Statistical modelling of international migration flows

The paper deals with uncertainty in estimating international migration flows for an interlinked system of countries. The related problems are discussed on the example of a dedicated model 'IMEM' (Integrated Model of European Migration). The IMEM is a hierarchical Bayesian model, which allows for combining data from different countries with meta-data on definitions and collection methods, as well as with relevant expert information. The model is applied to 31 EU and EFTA countries for the period 2002–2008. The expert opinion comes from a two-round Delphi survey carried out amongst 11 European experts on issues related to migration statistics. The adopted Bayesian approach allows for a coherent quantification of uncertainty stemming from different sources (data discrepancies, model parameters, and expert judgement). The outcomes produced by the model – whole posterior distributions of estimated flows – can be then used for assessing the true magnitude of flows at the European level, taking into account relative costs of overestimating or underestimating of migration flows. In this context, problems related to application of the decision statistical analysis to multidimensional problems are briefly discusse

Improving estimates of migration flows to Eurostat

In this paper we identify the current mandatory requirements and issues concerning the supply of detailed migration data to Eurostat. Using simple illustrations on immigration to the United Kingdom, we show how substantial and significant improvements can be made to the flows reported by the International Passenger Survey, which contain irregularities and missing data due to its relatively small sample size. Our general methodology is based on the idea of smoothing, repairing and combining data within multiplicative component framework

Forecasting environmental migration to the United Kingdom, 2010 - 2060: an exploration using Bayesian models

Over the next fifty years the potential impact on human livelihoods of environmental change could be considerable. One possible response may be increased levels of human mobility. This paper offers a first quantification of the levels of environmental migration to the United Kingdom that might be expected. The authors apply Bijak and Wi?niowski’s (2010) methodology for forecasting migration using Bayesian models. They seek to advance the conceptual understanding of forecasting in three ways. First, the paper is believed to be the first time that the Bayesian modelling approach has been attempted in relation to environmental mobility. Second, the paper examines the plausibility of Bayesian modelling of UK immigration by cross-checking expert responses to a Delphi survey with the expectations about environmental mobility evident in the recent research literature. Third, the values and assumptions of the expert evidence provided in the Delphi survey are interrogated to illustrate the limited set of conditions under which the forecasts of environmental mobility, as set out in this paper, are likely to hold

Augmenting migration statistics with expert knowledge

International migration statistics vary considerably from one country to another in terms of measurement, quality and coverage. Furthermore, immigration tend to be captured more accurately than emigration. In this paper, we first describe the need to augment reported flows of international migration with knowledge gained from experts on the measurement of migration statistics, obtained from a multi-stage Delphi survey. Second, we present our methodology for translating this information into prior distributions for input into the Integrated Modelling of European Migration (IMEM) model, which is designed to estimate migration flows amongst countries in the European Union (EU) and European Free Trade Association (EFTA), by using recent data collected by Eurostat and other national and international institutions. The IMEM model is capable of providing a synthetic data base with measures of uncertainty for international migration flows and other model parameters.

Utilising expert opinion to improve the measurement of international migration in Europe

In this article, we first discuss the need to augment reported flows of international migration in Europe with additional knowledge gained from experts on measurement, quality and coverage. Second, we present our method for eliciting this information. Third, we describe how this information is converted into prior distributions for subsequent use in a Bayesian model for estimating migration flows amongst countries in the European Union (EU) and European Free Trade Association (EFTA). The article concludes with an assessment of the importance of expert information and a discussion of lessons learned from the elicitation process.<br/

Integrated Modelling of European Migration Database Case Study

The Integrated Modelling of European Migration (IMEM) Database is an on-line tool for presenting the estimated international migration flows amongst countries in the European Union (EU) and European Free Trade Association (EFTA), as well as to and from the rest of the world, in the period 2002 to 2008. It allows extraction of various information and characteristics of the estimated flows, such as country of origin, country of destination, age and sex of migrants. The database can be used by academics, official statisticians or policymakers, who would like to obtain information about the recent migration dynamics in Europe

Towards Reliable Migration Statistics for the United Kingdom: Response to the House of Commons Public Administration Select Committee Call for Evidence on Migration Statistics

Executive Summary• This document discusses main sources of migration and asylum statistics in the United Kingdom in the international context, and makes recommendations considering the needs of data users.• In order to estimate detailed breakdowns of immigration flows, administrative data sources and statistical modelling should be used to augment the International Passenger Survey estimates.• To provide better estimates of emigration and immigration in the longer term, alternative sources of data, such as the e-Borders scheme, should be additionally included in the estimation.• Recording the timing of events during the asylum process would enable detailed policy evaluation and allow asylum seekers to be correctly incorporated into international migration estimates.• Meeting the requirements of the European law can be improved by combining migration data from other countries, alternative data sources and expert opinion, within a statistical framework.•Measures of uncertainty in migration statistics should be reported to the users of data, possibly in conjunction with a bespoke decision advice

Bayesian analysis of growth using stochastic frontier model

We employ Bayesian approach to the analysis of economic growth in Poland. The results of estimation of a stochastic frontier model applied to production function of Polish voivodships in 2000 - 2004 are presented. Stochastic frontier approach allows to decompose growth into technological change, input change and efficiency change. In order to compute the posterior characteristics of the growth components we employ the Gibbs MCMC sampler.Bayesian analysis, Gibbs sampler, economic growth, stochastic frontier analysis