Non-convexity (economics)

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In economics , non-convexity refers to violations of the convexity assumptions of elementary economics. Basic economics textbooks concentrate on consumers with convex preferences (that do not prefer extremes to in-between values) and convex budget sets and on producers with convex production sets; for convex models, the predicted economic behavior is well understood. [1] [2] When convexity assumptions are violated, then many of the good properties of competitive markets need not hold: Thus, non-convexity is associated with market failures, [3] [4] where supply and demand differ or where market equilibria can be inefficient. [1] [4] [5] [6] [7] [8] Non-convex economies are studied with nonsmooth analysis, which is a generalization of convex analysis. [8] [9] [10] [11]

Contents

Demand with many consumers

If a preference set is non-convex, then some prices determine a budget-line that supports two separate optimal-baskets. For example, we can imagine that, for zoos, a lion costs as much as an eagle, and further that a zoo's budget suffices for one eagle or one lion. We can suppose also that a zoo-keeper views either animal as equally valuable. In this case, the zoo would purchase either one lion or one eagle. Of course, a contemporary zoo-keeper does not want to purchase half of an eagle and half of a lion. Thus, the zoo-keeper's preferences are non-convex: The zoo-keeper prefers having either animal to having any strictly convex combination of both.

When consumer preferences have concavities, then the linear budgets need not support an equilibrium: Consumers can jump between two separate allocations (of equal utility). NonConvex.gif
When consumer preferences have concavities, then the linear budgets need not support an equilibrium: Consumers can jump between two separate allocations (of equal utility).

When the consumer's preference set is non-convex, then (for some prices) the consumer's demand is not connected; A disconnected demand implies some discontinuous behavior by the consumer, as discussed by Harold Hotelling:

If indifference curves for purchases be thought of as possessing a wavy character, convex to the origin in some regions and concave in others, we are forced to the conclusion that it is only the portions convex to the origin that can be regarded as possessing any importance, since the others are essentially unobservable. They can be detected only by the discontinuities that may occur in demand with variation in price-ratios, leading to an abrupt jumping of a point of tangency across a chasm when the straight line is rotated. But, while such discontinuities may reveal the existence of chasms, they can never measure their depth. The concave portions of the indifference curves and their many-dimensional generalizations, if they exist, must forever remain in unmeasurable obscurity. [12]

The difficulties of studying non-convex preferences were emphasized by Herman Wold [13] and again by Paul Samuelson, who wrote that non-convexities are "shrouded in eternal darkness ...", [14] according to Diewert. [15]

When convexity assumptions are violated, then many of the good properties of competitive markets need not hold: Thus, non-convexity is associated with market failures, where supply and demand differ or where market equilibria can be inefficient. [1] Non-convex preferences were illuminated from 1959 to 1961 by a sequence of papers in The Journal of Political Economy (JPE). The main contributors were Michael Farrell, [16] Francis Bator, [17] Tjalling Koopmans, [18] and Jerome Rothenberg. [19] In particular, Rothenberg's paper discussed the approximate convexity of sums of non-convex sets. [20] These JPE-papers stimulated a paper by Lloyd Shapley and Martin Shubik, which considered convexified consumer-preferences and introduced the concept of an "approximate equilibrium". [21] The JPE-papers and the Shapley–Shubik paper influenced another notion of "quasi-equilibria", due to Robert Aumann. [22] [23]

Non-convex sets have been incorporated in the theories of general economic equilibria. [24] These results are described in graduate-level textbooks in microeconomics, [25] general equilibrium theory, [26] game theory, [27] mathematical economics, [28] and applied mathematics (for economists). [29] The Shapley–Folkman lemma establishes that non-convexities are compatible with approximate equilibria in markets with many consumers; these results also apply to production economies with many small firms. [30]

Supply with few producers

Non-convexity is important under oligopolies and especially monopolies. [8] Concerns with large producers exploiting market power initiated the literature on non-convex sets, when Piero Sraffa wrote about on firms with increasing returns to scale in 1926, [31] after which Harold Hotelling wrote about marginal cost pricing in 1938. [32] Both Sraffa and Hotelling illuminated the market power of producers without competitors, clearly stimulating a literature on the supply-side of the economy. [33]

Contemporary economics

Recent research in economics has recognized non-convexity in new areas of economics. In these areas, non-convexity is associated with market failures, where equilibria need not be efficient or where no competitive equilibrium exists because supply and demand differ. [1] [4] [5] [6] [7] [8] Non-convex sets arise also with environmental goods (and other externalities), [6] [7] and with market failures, [3] and public economics. [5] [34] Non-convexities occur also with information economics, [35] and with stock markets [8] (and other incomplete markets). [36] [37] Such applications continued to motivate economists to study non-convex sets. [1] In some cases, non-linear pricing or bargaining may overcome the failures of markets with competitive pricing; in other cases, regulation may be justified.

