Skip to main content
Log in

Walrasian versus Cournot behavior in an oligopoly of boundedly rational firms

  • Regular Article
  • Published:
Journal of Evolutionary Economics Aims and scope Submit manuscript

Abstract

An evolutionary oligopoly game, where firms can select between the best-reply rule and the Walrasian rule, is considered. The industry is characterized by a finite number of ex-ante homogeneous firms that, characterized by naïve expectations, decide next-period output by employing one of the two behavioral rules. The inverse demand function is linear and all firms have the same quadratic and convex cost function (decreasing return to scale). Based upon realized profits, the distribution of behavioral rules is updated according to a replicator dynamics. The model is characterized by two equilibria: the Cournot-Nash equilibrium, where all firms adopt the best-reply rule and produce the Cournot-Nash quantity, and the Walrasian equilibrium, where all firms adopt the Walrasian rule and produce the Walrasian quantity. The analysis reveals that the Walrasian equilibrium is globally stable as long as the rate of change of marginal cost exceeds the sum of residual market price sensitivities to output. If not, the Walrasian equilibrium loses stability and an attractor, representing complicated dynamics with evolutionary stable heterogeneity, arises through a bifurcation. As the propensity of firms to select the more profitable behavioral rule increases, the attractor disappears through a global bifurcation and the Cournot-Nash equilibrium can become a global Milnor attractor. To sum up, the best-reply rule can be evolutionary dominant over the Walrasian rule and this can lead an oligopoly to select the Cournot-Nash equilibrium.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7

Similar content being viewed by others

Notes

  1. A linear price function is obtained by assuming that the utility function of the representative consumer is quadratic; see, e.g., Bischi et al. (2010) and Vives (2001).

  2. Note that p(t) indicates the price at time t, while P(⋅) indicates the inverse demand function or price function.

  3. Let us note that x(t + 1) ≥ 0 if and only if \(p^{e}_{BR}\left (t+1\right )\geq 0\).

  4. Let us note that y(t + 1) ≥ 0 if and only if p(t) ≥ 0.

  5. In the modeling framework of this paper, the replicator dynamics describes the time evolution of the probability of selecting a behavioral rule. This interpretation is beyond the evolutionary one originally proposed in biology, and it is consistent with the usual random matching hypothesis adopted in game theory; see, e.g., Hauert et al. (2006), van Veelen (2011) and references therein. As underlined by an anonymous referee, abandoning the probabilistic interpretation of the state variable r would require that r takes only rational numbers of type 0, 1/N, 2/N,…, 1. This modeling choice implies the loss of the mathematical tractability of the model and is employed in Vriend (2000), where a genetic algorithm confirms that firms select the Walrasian quantity whenever a learning mechanism based on relative performances, as the one implied by the replicator (11), is considered. The development of a computational model as the one in Vriend (2000) but based on behavioral rules would represent an interesting way of testing the results of the current paper.

  6. According to Eq. 11, firms can decide to switch to a less sophisticated behavioral rule, such as the Walrasian one, once they have experienced the more advanced best-reply rule. In this framework, it is a common approach to associate an additional fixed cost to the more sophisticated behavioral rule. In the current model, as long as it is small enough, such a cost would not affect the results and thus is omitted for the sake of simplicity.

  7. Steady states of model (13) are named equilibria instead of fixed points for analogy with both economic and game theory.

  8. As b measures market price sensitivity to output and the oligopoly includes N firms each characterized by a residual demand function, bN can be also seen as the sum of the residual market price sensitivities to output.

  9. Note that \(0<{\lambda ^{W}_{3}}<1\), where \({\lambda ^{W}_{3}}\) is the eigenvalue computed of the Walrasian equilibrium and associated to the eigenvector orthogonal to the subset r = 0. See proof of Proposition 1 in Appendix.

  10. It is worth pointing out that, despite the assumption of constant expectations as in Theocharis (1960), the well-know Theocharis’ stability result that more than three firms implies instability of the Cournot-Nash equilibrium does not hold within this modeling setup due to the assumption of non constant marginal costs.

  11. A Milnor attractor is an invariant set with a stable set of positive measure but not attracting in the topological sense (i.e. without an attracting neighborhood). In fact, initial conditions arbitrarily close to a Milnor attractor can generate trajectories that are locally repelled out from the Milnor attractor itself; see, e.g. Milnor (1985) and Bischi and Lamantia (2005).

