REGIONAL EVIDENCE FROM PALESTINE, JORDAN and EGYPT STOCK EXCHANGES - - PowerPoint PPT Presentation

FIRM`S VALUE & CAPITAL STRUCTURE DETERMINANTS: REGIONAL EVIDENCE FROM PALESTINE, JORDAN and EGYPT STOCK EXCHANGES

By SHADI ALI HAMAD Thesis Submitted in Fulfilment of the Requirements for the Degree of Doctor of Philosophy

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Presentation Contents

Introduction

Background of Study Problem Statement Literature Review

Research Flow

Methodology of Market Integration Methodology of Pearson Correlation Pooled OLS & Generalized Method of Moments (GMM) Methodology Empirical Findings

Conclusions and Discussion

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INTRODUCTION

Background : A study of Palestinian Stock Market (PEX)and its evolvement Palestine, Israel, Egypt and Jordan are neighboring countries with long shared history. Despite the territorial disputes and hostility among them, the four countries have been sharing economic resources, particularly labor factor for decades. Following the Israeli occupation of Palestinian territories in 1948 and in 1967, many Palestinians were expelled out of their home country and reside in neighboring countries, mainly in Jordan and Egypt. PEX started its first trading session on 18 February 1997. In early February 2010, it was converted into a public shareholder company in conformity with good governance and transparency rules. According to the Arab and international classification of financial markets, the Palestinian exchange has attained advanced status in 2009. On 5 Nov 2012, a total of forty- eight companies were listed on the Palestinian exchange, with a market value of $2.7 billion. Palestinian listed companies operate in five major sectors - banking and financial services, insurance, investment, industry, and services.

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ASE

PEX EGX DSE

BSE

TA-100

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Map of Palestine

Background of the Financial Markets ( Volatile Arab Region)

TA-100 (Israel) EGX (Egypt) ASE ( Jordan) PEX (Palestine) Description/2014 1953 1903 1999 1997

Year of Establishment

622 213 243 48

No of Companies

386 220 30.86 2.8

Market Capitalization )billion) USD

286 265 36.8 4.5

Nominal GDP (billion) USD

7.6 82 7.2 5.1

Population (Million)

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Problem Statement

1. The tested markets except TA-100 lost more than half of their market value in the recent five years, and the investors refrain from any additional investment in these developing markets. The volume of trade is in its minimum in all the four exchanges. Does the way of financing contribute and increase value to these firms and then the financial managers must draw more attention to their capital structure? 2. Palestine is occupied by Israel and totally neglected, the United Nations did not recognize the 12 million Palestinians . This could be the reason why no one pays attention to the financial market development of Palestine and the limitation of external financing. My study is an attempt to instill foreign investors confidence in Palestine Stock Exchange. 3. No much researches were done to investigate the determinants of capital structure of the Palestinian stock exchange or other exchanges in the neighboring countries ( Jordan and Egypt). Research Objectives:

1-To study and analyze the degree of financial market integration involving Palestine, Jordan, Egypt and Israel. 2-To examine the most credible factors that influence firm`s value within the capital structure theory. 3- To explore the financing choice of the listed companies in the region and the significant determinants that affect capital structure and the financing decision.

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2008 2009 2010 2011 2012 EGX30 5511 6651 4992 5082 5643 ASE 168674 118756 102477 84753 96841 PEX 624 504 498 488 482 TA-100 1065 912 795 1088 1203

5511 6651 4992 5082 5643 1065 912 795 1088 1203 200 400 600 800 1000 1200 1400 20000 40000 60000 80000 100000 120000 140000 160000 180000

Index values (PEX, ASE, EGX and TA-100) 2008-2012

EGX30 ASE PEX TA-100

TA-100 ASE PEX EGX 7

LITERATURE GAP

Filling the gap to the existing theories

1- Financial Market Development Theory ( 2013):

This is the first study ever done on the stock market integration between PEX and the neighboring stock markets ASE, EGX and TA-100. 2- Capital Structure Theories: This is one of the researches that provides valuable empirical results from the deployment of the four theories stated below and their relevance to individual stock market in the volatile Arab region (market index and sectorial effects). a- MM proposition 1 & 2 c- Pecking Order Theory d- Market Timing Theory 3- Capital Structure Determinants: This empirical study on the volatile Arab region provides some new determinants within capital structure theory.

