"Building Knowledge Economy (KE) Model for Arab Countries" DR. Thamer M. Zaidan Alany Professor of Econometrics And Director of Economic Relation Department, League of Arab States League of Arab States P.O. Box 11642 Cairo Egypt Email: thameralany@ hotmail.com 00201223311152 00201221761119 2016 1
1. The purpose of this study is to build an Econometric Model for knowledge economy (KE) for Arab countries for the period 2000-2015, based on the definitions of the WB. The study uses some assumptions to choose important variables out of large sets of KBE indicators and applies Generalized least squares(gls) (Cross Section weights) technique to investigate the most important variables behind the successful countries in the Arab region in transition towards KBEs. 2. The knowledge revolution and the technological and economic changes it implies clearly entail the need to rethink countries overall development strategies. Knowledge and innovation-related policies should be at the core of those strategies, which, we will argue, should be built on four pillars, economic and institutional, education and training, information technology and innovation. 3. Each of the four pillars in the KE framework must function efficiently in order to spur knowledge-driven growth. But more is needed: investments, in the four pillars must be balanced and coordinated so that the pillars interact to produce benefits greater than those obtainable from their independent operation. Figure 1 illustrates the relationship among the four pillars that make up the knowledge economy. Note that the economic and institutional regime is the base on which the other three pillars are erected. The interdependence of the pillars is illustrated by a few simple relationships. 2
Figure 1 : The Four Interactive Pillars of the Knowledge Economy for Arab Countries GDPPC : Per capita GDP ECO1: Free Trade ( Tariff and nontariff barriers) ECO2: Government efficiency ECO 3: Regulatory Quality EDU1: Gross Enrollment rate in Primary education EDU2 : Gross Enrollment rate in secondary education EDU3: Gross Enrollment rate in Higher education EDU4: Adult literacy rate (% age 15 and above) IT1: Telephone subscriptions per 100 population IT2: Mobile subscriptions per 100 population IT3:Internet Users per 100 population INN1: scientific and technical Journal articles per 1 million population INN2: Patents and Trademarks per 1 million population INN3: FDI as a percentage of GDP 3
Table 1 : The Economic and Institutional Variables Pillar of the Knowledge Economy for Arab Countries : Econometric Model By using data for Arab countries for the period 2000-2015, Economic and Institutional variables had statistically significant effects on economic growth and growth of per capita GDP for Arab Countries (Table 1). Variables Intercept ECO1 ECO2 ECO3 Regression coefficient 5.89 0.63-0.21 0.20 t-statistics 21.90 10.48-2.99 3.09 R 2 =0.97 F-Statistic= 347.3 R 2 = 0.96 D.W = 1.9 GDPPC = 5.89 + 0.63 ECO1-0.21 ECO2 + 0.20ECO3 (t) (21.90) (10.48) (-2.99) (3.09) (1) R 2 = 0.96 D.W=1.9 F= 347.3 4
According to the behavioral equation 1, of the econometric model, the most important variables of the economic and institutional pillar are Free trade (Tariff and nontariff barriers) ECO1 and regulatory quality ECO3, which are effecting significantly positively on per capita GDP (GDPPC), while government efficiency ECO2 is effecting negatively on GDPPC. The results show that 1 percent increase in ECO1 will increase GDPPC by 0.63 percent when other variables kept constant and so on, as well as the result indicate that the coefficient of determination R 2 means that the variations in the explanatory variables explain about 96 percent of the variations in the GDPPC. The F test indicates the significance of the whole model. The D.W test points out no existence of auto correction. 5
In the same way, school enrollment rates at the primary, secondary and higher education as proxies for initial human Capital, found that enrollment rates had statistical significant effects on growth of per capita GDP (Table 2). Table 2: The Education and training base Variables Pillar of the Knowledge Economy for Arab Countries : Econometric Model Variables Intercept EDU1 EDU2 EDU3 EDU4 Regression coefficient -5.48-3.8 0.48 0.20 2.99 t-statistics -7.69-2.69 3.93 4.55 18.27 R 2 =0.98 F-Statistic=517.1 R 2 = 0.97 D.W = 1.8 GDPPC = -5.48-3.8 EDU1 + 0.48 EDU2 + 0.20 EDU3 + 2.99 EDU4 (t) (-7.69) (-2.69) (3.93) (4.55) (18.27) R 2 = 0.97 D.W=1.8 F= 517.1 (2) 6
A growing body of evidence shows that ICTs contribute to a country s overall economic growth-and not just growth in its ICT sector (table 3). Table 3:The Information Technology Variables Pillar of the Knowledge Economy for Arab Countries : Econometric Model Variables Intercept IT1 IT2 IT3 Regression t-statistics coefficient 8.01 94.10-0.134-3.35 0.09 6.49 0.17 11.19 R 2 =0.99 F-Statistic=986.1 R 2 = 0.98 D.W = 1.9 GDPPC = 8.01 0.134 IT1 + 0.09 IT2 + 0.17 IT3 (t) (94.10) (-3.35) (6.49) (11.19) (3) R 2 = 0.98 D.W=1.9 F= 986.1 7
