and families, as is the case today with Alzheimer’s disease and more generally any form of dependency, must extend beyond the visibility they bestow on these peo-ple; public policies should be based on measures and interventions designed (and effectively put into practice) to allow the exercise of individual responsibility. To achieve this, public policies must increase the number of opportunities and choices offered to the sick and their families; they need to act to ensure a patient’s current and future freedom. In order to evaluate the fairness of public action concerning Alzheimers sufferers one needs to assess their capabilities and freedoms in the con-text of the elderly population more generally. By ’capabilities and freedoms’ we specifically mean the array of possibilities available to them and their freedom to choose the type of life they value from this array (Sen, 1992). Thus, our empirical results will provide useful insights for those responsible for devising public policies directed towards the enhancement of the capabilities of Alzheimer’s sufferers.
The first part of this chapter will introduce Sen’capability framework, providing a review of previous studies that deploy the capability approach in health related sub-jects and as far as family implications are concerned.The second part will explain the database and how we selected our capabilities, constructed the functionings, and chose the exogenous variables. We will then present our theoretical and empirical model with the results of the estimations. Finally, we will compare the estimated capabilities for both populations (Alzheimers and Non-Alzheimers) before drawing some conclusions.
2.2 Literature review
Most of the research work done in microeconomics relating to the behaviour of peo-ple with Alzheimer’s disease rests on (extra-)welfarism and utilitarianism. However, the utility-based approach fails to take into account differences in terms of capa-bility (notably regarding health) which exist between one individual and another.
The logic of effectiveness which underlies the approach struggles to accommodate the question of different needs. This approach also reduces interaction between for-mal and inforfor-mal helpers to a single alternative: substitution or complementarity.
Another problem associated with utilitarianism is that it fails to take into account people’s capacity for self-reflection. Finally, within this framework, choice is only valued in an instrumental way. This can lead to misinterpretations regarding pref-erences when they are merely deduced from the choices people make; people will choose what they can when what they actually want is not an available option.
Grewal, Lewis et al. (2006) provide a large overview of studies based on more classical approaches and the advantage of using the capability approach to analyze health care for older people.
The different economic approach adopted here, referred to earlier as the capability approach, and initiated by Amartya Sen, appeared in the 1980s as an alternative to the dominant paradigm in welfare economics which relied on income or consumption (and utility derived from it) as the appropriate measure of welfare. Sen’s work
argued for a new way of assessing well-being from the perspective of an individual’s ability to lead the kind of life that they have reason to value. These opportunities relate to all aspects of life - economic, social, cultural, political, environmental, and so on. All individuals possess or have access to certain resources and are able to
’convert’ these resources into possible well-being outcomes e.g. having income to buy food and nourish oneself, having the necessary infrastructure to go to school and receive an education, having access to clean water to drink, wash and cook, etc. As these simple examples show, the ‘conversion’ of ‘resources’ into potential welfare options depends on personal, social and environmental factors and hence varies from one individual to the next. Thus, people with the same resources may not end up with the same set of capabilities. Similarly, with any given a set of capabilities, the preferred (valued) outcomes (’beings and doings’) will differ from person to person. The following diagram summarizes the key features of the approach.
Figure 2.1: Capability approach (Farvaque 2005)
By focussing on choices and distinguishing between choices and outcomes, the capability approach has placed the individual rather than his or her resources at the centre of the public policy debate. Any public policy should therefore aim to enhance an individual’s capability set and their freedom of choice. Secondary analysis of studies, especially household studies, is a method frequently used to operationalise the capability approach (Anand, Hunter et al. 2004; Kuklys 2005;
Qizilbash and Clark 2005; Lorgelly, Lorimer et al. 2008). Many methods have already been mobilized to operationalise the capability approach. For example, there are methods involving the development of multidimensional scales, methods derived from the fuzzy set theory (Vero 2002; Chiappero Martinetti 2006), or based on the estimation of structural equations using Multiple Indicators and Multiple Causes (MIMIC), or Structural Equation Models (SEM)(Kuklys 2005; Di Tommaso 2007; Krishnakumar 2007; Krishnakumar and Ballon 2008; Di Tommaso, Shima et al. 2009). This last approach is increasingly being used in Anglo-American
2.2. Literature review literature because “The MIMIC model adds exogenous causes for the latent factors, thus providing an explanation for our capabilities”. Equally,“the structural equation model constitutes the most appropriate framework for the estimation of capabilities as it accounts for their simultaneous determination, their dependence on external causes as well as the impossibility of their direct measurement” (Krishnakumar and Ballon 2008).
