Land / Rogers Multidimensional Mathematical Demography

Proceedings of the Conference on Multidimensional Mathematical Demography Held at the University of Maryland, College Park, Maryland, March 23-25, 1981, Sponsored by the National Science Foundation
1. Auflage 2013
ISBN: 978-1-4832-6984-9
Verlag: Elsevier Science & Techn.
Format: PDF
Kopierschutz: 1 - PDF Watermark

E-Book, Englisch, 620 Seiten, Web PDF

Multidimensional Mathematical Demography is a collection of papers dealing with the problems of inaccurate or unavailable demographic data, transformation of data into probabilities, multidimensional population dynamic models, and the problems of heterogeneity. The papers suggest a unified perspective with emphasis on data structure to work out multidimensional analysis with incomplete data. To solve inaccuracies in data, one paper notes that designs and use of model multistate schedules, for example, methods of inferring data, should be a major part in multistate modeling. Other papers discuss the state-of-the-art in abridged increment-decrement life table methodology. They also describe the estimation of transition probabilities in increment-decrement life tables where mobility data available is from the count of movers from a population survey. One paper reviews the possible extension of a multiregional stochastic theorem associated in a single-regional case; and then analyzes what the stochastic model needs when it is used with real data. Another paper explains strategies concerning population heterogeneity when it pertains to the mixtures of Markov and semi-Markov processes; Markov processes subject to measurement error; and the Heckman and Borjas model. This collection can be read profitably by statisticians, mathematicians, mathematical demographers, mathematical sociologists, economists, professionals in census bureaus, and students of sociology or geography.

Autoren/Hrsg.

Land, Kenneth C

Rogers, Andrei

Inhaltsverzeichnis

1;Front Cover;1
2;Multidimensional Mathematical Demography;4
3;Copyright Page;5
4;Table of Contents;6
5;Contributors;10
6;Preface;12
7;Acknowledgments;14
8;Chapter 1. Multidimensional Mathematical Demography: An Overview;16
8.1;1. Introduction;16
8.2;2. Recent Developments in Multistate Demographic Models;23
8.3;3. The Conference on Multidimensional Mathematical Demography;30
8.4;4. Organization of the Volume;32
8.5;5. Conclusions and Next Steps;45
9;Chapter 2. Multidimensional Population Analysis with Incomplete Data;58
9.1;1. Introduction;58
9.2;2. Data Requirements and Data Availability;63
9.3;3. Modeling the Data in the Account;71
9.4;4. Parameter Estimation from Available Data;79
9.5;5. Numerical Applications;102
9.6;6. Conclusion;118
10;Chapter 3. Model Schedules in Multistate Demographic Analysis: The Case of Migration;128
10.1;1. Synthetic Model Migration Schedules: I. The Correlational Perspective;130
10.2;2. Synthetic Model Migration Schedules: II. The Relational Perspective;144
10.3;3. Concluding Remarks;165
10.4;Chapter 4. Multistate Life Table Methodology: A Probabilist Critique;170
10.4.1;1. Introduction;170
10.4.2;2. The Markov Chain Model;187
10.4.3;3. Integration Hypotheses;209
10.4.4;4. Occurrence/Exposure Rates;217
10.4.5;5. Other Observational Plans;234
10.4.6;6. Sampling and Heterogeneity;251
11;Chapter 5. Statistical Methods for Markov-Generated Increment–Decrement Life Tables with Polynomial Gross Flow Functions;280
11.1;1. Introduction;280
11.2;2. Model Specification;291
11.3;3. Age-Specific Methods for Occurrence/Exposure Rates;305
11.4;4. Marital Dissolution and Remarriage in Sweden: Application and Comparison of Methods;338
11.5;5. Application of the Methods to Survivorship Proportions;346
11.6;6. Concluding Comments;352
12;Chapter 6. Transition Probability Estimation in Increment- Decrement Life Tables: Using Mobility Data from a Census or a Survey;362
12.1;1. Introduction;362
12.2;2. Approach A: Estimation from Mobility Rates;364
12.3;3. Approach B: Estimation from Transition Proportions;379
12.4;4. A Brief Comparison of the Two Alternative Approaches;392
12.5;5. Conclusion;396
13;Chapter 7. Generalizing the Life Table Model to Incorporate Interactions between the Sexes;400
13.1;1. Introduction;400
13.2;2. Life Table Models;402
13.3;3. A TWOFIDS Model for the United States/California 1970;435
13.4;4. Conclusion;449
13.5;Appendix: The TWONUP First Marriage Matrix;452
13.6;Appendix: Input Data for the TWOFIDS Model;452
14;Chapter 8. Multiregional Population Projections by Place of Previous Residence;460
14.1;1. Introduction;460
14.2;2. Stationary and Stable Population Distributions;461
14.3;3. Multiregional Population Projections by Place of Birth;465
14.4;4. Multiregional Population Projections by Place of Previous Residence;472
14.5;5. Native-Dependent Multiregional Population Projections;476
14.6;6. Conclusion;483
14.7;Appendix A: Native-Independent Multistate Projection: Biregional Model;485
14.8;Appendix B: Separation Factors;488
15;Chapter 9. Multiregional Age-Structured Populations with Changing Rates: Weak and Stochastic Ergodic Theorems;492
15.1;1. Introduction;492
15.2;2. The Formalism of Multiregional Population Models;493
15.3;3. Weak Ergodic Theorems for Multiregional Populations Models;495
15.4;4. Stochastic Ergodic Theorems;507
15.5;5. Relative Rates of Convergence;512
15.6;6. Extensions and Applications;514
16;Chapter 10. High and Low-Intensity Model of Mobility;520
16.1;1. Introduction;520
16.2;2. The High- and Low-Intensity Model of Mobility;524
16.3;3. Solution of the Model;528
16.4;4. Verification of the Model;530
16.5;5. Implementation of the Model;539
16.6;6. A Possible Extension;543
16.7;Appendix;546
17;Chapter 11. Increment-Decrement Life Tables and Semi-Markovian Processes from a Sample Path Perspective;550
17.1;1. Introduction;552
17.2;2. Defining Basic Probabilities on Sample Paths;554
17.3;3. Semi-Markovian Processes;558
17.4;4. Parametric Forms of One-Step Transition Matrices, Competing Risks, and Likelihood Functions;561
17.5;5. One-Step Transition Matrices and Multiple Decrement Life Tables;566
17.6;6. The Kolmogorov Differential Equations;569
17.7;7. Integral Equations for Age-Dependent Semi-Markov Processes;572
17.8;8. Numerical Algorithms for Solving Renewal-Type Equations;574
18;Chapter 12. Population Heterogeneity in Demographic Models;582
18.1;1. Introduction;582
18.2;2. Duration Models and Unobservables;586
18.3;3. Sensitivity of Parameter Estimates;591
18.4;4. Qualitative Properties of Mixtures;593
18.5;5. Estimation in Mixture Models;599
18.6;6. Performance of the EM Algorithm and Revised Estimates for the Kiefer-Neumann Data;602
18.7;7. Discussion and Conclusions;607
19;Index;616
20;Participants;620