Optimization over time

The previously mentioned applications concern non-convexities in finite-dimensional vector spaces, where points represent commodity bundles. However, economists also consider dynamic problems of optimization over time, using the theories of differential equations, dynamic systems, stochastic processes, and functional analysis: Economists use the following optimization methods:

In these theories, regular problems involve convex functions defined on convex domains, and this convexity allows simplifications of techniques and economic meaningful interpretations of the results. [43] [44] [45] In economics, dynamic programing was used by Martin Beckmann and Richard F. Muth for work on inventory theory and consumption theory. [46] Robert C. Merton used dynamic programming in his 1973 article on the intertemporal capital asset pricing model. [47] (See also Merton's portfolio problem). In Merton's model, investors chose between income today and future income or capital gains, and their solution is found via dynamic programming. Stokey, Lucas & Prescott use dynamic programming to solve problems in economic theory, problems involving stochastic processes. [48] Dynamic programming has been used in optimal economic growth, resource extraction, principal–agent problems, public finance, business investment, asset pricing, factor supply, and industrial organization. Ljungqvist & Sargent apply dynamic programming to study a variety of theoretical questions in monetary policy, fiscal policy, taxation, economic growth, search theory, and labor economics. [49] Dixit & Pindyck used dynamic programming for capital budgeting. [50] For dynamic problems, non-convexities also are associated with market failures, [51] just as they are for fixed-time problems. [52]

Nonsmooth analysis

Economists have increasingly studied non-convex sets with nonsmooth analysis, which generalizes convex analysis. Convex analysis centers on convex sets and convex functions, for which it provides powerful ideas and clear results, but it is not adequate for the analysis of non-convexities, such as increasing returns to scale. [53] "Non-convexities in [both] production and consumption ... required mathematical tools that went beyond convexity, and further development had to await the invention of non-smooth calculus": For example, Clarke's differential calculus for Lipschitz continuous functions, which uses Rademacher's theorem and which is described by Rockafellar & Wets (1998) [54] and Mordukhovich (2006), [9] according to Khan (2008). [10] Brown (1995 , pp. 1967–1968) wrote that the "major methodological innovation in the general equilibrium analysis of firms with pricing rules" was "the introduction of the methods of non-smooth analysis, as a [synthesis] of global analysis (differential topology) and [of] convex analysis." According to Brown (1995 , p. 1966), "Non-smooth analysis extends the local approximation of manifolds by tangent planes [and extends] the analogous approximation of convex sets by tangent cones to sets" that can be non-smooth or non-convex. [11] [55]