References

  • Alós-Ferrer C (2004) Cournot versus Walras in dynamics oligopolies with memory. Int J Ind Organ 22:193–217

    Article  Google Scholar 

  • Anufriev M, Kopányi D (2017) Oligopoly game: price makers meet price takers. Discussion paper

  • Anufriev M, Kopányi D, Tuinstra J (2013) Learning cycles in Bertrand competition with differentiated commodities and competing learning rules. J Econ Dyn Control 37(12):2562–2581

    Article  Google Scholar 

  • Arnold L (1998) Random dynamical systems. Springer

  • Apesteguia J, Huck S, Oechssler J, Weidenholzer S (2013) Imitation and the evolution of Walrasian behavior: theoretically fragile but behaviorally robust. J Econ Theory 45(5):1603–1617

    Google Scholar 

  • Bischi G I, Lamantia F (2005) Nonlinear dynamical systems in economics - CISM lecture notes. Springer, chap coexisting attractors and complex basins in discrete-,time economic models, pp 187–231

  • Bischi G I, Chiarella C, Kopel M, Szidarovszky F (2010) Nonlinear oligopolies: stability and bifurcations. Springer-Verlag

  • Bischi G I, Lamantia F, Radi D (2015) An evolutionary Cournot model with limited market knowledge. J Econ Behav Org 116:219–238

    Article  Google Scholar 

  • Bosch-Domènech A, Vriend N J (2003) Imitation of successful behavioral in Cournot market. Econ J 113:495–524

    Article  Google Scholar 

  • Cabrales A, Sobel J (1992) On the limit points of discrete selection dynamics. J Econ Theory 57(2):407–419

    Article  Google Scholar 

  • Cavalli F, Naimzada A, Pireddu M (2015) Effects of size, composition, and evolutionary pressure in heterogeneous Cournot oligopolies with best response decisional mechanisms. Discret Dyn Nat Soc Article ID 273026:17

    Google Scholar 

  • Cerboni Baiardi L, Lamanta F, Radi D (2015) Evolutionary competition between boundedly rational behavioral rules in oligopoly games. Chaos Solitons Fractals 79:204–225

    Article  Google Scholar 

  • di Bernardo M, Budd CJ, Champneys AR, Kowalczyk P (2008) Piecewise-smooth dynamical systems: theory and applications. Springer-Verlag

  • Droste E, Hommes C H, Tuinstra J (2002) Endogenous fluctuations under evolutionary pressure in Cournot competition. Games Econ Behav 40(2):232–269

    Article  Google Scholar 

  • Fisher F M (1961) The stability of the Cournot oligopoly solution: the effect of speeds of adjustment and increasing marginal costs. Rev Econ Stud 28(2):125–135

    Article  Google Scholar 

  • Fouraker L E, Siegel S (1963) Bargaining behavior. McGraw-Hill, New York

    Google Scholar 

  • Hauert C, Michor F, Nowak M A, Doebeli M (2006) Synergy and discounting of cooperation in social dilemmas. J Theor Biol 239(2):195–202

    Article  Google Scholar 

  • Hofbauer J, Sigmund K (2003) Evolutionary game dynamics. Bull(New Series) Amer Math Soc 40(4):479–519

    Article  Google Scholar 

  • Hofbauer J, Weibull J W (1996) Evolutionary selection against dominated strategies. J Econ Theory 71(2):558–573

    Article  Google Scholar 

  • Hommes C H (1994) Dynamics of the cobweb model with adaptive expectations and nonlinear supply and demand. J Econ Behav Org 24:315–335

    Article  Google Scholar 

  • Kopel M, Lamantia F, Szidarovszky F (2014) Evolutionary competition in a mixed market with socially concerned firms. J Econ Dyn Control 48:394–409

    Article  Google Scholar 

  • Milnor J (1985) On the concept of attractor: correction and remarks. Commun Math Phys 102(3):517–519

    Article  Google Scholar 

  • Nelson R, Winter S (1982) An evolutionary theory of economic change. Harvard University Press, Cambridge

    Google Scholar 

  • Rhode P, Stegeman M (2001) Non-Nash equilibria of Darwinian dynamics with applications to duopoly. Int J Ind Organ 19:3–4

    Article  Google Scholar 

  • Riechmann T (2006) Cournot or Walras? Long-run results in oligopoly games. J Inst Theor Econ JITE 162:702–720

    Article  Google Scholar 

  • Schaffer M E (1989) Are profit-maximisers the best survivors?: a Darwinian model of economic natural selection. J Econ Behav Org 12:29–45

    Article  Google Scholar 

  • Sushko I, Gardini L (2010) Degenerate bifurcations and border collisions in piecewise smooth 1d and 2d maps. Int J Bifur Chaos 20(7):2045–2070

