Many empirical studies document power law behavior in size distributions of economic interest such as cities, firms, income, and wealth. One mechanism for generating such behavior combines independent and identically distributed Gaussian additive shocks to log-size with a geometric age distribution. We generalize this mechanism by allowing the shocks to be non-Gaussian (but light-tailed) and dependent upon a Markov state variable. Our main results provide sharp bounds on tail probabilities and simple formulas for Pareto exponents . We present two applications: (i) we show that  the tails of the wealth distribution in a heterogeneous-agent dynamic general equilibrium model with idiosyncratic endowment risk decay exponentially, unlike models with investment risk where the tails may be Paretian, and (ii) we show that a random growth model for the population dynamics of Japanese prefectures is consistent with the observed Pareto exponent but only after allowing for Markovian dynamics.
Many empirical studies document power law behavior in size distributions of economic interest such as cities, firms, income, and wealth. One mechanism for generating such behavior combines independent and identically distributed Gaussian additive shocks to log-size with a geometric age distribution. We generalize this mechanism by allowing the shocks to be non-Gaussian (but light-tailed) and dependent upon a Markov state variable. Our main results provide sharp bounds on tail probabilities , a simple equation determining Pareto exponents, and comparative statics . We present two applications: we show that (i) the tails of the wealth distribution in a heterogeneous-agent dynamic general equilibrium model with idiosyncratic investment risk are Paretian, and (ii) a random growth model for the population dynamics of Japanese municipalities is consistent with the observed Pareto exponent but only after allowing for Markovian dynamics.
R
and simple formulas for Pareto exponents
, a simple equation determining Pareto exponents, and comparative statics
D
(i)
A
(i)
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endowment risk decay exponentially, unlike models with investment risk where the tails may be
investment risk are
D
we show that
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prefectures
municipalities