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THE UNIVERSITY OF JOHANNESBURG JOURNAL FOR APPLIED ECONOMIC & ECONOMETRIC RESEARCH

EDITORIAL BOARD

CORE EDITORIAL BOARD

Chief Editor: Prof G van Zyl (UJ)

Review Editors: Prof L Greyling (UJ) & Allain Kabundi(UJ)

Language and Technical Advisor: Audrey Heyns

Subscription Editor: Dr P Bauer (UJ)

ADVISORY MEMBERS

Dr S Motamen-Samadian (University of Westminister)

Dr M Louw (SABMILLER)

Michael Mc’Clintock (SASOL)

Prof E Kleynhans (North-West University)

This journal will be published bi-annually and serves as an independent publication medium for applied scientific contributions to the broad field of economics & econometrics. Articles with an applied perspective in any of the sub-fields of economics, financial economics & econometrics will be considered for publication. The journal is also published in an electronic version. The website of the journal is www.uj.ac.za/economics.

Publisher: ECORIG; P/Box 10152; Aston Manor; 1630 South Africa

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THE UNIVERSITY OF JOHANNESBURG JOURNAL FOR APPLIED ECONOMIC & ECONOMETRIC RESEARCH

VOLUME 5 - July 2009

ISSN 1996-1251

CONTENT

• Wicked Policies and Righteous Economists

A. Wentzel 5

• Current Challenges of Risk Management in the South African Banking

Industry

A. Pampallis & EH Redda 26

• The Impact of Chinese Imports on South African Employment and Output

Growth: An Empirical Perspective

L. Bonga-Bonga & M Biyase 38

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GUIDELINES TO AUTHORS

1. Manuscripts should be typed in Arial 12 pitch, 1 spacing, in A-4 format and should

not exceed 25 pages (including tables, figures, appendixes and references).

2. Articles can only be submitted in English (UK English). The personal detail of the

author(s) (title, initials, surname, e-mail address and telephone number) and an

abstract of not more than 300 words must accompany the article.

3. The article must be forwarded electronically to: The Chief Editor of UJJAEE

(hardusvz@uj.ac.za).

4. The style adopted in listing the title, author, headings, tables, figures, references,

etc must be in accordance with the official policy of the Editorial Board. This policy

document is available at the back of this publication.

5. Copyright on published articles is reserved by the authors. The exclusive

responsibility in respect of the acknowledgement of author’s rights and/or copyright

rests in the responsible author(s). The Editor of this Journal cannot accept

responsibility for the infringement of author’s rights or copyright.

6. Individuals, organisations and businesses can subscribe to an e-version of the

Journal. Please contact the Subscription Editor of UJJAEE at peterb@uj.ac.za.

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WICKED POLICIES AND RIGHTEOUS ECONOMISTS

A Wentzel

ABSTRACT

While neoclassical economists' approach to understanding the economy is driven by considerations of method, a more problem-driven approach to economic policymaking is likely to be more fruitful. However, without an understanding of the social and political nature of economic problems, the problem-driven approach will not live up to its promise. In this paper, it will be explained that economic problems are not well-structured, and hence not solvable through the use of mathematics and econometric model-building. Instead, economic problems fall in the class of "wicked problems" meaning that they have no definitive statement, and hence no definitive solutions. Any solutions will consistently create further problems, because wicked problems are created by a constantly evolving set of constraints and stakeholders with different interests. Wicked problems require an approach that moves beyond the optimisation and equilibration mindset of neoclassical economists. This paper presents an approach to resolving wicked economic problems by first showing that problems can be structured as logical contradictions resulting from inconsistent premises. Since the source of inconsistent premises is found in the beliefs of agents, the paper proposes an approach that helps to identify inconsistent premises through a process of collective dialectical reasoning. The inconsistent premises are then used as the foundation for the development of innovative policy solutions.

THE PROBLEM OF ECONOMIC PROBLEM-SOLVING

Economic policy problems are not what they used to be, or what economic theorists thought they used to be. Most economic policy problems, such as underdevelopment or poverty, remain stubborn despite the efforts of generations of economic theorists to solve them. Other problems seem to get solved, then recur in another form or at another time, only to be re-solved. Theorists may rationalise such failures of economic theory to provide permanent solutions to economic problems by questioning the realities of policymaking: laying the blame on irrational behaviour by the agents involved, on bad policies or on the bad implementation of good policies. What is peculiar though is that solutions based on mainstream theory assume the existence of rational agents with consistent beliefs. Further, even if rationality is not questioned, there are several cases where apparently ‘bad’ policies had good results in solving problems, and cases where good implementation of ‘good’ policies created even more problems (Fox, 1997:49-52; Stiglitz, 2001:518-519). This paper will provide alternative explanations for the failure of economists and economic theories to have a permanent impact on the solution of economic policy problems. It will argue that an explanation cannot emerge from a denial of the reality of policymaking. Instead, it is proposed that economic theorists need to understand: (1) the structure and nature of real economic problems; (2) the process of generating economic policies designed to solve economic problems; and (3) the nature of feasible economic policies. The ideas will be illustrated with examples drawn from South African monetary policy in particular. HOW GOOD ECONOMISTS UNDERSTAND ECONOMIC PROBLEMS AND POLICIES

In textbooks, the central economic problem from which all other economic problems are derived is the scarcity problem. As originally formulated by Robbins, economic science should concern itself with problems of “…human behaviour as a relationship between ends and scarce means which have alternative uses” (Robbins, 1952:16). All economic problems should therefore share the same ends-means structure, and can be formulated either as a trade-off between given ends

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within the constraints of scarce means, or as a trade-off between scarce given means in pursuit of an agreed end. Figure 1: General representation of structured economic problems Source: Own construct Figure 1 shows the two simplest ways in which the general structure of the family of economic problems, derived from the scarcity problem, can be graphically represented. The basic structure is that of a trade-off, either between ends (Figure 1a) or means (Figure 1b). Most economic problems are represented in one of the two ways by theorists and policymakers. The problem of monetary policy, as defined by Taylor (1995:38), as a trade-off between output stability and price stability, fits the template of Figure 1a. Others that fit the same template are the social indifference curve and the production possibility frontier. The isoquant, for example, fits the template of figure 1b. In more complex cases, a problem may be structured as a U-shaped curve or with the aid of two curves, but essentially they remain trade-offs between givens ends or given means. The structure of a problem determines the methods to be used in solving it. Structured as ends-means problems, economic problems are best solved by optimisation – either maximising the achievement of multiple given ends within the constraints of a given set of means, or minimising the usage of all available given means in the pursuit of a given end. A problem can be defined as a gap between a perceived current state and a normatively valued state (Smith 1988:1491). Economic problems can thus be defined as gaps between a state perceived to be non-optimal state and an ideal state of optimality. Policies are designed to bridge this gap. Within this particular view of economic problems, the process of generating policy solutions involves collecting data to establish the current state, preferences and available means. An expert, or group of experts (usually economic theorists) then develop a model in which the trade-offs and their interactions are represented mathematically or statistically. The data is entered into the model, and alternative courses of action are tested. The course of action that achieves the optimal state is then presented as the policy solution. This linear process is known by some policy scientists as the Rational Planning Model (RPM) (Khisty, 2000:104). The RPM can only succeed if the problem to be solved is a well-structured or a so-called “tame” problem (Rittel and Webber, 1973:155). A well structured problem assumes that there is consensus among all role players on the ends, means and definition of the problem. It also assumes a constant problem space (certainty or at least measurable risk), that the appropriate problem-solving methods are available, that solution is a matter of computation, that problem-

End1

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solvers have the ability to do the computations and that solvers will know when they have reached the best solution (Simon, 1973:182-183). Policies, in this view, are rational solutions to objective and well-structured problems, and the result of a mainly deductive and inductive technical (non-participative) process. Due to consensus among role players, well-structured problems can be approached within a control paradigm using authoritative strategies. If the policy fails, it is believed to be the result of irrational behaviour and bad implementation. Such policies are rarely innovative, firstly since innovation cannot result from logic or the collection of data (Weber & Llorente, 1993:67; Redelinghuys, 2000:271), and secondly because innovative solutions are not required when a problem is well-structured. Monetary policy in South Africa is approached as a well-structured problem in a manner similar to the RPM. A group of experts (Monetary Policy Committee) meets every second month to feed the available data into a model. They do not disagree on what means are available and reach consensus on a course of action (usually with regard to the level of interest rate) that will ensure the achievement of a predetermined end (the inflation target). This occurs despite the fact that other agents do not agree with the ends or the means used. THE REALITY OF ECONOMIC PROBLEMS AND POLICIES Any policymaker will agree that few policy problems are well-structured. Economic problems are reduced to well-structured problems in order to suit the techniques used by the economics profession. It allows the policymaking process to be more controlled and faster, and makes the process appear rigorous and apolitical (Hisschemoller & Hoppe, 1995:45-46). If economic problems are not well-structured, then economists will have to rethink their role and develop new tools. This section will explore economic problems and policies as they exist in reality, to establish if such drastic action may be justified. Why do economic problems exist? Problems are essentially difficulties with human ideas (Popper, 1992:8-9). Economic problems are social constructs that have no objective existence apart from humans and their social reality (Smith, 1989:965; Dennett, 2003:165). This is obvious if we consider problems as gaps between a normatively valued ideal and a current perceived state of affairs that is believed to be difficult to close. Only humans can make normative judgements and have ideals. Gaps exist if perceptions differ from ideals, so without human perceptions, problems would not exist. Since perceptions and ideals change and are different between humans, not everyone will believe at all times that a problem exists. The idea of optimality will not exist if humans did not exist and will change over time. What was an optimal state in monetary policy in 1960, was not believed to be an optimal state in 1990, and not everyone even agreed that optimality was possible or an ideal. Even if there is agreement on the gap, not all problem-solvers perceive the same means or have the same abilities to solve the problem. What is seen as a serious problem to the South African central bank is quite possibly a trivial problem to the US Federal Reserve with different means and abilities at its disposal. Problems are therefore mismatches between human perceptions, human preferences and human abilities – they are not discovered, but created by human beliefs. With problems arising from human beliefs, no economic problem can exist if someone does not believe it exists. Unfortunately, it is not possible to do without our beliefs. Beliefs, in the form of assumptions, are needed to fill the gaps in our understanding of reality due to uncertainty and imperfect knowledge. All our knowledge is deduced from a set of beliefs that cannot be proven. Without these beliefs we would not be able to create knowledge. Hattiangadi (1978:352) explains that beliefs have evolved because they are also necessary for our physical survival. Without

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beliefs, crucial cognitive processes would be slowed down so much as to make everyday activities and responses in emergency situations impossible. When dealing with a problem, a group of affected agents will most likely have divergent perceptions regarding ideals, ends, preferences, means and methods. The complete set of beliefs in such a group will therefore contain several logical inconsistencies. For example, one group may believe that a central bank should stick to an inflation target another may believe that it should rather consider a wider range of indicators, while another might not even see a role for the central bank. Beliefs exist to compensate for imperfections in knowledge, so as the complexity and range of an issue increases more beliefs are required, making it likely that even the assumptions of a single agent will become inconsistent. Any person’s beliefs change and new ones are added as the environment changes, so that a person’s knowledge and ideas change imperceptibly over time. Inconsistencies in beliefs arise as a result as one part of a person’s knowledge base becomes misaligned with other parts (Hattiangadi, 1978:352). It may also be that those beliefs that are consciously held will conflict with beliefs held unconsciously, so that the inconsistency may exist without becoming apparent. The implications of certain beliefs are not always understood, which provides another possible reason for the existence of inconsistencies. When there are logical inconsistencies in a set of beliefs, a contradiction will inevitably follow. Any statement can be derived from inconsistent statements, including statements that contradict each other, also known as the principle of ex falso quodlibet (Tomassi, 1999:120). This makes any set of inconsistent beliefs useless since all courses of action can be derived from such a set, and will give no guidance on how to achieve certain ends. For example, a set of inconsistent beliefs about monetary policy will generate the conclusion that the central bank should increase the interest rate and decrease the interest rate at the same time. At best, this leads to indecisiveness and movement between extremes; at worst it leads to actions that aggravate the problem. In other words, inconsistent beliefs impede the achievement of goals, prevent the gap between perceived reality and ideal from being closed and thus constitute a problem. We can therefore describe problems as contradictions created by logically inconsistent beliefs (Hattiangadi, 1978:357). It should now be obvious that mainstream economic theory is unrealistic – it denies that economic problems can even exist, because beliefs are assumed to be consistent. Take for example this description of the foundations of rational expectations theory by Sargent (1993:6):

“The idea of rational expectations has two components: first, that each person’s behavior can be described as the outcome of maximizing an objective function subject to perceived constraints; second, that the constraints perceived by everybody in the system are mutually consistent. The first part restricts individual behavior to be optimal according to some perceived constraints, while the second imposes consistency of those perceptions across people… individual rationality and consistency of beliefs – has in in many contexts made rational expectations a powerful hypothesis…”

Note that ends and means are assumed to be known among all agents, and while the role of beliefs is acknowledged, it is assumed that they cannot be inconsistent. Constraints in this view may refer to physical resources or to beliefs about the system. If there is a problem in such a system, it is a trivial well-structured problem of computing the optimal achievement of an end with given means. No contradiction can result in such a system, so that the course of action is always clear. Mainstream economic theory is therefore unlikely to be able to give much guidance in approaching the less structured problems of the real economy created by inconsistent beliefs.