    Article  Google Scholar 

  • Theocharis R D (1960) On the stability of the Cournot solution on the oligopoly problem. Rev Econ Stud 27(2):133–134

    Article  Google Scholar 

  • Vallée T, ldzoğlu M Y (2009) Convergence in the finite Cournot oligopoly with social and individual learning. J Econ Behav Org 72:670–690

    Article  Google Scholar 

  • van Veelen M (2011) The replicator dynamics with n players and population structure. J Theor Biol 276(1):78–85

    Article  Google Scholar 

  • Vega-Redondo (1997) The evolution of walrasian behavior. Econometrica: J Econ Soc 65(2):375–384

    Article  Google Scholar 

  • Vives X (2001) Oligopoly pricing: old ideas and new tools. MIT Press

  • Vriend N J (2000) An illustration of the essential difference between individual and social learning, and its consequences for computational analyses. J Econ Dyn Control 24(1):1–19

    Article  Google Scholar 

  • Winter S (1964) Economic natural selection and the theory of firms, vol 4. Yale Economics Essays

Download references

Acknowledgements

The author thanks Gian Italo Bischi, Laura Gardini, Fabio Lamantia, Ivana Tuzharova, two anonymous reviewers and all participants in the Nonlinear Economic Dynamics 2015 conference in Tokyo (Tokyo NED conference) for their insightful comments and suggestions that have lead to several improvements in the paper. The author gratefully acknowledges the Department of Economics of Chuo University in Tokyo and the University of Urbino Carlo Bo for funding his participation in the Tokyo NED conference. Special thanks to Akio Matsumoto and the Local Organizing Committee of the Tokyo NED conference for having organized a wonderful meeting.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Davide Radi.

Ethics declarations

Conflict of interests

The author declares that he has no conflict of interest.

Appendix

Appendix

Proof of Lemma 1

From (13), it is straightforward to see that the steady states of the evolutionary model are obtained for r = 0, r = 1or any r ∈ (0, 1)for which Δπ = 0.With r = 0(all Walrasian firms), map (13) becomes:

$$ T^{0}:=\left\{\begin{array}{l} x\left( t+1\right)=\max\left[\frac{a-b\left( N-1\right)y\left( t\right)}{2\left( b+c\right)},0\right]\\ \\ y\left( t+1\right)=\max\left[\frac{a-bNy\left( t\right)}{2c},0\right] \end{array}\right. $$
(22)

where the second component is uncoupled from the first one, i.e. it is a one-dimensionaldifference equation (master equation) and it is piecewise linear, whereas the first componentdepends only on the second variable (slave equation). Thus, by straightforward algebra, E 0is the only equilibriumwhen r = 0and bysimple calculations \(p_{W}^{*}\)and π(E 0)are obtained.

With r = 1(all best-reply firms), map (13) becomes:

$$ T^{1}:=\left\{\begin{array}{l} x\left( t+1\right)=\max\left[\frac{a-b\left( N-1\right)x\left( t\right)}{2\left( b+c\right)},0\right]\\ \\ y\left( t+1\right)=\max\left[\frac{a-bNx\left( t\right)}{2c},0\right] \end{array}\right. $$
(23)

where the first component is uncoupled from the second one, i.e. it is a one-dimensional differenceequation (master equation) and it is piecewise linear, whereas the second componentdepends only on the first variable (slave equation). Thus, by straightforward algebra, E 1is the onlyequilibrium when r = 1and defining

$$ K = \frac{bN^{2}+2c\left( N-1\right)}{\left( 2c+b\left( N+1\right)\right)^{2}}b^{2}>0 $$
(24)

by simple calculation \(p^{*}_{CN}\)and π(E 1)are obtained.

Let us now investigate the existence of other equilibria (x , y , r )with r ∈ (0, 1). If (x , y , r )∈Ω1,then

$$ \left\{\begin{array}{l} x^{*}=R\left( x^{*},y^{*},r^{*}\right)\\ y^{*}=W\left( x^{*},y^{*},r^{*}\right)\\ {\Delta}{\Pi}\left( x^{*},y^{*},r^{*}\right)=0 \end{array} \right. $$
(25)

