Social Interaction and Urban Sprawl

Various authors, most notably Putnam (2000), have argued that low-density living reduces social capital and thus social interaction, and this argument has been used to buttress criticisms of urban sprawl. If low densities in fact reduce social interaction, then an externality arises, validating Putnam’s critique. In choosing their own lot sizes, consumers would fail to consider the loss of interaction benefits for their neighbors when lot size is increased. Lot sizes would then be inefficiently large, and cities excessively spread out. The paper tests the premise of this argument (the existence of a positive link between interaction and density) using data from the Social Capital Benchmark Survey. In the empirical work, social interaction measures for individual survey respondents are regressed on census-tract density and a host of household characteristics, using an instrumental-variable approach to control for the potential endogeneity of density.

Social Interaction and Urban Sprawl

Various authors, most notably Putnam (2000), have argued that low-density living reduces social capital and thus social interaction, and this argument has been used to buttress criticisms of urban sprawl. If low densities in fact reduce social interaction, then an externality arises, validating Putnam's critique. The paper tests this premise using data from the Social Capital Benchmark Survey. In the empirical work, social interaction measures for individual survey respondents are regressed on census-tract density and a host of household characteristics, using an instrumental-variable approach to control for the potential endogeneity of density.Urban sprawl; Social capital

Social interaction and urban sprawl

Various authors, most notably Putnam [Putnam, R.D., 2000. Bowling Alone. Simon and Schuster, New York], have argued that low-density living reduces social capital and thus social interaction, and this argument has been used to buttress criticisms of urban sprawl. If low densities in fact reduce social interaction, then an externality arises, validating Putnam's critique. In choosing their own lot sizes, consumers would fail to consider the loss of interaction benefits for their neighbors when lot size is increased. Lot sizes would then be inefficiently large, and cities excessively spread out. The paper tests the premise of this argument (the existence of a positive link between interaction and density) using data from the Social Capital Benchmark Survey. In the empirical work, social interaction measures for individual survey respondents are regressed on census-tract density and a host of household characteristics, using an instrumental-variable approach to control for the potential endogeneity of density.

EM algorithms for ordered probit models with endogenous regressors

We propose an EM algorithm to estimate ordered probit models with endogenous regressors. The proposed algorithm has a number of computational advantages in comparison to direct numerical maximization of the (limited information) log-likelihood function. First, the sequence of conditional M(aximization)-steps can all be computed analytically. Second, the algorithm updates the model parameters so that positive definiteness of the covariance matrix and monotonicity of cutpoints are naturally satisfied. Third, the variance parameters normalized for identification can be activated to accelerate convergence of the algorithm. The algorithm can be applied to models with dummy endogenous, continuous endogenous or latent endogenous regressors. A small Monte Carlo simulation experiment examines the finite sample performance of the proposed algorithms. Copyright The Author(s). Journal compilation Royal Economic Society 2009