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The wicked nature of economic problems Even if mainstream economic theorists admit the existence of economic problems, their approaches to solving such problems suggest that they treat them as well-structured. In reality, problems of economic policy are characterised by disagreement and confusion amongst agents, which alerts one to the fact that economic problems are not well-structured. In fact, the basic charasteristic of problems that are not well-structured is the existence of inconsistencies due to stakeholders’ different perceptions of problem (Mitroff & Mason, 1980:339). Problems that are not well-structured fall into the class of problems Herbert Simon (1973:185) labeled ill-structured. Ill-structure in problems results from uncertainty and a lack of knowledge about goals, heuristics and the problem space itself. Attempts to solve ill-structured problems have unintended consequences, so that the problem is continuously redefined (Simon, 1973:186). Ill-structured problems have no known algorithm that can be used to determine if the correct solution exists (Nickles, 1981:87) because there is no given means-ends structure for an efficient solution search – the means are perceived to be uncertain or the ends are disputed. The means-end structure provides a simple typology of problems, in which well-structured problems are a special case, as seen in figure 2. Figure 2: Typology of problems Source: Adapted from Khisty (2000:106) Figure 2 show that when both means and ends are certain, one has a well-structured problem, such as the majority of theoretical problems in economics. While policymakers prefer well-structured problems, many of those involved in implementation of policies, are aware that ends are disputed by agents and that means are uncertain (i.e. unstructured problems). To gain some perceived leverage on the problem, such unstructured problems are reduced to problems that are either ill-structured by means (assuming that there is consensus about ends) or ill-structured by ends (assuming that the means to solve the problem are certain). Rittel and Webber (1973:160) expand the concept of ill-structured problems with their idea of wicked problems. A wicked problem is an unstructured problem that will never be eliminated – it cannot be solved only continuously “re-solved”. Central bankers know this – every generation of central bankers appear to come closer to solving the problems of monetary policy, only to have them reappear at another time in a different form.

Well-

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The wickedness of economic problems emerges from agents’ inconsistent beliefs and conflicting preferences, values and perceptions about ends and means. Such agents will not be able to settle on a definitive formulation of the problem that affects them all. Without a definitive formulation of the problem, numerous explanations will be offered for the existence of the problem without any rule for determining the correct explanation. Without a clear explanation of the problem it would not be possible to know when the correct solution has been reached, no way to know when to stop searching for the solution and no specified set of solutions or operations to reach a solution. Every problem is uniquely situated in an open system; causally connected to other problems in an open system. This means every problem is a symptom of other problems, and every solution creates other wicked problems. Every solution has waves of real and irreversible consequences, and because policymakers are supposed to improve people’s lives, they have “no right to be wrong” (Rittel and Webber, 1973:161-166). With globalisation and the spread of the free market democratic system, the values and goals of agents are becoming more diverse. Judgements about solution differ between agents, so solutions cannot be true or false, only better or worse given an agent’s goals and values. The diversity of goals means that a true aggregate measure of welfare cannot be determined. This diversity also makes it unlikely that policy solutions will satisfy all agents. Pareto optimal solutions to wicked economic problems do not exist therefore, since there is no measure to optimise, and any policy solution will make at least one group worse off (Rittel and Webber, 1973:162-168). Any optimal solution to a wicked problem is likely to be only one agent’s version of the problem (Rosenhead, 1996:119). Wicked problems are difficult, if not impossible, to solve. At the core is the difficulty to define problems as a result of the diverse and inconsistent beliefs of agents. If economic problems did not affect humans (or affected only homogenous agents with consistent beliefs) so that only a single uncontested version of these problems existed, they would not be wicked. Unfortunately, economic problems affect a wide range of agents, so that all significant economic problems are likely to be wicked (Coyne, 2004:5; Simon, 1973:186). The social nature of economic problems

Several philosophers have pointed out that not all problems can be described as contradictions arising from inconsistent beliefs (Giunti, 1988:421-439; Nickles, 1981:94; Wettersten, 2002:487-536). It fails to describe the structure of empirical problems (problems that can be solved by collecting more data or explaining the data) but is better suited to describing conceptual problems (problems due to inconsistencies and incompleteness in our theories and concepts). Policy problems cannot be resolved by the collection of more data, and are therefore better treated as conceptual problems. This is because policy problems are social constructs and political constructs (Hisschemoller & Hoppe, 1995:45). Problems are social constructs because they arise, and are shaped, by the beliefs of humans who perceive the problem. As recorded in the research of various experimental and behaviour economists, systematic biases appear when humans form beliefs, and such biases often remain constant even if contradictory data becomes known. More data does not eliminate inconsistencies in beliefs (Barberis and Thaler, 2003:1063-1067). Problems serve a social purpose. They direct human attention to particular aspects of social reality so that action can be taken to change that reality (Smith, 1989:966). Problems are political constructs because they direct attention in the process of policymaking and because power determines this direction. In so-called policy games actors interact to influence how the problem is defined (Van Bueren, Klijn & Koppenjang, 2003:195). All role players who share a problem, will

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have an interest in trying to solve that problem to their advantage. If their beliefs are different, they will compete have their beliefs accepted. The agent whose definition of the problem is accepted, is the agent whose beliefs will dominate and have the power to dictate what information is relevant and what policy alternatives are to be considered (Hischemoller & Hoppe, 1995:46). Since the interests of agents play a critical role in the understanding of economic problems, agents will self-select different data or interpret the same data differently, in order to support their beliefs (Mitroff & Mason, 1980:335). Beliefs are intimately tied up with interests and power, and this provides an incentive for agents not to change their beliefs. This political aspect of policy problems makes beliefs resistant to empirical test, so that the inconsistencies in beliefs will remain. For example, labour unions believe that the current problem of monetary policy in South Africa is the conflict between pursuing an inflation target and reducing the unemployment rate. At the same time, the central bank does not perceive a contradiction, and therefore sees no problem in pursuing inflation targeting (Bisseker, 2006:26). Despite several protests, labour unions have no power to influence problem definition, and therefore the central bank determines what data and policy alternatives are relevant. Finding solutions to economic problems is a social process, despite the fact that the authoritative (non-participative) strategies of economic theorists and policymakers make it appear otherwise. Beyond policymakers and theorists, a much wider range of agents are affected by any economic policy, so it is to be expected that they will also want their beliefs to be considered in the policymaking process. This participation by other stakeholders virtually guarantees that inconsistencies will enter the process, if inconsistencies do not already exist in the beliefs of policymakers. While better suited to well-structured problems the widespread use of authoritative strategies do not imply that economic problems are well-structured. Instead it reflects the power of the stakeholders. If power is concentrated, a single agent (like the central bank) can impose a problem definition and policy alternatives despite disagreement about ends or means (Roberts, 2000:4). The nature of economic policies Economic theorist’s who want their ideas to have a meaningful impact on the economy, need to understand how ideas are converted into actions that create real economic change. One such conversion mechanism is policies. Without an understanding of the nature of policies and the policymaking process, theorists will find it difficult to get policymakers to put their ideas into practice (Colander, 2001:62; Edwards, 2002:19). Instead of denying the reality of policymaking (by blaming irrational agents or bad implementation) theorists will make more constructive contributions by trying to understand this reality. Some important aspects about economic policies that theorists need to bear in mind have already been pointed out. It has been argued that policies are solutions offered in response to wicked (unstructured) economic problems. Given the nature of wicked problems, it was also stated that policies are the result of a social and political process. If problems are unstructured, the process of finding policy solutions will be naturally unstructured as well (Van Bueren, 2003:197), unless a structure is imposed. Most theorists and policymakers prefer structured problems that suit the application of standardised problem-solving techniques, and may attempt to artificially increase the structure of unstructured problems by imposing their beliefs on other agents. Such an authoritative strategy involves denying the social and political nature of problems by introducing two biases to the process. The first bias denies the social

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aspect of economic problems, by reducing the number of agents allowed to participate in the policy process. The second bias denies the political aspect, by limiting the range of arguments allowed in the process (Hischemoller & Hoppe, 1995:44). The biases disguise the complexity of the problem without changing the causes of the complexity. It makes it likely that policymakers will address the wrong problem with the wrong techniques. Such biases in economic policymaking have been documented by Edwards (2002:19-24) in Australia and Rosenhead (1992:297-298) and Willets (1987) in the UK. These authors point out how policymaking is often based on caricaturised versions of the complexities of economic theory (Coats, 1989:111; Robbins, 1971:186). Expediency is lost if an authoritative strategy is not used. In a participative process diverse agents with inconsistent beliefs will try to influence each other. Such social interaction will inevitably run into a series of impasses. Impasses are dissolved only when a breakthrough occurs as a result of an innovation or learning that changes the beliefs of some or all the agents (Van Bueren et al., 2003:196). Authoritative strategies, by imposing problem definitions and restricting the problem-solving process, limit the possibilities for learning and innovation in a particular policy issue. Both biases are also observed in monetary policymaking in South Africa. The central bank allows for no discussion outside a group of employees who already agree on the end, the means and what data is relevant. Academics, economists and other interest groups are excluded from participating, and the range of arguments is implicitly restricted by an eclectic set of accepted economic theories and the derived inflation forecasting model. As one central banker said: “We hear, but we don’t listen” (Anon, 2006:7). This explains why the Monetary Policy Committee consistently achieves consensus in two days or less. Given the imposed standardisation of the process, it is not surprising that no significant policy innovation has recently emerged from South Africa’s central bank, or any other central bank that strictly introduces the biases to the policymaking process. They are content to merely copy “best practice” from mainly developed nations. Dangers of misunderstanding problems and policies

Reducing economic problems to well-structured problems is called “taming” (Churchman, 1967:B141). Taming involves denying the very aspects that makes real problems problematic – beliefs, imperfect knowledge, power plays, social interaction and uncertainty. Wicked problems can be tamed using one or more of the strategies explained below (Conklin, 2001:11). The first taming strategy is to fix the problem definition to fit a particular discipline’s view of it. This results in a second strategy which is to act as though there are only a limited set of alternative solutions, and focus efforts on choosing one from this set. A third strategy is to assume that the problem does not exist and declare it solved. Stiglitz illustrates this strategy in some detail in the context of his Nobel prize-winning research and his work in developing countries, where economic theorists often simply denied the existence of real trade-offs in their models and policy recommendations. In denying certain trade-offs at work in developing countries, economists have often exacerbated the trade-offs they denied, and created additional problems (Stiglitz, 2001:518-519). The South African central bank employs this strategy by denying the existence of even a well-structured problem or trade-off inspired by any version of a Phillips curve. This leaves them free to pursue a strict inflation target to the exclusion of all other goals. The fourth strategy is to reduce the problem to one that was solved before by screening out certain complications. This occurs in economics for example when a problem is reduced to searching for the optimum on a welfare function. Malthus, the originator of the concept of the optimum in economic theory, was sufficiently wise to recognise that it is impossible to determine

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the optimum in reality. He warned that policies in pursuit of a theoretically determined optimum would most likely divert the economy from the indeterminate true optimum (Pullen, 1982:279). Another taming strategy is to specify the measurement of success so that what is not measured can absorb the real problem. This turns attention away from the problem towards the question of measurement. The problems created from this strategy are evident in the measurement of economic growth. Pursuing economic growth as measured by GNP, means that economists feel no compunction to pay attention to factors that are harmed by such a pursuit, but not measured in the GNP. The last taming strategy is to decompose the problem, and to solve only that part that can be structured, leaving the untamed part to someone else. This strategy is often a particular frustration to those who have to live with the solutions. It involves neglecting the interrelations that make the larger problem unstructured. When these interrelations appear after implementing the policy solutions, unintended consequences cause these policies to degenerate as they are patched up with often conflicting solutions over time (Simon, 1973:190-1). This happens for example when changes in monetary policy create complications for fiscal policymakers, or when the changes create unforeseen difficulties in the banking sector. Taming economic problems therefore means diminishing the information content inherent in such problems. Taming strategies are attempts to convert an unfamiliar (unique) problem into a familiar problem, so that known solutions can be found. Such as process is not amenable to delivering the kind of innovation or learning that is required to substantially improve on previous solutions. In fact, because the nature of a problem is changed during the taming process, it is virtually certain that policymakers will solve a problem different from the real one, applying inappropriate methods and implementing solutions that are worse than the problem. All of the taming strategies employed contain an element of deception. Such strategies create the belief that wicked problems have been solved, when they still exist and likely to return when they are least expected. A central banker who states that price stability is a requirement for output stability and employment to improve, is taming the problem of a country’s economic performance by decomposition. By stating that monetary policy has led to the achievement of an inflation target, a central banker creates a false impression of control over a country’s economic performance. If agents base their decisions (e.g. incurring debt, investment, saving) based on the central banks pronouncements, they will later feel the real effects when economic performance does not improve and inflation does not remain under control. Applying solutions designed for well-structured problems to wicked problems, will always leave residual demands that have not been met (Smith, 1988:1499). The residual demands may be in the form unintended consequences, a residue of unsolved problems or additional problems created. Stiglitz (2001:19-21) explains that economists are particularly guilty of this. It can also take the shape of “intractable social controversies” (Hisschemoller & Hoppe, 1995:44) as a result of excluding affected parties from the solution-generating process. When agents are excluded from engaging with problems that affect them, there is a tendency for them to harden their positions, and resort to processes other than reasoned argument. Solutions to wicked problems that are generated by the rational planning method and designed for well-structured problems will therefore fail and create further social dissensus. This can lead to credibility problems for economic theorists in public and policy circles. When the apparently rational methods of economists fail to deliver on their promise, this opens the way for a “retreat from reason” and makes “hyperirrationalism” more attractive (Rosenhead, 1992:302). Economists will better protect their credibility if they take a more realistic view of economic problems and policies.

