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Title page 1

Contents 6

Foreword 4

Executive summary 9

1. Introduction 11

For whom is this handbook? 12

Forecasting for migration flows by categories versus (net) migration as a whole? 13

References 14

2. Current state of play 15

Where do OECD countries stand on migration forecasting? 15

Notes 16

3. What is the question to which forecasting is expected to respond? 17

What is the purpose of migration forecasting, and what are the associated challenges? What are policymakers looking for through forecasting? 17

References 20

4. Forecasters' toolkit: Choosing the right model for the task 21

What are the existing forecasting methods and models? 21

What is the appropriate forecasting model for each migration category? 25

What resources do countries need to run forecasting? 30

How complex should the model be? 32

How often should model results be updated? 33

References 34

5. What data are necessary to conduct the forecasting exercise? 38

How to assess the existing sources of data? 38

Where to find and how to incorporate qualitative data? 42

How to quantify policy indicators for statistical models? 45

Which software is the best fits for forecasting, causal effect estimation and projection? 48

References 50

Notes 53

6. How should the forecasting model be developed? 54

Is it still accurate to use traditional statistical and econometric time series analysis? 54

What are Bayesian Models, their principles, and key features? 56

How to include contextual knowledge in forecasting: Expert opinion and Delphi surveys 57

How to run a Delphi survey and how to include expert replies in the model? 58

How to develop machine learning models? 61

How to incorporate migration drivers into the machine learning models? 62

How to model causal influence in migration forecasting? 63

References 65

7. How can the model be evaluated? 68

How to validate model performance? 68

How to calibrate the model? 70

How to assess robustness? 72

How to back-test ML/Stat models? 73

How can expert knowledge and scenarios be back-tested? 73

References 75

8. How should forecasts be presented to policymakers and ensure effective interaction between policymaking and forecasting? 77

How to present forecasts and their inherent uncertainty to policymakers 77

How to use the forecast properly and effectively 83

References 85

Notes 86

9. What future developments can be expected in migration forecasting? 87

How to measure the potential effect of policies in countries of destination? 87

Is conformal prediction the final frontier in time series forecasting? 88

How can forecasting results in one migration category affect forecasting in other categories? 89

How can forecasts in one country affect forecasts in other countries (i.e. interaction across countries)? 90

References 91

Annex A. List of Migration Anticipation and Preparedness (MAP) task force members 93

Glossary 94

Tables 7

Table 2.1. Overview of the current forecasting practices in OECD countries 16

Table 3.1. National institutions in OECD countries currently engaged in forecasting activities 18

Table 4.1. Stylised characteristics of seven main types of migration flows, typical data, and recommendations for selecting possible forecasting methods 28

Table 4.2. What models are currently used in OECD countries? 29

Table 5.1. What data sources are currently used in OECD countries and by international organisations and agencies to forecast migration flows? 40

Figures 7

Figure 4.1. Decision tree to identify the best migration forecasting models according to national practitioners' needs and resources 26

Figure 5.1. Decision tree to identify the best data according to migration forecasting models 38

Figure 6.1. A hypothetical DAG illustrating a sequence of causal relationships 64

Figure 8.1. Forecasts of total immigration to the United Kingdom, averaged univariate models (in thousands) 1975-2060 78

Figure 8.2. Immigration of EU Citizens to the United Kingdom with different probability intervals, 1975-2013 79

Figure 8.3. Probability Density Function for Prognosis - Forecasted first asylum applications 2024 in the Netherlands 80

Figure 8.4. Cumulative probability for the Dutch number of first asylum applications in 2024 81

Boxes 18

Box 3.1. Classifying potential countries for future student migration 18

Box 4.1. Expert-based asylum forecasts: The example of Switzerland 21

Box 4.2. Probabilistic projections of future trends in international migration in World Population Prospects 2024 24

Box 4.3. Nowcasting: Short-time horizon forecasts and early warning systems 26

Box 4.4. Staffing Situation for Migration Forecasting in MAP Task Force countries 31

Box 5.1. Examples of digital sources collecting qualitative data 43

Box 6.1. The use of traditional statistical analysis as a relevant forecasting tool: The example of time series analysis for family migration and... 55

Box 6.2. Examples of Delphi questionnaires towards migration experts 59

Box 6.3. Machine learning approach to forecast outflows of international students from OECD countries 62

Box 6.4. Directed Acyclic Graph 64

Box 7.1. An open-source toolkit to validate forecasting models: The SEAVEA project 69

Box 7.2. How the United States evaluates forecasted numbers 74

Box 8.1. How the Netherlands presents its forecasts to policymakers 80

Box 8.2. Labour migration projections in Asian OECD countries 83

Box 8.3. A Practical Rule from Decision Theory 84

Box 9.1. Other approaches to causal inference 88

출판사 책소개

알라딘제공
Governments face increasing pressure to respond swiftly and effectively to rapidly evolving international migration flows - whether forced or planned. Anticipation is key to this response, but remains a challenge, and some important categories of migration are still not the object of forecast. This practical guide offers concrete measures to introduce, run and strengthen migration forecasting systems and preparedness strategies. Drawing on country practices, research and the lessons of the OECD's multi-country Migration Anticipation and Preparedness (MAP) Task Force, it addresses the following questions: for what should forecasting tools be used, why migration needs to be forecast by category rather than only in aggregate, how to select models and data that fit specific purposes, how to credibly evaluate performance, and how to communicate results to policymakers so that forecasts can be used effectively and appropriately.

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