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Impact of Financial Crisis on Economic Growth: A Stochastic Model

  • Calvin Tadmon ORCID logo and Eric Rostand Njike Tchaptchet EMAIL logo
Published/Copyright: February 24, 2022
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Abstract

In this paper, we develop a stochastic model to analyze how financial contagion may affect economic activity. In the deterministic case, we show that, according to specific parameter values, the economy may converge either to a stress-free equilibrium or to a stressed equilibrium: in the former situation, the level of economic growth is maximal, while in the latter, it is reduced by financial contagion. In the stochastic case, we compute a value around which the level of economic growth oscillates. Numerical simulations are performed to illustrate theoretical results obtained.

MSC 2010: 91B62; 91G30; 60H10

A Appendix

Proof of Proposition 3.1

(i) Let t 0 . From the second equation of (3.2), we have

y ( t ) = y ( 0 ) exp ( 0 t ( θ x ( s ) + μ y ( s ) - ( ξ + b + μ ) ) d s ) > 0 .

From the first equation of (3.2) and the positivity of y ( t ) , we get

x ( t ) = x ( 0 ) exp ( 0 t ( b + ( θ - μ ) y ( s ) ) d s ) + 0 t ( b + ξ y ( s ) ) exp ( t s ( b + ( θ - μ ) y ( u ) ) d u ) d s > 0 .

From the third equation of (3.2), we have

k ( t ) = k ( 0 ) exp ( 0 t ( λ 0 ( 1 - y ( s ) ) τ k α - 1 ( s ) - ( δ 0 + p ) ) d s ) > 0 .

(ii) Since x ( t ) and y ( t ) are positive and x ( t ) + y ( t ) = 1 , then 0 x ( t ) 1 and 0 y ( t ) 1 . From the positivity of k ( t ) and the third equation of (3.2), we have

( 1 - α ) k - α ( t ) k ˙ ( t ) = ( 1 - α ) λ 0 ( 1 - y ( t ) ) τ - ( 1 - α ) ( δ 0 + p ) k 1 - α ( t ) .

That is,

(A.1) d d t ( k 1 - α ( t ) ) = ( 1 - α ) λ 0 ( 1 - y ( t ) ) τ - ( 1 - α ) ( δ 0 + p ) k 1 - α ( t ) .

Since 0 y ( t ) 1 , (A.1) becomes

d d t ( k 1 - α ( t ) ) ( 1 - α ) λ 0 - ( 1 - α ) ( δ 0 + p ) k 1 - α ( t ) .

Thus, using the standard comparison theorem [19], we obtain

k 1 - α ( t ) λ 0 δ 0 + p + ( k 1 - α ( 0 ) - λ 0 δ 0 + p ) e - ( δ 0 + p ) t

and if k ( 0 ) ( λ 0 δ 0 + p ) 1 1 - α ,

(A.2) lim sup t k 1 - α ( t ) λ 0 δ 0 + p .

From (A.2), we deduce that k ( t ) ( λ 0 δ 0 + p ) 1 1 - α . ∎

Proof of Proposition 3.2

Consider the function Φ defined from R 3 to R 3 by

Φ ( x , y , k ) = ( b ( 1 - x ) - ( θ - μ ) x y + ξ y θ x y - ( ξ + μ + b ) y + μ y 2 λ 0 ( 1 - y ) τ k α - ( δ 0 + p ) k ) .

The function Φ is a continuously differentiable on R 3 ; hence it is locally Lipschitz. From the Cauchy–Lipschitz theorem [22], problem (3.2) admits a unique local solution. From Proposition 3.1, the solution is contained in a compact subset of R 3 and therefore is globally defined. ∎

Proof of Proposition 3.3

Since x ( t ) + y ( t ) = 1 , x ( t ) = 1 - y ( t ) and system (3.2) is equivalent to the following system:

(A.3) { y ˙ ( t ) = y ( t ) ( 1 - y ( t ) ) ( a + θ - g ) - ( ξ + b ) y ( t ) , k ˙ ( t ) = λ 0 ( 1 - y ( t ) ) τ k α ( t ) - ( δ 0 + p ) k ( t ) ,

( y , k ) is an equilibrium of system (A.3) if and only if ( 1 - y , y , k ) is an equilibrium of system (3.2).

A point ( y , k ) is an equilibrium of system (A.3) if it is a solution of the following system of algebraic equations:

(A.4) { y ( 1 - y ) ( a + θ - g ) - ( ξ + b ) y = 0 , λ 0 ( 1 - y ) τ k α - ( δ 0 + p ) k = 0 .

From the first equation of (A.3), we have

y ( 1 - y ) ( a + θ - g ) - ( ξ + b ) y = 0 y = 0 or y = θ - μ - ξ - b θ - μ .

