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Educational Research - the Ethics and Aesthetics of Statistics

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7 To Frame <strong>the</strong> Unframable: Quantifying Irregular Migrants’ Presence 99<br />

related to estimating irregular migrants has not prevented policy makers from focusing<br />

on this area. Paying lip service to unreliable figures is having far-reaching<br />

consequences. Before approaching this issue, I will consider, what is said in <strong>the</strong>se<br />

reports <strong>and</strong> <strong>the</strong> conclusions that have been drawn from <strong>the</strong> findings.<br />

7.2 Techniques for Estimating Irregular Migration Numbers<br />

A lot <strong>of</strong> creativity is put into action to estimate numbers <strong>of</strong> irregular migrants. The<br />

list <strong>of</strong> different techniques that can be used is long <strong>and</strong> varied. Without going too<br />

deeply into <strong>the</strong> particularities <strong>of</strong> different techniques <strong>and</strong> <strong>the</strong> problems each presents<br />

us with, an overview <strong>of</strong> methods is outlined here. Then attention is given to some<br />

examples <strong>of</strong> <strong>the</strong> most widespread methods <strong>and</strong> how <strong>the</strong>y are applied.<br />

In general, <strong>the</strong>re is a consensus on <strong>the</strong> classification <strong>of</strong> various techniques. Recent<br />

reports <strong>of</strong> <strong>the</strong> Cl<strong>and</strong>estino Project (Kraler & Vogel, 2008; Vogel & Kovacheva,<br />

2008; Picum, 2009) <strong>and</strong> <strong>the</strong> Home Office (Woodbridge, 2005; Pinkerton et al.,<br />

2004) all start from <strong>the</strong> distinction between ‘stocks’ <strong>and</strong> ‘flows’, in <strong>the</strong> line <strong>of</strong> earlier<br />

research (among o<strong>the</strong>rs Delauney & Tapinos, 1998; Pinkerton, McLaughlan,<br />

& Salt, 2004; J<strong>and</strong>l, 2004). This fundamental distinction is made in analogy with<br />

data on legal migration <strong>and</strong> refers to different statistical concepts: stocks (e.g. <strong>of</strong><br />

irregular residents or migrant workers) refer to a number <strong>of</strong> people that are present<br />

in a country at a particular point in time, while flows (e.g. <strong>of</strong> illegal entrants or<br />

migrants ‘overstaying’) refer to movements during a certain period. Flow estimates<br />

thus refer to <strong>the</strong> number <strong>of</strong> migrants crossing <strong>the</strong> border during a period<br />

in time. Estimations are mainly based on border apprehension data or entry-exit<br />

statistics. Given <strong>the</strong> volatile nature <strong>of</strong> migration flows, <strong>the</strong> scarcity <strong>of</strong> reliable indicators<br />

<strong>and</strong> <strong>the</strong> dearth <strong>of</strong> appropriate methods for estimating flows, most efforts have<br />

so far concentrated on estimating stocks ra<strong>the</strong>r than flows. Methods for estimating<br />

stocks <strong>of</strong> irregular migrants can be divided into direct <strong>and</strong> indirect approaches.<br />

Direct measurement is based on data that ‘captures’ <strong>the</strong> subject <strong>of</strong> research directly.<br />

Numbers <strong>of</strong> irregular migrants taken from administrative statistics based on refusals,<br />

infractions or regularisations are multiplied to estimate <strong>the</strong> total number in <strong>the</strong> population.<br />

Indirect estimates do not rely on such data. They mainly start from general<br />

data on <strong>the</strong> population to estimate irregular migrant numbers (e.g. by expecting<br />

similar proportions <strong>of</strong> irregular migrants or calculating residues in <strong>of</strong>ficial registers).<br />

Direct estimation approaches can be fur<strong>the</strong>r classified into multiplier methods<br />

(among which simple multiplier models, capture-recapture models <strong>and</strong> models<br />

using a comparison <strong>of</strong> administrative registers <strong>and</strong> r<strong>and</strong>om effect mixed modelling),<br />

methods <strong>of</strong> self-identification <strong>and</strong> snowball sampling methods. Among <strong>the</strong> indirect<br />

approaches, residual methods, demographic methods, subjective estimations<br />

or indicator methods, econometric methods on <strong>the</strong> size <strong>and</strong> structure <strong>of</strong> shadow<br />

economies, comparisons <strong>of</strong> immigration <strong>and</strong> emigration statistics, flow-stock methods<br />

<strong>and</strong> methods based on indirect inferences can be distinguished. It is not <strong>the</strong> aim<br />

here to provide an extensive discussion <strong>of</strong> all <strong>the</strong> methods mentioned above (for

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