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b- Trade-Off Theory

RESEARCH FLOW ON FIRM`S VALUE AND CAPITAL STRUCTURE DETERMINANTS

Literature Review and Gap

Research Objectives

1-To study and analyze the degree of financial market integration involving Palestine, Jordan, Egypt and Israel. 2-To examine the most credible factors that influence firm`s value within the capital structure theory. 3- To explore the financing choice of the listed companies in the region and the significant determinants that affect capital structure and the financing decision.

Financial Theories

Step1

• Financial Market Development theory (FMDT)
• Capital structure theories

Mathematical models Econometric models Data Hypothesis testing Forecasting or prediction Conclusions

Step2 Step3 Step4 Step5 Step6 Step7

• Time series (EG- Granger Co-integration test)
• Panel data analysis ( Pooled OLS and GMM)

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RESEARCH STRUCTURE

Step 1: Economic Theory

Financial Market Development Theory (FMDT)

• Stock market plays an important role in developing and sustaining

economic growth via efficient allocation of financial resources

Capital Structure Theories and Firm`s Value

• MM1, Trade-Off and Pecking-Order

Determinants of Capital Structure

• Non-debt tax shield, liquidity, profitability, growth, asset

structure, tangibility, size and debt ratio Engle-Granger: Augmented Dickey-Fuller Unit Root Test (ADF Test)

Yt = 0 + 1T + 2Yt-1 + iYt-i + t where i = 1, 2, 3…k

EG Co-Integration Test via Error Correction Model (ECM) Granger Causality Test

yt = α + ρ1yt−1 + ··· + ρkyt−k + z0 t−1γ1 + ··· + z0t−kγk + etc

.2) .......... .......... .......... .......... .......... v Θ ξ ΔY A μ ΔY

t n 1 i i n 1 i i t i i t

i t

   



 

  

Two-step GMM

1- Modigliani–Miller theorem Proposition I (With taxes)1963: VL=VU+ PV of Tax shield (T*D) VL: value of levered firm VU: value of unlevered firm PV: present value T: taxes D: debt 2- Trade-off Theory of Capital Structure VL=Vu+ PV of Tax shield (T*D)- PV of Bankruptcy Cost 3- Pecking Order: Retained earnings , debt , equity .

1 2

, (0, )

t t t t

y y WN    



  Autoregressive AR1-AR2 Test Step 2:Mathematical model Step 3: Econometric model

Engle-Granger Co-Integration model: PEXt = β0 + β1ASEt+ εt…………(1) PEXt = β0 + β1EGXt+ εt…………(2) PEXt = β0 + β1TA-100t+ εt…………(3)

Two-step GMM model:

Dit = α+β1 EBITDA it + β2 TANGIB it + β3 LIQ it + β4 NTDS it + β5 LNSALES it + β6 GROWTH it +β7 DEBT it+ ε it

Pearson Correlation: Step 4: Data

Data: Balanced (1998-2012) Observations : Time series analysis 169 observation for each of (PEX, ASE, EGX and TA-100) Note : I did not add the Simple Impulse Response Function Variance Decomposition(VDC) Two-step GMM data: Balanced ( 2008-2012) Observations: Panel data analysis 63 companies without any negative, missing or zero values ( PEX, ASE and EGX). Pearson Correlation data: quarterly Balanced (2008-2012) Observations: panel data analysis 18 companies in ASE. 58 EGX, 22 PEX

Step 5: Hypothesis

Engle-Granger Co-Integration hypothesis:

H0: Data series are non-stationary (unit root problem) H0: No long-term relationship exists between PEX and (ASE, EGX, TA-100) H0: No short run relationship exists between PEX and (ASE, EGX, TA-100)

