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Compositions vs Gini: A new metric to evaluate the effects of land-income disparities

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  • Mauricio Velasquez

Abstract

I show how compositional analysis developed in Geology is applied to the same data that are used to construct the Gini coefficient as a useful alternative to the Gini index to test specific hypothesis about the simultaneous interaction of classes (groups) in a multivariate regression environment. In this paper I propose using compositional analysis to study landownership dynamics as a productive alternative to the Land Gini. Specifically, I show that because identical Gini calculations result from drastically different land distributions it is wrong to narrow its interpretation to theories relating only the very rich and the very poor while ignoring the middle class. To illustrate this, I use cadastral longitudinal data from Colombia (capturing effects before and after local democratization) to compare results between identical multilevel longitudinal models in which the key independent variables are either balances calculated via compositions, or the land Gini coefficient. I show that even when the Gini is significantly correlated with developmental outcomes such as access to clean water and electricity, the most likely story is about a relatively stronger middle vs large landowning class.

Suggested Citation

  • Mauricio Velasquez, 2016. "Compositions vs Gini: A new metric to evaluate the effects of land-income disparities," 2016 Papers pve364, Job Market Papers.
    • Handle: RePEc:jmp:jm2016:pve364
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    References listed on IDEAS

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    1. Oded Galor & Omer Moav & Dietrich Vollrath, 2009. "Inequality in Landownership, the Emergence of Human-Capital Promoting Institutions, and the Great Divergence," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 76(1), pages 143-179.
    2. Stanley L. Engerman & Kenneth Lee Sokoloff, 2002. "Factor Endowments, Inequality, and Paths of Development Among New World Economies," Economía Journal, The Latin American and Caribbean Economic Association - LACEA, vol. 0(Fall 2002), pages 41-110, August.
    3. Deininger, Klaus & Squire, Lyn, 1998. "New ways of looking at old issues: inequality and growth," Journal of Development Economics, Elsevier, vol. 57(2), pages 259-287.
    4. Ansell,Ben W. & Samuels,David J., 2014. "Inequality and Democratization," Cambridge Books, Cambridge University Press, number 9781107000360.
    5. Lupu, Noam & Pontusson, Jonas, 2011. "The Structure of Inequality and the Politics of Redistribution," American Political Science Review, Cambridge University Press, vol. 105(2), pages 316-336, May.
    6. Easterly, William, 2001. "The Middle Class Consensus and Economic Development," Journal of Economic Growth, Springer, vol. 6(4), pages 317-335, December.
    7. Palma, J.G., 2011. "Homogeneous middles vs. heterogeneous tails, and the end of the ‘Inverted-U’: the share of the rich is what it's all about," Cambridge Working Papers in Economics 1111, Faculty of Economics, University of Cambridge.
    8. K. Hron & P. Filzmoser & K. Thompson, 2012. "Linear regression with compositional explanatory variables," Journal of Applied Statistics, Taylor & Francis Journals, vol. 39(5), pages 1115-1128, November.
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    JEL classification:

    • O - Economic Development, Innovation, Technological Change, and Growth
    • C - Mathematical and Quantitative Methods
    • A - General Economics and Teaching

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