ON THE EXISTENCE OF HOPF BIFURCATION IN AN OPEN ECONOMY MODEL

Size: px
Start display at page:

Download "ON THE EXISTENCE OF HOPF BIFURCATION IN AN OPEN ECONOMY MODEL"

Transcription

1 Proceedings of Equadiff , pp ISBN ON THE EXISTENCE OF HOPF BIFURCATION IN AN OPEN ECONOMY MODEL KATARÍNA MAKOVÍNYIOVÁ AND RUDOLF ZIMKA Abstract. In the paper a four dimensional open economy model describing the development of output, exchange rate, interest rate and money supply is analyzed. Sufficient conditions for the existence of equilibrium stability and the existence of business cycles are found. Formulae for the calculation of bifurcation coefficients are derived. Key words. dynamical model, equilibrium, stability, bifurcation, cycles AMS subject classifications. 37Gxx 1. Introduction. In economic theory there are many macroeconomic models describing the development of output Y in an economy. The majority of them are based on the well-known IS-LM model. One of them is the Schinasi s model (see [5]) describing the development of output Y, interest rate R and money supply L s in a closed economy. In [8] the Schinasi s model was extended to an open economy model of the kind Ẏ = α [ I(Y, R) + G + X(ρ) S(Y D, R) T (Y ) M(Y, ρ) ] ρ = β [M(Y, ρ) + C x (R) X(ρ) C m (R)] Ṙ = γ [L(Y, R) L S ] L S = G + M(Y, ρ) + C x (R) T (Y ) X(ρ) C m (R), (1.1) where Y output, ρ exchange rate, R interest rate, L S money supply, I investments, S savings, G government expenditures, T tax collections, X export, M import, C x capital export, C m capital import, L money demand, α, β, γ positive parameters, t time and Y D = Y T (Y ), Ẏ = dy dt, dρ ρ = dt, Ṙ = dr dt, L S = dl S dt. The economic properties of the functions in (1.1) are expressed by the following partial derivatives: I(Y, R) I(Y, R) T (Y ) X(ρ) ρ C x (R) C m (R) S(Y D, R) M(Y, ρ) L(Y, R) S(Y D, R) M(Y, ρ) ρ L(Y, R) < 0. (1.) Department of Mathematics and Descriptive Geometry, Faculty of Wood Sciences and Technology, Technical university Zvolen, Zvolen, Slovakia (kmakovin@vsld.tuzvo.sk). Department of Quantitative Methods and Informatics, Faculty of Economics, Matej Bel University, Banská Bystrica, Slovakia (rudolf.zimka@umb.sk). 9

2 30 K. Makovínyiová and R. Zimka The development of Y, ρ, R and L S in the model (1.1) in a neighborhood of its equilibrium was studied under fixed exchange rate regime in [6] and under flexible exchange rate regime in [] from the point of equilibrium stability and the existence of business cycles. In [4] this model was analyzed under assumption that both ρ and R are flexible. In the paper [4] the assertion on the existence of business cycles was formulated under assumption of the existence of the Liapunov bifurcation constant a. In the present paper a formula for the calculation of this Liapunov bifurcation constant a is found supposing that the functions I(Y, R) and S(Y D, R) are nonlinear with respect to Y and linear with respect to R, and other functions in (1.1) are linear with respect to all their variables except government expenditures G, which are constant. In the end of the paper an example illustrating the achieved results is presented.. Analysis of the model (1.1). Using denotation the model (1.1) has the form B(Y, R) = I(Y, R) S(Y D, R) C(R) = C m (R) C x (R) D(Y ) = G T (Y ) F (Y, ρ) = X(ρ) M(Y, ρ), Ẏ = α [B(Y, R) + D(Y ) + F (Y, ρ)] ρ = β [F (Y, ρ) + C(R)] Ṙ = γ [L(Y, R) L S ] L S = D(Y ) F (Y, ρ) C(R), (.1) where on the base of (1.) B(Y, R) C(R) D(Y ) F (Y, ρ) F (Y, ρ) ρ and the sign of B(Y,R) can be positive or negative or zero according to the properties of I(Y, R) and S(Y D, R). Assume: 1. The functions I(Y, R), S(Y D, R), T (Y ), C(R), D(Y ), F (Y, ρ), L(Y, R) are of the kind I(Y, R) = i 0 + i 1 Y i3 R, C(R) = c 0 + c 3 R, S(Y D, R) = s 0 + s 1 (Y D ) + s 3 R, D(Y ) = d 0 d 1 Y, Y D = Y T (Y ), F (Y, ρ) = f 0 f 1 Y + f ρ, T (Y ) = t 0 + t 1 Y, L(Y, R) = l 0 + l 1 Y l 3 R, with positive coefficients i 1, i 3, s 1, s 3, t 1, c 3, d 1, f 1, f, l 1, l 3.. The model (.1) has an isolated equilibrium E = (Y, ρ, R, L S ), Y ρ R L S > 0. Remark 1. A sufficient condition for the existence of an isolated equilibrium E of the model (.1) was presented in [4]. Consider an isolated equilibrium E = (Y, ρ, R, L S ) of (.1). After the transformation Y 1 = Y Y, ρ 1 = ρ ρ, R 1 = R R, L S 1 = L S L S,

3 Equadiff-11. On the existence of Hopf bifurcation in an open economy model 31 the equilibrium E goes into the origin E1 = (Y1 = 0, ρ 1 = 0, R1 = 0, L S 1 = 0) and the model (.1) takes the form Ẏ 1 = α [B(Y 1 + Y, R 1 + R ) + D(Y 1 + Y ) + F (Y 1 + Y, ρ 1 + ρ )] ρ 1 = β [F (Y 1 + Y, ρ 1 + ρ ) + C(R 1 + R )] Ṙ 1 = γ [L(Y 1 + Y, R 1 + R ) L S 1 L S 1 ] L S 1 = D(Y 1 + Y ) F (Y 1 + Y, ρ 1 + ρ ) C(R 1 + R ). (.) Performing Taylor expansion of the functions on the right-hand side in (.) at the equilibrium E1 we get the model [ 4 ] Ẏ 1 = α [(b 1 d 1 f 1 )Y 1 + f ρ 1 b 3 R 1 ] + α a k Y1 k + O( Y 1 5 ) ρ 1 = β (f 1 Y 1 f ρ 1 c 3 R 1 ) Ṙ 1 = γ (l 1 Y 1 l 3 R 1 L S 1 ) L S 1 = (f 1 d 1 )Y 1 f ρ 1 c 3 R 1, k= (.3) where b 1 = B(Y,R ), b 3 = i 3 + s 3, a k = k B(Y,R ), k =, 3, 4. k The linear approximation matrix of (.3) is α(b 1 d 1 f 1 ) αf αb 3 0 A(α, β, γ) = βf 1 βf βc 3 0 γl 1 0 γl 3 γ. (.4) f 1 d 1 f c 3 0 The characteristic equation of A(α, β, γ) is λ 4 + a 1 (α, β, γ)λ 3 + a (α, β, γ)λ + a 3 (α, β, γ)λ + a 4 (α, β, γ) = 0, (.5) where a 1 = α( b 1 + d 1 + f 1 ) + βf + γl 3, a = γc 3 + βγf l 3 + α(βf ( b 1 + d 1 ) + γ(b 3 l 1 + l 3 ( b 1 + d 1 + f 1 ))), a 3 = αγ(βf (l 1 (b 3 + c 3 ) + l 3 ( b 1 + d 1 )) c 3 ( b 1 + d 1 + f 1 ) b 3 (f 1 d 1 )), a 4 = αβγd 1 f (b 3 + c 3 ). As we are interested in equilibrium stability and in the existence of cycles in the model (.3) it is suitable to find such values of parameters α, β, γ at which the equation (.5) has a pair of purely imaginary eigenvalues λ 1 = iω, λ = iω, and the rest two eigenvalues λ 3, λ 4 are negative or have negative real parts. We shall call such values of parameters α, β, γ as critical values of the model (.3) and denote them α 0, β 0, γ 0. Mentioned types of eigenvalues are ensured by the Liu s conditions ([3]): a 1 a a 3 a 4 (.6) 3 = (a 1 a a 3 )a 3 a 1 a 4 = 0. (.7)