See also

Notes

  1. 1 2 3 4 5 Mas-Colell, A. (1987). "Non-convexity" (PDF). In Eatwell, John; Milgate, Murray; Newman, Peter (eds.). The New Palgrave: A Dictionary of Economics (first ed.). Palgrave Macmillan. pp. 653–661. doi:10.1057/9780230226203.3173. ISBN   9780333786765.
  2. Green, Jerry; Heller, Walter P. (1981). "1 Mathematical analysis and convexity with applications to economics". In Arrow, Kenneth Joseph; Intriligator, Michael D. (eds.). Handbook of mathematical economics, Volume I. Handbooks in economics. Vol. 1. Amsterdam: North-Holland Publishing Co. pp. 15–52. doi:10.1016/S1573-4382(81)01005-9. ISBN   0-444-86126-2. MR   0634800.
  3. 1 2 Salanié, Bernard (2000). "7 Nonconvexities". Microeconomics of market failures (English translation of the (1998) French Microéconomie: Les défaillances du marché (Economica, Paris) ed.). Cambridge, MA: MIT Press. pp. 107–125. ISBN   0-262-19443-0.
  4. 1 2 3 Salanié (2000 , p. 36)
  5. 1 2 3 Laffont, Jean-Jacques (1988). "3 Nonconvexities". Fondements de L'economie Publique [Fundamentals of public economics]. MIT. pp. 63–65. ISBN   0-262-12127-1.
  6. 1 2 3 Starrett, David A. (1972). "Fundamental nonconvexities in the theory of externalities". Journal of Economic Theory. 4 (2): 180–199. doi:10.1016/0022-0531(72)90148-2. MR   0449575.
  7. 1 2 3 Pages 106, 110–137, 172, and 248: Baumol, William J.; Oates, Wallace E.; with contributions by V. S. Bawa and David F. Bradford (1988). "8 Detrimental externalities and nonconvexities in the production set". The Theory of environmental policy (Second ed.). Cambridge: Cambridge University Press. ISBN   978-0-521-31112-0.
  8. 1 2 3 4 5 Page 1: Guesnerie, Roger (1975). "Pareto optimality in non-convex economies". Econometrica. 43 (1): 1–29. doi:10.2307/1913410. JSTOR   1913410. MR   0443877. ("Errata". Econometrica. Vol. 43, no. 5–6. 1975. p. 1010. doi:10.2307/1911353. JSTOR   1911353. MR   0443878.)
  9. 1 2 Mordukhovich, Boris S. (2006). "Chapter 8 Applications to economics". Variational analysis and generalized differentiation II: Applications. Grundlehren der Mathematischen Wissenschaften [Fundamental Principles of Mathematical Sciences]. Vol. 331. Springer. especially Section 8.5.3 "Enter nonconvexity" (and the remainder of the chapter), particularly page 495. ISBN   978-3-540-25438-6. MR   2191745.
  10. 1 2 Khan, M. Ali (2008). "Perfect competition". In Durlauf, Steven N.; Blume, Lawrence E. (eds.). The New Palgrave Dictionary of Economics (Second ed.). Palgrave Macmillan. pp. 354–365. doi:10.1057/9780230226203.1267. ISBN   978-0-333-78676-5.
  11. 1 2 Brown, Donald J. (1991). "36 Equilibrium analysis with non-convex technologies". In Hildenbrand, Werner; Sonnenschein, Hugo (eds.). Handbook of mathematical economics, Volume IV. Handbooks in Economics. Vol. 1. Amsterdam: North-Holland Publishing Co. pp. 1963–1995 [1966]. doi:10.1016/S1573-4382(05)80011-6. ISBN   0-444-87461-5. MR   1207195.
  12. Hotelling (1935 , p. 74): Hotelling, Harold (January 1935). "Demand functions with limited budgets". Econometrica. 3 (1): 66–78. doi:10.2307/1907346. JSTOR   1907346.
  13. Pages 231 and 239 (Figure 10 a–b: Illustration of lemma 5 [page 240]): Wold, Herman (1943b). "A synthesis of pure demand analysis II". Skandinavisk Aktuarietidskrift [Scandinavian Actuarial Journal]. Vol. 26. pp. 220–263. MR   0011939.

    Exercise 45, page 146: Wold, Herman; Juréen, Lars (in association with Wold) (1953). "8 Some further applications of preference fields (pp. 129–148)". Demand analysis: A study in econometrics. Wiley publications in statistics. New York: John Wiley and Sons, Inc. Stockholm: Almqvist and Wiksell. MR   0064385.

