Stochastic Models of Residential and Geographic Mobility for Heterogeneous Populations

Methods of incorporating population heterogeneity into probability models of intermetropolitan and intrametropolitan mobility are discussed. Two models are described in detail. One allows for heterogeneous transition matrices; methods of estimating the distribution of transition matrices in the population are given. The other focuses on the propensity to move, and allows individuals to change on relevant characteristics over time, thus significantly extending previous models relating various background factors to mobility.

[1]  Klaus Krickeberg,et al.  Markov learning models for multiperson interactions , 1962 .

[2]  Stephen E. Fienberg,et al.  The Analysis of Multidimensional Contingency Tables , 1970 .

[3]  Leo A. Goodman,et al.  A Modified Multiple Regression Approach to the Analysis of Dichotomous Variables , 1972 .

[4]  Richard F. Serfozo,et al.  Processes with conditional stationary independent increments , 1972, Journal of Applied Probability.

[5]  Y. Bishop Effects of collapsing multidimensional contingency tables. , 1971, Biometrics.

[6]  Carmelo Mammana Sul problema algebrico dei momenti , 1954 .

[7]  Ralph B. Ginsberg,et al.  Incorporating causal structure and exogenous information with probabilistic models: With special reference to choice, gravity, migration, and Markov chains , 1972 .

[8]  T. W. Anderson,et al.  Statistical Inference about Markov Chains , 1957 .

[9]  Leo A. Goodman,et al.  A General Model for the Analysis of Surveys , 1972, American Journal of Sociology.

[10]  S. Spilerman,et al.  Extensions of the Mover-Stayer Model , 1972, American Journal of Sociology.

[11]  Ralph B. Ginsberg,et al.  Critique of probabilistic models: Application of the Semi‐Markov model to migration , 1972 .

[12]  D. Freedman Mixtures of Markov Processes , 1962 .

[13]  Gareth Horsnell,et al.  Stochastic Models of Buying Behavior , 1971 .

[14]  Feller William,et al.  An Introduction To Probability Theory And Its Applications , 1950 .

[15]  Prem S. Puri,et al.  A method for studying the integral functionals of stochastic processes with applications: I. Markov chain case , 1971, Journal of Applied Probability.

[16]  An Estimate of the Compounding Distribution of a Compound Poisson Distribution , 1963 .

[17]  S. Spilerman,et al.  The Analysis of Mobility Processes by the Introduction of Independent Variables into a Markov Chain , 1972 .

[18]  Frederick Mosteller,et al.  Association and Estimation in Contingency Tables , 1968 .

[19]  R. Ginsberg The effect of lactation on the length of the post partum anovulatory period: an application of a bivariate stochastic model. , 1973, Theoretical population biology.

[20]  F. F. Stephan,et al.  The Industrial Mobility of Labor as a Probability Process , 1957 .

[21]  Neil Henry The Retention Model: A Markov Chain with Variable Transition Probabilities , 1971 .

[22]  Y. Bishop,et al.  Full Contingency Tables, Logits, and Split Contingency Tables , 1969 .

[23]  R. Serfozo Conditional Poisson processes , 1972 .

[24]  M. Neuts A QUEUE SUBJECT TO EXTRANEOUS PHASE CHANGES , 1971 .

[25]  M. Neuts,et al.  The Integral of a Step Function Defined on a Semi-Markov Process , 1967 .

[26]  Ralph B. Ginsberg,et al.  Semi‐Markov processes and mobility† , 1971 .

[27]  D. D. McFarland Intragenerational Social Mobility as a Markov Process: Including a Time- Stationary Mark-Ovian Model that Explains Observed Declines in Mobility Rates Over Time , 1970 .

[28]  E. Çinlar Markov renewal theory , 1969, Advances in Applied Probability.

[29]  H. Theil On the Estimation of Relationships Involving Qualitative Variables , 1970, American Journal of Sociology.