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Taking a more realistic view of economic problems has implications for the role of economists. The wickedness of economic problems is not an excuse to do nothing. Economic problems are of human concern and have to be addressed. However, they cannot be addressed using the mindset engendered by thinking of them as well-structured problems with an objective existence. To gain a handle on unstructured problems, they need to be structured somehow, and this is the challenge for economists. A replacement needs to found for the standard optimisable means-ends structure of economic problems. Whatever alternative structure is provided, it must allow for the existence of inconsistent beliefs and contradictions. The tools of classical logic and mathematics used by economists therefore will play a much smaller role. An alternative structure of economic problems must also be able to facilitate argumentation and learning, the surfacing of assumptions that constrain learning and innovation and the generation of solutions outside of the known. The structure should be useful in a participative social and political process that enables collective choice. CAN GOOD ECONOMISTS SOLVE WICKED PROBLEMS? Wicked problems can be daunting to economists trained in the use of mathematics and propositional logic but not in social and political processes. Most economists treat their problems as having an objective existence and are used to reasoning with other economists with whom they share at least similar problem definitions and values. Engaging with others outside this community, who are often seen as uninformed, is likely to be difficult to economists. Since the language and tradition for dealing with wicked problems do not exist in theoretical economics, this section will offer some suggestions on how economic problems and policymaking can be structured. Despite the fact the suggestions will deviate significantly from what economists are accustomed to, it will be argued that economists will continue to play a crucial role if wicked economic problems are to be adequately addressed. Structuring problems as contradictions

Problems emerge from inconsistent beliefs, and if beliefs are inconsistent, they necessarily give rise to a contradiction. Conceptual problems and wicked problems can be stated as contradictions. For problems that fit this basic structure, Goldratt (1994:22) suggested the conflict diagram that provides a simple yet powerful representation of problems. Figure 3 shows a possible conflict diagram involving a possible problem in monetary policy. It may result when a group of agents come together to discuss a country’s monetary policy at a time when both oil prices and unemployment are high, as is the case in South Africa currently. Figure 3 does not necessarily reflect the truth – its purpose is instead to display possible contradictory views on a problem derived from a set of inconsistent beliefs. It is derived from Taylor’s (1995:38) trade-off. Figure 3 shows a dilemma with five statements. Two conflicting actions (A and ~A) logically lead to the meeting of corresponding requirements (R and R’) in order to achieve a common objective (G). The assumptions that lead agents to believe that the statements are logically connected are shown by arrows I, II, III and IV. The arrow labelled V contains the assumptions that cause agents to believe that the actions are contradictory. The arrows play the role of conditional logical connectives.

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Figure 3: A possible problem in monetary policy Source: Own construct The figure implies that the agents can settle on a common objective for monetary policy – to create a stable economy. On the one hand, to achieve this objective, it is argued that price stability is required. To achieve price stability at this time, one side argues that the interest rate needs to be increased. On the other hand, to achieve the objective, it is argued that output stability needs to be maintained, which implies a reduction of the interest rate. The result is a problem for this group because increasing interest rates is in direct conflict with decreasing interest rates. Such a problem can be overcome by one group imposing their solution (e.g. the central bank deciding to stick to increasing the interest rate), by compromising between the extremes, or moving from one extreme to the other. Figure 3 follows the structure of one of the derived rules of inference in propositional logic – the constructive dilemma. Using the statements labeled A, ~A, R, R’ and G, the structure can be stated as: A�R • R�G; ~A�R’ • R’�G; ∴G Neither side of such a dilemma will agree with this conclusion, since it implies that the objective G will be reached regardless of whether A or ~A occurs. This is because the conditionals only follow given the beliefs of the agents arguing one side or the other. Furthermore, the conditionals are often necessary, but not sufficient. For example, most economists would argue that output stability is a necessary but not a sufficient condition for a stable economy. What all this implies is that in structuring problems, one cannot use propositional logic, but instead need to use later developments in logic, specifically modal logic and doxastix logic. Table 1 shows how contradiction can be rephrased within these logics. Note that in order to maintain economic sense, the direction of inference has to be reversed in the case of modal logic, and that a destructive dilemma then occurs. Modal logic is normally used when arguing for a policy. Table 1: Alternative logics used to express problem structure Doxastic logic Bx(A�R) • Bx(R�G)

By(~A�R’) • By(R’�G)

“Bx” symbolises “x believes that…”

Modal logic � (G�R) • � (R�A) � (G�R’) • � (R’�~A)

“� ” symbolises “it is necessary that…”

Source: Own construct

Create a stable

economy (G)

Maintain price stability

(R) I

Decrease interest rate

(~A) IV

Increase interest rate

(A)

Maintain output stability

(R’)

II

V

III

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Stating the problem in the alternative logics in table 1 can accommodate the fact that most agents will look at one side of a conflict diagram and not agree with the conclusions. For example, some theorists will challenge the statement that to maintain output stability in a time of high unemployment, the interest rate must be reduced, and proceed to give several reasons for their view. When they do so, they are challenging the assumptions that underlie the logic of arrow IV thereby demonstrating that beliefs were what created this problem and maintains it. A different set of beliefs may resolve this particular problem. Every one of the statements that appear in the boxes in figure 3 is a logical consequence of certain assumptions. The assumptions are contained in the connectives labelled I to V. The assumptions can be surfaced by first phrasing a conditional in one of the logics. The second step would be to ask the agent who agrees with the conditional to explain why one particular statement follows from another statement. One can also ask agents who do not agree with the conditional to state what needs to be true for the conditional to be true. For example, one would state the logic of connective II in modal logic as “it is necessary that if price stability is to be maintained then the interest rate must be increased.” When agents explain and justify this conditional, they will need to make further statements which will lead one to find the beliefs underlying arrow II. One may also ask why it follows that increasing the interest rate is in conflict with reducing the interest rate, and so find the beliefs of arrow V (e.g. “there is only one interest rate”). Following such a process, it is possible to find twenty or more assumptions that provide structure to the problem. The assumptions create the problem because they either lead to conflicting statements (connectives I, II, III or IV) or because they lead to the belief that a contradiction exists (connective V). As explained above, beliefs can only lead to a contradiction if at least one of them is inconsistent with at least one other beliefs. For example, under arrow II one may find assumptions that interference by the central bank will have no long term influence except for causing unexpected changes in the price level. However, under connective IV one may find an assumption that central bank interference can have a stabilising influence on the business cycle. The two assumptions are inconsistent, and thus lead to contradictory conclusions. Some assumptions also act as constraints if agents assume that such assumptions cannot be challenged. For example, an assumption that one may find under connective V is "there is only one interest rate". If agents accept this assumption, it will constrain the solution space, and they will not consider policies that suggest a system of multiple interest rates. Nickles (1981:109) proposed the idea that problems can be structured as sets of constraints. If some unquestioned beliefs are logically inconsistent, it means that the constraints will also be inconsistent. Problems with inconsistent constraints are over-determined, meaning that it is impossible to find solutions that satisfy all constraints (Nickles, 1981:87). The conflict representation and related logical expression of a conflict is preferable to the conventional representations of economic problems (mathematical equations or trade-off diagrams). To illustrate, the conventional representation will be contrasted against the problem representation proposed in this section. The conventional representation of the problem in figure 3 is given by the trade-off relationship (in figure 4) developed by Taylor (1995:38-41). This trade-off can also be converted into a mathematical function.

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Figure 4: An economist’s representation of figure 3 Source: Adapted from Taylor (1995:38) The concave curve in figure 4 shows all the possible combinations of output and inflation stability that are possible, given existing knowledge. Point C is impossible given our existing knowledge, so theorists tend to pay more attention to the points on the curve (e.g. A and B). The trade-off is visible when the economy moves from point A to point B – inflation becomes more stable, while output becomes less stable. The problem will be solved if a way can be found to experience more inflation stability and output stability at the same time (i.e. moving to point C). To achieve this, our knowledge needs to be broadened through learning or innovation. However, learning and innovation both involve a change in our beliefs, so a solution will only be found by surfacing the assumptions that structure this problem and questioning them. At first glance the trade-off may not appear to be a contradiction. A trade-off seems to depict a set of absolute constraints within which one has to maximise. However, the trade-off is structured entirely by beliefs. If this were not so, it would not be possible to shift the frontier in figure 4 outwards. Taylor (1995:39) recognises the role of beliefs when he states that point C cannot be reached given existing knowledge. The history of most sciences shows that there are very few problems with constraints that are absolute and beyond question (Simon, 1973:189). Progress in a field often occurs when a scientist finds a way to relax an assumption previously seen as a constraint (Nickles, 1981:95). How a problem is represented is crucial if a group of diverse agents are to be engaged. An appropriate representation must facilitate a structured approach for collective knowledge elicitation and creation. The trade-off representation and the derived mathematical models suffer from weaknesses in this regard. Mathematical equations, due to their unfamiliarity to most agents, are of little use in a participative process (Rosenhead, 1992:302). Equations fix the dimensions of a trade-off, and cannot generate (innovative) solutions outside its own constraints. The trade-off representation, while easy to understand, fails similarly. It does not provide cues (e.g. in the form of statements or connectives) that facilitates the surfacing of inconsistent beliefs. In fact, the trade-off representation hides or denies the role of beliefs by making the beliefs appear as absolute constraints that must be accepted as given. Constraints are not seen as constructed through social and political processes. Within absolute constraints, there is little room for

Output stability

Inflation stability

A C

B

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expanding the problem space through innovation, and the problem is reduced to one of constrained maximisation. The conflict representation and derived logical models on the other hand provide obvious cues that enable one to locate the beliefs from which the problem emerges. One must recognise that constraints are beliefs that are socially and politically imposed. Only this recognition can allow a social and political process that may lead to a change in beliefs, and turns the problem into one of innovation and human ingenuity. The conflict representation implies that agents have the power to change the problem as they engage with it, and is open to the possibility that any change will create new contradictions. Facilitating the social and political process

The source of the wickedness of economic problems is the social nature of such problems, which makes it difficult to define such problems. Wicked problems therefore require a social process of collaboration (Roberts, 2000:14). Collaboration does not mean searching for agreement between agents; it implies that agents reason within an agreed upon process with the purpose of finding breakthroughs and learning from each other. To enable a collective process of solution-seeking, a methodology must be found to enable diverse agents with inconsistent beliefs to reason together about a particular problem and its definition. One collaborative strategy suitable to approaching shared wicked problems is assumptional analysis, as developed by Mitroff et al. (1979). Its purpose is to find and challenge the assumptions that create a particular problem. Assumptional analysis recognises that problems are created by sets of critical but inconsistent assumptions, emerging from the beliefs of diverse and purposeful individuals. Different agents have problem definitions, goals and values that are conflicting to different degrees. The conflict prevents the agents from making progress towards solving the problem, unless some group imposes their beliefs. To make progress, policy solutions must be found that reconcile the conflicting beliefs by creating a change in the beliefs of agents (i.e. leads to learning and innovation). Authoritative strategies do not facilitate a change in beliefs, but may instead bring about polarisation and solutions that are similar to past solutions. The process of assumptional analysis involves three stages: group formation, assumption surfacing and dialectical dialogue (Mitroff et al., 1979:584). This analysis is complemented by a conflict representation of the problem. Assumptions are what create a problem, so to address the problem the crucial assumptions have to be surfaced. To surface as many assumptions as possible, agents must be divided into two groups with maximally different views of the problem. The problem perspectives of the two groups can be simplified and combined in a representation similar to the structure of the conflict diagram. For example, in figure 3, the view of the central bank would be depicted by the A�R�G, while the view of labour unions might be depicted by ~A�R’�G. If group formation is successful, one group will question assumptions that the other group takes for granted. This will become obvious when the groups are asked to determine the assumptions required to make the logical connective of each conditional statement valid. A group will find it easier to determine what assumptions an opposing group is making, which is why it is so important that the groups’ views are maximally different. Assumptions are then prioritised by perceived importance and certainty. Assumptions that are perceived as certain or viewed as obvious truths by all agents will act as constraints, and be given

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low priority. Assumptions that, if negated, will not materially change a policy, are considered unimportant, and are also given low priority, as per the method of Mitroff et al. (1979:587-588). Those assumptions that are most important and least certain are the critical assumptions around which dialogue will revolve. The purpose of the dialogue is to create an understanding of the role of assumptions in the conflicting problem perspectives and to challenge those assumptions either to persuade through argument or to generate policy innovations. Seeking policy solutions to an economic problem can therefore be structured either as process of argumentation or a process of innovation. The policy process as innovation The ideal for which groups should aim is to break impasses in the policy process caused by conflicting views, by generating breakthroughs or policy innovations that can be supported by all agents. For innovation to occur in any area, a solution must be found to reconcile the conflicting sides of a contradiction (Redelinghuys, 2000:272; Savransky, 2000:60-62; Nonaka & Toyama, 2002:995 and Beattie, 1999:4). A policy innovation occurs when a new set of synthetic assumptions can be found to support a new policy which is acceptable to all groups. Given a contradiction such as figure 3, breakthrough innovations occur when the critical assumptions underlying connective V is invalidated. In such a case the conflict dissolves as a proposed policy and its negation is synthesised. The assumptions create the impression of conflict and division between agents, so the first step is obviously to surface the assumptions (as explained before). For example, the validity of connective V depends on the fact that only one relevant interest rate exists, that only the central bank can change that relevant interest rate, that the inflation target is fixed by the central bank, or that this interest rate can only be changed in one way – by official announcement. After surfacing the assumptions, agents should attempt to invalidate any of the assumptions underlying connective V (which will naturally lead to new assumptions). Assumptions can be invalidated by challenging each one with any of the following three questions: � Is it necessarily so that [assumption]? � Is [assumption] true under all conditions? � What actions will make [assumption] invalid?