  14. Samuelson (1950 , pp. 359–360):
    It will be noted that any point where the indifference curves are convex rather than concave cannot be observed in a competitive market. Such points are shrouded in eternal darkness—unless we make our consumer a monopsonist and let him choose between goods lying on a very convex "budget curve" (along which he is affecting the price of what he buys). In this monopsony case, we could still deduce the slope of the man's indifference curve from the slope of the observed constraint at the equilibrium point.
    For the epigraph to their seventh chapter, "Markets with non-convex preferences and production" presenting Starr (1969) , Arrow & Hahn (1971 , p. 169) quote John Milton's description of the (non-convex) Serbonian Bog in Paradise Lost (Book II, lines 592–594):
    A gulf profound as that Serbonian Bog
    Betwixt Damiata and Mount Casius old,
    Where Armies whole have sunk.
  15. Diewert (1982 , pp. 552–553).
  16. Farrell, M. J. (August 1959). "The Convexity assumption in the theory of competitive markets". The Journal of Political Economy . 67 (4): 371–391. doi:10.1086/258197. JSTOR   1825163. S2CID   153653926.Farrell, M. J. (October 1961a). "On Convexity, efficiency, and markets: A Reply". Journal of Political Economy. 69 (5): 484–489. doi:10.1086/258541. JSTOR   1828538. S2CID   154398283.Farrell, M. J. (October 1961b). "The Convexity assumption in the theory of competitive markets: Rejoinder". Journal of Political Economy. 69 (5): 493. doi:10.1086/258544. JSTOR   1828541. S2CID   154200859.
  17. Bator, Francis M. (October 1961a). "On convexity, efficiency, and markets". The Journal of Political Economy. 69 (5): 480–483. doi:10.1086/258540. JSTOR   1828537. S2CID   153979194.Bator, Francis M. (October 1961b). "On convexity, efficiency, and markets: Rejoinder". Journal of Political Economy. 69 (5): 489. doi:10.1086/258542. JSTOR   1828539. S2CID   154255876.
  18. Koopmans, Tjalling C. (October 1961). "Convexity assumptions, allocative efficiency, and competitive equilibrium". The Journal of Political Economy. 69 (5): 478–479. doi:10.1086/258539. JSTOR   1828536. S2CID   154831335.

    Koopmans (1961 , p. 478) and others—for example, Farrell (1959 , pp. 390–391) and Farrell (1961a , p. 484), Bator (1961a , pp. 482–483), Rothenberg (1960 , p. 438), and Starr (1969 , p. 26)—commented on Koopmans (1957 , pp. 1–126, especially 9–16 [1.3 Summation of opportunity sets], 23–35 [1.6 Convex sets and the price implications of optimality], and 35–37 [1.7 The role of convexity assumptions in the analysis]):

    Koopmans, Tjalling C. (1957). "Allocation of resources and the price system". In Koopmans, Tjalling C (ed.). Three essays on the state of economic science. New York: McGraw–Hill Book Company. pp. 1–126. ISBN   0-07-035337-9.

  19. Rothenberg (1960 , p. 447): Rothenberg, Jerome (October 1960). "Non-convexity, aggregation, and Pareto optimality". The Journal of Political Economy. 68 (5): 435–468. doi:10.1086/258363. JSTOR   1830308. S2CID   154192326. (Rothenberg, Jerome (October 1961). "Comments on non-convexity". Journal of Political Economy. 69 (5): 490–492. doi:10.1086/258543. JSTOR   1828540. S2CID   154070123.)
  20. Arrow & Hahn (1980 , p. 182)
  21. Shapley & Shubik (1966 , p. 806): Shapley, L. S.; Shubik, M. (October 1966). "Quasi-cores in a monetary economy with nonconvex preferences". Econometrica. 34 (4): 805–827. doi:10.2307/1910101. JSTOR   1910101. S2CID   46271184. Zbl   0154.45303.
  22. Aumann (1966 , pp. 1–2): Aumann, Robert J. (January 1966). "Existence of competitive equilibrium in markets with a continuum of traders". Econometrica. 34 (1): 1–17. doi:10.2307/1909854. JSTOR   1909854. MR   0191623. S2CID   155044347. Aumann (1966) builds on two papers: Aumann ( 1964 , 1965 )

    Aumann, Robert J. (January–April 1964). "Markets with a continuum of traders". Econometrica. 32 (1–2): 39–50. doi:10.2307/1913732. JSTOR   1913732. MR   0172689.

    Aumann, Robert J. (August 1965). "Integrals of set-valued functions". Journal of Mathematical Analysis and Applications. 12 (1): 1–12. doi: 10.1016/0022-247X(65)90049-1 . MR   0185073.

  23. Taking the convex hull of non-convex preferences had been discussed earlier by Wold (1943b , p. 243) and by Wold & Juréen (1953 , p. 146), according to Diewert (1982 , p. 552).
  24. Pages 392–399 and page 188: Arrow, Kenneth J.; Hahn, Frank H. (1971). "Appendix B: Convex and related sets" . General competitive analysis. Mathematical economics texts [Advanced textbooks in economics]. San Francisco, CA: Holden-Day, Inc. [North-Holland]. pp.  375–401. ISBN   0-444-85497-5. MR   0439057.

