Fundamental theorems of welfare economics

Last updated

There are two fundamental theorems of welfare economics . The first states that in economic equilibrium, a set of complete markets, with complete information, and in perfect competition, will be Pareto optimal (in the sense that no further exchange would make one person better off without making another worse off). The requirements for perfect competition are these: [1]

Contents

  1. There are no externalities and each actor has perfect information.
  2. Firms and consumers take prices as given (no economic actor or group of actors has market power).

The theorem is sometimes seen as an analytical confirmation of Adam Smith's "invisible hand" principle, namely that competitive markets ensure an efficient allocation of resources. However, there is no guarantee that the Pareto optimal market outcome is equitative, as there are many possible Pareto efficient allocations of resources differing in their desirability (e.g. one person may own everything and everyone else nothing). [2]

The second theorem states that any Pareto optimum can be supported as a competitive equilibrium for some initial set of endowments. The implication is that any desired Pareto optimal outcome can be supported; Pareto efficiency can be achieved with any redistribution of initial wealth. However, attempts to correct the distribution may introduce distortions, and so full optimality may not be attainable with redistribution. [3]

The theorems can be visualized graphically for a simple pure exchange economy by means of the Edgeworth box diagram.

History of the fundamental theorems

Adam Smith (1776)

In a discussion of import tariffs Adam Smith wrote that:

Every individual necessarily labours to render the annual revenue of the society as great as he can... He is in this, as in many other ways, led by an invisible hand to promote an end which was no part of his intention... By pursuing his own interest he frequently promotes that of the society more effectually than when he really intends to promote it. [4]

Note that Smith's ideas were not directed towards welfare economics specifically, as this field of economics had not been created at the time. However, his arguments have been credited towards the creation of the branch as well as the fundamental theories of welfare economics. [5]

Léon Walras (1870)

Walras wrote that 'exchange under free competition is an operation by which all parties obtain the maximum satisfaction subject to buying and selling at a uniform price'. [6]

F. Y. Edgeworth (1881)

Edgeworth took a step towards the first fundamental theorem in his 'Mathematical Psychics', looking at a pure exchange economy with no production. He included imperfect competition in his analysis. [7] His definition of equilibrium is almost the same as Pareto's later definition of optimality: it is a point such that...

in whatever direction we take an infinitely small step, P and Π [the utilities of buyer and seller] do not increase together, but that, while one increases, the other decreases. [8]

Instead of concluding that equilibrium was Pareto optimal, Edgeworth concluded that the equilibrium maximizes the sum of utilities of the parties, which is a special case of Pareto efficiency:

It seems to follow on general dynamical principles applied to this special case that equilibrium is attained when the total pleasure-energy of the contractors is a maximum relative, or subject, to conditions... [9]

Vilfredo Pareto (1906/9)

Pareto stated the first fundamental theorem in his Manuale (1906) and with more rigour in its French revision (Manuel, 1909). [10] He was the first to claim optimality under his own criterion or to support the claim by convincing arguments. [ citation needed ]

He defines equilibrium more abstractly than Edgeworth as a state which would maintain itself indefinitely in the absence of external pressures [11] and shows that in an exchange economy it is the point at which a common tangent to the parties' indifference curves passes through the endowment. [12]

His definition of optimality is given in Chap. VI:

We will say that the members of a collectivity enjoy a maximum of ophelimity [i.e. of utility] at a certain position when it is impossible to move a small step away such that the ophelimity enjoyed by each individual in the collectivity increases, or such that it diminishes. [He has previously defined an increase in individual ophelimity as a move onto a higher indifference curve.] That is to say that any small step is bound to increase the ophelimity of some individuals while diminishing that of others. [13]

The following paragraph gives us a theorem:

For phenomena of type I [i.e. perfect competition], when equilibrium takes place at a point of tangency of indifference curves, the members of the collectivity enjoy a maximum of ophelimity.

He adds that 'a rigorous proof cannot be given without the help of mathematics' and refers to his Appendix. [14]

Wicksell, referring to his definition of optimality, commented:

With such a definition it is almost self-evident that this so-called maximum obtains under free competition, because if, after an exchange is effected, it were possible by means of a further series of direct or indirect exchanges to produce an additional satisfaction of needs for the participators, then to that extent such a continued exchange would doubtless have taken place, and the original position could not be one of final equilibrium. [15]

Pareto didn't find it so straightforward. He gives a diagrammatic argument in his text, applying solely to exchange, [16] and a 32-page mathematical argument in the Appendix [17] which Samuelson found 'not easy to follow'. [18] Pareto was hampered by not having a concept of the production–possibility frontier, whose development was due partly to his collaborator Enrico Barone. [19] His own 'indifference curves for obstacles' seem to have been a false path.

