Activity report of visit to InGRID research infrastructures
Jenny García
Project title: Urban bias in living Conditions:
An example of France and Portugal, 1981-2011
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Abstract (max 300-500 words)
In 1977, Michael Lipton introduced the urban bias component in development analysis around the world. With
his contribution, dependency theory has historically settled the main gap in living conditions in developing
countries in terms of spatially recognized patterns. These disparities are expected to be observed in favor of
urban population. Although, urban bias was not considered as present in European countries at the moment,
recent economic and social changes could be raising a different scenario. In this sense, the main aim is compare
European countries living conditions, when urban bias is considered during the recent years. For this purpose,
national census data are required to compare three aspects: living standards, education and employment.
Introduction and motivation of visit
Gaps in living conditions have been historically correlated in the recent world to all kinds of factors according to:
regions in the world (continents, OECD), countries (developed and developing) and even inside the national
level (strata, race, ethnicity, income, education, occupation, etc.) As it seems, these disparities do not necessarily
correspond to some spatial categories. In some cases they could be associated to more individual characteristics
and in others to wider structural conditions. Capability Approach (CA) analyzes inequalities integrating both
levels. In this way, the domain (empowerment) introduced by the CA is a combination of capacity with a
structure of opportunities. Action capability (Agency) is the endowment or capital available to an individual or a
community (material, financial, educational, organizational, and informational resource). It begins with the ability
to conceive options, alternatives or aspirations for their standard of living, and continues with the capacity to act
to carry them. These capabilities are exercised within the framework of rules, known as the opportunity
structure. Both structure capabilities and opportunities are differentiated according to the social strata and
geographical location (Gruson, 1993).
Michael Lipton introduced in 1977 the Urban Bias Thesis (UBT) as a framework to understand economic and
social singularities in developing countries; pointing how inequalities could be easily identified in the way that
development has been assumed differently in urban and rural areas. He acknowledged that macro- and
microeconomic policy initiatives have benefited the overdevelopment of urban areas and the underdevelopment
of rural areas as a product of capitalist economies (Lipton, 1977). The UBT claims that rural areas of developing
countries suffer from: too little spending on welfare and differences in taxes, salary and food prices policies that
promote and increase an unfair gap in the population and an inefficient resources distribution (Varshney, 1993).
Since then, different reviews and critics have been emitted to this theory; also various stages have been identified
in the way that rural-urban economics manifest into livelihood strategies (Jones and Corbridge, 2010). Even
when the concepts of urban bias has been mostly associated to developing countries, recent economic changes in
European countries could be introducing space to use it as an explanatory framework for some inequalities
below the national level. In this sense, an idea of the structures of opportunities and capabilities is needed to be
catch and confronted considering the possible manifestation of an urban bias.
The selection of a list of central capabilities for the assessment of well-being is one of the biggest challenges
related to the Capability Approach operationalization. In fact, there has not been agreement in specialized
literature on whether the list should be universal or context dependent, however some set of indicators for the
approximate measurement of a set of capabilities have been done and in any attempt it has been a consensus that
‘being well sheltered’ or ‘having adequate housing’ is basic (Roche, 2007). Then, adequacy in housing could be an
indicator to studying inequality in capabilities or life chances between social groups. As well, social groups could
be created according to the educational and organizational arrangement made and displayed around employment.
In order to get an insight in the ways urban bias could be manifesting through the recent years in the living
conditions in European countries, the Integrated European Census Microdata (IECM) and the Integrated Public
Use Microdata Series (IPUMS) offer an extraordinary opportunity to access to high quality, continuous,
harmonized and detailed data related to education, employment and dwellings characteristics, there basic
dimension to get a basic idea of the structures of opportunities and capabilities inside the countries. All that,
preserving them as statistically representative in a sufficiently small geographical scale within the national level
and still comparable at an international one.
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Scientific objectives of visit
According to European Commission statistics during the last decade proportion of people in risk of poverty or
social exclusion have been raising. In 2011, 22.9% of all Euro- Area population (18 countries considered) were
classified under this category. This risk varies between countries and of course in regard of some characteristics
attached both contexts as individual variables. In this sense, the scientific objective of my visit is to contribute to
the analysis of determinant of inequalities in Europe, using as framework urban-rural distinction.
Reasons for choosing research infrastructure and datasets/surveys/...
