In mathematical economics, the Arrow–Debreu model is a theoretical general equilibrium model. It posits that under certain economic assumptions (convex preferences, perfect competition, and demand independence) there must be a set of prices such that aggregate supplies will equal aggregate demands for every commodity in the economy.[1]
The model is central to the theory of general (economic) equilibrium and it is often used as a general reference for other microeconomic models. It was proposed by Kenneth Arrow, Gérard Debreu in 1954, and Lionel W. McKenzie independently in 1954,[2] with later improvements in 1959.[3] [4]
The A-D model is one of the most general models of competitive economy and is a crucial part of general equilibrium theory, as it can be used to prove the existence of general equilibrium (or Walrasian equilibrium) of an economy. In general, there may be many equilibria.
Arrow (1972) and Debreu (1983) were separately awarded the Nobel Prize in Economics for their development of the model. McKenzie, however, did not receive the award.[5]
This section follows the presentation in,[6] which is based on.[7]
The Arrow–Debreu model models an economy as a combination of three kinds of agents: the households, the producers, and the market. The households and producers transact with the market, but not with each other directly.
The households possess endowments (bundles of commodities they begin with), which one may think of as "inheritance". For the sake of mathematical clarity, all households are required to sell all their endowment to the market at the beginning. If they wish to retain some of the endowment, they would have to repurchase from the market later. The endowments may be working hours, use of land, tons of corn, etc.
The households possess proportional ownerships of producers, which can be thought of as joint-stock companies. The profit made by producer
j
j
The households receive a budget, as the sum of income from selling endowments and dividend from producer profits.
The households possess preferences over bundles of commodities, which under the assumptions given, makes them utility maximizers. The households choose the consumption plan with the highest utility that they can afford using their budget.
The producers are capable of transforming bundles of commodities into other bundles of commodities. The producers have no separate utility functions. Instead, they are all purely profit maximizers.
The market is only capable of "choosing" a market price vector, which is a list of prices for each commodity, which every producer and household takes (there is no bargaining behavior—every producer and household is a price taker). The market has no utility or profit. Instead, the market aims to choose a market price vector such that, even though each household and producer is maximizing their own utility and profit, their consumption plans and production plans "harmonize". That is, "the market clears". In other words, the market is playing the role of a "Walrasian auctioneer".
receive endowment and ownership of producers | ||
sell all endowment to the market | ||
plan production to maximize profit | ||
enter purchase agreements between the market and each other | ||
perform production plan | ||
sell everything to the market | ||
send all profits to households in proportion to ownership | ||
plan consumption to maximize utility under budget constraint | ||
buy the planned consumption from the market |
In general, we write indices of agents as superscripts, and vector coordinate indices as subscripts.
x\succeqy
\foralln,xn\geqyn
N | |
\R | |
+ |
x
x\succeq0
N | |
\R | |
++ |
x
x\succ0
\DeltaN=\left\{x\in\RN:x1,...,xN\geq0,\sumn\inxn=1\right\}
n\in1:N
N
p=(p1,...,pN)\in
N | |
\R | |
++ |
N
i\inI
ri\in
N | |
\R | |
+ |
\alphai,j\geq0
