Human Capital Investment and Economic Growth in Saudi Arabia: Error Correction Model

Transcription

1 International Journal of Economics and Financial Issues ISSN: available at htt: International Journal of Economics and Financial Issues, 27, 7(4), 4-2. Human Caital Investment and Economic Growth in Saudi Arabia: Error Correction Model Abla A. H. Bokhari* Deartment of Economics, Faculty of Economics and Administration, King Abdulaziz University, Jeddah, Saudi Arabia. * ABSTRACT To examine the relationshi between investment in human caital and economic growth in the Kingdom of Saudi Arabia for the eriod Quantitative research design has been imlemented. Granger Causality aroach has been emloyed, followed by error correction model. The data stationarity and integration order have been tested, using the augmented Dickey-Fuller. Any long-run or short-run causality was not observed between exenditure on education and economic growth (er caita gross domestic roduct). 73.6% variation has been indicated by fixed caital formation of gross national roduct, which is considered as an effective asect. The results indicated that results are statistically significant with P value (.) at 5% level of significance. Investment in human caital, with the right olicy assessments and rehabilitation, can be translated into an essential element of growth in the Saudi economy. Keywords: Economic Growth, Human Caital, Error Correction model JEL Classifications: G, G, G38. INTRODUCTION Human caital alludes mainly to heath, education on-job training. According to Imran et al. (22) the aggregation of the innate abilities and the knowledge and skills that individuals acquire and develo throughout their lifetime. According to OCEL Reort, human caital can be termed as the knowledge, skills, cometencies and attributes embodied in individuals that facilitate the creation of ersonal, social and economic well-being (OCED, 2.. 8). The human caital and economic growth relationshi lingered as an imortant subject matter in the literature of economic theory. It is coiously used in both historical literature and economic research. Nowadays, there is exanding evidence on the significance of human caital investment in sustaining economic growth. In Saudi Arabia, a considerable emhasis on human research was laced due to its essential role in accomlishing the objectives of socio-economic develoment and growth. Allocations assigned for human resources develoment, witnessed a remarkable continuous increase during the country s develoing rocess, and its nine (5-year) lans (97-25). Exenditure on human resource develoment accounted for SR7 billion during the first rogram (97-975), while investment in social and health amounted to SR3.5 billion. Maintaining to give riorities for human resources, the country allocated SR73.5 billion (5.6% of total Government Exenditure on develoment) for human resources during the ninth lan, and SR273.9 billion (8.96) for social and health (Ministry of Economics and Planning, 24). Coing with raid worldwide economic and technological changes, Saudi Arabia focuses on utting more efforts and rograms for the sake of develoing its human resources caacities. Desite this, several challenges need further efforts targeting the develoment of human resources. In addition to the heavy reliance on oil, Saudi Arabia is facing several economic challenges in term of its human resources. The rimary intention of the study was to find the imact of Saudi Arabian investments on human resources and economic growth. Exenditure on health and education was used as roxies for human caital investments. The fixed caital formation was the roxy for hysical caital, and economic growth was exlained by er caita gross domestic roduct (GDP). This amount was mainly allocated for education. 4 International Journal of Economics and Financial Issues Vol 7 Issue 4 27

2 Bokhari: Human Caital Investment and Economic Growth in Saudi Arabia: Error Correction Model The error correlation model has been alied to examine the human caital investment and economic growth in Saudi Arabia. The strong connection between the error correction and cointegration models stems from the Granger theorem of reresentation. This theorem states that two or more integrated time series, which are cointegrated have a reresentation of error correction. Precisely, these concets are isomorhic as each idea imlies of others. It is imortant that the statistically model integrated data must make reference to the many econometric error correction models (ECMs) (Grant and Lebo, 26). The causal relationshi is carried out for the eriod 97-24, following Granger causality and ECM aroaches. The study has been divided into three sections. The theoretical framework regarding the association between human caital and economic growth is reresented in the first section. Also, a brief of revious emirical studies has been reviewed. The second section concerns with the emirical model of investigating the relationshi between investment in human caital and economic growth. Estimates are carried out through E-views statistical ackage. Johansen (99) co-integration aroach has been erformed, followed by ECM and Granger causality test. In the third section, finally, the emirical results discussion, and resent some concluding remarks have been summarized. 