Two-step GMM hypothesis : H0:1-There is no relationship between capital structure and its determinants - non-debt tax shield, liquidity, profitability, growth, asset structure, tangibility, size and debt ratio. Pearson Correlation hypothesis : Ho: Closing price is not correlated with debt equity ratio (D/E) Ho: Closing price is not correlated with debt equity ratio EPS H0: EPS is not correlated with debt equity ratio (D/E). 10

Sargan Test:

Bi-variate Error Correction Model (ECM)

EG Co-Integration Test

Models:

PEX=f (ASE) PEX=f (EGX) PEX=f (TASE)

Augmented Dickey-Fuller Unit Root Test (ADF Test)

Vector Auto-Regressive Model (VAR) Causality Test

Pass when ê is stationary

Fail when ê is not stationary

Forecasting Causality Test Forecasting

END END

RESEARCH FLOW ON ENGLE-GRANGER CO-INTEGRATION TEST (PEX, ASE, EGX & TA-100)

Step 1--5: Economic theory – Hypothesis testing

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Financial Market Development Theory

EG Co-Integration Test

Error Correction Model (ECM)

Adopted Models:

PEXt = β0 + β1ASEt+ εt…………(1) PEXt = β0 + β1EGXt+ εt…………(2) PEXt = β0 + β1TASEt+ εt…………(3) Augmented Dickey-Fuller Unit Root Test (ADF Test)

Yt = 0 + 1T + 2Yt-1 + iYt-i + t where i = 1, 2, 3…k

END

RESEARCH FLOW ON ENGLE-GRANGER CO-INTEGRATION (PEX, ASE, EGX & TASE)

.2) .......... .......... .......... .......... .......... v Θ ξ ΔY A μ ΔY

t n 1 i i n 1 i i t i i t

i t

   



 

  

Granger Causality Test

yt = α + ρ1yt−1 + ··· + ρkyt−k + z0 t−1γ1 + ··· + z0t−kγk + etc

Step 1--5: Economic theory – Hypothesis testing

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Pearson Correlation tested relations:

Corr (CP, D/E) Corr (CP, EPS) Corr (EPS, D/E)

Firm`s value and capital structure theories

END

RESEARCH FLOW ON PEARSON CORRELATION (PEX, ASE, EGX )

Step 1--5: Economic theory – Hypothesis testing

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Capital structure theories

Pooled OLS Static Model (Base-Line)

Pooled OLS estimators (BLUE)

Best Linear Unbiased Estimators

• No Autocorrelation of the errors
• The regressors are exogenous
• The errors are homoscedastic ( serially uncorrelated)

Pooled Dataset (PEX,ASE & EGX) Base-Line Analysis (preliminary analysis on the tested capital structure determinants and

non of the statistical results are put into consideration)

D/E it = α+β1 EBITDA it + β2 TANGIB it + β3 LIQ it + β4 NTDS it + β5 LNSALES it + β6 GROWTH it +β7 DEBT it+ ε it

Results

Endogeneity

No Autocorrelation

Multicollinearity

Step 1--5: Economic theory – Hypothesis testing

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Capital structure determinants

Testing the determinants of capital structure (Dynamic Model)

Test for exogeneity of instruments (Sargan Test) via Chi- squared distribution

Weak model or the model is mis-specified

• r invalid

Two-Step GMM (Generalized Method of Moments) The instruments used in the GMM estimation are not valid Non -existence of the serial Correlation (AR1 & AR2) The instruments used in the GMM estimation are valid

Strong model Testing the determinants of capital structure (Model) and the validity of Pecking Order, Trade-Off Theory (sector & country level).

RESEARCH FLOW ON TWO-STEP GMM TEST AND CAPITAL STRUCTURE MODEL

Step 1--5: Economic theory – Hypothesis testing

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Capital structure determinants

GMM DYNAMIC MODEL

ESTIMATING PARAMETERS

Strong Model

• No Autocorrelation of the errors (AR1 & AR2)
• The instruments are exogenous (Sargan Test)
• The errors are homoscedastic ( serially uncorrelated)
• No Simultaneity problem

Panel Dataset (PEX,ASE & EGX) GMM estimators (Weak Model)

• Endogeneity- the regressors are correlated with the errors
• Heteroscedasticity
• Multicollinearity ( correlation between predictors)

