Aug 10-Aug 17-Aug 24-Aug 31-Aug 07-Sep 14-Sep 21-Sep 28-Sep Cost

Remote Server R 1 200,00 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 R 108 000,00 Printer R 300,00 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 R 27 000,00 R - R -

R 7 500,00

R 7 500,00

R 7 500,00

R 7 500,00

R 7 500,00

R 7 500,00

R 7 500,00

R 7 500,00

R 7 500,00

R 7 500,00

R 7 500,00

R 7 500,00

R 7 500,00

R 7 500,00

R 7 500,00

R 7 500,00

R 7 500,00

R 7 500,00 R 135 000,00

Total Costs Human Resources R 616 500,00 Other Resources R 135 000,00 Other Expenses R - Total R 751 500,00 Contingency (%) R 10,00 Contingency Amount R 75 150,00 Grand Total R 826 650,00

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Recruitment and placement of students The Gauteng Outlet Census is a complex project, as such is the Physical Verification of Liquor Outlets. The total number of workers to be employed which will make it possible for the successful implementation and carrying-out of the project amounts to approximately 3 990 staff members, which consist of fieldworkers, supervisors and GOC fieldwork coordinators. The total number of students to be used in this project may go well up to 1000 students or more, as the GOC pre-enumeration phase involves over 1000 temporary staff, who are to concurrently demarcate enumeration areas, evaluate questionnaires and develop satellite office logistics. The office structure is broken down as follows:

1. Head office with the main function of providing support to the lower levels, and through committees. 2. District offices who are to be responsible for coordination of all activities at their associated local and

satellite offices. 3. Local/Satellite offices who implement the fieldwork operations throughout the province.

Stipend disbursement Enumerators would be paid a flat fee of R 3,500. Students would be paid a flat fee of R 2, 500 The payment of GOC field workers is expected to cost a total of R 4,7 million out of a total proposed Gauteng Outlet Census budget of R64 million The logistics of Fieldworker payment will be managed by Recruitment, Appointment, Administration, Payment, Termination and Reconciliation (RAAPTR) committee, who will aim to deliver payment a week after completion of work. Coaching, training and mentoring The recruitment process for permanent and temporary staff members must be held over a 6-9 month period. It involves Capacity Building, Training Projects, targeted recruitment, employment agencies and a province-wide advertising campaign through multiple channels targeted for locals. A learnership can be created for the students. And the use of consultants will come in handy for the deliverable around mentoring and training, over topics such as data handling, data capturing and overall statistics. Business management The business management will be held through office of a consulting company. Project management 5 Professional Staff will be appointed to undertake the role of project management. This service should come at a cost of approximately R 8 million over a three year term.

IMPORTANT TO NOTE: A narrative written charter must be circulated and signed by the project sponsors. It is advised to attach a completed version of this template to the GOCs narrative written charter in an effort to keep it short and concise. Responsible persons make sure they meet with the project team and sponsors before completing such a template. Much of the information required will need to come from a discussion with team members and sponsors.

Gauteng Outlet Census Project Charter (Template) General Project Information Project Name

Project Sponsor Project Manager Email Address Phone Number Organizational Unit Process Impacted Expected Start Date Expected Completion Date Expected Savings R - Estimated Costs R 521 520,00 Green Belts Assigned Black Belts Assigned

Describe the Problem or Issue, Goals, Objectives, and Deliverables of this Project

Problem or Issue

Purpose of Project

Business Case

Goals / Metrics

Expected Deliverables

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Define the Project Scope and Schedule

Within Scope

Outside of Scope

Tentative Schedule

Key Milestone Start Complete Form Project Team / Preliminary Review / Scope Finalize Project Plan / Charter / Kick Off Define Phase Measurement Phase Analysis Phase Improvement Phase Control Phase Project Summary Report and Close Out