2. THEORETICAL FRAMEWORK Economists have long recognized human resource as an essential element of nations wealth. The idea that investment in human resources results in increased economic growth, date back to the time of Smith (776), or even earlier 2. In this book Wealth of Nations, Smith introduced human being as a art of the nations wealth, by which he develoed the basic concets of growth theory. Subsequently, many other scholars involved imortance to the idea of human caital as an investment that generates a return. However, these contributions had not been firmly develoed into theoretical formation till the second half of the twentieth century. In ursuit of the usurge of growth theory in the 95s and 96s, the relationshi between human caital and economic growth gained increasing visibility and had been extensively discussed in the economic literature. A growing attention was given to the quality of labor, esecially the level of education and training. Based on Solow s (956), the contribution and the analysis of growth accounting turn out to be increasingly revalent. Following by Chicago school studies (Schultz, 96; Becker, 29), the obvious entrant was human caital. Earlier, economists limited their views of human caital to the imortance of acquired skills through education from which better oortunities and salary differentiation can be accrued. In its lace, Chicago school theories measured the imact of human caital on economic growth at the macro level. Theodore Schultz (96) 3 layed a crucial role in emerging the awareness for the imortance of human caital investment. It has mainly recognized the human caital as one of the imortant factors that determine economic growth. This theory concentrated on the investment in human caital that yields a return over an extended eriod. Six major categories have been discussed: Healthcare services and facilities; on-job training; formal education, elementary, secondary and higher levels; study rograms for adults; and migration for the sake of job oortunities. Becker (29) develoed the main idea of what is termed as the economic aroach of human behavior, resenting education as an instrument to obtain qualified and better-aid job oortunity. Investment logic was atiently embraced when seaking about education and training, using the imact of differences in abilities and differences in oortunities. Later, Becker the work of 962, defined human caital theory in terms of the individuals investment in education u to the oint, where their return from extra income will be equal to the cost of education 4. Subsequently, the endogenous theories of growth focus on the significance of human caital on economic growth and emerging a notable ioneering study in this field (Romer, 986; Barro, 99). Similar to hysical caital, Lucas (988) clarified human caital as a factor of roduction in theory. It has been claimed that the accumulation of human caital is accountable for a sustained economic growth. Barro (99) declared that educational situation of a country is considered as a motor generating tool for economic growth. Thus, based on this theory, Human caital imact on economies aear mainly through caital accumulation, which is generated through education and health. When the society education and the oulation health (human caital) increase, the roductivity increases, and corresondingly, welfare and economic growth increase. Over the last four decades, a large body of literature on economic growth has been roduced exloring the association between human caital investment and economic growth directly. A large number of growth regressions including human caital variables have been resented. In this study, Barro (99) alied data for 98 countries for the eriod , where the school enrollment rates of 96 were used as a roxy for human caital as related to the real growth rate er caita GDP. The results showed that % ercentage increase in the enrollment of rimary school and secondary school caused 2.5% and 3% increase in GDP growth resectively. It has been concluded that there is a significant difference between the GDP growth and education. Akolat (24) studied the long-run imact of both human and hysical caitals on economic growth, using the anel data set of thirteen develoed and eleven develoing countries. The results suggested that the effect of hysical caital and education exenditures on economic growth during 97-2 in the develoed countries was higher than effects in the develoing countries. Inversely, the influence of life exectancy at birth on economic growth is higher in the develoing countries. 