4 3 K. Makovínyiová and R. Zimka The conditions (.6) are satisfied if b 1 + d 1 0, α > α = c 3 l 3 ( b 1 + d 1 + f 1 ) + b 3 l 1, ( b 1 + d 1 + f 1 )c 3 + (f 1 d 1 )b 3 < 0. The relation (.7) can be expressed in the form [ ] a (1) (β, γ)β + a () γ α + where in the power of (.8) there is [ b (1) (β, γ)β + b () (γ)γ a () = ( b 1 + d 1 + f 1 )[b 3 (f 1 d 1 ) ] α + c (1) (β, γ)β + c () γ = 0, +c 3 ( b 1 + d 1 + f 1 )][ b 3 l 1 l 3 ( b 1 + d 1 + f 1 )] c () = c 3 l 3 [b 3 (f 1 d 1 ) + c 3 ( b 1 + d 1 + f 1 )] < 0. Take γ at any positive level and denote it γ 0. Then a () γ 0 > 0 and c () γ 0 < 0. Denote A(β) = a (1) (β, γ 0 )β + a () γ 0, B(β) = b (1) (β, γ 0 )β + b () (γ 0 )γ 0, C(β) = c (1) (β, γ 0 )β + c () γ 0. (.8) Take β such small that A(β) > 0 and C(β) < 0. Denote this β as β 0. Then the equation A(β 0 )α + B(β 0 )α + C(β 0 ) = 0 has two roots α 1, = B(β 0) ± { (B(β 0 )) 4A(β 0 )C(β 0 ) α1 < 0 = A(β 0 ) α > 0, and the function 3 (α) = A(β 0 )α + B(β 0 )α + C(β 0 ) has the following form (Fig..1): Fig..1. Denote α = α 0. The triple (α 0, β 0, γ 0 ) is the critical triple of the model (.3). Thus for given specific values of β 0, γ 0 it is always possible to find such a value α 0 that the condition (.7) is satisfied. From Figure 1 we get in a small neighborhood of α 0 : If α > α 0 then 3 (α) = (a 1 a a 3 )a 3 a1 a 4 > 0. If α < α 0 then 3 (α) = (a 1 a a 3 )a 3 a1 a 4 < 0. (.9) If α = α 0 then 3 (α) = (a 1 a a 3 )a 3 a1 a 4 = 0.

5 Equadiff-11. On the existence of Hopf bifurcation in an open economy model 33 Consider a critical triple (α 0, β 0, γ 0 ) of the model (.3). Further we shall investigate the behavior of Y 1, ρ 1, R 1 and L S1 around the equilibrium E 1 with respect to parameter α, α (α 0 ε, α 0 + ε), ε and fixed parameters β = β 0, γ = γ 0. Performed considerations enable us to answer the question about the stability of the equilibrium E 1 of the model (.3) in a small neighborhood of the critical value α 0. Theorem 1. Let the conditions (.8) be satisfied and let (α 0, β 0, γ 0 ) be such a critical triple of the model (.3) that A(β 0 ) > 0 and C(β 0 ) < 0. Then: 1. If α 0 α then at every α > α the equilibrium E 1 is asymptotically stable.. If α 0 > α then at every α > α 0 the equilibrium E 1 is asymptotically stable and at every α < α < α 0 the equilibrium E 1 is unstable. Proof. The conditions (.8) guarantee that a 1 a a 3 and a 4 > 0 what together with (.9) at α > α α 0 means that the Routh-Hurwitz necessary and sufficient conditions for all the roots of the equation (.5) to have negative real parts ( 1 (α) > 0, (α) 3 (α) 4 (α) > 0) are satisfied. If α < α < α 0 then 3 (α) < 0 what means that the Routh-Hurwitz conditions are not satisfied. To gain the bifurcation equation of the model (.3) it is suitable to transform (.3) to its partial normal form on invariant surface. After the shift of α 0 into the origin by relation α 1 = α α 0 the model (.3) takes the form Ẏ 1 = α 0 [(b 1 d 1 f 1 )Y 1 + f ρ 1 b 3 R 1 ] + (b 1 d 1 f 1 )Y 1 α f ρ 1 α 1 b 3 R 1 α 1 + α 0 a k Y1 k + α 1 a k Y1 k + O( Y 1 5 ) k= ρ 1 = β 0 (f 1 Y 1 f ρ 1 c 3 R 1 ) Ṙ 1 = γ 0 (l 1 Y 1 l 3 R 1 L S 1 ) L S 1 = (f 1 d 1 )Y 1 f ρ 1 c 3 R 1. k= (.10) Consider the matrix M which transfers the matrix A(α 0, β 0, γ 0 ) into its Jordan form J. Then the transformation x = My, x = (Y 1, ρ 1, R 1, L S1 ) T, y = (Y, ρ, R, L S ) T takes the model (.10) into the model Ẏ = λ 1 Y + F 1 (Y, ρ, R, L S, α 1 ) ρ = λ ρ + F (Y, ρ, R, L S, α 1 ) Ṙ = λ 3 R + F 3 (Y, ρ, R, L S, α 1 ) L S = λ 4 L S + F 4 (Y, ρ, R, L S, α 1 ), (.11) where ρ = Y, F = F 1, and F 3, F 4 are real (the symbol - means complex conjugate expression in the whole article; for the sake of simplicity we suppose that λ 3, λ 4 are real and not equal). Theorem. There exists a polynomial transformation Y = Y 3 + h 1 (Y 3, ρ 3, α 1 ) ρ = ρ 3 + h (Y 3, ρ 3, α 1 ) R = R 3 + h 3 (Y 3, ρ 3, α 1 ) L S = L S3 + h 4 (Y 3, ρ 3, α 1 ), (.1)

6 34 K. Makovínyiová and R. Zimka where h j (Y 3, ρ 3, α 1 ), j = 1,, 3, 4, are nonlinear polynomials with constant coefficients of the kind h j (Y 3, ρ 3, α 1 ) = ν (m1,m,m3) Y m1 3 ρ m 3 α m3 1, j = 1,, 3, 4, h = h 1, m 1,m,m 3 with the property h j ( α 1 Y 3, α 1 ρ 3, α 1 ) = m 1,m,m 3 ν (m1,m,m3) ( α 1 ) k Y m1 3 ρ m 3, k 4, which transforms the model (.11) into its partial normal form on invariant surface Ẏ 3 = λ 1 Y 3 +δ 1 Y 3 α 1 +δ Y 3 ρ 3 +U (Y 3, ρ 3, R 3, L S3, α 1 )+U (Y 3, ρ 3, R 3, L S3, α 1 ) ρ 3 = λ ρ 3 + δ 1 ρ 3 α 1 + δ Y 3 ρ 3 + U + U Ṙ 3 = λ 3 R 3 + V (Y 3, ρ 3, R 3, L S3, α 1 ) + V (Y 3, ρ 3, R 3, L S3, α 1 ) L S 3 = λ 4 L S3 + W (Y 3, ρ 3, R 3, L S3, α 1 ) + W (Y 3, ρ 3, R 3, L S3, α 1 ), (.13) where U (Y 3, ρ 3, 0, 0, α 1 ) = V (Y 3, ρ 3, 0, 0, α 1 ) = W (Y 3, ρ 3, 0, 0, α 1 ) = 0 and U ( α 1 Y 3, α 1 ρ 3, α 1 R 3, α 1 L S3,α 1 )=V ( α 1 Y 3, α 1 ρ 3, α 1 R 3, α 1 L S3,α 1 ) = W ( α 1 Y 3, α 1 ρ 3, α 1 R 3, α 1 L S3, α 1 ) = O( α 1 ) 5. The resonant terms δ 1 and δ in the model (.13) are determined by the formulae δ 1 = F 1 α 1, δ = 1 λ F 1 F F 1 ρ 6λ 1 ρ F + 1 λ 1 F 1 ρ F ρ 1 λ 3 F 1 F 3 ρ + 1 F 1 F 3 (λ 1 λ 3 ) ρ 1 F 1 F 4 1 F 1 F 4 + λ 4 Ls ρ (λ 1 λ 4 ) ρ Ls F 1 ρ, where all derivatives in δ 1 and δ are calculated at E 1 and α 1 = 0. Proof. Differentiating (.1) in the power of (.11) and (.13) we get the equations for the determination of the individual terms of the polynomials h j, j = 1,, 3, 4, and the resonant terms δ 1, δ by standard step by step procedure. As the whole record of this procedure is rather long we are omitting it. The model (.13) takes in polar coordinates Y 3 = re iϕ, ρ 3 = re iϕ the form ṙ = r(ar + bα 1 ) + Ũ (r, ϕ, R 3, L S3, α 1 ) + Ũ (r, ϕ, R 3, L S3, α 1 ) ϕ = ω + cα 1 + dr + 1 r [Φ (r, ϕ, R 3, L S3, α 1 ) + Φ (r, ϕ, R 3, L S3, α 1 )] Ṙ 3 = λ 3 R 3 + Ṽ 1 (r, ϕ, R 3, L S3, α 1 ) + Ṽ 1 (r, ϕ, R 3, L S3, α 1 ) L S 3 = λ 4 L S3 + W 1 (r, ϕ, R 3, L S3, α 1 ) + W 1 (r, ϕ, R 3, L S3, α 1 ), (.14) where a = Re δ, b = Re δ 1.

