TFP convergence across European regions: a comparative spatial dynamics analysis

This paper proposes a fixed-effect panel methodology that enables us to simultaneously take into account both TFP and traditional neoclassical convergence. We analyse a sample of 199 regions in EU15 (plus Norway and Switzerland) between 1985 and 2006 and find the absence of an overall process of TFP convergence as we observe that TFP dispersion is virtually constant across the two sub-periods. This result is proved robust to the use of different estimation procedures such as simple LSDV, spatially corrected LSDV, Kiviet-corrected LSDV, and GMM à la Arellano and Bond. However, we also show that this absence of a strong process of global TFP convergence hides interesting dynamic patterns across regions. These patterns are revealed by the use of recent exploratory spatial data techniques that enable us to obtain a complete picture of the complex EU cross-regions dynamics. We find that, between 1985 and 2006, there has been numerous regional miracles and disasters in terms of TFP performance and that polarization patterns have significantly changed along time. Overall, results seem to suggest that a few TFP leaders are emerging and are distancing themselves from the rest, while the cluster of low TFP regions is increasing

Education and Italian Regional Development

Given recent emphasis on externality to education, macroeconomic studies have a role to play in the analysis of return to schooling. In this paper we study the connection between growth and human capital in a convergence regression for the panel of Italian regions. We include measures of average, primary, secondary and tertiary education. We find that increased education seems to contribute to growth only in the South. Decomposing total schooling into its three constituent parts, we find that only primary education in the South seems to be important. The results thus suggest that the Italian growth benefited from the elimination of illiteracy in the South, mainly in the 1960s, but not from the substantial increases in education at the other levels.Returns to education, regional Italian growth

Length of stay in the host country and educational achievement of immigrant students: the Italian case

Using Italian data on language standardized tests for different levels of schooling we investigate 1) if the observed gap in educational attainments in first generation immigrants tends to lower the longer their stay in Italy and 2) if younger children tend to catch up faster than their older schoolmates. The analysis confirms the presence of a significant gap between natives and immigrants students in school outcomes for all grades, with first generation immigrants showing the largest gap. Further, the comparison between both first and second generation immigrant students and the results across the different grades suggest that the significant gap observed in the first generation is mainly due to the negative performance of immigrant children newly arrived in Italy and that interventions at younger ages are likely to be more effective. Finally, we find that also the immigrant students’ area of origin play a role in their schooling performance, suggesting that cultural differences affect children from different origins differently. We control for endogeneity concerns using both schools and classroom FE estimators, and results are robust to a specific sub-sample that controls for cheating, different model specifications and the use of math test scores as dependent variable

Convergence clubs and the role of human capital in spanish regional growth

This paper estimates returns to schooling at Spanish regional level. We identify two different convergence clubs of rich/educated and poor/uneducated regions. Overall our results stress the importance of the relationship existing between the level of development of an economy and returns to different levels of education. In particular, the Spanish evidence suggests that, while primary schooling seems to contribute to growth in poorly developed areas, more skilled human capital has a stronger growth-enhancing effect in more developed economies. In other words, our evidence emphasizes that there is likely to be heterogeneity in rates of returns to education across economies since the effect of schooling in growth regressions is influenced by the level of development of an economy. Failing to take this heterogeneity into account in empirical analysis may produce misleading result

Convergence and divergence in Neoclassical Growth models with human capital

Among the determinants of the growth and convergence processes identified by the theoretical literature, human capital is certainly one of the most important. This paper offers a selective survey of the more recent contributions of the theory of human capital and growth. In particular, our aim is to provide the necessary link between the theory on growth, convergence and human capital and the empirics of convergence. Summarising with a play on words, we might conclude that during the last fifteen years there has been a convergence of ideas between endogenous and exogenous models with respect to the convergence hypothesis where human capital plays an important role. Despite the still theoretically important difference between models that assume exogenous versus models that assume endogenous long-run growth rates, both theories predict that a mechanism of convergence is possible, but it will only be so among similar economies. In particular, most theoretical literature assumes that similar levels of human capital are fundamental for catch up to take place. Therefore, both theories are currently able to explain a stylised fact of the empirical literature on growth, namely the observed convergence among groups of homogeneous countries and the absence of convergence when large and heterogeneous data sets are introduced. This observation explains why, with current econometric techniques, it is not possible to discriminate endogenous versus exogenous models by simply using a convergence regression

A panel technique for the analysis of technology convergence: The case of the Italian regions