2 The concet of co-integration has been introduced by Granger (983) followed by Engle and Granger (988), then tested with the VAR aroach by Johansen (988). Johansen method allows for more than one cointegrating regression, unlike the Engle Granger aroach. 3 Schultz is a Nobel Prize-winning economist who was credited for embedding the concet human caital, and he was the first to relate roductivity and education. 4 In his Nobel lecture The economic way of looking at life, ublished by Journal of Political Economy. International Journal of Economics and Financial Issues Vol 7 Issue

3 Bokhari: Human Caital Investment and Economic Growth in Saudi Arabia: Error Correction Model Various theoretical literatures assessed the imortance of human caital as an element of the economic growth; emirical studies revealed conflicted results and human caital has been deicted as a driver of economic growth for develoing countries as well (Hanushek, 23; Whalley and Zhao, 23; Murhy and Toel, 26). Human caital rovides with the skills and knowledge that is brought by an individual to an organization (Hanushek, 23). Some of them state that human caital ositively affects the economic growth, while some deny the existence of any relation between economic growth and human caital comonents. Their mixed and ambiguous results may be due to several reasons, which includes the adoted methodology and estimating aroach, surious regressions, data quality and the selected variables as roxies for human caital. 3. EMPIRICAL STUDIES Human caital is introduced differently in emirical studies deending on the theory, and often been measured concerning exlicit knowledge and cognitive skills. Hence, education and training are considered as key contributors to knowledge and exertise develoment and used to influence the human caital imact in the roduction and growth rocess (Wilson and Briscoe, 24). While, Barro (99) measured school enrollment rates for the urose of examining the association between economic growth and human caital. Some other economists estimated the stock of human caital emloying different educational factors such as education exenditure (Akolat, 24), tertiary education (Chudárková and Verner, 22), quality of schooling (Hanushek and Kimko, 2) 5, skilled-adults (Romer, 986) or research and develoment (R and D) (Khan et al., 25). Factors such as high-level qualification; the level of graduation outut; the number of hours er week sent on self-study; rates of return to education; matching of education to occuation; and many others are mentioned by OCED (2) 6. Mostly, standard health indicators used in literature included the ublic sending on healthcare exenditure (Elmi and Sadeghi, 22); er caita health exenditures (Hassan and Kalim, 22); numbers of beds in medical institutions (Taban, 26); life exectancy at birth (Akolat, 24; Taban, 26). Regarding the society, health level is an essential element that contributes to human caital; Taban (26) examined the causal relationshi between health and economic growth in Turkey. Several health indicators have been used in the matter of its relation to economic growth. The number of beds in medical institutions, the number of ersons er health care roviders, and life exectancy at birth were utilized as roxies for human caital. All revious indicators have found a causal relation with GDP, excet the number of medical institutions. Rivera and Currais (23) investigated the effect of health investment on roductivity in Organization for Economic 5 However, Hanushek and Kimko (2) does not attemt to use alternative formulations of modeling alication, but rather they concentrate on constructing new measures of labor-force quality and student cognitive erformance. These two factors were found to be necessary for growth. 