7 Equadiff-11. On the existence of Hopf bifurcation in an open economy model 35 The behavior of solutions of the model (.14) around its equilibrium for small parameters α 1 depends on the signs of the constants a, b. It is known that to every constant solution of the bifurcation equation ar +bα 1 = 0 a periodic solution of (.14) corresponds (see for example [1]). The following theorem ([4]) gives a sufficient condition for the negativeness of the coefficient b. Theorem 3. Let the assumptions of Theorem 1 be satisfied. Let in addition α 0 > α and the critical value β 0 be such that c 3 β 0 f l 3 > 0. Then the value of the coefficient b is negative. Analyzing the model (.14) and taking into account all transformations which have been done to get (.14) we can formulate on the base of Poincaré-Andronov-Hopf bifurcation theorem (see for example [7]) the following statement. Theorem 4. Let the assumptions of Theorem 1 be satisfied. Let in addition α 0 > α and the critical value β 0 be such that c 3 β 0 f l 3 > 0. Then: 1. If a > 0 then the equilibrium E 1 of the model (.3) is unstable also at the critical triple (α 0, β 0, γ 0 ) and to every α > α 0 there exists an unstable limit cycle.. If a < 0 then the equilibrium E 1 of the model (.3) is asymptotically stable also at the critical triple (α 0, β 0, γ 0 ) and to every α < α < α 0 there exists a stable limit cycle..1. Numerical example. Take the functions I, S, T, C, D, F, L from the model (1.1) in the form I = Y 0.3R, S = (Y D ) + 0.3R, Y D = 0.7Y + 0., T = Y, C = R, D =.7 0.3Y, F = Y ρ, L = + 0.8Y 0.R. Then (1.1) has the following form [ Ẏ = α 0.6 ] Y 0.01(0.7Y + 0.) 0.35Y ρ 0.6R ρ = β ( 0.05Y ρ + 0.R 0.576) Ṙ = γ (0.8Y 0.R L S + ) L S = 0.5Y 0.03ρ 0.R (.15) The equilibrium of (.15) is E = (Y = 9, ρ = , R = , L S = ), where the values of Y and L S are taken in 10 milliards. After the transformation of E into the origin and Taylor expansion the model (.15) has the form Ẏ 1 = α( 0.341Y ρ 1 0.6R 1 ) [ + α Y Y ] 9331 Y O( Y 1 5 ) ρ 1 = β (0.05Y ρ 1 0.R 1 ) Ṙ 1 = γ (0.8Y 1 0.R 1 L S 1 ) L S 1 = 0.5Y ρ 1 0.R 1. (.16)

8 36 K. Makovínyiová and R. Zimka The matrix of linear approximation of this model is A(α, β, γ) = 0.341α 0.03α 0.6α β 0.03β 0.β 0 0.8γ 0 0.γ γ = The eigenval- Take β 0 = 1, γ 0 = 1. Then α 0 = 5( ) ues of the matrix A(α 0, β 0, γ 0 ) are. λ 1. = i, λ. = i, λ3. = , λ4. = The formulae for the calculation of the resonant constants δ 1 and δ, which are introduced in Theorem, give the values The bifurcation coefficients are δ 1. = i, δ. = i. a = Re δ. = 0.000, b = Re δ1. = , and the partial normal form of the model (.16) on invariant surface for critical triple (α 0, β 0, γ 0 ) = (0.6774, 1, 1) in polar coordinates is ṙ = r(0.000r α 1 ) + Ũ (r, ϕ, R 3, L S3, α 1 ) + Ũ (r, ϕ, R 3, L S3, α 1 ) ϕ = α r + 1 r [Φ + Φ ] Ṙ 3 = R 3 + Ṽ 1 (r, ϕ, R 3, L S3, α 1 ) + Ṽ 1 (r, ϕ, R 3, L S3, α 1 ) L S 3 = 0.086L S3 + W 1 (r, ϕ, R 3, L S3, α 1 ) + W 1 (r, ϕ, R 3, L S3, α 1 ). The value of α from (.8) is α. = On the base of the values a and b we get. the following result: To every value of parameter α > α 0 = the equilibrium of the model (.15) is asymptotically stable and there exists an unstable limit cycle. To every value of parameter α (0.3648, ) this equilibrium is unstable. REFERENCES [1] Yu. N. Bibikov, Multi-frequency non-linear oscillations and their bifurcations, The Publishing House of the Saint Petersburg University, Saint Petersburg, 1991, (in Russian). [] P. Fellnerová and R. Zimka, On Stability and Fluctuations in Open Economy Model under Flexible Exchange Rate Regime, Prace Naukowe Akademii Ekonomicznej we Wroclawiu, 1036 (004), [3] W. M. Liu, Criterion of Hopf Bifurcations without using Eigenvalues, Journal of Mathematical Analysis and Applications, 18 (1994), [4] K. Makovínyiová and R. Zimka, On Fluctuations in an Open Economy Model, Proceeding of the 7 th International conference Applications of Mathematics and Statistics in Economy, University of Economics Prague, Faculty of Informatics and Statistics, Professional Publishing, Prague (004), [5] G. J. Schinasi, Fluctuations in a Dynamic, Intermediate-Run IS-LM Model: Applications of the Poincaré-Bendixon Theorem, Journal of Economics Theory, 8 (198), [6] L. Striežovská and R. Zimka, Cycles in an Open Economy Model under Fixed Exchange Rate Regime with Pure Money Financing, Operations Research and Decisions, Quarterly 3 4, Wroclaw (00), [7] S. Wiggins, Introduction to Applied Nonlinear Dynamical Systems and Chaos, Springer-Verlag, Berlin, [8] E. Zimková and R. Zimka, The Stability of an Open Economy Model, Mundus Symbolicus 10, Economic University, Prague (00),

Dynamic IS-LM model with Philips Curve and International Trade

Dynamic IS-LM model with Philips Curve and International Trade Journal of Mathematics and System Science 6 (2016) 147-158 doi: 10.17265/2159-5291/2016.04.003 D DAVID PUBLISHING Dynamic IS-LM model with Philips Curve and International Trade Michiya Nozaki Gifu Keizai

More information

ASYMPTOTIC BEHAVIOUR AND HOPF BIFURCATION OF A THREE-DIMENSIONAL NONLINEAR AUTONOMOUS SYSTEM

ASYMPTOTIC BEHAVIOUR AND HOPF BIFURCATION OF A THREE-DIMENSIONAL NONLINEAR AUTONOMOUS SYSTEM Georgian Mathematical Journal Volume 9 (), Number, 7 6 ASYMPTOTIC BEHAVIOUR AND HOPF BIFURCATION OF A THREE-DIMENSIONAL NONLINEAR AUTONOMOUS SYSTEM LENKA BARÁKOVÁ Abstract. A three-dimensional real nonlinear

More information

Solutions to Dynamical Systems 2010 exam. Each question is worth 25 marks.