Shortly after stating the first fundamental theorem, Pareto asks a question about distribution:

Consider a collectivist society which seeks to maximise the ophelimity of its members. The problem divides into two parts. Firstly we have a problem of distribution: how should the goods within a society be shared between its members? And secondly, how should production be organised so that, when goods are so distributed, the members of society obtain the maximum ophelimity?

His answer is an informal precursor of the second theorem:

Having distributed goods according to the answer to the first problem, the state should allow the members of the collectivity to operate a second distribution, or operate it itself, in either case making sure that it is performed in conformity with the workings of free competition. [20]

Enrico Barone (1908)

Barone, an associate of Pareto, proved an optimality property of perfect competition, [21] namely that – assuming exogenous prices – it maximises the monetary value of the return from productive activity, this being the sum of the values of leisure, savings, and goods for consumption, all taken in the desired proportions. [22] He makes no argument that the prices chosen by the market are themselves optimal.

His paper wasn't translated into English until 1935. It received an approving summary from Samuelson [23] but seems not to have influenced the development of the welfare theorems as they now stand.

Abba Lerner (1934)

In 1934 Lerner restated Edgeworth's condition for exchange that indifference curves should meet as tangents, presenting it as an optimality property. He stated a similar condition for production, namely that the production–possibility frontier (PPF, to which he gave the alternative name of 'productive indifference curve') should be tangential with an indifference curve for the community. He was one of the originators of the PPF, having used it in a paper on international trade in 1932. [24] He shows that the two arguments can be presented in the same terms, since the PPF plays the same role as the mirror-image indifference curve in an Edgeworth box. He also mentions that there's no need for the curves to be differentiable, since the same result obtains if they touch at pointed corners.

His definition of optimality was equivalent to Pareto's:

If... it is possible to move one individual into a preferred position without moving another individual into a worse position... we may say that the relative optimum is not reached...

The optimality condition for production is equivalent to the pair of requirements that (i) price should equal marginal cost and (ii) output should be maximised subject to (i). Lerner thus reduces optimality to tangency for both production and exchange, but does not say why the implied point on the PPF should be the equilibrium condition for a free market. Perhaps he considered it already sufficiently well established. [25]

Lerner ascribes to his LSE colleague Victor Edelberg the credit for suggesting the use of indifference curves. Samuelson surmised that Lerner obtained his results independently of Pareto's work. [26]

Harold Hotelling (1938)

Hotelling put forward a new argument to show that 'sales at marginal costs are a condition of maximum general welfare' (under Pareto's definition). He accepted that this condition was satisfied by perfect competition, but argued in consequence that perfect competition could not be optimal since some beneficial projects would be unable to recoup their fixed costs by charging at this rate (for example, in a natural monopoly). [27]

Oscar Lange (1942)

Lange's paper 'The Foundations of Welfare Economics' is the source of the now-traditional pairing of two theorems, one governing markets, the other distribution. He justified the Pareto definition of optimality for the first theorem by reference to Lionel Robbins's rejection of interpersonal utility comparisons, [28] and suggested various ways to reintroduce interpersonal comparisons for the second theorem such as the adjudications of a democratically elected Congress. Lange believed that such a congress could act in a similar way to a capitalist: through setting price vectors, it could achieve any optimal production plan to have achieve efficiency and social equality. [29]

His reasoning is a mathematical translation (into Lagrange multipliers) of Lerner's graphical argument. The second theorem does not take its familiar form in his hands; rather he simply shows that the optimisation conditions for a genuine social utility function are similar to those for Pareto optimality.

