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8   Counting the homeless in Europe: ‘compare before harmonising’



99



- in the home of friends and relatives ;

- in registered squats.’

In order to assess the way in which this definition was perceived and to compare the

various concepts of the ‘homeless’ category, Insee carried out a questionnaire-based survey

among 150 individuals from 28 countries and a variety of professional backgrounds. From a

list of 30 situations, these individuals were asked to indicate which ones, in their view, came

under the definition of homelessness. In response to the first question, some stated that the

definition drawn up by the statistical office covered an excessively wide range of situations,

while others deplored the absence of numerous scenarios, such as households in very bad

housing, women who still have a home but are victims of domestic violence, tenants waiting

to be evicted or employees in tied accommodation and those about to leave prison or hospital

without any accommodation to go to. Yet others, finally, thought that the definition

overemphasised housing conditions, thereby reflecting the concerns of Western European

countries rather than of those in the East, where the increase in the number of rough sleepers

was the only real social question.

Respondents from the same professional backgrounds expressed fairly similar opinions

even when they were representing different countries. Statisticians from national statistical

institutes often had a narrow concept of the homeless category, which was close to that of the

public at large and of the images conveyed by the media. For statisticians, after all, the

homeless stretch their ability to count almost to its very limit, since they cannot, almost by

definition, be captured by traditional sample surveys, which are geared to households with a

known address, and may well not be registered with the authorities or known to social

services (Table 8.1).

Table 8.1: Average number of situations classified as homelessness by professional group



Type of institution



Situations

classified as

homelessness



Situations

considered

difficult to

classify



Situations NOT

classified as

homelessness



statisticians

in national statistics institutes



7.5



6.7



14.8



students, lecturers



8.6



6.7



13.5



government



11.9



6.3



10.7



university researchers



13.6



7.7



7.6



NGOs, charities



14.3



6.5



7.9



All



11.7



6.9



11.3



NGOs, researchers outside European

institutions



12.2



7.7



9.0



NGOs, researchers within European



17.8



5.9



5.1



100



C. Brousse



institutions

All



13.9



7.1



7.8



Source: consultation on the definitions of the term ‘homeless’, Eurostat, 2003.



Conversely, a majority made up of the NGOs and the academic researchers favoured a

broader definition, in particular one that included individuals ‘at risk of homelessness in the

future’. As for the representatives of government departments, they often tended to draw up

complex definitions based on the legislation in force in their own countries, making a

distinction between the homeless, on the one hand, and, on the other, those individuals

capable of meeting their needs without the aid of the public authorities (those households in

sub-standard accommodation) or those who were the responsibility of another department

(foreigners without a residence permit, for example). As far as the scope of the definition was

concerned, the government departments occupied an intermediate position between the

statisticians and the NGO representatives. While the charitable organisations operating on the

front line used definitions that were relatively similar to those of the government departments,

the large organisations or national federations and the researchers working in FEANTSA’s

observatory advocated broader definitions, including among the homeless people living with

friends for want of a home of their own and those living in accommodation without heating or

sanitary facilities. Unlike local associations, the large NGOs intercede in the political arena in

support of the homeless. In this instance, they were trying to highlight groups within the

population who were in “housing” need but not identified as such by government departments

or statistical offices.

The statisticians taking part in the task force were able to reach an agreement on the

definition of homelessness because the boundaries and subdivisions they put in place were

compatible with the way statistical tasks were organised in their own countries. It may also be

that they preferred not to influence the course of the debate; this is a fairly common attitude

among statisticians, who in many countries are not authorised to take such decisions. For the

NGOS affiliated to Feantsa, the choices to be made in drawing up the definitions were also

indissociable from the ways in which their activities were coordinated. From their point of

view, defining homelessness amounted to describing what united them at the European level.

However, even within this federation, conceptions differed, as is demonstrated by analyses of

the speeches given by officials of national associations.

In Catholic countries, charitable organisations have a very extensive sphere of

operations; they work with the most destitute, although the homeless do not form their main

clientele. Thus in Spain, Italy and Poland, Caritas undertakes a very wide range of activities:

remedial teaching, clothes and food banks, housing, community clinics, retirement homes etc.

Defining the homeless population does not figure particularly highly on the agenda of these

charitable associations, which are more active in tackling poverty and ‘social distress’.

Conversely, in Protestant countries, where the charitable sector is less unified and more

secular, the provision of in-kind aid is less developed, except in the case of housing.

