4th International Conference on Economics and ...

4th International Conference on Economics and Social Sciences (ICESS-2014) Istanbul, Turkey, October 25-26, 2014 Abdulkarim K. Alhowaish College of Architecture and Planning, University of Dammam Dammam, Saudi Arabia

Dated: July 30, 2014

Ref: ICESS-14-474 Subject: Acceptance Letter Dear Sir (s)/Madam (s) Congratulations! We are pleased to inform you that based on peer review process your submission entitled: SECTORAL LINKAGES AND ECONOMIC GROWTH: EMPIRICAL EVIDENCE FROM EIGHT ARAB WORLD COUNTRIES has been accepted for oral presentation at 4th International Conference on Economics and Social Sciences (ICESS-2014) to be held at Hotel Holiday Inn Istanbul City, Istanbul, Turkey on October 25– 26, 2014. On behalf of International Foundation for Research and Development (IFRD), we invite you to attend the conference and present your paper. Date and time of your session will be emailed to you approximately four weeks prior to the conference. Please complete the following steps at your earliest to get benefit of early bird registration. - Fill in the attached registration form and submit your registration fee. - Each attending participant must complete a separate registration form and submit required registration fee. - Submit your revised paper according to suggestions of the reviewers and author guidelines. Please feel free to contact us if you have any query through email by quoting your manuscript number, we will be happy to assist you. We are looking forward to meet you in wonderful Istanbul.

Sincerely Yours,

Conference Co Chair Alexandru Trifu, PhD 4th ICESS-2014

Website: www.ifrnd.org, email: [email protected], [email protected]

SATURDAY, OCTOBER 25, 2014 0800-0900

Welcome and Registration

INAUGURAL CEREMONY 0900-0915

Welcome Address-Prof. Dr. Alexandru Trifu

0915-0945

Keynote Speech-Prof. Dr. Ismail OZSOY

0945-1000

Vote of Thanks-Prof. Dr. Zehra Vildan Serin

1000-1030

MORNING TEA

1030-1300

TECHNICAL SESSION Room 1: Session Chair- Prof. Dr. Alexandru Trifu

1030-1045 1050-1105 1110-1125 1130-1145 1150-1205 1210-1225 1230-1245

Room 2: Session Chair-Dr. Anita Derecskei

The financial strategies of Polish households-Paulina Anioła, Zbigniew Gołaś The effect of social transfers on adult labour supply: a unitary discrete choice model for the case of Ecuador-Andrés Mideros, Cathal O’Donoghue Comparative Effectiveness of Non-Market Financial Flows Towards Developing Countries-Syeed-Uz-Zaman Khan Analyzing the Similarities between Energy Consumption and GDP Levels of World Countries with Multidimensional Scaling MethodAyhan KAPUSUZOGLU, Merve KARACAER Sectoral Linkages and Economic Growth: Empirical Evidence From Eight Arab World Countries-Abdulkarim K. Alhowaish Improvement of dolly women quality through the women's school based self-reliance-Ratih Khoirunnisa, Sayyida Saida Syarifa, Septi Ayu Azizah Development of Capitalism in Georgia and its influence on transformation-Tsotne Zhghenti, Nazira Kakulia

Towards an agenda for India Inc.-Sorab Sadri, Vinit Agarwal Discussion of the Discount Rate for Venture Capitalists: IranPayam Mansour Hosseini, Siamak Tahvildar, Alireza Babazadeh The Study of Human Judgment Formation Limitations through the Factors Necessary for the Work Performance-Viktor Nagy The Evaluation of Psychological Factors Influencing the Criteria for Investment Decisions of Individuals-Selim AREN, Sibel DİNÇ AYDEMİR Green Business in the Cross-Border Area-Vasiliki Rigatou, Stavros Goutsos, Eleni Karfaki Organizational Innovativeness from the Perspective of Top Management Team: the Moderation Effect of Debate-Herri, Herri, Arief Prima Johan Searching a theoretical framework for the business survival of an independent new micro firm-Stavros Goutsos, Jukka Kallio

1300-1400

LUNCH BREAK

1400-1600

TECHNICAL SESSION

1400-1415 1420-1435 1440-1455 1500-1515 1520-1535 1540-1555

Room 1: Session Chair-Dr. Siti Rahmah binti Awang

Room 2: Session Chair- Dr. VIKTOR NAGY

The Management of Traditional Knowledge Related to Medicinal Plants Among the Batek Community in Kuala Koh, Gua Musang, Kelantan-Amran Alias, Hood Salleh Illicit Drug Syndication Threat Towards Juvenile in Malaysia-Zarina Othman Dan, Mohamad Daud Druis Carbon Intensity Reduction in Malaysia: Does It Lead to a Low Carbon Economy?-Khalid Abdul Rahim Relationship Between Human Capital Investment and Economic Growth: Evidence from Nigeria-William, Chimee Nwaoha, Clement, Nwankwo Ukandu Determinants of Child Immunization and Measurement of Gender Bias-Poulami Chatterjee (In) competency Aspects of Microfinance Industry: Via SFA approachMadiha Riaz, Pathiban S. Gopal

Do financial development and trade liberalization cause economic growth in BRICS & MIKT countries? New insights from a panel causality approach-Mert GÜL Effects of Good Governance on Agricultural Efficiency-Nizamettin Bayyurt, Zehra Vildan Serin, Fatma Eban Arıkan The Creative Man for the Creative Place?-Anita Derecskei Determinants of Income Differences of Farmers in Turkey: A Discriminant Analytical Approach-Filiz KADI, Zehra Vildan SERİN, Fatma Eban ARIKAN Converting Core Competence to Competitive Advantage; An Indian Perspective-Jayashree Sadri, Mukund Modi An enquiry into Governance and Efficiency A case study of Botswana listed Companies-S. Ranganathan

1545-1615

AFTERNOON TEA

1600-1730

TECHNICAL SESSION

1600-1615 1620-1635 1640-1655

Room 1: Session Chair-Prof. Dr. Khalid Abdul Rahim Inverse Ability Test in Epilepsy (i-ATIE)-Siti Rahmah Awang, Tahir Ahmad, Raja Mohamad Fairuz, Raja Mohamad Yusoff Rectifying the Civil-Military Imbalance–What Pakistan Can Learn From the Turkish Experience-Maheen Saleem Khosa Social aspects of Code-Switching: An analysis of Television advertisements-Aalia Mehar Khan

1700-1715

Living in Cultural Diversity: The Classification of the Japanese Expatriates in Malaysia-Md. Rosli bin Haji Ismail

1715-1730

The Implication of Business Generic Strategy on the Performance of SMEs in Malaysia-Asmawi Noor Saarani, Faridah Shahadan, Md Rosli Ismail

Room 2: Session Chair-Prof. Dr. S. Ranganathan Default Risk Assessment of Tunisian SMEs: Multiple Criteria Decision Making Approaches-Salah BEN HAMAD, Nesrine TURKI Patients' satisfaction with primary health care in Egypt: exploring the gap between rural and urban governorates-Dina Metwally Country Personality: An Exploratory Research-Kullanun Sripongpun, Kawpong Polyorat, Walee Khanthuwan Differences in Egyptian Students’ Attitudes to Academic Dishonesty and Related Behaviors: The Case of Business StudentsDina Metwally Influence of Meat Traceability System Trust for Decreasing Fear of Seller Opportunism in Consumer Mind-Nathamon Buaprommee, Kawpong Polyorat

SUNDAY, OCTOBER 26, 2014 0900-1030

0900-0915 0920-0935 0940-0955 1000-1015 1020-1035

TECHNICAL SESSION Room 1: Session Chair-Prof. Dr. Zehra Vildan Serin

Room 2: Session Chair- Prof. Dr. Fatma Gülruh Gürbüz

Human Resource Flexibility and Employee Performance-Norihiko Takeuchi Delineation and analysis of intra organizational formal and informal relationships through network analysis-Sayyed Mohammad Reza Davoodi, Mohammad Reza Dalvi

An Islamic View of Education and Business Performance: A Study Case in Republic of Indonesia-Ahmad Rafiki, Imam Buchari Exploring nature of innovative orientation: perspectives from case study-F. Gulruh Gurbuz, H. Sinem Ergun, S. Begum Samur Teraman Assessing Effect of Insecurity on SME Operations and Impact on Socio-Economic Development of Yobe State, Nigeria-Sani Mohammed

Effectiveness of Dance in Enhancing Preschooler’s Flexibility-Syed Kamaruzaman Syed Ali, Habib Mat Som A model for effective factors in staff performance regarding to brandMohammad Reza Dalvi, Sayyed Mohammad Reza Davoodi Language Performance and Motivation : A Study of Students Admitted to Post-Hifz Schools-Maria B Shahid

1030-1100

MORNING TEA

1100-1300

TECHNICAL SESSION Room 1: Session Chair-Dr. Syed Kamaruzzaman Syed Ali

1100-1115 1120-1135 1140-1155

1200-1215 1220-1235 1240-1255

Problems & Prospects of Small Scale Industries in India in Changing Economic Scenario-Krishn Awatar Goyal