Define the Project Resources and Costs

Project Team

Support Resources

Special Needs

Cost Type Vendor / Labour Names Rate Qty Amount

Labour R 185,00 800 R 148 000,00 Labour R 170,00 580 R 98 600,00 Labour R 162,00 580 R 93 960,00 Labour R 162,00 580 R 93 960,00 Labour R 150,00 580 R 87 000,00 Miscellaneous R -

Total Costs R 521 520,00

Define the Project Benefits and Customers Process Owner

Key Stakeholders

Final Customer

Expected Benefits

Type of Benefit Describe Basis of Estimate Est Benefit Specific Cost Savings Enhanced Revenues Higher Productivity (Soft) Improved Compliance Better Decision Making Less Maintenance Other Costs Avoided R0

Describe Project Risks, Constraints, and Assumptions Risks

Constraints

Assumptions

Prepared by: Green Lantern Consulting Date:

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The following is a spreadsheet outlining the possible expenses for the GOC. Total project cost has been out-lined above.

Proposed Budget The table below outlines the proposed budget for conducting the Gauteng Outlet Census (GOC) Table 4: Census Costs for Gauteng Outlets Year Census Costs (in

Rands) Housing Units

Cost per hous-ing unit (with outlets)

Population (out-lets)

Cost per outlet (in Rands)

2017 65 000 000 3 909 022 43,50 260 000 23,50 2018 68 000 000 4 246 452 42;30 265 000 22, 70 2019 70 000 000 4 654 356 44,65 270 000 28, 45

SAFETY MEASURES The following are safety precautions which will be communicated to the staff on a daily basis before the day's work commences: SAFETY PRECAUTIONS 1. Remember where you parked. 2. Keep in sight of team members – never venture off alone. 3. Wear appropriate and comfortable clothing – sneakers, jeans, sweatshirts. Please don’t wear flashy clothes (tank tops, jewelry, skirts, etc.) that might make you stand out. 4. Check in and out with team leader. 5. Don’t give any money to the participants. 6. Be cautious of health risks. 7. Provide personal space. 8. For street count volunteers – bring charged cell phone and flashlight. Other precautions are to be related to state laws such as adherence to traffic rules and road rules – safe driving and alertness. Also, groups will be encouraged to travel in consistent and assigned groups, traversing their particular areas in a systematic way. Prior to Commencement Month, posters and pamphlets will be put up and handed out to local communities for the local residents to be able to recognize the fieldworkers. Fieldworkers will be discouraged from travelling with valuables. Strict adherence to GOC uniforms will be preached. This normally means jeans and a branded t-shirt plus a cap, all to be of a decent cut, without features which would attract attention.

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PAST PROJECT SAMPLE Below is a sketch done by one of the Moss Movement draftsmen for a customer who owned an outlet who wished to extend their residence during the SAB Outlet Verification Project in 2013:

This feature is a good feature to use for the verification of the outlets. Floor plans were drafted for each out-let, photos taken of the entire premises, yard measurements made and stored on file, digitally and on hard copy.

Figure 1.1: Map of Gauteng showing metros, district municipalities and localities

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Figure 1.2: Aerial View of portion of Soweto

This aerial view gives direction on how the enumeration areas may be established (EAs). 278 EAs are pro-posed for the GOC project, with each locality in the Gauteng province hosting two. There are 135 localities in the province. The Additional EAs will serve as administrative support through ad-hoc.

Aerial View of Soweto (Orlando, Diepkloof, Pimville, Meadowlands)