    Pages 52–55 with applications on pages 145–146, 152–153, and 274–275: Mas-Colell, Andreu (1985). "1.L Averages of sets". The Theory of General Economic Equilibrium: A Differentiable Approach. Econometric Society Monographs. Cambridge University Press. ISBN   0-521-26514-2. MR   1113262.

    Theorem C(6) on page 37 and applications on pages 115-116, 122, and 168: Hildenbrand, Werner (1974). Core and equilibria of a large economy. Princeton studies in mathematical economics. Princeton, NJ: Princeton University Press. ISBN   978-0-691-04189-6. MR   0389160.

  25. Varian, Hal R. (1992). "21.2 Convexity and size". Microeconomic Analysis (3rd ed.). W. W. Norton & Company. pp.  393–394. ISBN   978-0-393-95735-8. MR   1036734.

    Page 628: Mas–Colell, Andreu; Whinston, Michael D.; Green, Jerry R. (1995). "17.1 Large economies and nonconvexities". Microeconomic theory. Oxford University Press. pp. 627–630. ISBN   978-0-19-507340-9.

  26. Page 169 in the first edition: Starr, Ross M. (2011). "8 Convex sets, separation theorems, and non-convex sets in RN". General equilibrium theory: An introduction (Second ed.). Cambridge: Cambridge University Press. doi:10.1017/CBO9781139174749. ISBN   978-0-521-53386-7. MR   1462618.[ clarification needed ]

    Ellickson (1994 , p. xviii), and especially Chapter 7 "Walras meets Nash" (especially section 7.4 "Nonconvexity" pages 306–310 and 312, and also 328–329) and Chapter 8 "What is Competition?" (pages 347 and 352): Ellickson, Bryan (1994). Competitive equilibrium: Theory and applications. Cambridge University Press. ISBN   978-0-521-31988-1.

  27. Theorem 1.6.5 on pages 24–25: Ichiishi, Tatsuro (1983). Game theory for economic analysis. Economic theory, econometrics, and mathematical economics. New York: Academic Press, Inc. [Harcourt Brace Jovanovich, Publishers]. ISBN   0-12-370180-5. MR   0700688.
  28. Cassels, J. W. S. (1981). "Appendix A Convex sets". Economics for mathematicians. London Mathematical Society lecture note series. Vol. 62. Cambridge, New York: Cambridge University Press. pp. 33–34 and 127. ISBN   0-521-28614-X. MR   0657578.
  29. Pages 93–94 (especially example 1.92), 143, 318–319, 375–377, and 416: Carter, Michael (2001). Foundations of mathematical economics. Cambridge, MA: MIT Press. ISBN   0-262-53192-5. MR   1865841.

    Page 309: Moore, James C. (1999). Mathematical methods for economic theory: Volume I. Studies in economic theory. Vol. 9. Berlin: Springer-Verlag. doi:10.1007/978-3-662-08544-8. ISBN   3-540-66235-9. MR   1727000.

    Pages 47–48: Florenzano, Monique; Le Van, Cuong (2001). Finite dimensional convexity and optimization. Studies in economic theory. Vol. 13. in cooperation with Pascal Gourdel. Berlin: Springer-Verlag. doi:10.1007/978-3-642-56522-9. ISBN   3-540-41516-5. MR   1878374. S2CID   117240618.