Investigating the Possibility of Strategic Planning through SWOT Analysis (Isfahan Industrial Estates Company as a Case Study)-Sayyed Rasoul Aghadavood, Amir Hajipor The consumers of a special product/service within a changing business and social environment-Alexandru Trifu A Welfare Based Approach for Choosing the Inflation Targeting and the Exchange Regime in Tunisia-ABDELLI Soulaima, BELHADJ Besma The Mediating Effect of Accountability, Job-Relevant Information and Organizational Commitment on the Relationship between Budgetary Participation and Managerial Performance-Ria Nelly Sari, Rita Anugerah, Kamaliah, Vince Ratnawati TV Shows as Sources of Authentic Language Input And SLA in Informal Settings-Taher Bahrani, Marziyeh Nekoueizadeh Is women’s increased accessibility to land a path to sustainable development? The case of urban Maseru, lesotho-Keneuoe Anacletta Mots’oene

Room 2: Session Chair-- Prof. Dr. Herri Herri The Relationship of Supply Chain Management (SCM) and Strategic Planning: Strategy as Practice View on a Durable Consumer Goods Company in Turkey-F.Gülruh GÜRBÜZ, Sinem ERGUN, Ahmet DOĞANAY Assessing the Performance of the Personnel by an Integrated Method-Mohammad Yari Naserieh, Mohsen Gholamrezaei

A Conceptual Framework for an Effective Economic Valuation of Heritage Building-Junainah Mohamad, Suriatini Ismail, Rosdi AbRahman, Ahmad Rasdan Ismail Marketing System Management at Industrial OrganizationsMostafa Houshyar Study of relationship between Compensation system and Counterproductive behavior among the employees of copper complex of sarcheshme (Iran)-Mohammad Ziaaddini

1300-1400

LUNCH BREAK

1400-1545

TECHNICAL SESSION Room 1: Session Chair-Andrés Mideros Mora

1400-1415 1420-1435 1440-1455 1500-1515 1520-1535

Room 2: Session Chair-Dr. Selim AREN

An Evaluation of the Management of Organizational Experience among the Staff of Islamic Azad University, Shabestar Branch-Omidali Hoseinzade, Nima Shahidy Regional Cooperation in Addressing Issues of Food Security Threats in Southeast Asia: A Malaysian Perspective-Bakri Mat, Zarina Othman Multi Dimensional of Teaching Approaches: Teachers’ Role as Spiritual Leader in Shaping Student Characteristics-Habib Mat Som, Syed Kamaruzzaman Syed Ali Human Development and Gender Equality: A Case Study of PakistanFauzia Maqsood, Sami Ullah A Structural Model for the Relationship between Self-efficacy and Organizational Commitment with Teaching Quality of Faculty Members-Nima Shahidi, Omidali Hoseinzade, Sara Baezat

Just Determined System Strategic Approach as Organizational Justifying-Nasser Fegh-hi Farahmand BEFORE. B-e-f-o-r-e. Not b4. We Write English, not Bingo!… Academic English and Pakistani Digital Natives-Akifa Imtiaz

Trends in Domestic Terms of Trade of Agricultural Sector of Pakistan-Anwar Hussain, Muhammad Iqbal

1540-1610

AFTERNOON TEA

1600-1730

TECHNICAL SESSION

1600-1615 1620-1635 1640-1655

Room 1: Session Chair-

Room 2: Session Chair-

Problems and factors of non-completion of promising projects by young entrepreneurs: The case of Tunisia-Salah BEN HAMED, Samira Boussema Impact of Manufacturing Sector on Climate Change in Pakistan-Nadia Farooq

Manufacturing Production and Non-Agricultural Employment rate in South Africa: Time Series Analysis-Paul-Francois Muzindutsi, Magdeline M. Maepa Sources of Information Referred for Higher Education Institution Selection-Noor Ismawati Mohd Jaafar The Review of Lesotho Government Policy Measures for Sustainable Food Availability-Moses M. M. Daemane

Economic Growth and Deforestation in Pakistan-Maria Rauf

1700-1715 1715-1730

Educated Females Participation in Labor Market: The Role of Structural Barriers-Sidra Maqsood The Analysis of Constraints in food Security and Intensified Sustainable Crops Production Development in Lesotho-Moses M. M. Daemane

CLOSE

Denied investment: a case of community member’s attitudes towards volunteering in corporate social investment initiativesPaul-Francois Muzindutsi, Ferdinand Niyimbanira

Proceedings of 4th International Conference on Economics and Social Sciences (ICESS-2014)

Proceedings 4th International Conference on Economics and Social Sciences Istanbul, Turkey 25 -26, October 2014 ISSN 2301-7549 CD-ROM

Organized by

International Foundation for Research and Development (IFRD)

i


Preface Dear Distinguished Delegates and Guests, The Conference Committee warmly welcomes our distinguished delegates and guests to the 2014 International Conference on Economics and Social Sciences (ICESS-2014) held on October 25-26 in Istanbul, Turkey. The ICESS-2014 is organized by International Foundation for Research and Development (IFRD). The conference is aimed at discussing with all of you the wide range of problems encountered in present and future issues in economies and Societies. The ICESS-2014 is organized in collaboration with Yildirim Beyazit University, Turkey, Shinawatra International University, Thailand, PERTRE ANDERI of IASI, Romania and National Academy of Management, Ukraine where researchers from around the world presented their work. The conference committee is itself quite diverse and truly international, with membership around the world. The proceeding records the fully refereed papers presented at the conference. The main conference themes and tracks are Economics, Business and social sciences. The conference aims to bring together researchers, scientists, engineers and practitioners to exchange and share their experiences, new ideas and research results about all aspects of the main conference themes and tracks and discuss the practical challenges encountered and the solutions adopted. The main goal of the event is to provide a scientific forum for exchange of new ideas in a number of fields that interact in depth through discussions with their peers from around the world. The conference has solicited and gathered technical research submission related to all aspects of major conference themes and tracks. All the submitted papers have been peer reviewed by the reviewers drawn from the scientific committee, external reviewers and editorial board depending on the subject matter of the paper. Reviewing and initial selection were undertaken electronically. After the rigorous peer-review process, the submitted papers were selected based on originality, significance, and clarity for the purpose of the conference. The conference program is extremely rich, featuring high-impact presentations. The high quality of the program guaranteed by the presence of an unparalleled number of internationally recognized top experts. The conference will therefore be a unique event, where attendees will be able to appreciate the latest results in their field of expertise, and to acquire additional knowledge in other fields. The program has been strutted to favor interactions among attendees coming from many diverse horizons, scientifically, geographically, from academia and from industry. We would like to thank the program chairs, organization staff, and members of the program committee for their work. We are grateful to all those who have contributed to the success of ICESS -2014 especially our partners. We hope that all participants and other interested readers benefit scientifically from the proceedings and find it stimulating in the process. Finally, we would like to wish you success in your technical presentations and social networking. We hope you have a unique, rewarding and enjoyable time at ICESS-2014 in Istanbul. With our warmest regards, Conference Committee October 25–26, 2014 Istanbul, Turkey.

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ICESS-2014 Conference Committee Conference Chair Ayhan Kapusuzoglu, Ph. D., Yildirim Beyazit University, Turkey Conference Co Chair Alexandru Trifu, Ph. D., University, Petre Andrei, Iasi, Romania Conference Convener Zehra Vildan SERİN, Ph. D., Fatih University, Istanbul, Turkey Members John Walsh, Ph. D., Shinawatra International University, Bangkok, Thailand Sisira R. N. Colombage, Ph. D., Monash University, Victoria, Australia Nek Kamal Yeop Yunus, Ph. D., Univerisiti Pendidikan Sultan Idris , Perak, Malaysia R K Uppal, Ph. D., DAV College, Punjab, India Dileep Kumar, M., Ph. D., University Utara Malaysia, Malaysia Rishidaw Balkaran, Ph. D., Durban University of Technology, South Africa M. Saman Dassanayake, Ph. D., University of Colombo, Colombo, Sri Lanka Katalin Jackel, Ph. D., Budapest Business School, Budapest, Hungary Wei-Bin Zhang, Ph. D., Ritsumeikan Asia Pacific University, Japan Susantha Herath, Ph. D., St. Cloud State University, USA Chandana Prasad Withana, Ph. D., Charles Sturt University, Sydney, Australia Chux Gervase Iwu, Ph. D., Cape Peninsula University of Technology, South Africa Somnath Sen, Ph. D., University of Birmingham, United Kingdom Johan de Jager, Ph. D., Tshwane University of Technology, South Africa Kevin Feeney, Ph. D., American University in Bulgaria Ahasanul Haque, Ph. D., International Islamic University Malaysia (IIUM), Malaysia Izah Mohd Tahir, Ph. D., University Sultan Zainal Abidin, Terengganu, Malaysia Pratibha Samson Gaikwad, Ph. D, Shivaji University of Pune, India