Solutions to Dynamical Systems 2010 exam. Each question is worth 25 marks. Solutions to Dynamical Systems exam Each question is worth marks [Unseen] Consider the following st order differential equation: dy dt Xy yy 4 a Find and classify all the fixed points of Hence draw the

More information

Nonlinear IS-LM Model with Tax Collection*

Nonlinear IS-LM Model with Tax Collection* $ /$ 1899 2014 47-55 47 Nonlinear IS-LM Model with Tax Collection* Akio Matsumoto Department of Economics Chuo University 1 Introduction Since the pioneering work of Kalecki (1933) the seminal work of

More information

5.2.2 Planar Andronov-Hopf bifurcation

5.2.2 Planar Andronov-Hopf bifurcation 138 CHAPTER 5. LOCAL BIFURCATION THEORY 5.. Planar Andronov-Hopf bifurcation What happens if a planar system has an equilibrium x = x 0 at some parameter value α = α 0 with eigenvalues λ 1, = ±iω 0, ω

More information

Dynamical Systems. Pierre N.V. Tu. An Introduction with Applications in Economics and Biology Second Revised and Enlarged Edition.

Dynamical Systems. Pierre N.V. Tu. An Introduction with Applications in Economics and Biology Second Revised and Enlarged Edition. Pierre N.V. Tu Dynamical Systems An Introduction with Applications in Economics and Biology Second Revised and Enlarged Edition With 105 Figures Springer-Verlag Berlin Heidelberg New York London Paris

More information

APPPHYS217 Tuesday 25 May 2010

APPPHYS217 Tuesday 25 May 2010 APPPHYS7 Tuesday 5 May Our aim today is to take a brief tour of some topics in nonlinear dynamics. Some good references include: [Perko] Lawrence Perko Differential Equations and Dynamical Systems (Springer-Verlag

More information

BIFURCATION DIAGRAM OF A CUBIC THREE-PARAMETER AUTONOMOUS SYSTEM

BIFURCATION DIAGRAM OF A CUBIC THREE-PARAMETER AUTONOMOUS SYSTEM Electronic Journal of Differential Equations, Vol. 2005(2005), No. 8, pp. 1 16. ISSN: 1072-6691. URL: http://ejde.math.txstate.edu or http://ejde.math.unt.edu ftp ejde.math.txstate.edu (login: ftp) BIFURCATION

More information

Some notes on the structure of limit sets in IS-LM models

Some notes on the structure of limit sets in IS-LM models Available online at www.sciencedirect.com Scienceirect Procedia - Social and Behavioral Scien ce s 08 ( 04 ) 60 69 AIRO Winter 0 Some notes on the structure of limit sets in IS-LM models Giovanni Bella

More information

Masanori Yokoo. 1 Introduction

Masanori Yokoo. 1 Introduction Masanori Yokoo Abstract In many standard undergraduate textbooks of macroeconomics, open economies are discussed by means of the Mundell Fleming model, an open macroeconomic version of the IS LM model.

More information

The Foley Liquidity / Profit-Rate Cycle Model Reconsidered

The Foley Liquidity / Profit-Rate Cycle Model Reconsidered MPRA Munich Personal RePEc Archive The Foley Liquidity / Profit-Rate Cycle Model Reconsidered Helmar Nunes Moreira and Ricardo Azevedo Araujo and Peter Flaschel Department of Mathematics, University of

More information

FLUCTUATIONS IN A MIXED IS-LM BUSINESS CYCLE MODEL

FLUCTUATIONS IN A MIXED IS-LM BUSINESS CYCLE MODEL Electronic Journal of Differential Equations, Vol. 2008(2008), No. 134, pp. 1 9. ISSN: 1072-6691. URL: http://ejde.math.txstate.edu or http://ejde.math.unt.edu ftp ejde.math.txstate.edu (login: ftp) FLUCTUATIONS

More information

Linearized geometric dynamics of Tobin-Benhabib-Miyao economic flow

Linearized geometric dynamics of Tobin-Benhabib-Miyao economic flow Linearized geometric dynamics of Tobin-Benhabib-Miyao economic flow Constantin Udrişte and Armando Ciancio Abstract The aim of this paper is to study the influence of the Euclidean-Lagrangian structure

More information

Lotka Volterra Predator-Prey Model with a Predating Scavenger

Lotka Volterra Predator-Prey Model with a Predating Scavenger Lotka Volterra Predator-Prey Model with a Predating Scavenger Monica Pescitelli Georgia College December 13, 2013 Abstract The classic Lotka Volterra equations are used to model the population dynamics

More information

The Fractional-order SIR and SIRS Epidemic Models with Variable Population Size

The Fractional-order SIR and SIRS Epidemic Models with Variable Population Size Math. Sci. Lett. 2, No. 3, 195-200 (2013) 195 Mathematical Sciences Letters An International Journal http://dx.doi.org/10.12785/msl/020308 The Fractional-order SIR and SIRS Epidemic Models with Variable

More information

(8.51) ẋ = A(λ)x + F(x, λ), where λ lr, the matrix A(λ) and function F(x, λ) are C k -functions with k 1,

(8.51) ẋ = A(λ)x + F(x, λ), where λ lr, the matrix A(λ) and function F(x, λ) are C k -functions with k 1, 2.8.7. Poincaré-Andronov-Hopf Bifurcation. In the previous section, we have given a rather detailed method for determining the periodic orbits of a two dimensional system which is the perturbation of a

More information

= F ( x; µ) (1) where x is a 2-dimensional vector, µ is a parameter, and F :

= F ( x; µ) (1) where x is a 2-dimensional vector, µ is a parameter, and F : 1 Bifurcations Richard Bertram Department of Mathematics and Programs in Neuroscience and Molecular Biophysics Florida State University Tallahassee, Florida 32306 A bifurcation is a qualitative change

More information

TWELVE LIMIT CYCLES IN A CUBIC ORDER PLANAR SYSTEM WITH Z 2 -SYMMETRY. P. Yu 1,2 and M. Han 1

TWELVE LIMIT CYCLES IN A CUBIC ORDER PLANAR SYSTEM WITH Z 2 -SYMMETRY. P. Yu 1,2 and M. Han 1 COMMUNICATIONS ON Website: http://aimsciences.org PURE AND APPLIED ANALYSIS Volume 3, Number 3, September 2004 pp. 515 526 TWELVE LIMIT CYCLES IN A CUBIC ORDER PLANAR SYSTEM WITH Z 2 -SYMMETRY P. Yu 1,2

More information

Relationships between phases of business cycles in two large open economies

Relationships between phases of business cycles in two large open economies Journal of Regional Development Studies2010 131 Relationships between phases of business cycles in two large open economies Ken-ichi ISHIYAMA 1. Introduction We have observed large increases in trade and

More information

Chapter 2 Hopf Bifurcation and Normal Form Computation

Chapter 2 Hopf Bifurcation and Normal Form Computation Chapter 2 Hopf Bifurcation and Normal Form Computation In this chapter, we discuss the computation of normal forms. First we present a general approach which combines center manifold theory with computation

More information

On the convergence of normal forms for analytic control systems

On the convergence of normal forms for analytic control systems Chapter 1 On the convergence of normal forms for analytic control systems Wei Kang Department of Mathematics, Naval Postgraduate School Monterey, CA 93943 wkang@nps.navy.mil Arthur J. Krener Department