If any of the assumptions underlying connective V in figure 3 is invalidated, the connective collapses, and A and ~A is reconciled. In such a case the central bank will either be able to maintain both price and output stability with a single decision on interest rates, or increase and decrease interest rates at the same time (not as absurd as it sounds if one considers the assumptions). If this synthesis is achieved, it could be represented on figure 4 as a movement to a new frontier intersecting point C. The movement to this previously impossible region constitutes progress, and will only be achieved if our existing knowledge is improved through learning or innovation. Some of the changes to monetary policy suggested by economists in South Africa are attempts to create a synthesis, such as requesting the Minister of Finance to change the inflation target, adopting more than one relevant interest rate or for the central bank governor “to talk tough so he doesn’t have to act tough” (Bisseker, 2006:23). Each of the suggestions has weaknesses and is based on other assumptions, but they illustrate synthetic thinking. For example, if the Minister of Finance widens the inflation target, it becomes possible for the central bank to pursue price stability (now with a redefined meaning) without increasing the interest rate. A critical assumption underlying this suggestion is that central bank independence will not be questioned. This also

20

demonstrates that meanings (created by beliefs) maintain problems (Wettersten, 2002:507) and that synthesis often occurs when the meaning of concepts are challenged and redefined. It can be seen that assumptional analysis, in conjunction with the conflict representation of economic problems, is preferred to taming strategies because it does not lead to a loss of information. Instead, by making assumptions explicit, agents are able to question those assumptions. If the questioning of assumptions is successful this results in learning or innovation as agents change their beliefs. The policy process as argument

If dialectical dialogue fails to realise the ideal of finding a new set of synthetic beliefs, it should attempt to change agent’s beliefs through a collective process of argumentation. Argumentation is appropriate since policies can be understood as being the outcome of a complex argument. An argument seeks to establish the credibility of a particular policy decision, and it changes over time as agents engage with each other and change their beliefs (Mitroff & Mason, 1980:331-332). Changes in monetary policy, for example, has been the result of an ongoing and developing process of argumentation between central bankers and economic theorists (Colander, 2001:70). By structuring the policy process as a complex argument, groups are enabled to deal with their inconsistent beliefs without loss of information. In fact, the argument structure recognises that conflicting views often depend on each other for their existence. Since this structure can incorporate inconsistent beliefs, it allows the use of conflicting beliefs in the policy process without needing to determine the truth of these beliefs. The purpose of argumentation is to facilitate the kind of change in beliefs (i.e. learning) that normally happens at a slower pace if agents do not engage in a structured way. Structuring the collective policy process of argumentation also requires that the critical assumptions be surfaced, since these assumptions form the premises of the argument. These assumptions can be used in two approaches to argumentation. The first approach involves structuring one of the proposed policies as a Toulmin-like argument (Mitroff & Mason, 1980:334) as shown by figure 5. It is more complex than the classic syllogism and was developed by Toulmin (1958) to better handle the intricacies of reasoning. Figure 5: A Toulmin-like argument structure Source: Adapted from Mitroff & Mason (1980:337)

Claim

C

Warrant

D�C

Backing B

Data D Rebuttal

~C

~(D�C)

~D

~B

Claims of previous

arguments

21

A policy is the consequence of a complex argument that will result in a claim (C) about reality which is neither certain nor complete. The claim is a statement about the state of reality and the action that should be taken to transform this into a more ideal state. The data (D) provides the (objective and subjective) evidence that supports the claim, and is the result of the claims of previous arguments. The warrant (W) contains the assumptions that justify why the data can be interpreted as support for the claim. Those assumptions entitle one to state that if the data are true, then the claim will follow. The backing (B) are the background (often metaphysical) beliefs about truth and reality that make the warrant believable. The complex argument is rebutted by others who deny the background beliefs (~B), believe that the data is incorrect (~D), believe that the warrant is not reasonable (~(D�C)) or that the claim is not legitimate (~C) (Mitroff, 1980:334-335). Bisseker (2006:22-26) provides a good case study of the conflicting views of economists on monetary policy in South Africa in mid-2006. Of the ten economists interviewed, half believed that interest rates should be reduced or stay constant, while the other half argued for a rate increase. Given the assumptions surfaced through the interviews, an argument to reduce interest rates might appear as follows: � C: reduce interest rates; � D: inflation rate of 3,7% which is well within the target of 3-6%; � D�C: if the inflation rate is within the target range then the central bank should reduce

interest rates because the inflation outlook is positive; � B: the central bank is responsible for maintaining the inflation target; the mission of the

central bank is to protect only the internal buying power of the currency; and the central bank should maximise social welfare.

All of these were rebutted by other economists. Rebuttals came from those who argued (from different premises) for a rate decrease, and from those who argued for a rate increase. The following rebuttals are therefore just a list of possible rebuttals, and not a coherent argument in support of the claim or its negation: � ~C: increase interest rates; � ~D: one needs to consider inflation expectations and forecasts of inflation; other data need to

be considered that might undermine the economy in the future such as the current account deficit, household savings, rising house prices and credit growth;

� ~(D�C): the inflation outlook is not necessarily good if the current inflation rate is well within the target range, since some forecasts show a high probability of inflation exceeding the target; an increase might reinforce the central bank’s credibility;

� ~B: it is more important for the central bank to be consistent rather than maximising current welfare; actions by government departments counteract the efforts of the central bank

Once the argument has been constructed from the agents’ full set of critical assumptions, policies can be derived from them without rejecting inconsistent assumptions. In their seminal work in modal logic, Rescher and Manor (1970:182) developed the concept of the maximally consistent subset (mcs) that enables agents to derive conclusions from inconsistent beliefs. The mcs is the largest set of statements that can be conjoined without contradiction, so that policies can be derived from a mcs. Mitroff et al. (1982:1395-1400) developed a methodology for deriving policies from the inconsistent assumptions that structure a Toulmin-like argument. The complete set of maximally consistent sets is first derived from the argument and inconsistent sets discarded. For example, from figure 5 one can derive eight maximally consistent sets e.g. {B, D, D�C, C} or {~B, D, ~(D�C), ~C}. Neither of these two sets contains logical inconsistencies.

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This is followed by determining the logical consequent of each mcs. From the set {B, D, D�C, C} one derives the logical consequents B & D & C while from the mcs {~B, D, ~(D�C), ~C} one derives ~B & D & ~C. The conjunction of the logical consequents of each mcs forms an argument for a policy proposal. The last step is to rank order each mcs according to plausibility and choosing the policy derived from the mcs with the highest plausibility. Mitroff & Mason (1982:334-345) provides a method for measuring plausibility of maximally consistent sets on an interval scale and transforming the choice of the most plausible mcs into a linear programming problem given certain plausibility constraints. Mitroff and Mason (1982:346-348) also demonstrate how agents can develop synthetic positions (where C and ~C are true) by relaxing particular plausibility constraints. No information is lost by treating a wicked problem as a complex argument. The inconsistent assumptions are used to create knowledge and promote learning, especially if synthetic positions are developed. In fact, it would not be possible to develop a synthetic position (through argument or innovation) without the inconsistent beliefs of diverse agents. If beliefs were consistent, there would only be one argument, from which only one set of policies would be derived repeatedly – innovation would not occur at all. So if policymakers deny the social nature of economic problems, they also preclude innovation. The second approach to argumentation requires only the conflict diagram, and is more confrontational. It is an attempt to invalidate opposing perspectives by challenging connectives I, II, III and IV. For example, connective III in figure 3 is based on the assumption that decisions of agents only depend on past and current policy actions. The central bank may argue that this assumption is invalid since decisions are also based on expectations of future policy actions, and that a decrease in the interest rate will destabilise the economy in the long run. If the central bank is able to convince labour unions that this assumption is invalid, the contradiction is eliminated, and the problem no longer exists. Empirical research could be used as a tool of persuasion, and knowing the critical assumptions for connectives I to IV provide a focus for such research. Successfully challenging connectives I to IV results in one group of agents learning from another, but it does not necessarily lead to policy innovation. The policy processes of innovation and argument are complementary. In economic policymaking, there is often innovation and two-way learning as theorists and policymakers engage in dialogue (Barber, 1989:119-126). Innovation in policy may occur collectively or when either the theorists develop a new perspective on a particular problem. Once the innovation is developed, theorists and policymakers engage in an unfolding argument. Such an argument ideally leads to a change in beliefs on both sides (learning) as the innovation is refined and a synthetic position is developed. Central banks, like those in South Africa, who exclude various groups from the policy process, are not likely to create new knowledge, and will merely copy innovations from other countries. CONCLUSION Economic problems for which policies needs to be developed, are not the well-structured constrained maximisation problems as they appear in texts. In fact, economic problems should not even exist given the assumptions of neoclassical economic theory. In reality, however, economic problems exist and have a wicked nature. Wicked problems are unstructured problems caused by the inconsistent beliefs of agents and can never be solved permanently. Unfortunately, the language and tradition to deal with such problems do not exist in economic theory, and prevent economists from making substantial contributions to the solution of wicked problems. Solving wicked problems with the tools suited to well-structured problems lead to solutions that aggravate the problem. This paper offered methodologies that could be used in solving wicked economic problems.

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Wicked economic problems require a different set of tools from those that economists are used to. Some of the tools, such as modal logic, are derived from tools with which some economists are already familiar. The most important mindshift economists and policymakers have to make in approaching wicked problems, is to recognise the social and political nature of such problems. Agents affected by a wicked problem need to be engaged in a social process. To solve wicked problems, the inconsistent beliefs of all affected agents must be surfaced and challenged so that new knowledge can be developed. Economists should be participants in such collective policy processes. Assumptions are the basic tools of economists as model-builders, and they are likely to play a significant role in such processes by applying their skill in identifying assumptions. Economists have a vaster “negative knowledge” about the economy than non-economists (Machlup, 1980) that is they know better what is not, than what is. This negative knowledge will make economists invaluable in the challenging of assumptions required for argument and innovation.

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CURRENT CHALLENGES OF RISK MANAGEMENT IN THE SOUTH AFRICAN BANKING INDUSTRY

A Pampallis & E H Redda

ABSTRACT The banking industry has a unique and central place in the economy of the country by the role it plays in financial intermediation, transmission of economic policy and financial innovation. The banking industry is a dynamic, complex and highly regulated industry. The current business environment makes it dynamic and complex, and due to the banks` role in the economy, political motives and intervention make it a highly regulated and controversial in many instances. The South African banking industry is undergoing through a number of changes, along with opportunities, providing banks with the ever-highest challenges in their history. Market volatility, corporate irregularities and troubled capital markets have shaken the banking industry. It highlighted the dangers of poor risk management. The nature of competition has changed in today’s financial services marketplace. These all entail a high level of risk to bank management - a risk that can endanger the functioning of the economic system at large. Various risk management professionals agree that traditional risk systems cannot capture the inter-relationships between various types of risks. In the face of such complexities, there is a need to have a sound banking system to address the macroeconomic objectives without which nothing much can be done. There is a need to have a banking system that effectively and efficiently fulfils its role in financial intermediation, transmission of economic policy and financial innovation, and a banking system that creates confidence for businesses in the economy at large. And that requires a new approach to risk management in the current fast pace changing business environment. The aim of this research is to identify the various risks and the impact they have in the success and survival of the banks, and investigate the currently employed risk management practices with a view of looking at “Risk management” in the banking sector from a strategic approach.