However, the organisations dealing with homelessness have a high profile and the question of

defining the homeless population seems more fundamental to their activities. Shelter in the



8   Counting the homeless in Europe: ‘compare before harmonising’



101



UK is the emblematic example. It is an extremely important pressure group; it publishes

information bulletins and lobbies governments, but does not itself provide housing services.

These two traditions (charitable assistance vs. lobbying/protest) had to reach agreement

within Feantsa on a common definition. Since the Northern European countries such as the

UK and Germany occupied positions of power within the federation, the federation’s political

tendency prevailed over the charitable tradition, which is why a relatively broad definition

was adopted, despite the fact that, in the past, Feantsa had recommended more limited

definitions. The definition of the homeless population eventually adopted by Eurostat, which

is close to that recommended by Feantsa, is broader than the one adopted in many countries or

by professional groups.

2. The charity sector and the state

The debates that brought Eurostat and the NGOs into conflict revolved around three,

seemingly technical questions:

1.

What should be measured flows or stocks?

2.

Should data collection be based on random sampling or full counts?

3.

Should the homeless be registered on entry into reception centres or hostels or should

reception centre/hostel managers be questioned?40

These pairs of alternatives reflect the political issues linked to the representations

associated with homelessness as well as to the respective responsibilities of government

departments and charitable organisations. In order properly to understand the administrative

sources, ‘it is necessary to investigate the organising principles of the institutions concerned’

(Desrosières, 2004, page 13).

2.1. What is to be measured stocks or flows?

In general terms, and with the exception of Denmark, the public sector measures the

number of individuals or households who are homeless on a given date, whereas charitable

organisations record the individuals offered assistance over the course of a year. In Germany,

for example, Caritas calculates the number of homeless people who use its services in the

course of a year. In the Netherlands, the Federatie Opvang proceeds in the same way with

regard to the individuals accommodated in reception centres or hostels. From the point of

view of local charitable organisations, a person provided with accommodation or eating at a

soup kitchen is an individual passing through, defined by the fact that he is mobile or is

sleeping on the streets and no longer has any social ties. Such an approach, by its very nature,

leads to a count based on the number of people passing through the facilities managed by

charities rather than on a census of individuals on a given date. And the choice of a year as the

reference period undoubtedly reflects the requirement on NGOs to give an annual account of

their activities, since properly audited accounts are essential for obtaining donations and other

funding. On the other hand government statistics, which view individual trajectories in close-



40



. The description of the modes of data collection relates to the period 2000-2004.



102



C. Brousse



up, reflect only a single dimension of reality, namely individuals’ housing situation on a

reference date.

It is true that such simplification is an essential precondition for quantification (it would

be impossible to track all individuals day by day), but it also produces a change of

perspective, with the focus of attention shifting from individuals and the people or institutions

looking after them to housing conditions, that is society’s ability (or rather inability) to ensure

housing for all. This shift marks a break with the philanthropic approach, which places the

individual at the centre of charitable activity. Not only are individuals no longer perceived in

terms of their biographical trajectories but the emotive power attached to the standard

category is weakened. At the same time, space is opened up for comparisons with other

citizens, whose lives are captured in cross-sectional datasets by most of the other statistical

systems.

2.2. Full count or sample survey?

Feantsa proved to be sceptical about the opportunities for using surveys based on

samples. The position of the NGOS represented at Eurostat was not surprising: in general

terms, sample methods have little credibility with the public at large. More fundamentally,

however, and over and above the doubt that surrounds practices based on probabilities,

sample surveys have the disadvantage of not producing territorialised data. Unlike a census of

homeless people living on the streets or the gathering of official statistics on the number of

homeless people, as is the practice in the UK, the French survey, based on a sample of service

users, and the Italian survey, which is based on area sampling, do not provide any local data.

As a result, they reflect the responsibilities of central government but ignore the intermediate

levels of government. A full count of the homeless population carried out under the aegis of

central government (statistical institute or ministry department), on the other hand, forces

local authorities to fulfil their responsibilities towards people deprived of housing, to make

available the funding required for their programmes and to evaluate the effects of the

measures taken. Finland is an exemplary case in this respect. The survey carried out each year

for the past 18 years by the Housing Fund of Finland aims to estimate the size of the homeless

population at local council level. It is a subset of a wider survey of the housing market that

gathers data on the housing situation in every local authority and, more specifically, on the

gap between the supply of and demand for social housing. These data are used to calculate the

subsidies to be paid by central government to local or regional authorities in deficit.

