Chapter 4 examines the requirement in Article XX GATT 1994 and Article XIV GATS (the General Exceptions) as well as Article 2.2 of the TBT Agreement that a Member’s measure must contribute to a certain policy objective. The chapter argues that this requirement is essentially a causal requirement, and raises some jurisprudence that has argued the same. The chapter also traces through parts of the jurisprudence that would seem to support a non-attribution analysis of some kind being used in this context. The chapter concludes by proposing that the Tripartite Non-attribution/Causal Link Analysis might be applied to make a determination of causation for the purposes of this requirement under the General Exceptions and Article 2.2 of the TBT Agreement. The chapter concludes by setting out in detail how the Tripartite Non-attribution/Causal Link Analysis might be applied to make causal determinations for the purposes of the General Exceptions and Article 2.2 of the TBT Agreement.

Chapter 1 introduces the distinction between cause-in-fact and cause-in-law and defines both. Under ’cause-in-fact’, this chapter introduces different approaches to determining causation based on non-quantitative approaches (e.g., sine qua non and weak necessity/strong sufficiency tests) vis-à-vis quantitative approaches (e.g., the Statistical Significance Test and Linear Regression Analysis). The chapter also discusses the benefits and drawbacks of each of these tests. Chapter 1 also introduces the concept of ’cause-in-law’ theories, but explains why they are less relevant for the purposes of the book. To this end, it argues that the quantitative methods that are inherent in the use of the Tripartite Non-attribution/Causal Link Analysis serve to delimit responsibility for injury.

Chapter 2 lays out the causal questions inherent in the legal implementation of safeguard measures, antidumping measures and countervailing duties (collectively, ’trade remedies’). It notes that the legal instruments require that domestic competent authorities engage in a process of determining both causation (i.e., drawing a causal link) and non-attribution (i.e., disaggregating non-causal factors) before implementing trade remedies. The chapter then turns to examine how these causal questions have been interpreted in the jurisprudence. To this end, it notes that a multi-factorial approach over a single-factor approach has been preferred in the jurisprudence. The chapter turns to discuss how domestic competent authorities have sought to conduct causation and non-attribution determinations. The chapter concludes by discussing how the Tripartite Non-attribution/Causal Link Analysis, based on econometric methods, offers an alternative approach to satisfying the legal requirements of determining causation for the purposes of implementing trade remedies.

The introduction sets out the different types of causal relationships that the law of the World Trade Organization (WTO) raises. It also defines both causation and non-attribution in the law of the WTO and discusses the fact that both are required in this legal context. The introduction foreshadows the contents of each of the five substantive chapters that follow. It explains the concept of the Tripartite Non-attribution/Causal Link Approach and discusses the advantages and disadvantages of taking an econometric approach to analysing causation. The introduction also explicates those causal questions in WTO law that fall outside the scope of the book as it explains why they do not fit with the concept of the Tripartite Non-attribution/Causal Link Approach. The introduction also explores some of the limitations of the book as well as containing a brief discussion of the sources and methodology of the book.

Not only has this study confronted the question of determining causation in respect of certain provisions of WTO law, but also how to precede the determination of a causal link with an effective non-attribution analysis. In other words, the particular type of causal analysis that has been at the heart of this book has had a dual character – namely, the question of not only how to draw a causal link between two factors, but also the question of how to exclude causation between an effect and other known factors. In this sense, the causal analysis with which this book has been concerned has both positive and negative features to it.

Social aggregation theory deals with the problem of amalgamation of the values assigned by different individuals to alternative social or economic states in a society into values for the entire society. A social state provides a description ofmaterials that are related to thewell-being of a population in different ways. One fundamental question that arises at the outset is how an individual can rank two alternative states in a well-defined manner. The problem of social aggregation theory can then be regarded as one of clubbing individual rankings into a social ranking in a meaningful way.

Chapter 1 presents an introductory outline of the materials analyzed in the remaining chapters. Chapter 2 of the monograph formally defines individual and social rankings of alternative states of affairs. Chapter 3 provides a rigorous discussion on May’s remarkable theorem on “social choice functions,” which represents group or collective decision rules, limited to two alternatives. In Chapter 4 we analyze Arrow’s social welfare function, a mapping from the set of all possible profiles of individual orderings of social states to the set of all possible orderings. We discuss this with some elaboration in view of the fact that Arrow’s model forms the basis of almost the entire social choice theory. Chapter 5 investigates to what extent the “dictatorship” result can be avoided when some of Arrow’s axioms are relaxed. In Arrow’s framework, when individual preferences are represented by utility functions, utilities are of the ordinal and non-comparable types. Arrow’s theorem with utility functions constitutes a part of Chapter 6 of the book. We use geometric technique to prove this fundamental result. In the recent past, the non-comparability assumption has been relaxed to partial and full comparability assumptions. A discussion on alternative notions of measurability and comparability of utility functions is also presented in Chapter 6. Simple numerical examples have been provided to illustrate the ideas. Possibilities of social welfare functions are expanded as a consequence of interpersonal comparability. Proofs of most theorems in the literature are sophisticated mathematically, which may not be easygoing for non-specialist readers. In view of this, we use simple graphical proofs for many such results.