Dit = α+β1 EBITDA it + β2 TANGIB it + β3 LIQ it + β4 NTDS it + β5 LNSALES it + β6 GROWTH it +β7 DEBT it+ ε it

Results

Endogeneity

No Autocorrelation AR1 –AR2

• 1<ᵖ<1

Reduce Multicollinearity

Sargan Test

Simultaneity Problem

Step 1--5: Economic theory – Hypothesis testing

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Capital structure determinants

GMM

• GMM is a generic method for estimating parameters of a model. Usually it is applied in the context of

semi parametric models, where the parameter of interest is finite-dimensional. The GMM estimators are known to be consistent, and efficient in the class of all estimators that don’t use any extra information aside from that contained in the moment conditions.

Sargan Test

• Sargan Test : It is a statistical test used for testing over-identifying restrictions in a statistical model.

Under the null hypothesis that the over-identifying restrictions are valid, the statistic is asymptotically distributed as a chi-square variable with (m − k) degrees of freedom (where m is the number of instruments and k is the number of endogenous variables).

• Autocorrelation
• Autocorrelation Non -existence of the serial Correlation (AR1 & AR2 ) of error is the cross correlation
• f a signal with itself. Informally, it is the similarity between observations as a function of the time lag

between them.

GMM Test

Step 1--5: Economic theory – Hypothesis testing

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Why GMM Test?

1. provide more efficient instruments that control for endogeneity. 2. It includes unobservable shocks in the cross-sectional component and time dummies in the model. 3. GMM employs panel data which increases the number of observations. This set improves efficiency by reducing the multicollinearity problem and increasing the degree of freedom between the explanatory variables. 4. Firms are different in their capital structure choice. Cross-sectional data does not cope with this problem. Thus, panel data approach has the advantage of solving the unobserved firm- specific effects. 5. Moreover, compared to cross-sectional data, choosing variables and instruments is easy and more flexible. The endogeneity problem is one of the factors that supports the implementation of GMM.

Step 1--5: Economic theory – Hypothesis testing

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Objective – Questions –Hypothesis and Findings of the Study

Objective Research Question Null Hypothesis Findings

1-Studying and analyzing the degree of financial market integration involving Palestine, Jordan, Egypt and Israel. 1-Is there a significant degree of financial market integration involving Palestine and its neighboring countries, Jordan, Egypt and Israel? 1-The Palestinian stock exchange is not cointegrated with the Egyptian, Jordanian and Israeli stock exchange. 1- There is a long-run relationship between, ASE, EGX, TE-100 and PEX but absence of dynamic relations in all four stock markets.

Step 6-7: Forecasting and conclusions

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Pearson Correlation between DE & CP, EPS across PEX, ASE and EGX (aggregated data) from 2008 to 2012.

Country Level

Mean (D/E)

Correlation of mean CP and mean of DE Correlation of mean EPS & mean of CP Aggregate Results Manufacturing

0.41 0.83 0.73

Service

0.40 0.69 0.54

Property

0.50 0.51 0.13

Firm`s Value and Capital Structure Theories

Step 6-7: Forecasting and conclusions

Pearson Correlation between D/E, EPS and CP & EPS across Sectors in PEX, ASE, EGX (2008 to 2012).

Country Level Mean (D/E) Correlation of mean CP and mean of DE Correlation of mean EPS & mean of DE Correlation of mean EPS & mean of CP Palestine

N=22

Manufacturing 0.22 0.03 0.07 0.38 Service 0.64

• 0.13
• 0.21
• 0.10

Property 0.38 0.64 0.04 0.23 Egypt

N=58

Manufacturing 0.32 0.46

• 0 .47

0.67 Service 0.56

• 0.36

0.35 0.36 Property 0.33

• 0.73
• 0.72

0.21 Jordan

N=18

Manufacturing 0.17

• 0.16
• 0.68

0.52 Service 0.53 0.45 0.25 0.92 Property 0.81

• 0.97
• 0.74

0.90

Pearson Correlation between DE & CP, EPS across Countries (aggregated) from 2008 to 2012. 20

1- D/E ratio is significantly and positively correlated with closing price and EPS. 2- Significant positive relation is found between closing price and EPS.

