Dynamic Oligopolies and Intertemporal Demand Interaction

Transcription

1 CUBO A Mathematical Journal Vol.11, N ō 02, May 2009 Dynamic Oligopolies Intertemporal Dem Interaction Carl Chiarella School of Finance Economics, University of Technology Sydney, P.O. Box 123, Broadway, NSW 2007, Australia carl.chiarella@uts.edu.au Ferenc Szidarovszky Systems & Industrial Engineering Department, The University of Arizona, Tucson, Arizona, , USA szidar@sie.arizona.edu ABSTRACT Dynamic oligopolies are examined with continuous time scales under the assumption that the dem at each time period is affected by earlier dems consumptions. After the mathematical model is introduced the local asymptotical stability of the equilibrium is examined, then we will discuss how information delays alter the stability conditions. We will also investigate the occurrence of a Hopf bifurcation giving the possibility of the birth of limit cycles. Numerical examples will be shown to illustrate the theoretical results. RESUMEN Dinámica de oligopolios son examinados en escala de tiempo continuo y bajo la suposición que la dema en todo tiempo periodico es afectada por la dema e

2 86 Carl Chiarella Ferenc Szidarovszky CUBO consumo temprano. Es presentado el modelo matemático y examinada la estabilidad asintótica local y entonces discutiremos como la información de retrazo altera las condiciones de estabilidad. También investigamos el acontecimiento de bifurcación de Hofp do la posibilidad de nacimiento de ciclos limites. Ejemplos númericos son exhibidos para ilustrar los resultados teóricos. Key words phrases: Noncooperative games, dynamic systems, time delay, stability. Math. Subj. Class.: 91A20, 91A06. 1 Introduction Oligopoly models are the most frequently studied subjects in the literature of mathematical economics. The pioneering work of [3] is the basis of this field. His classical model has been extended by many authors, including models with product differentiation, multi-product, labor-managed oligopolies, rent-seeking games to mention a few. A comprehensive summary of single-product models is given in [6] their multi-product extensions are presented discussed in [7] including the existence uniqueness of static equilibria the asymptotic behavior of dynamic oligopolies. In both static dynamic models the inverse dem function relates the dem price of the same time period, however in many cases the dem for a good in one period will have an effect on the dem price of the goods in later time periods. In the case of durable goods the market becomes saturated, even in the case of non-durable goods the dem for consumption of the goods in earlier periods will lead to taste or habit formation of consumers that will affect future dems. Intertemporal dem interaction has been considered by many authors in analyzing international trade see for example, [4] [9]. More recently [8] have developed a two-stage oligopoly examined the existence uniqueness of the Nash equilibrium. In this paper we will examine the continuous counterpart of the model of [8]. After the dynamic model is introduced, the asymptotic behavior of the equilibrium will be analyzed. We will show that under realistic conditions the equilibrium is always locally asymptotically stable. We will also show that this stability might be lost when the firms have only delayed information about the outputs of the competitors about the dem interaction. 2 The Mathematical Model An n-firm single-product oligopoly is considered without product differentiation. Let x k be the output of firm k let C k x k be the cost of this firm. It is assumed that the effect of market saturation, taste habit formation, etc. of earlier time periods are represented by a time-

3 CUBO Dynamic Oligopolies Intertemporal Dem Interaction 87 dependent variable Q, which is assumed to be driven by the dynamic rule n Q = H x k, Q, 2.1 where H is a given bivariate function. It is also assumed that the price function depends on both the total production level of the industry Q. Hence the profit of firm k can be formulated as Π k = x k f x k + S k, Q C k x k 2.2 where S k = l =k x l. If L k denotes the capacity limit of firm k, then 0 x k L k 0 S k l =k L l. The common domain of functions H f is [0, n L k] R +, the domain of the cost function C k is [0, L k ]. Assume that H is continuously differentiable, f C k are twice continuously differentiable on their entire domains. With any fixed values of S k [0, l =k L l] Q 0, the best response of firm k is R k S k, Q = arg max {x k fx k + S k, Q C k x k }, x k L k which exists since Π k is continuous in x k the feasible set for x k is a compact set. As it is usual in oligopoly theory we make the following additional assumptions: A f x < 0; B f x + x k f xx 0; C f x C k < 0 for all k feasible x k, S k Q. Under these assumptions Π k is strictly concave in x k, so the best response of each firm is unique can be obtained as follows: 0 if fs k, Q C k 0 0 R k S k, Q = L k if L k f x L k + S k, Q + fl k + S k, Q C k L k otherwise, x k where x k is the unique solution of equation fx k + S k, Q + x k f x x k + S k, Q C k x k = in interval 0, L k.