More information

The Invariant Curve in a Planar System of Difference Equations

The Invariant Curve in a Planar System of Difference Equations Advances in Dynamical Systems and Applications ISSN 0973-5321, Volume 13, Number 1, pp. 59 71 2018 http://campus.mst.edu/adsa The Invariant Curve in a Planar System of Difference Equations Senada Kalabušić,

More information

Production, Capital Stock and Price Dynamics in A Simple Model of Closed Economy *

Production, Capital Stock and Price Dynamics in A Simple Model of Closed Economy * Production, Capital Stoc and Price Dynamics in Simple Model of Closed Economy * Jan Kodera 1,, Miloslav Vosvrda 1 1 Institute of Information Theory, Dept. of Econometrics, cademy of Sciences of the Czech

More information

UNIVERSITY of LIMERICK

UNIVERSITY of LIMERICK UNIVERSITY of LIMERICK OLLSCOIL LUIMNIGH Faculty of Science and Engineering Department of Mathematics & Statistics END OF SEMESTER ASSESSMENT PAPER MODULE CODE: MS08 SEMESTER: Spring 0 MODULE TITLE: Dynamical

More information

2 The model with Kaldor-Pasinetti saving

2 The model with Kaldor-Pasinetti saving Applied Mathematical Sciences, Vol 6, 2012, no 72, 3569-3573 The Solow-Swan Model with Kaldor-Pasinetti Saving and Time Delay Luca Guerrini Department of Mathematics for Economic and Social Sciences University

More information

There is a more global concept that is related to this circle of ideas that we discuss somewhat informally. Namely, a region R R n with a (smooth)

There is a more global concept that is related to this circle of ideas that we discuss somewhat informally. Namely, a region R R n with a (smooth) 82 Introduction Liapunov Functions Besides the Liapunov spectral theorem, there is another basic method of proving stability that is a generalization of the energy method we have seen in the introductory

More information

Andronov Hopf and Bautin bifurcation in a tritrophic food chain model with Holling functional response types IV and II

Andronov Hopf and Bautin bifurcation in a tritrophic food chain model with Holling functional response types IV and II Electronic Journal of Qualitative Theory of Differential Equations 018 No 78 1 7; https://doiorg/10143/ejqtde018178 wwwmathu-szegedhu/ejqtde/ Andronov Hopf and Bautin bifurcation in a tritrophic food chain

More information

EE222 - Spring 16 - Lecture 2 Notes 1

EE222 - Spring 16 - Lecture 2 Notes 1 EE222 - Spring 16 - Lecture 2 Notes 1 Murat Arcak January 21 2016 1 Licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License. Essentially Nonlinear Phenomena Continued

More information

Dynamical systems tutorial. Gregor Schöner, INI, RUB

Dynamical systems tutorial. Gregor Schöner, INI, RUB Dynamical systems tutorial Gregor Schöner, INI, RUB Dynamical systems: Tutorial the word dynamics time-varying measures range of a quantity forces causing/accounting for movement => dynamical systems dynamical

More information

Bifurcation and Stability Analysis of a Prey-predator System with a Reserved Area

Bifurcation and Stability Analysis of a Prey-predator System with a Reserved Area ISSN 746-733, England, UK World Journal of Modelling and Simulation Vol. 8 ( No. 4, pp. 85-9 Bifurcation and Stability Analysis of a Prey-predator System with a Reserved Area Debasis Mukherjee Department

More information

STABILITY. Phase portraits and local stability

STABILITY. Phase portraits and local stability MAS271 Methods for differential equations Dr. R. Jain STABILITY Phase portraits and local stability We are interested in system of ordinary differential equations of the form ẋ = f(x, y), ẏ = g(x, y),

More information

AN AK TIME TO BUILD GROWTH MODEL

AN AK TIME TO BUILD GROWTH MODEL International Journal of Pure and Applied Mathematics Volume 78 No. 7 2012, 1005-1009 ISSN: 1311-8080 (printed version) url: http://www.ijpam.eu PA ijpam.eu AN AK TIME TO BUILD GROWTH MODEL Luca Guerrini

More information

investment M. R. Grasselli EPOG Seminar Paris Nord, November 18, 2016

investment M. R. Grasselli EPOG Seminar Paris Nord, November 18, 2016 Mathematics and Statistics, McMaster University Joint A. Nguyen Huu (Montpellier) EPOG Seminar Paris Nord, November 18, 2016 Cycles Small fraction of output (about 1% in the U.S.) but major fraction of

More information

2 Lecture 2: Amplitude equations and Hopf bifurcations

2 Lecture 2: Amplitude equations and Hopf bifurcations Lecture : Amplitude equations and Hopf bifurcations This lecture completes the brief discussion of steady-state bifurcations by discussing vector fields that describe the dynamics near a bifurcation. From

More information

Introduction to Applied Nonlinear Dynamical Systems and Chaos

Introduction to Applied Nonlinear Dynamical Systems and Chaos Stephen Wiggins Introduction to Applied Nonlinear Dynamical Systems and Chaos Second Edition With 250 Figures 4jj Springer I Series Preface v L I Preface to the Second Edition vii Introduction 1 1 Equilibrium

More information

CHAOTIC BEHAVIOR IN A TWO-DIMENSIONAL BUSINESS CYCLE MODEL

CHAOTIC BEHAVIOR IN A TWO-DIMENSIONAL BUSINESS CYCLE MODEL CHAOTIC BEHAVIOR IN A TWO-DIMENSIONAL BUSINESS CYCLE MODEL CRISTINA JANUÁRIO Department of Chemistry, Mathematics Unit, Instituto Superior de Engenharia de Lisboa, Rua Conselheiro Emídio Navarro, 1949-014

More information

Hamad Talibi Alaoui and Radouane Yafia. 1. Generalities and the Reduced System

Hamad Talibi Alaoui and Radouane Yafia. 1. Generalities and the Reduced System FACTA UNIVERSITATIS (NIŠ) Ser. Math. Inform. Vol. 22, No. 1 (27), pp. 21 32 SUPERCRITICAL HOPF BIFURCATION IN DELAY DIFFERENTIAL EQUATIONS AN ELEMENTARY PROOF OF EXCHANGE OF STABILITY Hamad Talibi Alaoui

More information

Complicated behavior of dynamical systems. Mathematical methods and computer experiments.

Complicated behavior of dynamical systems. Mathematical methods and computer experiments. Complicated behavior of dynamical systems. Mathematical methods and computer experiments. Kuznetsov N.V. 1, Leonov G.A. 1, and Seledzhi S.M. 1 St.Petersburg State University Universitetsky pr. 28 198504

More information

EC744 Lecture Notes: Economic Dynamics. Prof. Jianjun Miao

EC744 Lecture Notes: Economic Dynamics. Prof. Jianjun Miao EC744 Lecture Notes: Economic Dynamics Prof. Jianjun Miao 1 Deterministic Dynamic System State vector x t 2 R n State transition function x t = g x 0 ; t; ; x 0 = x 0 ; parameter 2 R p A parametrized dynamic

More information

Problem Set Number 5, j/2.036j MIT (Fall 2014)

Problem Set Number 5, j/2.036j MIT (Fall 2014) Problem Set Number 5, 18.385j/2.036j MIT (Fall 2014) Rodolfo R. Rosales (MIT, Math. Dept.,Cambridge, MA 02139) Due Fri., October 24, 2014. October 17, 2014 1 Large µ limit for Liénard system #03 Statement:

More information

BIFURCATION PHENOMENA Lecture 4: Bifurcations in n-dimensional ODEs

BIFURCATION PHENOMENA Lecture 4: Bifurcations in n-dimensional ODEs BIFURCATION PHENOMENA Lecture 4: Bifurcations in n-dimensional ODEs Yuri A. Kuznetsov August, 2010 Contents 1. Solutions and orbits: equilibria cycles connecting orbits compact invariant manifolds strange

More information

A Note on the Ramsey Growth Model with the von Bertalanffy Population Law

A Note on the Ramsey Growth Model with the von Bertalanffy Population Law Applied Mathematical Sciences, Vol 4, 2010, no 65, 3233-3238 A Note on the Ramsey Growth Model with the von Bertalanffy Population aw uca Guerrini Department of Mathematics for Economic and Social Sciences