Objective – Questions –Hypothesis and Findings of the Study

Objective Research Question Null Hypothesis Findings

2-Testing the correlation between firm`s value with D/E ( leverage) and EPS 1-What is the relation of D/E

• n the firm’s value

2-What is the relation of EPS

• n the firm’s value

3-What is the relation of D/E

• n EPS?

1-Closing price is not correlated with debt equity ratio (D/E). 2- EPS is not correlated with debt equity ratio (D/E). 3-Closing price is not correlated with EPS. 1- D/E ratio is significantly and positively correlated with closing price and EPS. 2- Significant positive relation is found between closing price and EPS. 3- These significant results indicate how strong the relation between capital structure with firm`s value. The Trade-Off Theory and MMI are clearly applicable across sectors and countries.

Step 6-7: Forecasting and conclusions

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Objective – Questions –Hypothesis and Findings of the Study

Objective Research Question Null Hypothesis Findings

3- Exploring the financing choice of the listed companies in the region and the significant determinants that affect capital structure and the financing decision. 1-What are the significant determinants of capital structure in each economic sectors of PEX, ASE, and EGX markets? Do they differ across countries and industries? 1-There is no relationship between capital structure and its determinants - non- debt tax shield, liquidity, profitability, growth, asset structure, tangibility, size and debt ratio. 1-Employing the Pooled OLS, The results of the analysis show that all the tested variables and determinants have significant results and high coefficients except profitability. General financing behavior depends and is influenced by these determinants. 2- GMM test`s results indicate that all the examined determinants have significant relationship with leverage. Negative relation is found between D/E and liquidity, non-debt tax shield, profitability, size and growth. The Egyptian firms have some uniqueness in its trend., assets structure, debt ratio and liquidity behave positively with leverage while growth and non-debt tax shield trends negatively. All the tested determinants of the Egyptian manufacturing companies are not significant except profitability with negative result.

Step 6-7: Forecasting and conclusions

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CONCLUSIONS

A- PEX integration with ASE, EGX & TA-100 Results: 1. ASE, EGX and TA-100 had a long-run relationship with PEX but an absence of dynamic relations on the short run. B- Firm`s Value Results: 1. Capital structure has significant impact on firm`s value. This result is applicable to all the tested markets (PEX, ASE and EGX ) and sectors (manufacturing, property and service) with slight differences in their strength . C- Determinants of capital Structure Results via GMM:

• 1. All the examined determinants ( size, liquidity, assets structure, growth, non-debt tax shield, profitability) have significant

relationship with leverage (D/E). Those which have negative value are liquidity, non-debt tax shield, profitability, size and growth (aggregated data).

• 2. The Egyptian firms have some uniqueness in its trend. Debt ratio, assets structure and liquidity behave positively with

leverage except growth and non-debt tax shield. Non-debt tax shield, growth, profitability and size determinants of the Egyptian companies are not significant.

• 3. All the tested determinants of the Egyptian manufacturing companies are not significant, except profitability

with negative result.

1.

Step 6-7: Forecasting and conclusions

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 DISCUSSION 1- Market`s Integration

Step 6-7: Forecasting and conclusions

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There is a long-run relationship between, ASE, EGX, TE-100 and PEX but absence of dynamic relations in all four stock markets.

• 1. Some of the companies (Jordanian in particular) are listed in more than one stock exchanges ( PEX

and ASE).

• 2. Despite the territorial disputes and hostility between Israel and the Arab countries, they have been

sharing economic resources and intensive bilateral trade, 90% of the Palestinian commodity trade is with Israel.

• 3. The governments of Jordan, Palestine and Egyptian have strong relations with Israel, supported by

international and economic agreements (under the auspice of United Nations) .

• 4. Some Israeli companies are now established in Jordan with huge capital investment.
• 5. Israel signed long run agreements to provide gas and electricity to Jordan, Palestine and Egypt as part
• f the effort to spur long-term economic relationships.

