John Rawls' a theory of justice. Social contract vs utilitarianism Rawls' A Theory of Justice constructs a modem version of the theory of social contract by emphasizing distributive justice, which attempts to offer an alternative to the utilitarian doctrine. Unlike utilitarianism, Rawls' theory is neither altruistic nor teleogical, but deontological : one must try to find the right rules without taking a stand on the purposes of individuals. These rules, the two principles of justice — the broadest basic liberties and democratic equality together with advantage granted to the underprivileged (fraternity) —, are in lexicographic order. They form a social optimum (what is right) compatible with, but taking precedence over, the economic optimum (relative only to what is good). The choice of these principles belongs to game theory. The players will choose them rather than those pertaining to any other doctrine because of the maximin criterion. Rawls is open to « public choice » critics who reject distributive justice (fraternity) on the basis of utilitarian arguments. Rawls' constructivism does not agree easily with the individualism and liberalism which he claims.
Le statut de loi que Marx confère à son énoncé s'avère ambigu dans la mesure où il se déploie au sein de différents espaces relativement étanches (ceux des biens, des valeurs, et des prix). Les controverses portent sur les principales contre tendances — la croissance du taux d'exploitation (pl/v) et la constance de la composition organique du capital (c/v) — qui relèvent de la théorie de la répartition (la thèse du prof it squeeze) et de celle de la concurrence (le théorème d'Okishio). L'analyse empirique, fondée sur la cas de la France depuis la dernière guerre mondiale, aboutit à une information assez paradoxale : pl/v et c/v exprimés en termes monétaires demeurent constants jusqu'à l'ouverture de la crise. La baisse du taux de profit apparaft donc comme une conséquence et non comme une cause de la crise.
Myths and Facts in Algerian Land Reform ; an Evaluation Ten Years afterwards.
The Algerian Land Reform which became operational under State control in 1971, aimed at removing the dualist agrarian framework so as to increase output, reduce unemployment and set up rural structures. Ten years later, what in fact has been achieved is rather disappointing. Extension of the agricultural public sector reproduces — in a different pattern — the previous dualism, land re-distribution is limited and output almost stationary ; making new jobs, characterized by the development of salaried posts, is still insufficient and fittings of rural structures have not gone beyond the blue-print stage. Failure to make the Reform truly applicable is marked by the secondary role agriculture is dedicated to play, a constant subordinate to industrialization.
AbstractFactors detrimental to funding females or micro‐entrepreneurs arise both from the demand side of businesses, such as the absence of funding need versus self‐selection despite account holding, and from the supply side of financial institutions, such as deficient financial infrastructure and discrimination towards loan applicants. A sequential model addresses both the demand and the supply sides, prior and during the COVID‐19 pandemic, upon four MENA countries, namely Egypt, Jordan, Morocco and Tunisia. Probit regressions use two distinct though comparable sub‐samples of micro‐enterprises from the 2020 World Bank Enterprise Survey (WBES) and the Economic Research Forum (ERF) COVID‐19 Monitor in 2021. Prior the pandemic, micro‐enterprises are prone to self‐selection vis‐à‐vis loan application in Tunisia (ERF) and in all North African countries (WBES). During the pandemic, no self‐selection vis‐à‐vis government support affects either female or micro‐entrepreneurs. Prior the pandemic, females or micro‐entrepreneurs face no loan discrimination (WBES). During the pandemic, females face no discrimination regarding government support, whereas Moroccan micro‐entrepreneurs do (ERF). Prior the pandemic, financial inclusion runs opposite to both self‐selection and discrimination (WBES), but not for self‐selection (ERF), whereas it proves insignificant during the pandemic with respect to self‐selection or discrimination, whatever the sub‐sample.
50 ans de recherche suggèrent que le concept d'économie informelle constitue un ensemble flou. Les diverses théories, dualisme, structuralisme et institutionnalisme n'identifient pas les mêmes causes de l'informalité, ni les mêmes mécanismes d'ajustement sur les marchés. La définition toujours plus large de l'économie informelle, cependant distincte de l'économie non-observée, demeure tributaire de la genèse de ses différentes mesures : unité de production ou emploi ? Les trends et les cycles relatifs à l'économie informelle permettent d'établir des faits stylisés. Les enjeux et les résultats de la formalisation de l'économie informelle sont illustrés par le cas l'Afrique du Nord. Classification JEL : E26, J46, O17
Nous examinons la place des jeunes dans l'emploi informel, ainsi que leur contribution aux différentiels de revenus entre hommes et femmes au sein de l'économie informelle. Nous appliquons la méthode de décomposition Oaxaca-Ransom à un échantillon de 7816 jeunes de 15-29 ans en 2015 d'Afrique du Nord. Des régressions quantiles analysent la répartition du revenu par genre, selon la distinction emploi formel / informel, sur un sous-échantillon de 1 941 salariés et non-salariés. Selon un modèle de décomposition qui évalue l'écart de revenu selon le genre et le statut dans l'emploi, les femmes sont discriminées.