2.3. Registration of the homeless or survey of reception centre/hostel managers?

There was a lively debate between advocates of the electronic registration of homeless

individuals using reception centres and hostels (mainly the NGOs) and supporters of a full

survey, or even a sample survey, of hostel managers (the INSEE expert). This debate was

linked in part to the two previous ones, since registering individuals facilitates longitudinal

monitoring (measurement of flows), while surveys of hostel managers are easier to design for

a short reference period (measurement of stocks). Moreover, registration of individuals leads

to a full count, while a survey of hostel managers may be based on a sample. However, this



8   Counting the homeless in Europe: ‘compare before harmonising’



103



debate is also implicitly about the distribution of statistical tasks between charitable

organisations and statistical institutes. Charities do not have the resources to conduct largescale surveys, just as national statistical offices are unable to organise a continuous data

gathering operation in hostels for the homeless. However, being responsible for a statistical

count gives an institution considerable power over the individuals it is counting, namely the

power to obtain information and to retain and process it.

INSEE’s proposal that national statistical institutes should keep a list of hostels for the

homeless and then survey the charities or social service departments that manage them,

notably in order to ascertain the number of service users, was interpreted as a desire on the

part of central government to control charities’ activities. After all, surveys of hostel

managers may be somewhat inquisitorial. Thus a survey commissioned from a researcher by

the city of Brussels asked hostel managers: ‘What are the largest sources of funding currently

available to you?’ Moreover, these assessments and surveys carried out by institutions outside

the charity sector deprive charities of the possibility of defining their own remit and

describing their sphere of operation.

Rather than these surveys conducted by central or local government, the voluntary

associations represented in the Eurostat task force preferred a ‘self-managed’ information

system of the type set up by the Dutch federation of voluntary associations, in which clients

are registered individually on entry into and exit from reception centres and hostels. They

preferred, as it were, to monitor the homeless rather than submit themselves to statistical

monitoring by central or local government. However, the demand for a self-managed data

collection system comes up against certain obstacles, since the charitable sector is relatively

fragmented and in some cases even extremely divided. While automated local or specific

systems for registering the unemployed do exist (Salvation Army, BAG, Samu social in Paris,

Focus Ireland in Dublin), introducing them at national level would require intervention by

central government. In the Netherlands, for example, the Ministry of Health helped to unify

the system by awarding subsidies only to those associations affiliated to the federation

responsible for managing the information system.

We have shown that the process of choosing statistical tools went well beyond a simple

technical debate. It brought into play the actors’ own sphere of responsibility, their

representations of the social world and their view of their position within it. Ultimately, in

order not to favour one model over another and at the request of the representative of the

Dutch statistical office, Eurostat abandoned the idea of give national statistical institutes the

responsibility for measuring the size of the homeless population. Although a system was put

in place, it was left up to each country to decide whether to give responsibility for operating it

to central government or to the charity sector. This decision marked a step towards ex post

harmonisation of the data.

3. Divisions between countries

Besides the divisions between the public and charity sectors, the debates at Eurostat also

revealed splits between countries, which here too could be observed in the variety of

statistical tools used and the diversity of ways in which the quantitative data were presented.

International comparison of data gathering systems and the uses to which they are put sheds



104



C. Brousse



further light on the objectives the data are intended to serve and the social policies of which

the homeless are the target.

3.1. Statistical and legal categories

In some countries (or regions), the statistical categories relating to the homeless are

based on a clearly defined legal framework. Thus in North Rhine-Westphalia (NRW,

Germany), the homeless are defined by the fact that they have lost their housing (as a result of

termination of their lease, breaking of rental agreement, non-renewal of lease, demolition of

apartment block). In this region, the local authorities carry out an annual review of the way in

which they organise accommodation for people who have had to leave their homes. In the

UK, the homeless are defined by the fact that their local authority will give them priority in

the allocation of housing over other groups in the population. Local authorities are required to

compile a quarterly report on their procedures for allocating housing to this specific group.

In contrast to the data gathering systems based on legal categories, surveys of

organisations providing assistance to the homeless are not based on any legal framework.

Consequently, those designing these surveys (government departments, researchers,

charitable organisations or statistical institutes) have to ensure there is a minimum level of

agreement as to the meaning of the categories they use. Thus the interviews the Brussels

research team conduct with the managers of reception centres and hostels for the homeless

begin with a general question: ‘What is a homeless person?’. Before supplying an estimate of

the number of homeless people in their local authority area, hostel managers or experts in the

field in Spain have to answer the following question: ‘In your opinion, when we speak of

homelessness [sin hogar], who are we talking about?’. And the Prague survey begins with the

same question: ‘What is your understanding of the term ‘homeless’?’.