6 A total of 24 factors are introduced to measure human caital by the OECD in 2 on The Well-being of Nations: The Role of Human and Social Caital. Co-oeration and Develoment (OECD) countries emloying log-linear equation based on the augmented Solow model. The results have shown the ositive imact in the health sector of the economy (Helliwell et al., 24). With the higher rates of human caital and hysical accumulation, long-term sustainable economic growth is established. It relies on the caability of economy to assemble financial resources and to ensure the admittance by eole to the roductive assets, which must be invested more effectively. This rocess may review the role that financial institutions have layed in growth and financial intermediation, exlicitly to assemble the savings and allocate them to most growth-romoting and roductive activities. The main disute is that greater financial intermediation, rovides rise to the higher roductivity; and thus, obtaining higher national income/er caita (Mahran, 22). A study by Mahran (22) examined the emirical association between financial intermediation and economic growth for Saudi Arabia during the last decades. The autoregressive distributed lag technique has been adoted to co-integrate the related ECM. The results indicated that financial intermediation has influenced negatively on long-run real GDP desite the minimal limitations imosed on the working of domestic financial system. Samargandi et al. (24) investigated the influence of the financial develoment on economic growth concerning the oil-rich economy of Saudi Arabia. By doing so, a difference has been established between the influences of financial develoment on the non-oil or oil sectors of the economy. The results have evaluated that the financial develoment has a ositive effect on growth of the associated non-oil sectors. In comarison, its effect on the total GDP growth and oil-sector growth is either insignificant or negative. It has been recommended that the association between the growth and financial develoment might be essentially diverse in resource dominated economies. Other studies confirmed the ositive bidirectional causality between human caital and economic growth in the short-run or the long-run terms, the role of hysical and human formation has also been studied (Tang, 2; Aka and Dumont, 28; Bilgili and Ozturk, 25). Following the EMC methodology, Rahman (2) found bidirectional causality between education exenditure and GDP in Bangladesh for the eriod Elmi and Sadeghi (22) revealed that there is a unidirectional short-run causality from GDP to health care sending in develoing countries during the eriod Hussin et al. (22) found that economic growth has a bidirectional longrun with education and labor while, in the short-run Granger causality indicated a significant coefficient of education. Whereas, insignificant coefficient of labor as related to GDP growth in Malaysian economy was also indicated during the eriod Hassan and Kalim (22) found long-run triangular bidirectional causality between education, health and GDP in Pakistan during Rehman et al. (24) suggested bidirectional causality in long-run and short-run causality between enrollment in both rimary and high schools and economic growth. However, a significant imact aears 6 International Journal of Economics and Financial Issues Vol 7 Issue 4 27

4 Bokhari: Human Caital Investment and Economic Growth in Saudi Arabia: Error Correction Model for rimary school comared to high school enrollment on the economic growth in Pakistan. Figure : Procedure to evaluate the imact of human caital investment on the economic growth in Saudi Arabia 4. METHODOLOGY The imact of human caital investment on the economic growth in Saudi Arabia during has been evaluated by utilizing qualitative and quantitative method. Augmented Dickey-Fuller (ADF) unit root tests was alied to test the data roerties and their stationarity. The existence of log-run relationshi between the series of variable was evaluated. Vector ECM (VECM) was established to identify short-run relationshi and error correction term (ECT). Granger causality was alied to examine the evidence of a bidirectional causal relationshi between investment on health and economic growth. Figure has elaborated the rocedure grahically below. Furthermore, the study has evaluated the imact of human caital investment on the economic growth by alying regression analysis using SPSS version 2 and Eviews. 