More information

Automatic Control Systems theory overview (discrete time systems)

Automatic Control Systems theory overview (discrete time systems) Automatic Control Systems theory overview (discrete time systems) Prof. Luca Bascetta (luca.bascetta@polimi.it) Politecnico di Milano Dipartimento di Elettronica, Informazione e Bioingegneria Motivations

More information

AN EFFICIENT METHOD FOR COMPUTING THE SIMPLEST NORMAL FORMS OF VECTOR FIELDS

AN EFFICIENT METHOD FOR COMPUTING THE SIMPLEST NORMAL FORMS OF VECTOR FIELDS International Journal of Bifurcation and Chaos, Vol. 3, No. (2003) 9 46 c World Scientific Publishing Company AN EFFICIENT METHOD FOR COMPUTING THE SIMPLEST NORMAL FORMS OF VECTOR FIELDS P. YU and Y. YUAN

More information

8.385 MIT (Rosales) Hopf Bifurcations. 2 Contents Hopf bifurcation for second order scalar equations. 3. Reduction of general phase plane case to seco

8.385 MIT (Rosales) Hopf Bifurcations. 2 Contents Hopf bifurcation for second order scalar equations. 3. Reduction of general phase plane case to seco 8.385 MIT Hopf Bifurcations. Rodolfo R. Rosales Department of Mathematics Massachusetts Institute of Technology Cambridge, Massachusetts MA 239 September 25, 999 Abstract In two dimensions a Hopf bifurcation

More information

QUARTERLY OF APPLIED MATHEMATICS

QUARTERLY OF APPLIED MATHEMATICS QUARTERLY OF APPLIED MATHEMATICS Volume LIV December 1996 Number 4 DECEMBER 1996, PAGES 601-607 ON EXISTENCE OF PERIODIC ORBITS FOR THE FITZHUGH NERVE SYSTEM By S. A. TRESKOV and E. P. VOLOKITIN Institute

More information

Hopf Bifurcation of a Nonlinear System Derived from Lorenz System Using Centre Manifold Approach ABSTRACT. 1. Introduction

Hopf Bifurcation of a Nonlinear System Derived from Lorenz System Using Centre Manifold Approach ABSTRACT. 1. Introduction Malaysian Journal of Mathematical Sciences 10(S) March : 1-13 (2016) Special Issue: The 10th IMT-GT International Conference on Mathematics, Statistics and its Applications 2014 (ICMSA 2014) MALAYSIAN

More information

CONTROLLING IN BETWEEN THE LORENZ AND THE CHEN SYSTEMS

CONTROLLING IN BETWEEN THE LORENZ AND THE CHEN SYSTEMS International Journal of Bifurcation and Chaos, Vol. 12, No. 6 (22) 1417 1422 c World Scientific Publishing Company CONTROLLING IN BETWEEN THE LORENZ AND THE CHEN SYSTEMS JINHU LÜ Institute of Systems

More information

Direction and Stability of Hopf Bifurcation in a Delayed Model with Heterogeneous Fundamentalists

Direction and Stability of Hopf Bifurcation in a Delayed Model with Heterogeneous Fundamentalists International Journal of Mathematical Analysis Vol 9, 2015, no 38, 1869-1875 HIKARI Ltd, wwwm-hikaricom http://dxdoiorg/1012988/ijma201554135 Direction and Stability of Hopf Bifurcation in a Delayed Model

More information

Stability and Hopf Bifurcation for a Discrete Disease Spreading Model in Complex Networks

Stability and Hopf Bifurcation for a Discrete Disease Spreading Model in Complex Networks International Journal of Difference Equations ISSN 0973-5321, Volume 4, Number 1, pp. 155 163 (2009) http://campus.mst.edu/ijde Stability and Hopf Bifurcation for a Discrete Disease Spreading Model in

More information

Dynamical System of a Multi-Capital Growth Model

Dynamical System of a Multi-Capital Growth Model Applied Mathematical Sciences, Vol. 9, 2015, no. 83, 4103-4108 HIKARI Ltd, www.m-hikari.com http://dx.doi.org/10.12988/ams.2015.53274 Dynamical System of a Multi-Capital Growth Model Eva Brestovanská Department

More information

Routes to Complexity in a Macroeconomic Model Described by a Noninvertible Triangular Map

Routes to Complexity in a Macroeconomic Model Described by a Noninvertible Triangular Map Cubo A Mathematical Journal Vol.05/N ō 03 OCTOBER 2003 Routes to Complexity in a Macroeconomic Model Described by a Noninvertible Triangular Map Roberto Dieci Dipartimento di Studi Economici e Quantitativi,

More information

Chapter 3. Second Order Linear PDEs

Chapter 3. Second Order Linear PDEs Chapter 3. Second Order Linear PDEs 3.1 Introduction The general class of second order linear PDEs are of the form: ax, y)u xx + bx, y)u xy + cx, y)u yy + dx, y)u x + ex, y)u y + f x, y)u = gx, y). 3.1)

More information

Example of a Blue Sky Catastrophe

Example of a Blue Sky Catastrophe PUB:[SXG.TEMP]TRANS2913EL.PS 16-OCT-2001 11:08:53.21 SXG Page: 99 (1) Amer. Math. Soc. Transl. (2) Vol. 200, 2000 Example of a Blue Sky Catastrophe Nikolaĭ Gavrilov and Andrey Shilnikov To the memory of

More information

IS-LM Analysis. Math 202. Brian D. Fitzpatrick. Duke University. February 14, 2018 MATH

IS-LM Analysis. Math 202. Brian D. Fitzpatrick. Duke University. February 14, 2018 MATH IS-LM Analysis Math 202 Brian D. Fitzpatrick Duke University February 14, 2018 MATH Overview Background History Variables The GDP Equation Definition of GDP Assumptions The GDP Equation with Assumptions

More information

ZERO-HOPF BIFURCATION FOR A CLASS OF LORENZ-TYPE SYSTEMS

ZERO-HOPF BIFURCATION FOR A CLASS OF LORENZ-TYPE SYSTEMS This is a preprint of: Zero-Hopf bifurcation for a class of Lorenz-type systems, Jaume Llibre, Ernesto Pérez-Chavela, Discrete Contin. Dyn. Syst. Ser. B, vol. 19(6), 1731 1736, 214. DOI: [doi:1.3934/dcdsb.214.19.1731]

More information

Application demonstration. BifTools. Maple Package for Bifurcation Analysis in Dynamical Systems

Application demonstration. BifTools. Maple Package for Bifurcation Analysis in Dynamical Systems Application demonstration BifTools Maple Package for Bifurcation Analysis in Dynamical Systems Introduction Milen Borisov, Neli Dimitrova Department of Biomathematics Institute of Mathematics and Informatics

More information

PROJECTS on. Multiple Bifurcations of Sample Dynamical Systems

PROJECTS on. Multiple Bifurcations of Sample Dynamical Systems Course on Bifurcation Theory, a.y. 2010/11 PROJECTS on Multiple Bifurcations of Sample Dynamical Systems Students of the Bifurcation Theory course can carry out an individual homework, to be discussed

More information

Adaptive Learning and Applications in Monetary Policy. Noah Williams

Adaptive Learning and Applications in Monetary Policy. Noah Williams Adaptive Learning and Applications in Monetary Policy Noah University of Wisconsin - Madison Econ 899 Motivations J. C. Trichet: Understanding expectations formation as a process underscores the strategic

More information

Additive resonances of a controlled van der Pol-Duffing oscillator

Additive resonances of a controlled van der Pol-Duffing oscillator Additive resonances of a controlled van der Pol-Duffing oscillator This paper has been published in Journal of Sound and Vibration vol. 5 issue - 8 pp.-. J.C. Ji N. Zhang Faculty of Engineering University

More information

On Returns to Scale Assumption in Endogenous Growth

On Returns to Scale Assumption in Endogenous Growth International Journal of Sciences: Basic and Applied Research (IJSBAR) ISSN 2307-453 (Print & Online) http://gssrr.org/index.php?journaljournalofbasicandapplied ---------------------------------------------------------------------------------------------------------------------------

More information

Part A: Answer question A1 (required), plus either question A2 or A3.