3.2. Purpose of interventions and the unit of count (household vs. individual)

In countries in which policies for helping the homeless are focused on access to

housing, the statistical systems use the household as the unit of count (UK, Ireland, Finland

and NRW)41. The temporary housing conditions of the households concerned are described in

detail, whether or not they are actually homeless42. The ‘homeless’ category figures in more

general classifications of housing conditions. Of course the classifications differ from one

country or region to the next, but they all include the standard of housing offered to the

homeless, with a distinction being made, for example, between shared and individual

accommodation (Germany, Scotland) or between bed and breakfast establishments and others

types of accommodation (UK). Other criteria used include a distinction between local

authority and private housing (Germany and UK).

Conversely, data on hostel residents is collected at the level of the individual rather than

the household. In such systems, the problems associated with access to housing receive little

attention: the women and children accompanying the residents do not constitute households

41



. The systems in place in Finland and NRW are mixed, since they provide for the possibility of individual and

household-based censuses.

42

. With the exception of the Irish system.



8   Counting the homeless in Europe: ‘compare before harmonising’



105



but are regarded as separate individuals. This approach is also consistent with the need for

hostel managers to be fully informed about their operations, which are better defined by the

number of individuals given assistance than by the number of households (which may be of

different sizes). The individuals provided with accommodation are represented by two types

of classifications. One type relates to the ‘problems’ that are assumed to characterise these

individuals, explain their situation or justify a particular form of treatment (drug addiction,

alcoholism, domestic violence, discharge from prison). The other relates to their family

situation (single man/women, one half of a couple, accompanied by children, unaccompanied

minors). It should be noted that this representation is consistent with the perception of the

institutions’ role, whose purpose is to provide the individuals in their care with the support

appropriate to their personal difficulties, with the aim of ‘reintegrating’ them into society.

3.3. Uses and modes of presenting the data

‘A statistical survey is inseparable from the uses to which it is put. This point is often

forgotten, concealed as it is by the division of labour between the producers and users of data’

(Desrosières 2000, 8). If we acknowledge this point, a distinction has to be made between

four different types of statistical documents devoted to the homeless: general pictures of

society as a whole drawn up as part of the provision of public statistics, the housing accounts

published by ministries of housing, reports on poverty and social exclusion published by

ministries of social affairs and, finally reports on the activities of organisations providing

assistance to the homeless, circulated by local authorities or NGOs. These modes of

presentation reflect particular ways of tackling the problems associated with homelessness.

The first type of document is akin to what might be called a picture of the general state

of society. The Swedish and Danish statistical publications are examples of this generalist

approach. Thus in Sweden, the data on the homeless are not specifically linked to the

problems of housing or poverty but form part of a complete description of society, made up of

extensive chapters on the labour market, living standards, social vulnerability and social

segregation. Homelessness is considered here as a particular case of social vulnerability, in

the same way as alcoholism, criminality or prostitution.

The second category of documents compares housing supply and demand in the form of

a count of stocks and flows broken down by county in the case of the UK (HIP 2000) and

Ireland or by local authority area in Finland (Valtion asuntorahasto 2002). In those countries

that use this mode of presentation, homeless households are regarded as people waiting to be

housed. The statistical data are published at regular intervals in the form of accounting tables;

the definitions of the homeless population are broad and based on a clearly defined legal

framework. The number of homeless people measured in this way serves as an indicator in the

housing market and can be used alongside other parameters to guide local authority policies

on house building and housing subsidies.

The third way of presenting the data is in reports on poverty and social exclusion. These

documents tackle subjects such as income inequalities, social minima and the groups in the

population that are particularly affected: in Italy, children (CIES 2000), in France (ONPES



106



C. Brousse



2002) foreigners and in every report the homeless (Belgique) (Perdaens et al. 2002). The

subject of housing may be broached in these publications but the question of homelessness is

tackled separately, in sections on indicators of poverty (Bruxelles-Capitale) or chapters on the

‘faces’ of poverty (France).