4.. Emirical Model In this section, ECM is alied to examine the causal relationshi between investment in human caital and economic growth. Income (GDP) er caita has been used 7 to measure the economic growth. For human caital investment, two roxies have been used, which includes education as measured by government exenditure on education (formal and literacy) and health as measured by government sending on health. As both human and hysical caitals directly affect the roductive caacity of the economy, gross fixed caital formation is induced in the model, as a roxy for hysical caital. The time series data for all variables during the eriod was attained from official national statistics, ublished by the Saudi Arabian Monetary Agency. Adoting error correction mechanism in examining the relationshi between investment in human caital and GDP growth involves three main stes. First, determining the integration order by using ADF unit root test, second, running co-integration test, Third and last, investigating the long-run and short-run causality relationshi Model secification The model equations variables were converted to the logarithmic form, as followed: LG t = α + β LE t + δ LH t + γ LF t + ε t () LE t = α 2 + ϕ 2 LG t + δ 2 LH t + γ LF t + ε t2 (2) LH t = α 3 + ϕ 3 LG t + β 3 LE t + γ 3 LF t + ε t3 (3) LF t = α 3 + ϕ 4 LG t + β LE t + δ 4 LH t + ε t4 (4) Where, t LG = Per caita gross domestic roduct, 7 as; it enables to exand the country s outut at a faster rate than its oulation growth rate. LE = Exenditures on education, LH = Exenditures on health, LF = Gross fixed caital formation, α, β, δ, γ, ϕ = Variables arameters, ε = Random disturbance term Unit root test To examine the above-mentioned relationshi, the first and most imortant hase to run a non-surious regression, detecting the non-stationary variables has been carried out 8. Data series was examined for the existence of ossible unit roots to detect the integration order of the model variables. ADF, initially formulated by Dickey and Fuller (979; 98), unit root test was obtained to check data stationarity 9. Since the absolute value of ADF statistic at level is lower than the critical value; the four variables have a unit root (not stationary). But they became stationary after the first difference (with intercet, with intercet and trend, and without both), at % level of significance, as shown in Figure. When the first difference was taken, the unit root was eliminated, as shown in Table. Thus, the first difference series, can be directly used for the time series econometric modeling (co-integration regression) Co-integration Using the methodology develoed in Johansen (99) enables to run the vector auto-regression (VAR) model based on co-integration test. 8 Generally, non-stationary of exlanatory variables due to the resence of unit roots lead to surious regression and misleading results. In surious regression, a high value of R and a lower value of Durbin Watson statistics are likely to be found. 9 A series is thought to be stationary when the mean and autocovariance of the considered series do not deend on time. If time series are not stationary (non-stationary), the assumtions for the asymtotic analysis of Engle/ Granger causality test will not be useable. International Journal of Economics and Financial Issues Vol 7 Issue

5 Bokhari: Human Caital Investment and Economic Growth in Saudi Arabia: Error Correction Model Table : Results of ADF unit root Variables At level First difference Intercet/no trend Intercet/trend No intercet/no trend Intercet/no trend Intercet/trend No intercet/no trend LG (.39) (.926) (.9448) (.2) (.2) LE (.2) (.9997) LH (.998) (.789) (.9984) (.49) (.2) (.42) LF (.2744) (.334) (.999) Results of Johansen co integration test Hyothesized number of CE (s) Trace statistic.5 critical Max Eigen.5 critical value value statistic None At most At most At most ADF: Augmented Dickey Fuller LG = α + ϕ LG + β LE + δ LH t t t t + γ LF + ω LG + φ LE t t i t i i= i= + θ LH + ψ LF + U t i t LE = α + ϕ LG + β LE + δ LH t 2 2 t 2 t 2 t + γ LF + ω LG + φ LE 2 t 2 t i 2 t i + θ LH + ψ LF + U 2 2 t i t LH = α + ϕ LG + β LE + δ LH t 3 3 t 3 t 3 t + γ LF + ω LG + φ LE 3 t 3 t i 3 t i + θ LH + ψ LF + U 3 3 t i t i= t= (5) (6) (7) manner. To do that, several selection information criteria can be used. In this study, Akaike information criterion (AIC) has been selected. The criterion secified otimal lag length at P = 2 (2 nd order) of the VAR model subjected to co-integration restrictions. The two suggested tests find out the number of co-integration vectors the included the trace and maximal Eigen value statistics alied. According to the results in Table 2, both trace test and max-eigen value test yield two co integrating equations at the.5 level ECM and causality test As series are known to be co-integrated confirming two co-integration vectors, hence a long-run equilibrium relationshi existed between investment on education, health, fixed caital formation and er caita GDP. Granger causality test and the VECM can be carried out at this stage. ECT is demonstrated as shown in the following equations: LG = α + ω LG + φ LE t t i t i i= i= + θ LH + ψ LF + η ECT + µ t i t t (9) LF = α + ϕ LG + β LE + δ LH t 4 4 T 4 t 4 t + γ LF + ω LG + φ LE 4 t 4 t i 4 t i + θ LH + ψ LF + U 4 4 t i t (8) LE = α + ω LG + φ LE t t i 22 t i + θ LH + ψ LF + η ECT + µ t i 2 t t2 () As Johansen (99) aroach is quite sensitive to the lag length, the suitable number of lag should be determined in a systematic Such as, AIC; Hannan-Quinn criterion; Schwartcz Information criterion; mean absolute error; and final rediction error criterion. 8 International Journal of Economics and Financial Issues Vol 7 Issue 4 27