DISCUSSION In this submission we proposed to apply spatial analytical techniques to evaluate the current and estimate the future distribution of alcohol outlets in Gauteng. We chose this approach for specific reasons: the distribution of alcohol outlets has important ramifications for quality of life and public health, and we envisage Gauteng to championing to a privatised alcohol distribution system. Privatization, which essentially removes state control and its associated monopoly on alcohol sales, would have profound implications for alcohol availability, outlet distribution, and a variety of public health and safety outcomes. The goals of our analytical-submission are to (1) examine the current alcohol outlet distribution in Gauteng to provide a benchmark from which assessment of ordinances restricting alcohol outlet placement is possible and (2) estimate prospectively the impact of alcohol license privatization on the number and placement of alcohol outlets. The development of this framework and associated analysis is important for two main reasons. First, the ability to benchmark the existing distribution of alcohol outlets and compare it against existing policy guidelines is an important first step in understanding features, including biases, of the current licensing system. Second, if full privatization were to occur, the existing distribution of outlets can be compared against alternative scenarios, where there are fewer controls on the number and location of outlets and retailers, reflecting a deregulated urban market. Further, this type of con-tingency analysis allows the public health implications of alcohol availability in a community to be evaluated prior to policy change. Controlling and promoting the sales of alcohol are a conflict of interests. To a certain extent, dispersion ordinances limit access (and profits), effectively regularizing and thinning retail distributions, but itis widely recognized that some type of control is needed because the public health and quality of life implications of high intensity alcohol retailing and consumption are significant. In this context, policy assessment requires retailer behavior to be translated or interpreted in the distribution of alcohol outlets. It is clear then that as many outlets as the market will bear can be expected to emerge under privatization, subject to established ordinances and land use restrictions. Further, it is possible to estimate the likely distribution of alcohol outlets over the long term using a spatial analytical model that mimics retailer behavior while imposing restrictions. Yet, the situation on the ground is further complicated. 3This research identified four forms of liquor micro-enterprises, namely i) taverns (licensed premises), ii) shebeens (unlicensed liquor retailers), iii) spaza-shebeens (spaza shops that sell liquor without a licence) and iv) businesses that micro manufacture traditional beer or other concoctions for on-site consumption. Shebeens are the most numerous of these categories. We found that there is no archetypical shebeen; rather, there is a great diversity of shebeen businesses targeting different market segments. It is common for each shebeen to target different clientele. The niche characteristics of the informal liquor market have arisen through the varying social prefer-ences within local neighbourhoods for contrasting environments, with, as a result, some shebeens offering music and games and others not. Some shebeens permitting women to purchase liquor and others not, some shebeens selling liquor to all customers, and others restricting entry to specific age cohorts. Less than 20% of the 465 businesses that we surveyed provided entertainment in the forms of games, television or juke boxes. The political stereotype that shebeens generally play (loud) music and attract a youth-based clientele was found to be incorrect and misleading. In order to distinguish businesses in terms of their size, the research used weekly beer sales as a proxy indicator (using the unit, 1 beer crate = 12 x 750 ml bottles). It then categorised all businesses into one of three size groupings; • Low volume = those selling less than 16.5 crates of beer per week, a volume equivalent to 150 3 The Sustainable Livelihoods Foundation – Informal Liquor trading Report

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litres, the maximum permitted volume threshold under the Gauteng Liquor Act for home consumption. • Medium volume = those selling between 16.5 crates and 65 crates of beer per week. • High volume = those selling above 66 crates per week, equivalent (formerly) to one pallet, the minimum quantity for direct delivery from the manufacturers. In terms of size, the sector is heavily skewed towards businesses selling less than 16.5 crates of beer per week with 60% (273 of the 465) of the surveyed businesses falling into this category. A mere 27 businesses sell high volumes of liquor. The sector structure, in volume terms, is shown in Figure 1, illustrating the pyramidal structure of informal liquor retailing with most businesses operating at the base level. In terms of their legal status, 30 businesses held liquor licences, representing 6.5% of the 465 surveyed liquor retailers. Eighty three businesses (inclusive of those with liquor licences) had at some point in the past five years made an effort to conform to legislation by applying for a liquor licence, with many applying in the past 12 months. A consid-erable number of licence applicants have been waiting years for the outcome of their application. Despite the efforts of a minority to formalise, over 80% of all informal liquor retailers – primarily the smallest operators - have not engaged the current formalisation process at all.