If y = 0 , then x = 1 , and from the second equation of (A.4), we obtain k = ( λ 0 δ 0 + p ) 1 1 - α . If θ > ξ + μ + b , then y = θ - μ - ξ - b θ - μ is a valid solution of (A.4), i.e. 0 < θ - μ - ξ - b θ - μ < 1 . Hence

x = 1 - θ - μ - ξ - b θ - μ = ξ + b θ - μ ,

and from the second equation of (A.4), we obtain

k = ( λ 0 δ 0 + p ) 1 1 - α ( ξ + b θ - μ ) τ 1 - α .

Proof of Proposition 3.4

The first line of (A.3) is an equation with separable variables. After few transformations, it becomes

(A.5) d y ( t ) ( 1 y ( t ) + θ - μ ( - ( θ - μ ) y ( t ) + ( θ - μ - ξ - b ) ) ) = ( θ - μ - ξ - b ) d t .

Solving (A.5) gives

(A.6) y ( t ) = ( θ - μ - ξ - b ) A e ( θ - μ - ξ - b ) t 1 + ( θ - μ ) A e ( θ - μ - ξ - b ) t ,

where 𝐴 is a constant positive real number.

(i) If θ ξ + μ + b , taking the limit as 𝑡 tends to ∞ on both sides of (A.6) yields

lim t y ( t ) = lim t ( θ - μ - ξ - b ) A e ( θ - μ - ξ - b ) t 1 + ( θ - μ ) A e ( θ - μ - ξ - b ) t = 0 .

That is, whatever the initial condition y ( 0 ) is, the solution y ( t ) converges to zero as 𝑡 tends to ∞. Therefore, as x ( t ) = 1 - y ( t ) , we have lim t x ( t ) = 1 .

Since y ( t ) converges to 0 as 𝑡 tends to ∞, for all ϵ > 0 sufficiently small, there exists a real number M > 0 such that, for all t > M ,

(A.7) - ϵ - y ( t ) ϵ .

From the second equation of (A.3) and the second inequality of (A.7), we obtain

(A.8) k ˙ ( t ) = λ 0 ( 1 - y ( t ) ) τ k α ( t ) - ( δ 0 + p ) k ( t ) λ 0 ( 1 + ϵ ) τ k α ( t ) - ( δ 0 + p ) k ( t ) .

Using the nonnegativity of k ( t ) and (A.8), we get

(A.9) d k 1 - α ( t ) d t λ 0 ( 1 + ϵ ) τ - ( δ 0 + p ) k 1 - α ( t ) .

By the comparison theorem [19], (A.9) yields

k 1 - α ( t ) k 0 1 - α e - ( 1 - α ) ( δ 0 + p ) t + λ 0 ( 1 + ϵ ) τ δ 0 + p ( 1 - e - ( 1 - α ) ( δ 0 + p ) t ) .

Thus,

(A.10) lim sup t k 1 - α ( t ) λ 0 ( 1 + ϵ ) τ δ 0 + p .

From the arbitrariness of 𝜖, we deduce from (A.10) that

(A.11) lim sup t k 1 - α ( t ) λ 0 δ 0 + p .

Using once more the second equation of (A.3) and the first inequality of (A.7), we obtain

k ˙ ( t ) = λ 0 ( 1 - y ( t ) ) τ k α ( t ) - ( δ 0 + p ) k ( t ) λ 0 ( 1 - ϵ ) τ k α ( t ) - ( δ 0 + p ) k ( t ) .

Using the positivity of k ( t ) and the comparison theorem [19], we deduce that

(A.12) lim inf t k 1 - α ( t ) λ 0 ( 1 - ϵ ) τ δ 0 + p .

Thus, from the arbitrariness of 𝜖, we deduce from (A.12) that

(A.13) lim inf t k 1 - α ( t ) λ 0 δ 0 + p .

It then follows from (A.11) and (A.13) that

lim inf t k 1 - α ( t ) λ 0 δ 0 + p lim sup t k 1 - α ( t ) .

This lets us infer that

lim t k 1 - α ( t ) = λ 0 δ 0 + p .

That is, lim t k ( t ) = ( λ 0 δ 0 + p ) 1 1 - α .

(ii) If θ > ξ + μ + b , taking the limit as 𝑡 tends to ∞ on both sides of (A.6) yields

lim t y ( t ) = lim t ( θ - μ - ξ - b ) A e ( θ - μ - ξ - b ) t 1 + ( θ - μ ) A e ( θ - μ - ξ - b ) t = θ - μ - ξ - b θ - μ

That is, whatever the initial condition y ( 0 ) is, the solution y ( t ) converges to θ - μ - ξ - b θ - μ as 𝑡 tends to ∞. Therefore, as x ( t ) = 1 - y ( t ) , we have lim t x ( t ) = ξ + b θ - μ .

Since y ( t ) converges to θ - μ - ξ - b θ - μ as 𝑡 tends to ∞, for all ϵ > 0 sufficiently small, there exists a real number N > 0 such that, for all t > N ,

(A.14) - ϵ θ - μ - ξ - b θ - μ - y ( t ) ϵ .