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International Conference on Economics and Social Sciences (ICESS-2014)

Table of Contents Description

Pages

Preface

ii

Conference Committee

iii

Table of Contents

iv

Papers

Vi

Determinants of Child Immunization and Measurement of Gender Bias, Poulami Chatterjee

1

The financial strategies of Polish households, Paulina Anioła, Zbigniew Gołaś

11

The Influence of Workplace Condition and Employee Satisfaction on Employee Commitment: A Behavioural Decision Making Perspective, Elizabeth Chinomona, Teboho Mofokeng The Effect of Social Transfers on Adult Labour Supply: A Unitary Discrete Choice Model for the Case of Ecuador, Andrés Mideros, Cathal O’Donoghue

21

Economic Growth and Deforestation in Pakistan, Maria Rauf

46

Effectiveness of Dance in Enhancing Preschooler’s Flexibility, Syed Kamaruzaman Syed Ali, Habib Mat Som, Jenny Wong Eng Yee1 Trends in Domestic Terms of Trade of Agricultural Sector of Pakistan, Anwar Hussain, Muhammad Iqbal Human Development and Gender Equality: A Case Study of Pakistan, Fauzia Maqsood, Sami Ullah The Analysis of Constraints Infood Security and Intensified Sustainable Crops Production Development in Lesotho, Moses M. M. Daemane A Structural Model for the Relationship between Self-efficacy and Organizational Commitment with Teaching Quality of Faculty Members, Nima Shahidi, Omidali Hoseinzade, Sara Baezat An Evaluation of the Management of Organizational Experience among the Staff of Islamic Azad University, Shabestar Branch, Omidali hoseinzade, Nima shahidy Comparative Effectiveness of Non-Market Financial Flows towards Developing Countries, Syeed Khan

60

33

72 85 92 104 110 117

Social Aspects of Code-Switching: An Analysis of Television Advertisements, Aalia Mehar Khan

126

Investigating the Possibility of Strategic Planning through SWOT Analysis (Isfahan Industrial Estates Company as a Case Study), Sayyed Rasoul Aghadavood, Amir Hajipor A Model for Effective Factors in Staff Performance Regarding to Brand, Mohammad Reza Dalvi, Sayyed Mohammad Reza Davoodi Delineation and Analysis of Intra Organizational Formal and Informal Relationships through Network Analysis, Sayyed Mohammad Reza Davoodi, Mohammad Reza Dalvi The Consumers Of A Special Product/Service Within A Changing Business And Social Environment, Alexandru Trifu Multi Dimensional of Teaching Approaches: Teachers’ Role as Spiritual Leader in Shaping Student Characteristics, Habib Mat Som, Syed Kamaruzzaman Syed Ali, HABIB MAT SOM

137

Impact of Manufacturing Sector on Climate Change in Pakistan,Nadia Farooq

170

The Challenges of Managing Traditional Knowledge Related to Medicinal Plants among the Batek Community in Kuala Koh, Gua Musang, Kelantan, Malaysia, Amran Alias, Hood Salleh

179

iv

143 150 159 165

Proceedings of 4th International Conference on Economics and Social Sciences (ICESS-2014) (In) Competency Aspects of Microfinance Industry: Via SFA approach, Madiha Riaz, Pathiban S.Gopal Development of Capitalism in Georgia and its Influence on Transformation, Tsotne Zhghenti, Nazira Kakulia Living in the Cultural Diversity: The Classification of the Japanese Expatriates in Malaysia, Md Rosli Ismail Sources of Information Referred for Higher Education Institution Selection, Noor Ismawati Mohd Jaafar Illicit Drug Syndication Threat towards Juvenile in Malaysia, Zarina Othman Dan Mohamad Daud Druis Carbon Intensity Reduction in Malaysia: Does It Lead to a Low Carbon Economy? Khalid Abdul Rahim Regional Cooperation in Addressing Issues of Food Security Threats in Southeast Asia: Malaysian Perspectives, Bakri Mat, Zarina Othman Rectifying the Civil-Military Imbalance – What Pakistan Can Learn From the Turkish Experience, MaheenSaleemKhosa Sectoral Linkages and Economic Growth: Empirical Evidence from Eight Arab World Countries, Abdulkarim K. Alhowaish The Implication of Business Generic Strategy on the Performance of SMEs in Malaysia, Asmawi Noor Saarani, Faridah Shahadan, Md Rosli Ismail Improvement of Dolly Women Quality through the Women's School Based Self-Reliance, Ratih Khoirunnisa, Sayyida Saida Syarifa, Septi Ayu Azizah Educated Females Participation in Labor Market: The Role of Structural Barriers, Sidra Maqsood Language Performance and Motivation: A Study of Students Admitted to Post-Hifz Schools, Maria B Shahid TV Shows as Sources of Authentic Language Input and SLA in Informal Settings, Taher Bahrani, Marziyeh Nekoueizadeh A Welfare Based Approach for choosing the Inflation Targeting and the Exchange Regime in Tunisia, ABDELLI Soulaima, BELHADJ Besma Relationship between Human Capital Investment and Economic Growth: Evidence from Nigeria, William Chimee Nwaoha, Clement Nwankwo Ukandu Inverse Ability Test in Epilepsy (i-ATIE), Siti Rahmah Awang, Tahir Ahmad, Raja Mohamad Fairuz Raja Mohamad Yusoff Problems and Factors of Non-Completion of Promising Projects by Young Entrepreneurs: The Case of Tunisia, Salah Ben Hamed, Samira Boussema

189

Human Resource Flexibility and Employee Performance, Norihiko Takeuchi

361

The Mediating Effect of Accountability, Job-Relevant Information and Organizational Commitment on the Relationship between Budgetary Participation and Managerial Performance, Ria Nelly Sari, Rita Anugerah, Kamaliah, Vince Ratnawati Is Women’s Increased Accessibility to land a path to Sustainable Development? The case of Urban Maseru, Lesotho, k_motsoene Cultural Engagement: A Platform for Strengthening Ethnic Relations among Studentsin UKM, Fazilah Idris*, ShahizanShahuddin, SyaidatunNazirah Abu Zahrin, Ahmad ZamriMansor Cross-Cultural Issues in Mergers & Acquisitions: A Review in Indian Context, Krishn A. Goyal, Vijay Joshi Just Determined System Strategic Approach as Organizational Justifying, Nasser Fegh-hi Farahmand Ethical Aspect in Using of Non-Herbal Materials (Plant Therapy): An Application among Operators in Islamic Alternative and Complementary Medicine in Malaysia, Abdullah Yusof, Rushdi Ramli, Khader Ahmad

v

201 204 210 220 228 236 246 255 268 274 280 287 314 321 337 342 350

371 380 381 389 398 404


International Conference on Economics and Social Sciences (ICESS-2014)

PAPERS

vi


Sectoral Linkages and Economic Growth: Empirical Evidence from Eight Arab World Countries Abdulkarim K. Alhowaish University of Dammam, Saudi Arabia [email protected] Abstract: Thisstudy empirically investigates the dynamic relationship between sectoral linkages and economic growth in eight Arab world nations.The sectors are agriculture, industry, and services. The countries are Algeria, Comoros, Egypt, Jordan, Mauritania, Morocco, Saudi Arabia, and Tunisia. The sample period is 1968–2012, except for Comoros and Jordan, whose sample period is 1980–2012. The study uses a multivariate co-integration framework fortime–series analysis. The empirical results suggest that the incomes of most Arab economies depend largely on income generated from growth in either the industrial or services sectors, while the agricultural sector has a neutral effect in most cases. Furthermore, in terms of sectoral linkages, the findings demonstrate that the interaction between growth of the industrial and services sectorsappears to be much stronger than the interaction between other sectoralpairs. Keywords: Sectorallinkages, Economic growth, Agriculture, Industry, Services, Arab world, Multivariate analysis 1. Introduction Which economic sectors should be the focus of an economy’s development efforts? Furthermore, which sectorshave a multiplier impact on growth and development by promoting greater economic activity in other sectors? These are important questions for all economies, which can be answered by examining the dynamic relationship between sectoral linkages and the economic growth of national or regional economies over both the short term and the long term. According to traditional economic development theories, economic growth is obtained by the process of structural transformationof an economy away from an agriculture base toward industrial and services activities (Chenery, 1979; Fei and Ranis, 1961; Rostow, 1960). This process in turn leads to structural shifts, and consequently, diminishing significance of agricultural activities and growing dominance of industrial and services activities. It produces substantial changes in production processes, consumption patterns, and several socio-economic indicatorssuch as institutional governance, society freedom, as well as human resource development (Fuchs, 1968; Hirschman, 1958; Kuzents, 1971). Consequently, policy makers, researchers, and practitioners in the field of economic development need to develop strategies to deal with rapid changes in the world economy associated with these structural shifts, not only to react adequately to resolve their own socio-economic problems, but also to remain competitive in the global economy. The challenge for any actor involved in the process of economic transformation is not only to react to external events but also to positively influence and shape the transformation process in order to benefit from opportunities that emerge from these processes, both internally and externally. To understand these processes successfully requires, on the one hand, an extensive understanding of the interaction process between different economic sectors of an economy and, on the other,information to determine their long- and short-term stimulus effects on each other. Accordingly, it is very important to understand the role of economic sectors and their linkages to the rest of an economy. In Arab world countries, which comprise the specific regional focus of this paper,it is generally agreed that poverty, unemployment, and inequality areprevalent and widespread (Todaro and Smith, 2012). Studies of sectoral linkages are deemed to be extremely important, not only to identify key sector or sectors, but also to overcome various socio-economic problems facing these countries. Furthermore, investigation of structural relationships among economic sectors is crucial from a policy perspectivebecause it aids understandingof both the evolution and progression of these relationships andsectoral adjustments over time. A clear perspective on sectoral dynamics can also be useful in creating suitable and sustainable long-term development strategies. Against this background, this research study examines the dynamic relationship between sectoral linkages and economic growth for eight Arab world nations, including Algeria, Comoros, Egypt, Jordan, Mauritania,

