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Suppose you have a cumulative distribution that is changing with time, namely $ P_t(x) $. Assume $ P_t $ is monotone increasing and smooth enough so that we can define $ x_t(P) = P_t^{-1} $. We want to track percentiles over time, so that the rate of change of the median would be described by \begin{equation*} \frac{d}{dt} x_t(1/2). \end{equation*} We could define a kind of fixed point (``fixed percentile''?) of the time evolution in the following sense: $ P_\ast $ is a fixed percentile at time $ t $ if it satisfies \begin{equation*} \frac{d}{dt} x_t(P_\ast) = 0. \end{equation*}

My question is: Does this ``fixed percentile'' have an established or better name? Is it used and defined in the literature? Do we know any of its properties, such as under what conditions it will exist and/or be unique?

For a concrete example, consider the Pareto distribution with scale parameter $ \beta(t) $ and shape parameter $ \alpha(t) $ so that \begin{equation*} P_t(x) = 1 - \left( \frac{\beta}{x} \right)^\alpha, \end{equation*} with $ x \geq \beta $. Then \begin{equation*} x_t(P) = \frac{\beta}{(1-P)^{1/\alpha}} \end{equation*} and \begin{equation*} \frac{dx_t}{dt} = \frac{\beta' \alpha^2 + \beta \alpha' \ln (1-P)}{\alpha^2 (1-P)^{1/\alpha}} \end{equation*} Solving for a fixed percentile, we get \begin{equation*} P_\ast = 1 - \exp\left(\frac{-\beta' \alpha^2}{\beta \alpha'}\right). \end{equation*} To make it even more concrete, let $ \beta(t) = t $ and \begin{equation*} \alpha = \frac{-\ln (2)}{\ln (t) - 5} \end{equation*} then $ P_\ast = 1/2 $ is independent of time ($ 1 \leq t < e^5 $), and the distribution is moving to the right ($ \beta' > 0 $) while simultaneously spreading out ($ \alpha' < 0 $) so that the median remains constant. In this case the median is a repelling fixed point of the distribution, separating the rich getting richer from the poor getting poorer.

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Do you want $\dfrac{d}{dt} x_t(P^*) = 0$ only at some particular $t$, or do you want it for all $t$? – Robert Israel Jul 30 '12 at 19:47
It is perhaps more interesting if it holds for all $ t $, but I'm interested either way. – Andrew T. Barker Jul 30 '12 at 19:53

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