• Corpus ID: 15073206

Spatial Interaction of Crime Incidents in Japan 1 1

@inproceedings{Kakamu2005SpatialIO,
  title={Spatial Interaction of Crime Incidents in Japan 1 1},
  author={Kazuhiko Kakamu and Wolfgang Polasek and Hajime Wago},
  year={2005}
}
Since the seminal work of Becker (1968), a large empirical literature has developed around the estimation and testing of economic models of crime. Recently, spatial interactions of crime incidents have become one of the research areas in economics in connection with the progress of spatial econometrics. But these models of crime based on aggregated data relied heavily on cross-sectional econometric techniques, and therefore previous attempts do not control for unobserved heterogeneity. 

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SHOWING 1-10 OF 13 REFERENCES
Estimating the Economic Model of Crime with Panel Data
Previous attempts at estimating the economic model of crime with aggregate data relied heavily on cross-section econometric techniques and, therefore, do not control for unobserved heterogeneity.
Specification and Estimation of Spatial Panel Data Models
This article provides a survey of the specification and estimation of spatial panel data models. These models include spatial error autocorrelation, or the specification is extended with a spatially
Spatial Econometrics: Methods and Models
1: Introduction.- 2: The Scope of Spatial Econometrics.- 3: The Formal Expression of Spatial Effects.- 4: A Typology of Spatial Econometric Models.- 5: Spatial Stochastic Processes: Terminology and
Bayesian Estimation of Spatial Autoregressive Models
Spatial econometrics has relied extensively on spatial autoregressive models. Anselin (1988) developed a taxonomy of these models using a regression model framework and maximum likelihood estimation
Posterior distribution of hierarchical models using CAR(1) distributions
SUMMARY We examine properties of the conditional autoregressive model, or CAR( 1) model, which is commonly used to represent regional effects in Bayesian analyses of mortality rates. We consider a
Bayesian Treatment of the Independent Student- t Linear Model
This article takes up methods for Bayesian inference in a linear model in which the disturbances are independent and have identical Student-t distributions. It exploits the equivalence of the
Evaluating the accuracy of sampling-based approaches to the calculation of posterior moments
TLDR
Methods for spectral analysis are used to evaluate numerical accuracy formally and construct diagnostics for convergence in the normal linear model with informative priors, and in the Tobit-censored regression model.
Sampling-Based Approaches to Calculating Marginal Densities
Abstract Stochastic substitution, the Gibbs sampler, and the sampling-importance-resampling algorithm can be viewed as three alternative sampling- (or Monte Carlo-) based approaches to the
Weak convergence and optimal scaling of random walk Metropolis algorithms
This paper considers the problem of scaling the proposal distribution of a multidimensional random walk Metropolis algorithm in order to maximize the efficiency of the algorithm. The main result is a
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