Multilevel Analysis in Household Survey: An Application to Health Condition Data

The aim of this thesis is to apply multilevel regression model in context of household surveys. Hierarchical structure in this type of data is characterized by many small groups. In last years comparative and multilevel analysis in the field of perceived health have grown in size. The purpose of this thesis is to develop a multilevel analysis with three level of hierarchy for Physical Component Summary outcome to: evaluate magnitude of within and between variance at each level (individual, household and municipality); explore which covariates affect on perceived physical health at each level; compare model-based and design-based approach in order to establish informativeness of sampling design; estimate a quantile regression for hierarchical data. The target population are the Italian residents aged 18 years and older. Our study shows a high degree of homogeneity within level 1 units belonging from the same group, with an intraclass correlation of 27% in a level-2 null model. Almost all variance is explained by level 1 covariates. In fact, in our model the explanatory variables having more impact on the outcome are disability, unable to work, age and chronic diseases (18 pathologies). An additional analysis are performed by using novel procedure of analysis :"Linear Quantile Mixed Model", named "Multilevel Linear Quantile Regression", estimate. This give us the possibility to describe more generally the conditional distribution of the response through the estimation of its quantiles, while accounting for the dependence among the observations. This has represented a great advantage of our models with respect to classic multilevel regression. The median regression with random effects reveals to be more efficient than the mean regression in representation of the outcome central tendency. A more detailed analysis of the conditional distribution of the response on other quantiles highlighted a differential effect of some covariate along the distribution.

Environmental accounting and reporting in Italian local governments: a longitudinal analysis of changes in context, content and process

This research aims at contributing to a better understanding of changes in local governments’ accounting and reporting practices. Particularly, ‘why’, ‘what’ and ‘how’ environmental aspects are included and the significance of changes across time. It adopts an interpretative approach to conduct a longitudinal analysis of case studies. Pettigrew and Whipp’s framework on context, content and process is used as a lens to distinguish changes under each dimension and analyse their interconnections. Data is collected from official documents and triangulated with semi-structured interviews. The legal framework defines as boundaries of the accounting information the territory under local governments’ jurisdiction and their immediate surrounding area. Organisational environmental performance and externalities are excluded from the requirements. An interplay between the local outer context, political commitment and organisational culture justifies the implementation of changes beyond what is regulated and the implementation of transformational changes. Local governments engage in international networks to gain access to funding and implement changes, leading to adopting the dominant environmental agenda. Key stakeholders, like citizens, are not engaged in the accounting and reporting process. Thus, there is no evidence that the environmental aspects addressed and related changes align with stakeholders’ needs and expectations, which jeopardises its significance. Findings from the current research have implications in other EU member states due to the harmonisation of accounting and reporting practices and the common practice across the EU in using external funding to conceptualise and implement changes. This implies that other local governments could also be representing a limited account related to environmental aspects.