Latent variables are representations of concepts that cannot be directly observed or measured; in our context, the individual’s degree of freedom to be and to do
‘valued’ things in life. Much work has been done on latent variable models in social sciences, especially in psychology, where they are often used. Excellent cov-erage of most of these models with applications can be found in Bollen (1989), Bartholomew and Knott (1999), Muth´en (2002) and Skrondal and Rabe-Hesketh (2004). The factor analysis model is the earliest in this category and in this model the observed outcomes are postulated as manifestations of a certain number (fewer) of unobserved latent variables (called factors) as the same latent concept manifests itself in many observed responses. For example, test scores are manifestations of a person’s (latent) intelligence, voting responses are manifestations of one’s per-sonal politics, and so on. Thus, factor analysis provides a theoretical framework for linking (observed) functionings to (latent) capabilities, assuming the former to be manifestations of the latter. However, this model does not explain the latent variables themselves (nor the capabilities in our context) in that it does not say what causes these capabilities to change.
It is not enough to measure how much is achieved, it is also essential to be able to say how things can be improved. The MIMIC model (cf. J¨oreskog and Goldberger (1975)) and its various extensions of (we will not go into details here) provide a solution. In this setting it is not only assumed that the observed variables are manifestations of a latent concept but also that there are other exogenous variables that “cause” and influence the latent factor(s). This structure is highly relevant in our context as we have always argued that institutional and social arrangement factors have a profound impact on the set of opportunities and freedoms available to a person. When several dimension freedoms are considered, it is also important to take into account possible interdependencies among them. Indeed, freedom in one dimension can encourage freedom in another and vice versa. In our case, if people are able to move about freely then they should also be able to participate in domestic and other activities. This is precisely why we need to move beyond one-way causal links towards structural equation models (SEM), including several interdependent latent endogenous variables and exogenous “causes”. By estimat-ing the resultestimat-ing econometric model usestimat-ing real data, we will be able to verify our assumptions about the mutual reinforcing of various capabilities and surrounding factors that influence an individual’s capablilities. The following review will specif-ically focus on applications of latent variable methodology in the area of capability approach.
An important reference in this literature is Kuklys (2005) in which the author uses a MIMIC model in order to measure the unobserved functioning in health
and housing, each observed through a range of indicators. The model is estimated using data from the British Household Panel Survey for 1991 and 2000. Having generated the latent variable scores, the author finds notable difference between welfare viewed in the functioning space and that viewed in the income space, and hence concludes that resource-based measures do not adequately capture the lack of performance in the achievement space.
The same MIMIC model is adopted by another work (Di Tommaso (2007)) to conceptualise children’s well-being in India. Well-being is measured by four func-tionings: height for age, weight for age, enrolment in school, and the child’s work status. The last two are found to be the most important for describing achievement in the well-being dimension. The parents’ literacy levels and the child’s gender are the most influential ‘causes’, followed by income and wealth (assets and durables).
Wagle (2007) uses a SEM for deriving multidimensional poverty measures using household data from a survey conducted in Kathmandu, Nepal in 2002 and 2003.
Five major dimensions of well-being are considered: subjective economic well-being, objective economic well-being, economic well-being, economic inclusion, political inclusion and civic/cultural inclusion. Each of these dimensions is measured by a series of indicators and they influence one another through a system of simultaneous equations but there are no exogenous variables in the model. The author finds that objective poverty is adequately measured by income and consumption whereas the subjective notion of poverty is reflected in the householders’ views concerning the adequacy of income for food and non-food expenses.
Krishnakumar (2007) proposes a more general SEM with exogenous variables in both the structural and measurement parts as an appropriate system for opera-tionalising all the features of the capability approach. Based on the estimation of the parameters of the model, a multidimensional index of human development is derived and the theory is illustrated with an application using worldwide country-level data. The data relate to a cross section of middle and low income countries across the world for the year 2000 (or the year closest to it i.e. 1999 or 1998 for a few variables). Based on the availability of data, the author considers three fundamental capability dimensions. These are knowledge (education), health, and political freedom. Income was not considered as a dimension in itself due to its
“instrumental” role in promoting human development rather than being a compo-nent of it. The model was estimated by maximum likelihood method and ‘robust’
standard errors were calculated. The chapter confirms the interdependent nature of capability sets in the three dimensions. The chapter’s main contribution lies in its identification of factors that may enhance capabilities. It empirically confirms that improvements in political and social infrastructure facilitate the fulfillment of capabilities and significantly raise the level of capabilities. The author concludes by elaborating “capability indices” from the latent variables scores and comparing them with the Human Development Index (HDI) and GDP per capita. The ranking of countries changes considerably among the three evaluation criteria.
Krishnakumar and Ballon (2008) study capabilities of Bolivian children in two basic dimensions, namely knowledge and living conditions, using the above structural
2.3. Database