4 88 Carl Chiarella Ferenc Szidarovszky CUBO If we assume that at each time period each firm adjusts its output into the direction towards its best response, then the resulting dynamism becomes ẋ k = K k R k S k, Q x k k = 1, 2,, n, 2.6 where K k is the speed of adjustment of firm k, if we add the dynamic equation 2.1 to these differential equations, an n + 1-dimensional dynamic system is obtained. Clearly, x 1,, x n, Q is a steady state of this system if only if n H x k, Q = x k = R k l =k x l, Q 2.8 for all k. The asymptotic behavior of the steady states will be examined in the next section. 3 Stability Analysis Assume that x 1,, x N, Q is an interior steady state, that is, both f l =k x l, Q C k0 L k f x L k + l =k x l, Q + fl k + l =k x l, Q C k L k are nonzero for all k. If x k = 0 or x k = L k, then clearly both R k S k R k Q are equal to zero. Otherwise these derivatives can be obtained by implicitly differentiating equation 2.5 with respect to S k Q: Assumptions B C imply that if we assume that r k = R k = S k f x + x kf xx 2f x + x k f xx C k 3.1 r k = R k Q = f Q + x kf xq 2f x + x kf xx C. 3.2 k 1 < r k 0, 3.3 D f Q + x kf xq 0

5 CUBO Dynamic Oligopolies Intertemporal Dem Interaction 89 for all k feasible x k, S k Q, then r k Notice that relations hold for all interior steady states. where The Jacobian of system given by the differential equations has the special form K 1 K 1 r 1 K 1 r 1 K 1 r 1 K 2 r 2 K 2 K 2 r 2 K 2 r 2 J =.... K n r n K n r n K n K n r n h h h h h = H x The main result of this section is the following. h = H Q. Theorem 1 Assume that at the steady state, h 0 r k h rk h > 0 for all k. Then the steady state is locally asymptotically stable. Proof. We will prove that the eigenvalues of J have negative real parts at the steady state. The eigenvalue equation of J can be written as K k u k + K k r k u l + K k r k v = λu k 1 k n 3.5 l =k Let U = n u k, then from 3.6, n h u k + hv = λv. 3.6 hu = λ hv. Assume first that h = 0. Then the eigenvalues of J are h the eigenvalues of matrix K 1 K 1 r 1 K 1 r 1 K 2 r 2 K 2 K 2 r K n r n K n r n K n Notice that this matrix is the Jacobian of continuous classical Cournot dynamics it is wellknown that its eigenvalues have negative real parts if K k > 0 1 < r k 0 for all k see for example, [1]. In this case the assumptions of the theorem imply that h < 0, so all eigenvalues of J have negative real parts.