From the second equation of (A.3) and the second inequality of (A.14), we obtain

(A.15) k ˙ ( t ) = λ 0 ( 1 - y ( t ) ) τ k α ( t ) - ( δ 0 + p ) k ( t ) λ 0 ( ξ + b θ - μ + ϵ ) τ k α ( t ) - ( δ 0 + p ) k ( t ) .

Using the nonnegativity of k ( t ) and (A.15), we get

(A.16) d k 1 - α ( t ) d t λ 0 ( ξ + b θ - μ + ϵ ) τ - ( δ 0 + p ) k 1 - α ( t ) .

By the comparison theorem [19], (A.16) yields

k 1 - α ( t ) k 0 1 - α e - ( 1 - α ) ( δ 0 + p ) t + λ 0 ( ξ + b θ - μ + ϵ ) τ δ 0 + p ( 1 - e - ( 1 - α ) ( δ 0 + p ) t ) .

Thus,

(A.17) lim sup t k 1 - α ( t ) λ 0 ( ξ + b θ - μ + ϵ ) τ δ 0 + p .

From the arbitrariness of 𝜖, we deduce from (A.17) that

(A.18) lim sup t k 1 - α ( t ) λ 0 ( ξ + b θ - μ ) τ δ 0 + p .

Using once more the second equation of (A.3) and the first inequality of (A.14), we obtain

k ˙ ( t ) = λ 0 ( 1 - y ( t ) ) τ k α ( t ) - ( δ 0 + p ) k ( t ) λ 0 ( ξ + b θ - μ - ϵ ) τ k α ( t ) - ( δ 0 + p ) k ( t ) .

Using the positivity of k ( t ) and the comparison theorem [19], we deduce that

(A.19) lim inf t k 1 - α ( t ) λ 0 ( ξ + b θ - μ - ϵ ) τ δ 0 + p .

Thus, from the arbitrariness of 𝜖, we deduce from (A.19) that

(A.20) lim inf t k 1 - α ( t ) λ 0 ( ξ + b θ - μ ) τ δ 0 + p .

It then follows from (A.18) and (A.20) that

lim inf t k 1 - α ( t ) λ 0 ( ξ + b θ - μ ) τ δ 0 + p lim sup t k 1 - α ( t ) .

This lets us infer that

lim t k 1 - α ( t ) = λ 0 ( ξ + b θ - μ ) τ δ 0 + p .

That is, lim t k ( t ) = ( λ 0 δ 0 + p ) 1 1 - α ( ξ + b θ - μ ) τ 1 - α . ∎

Proof of Proposition 3.5

Let ( x ( 0 ) , y ( 0 ) , k ( 0 ) ) Γ . Since the coefficients of system (3.1) are C 1 functions, they are locally Lipschitz continuous. Therefore, for any given initial value ( x ( 0 ) , y ( 0 ) , k ( 0 ) ) , there is a unique local solution ( x ( t ) , y ( t ) , k ( t ) ) on t [ 0 , τ e ) , where τ e is the explosion time. Let q 0 > 1 be sufficiently large so that x ( 0 ) and y ( 0 ) lie within the interval [ 1 q 0 , 1 ] and k ( 0 ) is in [ 1 q 0 , ( λ 0 δ 0 + p ) 1 1 - α ] . For each integer q q 0 , define the stopping time τ q by

τ q = inf { t [ 0 , τ e ) , min ( x ( t ) , y ( t ) , k ( t ) ) 1 q } ,

where, throughout this paper, we set inf ϕ = (as usual, 𝜙 denotes the empty set).

According to the definition, τ q is increasing as k . Denoting τ * = lim q τ q , we have τ * τ e almost surely (a.s.). If we can show that τ * = , then τ e = , and the solution ( x ( t ) , y ( t ) , k ( t ) ) is such that x ( t ) > 0 , y ( t ) > 0 and k ( t ) > 0 a.s. for all t 0 . In fact, if, for all t 0 , x ( t ) and y ( t ) are positive a.s., then, by definition of these variables, the equality x ( t ) + y ( t ) = 1 leads to 0 x ( t ) 1 and 0 y ( t ) 1 a.s.

Furthermore, using the almost sure positivity of y ( t ) and k ( t ) , we can proceed as in Proposition 3.1 and prove that

0 < k ( t ) ( λ 0 δ 0 + p ) 1 1 - α a.s.

In other words, to complete the proof, all we need to show is τ * = a.s. If this assertion is false, then there exists a pair of constants T > 0 and ϵ ( 0 , 1 ) such that P ( { τ * T } ) > ϵ . Hence there is an integer q 1 q 0 such that P ( { τ q T } ) ϵ for all q q 1 . Now define a C 2 function V : R + 3 R by

V ( x , y , k ) = ln ( ( λ 0 δ 0 + p ) 1 1 - α x y k ) ,

where R + 3 = { ( x 1 , x 2 , x 3 ) R , x i > 0 , i = 1 , 2 , 3 } .