 DISCUSSION 2- Firm`s Value and Capital Structure Theories

Step 6-7: Forecasting and conclusions

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Study Proxy variables Methodology Findings My Thesis Findings

Samuel Antwi & Ebenezer Fiifi (2012), Firm value = f (capital structure) Firm value = f (Equity, Debt) With the linear expression of the model being: FV = a0 + b1EQUITY + b2 LTDEBT + μe a0, b1 and b2 are parameters to be estimated. The ordinary least squares method of regression (OLS) In testing Ghana Stock Exchange, the study found Positive impact of long-term- debt on firm's value just like equity capital. 1- D/E ratio (leverage) is significantly and positively correlated with closing price and EPS. 2- Significant positive relation is found between closing price and EPS (aggregated data). 3- Empirical results indicate strong relationship between capital structure and firm`s value. The Trade- Off Theory and MMI are clearly applicable across sectors and countries. Ogbulu Maxwell And Emeni Kehinde (2012) Firm value = f (capital structure) Firm value = f (Equity, Debt) With the linear expression of the model being: FV = a0 + b1EQUITY + b2 LTDEBT + μe a0, b1 and b2 are parameters to be estimated. The ordinary least squares method of regression (OLS) Equity component of the listed companies in Nigeria Stock Exchange is irrelevant of the value of the firm, and the long-term debt has the major effect Roland F. 1966 USA Earning /Price Ratio= a+ b1 Leverage+ b2 Growth + b3 Payout+ b4 Log Size+ b5..b10 Industry Dummy variable Multiple Regression analysis The firms value is enhanced by the use of debt and fixed commitments Anup Chowdhury, Suman Paul Chowdhury 2010 Share price as proxy Price= a+ b1 eps+ b2 dpratio+ b3 public+ b4 fato+ b5 ltdebtas+ b7 operlev+ b8 salesgr+ b9 sharecap+ei Multiple Regression Analysis, Correlation Analysis Cost of capital has a negative correlation

• n Bangladesh Stock Exchange.

Changing the capital structure composition of a firm can increase its value in the market Nor Edi Azhar Bte Mohamad and Fatihah Norazami Bt Abdullah 2012 Dependents Variables

• 1. Return on Equity

2.Return on Asset

• 3. Return on Capital

Independents Variables;

• 4. Debt to Equity Ratio
• 5. Debt to Total Asset Ratio
• 6. Long-term debt to total capital
• 7. Size

Multiple Regression Analysis, Correlation Analysis A significant relationship between sources

• f finance and firms' performance of the

Malaysian companies.

 DISCUSSION 2- Firm`s Value

Step 6-7: Forecasting and conclusions

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Consistent with the prediction of capital structure theories and the empirical studies, the results of this study show that firms and sectors with high level of debt have positive effect on firm`s value.

• 1. The financial managers must opt for debt financing, as one of the ways to increase

company's market value.

• 2. The political instability in the volatile region makes borrowing difficult and complicate

process of external funding.

• 3. There is company specific effect on the firm`s value and not just a country effect. This

implies that managers must provide rational financial solutions that compensates for the persistence of value losses in the recent years.

 DISCUSSION 3- Determinants of Capital Structure in the Volatile Arab Region

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Study Proxy variable Methodology Findings My Thesis Findings

Faris M.(2011) The Determinants Of Capital Structure Of Palestine-Listed Companies Dependents Variables

• 1. Tangibility
• 2. Size
• 3. Liquidity
• 4. Age
• 5. Short term debt
• 6. Long term debt
• 7. Total debt

The correlation analysis and ANOVA test Data (2000-2004) Total debt (TD) is positively and significantly related to TAN. On the contrary, no significant relationship exists between the long term debt (LTD) and short term debt (STD) on the one hand and any age, growth, liquidity (LQ), tangibility (TAN), and size

• n the other hand

1- All the examined determinants have significant relationship with

• leverage. Negative relation is found

between D/E and liquidity, non- debt tax shield, profitability, size and growth (aggregated data). 2-The Egyptian firms have some uniqueness in its trend, assets structure, debt ratio and liquidity behave positively with leverage while growth and non-debt tax shield have negative relationship. 3-All the tested determinants of the Egyptian manufacturing companies are not significant except profitability with negative result. Khaldoun M. Al-Qaisi 2013 Determinants of Capital Structure: Palestinian Case (2003 – 2007) Dependents Variables

