MASTER THESIS: THE EFFECT OF EDUCATION ON ECONOMIC GROWTH

MASTER THESIS: THE EFFECT OF EDUCATION ON ECONOMIC GROWTH ALFREDO ALARCON YANEZ 1. Introduction Much has been written in the economic literature about the theoretical and empirical eects of schooling on economic growth. Using dierent approaches, such as structural modelizations, and OLS and IV regressions, this subject has been giving contradictory results, using dierent databases and regression specications. In this master thesis I will rstly revise the theory on returns to schooling, either private or social. By doing this, I will present the Mincerian regression, one of the most calculated equations in the modern economic literature because of its facility to get the variables and its suitability to the data. Then I will explain how this micro regression can be used to calculate the social return to education in macro terms, where log wage is replaced by log GDP per capita, and discuss some identication problems. Given the huge amount of contradictory results in the scientic literature, I will present some important studies that propose alternative strategies to overcome this problem. Spe-cially important for my study is the trend of papers by Belzil and Hansen (2007, 2011a, 2011b), in which it is taken into account the heterogeneity across individuals in a given country. One of the main conclusions of these articles is that heterogeneity accounts for much of the dispersion in wages, and that in countries where the educational level has been attained through mandatory schooling policies, the impact of education will be lower than in other cases, since some individuals which are more productive at work will be forced to spend their time in schooling. In order to prove this conclusion at the macro level, I used three educational attainment databases to see whether countries have eectively followed a mandatory schooling policy. I dened ve classes of countries, and for each one I made a separate regression in order see the eect of education in those ve cases. As a conclusion, the eect of education on economic growth in countries with a highly eective mandatory schooling policy are much lower (even negative in some cases) than in countries where enrollment has increased solely because of amelioration of conditions to school. Date: July 16, 2012. 1 2 ALFREDO ALARCON YANEZ 2. Literature Review 2.1. The Return to Education: Theoretical Approach. 2.1.1. Estimating the Private Return to Schooling: The Mincer model. The study of the social and private return to schooling has been a topic that has inter-ested economists for a longtime. Questions such as if education is only a signal or it really develops new skills are very dicult to answer and make dicult the interpretation of the results of econometric analysis. The fact that people able to attain a higher level of schools have other competences that makes them earn more during their working period may lead to some endogeneity problems to deal with. In fact, if these competences and characteristics are not accounted for, there might be an ability bias in the estimates that would lead to a loss of signicance. Some attempts to control for it have been the analysis on siblings to dierence unobserved family characteristics, and regression analysis that consider also observed characteristics such as IQ and parental education (Kruegel, Lindahl, 2001). Through this article I will focus on a specic literature trend in which the ability bias is avoided considering heterogeneity in ability across individuals (see below). The Mincer model was proposed by Jacob Mincer in 1974 by showing that "if the only cost of attending school an additional year is the opportunity cost of students time, and if the proportional increase in earnings caused by this additional year is constant over time, then the log of earnings would be linearly related to individual’s years of schooling" (Kruegel, Lindahl, 2001). He considers also the fact that on-the-job experience can also enhance productivity and thus wages, and he gets the following Mincerian equation: lnWi = 0 +1Si +2Xi +3X2 +i: where Wi corresponds to individual i’s wage, Si her level of schooling and Xi her years in the labor market (experience) and i a disturbance term. Since the variables considered in this regression are quite easy to get from panel data sur-veys in dierent countries, this equation has become one of the most calculated regression in the economic literature. Psacharapoulous (1994, 2004) has calculated these estimates for a wide range of countries, with an eort to make the estimates comparable among them. One of the main conclusions of his work is that the mincerian regression adjusts quite well the data and that the correlation between return to schooling and GDP per capita in a MASTER THESIS: THE EFFECT OF EDUCATION ON ECONOMIC GROWTH 3 given country is negative and statistically signicant. In this equation 1 is the key variable to take into account and corresponds to the gain in log wage for an individual deciding to study an additional year instead of going directly to the labor market. Widely speaking, these estimates range from 0.05 to 0.15, with slightly larger estimates for women than for men (Kruegel and Lindahl, 2001). An