| Description |
1 online resource (xxiii, 308 pages) : illustrations |
| Series |
The Springer series on demographic methods and population analysis, 1389-6784 ; 24 |
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Springer series on demographic methods and population analysis ; 24.
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| Contents |
Note continued: 4.1.1. Judgmental Migration Scenarios -- 4.1.2. Delphi Method and Surveys Among Experts -- 4.1.3. 'Migration Potential' Assessment Surveys -- 4.1.4. Macro-Level Mathematical Models in Demography -- 4.1.5. Demo-Economic Modeling Attempts -- 4.2. Probabilistic Migration Forecasts: Assessing Uncertainty -- 4.2.1. Markovian and Related Models of Aggregate Population Flows -- 4.2.2. Micro-Level Methods: Event-History Analysis and Ethnosurvey -- 4.2.3. Selected Attempts to Bridge the Micro and Macro Perspectives -- 4.2.4. Econometric Forecasts of International Migration -- 4.2.5. Limitations of Econometric Models -- 4.2.6. Stochastic Forecasts of Migration Time Series -- 4.3. Bayesian Approach in Migration Studies and Demography -- 4.3.1. Bayesian Models and Forecasts of Population Flows -- 4.3.2. Bayesian Methods in Demography: A Concise Survey -- 4.4. From Migration Theories to Model-Based Forecasting -- 4.4.1. Migration Forecasting Methods and Models: State of the Art and Typology -- 4.4.2. Deterministic Character of Many Existing Predictions -- 4.4.3. Notes on Including Theory in Population and Migration Forecasts -- 4.4.4. Implications for the Current and Future Studies -- 5. Bayesian Model Selection and Forecast Averaging -- 5.1. Selection and Averaging Problems: Simple Stochastic Processes -- 5.1.1. Methodological Foundations of Bayesian Model Selection -- 5.1.2. Bayesian Forecast Averaging (Inference Pooling) -- 5.1.3. Empirical Application: Specification of Forecasting Models -- 5.1.4. Computations: The Carlin[--]Chib Algorithm -- 5.2. Simple Time Series Forecasts: Individual and Averaged -- 5.2.1. Estimation of the Models and Calculation of Their Posterior Probabilities -- 5.2.2. Predictions Based on the Formally-Selected and Averaged Stochastic Processes |
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Note continued: 5.2.3. Interpretation of Forecasts and the Comparison of Ex-Post Errors for 2005-2007 -- 6. Bayesian VAR Modeling 'from General to Specific' -- 6.1. VAR Processes and Lindley's Tests for Restrictions -- 6.1.1. Selection of Predictors in Econometric Models: Rationale for the VAR Modeling -- 6.1.2. VAR Models and the 'from General to Specific' Approach -- 6.1.3. Inference on the Impact of Additional Variables on Migration -- 6.2. Example: Migration Forecasts from General and Reduced VARs -- 6.2.1. Applying the Reduction Approach: Model Specification, Estimation, and Testing -- 6.2.2. Results of Forecasts from the General VAR and Marginal AR Models -- 6.2.3. 'From General to Specific' Modeling: Discussion of the Outcomes -- 7. Selected Approaches to Discontinuities in Trends -- 7.1. From Deterministic Analogies to Stochastic Volatility -- 7.1.1. Simplest Options: Dummy Variables and Forecasting by Analogy -- 7.1.2. Models with Changing Conditional Variance ARCH, GARCH, Stochastic Volatility -- 7.2. Example: Forecasts from Models with Discontinuities -- 7.2.1. Application to Polish-German Flows: Models with Analogy to Iberian Migration -- 7.2.2. Models with Changing Conditional Variance: Model Selection for AR(1) Extensions -- 7.2.3. Predictions Prepared with Models Acknowledging Discontinuity in Trends -- 8. Evaluation of Presented Forecasts of European Migration -- 8.1. Robustness of Forecasts Against Certain Changes In Priors -- 8.1.1. Role of Sensitivity Analysis in the Bayesian Approach: Basic Remarks -- 8.1.2. Robustness of Forecasts Yielded by Selected Models -- 8.1.3. Discussion and Tentative Conclusions -- 8.2. Comparison of Selected Bayesian and Frequentist Forecasts -- 8.2.1. General Remarks on Ex-Ante and Ex-Post Prediction Errors -- 8.2.2. Likelihood-Based Estimation and Model Selection Framework |
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Note continued: 8.2.3. Selected Bayesian and Frequentist Migration Forecasts for 2000-2007 -- 8.2.4. Comparison of Ex-Ante and Ex-Post Errors for Various Predictions -- 9. Bayesian Computing in Practice -- 9.1. Short Survey of Available Bayesian Software -- 9.1.1. R programming Language -- 9.1.2. Octave -- 9.1.3. BUGS -- 9.2. Bayesian Computation in WinBUGS -- 9.2.1. Model and Data Specification -- 9.2.2. Model Compilation, Initialisation and Updating -- 9.2.3. Convergence Diagnostics and Inference -- 9.3. Example of Bayesian Computation in R Language -- 9.3.1. Forecasting Migration Using R -- 9.3.2. Model of Immigration Flows -- 9.3.3. Sampling -- 9.3.4. Carlin[-]Chib