Existing inequalities in European countries during the recent years may or not be given evidence to respond a
peculiar geographical pattern within the national level. In the search for constructing a map that allows us to set
the lines determining the main gaps, census data seems to be suitable and representable enough of the diversity
inside countries. It allows building a scale in which occupation, education and status of employment would be
resembled as a stratification of capabilities, and they could be related to variables associated to the living
standards of the population. Besides, how these occupational characteristics could also vary according to
geographical categories. In summary, let us combine individual and aggregated information during long periods
of time.
Meanwhile, the Centre d'Estudis Demogràfics (CED) is recognized as one of the most important research
centers in Europe. CED's researchers have developed long experience as technicians and users of IPUMS and
EICM data, becoming reference in the subject. Beyond that, their continuous studies in inequality and
development showed out to be a plus for enriching my experience.
Activities during your visit (research, training, events ...)
During my five-days visit to the CED, I had the opportunity to receive special training in IPUMS- EICM
database. Particularly in the multiples ways and more suitable to extract the data I needed to my research. By
the hand of Antonio Lopez Gay, I enlarged my knowledge above the decision taken behind harmonization
of variables and categories in both datasets and the algorithm logic used to construct new ones. Most of the
training activity was focused in learn all the possible arrangements that could be done to the samples extracted
according to special conditions needed, as well as how to review and adjust data asked.
Regarding my research I concentrated the analysis on two countries and use them as an example about how to
construct an occupational status indicator using the harmonized employment variables found in IPUMS-EICM
database and to describe how working population is distributed according to urban- rural and occupational
status. Besides the formal activities, I could be involved in informal meeting with several ED's researchers with
different levels of experience who gave me a valuable feedback about my current research. To have developed
my work close to an experienced expert team has improved –without doubt– the results I could obtain in my
future research. Throughout numerous advices and insights about how give the best use to the data; I was able
to engage in deeper understanding about how to measure inequality in Europe.
Method and set-up of research
The analysis needed in this first approach is descriptive in nature. Its aim is to describe changes in the
distribution of the occupational status according to urban-rural areas across time and set the first inside in how
the living conditions of the population differs within status categories and areas.
Taking 5% of the sample for two countries (France and Portugal) in two census each (1981- Portugal, 1982France and 2011 for both) and due to completeness information, it was possible to characterize 99.6% of the
households with working people (older than 24 years) in the four censuses selected 1. Three variables were used
to create the occupational status indicator: 1) Educational Attainment, 2) Occupation and 3) Status in
Employment. Through the combination of these variables, an occupational status was elaborated to split the
It represents 20,106,240 (1982) and 26,167,185 (2011) cases of working people over 24 years old for France and 3,455,080
(1981) and 4,279,480 (2011) for Portugal
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aforementioned population2 into five categories:
Table 1. Occupational Status
Occupational Status
HQ
(Highly qualified)
NQ
(No-Manual Qualified)
MQ
(Manual qualified)
NL (No-Manual low
qualified)
ML
(Manual Low qualified)
Educational
attainment
University
completed
University
completed or
Secondary
completed
Primary completed
or Less than
primary completed
Occupation
Status in employment
Legislators, senior officials and managers,
Professionals
Professionals, Technicians and associate
professionals, Service workers and shop and market
sales, Clerks and Armed forces
Employees or
Employers
Employees or Ownaccount worker
Skilled agricultural and fishery workers and Crafts
Employees or
and related trades workers
Employers
Service workers and shop and market sales, Other
Employees, Ownoccupations, unspecified or n.e.c.
account worker,
Contributing family
Crafts and related trades workers
workers, Members of
Plant and machine operators and assemblers,
producers' co- operatives
Elementary occupations
Source: Elaborated by the author.
By the other hand, two variables were considered to analyze the living conditions of the population: the first one
directly from the collected information in the census: ownership of the dwelling, and a second one, density
of the household, measured as the ratio of persons in the household and the number of rooms declared. It could
be recognized that having less persons per room in the dwelling as well as to own it, constitute desirable
particularities in living condition. However it also acknowledges that, indeed, they are cultural behaviors and
preferences that set patterns far from point these variables as indicators of wealth or hierarchy in living
standards. In this case, they are used just as an example of how resources turn out to be distributed in the
population and to compare occupational status and geographical area.
Project achievements during visit (and possible difficulties encountered)
The variety of concepts that categorized the urban-rural variable is also translated into a variety of urban-rural
classifications of territories and populations in the European censuses database through history. It means that
under the consideration of rural population is possible to find diverse criteria setting limits between what is
considered urban and rural areas. This dilemma has been quite discussed in specializing literature and it
becomes usual issue when geographical comparison needs to be done. In order to achieve a suitable
comparison between censuses, France (1982 and 2011) and Portugal (1981 and 2011) were selected as an
example to create and compare the occupational status. The four censuses keep the same definition:
“urban areas are defined as localities with 2,000 or more population”. This criterion is going to be kept for
my future research on this subject.