Abram Bergson and Paul Samuelson (1947)

Samuelson (crediting Abram Bergson for the substance of his ideas) brought Lange's second welfare theorem to approximately its modern form. [30] He follows Lange in deriving a set of equations which are necessary for Pareto optimality, and then considers what additional constraints arise if the economy is required to satisfy a genuine social welfare function, finding a further set of equations from which it follows 'that all of the action necessary to achieve a given ethical desideratum may take the form of lump sum taxes or bounties'. [31]

Kenneth Arrow and Gérard Debreu (separately, 1951)

Arrow's and Debreu's two papers [32] (written independently and published almost simultaneously) sought to improve on the rigour of Lange's first theorem. Their accounts refer to (short-run) production as well as exchange, expressing the conditions for both through linear functions.

Equilibrium for production is expressed by the constraint that the value of a manufacturer's net output, i.e. the dot product of the production vector with the price vector, should be maximised over the manufacturer's production set. This is interpreted as profit maximisation.

Equilibrium for exchange is interpreted as meaning that the individual's utility should be maximised over the positions obtainable from the endowment through exchange, these being the positions whose value is no greater than the value of his or her endowment, where the value of an allocation is its dot product with the price vector.

Arrow motivated his paper by reference to the need to extend proofs to cover equilibria at the edge of the space, and Debreu by the possibility of indifference curves being non-differentiable. Modern texts follow their style of proof.

Greenwald-Stiglitz theorem

In their 1986 paper, "Externalities in Economies with Imperfect Information and Incomplete Markets", Bruce Greenwald and Joseph Stiglitz showed that the fundamental welfare theorems do not hold if there are incomplete markets or imperfect information. [33] The paper establishes that a competitive equilibrium of an economy with asymmetric information is generically not even constrained Pareto efficient. A government facing the same information constraints as the private individuals in the economy can nevertheless find Pareto-improving policy interventions. [34]

Greenwald and Stiglitz noted several relevant situations, including how moral hazard may render a situation inefficient (e.g. an alcohol tax may be pareto improving as it reduces automobile accidents). [35]

Assumptions for the fundamental theorems

In principle, there are two commonly found versions of the fundamental theorems, one relating to an exchange economy in which endowments are exogenously given, and one relating to an economy in which production occurs. The production economy is more general and entails additional assumptions. The assumptions are all based on the standard graduate microeconomics textbook. [36]

The fundamental theorems do not generally ensure existence, nor uniqueness of the equilibria.

First Fundamental Theorem

Second Fundamental Theorem

The second fundamental theorem has more demanding conditions.

Common failures of the assumptions

The following provides a non-exhaustive list of common failures of the assumptions underlying the fundamental theorems.

Another instance in which the welfare theorems fail to hold is in the canonical Overlapping generations model (OLG). A further assumption that is implicit in the statement of the theorem is that the value of total endowments in the economy (some of which might be transformed into other goods via production) is finite. [37] In the OLG model, the finiteness of endowments fails, giving rise to similar problems as described by Hilbert's paradox of the Grand Hotel.

Whether the assumptions underlying the fundamental theorems are an adequate description of markets is at least partially an empirical question and may differ case by case.

Proof of the first fundamental theorem

The first fundamental theorem holds under general conditions. [38] A formal statement is as follows: If preferences are locally nonsatiated, and if is a price equilibrium with transfers, then the allocation is Pareto optimal. An equilibrium in this sense either relates to an exchange economy only or presupposes that firms are allocatively and productively efficient, which can be shown to follow from perfectly competitive factor and production markets. [38]

Given a set of types of goods we work in the real vector space over , and use boldface for vector valued variables. For instance, if then would be a three dimensional vector space and the vector would represent the bundle of goods containing 1 unit of butter, 2 units of cookies and 3 units of milk.

Suppose that consumer i has wealth such that where is the aggregate endowment of goods (i.e. the sum of all consumer and producer endowments) and is the production of firm j.

Preference maximization (from the definition of price equilibrium with transfers) implies (using to denote the preference relation for consumer i):

if then

In other words, if a bundle of goods is strictly preferred to it must be unaffordable at price . Local nonsatiation additionally implies:

if then

To see why, imagine that but . Then by local nonsatiation we could find arbitrarily close to (and so still affordable) but which is strictly preferred to . But is the result of preference maximization, so this is a contradiction.

An allocation is a pair where and , i.e. is the 'matrix' (allowing potentially infinite rows/columns) whose ith column is the bundle of goods allocated to consumer i and is the 'matrix' whose jth column is the production of firm j. We restrict our attention to feasible allocations which are those allocations in which no consumer sells or producer consumes goods which they lack, i.e.,for every good and every consumer that consumers initial endowment plus their net demand must be positive similarly for producers.

