c3d81f626e06185b6e997d54824a9527.ppt

- Количество слайдов: 29

Bridging the Gap: the Role of Trade and FDI in the Mediterranean June 8 -9, 2006 Convergence and FDI in the Mediterranean basin: an empirical evidence Giuseppe Notarstefano - Raffaele Scuderi Dipartimento di Contabilità Nazionale ed Analisi dei Processi Sociali Università degli Studi di Palermo, Italy

Structure 1 – Purpose 2 – Statistical approaches to test convergence hypothesis i. Review of literature: choice of the methodology ii. Methodology: the Stochastic Kernel iii. Empirical findings 3 – Relationship between FDI and growth i. Review of literature ii. Methodology: the Stochastic Kernel in a deterministic conditioning scheme iii. Empirical findings 4 – Conclusions

1. Purpose To assess growth dynamics of countries agreeing to the Euro-Mediterranean Partnership (EMP) In particular: Per capita income convergence test Role of Foreign Direct Investments (FDI) for economic growth

2. i – Convergence: Review (1) Implication of neoclassical theory of growth: long term reduction of per capita income gaps (Solow, 1956; Cass, 1965; Koopmans, 1965) Decreasing marginal productivity of capital CONVERGENCE HYPOTHESIS (CH)

2. i – Convergence: Review (2) CONVERGENCE HYPOTHESIS TESTS Contributions are classified into two categories Absolute convergence Per capita incomes of a given set of countries converge to the unique steady state Conditional convergence Each economy converges towards its own steady state, proxied by variables Per capita income needs to be conditioned to a set of proxies Test the influence of proxy variables to economic growth (endogenous growth theory) No strong empirical evidence is found about factors influencing economic growth Durlauf and Quah (1998) - the choice of steady state’s proxies depends on the interest of the researcher

2. i – Convergence: Review (3) CONVERGENCE HYPOTHESIS TESTS Absolute convergence Conditional convergence

2. i – Convergence: Review (3) CONVERGENCE HYPOTHESIS TESTS Absolute convergence Conditional convergence “[…] there are reasons other than the testing of economic growth theories for the empirical study of economic convergence. We, as economists, are interested in knowing whether the distribution of income changes over time” (Sala-i-Martin, 1996) “[…] the new research no longer makes production function accounting a central part of the analysis. Instead, attention shifts more directly to questions like, Why do some countries grow faster than others? It is this changed focus that, in our view, has motivated going beyond the neoclassical growth model” (Durlauf and Quah, 1998) Classification of the approaches, according to the methodology employed Cross-section Panel data Time series

2. i – Convergence: Review (4) Cross-section approach Sigma convergence: variability of per capita income, as measured by the coefficient of variation, reduces over time Beta convergence: absolute: no Xi, t → reject CH on a set of world countries Baumol (1986) country i’s per capita income at time t conditional → accept CH on a set of world countries Barro and Sala-i-Martin (1992) Mankiw et al. (1992)

2. i – Convergence: Review (4) Cross-section approach Sigma convergence: variability of per capita income, as measured by the coefficient of variation, reduces over time Beta convergence: absolute: no Xi, t → reject CH on a set of world countries Baumol (1986) country i’s per capita income at time t Quah’s criticisms: conditional → accept CH on a set of world countries Barro and Sala-i-Martin (1992) Mankiw et al. (1992) - parametric tests generally refer to the behaviour of a representative unit, and they are then unsuitable to catch the more real situations of polarization and club convergence - sigma and beta convergence approaches are shown to be uninformative about convergence in some cases - beta convergence approach does not properly consider dynamics

2. i – Convergence: Review (5) Panel data approach Islam (1995): each steady state is better proxied by employing a fixed effects → accept CH panel estimator, otherwise convergence effect would be underestimated. on a set of world countries Quah’s criticism: “individual heterogeneities“ conditioned out by panel data regression contain those characteristics which are treated as something not consistently estimable (Quah, 1999) Time series approach Bernard and Durlauf (1995) test the presence of common long-run trends between per capita GDP series Hobjin and Franses (2000) propose an algorithm to detect clubs of converging countries → reject CH Evans and Karras (1996) perform a unit root test on panel data → accept CH Quah’s criticism: these tests do not put in account cross-sectional information

2. ii – Convergence: Methodology (0) “parametric tests generally refer to the behaviour of a representative unit, and they are then unsuitable to catch the more real situations of polarization and club convergence”