INTRODUCTION

In this chapter, we explore the extent to which we can escape the dictatorship result if we relax some of Arrow’s axioms. If we relax independence of irrelevant alternatives, then we get the Borda Count which is a well-defined social welfare function satisfying unrestricted domain and weak Pareto. This we have already discussed is Example 4.5 of Chapter 4. In Section 5.2, we relax weak Pareto and replace it by a weaker axiom of non-imposition and then we get the result due to Wilson (1972) that stipulates that a social welfare function satisfying unrestricted domain, independence of irrelevant alternatives, and non-imposition axioms must be null or dictatorial or inverse-dictatorial, given that the number of alternatives is not less than three. Both inverse-dictatorial and null social welfare functions are quite uninteresting. Inverse-dictatorship requires that there exists an agent i whose strict preference over every pair of alternatives is reversed for the society under all profiles in the domain. Like inverse-dictatorial social welfare function, the null social welfare function is also uninteresting since the society is always indifferent across all alternatives for all possible profiles in the domain.

In Section 5.3, we relax transitivity of social preferences and then either we end up in oligarchy or we end up violating the no veto power. Specifically, the oligarchy result, due to Weymark (1984), specifies that a social quasi-ordering that satisfies unrestricted domain, weak Pareto, and independence of irrelevant alternatives must be oligarchic, given that the number of alternatives is not less than three and the set of individuals is finite. In this context, we also derive the Liberal Paradox due to Sen (1970b) that shows that there is no social weak quasi-ordering that satisfies unrestricted domain, weak Pareto, and a very weak form of liberalism. Finally, in Section 5.4, we relax the axiom of unrestricted domain and assume single-peaked preferences and then we can escape Arrow’s dictatorship conclusion. A set of individuals is said to have single-peaked preferences over a set of possible alternatives if the alternatives can be ordered along a line such that the following two conditions hold: (i) each agent has a best (or most preferred) alternative in the set, and (ii) for each agent, alternatives that are further from his or her best alternative are preferred less.

MOTIVATIONS

Often income as the sole dimension of the well-being of a population does not give us an appropriate picture of the living condition of the population since there are non-income dimensions that affect human welfare, for example, habitation, longevity, availability of opportunities from the point of view of contentment, and so on. So, by concentrating on income only, it is implicitly assumed that persons enjoying the same income are considered equally well off regardless of their attainments in the non-income dimensions. However, a non-monetary dimension of well-being need not be perfectly correlated with income. For instance, an income-rich person may not be able to improve the level of sub-optimal supply of a local public good, say, the irregularities of a TV signal that can be received within a specified distance of the signaling station. Thus, apart from the distribution of income, a policy maker might be concerned with the distributions of various non-income goods or dimensions. Examples of such non-income dimensions are health, literacy, housing, and environment. Therefore, to get a complete picture of human well-being it is quite sensible to supplement income with non-income dimensions that influence the contentment of the population. In other words the well-being of a population is a multidimensional phenomenon. This is, in fact, a concretization of our assumption made in the earlier chapters that an individual’s (and hence society’s) utility depends on several states of nature.

In the words of Stiglitz, Sen, and Fitoussi (2009, 14):

Intrinsic to the notion of the capability-functioning approach to the evaluation of human well-being is multidimensionality, where functionings refer to the various things such as income, literacy, housing, life expectancy, communing with others, and so on about which a person cares.

INTRODUCTION

In this chapter, we introduce some basic concepts that will be used throughout this book. In Section 2.2, we start by defining the “at least as good as” relation ≿ that describes the preferences of the individuals over the set of alternatives that they face. We specify certain properties associated with these preference relations. In Section 2.3, we introduce the notion of maximal sets (or choice sets) and link it with the properties of ≿. Finally, in Section 2.4, we discuss social orderings, that is, given a set of agents in a society along with their preferences, how do we aggregate them into social preferences. Specifically, in Section 2.4, we discuss some well-known social aggregation rules like plurality rule, Borda count, anti-plurality rule, oligarchy, and pairwise majority rule.

