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GLOBALISATION AND CONVERGENCE DeLONG AND DOWRICK PAPER FOR NBER PRE-CONFERENCE MEETING TO BE HELD ON NOVEMBER 16TH, 2000 This is a very preliminary draft – some of it still in note form. POST WAR GLOBALISATION & CONVERGENCE 1: Introduction Over the past half century the expansion of world trade and capital flows has [MATCHED / EXCEEDED ?] the globalisation that occurred in the fifty years up to the First World War – although migration of people has probably not matched the mass migrations of the late nineteenth century. Growth theoreticians have been contrasting the convergence predictions of the neo-classical growth models of Swan (1956) and Solow (1956) with predictions of potential non-convergence from the newer models of endogenous technological progress of Romer (1990) and Aghion and Howitt (1998). In most models, globalisation is predicted to speed up convergence through capital flowing to the capital poor countries where marginal returns are high or through ideas flowing to the technologically less advanced. Modern econometric studies have been dominated by controversies and confusion over the definition and measurement of convergence. Convergence is typically treated as conditional on some array of pre-determined factors, and recent estimates of the rate range from two to thirty-five percent per year. All of this concentration on conditional convergence has tended to obscure the observation1 that 1 Qualification: this statement depends on the sample of countries, measure of dispersion, PPP method, and weighting of observations. I am referring to the unweighted variance of log GDP per capita from PWT5.6a, extrapolated to 1998, for a sample of 106 countries. A recent report by the Norwegian Institute of International Affairs (NUPI, October 2000) reports that the population weighted Gini coefficient for 136 countries has been declining steadily since 1975. We find that the population weighted variance declines between 1980 and 1998. 1 country income levels have been diverging rather than converging over the past fifty years. The first puzzle to be explained is why 50 years of globalisation has been accompanied by divergence rather than convergence. A mechanical answer is that some of the ‘conditioning’ variables in the standard convergence regressions are distributed in such a way as to promote divergence – eg faster population growth and lower rates of investment in poorer countries. In autarchic models, the development poverty trap is readily explained: a population living close to subsistence is unable to mobilise the surplus required for substantial domestic investment; they will typically face an exchange rate that is undervalued relative to purchasing power parity, hence high prices for imported capital goods; they may well be caught in a prisoner’s dilemma whereby each family substitutes quantity of children for quality of human capital investment (schooling) in attempting to maximise family welfare, running foul of diminishing returns to labour in the aggregate. But globalisation is typically presumed to overcome such poverty traps – especially through the flow of capital towards capital-poor economies, through trade-induced factor price equalisation and through knowledge spillovers. Why might globalisation have failed to produced convergence over the past fifty years? A number of hypotheses have been suggested: Lucas (1990) suggests that human capital complementarity may block the capital channel – though that argument requires in turn some explanation, such as moral hazard, for failure of international capital markets to invest in human capital. Ventura (1997) shows that convergence is not necessarily induced by trade in a neoclassical two-sector model with a high degreee of substitution between capital and labour [FURTHER EXPLANATION …]. Knowledge spillovers may be insufficient (due to Abramovitz’s lack of social capability) to overcome the divergent tendencies of autarchic endogenous technology growth. Sachs and Warner (1995) argue that globalisation does indeed induce convergence – but only to those countries that allow relatively free movement of goods and capital. 