...'residual' 87.5 percent. Later was realized that much of this residual might be due to human capital. Hence researchers developed augmented Solow models, which contain human capital as a regressor in explaining GDP growth.

The topic is important in the context of education and human capital policies and budget allocations in developing countries. Some versions of augmented models are found in Romer (1990), Barro and Sala-i-Martin (1995), Knight, Loyaza, and Villanueva (1993), Benhabib and Spiegel (1994) and Lucas (2002). Using a variety of older data and standard estimation and inference techniques these authors did not find human capital to be statistically significant. Barro and Lee (1993) constructed a measure of human capital based on the number of years of schooling of adults 25 or older for 129 countries. However, Barro and Lee (1994, 1996) or Caselli, Esquivel and Lefort (1996) did not find any unique importance of the human capital variable.

Mankiw, Romer and Weil (1992, hereafter "MRW") state that: "particularly for the developing countries, investment in human capital also becomes more quantitatively important when a more open trading environment and a better public infrastructure are in place." However, Temple (1998) applies robustness tests to MRW results and does not find human capital to be significant. By contrast, Judson (1998) studies the efficiency of existing educational allocations in a panel of countries. He uses cross-country growth decomposition regression to show that the correlation of human capital with capital accumulation and GDP growth is not significant in countries with poor allocations but is significant and positive in countries with better allocations. Thus better allocations and open trading environment might reverse the conclusions regarding the significance of human capital, since the earlier doubts were based on older data.

Recently many developing countries have opened up their markets to global competition and are installing the needed knowledge infrastructure. Has the time come to start investing in human capital? Bassanini, Scarpetta and Visco (2000) and Bassanini and Scarpetta (2002, 2001, "BaS" hereafter) use the data for OECD countries to find that human capital is statistically significant. The issue is very important for developing countries. Mamuneas, Savvides and Stengos (2006) also find a positive impact of human capital on economic growth in a group of high, middle, and low-income countries across continents consistent with BaS.

This paper applies the BaS version of the augmented Solow model to a panel of eighteen large developing countries over twenty years (1982-2001) measuring the importance of human capital in explaining the GDP growth. An earlier version of this paper used Vinod's (2003, 2004) new ME bootstrap for "dependent data," which was developed as an alternative to the moving blocks bootstrap for inference in financial economics. We note in passing that the use of modern bootstrap inference tools support the results reported here. We are using a larger sample of important developing countries with more recent data.

Recent less formal data analyses under the World Education Indicators (WEI) program has developed newer education indicators for the following developing countries: Argentina, Brazil, Chile, China, Egypt, India, Indonesia, Jamaica, Jordan, Malaysia, Paraguay, Peru, the Philippines, the Russian Federation, Sri Lanka, Thailand, Tunisia, Uruguay and Zimbabwe. Soto (2002) and Karine Tremblay (2002) find that education receives 4.9 % of GDP in OECD, 4.2% in WEI countries and 5.5% of national wealth in both. There is a more limited access to upper secondary and tertiary education in WEI compared with OECD countries. Accumulation of human capital improves economic growth through many channels and externalities. World Bank (1999) finds that education is the single most important key to poverty alleviation and that tertiary education increases income from 82% to 300% in WEI countries. World Bank (2000), and Cohen & Soto (2001) find a positive correlation between the number of years of schooling and per capita income growth from 1960 to 2000. Thus the informal analyses also point to a need to do more formal study of this paper.

The plan of the remaining paper is as follows. Section 2 describes the data and briefly reviews the endogenous growth theory behind the estimation equation. Section 3 describes our estimates based on time series and panel data. Section 4 has our conclusions.

II. The Data and Model Estimates

First let us briefly review the MRW model on which the BaS model is based. Being an augmented Solow model, one starts with a constant returns to scale production function where output is a function of capital (regular and human) and augmented labor. Let Y, K, H, L denote output, physical capital, human capital and labor, respectively. Now the starting production function is:

Y(t) = [K(t).sup.[alpha]] [H(t).sup.[beta]][(A(t)L(t)).sup.1-[alpha]-[beta]] (2.1)

where [alpha] and [beta] are parameters and A is the augmentation of labor. The...

NOTE: All illustrations and photos have been removed from this article.



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