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Proceedings of 4th International Conference on Economics and Social Sciences (ICESS-2014) Morocco, Saudi Arabia, and Tunisia. Most previous studies onsectorallinkages have been carried out either for developed countries or non-Arab developing countries. Thus, focusing on Arab world countries fills a gap in the literature. The rest of this paper is organized as follows. Section 2 presents a review of the literature. Section 3 provides a brief description of the data and econometric methodology. Section 4 provides the empirical results and Section 5 concludes. 2. Literature Review The linkages between economic sectors and economic growth have been investigated widely in development literature. In the early stages of development literature, researchers paid greater attention to the relationship between the agricultural and industrial sectors (Hwa, 1988; Lewis, 1954; Singer, 1979; Wright, 1979). They argued that growth in the agricultural sector has a direct stimulating impact on industrial growth through its forward and backward effects as well as supply–demand linkages (e.g. capital, labour, and raw material outflows). On the other hand, industrial growth can also promote demand for agricultural production indirectly through higher wages and directly through production that is linked to agricultural growth, such as technology for irrigation, chemicals, and biochemicals (Adelman et al., 1995; Chowdhury and Chowdhury, 1995; Field, 1978; Katircioglu, 2006; Mokyr, 1976). Hence, researchers predicted that there are two-way feedback effects (i.e. a bi-directional causal relationship) between these two sectors.This in turn positively leads to greater productivity in the use of resources and sustainable economic growth. However, the law of comparative advantage suggests a negative link between agricultural growth and industrial growth. According to this view, the industrial sector has to compete with the agricultural sector for labour. Low productivity in agriculture implies an abundant supply of ‘cheap labour’, which the industrial sector can utilize (Ocampo, 2005; Rashid, 2004; Subramaniam and Reed, 2009; Vogel, 1994; Wright, 1979). In addition, rising labour wages in the industrial sector are a direct cause of labour force decline in the agricultural sector. More recently, development analysts have shifted their focus toward the prominent role of the services sector in the developmental process, and the links between this sector and other economic sectors (Bhagwati, 1984; Blades et al., 1974; Gemmell, 1982; Gemmellet al., 1998; Tiffin and Irz, 2006). The services sector includes banking, telecommunications, transport, and infrastructure. The contribution of services activities, such as distribution, communication, and retailing, to both the agricultural and industrialsectors are obvious and have been observed to increase over time. Unlike agricultural and industrial jobs, the majority of service jobs cannot be replaced by equipment or machines, and therefore, the demand for high quality service personnel will increase continually. Consequently, as an economy advances, ever increasing demand for services sector jobs will attract more and more resources from the industrial and agricultural sectors, which could create negative linkagesbetween the services sector and the other two sectors. Alternatively, the growing services sector could encourage other economic sectors to take advantage of the benefits of economies of scale and create positive linkages with the rest of the economy (Blunch and Verner, 2006; Craigwellet al., 2005). The abovementioned development studies have helped to contributed toward understanding the links between different economic sectors and their impacts on national growth. Furthermore, these studies suggest that the linkages between different economic sectors are extremely complicated and multi-directional in nature, and thus, it is not an easy task to predict them. Experts have also argued that the contribution of these sectors to economic growth varies significantly from place to place as well as from one time period to another within the same economy. Nevertheless, recent sophisticated statistical methodologies and software programmes have enabled analysts to undertake more complicated econometric models to quantify the contribution of each and every sector to economic growth, alongsidethe understanding ofsectoral linkages in the economy. To this end, vector autoregressive (VAR) models and co-integration analyses are the most suitable econometric analyses and both are welldeveloped in most advanced software packages. These econometric models solve endogeneity problems among variables that arise in such studies; the models are able to distinguish short-run effects from long-run effects. Thus, the question of the dynamic relationship between sectoral linkages and economic growth has become more intenselystudied in recent literature.Furthermore,policy makers have become increasingly receptive toward theirresults, in particular those in Arab nations.

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Proceedings of 4th International Conference on Economics and Social Sciences (ICESS-2014) 3. Methodology Data: The analysis is based on annual time–series data on real gross domestic product (GDP), real agriculture value added, real industrial value added, and real services value added in US$ currency units (base year 2005) for eight selected Arab nations. The data were obtained directly from the World Bank’s World Development Indicators database31.The database defined sectoral value added as the net output of a sector (agriculture, industry, and services) after adding up all outputs and subtracting intermediate inputs. It is calculated without making deductions for depreciation of fabricated assets or depletion and degradation of natural resources. The origin of value added is determined by the International Standard Industrial Classification (ISIC), revision 3. Agriculture sector corresponds to ISIC divisions 1-5 and includes forestry, hunting, and fishing, as well as cultivation of crops and livestock production. Industry sector corresponds to ISIC divisions 10-45 and includes manufacturing (ISIC divisions 15-37). It comprises value added in mining, manufacturing (also reported as a separate subgroup), construction, electricity, water, and gas. While, Services sector correspond to ISIC divisions 50-99. They include value added in wholesale and retail trade (including hotels and restaurants), transport, and government, financial, professional, and personal services such as education, health care, and real estate services. Also included are imputed bank service charges, import duties, and any statistical discrepancies noted by national compilers as well as discrepancies arising from rescaling. Additionally, the World Bank indicators defined gross domestic production (GDP) at purchaser's prices as the sum of gross value added by all resident producers in the economy plus any product taxes and minus any subsidies not included in the value of the products. The country samplesare Algeria, Comoros, Egypt, Jordan, Mauritania, Morocco, Saudi Arabia, and Tunisia. The sample period is 1968–2012, except for Comoros and Jordan, whose sample period is 1980–2012. We omitted other Arab world countries mainly because there was no data available and/or the timespan of data was very short. It is well known that unit root and co-integration tests require a long time spanof data rather than merely a large number of observations (Campbell and Perron, 1991; Hakkio and Rush, 1991). The dataset has an average timespan of 44 years (and 32 years in the case of Comoros and Jordan), which is long enough to capture the long-run relationship between fundamental variables and economic growth. All the variables in the dataset are transformed into natural logarithms, that is, real GDP growth (lngdp), real agriculturalgrowth (lnagr), real industry growth (lnind), and real services growth (lnserv), for the usual statistical reasons. The logarithmic plots of time–series are shown in Figure 1, which clearly demonstrates that individual variables for each country exhibit strong upward trends and suggests that these variables may move collectively. The share of economic sectors in GDP for each of selected Arab world countries is presented in Table 1. Over the period of 1970 to 2010, however, the share of agriculture sector in GDP decreased by more than 15 per cent, followed by a decline in industrial share by 14.5 per cent while the share of services sector value added in GDP increased by almost 17 per cent. For individual country, however, the share of agriculture value added in GDP exhibited a sharp decline for almost all selected Arab world countries except Comoros and to some extent Algeria countries. In Comoros, the share of agriculture production in GDP increased from 34 per cent in 1980 to more than 46 per cent in 2010. Algerian agriculture value added share in GDP slightly fall from almost 9.1 per cent in 1970 to about 8.6 per cent in 2010. During the period of 1970 to 2010, the decline in share of agriculture value added in GDP for the other six Arab countries ranged from 70.7 per cent as in the case of Jordan to about 41 per cent as in the case of Mauritania. On the other hand, the share of industrial value added in GDP increased from 45.4 per cent to 51.4 per cent in Algeria, from 28.1 per cent to 37.5 per cent in Egypt, from 38.4 per cent to 45.4 per cent in Mauritania, from 25.3 per cent to 29.6 per cent in Morocco, from 23.8 per cent to 31 per cent in Tunisia, and from 18.9 per cent to 30.7 per cent in Jordan. In Saudi Arabia and Comoros, however, the share of industrial production in GDP accounted for 58.5 per cent and 12.1 per cent of GDP in 2010, down slightly from 62.5 per cent and 13.1 per cent of GDP in 1970, respectively. In addition, the share of services sector value added in GDP increased from 41.2 per cent to almost 55 per cent in Morocco, from 34 per cent to 39 per cent in Saudi Arabia, from 32.3 per cent to 37.1 per cent in Mauritania, from 42.3 per cent to 48.4 per cent in Egypt, and from 56.4 per cent to almost 61 per cent in Tunisia. During the period of 1970 to 2010, the share of services value added in GDP for Comoros, Algeria 31