2. ii – Convergence: Methodology (0) “parametric tests generally refer to the behaviour of a representative unit, and they are then unsuitable to catch the more real situations of polarization and club convergence” Univariate density estimates of per capita income 1982 All (1960 -2003) 26 countries: Algeria, Austria, Belgium, Cyprus, Denmark, Egypt, Finland, France, Germany, Greece, Ireland, Israel, Italy, Jordan, Lebanon, Luxembourg, Malta, Morocco, Netherlands, Portugal, Spain, Sweden, Syria, Tunisia, Turkey, United Kingdom 1971 1993

2. ii – Convergence: Methodology (1) Quah’s distribution dynamics approach: the stochastic kernel (SK) - Time series methodology which also considers sectional information - Each period’s observation is not a scalar or a finite-dimensional vector, but a distribution - Nonparametric estimate of the law of motion of the evolving income distribution; based on some properties of Markov chains SK is a transition probability matrix in the continuum. It tracks income distribution’s evolution over time

2. ii – Convergence: Methodology (1) Quah’s distribution dynamics approach: the stochastic kernel (SK) - Time series methodology which also considers sectional information - Each period’s observation is not a scalar or a finite-dimensional vector, but a distribution - Nonparametric estimate of the law of motion of the evolving income distribution; based on some properties of Markov chains SK is a transition probability matrix in the continuum. It tracks income distribution’s evolution over time λt (1) M is a measure corresponding to Ft (the cross-country distribution of per capita income at time t) λt+1= M * λt the relation that links λt+1 with λt is analogous to a standard time-series first-order vector autoregression maps then how yt evolves at t+1; it also contains information about distribution dynamics and shape. Iteration of (1) estimates future density distribution: λt+s= (M * … * M) * λt = Ms * λt

2. ii – Convergence: Methodology (2) Stochastic kernel: estimation (Quah, 1995; 1997) We consider relative to the mean income - Epanechnikov kernel nonparametrically estimates the joint density of relative income at dates t and t+5: Silverman’s criterion is employed for the choice of the bandwidth h - The current-period marginal density, implied by that estimated joint density, is calculated by integration - Stochastic kernel is obtained by dividing the joint density by the marginal

2. ii – Convergence: Methodology (3) Stochastic kernel: output and interpretation Ft = Ft+1 = λt λt+1 then $ M | λt+1= M * λt PROBABILITY MASS - Located along the 45 -degree diagonal: persistence in the economies’ relative position - Concentrated along the perpendicular line to the 45 degree diagonal: overtaking of economies in their rankings. - Parallel to t+k axis: the probability of being in any state at period t+k is independent of economies’ position at t - Parallel to the t axis: convergence

2. iii – Convergence: Results Convergence analysis of relative per capita GDP over 1960 -2003, 5 years transition (EMP) 26 countries: Algeria, Austria, Belgium, Cyprus, Denmark, Egypt, Finland, France, Germany, Greece, Ireland, Israel, Italy, Jordan, Lebanon, Luxembourg, Malta, Morocco, Netherlands, Portugal, Spain, Sweden, Syria, Tunisia, Turkey, United Kingdom Data source: The World Bank (2005)

3. i – FDI-growth: Review (1) Foreign debt crisis of developing countries (Eighties) Attention to no debt creating flows like FDI Many countries offered tax incentives and subsidies to attract foreign capital FDI nowadays accounts for over 60 percent of private capital flows Increase of FDI towards Mediterranean developing countries (DCs) has been considerably smaller than the one shown by all the DCs FDI/GDP ratio LMIC = Low and Middle Income Countries MPC = Mediterranean Partner Countries

3. i – FDI-growth: Review (2) Theoretical FDI spillover effects: - stock of human capital - propension to invest - per capita income … but … Carkovic and Levine (2002): “While there are sound conceptual reasons for believing that FDI can ignite economic growth, the empirical evidence is divided”

3. i – FDI-growth: Review (3) Macroeconomic analyses Prevailing literature: positive relationship between FDI and growth Borensztein et al. (1995) – set of 69 developing countries receiving flows from industrialized countries Balasubramanyam et al. (1999) – Asian and South American countries Alfaro et al. (2000) – three samples of countries, ranging from developing to advanced Berthélemy and Démurger (2000) – Chinese provinces Nair-Reichert and Weinhold (2001) – sample of 24 developing countries Notarstefano and Scuderi (2004) – EMP countries Carkovic and Levine (2002) They criticise methodologies employed by macroeconomic approaches, which often do not control for simultaneity distortions and specific country effects. Dynamic panel estimation on a set of countries, ranging from developing to advanced. FDI are found to be not related with growth