From the third equation of the system we obtain either x = y or\(r^{*}=\frac {c\left (x^{*}+y^{*}\right )+bNy^{*}-a}{bN\left (y^{*}-x^{*}\right )}\). Solving the first andthe second equation for x = y ,we obtain x y ,which is a contradiction. Analogously, substituting\(r^{*}=\frac {c\left (x^{*}+y^{*}\right )+bNy^{*}-a}{bN\left (y^{*}-x^{*}\right )}\)in the first and secondequation we obtain \(x^{*}=-y^{*}-\frac {a}{\left (N-1\right )c}\)and x = −y , respectively. Thus, afurther equilibrium in Ω1cannot exist. An equilibrium (x , y , r )in Ω2implies y = 0, x = R(x , 0, r )and Δπ(x , y , r ) = 0. Solving,we obtain \(x^{*}=\frac {a}{2Nb+cN+c}\)and \(r^{*}=\frac {2b+c}{b}\). Since r > 1, an equilibrium in Ω2cannot exist. Moreover, theonly possible equilibrium in Ω3is (0, 0, r )which does not belongto such region. Thus, E 0and E 1are the only possibleequilibria of the model (13). □

Proof of Proposition 1

A straightforward computation allows us to obtain the Jacobian matrix of model (13),when r = 0and (x, y, r) ∈Ω1,given by

$$ J\left( x,y,0\right)=\left[ \begin{array}{ccc} 0 & \frac{-b\left( N-1\right)}{2\left( b+c\right)} & \frac{b\left( N-1\right)\left( y-x\right)}{2\left( b+c\right)} \\ 0 & \frac{-bN}{2c} & \frac{bN\left( y-x\right)}{2c} \\ 0 & 0 & J_{33}\left( x,y,0\right) \end{array} \right]\quad \text{ where }\quad J_{33}\left( x,y,0\right)=e^{-\beta \left( a-bNy-c\left( x+y\right)\right)\left( y-x\right)} $$
(26)

which is singular and upper triangular. Thus, the associated eigenvalues are the diagonal entriesand the eigenvalues for the Jacobian matrix computed at the Walrasian equilibrium, i.e. J(E 0),are:

$$ {\lambda^{W}_{1}}=0\text{, }\quad {\lambda^{W}_{2}}=\frac{-bN}{2c}=\frac{\frac{\partial P\left( E_{0}\right)}{\partial y}}{\frac{\partial^{2} C}{\partial y^{2}}}\text{, }{\quad\lambda^{W}_{3}}=J_{33}\left( E_{0}\right)=e^{-\beta c\left( \frac{ab}{\left( 2c+bN\right)2\left( b+c\right)}\right)^{2}} $$
(27)

Imposing the well-known conditions for the local asymptotic stability of a fixed point, i.e. alleigenvalues of J(E 0)inside the unit circle, we obtain the first part of the proposition.

Similar computation allows us to obtain the Jacobian matrix of model (13), when r = 1and (x, y, r) ∈Ω1, givenby

$$ J\left( x,y,1\right)=\left[ \begin{array}{ccc} \frac{\partial R\left( x,y,1\right)}{\partial x} & 0 & \frac{b\left( N-1\right)\left( y-x\right)}{2\left( b+c\right)} \\ \frac{-bN}{2c} & 0 & \frac{bN\left( y-x\right)}{2c} \\ 0 & 0 & J_{33}\left( x,y,1\right) \end{array} \right]\quad \text{ where }\quad J_{33}\left( x,y,1\right)=e^{-\beta \left( a-bNx-c\left( x+y\right)\right)\left( y-x\right)} $$
(28)

Thus, the eigenvalues for the Jacobian matrix computed at the Cournot-Nash equilibrium, i.e. J(E 1),are:

$$ \lambda_{1}^{CN}=\frac{\partial R\left( E_{1}\right)}{\partial x}=\frac{-b\left( N-1\right)}{2\left( b+c\right)} , \quad \lambda^{CN}_{2}=0, \quad \lambda^{CN}_{3}=e^{\beta \frac{a^{2}b^{2}}{4c\left( 2c+b\left( N+1\right)\right)^{2}}} $$
(29)

Noting that \(\lambda ^{CN}_{3}>1\),the transverse instability of the Cournot-Nash equilibrium follows. □

Proof of Proposition 2

The restriction of map (13) to the invariant plane r = 0reduces to the two-dimensional map\(T^{0}:\mathbb {R}^{2}_{+}\rightarrow \mathbb {R}^{2}_{+}\)defined in Eq. 22. Let us divide the plane\(\mathbb {R}^{2}_{+}\)into the following three regions:

$$ \begin{array}{l} {{\Omega}^{0}_{1}}=\left\{\left( x,y\right)| 0\leq y<\frac{a}{bN}\right\}\\ {{\Omega}^{0}_{2}}=\left\{\left( x,y\right)| \frac{a}{bN}\leq y<\frac{a}{b\left( N-1\right)}\right\}\\ {{\Omega}^{0}_{3}}=\left\{\left( x,y\right)| \frac{a}{b\left( N-1\right)}\leq y\right\} \end{array} $$
(30)