Applying Itô’s formula [17] to system (3.1) for ω { τ * T } and t [ 0 , τ * ) , we obtain

(A.21) d V ( x , y , k ) = V ( x , y , k ) x d x + V ( x , y , k ) y d y + V ( x , y , k ) k d k + 1 2 2 V ( x , y , k ) x 2 ( d x ) 2 + 1 2 2 V ( x , y , k ) y 2 ( d y ) 2 + 1 2 2 V ( x , y , k ) k 2 ( d k ) 2 + 2 V ( x , y , k ) x y d x d y + 2 V ( x , y , k ) x k d x d k + 2 V ( x , y , k ) y k d y d k = LV ( x , y , k ) d t + σ y d W t - σ x d W t ,

where

LV ( x , y , k ) = - ( 2 a + 2 b + ξ + μ + δ 0 + p ) + b x + ( 2 a + θ ) x + θ y - 1 2 σ 2 x 2 + - 1 2 σ 2 y 2 + ξ y x + λ 0 ( 1 - y ) τ k α - 1 .

Setting

G ( x , y , k ) = - ( 2 a + 2 b + ξ + μ + δ 0 + p ) + ( 2 a + θ ) x + θ y - 1 2 σ 2 x 2 + - 1 2 σ 2 y 2 + ξ y x + λ 0 ( 1 - y ) τ k α - 1 ,

we have

(A.22) LV ( x , y , k ) G ( x , y , k ) .

By virtue of x + y = 1 , k ( λ 0 δ 0 + p ) 1 1 - α and the continuity of 𝐺 on R + 3 , there exists a constant M 1 < 0 such that

(A.23) G ( x , y , k ) > M 1 for all ( x , y , k ) Γ .

Hence, for any q q 1 , integrating both sides of (A.21) from 0 to T τ q = min ( T , τ q ) , we have

(A.24) V ( x ( T τ q ) , y ( T τ q ) , k ( T τ q ) ) - V ( x ( 0 ) , y ( 0 ) , k ( 0 ) ) = 0 T τ q LV ( x ( u ) , y ( u ) , k ( u ) ) d u + 0 T τ q σ y ( u ) d W u - 0 T τ q σ x ( u ) d W u .

It is straightforward that 0 T τ q σ y ( u ) d W u and 0 T τ q σ x ( u ) d W u are martingales, and this lets us infer that

E ( 0 T τ q σ y ( u ) d W u ) = E ( 0 T τ q σ x ( u ) d W u ) = 0 ,

where 𝔼 is the expectation with respect to probability ℙ.

Therefore, taking the expectation in both sides of (A.24) leads to

(A.25) E ( V ( x ( T τ q ) , y ( T τ q ) , k ( T τ q ) ) ) - V ( x ( 0 ) , y ( 0 ) , k ( 0 ) ) = E ( 0 T τ q LV ( x ( u ) , y ( u ) , k ( u ) ) d u ) .

From (A.22) and (A.23), (A.25) leads to

(A.26) A ( ( x ( T τ q ) , y ( T τ q ) , k ( T τ q ) ) ) E ( 0 T τ q G ( x ( u ) , y ( u ) , k ( u ) ) d u ) M 1 T > - ,

where A ( x ( T τ q ) , y ( T τ q ) , k ( T τ q ) ) = E ( V ( x ( T τ q ) , y ( T τ q ) , k ( T τ q ) ) ) - V ( x ( 0 ) , y ( 0 ) , k ( 0 ) ) .

Set Ω q = { ω Ω , τ q ( ω ) T } for q q 1 . Letting I Ω q be the indicator function of Ω q , we have P ( Ω q ) ϵ .

On the other hand, noting that x + y = 1 and k ( λ 0 δ 0 + p ) 1 1 - α , we have

(A.27) E ( V ( x ( T τ q ) , y ( T τ q ) , k ( T τ q ) ) ) E [ ln ( x ( T τ q ) ) ] E [ I Ω q ln ( x ( τ q , ω ) ) ] ϵ ln 1 q .

Letting q , (A.26) and (A.27) yield the contradiction - M 1 T > - . Therefore, we obtain τ * = a.s. This completes the proof. ∎

Proof of Proposition 3.6

Consider the functions

ϕ 1 ( y ) = ( θ - μ ) ( 1 - y ) - ( ξ + b ) - σ 2 ( 1 - y ) 2 2 and ϕ 2 ( x ) = ( θ - μ ) x - ( ξ + b ) - σ 2 x 2 2 .

We have ϕ 1 ( 0 ) = ϕ 2 ( 1 ) = θ - ( μ + ξ + b + σ 2 2 ) .

(i) Let us assume that θ < ξ + μ + b + σ 2 2 . That is, ϕ 1 ( 0 ) < 0 . Since ϕ 1 is a continuous function, one can choose sufficiently small ρ > 0 such that

ϕ 1 ( 0 ) + ρ < 0 .