  30. Economists have studied non-convex sets using advanced mathematics, particularly differential geometry and topology, Baire category, measure and integration theory, and ergodic theory: Trockel, Walter (1984). Market demand: An analysis of large economies with nonconvex preferences. Lecture Notes in Economics and Mathematical Systems. Vol. 223. Berlin: Springer-Verlag. doi:10.1007/978-3-642-46488-1. ISBN   3-540-12881-6. MR   0737006.
  31. Sraffa, Piero (1926). "The Laws of returns under competitive conditions". Economic Journal. Vol. 36, no. 144. pp. 535–550. JSTOR   2959866.
  32. Hotelling, Harold (July 1938). "The General welfare in relation to problems of taxation and of railway and utility rates". Econometrica. 6 (3): 242–269. doi:10.2307/1907054. JSTOR   1907054.
  33. Pages 5–7: Quinzii, Martine (1992). Increasing returns and efficiency (Revised translation of (1988) Rendements croissants et efficacité economique. Paris: Editions du Centre National de la Recherche Scientifique ed.). New York: Oxford University Press. ISBN   0-19-506553-0.
  34. Starrett discusses non-convexities in his textbook on public economics (pages 33, 43, 48, 56, 70–72, 82, 147, and 234–236): Starrett, David A. (1988). Foundations of public economics. Cambridge economic handbooks. Cambridge: Cambridge University Press. ISBN   9780521348010.
  35. Radner, Roy (1968). "Competitive equilibrium under uncertainty". Econometrica. 36 (1): 31–53. doi:10.2307/1909602. JSTOR   1909602.
  36. Page 270: Drèze, Jacques H. (1987). "14 Investment under private ownership: Optimality, equilibrium and stability". In Drèze, J. H.location=Cambridge (ed.). Essays on economic decisions under uncertainty. Cambridge University Press. pp. 261–297. doi:10.1017/CBO9780511559464. ISBN   0-521-26484-7. MR   0926685. (Originally published as Drèze, Jacques H. (1974). "Investment under private ownership: Optimality, equilibrium and stability". In Drèze, J. H. (ed.). Allocation under Uncertainty: Equilibrium and Optimality. New York: Wiley. pp. 129–165.)
  37. Magille & Quinzii , Section 31 "Partnerships", p. 371): Magill, Michael; Quinzii, Martine (1996). "6 Production in a finance economy". The Theory of incomplete markets. Cambridge, Massachusetts: MIT Press. pp. 329–425.
  38. Ramsey, F. P. (1928). "A Mathematical Theory of Saving". Economic Journal . 38 (152): 543–559. doi:10.2307/2224098. JSTOR   2224098. S2CID   154223797.
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  43. Troutman, John L. (1996). With the assistance of William Hrusa (ed.). Variational calculus and optimal control: Optimization with elementary convexity. Undergraduate Texts in Mathematics (Second ed.). New York: Springer-Verlag. doi:10.1007/978-1-4612-0737-5. ISBN   0-387-94511-3. MR   1363262.
  44. Craven, B. D. (1995). Control and optimization. Chapman and Hall Mathematics Series. London: Chapman and Hall, Ltd. doi:10.1007/978-1-4899-7226-2. ISBN   0-412-55890-4. MR   1349574.
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  47. Merton, Robert C. (1973). "An Intertemporal Capital Asset Pricing Model". Econometrica. 41 (5): 867–887. doi:10.2307/1913811. JSTOR   1913811. S2CID   1504746.
  48. Stokey, Nancy; Lucas, Robert E.; Prescott, Edward (1989). Recursive Methods in Economic Dynamics. Harvard Univ. Press. ISBN   0-674-75096-9.
  49. Ljungqvist, Lars; Sargent, Thomas (2004). Recursive Macroeconomic Theory. MIT Press. ISBN   0-262-12274-X.
  50. Dixit, Avinash; Pindyck, Robert (1994). Investment Under Uncertainty. Princeton Univ. Press. ISBN   0-691-03410-9.
  51. Dasgupta & Heal (1979 , pp. 96–97, 285, 404, 420, 422, and 429)
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  55. Algebraic topology has also been used to study convex and non-convex sets in economics: Chichilnisky, G. (1993). "Intersecting families of sets and the topology of cones in economics" (PDF). Bulletin of the American Mathematical Society. New Series. 29 (2): 189–207. doi:10.1090/S0273-0979-1993-00439-7. MR   1218037.

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Sanford "Sandy" Jay Grossman is an American economist and hedge fund manager specializing in quantitative finance. Grossman’s research has spanned the analysis of information in securities markets, corporate structure, property rights, and optimal dynamic risk management. He has published widely in leading economic and business journals, including American Economic Review, Journal of Econometrics, Econometrica, and Journal of Finance. His research in macroeconomics, finance, and risk management has earned numerous awards. Grossman is currently Chairman and CEO of QFS Asset Management, an affiliate of which he founded in 1988. QFS Asset Management shut down its sole remaining hedge fund in January 2014.