Now consider an allocation that Pareto dominates . This means that for all i and for some i. By the above, we know for all i and for some i. Summing, we find:

.

Because is profit maximizing, we know , so . But goods must be conserved so . Hence, is not feasible. Since all Pareto-dominating allocations are not feasible, must itself be Pareto optimal. [38]

Note that while the fact that is profit maximizing is simply assumed in the statement of the theorem the result is only useful/interesting to the extent such a profit maximizing allocation of production is possible. Fortunately, for any restriction of the production allocation and price to a closed subset on which the marginal price is bounded away from 0, e.g., any reasonable choice of continuous functions to parameterize possible productions, such a maximum exists. This follows from the fact that the minimal marginal price and finite wealth limits the maximum feasible production (0 limits the minimum) and Tychonoff's theorem ensures the product of these compacts spaces is compact ensuring us a maximum of whatever continuous function we desire exists.

Proof of the second fundamental theorem

The second theorem formally states that, under the assumptions that every production set is convex and every preference relation is convex and locally nonsatiated, any desired Pareto-efficient allocation can be supported as a price quasi-equilibrium with transfers. [38] Further assumptions are needed to prove this statement for price equilibria with transfers.

The proof proceeds in two steps: first, we prove that any Pareto-efficient allocation can be supported as a price quasi-equilibrium with transfers; then, we give conditions under which a price quasi-equilibrium is also a price equilibrium.

Let us define a price quasi-equilibrium with transfers as an allocation , a price vector p, and a vector of wealth levels w (achieved by lump-sum transfers) with (where is the aggregate endowment of goods and is the production of firm j) such that:

i. for all (firms maximize profit by producing )
ii. For all i, if then (if is strictly preferred to then it cannot cost less than )
iii. (budget constraint satisfied)

The only difference between this definition and the standard definition of a price equilibrium with transfers is in statement (ii). The inequality is weak here () making it a price quasi-equilibrium. Later we will strengthen this to make a price equilibrium. [38] Define to be the set of all consumption bundles strictly preferred to by consumer i, and let V be the sum of all . is convex due to the convexity of the preference relation . V is convex because every is convex. Similarly , the union of all production sets plus the aggregate endowment, is convex because every is convex. We also know that the intersection of V and must be empty, because if it were not it would imply there existed a bundle that is strictly preferred to by everyone and is also affordable. This is ruled out by the Pareto-optimality of .

These two convex, non-intersecting sets allow us to apply the separating hyperplane theorem. This theorem states that there exists a price vector and a number r such that for every and for every . In other words, there exists a price vector that defines a hyperplane that perfectly separates the two convex sets.

Next we argue that if for all i then . This is due to local nonsatiation: there must be a bundle arbitrarily close to that is strictly preferred to and hence part of , so . Taking the limit as does not change the weak inequality, so as well. In other words, is in the closure of V.

Using this relation we see that for itself . We also know that , so as well. Combining these we find that . We can use this equation to show that fits the definition of a price quasi-equilibrium with transfers.

Because and we know that for any firm j:

for

which implies . Similarly we know:

for

which implies . These two statements, along with the feasibility of the allocation at the Pareto optimum, satisfy the three conditions for a price quasi-equilibrium with transfers supported by wealth levels for all i.

We now turn to conditions under which a price quasi-equilibrium is also a price equilibrium, in other words, conditions under which the statement "if then " imples "if then ". For this to be true we need now to assume that the consumption set is convex and the preference relation is continuous. Then, if there exists a consumption vector such that and , a price quasi-equilibrium is a price equilibrium.

To see why, assume to the contrary and , and exists. Then by the convexity of we have a bundle with . By the continuity of for close to 1 we have . This is a contradiction, because this bundle is preferred to and costs less than .