Consider the Lyapunov function Ψ ( x , y ) = y β , where β ( 0 , 1 ) is a constant to be determined. Applying Itô’s formula, we have

(A.28) d Ψ ( x , y ) = L Ψ ( x , y ) + β y β σ x d W t ,

where L Ψ ( x , y ) = β y β ϕ 1 ( y ) + 1 2 β 2 y β σ 2 x 2 . For a constant 𝑤 in ( 0 , 1 ) , denote

Γ w 1 = { ( x , y ) : 1 - w < x 1 ,  0 y < w } .

By continuity of ϕ 1 , we can choose w ( 0 , 1 ) sufficiently small such that, for any y [ 0 , w ) ,

ϕ 1 ( y ) ϕ 1 ( 0 ) + ρ 2 .

In addition, we let β ( 0 , 1 ) be sufficiently small such that, for any w Γ w 1 , we have

1 2 β σ 2 ( 1 - y ) 2 ρ 2 .

Thus, when 𝛽 and 𝑤 are small enough, for any ( x , y ) Γ w 1 , we have

L Ψ ( x , y ) β ( ϕ 1 ( 0 ) + ρ ) Ψ ( x , y ) for ( x , y ) Γ w 1 .

By [23, Theorem 3.3, Chapter 4] and (A.28), for any γ > 0 , there is w 1 ( 0 , w ) such that

(A.29) P { lim t ( x ( t ) , y ( t ) ) = ( 1 , 0 ) } 1 - γ for ( x ( 0 ) , y ( 0 ) ) Γ w 1 1 .

From the arbitrariness of 𝛾, we deduce that

P { lim t ( x ( t ) , y ( t ) ) = 0 } = 1 for ( x ( 0 ) , y ( 0 ) ) Γ w 1 1 .

Moreover, we further prove that any solution ( x ( t ) , y ( t ) , k ( t ) ) starting in Γ is such that ( x ( t ) , y ( t ) ) will eventually enter Γ w 1 1 . Define T w 1 = inf { t > 0 : y ( t ) w 1 } . Consider the function Ψ ¯ ( x , y ) = - ( y + 1 ) ν , where 𝜈 is a sufficiently large number such that

(A.30) y ( 1 - y 2 ) ( θ - μ ) - ( ξ + b ) ( 1 + y ) + 1 2 σ 2 ( ν - 1 ) y 2 ( 1 - y ) 2 w 1 for any y [ w 1 , 1 ) .

In fact, applying Itô’s formula to Ψ ¯ ( x , y ) , we have

d Ψ ¯ ( x , y ) = L Ψ ¯ ( x , y ) - ν σ ( 1 + y ) ν - 1 x y d W t ,

where

L Ψ ¯ ( x , y ) = - ν ( 1 + y ) ν - 2 ( y ( 1 - y 2 ) ( θ - μ ) - ( ξ + b ) ( 1 + y ) + 1 2 σ 2 ( ν - 1 ) y 2 ( 1 - y ) 2 ) .

Using (A.30), we get

L Ψ ¯ ( x , y ) - ν w 1 for y [ w 1 , 1 ) .

By Dynkin’s formula and the boundedness of ( 1 + y ) ν - 1 x y , we have

E [ Ψ ¯ ( x ( T w 1 ) , y ( T w 1 ) ) ] = Ψ ¯ ( x ( 0 ) , y ( 0 ) ) + E 0 T w 1 L Ψ ¯ ( x ( t ) , y ( t ) ) d t Ψ ¯ ( x ( 0 ) , y ( 0 ) ) - ν w 1 E [ T w 1 ] .

Since Ψ ¯ ( x , y ) is bounded on [ 0 , 1 ] × [ 0 , 1 ] , we have E [ T w 1 ] < . Thanks to the strong Markov property, E [ T w 1 ] < and (A.29) imply that, for any γ > 0 ,

P { lim t ( x ( t ) , y ( t ) ) = ( 1 , 0 ) } 1 - γ for ( x ( 0 ) , y ( 0 ) ) [ 0 , 1 ] × [ 0 , 1 ] .

From the arbitrariness of 𝛾, we deduce that

(A.31) P { lim t ( x ( t ) , y ( t ) ) = ( 1 , 0 ) } = 1 for ( x ( 0 ) , y ( 0 ) ) [ 0 , 1 ] × [ 0 , 1 ] .

From (A.31), we deduce that, for ϵ > 0 sufficiently small, there exists M 2 > 0 such that, for t M 2 ,

1 - ϵ 1 - y ( t ) 1 + ϵ a.s.

Proceeding as in item (i) of the proof for Proposition 3.4, we obtain

(A.32) lim t k ( t ) = ( λ 0 δ 0 + p ) 1 1 - α a.s.