• 1. Assets structure
• 2. Profitability
• 3. size
• 4. Growth
• 5. total debt ratio
• 6. long term debt ratio

The ordinary least squares method of regression (OLS) Data (2003-2007) listed Palestinian firms have low leverage ratios, long-term debt is literally non-existent and capital structure (firm size and firm profitability) are applicable to the Palestinian case. Husni Ali Khrawish and Ali Husni Ali Khraiwesh (2007) The Determinants of the Capital Structure: Evidence from Jordanian Industrial Companies Dependents Variables

• 1. Profitability
• 2. Tangibility
• 3. Total Assets
• 4. Long term debt
• 5. Short term debt
• 6. Total debt

Correlation Analysis A significant positive relationship exists between LTD/TD and size (TA), Tangibility (Tang), and long-term debt (LTD) and there was a negative relationship between LTD/TD and short-term debt of the firm. Also, the results showed that Total assets, Tangibility, Long-term debt, had a positive correlation with LTD/TD, while, short-term debt had a negative correlation with LTD/TD. Profitability has a negative correlation with short-term debt and total debt ratios. Aktham Maghyereh (2005) Dynamic Capital Structure: Evidence From The Small Developing Country Of Jordan GMM size, tangibility, profitability, growth opportunity, and earnings volatility exert significant effects on the capital structure choice of Jordanian firms

 DISCUSSION 3- Determinants of Capital Structure in the Volatile Arab Region

Step 6-7: Forecasting and conclusions

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Tested Markets and Sectors Study Findings Findings

PEX, ASE and EGX, (Aggregated data)

• All determinants are significant
• Liquidity, non-debt tax shield,

profitability, size and growth have negative relation with D/E The more liquidity the firm has, the less need for debt financing. Firms that have more liquidity employ less debt in their capital structure. This result supports the Pecking Order Theory, where firms prefer internal cash flow to external

• sources. This finding supports the studies by Ozkan (2001).

The impact of size on leverage ratios shows negative significant results. This output is not consistent with the Trade-Off Theory ,So, while small firms which face higher bankruptcy risks and costs try to reduce their debt, large firms, which have an easy access to creditors, do not refrain from using debt in leverage (Bennett and Donnelly, 1993; Antoniou et al., 2008; Flannery and Rangan, 2006). The tested companies did not comply with these positive debt and size relations. The results indicate that non-debt tax shields had negative relation with debt, In a study by DeAngelo and Masulis (1980), the authors consider investment tax credits and tax deductions for depreciation as substitutes for the tax benefits arising from debt financing. Hence, less debt is included in the capital structure of firms that have a large non-debt tax shields compared to their expected cash flow. Hence, one cannot defend the claim of the existence of a substitution effect of non-debt tax shields, as mentioned in the study of Wijst and Thurik (1993). EGX companies

• Assets structure, debt ratio and

liquidity have Positive relation with D/E.

• growth and non-debt tax shield

have negative relation with D/E. It is reasonable to assert that tangible assets reduce the loss that financiers of the firms may face in case of its default, and consequently of the positive relationship between leverage and the proportion of tangible assets Manufacturing Companies (Aggregated data)

• Profitability has a negative

relationship with D/E. The Pecking Order Theory predicts that firms with high profitability use less debt than retained earnings in their capital structure ,Booth., (2001); and Rajan and Zingales, (1995).

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 LIMITATIONS OF THE STUDY

• 1. With respect to Engle Granger Co-Integration test, my study did not include Impulse

Response Functions (IRF) and Variance Decomposition (VDC)

• 2. The time dimension of the study is limited with just five years data (2008-2012).
• 3. In testing the profitability determinant by GMM and Pooled OLS models, all the

negative values are omitted. This process may lead to the phenomenon of survival- ship bias.

• 4. The aggregated data are obtained on quarterly basis rather than monthly basis. That

reduces the number of observations.

Thank You

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