6 90 Carl Chiarella Ferenc Szidarovszky CUBO Assume next that h 0. Then from 3.6, U = λ h v, 3.7 h from 3.5, u k = K kr k U + K k r k v λ + K k 1 + r k = K kr k λ h + K k r k h v. 3.8 λ + K k 1 + r k h By adding these equations for all values of k using 3.7 we have n K k r k λ + K k r k h r k h λ + K k 1 + r k since v 0, otherwise 3.8 would imply that u k = 0 for all k. = λ h, 3.9 Assume next that λ = A + ib is a root of equation 3.9 with A 0. Let gλ denote the left h side of this equation. Then Re gλ = Re K kr k A + r k h r k h + ikk r k B A + K k 1 + r k + ib = K kr k A + r k h r k ha + Kk 1 + r k + K k r k B 2 A + K k 1 + r k 2 + B 2 < 0 Re λ h = A h 0, which is an obvious contradiction. The conditions of the theorem are satisfied in the special model of [7, section 5.4] on oligopolies with saturated markets, where the dynamic rule of Q is assumed to be linear, Q = n x k C Q with some C > 0. In this case h = 1 h = C, so h 0 r k h rk h = Cr k r k > 0 unless r k = r k = 0. 4 The Effect of Delayed Information In this section, we assume that the conditions of Theorem 1 hold, the firms have only delayed information on their own outputs as well as on the output of the rest of the industry. It is also assumed that they have also delayed information on the value of parameter Q. A similar situation occurs when the firms react to average past information rather than reacting to sudden market

7 CUBO Dynamic Oligopolies Intertemporal Dem Interaction 91 changes. As in [2] we assume continuously distributed time lags, will use weighting functions of the form { 1 t s T e T if m = 0 wt s, T, m = m t s m e t sm T if m 1 1 m m T where T > 0 is a real m 0 is an integer parameter. The main properties the applications of such weighting functions are discussed in detail in [2]. By replacing the delayed quantities by their expectations, equations 2.6 become a set of Volterra-type integro-differential equations: ẋ k t = K k R k t 0 t 0 wt s, T k, m k l =k x l sds, wt s, V k, l k x k sds t 0 wt s, U k, p k Qsds 1 k n 4.2 accompanied by equation 2.1. It is well-known that equations 4.2 are equivalent to a higher dimensional system of ordinary differential equations, so all tools known from the stability theory of ordinary differential equations can be used here. Linearizing equation 4.2 around the steady state we have ẋ kδ = K k r k + r k t 0 t 0 wt s, T k, m k l =k x lδ sds wt s, U k, p k Q δ sds t 0 wt s, V k, l k x kδ sds where x kδ Q δ are deviations of x k Q from their steady state levels. We seek the solution in the form x kδ t = u k e λt Q δ = ve λt, then we substitute these into equation 4.3 let t. The resulting equation will have the form λ + K k 1 + λv lk +1 k u k + K k r k 1 + λt mk +1 k u l c k a k l =k + K k r k 1 + λu pk +1 k v = b k 4.3 where { 1 if m k = 0 a k = m k otherwise, { 1 if p k = 0 b k = p k otherwise, { 1 if l k = 0 c k = l k otherwise,

8 92 Carl Chiarella Ferenc Szidarovszky CUBO we use the identity 0 ws, T, me λs ds = Linearizing equation 2.1 around the steady state we have Q δ t = h { 1 + λt 1 if m = λt m+1 m if m 1. n x kδ t + hq δ t 4.5 by substituting x kδ t = u k e λt Q δ = ve λt into this equation we have For the sake of simplicity introduce the notation A k λ = λ + K k 1 + λv lk +1 k, h n u k + h λv = c k B k λ = K k r k 1 + λt mk +1 k, a k then equation 4.4 can be rewritten as C k λ = K k r k 1 + λu pk +1 k, b k A k λu k + B k λ l =k u l + C k λv = 0 1 k n. 4.7 Equations 4.7,4.6 have nontrival solution if only if A 1 λ B 1 λ B 1 λ C 1 λ B 2 λ A 2 λ B 2 λ C 2 λ det.... = B n λ B n λ A n λ C n λ h h h h λ Assume first that h = 0. Then the conditions of Theorem 1 imply that h < 0. The eigenvalues are therefore λ = h, which is negative, the roots of equation A 1 λ B 1 λ B 1 λ B 2 λ A 2 λ B 2 λ det... = B n λ B n λ A n λ