6 Bokhari: Human Caital Investment and Economic Growth in Saudi Arabia: Error Correction Model LH = α + ω LG + φ LE t t i 33 t i + θ LH + ψ LF + η ECT + µ t i 3 t t3 () corrected by the system in the current eriod. In the same way, 36% of the revious year s GDP disequilibrium in the long-run will be eliminated each year. The ECT is insignificant neither the education nor in fixed caital formation equations. In the health equation, the coefficient on the ECT ( ) is.9, indicating that.9% of adjustment is needed in the long-run (Table 3). LF = α + ω LG + φ LE t t i 44 t i + θ LH + ψ LF + η ECT + µ t i 4 t t4 (2) The VECM estimated results based on the baseline co-integrated model indicated that ECT found to be significant, insuring the existence of a long-run equilibrium between variables. The seed of adjustment toward long-run equilibrium is about.36, meaning that 36% of the receding eriod s disequilibrium, which was Table 2: VECM Variable Coefficient SE t statistics ECT ( ) D(LG ( )) D(LG ( 2)) D(LE ( )) D(LE ( 2)) D(LH ( )) D(LH ( 2)) D(LF ( )) D(LF ( 2)) C R F statistic Adjusted R P (F statistic).9 SE of regression.396 Mean deendent.584 variable Sum squared.5459 SD deendent.2536 residual variable Log likelihood Durbin Watson statistics SE: Standard error, SD: Standard deviation, VECM: Vector error correction models, ECT: Error correction term Figure 2: Variables conversion to stationary When long-run co-integration between variables is confirmed, Engle and Granger (987) suggested that the existed causal association must be either in one direction (unidirectional causality) or both directions (bidirectional causality). At this oint, causality test can be emloyed, noting that the standard causality test is more suitable for the stationary series. Alternatively, Granger causality/block exogeneity Wald test has been emloyed based on VECM to determine the causality directions. Table 4 dislayed Chi-squared statistics for the joint significance of the model exlanatory variables. As shown, there is no causality association between exenditure on education and GDP growth, but between education exenditure and health. Unidirectional causality has been found from fixed caital formation and GDP, and from health exenditure to caital formation. The relationshi between health exenditure and GDP seems to be the only bidirectional causality in the model. The short-run causal relationshis are conducted using the Wald test, from which the results suggested that LH and LF are the Granger causality of the LG in the short-run. This stated that in the short-run er caita GDP will be affected by health exenditure and fixed caital formation. While, insignificant coefficient of education exenditure (LE) indicated that investment on education does not influence economic growth in the short-run. Additionally, LG and LE are the Granger causality for health exenditure (LH), which is, in turn, Granger causality for caital formation (LF) in the short-run. In comarison with hysical caital (fixed caital formation), investment in human caital (exenditure on education and exenditure on health) jointly have a higher significant imact on economic growth (er caita GDP). The results in Table 5 have shown the Pearson correlation between gross national roduct (GNP) and exenditure on education. The relationshi between GNP and exenditure on education is highly and ositive correlated. The results also redicted that this relationshi is statistically significant at 5% level of significance (. <.5, n = 44). The results have shown correlation between GNP and exenditure on health. The relationshi between GNP and exenditure on health illustrated to be highly and ositive correlated. With the P =., the results redicted to be statistically significant at 5% level of significance. Pearson correlation test has also been alied among GNP and fixed caital formation. The Pearson correlation coefficient has determined that the relationshi between GNP and fixed caital Source: E-views results. Test the degree of causality among two variables, determining whether the endogenous variable can be treated as an exogenous variable or not. Meanwhile, the block exogeneity causality in VECM eliminates the influence of all other endogenous variables other than the lag of the considered deendent variable. International Journal of Economics and Financial Issues Vol 7 Issue

