Toutes mes réponses sur les forums
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@ngjm95 159671 wrote:
Et le refus à un membre de parler de la Thailande parce qu’il n’est pas vietnamien à 100% ! Ce n’est pas du racisme?Cette tentative de discrimination est-elle basée sur des arguments solides ?
Bien sûr que non.
@ngjm95 159671 wrote:
A la lecture de ce qui est présenté dans cette discussion, on voit bien que la Thailande présente des tares importantes (corruption, infractions aux droits de l’homme, une démocratie de façade etc…) Ce pays montré en exemple dans l’Asie du Sud-Est ne vaut pas mieux que ses voisins .
Cela relativise beaucoup les reproches habituels adressés au Vietnam d’où ma conclusion que le Vietnam est devenu très fréquentable. Soyez sans crainte, d’autres révélations ne vont pas tarder:Voilà un tableau sur l’inégalité ses revenus de la Thailande plus importante celle du Vietnam :Vietnam:
Income inequality in Thailand
Incomes of poorest & richest have risen quickly in the past, economic pressures on Thai lower middle class now the real problem.
Map above shows differences in national income equality around the world as measured by the national Gini coefficient. A higher Gini coefficient means that a country has higher income inequality (Source: Wikipedia).
OK , l’index Gini montre qu’il y a plus d’inégalité en Thailande qu’au Vietnam. Mais je crois qu’il y a une petite erreur dans les calculs suivant
The Gini index is defined as a ratio of the areas on the Lorenz curve diagram. If the area between the line of perfect equality and the Lorenz curve is A, and the area under the Lorenz curve is B, then the Gini index is A / (A + B). Since A + B = 0.5, the Gini index is G = 2 * A or G = 1 – 2 B.
If the Lorenz curve is represented by the function Y = L (X), the value of B can be found with integration and:
In some cases, this equation can be applied to calculate the Gini coefficient without direct reference to the Lorenz curve. For example (taking y to mean the income or wealth of a person or household):- For a population uniform on the values yi, i = 1 to n, indexed in non-decreasing order (yi ≤ yi+1):
This may be simplified to:
This formula actually applies to any real population, since each person can be assigned his or her own yi.[14]- For a discrete probability function f(y), where yi, i = 1 to n, are the points with nonzero probabilities and which are indexed in increasing order (yi < yi+1):
where
and 
- For a cumulative distribution function F(y) that has a mean μ and is zero for all negative values of y:
(This formula can be applied when there are negative values if the integration is taken from minus infinity to plus infinity.)- Since the Gini coefficient is half the relative mean difference, it can also be calculated using formulas for the relative mean difference. For a random sample S consisting of values yi, i = 1 to n, that are indexed in non-decreasing order (yi ≤ yi+1), the statistic:
is a consistent estimator of the population Gini coefficient, but is not, in general, unbiased. Like G, G (S) has a simpler form: 
.
