Oleg A. Smirnov

Workings of the Melting Pot: Social Networks and the Evolution of Population Attributes

This paper links the two nascent economic literatures on social networks and cultural assimilation by investigating the evolution of population attributes in a simple model where agents are influenced by their acquaintances. The main conclusion of the analysis is that attributes converge to a melting-pot equilibrium, where everyone is identical, provided the social network exhibits a sufficient degree of interconnectedness. When the model is extended to allow an expanding acquaintance set, convergence is guaranteed provided a weaker interconnectedness condition is satisfied, and convergence is rapid. If the intensity of interactions with acquaintances becomes endogenous, convergence (when it occurs) is slowed when agents prefer to interact with people like themselves and hastened when interaction with dissimilar agents is preferred.

An O(N) parallel method of computing the Log-Jacobian of the variable transformation for models with spatial interaction on a lattice

A parallel method for computing the log of the Jacobian of variable transformations in models of spatial interactions on a lattice is developed. The method is shown to be easy to implement in parallel and distributed computing environments. The advantages of parallel computations are significant even in computer systems with low numbers of processing units, making it computationally efficient in a variety of settings. The non-iterative method is feasible for any sparse spatial weights matrix since the computations involved impose modest memory requirements for storing intermediate results. The method has a linear computational complexity for datasets with a finite Hausdorff dimension. It is shown that most geo-spatial data satisfy this requirement. Asymptotic properties of the method are illustrated using simulated data, and the method is deployed for obtaining maximum likelihood estimates for the spatial autoregressive model using data for the US economy.

Spatial Econometrics Approach to Integration of Behavioral Biases in Travel Demand Analysis

Random utility models customarily assume strict independence of individual decision makers. Evidence of crowding, peer pressure, herd behavior, and other instances of spontaneous discrete choice coordination indicates that decision makers interact and thus affect choices made by others. Socially influenced individual choices become biased toward either agreeing with or contradicting the choices made by peers. Because many social interdependencies are spatial, a basic spatial discrete choice model was obtained by extending random utility theory to discrete choices made by heterogeneous spatially dependent individuals. Although interdependencies are unobserved, the model permits the study of behavioral biases arising from spatial interdependencies. The spatial discrete choice model is shown to address the effects of behavioral biases on conditional choice probabilities, the marginal effects of exogenous variables on revealed preferences, and the spatial patterns of discrete choices. A pseudo maximum likelihood (PML) estimator for the model is developed, and closed-form expressions for conditional choice probability estimates are derived. The PML estimator is shown to be consistent and computationally feasible for large spatial data sets. Simulated data were used to illustrate the performance of the PML estimator for the spatial discrete choice model.

Transportation Infrastructure, Industrial Productivity, and Return on Investment: Spatial Spillover Approach

This study examined the North American Industrial Classification System–based manufacturing industry (NAICS 31-33) from 1997 to 2010 in a cost-based framework. First, both profit and production function models were constructed and estimated for the U.S. manufacturing industry at the state level to allow for spatial spillovers and interactions. A model based on profit and production provided an alternative approach to the dual-cost function. Elasticities associated with infrastructure investment and industry total costs were determined by the inclusion of data on transportation infrastructure spending. Results of the spatial econometric models and the computed elasticities were then delivered in a geographic information system.

How to Value an Urban Network

This article develops a simple model of an urban network by combining a graph-theoretic approach with basic micro-economic theory. Use value of the urban network is defined by total rents earned by economically independent rent-charging node-owners. In the equilibrium, the economic rent in the urban network is the dominant factor affecting the size and the core-periphery composition of the spatial economy. The marginal cost of transportation and production, and hence, location rents and producer profits, are weaker determinants of the spatial economy that are significant only in smaller economies and mostly vanish in larger ones.

Maximum Likelihood Estimator for Multivariate Binary Response Models

The paper considers a multivariate binary response model that allows for a range of response distribution functions and pairwise response dependencies. The maximum likelihood estimator (MLE) for the model is derived and its asymptotic distribution and convergence properties are established. First, the analytically tractable closed form of necessary binary response probabilities is obtained. Second, the asymptotic information matrix is derived. Third, it is shown that identification is possible under fairly modest model assumptions. Fourth, the MLE for this model is consistent, asymptotically normal, and achieves the Cramer-Rao lower bound; the estimator for this model has a semi-quadratic rate of convergence, which is standard for maximum likelihood estimators.