The study have shown that innovation and the generation of technical knowledge have substantial effects on economic growth and growth in productivity (Table 4). Table 4: The Innovation Variables Pillar of the Knowledge Economy for Arab Countries : Econometric Model Variables Intercept INN1 INN2 INN3 Regression coefficient 6.60 0.44 0.19 0.10 t-statistics 68.67 15.88 5.34 4.20 R 2 =0.97 F-Statistic=461.9 R 2 = 0.96 D.W = 1.9 GDPPC = 6.60 +0.44 INN1 + 0.19 INN2 + 0.10 INN3 (t) (68.67) (15.88) (5.34) (4.20) R 2 = 0.96 D.W=1.9 F= 461.9 (4) 8
We have seen that each of the four pillars in the KE framework functioned efficiently in order to spur knowledge- driver growth. But more is needed; investments in the four pillars must be balanced and coordinated so that the pillars interact to produce benefits greater than those obtainable from their independent operation (Table 5). Table 5:The Four Interactive Pillars of the Knowledge Economy for Arab Countries : Econometric Model Variables Intercept ECO1 ECO2 ECO3 EDU1 EDU2 EDU3 EDU4 INN1 INN2 INN3 IT1 IT2 IT3 Regression t-statistics coefficient 4.6 4.86 0.08 1.92 0.09 2.57 0.01 0.28 0.11 0.84-0.15-1.43-0.076-2.26 0. 655 3.42 0.069 2.48 0.11 4.62 0.02 1.57-0.13-3.37 0. 10 7.10 0.11 6.33 R 2 =0.99 F-Statistic=758.97 R 2 = 0.97 D.W = 2.0 9
Table 6 : The positive effect of knowledge Economy on per capita income in Arab countries (2000-2015). The country Qatar UAE Kuwait Morocco Bahrain Saudi Arabia Oman Lebanon Iraq Mauritania Elasticity The effect 2.027 1.620 1.475 1.078 0.921 0.889 0.776 0.097 0.081 0.081 Source : prepared by the author according to Eviews software Ranking 1 2 3 4 5 6 7 8 9 10 The countries which have no positive effect of knowledge on per capita income are, Tunisia(-0.138), Egypt (-0.682), Syria (-0.812), Jordan(-0.857), Algeria (-0.762), Yemen (-0.420), Libya (-1.184), Sudan(-1.164),Djibouti(-1.528),Palestine(-1.042). It means that there is no significant effect of knowledge on per capita income in these Arab countries. 10
Knowledge Economy Index (KEI) The KEI 2012 ranking for 146 countries presents Sweden retains its first place position as the world's most advanced knowledge economy, with a 2012 KEI of 9.43, followed by Finland in the second place, Denmark in the third place, Germany 8 place, Taiwan 13 place, Hong kong18 place. While Japan has taken 22 place, Singapore 23 place, Korea Rep, 29 place and Greece 36 place. The KEI is based on a simple average of four sub indexes, which represent the four pillars of the KE: economic incentive and institutional regime (EIR), innovation and technological adoption, education, training and information and communication technologies (ICT) infrastructure. Table (7), also lists Kuwait, Jordan, Morocco and Egypt with largest decreases in KEI ranking between 2000 and 2012 due to deterioration in their EIR and ICT pillars. 11
Table (7) Knowledge Economy Index (KEI) for some Arab Countries Economy 2012 Rank KEI 2012 2000 Rank Bahrain 43 6.9 41-2 Egypt 97 3.78 88-9 Jordan 75 4.95 57-18 Kuwait 64 5.33 46-18 Morocco 102 3.61 92-10 Oman 47 6.14 65 18 Qatar 54 5.84 49-5 Saudi Arabia 50 5.96 76 26 United Arab Emirates 42 6.94 48 6 Source: World Bank, knowledge for Development database. Change from 2000 12
Conclusion * The results of the econometric model, show Free Trade (Tariff and nontariff barriers) and regulatory quality in Economic and Institutional Pillar, Gross Enrollment rate in secondary education, Gross Enrollment rate in Higher education and Adult literacy rate (% age 15 and above) in education and training Pillar, Mobile subscriptions per 100 population and Internet Users per 100 population in information technology Pillar, scientific and technical Journal articles per million population and Patents and Trademarks per 1 million population and FDI as a percentage of GDP in Innovation Pillar, are generally the most important variables for the Arab countries in transition into knowledge economy KE, and have positive effect on per capita GDP. * According to the econometric model and the four interactive pillar of the knowledge Economy, the Arab countries which have positive effect on economic growth of per capita income are Qatar,UAE,Kuwait, Morocco, Bahrain, Saudi Arabia, Oman, Lebanon, Iraq, Mauritania, while the study found that there is no significant effect of knowledge Economy on Per Capita income, in Tunisia, Egypt, Syria, Jordan, Algeria, Yemen, Libya, Sudan, Djibouti and Palestine. * Based on the findings, the study recommends that to improve transition to knowledge economy, It is essential for Arab countries to strengthen and improve knowledge Economy Index (KEI) by investing heavily in human capital, mainly education and training, boosting innovation through intensive spending on research and development, improve innovation pillar, capacity for innovation, localization of technology and enhance global innovation index, knowledge absorption index, and bridge the gap between outputs of education system and labor market needs, promoting technical and vocational education and removing the stigma attached to that kind of education in the Arab region. 13