3. i – FDI-growth: Review (4) Microeconomic analyses at firm level Positive spillover effects of FDI Liu (2002), – 29 manufacturing Chinese industries Branstetter (2006) – Japanese firms investing to the US Absence of spillover effects Aitken and Harrison (1999) – firms in Venezuela see also Germidis (1977), Haddad and Harrison (1993), Mansfield and Romeo (1980)

3. ii – FDI-growth: Methodology (1) Stochastic Kernel: deterministic conditioning scheme (Quah, 1997) Nonparametric analysis of original distribution compared to its conditioned version The approach aims to catch how a conditioning factor “alters” the original distribution Regression-like rationale

3. ii – FDI-growth: Methodology (1) Stochastic Kernel: deterministic conditioning scheme (Quah, 1997) Nonparametric analysis of original distribution compared to its conditioned version The approach aims to catch how a conditioning factor “alters” the original distribution Regression-like rationale an integer indicating the lag in time Conditioning scheme G – collection of the triple a subset of countries from the set I a set of probability weights, which sum to 1 value of the original distribution Y at time t in region i conditioned version of

3. ii – FDI-growth: Methodology (2) Our estimation is the absolute distance of FDI value in region i from the value in region j. Following Quah (1995, 1997): mean-relative per capita GDP Silverman’s criterion for the choice of the bandwidth h Epanechnikov kernel is the ratio

3. iii – FDI-growth: Results (1) Original and conditioned-to-FDI-inflows per capita GDP, over 1990 -2003 EMP countries 32 countries: Algeria, Austria, Belgium, Cyprus, Czech Republic, Denmark, Egypt, Estonia, Finland, France, Germany, Greece, Hungary, Ireland, Israel, Italy, Jordan, Latvia, Lebanon, Lithuania, Morocco, Netherlands, Poland, Portugal, Slovak Republic, Slovenia, Spain, Sweden, Syria, Tunisia, Turkey, United Kindgom Data source: The World Bank (2005)

3. iii – FDI-growth: Results (2) Original and conditioned-to-FDI-inflows per capita GDP, over 1990 -2003 non-EU-in-1992 EMP countries 10 countries: Algeria, Cyprus, Egypt, Israel, Jordan, Lebanon, Morocco, Syria, Tunisia, Turkey Data source: The World Bank (2005)

3. iii – FDI-growth: Results (3) Original and conditioned-to-Italian-FDI-inflows per capita GDP, over 2000 -2003 EMP countries 34 economies: Algeria, Austria, Belgium, Cyprus, Czech Republic, Denmark, Egypt, Estonia, Finland, France, Germany, Greece, Hungary, Ireland, Israel, Jordan, Latvia, Lebanon, Lithuania, Luxembourg, Malta, Morocco, Netherlands, Poland, Portugal, Slovak Republic, Slovenia, Spain, Sweden, Syria, Tunisia, Turkey, United Kindgom, West Bank and Gaza Data source: The World Bank (2005) and Italian Exchange Office (Ufficio Italiano Cambi, 2006)

3. iii – FDI-growth: Results (4) Original and conditioned-to-Italian-FDI-inflows per capita GDP, over 2000 -2003 non-EU-in-1992 EMP 12 economies: Algeria, Cyprus, Egypt, Israel, Jordan, Lebanon, Malta, Morocco, Syria, Tunisia, Turkey, West Bank and Gaza. Data source: The World Bank (2005) and Italian Exchange Office (Ufficio Italiano Cambi, 2006)

4 – Conclusions - Literature on convergence hypothesis tests has been divided about the methods to employ, and the presence of convergence in real data - The choice of the methodology has been driven by statistical consideration about methodologies previously applied and by characteristics of per capita income density estimate - SK analysis suggests that no convergence has occurred between countries agreeing to the Euro-Mediterranean Partnership, as expected. Income gaps have then persisted over 1960 -2003. - A regression-like rationale has been applied to SK as done in Quah (1997). Evidence indicates that FDI have a positive influence on income distribution. This confirms the evidence of the prevailing macroeconomic empirical analyses. - Cluster persistence within EMP countries, as well as the influence of FDI for growth, have also been shown in a previous contribution (Notarstefano and Scuderi, 2004) - Future research may be based on the concept of growth as multidimensional phenomenon, as pointed out by recent literature on living standards, and as also done in our previous work