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Title: Determinants of Capital Structure Choice: A Structural Equation Modeling Approach


1
Determinants of Capital Structure Choice A
Structural Equation Modeling Approach
  • Cheng F. Lee
  • Distinguished Professor of Finance
  • Rutgers, The State University of New
    JerseyEditor of Review of Quantitative Finance
    and Accounting and Review of Pacific Basin
    Financial Markets and Policies

The 15th Annual Conference on PBFEAM at Ho Chi
Minh City, Vietnam
2
OUTLINE
  • I. Introduction
  • II. Measures and Determinants of
  • Capital Structure
  • III. Sample
  • IV. Methodology
  • V. Empirical Results
  • IV. Conclusion

3
I. Introduction
A. History of Finance B. Theoretical Framework of
Finance      a. Classical Theory      b. New
classical theory      c. CAPM and APT      d.
Options and Futures Theory C. Policy
Framework of Finance      a. Investment Policy
b. Financial Policy      c. Dividend Policy d.
Production PolicyD. Accounting Approach to
Determine Capital Structure a.
Static Ratio Analysis b. Dynamic Ratio
Analysis E. Finance Approach to Determine
Capital Structure a. Traditional
Approach b. Option Approach  
4
II. Measures and Determinants of Capital
Structure
  • A. Growth
  • B. Uniqueness
  • C. Non-Debt Tax Shields
  • D. Collateral Value of Assets
  • E. Profitability
  • F. Volatility
  • G. Industry Classification

5
III. Sample
6
Table 1 Descriptive Statistics for the Pooled
Sample during 1988-2003
7
Table 2 Pearson Correlation Coefficients for
the Pooled Sample during 1988-2003, N 13,387
8
IV. Methodology
  • A. MIMIC Model
  • B. Estimation Criterion
  • C. Model Fit Evaluation

9
Table 3 Constructs and Indicators in Titman and
Wessels (1988) Model
10
Figure 1. Path Diagram of a Simplified MIMIC
A. MIMIC Model
11
  • (1) ? ? ? ? ? ? ?
  • Y ?y ? ? ?
  1. X ?x ? ? ?,

12
Let ?0, X??, ?xI, and ?0, the full structural
equation model becomes a MIMIC model
? ? X ? Y ?y ? ? ?,
where ? is a (m x 1) vector of endogenous
variables with zeros on the diagonal ? is a
(n x 1) vector of exogenous variables ? is a (m
x 1) vector of errors in equation.
13
The latent variable ? is linearly determined by a
set of observable exogenous causes, X (X1,
X2, , Xq), and a disturbance ?. In matrix
form ? ? X ? or in equation form ? ?X
? ?1 X1 ?2 X2 ?q Xq ?.
14
The latent variable, in turn, linearly determines
a set of observable endogenous indicators, Y
(Y1, Y2, , Yp) and a corresponding set of
disturbance, ? (?1, ?2, , ?p).
In matrix form Y ?y ? ? ?. In equation
form Y1 ?1? ?1 Y2 ?2 ? ?2
Yp ?p ? ?p.
15
The disturbances are mutually independent due to
the fact that correlations of Ys are already
accounted for by their common factor or so-called
latent variable, ?. For convenience, all
variables are taken to have expectation zero.
That is, the mean value of each variable is
subtracted from each variable value. Thus, E(?
?) 0, E(?2) ?, E(??) ??, where ? is a
(p x p) diagonal matrix with the vector of
variances of the ?s, ?, displayed on the
diagonal.
16
The equations can be combined to yield a reduced
form
Y ?y ? ? ? ?y (?X ?) ? (?y ?) X
?y ? ? ? X (?y ? ?) ? X z,
where ? ?y ? is the reduced form coefficient
matrix z ?y ? ? is the reduced form
disturbance vector.
17
The disturbance vector has covariance matrix
Cov(z) ? E(zz) E(?y ? ?)(?y ? ?)
?y ?y ? ?? Where ? Var(?) and
?? is diagonal covariance matrix of ?.
18
B. Estimation Criterion
F log ? tr(S?-1) logS - (p q),
Where ? is the population covariance matrix S
is the model-implied covariance matrix p is the
number of exogenous observable variables q is
the number of endogenous observable variables.
19
V. Empirical Result
20
Table 4 Constructs, Causes and Effects in MIMIC
Model
21
Table 5Goodness-of-Fit Measures
22
Table 6Completely Standardized Loadings
23
Table 6(Contd) Completely Standardized Loadings
24
Table 7 Significance of Unstandardized Total
Effect of Determinants of Capital Structure
25
Table 8 Signs of Total Effect of Determinants
of Capital Structure
26
Figure 2Relative Impact of Determinants of
Capital Structure
27
Table 9Squared Multiple Correlations
28
Table 10Comparison of the Empirical Results
29
VI. Conclusion
A. The Results Obtained from MIMIC Model
Performed Better than those from LISREL Model B.
Growth, Uniqueness, Non-Debt Tax Shields,
Collateral Value of Assets, Profitability,
Volatility, and Classification are the Six
Important Characteristics for Determining
the Capital Structure of a Firm C. In
Practice, Capital Structure Information can be
used to Estimate Financial Z-score, Cost of
Capital Estimation. In addition, Capital
Structure is Important for Performing
Credit Risk Analysis. D. Capital Structure
Theories can also be used to do
Macro-Finance and Economic Policy Research E.
Investment, Financing, and Dividend and
Production Policies are Important in
Corporate Governance Research.
30
Appendix A. Path Diagram Implied in Titman and
Wessels (1988) Model
31
Appendix B Completely Standardized Total Effect
of Determinants of Capital Structure
32
Appendix B Completely Standardized Total Effect
of Determinants of Capital Structure
33
Appendix B Completely Standardized Total Effect
of Determinants of Capital Structure
34
Appendix B Completely Standardized Total Effect
of Determinants of Capital Structure
35
Appendix B Completely Standardized Total Effect
of Determinants of Capital Structure
36
Appendix B Completely Standardized Total Effect
of Determinants of Capital Structure
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