RECOMMENDATIONS Following the 'SAB Shebeen Liquor License Project' (2013) – which Moss Movement was a part of through rendering the services of Architectural Draftsmen to the Egoli Region whereby outlets who were holders of permits were encouraged to upgrade to license holders through a system of consultation organised, as it ap-peared, by SAB – it came to the attention of Moss Movement that a lot of work still needed to be done with regards to achieving the Liquor License Project Aims, which includes the advancement of Shabeens and Taverns as small businesses; alluding to Local Economic Development. As a result of participating in the project, Moss Movement identified other particularities relating to the chal-lenges which are faced by the Shabeens and Taverns relating to accounting, bookkeeping, tax returns and overall compliance as small businesses, as well as applications for a License to trade. It was thereupon where Green Lantern embarked on a non-resident yet parallel pilot project to advise the business owners with a vision to assist in disentangling those challenges and see them operate as fully fledged, well run and fruitful small businesses that are in full compliance with state laws. It thus could not have come at a better time this request for information, during the time that Moss Movement by virtue of Green Lantern Consulting has set about on a similar project out of its own accord. Moss Movement has been engaging with outlet owners and liquor trader's associations to continue its research on the issues on the ground. The main idea is to offer these outlets the opportunity to apply for licenses at a rate which they can afford. We have proposed to do bookkeeping for these outlets and to help them apply for licenses, through a system of consultation and advocacy. We have thus since acquired 100 customers, and the project is set to begin on September 2016. Our recommendation is thus that the toughness and red-tapes of the application be relieved, as such there exists a potential for the province to benefit from this informal sector should a smooth transition be achieved

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CONTACTS Collin Mkhonza (c) 079 281 7130 (t) 011 039 9897 (e) [email protected]

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REFERENCES - University Of Florida, Forms, https://www.unf.edu/uploadedFiles/aa/coas/cci/homeless/FORMS_Safety_Etiquette.pdf - FY2017 U.S. CENSUS BUREAU APPROPRIATIONS Why Full Funding Matters February 2016 Brookings Institution, “Counting for Dollars: The Role of the Decennial Census in the Distribution of Federal Funds” (March 2010), and “Surveying for Dollars: The Role of the American Community Survey in the Geo-graphic Distribution of Federal Funding” < http://www.brookings.edu/research/reports/2010/07/26-acs-reamer > (July 2010). - List of Cities and Towns in Gauteng, Wikipedia https://en.wikipedia.org/wiki/List_of_cities_and_towns_in_Gauteng - Sustainable Livelihoods Foundation South Africa, Informal Liquor Retailing http://livelihoods.org.za/wp-content/uploads/2015/05/SLF-Informal-Liquor-final.pdf - Charman, A., Petersen, L. & Piper, L. (2013). Enforced Informalisation: the case of liquor retailers in South Africa. DEVELOPMENT SOUTHERN AFRICA, 30(4–5): 580–595 - Unlock Your Leadership Potential, Florida 4-H Leadership Program, Cooperative Extension Service, Univer-sity of Florida - A Kaleidoscope of Leadership, Minnesota Extension Service, University of Minnesota - A Winning Hand in 4-H Leadership, Texas Agricultural Extension Service, Texas A&M University - Ridpath, J. C. (1881). The Life and Work of James A. Garfield. Available at http://www.todayinsci.com/QuotationsCategories/C_Cat/Census-Quotations.htm (Accessed January 2014). - Statistics Canada. (2011). National Household Survey. Available at http://www.statcan.gc.ca/survey-enquete/household-menages/nhs-enm-eng.htm (AccessedAugust 2014). - Taber, J. (2010). “Clement feels 'alone' in census feud.”Ottawa Notebook. Available at http://www.theglobeandmail.com/news/politics/ottawa-notebook/clement-feelsalone-in-census-feud/arti-cle1669378/ - Getty Images (google)