Alongside these publications, there is a fourth type of document that deals more

specifically with the homeless population and the services provided for it, whether in a town,

region or country as a whole. These documents take the form of an activity report. They focus

on the programmes put in place by service providers and leave considerable scope for service

managers (Cabrera Cabrera 2000) or even the homeless themselves to have their say (Rea et

al. 2001). These reports, which are similar in some respects to customer case studies, are

structured as follows: description of services, characteristics of the clientele and, possibly,

clientele’s opinion of the services and service providers’ opinion on the homelessness

question and the best way to tackle it. These reports take stock of the situation and show the

role played by the actors, particularly those who commissioned the study (Laird et al. 2002).

The countries can be divided schematically into four groups on the basis of the way the

statistics are produced. The first group contains those countries in which there is no specific

public policy aimed at the homeless, but rather a system of social protection and a generalist

policy of access to housing (Sweden, Denmark). Here, the homelessness data are included in

the general statistical overview of society and the changes it is undergoing.

In the second group of countries, the public sector directly helps the homeless to find

housing (the UK and Ireland) or tenants to stay in their homes (Germany, NRW). Data on the

homeless are included in housing accounts and are published annually. The production of

housing accounts, like the publication of general pictures of society, incidentally, is based on

a system of regular data collection and a stable classification.

On the other hand, in the third group of countries, homelessness is analysed in terms of

poverty or social handicap rather than of disequilibria in the housing market. The public

sector makes specific interventions by providing financial support for the organisations that

provide accommodation for the homeless and/or by giving them a legal framework (France,

Netherlands, Belgium, Italy and Spain). Data on homelessness are included at very irregular

intervals in specific reports on poverty and social exclusion.

In contrast, a fourth group of countries, comprising Greece, Portugal and the new

accession countries in Eastern Europe, do not have a specific public policy either but, since

they provide a low level of social protection, an important role is allotted to the charity sector.

There are no official statistical publications but a few activity reports are published, more or

less regularly, by voluntary associations.

Each country has its own way addressing the problem of homelessness and hence a

specific way of counting the homeless. Each responds in its own way to the three central

questions in any quantification project. What is the population to be counted and how is to be

defined? Who is responsible for the statistical operation? How are the data to be collected?

The definitions and, to an even greater extent, the modes of data collection are still very

varied, since the statistical data are all based - to a greater or lesser degree – on the

mechanisms by which assistance is provided to the homeless, which on the face of it makes

them difficult to compare. This makes it clear just how difficult it is for the European



8   Counting the homeless in Europe: ‘compare before harmonising’



107



commission and its statistical office to devise a harmonised indicator of homelessness; in the

absence of a common policy on homelessness at the European level, it has proved difficult to

define a statistical category. It would appear, incidentally, that the plan to develop an

indicator of homelessness is in abeyance. Nevertheless, in the countries in which government

departments or statistical institutes have made attempts at quantification with a view to

harmonisation, perception of the homelessness issue has changed as a result. In conclusion, as

Alain Desrosières, noted, the ‘demands that national statistical results be made comparable

are a powerful encouragement to get to grips with, and possibly call into question, tools

which, within their restricted national contexts, may long have been encapsulated in “black

boxes”’ (Desrosières 2003, 52).



References

Brousse, C. (2004). The Production of Data on Homelessness and Housing Deprivation in the

European Union : Survey and Proposals, Eurostat Working Paper, Theme 3: Population and

social conditions.

Cabrera Cabrera, P.J. (2000). La acción social con personas sin hogar en Espa. Madrid :

Cáritas Española and Universidad Pontificia Comillas.

CIES (2000). Rapporto annuale sulle politiche contro la povertà e l’esclusione sociale.

Roma : Commissione di indagine sull’esclusione sociale, Dipartimento per gli Affari sociali,

Presidenza del Consiglio.

Dezalay, Y. (1993) Multinationales de l’expertise et “dépérissement de l’État”, Actes de la

recherche en sciences sociales, 96-97, 3-20.

Desrosières, A. (1991). Remarques à propos du livre : ‘Deux siècles de travail en France’ »,

Séries longues et conventions d’équivalence, Courrier des statistiques, 57, 56-58.

Desrosières, A. (2000). L’État, le marché et les statistiques : cinq faỗons dagir sur

lộconomie, Courrier des statistiques, 95-96, 3-10.

Desrosiốres, A. (2002). Comment fabriquer un espace de commune mesure : harmonisation

des statistiques et réalismes de leurs usages. In M. Lallement & J. Spurk (Eds). Stratégies des

comparaisons internationales (pp. 151-166). Paris : CNRS.