\sumi\in\alphai,j=1 \forallj\inJ
M
CPSi\subset
N | |
\R | |
+ |
\succeqi
CPSi
\succeqi
ui:CPSi\to[0,1]
CPSi
xi
i(x | |
U | |
+ |
i)
xi
p
Di(p)\in
N | |
\R | |
+ |
p\in
N | |
\R | |
++ |
j\inJ
PPSj
(-1,1,0)
PPSj
yj
p
Sj(p)\in\RN
p\in
N | |
\R | |
++ |
CPS=\sumi\inCPSi
PPS=\sumj\inPPSj
r=\sumiri
D(p):=\sumiDi(p)
S(p):=\sumjSj(p)
Z(p)=D(p)-S(p)-r
(N,I,J,CPSi,\succeqi,PPSj)
(ri,\alphai,j)i\in
((pn)n\in,
i) | |
(x | |
i\inI |
,
j) | |
(y | |
j\inJ |
)
xi\inCPSi
yj\inPPSj
\sumi\inxi\preceq\sumj\inyj+r
r
PPSr:=\{y\inPPS:y+r\succeq0\}
p
(p,
i(p)) | |
(D | |
i\inI |
,
j(p)) | |
(S | |
j\inJ |
)
p
CPSi | Technical assumption necessary for proofs to work. | No. It is necessary for the existence of demand functions. | ||||||
local nonsatiation: \forallx\inCPSi,\epsilon>0, \existsx'\inCPSi,x'\succix,\ | x' - x\ | < \epsilon | Households always want to consume a little more. | No. It is necessary for Walras's law to hold. | ||||
CPSi | strictly diminishing marginal utility | Yes, to mere convexity, with Kakutani's fixed-point theorem. See next section. | ||||||
CPSi | diminishing marginal utility | Yes, to nonconvexity, with Shapley–Folkman lemma. | ||||||
continuity:
i) | Technical assumption necessary for the existence of utility functions by the Debreu theorems. | No. If the preference is not continuous, then the excess demand function may not be continuous. | ||||||
i) | For two consumption bundles, any bundle strictly between them is strictly better than the lesser. | Yes, to mere convexity, with Kakutani's fixed-point theorem. See next section. | ||||||
i) | For two consumption bundles, any bundle between them is no worse than the lesser. | Yes, to nonconvexity, with Shapley–Folkman lemma. | ||||||
The household always has at least one feasible consumption plan. | no bankruptcy | No. It is necessary for the existence of demand functions. |
PPSj | diseconomies of scale | Yes, to mere convexity, with Kakutani's fixed-point theorem. See next section. | ||||||
PPSj | no economies of scale | Yes, to nonconvexity, with Shapley–Folkman lemma. | ||||||
PPSj | Producers can close down for free. | |||||||
PPSj | Technical assumption necessary for proofs to work. | No. It is necessary for the existence of supply functions. | ||||||
PPS\cap
| There is no arbitrarily large "free lunch". | No. Economy needs scarcity. | ||||||
PPS\cap(-PPS) | The economy cannot reverse arbitrarily large transformations. |
The functions
Di(p),Sj(p)
p
t
\sqrt{(t+1)2-1}
p1/p2<1
\Pij(p)=+infty
Sj(p)
Consequently, we define "restricted market" to be the same market, except there is a universal upper bound
C
\|yj\|\leqC
\|xi\|\leqC
\tildeZ(p)
C
C
x
x\succeq0,\|x\|=C
(yj\in
j) | |
PPS | |
j\inJ |
\sumj\inyj+r\succeq0
\|yj\|<C
j\inJ
r
Each requirement is satisfiable.
PPSr=\left\{\sumj\inyj:yj\inPPSjforeachj\inJ,and\sumj\inyj+r\succeq0\right\}
PPSr
r\succeq0
j | |
PPS | |
r |
:=\{yj\inPPSj:yjisapartofsomeattainableproductionplanunderendowmentr\}
j | |
PPS | |
r |
j\inJ,r\succeq0
The two requirements together imply that the restriction is not a real restriction when the production plans and consumption plans are "interior" to the restriction.
p
\|\tildeSj(p)\|<C
Sj(p)
\tildeSj(p)
C
Sj(p)=\tildeSj(p)
\|\tildeDi(p)\|<C
Di(p)
\tildeDi(p)
C
These two propositions imply that equilibria for the restricted market are equilibria for the unrestricted market:
As the last piece of the construction, we define Walras's law:
p
Sj(p),Di(p)
\langlep,Z(p)\rangle=0
p
\langlep,\tildeZ(p)\rangle=0
Walras's law can be interpreted on both sides:
Note that the above proof does not give an iterative algorithm for finding any equilibrium, as there is no guarantee that the function
f
See main article: Kakutani fixed-point theorem.
See also: Convex set, Compact set, Continuous function, Fixed-point theorem and Brouwer fixed-point theorem.