9 CUBO Dynamic Oligopolies Intertemporal Dem Interaction 93 By introducing D = diag A 1 λ B 1 λ,, A n λ B n λ,1 = 1,, 1 this equation can be rewritten as b = B 1 λ,..., B n λ, detd + b 1 = detddeti + D 1 b 1 [ ] n n B k λ = A k λ B k λ 1 = A k λ + B k λ Therefore in this case we have to examine the locations of the roots of equations A k λ + B k λ = 0 1 k n 4.11 n B k λ A k λ + B k λ = Assume next that h 0 A k λ + B k λ 0. By introducing the new variable U = n u k, equation 4.7 can be rewritten as B k λu = By combining this equation with 4.6 we have A k λ + B k λ u k C k λv. u k = hc kλ + B k λλ h h A k λ + B k λ v, 4.13 where we assume that the denominator is nonzero. Adding this equation for all values of k using 4.6 again we see that n hc k λ + B k λλ h A k λ + B k λ = λ h Here we also used the fact that v 0, since otherwise u k would be zero for all k from equation 4.13, eigenvectors must be nonzero. Notice first that in the absence of information lags T k = U k = V k = 0 for all k, in this special case equation 4.14 reduces to 3.9 as it should. The analysis of the roots of equations 4.11, in the general case requires the use of computer methods, however in the case of symmetric firms special lag structures analytic results can be obtained. Assume

10 94 Carl Chiarella Ferenc Szidarovszky CUBO symmetric firms with identical cost functions, same initial outputs, identical time lags speeds of adjustment. Then the firms also have identical trajectories, A k λ Aλ, B k λ Bλ, C k λ Cλ therefore u k u. Because of this symmetry equations become Aλ + n 1Bλ u + Cλv = nhu + h λv = If h = 0, then from the conditions of Theorem 1 we know that h < 0. Equation 4.16 implies that in this case either λ = h or v = 0. In the first case this eigenvalue is negative, which cannot destroy stability. In the second case u 0 equation 4.15 implies that If h 0, then Aλ + n 1Bλ = u = h λ nh v 4.18 by substituting this relation into equation 4.15 we get a single equation for v: Aλ + n 1Bλ h λ + Cλ v = nh Notice that v 0, otherwise from 4.18 u = 0 would follow eigenvectors must be nonzero. Therefore we have the following equation: nhcλ + n 1Bλλ h Aλλ h = 0. Notice first that in the case of h = 0 this equation reduces to 4.17 λ = h. Note next that this equation can be rewritten as the polynomial equation λλ h 1 + λt a m λu b + λ hk 1 + λt a nhk r 1 + λt a p λv c m λu b m λv c n 1λ hkr 1 + λu b l+1 l+1 p+1 p λv c l+1 =

11 CUBO Dynamic Oligopolies Intertemporal Dem Interaction No information lag Assume first that there is no information lag. Then T = U = V = 0, equation 4.20 specializes as which is quadratic, λλ h + λ hk nhk r n 1λ hkr = 0 λ 2 + λ h + K n 1Kr + hk nhk r + n 1 hkr = Under the conditions of Theorem 1, all coefficients are positive. Therefore the roots have negative real parts. We have already proved this fact in Theorem 1 in the more general case. 4.2 Time lag in Q Assume next that there is no time lag in the outputs but there is time lag in assessing the value of Q. Then T = V = 0, if p = 0, then equation 4.20 becomes λλ h1 + λu + λ hk1 + λu nhk r n 1λ hkr1 + λu = 0 or λ 3 U + λ UK h nkr + Kr + λ h + K nkr + Kr + U K h + nkr h Kr h + hkr Knr h rh = Under the conditions of Theorem 1, all coefficients are positive. By applying the Routh Hurwitz criterion all roots have negative real parts if only if [ h + K1 U h 1 n 1r ][ 1 U h + UK 1 n 1r ] > U hk 1 n 1r Knh r, 4.23 which is a quadratic inequality in U. By introducing the notation z = 1 n 1r > 0 it can be written as U 2 K hz h Kz + U h Kz 2 + Knh r + h + Kz > 0, 4.24 where the leading coefficient is nonnegative the constant term is positive. We have to consider next the following cases: Case 1. If h 0, then 4.24 holds for all U > 0, since all coefficients are positive.

