L'objet de cette thèse est l'analyse des comportements de consommation de soins et de leur impact sur l'évolution et la répartition de la dépense de santé dans la population. Nous menons une analyse sur données individuelles et mettons en oeuvre des méthodes originales de micro-simulations afin de mettre en évidence les effets de l'hétérogénéité des omportements au niveau individuel. <br /><br />Un premier chapitre expose les méthodes économétriques employées lors de l'estimation d'équations explicatives de la consommation de<br />soins sur données individuelles. <br /><br />Un deuxième chapitre développe une méthode originale visant à comparer les effets du vieillissement démographique à d'autres effets influençant la hausse des dépenses de santé entre les années 1992 et 2000. Nous montrons que la hausse des dépenses est principalement due aux changements de comportement face à la maladie, ces changements de comportements pouvant être en grande partie liés au progrès technique. Le vieillissement démographique n'a qu'un rôle mineur dans l'explication de la hausse des dépenses<br />de santé. De plus, nous montrons que l'état de santé moyen s'améliore. <br /><br />Un troisième chapitre propose une méthode novatrice de décomposition des inégalités de consommation de soins par facteur. A morbidité donnée, la consommation de soins est concentrée chez les individus les plus riches de la distribution ; or nous montrons que cette inéquité est pour moitié due à l'hétérogénéité des comportements due à la position des individus dans l'échelle des revenus, cette hétérogénéité n'étant pas identifiable dans les décompositions standard. Trois applications sont proposées : la décomposition des inégalités par facteur pour la France en 1998, l'évaluation de l'impact de la CMU-C sur l'évolution des inégalités de consommation de soins, enfin la comparaison des sources d'inégalité entre les personnes âgées (65 ans et plus) et les autres.

This doctoral thesis analyses the changes in income inequality in post-apartheid South Africa. The thesis adds to the existing literature by explaining the underlying causes of the changes in observed income inequality. As such, this thesis applies different decomposition methods to the Gini coefficient. In the analysis of household income sources, traditional static decompositions are supplemented by applying micro-simulations that allow for a dynamic decomposition of changes in income sources reported in household surveys. The results corroborate previous findings of the significant contribution of labour market incomes and governmen grants. However, the application of advanced dynamic methods highlights the effects of changes in other factors, such as investment income and the role of employed household members, which have previously received less attention. Further study of household survey data and a unique set of tax administration data enabled a decomposition of the Gini coefficient of taxable income to investigate the effect of high earners on income inequality and the accuracy of capturing them in household surveys. This analysis highlights a significant weighting issues of high earners in the latest wave of the household survey data. Therefore, when combining the two types of data sets, a significant decrease in overall inequality of taxable income can be found between 2011 and 2014. The results ascertain the vast differences between the top and the bottom of the income distribution and concrete policies addressing both sides of the issue need to be implemented in order to overcome persisting income inequality. Finally, the strong effects of labour market incomes on overall income inequality warrant further investigation. Therefore, changes in earnings inequality are decomposed to assess the effect of changes in the labour market. The application of micro-simulations thereby allows to decompose the changes in earnings inequality into ‘price effect' and ‘endowment effect' but also to assess the effect of changes in labour market participation, employment, occupational structure and unobserved characteristics. The results show that key drivers of an increase in earnings inequality between 1993 and 2012 were changes in the endowments of working age individuals. This effect was partially counteracted by the price effect. The findings show persisting discrepancies between male and female employment in the labour market and the ongoing marginalization particularly of African women which highlights the need for a revision of existing affirmative action laws and their implementation. The National Development Plan offers several strategies for more inclusive growth for South Africa, however, government is already falling behind with its implementation. Therefore, policy makers need to re-examine the efficiency of current social spending and labour laws in order to set the right growth path for the South African economy. The methods utilized throughout this thesis harmonise different sources of information and enable an integrated analysis of the dynamics of the South African income distribution. The static and dynamic decompositions make use of the 1993 household survey of the Project for Statistics on Living Standards and Development (PSLSD) and the 2008 and 2014 National Income Dynamics Study (NIDS). The assessment of high earners is performed by comparing tax administration data provided by the South African Revenue Service (SARS) for the 2010 and 2014 tax years with household survey data from NIDS in 2011 and 2014. Finally, the decomposition of earnings inequality is carried out using data sets from the Post-Apartheid Labour Market Series (PALMS) between 1993 and 2012.