The lines

$$ \tilde{BC}_{1} := y=\frac{a}{bN}\quad \text{ and }\quad \tilde{BC}_{2} := y=\frac{a}{b\left( N-1\right)} $$
(31)

mark the borders of non differentiability between regions\({{\Omega }^{0}_{1}}\)and\({{\Omega }^{0}_{2}}\)andbetween \({{\Omega }^{0}_{2}}\)and \({{\Omega }^{0}_{3}}\),respectively.

By straightforward considerations, see Lemma 1, it follows that\(\tilde {E}_{0}=\left (q^{*}_{W}\frac {b+2c}{2\left (b+c\right )},q^{*}_{W}\right ){\in {\Omega }_{1}^{0}}\), with\(q^{*}_{W}=\frac {a}{2c+bN}\), is the uniquefixed point of T 0.

For bN < 2c, we have thatall points of region \({{\Omega }^{0}_{2}}\)and \({{\Omega }^{0}_{3}}\)are mapped inone iteration in \({{\Omega }^{0}_{1}}\). Infact, all points of region \({{\Omega }^{0}_{2}}\)are mapped in \(\left \{\left (y,x\right )|y=0\text {,} \ x\geq 0\right \}{\in {\Omega }^{0}_{1}}\)and allpoints of \({{\Omega }^{0}_{3}}\)are mappedin \(\left (0,0\right ){\in {\Omega }^{0}_{1}}\). Moreover, themap T 0is linear in\({{\Omega }^{0}_{1}}\)with a unique innerfixed point \(\tilde {E}_{0}\). Theeigenvalues associated to \(\tilde {E}_{0}\)are \(\tilde {\lambda }_{1}^{W}=0\)and \(\tilde {\lambda }_{2}^{W}=\frac {-bN}{2c}\)with \(-1<\tilde {\lambda }_{2}^{W}<0\).Thus, \(\tilde {E}_{0}\)is locally asymptotically stable and the image of region\({{\Omega }^{0}_{1}}\)is the manifold spannedby the eigenvector \(v=\left [1,\frac {N\left (b+c\right )}{c\left (N-1\right )}\right ]^{\prime }\)associated to \(\tilde {\lambda }_{2}^{W}\):

$$ x=\frac{c\left( N-1\right)}{N\left( b+c\right)}y+\frac{a}{2N\left( b+c\right)} $$
(32)

Noting that after one iteration \(y\in \left [0,\frac {a}{2c}\right ]\),it follows that the following region:

$$ \tilde{A}=\left\{\left( x,y\right)| y\in\left[0,\frac{a}{2c}\right]\text{,} \ x=\frac{c\left( N-1\right)}{N\left( b+c\right)}y+\frac{a}{2N\left( b+c\right)}\right\} $$
(33)

is invariant and attracts all points of \(\mathbb {R}^{2}_{+}\)in at most two iterations. In addition, \(\tilde {E}_{0}\in \tilde {A}\).

For bN = 2c, the eigenvaluesassociated to \(\tilde {E}_{0}\in \tilde {A}\)are \(\tilde {\lambda }^{W}_{1}=0\)and\(\tilde {\lambda }^{W}_{2}=-1\). Then, thelinearity of T 0in \(\tilde {A}\)implies a degenerate flip bifurcation through which an infinity of 2-cycles that fill region\(\tilde {A}\)are originated.It follows that \(\tilde {\mathcal {C}}_{1}^{W}=\left \{\mathcal {\bar {C}}_{0}^{W},\mathcal {\underline {C}}_{0}^{W}\right \}\),where

$$ \mathcal{\bar{C}}_{0}^{W}=\left( \frac{a}{2\left( b+c\right)},\frac{a}{2c}\right) \quad \text{and} \quad \mathcal{\underline{C}}_{0}^{W}=\left( a\frac{2c-b\left( N-1\right)}{4c\left( b+c\right)},0\right) $$
(34)

are the borders of region \(\tilde {A}\), isa 2-cycle. Since \(\mathcal {\bar {C}}_{0}^{W}\)lies on theborder of non differentiability \(\tilde {BC}_{1}\),we have that \(\tilde {\mathcal {C}}_{1}^{W}\)undergoes a persistence border collision.

