Coverart for item
The Resource Forecasting international migration in Europe : a Bayesian view, Jakub Bijak ; (with contribution by Arkadiusz Wiśniowski), (electronic resource)

Forecasting international migration in Europe : a Bayesian view, Jakub Bijak ; (with contribution by Arkadiusz Wiśniowski), (electronic resource)

Label
Forecasting international migration in Europe : a Bayesian view
Title
Forecasting international migration in Europe
Title remainder
a Bayesian view
Statement of responsibility
Jakub Bijak ; (with contribution by Arkadiusz Wiśniowski)
Creator
Subject
Genre
Language
eng
Member of
http://library.link/vocab/creatorName
Bijak, Jakub
Dewey number
304.8094
Illustrations
illustrations
Index
index present
Literary form
non fiction
Nature of contents
  • dictionaries
  • bibliography
  • statistics
Series statement
The Springer series on demographic methods and population analysis,
Series volume
24
http://library.link/vocab/subjectName
  • Bayesian statistical decision theory
  • Europe
  • Europe
Label
Forecasting international migration in Europe : a Bayesian view, Jakub Bijak ; (with contribution by Arkadiusz Wiśniowski), (electronic resource)
Instantiates
Publication
Bibliography note
Includes bibliographical references and indexes
Color
multicolored
Contents
  • 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.
  • Note continued:
  • 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.
  • 4.1.1.
  • 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.
  • Judgmental Migration Scenarios
  • 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.
  • 4.1.2.
  • 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.
  • Delphi Method and Surveys Among Experts
  • Predictions Based on the Formally-Selected and Averaged Stochastic Processes
  • 4.1.3.
  • 'Migration Potential' Assessment Surveys
  • 4.1.4.
  • 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.
  • Note continued:
  • 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.
  • 5.2.3.
  • 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.
  • Interpretation of Forecasts and the Comparison of Ex-Post Errors for 2005-2007
  • 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.
  • 6.
  • 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
  • Bayesian VAR Modeling 'from General to Specific'
  • 6.1.
  • VAR Processes and Lindley's Tests for Restrictions
  • 6.1.1.
  • 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.
  • Note continued:
  • 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.
  • 8.2.3.
  • 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.
  • Selected Bayesian and Frequentist Migration Forecasts for 2000-2007
  • 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.
  • 8.2.4.
  • 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.
  • Comparison of Ex-Ante and Ex-Post Errors for Various Predictions
  • 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
  • 9.
  • Bayesian Computing in Practice
  • 9.1.
  • 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.
  • Note continued:
  • 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.
  • 11.1.1.
  • 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.
  • Background: Selected Insights into Decisions and Attitudes Towards Uncertainty
  • 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
  • 11.1.2.
  • Estimation and Prediction in the Bayesian Decision Framework
  • 11.1.3.
  • Bayesian Decision Analysis: Some Stylised Examples
  • 11.1.4.
Control code
ocn682907391
Dimensions
unknown
Extent
1 online resource (xxiii, 308 p.)
Form of item
online
Isbn
9789048188970
Isbn Type
(electronic bk.)
Other physical details
ill
Specific material designation
remote
System control number
(OCoLC)682907391
Label
Forecasting international migration in Europe : a Bayesian view, Jakub Bijak ; (with contribution by Arkadiusz Wiśniowski), (electronic resource)
Publication
Bibliography note
Includes bibliographical references and indexes
Color
multicolored
Contents
  • 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.
  • Note continued:
  • 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.
  • 4.1.1.
  • 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.
  • Judgmental Migration Scenarios
  • 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.
  • 4.1.2.
  • 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.
  • Delphi Method and Surveys Among Experts
  • Predictions Based on the Formally-Selected and Averaged Stochastic Processes
  • 4.1.3.
  • 'Migration Potential' Assessment Surveys
  • 4.1.4.
  • 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.
  • Note continued:
  • 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.
  • 5.2.3.
  • 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.
  • Interpretation of Forecasts and the Comparison of Ex-Post Errors for 2005-2007
  • 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.
  • 6.
  • 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
  • Bayesian VAR Modeling 'from General to Specific'
  • 6.1.
  • VAR Processes and Lindley's Tests for Restrictions
  • 6.1.1.
  • 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.
  • Note continued:
  • 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.
  • 8.2.3.
  • 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.
  • Selected Bayesian and Frequentist Migration Forecasts for 2000-2007
  • 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.
  • 8.2.4.
  • 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.
  • Comparison of Ex-Ante and Ex-Post Errors for Various Predictions
  • 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
  • 9.
  • Bayesian Computing in Practice
  • 9.1.
  • 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.
  • Note continued:
  • 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.
  • 11.1.1.
  • 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.
  • Background: Selected Insights into Decisions and Attitudes Towards Uncertainty
  • 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
  • 11.1.2.
  • Estimation and Prediction in the Bayesian Decision Framework
  • 11.1.3.
  • Bayesian Decision Analysis: Some Stylised Examples
  • 11.1.4.
Control code
ocn682907391
Dimensions
unknown
Extent
1 online resource (xxiii, 308 p.)
Form of item
online
Isbn
9789048188970
Isbn Type
(electronic bk.)
Other physical details
ill
Specific material designation
remote
System control number
(OCoLC)682907391

Library Locations

    • InternetBorrow it
      Albany, Auckland, 0632, NZ
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