12 96 Carl Chiarella Ferenc Szidarovszky CUBO Case 2. Assume next that h > 0. If r h Kz 2 Knh then the linear coefficient is also nonnegative, so 4.24 holds for all U > 0. If r < h Kz 2 Knh then the linear coefficient of 4.24 is negative. We have now the following subcases. A Assume first that h = 0. Then the conditions of Theorem 1 imply that r < 0 h > 0. In this special case 4.24 becomes linear, so it holds if only if U < The stability region in the r, U space is illustrated in Figure 1.,, Kz Kz 2 + Knh r Figure 1: Stability region in the r, U space for h = 0 B Assume next that h 0, then h < 0. The discriminant of 4.24 is zero, if r = r = Kz h 2 2Kz h K hz Knh In this case 4.24 has a real positive root U, the equilibrium is locally asymptotically stable if U U. If r > r, then the discriminant is negative, 4.24 has no real roots, so it is satisfied for all U, that is, the equilibrium is locally asymptotically stable. If r < r, then the discriminant is positive, there are two real positive roots U 1 < U 2, the equilibrium is locally asymptotically stable if U < U 1 or U > U 2. The stability region in the r, U space is shown in Figure 2.

13 CUBO Dynamic Oligopolies Intertemporal Dem Interaction 97 2 Figure 2: Stability region in the r, U space for h < 0 Returning to Case A, assume that r < Kz2 Knh. Starting from a very small value of U, increase its value gradually. Until reaching the critical value U = Kz Kz 2 + Knh r, 4.27 the equilibrium is locally asymptotically stable. This stability is lost after crossing the critical value. We will next prove that at the critical value a Hopf bifurcation occurs giving the possibility of the birth of limit cycles. Notice first that since h = 0, equation 4.22 has the special form 4.23 specializes as λ 3 U + λ UKz + λkz + Knh r = 0, 4.28 Kz1 + UKz > UKnh r At the critical value this inequality becomes equality, so at the critical value 4.28 can be rewritten as 0 = λ 3 U + λ UKz + λ UKnh r 1 + UKz Knh r = λ 2 Knh r Uλ UKz 1 + UKz

14 98 Carl Chiarella Ferenc Szidarovszky CUBO so the roots are with λ 1 = 1 + UKz U α 2 = Knh r = Kz. 1 + UKz U λ 23 = ±iα So we have a negative real root a pair of pure complex roots. Select now U as the bifurcation parameter consider the eigenvalues as functions of U. By implicitly differentiating equation 4.28 with respect to U, with the notation λ = dλ du we have implying that At the critical values λ = ±iα, so with real part 3λ 2 λu + λ 3 + 2λ λ1 + UKz + λ 2 Kz + λkz = 0 λ = Re λ = λ = so all conditions of Hopf bifurcation are satisfied. λ 3 λ 2 Kz 3λ 2 U + 2λ1 + UKz + Kz. ±iα 3 + α 2 Kz 2α 2 U ± 2αi1 + UKz 2α 4 4α 4 U 2 + 4α UKz 2 > The other case of h 0 can be examined in a similar way. The details are omitted. We will however illustrate this case later in a numerical study. 4.3 Time lag in S k Assume next that the firms have instantaneous information about their own outputs parameter Q, but have only delayed information about the output of the rest of the industry. In this case U = V = 0, T > 0. By assuming m = 0, equation 4.20 becomes which is again a cubic equation: λλ h1 + λt + λ hk1 + λt nhk r1 + λt n 1λ hkr = 0, 4.31 λ 3 T + λ 2 1 ht + TK + λ h + K K ht nhkt r n 1Kr + K h nhk r + n 1Kr h = 0.