2 2: Evidence on growth and convergence 1960-98 Descriptive statistics are given in Table 1 for real GDP per capita (RGDP) for 109 countries in 1960, 1980 and 19982, using the Penn World Tables 5.6a.3 We also report real GDP per member of the workforce (RGDPW) and real GDP per capita as adjusted by Summers and Heston (1991) for changes in the terms of trade (RGDPTT). This terms of trade adjustment gives a better measure of changes in average welfare than the fixed price measure. These latter two measures are available only up until 1992. Dispersion is measured by the variance of the logarithm. Other measures of dispersion are often used, particularly in welfare analysis; but the log variance is particularly useful in that it can be directly related to the regression analysis of growth rates. Table 1 reports changes in population weighted variances for the whole sample, a measure appropriate to analysis of inequality across individuals. For the most part, however, we take a positivist approach with a view to hypothesis testing and treat each country’s performance over a defined period as a single, unweighted observational unit. All three measures of real GDP show increasing dispersion over the whole sample. We have divided the sample of 109 countries into three income groups, depending on whether 1960 RGDP was above or below I$1,500 or I$5,000 (measured in constant international prices with the I$ normalised to the purchasing power of the US$ in 1985). Divergence has occurred within each group, except for the richest 19 countries between 1960 and 1980. But the principal cause of overall divergence has been the failure of the poorest economies to match the growth rates of the more developed. Between 1960 and 1980, the middle income countries grew fastest, at 3.2 percent per year, followed by the rich countries at 2.7 percent and the poorest countries at 2.1 percent. Over the subsequent two decades growth rates slowed for all groups, averaging a meagre 0.6 percent per year for the 55 poorest economies. It is this falling behind of the poorest countries, in a period of increasing globalisation, that we investigate. In particular we examine the ways in which these countries have, or have not, engaged in the global economy and use regression analysis to identify the relative importance of these characteristics. 2 To reduce the influence of asynchronous business cycles, the data labelled 1960 are actually five-year averages for the period 1960-64; similarly 1978-82 averages for 1980, 1988-92 for 1990 and 1994-98 for 1998. 3 We have at the last minute identified some problems with the PWT population and real GDP series between 1970 and 1971 which will require correction and subsequent adjustment to all the empirical results presented in this draft. 3 2.1: NOTES ON COUNTRY CHARACTERISTICS SUMMARISED IN TABLE 2 POOR COUNTRIES ARE CHARACTERISED BY SLOW GROWTH, LOW INVESTMENT, HIGH POPULATION GROWTH, FALLING RATIOS OF WORKFORCE TO POPULATION, HIGH PRICES FOR INVESTMENT GOODS, POOR PERFORMANCE ON VARIOUS MEASURES OF OPENESS AND TRADE. THE SLOWEST GROWERS AMONGST THIS GROUP ARE EVEN WORSE OFF IN TERMS OF THESE CHARACTERISTICS THAN THE OTHER COUNTRIES WHICH HAD SIMILAR LEVEL OF RGDP IN 1960. 2.2: EXPLORATORY REGRESSIONS TO UNTANGLE THE RELATIONSHIPS BETWEEN THE VARIABLES MENTIONED ABOVE AND TO ESTIMATE PARAMETER MAGNITUDES - RELATIONSHIP BETWEEN SIGMA AND BETA CONVERGENCE AND THE CORRELATION BETWEEN ‘CONDITIONING’ VARIABLES AND INCOME LEVELS; - INTERPRETATION OF THE COEFFICIENT ON INITIAL INCOME LEVELS – CAN BE RATE OF CONVERGENCE TO NEO-CLASSICAL STEADY STATE AND / OR RATE OF TECHNOLOGY TRANSFER - INTERPRETATION OF ‘CONDITIONING’ VARIABLES EITHER AS DETERMINANTS OF NEO-CLASSICAL STEADY STATE OR AS DETERMINANTS OF LONG-RUN TECHNOLOGICAL GROWTH INTERACTION BETWEEN INITIAL INCOME TERM AND MEASURES OF ‘GLOBALISATION’ The regressions reported in Table 3 replicate some of the analysis carried out by Sachs and Warner (Brookings Paperes, 1995). We use the S&W distinction between open and closed economies for the period 1960-80 to construct a dummy variable equal to 1 for countries they deemed to be open 4 for the period 1970-89. Since we are also examining growth over the period 1980-98, we extend the S&W classification to our later period, reclassifying countries as open if S&W report that have been open for a significant number of years since 1980.4 This enables us to check whether the Sachs Warner results carry over to the 1990s – in particular for the 24 poor and middle-income countries that have only recently opened their economies. Regression 1 in Table 3 confirms the Sachs-Warner result that open economies grew substantially faster than closed economies over the period 1960-80. Our estimate of a 2.0 percentage point growth premium is only slightly lower than the S&W estimates for 1970-89. By any standards, it is a huge premium – implying that 20 years of openness lifts per capita GDP by a cumulative fifty percent. When we interact openness with initial income, regression 