In 1954, McKenzie and the pair Arrow and Debreu independently proved the existence of general equilibria by invoking the Kakutani fixed-point theorem on the fixed points of a continuous function from a compact, convex set into itself. In the Arrow–Debreu approach, convexity is essential, because such fixed-point theorems are inapplicable to non-convex sets. For example, the rotation of the unit circle by 90 degrees lacks fixed points, although this rotation is a continuous transformation of a compact set into itself; although compact, the unit circle is non-convex. In contrast, the same rotation applied to the convex hull of the unit circle leaves the point (0,0) fixed. Notice that the Kakutani theorem does not assert that there exists exactly one fixed point. Reflecting the unit disk across the y-axis leaves a vertical segment fixed, so that this reflection has an infinite number of fixed points.
See also: Shapley–Folkman lemma and Market failure.
The assumption of convexity precluded many applications, which were discussed in the Journal of Political Economy from 1959 to 1961 by Francis M. Bator, M. J. Farrell, Tjalling Koopmans, and Thomas J. Rothenberg.[9] proved the existence of economic equilibria when some consumer preferences need not be convex.[9] In his paper, Starr proved that a "convexified" economy has general equilibria that are closely approximated by "quasi-equilbria" of the original economy; Starr's proof used the Shapley–Folkman theorem.[10]
(Uzawa, 1962)[11] showed that the existence of general equilibrium in an economy characterized by a continuous excess demand function fulfilling Walras’s Law is equivalent to Brouwer fixed-Point theorem. Thus, the use of Brouwer's fixed-point theorem is essential for showing that the equilibrium exists in general.[12]
In welfare economics, one possible concern is finding a Pareto-optimal plan for the economy.
Intuitively, one can consider the problem of welfare economics to be the problem faced by a master planner for the whole economy: given starting endowment
r
i) | |
((x | |
i\inI |
,
j) | |
(y | |
j\inJ |
)
Define the Pareto ordering on the set of all plans
i) | |
((x | |
i\inI |
,
j) | |
(y | |
j\inJ |
)
i) | |
((x | |
i\inI |
,
j) | |
(y | |
j\inJ |
)
i) | |
\succeq((x' | |
i\inI |
,
j) | |
(y' | |
j\inJ |
)
xi\succeqix'i
i\inI
Then, we say that a plan is Pareto-efficient with respect to a starting endowment
r
In general, there are a whole continuum of Pareto-efficient plans for each starting endowment
r
With the set up, we have two fundamental theorems of welfare economics:[13]
Proof idea: any Pareto-optimal consumption plan is separated by a hyperplane from the set of attainable consumption plans. The slope of the hyperplane would be the equilibrium prices. Verify that under such prices, each producer and household would find the given state optimal. Verify that Walras's law holds, and so the expenditures match income plus profit, and so it is possible to provide each household with exactly the necessary budget.
The assumptions of strict convexity can be relaxed to convexity. This modification changes supply and demand functions from point-valued functions into set-valued functions (or "correspondences"), and the application of Brouwer's fixed-point theorem into Kakutani's fixed-point theorem.
This modification is similar to the generalization of the minimax theorem to the existence of Nash equilibria.
The two fundamental theorems of welfare economics holds without modification.
PPSj | PPSj | |
CPSi | CPSi | |
\succeqi | \succeqi | |
\tildeSj(p) | \tildeSj(p) | |
\tildeSj(p) | \tildeSj(p) | |
\langlep,\tildeZ(p)\rangle\leq0 | \langlep,z\rangle\leq0 z\in\tildeZ(p) | |
... | ... | |
equilibrium exists by Brouwer's fixed-point theorem | equilibrium exists by Kakutani's fixed-point theorem |
The definition of market equilibrium assumes that every household performs utility maximization, subject to budget constraints. That is, The dual problem would be cost minimization subject to utility constraints. That is,for some real number
i | |
u | |
0 |
In the model, all producers and households are "price takers", meaning that they simply transact with the market using the price vector
p
In detail, we continue with the economic model on the households and producers, but we consider a different method to design production and distribution of commodities than the market economy. It may be interpreted as a model of a "socialist" economy.
yj\inPPSj
y\inPPS
((xi)i\in,y)
This economy is thus a cooperative game with each household being a player, and we have the following concepts from cooperative game theory:
Since we assumed that any nonempty subset of households may eliminate all other households, while retaining control of the producers, the only states that can be executed are the core states. A state that is not a core state would immediately be objected by a coalition of households.