For b(N − 1) < 2c < bN, we havethat \(T^{0}\left (\mathcal {\underline {C}}_{0}^{W}\right )=\mathcal {\bar {C}}_{0}^{W}{\in {\Omega }^{0}_{2}}\)and all pointsof subregion \({{\Omega }^{0}_{2}}\)aremapped in \(\mathcal {\underline {C}}_{0}^{W}\)in oneiteration. Thus, \(\tilde {\mathcal {C}}_{1}^{W}\)is a2-cycle for T 0. Moreover,we have that \(\tilde {\lambda }^{W}_{1}=0\)and \(\tilde {\lambda }^{W}_{2}<-1\). Thus,\(\tilde {E}_{0}\)is a repellor and by the linearityof map T 0is possible to excludethe existence of 2-cycles in \({{\Omega }^{0}_{1}}\).This implies that, except for \(\tilde {\mathcal {C}}_{1}^{W}\), all2-cycles that filled region \(\tilde {A}\)havedisappeared. Since all points of \({{\Omega }^{0}_{2}}\)are mapped in \(\mathcal {\underline {C}}_{0}^{W}\),all points of \({{\Omega }^{0}_{3}}\)aremapped in (0, 0),\(T^{0}\left (0,0\right )=\mathcal {\bar {C}}_{0}^{W}\)and in\({{\Omega }^{0}_{3}}\)the map T 0is linear with insidea unique repellor \(\tilde {E}_{0}\), itfollows that \(\tilde {\mathcal {C}}_{1}^{W}\)attractsall the point of \(\mathbb {R}^{2}_{+}\)except for \(\tilde {E}_{0}\).

For b(N − 1) = 2c,\(\mathcal {\bar {C}}_{0}^{W}\)collides with the borderof non-differentiability \(\tilde {BC}_{2}\).Thus \(\tilde {\mathcal {C}}_{1}^{W}\)undergoes a border collision bifurcation and disappears. Moreover, let us define\(\mathcal {\hat {C}}_{0}^{W}=\left (0,0\right )\). Since\(T^{0}\left (\mathcal {\hat {C}}_{0}^{W}\right )=\mathcal {\bar {C}}_{0}^{W}\),\(T^{0}\left (\mathcal {\bar {C}}_{0}^{W}\right )=\mathcal {\hat {C}}_{0}^{W}\)and\(\mathcal {\bar {C}}_{0}^{W}\in \tilde {BC}_{2}\), it followsthat the 2-cycle \(\tilde {\mathcal {C}}_{2}^{W}=\left \{\mathcal {\bar {C}}_{0}^{W},\mathcal {\hat {C}}_{0}^{W}\right \}\)appears through a border collision bifurcation.

For 2c < b(N − 1),as \(T^{0}\left (\mathcal {\hat {C}}_{0}^{W}\right )=\mathcal {\bar {C}}_{0}^{W}\)and\(T^{0}\left (\mathcal {\bar {C}}_{0}^{W}\right )=\mathcal {\hat {C}}_{0}^{W}\), it follows that\(\tilde {\mathcal {C}}_{2}^{W}\)is a 2-cycle for T 0. In addition,since all points of \({{\Omega }^{0}_{3}}\)are plotted in \(\mathcal {\hat {C}}_{0}^{W}\),all points of \({{\Omega }^{0}_{2}}\)aremapped in \({{\Omega }^{0}_{1}}\),and in this latter region the map is linear with a unique inner repellor\(\tilde {E}_{0}\), it followsthat \(\tilde {\mathcal {C}}_{2}^{W}\)attractsall the points of \(\mathbb {R}^{2}_{+}\)except for \(\tilde {E}_{0}\).

Since \(\frac {\partial ^{2} C}{\partial y^{2}}=2c\),\(\frac {\partial P\left (E_{0}\right )}{\partial y}=-bN\)and T 0is the restriction of map(13) on the invariant plane r = 0, the results on E 0,\(\mathcal {C}_{1}^{W}\),\(\mathcal {C}_{2}^{W}\)and region A, defined as in the statement of the Proposition, follow by the results on\(\tilde {E}_{0}\),\(\tilde {\mathcal {C}}_{1}^{W}\),\(\tilde {\mathcal {C}}_{2}^{W}\)and\(\tilde {A}\).