Model Selection Procedure -- 9.4. Conclusions -- 10. Extensions and Limitations of Migration Forecasts -- 10.1. Data, Theories and Judgment: Towards a Synthesis? -- 10.1.1. Theory in an Atheoretical Setting: Prior Distributions in Multivariate Models -- 10.1.2. Data Versus Judgment: Elicitation of Expert Knowledge -- 10.2. Controlling Plausibility of Outcomes in Demographic Models -- 10.2.1. Combining Deterministic Population Models with Stochastic Forecasts -- 10.2.2. Bayesian Melding Approach: Outline and Discussion -- 10.3. Imperfect Knowledge Forecasting of Migration and Population -- 10.3.1. Micro-level Foundations in Macro-level Forecasting -- 10.3.2. Imperfect Knowledge Paradigm: Quantitative Versus Qualitative Predictions -- 10.4. Implications for Forecast-Makers and Future Research Agenda -- 10.4.1. Limitations of Predictability and Plausible Horizon of Non-stationary Forecasts -- 10.4.2. Forecasting Migration and Population: Proposal for a Research Agenda -- 11. Dealing with Uncertain Forecasts: A Policy Perspective -- 11.1. Preliminaries of the Decision Analysis: A Bayesian Perspective |
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Note continued: 11.1.1. Background: Selected Insights into Decisions and Attitudes Towards Uncertainty -- 11.1.2. Estimation and Prediction in the Bayesian Decision Framework -- 11.1.3. Bayesian Decision Analysis: Some Stylised Examples -- 11.1.4. Possible Extensions of the Decision Framework -- 11.2. Limitations of Uses of Migration and Population Predictions -- 11.2.1. Alternatives to the Use of Optimal Forecasts -- 11.2.2. Which Questions Can the Forecasts Answer? -- 11.2.3. Towards Interactive Demographic Forecasting? -- 12. Summary and Conclusion: Beyond Migration Forecasting -- 12.1. Summary of the Key Findings -- 12.1.1. Bayesian Model Selection and Forecast Averaging -- 12.1.2. Vector Autoregression Models and Their Reduction -- 12.1.3. Models Acknowledging Discontinuity in Trends -- 12.1.4. Sensitivity of the Results to Changes in Priors -- 12.1.5. Ex-ante and Ex-post Comparison of Forecasts: Implications for Users -- 12.1.6. General Conclusions -- 12.2. Bayesian Forecasts in the Population Forecasting Debates -- 12.2.1. Bayesian Methods in Perspective: Uncertainty, Judgment and Occam's Razor -- 12.2.2. Migration Forecasting as a Continuous Process -- 12.2.3. From Point Predictions to Decision Support: In Need of a Paradigm Shift? -- 12.3. Possible Future of Migration and Its Forecasts -- Migration Flows -- Population Stocks -- Economic Variables |
| Summary |
International migration is becoming an increasingly important element of contemporary demographic dynamics and yet, due to its high volatility, it remains the most unpredictable element of population change. In Europe, population forecasting is especially difficult because good-quality data on migration are lacking. There is a clear need for reliable methods of predicting migration since population forecasts are indispensable for rational decision making in many areas, including labour markets, social security or spatial planning and organisation. In addressing these issues, this book adopts a |
| Bibliography |
Includes bibliographical references and indexes |
| Notes |
Print version record |
| Subject |
Bayesian statistical decision theory.
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SOCIAL SCIENCE -- Emigration & Immigration.
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Sciences sociales.
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Droit.
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Sciences humaines.
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Bayesian statistical decision theory
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Emigration and immigration
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Emigration and immigration -- Forecasting
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| SUBJECT |
Europe -- Emigration and immigration -- Forecasting
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Europe -- Emigration and immigration -- Statistics
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| Subject |
Europe
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| Genre/Form |
Statistics
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Statistics.
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Statistiques.
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| Form |
Electronic book
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| ISBN |
9789048188970 |
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9048188970 |
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9048188962 |
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9789048188963 |
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