Suchergebnisse

AbstractThis study elucidates the link and effect of ethical reinforcement in the post‐financial crisis era by taking two congruent directions to demonstrate that ethical reinforcement can be accomplished by either a continuous ethical training or a meticulous code of business ethics—which members of the mutual fund industry claim they adhere to—as both have a positive effect on the funds' performance, including sizeable gains to investors. Furthermore, evidence divulges that ethical reinforcement moderates the performance of ethical or socially responsible investments (SRI) funds more than nonethical investments, suggesting that a perspective of ethical or SRI classification of a fund alone is not sufficient, but it is necessary to have the institutional ethical environment and/or managers' continuous ethical training. This result supports the notion of financial market discipline and reveals some factors behind SRI or ethical funds returns, notably during the period following the recent financial crisis.

In this scooping paper on the Tunisian economy we review the historical background of the economy which has undergone substantial structural change since independence in 1956. In particular we emphasize that past record of consistent growth has often masked inequality, regional disparities and high unemployment rates among educated youth. We then evaluate the performance of the manufacturing industry over the past five decades in terms of exports, production and foreign direct investment. We conclude with a review of the main industrial policies undertaken by the government since independence.

Amara M, Ayadi M. The local geographies of welfare in Tunisia: Does neighbourhood matter?The aim of this article is to show that spatial analysis techniques outperform non‐spatial statistical counterparts for understanding the geographic determinants of welfare and poverty in Tunisia. First, an Exploratory Spatial Data Analysis, based on a Geographical Information System, was conducted to visualise the local spatial structure of welfare. Second, a spatial autoregressive (SAR) model and a geographically weighted regression (GWR) model, respectively, were used to deal with both spatial autocorrelations and unobserved spatial heterogeneity of households' behaviours. Spatial and non‐spatial models were compared according to their predictive performances. Results of this case study confirm that SAR and GWR spatial models are preferable to the traditional non‐spatial regression model and that they give a better approximation of the Tunisian poverty map.