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221013 ||| eng |
| 100 |
1 |
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|a Jones, Sam
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| 245 |
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|a Identifying Catch-Up Trajectories in Child Growth
|h Elektronische Ressource
|b New Methods with Evidence from Young Lives
|c Jones, Sam
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| 260 |
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|a Washington, D.C
|b The World Bank
|c 2018
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| 300 |
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|a 55 pages
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| 700 |
1 |
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|a Dang, Hai-Anh H.
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| 700 |
1 |
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|a Behrman, Jere R.
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| 700 |
1 |
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|a Anand, Paul
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| 041 |
0 |
7 |
|a eng
|2 ISO 639-2
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| 989 |
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|b WOBA
|a World Bank E-Library Archive
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| 490 |
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|a World Bank E-Library Archive
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| 028 |
5 |
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|a 10.1596/1813-9450-8353
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| 856 |
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|u http://elibrary.worldbank.org/doi/book/10.1596/1813-9450-8353
|x Verlag
|3 Volltext
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| 082 |
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|a 330
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| 520 |
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|a Definitions of catch-up growth in anthropometric outcomes among young children vary across studies. This paper distinguishes between catch-up in the mean of a group toward that of a healthy reference population versus catch-up within the group, associated with a narrowing of the outcome distribution. In contrast to conventional empirical approaches based on dynamic panel models, the paper shows how catch-up can be tested via a latent growth framework. Combined with a flexible estimator incorporating individual-specific intercepts and slopes, this enables between- and within-group forms of catch-up to be tested in a unified setting. The application of the proposed approach reveals significant differences in the nature, extent, and drivers of catch-up growth across the four Young Lives countries (Ethiopia, India, Peru, and Vietnam). In addition, the paper shows how conclusions about catch-up are sensitive to the way in which anthropometric outcomes are expressed
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