PurposeThis paper aims to address the following research question: Is loan funding to female entrepreneurs in Egypt, Tunisia and Morocco affected by self-selection from borrowers or/and discrimination from lenders? This paper sheds light on empirical literature review, which displays mixed evidence.Design/methodology/approachThe authors use a pooled sample of 3,896 businesses in Egypt, Morocco and Tunisia drawn from the 2013 World Bank Enterprise Survey (WBES). Despite selection biases and overweighing, the sample provides descriptive statistics upon gender ownership and gender management (human capital characteristics and financial data). The authors design two regression logistic models with interaction to investigate loan demand and loan granting with respect to self-selection vs discrimination. Female management is disentangled from female ownership with respect to entrepreneurship.FindingsNeither self-selection nor discrimination affects female owners compared with their male counterparts, whereas female managers do self-select themselves. In as much as the WBES female subsample include several biases, the authors eventually emphasise the importance of the non-surveyed informal sector, which includes most (micro-)businesses, and loan funding provided by the microfinance industry to these female businesses. Microfinance fills the gap for working capital but not for fixed assets. The size of the business is a major factor explaining both self-selection and discrimination.Research limitations/implicationsFindings of this study have important policy implications for closing the gender gap in accessing finance. In addition to supply-side factors, demand-side factors should be addressed. Informality also needs to be addressed, as many micro and small enterprises owned or managed by women are informal entities without registration or/and social protection. One way to increase women's demand for financial services is to introduce financial products to meet their needs (e.g. social protection basic coverage). Governments can help develop these new products by strengthening the microfinance industry with a favourable regulatory and institutional framework. The authors also wonder about the extension of this study. Thus, a new cross-sectional analysis of the most recent surveys in the North African region would allow the authors to enlarge the overall sample and measure the evolution of the gender gap over time.Originality/valueSo far, funding female entrepreneurship remained little investigated in these North African countries. Several sampling biases in the WBES – small businesses underestimation and manufacturing industry overweighting, which have been overlooked so far, explain the absence of self-selection and discrimination. In contrast, size plays an important role. Hence, the focus on microenterprises (the informal sector) and the microfinance industry suggests indeed that female entrepreneurs operating in small businesses have to cope with both self-selection and discrimination.
Les déterminants du taux d'intérêt débiteur sont estimés grâce à un modèle à variables instrumentales sur un panel de 66 IMF de la région Moyen-Orient et Afrique du Nord de 2004 à 2014. Cinq hypothèses relatives aux observations de la littérature sur la microfinance sont testées. Les hypothèses relatives aux facteurs internes (charges d'exploitation et âge) ne sont pas corroborées et la performance sociale exerce un impact contrasté sur le taux d'intérêt dont la performance financière est souvent le principal déterminant. Les facteurs externes (concurrence et réglementation) corroborent les observations. La région MOAN apparaît plutôt atypique au sein de la microfinance. Classification JEL : C13, C33, D23, G21, I3
International audience ; Prostitution regimes in the EU-28 include prohibition, regulation and abolition; we tackle this typology from the perspective of both free sex work and forced labour, in order to gauge the magnitude of the European sex market as of 2010. We document the behaviour of customers on the demand-side for prostitution. Next, we address the supply-side, using HIV prevalence among sex workers to achieve a first series of two estimates. We design a second series of two estimates from miscellaneous sources (NGOS and the police). We investigate forced sexual labour trafficking, providing an additional series of estimates from the ILO and from Eurostat and UNODC. We check the magnitude of prostitution as regards employment figures and ranking with respect to the distribution of population in the EU countries. Thanks to an ordered probit, we test all five estimates; eventually, we come up with one best estimate (from HIV prevalence) that is also the lowest one.