World Bank database website: http://data.worldbank.org/indicator (access: June 2, 2014)

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Proceedings of 4th International Conference on Economics and Social Sciences (ICESS-2014) and Jordan cases exhibited a decline by 22 per cent, 11.7 per cent and 5.1 per cent respectively. Today, the economic activities in Arab world countries are primary dominated by industrial sector activities which represent about 49 per cent of the GDP in 2010. The services sector accounts for another 41.4 per cent of the GDP and finally, agriculture sector accounts for about 6.1 per cent of the Arab World GDP combined. Method: Co-integration tests are performed to examine the presence of long-run equilibrium relationships among a set of economic time–series variables. Since co-integration is possible only with those variables that are integrated of the same order, we employ an Augmented Dickey–Fuller (ADF) test (Dickey and Fuller, 1979) and a Phillips–Perron (PP) test (Phillips and Perron, 1988) to determine the order of integration for each time–series. This primary step is a prerequisite for testing for the presence of unit root. The unit root test assures that final regression outcomes based on test variables in their current state will not produce spurious regression results, a condition normally associated with non-stationary variables. Once the order of integration is determined, the next step is to determine the lag length in the level of VAR system using various information criterion procedures, such as the Akaike information criterion (AIC) test (Akaike, 1969) and the Schwarz Bayesian information criterion (SBC) test (Schwarz, 1978). Once the order of integration of the series is recognized, and once the lag length of the VAR model is identified, the third step is to test for cointegration between variables. Johansen and Juselius (1992) developed a procedure to estimate a cointegrated system involving several variables. This process is independent of the choices of the endogenous variables and allows researchers to estimate and test for the existence of more than one co-integrating vector in the multivariate system. The typical model, that is, vector error correction model (VECM), can be described as follows: 𝑝−1

∆𝑌𝑡 = 𝛱𝑌𝑡−𝑝 +

𝛤𝑖 ∆𝑌𝑡−𝑖 + 𝜇𝐷𝑖 + 𝜀𝑡

(1)

𝑖=1

whereYt is the column vector of the current values of all the variables in the system (integrated of order one);Dtis a matrix of deterministic variables, such as an intercept and time trend;ɛt is the vector of errors;and Г, Π, and µ are matrices of parameters. pis the number of lag periods included in this model, which is determined by using the AIC and SBC. The first term in Equation (1) captures the long-run effects on the regressors and the second term captures the short-run impact. In the long-run parameter matrix,Π will be of order n x n, with a maximum possible rank of n. Then, using the Granger representation theorem (Engel and Granger, 1987), the rank of Π is found to be r < n, the matrix may be factored as αβ’,where α and β are both of order n x r. Matrix β is such that β’Ytis I(0) even though Ytitself is I(1). In other words, matrix β is the co-integrating matrix describing the long-run relationships in the model. The weighted matrix, α, gives the speed of adjustment of specific variables on account of deviations from the long-run relationship. The co-integration rank is usually tested by using the maximum eigenvalue and trace statistics proposed by Johansen (1988).The long-run information of the series is taken into account in analysing short-run sectoral growth and the resulting model is a short-run error correction model. The number of distinct co-integrating vectors can be obtained by checking the significance of the characteristic roots of Π. This means that the rank of matrix is equal to the number of its characteristic roots that differ from zero. The test for the number of characteristic roots that are insignificantly different from unity can be conducted using the following test statistics. 𝑝

𝜆𝑡𝑟𝑎𝑐𝑒 𝑟 = −𝑇

𝐼𝑛 1 − 𝜆𝑖

(2)

𝑖=𝑟+1

𝜆𝑚𝑎𝑥 𝑟, 𝑟 + 1 = −𝑇 𝐼𝑛 1 − 𝜆𝑟+1 (3) The trace test (λtrace) tests the null hypothesis (H0) that the number of distinct co-integrating vectors is less than or equal to r against the alternative hypothesis of more than r co-integrating vectors. The maximum eigenvalue test (λmax) tests the null hypothesis (H0) that the number of co-integrating vectors is r against the alternative of r +1 co-integrating vectors. T is the number of useable observations and λirepresents the eigenvalues obtained from the estimated Πmatrix in Equation (1).

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Proceedings of 4th International Conference on Economics and Social Sciences (ICESS-2014) 4. Results This empirical study uses time–series analysis to investigate the dynamic relationships between sectoral linkages and economic growth in eight Arab world countries. The initial step in this investigation is to test the order of integration of each series. Both the ADF and PP tests are employed to perform unit root tests. Table 2 shows that all four variables fail to reject the unit root hypothesis at levels of series and reject the unit root hypothesis at the firstdifference. Thisoutcome reveals that the series are integrated at the first order, I(1). The results are in line with the view that most macroeconomic variables are non-stationary in level but stationary in the first difference (Nelson and Plosser, 1982). Since all the series are at the same order,I(1), the dataset is suitable for further investigation. The co-integration test is designed to test for the presence of common stochastic trends between a set of variables that is individually non-stationary in levels. The AIC and SBC information criterion tests are used to select the optimal lag length. However, based on these procedures, the optimal lag lengths used are Algeria (2), Comoros (1), Egypt (2), Jordan (1),Mauritania (1), Morocco (1), Saudi Arabia (3), and Tunisia (1).This uniform lag framework of the VAR system will be used for the VECMs. The results of using the optimal lag structure for the VAR models are summarized in Table 3. The number of co-integrating vectors (r) is determined by two likelihood ratio tests, namely, maximal eigenvalue and trace statistics. The critical values for the trace and maximal eigenvalue statistics are from MacKinnon et al. (1999). In the cases of Algeria, Comoros, Jordan, Mauritania, Saudi Arabia, and Tunisia, the values of the test statistics indicate that the null hypothesis of no co-integration is rejected by both tests at the 5 per cent significance level. Hence, it can be inferred that there is evidence of a long-run equilibrium relationship between the growth of economic sectors and economic growth in these countries. In the case of Egypt, both the maximum eigenvalue and trace likelihood ratio tests reject the null hypothesis of zero co-integration and the null hypothesis for one and two co-integrating vectors at the 5 per cent significant level. This implies the existence of at least three co-integrating vectors in this system. According to the Granger representation theorem (Engel and Granger, 1987), a system of co-integrated variables has an errorcorrection representation that combines the short-run dynamics of the variables with their long-run properties, as implied by the cointegrating relationships. Consequently, VECMs are estimated to determine the nature of interdependence between agricultural growth, industrial growth, services growth, and economic growth for our eight selected Arab nations, and the results are reported in Table 4. Columns 2, 3, 4, and 5 report the χ2statistic for the joint significance of the lagged independent variables, while Column 6 provides the t-statistics for the errorcorrection terms (ECTt-1). The statistical significance of the ECTt-1 and the χ2statistic indicates the presence of long-run and short-run causality, respectively. In the case of Algeria, the error correction term is significant for industrialgrowth and services growth only.This implies the presence of long-run causality from, on the one hand, economic, services, and agricultural growth to industrial growth at the 1 per cent level of significance, and on the other hand, from economic, agricultural, and industrial growth to services growth at the 1 per cent level of significance. However, in the shortrun, there is evidence of bi-directional causality between industrial growth and economic growth and between services growth and economic growth at the 1 per cent and 5per cent levels of significance, respectively. In addition, there is evidence of bi-directional causality between industrial growth and services growth at the 1per cent level of significance. The results, however, reveal no evidence of causality between industrial growth and agricultural growth in either direction, while there is evidence of uni-directional causality running from agriculturalgrowth to economic and services growth, while the converse causality is true for services growth only. In the case of Egypt, the error correction term is significant for economic growth, industrialgrowth,and services growth, indicating the presence of long-run causality from industrial, services, and agriculturalgrowth to economic growth; from economic, services, and agriculturalgrowth to industrial growth; and from economic, agricultural, and industrial growth to services growth at the 1 per cent level of significance. However, in the shortrun, there is evidence of uni-directional causality between economic growth and agriculturalgrowth as well as between economic growth and industrial growth, running from economic growth to both agricultural and industrial growth at the 5 per cent and 10 per cent levels of significance, respectively. The agricultural sector displays Granger-cause services growth at the 5 per cent level of significance, but the converse is not true. The industrial sector displays Granger-cause agriculturalgrowth at the 5 per cent level of significance, but the converse is not true. Given the