RELATIONS

Let A = ﹛x,y, z,w …﹜ be the set of alternative states of affairs (alternatives, for short). A relation ≿ on A is a subset of A × A. We shall write x ≿ y if (x, y) ∊ ≿. We say that x and y are unordered by ≿ if neither x ≿ y nor y ≿ x. They are ordered by ≿ if they are not unordered, that is, either x ≿ y holds or y ≿ x holds. We will call ≿ as the “at least as good as” relation defined on the set of alternatives A. Given ≿, let ≻ and ∼ be the asymmetric and the symmetric parts of ≿. That is, x ≻ y if and only if x ≿ y and ￢(y ≿x), where ￢ (y ≿ x) means that y ≿ x is not true. Moreover, x ∼ y if and only if x ≿ y and y ≿ x. We will also refer to ∼ as the strict preference part of ≿ and we will also refer to ∽ as the indifference part of ≿. In words, for any person (society) with the preference relation ≿, between any two alternatives x and y, x ≻ y means that the person (society) strictly prefers x to y and x ∼ y means that the person (society) is indifferent between x and y.

INTRODUCTION

Following the Gibbard–Satterthwaite theorem, several relaxations of the unrestricted domain assumption have been investigated. We have already discussed single-peaked preferences in the previous chapter, which is a relaxation of the unrestricted domain assumption. A second relaxation of the unrestricted domain assumption amounts to assuming that side-payments are allowed among agents (implying the cardinality of their utility functions). Specifically, in this second kind of relaxation, it is assumed that agents have quasi-linear preferences that are represented with quasi-linear utility functions. This assumption of quasi-linearity creates several strategyproof mechanisms. The economic implications of these strategyproof mechanisms are numerous and have been systematically investigated in the vast literature about Vickrey–Clarke–Groves (or VCG) mechanisms (see Vickrey 1961; Clarke 1971; and Groves 1973). The VCGmechanisms, in its most general form, was specified by Groves (1973), though its special cases were identified earlier—first by Vickrey (1961), who specified the second price auction in the context of auction theory, and then by Clarke (1971), who provided the pivotal mechanism for the non-excludible pure public goods problem. There is another class of mechanisms, known as Roberts’ mechanisms for affine maximizers, that generalizes the VCG mechanisms (Roberts 1980). In this chapter, we discuss these strategyproof mechanisms for quasi-linear domains. The problem of designing strategyproof mechanisms is also referred to as dominant strategy mechanism design problem under incomplete information.

In Section 11.2, we introduce a non-excludible pure public goods problem and introduce the VCG mechanisms and show that this is the unique class of mechanisms that satisfies outcome efficiency (that maximizes the sum of utilities of all the agents from the public decision) and strategyproofness (also called dominant strategy incentive compatibility). We then argue that for the pure public goods problems, the VCG mechanisms fail to satisfy Pareto optimality. We then discuss some nice properties of the pivotal mechanism, which is a specific mechanism in the class of VCG mechanisms that was first identified by Clarke (1971). In Section 11.3, we introduce a single indivisible private good allocation problem and show that the pivotal mechanism of Clarke (1971) is identical to the second price Vickrey auction (Vickrey 1961).

INTRODUCTION

In the earlier chapters, it has been assumed that social states are characterized by complete certainty in the sense that they are fully observable by the individuals under consideration. Consequently, each state may be regarded as a certain prospect. An individual can therefore order alternative social states using his preferences without any ambiguity. Thus, the decisions taken by the individuals are taken in an environment of certainty. But when states are affected by uncertainty, the decision criterion may be of a different type. To understand this, consider two farmers for whom the extent of rainfall has a very high impact on their crop outputs from their respective lands. Rainfall conditions may be subdivided into the following categories: (i) flood, (ii) optimum, (iii) hardly sufficient, (iv) less than hardly sufficient, and (v) drought. Each of these categories represents a circumstance of nature. In such a situation, each farmermaximizes his expected (von Neumann–Morgenstern) utility function. A natural question that arises in this context is the following: howare the individual utilities aggregated to arrive at a social utility? John C.Harsanyi (1955) made an excellent recommendation along this line. Harsanyi assumed at that outset that individual and social preferences fulfill the expected utility axioms and these preferences are portrayed by von Neumann–Morgenstern utility functions. The set of alternatives on which individual and social preferences are defined is constituted by the lotteries bred from a finite set of well-defined basic prospects. By including a Pareto principle within the framework, Harsanyi demonstrated that social utility function can be expressed as an affine combination of individual utility functions. In other words, given that the origin of the social utility function has been appropriately normalized, social utility comes to be a weighted sum of individual utilities. This relationship is referred to as theHarsanyi social aggregation theorem (Weymark 1991, 1994).

In Harsanyi’s social aggregation theorem, individual and social preferences are defined on the set of lotteries generated from a finite set of basic prospects. These preferences are expected to satisfy expected utility hypothesis and are represented by von Neumann–Morgenstern utility functions. The only link between the individual and social preferences is the requirement that the society should be indifferent between a pair of lotteries when all individuals are indifferent between them.