INTRODUCTION

The aim of this paper is to identify a strategic approach that is employed in managing financial risks in the South African banking industry. The Chinese character meaning “opportunity” is the same as the symbol that stands for “crisis”. Perhaps the Chinese were the first people to recognize this important truth: namely, that risk and reward are two sides of the same coin (Errington, 1993:14). The origins of risk financing can be traced as far back as 1700 BC when the Babylonians established bottomry as a means to handle the risks associated with international trade. Bottomry was a type of loan; a grantee issued a loan on the value of goods, which were shipped between counties. Repayment of the loan was based on the safe arrival of the goods – the seller had to repay the grantee if the goods arrived safely, if not the loan did not have to be repaid (Valsamakis, Vivian & Toit, 1995:2). A lot can be said about the historical development of risk and risk management. Falkena, Koke & Meijer, (1989:2), describe banks as managers of risk. They further stress that banks and commercial banks in particular, transmit monetary policy to the money market and the economy

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in general and that commercial banks are at the heart of the financial system, distinguished from other banks by the breadth of their involvement in the financial markets. Banks, as professional risk managers par excellence, have to ensure that they are sufficiently rewarded for the commercial risks they take (Falkena & Llewellyn, 1999:22). It is crystal clear that banks are key players in the economy. A sound banking system is, therefore, vital if not a prerequisite to achieve the broader macroeconomic objectives of a country. The South African banking industry faces probably the most challenging time in its history. Following the country’s readmission to the world community, overseas banks have come into the country focusing on the more lucrative segments of the corporate market (Goosen, Pampallis, Van Der Merwe & Mdluli, 1999:182). In the broader context of global developments, South Africa financial system is confronted with a number of specific challenges to ensure its “safety and soundness”. These challenges can be categorized in to various risk classes, such as systemic risk, market risks or operational risks (Falekena & Llewellyn, 1999:40). Over the past decade or so, various events have had a major effect on the business of banking and the nature of competition in the banking industry, both in the United States and abroad. These events include the disintermediation of short-term corporate lending, the transformation of excess international liquidity into loan to less developed countries, substantial growth in products not accounted for on balance sheet, and technological advancements enabling business instantaneous global communications and twenty-four-hour trading (Fraser & Rose, 1990:39). Today banks are no longer the only suppliers of banking services: there are many traditional activities of banks that can now be undertaken equally well by markets, non-banking financial institutions and non-financial companies (Fourie, Falkena & Kok, 2001:90). The overall impact is that the nature of competition in the industry has changed. Market volatility, corporate irregularities and troubled capital markets have shaken the banking industry. It highlighted the dangers of poor risk management. Traditional risk systems cannot capture the inter-relationships between various risk types across geographies, departments and lines of business. And the new Basel Capital Accord is creating a system for banks to improve their risk management practices (Yeoh, 2005:2) As the rules of wealth creation and preservation evolve in the new economy, traditional risk management approaches will not get the job done unless they are robust enough - even holistic enough - to assure success. In fact they may even contribute to failure (Deloach, 2000:4). He further states that sophisticated ways of creating value mean one thing: risk profiles are changing – faster than ever and risk is more significant and less understood than ever before. He proposes a new approach: Enterprise-Wide Risk Management (EWRM). EWRM is a structured and disciplined approach: it aligns strategy, processes, people, technology and knowledge with the purpose of evaluating and managing the uncertainties the enterprise faces as it creates value (Deloach, 2000: 5). The banking industry is a dynamic, complex and regulated industry. The current business environment makes it dynamic and complex and due to their (banks) role in the economy, political motives and intervention make it a highly regulated and controversial at many instances. These all entail a high level of risk to bank management; risk that can endanger the functioning of the economic system at large. In the face of such complexities, there is a need to have a sound banking system to address the broader macroeconomic objectives without which nothing much can be done. Any country wishing to attract investment must have a solid and profitable banking sector (Goosen, et al., 1999:183). The contemporary South African business environment, however, seems to put much pressure in the banking industry. Looking ahead, it will ask much more - a new way of approaching to risk management. Regardless of what the business environment has to offer to the banking industry, it is imperative to have a sound banking system. A banking system that effectively and efficiently fulfils

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its role of channeling funds from surplus units to deficits units and a banking system that creates confidence for businesses in the economy at large. From South African banking industry perspective, the following issues should be raised and addressed:

• What are the various risks and their impact in the success and survival of the banks? • And what are the currently employed risk management practices? And how are these systems

integrated across the bank? and • How can you create and execute a solid corporate strategy that would enable a bank to deliver

maximum stakeholders value? From its humble origins as an insurance-buying activity and a security function, risk management has developed into a fully-fledged management function which is the beginning to move into areas which were originally considered unrelated (Valsamakis, et al., 1995:7). Risk management is now emerging as a profession in its own right. People who have become lawyers, doctors, or engineers are now becoming risk managers, and the best of them are being handsomely rewarded for doing so (Borge, 2001:3). According to (Valsamakis, et al., 1995:6), risk management started to develop in South Africa only since 1970s and they further sketch its historical development till the 1990s. So, it is fairly young discipline of study, which a lot can be done on it. Banks play an important role in the economy through their financial intermediation and innovations and in doing so they have to manage a great variety of risks including financial risks, operational risk and market risk. They are in the business of managing risk. The rationale of choosing the topic is made against such background. With the reasoning that a lot should and can be done on the field of risk, be it financial or general, particularly in the banking industry. The value of the research is two-fold. Firstly, the research will identify the risks involved, their impact and the tools/instruments employed in managing them. It will make a thorough understanding of the complexities involved in bank risk management. Secondly, as mentioned above, risk management is fairly a recent concept and it is in a process of development. So, it will make an invaluable contribution to the different banks in South Africa. RISK MANAGEMENT IN THE BANKING INDUSTRY Sources of Risk Different definitions and classifications can be used in managerial practice. A general classification may use physical, social and economic sources. But an in-depth investigation of the problem of risk identification may need classification that can cover all types of risk in more detail. Therefore the sources of risk can be represented depending on the environment in which they arise as follows (Williams et al., 1998): Physical environment The physical environment is an important source of risk. Natural disasters like earthquakes, storms, flooding etc lead to serious losses. The environmental influence on the people and people’s influences on the environment are important aspects of this source of risk. The physical environment can be a source of profitable opportunities, for example real estate as an investment, or appropriate climate for the agriculture business or tourism. Social environment The changes in people’s values, human behaviour and state of social structures are another source of risk. Civil unrest, social riots and strikes are events underlining the importance of the social environment as a source of risk. The level of worker skills and loyalty to the organisation determine to a large extent the success of the organisation. The difference in social values and culture, for

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example, the businessman from Europe, America and Asia, creates a high level of uncertainty. At the same time the changes of culture create opportunities. For example, in many countries the equal opportunities of minorities lead to faster development. Political environment The political environment is an important source of risk in all countries. The ruling party can affect organisations in different ways, for example by cutting aid to some industry branches or protecting some branch or region, by implementing strict rules about the environment, etc. The political environment is a more complex and important source of risk in an international aspect. The difference in the ruling system raises different attitudes and policies toward business. For example, foreign investment might be confiscated, or taxation systems might change significantly, which will hurt the investor’s interests. The political environment can present opportunities as well, for example the change in the political system and transfer to the market economy in Bulgaria. Operational environment Operational activities of the organisation create risk and uncertainty. For example, damage in installation or production processes might result in fiscal injuries of workers. Unfavourable working conditions can threaten both the physical and mental health of the workers. The formal procedures of hiring or firing employees may generate a legal problem. The manufacturing processes may produce harm to the environment. In this case the organisation is a source of risk. The international business can suffer from risks in the transport system. The operational environment also provides opportunities, because the results of organisational activities improve the level of life and work of the people. Economic environment The economic environment usually is hardly influenced by the political environment in a single country, but the globalisation of the market creates a market that is greater than a single market and needs to be considered separately. Although a particular activity of the government can affect the international capital market, the control of the market is impossible for a single government. Examples of sources of risk generated from the economic environment are, in a global aspect, economic recession and depression, and at a local level, interest rate, credit policy, etc. Legal environment The legal environment creates risk and uncertainty in business. This opinion is valid for all countries, but is very important in Bulgaria during the last ten years. The legal system creates risk by disparity of current or new laws to the environment. In the international domain, complexity increases because of the variation of legal standards in different countries and can lead to conflict among the partners. The legal system creates opportunities also by stabilising the society and, due to that organisations know the restrictions in their work. The legal system provides also a protection of rights, such as author’s right, copy right, unemployment protection. Cognitive environment The risk managers’ ability to reveal, understand and assess risk is not perfect. The difference between perception and reality for different people is an important source of risk for an organisation. The cognitive environment is a big challenge to the risk manager. The questions of how to assess the effect of the uncertainty on the organisation and how to understand whether the perception of risk is real are considered. The Chernobyl accident and a lot of production accidents caused by carelessness and human factors are clear examples of the risk arising from the cognitive environment. THE NATURE OF RISK IN THE BANKING INDUSTRY Hollman and Forrest (1991:50) propose a five-step routine for a service business to reduce the uncertainty associated with pure loss exposures and to accomplish its risk management objectives.

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The business of banking involves risk. Banks make profit by taking risk and managing risk. The traditional focus of risk management in banks has typically arisen out of its main business intermediation – the process of making loans and taking deposits (Matthews and Thompson, 2005:183). Banks are subjected to a wide array of risks in the course of their operations. In general, banking risks fall into four categories: financial, operational, business and event risks (Van Greuning and Bratanovic, 2000:3). In the banking environment there are a large number of risks. Most are well known. However, there has been a significant extension of focus, from the traditional qualitative risk assessment towards the quantitative management of risks, due to both evolving risk practices and strong regulatory incentives (Bessis, 2002:11). There are risks relating to management of the balance sheet of the bank and are identifiable as credit risk, liquidity risk and interest rate risk. The advance of off-balance sheet activity of the bank has given rise to other types risk relating to its trading and income generating activity. These activities give rise to position and market risk (Matthews and Thompson, 2005:183). Many banks engage in activities off-balance sheet. This means that they enter into agreements that do not have a balance sheet reporting impact until a transaction is effected. Off-balance sheet risk refers to the volatility in income and market value of bank equity that may arise from unanticipated looses due to theses off-balance sheet liabilities (Koch and Macdonald, 2003:126-127). According to Koch and Macdonald (2003:118) the Federal Reserve Board identifies six types of risk: credit risk, liquidity risk, market risk, operational risk, reputation risk and legal risk. Risk categories and dimensions are generally well identified by banks as well as the regulatory agencies. While regulatory definitions for the various categories differ somewhat, there is general agreement that banks face strategic, credit, market, liquidity, operational, compliance/legal/regulatory and reputation risk (Daberko, 1999:9). In the broader context of global developments South Africa’s financial system is confronted with a number of challenges to ensure its “safety and soundness”. These challenges can be categorised into various risk classes, such as system risks, market risks and operational risks (Falkena and Llewellyn, 1999:40) Oldfield and Santomer (1997:4) argue that the risks facing all financial institutions can be segmented into three separable types, from a management perspective. These are (i) risks that can be eliminated or avoided by simple business practices, (ii) risks that can be transferred to other participants and (iii) risks that must be actively managed at the firm level. RISKS THE BANKS ARE EXPOSED TO Credit Risk Credit risk may be defined as the risk of a debtor failing to meet punctually the financial commitments stemming from credit agreement – i.e. he must be able to service the interest and be in a position to repay the capital when it falls due (Falkena and Kok, 1991:18). Credit risk is the first of all in terms of importance. Default triggers a total or a partial loss of any amount lent to a counter party. Credit risk is critical since the default of a small number of important customers can generate large losses, potentially leading to insolvency (Bessis, 2002:13). Broadly the counter parties/debtors can be categorised as individuals, companies/firms and countries and therefore they are identifies as:

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Personal (Consumer) Risk This is the risk of default of a debtor where the debtor is an individual person who was granted a loan (credit) for a number of things such as mortgage finance, car finance and the like. Company (Corporate) Risk and This is the risk of default of a debtor where the debtor is a corporate (legal entity). The loan (credit) could be granted for financing project, purchase of equipments among other things. Country (Sovereign) Risk In this case the loan receiver is another state (country). States are sovereign countries and they have different legal practices and they cannot be declared as bankrupt. But this does not mean there is no risk in international credit. Liquidity Risk Liquidity risk is the current and potential risk to earnings and the market value of stockholder’s equity that results from a bank’s inability to meet payment or clearing obligations in a timely and cost-effective manner. The risk can be the result of either funding problems or market liquidity risk (Koch and Macdonald, 2003:118). Funding liquidity risk is the inability to liquidate assets or obtain adequate funding from new borrowing and market liquidity risk is the inability of a bank to easily unwind or offset specific exposures without significant losses from inadequate market depth or market disturbances. Liquidity risk, therefore, can be defined as the inability of a bank to generate sufficient cash to meet its maturing deposits. In short, bank liquidity refers to the closeness of bank assets to money (Falkena and Kok, 1991:78). Interest Rate Risk Interest rate risk exposure is a characteristic of any financial institution and stems from assets and liabilities maturing (being repriced) at different times. Liabilities may mature before assets do, necessitating the rollover of such assets until sufficient quantity of assets mature to repay liabilities and assets may mature before liabilities do, in which case have to be reinvested until they are needed to repay the liabilities (Falkena and Kok, 1991:78). The risk lies when interest rate rise moves unfavourably to the bank. When liabilities mature before assets and interest rate rises it means that these expensive funds (liabilities) are used to fund assets that yielding lower returns. And the other scenario is risk lies when assets mature before liabilities and interest fall. In this case the reinvestment of the already matured assets will earn low rates and the bank will have to pay the higher rate on the liabilities to be retired. Currency Risk Foreign exchange risk arises from changes in foreign exchange rates that affect the value of assts, liabilities, and off-balance sheet activities denominated in currecncies different from the bank`s domestic (home) currency. It exists because some banks hold assets and issue liabilities denominated in different currencies liabilities (Koch and Macdonald, 2003:124). The risk that exchange rates may move against the bank, causing the net value of its foreign currency assets/liabilities to deteriorate (Matthews and Thompson, 2005:44). It is a risk of volatility due to a mismatch, and may cause a bank to experience losses as a result adverse exchange rate movements during a period in which it has an open on – or of balance sheet position, either spot or forward, in an individual currency (Van Greuning and Bratanovic, 2000:211). It is clear that currency risk arises from a mismatch between the values of assets, liabilities and capital denominated in foreign currency or

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vice versa or because of a mismatch between foreign receivable and foreign payables that are expressed in domestic currency. Van Greuning and Bratanovic (2000:212) state that in practical terms, currency risk comprises transaction risk, economic or business risk and revaluation risk or translation risk. Transaction risk Transaction risk, or price based impact of exchange rate changes on foreign receivable and foreign payables – i.e. the difference in price at which they are collected or paid and the price at which they are recognised in local currency in the financial statements of a bank or corporate entity. Economic or business risk Risk related to the impact of exchange rate changes on a country’s long term or company competitive position. For example, a depreciation of the local currency may cause a decline in imports and growth of exports. Revaluation risk or translation risk Risk which arises when a bank’s foreign currency positions are revalued in domestic currency, or when a parent institution conducts financial reporting or periodic consolidation of financial statements. Investment risk Investment risk concerns a decline in the value of marketable securities and fixed assets caused by factors other than default or delayed payment. Investment losses are incurred only when a marketable asset is sold at a price below that at which it is shown on a balance sheet (Falkena and Kok, 1991:121). Capital risk