Hence, for price quasi-equilibria to be price equilibria it is sufficient that the consumption set be convex, the preference relation to be continuous, and for there always to exist a "cheaper" consumption bundle . One way to ensure the existence of such a bundle is to require wealth levels to be strictly positive for all consumers i. [38]

See also

Related Research Articles

<span class="mw-page-title-main">Normed vector space</span> Vector space on which a distance is defined

In mathematics, a normed vector space or normed space is a vector space over the real or complex numbers on which a norm is defined. A norm is a generalization of the intuitive notion of "length" in the physical world. If is a vector space over , where is a field equal to or to , then a norm on is a map , typically denoted by , satisfying the following four axioms:

  1. Non-negativity: for every ,.
  2. Positive definiteness: for every , if and only if is the zero vector.
  3. Absolute homogeneity: for every and ,
  4. Triangle inequality: for every and ,

In mathematics, the Lp spaces are function spaces defined using a natural generalization of the p-norm for finite-dimensional vector spaces. They are sometimes called Lebesgue spaces, named after Henri Lebesgue, although according to the Bourbaki group they were first introduced by Frigyes Riesz.

In game theory, the Nash equilibrium is the most commonly-used solution concept for non-cooperative games. A Nash equilibrium is a situation where no player could gain by changing their own strategy. The idea of Nash equilibrium dates back to the time of Cournot, who in 1838 applied it to his model of competition in an oligopoly.

In welfare economics, a Pareto improvement formalizes the idea of an outcome being "better in every possible way". A change is called a Pareto improvement if it leaves everyone in a society better-off. A situation is called Pareto efficient or Pareto optimal if all possible Pareto improvements have already been made; in other words, there are no longer any ways left to make one person better-off, unless we are willing to make some other person worse-off.

In statistics, the Gauss–Markov theorem states that the ordinary least squares (OLS) estimator has the lowest sampling variance within the class of linear unbiased estimators, if the errors in the linear regression model are uncorrelated, have equal variances and expectation value of zero. The errors do not need to be normal for the theorem to apply, nor do they need to be independent and identically distributed.

<span class="mw-page-title-main">Covariance matrix</span> Measure of covariance of components of a random vector

In probability theory and statistics, a covariance matrix is a square matrix giving the covariance between each pair of elements of a given random vector.

<span class="mw-page-title-main">Projection (linear algebra)</span> Idempotent linear transformation from a vector space to itself

In linear algebra and functional analysis, a projection is a linear transformation from a vector space to itself such that . That is, whenever is applied twice to any vector, it gives the same result as if it were applied once. It leaves its image unchanged. This definition of "projection" formalizes and generalizes the idea of graphical projection. One can also consider the effect of a projection on a geometrical object by examining the effect of the projection on points in the object.

<span class="mw-page-title-main">Edgeworth box</span> Model of an economic market

In economics, an Edgeworth box, sometimes referred to as an Edgeworth-Bowley box, is a graphical representation of a market with just two commodities, X and Y, and two consumers. The dimensions of the box are the total quantities Ωx and Ωy of the two goods.

In mathematical economics, the Arrow–Debreu model is a theoretical general equilibrium model. It posits that under certain economic assumptions there must be a set of prices such that aggregate supplies will equal aggregate demands for every commodity in the economy.

In mathematics, Farkas' lemma is a solvability theorem for a finite system of linear inequalities. It was originally proven by the Hungarian mathematician Gyula Farkas. Farkas' lemma is the key result underpinning the linear programming duality and has played a central role in the development of mathematical optimization. It is used amongst other things in the proof of the Karush–Kuhn–Tucker theorem in nonlinear programming. Remarkably, in the area of the foundations of quantum theory, the lemma also underlies the complete set of Bell inequalities in the form of necessary and sufficient conditions for the existence of a local hidden-variable theory, given data from any specific set of measurements.

In mathematics and economics, transportation theory or transport theory is a name given to the study of optimal transportation and allocation of resources. The problem was formalized by the French mathematician Gaspard Monge in 1781.

Competitive equilibrium is a concept of economic equilibrium, introduced by Kenneth Arrow and Gérard Debreu in 1951, appropriate for the analysis of commodity markets with flexible prices and many traders, and serving as the benchmark of efficiency in economic analysis. It relies crucially on the assumption of a competitive environment where each trader decides upon a quantity that is so small compared to the total quantity traded in the market that their individual transactions have no influence on the prices. Competitive markets are an ideal standard by which other market structures are evaluated.

The Price of Anarchy (PoA) is a concept in economics and game theory that measures how the efficiency of a system degrades due to selfish behavior of its agents. It is a general notion that can be extended to diverse systems and notions of efficiency. For example, consider the system of transportation of a city and many agents trying to go from some initial location to a destination. Here, efficiency means the average time for an agent to reach the destination. In the 'centralized' solution, a central authority can tell each agent which path to take in order to minimize the average travel time. In the 'decentralized' version, each agent chooses its own path. The Price of Anarchy measures the ratio between average travel time in the two cases.