7 Bokhari: Human Caital Investment and Economic Growth in Saudi Arabia: Error Correction Model Table 3: VEC Granger causality/block exogeneity Wald tests Deendent variable LG Deendent variable LE Deendent variable LH Deendent variable LF Variables Chi square Variables Chi square Variables Chi square Variables Chi square LE.8329 (.64) LG (.287) LG (.235) LG.2857 (.5269) LH (.275) LH (.399) LE (.93) LE (.7796) LF (.442) LF (.77) LF (.325) LH ALL ALL (.78) ALL (.7) ALL Pearson correlation tests Correlation between GDP and exenditure on education.897 Correlation between GDP and exenditure on health.93 Correlation between GDP and fixed caital formation.858 GDP: Gross domestic roduct, VEC: Vector error correction Table 4: Regression analysis Variables Coefficient SE t statistic P GNP and exenditure on education GNP and exenditure on health GNP and fixed caital formation GNP: Gross national roduct, SE: Standard error formation, which was ositively correlated. The results have also stated that this relationshi is statistically significant with the P value (.) at 5% level of significance. The results for regression analysis have shown the deendency of education exenditure on GNP. The coefficient of determination (R 2 ) has determined the total variation by the education exenditure in the GNP. A total of 8.5% variation is indicated by the exenditure on education in the total variation of GNP, which is assumed to be large. The results also indicated that results are statistically significant with P value (.) at 5% level of significance. It means that GNP of Saudi Arabia can be increased with an increase in exenditure on education. The regression analysis between GNP and health exenditure has also been evaluated. The results have indicated that these two variables are statistically significant with P value (.) at 5% level of significance. However, the total variation in the GNP has been exlained by the health exenditure. The coefficient of determination has indicated that 83.4% variation is exlained by health exenditure on GNP. It can be determined that, with the increase in health exenditure GNP also increases. The results for regression analysis have shown the deendency of fixed caital formation on GNP. The coefficient of determination (R 2 ) has determined the total variation by the fixed caital formation in the GNP. A total of 73.6% variation is indicated by the fixed caital formation in the total variation of GNP, which is assumed to be large. The results were statistically significant with P value (.) at 5% level of significance. It means that GNP of Saudi Arabia can be increased with an increase in fixed caital formation. The results have also shown the results obtained by alying the regression analysis through Eviews, taking deendent variable GNP, and indeendent variables exenditure on education, exenditure on health and fixed caital income formation resectively. The results of all three variables are same as the regression alied on SPSS. The results for all three indeendent variable taking GNP as deendent variable are found to be statistically significant. 5. DISCUSSION In the resent study, exenditure on health and education has been considered as the core roxy for investment in human caital. Physical caital has been emloyed in emirical studies with a comarison of human caital and associated imact on the economic growth 2. Even though the imact of human caital on economic growth is the targeted subject; whereas, hysical caital, and economic growth relationshi are also noteworthy. The causal relationshi between human caital and GDP in Bangladesh for the eriod has been studied by Rahman (2), which included the real gross fixed caital formation in the roosed emirical model. A significant stable long-run relationshi existed between all variables according to the results. It has been mentioned that including human caital investment in the growth model of Bangladesh imroved the significance of hysical caital coefficients. Imran et al. (22) reorted that hysical caital did not contribute to economic growth in Pakistan because the human caital was not suorted as required. Total roductivity relies on the effective interaction of human and hysical caitals. Hussin et al. (22) revealed that fixed caital formation (hysical caital) has a ositive relationshi with GDP. Examining a anel set of data for the eriod 97-2 of 3 develoed and develoing countries, Akolat (24) realized that investment in hysical caital and education are more efficient to increase 2 Rahman (2), Imran et al. (22), Hussin et al.(22), Akolat (24), Khan et al. (25) and many others. International Journal of Economics and Financial Issues Vol 7 Issue 4 27