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Proceedings of 4th International Conference on Economics and Social Sciences (ICESS-2014) long-run causality impact of services sector, this sector does not have any casual impacts whatsoever on other variables in the shortrun. Inthe case of Mauritania, the error correction term is significant for services growth only, indicating the existence of long-run causality from other variables to services growth at the 5 per cent level of significance. No short-run causal relationship exists between variables in any direction. In the case of Morocco, the error correction term is significant for industrial growth only, revealing the presence of long-run causality from economic, agricultural, and services growth to industrial growth at the 5 per cent level of significance. In the short-run, however, there is no evidence of bi-directional causality between variables, while there is unidirectional causality running from industrial growth to economic and agriculturalgrowth; from services growth to industrial growth; and from economic growth to agriculturalgrowth. Agriculturalgrowth has no effect at all on other variables, neither in the longrun nor in the shortrun. In the case of Saudi Arabia, the error correction term is significant for economic, agricultural, and industrial growth, indicating the existence of long-run causality from agricultural, industrial, and services growth to economic growth; from economic, services, and industrial growth to agricultural growth; and from economic, agricultural, and services growth to industrial growth at the 5 per cent, 1 per cent, and 10 per cent levels of significance, respectively. In the shortrun, however, there is evidence of bi-directional causality between economic growth and services growth at the 1% level of significance, implying a two-way causal relationship between these two variables. The analysis reveals that there is a one-waycausal effect running from industrial growth to services growth at the 5 per cent level of significance. The short-run results also reveal that there is uni-directional causality running from economic, industrial,and services growth to agriculturalgrowth at the 1 per cent level of significance with no feedback effects. The error correction term for the case of Tunisia is significant for economic and industrial growth, suggesting the existence of long-run causality from agricultural, industrial, and services growth to economic growth at the 10 per cent level of significance; and from economic, agricultural, and services growth to industrial growth at the 1 per cent level of significance. In the shortrun, however, there is evidence of bi-directional causality between economic growth and industrial growth, implying a two-way causal relationship between these two variables. The results also reveal that there is a uni-directional causal relationship running from services growth to industrial growth at the 5 per cent level of significance, and from agriculturalgrowth to economic growth at the 10 per cent level of significance, without any feedback effects. In the case of Comoros, the error correction term is significant for economicand services growth, indicating the presence of long-run causality from agricultural, industrial, and services growth to economic growth; and from economic, agricultural, and industrial growth to services growth at the 1 per cent level of significance, respectively. For short-run causality, however, there is no evidence of relationship between variables, except for a onedirectional causal relationship running from economic growth to services growth. Finally, the error correction term for the case of Jordan is significant for economic growth only, indicating the presence of longrun causality from agricultural, industrial, and services growth to economic growth at the 5 per cent level of significance. In the shortrun, however, there is evidence of a uni-directional causal relationship running from industrial growth to both economic and services growth at the 5 per cent and 10 per cent levels of significance, respectively, and from agriculturalgrowth to economic growth at the 5per cent level of significance, with no feedback effects. 5. Conclusion and Implications Much research has focused on the extent to which the agricultural sector is more important for growth than the industrial and services sectors; whether the industrial sector should be treated as the engine for growth; and how the services sector is linked to the other two sectors. It is widely believed that Arab world countries can enhance their overall economic growth and development by transforming each of their economic structures away from an agricultural base toward industry and services. Up until the mid-1970s, agricultureled growth policies prevailed in most Arab world nations, but the emphasis then shifted toward industrial promotion strategies in an effort to achieve stable economic growth and development in the long run. It was hoped that industrial-led growth strategies would result in better resource allocation, economies of scale and production efficiency through innovation, technological development, capital formation, and employment creation. In view of these considerations mainly, many policymakers in the Arab world have adopted

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Proceedings of 4th International Conference on Economics and Social Sciences (ICESS-2014) industrial expansion policies as part of their development strategies. Recently, however, the emphasis in some Arab world nations such as Tunisia, and Morocco, has shifted toward services-led growth strategies in an effort to follow the path of developed economies. However, a development strategy that does not fully take into account the interaction process between sectoral linkages and economic growth and their interdependencywill fall short and may be replaced quickly by another strategy. Consequently, it is extremely important to understand the role of economic sectors and their linkages to the rest of the economy. This study conducted an empirical investigation of the dynamic relationship between sectoral linkages and economic growth for eight Arab world nations using a co-integration and multivariate causality framework. The ADF andPP tests were used to check whether the time–series of variables under investigation were stationary. The co-integration test was performed to obtain the number of co-integrating vectors between series, and VECM Granger causality was employed to examine the nature of interdependence between variables. The present study strongly supports a long-run causal relationship between growth of the industrial sector and economic growth in the cases of Algeria, Egypt, Morocco, Saudi Arabia, and Tunisia, and between growth of the services sector and economic growth in the case of Algeria, Egypt, Mauritania, and Comoros. The results further predict a long-run causal relationship between growth of the agricultural sector and economic growth in the case of Saudi Arabia only. However, in the shortrun, there are strong feedback effects between industrial sector growth and economic growth in the case of Algeria and Tunisia only. There is also evidence of bi-directional causality between growth of the services sector and economic growth in Algeria and Saudi Arabia. There is no evidence of a bi-directional causal relationship between agriculturalgrowth and economic growth in any country. However, there is a uni-directional causal relationship running from agriculturalgrowth to economic growth in the case of Algeria, Tunisia, and Jordan. The converse causality (i.e. from economic growth to agricultural sector growth) is true for Egypt, Saudi Arabia, and Morocco. As for causal relationships between growth in the agricultural, industrial, and services sectors, there is no evidence in any country of a bi-directional short-run causal relationship from agricultural growth to either industrial or services sector growth. However, there is a uni-directional causal relationship from industrial sector growth to agricultural sector growth in the case of Egypt, Morocco, and Saudi Arabia, albeit with no evidence of converse causality in any country. The services sector does cause agricultural sector growth in the case of Saudi Arabia, and the converse causality is true for Algeria and Egypt only. The overall results of this research analysis have several policy implications that need to be considered when developing sustainable economic growth strategies appropriate for Arab world countries. These policy implications are highlighted as follows: - This study showed that the income of the Algerian economy depends largely on income generatedby the industrial and services sectors. These two sectors are key contributors to the success of economic growth and performance in this country. Thus, industrial and services sectors should remain the key priorities for government policies. - For the Saudi Arabian economy, the study revealed that economic growth and industrial sector growth independently affect the growth of other sectors in the economy. Thus, in order to sustain the agricultural and services sectors, high levels of industrial growth need to be maintained and developed. Otherwise, growth of the service and agricultural sectors will decline in tandem with any fall in industrial growth. Accordingly, diversification of the industrial sector and its sub-sectors should be the goal of future development strategies. - To some extent, the economic systems of Morocco and Tunisia follow the same pattern of development. The incomes of these two economies depend largely on income generated from the industrial sector, which in turn depends on growth of the services sector. Therefore, in order for these two countries to foster rapid, sustained, and broad-based growth, their industrial and services sectors should remain key priorities for government policies. - In the case of Jordan, income generated from the industrial and agricultural sectors contribute positively to the national economy. The contribution of the industrial sector,although relatively weak, has a significant positive impact on services sector income. In order to foster rapid economic growth, the Jordanian government should develop and strengthen strong linkages between economic sectors. Otherwise, the status quo would remain.

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For the Egyptian economy, our results revealed that growth in industrial production largely affects agricultural production, which in turn positively impactson services sector income. Therefore, the Egyptian government should pay extra attention to sustaining the linkagesbetween the agricultural and industrial sectors,a critical factor in supporting rapid economic growth and development in the country. In addition, linkages between the industrial and services sectors should be developed and strengthened. No clear policy implications can be drawn from our analysis for eitherthe MauritanianorComoran economies. The results clearly indicated a mismatch or mismanagement linkage between sectors and economic growth in these two countries. Given theirstrong agricultural background, public policy needs to be geared towards agricultural reforms and, at the same time, strengthening the agriculture–services relationship. Otherwise, the status quo would be maintained.