<span class="mw-page-title-main">Stokes' theorem</span> Theorem in vector calculus

Stokes' theorem, also known as the Kelvin–Stokes theorem after Lord Kelvin and George Stokes, the fundamental theorem for curls or simply the curl theorem, is a theorem in vector calculus on . Given a vector field, the theorem relates the integral of the curl of the vector field over some surface, to the line integral of the vector field around the boundary of the surface. The classical theorem of Stokes can be stated in one sentence: The line integral of a vector field over a loop is equal to the surface integral of its curl over the enclosed surface. It is illustrated in the figure, where the direction of positive circulation of the bounding contour ∂Σ, and the direction n of positive flux through the surface Σ, are related by a right-hand-rule. For the right hand the fingers circulate along ∂Σ and the thumb is directed along n.

Within bayesian statistics for machine learning, kernel methods arise from the assumption of an inner product space or similarity structure on inputs. For some such methods, such as support vector machines (SVMs), the original formulation and its regularization were not Bayesian in nature. It is helpful to understand them from a Bayesian perspective. Because the kernels are not necessarily positive semidefinite, the underlying structure may not be inner product spaces, but instead more general reproducing kernel Hilbert spaces. In Bayesian probability kernel methods are a key component of Gaussian processes, where the kernel function is known as the covariance function. Kernel methods have traditionally been used in supervised learning problems where the input space is usually a space of vectors while the output space is a space of scalars. More recently these methods have been extended to problems that deal with multiple outputs such as in multi-task learning.

In economics and consumer theory, a linear utility function is a function of the form:

Efficiency and fairness are two major goals of welfare economics. Given a set of resources and a set of agents, the goal is to divide the resources among the agents in a way that is both Pareto efficient (PE) and envy-free (EF). The goal was first defined by David Schmeidler and Menahem Yaari. Later, the existence of such allocations has been proved under various conditions.

Weller's theorem is a theorem in economics. It says that a heterogeneous resource ("cake") can be divided among n partners with different valuations in a way that is both Pareto-efficient (PE) and envy-free (EF). Thus, it is possible to divide a cake fairly without compromising on economic efficiency.

In theoretical economics, an abstract economy is a model that generalizes both the standard model of an exchange economy in microeconomics, and the standard model of a game in game theory. An equilibrium in an abstract economy generalizes both a Walrasian equilibrium in microeconomics, and a Nash equilibrium in game-theory.

Market equilibrium computation is a computational problem in the intersection of economics and computer science. The input to this problem is a market, consisting of a set of resources and a set of agents. There are various kinds of markets, such as Fisher market and Arrow–Debreu market, with divisible or indivisible resources. The required output is a competitive equilibrium, consisting of a price-vector, and an allocation, such that each agent gets the best bundle possible given the budget, and the market clears.