important point here is the interpretation of the values of 1. As it is well stated by Kruegel and Lindahl (2001), does this estimate reect unobserved ability and other char-acteristics that are correlated with education, or the true reward that the labor market places on education? Is education rewarded because it is a signal of ability or because it increases productive capabilities? Most importantly, is the social return to schooling higher or lower than the private return? Does every individual increase their income in the same proportion when increasing education or does it depend on her characteristics? All these questions have been subject to debate but no nal conclusion has been reached up to date. The endogeneity bias discussed above has also been discussed in the literature, as for example Col Harmon and Ian Walker (1995) by using an IV approach examining the ef-fect of compulsory schooling in the UK. Some other studies have taken other IV strategies using natural experiments and most of them conclude that IV estimates exceed their corre-sponding OLS estimates, although their dierence is not statistically signicant (Krueger, Lindahl 2001). The Mincerian regression is therefore very useful to calculate return to schooling, and has been widely used in dierent countries and with dierent approaches, specically with OLS and IV techniques. Angrist and Krueger (1991) conclude that the upward bias in the return to schooling due to endogeneity problems is of about the same order of magnitude as the downward bias due to measurement error in schooling. This result is very important in the literature since OLS estimation has largely overcome IV techniques in the literature, and this is the approach I will use in this article. One critic to the Mincerian regression is that it focuses exclusively on the pecuniary aspects of schooling, instead of its social return. Actually, if education is supposed to be only a signal to abilities instead of increasing individual’s productivity, the social return to schooling will be much lower than the pecuniary return. On this sense, the absence of externalities analysis in the micro/mincerian analysis motivates the macro analysis that will be developed in the next section. 4 ALFREDO ALARCON YANEZ 2.1.2. Macroeconomic Approach to the Return to Education. In this section I will describe how we can use the mincerian equation in order to estimate the impact of schooling on economic growth. Let’s begin with the Mincerian wage equation, lnWitj = 0jt +1jtSijt +ijt where Witj corresponds to the wage of individual i in country j at date t, and Sint her years of schooling. The experience term considered above has been deleted for the sake of simplicity. Krueger and Lindahl (2001) state that a main conclusion in macroeconomic work on this subject up to 2001 is that only initial stock of human capital matters, not its change (we will see later that this assumption has been dismissed by Sunde and Vischer, 2011). Now I can integrate this equation across individuals each year by taking mean values in the population in order to get the "Macro-Mincer equation": lnYjt = 0jt +1jtSjt +jt where Yitj denotes the geometric mean wage (a proxy for mean GDP per capita) and Sjt the average years of schooling in country j at date t. This equation can be dierenced between year t and year t-1 to get: lnYg = 0 +1jtSjt 1jtSjt 1 +jt This formulation can remove the eects of any additive, permanent dierences in tech-nology. Considering return to schooling constant over time, we get a simpler version of this last expression: lnYg +0 +1jSj +jt where we can see that the coecient representing the return to schooling, 1, is allowed to vary across country, a feature that will be fully used by Bils and Klenow (2000), see next section. MASTER THESIS: THE EFFECT OF EDUCATION ON ECONOMIC GROWTH 5 If we consider that return to schooling varies over time, by adding and subtracting 1jtSjt 1 from the right-hand-side of the last expression we get: lnYg = 0 +1jtSj +Sjt 1 +jt where denotes the change in return to schooling. 2.2. Applied Studies. A huge amount of articles has been published on this subject, with rather contradictory results. Some have found a positive signicant relationships, others a negative and others no eect at all. In this section I will describe some specic studies in which some answers have been given in order to explain these contradictory ndings. 2.2.1. Heterogeneity among countries and reverse causality: Bils and Klenow (2000). Bils and Klenow (2000) develop a structural model to analyze the sense of casualty among education and economic growth. Using Barro and Lee’s educational attainment database, they calculate a correlation of 0.023 (statistically signicant) between economic growth and initial schooling attainment (i.e. in 1960). How can this correlation be explained? Two possible answers are evoked : Schooling attainment helps economic growth through dierent channels. Economic growth gives incentives to people to study more because of higher ex-pected future outcomes. In order to solve this question, a mathematical modelization is used. 2.2.2. The channels from schooling to growth. Let’s consider an economy with production function Yt = K[AtHt]1 ... - tailieumienphi.vn