Overall, our results suggest that in order for Arab countries to be competitive in the current global economy, existingmacroeconomic strategies need to be supported by other complementary policies that would ensure the perpetuation of high-quality growth and development. The accelerationof human resource development, in particular betterskilled labour forces, welltrained human capital, knowledge, and innovation, are examples of suchcomplementary policies. To this end, this analysis was conducted by employing the availability of macroeconomic indicators. It might be useful for future research to expand the analysis to see the impact of these aggregate sectors (agriculture, industry, and services) behaviour towards more disaggregated subsectors. It is also important to point out that the foregoing results do not take into account the cross-country spillover effects of sectoral growth linkages. Recent theoretical and empirical literature has emphasised the neighbouring spillover effects of growth which may result from a number of factors including, for example, regionally conditioned perceptions of investors, trade linkages, factor mobility, and policy emulation. Further analysis along these and similar lines appears to be promising avenues for future research. References Adelman, I., J. Bourniaux, and J. Waelbroeck (1995) ‘Agricultural Development Led Industrialization in a Global Perspective’, in I. Adelman (ed) Institutions andDevelopment Strategies: The Selected Essays of Irma Adelman, Vol. 1, pp. 303–22. Brookfield, Vermont: Edward Elgar. Akaike, H. (1969) ‘Fitting Autoregression for Prediction’, Annals of the Institute of Statistical Mathematics 21: 203–17. Bhagwati, J.N. (1984) ‘Splintering and Disembodiment of Services and Developing Nation’, World Economy 7: 133–43. Blades, D., D.D. Johnson, and W. Marczewski (1974) ‘Service Activities in Developing Countries’. Paris: Organization for Economic Cooperation and Development. Blunch, N.-H.and D. Verner (2006) ‘Shared Sectoral Growth versus the Dual Economy Model: Evidence from Côte d’Ivoire, Ghana, and Zimbabwe’,African Development Review 18(3): 283–308. Campbell, J.Y. and P. Perron (1991) ‘Pitfalls and Opportunities: What Macroeconomists should know about Unit Roots’, in O.J. Blanchard and S. Fischer (eds) NBER Macroeconomics Annual, USA: MIT Press. Chenery, H.B. (1979) Structural Change and Development Policy. New York: Oxford University Press. Chowdhury, K. and M.B. Chowdhury (1995) ‘Sectoral Linkages and Economic Growth in Asia, Evidence from Granger Causality Test’, The Indian Economic Journal 42: 59–75. Craigwell, R., D. Downes, K. Greendige, and K. Steadmago (2005) ‘Sectoral Output Growth and Economic Linkages in the Barbados Economy over the Past Fifty Years’.CBB Working Paper. Barbados: Central Bank of Barbados. Dickey, D.A. and W.A. Fuller (1979) ‘Distribution of the Estimators for Autoregressive Time Series with a Unit Root’,Journal of the American Statistical Association 74: 427–31. Engel, R.E. and C.W.J. Granger (1987) ‘Cointegration and Error Correction: Representation, Estimation and Testing’,Econometrica 55: 251–76. Fei, J.C.H. and G. Ranis (1961) ‘A Theory of Economic Development’, American Economic Review 51: 533–65. Field, A.J. (1978) ‘Sectoral Shifts in Antebellum Massachusetts: A Reconsideration’,Explorations in Economic History 15: 146–71. Fuchs, V. (1968) The Service Economy. New York: National Bureau of Economic Research. Gemmell, N. (1982) ‘Economic Development and Structural Change, The Role of Service Sector’, Journal of Development Studies 19: 37–66.

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Proceedings of 4th International Conference on Economics and Social Sciences (ICESS-2014) Gemmell, N., T. Lloyd, and M. Mathew (1998) ‘Dynamic Sectoral Linkages and Structural Change in a Developing Economy’. Centre for Research in Economic Development and International Trade, Discussion Paper No 98/3. Nottingham: University of Nottingham. Hakkio, C.S. and M. Rush (1991) ‘Cointegration: How Short is the Long-Run?’,Journal of International Money and Finance 10: 571–81. Hirschman, A.O. (1958). The Strategy of Economic Development New York: Yale University Press. Hwa, E.C. (1988) ‘The Contribution of Agriculture to Economic Growth: Some Empirical Evidence’,World Development 16(11): 1329–39. Johansen, S. (1988) ‘Statistics Analysis of Cointegration Vectors’,Journal of Economic Dynamics and Control 12: 231–54. Johansen, S. and K. Juselius (1992) ‘Testing Structural Hypotheses in a Multivariate Cointegration Analysis of the PPP and the UIP for UK’,Journal of Econometrics 53: 211–44. Katircioglu, S.T. (2006) ‘Causality between Agriculture and Economic Growth in a Small Nation under Political Isolation: A Case from North Cyprus’,International Journal ofSocial Economics 33(4): 331–43. Kuzents, S. (1971) Economic Growth of Nations: Total Outputs and Productive Structure. Cambridge: Harvard University Press. Lewis, W.A. (1954) ‘Economic Development with Unlimited Supplies of Labor’,Manchester School of Economic and Social Studies 22(2): 139–91. MacKinnon, J.G. (1996) ‘Numerical Distribution Functions for Unit Root and Cointegration Tests’, Journal of Applied Econometrics 11(6): 601–18. MacKinnon, J.G, A. Haug, and L. Michelis (1999) ‘Numerical Distribution Functions of Likelihood Ratio Tests for Cointegration’,Journal of Applied Econometrics 14(5): 563–77. Mokyr, J. (1976) Industrialization in the Low Countries, 1795–1850. New Haven, CT: Yale University Press. Nelson, C.R. and C.I. Plosser (1982) ‘Trends and Random Walks in Macroeconomic Time Series: Some Evidence and Implications’, Journal of Monetary Economics 10: 139–62. Ocampo, J.A. (2005) ‘The Quest for Dynamic Efficiency: Structural Dynamics and Economic Growth in Developing Countries’,in J.A. Ocampo (ed) Beyond Reforms—Structural Dynamics and Macroeconomic Vulnerability,pp. 3–43. Palo Alto: Stanford University Press. Phillips, P.C.B. and P. Perron (1988) ‘Testing for a Unit Root in Time Series Regression’, Biometrika 75: 335– 46. Rashid, A. (2004) ‘Sectoral Linkages; Identifying the Key Growth Stimulating Sector of the Pakistan Economy’, MPRA Paper 27210. Rostow, W.W. (1960) The Stages of Economic Growth: A Non-Communist Manifesto. Cambridge, UK: Cambridge University Press. Schwarz, G. (1978) ‘Estimating the Dimension of a Model’, The Annals of Statistics 6: 461–4. Singer, H. (1979) ‘Policy Implications of the Lima Target’,Industry and Development 3: 17–23. Subramaniam V. and M. Reed (2009) ‘Agricultural Inter-Sectoral Linkages and its Contribution to Economic Growth in the Transition Countries’. Paper presented at theInternational Association of Agricultural Economists Conference, Beijing, China, (16–22 August). Tiffin, R. and X. Irz (2006) ‘Is Agriculture the Engine of Growth?’,Agricultural Economics 35(1): 79–89. Todaro, M.P. and S.C. Smith (2012) Economic Development.11th Edition.USA: Addison Wesley Publishing Company Inc. Vogel, S.J. (1994) ‘Structural Changes in Agriculture: Production Linkages and Agricultural Demand-led Industrialization’,Oxford Economic Papers 46(1): 136–56. Wright, G. (1979) ‘Cheap Labour and Southern Textiles before 1880’, Journal of Economic History 39: 313–48.

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Proceedings of 4th International Conference on Economics and Social Sciences (ICESS-2014) Figure 1: Logs of Economic Growth (GDP), Agriculture, Industry, and Services Value Added in Eight Selected Arab Countries Saudi Arabia, 1968–2012 Algeria, 1968–2012 27

26

GDP 26

GDP

25

Industry 25

Services

Industry

24

Services 24 23 23

Agriculture Agiculture 22

22

21

21 1970

1975

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Egypt, 1968–2012

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25.2

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GDP

24.8

24.4

24.4

24.0

Services

Services

24.0 23.6 23.6

Industry

Industry

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23.2 22.8

22.8

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GDP

GDP

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21.0

Services

23

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18.5 1970

1975

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1980

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Services

22

18.8

Agricutlure

Industry

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18.4 18.0

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Industry

17.6

Agriculture

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1980

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1985

1990

1995

2000

2005

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Proceedings of 4th International Conference on Economics and Social Sciences (ICESS-2014) Table 1: Sectoral Share in GDP – Arab World Countries Country Algeria Egypt Mauritania Morocco Saudi Arabia Tunisia Comoros Jordan Arab World

Sector Agriculture Industry Services Agriculture Industry Services Agriculture Industry Services Agriculture Industry Services Agriculture Industry Services Agriculture Industry Services Agriculture Industry Services Agriculture Industry Services Agriculture Industry Services

1970 9.2 45.5 45.2 29.4 28.1 42.3 29.3 38.4 32.3 26.3 25.3 41.2 4.5 62.5 33.9 19.7 23.8 56.4 N/A N/A N/A 11.6 18.9 69.3 7.2 57.3 35.4

1980 8.5 57.6 33.8 18.2 36.7 44.9 30.2 25.9 43.6 18.4 31.0 50.4 0.98 71.5 27.4 16.3 35.9 47.7 34.0 13.1 52.8 7.8 24.1 67.9 6.2 57.8 37.0

1990 11.3 48.1 40.4 19.3 28.6 51.9 29.6 28.8 41.5 18.2 33.4 48.3 5.7 48.7 45.4 17.7 33.6 48.6 41.4 8.2 50.3 7.7 26.2 66.0 9.4 45.3 45.3