Using (A.31) and (A.32), we deduce that if θ < ξ + μ + b + σ 2 2 , the financial crisis dies out and ( x ( t ) , y ( t ) , k ( t ) ) tends to ( 1 , 0 , ( λ 0 δ 0 + p ) 1 1 - α ) almost surely as 𝑡 tends to ∞.

(ii) Let us assume that θ > ξ + μ + b + σ 2 2 . We prove that the equation ϕ 2 ( x ) = 0 admits a unique solution x * in ( 0 , 1 ) . Since θ > ξ + μ + b + σ 2 2 , the discriminant Δ of the polynomial ϕ 2 ( x ) satisfies

Δ = ( θ - μ ) 2 - 2 σ 2 ( ξ + b ) > ( ξ + b - σ 2 2 ) 2 0 .

Therefore, the equation ϕ 2 ( x ) = 0 admits two solutions x 1 and x 2 defined by

x 1 = θ - μ - ( θ - μ ) 2 - 2 σ 2 ( ξ + b ) σ 2 , x 2 = θ - μ + ( θ - μ ) 2 - 2 σ 2 ( ξ + b ) σ 2 .

It is straightforward that

x 1 + x 2 = 2 ( θ - μ ) σ 2 > 0 and x 1 x 2 = 2 ( ξ + b ) σ 2 > 0 .

Thus, the solutions x 1 and x 2 are positive. It is also easy to verify that x 1 < x 2 .

Since ϕ 2 ( 0 ) = - ( ξ + b ) < 0 and ϕ 2 ( 1 ) = θ - ( ξ + μ + b + σ 2 2 ) > 0 , by the Bolzano–Cauchy intermediate-value theorem [34], at least one of these solutions, x 1 , belongs to the interval ( 0 , 1 ) . If both of them belong to ( 0 , 1 ) , using the equality ϕ 2 ( x ) = - σ 2 2 ( x - x 1 ) ( x - x 2 ) leads to ϕ 2 ( 1 ) = - σ 2 2 ( 1 - x 1 ) ( 1 - x 2 ) < 0 , which is in contradiction with ϕ 2 ( 1 ) > 0 . Therefore, the unique solution in ( 0 , 1 ) is x * = x 1 .

Next, we prove that the values of x ( t ) for t 0 oscillate around x * almost surely. That is,

(A.33) lim inf t x ( t ) < x * < lim sup t x ( t ) a.s.

First, we prove that lim sup t x ( t ) > x * . If it is not true, then there exists a sufficiently small ϵ ( 0 , 1 ) such that P ( Ω 1 ) > ϵ , where Ω 1 = { ω Ω , lim sup t x ( t , ω ) x * - 2 ϵ } . Hence, for every ω Ω 1 , there is T 1 = T 1 ( ω ) such that

(A.34) x ( t , ω ) x * - ϵ for t T 1 ( ω ) .

Since ϕ 2 ( x * ) = ( θ - μ ) 2 - 2 σ 2 ( ξ + b ) > 0 , the function ϕ 2 is monotonically increasing at x * and (A.34) leads to

(A.35) ϕ 2 ( x ( t , ω ) ) ϕ 2 ( x * - ϵ ) for t T 1 ( ω ) .

On the other hand, by the large number theorem for martingales, there is an Ω 2 Ω with P ( Ω 2 ) = 1 such that, for every ω Ω 2 ,

(A.36) lim t 1 t 0 t σ x ( s , ω ) d W ( s , ω ) = 0 .

Now, fix any ω Ω 1 Ω 2 . From (A.35), for t T 1 ( ω ) , we get

(A.37) ln y ( t , ω ) = ln ( y ( 0 ) ) + 0 T 1 ( ω ) ϕ 2 ( 1 - y ( s , ω ) ) d s + T 1 ( ω ) t ϕ 2 ( 1 - y ( s , ω ) ) d s + 0 t σ ( 1 - y ( s , ω ) ) d W ( s , ω ) = ln ( y ( 0 ) ) + 0 T 1 ( ω ) ϕ 2 ( x ( s , ω ) ) d s + T 1 ( ω ) t ϕ 2 ( x ( s , ω ) ) d s + 0 t σ x ( s , ω ) d W ( s , ω ) ln ( y ( 0 ) ) + 0 T 1 ( ω ) ϕ 2 ( x ( s , ω ) ) d s + ( t - T 1 ( ω ) ) ϕ 2 ( x * - ϵ ) + 0 t σ x ( s , ω ) d W ( s , ω ) .

Using (A.36), (A.37) leads to lim sup t ln ( y ( t , ω ) ) t ϕ 2 ( x * - ϵ ) < 0 . Thus,

(A.38) lim t y ( t , ω ) = 0 .

From (A.38), we deduce that lim t x ( t , ω ) = 1 , which contradicts (A.34). Therefore, we must have the desired assertion. That is,

lim sup t x ( t ) > x * .