By the smoothness of map (13) in a neighborhood of\(\mathcal {\bar {C}}^{W}\)and\(\mathcal {\underline {C}}^{W}\), and from the Jacobianmatrix of this map when r = 0(see, e.g., (26)) follows that the transverse eigenvalue of\(\mathcal {C}_{1}^{W}\)is given by\(J_{33}\left (\mathcal {\bar {C}}^{W}\right )J_{33}\left (\mathcal {\underline {C}}^{W}\right )\). Since\(J_{33}\left (\mathcal {\bar {C}}^{W}\right )>1\)and\(J_{33}\left (\mathcal {\underline {C}}^{W}\right )\geq 1\)the transverseinstability of \(\mathcal {C}_{1}^{W}\)follows. By similar considerations and calculations we have that\(J_{33}\left (\mathcal {\bar {C}}^{W}\right )J_{33}\left (\mathcal {\hat {C}}^{W}\right )>1\), from which the transverseinstability of the 2-cycle \(\mathcal {C}_{2}^{W}\)follows. □

Proof of Proposition 2

The restriction of map (13) to the invariant plane r = 1reduces to the two-dimensional map\(T^{1}:\mathbb {R}^{2}_{+}\rightarrow \mathbb {R}^{2}_{+}\)defined in Eq. 23. Let us divide the plane\(\mathbb {R}^{2}_{+}\)into the following three regions:

$$ \begin{array}{l} {{\Omega}^{1}_{1}}=\left\{\left( x,y\right)| 0\leq x<\frac{a}{bN}\right\}\\ {{\Omega}^{1}_{2}}=\left\{\left( x,y\right)| \frac{a}{bN}\leq x<\frac{a}{b\left( N-1\right)}\right\}\\ {{\Omega}^{1}_{3}}=\left\{\left( x,y\right)| \frac{a}{b\left( N-1\right)}\leq x\right\} \end{array} $$
(35)

The lines

$$ \bar{BC}_{1} := x=\frac{a}{bN}\quad \text{ and }\quad \bar{BC}_{2} := x=\frac{a}{b\left( N-1\right)} $$
(36)

mark the borders of non differentiability between regions\({{\Omega }^{1}_{1}}\)and\({{\Omega }^{1}_{2}}\)andbetween \({{\Omega }^{1}_{2}}\)and \({{\Omega }^{1}_{3}}\),respectively.

By straightforward considerations, see Lemma 1, it follows that\(\tilde {E}_{1}=\left (q^{*}_{CN},q^{*}_{CN}\frac {b+2c}{2c}\right ){\in {\Omega }_{1}^{1}}\), with\(q^{*}_{CN}=\frac {a}{2c+b\left (N+1\right )}\), is the uniquefixed point of T 1.

For b(N − 3) < 2c, we have thatall points of region \({{\Omega }^{1}_{2}}\)and \({{\Omega }^{1}_{3}}\)are mapped inone iteration in \({{\Omega }^{1}_{1}}\). Infact, all points of region \({{\Omega }^{1}_{2}}\)are mapped in \(\left \{\left (y,x\right )|y=0\text {,} \ x\geq 0\right \}{\in {\Omega }^{1}_{1}}\)and allpoints of \({{\Omega }^{1}_{3}}\)are mappedin \(\left (0,0\right ){\in {\Omega }^{1}_{1}}\). Moreover, themap T 1is linear in\({{\Omega }^{1}_{1}}\)with a unique innerfixed point \(\tilde {E}_{1}\). Theeigenvalues associated to \(\tilde {E}_{1}\)are \(\tilde {\lambda }_{1}^{CN}=\frac {-b\left (N-1\right )}{2\left (b+c\right )}\)and \(\tilde {\lambda }_{2}^{CN}=0\)with \(-1<\tilde {\lambda }_{1}^{CN}<0\).Thus, \(\tilde {E}_{1}\)is locally asymptotically stable and the image of region\({{\Omega }^{1}_{1}}\)is the manifold spannedby the eigenvector \(v=\left [1,\frac {N\left (b+c\right )}{c\left (N-1\right )}\right ]^{\prime }\)associated to \(\tilde {\lambda }_{1}^{CN}\):

$$ y=\frac{N\left( b+c\right)}{c\left( N-1\right)}x-\frac{a}{2c\left( N-1\right)} $$
(37)

Noting that, after one iteration, \(x\in \left [0,\frac {a}{2\left (b+c\right )}\right ]\)and y cannot be negative, it follows that the region:

$$ \tilde{B}=\left\{\left( x,y\right)| x\in\left[0,\frac{a}{2\left( b+c\right)}\right]\text{,} \ y=\max\left[\frac{N\left( b+c\right)}{c\left( N-1\right)}x-\frac{a}{2c\left( N-1\right)},0\right]\right\} $$
(38)

is invariant and attracts all points of \(\mathbb {R}^{2}_{+}\)in at most two iterations. In addition, \(\tilde {E}_{1}\in \tilde {B}\).