Capital risk refers to the risk of an institution’s own capital resources (i.e. total shareholder’s interest) being adversely affected by unfavourable external developments. According to accounting principles capital is defined as the difference between the stated (or book) value of assets and liabilities (Falkena and Kok, 1991:149). Capital is one of the key factors to be considered when the safety and soundness of a particular bank is assessed. An adequate capital serves a safety net for variety to which an institution is exposed in the course of its business (Van Greuning and Bratanovic, 2000:105). Capital is also the ultimate determinant of a bank’s lending capacity – thus a bank’s balance cannot be expanded beyond the level determined by the capital adequacy ratio. Basel II It is relevant here to look at the benefits and implications of the Basel II: International Convergence of Capital Measurement and Capital Standards: a Revised Framework 2004. The Basel capital adequacy standard is based on the principle that the level of a banks capital should be related to the bank`s specific risk profile. In addition to directly relating capital to bank`s risks, this framework was deemed flexible enough to allow consistent incorporation of other types risks and was expected to provide a fairer baises for comparison of banking systems (Van Greuning and Bratanovic, 2000:111). The fundamental objective of the Committee’s work to revise the 1988 Accord II has been to develop a framework that would further strengthen the soundness and stability of the international banking

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system while maintaining sufficient consistency that capital adequacy regulation will not be a significant source of competitive inequality among internationally active banks. In developing the revised Framework, the Committee has sought to arrive at significantly more risk-sensitive capital requirements that are conceptually sound and at the same time pay due regard to particular features of the present supervisory and accounting systems in individual member countries. The Committee believes that the revised Framework will promote the adoption of stronger risk management practices by the banking industry, and views this as one of its major benefits. The Committee also seeks to continue to engage the banking industry in a discussion of prevailing risk management practices, including those practices aiming to produce quantified measures of risk and economic capital. The Basel II accord is basically aimed at strengthening the soundness and stability of the banking system across the banking industry and the document produces three pillars: The First Pillar ─ Minimum Capital Requirements The first pillar presents the calculation of the total minimum capital requirements for credit, market and operational risk. Total risk-weighted assets are determined by multiplying the capital requirements for market risk and operational risk by 12.5 (i.e. the reciprocal of the minimum capital ratio of 8%) and adding the resulting figures to the sum of risk-weighted assets for credit risk (Basel II, 2004:12). The Second Pillar – Supervisory Review Process This section discusses the key principles of supervisory review, risk management guidance and supervisory transparency and accountability produced by the Committee with respect to banking risks, including guidance relating to, among other things, the treatment of interest rate risk in the banking book, credit risk (stress testing, definition of default, residual risk, and credit concentration risk), operational risk, enhanced cross-border communication and cooperation, and securitisation (Basel II, 2004:158). The Third Pillar – Market Discipline The purpose of Pillar 3 ─ market discipline is to complement the minimum capital requirements (Pillar 1) and the supervisory review process (Pillar 2). The Committee aims to encourage market discipline by developing a set of disclosure requirements which will allow market participants to assess key pieces of information on the scope of application, capital, risk exposures, risk assessment processes, and hence the capital adequacy of the institution. The Committee believes that such disclosures have particular relevance under the Framework, where reliance on internal methodologies gives banks more discretion in assessing capital requirements (Basel II, 2004:175). The benefit of the Basel II accord is to promote the adoption of a stronger risk management practices by the banking industry and therefore to strengthen the safety and soundness of the banking system. The South African banks are about to adopt the Basel II accord. In the annual report of the South African Reserve Bank (ASRB) (2004:29) it is stated that the Bank Supervision Department will require South African banks to be Basel II compliant by 2008 and is of the view that adoption of Basel II standards has the potential to ensure a safe and sound banking system, improve risk management within the system, attract foreign funds into South Africa and make South African banks more competitive internationally. Market Risk

Market risk is the risk that a financial institution's earnings and capital, or its ability to meet its business objectives, will be adversely affected by movements in market rates or prices such as interest rates, foreign exchange rates, equity prices, credit spreads and/or commodity prices

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(Daberko, 1999:29). Market risk is the current and potential risk to earnings and stockholders` equity resulting from adverse movements in market rates or prices. The three areas of market risk are: interest rate or reinvestment rate risk, equity or security price risk, and foreign exchange rate risk liabilities (Koch and Macdonald, 2003:124). Operational Risk

Operational risk is defined as the risk of loss resulting from inadequate or failed internal processes, people and systems or from external events. This definition includes legal risk, but excludes strategic and reputational risk (Basel II, 2004:137). Operational risk arises from the potential that inadequate information systems, technology failures, breaches in internal controls, fraud, unforeseen catastrophes, or other operational problems may result in unexpected losses or reputation problems (Daberko, 1999:37). Reputation Risk Reputation risk is the exposure incurred from unexpected incidents, or from unanticipated response to the institution's initiatives, actions or day-to-day activities (Daberko, 1999:45). Reputation risk is the risk that negative publicity, either true or untrue, adversely affects the bank`s customer base or brings forth costly litigations, hence negatively affecting profitability. Because these risks are basically unforeen, they are all but impossible to measure liabilities (Koch and Macdonald, 126. Systemic Risk According to Lodfield and Santomero (1997:10) Systematic risk is the risk of asset value change associated with systemic factors. As such, it can be hedged but cannot be diversified completely away. In fact, systematic risk can be thought of as undiversifiable risk. Financial institutions assume this type of risk whenever assets owned or claims issued can change in value as a result of broader economic conditions. As such, systematic risk comes in many different forms. For example, as interest rates change, different assets have somewhat different and unpredictable value responses. Energy prices affect transportation firms' stock prices and real estate values differently. Large scale weather effects can strongly influence both real and financial asset values, for the better or worse. These are a few types of systematic risks associated with asset values. Legal Risk Legal risk arises from the necessity of the institution to conduct its transaction in conformity with the business and contractual legal principles applicable in each of the jurisdictions where the institution conducts its business and the possibility that a failure to meet these legal requirements may result in unenforceable contracts, litigation or other adverse consequences. Regulatory risk is the risk that laws or regulations may change in a way that adversely affects an institution's operations and competitive viability. Compliance risk arises from the potential that violations of regulatory laws and rules may result in adverse judgments in lawsuits, or regulatory sanctions such as civil money penalties, and therefore negatively affect the institution's ability to meet its business objectives (Daberko, 1999:41). Asset Risk The risk that assets held by banks may not be redeemable at their book value. This can be the result of price changes of investment securities or non repayment; i.e. default. Asset risk not only refers to capital value but also the interest paid on the assets (Mathews and Thompson, 2005:54).

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Solvency Risk Solvency risk is the risk of being unable to absorb losses, generated by all types of risks with available capital. It differs from bankruptcy risk resulting from defaulting on debt obligations and inability to raise funds for meeting such obligations. Solvency risk is equivalent to the default risk of a bank (Bessis, 2002:20) Considering the major changes in regulatory approach to bail out procedures, financial institutions running into solvency problems in the future will be dealt with very differently than in the past. Any bailout now implies that owners and long term subordinated debt holders will lose their full investment that before formal assistance (taxpayers` money) will become available (Falkena and Llewellyn, 1999:46). Payments Risk It is risk that arises from the operation of the payments mechanism and the possibility of failure of a bank to be able to make the required settlements. Risk of settlement (also known as Herstatt risk) is the loss in a foreign currency exchange trading that one part will deliver foreign exchange but the other party fails to meet its end of the bargain (Mathews and Thompson, 2005:54-55). Mismanagement and Fraud Overall risk management policies and tolerances should be set on a comprehensive, organization-wide basis by Senior Management, and reviewed with—and where appropriate, approved by—the Board of Directors. Policies and tolerances addressing risk identification, measurement, monitoring and control should be clearly communicated to those areas affected throughout the organization (Deberko, 1999:3-4). New corporate governance measures around the world have placed a host of new demands on banks. Boards of directors and audit committees are being given more responsibilities than ever before, requiring higher levels of independence, commitment and education (Deloitte, 2005:14). To be effective, concern for and tone for risk management must start at the top. It must become a part of the way the organization does business and not be viewed as an independent analysis. Proper risk assessment, analysis and management will not take place unless it is woven into strategic planning, budgeting process, operating plans, and business decisions (Deberko, 1999:6). As the participants underlined, the challenge in today’s increasingly diverse organisations is, therefore, not only how to create the necessary infrastructure of risk and control to guard against such lapses, but also how to instill a culture of risk awareness and stewardship across the entire business. Risk teams are developing a more proactive and holistic approach to risk management in keeping with the challenges and opportunities of a fast changing marketplace (Rice Waters House Coopers, 2005:18). Following a number of high-profile corporate failures in recent years, both locally and abroad, increasing emphasis is being placed worldwide on the accountability and responsibilities of boards of directors. Some thoughts on the need for bank directors, particularly non-executive directors, to receive training to enable them to fulfil their duties are therefore deemed appropriate. Basic management experience and skills necessary to succeed in other endeavors are equally applicable to banks. Thus, the knowledge and experience you have developed in other walks of life can be effectively used in looking after bank affairs. Add to this a questioning attitude and a willingness to commit time and energy to bank matters and you have many of the attributes of an effective bank

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director. The only thing that may be missing is a basic knowledge of banking and an awareness of specific matters to consider in overseeing a bank (SARB annual report: 2004:2). Strategic Risk Strategic risk is the risk assumed as a result of decisions made or not made in the course of managing the business (Daberko, 1999:21). Risk Management Approaches The banking Industry has long viewed the problem of risk management as the need to control four of the above risks which make up most, if not all, of their risk exposure, viz., crddit, interest rate, foreign exchange and liquidity risk. While they recognize counterparty and legal risks, they view them as less central to their concerns. Where counterparty risk is significant, it is evaluated using standard credit risk procedures, and often within the credit department itself. Likewise, most bankers would view legal risk as arising from their credit decisions or, more likely, proper process not employed in financial contracting (Santomero, 1995:11). CONCLUSION It is clear from the above discussions that the Banks of today, who have a unique and central role in the economy of the country, need to look at risk in a more holistic fashion incorporating a lot more of the risks mentioned above in their strategic approach to risk management. By having a sound risk management practice looking at most of the risks across the banking industry, this would create an excellent platform for economic growth and prosperity.

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THE IMPACT OF CHINESE IMPORTS ON SOUTH AFRICAN EMPLOYMENT AND OUTPUT GROWTH: AN EMPIRICAL

PERSPECTIVE

M Biyase and L Bonga-Bonga

ABSTRACT

This paper provides some empirical perspective on the effects of Chinese imports on employment and output growth in South Africa. The paper also assesses the current policy by the South African government to restrict trade with China on some specific textile and clothing products. The Structural Vector Autoregressive (SVAR) models are used to characterize the joint dynamics of output, sectoral and total employment in response to China’s import shocks. Using the contemporaneous restrictions that identify different shocks, this study concludes that while an increase in imports from China may reduce employment in the textile and Clothing industry, the effect is positive as far as total employment and output growth in South Africa are concerned. Appropriate Policy responses such as the provision for more training for the affected sector are recommended.

INTRODUCTION China’s resurgence as a major textile and clothing exporter has changed the landscape of world textile and clothing trade” Yongzheng Yang (2003:3). And this has brought mixed reaction: Some people see China as an opportunity, while others see it as a threat. For example some South African organizations (such as Congress of South African Trade Unions, the National Council of Trade Unions, the Federation of Unions of South Africa and SACTWU) have criticized China, saying it negatively affect the textile and clothing sectors. More particularly, thousands of jobs have been lost over the past ten years, 17 000 in the past 12 months and 800 in January 2005, while the volume of Chinese imports increased substantially (City Press, April 2005). In view of this problem, calls for renegotiation and restricting trade with China have enjoyed popular support by these trade unions in South Africa. Their call for trade restriction has been materialized in July 2006 when the trade and industry department signed the agreement with the Chinese government placing limitation on 31 product categories until the end of 2008 (Business Report, June 2006). Yet not much evidence has ever been reported on the true impact of Chinese import on employment in South Africa, not to mention the gains which are likely to accrue from trade with China. This paper will attempt to pursue these issues in trying to assess the dynamic of output, sectoral and total employment in response to trade variable shocks implied by the Chinese import in South Africa. The paper has four parts: section 2 provides a brief overview of the history of textile and clothing sectors in these two countries, namely, South Africa and China. Section 3 will consider reasons for huge influx of Chinese goods into South Africa. The recent development and trends in trade between SA and China are conducted in section 4 and 5 respectively. Finally in section 6 the empirical evidence will be considered of the impact of Chinese imports on economic growth and total employment, before the conclusion in section 7. HISTORY OF THE TEXTILE AND CLOTHING SECTORS IN SOUTH AFRICA AND CHINA Like most countries, South African textile and clothing industry were built up under a protectionist structure of tariffs and quantitative restrictions. These sectors received a lot of support for investment from the State-owned Industrial Development Corporation (IDC). Due to these restrictions production was almost completely determined by domestic demand. Exports contributed less than 7% of domestic production during the 1970s (Dunne and Edwards, 2006).