2 indicates that the growth premium for openness tends to be higher for poorer countries – averaging 3.4 percentage points compared with 1.0 points for rich countries. Controlling for openness, these regression show no evidence of conditional convergence, indeed the beta coefficients are positive implying that there were additional factors slowing the growth of the poorest relative to the richest countries. Regression 3 confirms that the usual suspects were involved – investment rates and demographic differences accounted for 1.3 percentage points of slower growth for the poor countries. Taking account of factor accumulation, and of the differential effects of openness, there is now some weak evidence of conditional convergence. This should be interpreted as conditional convergence in multi-factor productivity, proceeding at a slow rate of only 0.4 percent per year, possibly resulting from international technology transfer. Since the regression is controlling for trade effects, any such technology spillovers are not operating through trade. We perform similar analysis to explain growth between 1980 and 1998 – see Regressions 4 –6 in Panel B of Table 3. Conditional convergence is still weak. Openness appears to deliver a smaller growth premium than that of the previous twenty years, although 1.3 percentage points is still a very substantial addition to annual growth rates. The interactive term, introduced in regression 8, suggests that the poorer countries benefit less from openness than do rich countries – the opposite of For example, S&W classify Israel as closed but “open since 1985”, so we reclassify Israel for our second period. The other countries becoming open are: Benin, Botswana, Chile, Colombia, Costa Rica, El Salvador, Gambia, Ghana, Guatemala, Guinea, Guinea-Bissau, Guyana, Mali, Mexico, Morocco, New Zealand, Paraguay, Phillipines, Sri Lanka, Tunisia, Turkey, Uganda and Uruguay. 4 5 the pattern observed for the earlier period.5 Slower capital deepening in the poorer countries now contributes 2.2 points of slower growth. Technology catch-up is statistically significant and approaching one percent per year over this most recent period. The next three rows of Table 3 report regressions on a larger group of countries (109 compared to 96) for which we have derived an alternative measure of openness. This measure, based on the unsurprising observation that countries with small populations tend to engage in more international trade than do more populous nations, consists of the residuals from a very simple regression which explains half of the observed variation in trade shares over the pooled sample: Log (exports + imports / GDP) = 6.23 - 0.25 log (population) ; n=218, R2 = 0.498. This measure behaves similarly to the S&W measure in that it is positively correlated with income level and it increases over time for all three income groups. It has the advantage of being a continuous variable, it does not require subjective classification rules and it covers more countries. Use of this measure of openness confirms that whilst there is a significant growth premium resulting from openness for the period 1980-98, the benefits of openness accrue mostly to the richer nations. The coefficient on the trade-income interaction term is again positive and significant, see regression 8, implying that the premium for the average poor country is 1.4 percentage points, but for the average country in the rich group it is 1.9 points. Strong correlation between the level of openness and the interactive term (r=0.992) make their joint inclusion in the regression problematic. Accordingly we revert to the sample of 96 countries for which the extended Sachs-Warner index is available so that we can use the SW index for one term and the trade share variable for the other term. The strongly significant coefficients on the tradeincome interaction term in regressions 11 and 12 confirm that the benefits of openness are skewed towards the richer countries, whether or not we control for factor accumulation. THIS REMARKABLE TURN-AROUND IN THE DISTRIBUTION OF BENEFITS FROM OPENNESS REQUIRES MORE DETAILED INVESTIGATION. 5 When the openness variable and the interactive variable are included together, the latter is not statistically significant. 