Determination of Pareto Exponents in Economic Models Driven by Markov Multiplicative Processes
研究了动态经济系统中单位规模稳态分布的尾部形状，发现其具有帕累托上尾，指数由矩阵值函数谱半径的方程唯一正解给出，并提供了上尾中类型分布的刻画。
This article contains new tools for studying the shape of the stationary distribution of sizes in a dynamic economic system in which units experience random multiplicative shocks and are occasionally reset. Each unit has a Markov‐switching type, which influences their growth rate and reset probability. We show that the size distribution has a Pareto upper tail, with exponent equal to the unique positive solution to an equation involving the spectral radius of a certain matrix‐valued function. Under a nonlattice condition on growth rates, an eigenvector associated with the Pareto exponent provides the distribution of types in the upper tail of the size distribution.