<span class="mw-page-title-main">Quasiconvex function</span> Mathematical function with convex lower level sets

In mathematics, a quasiconvex function is a real-valued function defined on an interval or on a convex subset of a real vector space such that the inverse image of any set of the form is a convex set. For a function of a single variable, along any stretch of the curve the highest point is one of the endpoints. The negative of a quasiconvex function is said to be quasiconcave.

In mathematics, a vector measure is a function defined on a family of sets and taking vector values satisfying certain properties. It is a generalization of the concept of finite measure, which takes nonnegative real values only.

Lawrence E. Blume is the Distinguished Arts and Sciences Professor of Economics and Professor of Information Science at Cornell University, US.

Mathematical economics is the application of mathematical methods to represent theories and analyze problems in economics. Often, these applied methods are beyond simple geometry, and may include differential and integral calculus, difference and differential equations, matrix algebra, mathematical programming, or other computational methods. Proponents of this approach claim that it allows the formulation of theoretical relationships with rigor, generality, and simplicity.

<span class="mw-page-title-main">History of macroeconomic thought</span>

Macroeconomic theory has its origins in the study of business cycles and monetary theory. In general, early theorists believed monetary factors could not affect real factors such as real output. John Maynard Keynes attacked some of these "classical" theories and produced a general theory that described the whole economy in terms of aggregates rather than individual, microeconomic parts. Attempting to explain unemployment and recessions, he noticed the tendency for people and businesses to hoard cash and avoid investment during a recession. He argued that this invalidated the assumptions of classical economists who thought that markets always clear, leaving no surplus of goods and no willing labor left idle.

<span class="mw-page-title-main">Shapley–Folkman lemma</span> Sums of sets of vectors are nearly convex

The Shapley–Folkman lemma is a result in convex geometry that describes the Minkowski addition of sets in a vector space. It is named after mathematicians Lloyd Shapley and Jon Folkman, but was first published by the economist Ross M. Starr.

Roger Guesnerie is an economist born in France in 1943. He is currently the Chaired Professor of Economic Theory and Social Organization of the Collège de France, Director of Studies at the École des hautes études en sciences sociales, and the chairman of the board of directors of the Paris School of Economics.

<span class="mw-page-title-main">Andreu Mas-Colell</span> Catalan economist and politician from Spain

Andreu Mas-Colell is an economist, an expert in microeconomics and a prominent mathematical economist. He is the founder of the Barcelona Graduate School of Economics and a professor in the department of economics at Pompeu Fabra University in Barcelona, Catalonia, Spain. He has also served several times in the cabinet of the Catalan government. Summarizing his and others' research in general equilibrium theory, his monograph gave a thorough exposition of research using differential topology. His textbook on microeconomics, co-authored with Michael Whinston and Jerry Green, is the most used graduate microeconomics textbook in the world.

Ross Marc Starr is an American economist who specializes in microeconomic theory, monetary economics and mathematical economics. He is a professor at the University of California, San Diego.

Convexity is an important topic in economics. In the Arrow–Debreu model of general economic equilibrium, agents have convex budget sets and convex preferences: At equilibrium prices, the budget hyperplane supports the best attainable indifference curve. The profit function is the convex conjugate of the cost function. Convex analysis is the standard tool for analyzing textbook economics. Non‑convex phenomena in economics have been studied with nonsmooth analysis, which generalizes convex analysis.

<span class="mw-page-title-main">Ivar Ekeland</span> French mathematician

Ivar I. Ekeland is a French mathematician of Norwegian descent. Ekeland has written influential monographs and textbooks on nonlinear functional analysis, the calculus of variations, and mathematical economics, as well as popular books on mathematics, which have been published in French, English, and other languages. Ekeland is known as the author of Ekeland's variational principle and for his use of the Shapley–Folkman lemma in optimization theory. He has contributed to the periodic solutions of Hamiltonian systems and particularly to the theory of Kreĭn indices for linear systems. Ekeland is cited in the credits of Steven Spielberg's 1993 movie Jurassic Park as an inspiration of the fictional chaos theory specialist Ian Malcom appearing in Michael Crichton's 1990 novel Jurassic Park.

References

Heal, G. M. (April 1998). The Economics of Increasing Returns (PDF). PaineWebber working paper series in money, economics, and finance. Columbia Business School. PW-97-20. Archived from the original (PDF) on 15 September 2015. Retrieved 5 March 2011.