15 CUBO Dynamic Oligopolies Intertemporal Dem Interaction 99 However, in contrast to the previous case there is no guarantee that the coefficients are all positive. Under the conditions of Theorem 1, the cubic quadratic coefficients are positive, the linear coefficient is positive if the constant term is positive if nhkt r < h + Kz K ht 4.32 nhk r < K hz If these relations hold, then the Routh-Hurwitz stability criterion implies that the eigenvalues have negative real parts if only if 1 ht + TK h + Kz K ht nhkt r > T K hz nhk r 4.34 which can be written as a quadratic inequality of T: T 2 K h K h + nh r + T h K 2 n 1K 2 r + Kz h > We have to consider now two cases: Case 1. If h = 0, then r < 0 h > 0, so all coefficients of 4.35 are positive, so it holds for all T > 0. Notice that in this case are also satisfied, so the equilibrium is locally asymptotically stable. Case 2. If h 0, then h < 0. The linear coefficient the constant term of 4.35 are both positive, however the sign of the quadratic coefficient is indeterminate. Therefore we have to consider two subcases: A Assume first that h + nh r 0. Then the quadratic coefficient is nonnegative, so 4.35 holds for all T > 0. In this case nhkt r hkt, so 4.32 also holds. Assume first that h 0, then 4.33 is also satisfied, consequently the equilibrium is locally asymptotically stable. Assume next that h < 0, then the conditions of Theorem 1 imply that both r h are negative. Therefore nhk r K h < K h + K hn 1r = K hz, so 4.33 also holds, the equilibrium is locally asymptotically stable again. B Assume next that h + nh r > 0. In this case both h r must be negative. In this case r < h nh, 4.36 the quadratic coefficient of 4.35 is negative, therefore 4.35 has two real roots, one is positive, T, the other is negative. Clearly, 4.35 holds if T < T.

16 100 Carl Chiarella Ferenc Szidarovszky CUBO Relation 4.33 holds if under conditions , relation 4.32 holds if T < r > hz nh, 4.37 Kz h nhk r + K h = T. We will next prove that T < T, so this last condition is irrelevant for the local asymptotic stability of the equilibrium. Let pt denote the left h side of 4.35, then T < T if pt < 0. This inequality is the following: Kz h 2 h K Knh r + h which can be simplified as + Kz h [ h K 2 n 1K 2 r ] Knh r + h + Kz h < 0 Kz h h K + h K 2 n 1K 2 r + Knh r + h < 0. This relation is equivalent to the following: 0 > z h + nh r = h n hr + hr + nh r = h1 + r n hr h r where both terms are negative, which completes the proof. Figure 3 shows the stability region in the r, T space. The occurrence of Hopf bifurcation at the critical value T can be examined in the same way as shown before, the details are omitted, however a numerical study of his case will be presented in the next section. 5 Numerical Examples We will examine next a special case of the oligopoly model of [7] with saturated markets. It is assumed that n Q = x k αq with some 0 < α < 1, the market price the cost functions are linear: n n f x k, Q = A x k + βq C k x k = c k x k k = 1, 2,...,n.

17 CUBO Dynamic Oligopolies Intertemporal Dem Interaction 101 Figure 3: Stability region in the r, T space for h < 0 In this case the best response of firm k is R k S k, Q = S k βq + A c k. 2 We also assume that K k K c k c. It is easy to see that h = 1, h = α, r = 1 2, r = β 2 z = 1 n = n Assume U > 0, T = V = 0 as in subsection 4.2. From case 2B we know that the equilibrium is locally asymptotically stable if 2 Kn+1 r > r 2 + α + 2 Kn+1 Kαn α 2 =. Kn If r = r, then it is locally asymptotically stable if Kαn+1 U U 2 2 = = Kαz Kαn + 1, if r < r, then the equilibrium is locally asymptotically stable if U < U 1 or U > U 2, where U 1 U 2 are the positive roots of the left h side of We have selected the numerical values A = 25, c = 5, α = K = z = 2 r = ,. n = 3. In this case