Next, let us prove that lim inf t x ( t ) < x * . If it is not true, then there is a sufficiently small ϵ 1 ( 0 , 1 ) such that P ( Ω 3 ) > ϵ 1 , where Ω 3 = { ω Ω , lim inf t x ( t , ω ) x * + 2 ϵ 1 } . Hence, for every ω Ω 3 , there is a T 2 = T 2 ( ω ) such that

(A.39) x ( t , ω ) x * + ϵ 1 for t T 2 ( ω ) .

Since the function ϕ 2 is monotonically increasing at x * , (A.39) leads to

(A.40) ϕ 2 ( x ( t , ω ) ) ϕ 2 ( x * + ϵ 1 ) > 0 for t T 2 ( ω ) .

Now, fixing ω Ω 2 Ω 3 , from (A.40), we get

ln y ( t , ω ) = ln ( y ( 0 ) ) + 0 T 1 ( ω ) ϕ 2 ( 1 - y ( s , ω ) ) d s + T 1 ( ω ) t ϕ 2 ( 1 - y ( s , ω ) ) d s + 0 t σ ( 1 - y ( s , ω ) ) d W ( s , ω )
= ln ( y ( 0 ) ) + 0 T 1 ( ω ) ϕ 2 ( x ( s , ω ) ) d s + T 1 ( ω ) t ϕ 2 ( x ( s , ω ) ) d s + 0 t σ x ( s , ω ) d W ( s , ω )
(A.41) ln ( y ( 0 ) ) + 0 T 1 ( ω ) ϕ 2 ( x ( s , ω ) ) d s + ( t - T 2 ( ω ) ) ϕ 2 ( x * + ϵ 1 ) + 0 t σ x ( s , ω ) d W ( s , ω ) .
Using (A.36), (A.41) leads to lim inf t ln ( y ( t , ω ) ) t ϕ 2 ( x * + ϵ 1 ) > 0 . Hence, lim t y ( t , ω ) = , which contradicts y ( t , ω ) 1 . This completes the proof of the assertion lim inf t x ( t ) < x * .

Relation (A.33) means that y ( t ) is always oscillating between 0 and 1. That is, the financial crisis is persistent. The third equation of (3.1) can be rewritten as

d k ( t ) = λ 0 x τ ( t ) k α ( t ) - ( δ 0 + p ) k ( t ) .

Hence, using (A.33), we obtain the asymptotic behavior of the economic growth. It oscillates almost surely around the value ( λ 0 x * τ δ 0 + p ) 1 1 - α . This completes the proof of Proposition 3.6. ∎

  1. Conflict of Interest: The authors declare that they have no conflict of interest.

References

[1] F. Allen and D. Gale, Financial contagion, J. Polit. Econ 108 (2000), 1–33. 10.1086/262109Search in Google Scholar

[2] J. L. Arcand, E. Berkes and U. Panizza, Too much finance?, J. Econ. Growth 20 (2015), 105–148. 10.1007/s10887-015-9115-2Search in Google Scholar

[3] B. Bolos, V. Bacarea and M. Marusteri, Approaching economic issues through epidemiologyan introduction to business epidemiology, Romanian J. Econ. Forecasting 14 (2011), 257–276. Search in Google Scholar

[4] A. Boyko, V. Kukartsev and V. Tynchenko, Simulation-dynamic model of long-term economic growth using solow model, J. Phys. Conf. Ser. 1 (2019), no. 1353, 1–6. 10.1088/1742-6596/1353/1/012138Search in Google Scholar

[5] S. Brusco and F. Castiglionesi, Liquidity coinsurance, moral hazard, and financial contagion, J. Finance 62 (2007), no. 5, 2275–2302. 10.1111/j.1540-6261.2007.01275.xSearch in Google Scholar

[6] A. Bucci, D. La Torre, D. Liuzzi and S. Marsiglio, Financial contagion and economic development: An epidemiological approach, J. Econ. Behavior Organ. 162 (2019), 211–228. 10.1016/j.jebo.2018.12.018Search in Google Scholar

[7] A. Bucci, S. Marsiglio and C. Prettner, On the (nonmonotonic) relation between economic growth and finance, Macroecon. Dynam. (2018), 1–20. 10.1017/S1365100518000305Search in Google Scholar

[8] R. J. Caballero and A. Krishnamurthy, Collective risk management in a flight to quality episode, J. Finance 63 (2008), no. 5, 2195–2230. 10.3386/w12896Search in Google Scholar

[9] S. G. Cecchetti and E. Kharrouchi, Reassessing the impact of finance on growth, BIS Working Papers 381, Bank for International Settlements, 2012. Search in Google Scholar

[10] D. W. Diamond and P. H. Dybvig, Bank runs, deposit insurance, and liquidity, J. Polit. Econ. 91 (1983), no. 3, 401–419. 10.1086/261155Search in Google Scholar

[11] P. Gai and A. H. S. Kapadia, Complexity, concentration and contagion, J. Monetary Econ. 58 (2011), no. 5, 453–470. 10.1016/j.jmoneco.2011.05.005Search in Google Scholar