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As for China, as early as 1950s it was already a major textile and clothing exporter, however inward-looking policies (such as import substitution) by central planning resulted in a decline of China’s market share. In 1970, China’s share as a percentage of total textile export was less 14%, while its share as a percentage of total clothing export was below 5%. When trade reforms begun in the late 1970s China took advantage of it and this stimulated a sustained growth of both textile and clothing sectors. Between 1988 and 1994 these sectors were blossoming: textile market had peaked, having increased to 22% of total textile exports from developing countries. And clothing export experiencing a continuous increase (Yang, 2003:3) Chinese import in South Africa Statistics from the South African department of trade and industry (DTI) have shown that the total import from china has increase by close to 293% from September 2001 to January 2006.1 The reasons for such a huge influx of Chinese import in South Africa are attributed mainly to two factors: Chinese labour cost advantage compared to most countries in the world and the trade liberalization commitment taken by the South African government. China’s Labour cost advantages In her article entitled “Don’t Blame Trade Liberalization for Labor Market Chaos” Chang (2002) remarks that trade economists have long known that a country opening up to trade will specialize in certain sectors, putting resources into producing goods and services that are more efficient, and abandoning those that are relatively inefficient. This cast some light on why countries like China have become major clothing and textiles exporters – they have a comparative advantage in the production of these goods. Put it another way China produces these goods at a relatively lower cost than other countries (i.e. low wage economy) Shafaeddin (2002:4). Table 1 which compares hourly labour cost in the textile industry of China and other selected countries illustrate this point. Measured in term of US dollar, the 1998 figures shows that China, together with other countries in the Far East are among the low cost countries in the textile as far as the wages in the textile sector are concerned. This has given China the edge over other countries in Africa as well as in Europe and America as far as productivity in the textile industry is concerned. As it is clear from table 1, China has a comparative advantage over most countries. At the fourth column for example, it is noticed that the cost of labour per hour in China is 0,62 compared to say Italy where it is 15,81. Compared with South Africa, where the cost of labour per hour is high, at 2.05 in terms of US dollar, Chinese labour cost is almost three times less to that of South Africa. China comparative advantage is not only in term of average wages but also in terms of productivity. According to the World Bank estimates, China’s economy is adding more industrial production each year than any other economy in the world (World Bank, 1997). China’s industry grew at an average annual rate of 15% from 1980 to 1999 (Jefferson and Singh, 1999).

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Table 1: Hourly Textile Sector Wages for selected countries

Trade liberalization Since 1994, the new Government of National Unity (GNU) has undertaken an accelerated and extensive trade liberalization programme as agreed upon under the General Agreement on Tariffs and Trade (GATT) and put into operation by the World Trade Organisation (WTO). As far as the textile industry is concerned, the WTO’s agreement on textile and Clothing, make official in 1995, required that WTO members gradually reduce quotas on textile import over 10 years and bring their industries in line with the regulation decided upon under the GATT accord. As far as the compliance to this requirement is concerned, conflicting views have been raised on the matter; Bleaney and Holden (1996:2) argue that a striking feature of South Africa’s trade liberalization is that, until 1995, it did not involve any import liberalization. Furthermore, in 2001 Fedderke and Vase, cited in Edward’s paper (2005:754) came to the conclusion that the much-hyped liberalization of the South African economy in the 1990s has not been fully realized and most of South Africa’s output is protected by tariff in 1998 than in 1988. On the other side, Responding to this view Rangasamy and Harmse (2003) also cited in Edwards (ibid) came up with different conclusion when they argue that it is not always true that most of South Africa’s outputs have been subjected to increased levels of protection during the 1990s. According to them, this fact is not only incorrect but is also a misrepresentation of facts. So despite disagreements in terms of the extent of trade liberalization among the above-cited authors, table 2 shows the steps taken by the South African government in liberalizing the textile and Clothing sectors. The evidence from table 2 has shown that the nominal tariff has fallen considerably in South Africa in the textile industry in general.

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Table 2: South African tariff liberalization in textile industry in general

1994 1995 1996 1997 1998 1999 2000 2001 2002 Synthetic fibre 25 23 21 19 17 15 13 11 7.5 Yarn 32 30 28 26 24 22 20 18 15 Fabric 45 42 39 36 33 30 27 24 22 Clothing 90 84 78 72 66 60 54 47 40

Source: department of trade and industry, South Africa

RECENT TRADE DEVELOPMENT BETWEEN SOUTH AFRICA AND CHINA

South Africa is the largest trading partner of China in Africa. The trade volume between China and South Africa accounted for 19.4 % of the total trade volume between China and Africa. The bilateral trade volume in 2000 amounted to 2050 million US dollars, 19.1 % up on that of 1999. China's total investment in South Africa has reached some US$ 150 million (People’s Daily (December, 2001)). However, China’s relations with South Africa have been called into question by organizations such as SACTWU and COSATU. They complain about trade imbalances which are increasingly in China’s favour and large-scale dumping of cheap manufactured products are undercutting local industries. The South African clothing and textile sector has lost more than 100 000 jobs since 1995 as a result of flood of cheap Chinese textile imports. Further, as said above, they argue that the WTO required that its members gradually reduce quotas on textile imports. Under the agreement, all quotas were to be removed by 1 January 2005. But unlike other countries South Africa’s tariff liberalization programme, went far further and was significantly hastier than required by the GATT agreement and WTO regulations – so much so that it has given the domestic industry a dangerously short time to adjust.

After several rounds of talks China and SA, in July this year (2006), signed a three year agreement to place a limit on 31 product categories until the end of 2008. The aim of this agreement is to allow the local industry to modernize its factories and improve worker training on a scale that would possibly develop South Africa into a world-class producer. This new restriction has brought mixed reaction: The Congress of South African Trade Unions, the National Council of Trade Unions, the Federation of Unions of South Africa and SATWU take the view that the restriction will help in the way of rebuilding the industry and save thousands of jobs. While the South African retailers, Political parties such as the Democratic alliance (DA) and institutions such as the South African Reserve Bank (SARB) took the view that the new restrictions could impose painful costs on the South African economy. According to them the consequences of these policies may lead to upward pressure on prices and probably higher unemployment in the SA retail industry (Mail and Guardian 25 October 2006). Which of the above two views is correct? This is in fact the aim of this paper in analyzing the impact of Chinese import in total and sectoral employments as well as in the output growth in South Africa. In doing so, this paper will also try to understand what would the implications of the current trade restriction be in the South African economy in general.

CHINA-SOUTH AFRICA TRADE RELATION AND ECONOMIC THEORY

A number of international trade theories such as the ‘absolute advantage theory’ by Adam Smith, the ‘comparative advantage theory’ by David Ricardo and the ‘factor endowment theory’ by Hecksher and Ohlin, to quote only a few, all support the principle of free trade whereby nations would reap the most benefit of trade if they specialise in the product in which they have the greatest comparative advantage and engage in a free trade (without restrictions) with other countries (Kreinin, 2006). In the light of these theories, proponents of the free trade theory would question the decision of the South African government in restricting trade with China, a country that clearly has a comparative advantage in the textile sector. The restriction announced by the South African government, in the view of the proponent of free trade, will result in a welfare cost for the South African consumer. Nevertheless the free trade argument is not without challenges. One of the notable arguments against the free trade principle is the ‘infant industry’ argument.

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According to this argument it is unfair for well-established firms to compete head to head with new firms in less developed countries. This is because the former firms have enough in the way of experience; they have improved their efficiency in production (Pugel and Lindert, 2000:171). Over and above that they have acquired substantial information and knowledge regarding production process. In a nut shell the well established firms know the rules of the games.

Figure 1: Total Employment, Employment in the textile and clothing and retail sectors

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Source: Own construct

Firms in less developed countries on the other hand have very little in the way of experience – they lack all the necessary skills of its well established rival. Thus a form of protection, preferably tariff, is required in order to protect the potential industry in its infancy until it is able to compete internationally. Once the infant industry has grown to its maturity, then these tariffs could be removed. Although this is a powerful argument some economists such as Milton Friedman and Rose Friedman have expressed their scepticism, saying “the infant industry is a smoke screen. The so-called infants industry never grows up”. That is after imposing these tariffs it is difficult to

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remove them – they are likely to mount political pressure (Friedman and Friedman, 1997). Reaching similar conclusion Johnson (1965) takes the view that tariffs aimed at addressing domestic distortions may in fact have unintended consequences, it causes a relative welfare loss to consumers by increasing the domestic prices of the imported good above its world price.

Before attempting to assess the dynamic of output, sectoral and total employment in response to trade variable shocks implied by the Chinese import in South Africa as well as the consequences of the current trade restriction between South Africa and China this section presents the trends of employment in South Africa. Figure 1 presents the trend of employment in the South African textiles and clothing, retail and wholesale and total employment respectively. It is noticed from figure 1 that the total employment has picked up from the mid- 2002 and beginning of 2003. The trend in total employment coincided with the trend depicted by the employment in the retail and wholesale sectors in South Africa. It is worth mentioning that different views have been formulated for the sudden ‘leap’ in employment from the mid-2002 and beginning of 2003. While the government took pride of this fact, Casale et al (2004) argued that this soaring figure of employment has to do with the shift from the October household survey (OHS), as a survey for measuring employment from 1993 to 1999, to the introduction of the labour force survey (LFS) in 2000. In fact the two surveys used different population weights which result to figures that cannot reliably be compared. This study introduces a dummy variable to account for this structural break.

Figure 1 also shows a correlation between the total employment and employment in the retail and wholesale sector. The significant correlation between the total employment and employment in the retail and wholesale sector, noticed in 2002-2003 period, happens when the employment in the textile and clothing industry was dropping considerably in the same period. This should infer that employment in the retail sector has been able to more than offset for the loss of employment by the textile industry.

EMPIRICAL SPECIFICATION The empirical part of this study assesses what would the prospect of an increase in textile and clothing imports from China be on employment in the textile and clothing industry as well as in the total employment in South Africa. Thereafter the implications of the current trade restriction with China will then be assessed. The empirical analysis presented in this section makes use of the impulse responses functions (IRF) obtained from the Structural Vector Autoregressive (SVAR) model to analyse the dynamics of China’s imports shocks on employments and output growth in South Africa. The Structural Vector Autoregressive models The “traditional” VAR approach to modelling dynamic behaviours of economic variables was widely used and provided interesting insights in forecasting the dynamic of variables through its impulse response function analysis. Nevertheless since there are little economic inputs in a VAR modeling, it should not be surprising that there is a little economic content in the results provided from the IRF or the variance decomposition analysis. To emphasise the shortcoming of the VAR model, Cooley and LeRoy (1985), cited by LutKepohl et al (2004) argued that VAR have the status of “reduced form” models and therefore are only vehicles to summarise the dynamic properties of the data as they lack any reference to a specific economic structure. What eventually the SVAR model attempted to achieve is to deduce a structural form relationship from the reduced form VAR, and in this way a VAR can be viewed as the reduced form of a general dynamic structural model. To understand the link between a reduced form VAR and

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SVAR, let us consider equation (1) below, representing a dynamic structural model. The reparametrisation of equation (1) leads to reduced form relationship represented by equation (2).

ГYt = B(L)Yt + et (1) Yt = Г-1B(L)Yt + Г-1et or Yt = B*(L)Yt + ut (2)

We can infer from the two equations that: B*= Г-1B (3) and ut= Г-1et (4). Equation (4) is the core representation of the SVAR model whereby the reduced-form disturbance ut is related to the underlying structural shocks et. Furthermore because we are interested in our analysis on assessing the response of structural variables (Yt) to a unit structural innovation (et), equations (2) and (4) are reparameterized to obtain the followings: Yt = (I-B*(L))-1 ut or Yt = C(L)ut (5) where C(L)= (I-B*(L))-1. And in the form of structural innovation one obtains: Yt = C(L) Г-1et or Yt = C(L)*et (6) where C(L)*= C(L) Г-1. The parameters C(L)*= C(L) Г-1 contain the IRF of the structural variables to the structural innovations et and because the structural innovations have an economic interpretations, therefore the IRF obtained from this representation can be interpreted in a meaningful way. The IRF obtained form equation (5) is atheoretic and devoted of any economic meanings. Among the important challenges in a SVAR modelling is to recover the structural shocks (et) from the observed reduced form innovation (ut). This refers to the identification problem which is done by imposing some restrictions on equation (4). Two types of restrictions need to be done, first, to assure that structural innovations are uncorrelated and independents from each other, the orthogonality restriction is applied where the covariance’s of the structural innovations or shocks are restricted to zero. The second restriction is imposed on the parameter matrix Г, just as it is done in traditional dynamic simultaneous models using the order and rank conditions of identification with the only difference that in SVAR models the parameter matrix Г models the contemporaneous relationship between the reduced form and structural form innovations, whereas in the simultaneous equation models, the parameter matrix Г models relationship between variables in the model. As far as the number of restriction in the system is concerned, for a k-dimensional system, k(k-1)/2 restrictions are necessary for orthogonalising the shocks because this corresponds to the number of instantaneous covariance’s given such a dimension (Lutkepohl et al., 2004:162). It is essential to note that SVAR model deals only with modeling unexpected changes in the variables. This can be seen when subtracting the expected value of Yt, conditional on information in time t-1 from equation (1). In doing so, one also obtains the relationship, ut= Г-1et , as in relation (4). Data Analysis

The SVAR modelling applied in this study will attempt to answer empirically the study question by assessing:

• How an increase in textile import shocks affect total employment as well as employment in the textile and clothing industry in South Africa?