Differences in productivity levels represent a major component of the large cross-country differences in per capita income observed in international datasets and even in some regional ones. Nowadays, few economists would dispute neither this finding, nor that differences in productivity reflects – among other things – differences in technology levels. More controversial is the question of whether such differences in technology are stationary or temporary – that is, whether technology convergence is taking place, at what speed, under what conditions. This state of affairs is the result of several different difficulties faced by the empirical analysis on cross-country differences in per capita income growth rates. Recently, things have improved on both the analytical and the empirical side. On the analytical side, simple models in which technology convergence and capital-deepening can be studied within a common framework are now available. In these models the transitional dynamics is simple enough to be useful for empirical analysis [for instance, De la Fuente (1996) and (1997)]. On the empirical side, Islam (1995) has shown that we can test for the presence of technology heterogeneity in cross-country convergence analysis by using an appropriate fixed-effect panel estimator. The contribution of the present paper is on the empirical side. We propose a method designed to test whether part of the observed economic convergence is due to technology convergence. The method is based on the contribution by Islam (1995), but it extends it as follows. Islam’s technique was originally designed – and is currently applied – to measure cross-country differences in technology levels, assuming that such (relative) differences are at their stationary values and therefore that no technology convergence is present. The extension proposed in this paper builds on the a standard implication of models of technology convergence. If such convergence is present, the cross-sectional variance of the logs of our measure of technology should decreases over time approaching its stationary value. Alternatively, if technology convergence is absent, the variance is at its stationary value and no significant time-trend should be detected in its value. We exploit this difference to test for the presence of technology convergence in the data. First, we estimate the convergence equation over several sub-periods and use the values of the individual intercepts to compute the TFP levels. Then, we obtain the cross-section variance of the logs of our measures of TFP for each sub-period, and check whether the observed pattern is consistent either with catching-up hypothesis or with the hypothesis that the current degree of technology heterogeneity is at its stationary value. In this paper we use a panel dataset of the Italian regions, 1960-95. We apply our proposed methodology to the Italian case because it is notoriously characterized by a remarkable degree of regional heterogeneity. In spite of being one of the best known cases of regional divide, no explicit analysis of technology convergence across Italian regions is available yet. We use dynamic panel techniques (LSDV and GMM) to estimates our growth regressions. We split the whole sample period in several sub-periods to check for the presence of technology convergence. Our preliminary results reveal a significant presence of technology convergence, which reached its peak between the first and the second sub-period, and stayed significant but at a slower pace in later sub-periods. The emerging picture points to the simultaneous presence of technology convergence in a context otherwise characterized by weak output per-worker convergence. This is consistent with some recent results based on international datasets (e.g. Dowrick and Rogers [OEP (2002]).

Tourism and Development: A Recent Phenomenon Built on Old (Institutional) Roots?

Is tourism an opportunity for lagging countries in the elusive quest for growth (Easterly, 2002)? Recent empirical evidence suggests that the answer is a cautious yes. Aggregate cross-country data show that tourism specialization is likely to be associated with higher per capita GDP growth rates than those observed in industrialized countries. However, this evidence ignores the importance of institutional quality and results are likely to be biased by omitted variable problems. In this paper we frame our starting question within the general debate about the importance of good/bad institutions as fundamental determinants of economic growth (Acemoglu et al., 2001) and ask whether previous positive results of tourism on growth are in fact driven by the presence of growth enhancing institutions. Our empirical analysis exploits newly available datasets and controls the robustness of previous results on growth and tourism in the presence of several institutional quality variables. By means of descriptive statistics and some simple cross-country regressions we confirm that the quality of institutions is important for growth. Yet our results strongly suggest that the weight of tourism in an economy is an independent and robust predictor of higher-than-average growth.Economic Development, Tourism Specialization, Institutions

How to Measure the Unobservable: A Panel Technique for the Analysis of TFP Convergence

This paper proposes a fixed-effect panel methodology that enables us to simultaneously take into account both TFP convergence and the traditional neoclassical-type of convergence. We analyse a sample of Italian regions between 1963 and 1993 and find strong evidence that both mechanisms were at work during the process of aggregate regional convergence observed in Italy up to the mid-seventies. Finally, we find that our TFP estimates are highly positively correlated with standard human capital measures, where the latter is not statistically significant in growth regressions. This evidence confirms one of the hypotheses of the Nelson and Phelps approach, namely that human capital is the main determinant of technological catch-up. Our results are robust to the use of different estimation procedures such as simple LSDV, Kiviet-corrected LSDV, and GMM à la Arellano and Bond.TFP, Panel data, Regional convergence

Some Econometric Issues In Convergence Regressions

Despite the abundance of different econometric techniques introduced in the empirical literature on convergence, it is usually assumed that shocks are uncorrelated across countries. This is surely unlikely for most of the datasets considered and we investigate a possibility so far ignored, namely the annual panel estimator where shocks are allowed to be correlated across countries. Our analysis is restricted to the case of more time periods than countries (T>N) which allows us to estimate by Maximum Likelihood with an unrestricted variance-covariance matrix of cross-country shocks. The paper examines by Monte Carlo robustness against certain possible mis-specifications, namely measurement error and heterogeneity of the convergence coefficients. Our analysis indicates that ML estimators are robust to plausible measurement error and variation of convergence rates across countries and are more efficient than conventional estimators for plausible values of cross-country error correlation. We consider in detail the relationship between the distribution of the ML estimator and the initial conditions. Applying our findings to a panel of OECD countries for the post-war period, we show that ML is effectively unbiased and more efficient than or conventional panel estimators OLS on a cross-section of countries. We argue the reason this estimators is so well behaved is that many OECD countries were far from their equilibrium values at the beginning of the period

Human capital stocks and the development of italian regions: a panel approach

Given recent emphasis on externality to education, macroeconomic studies have a role to play in the analysis of return to schooling. In this paper we study the connection between growth and human capital for the Italian regions in a convergence regression framework. We confirm the usual result on Italian regional convergence that this process began to diminish or fail after about 1975. We include a measure of human capital in the convergence regression as a stock rather than a flows. We find this variable is significant if and only if we control for the size of the public sector. The public sector is itself strongly negative. Decomposing the human capital measure into its constituents, we find that average years of primary and secondary education act positively on growth, but that tertiary education acts negatively. When we estimate the convergence regression for the South and the North-Centre separately, we find no break in the pattern of convergence around 1975. Thus both areas seem to be converging according to a similar process, albeit to different levels of GDP per capita. The role of the human capital is strikingly similar in the two clubs. Finally, we find educating women leads to faster growt