[12] P. Glasserman and H. P. Young, Contagion in financial networks, J. Econ. Literature 54 (2016), no. 3, 779–831. 10.1257/jel.20151228Search in Google Scholar

[13] J. D. Gregorio, Borrowing constraints, human capital accumulation, and growth, J. Monetary Econ. 37 (1996), 49–71. 10.1016/0304-3932(95)01234-6Search in Google Scholar

[14] J. D. Gregorio and S.-J. Kim, Credit markets with differences in abilities: Education, distribution and growth, Internat. Econom. Rev. 41 (2000), no. 3, 579–607. 10.1111/1468-2354.00077Search in Google Scholar

[15] D. J. Higham, An algorithmic introduction to numerical simulation of stochastic differential equations, SIAM Rev. 43 (2001), no. 3, 525–546. 10.1137/S0036144500378302Search in Google Scholar

[16] R. G. King and R. Levine, Finance and growth: Schumpeter might be right, Quart. J. Econ. 108 (1993), no. 3, 717–737. 10.2307/2118406Search in Google Scholar

[17] F. C. Klebaner, Introduction to Stochastic Calculus with Applications, 2nd ed., Imperial College, London, 2005. 10.1142/p386Search in Google Scholar

[18] O. Kostylenko, H. S. Rodrigues and D. F. M. Torres, Banking risk as an epidemiological Model: An optimal control approach, Operational Research, Springer Proc. Math. Stat. 223, Springer, Cham (2017), 165–176. 10.1007/978-3-319-71583-4_12Search in Google Scholar

[19] V. Lakshmikantham, S. Leela and A. A. Martynyuk, Stability Analysis of Nonlinear Systems, Dekker, New York, 1989. 10.1142/1192Search in Google Scholar

[20] S. H. Law and N. Singh, Does too much finance harm economic growth?, J. Banking Finance 25 (2004), 49–70. Search in Google Scholar

[21] R. Levine, Finance and growth: Theory and evidence, Handbook of Economic Growth, Elsevier, Amsterdam (2005), 866–934. 10.3386/w10766Search in Google Scholar

[22] X. Liao, L. Wang and P. Yu, Stability of Dynamical Systems. Vol. 5, Monogr. Ser. Nonlinear Sci. Complex., Springer, Cham, 2007. 10.1016/S1574-6917(07)05001-5Search in Google Scholar

[23] X. Mao, Stochastic Differential Equations and Applications, 2nd ed., Horwood, Chichester, 2008. 10.1533/9780857099402Search in Google Scholar

[24] M. F. Morales, Financial intermediation in a model of growth through creative destruction, Macroecon. Dynam. 7 (2003), no. 3, 363–393. 10.1017/S1365100502020138Search in Google Scholar

[25] J. Müller, Interbank credit lines as a channel of contagion, J. Financial Services Res. 29 (2006), 37–60. 10.1007/s10693-005-5107-2Search in Google Scholar

[26] M. Pagano, Financial markets and growth: An overview, Eur. Econ. Rev. 37 (1993), 2–3., 613-622. 10.1016/0014-2921(93)90051-BSearch in Google Scholar

[27] R. M. Solow, A contribution to the theory of economic growth, Quart. J. Econ. 70 (1956), 65–94. 10.2307/1884513Search in Google Scholar

[28] T. W. Swan, Economic growth and capital accumulation, Econ. Record 32 (1956), no. 2, 334–361. 10.1111/j.1475-4932.1956.tb00434.xSearch in Google Scholar

[29] M. Toivanen, Contagion in the interbank network: An epidemiological approach, Research Discussion Papers 19, Bank of Finland, 2013. 10.2139/ssrn.2331300Search in Google Scholar

[30] A. Trew, Efficiency, depth and growth: Quantitative implications of finance and growth theory, J. Macroecon. 30 (2008), no. 4, 1550–1568. 10.1016/j.jmacro.2007.12.005Search in Google Scholar

[31] A. Trew, Finance and balanced growth, Macroecon. Dynam. 18 (2014), no. 4, 883–898. 10.1017/S1365100512000661Search in Google Scholar

[32] C. Viladent, An epidemiologic approach of financial markets, Globalization and the Reform of the International Banking and Monetary System, Springer, Cham (2009), 258–265. 10.1057/9780230251069_13Search in Google Scholar

[33] W. Wagner, In the quest of systemic externalities: A review of the literature, CESifo Econ. Stud. 56 (2010), 96–111. 10.1093/cesifo/ifp022Search in Google Scholar

[34] V. A. Zorich, Mathematical Analysis. II, Universitext, Springer, Berlin, 2002 Search in Google Scholar

Received: 2021-10-05
Revised: 2021-12-28
Accepted: 2021-12-29
Published Online: 2022-02-24
Published in Print: 2022-06-01

© 2022 Walter de Gruyter GmbH, Berlin/Boston

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