Separación de Glicerina y AGL’s:

Under the scope of present analysis, a layered framework was designed to provide grounded feedback to governments on how they can better promote the employment of disabled people. While the macro-level analysis employs a quantitative method, micro-level analysis administers a mixed-method approach to providing a more comprehensive understanding of the current situation of employment of disabled people. Still, there are some limitations affecting the merit of the present analysis that should be kept in mind.

The first limitation to be acknowledged is about the OECD disability policy typology, which was utilised for the macro-level analysis. While developing the scale, the OECD team mostly used information from its previous works on sickness and disability (OECD, 2003; 2007; 2008). Countries like the Czech Republic, Greece, Hungary, Iceland, Japan, New Zealand and the Slovak Republic were sent an additional questionnaire to gather related information to develop

a disability policy typology (OECD, 2008b). The scaling approach, employed by OECD, reflects aggregated consequences of the data gathered through an open-ended questionnaire (OECD, 2008b). This, in turn, does not allow tracing of national policy process. The OECD’s employer obligations for their employees and new hires subdimension holds further limitation. When the scaling for this policy mechanism is revisited (See Annex B), it was observed that obligations over employees are coupled with anti-discrimination legislations.

This approach is particularly risky. For Waddington and Diller (2000) rights-based anti- discrimination and traditional employment quota systems cannot coexist. When those are intertwined, there is a possibility that they may create ‘a confusing jumble of policies.’ (Waddington and Diller, 2000, p. 21). The contradictory nature of anti-discrimination legislation and quota systems was briefly mentioned in the literature review (Fuchs, 2014; Eichhorst, et al., 2010). The OECD 2010 team itself acknowledges this when discussing the results of their multivariate regression analysis. While relating their result with the literature, the OECD team concluded that ‘legislation while protecting workers in existing employment, may hinder the hiring of workers with health problems’ (OECD, 2010, p. 93). When relating the finding to the existing literature, the OECD cites a number of studies revealing the adverse effect of anti- discrimination legislations (Begle and Stock, 2003; Jolls and Prescott, 2004). The contradictory nature of these two approaches, merging anti-discrimination legislations and quota systems might have the potential to dilute the effect of each (Waddington and Diller, 2000; Fuchs, 2014). Therefore, readers of this thesis should bear in mind the limitations attached to OECD’s scaling. There are also dataset limitations to be identified. The EU-LFS ad hoc module 2011 (EUROSTAT, 2015) dataset, which was used for the macro-level analysis, has limitations due to the structure of the survey. Firstly, the survey is carried out in households, which eliminates the involvement of disabled individuals who are living in a residential institutional environment. In addition, it does not have precise questions that ask about the types and the levels of disability. Secondly, the EU-LFS ad hoc module 2011 survey was carried out at the peak of economic recent economic crises, which may directly affect the employment status and unlikely to be repeated until 2021. It remains uncertain how these factors may influence employment outcomes once the global crisis is over.

For the EB 2012 (EC, 2012) dataset, which was utilised for the quantitative phase of the micro- level analysis, a proxy employer sample was generated for the stakeholder positioning variable. It was composed of general managers, middle-rank managers, business owners, shop owners, and supervisors extracted from the total survey population. Still, within the given sample, there might be employers who have relatively more or less responsibility. Amongst the respondents, there were 225 employers with disabling health conditions. This may have the potential to affect their approach to disability-related issues. Another limitation is that the EB 2012 (EC, 2012) dataset does not permit the researcher to differentiate between public and private sector managers. Likewise, no information is available as to whether the employers have disabled employees within their workforce. Another limitation to be acknowledged for the EB 2012 (EC, 2012) is the social desirability effect. Social desirability is defined as the tendency to reflect more positive thoughts than the negative ones (Scruggs, et al., 1996; Hernandez, Keys and Balcazaar, 2000; Deal, 2006; Hannon, 2007).

Literature also cited the effect of having an earlier experience of working with disabled people or having acquaintances with a disability (Honey, et al., 1993; NDA, 2002; Unger, 2002; Hannon, 2007). For the qualitative phase of the micro-level analysis, workplaces where a disabled employee(s) works were visited to illustrate the employment of disabled people in actual social environment. Employers who were interviewed were those who have already taken a decisive action on promoting the employment of disabled people. Another limitation regarding the qualitative phase of the analysis was a lack of interviews with disabled employees who have chronic illnesses or mental health problems. However, some of the interviewed employers disclosed that they have employees who have a chronic illness or mental health problems. To some extent, these transcripts provide indirect information about the employment context of people who have chronic illnesses or mental health problems.

There are also methodological concerns and contextual aspects to be discussed under the scope of limitations section. Shalev (2007) claims that the interpretation and definition of concepts are likely to be different at various macro-units. Both in the EU-LFS ad hoc module 2011 and the EB 2012, disability is based on self-reporting by the respondents. People with similar health may or may not identify themselves as disabled depending on the culture in which they are living. Policy definition, country context and language issues may, therefore, have an effect on both the

disability prevalence and employment rates (Gronvik, 2009; Molden and Tosserbro, 2012). Similarly, it does not clearly distinguish disability groups from one another due to the nature of the questions.

For the contextual aspects, Hantrais (1999; 2009) highlights the context-dependent characteristics of policies: since policy implementation depends heavily on the context in which policies are developed and implemented even subtle differences can result in differentiation in policy outcomes. She further claims that ‘as long as the inputs and outputs of policies vary, so will be the outcomes’ (Hantrais, 1999, p.104). Thus, one can never be sure about the comparability of the units or the generalisability of the findings. Thematic analysis technique, which is utilised for the qualitative analysis, also has certain inherent weaknesses due to such contextual differences. It works on the principle of de-contextualization where sentences in the transcripts are assigned codes. These codes, later, are brought together and grouped under overarching themes to answer the research question. The subjectivity of the data analysis, language and definitions are listed amongst the drawbacks (Hantrais, 2009). Zarifis (2008) touched upon the role of language and the use of contextual experience when conducting comparative qualitative research. He proposed contextual de-contextualization, the recontextualization of the themes and searching for consensus that emerged from the comparison. The author of the present thesis can deliver both the general thematic coding while displaying contextual differences from the perspectives of interview participants that would provide grounds to display differences. Still, the results are only applicable to the context where data are gathered and cannot usually be generalised or transferred to other countries.

There are also limitations that are associated with running multilevel analysis. Reliability of the estimates of county level factors claimed to be compromised when the cross national multilevel dataset composed of small number of countries and/or varying national sample sizes. It is not possible to decide which factors can be reliable when crucial factors like labour market conditions, GDP, general employment rate, social welfare expenditures remain unobserved (Snijder and Bosker, 1999; Bryan and Jenkins, 2013).

All these limitations make it difficult to draw causal inferences when running cross-sectional analysis in a cross-national context. It is, therefore, advised to consider the limitations mentioned above when evaluating the findings of the present research. The main purpose of the initial stages

of analysis in particular was to generate indicative lines for deeper enquiry and not as a form of conclusive causal explanation. Despite these limitations, this study provides significant new insight, and associations drawn from the analysis provide useful information in generating hypotheses for further investigation.