References

  1. https://web.stanford.edu/~hammond/effMktFail.pdf [ bare URL PDF ]
  2. Stiglitz, Joseph E. (1994), Whither Socialism?, MIT Press, ISBN   978-0-262-69182-6
  3. See the discussion on pp. 556 f of Mas-Colell et al.
  4. 'Wealth of nations' (1776), Book IV, Chap II.
  5. Feldman, Allan M. (2017), "Welfare Economics", The New Palgrave Dictionary of Economics, London: Palgrave Macmillan UK, pp. 1–14, doi:10.1057/978-1-349-95121-5_1417-2, ISBN   978-1-349-95121-5 , retrieved 2021-11-12
  6. Paraphrased from Leçon 18 (first ed.) of the Éléments. 'L'échange de deux marchandises entre elles sur un marché régi par la libre concurrence est une opération par laquelle tous les porteurs soit de l'une des deux marchandises, soit de l'autre, soit de toutes les deux, obtiennent la plus grande satisfaction de leurs besoins compatible avec cette condition de donner de la marchandise qu'ils vendent et de recevoir de la marchandise qu'ils achètent dans une proportion commune et identique.' According to Wicksell this passage moved to Leçon 10 in the 4th ed.
  7. Paul Samuelson backed him up, saying that the locus of Paretian optima can be obtained under multilateral monopoly. 'Foundations of Economic Analysis' (1947), p. 214.
  8. p. 21.
  9. p. 25. See also John Creedy, 'Francis Ysidro Edgeworth and Philip Henry Wicksteed' (2010), https://core.ac.uk/reader/6561724.
  10. Manuale di Economia Politica con una Introduzione alla Scienza Sociale (1906) / Manuel d'Économie Politique (1909).
  11. Manuale / Manuel Chap III, §22.
  12. §116.
  13. §33.
  14. §35.
  15. K. Wicksell, 'Lectures on Political Economy' I (1906), Eng. tr. (1934), pp. 82 f.
  16. §35.
  17. Manuel, §109–end.
  18. P. A. Samuelson, 'Foundations of Economic Analysis' (1947), p. 212.
  19. Thomas M. Humphrey, 'The Trade Theorist's Sacred Diagram: its Origin and Early Development' (1988).
  20. This and the preceding quotation have been condensed from §53 and §55 of Chap. VI.
  21. E. Barone, 'Il Ministro della Produzione nello Stato Colletivistica' (1908).
  22. In fact he divides this value by the price of an arbitrarily chosen item, but since prices are assumed fixed this merely introduces an irrelevant asymmetry.
  23. P. A. Samuelson, 'Foundations of Economic Analysis' (1947), pp. 214–217.
  24. A. Lerner, 'The Diagrammatical Representation of Cost Conditions in International Trade' (1932), cited in Thomas M. Humphrey, 'The Trade Theorist's Sacred Diagram: its Origin and Early Development' (1988).
  25. E.g. 'Nothing but prime cost [i.e. marginal cost] enters necessarily and directly into the supply price for short periods': Alfred Marshall, 'Principles of Economics', V.v.6 (eighth ed. consulted). And cf. Knut Wicksell's 'provisional conclusion that free competition is normally a sufficient condition to ensure maximization of production', 'Lectures on Political Economy' I (1906), Eng. tr. (1934), p. 141.
  26. P. A. Samuelson, 'Foundations of Economic Analysis' (1947), p. 217.
  27. H. Hotelling, 'The General Welfare Problem in Relation to Problems of Taxation and of Railway and Utility rates' (1938), Econometrica, pp. 260, 267.
  28. 'All that part of the theory of Public Finance which deals with "Social Utility" goes by the board': L. Robbins, 'An Essay on the Nature and Significance of Economic Science' (1932), p. 125. J. A. King commented that 'This defence of privilege required an unconvincingly solipsistic approach to the problem of comparing the states of mind of different individuals...' ('Nicholas Kaldor' (2009), quoted in a 2011 review by Harvey Gram).
  29. Feldman, Allan M. (2017), "Welfare Economics", The New Palgrave Dictionary of Economics, London: Palgrave Macmillan UK, pp. 1–14, doi:10.1057/978-1-349-95121-5_1417-2, ISBN 978-1-349-95121-5, retrieved 2021-11-12
  30. P. A. Samuelson, 'Foundations of Economic Analysis' (1947), pp. 219–249.
  31. p. 245.
  32. K. Arrow, 'An Extension of the Basic Theorems of Classical Welfare Economics' (1951); G. Debreu, 'The Coefficient of Resource Utilization' (1951).
  33. Greenwald, Bruce C.; Stiglitz, Joseph E. (1986). "Externalities in Economies with Imperfect Information and Incomplete Markets". The Quarterly Journal of Economics. 101 (2): 229–264. doi: 10.2307/1891114 . ISSN   0033-5533. JSTOR   1891114.
  34. Avinash Dixit, 'Whither Greenwald-Stiglitz?' (2003).
  35. Greenwald and Stiglitz (1986), p. 238.
  36. Mas-Colell, Andreu; Whinston, Michael D.; Green, Jerry R. (1995). Microeconomic theory. New York, NY: Oxford Univ. Press. ISBN   978-0-19-507340-9.
  37. Acemoglu, Daron (2009). Introduction to modern economic growth. Princeton, New Jersey Oxford: Princeton University Press. ISBN   978-0-691-13292-1.
  38. 1 2 3 4 5 6 Mas-Colell, Andreu; Whinston, Michael D.; Green, Jerry R. (1995), "Chapter 16: Equilibrium and its Basic Welfare Properties", Microeconomic Theory , Oxford University Press, ISBN   978-0-19-510268-0