Please use this identifier to cite or link to this item: https://www.um.edu.mt/library/oar/handle/123456789/72315
Title: Rawlsian land reform with human capital : a social inclusion process for the landless ‘underdog’
Authors: Rocha de Sousa, Miguel
Keywords: Land reform -- Case studies
Human Capital
Welfare economics
Issue Date: 2016
Publisher: ISMASYSTEMS Scientific Research
Citation: Rocha de Sousa, M. (2016). Rawlsian land reform with human capital: a social inclusion process for the landless ‘underdog’. International Journal of Finance, Insurance and Risk Management, 6(4), 1238-1243.
Abstract: Focusing on the concept of Rawlsian-welfare-analysis, we evaluate land reform in a context of human capital. This theoretical and conceptual analysis is applied to the question of equity and social inclusion: our model previews that latifundia will be divided creating either mesofundia or microfundia. The way the social optimum is achieved, and the way we express the social welfare function is new to the literature, as far as we know, no Rawlsian including land reform has been tempted. The Rawlsian welfare function, in a context of uncertainty, corresponds to the max-min criteria. This means that if land is given to the social underdog, then his welfare improves, but the amount of land must be large enough in order to get him out of the poverty trap (human capital defined) threshold. The iteration of this principle to the successive “underdogs” creates the notion of a dynamic social including Rawlsian land reform. Equity can be improved if we look by the planner’s eyes in a Rawlsian way. This analysis then can be expanded to free market analysis, using the Second Fundamental Theorem of Welfare Analysis and market prices can be retrieved by the Negishi procedure. We also present a criticism to Rawlsian land reform, in the form of the least state interventionism, an utmost version of the liberal paradigm, the anarchic one - Nozickian land reform.
URI: https://www.um.edu.mt/library/oar/handle/123456789/72315
Appears in Collections:Volume 6, Issue 4, 2016

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