Trade liberalization in Kenya started in the early 1980s with the structural adjustment programmes, and continued under the multilateral framework of the WTO. During the same period, the incidence of poverty and level of inequality also worsened. The government’s focus on trade negotiations has been to ensure that there is policy space for the daily running of the economy even though welfare impacts are also important. Non-state actors have argued that trade liberalization has negatively affected the poor; particularly the farmers, since they cannot compete with the developed countries whose farmers enjoy significant government support through subsidies, making their products much cheaper in the world market. Government officials, on the other hand, contend that trade liberalization is good as it brings in competition and transfer of technology which is good for an economy. It is important to examine how trade liberalization has affected household’s welfare in Kenya, given that this kind of analysis has not been conducted in Kenya. This study is unique because it does not assume the existence of a trade liberalization– poverty relationship, unlike most studies. It uses a multi-method approach to first test the hypothesis that there is no statistically significant relationship between trade liberalization and poverty, it further tests for multiplier effects of trade liberalization on poverty determinants. Trade Liberalization and poverty is found to have a stochastic relationship, furthermore investments and capital stock were found to significantly affect poverty determinants in the stochastic model. Due to unavailability of household welfare measure data in time series, a CGE model was used to establish the dynamics of trade liberalization on poverty at a point in time using the 2003 Social Accounting Matrix Data for Kenya. Overall, trade liberalization accompanied by FDI had the greatest impact on household welfare. Trade liberalization had a positive impact on household welfare since household incomes and consumption increased. Micro simulations results, based on changes in consumption, also showed that poverty incidence reduced for all households, even though the urban households experienced higher decreases. The study found that there was little difference in protecting sensitive products and not protecting them; secondly, trade liberalization accompanied by foreign direct investment had greater impact on improving the household welfare. Consumption and incomes increased, resulting in overall poverty reduction. The welfare of urban households was much higher than rural households in terms of income and consumption increases. However, income inequality was much higher in urban than rural areas. / Economics / D. Litt. et Phil. (Economics)

Trade liberalization in Kenya started in the early 1980s with the structural adjustment programmes, and continued under the multilateral framework of the WTO. During the same period, the incidence of poverty and level of inequality also worsened. The government’s focus on trade negotiations has been to ensure that there is policy space for the daily running of the economy even though welfare impacts are also important. Non-state actors have argued that trade liberalization has negatively affected the poor; particularly the farmers, since they cannot compete with the developed countries whose farmers enjoy significant government support through subsidies, making their products much cheaper in the world market. Government officials, on the other hand, contend that trade liberalization is good as it brings in competition and transfer of technology which is good for an economy. It is important to examine how trade liberalization has affected household’s welfare in Kenya, given that this kind of analysis has not been conducted in Kenya. This study is unique because it does not assume the existence of a trade liberalization– poverty relationship, unlike most studies. It uses a multi-method approach to first test the hypothesis that there is no statistically significant relationship between trade liberalization and poverty, it further tests for multiplier effects of trade liberalization on poverty determinants. Trade Liberalization and poverty is found to have a stochastic relationship, furthermore investments and capital stock were found to significantly affect poverty determinants in the stochastic model. Due to unavailability of household welfare measure data in time series, a CGE model was used to establish the dynamics of trade liberalization on poverty at a point in time using the 2003 Social Accounting Matrix Data for Kenya. Overall, trade liberalization accompanied by FDI had the greatest impact on household welfare. Trade liberalization had a positive impact on household welfare since household incomes and consumption increased. Micro simulations results, based on changes in consumption, also showed that poverty incidence reduced for all households, even though the urban households experienced higher decreases. The study found that there was little difference in protecting sensitive products and not protecting them; secondly, trade liberalization accompanied by foreign direct investment had greater impact on improving the household welfare. Consumption and incomes increased, resulting in overall poverty reduction. The welfare of urban households was much higher than rural households in terms of income and consumption increases. However, income inequality was much higher in urban than rural areas. / Economics / D. Litt. et Phil. (Economics)