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C(3)+C(23)+C(30)+C(37)=0
Null Hypothesis Summary:
 

Null Hypothesis Summary:
 
 
 
 
 

 
 
 
 
Normalized Restriction (= 0)
Value
Std. Err.

Normalized Restriction (= 0)
Value
Std. Err.
C(2) + C(4) + C(8) + C(15)
0.857768
0.13935

C(3) + C(23) + C(30) + C(37)
0.272117
0.074308
Restrictions are linear in coefficients.

Restrictions are linear in coefficients.

Wald Test:
 
 

Wald Test:
 
 
Equation: EQ04
 
 

Equation: EQ04
 
 
 
 
 
 

 
 
 
 
Test Statistic
Value
df
Probability

Test Statistic
Value
df
Probability
t-statistic
7.182746
1142

t-statistic
3.415254
1142
0.0007
F-statistic
51.59184
(1, 1142)

F-statistic
11.66396
(1, 1142)
0.0007
Chi-square
51.59184
1

Chi-square
11.66396
1
0.0006
 
 
 
 

 
 
 
 
Null Hypothesis: C(2)+C(4)+C(7)+C(17)=0
 
Null Hypothesis: C(3)+C(23)+C(29)+C(39)=0
Null Hypothesis Summary:
 

Null Hypothesis Summary:
 
 
 
 
 

 
 
 
 
Normalized Restriction (= 0)
Value
Std. Err.

Normalized Restriction (= 0)
Value
Std. Err.
C(2) + C(4) + C(7) + C(17)
0.63551
0.088477

C(3) + C(23) + C(29) + C(39)
0.230042
0.067357
Restrictions are linear in coefficients.

Restrictions are linear in coefficients.

Wald Test:
 
 

Wald Test:
 
 
Equation: EQ04
 
 

Equation: EQ04
 
 
 
 
 
 

 
 
 
 
Test Statistic
Value
df
Probability

Test Statistic
Value
df
Probability
t-statistic
6.929527
1142

t-statistic
3.479873
1142
0.0005
F-statistic
48.01835
(1, 1142)

F-statistic
12.10951
(1, 1142)
0.0005
Chi-square
48.01835
1

Chi-square
12.10951
1
0.0005
 
 
 
 

 
 
 
 
Null Hypothesis: C(2)+C(4)+C(7)+C(16)=0
 
Null Hypothesis: C(3)+C(23)+C(29)+C(38)=0
Null Hypothesis Summary:
 

Null Hypothesis Summary:
 
 
 
 
 

 
 
 
 
Normalized Restriction (= 0)
Value
Std. Err.

Normalized Restriction (= 0)
Value
Std. Err.
C(2) + C(4) + C(7) + C(16)
0.829655
0.119728

C(3) + C(23) + C(29) + C(38)
0.257766
0.074073
Restrictions are linear in coefficients.

Restrictions are linear in coefficients.

Wald Test:
 
 

Wald Test:
 
 
Equation: EQ04
 
 

Equation: EQ04
 
 
 
 
 
 

 
 
 
 
Test Statistic
Value
df
Probability

Test Statistic
Value
df
Probability
t-statistic
7.128977
1142

t-statistic
3.555237
1142
0.0004
F-statistic
50.82231
(1, 1142)

F-statistic
12.63971
(1, 1142)
0.0004
Chi-square
50.82231
1

Chi-square
12.63971
1
0.0004
 
 
 
 

 
 
 
 
Null Hypothesis: C(2)+C(4)+C(7)+C(15)=0
 
Null Hypothesis: C(3)+C(23)+C(29)+C(37)=0
Null Hypothesis Summary:
 

Null Hypothesis Summary:
 
 
 
 
 

 
 
 
 
Normalized Restriction (= 0)
Value
Std. Err.

Normalized Restriction (= 0)
Value
Std. Err.
C(2) + C(4) + C(7) + C(15)
0.849466
0.119157

C(3) + C(23) + C(29) + C(37)
0.266592
0.074986
Restrictions are linear in coefficients.

Restrictions are linear in coefficients.

Wald Test:
 
 
Equation: EQ04
 
 
 
 
 
 
Test Statistic
Value
df
Probability
t-statistic
6.133682
1142

F-statistic
37.62205
(1, 1142)

Chi-square
37.62205
1

 
 
 
 
Null Hypothesis: C(3)+C(23)+C(28)+C(36)=0
Null Hypothesis Summary:
 
 
 
 
 
Normalized Restriction (= 0)
Value
Std. Err.
C(3) + C(23) + C(28) + C(36)
0.595516
0.097089
Restrictions are linear in coefficients.

این مطلب رو هم توصیه می کنم بخونین:   دانلود تحقیق با موضوعرتبه بندی، سلسله مراتبی، مقایسات زوجی

Abstract
The combination of an optimal capital structure for companies, For years, one of the most complex issues in the field of of corporate financial management for financial managers and researchers in the field and cause the various theories in the field of capital structure has been created. The purpose of this study is the first to examine the effects of macroeconomic risk and firm-specific risk as directly and indirectly (from the channel profitability) of static and dynamic trade-off theory view on the firm’s leverage ratio. The results showed a significant positive relationship between firm-specific risks in the static state and a negative relationship between macroeconomic risk and firm-specific risks in dynamic state on the ratio of leverage. The relationship between firm-specific risk and macroeconomic risks of channel profitability on leverage in the dynamic mode is significant and respectively the effect has positive and negative. In the following, The effect of risk on the process adjustment of actual capital structure over time towards the optimal capital structure is discussed. The results showed significant effects of asymmetric and firm-specific risk and macroeconomic risk levels despite the deviation between the actual leverage (up, down) from the target leverage. At the end of the financial position of the company (financial deficit, financial surplus) to adjustment the capital structure of our model. At the end, We’ve entered the financial position of the firm (financial deficit, financial surplus) in the capital structure adjustment model. The results indicate a significant risk of asymmetric effect on the speed of capital structure adjustment in the different financial status. The method used to estimate models of dynamic panel estimator GMM (generalized moments). For this purpose, the data have been selected from a sample of 153 company from the firms listed in Tehran Stock Exchange for the period 1380 to 1392.

Keywords:
macroeconomic risk, firm-specific risk, Profitability, leverage ratio ,capital structure rebalancing, speed of adjustment, deviations from target leverage, financial deficits /surpluses, estimator GMM (Generalized Method Of Moments)

Alborz Institution of Higher Education

A Thesis Submitted in Partial Fulfillment of the Requirments for
the Degree of M.Sc in Financial Management

Title

Speed of Capital Structure Adjustment With an Emphasis on Macroeconomic Risk and Firm-Specific

Supervisor
Phd. Seed Jalal Sadeghi Sharif

By
Saeid Khazaei

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