Preliminary project results and conclusions
When occupational status indicator is constructed it is possible to see structural difference between countries in
how working population over 24 years old is distributed according to the educational level and the status they
play. Table 2 shows working population’s distribution for each country –France and Portugal– and each census.
The first element to see is the similarity between Portugal distribution in 2011 and France in 1982. This similarity
is mostly due to education level achieved by the population.
Low qualified Manual workers were the biggest group in Portugal in 1981 (56.1%) and keep being largely
important in 2011 (32.5%), even when following France's tendency of reducing, especially due to changes in
educational level composition of the population. While most manual works keep being done by population with
low educational level in Portugal, France has increased significantly its no-manual works developed by qualified
population (56.8%).
The only similarity that seems to manifest both countries is the proportion of highly qualified workers for both
dates. Even when they could have different economic structure, proportion of working population occupying
the most qualified employments is similar.
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Over 24 years old working population was selected because of considering achieving definitive educational level.
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Table 2. Distribution of working population over 24 years old according
to Occupational Status, France (1982, 2011) and Portugal (1981, 2011). (Percentage)
FRANCE
PORTUGAL
Occupational Status
1982
2011
1981
2011
HQ
5.0
8.0
5.0
8.60
NQ
32.6
56.8
18.0
36.9
MQ
13.9
19.7
0.60
5.8
NL
16.6
6.90
20.3
16.2
ML
31.9
8.60
56.1
32.5
Total
Source: EICM-IPUMS
100.0
100.0
100.0
100.0
In order to have an idea about how the occupation status behaves related to other variables, it was compare with
urban-rural areas using number of persons per room and proportion of ownership of the dwellings. As it was
mentioned before, bigger proportions of ownership of the dwelling it is not necessary an indicator of better
conditions in living standards, but also dwelling availability for buying and cost must be considered. For this
reason the most important element to follow is the change in scattering, which means the distance within the
occupational status categories and the changes through time for both countries. Even so, occupational status
scales for both indicators, the higher the status the fewer persons per room, were declared and the biggest the
proportion of people owning the dwelling (Except for Portugal in 1981).
Figure 1. Proportion of ownership of dwellings and persons per room according
to occupational Status, France (1982, 2011) and Portugal (1981, 2011).
FRANCE
PORTUGAL
Source: EICM-IPUMS
It is possible to see the different way in which changes took place in both countries. It seems there is nosignificant differences through time in France, instead Portugal either rural or urban areas show an important
change both increase in the proportion of ownership for all status as decreasing of persons per room. Probably,
due to change in living conditions in the whole country.
The scale in which occupation status organizes turns out also different between urban and rural areas for both
countries. Even when they keep the hierarchy, their scatterings is wider in rural areas, referring to more unequal
living conditions between the occupational statuses.
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Outcomes and future studies
Results obtained show how resources are distributed differently when urban-rural areas are considered within
the occupational status. However more focused research should be done regarding the occupational categories
constructed from the census. It will be necessary a better understanding of the harmonization of the variable to
get a more precise status indicator. Moreover, it would be also necessary to continue this analysis
considering other countries for longer periods of time to be able to catch possible patterns in the way that
resources are distributed and how the opportunity and capabilities structure could be analyzed in different
European countries when urban bias is considered.
References
GRUSON, Alberto. (1993) Las disparidades en las condiciones de vida de la población de Venezuela.
Socioscopio n. 1. CISOR. 37 Pág. Caracas.
JONES, G.; CARBRIDGE, S. (2010). “The continuing debate about urban bias: The thesis, its critics, its
influence and its implications for poverty-reduction strategies”.
LIPTON, M. (1962). “Balanced and Unbalanced rowth in Underdeveloped countries” The Economic Journal,
Vol 72, N°287 (Sep., 1962), pp 641-657.
ROCHE, José Manuel. Paper to be presented at the 2007 Conference of the HDCA: "Ideas Changing History",
New York, September 17-20, 2007
VARSHHNEY, A. (1993). “Introduction: Urban Bias in Perspective”. The Journal of Development Studies.
Volume 29, Issue 4, 1993. Special Issue: Beyond Urban Bias. P 3-22.
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