6 3: Non-trade Dimensions of Globalisation and Convergence ? ? ? ? ? ? ? ? ? ? REFERENCES 7 TABLE 2: AVERAGE CHARACTERISTICS OF INCOME GROUPS1 RICH MID POOR SLOWEST GROWERS 1960 7117 2433 855 800 1980 11475 4579 1385 978 1990 13416 5365 1555 878 1998 14788 6398 1808 885 1960-80 0.027 0.032 0.021 0.007 1980-98 0.015 0.013 0.006 -0.007 PROPORTION AFRICAN 0.000 0.143 0.618 0.806 PROPORTION OECD 0.895 0.171 0.000 0.000 REAL GDP PER CAPITA (I$) RGDP GROWTH RATE (annual average) PROPORTION OPEN 1960-80 0.833 0.393 0.120 0.032 (Sachs-Warner) 1980-98 0.889 0.750 0.320 0.226 (IMPORTS+EXPORTS) / GDP 1960-80 0.621 0.702 0.517 0.479 1980-98 0.712 0.851 0.623 0.540 ADJUSTED TRADE SHARE 1960-80 0.016 -0.105 -0.221 -0.283 1980-98 0.209 0.171 0.100 -0.017 REAL INVESTMENT /GDP 1960-80 SHARE 1980-98 0.262 0.203 0.113 0.085 0.232 0.178 0.115 0.073 RELATIVE PRICE OF INVESTMENT GOODS 1960-80 1.022 1.358 2.379 2.899 1980-98 0.938 1.391 2.483 2.992 POPULATION GROWTH RATE (annual average) 1960-80 0.010 0.020 0.025 0.026 1980-98 0.007 0.016 0.024 0.027 GROWTH OF WORKFORCE / POPULATION 1960-80 0.005 0.002 -0.003 -0.005 1980-98 0.005 0.005 0.002 0.000 1. ‘Rich’ group is composed of 19 countries with RGDP 1960-64 averaging above I$5,000; the ‘poor’ group comprises 55 countries with RGDP 1960-64 averaging below I$1,500. The ‘slow growers’ are the 35 slowest-growing countries within the ‘poor’ group. 8 TABLE 3: EXPLORATORY REGRESSIONS RELATING TRADE AND CONVERGENCE The dependent variable is the annual growth rate of real GDP per capita, measured at 1995 local prices, between 1960 and 1980, or between 1980 and 1998, from World Bank World Tables. White’s heteroscedasticity-adjusted t-statistics are reported in brackets. Coefficients that are significantly different from zero at the 95% confidence level are shown in bold. A: VARIABLES AVERAGED OVER 1960-80 1 2 Openness measure Sachs & Warner dummy variable 3 No. of obs. 96 96 96 ln RGDP0 - 0.0014 (0.7) 0.0026 (1.0) - 0.004 (-1.5) Open 0.020 (4.9) 0.108 (3.3) 0.077 (2.1) Open x logRGDP0 Investment2 Pop growth W/Pop growth adj. R2 0.208 - 0.011 (-2.8) -0.008 (-1.8) 0.247 0.078 (2.9) 0.09 (0.4) 0.68 (2.1) 0.347 W/Pop growth adj. R2 B: VARIABLES AVERAGED OVER 1980-98 4 5 Openness measure Sachs & Warner dummy variable 6 7 8 11 12 96 96 96 Population adjusted trade share 9 10 No. of obs. 109 109 109 Mixed measures: (T = pop adjusted trade share) 96 96 96 ln RGDP0 Open 0.004 (2.1) 0.003 (1.4) - 0.008 (-2.5) 0.005 (3.0) 0.005 (2.9) - 0.004 (-1.5) 0.013 (2.8) 0.002 (0.9) 0.003 (1.3) - 0.007 (-2.4) 0.019T (3.9) 0.010sw (2.3) 0.005sw (1.1) Open x logRGDP0 Investment2 Pop growth 0.174 0.002 (3.0) 0.005 (1.2) 0.020 (4.4) 0.176 0.143 (3.8) - 0.70 (-2.8) 0.67 (1.8) 0.409 0.226 0.002 (4.8) 0.016 (3.6) 0.225 0.084 (2.3) 0.001SW (2.4) 0.002T (4.3) 0.002T (3.1) - 0.65 (-2.8) 0.46 (1.3)) 0.386 0.289 0.286 0.097 (2.5) -0.82 (-3.4) 0.50 (1.4) 0.451 1.RGDP0 is real GDP per capita at the beginning of the period (Penn World Tables 5.6a). Investment is the average share of investment in GDP over the whole period, measured at constant international prices (PWT). W/Pop growth is the growth of the ratio of workforce to population (PWT). 2. Regressions using investment are estimated using 2SLS with beginning of period investment and investment price as instruments. 3. The population adjusted trade share is the residual from regressing log(trade share in GDP) on log(population) for the full pooled sample with 218 observations. 9 TABLE 1: BREAKDOWN OF SIGMA DIVERGENCE 1960-98: COUNTRIES RANKED BY RGDP 1960 REAL GDP per capita (1985$) 1960 1980 1998 REAL GDP per worker (1985$) 1960 1980 1990 REAL GDPpc terms of trade adjusted (1985$) 1960 1980 1990 WHOLE SAMPLE: 1960-80 2454 4170 5544 MEAN 0.025 0.010 Annual Growth Rate 0.815 1.004 1.347 VAR(log) Change in VAR(log) + 0.189 + 0.343 Change in Var – population weighted + 0.097 - 0.158 RICH SAMPLE: y60>$5,000 : N=19 7117 11475 14788 MEAN 0.027 0.015 Annual Growth Rate 0.042 0.023 0.064 VAR(log) Change - 0.019 + 0.041 MIDDLE SAMPLE: $1,500 < Y60 < $5,000 : N=35 2434 4579 6398 MEAN 0.032 0.013 Annual Growth Rate 0.008 0.035 0.466 VAR(log) Change + 0.027 + 0.431 POOR SAMPLE: Y60 < $1,500 : N=55 855 1385 1808 MEAN 0.021 0.006 Annual Growth Rate VAR(log) Change 0.187 0.329 0.622 + 0.142 + 0.293 4079 0.027 0.955 6629 6971 0.005 1.047 1.156 + 0.092 + 0.109 - 0.002 17168 0.022 0.049 25588 0.010 0.016 - 0.033 6478 0.031 0.009 11393 0.001 0.048 + 0.039 1850 2945 0.026 0.323 0.003 0.495 + 0.172 1631 0.027 0.815 - 0.035 28182 0.032 + 0.016 11551 0.270 + 0.222 + 0.084 6906 0.028 0.050 11365 0.014 0.025 - 0.025 2314 0.033 0.007 4201 0.005 0.034 + 0.027 3027 793 0.575 0.022 0.198 + 0.080 2628 2831 0.007 1.015 1.209 + 0.200 + 0.194 - 0.081 13127 0.066 + 0.041 4410 0.419 + 0.385 1176 1219 0.004 0.347 0.451 + 0.149 + 0.104 Source: Penn World Tables 5.6a, RGDPCH extrapolated to 1998 using World Bank World Tables measures of constant domestic price growth rates