Desrosières, A. (2003). Les qualités des quantités, Courrier des statistiques, 105-106, 51-63.

Desrosières, A. (2004). Enquêtes versus registres administratifs : réflexions sur la dualité des

sources statistiques, Courrier des statistiques, 111, 3-16.

Desrosières, A., & Blanc, M. (2002). Entre décentralisation et coordination : une analyse des

spécificités des SSM. Courrier des statistiques, 104, 9-25.

HIP (2002). Housing report. London: Housing Investment Programme.

Laird, A., Mulholland, S., Campbell-Jack, D. (2002). Rough sleepers initiative – monitoring

the target of ending the need to sleep rough by 2003 – second report, 2001-2002.

NBHW (2001). Social report. Stockholm: National Board of Health and Welfare.



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ONPES (2002). Le rapport de l’Observatoire national de la pauvreté et de l’exclusion

sociale, 2001-2002. Paris : La Documentation franỗaise.

Perdaens, A., & Roesems, T. (2002). 8e rapport sur lộtat de la pauvreté en Région de

Bruxelles-Capitale. Brussels : Observatoire de la Santé et du Social, Commission

communautaire commune de Bruxelles-Capitale.

Pleace, N., Burrows, R., Quilgars, D. (1997). Homelessness in Contemporary Britain :

Conceptualisation and Measurement. In N. Pleace, R. Burrows, D. Quilgars (Eds),

Homelessness and social policy (pp. 1-17). London: Routledge.

Rea, A., Schmitz, P., Mondelaers, N., Giannoni, D. (2001). La problématique des personnes

sans-abri en Région de Bruxelles-Capitale. Rapport final. Brussels : ULB/ Institut de

Sociologie/GERME.

The Housing Fund of Finland (2002). Selvityksiä. Report, Helsinki: Valtion asuntorahasto

(ARA).



 



Chapter 9. The statistical backbone of the new European economic

governance: the Macroeconomic Imbalance Procedure Scoreboard

Gilles Raveaud



Abstract The Macroeconomic Imbalance Procedure Scoreboard monitors economic

developments in member states in order to anticipate and avoid future crises. The Scoreboard

focus on “competitiveness”, paying much attention to the external position of economies and

wage developments occurring in member states. In so doing, it encourages policies such as

the decentralisation of wage bargaining that increase inequalities while having no clear effect

on job creation. And when the Scoreboard addresses unemployment, it is in order to denounce

the “rigidities” of the “labour market”. Finally, the Scoreboard ignores the roots of the current

economic stagnation in Europe, namely excess profits and high inequalities, which are the

true disequilibria from which Europe suffers and which impedes economic recovery, while

the increase in the share of profits of the past decades has not led to the expected rise in

private investment and private employment.

“Statistics (…) transform the world by their very existence, by their diffusion and their use in

the media, in science or in politics. Once quantification procedures have been codified and

have emerged as routines, their products become real. They have a tendency to become “the

reality”, in an apparently irreversible fashion.” (A. Desrosières, 2010)

“The Council underlines the important communication role of the Scoreboard, as the choice

of indicators sends a clear awareness-raising message to policy makers and stakeholders on

the types of macroeconomic developments which could potentially be a source of concern and

where there is thus a need for enhanced surveillance.” (Council of the EU, 2011)

As the euro crisis unfolded, one lesson seemed to be shared by most: the economic

governance of Europe had to be reformed. It was thus decided to reinforce the monitoring of

national economic policies. A “European Semester” was set up to better coordinate national

budgets and to ensure that European goals are pursued at the national level.

In particular, the purpose of this Semester is to intervene – through “advice” – before

budgets are adopted in the member states. The process begins in March with the adoption by

the European Council (the meeting of heads of state and governments) of policy guidelines

that member states have to follow in the plans they submit in April. These plans are then

assessed by the Commission (in May), which then issues country-specific recommendations

that are formally adopted by the Council in June. Member states have to implement these

recommendations; compliance is monitored by the Commission.43

43



See http://ec.europa.eu/europe2020/making-it-happen/ for a fuller explanation.

G. Raveaud

Institut d'Etudes Européennes - Université Paris 8 Saint-Denis, Saint-Denis, France

email : gillesraveaud@gmail.com



© Springer International Publishing Switzerland 2016

I. Bruno et al. (eds.), The Social Sciences of Quantification, Logic, Argumentation

& Reasoning 13, DOI 10.1007/978-3-319-44000-2_9



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