• Also, how the increase in textile import shocks affects output growth in South Africa? T o assess the impulse responses of trade policy shocks on output and employment this paper makes use of two separate vectors constitute each of three variables. Variables in the first vector are made of real GDP (lnY), total employment (lnemploto) and total real import from China (lnImport), all expressed in natural logarithm. In the second vector variables of analysis are real GDP (lnY), sectoral employment (lnemploy) and total import (lnImport). The data is quarterly and

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are from 1992 Q1 to 2004 Q4. The above variables are represented in figure 1 but import from China. Import from China is shown in appendix 1. These data, except import from China, are obtained from Statistics South Africa time series. Data for import from China are obtained from the South African department of trade statistics. The Augmented Dickey-Fuller (ADF) test of unit root of the above variables, as shown in appendix 1, demonstrates that all variables are integrated of order one. Furthermore within each vector the Johansen test of cointegration, still in appendix 1, shows that within each vector variables are not cointegrated. This conclusion supports the use of the SVAR technique to identify the shock in the system instead of the structural vector error correction (SVECM) model that is used to identify shocks in a cointegrated system. To assess the impulse of trade shocks we apply the SVAR analysis of the AB-model (Lutkephol, 2004). With this model the relationship between the structural shock and the reduced form residuals is given by:

A tµ = Bet (7).

This relates the reduced form disturbance tµ to the underlying structural shock et. Where the

matrix B is not necessarily an identity matrix, but diagonal coefficients are eventually estimated. With a system constituting of 3 variables (k=3) the condition for identification requires k(k-1)/2 restrictions on matrix A given matrix B is diagonal. Matrix A will therefore need 3 restrictions. To just-identify the shocks we impose an upper triangular restriction in matrix A supported by economic theory as explained below. The starting point of our analysis is a reduced form VAR (2). This lag length is chosen from the Akaike Information criteria and the condition for the stability of the VAR system. The proposed identification scheme in this study is as follow:

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001

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The vector on the right-hand side contains the structural shocks and the vector on the left hand side the reduced-form innovations. The system is just-identified and the economic interpretations presented in terms of contemporaneous relationship among the residuals of the VAR equations is that, firstly, import shocks are exogenous and depend only on its innovation. The reason behind this interpretation is that South Africa imports from China increases mostly because of the degree of China competitiveness rather than any South African internal reason. The second economic interpretation is that employment in textile industry is contemporaneously affected by the flow of imports from China. The third interpretation is that GDP in South Africa is dependent of the level of import from China as well as the level of employment in the textile industry (supply side of GDP). The second vector composed of import, total employment and GDP is interpreted in the same way as the above interpretation. Total employment is seen as the proxy for employment in the textile industry, that is that economic interpretation formulated for employment in the textile industry also stands for total employment. It is worthy noting that though the study used the Choleski decomposition with a triangular restriction in orthogonalising the reduced-form error there is nonetheless other types of restriction for the identification of structural shocks. Estimation results and impulse responses

Matrices A and B are estimated by maximum likelihood for each vector and results are presented in table 6 and table 7. As it is a tradition with SVAR modelling, interpretations of the effects of

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shocks are conducted with the impulse response functions rather than with the parameters estimates of equation (7) and represented in table 6 and table 7 below. Table 3: Structural parameter estimates of the matrices A and B for the first vector

Structural VAR Estimates Included observations: 46 after adjustments Structural VAR is just-identified

Model: Ae = Bu where E[uu']=I Restriction Type: short-run pattern matrix

Coefficient Std. Error z-Statistic Prob. a21 0.405021 0.301197 1.344703 0.1787

a31 -1.163819 0.120749 -9.638307 0.0000 a32 -0.010668 0.057981 -0.183990 0.8540 b11 0.185711 0.019362 9.591663 0.0000 b22 0.379373 0.039552 9.591663 0.0000 b33 0.149186 0.015554 9.591663 0.0000

Source: Own construct Table 4: Structural parameter estimation of the matrices A and B for the second vector

Structural VAR Estimates Included observations: 46 after adjustments Convergence achieved after 9 iterations Structural VAR is just-identified Model: Ae = Bu where E[uu']=I Restriction Type: short-run pattern matrix

Coefficient Std. Error z-Statistic Prob.

C(1) -0.126539 0.311298 -0.406490 0.6844 C(2) -1.151740 0.118685 -9.704199 0.0000 C(3) -0.067552 0.056113 -1.203859 0.2286 C(4) 0.188954 0.019700 9.591663 0.0000 C(5) 0.398943 0.041593 9.591663 0.0000 C(6) 0.151828 0.015829 9.591663 0.0000

Source: Own construct Figure 2: Responses to import shock, first vector.

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Response to Cholesky One S.D. Innovations ± 2 S.E.

*Note: blue lines show the IRF and the red line shows the 95% confidence band.

Source: Own construct

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Figure 3: Response to import shock, second vector

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*Note: blue lines show the IRF and the red line shows the 95% confidence band.

Source: Own construct The results of the impulse response functions are presented in figure 2 and figures 3. It is worthy noting that the estimation of the VAR system is obtained by taking account of the exogenous dummy variable that accounted for the structural change from the last quarter of the year 2002. The measure applied in this study is in term of the effect of a one-standard deviation shock of structural error on a corresponding variable. For example in figure 2, the first graph shows the response of the textile sector employment on one-standard deviation shock from import from china. The impulse response functions have been normalized to enable the IRF to be plotted on a single scale for an easy comparison. 95% confidence bands have been estimated for the IRF using the Monte Carlo bootstrapping approach. Use has been made of 2000 replications to calculate the standard error for the parameter and the IRF. Figure 2 shows that there is a negative relationship between import and employment from the textile industry. The relationship is statistically significant, especially from the second quarter. The effect of the shock of import from China is persistent at least for ten quarters. This shows the extent to which import flow from China has a negative effect on textile employment. But nevertheless the impact of China import on GDP is positive as shown in figure 2. Import shocks are persistent in the system as shown by the middle graph in figure 2. Figure 3 shows that import from China has a positive effect on total employment as well on GDP, and also confirms the positive relationship between imports from China and Output growth in South Africa. The results from Figure 2 and Figure 3, especially on the effect on GDP of import from China shocks, necessitate a further scrutiny. While the expenditure method for the calculation of GDP would assume that an increase in import would decrease GDP, Figure 4 and Figure 5 explain why it is not be the case as far as imports from China are concerned. Figure 4, for example shows that the negative effect of imports from China on GDP has been compensated by more than proportional increase in the final consumption expenditure by household on textile and clothing items. Retailers and wholesalers importing textile materials from China benefit considerably as reported by an incessant increase in the gross value added by the sector (Figure 5). The increase in the gross value added has been supported by the constant increase in the final consumption expenditure by households of textile items.

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Figure 4: Final consumption expenditure by household: clothing and footwear

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Source: Own construct From these empirical findings, we raise some concerns on the current trade restrictions. Our first concern is about the capacity of the textile industry in South Africa to compensate for the decrease in import from China. Secondly, we believe that it is doubtful that the textile industry will be able to offset for the loss of employment that might result from the wholesale and retail sector. The high operational cost that the retail sector will suffer from buying stocks from a more expensive source will necessary lead to loss of employment in the sector. Thirdly we are of the opinion that this policy of trade restriction does not make economic sense. If it were an “infant industry” protection, the restriction could be for textile imports from all countries. With such a limited restriction, retailer can divert their trade from other sources such as Malaysia, India and others. With this the aim of this policy, namely buying from South Africa, will not reach its goal. Lastly imposing retailers to buy textile from South Africa, a high cost source, will lead retailers to pass this cost to consumers. In doing so, the consumer surplus will decrease, the level of inflation will increase and this will comprise the anchor of monetary policy in South Africa, namely containing inflation within a certain interval. Fiscal authority will also not be spared, as its aim of poverty reduction in the face of high inflation will be compromised. In the light of our empirical finding, we may conclude that import from China has done more good than wrong in the South African economy. The only concern with employment in the textile industry could be solved with more training that would make the sector competitive. Also to be able to compete fro export we suggest that the textile industry be given tax incentive such as privilege entails by the export processing zone.

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CONCLUSION

This paper attempted to assess the prospects of the dynamics of China’s import shocks on employments and output growth in South Africa, as well as the implications of the current decision by the government to restrict textile imports from China. Using the SVAR analysis, this study shows that an increase in import from China has positive effects on total employment as well as GDP. But the effect is negative as far as the employment in the textile sector is concerned. The idea that the government would like to revive the textile industry by restricting trade with China may not succeed for many reasons including the current high cost of production incurred by the textile industry that can impact negatively on the price level in South Africa as well as on the monetary policy instance in the republic, the lack of capacity by the textile industry to compensate for the decrease in import from China as well as the decrease in employment by the retail sector. We also raise a concern that such a limited restriction can lead to “trade diversion” whereby retailers can source their stocks from other countries instead of buying from South Africa..

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REFERENCES Bleaney, M. and Holden, M. (1996) “The trade liberalization in Sub-Saharan Africa; case study of South Africa”, the centre for the study of African economies, working paper series (42). Casale, D., Muller,C. and Posel, D. (2004) “Two million net jobs’: A reconsideration of the rise in employment in South Africa, 1995-2003”, South African Journal of Economics, 72(5), 978-1002 Chang, H. K. (2002) “Don’t Blame Trade Liberalization for Labor Market Chaos”, Stanford GSB. Dunne, P. and Edwards, L. (2006) “Trade and Poverty in South Africa: Exploring the trade-labour linkage”, Trade and Poverty Project, Southern African Labour and Development Research Unit, university of Cape Town Edwards, L. (2005). “Has South Africa liberalized its trade?”, South African Journal of Economics, 73 (4): 754. Fedderke, J. and Vase, P. (2001) “The nature of South Africa’s trade patterns by economic sector, and the extent of trade liberalization during the course of the 1990’s”, South African Journal of Economics, vol. 69(3):436-473.

Friedman, M and R. Friedman (1997), “The case for Free Trade”, Hoover Digest: Research and Opinion on Public Policy.

Jefferson, G.H. and Singh, I. (1999) “Enterprise Reform in China: Ownership, Transition and Performance”, New York: Oxford University Press.

Johnson,H.G (1965), “Optimal Trade Intervention in the presence of Domestic Distortions” in Trade, Growth, and Balance of Payments. Essays in Honor of Gottfried Haberler. Chicago: Rand Mcnally.

Lutkepohl, H; and Kratzig, M. (2004) “Applied time series Econometrics. Cambridge”, Cambridge University Press: Cambridge. Lynn Salinger, B. (2003) “Qualitative Dimensions to Competitiveness Assessments: Lessons from Textile and Garment industry Assessment in South Africa, Vietnam, and Morocco”, Concepts and Measurements of International Competitiveness Panel, International Industrial Organization Conference, April 4-5, 2003, Boston, MA. Rangasamy, L. and Harmse, C. (2003) “Revisiting the extent of trade liberalization in the 1990’s.”, South African Journal of Economics, vol. 70 (4): 705-728. Shafaeddin, S.M. (2002) “The impact of China’s accession to WTO on the exports of developing countries”, United Nations conference on trade and development, no. (160). World Bank (1997) “World Development Report 1997: The state in a changing world, New York: Oxford University Press. Xinhua , V. (2006) “China willing to strengthen friendly exchanges with South Africa”, people’s daily, November 2006 Yang, Y.(2003) “China’s textile and clothing exports: changing international comparative advantage and its policy implications”, Asia Pacific School of Economics and Management working papers.

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GUIDELINES FOR AUTHORS

THE TITLE OF THE PAPER

Name and academic title of the first author Institution/Affiliation

Postal Address Phone: Fax: E-mail address:

Name and academic title of the second author

Institution/Affiliation Postal Address

Phone: Fax: E-mail address: THE FIRST-LEVEL HEADING

The sub-heading Other sub-heading The text is to be typed in Times New Roman, font size 12pt, regular style, alignment justified, single spaced, with one-line space between paragraphs. ANOTHER FIRST-LEVEL HEADING Another sub-heading Footnotes should be quoted with continuous numbering at the bottom of the page as they appear in the text.2 References should be written in alphabetical order, font size 12pt, regular style, justified, single spaced, with one-line space between paragraphs. BIBLIOGRAPHY: <Here is the reference for a Book> Krugman, P. (1997): The Age of Diminished Expectations: U.S. Economic Policy in 1990's, Third

Edition, Cambridge: MIT Press

<Here is the reference for an Edited Book:> Shocker, A.D. (2002): 'Determining the Structure of Product-Markets: Practices, Issues, and

Suggestions', in B.A. Weitz and R. Wensley, ed.: Handbook of Marketing, London: Sage

Publications, pp. 106-125

<Here is the reference for a Book of Proceedings:> Pöschl, J. (2003): ‘Re-starting the Engines of Growth in Transition’, in: Second International Conference ICES2003 'From Transition to Development: Globalisation and Political Economy of

2 <This is an example of how to format footnotes. Font size 10pt, regular style, justified>

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Development in Transition Economies', Proceedings, Faculty of Economics University of Sarajevo, Sarajevo, October 9-11, 2003, pp. 133-151 <Here is the reference for a Journal Article:> Porter, M.E. and Kramer, M.R. (2002): ‘The Competitive Advantage of Corporate Philanthropy’, Harvard Business Review (December 2002): 5-16 <Here is the reference for a Working Paper:> Kandogan, Y. (2003): ‘Intra-industry Trade of Transition Countries: Trends and Determinants’, The William Davidson Institute, University of Michigan Business School, Working Paper, No. 566, May 2003 <Here is the reference for an Internet Resource:> Kim, Y. (2001): ‘Borrowing Constraints and Technology Diffusion: Implications of Intra-industry Trade’, USC Center for Law, Economics and Organization, http://papers.ssrn.com/abstract_id=340760 [Accessed 15.09.2004]