A new database on human capital stock in developing and industrial countries: Sources, methodology, and results

Nehru, Vikram; Swanson, Eric; Dubey, Ashutosh Kumar

doi:10.1016/0304-3878(94)00054-g

Cited by 476 publications

(456 citation statements)

References 3 publications

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“…The main drawback of the Barro and Lee methodology is that the authors used existing real data and interpolated gaps based on enrolment rates, making the data very sensitive to inconsistencies in the educational categories used, as mentioned above. Similar independent efforts have been made by Kyriacou (1991), Lau et al (1991), Nehru et al (1995), De la Fuente and Doménech (2006) and by Cohen and Soto (2007), which in many cases result in quite different estimates of mean years of schooling, with most of the estimates being significantly higher than Barro and Lee. A recent summary of available educational datasets can be found in and Bloom (2006).…”

Section: Existing Data and Previous Reconstruction Effortsmentioning

confidence: 61%

Reconstruction of populations by age, sex and level of educational attainment for 120 countries for 1970-2000

Lutz

Goujon²,

Sanderson³

2007

Populationyearbook

196

192

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Using demographic multi-state methods for back projecting the populations of 120 countries by age, sex and level of educational attainment from 2000 to 1970 (covering 93 percent of the 2000 world population), this paper presents an ambitious effort to reconstruct human capital data which are essential for empirically studying the aggregate level returns to education. Unlike earlier reconstruction efforts, this new dataset jointly produced at the International Institute for Applied Systems Analysis (IIASA) and the Vienna Institute of Demography (VID) gives the full educational attainment distributions for four categories (no education, primary, secondary and tertiary education) by five-year age groups and with definitions that are strictly comparable across time. Based on empirical distributions of educational attainment by age and sex for the year 2000, the method moves backward along cohort lines while explicitly considering the fact that men and women with different education have different levels of mortality. The resulting dataset will allow new estimates on the impact of agespecific human capital growth on economic growth and first results show-unlike earlier studies-a consistently positive effect.

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Section: Existing Data and Previous Reconstruction Effortsmentioning

confidence: 61%

Reconstruction of populations by age, sex and level of educational attainment for 120 countries for 1970-2000

Lutz

Goujon²,

Sanderson³

2007

Populationyearbook

196

192

View full text Add to dashboard Cite

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“…Data on GDP and its volatility are obtained from Mark.5.6 of Penn's Tables (Summer and Heston 1991) extended to 1995using UNDP (2001. Data on income inequality are from Deininger and Squire (1996), data on physical capital stocks are from Nehru and Dhareshwar (1993) and data on liquidity measures are from King and Levine (1993). Descriptive statistics are reported in table 1.…”

Section: Data Sources and Empirical Strategymentioning

confidence: 99%

Risk and the distribution of human capital

Checchi

Garcı́a-Peñalosa

2004

Economics Letters

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We develop a model in which aggregate production risk affects individuals' education decisions, and hence determines both the average level of education and the distribution of human capital. The model predicts that greater risk should be associated with greater educational inequality and a lower average attainment. An empirical test using panel data supports this conclusion. JEL classification numbers: I20; J24; O15; N30

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“…6 We measure the average productivity of capital by the ratio of the flow of current output to the capital stock. Data on the capital stock for the period 1963-90 were obtained from the World Bank Database compiled by Nehru et al (1993). Capital stock figures from 1991 to 1997 were constructed following the perpetual inventory method assuming a depreciation rate of 4 per cent and uprating the price of capital goods in line with the GDP deflator.…”

Section: Resultsmentioning

confidence: 99%

Excess Credit and the South Korean Crisis

Demetriades¹,

Fattouh²

2008

Domestic Resource Mobilization and Financial Development

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We provide a novel empirical analysis of the South Korean credit market that reveals large volumes of excess credit since the late 1970s, indicating that a sizeable proportion of total credit was being used to refinance unprofitable projects. Our findings are consistent with theoretical literature that suggests that soft budget constraints and overborrowing were significant factors behind the Korean financial crisis of 1997-98.

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A new database on human capital stock in developing and industrial countries: Sources, methodology, and results

Cited by 476 publications

References 3 publications

Reconstruction of populations by age, sex and level of educational attainment for 120 countries for 1970-2000

Reconstruction of populations by age, sex and level of educational attainment for 120 countries for 1970-2000

Risk and the distribution of human capital

Excess Credit and the South Korean Crisis

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