Equity Financing Regulation and Corporate Capital Structure A Model and the Simulation

Transcription

1 25 1 Vol. 25 No OPERATIONS RESEARCH AND MANAGEMENT SCIENCE Feb F A doi /orms Equity Financing Regulation and Corporate Capital Structure A Model and the Simulation WANG Zheng-wei 1 ZHU Wu-xiang 2 ZHAO Dong-qing 2 1. PBC School of Finance Tsinghua University Beijing China 2. School of Economics and Management Tsinghua University Beijing China Abstract The purpose of this paper is to find whether there is a strict relationship between corporate capital structure adjustment and corporate financing friction. This paper builds a financing model with market regulation and uses a computer simulation method to examine the effects of equity financing regulation friction on company s target capital structure and the adjustment of capital structure. At the same time it also tests the applicability of the capital structure adjustment model. The results show that the change of external equity financing frictions is not only an important influencing factor on the target capital structure but also an important factor on the adjustment speed of company s capital structure which provides a unique view to observe the financing friction of capital market. In addition the test on the existing model of the capital structure adjustment tells us that the model widely used by previous authors ignores a strong constraint between variables which will lead to serious model specification bias. Key words corporate finance equity financing regulation computer simulation method capital structure capital structure adjustment 0 Trade-off Pecking order Market timing Modigliani Miller MM Shyam-Sunder Myers

2 Fama French 3 Loof 4 Flannery Rangan 5 Byoun 6 Wang Zhu 7 Flannery Rangan 2 30% 1965 ~ Flannery Rangan 100% Dewaelheynsa Hulle 11 Cook Tang IPO t 1 I t t + 1 a t + 1 f I t f

3 f 0 = 0 f' > 0 f < 0 a t + 1 b t b t 0-1 p 1 1 t a t - p 0 t D t E t δ t 0 r D τ δ t 0 if b t = 0 5 t t δ t δ t δ t δ t < 0 E t + D t δ t > 0 1 d t D t E t D t = D t d t 1 I t E t + D t 6 E t = E t a t f I t I t D t - 1 r D 1 - τ - δ t max V = E 1 T t = 1 δ t 1 + r E t ~ 6 E t > E t 0 t = 1 18 E r E δ t = 0 D t = 0 I t = 0 if E t < 0 7 r E r D 1. 2 MM 1 2 Baker 17 L D t L 4 D t + E t b t = 0 δ t 0 t b = b t = 1 b t = 0 t b t = 1 t t

4 1 161 b t =1 b t = 0 δ t 0 L 60% 90% T 1 τ = 25% r E 8% 12% r D 4% 8% p 0 1 p b t p 11 - p 0 p 2 p 3 p T = 30 p 300 T = a 1 = 1 a t + 1 = a t η t + 1 lnη t + 1 N μ t + 1 σ 2 t + 1 μ t 20% σ t 0. 1 p = 0. 3 p = 0. 5 p = 0. 7 a t 3. 1 MATLAB t t t t H0 H1

5 t p = 0. 3 p = 0. 5 p = ~ 6 L i t - L i t - 1 = λ L * i t - L i t L i t i t L * i t i t 1% 3. 2 λ λ λ = 1 λ = 0 0 < λ < 1 λ > 1 λ < 0 p 2 2 p = 0. 3 / p = 0. 5 p = 0. 7 ANOVA L i t = α + λl * i t λ L i t ε i t 9 p = 0. 3 p = 0. 5 p = 0. 7 α ε i t 9 t t t / t F Pr > F < t t t t 2. F ANOVA / 8 λ λ Panel data Pooled Fixed-Effect Model Random-Effect Model 4 2 t 1 p F LM Hausman Baltagi

6 p = 0. 3 p = 0. 5 p = *** *** *** L i t *** *** *** L * i t *** *** *** year Yes no no F F = pr > F = F = Pr > F = F = Pr > F = LM chi 2 = Pr > chi 2 = chi 2 = Pr > chi 2 = chi 2 = Pr > chi 2 = Hausman chi 2 = Pr > chi 2 = chi 2 = Pr > chi 2 = chi 2 = Pr > chi 2 = R % % % 1. t 2. t *** 1% 0 3. L i t - 1 L * i t VIF 1 4. year yes F no F year yes year no LM hausman 3 p = λ p' = 0. 3 = λ 'p = 0. 5 = λ p' = 0. 7 F = L i t - 1 λ LM λ 5% Hausman 1% 9 L * i t p = 0. 3 λ L i t λ 1 p = 0. 5 L * i t L i t - 1 p = L * i t + L i t - 1 R 2 R 2 = 1 F 1% % % % 9 9 L i t λ 1 - L * 4 ~ i t 6 L * i t L i t - 1 λ p = 0. 3 = λ p = 0. 5 = λ p = 0. 7 = ΔReal i t = α + λδtarget i t + ε i t 10 ΔReal i t L i t - L i t - 1 ΔTarget i t L * i t - L i t - 1 α ε i t 9 9 L * i t 4 λ 4 p =

7 % % R % 4 10 p = 0. 3 p = 0. 5 p = *** *** *** ΔTarget i t *** *** *** year yes no no F F = pr > F = F = Pr > F = F = Pr > F = LM chi 2 = Pr > chi 2 = chi 2 = Pr > chi 2 = chi 2 = Pr > chi 2 = Hausman chi 2 = Pr > chi 2 = chi 2 = Pr > chi 2 = chi 2 = Pr > chi 2 = R % % % 1. t 2. t *** 1% 0 3. year yes F no F year yes year no LM hausman 4 ΔTarget i t ΔTarget i t 1% 10 ΔTarget i t λ λ p = 0. 3 = λ p = 0. 5 = λ p = 0. 7 = λ λ' 1 λ λ λ' 9 λ 2 λ'

8 Dewaelheyns N Hulle C V. Capital structure adjustments in private business group companies J. Applied Financial Economics Cook D O Tang T. Macroeconomic conditions and capital structure adjustment speed J. Journal of Corporate Finance J J Hackbarth D Miao J Morellec E. Capital structure 1 Modigliani F and M Miller. The cost of capital corporation finance and the theory of investment J. American Economic Review Shyam-Sunder L Myers S C. Testing static tradeoff against pecking order models of capital structure J. Journal of Financial Economics Fama E French K. Testing trade-off and pecking order predictions about dividends and debt J. Review of Financial Studies L f H. Dynamic optimal capital structure and technical change J. Structural change and economic dynamics Flannery M J Rangan K P. Partial adjustment toward target capital structures J. Journal of Financial Economics Byoun S. How and when do firms adjust their capital structures toward targets J. Journal of Finance Zhu W Wang Z. Equity financing constraints and corporate capital structure a model J. China Finance Review International credit risk and macroeconomic conditions J. Journal of Financial Economics Strebulaev I A. Do tests of capital structure theory mean what they say J. Journal of Finance Baker M Stein J Wurgler J. When does the market matter stock prices and the investment of equity dependent firms J. Quarterly Journal of Economics Myers S C. The determinants of corporate borrowing J. Journal of Financial Economics Baltagi B H. Econometric Analysis of Panel Data M. John Wiley & Sons t T = J L i t - 1 J J