Part A: Answer question A1 (required), plus either question A2 or A3. Ph.D. Core Exam -- Macroeconomics 5 January 2015 -- 8:00 am to 3:00 pm Part A: Answer question A1 (required), plus either question A2 or A3. A1 (required): Ending Quantitative Easing Now that the U.S.

More information

Hopf Bifurcation and Limit Cycle Analysis of the Rikitake System

Hopf Bifurcation and Limit Cycle Analysis of the Rikitake System ISSN 749-3889 (print), 749-3897 (online) International Journal of Nonlinear Science Vol.4(0) No.,pp.-5 Hopf Bifurcation and Limit Cycle Analysis of the Rikitake System Xuedi Wang, Tianyu Yang, Wei Xu Nonlinear

More information

EE 380. Linear Control Systems. Lecture 10

EE 380. Linear Control Systems. Lecture 10 EE 380 Linear Control Systems Lecture 10 Professor Jeffrey Schiano Department of Electrical Engineering Lecture 10. 1 Lecture 10 Topics Stability Definitions Methods for Determining Stability Lecture 10.

More information

Delay Kaldor-Kalecki Model Revisited. September 2014

Delay Kaldor-Kalecki Model Revisited. September 2014 Discussion Paper No.234 Delay Kaldor-Kalecki Model Revisited Akio Matsumoto Chuo University Ferenc Szidarovszky University of Pécs September 2014 INSTITUTE OF ECONOMIC RESEARCH Chuo University Tokyo, Japan

More information

NBA Lecture 1. Simplest bifurcations in n-dimensional ODEs. Yu.A. Kuznetsov (Utrecht University, NL) March 14, 2011

NBA Lecture 1. Simplest bifurcations in n-dimensional ODEs. Yu.A. Kuznetsov (Utrecht University, NL) March 14, 2011 NBA Lecture 1 Simplest bifurcations in n-dimensional ODEs Yu.A. Kuznetsov (Utrecht University, NL) March 14, 2011 Contents 1. Solutions and orbits: equilibria cycles connecting orbits other invariant sets

More information

ANALYSIS AND CONTROLLING OF HOPF BIFURCATION FOR CHAOTIC VAN DER POL-DUFFING SYSTEM. China

ANALYSIS AND CONTROLLING OF HOPF BIFURCATION FOR CHAOTIC VAN DER POL-DUFFING SYSTEM. China Mathematical and Computational Applications, Vol. 9, No., pp. 84-9, 4 ANALYSIS AND CONTROLLING OF HOPF BIFURCATION FOR CHAOTIC VAN DER POL-DUFFING SYSTEM Ping Cai,, Jia-Shi Tang, Zhen-Bo Li College of

More information

2D-Volterra-Lotka Modeling For 2 Species

2D-Volterra-Lotka Modeling For 2 Species Majalat Al-Ulum Al-Insaniya wat - Tatbiqiya 2D-Volterra-Lotka Modeling For 2 Species Alhashmi Darah 1 University of Almergeb Department of Mathematics Faculty of Science Zliten Libya. Abstract The purpose

More information

HJB equations. Seminar in Stochastic Modelling in Economics and Finance January 10, 2011

HJB equations. Seminar in Stochastic Modelling in Economics and Finance January 10, 2011 Department of Probability and Mathematical Statistics Faculty of Mathematics and Physics, Charles University in Prague petrasek@karlin.mff.cuni.cz Seminar in Stochastic Modelling in Economics and Finance

More information

Lyapunov Stability Theory

Lyapunov Stability Theory Lyapunov Stability Theory Peter Al Hokayem and Eduardo Gallestey March 16, 2015 1 Introduction In this lecture we consider the stability of equilibrium points of autonomous nonlinear systems, both in continuous

More information

Monotone and oscillatory solutions of a rational difference equation containing quadratic terms

Monotone and oscillatory solutions of a rational difference equation containing quadratic terms Monotone and oscillatory solutions of a rational difference equation containing quadratic terms M. Dehghan, C.M. Kent, R. Mazrooei-Sebdani N.L. Ortiz, H. Sedaghat * Department of Mathematics, Virginia

More information

Nonlinear Phillips Curves, Complex Dynamics and Monetary Policy in a Keynesian Macro Model

Nonlinear Phillips Curves, Complex Dynamics and Monetary Policy in a Keynesian Macro Model Nonlinear Phillips Curves, Complex Dynamics and Monetary Policy in a Keynesian Macro Model Carl Chiarella School of Finance and Economics, University of Technology, Sydney, Australia Peter Flaschel Faculty

More information

Phase Synchronization

Phase Synchronization Phase Synchronization Lecture by: Zhibin Guo Notes by: Xiang Fan May 10, 2016 1 Introduction For any mode or fluctuation, we always have where S(x, t) is phase. If a mode amplitude satisfies ϕ k = ϕ k

More information

Assignment #5. 1 Keynesian Cross. Econ 302: Intermediate Macroeconomics. December 2, 2009

Assignment #5. 1 Keynesian Cross. Econ 302: Intermediate Macroeconomics. December 2, 2009 Assignment #5 Econ 0: Intermediate Macroeconomics December, 009 Keynesian Cross Consider a closed economy. Consumption function: C = C + M C(Y T ) () In addition, suppose that planned investment expenditure

More information

AUTOMATIC CONTROL. Andrea M. Zanchettin, PhD Spring Semester, Introduction to Automatic Control & Linear systems (time domain)

AUTOMATIC CONTROL. Andrea M. Zanchettin, PhD Spring Semester, Introduction to Automatic Control & Linear systems (time domain) 1 AUTOMATIC CONTROL Andrea M. Zanchettin, PhD Spring Semester, 2018 Introduction to Automatic Control & Linear systems (time domain) 2 What is automatic control? From Wikipedia Control theory is an interdisciplinary

More information

Solutions for B8b (Nonlinear Systems) Fake Past Exam (TT 10)

Solutions for B8b (Nonlinear Systems) Fake Past Exam (TT 10) Solutions for B8b (Nonlinear Systems) Fake Past Exam (TT 10) Mason A. Porter 15/05/2010 1 Question 1 i. (6 points) Define a saddle-node bifurcation and show that the first order system dx dt = r x e x

More information

Research Article Hopf Bifurcation Analysis and Anticontrol of Hopf Circles of the Rössler-Like System

Research Article Hopf Bifurcation Analysis and Anticontrol of Hopf Circles of the Rössler-Like System Abstract and Applied Analysis Volume, Article ID 3487, 6 pages doi:.55//3487 Research Article Hopf Bifurcation Analysis and Anticontrol of Hopf Circles of the Rössler-Like System Ranchao Wu and Xiang Li

More information

Analysis of the Takens-Bogdanov bifurcation on m parameterized vector fields

Analysis of the Takens-Bogdanov bifurcation on m parameterized vector fields Analysis of the Takens-Bogdanov bifurcation on m parameterized vector fields Francisco Armando Carrillo Navarro, Fernando Verduzco G., Joaquín Delgado F. Programa de Doctorado en Ciencias (Matemáticas),

More information

Introduction to Nonlinear Control Lecture # 3 Time-Varying and Perturbed Systems

Introduction to Nonlinear Control Lecture # 3 Time-Varying and Perturbed Systems p. 1/5 Introduction to Nonlinear Control Lecture # 3 Time-Varying and Perturbed Systems p. 2/5 Time-varying Systems ẋ = f(t, x) f(t, x) is piecewise continuous in t and locally Lipschitz in x for all t

More information

1. < 0: the eigenvalues are real and have opposite signs; the fixed point is a saddle point

1. < 0: the eigenvalues are real and have opposite signs; the fixed point is a saddle point Solving a Linear System τ = trace(a) = a + d = λ 1 + λ 2 λ 1,2 = τ± = det(a) = ad bc = λ 1 λ 2 Classification of Fixed Points τ 2 4 1. < 0: the eigenvalues are real and have opposite signs; the fixed point

More information

Theoretical premises of the Keynesian approach

Theoretical premises of the Keynesian approach origin of Keynesian approach to Growth can be traced back to an article written after the General Theory (1936) Roy Harrod, An Essay in Dynamic Theory, Economic Journal, 1939 Theoretical premises of the

More information

11 Chaos in Continuous Dynamical Systems.

11 Chaos in Continuous Dynamical Systems. 11 CHAOS IN CONTINUOUS DYNAMICAL SYSTEMS. 47 11 Chaos in Continuous Dynamical Systems. Let s consider a system of differential equations given by where x(t) : R R and f : R R. ẋ = f(x), The linearization

More information

Mathematical Foundations of Neuroscience - Lecture 7. Bifurcations II.