We need one more assumption on
PPS
k ⋅ PPS\subsetPPS
k\geq0
PPS
PPS
y\succ0
y
PPS
PPS
In Debreu and Scarf's paper, they defined a particular way to approach an infinitely large economy, by "replicating households". That is, for any positive integer
K
K
i
Let
xi,
k
i
xi,\simixi,
i\inI
k,k'\inK
In general, a state would be quite complex, treating each replicate differently. However, core states are significantly simpler: they are equitable, treating every replicate equally.
Consequently, when studying core states, it is sufficient to consider one consumption plan for each type of households. Now, define
CK
K
C1\supsetC2\supset …
C:=
infty | |
\cap | |
K=1 |
CK
We have seen that
C
The assumption that
PPS
CPSi
C
The assumption that production possibility sets are convex is a strong constraint, as it implies that there is no economy of scale. Similarly, we may consider nonconvex consumption possibility sets and nonconvex preferences. In such cases, the supply and demand functions
Sj(p),Di(p)
However, we may "convexify" the economy, find an equilibrium for it, then by the Shapley–Folkman–Starr theorem, it is an approximate equilibrium for the original economy.
In detail, given any economy satisfying all the assumptions given, except convexity of
PPSj,CPSi
\succeqi
PPS'j=Conv(PPSj)
CPS'i=Conv(CPSi)
x\succeq'iy
\forallz\inCPSi,y\in
i(z)) | |
Conv(U | |
+ |
\impliesx\in
i(z)) | |
Conv(U | |
+ |
where
Conv
With this, any general equilibrium for the convexified economy is also an approximate equilibrium for the original economy. That is, if
p*
d( ⋅ , ⋅ )
L
PPSj,CPSi
The convexified economy may not satisfy the assumptions. For example, the set
\{(x,0):x\geq0\}\cup\{(x,y):xy=1,x>0\}
The commodities in the Arrow–Debreu model are entirely abstract. Thus, although it is typically represented as a static market, it can be used to model time, space, and uncertainty by splitting one commodity into several, each contingent on a certain time, place, and state of the world. For example, "apples" can be split into "apples in New York in September if oranges are available" and "apples in Chicago in June if oranges are not available".
Given some base commodities, the Arrow–Debreu complete market is a market where there is a separate commodity for every future time, for every place of delivery, for every state of the world under consideration, for every base commodity.
In financial economics the term "Arrow–Debreu" most commonly refers to an Arrow–Debreu security. A canonical Arrow–Debreu security is a security that pays one unit of numeraire if a particular state of the world is reached and zero otherwise (the price of such a security being a so-called "state price"). As such, any derivatives contract whose settlement value is a function on an underlying whose value is uncertain at contract date can be decomposed as linear combination of Arrow–Debreu securities.
Since the work of Breeden and Lizenberger in 1978,[18] a large number of researchers have used options to extract Arrow–Debreu prices for a variety of applications in financial economics.[19]
Typically, economists consider the functions of money to be as a unit of account, store of value, medium of exchange, and standard of deferred payment. This is however incompatible with the Arrow–Debreu complete market described above. In the complete market, there is only a one-time transaction at the market "at the beginning of time". After that, households and producers merely execute their planned productions, consumptions, and deliveries of commodities until the end of time. Consequently, there is no use for storage of value or medium of exchange. This applies not just to the Arrow–Debreu complete market, but also to models (such as those with markets of contingent commodities and Arrow insurance contracts) that differ in form, but are mathematically equivalent to it.[20]
See main article: Computable general equilibrium. Scarf (1967)[21] was the first algorithm that computes the general equilibrium. See Scarf (2018) and Kubler (2012) for reviews.
Certain economies at certain endowment vectors may have infinitely equilibrium price vectors. However, "generically", an economy has only finitely many equilibrium price vectors. Here, "generically" means "on all points, except a closed set of Lebesgue measure zero", as in Sard's theorem.
There are many such genericity theorems. One example is the following:[22] [23]