Abstract
Measuring human capital has been a challenge for economists. In the MENA region, scarcity of comparable and reliable data complicates the task. To overcome this challenge, we rely on an international survey that covers most of the region. In addition to current estimates, we make a forward-looking assessment of how human capital stocks may change in the future. We found human capital stocks are low in most SEMC, except in Israel and Turkey, where returns to education are flat. Despite high attainment levels, Greece, Spain, and Portugal perform poorly, only marginally surpassing the bottom-ranked SEMC. Thus improving attainment levels can produce measurable gains in the future only when the returns to education are high.
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Notes
- 1.
See Woessmann (2003) for a review of literature using a variety of measures.
- 2.
A more detailed description of the model, its underlying assumptions and results can be found in Arbak (2012).
- 3.
The incomes data were incomplete for most countries of interest for the fifth wave of the survey. In particular, subjects were asked to rank their incomes on a subjective scale, rather than a pre-defined and clearly stated income ranking, as was the case in our database.
- 4.
A more appropriate measure would be the years employed; however, the survey does not contain respective data.
- 5.
Note that under the previous specification, the income scales, a, may differ between countries.
- 6.
A similar approach was used by Krueger and Lindahl (2001) to resolve the interval data for income in the WVS dataset. In particular, the authors have resolved the top-coding problem by fitting a Pareto distribution to family incomes beyond the median income and calculating the mean for the censored distribution for the top income category. For all other cases, the authors assign mid-points of each income interval.
- 7.
Although we use only household income, the human capital measure in Eq. 17.1 is essentially a ratio of two incomes, which should limit this bias.
- 8.
Barro and Lee (2010) use a specific methodology for filling in missing observations. These methods were closely followed here to generate the forecasts using backward extrapolation.
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Arbak, E. (2015). Measuring Returns to Education and Human Capital. In: Ayadi, R., Dabrowski, M., De Wulf, L. (eds) Economic and Social Development of the Southern and Eastern Mediterranean Countries. Springer, Cham. https://doi.org/10.1007/978-3-319-11122-3_17
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