For b(N − 3) = 2c, the eigenvaluesassociated to \(\tilde {E}_{1}\in \tilde {B}\)are \(\tilde {\lambda }^{CN}_{1}=-1\)and\(\tilde {\lambda }^{CN}_{2}=0\). Then, the linearity(with respect to x) of T 1in \(\tilde {B}\)implies a degenerate flip bifurcation through which an infinity of 2-cycles that fill region\(\tilde {B}\)are originated.It follows that \(\tilde {\mathcal {C}}^{CN}=\left \{\mathcal {\bar {C}}_{1}^{CN},\mathcal {\underline {C}}_{1}^{CN}\right \}\),where

$$ \mathcal{\bar{C}}_{1}^{CN}=\left( \frac{a}{2\left( b+c\right)},\frac{a}{2c}\right) \quad \text{and} \quad \mathcal{\underline{C}}_{1}^{CN}=\left( 0,0\right) $$
(39)

are the borders of region \(\tilde {B}\), isa 2-cycle. Since \(\mathcal {\bar {C}}_{1}^{CN}\)lies on theborder of non differentiability \(\bar {BC}_{2}\),we have that \(\tilde {\mathcal {C}}^{CN}\)undergoes a persistence border collision.

For 2c < b(N − 3), we havethat \(T^{1}\left (\mathcal {\underline {C}}_{1}^{CN}\right )=\mathcal {\bar {C}}_{1}^{CN}{\in {\Omega }^{1}_{3}}\)and all pointsof subregion \({{\Omega }^{1}_{3}}\)aremapped in \(\mathcal {\underline {C}}_{1}^{CN}\)in oneiteration. Thus, \(\tilde {\mathcal {C}}^{CN}\)is a2-cycle for T 1. Moreover,we have that \(\tilde {\lambda }^{CN}_{1}<-1\)and \(\tilde {\lambda }^{CN}_{2}=0\). Thus,\(\tilde {E}_{1}\)is a repellor and bythe linearity of map T 1(with respect to x) it is possible to exclude the existence of 2-cycles in\({{\Omega }^{1}_{1}}\)and\({{\Omega }^{1}_{2}}\). This implies that, exceptfor \(\tilde {\mathcal {C}}_{1}^{CN}\), all 2-cycles that filledregion \(\tilde {B}\)have disappeared.Moreover, since all points of \({{\Omega }^{1}_{2}}\)are mapped in \({{\Omega }_{1}^{1}}\),all points of \({{\Omega }^{1}_{3}}\)aremapped in \(\mathcal {\underline {C}}_{1}^{CN}\),\(T^{1}\left (\mathcal {\underline {C}}_{1}^{CN}\right )=\mathcal {\bar {C}}_{1}^{CN}\)and in\({{\Omega }^{1}_{1}}\)the map T 1is linear with insidea unique repellor \(\tilde {E}_{1}\), itfollows that \(\tilde {\mathcal {C}}^{CN}\)attractsall the point of \(\mathbb {R}^{2}_{+}\)except for \(\tilde {E}_{1}\).

Since \(\frac {\partial R\left (E_{1}\right )}{\partial x}=\frac {-b\left (N-1\right )}{2\left (b+c\right )}\)and T 1is the restriction of map(13) on the invariant plane r = 1,the results on E 1,\(\mathcal {C}^{CN}\)and region B, defined as in the statement of the Proposition, follow by the results on\(\tilde {E}_{1}\),\(\tilde {\mathcal {C}}^{CN}\)and\(\tilde {B}\).

By the smoothness of map (13) in a neighborhood\(\mathcal {\bar {C}}^{CN}\)and\(\mathcal {\underline {C}}^{CN}\), and from the Jacobianmatrix of this map when r = 1,see, e.g., (28), follows that the transverse eigenvalue of\(\mathcal {C}^{CN}\)is given by\(J_{33}\left (\mathcal {\bar {C}}^{CN}\right )J_{33}\left (\mathcal {\underline {C}}^{CN}\right )\). Since\(J_{33}\left (\mathcal {\bar {C}}^{CN}\right )<1\)and\(J_{33}\left (\mathcal {\underline {C}}^{CN}\right )\leq 1\), the transverseattractiveness of \(\mathcal {C}_{1}^{CN}\)follows. □

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Radi, D. Walrasian versus Cournot behavior in an oligopoly of boundedly rational firms. J Evol Econ 27, 933–961 (2017). https://doi.org/10.1007/s00191-017-0536-2

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00191-017-0536-2

Keywords

JEL Classifications

Navigation