Yannis M. Ioannides

The evolution of city size distributions

We review the accumulated knowledge on city size distributions and determinants of urban growth. This topic is of interest because of a number of key stylized facts, including notably Zipf’s law for cities (which states that the number of cities of size greater than S is proportional to 1/S) and the importance of urban primacy. We first review the empirical evidence on the upper tail of city size distribution. We offer a novel discussion of the important econometric issues in the characterization of the distribution. We then discuss the theories that have been advanced to explain the approximate constancy of the distribution across very different economic and social systems, emphasizing both bare-bone statistical theories and more developed economic theories. We discuss the more recent work on the determinants of urban growth and, in particular, growth regressions, economic explanations of city size distributions other than Gibrat’s law, consequences of major shocks (quasi natural experiments), and the dynamics of U.S. urban evolution.

Zipf's law for cities: an empirical examination

We use data for metro areas in the United States, from the US Census for 1900 - 1990, to test the validity of Zipfs Law for cities. Previous investigations are restricted to regressions of log size against log rank. In contrast, we use a nonparametric procedure to calculate local Zipf exponents from the mean and variance of city growth rates. This also allows us to test for the validity of Gibrats Law for city growth processes. Despite variation in growth rates as a function of city size, Gibrats Law does hold. In addition the local Zipf exponents are broadly consistent with Zipfs Law. Deviations from Zipfs Law are easily explained by deviations from Gibrats Law.

Interactions, neighborhood selection and housing demand

This paper contributes to the growing literature that identifies and measures the impact of social context on individual economic behavior. We develop a model of housing demand with neighborhood e®ects and neighborhood choice. Modelling neighborhood choice is of fundamental importance in estimating and understanding endogenous and exogenous neighborhood effects. That is, to obtain unbiased estimates of neighborhood effects, it is necessary to control for non-random sorting into neighborhoods. Estimation of the model exploits a unique data set of household data that has been augmented with contextual information at two di®erent levels (“scales”) of aggregation. One is at the neighborhood cluster level, of about ten neighbors, with the data coming from a special sample of the American Housing Survey. A second level is the census tract to which these dwelling units belong. Tract-level data are available in the Summary Tape Files of the decennial Census data. We merge these two data sets by gaining access to confidential data of the U.S. Bureau of the Census. We overcome some limitations of these data by implementing some significant methodological advances in estimating discrete choice models. Our results for the neighborhood choice model indicate that individuals prefer to live near others like themselves. This can perpetuate income inequality since those with the best opportunities at economic success will cluster together. The results for the housing demand equation are similar to those in our earlier work [Ioannides and Zabel (2000] where we find evidence of significant endogenous and contextual neighborhood effects. (This abstract was borrowed from another version of this item.)

Dynamic aspects of consumer decisions in housing markets

Abstract In this study we estimate a model of the joint tenure, length of stay, and consumption level choices of families in the housing market. This is the first attempt we know of to do this type of estimation. The data pertain to a single residence spell per household from the Panel Study of Income Dynamics. Wealthier and better educated families were found to be more mobile. In terms of housing consumption, after accounting for tenure choice and controlling for planned length of stay, renters and owners were found to have similar demand function relationships in terms of the impacts of socioeconomic variables. This confirms the notion that renters and owners are not differentiated by housing choice but simply in life-cycle circumstances as to when it is optimal to own or rent.

Estimating the consumption and investment demands for housing and their effect on housing tenure status

Theoretical work suggests that families live in owner-occupied housing if their investment demand for housing exceeds their consumption demand for housing. Using household data from the 1983 Survey of Consumer Finances, the authors test this theory by estimating an ordered probit model of whether families rent without owning property, rent while owning property other than their home, own their home without owning other properties, or own their home in addition to other properties. For owner-occupiers who own additional property, both the investment and consumption demands are directly observed, enabling the authors to separately identify these functions. Copyright 1994 by MIT Press.

RESIDENTIAL NEIGHBORHOOD EFFECTS

Abstract This paper reports an empirical investigation of housing maintenance decisions which allows for social interactions within small residential neighborhoods with data from the American Housing Survey for 1985 and 1989. The study explores a neglected feature of the data, namely the availability of data of neighborhood clusters for metropolitan areas in the United States, with neighborhoods consisting of a dwelling unit and its 10 nearest neighbors. The paper identifies an important, and statistically very significant, effect of social interactions, while individual and dwelling unit characteristics are accounted for.

Spatial interactions among U.S. cities: 1900-1990

Abstract We test implications of economic geography by exploring spatial interactions among U.S. cities. We use a data set consisting of 1900–1990 metro area populations, and spatial measures including distance from the nearest larger city in a higher-tier, adjacency, and location within U.S. regions. We also date cities from their time of settlement. We find that among cities which enter the system, larger cities are more likely to locate near other cities. Moreover, older cities are more likely to have neighbors. Distance from the nearest higher-tier city is not always a significant determinant of size and growth. We find no evidence of persistent non-linear effects on urban growth of either size or distance, although distance is important for city size for some years.

Residential mobility and housing tenure choice

Abstract This paper treats housing tenure choice and residential moves as joint decisions. The parameters of a semi-Markov model with two states, renting and owning and continuous time, length of stay, are estimated with data from the U.S. Panel Study of Income Dynamics for 1970–1980. Several distributional assumptions for residence spells confirm the basic role played by housing prices, wealth and other characteristics. Higher wealth implies higher likelihood of owning higher mobility for renters and lower for owners. Households with educated hands are more mobile. Housing modal prices may have statistically very significant coefficients, but not always as anticipated.

Neighborhood Effects: Accomplishments and Looking Beyond Them

The paper addresses the empirical significance of the social context in economic decisions. Decisions of individuals who share spatial and social milieus are likely to be interdependent, and econometric identification of social effects poses intricate data and methodological problems, including dealing with self-selection in spatial and social groups. It uses a simple empirical framework to introduce social interactions effects at different levels of aggregation, and examines estimation problems in linear models, the impact of self-selection and of nonlinearities. It also examines neighborhood effects in job matching and proposes a research agenda that offers new techniques and data sources.

The Effect of Information and Communication Technologies on Urban Structure

Two innovations in the last century have changed dramatically the cost of communicating and transmitting information: The first is the widespread adoption of telephony; the second is the internet. We study the implications of these changes in ICT for urban structure. We find robust evidence that increases in the number of telephone lines per capita lead to a more concentrated distribution of city sizes and so correspondingly to more dispersion in the distribution of economic activity in space. The evidence on internet usage is more speculative, although it goes in the same direction. This empirical result is rationalized in a theoretical model.