2000 8.8 58.6 32.5 16.7 33.1 50.1 36.6 27.9 35.3 14.9 29.1 55.9 4.9 53.9 41.1 11.3 30.3 58.3 48.5 11.5 39.9 2.3 25.5 72.1 7.9 47.8 40.6

2010 8.6 51.4 39.9 13.9 37.5 48.4 17.3 45.4 37.1 15.3 29.6 54.9 2.3 58.5 39.0 7.9 31.0 60.9 46.3 12.1 41.2 3.4 30.7 65.8 6.1 49.0 41.4

Source: World Bank Indicators database website, http://data.worldbank.org/indicator Table 2: Stationary Test Results Countries Variables Algeria (1968–2012) lngdp lnagr lnind lnserv Egypt (1968–2012) lngdp lnagr lnind lnserv Mauritania (1968–2012) lngdp lnagr lnind lnserv Morocco (1968–2012) lngdp lnagr lnind lnserv Saudi Arabia (1968–2012) lngdp lnagr lnind lnserv Tunisia (1968–2012) lngdp lnagr lnind lnserv Comoros (1980–2012) lngdp lnagr

ADF Level

1st Difference

PP Level

1st Difference

-2.256 -0.382 -1.525 -0.737

-8.280* -8.234* -8.143* -2.847*

-2.316 -0.539 -1.052 -0.737

-8.041* -14.45* -17.88* -6.739*

-1.765 1.475 -1.447 -3.596

-3.597* -8.029* -4.375* -4.231*

-1.503 0.912 -1.447 -2.974

-3.686* -8.674* -4.375* -4.510*

1.118 -2.423 0.059 -1.085

-7.931* -8.062* -7.141* -4.911*

2.468 -2.366 1.131 -1.093

-7.914* -8.471* -8.164* -4.753*

-0.742 -0.465 -1.794 -1.045

-11.14* -13.54* -6.855* -9.210*

-0.909 -1.495 -1.873 -2.564

-10.64* -14.39* -6.884* -9.131*

-2.994** -1.944 -2.-21 -2.431

-3.116** -1.742 -4.739* -2.650***

-2.781 -1.958 -2.019 -2.583

-3.071** -5.776* -4.785* -2.780***

-2.353 -1.592 -3.437** -1.293

-6.562* -4.735* -5.541* -6.058*

-2.712*** -1.821 -3.809** -1.281

-6.562* -9.548* -5.772* -6.067*

-1.387 -1.596

-7.806* -6.168*

-1.427 -1.687

-7.749* -6.168*

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Jordan (1980–2012)

lnind lnserv

-1.027 -3.162**

-4.614* -5.620*

-1.027 -3.201**

-4.622* -5.072*

lngdp lnagr lnind lnserv

0.808 -0.993 1.019 0.985

-3.903* -6.679* -2.532 -3.895*

0.303 -0.899 0.765 0.985

-3.777* -6.719* -4.990* -3.931*

Notes: *, **, and *** denote statistical significance at 1%, 5%, and 10% levels, respectively. ADF and PP critical values are based on Mackinnon (1996) one-sided p-values. Lag length criteria follows the AIC criterion. lngdp, lnagr, lnind, and lnserv denote the natural logarithms of economic growth (GDP), agriculture, industry, and services value added. Table 3: Co-integration Test Results Null Alternative Algeria (Lag = 2) r=0 r=1 r≤1 r=2 r≤2 r=3 r≤3 r=4 Egypt (Lag = 2) r=0 r=1 r≤1 r=2 r≤2 r=3 r≤3 r=4 Mauritania (Lag = 1) r=0 r=1 r≤1 r=2 r≤2 r=3 r≤3 r=4 Morocco (Lag = 1) r=0 r=1 r≤1 r=2 r≤2 r=3 r≤3 r=4 Saudi Arabia (Lag = 3) r=0 r=1 r≤1 r=2 r≤2 r=3 r≤3 r=4 Tunisia (Lag = 1) r=0 r=1 r≤1 r=2 r≤2 r=3 r≤3 r=4 Comoros (Lag = 1) r=0 r=1 r≤1 r=2 r≤2 r=3 r≤3 r=4 Jordan (Lag = 1) r=0 r=1 r≤1 r=2 r≤2 r=3 r≤3 r=4

𝜆-trace

Statistics

5% CV

Prob.

56.283 18.682 5.697 1.569

47.856 29.797 15.494 3.841

114.04 46.906 22.038 3.134

𝜆-max

Statistics

5% CV

Prob.

0.006 0.515 0.730 0.210

37.600 12.985 4.127 1.569

27.584 21.131 14.264 3.841

0.001 0.453 0.848 0.210

47.856 29.797 15.494 3.841

0.000 0.000 0.004 0.076

67.142 24.867 18.904 3.134

27.584 21.131 14.264 3.841

0.000 0.014 0.008 0.076

54.295 24.527 7.653 3.079

47.876 29.797 15.494 3.841

0.011 0.179 0.503 0.079

29.767 16.873 4.573 3.079

27.584 21.131 14.264 3.841

0.025 0.178 0.794 0.079

56.852 30.331 11.815 2.227

47.856 29.797 15.494 3.841

0.005 0.043 0.166 0.135

29.520 18.515 9.588 2.227

27.584 21.131 14.264 3.841

0.027 0.117 0.240 0.135

87.727 25.859 9.467 0.0001

47.876 29.797 15.494 3.841

0.000 0.133 0.323 0.992

61.867 16.391 9.467 0.0001

27.584 21.131 14.264 3.841

0.000 0.202 0.249 0.992

52.270 29.367 14.321 0.596

47.876 29.797 15.494 3.841

0.018 0.056 0.074 0.439

28.903 15.045 13.725 0.569

27.584 21.131 14.264 3.841

0.039 0.285 0.600 0.439

63.317 29.435 11.249 0.325

47.876 29.797 15.494 3.841

0.000 0.055 0.196 0.568

33.881 18.186 10.924 0.325

27.584 21.131 14.264 3.841

0.006 0.123 0.158 0.568

52.168 23.992 7.566 0.688

47.876 29.797 15.494 3.841

0.018 0.200 0.512 0.406

28.176 16.425 6.877 0.688

27.584 21.131 14.264 3.841

0.042 0.201 0.503 0.406

Notes: CV denotes critical value.

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Proceedings of 4th International Conference on Economics and Social Sciences (ICESS-2014) Table 4: Multivariate Causality Test Results Dependent Variable Algeria (lag = 2) ∆lngdp ∆lnagr ∆lnind ∆lnserv Egypt (lag = 2) ∆lngdp ∆lnagr ∆lnind ∆lnserv Mauritania (lag = 1) ∆lngdp ∆lnagr ∆lnind ∆lnserv Morocco (lag = 1) ∆lngdp ∆lnagr ∆lnind ∆lnserv Saudi Arabia (lag = 3) ∆lngdp ∆lnagr ∆lnind ∆lnserv Tunisia (lag = 1) ∆lngdp ∆lnagr ∆lnind ∆lnserv Comoros (lag = 1) ∆lngdp ∆lnagr ∆lnind ∆lnserv Jordan (lag = 1) ∆lngdp ∆lnagr ∆lnind ∆lnserv

χ2- statistics Short run (Wald test) ∆lngdp ∆lnagr

∆lnind

∆lnserv

0.150 51.31* 7.310**

5.434*** 4.408 1.424**

43.32* 2.063 26.44*

72.18* 2.984 94.70* -

0.007 0.138 0.429* 0.776*

22.23* 5.679*** 4.068

0.236 1.091 8.436**

2.339 8.462** 2.084

3.725 23.46 0.549 -

0.626* 0.424* 0.475 1.029*

0.537 0.130 0.064

1.342 0.038 0.169

0.001 0.318 0.014

0.127 1.030 0.044 -

0.033 0.695 0.522 1.939*

5.872** 1.182 2.360

0.097 1.656 1.419

4.123** 6.964* 0.516

0.255 2.263 2.789*** -

0.214 5.413 1.822* 0.105

12.29* 1.972 14.87*

5.567 3.774 0.365

3.444 11.51* 9.545**

7.899** 15.54* 4.372 -

0.509** 1.063* 0.968*** 0.026

0.159 4.533** 0.786

3.423*** 1.470 2.318

2.988*** 1.211 0.733

1.345 0.374 3.784** -

0.682*** 0.246 1.633* 0.461

1.451 2.848 7.123**

1.190 2.275 4.281

2.013 0.989 2.823

1.783 1.110 2.030 -

1.189* 0.627 0.307 2.459*

0.827 0.102 2.077

5.715** 0.650 2.077

4.886** 1.398 2.819***

1.619 0.179 1.202 -

1.227** 1.167 1.186 0.064

ECTt-1

Notes: *, **, and *** represent statistical significance levels at 1%, 5%, and 10%, respectively.

267