Explaining the size distribution of cities: x-treme economies

We criticize the theories used to explain the size distribution of cities. They take an empirical fact and work backward to obtain assumptions on primitives. The induced theoretical assumptions on consumer behavior, particularly about their inability to insure against the city-level productivity shocks in the model, are untenable. With either self insurance or insurance markets, and either an arbitrarily small cost of moving or the assumption that consumers do not perfectly observe the shocks to firms' technologies, the agents will never move. Even without these frictions, our analysis yields another equilibrium with insurance where consumers never move. Thus, insurance is a substitute for movement. We propose an alternative class of models, involving extreme risk against which consumers will not insure. Instead, they will move, generating a Fréchet distribution of city sizes that is empirically competitive with other models.Zipf's Law; Gibrat's Law; Size Distribution of Cities; Extreme Value Theory

Explaining the Size Distribution of Cities: X-treme Economies

We criticize the theories used to explain the size distribution of cities. They take an empirical fact and work backward to obtain assumptions on primitives. The induced theoretical assumptions on consumer behavior, particularly about their inability to insure against the city-level productivity shocks in the model, are untenable. With either self insurance or insurance markets, and either an arbitrarily small cost of moving or the assumption that consumers do not perfectly observe the shocks to firms' technologies, the agents will never move. Even without these frictions, our analysis yields another equilibrium with insurance where consumers never move. Thus, insurance is a substitute for movement. We propose an alternative class of models, involving extreme risk against which consumers will not insure. Instead, they will move, generating a Fréchet distribution of city sizes that is empirically competitive with other models.Zipf's Law; Gibrat's Law; Size Distribution of Cities; Extreme Value Theory

A scale-free transportation network explains the city-size distribution

Zipf’s law is one of the best-known empirical regularities of the city-size distribution. There is extensive research on the subject, where each city is treated symmetrically in terms of the cost of transactions with other cities. Recent developments in network theory facilitate the examination of an asymmetric transport network. Under the scale-free transport network framework, the chance of observing extremes becomes higher than the Gaussian distribution predicts and therefore it explains the emergence of large clusters. City-size distributions share the same pattern. This paper proposes a way to incorporate network structure into urban economic models and explains the city-size distribution as a result of transport cost between cities.Zipf’s law; city-size distribution; scale-free network

Explaining the size distribution of cities: x-treme economies

The methodology used by theories to explain the size distribution of cities takes an empirical fact and works backward to first obtain a reduced form of a model, then pushes this reduced form back to assumptions on primitives. The induced assumptions on consumer behavior, particularly about their inability to insure against the city-level productivity shocks in the model, are untenable. With either self insurance or insurance markets, and either an arbitrarily small cost of moving or the assumption that consumers do not perfectly observe the shocks to firms' technologies, the agents will never move. Even without these frictions, our analysis yields another equilibrium with insurance where consumers never move. Thus, insurance is a substitute for movement. Even aggregate shocks are insufficent to generate consumer movement, since consumers can borrow and save. We propose an alternative class of models, involving extreme risk against which consumers will not insure. Instead, they will move.Zipf's Law, Gibrat's Law, Size Distribution of Cities, Extreme Value Theory

Explaining the size distribution of cities: x-treme economies

We criticize the theories used to explain the size distribution of cities. They take an empirical fact and work backward to obtain assumptions on primitives. The induced theoretical assumptions on consumer behavior, particularly about their inability to insure against the city-level productivity shocks in the model, are untenable. With either self insurance or insurance markets, and either an arbitrarily small cost of moving or the assumption that consumers do not perfectly observe the shocks to firms' technologies, the agents will never move. Even without these frictions, our analysis yields another equilibrium with insurance where consumers never move. Thus, insurance is a substitute for movement. We propose an alternative class of models, involving extreme risk against which consumers will not insure. Instead, they will move, generating a Fréchet distribution of city sizes that is empirically competitive with other models.Zipf's Law; Gibrat's Law; Size Distribution of Cities; Extreme Value Theory

Explaining the size distribution of cities: x-treme economies

We criticize the theories used to explain the size distribution of cities. They take an empirical fact and work backward to obtain assumptions on primitives. The induced theoretical assumptions on consumer behavior, particularly about their inability to insure against the city-level productivity shocks in the model, are untenable. With either self insurance or insurance markets, and either an arbitrarily small cost of moving or the assumption that consumers do not perfectly observe the shocks to firms' technologies, the agents will never move. Even without these frictions, our analysis yields another equilibrium with insurance where consumers never move. Thus, insurance is a substitute for movement. We propose an alternative class of models, involving extreme risk against which consumers will not insure. Instead, they will move, generating a Fréchet distribution of city sizes that is empirically competitive with other models.Zipf's Law; Gibrat's Law; Size Distribution of Cities; Extreme Value Theory

Explaining the size distribution of cities: x-treme economies

We criticize the theories used to explain the size distribution of cities. They take an empirical fact and work backward to obtain assumptions on primitives. The induced theoretical assumptions on consumer behavior, particularly about their inability to insure against the city-level productivity shocks in the model, are untenable. With either self insurance or insurance markets, and either an arbitrarily small cost of moving or the assumption that consumers do not perfectly observe the shocks to firms' technologies, the agents will never move. Even without these frictions, our analysis yields another equilibrium with insurance where consumers never move. Thus, insurance is a substitute for movement. We propose an alternative class of models, involving extreme risk against which consumers will not insure. Instead, they will move, generating a Fréchet distribution of city sizes that is empirically competitive with other models.Zipf's Law; Gibrat's Law; Size Distribution of Cities; Extreme Value Theory

Explaining the Size Distribution of Cities: X-treme Economies

The methodology used by theories to explain the size distribution of cities takes an empirical fact and works backward to first obtain a reduced form of a model, then pushes this reduced form back to assumptions on primitives. The induced assumptions on consumer behavior, particularly about their inability to insure against the city-level productivity shocks in the model, are untenable. With either self insurance or insurance markets, and either an arbitrarily small cost of moving or the assumption that consumers do not perfectly observe the shocks to firms' technologies, the agents will never move. Even without these frictions, our analysis yields another equilibrium with insurance where consumers never move. Thus, insurance is a substitute for movement. Even aggregate shocks are insufficent to generate consumer movement, since consumers can borrow and save. We propose an alternative class of models, involving extreme risk against which consumers will not insure. Instead, they will move.Zipf's Law, Gibrat's Law, Size Distribution of Cities, Extreme Value Theory

Explaining the size distribution of cities: x-treme economies

We criticize the theories used to explain the size distribution of cities. They take an empirical fact and work backward to obtain assumptions on primitives. The induced theoretical assumptions on consumer behavior, particularly about their inability to insure against the city-level productivity shocks in the model, are untenable. With either self insurance or insurance markets, and either an arbitrarily small cost of moving or the assumption that consumers do not perfectly observe the shocks to firms' technologies, the agents will never move. Even without these frictions, our analysis yields another equilibrium with insurance where consumers never move. Thus, insurance is a substitute for movement. We propose an alternative class of models, involving extreme risk against which consumers will not insure. Instead, they will move, generating a Fréchet distribution of city sizes that is empirically competitive with other models.Zipf's Law; Gibrat's Law; Size Distribution of Cities; Extreme Value Theory