8 Bokhari: Human Caital Investment and Economic Growth in Saudi Arabia: Error Correction Model GDP in the develoed countries as comared to the develoing countries. The direction of causal relationshi between hysical caital and economic growth has been embraced in the causality analysis imlemented by Khan et al. (25). While investigating human caital and economic growth nexus, the result indicated the imortance of hysical caital as a factor of roduction in the economic growth of Pakistan. Concerning the Granger causality relationshi, emirical studies fall short of roviding the consensus results. Several studies could not confirm the influence of human caital on economic growth. Amassoma and Nwosa (2) found no causality between human caital develoment and economic growth in Nigeria. Khan et al. (25) stated that there were no long-run or short-run causal relation between health and economic growth in Pakistan during the eriod Hassan and Kalim (22) suggested that no causality found between er caita health exenditure and caita GDP in the short-run, but it exists on the long-run. Jihène (23) found no significant relationshi between human caital and economic growth in Morocco and Tunisia, while a significant relation existed in case of Jaan and Korea. Unlike revious studies, a unidirectional causal relationshi has been identified in several studies, either from human caital to growth or from growth to human caital. Mehrara and Musai (2) indicated a unidirectional causal imact from GDP to health exenditure while they have no suorted evidence that health exenditure can romote long-run economic growth in Iran. In a later study, Mehrara and Musai (23) found a strong causality from economic growth to education. Education does not have any significant imact on economic growth in short- or long-run. In Greece, Solaki (23) suggested a ositive relationshi between education and economic growth in the eriod The results mentioned a unidirectional causality running from tertiary education and ublic exenditure on education to real er caita GDP. Secondary education seems to be oositely directed referring to the influence from real er caita GDP to secondary education. However, Elmi and Sadeghi (22) confirmed a unidirectional short-run causality from GDP to health care sending; however, in the long-run, bidirectional relationshi has been found between health care sending and economic growth. Briefly, according to the revious emirical studies reviewed in the resent study showed that the imact of investment in human caital on economic growth is still arguable. While some might have declared that it has the significant effect, others fail to rove this. The casual direction of the relationshi between factors included as human caital and economic growth have also been observed arguable. Consequently, the resent study has evaluated the long-run and short-run causal relationshis between investment in human caital (namely education and health) and Saudi Arabian economic growth have been attemted. 6. CONCLUSION In the attemt to investigate the imact of human caital investment on economic growth in Saudi Arabia during 97-24, the ECM aroach has been emloyed. Data roerties were examined to verify their stationarity using ADF unit root tests, which indicated that variables tested stationary at first order. Johansen (99) co-integration was confirmed, which clarified the existence of the long-run relationshi between the four variables series. Afterword, VECM was established to identify short-run relationshi and ECT. Exenditure on education and fixed caital formation have found to be with non-significant imact on GDP. However, exenditure on health was observed strongly correlated with er caita GDP in the long-run and short-run. Granger causality found evidence of a bidirectional causal relationshi between investment on health and economic growth. It has shown a unidirectional causality from investment in health to investment in education and from hysical caital to economic growth. However, it is ertinent to inoint that investment in human caital (exenditure on education and exenditure on health) jointly have a higher significant imact on economic growth (er caita GDP) than investment in hysical caital (fixed caital formation). These results roved that the massive investments in education fail to generate roductivity and growth in Saudi Arabia, but investment in health and hysical caital significantly contribute to economic growth. 7. RECOMMENDATIONS The desirable olicy which government needs to estimate, can be through reforming its educational system to become more market oriented. 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