18 102 Carl Chiarella Ferenc Szidarovszky CUBO so if we select β > then we have two real roots of the left h side of So if β = 0.5, then it has the form with the roots so the critical values are U U = 0 U 1,2 = 5011 ± 119, U U In Figure 4, Figure 5 Figure 6 we have illustrated this phenomenon. Figure 4 shows a shrinking cycle with U = 3. Figure 5 shows the complete limit cycle with U = U 1, Figure 6 illustrates an exping cycle with U = 6. Figure 4: Shrinking cycle We will next illustrate a model with delay in the output of the rest of the industry as in subsection 4.3. Assume now the dynamic equation Q = γ n x k αq

19 CUBO Dynamic Oligopolies Intertemporal Dem Interaction 103 Figure 5: Complete cycle with positive γ α. Assume also that K k K, the price function the cost functions are the same as in the previous case, so we have h = γ, h = α, r = 1 2 r = β 2, so z = n+1 2 as before. We now assume T > 0, U = V = 0. Conditions are satisfied if β 2 < α nγ β 2 > α n+1 2 nγ, that is, 2α nγ < β < αn + 1 nγ In this case T is the positive solution of equation T 2 Kα + Knβγ 2α + T2α 2 + 4αK + K 2 n α + Kn + 1 = 0.. We have selected the numerical values A = 25, c k = 5,α = K = γ = 1 10 n = 3. The value of β has to be between , so for the sake of simplicity we have chosen β = 1. Then the quadratic equation 4.35 for T has the form T T = 0

20 104 Carl Chiarella Ferenc Szidarovszky CUBO Figure 6: Exping cycle with positive root T = With this critical value a complete limit cycle is obtained, if T < T then the limit cycle changes to a shrinking one if T > T it becomes an exping cycle. The resulting figures are very similar to those presented in the previous case, so they are not shown here. 6 Conclusions In this paper dynamic oligopolies were examined with continuous time scales intertemporal dem interaction. The effect of earlier dems consumptions were modelled by introducing an additional state variable, in an n-firm oligopoly this concept resulted in an n + 1-dimensional continuous system. The local asymptotical stability of the equilibrium has been proved under general conditions. This stability however might be lost if the firms have only delayed information on the dem interaction, on their own outputs also on the outputs of the competitors. By assuming continuously distributed time lags stability conditions were derived for important special cases in cases when instability occurs the occurrence of Hopf bifurcation was investigated giving the possibility of the birth of limit cycles. The theoretical results have been illustrated by computer studies. Received: April 21, Revised: May 09, 2008.

21 CUBO Dynamic Oligopolies Intertemporal Dem Interaction 105 References [1] Bischi, G., Chiarella, C., Kopel, M. Szidarovszky, F., Dynamic oligopolies: Stability bifurcations., Springer-Verlag, Berlin/Heidelberg/New York in press, [2] Chiarella, C. Szidarovszky, F., The birth of limit cycles in nonlinear oligopolies with continuously distributed information lags, In M. Dror, P. L Ecyer, F. Szidarovszky, editors, Modelling Uncertainty, Kluwer Academic Publishers, Dordrecht, 2001, pp [3] Cournot, A., Recherches sur les principles mathématiques de la théorie de richessess, Hachette, Paris. English translation 1960: Researches into the Mathematical Principles of the Theory of Wealth, Kelley, New York, [4] Froot, K. Klemperer, P., Exchange rate pass-through when market share matters, American Economic Review, , [5] Guckenheimer, J. Holmes, P., Nonlinear oscillations, dynamical systems bifurcations of vector fields, Springer-Verlag, Berlin/New York, [6] Okuguchi, K., Expectations stability in oligopoly models, Springer-Verlag, Berlin/Heidelberg/New York, [7] Okuguchi, K. Szidarovszky, F., The theory of oligopoly with multi-product firms. Springer-Verlag, Berlin/Heidelberg/New York, 2nd edition, [8] Okuguchi, K. Szidarovszky, F., Oligopoly with intertemporal dem interaction, Journal of Economic Research, 82003, [9] Tivig, T., Exchange rate pass-through in two-period duopoly, International Journal of Industrial Organization, ,