Mathematical Foundations of Neuroscience - Lecture 7. Bifurcations II. Mathematical Foundations of Neuroscience - Lecture 7. Bifurcations II. Filip Piękniewski Faculty of Mathematics and Computer Science, Nicolaus Copernicus University, Toruń, Poland Winter 2009/2010 Filip

More information

Technical appendices: Business cycle accounting for the Japanese economy using the parameterized expectations algorithm

Technical appendices: Business cycle accounting for the Japanese economy using the parameterized expectations algorithm Technical appendices: Business cycle accounting for the Japanese economy using the parameterized expectations algorithm Masaru Inaba November 26, 2007 Introduction. Inaba (2007a) apply the parameterized

More information

HOPF BIFURCATION WITH S 3 -SYMMETRY

HOPF BIFURCATION WITH S 3 -SYMMETRY PORTUGALIAE MATHEMATICA Vol. 63 Fasc. 006 Nova Série HOPF BIFURCATION WITH S 3 -SYMMETRY Ana Paula S. Dias and Rui C. Paiva Recommended by José Basto-Gonçalves Abstract: The aim of this paper is to study

More information

Lecture 5. Outline: Limit Cycles. Definition and examples How to rule out limit cycles. Poincare-Bendixson theorem Hopf bifurcations Poincare maps

Lecture 5. Outline: Limit Cycles. Definition and examples How to rule out limit cycles. Poincare-Bendixson theorem Hopf bifurcations Poincare maps Lecture 5 Outline: Limit Cycles Definition and examples How to rule out limit cycles Gradient systems Liapunov functions Dulacs criterion Poincare-Bendixson theorem Hopf bifurcations Poincare maps Limit

More information

ECON0702: Mathematical Methods in Economics

ECON0702: Mathematical Methods in Economics ECON0702: Mathematical Methods in Economics Yulei Luo SEF of HKU January 14, 2009 Luo, Y. (SEF of HKU) MME January 14, 2009 1 / 44 Comparative Statics and The Concept of Derivative Comparative Statics

More information

Research Article A Dynamic Economic Model with Discrete Time and Consumer Sentiment

Research Article A Dynamic Economic Model with Discrete Time and Consumer Sentiment Hindawi Publishing Corporation Discrete Dynamics in Nature and Society Volume 2009, Article ID 509561, 18 pages doi:10.1155/2009/509561 Research Article A Dynamic Economic Model with Discrete Time and

More information

A modification of Kaldor-Kalecki model and its analysis

A modification of Kaldor-Kalecki model and its analysis A modification of Kaldor-Kalecki model and its analysis 1 Introduction Jan Kodera 1, Jarmila Radová 2, Tran Van Quang 1 Abstract. This paper studies the investment cycle as an endogenous phenomenon using

More information

Dynamical Systems in Neuroscience: Elementary Bifurcations

Dynamical Systems in Neuroscience: Elementary Bifurcations Dynamical Systems in Neuroscience: Elementary Bifurcations Foris Kuang May 2017 1 Contents 1 Introduction 3 2 Definitions 3 3 Hodgkin-Huxley Model 3 4 Morris-Lecar Model 4 5 Stability 5 5.1 Linear ODE..............................................

More information

(a) Write down the Hamilton-Jacobi-Bellman (HJB) Equation in the dynamic programming

(a) Write down the Hamilton-Jacobi-Bellman (HJB) Equation in the dynamic programming 1. Government Purchases and Endogenous Growth Consider the following endogenous growth model with government purchases (G) in continuous time. Government purchases enhance production, and the production

More information

Hopf bifurcations analysis of a three-dimensional nonlinear system

Hopf bifurcations analysis of a three-dimensional nonlinear system BULETINUL ACADEMIEI DE ŞTIINŢE A REPUBLICII MOLDOVA. MATEMATICA Number 358), 28, Pages 57 66 ISSN 124 7696 Hopf bifurcations analysis of a three-dimensional nonlinear system Mircea Craioveanu, Gheorghe

More information

A two-sector Keynesian model of business cycles

A two-sector Keynesian model of business cycles Discussion Paper No.281 A two-sector Keynesian model of business cycles Hiroki Murakami Faculty of Economics, Chuo University July 2017 INSIUE OF ECONOMIC RESEARCH Chuo University okyo, Japan A two-sector

More information

LIMIT CYCLES COMING FROM THE PERTURBATION OF 2-DIMENSIONAL CENTERS OF VECTOR FIELDS IN R 3

LIMIT CYCLES COMING FROM THE PERTURBATION OF 2-DIMENSIONAL CENTERS OF VECTOR FIELDS IN R 3 Dynamic Systems and Applications 17 (28 625-636 LIMIT CYCLES COMING FROM THE PERTURBATION OF 2-DIMENSIONAL CENTERS OF VECTOR FIELDS IN R 3 JAUME LLIBRE, JIANG YU, AND XIANG ZHANG Departament de Matemàtiques,

More information

Counting Roots of the Characteristic Equation for Linear Delay-Differential Systems

Counting Roots of the Characteristic Equation for Linear Delay-Differential Systems journal of differential equations 136, 222235 (1997) article no. DE963127 Counting Roots of the Characteristic Equation for Linear Delay-Differential Systems B. D. Hassard* Department of Mathematics, SUNY

More information

BIFURCATION PHENOMENA Lecture 1: Qualitative theory of planar ODEs

BIFURCATION PHENOMENA Lecture 1: Qualitative theory of planar ODEs BIFURCATION PHENOMENA Lecture 1: Qualitative theory of planar ODEs Yuri A. Kuznetsov August, 2010 Contents 1. Solutions and orbits. 2. Equilibria. 3. Periodic orbits and limit cycles. 4. Homoclinic orbits.

More information

Extended IS-LM model - construction and analysis of behavior

Extended IS-LM model - construction and analysis of behavior Extended IS-LM model - construction and analysis of behavior David Martinčík Department of Economics and Finance, Faculty of Economics, University of West Bohemia, martinci@kef.zcu.cz Blanka Šedivá Department

More information

Exercises for Chapter 7

Exercises for Chapter 7 Exercises for Chapter 7 Exercise 7.1 The following simple macroeconomic model has four equations relating government policy variables to aggregate income and investment. Aggregate income equals consumption

More information

Two-Country Model. Masato Nakao. Graduate School of Economics, Chuo University. Abstract

Two-Country Model. Masato Nakao. Graduate School of Economics, Chuo University. Abstract Theoretical Analysis of the Effect of Fiscal Union: Keynesian Two-Country Model Masato Nakao Graduate School of Economics, Chuo University Abstract In this paper, we investigate the effect of fiscal union

More information

Nonlinear stability of steady flow of Giesekus viscoelastic fluid

Nonlinear stability of steady flow of Giesekus viscoelastic fluid Nonlinear stability of steady flow of Giesekus viscoelastic fluid Mark Dostalík, V. Průša, K. Tůma August 9, 2018 Faculty of Mathematics and Physics, Charles University Table of contents 1. Introduction

More information