近幾年針對資本結構的研究發現,在比較先進國家的企業確實有逐步調整回自己的最適資本結構的動作。本論文進一步將研究擴大到開發中國家，發現研究中的32個國家，不論是已開發或是發開中國家的企業，確實都有維持最適資本結構的動作。當資本結構偏離時，企業會逐步地調整回其最適值，然而每個國家調整回最適資本結構的調整速度則存在著差異性。本論文進一步利用國家間法律、會計、制度以及規範面的差異下去分析，發現國家發展程度以及會計制度是影響調整回最適資本結構的速度快慢的重要因子。此外，本論文亦探討融資順位理論及擇時理論的影響，發現加入融資順位理論因子後，調整速度會有相當程度的減緩，而減緩的幅度，則與國家發展程度、法律保護、公司稅率以及會計制度有顯著的關連性。 / Recent empirical literature provides evidences that firms in most developed countries do partially adjust toward their target capital structure. In this paper, we show that no only firms in developed countries, but also those in emerging countries gradually move back to their long-run equilibrium when they are away from it. But the adjustment speeds vary from country to country. We study the determinants of adjustment speeds around the world by focusing on differences in laws and regulations across countries. Our evidences show that firms in countries with common-law tradition, stronger shareholder right, or more completed accounting standards tend to move back to their optimal leverage quicker. Furthermore, we add two variables related to other two main capital structures (pecking order and market timing) in our analysis to capture their effects. Both theories add some information in explaining capital structure, but the impacts differ when applying different leverage measures. When we define leverage ratio as long-term debts dividend by net assets, we observe that pecking order factor lowers the adjustment speed a lot. And the magnitude of decrease on adjustment speed is significantly correlated with market condition, law enforcement, corporate tax rate and accounting standard. More developed countries and countries with stronger law enforcement, higher corporate tax rate, or more completed accounting standards tend to have less reduction on adjustment speed when including pecking order factor, because they have less information asymmetries.

The informal sector has emerged as an important sector in Africa where many countries are striving to attain Sustainable Development Goal (SDG) number 8 on decent work and economic growth. The presence of a growing number of individuals and firms in the informal sector in Africa and the need to attain SDG 8 through formalisation have reignited the debate on informality and its possible causes and effects on the growth trajectory of African economies. Empirical questions on the determinants of informality are still not adequately answered. One question which continues to generate a lot of debate and contrasting results is the relationship between the informal sector and corruption. Both informality and corruption have emerged as ‘twin challenges’ in Africa, with a far reaching impact on economic development. The relationship between the informal sector and corruption has been an inconclusive and a polemical issue in both academic and developmental discourse. From a theoretical perspective, the two can be substitutes or complements, but the exact nature of the relationship is not clear. The main objective of this study is to empirically investigate the relationship between the informal sector, corruption and economic development in Africa, over the period 2005 to 2015. The objective of the study was answered through two ways: theoretical and empirical methodology. In the theoretical methodology, a classical approach was applied. The classical theory suggests that in the presence of a market for corruption, corruption control can reduce the size of the informal sector through reducing the supply of corruption, thereby raising the price of corruption. The negative relationship between corruption control and the size of the informal sector is supported by the described empirical data for Africa. The results from descriptive statistics, in particular the scatter plots, demonstrate that control of corruption, government effectiveness and economic development as measured by the Human Development Index (HDI) are negatively associated with the size of the informal sector. The negative association between the control of corruption and the size of the informal sector entails that corruption increases the size of the informal sector. With regards to the empirical solution, the total population of 54 African countries was considered for the study. However, a panel of 46 countries was analyzed as the other eight countries, although considered together with the rest, were scientifically isolated from the panel due to data challenges. Robustness checks were carried out to check if estimates are not sensitive to sample size or region. Further, for purposes of this study, the sample was also divided into Southern and Eastern Africa, and Northern and Western Africa. Panel data was applied in order to account for both time and country-specific heterogeneity. The use of panel data allows one to study variability through comparability of the level of informality in countries such as Zimbabwe where the economy has remained largely informalised. Four panel estimators, namely, the Pooled Effects, Fixed Effects or Within Effects, Random Effects or GLS, and Dynamic Panel Model (Arrelano-Bond), were applied. Model specification tests identified the Fixed Effect Model as the most appropriate model. Hence, the discussed results are largely from the Fixed Effects Model. On measurement of informality, the study relied on the shadow economy estimates constructed by Medina and Schneider (2018) for 158 countries from 1991 to 2015. On corruption, the study used the Control of Corruption Index (COCO) published by the World Bank, in the Governance Index Report. Unlike previous studies which used GDP per capita only as a proxy for economic development, this study went a step further and used Human Development Index (𝐻𝐷𝐼) as a proxy for economic development. Profit tax as a percentage of GDP was also tested as a potential determinant of informality. The endogeneity of the corruption variable was corrected using an instrumental variable. The findings show that an improvement in the control of corruption or government effectiveness reduces the level of informality in Africa while, an increasing informal sector is a breeding ground for corruption. The two variables are complements or jointly determined. Countries with large underground economies possess high levels of corruption, and countries with high levels of corruption are associated with large underground economies. The complementarity of corruption and the size of underground economy implies that policies that target one of the two will also help in tackling the other. In addition, the results show that economic development reduces the magnitude of informality, while a larger informal sector today implies a bigger informal sector in the future. One of the findings of this study is that previous studies which applied GDP per capita as a measure of economic development largely underestimated the impact of economic development on the size of the informal sector. The findings of the study show that the negative association between the control of corruption and the size of the informal sector holds for both the Northern and Southern regions of Africa. The impact is however bigger in the Northern Region, as a marginal improvement in corruption control has a bigger impact in reducing the size of the informal sector compared to the Southern Region. The results from the study also show that the level of informality in a country has a memory. A bigger informal sector today is likely to propel the level of the informal sector in the future. The findings show that a growth of the informal sector by one percentage point today will increase the informal sector by about 0.185 percentage points in the following year. The results from time dummies also indicate that the size of the informal sector in Africa started to grow significantly during the financial crisis period in 2009. The main implication of these findings is that African countries can target one of the two in order to reduce both the size of the underground economy and corruption. The other implication is that a policy that targets curing one of the problems will have positive external effects in curing the other unintended problem. Furthermore, the findings imply that African countries with large underground economies may continue to experience growing informal economies due to lack of regulatory capacity and weak enforcement. Solving the two problems is a double hurdle for African countries. / Economics / D. Com. (Economics)

Dans le but de faire face aux défis interdépendants en termes d’épuisement des ressources énergétiques, de dégradation environnementale et des préoccupations de santé publique dans le contexte chinois en réponse au développement durable, nous nous concentrons sur l'étude des politiques en matière d’énergie, d’environnement et de santé en Chine. Dans le chapitre 1, nous donnons un aperçu des politiques chinoises en matière d’énergie, d’environnement et de santé au cours des 20 dernières années afin de connaître les orientations politiques futures auxquelles le gouvernement n'a pas donné une attention suffisante. Dans les trois chapitres suivants, nous proposons une série d'études empiriques afin de tirer quelques implications politiques utiles. Dans le chapitre 2, nous étudions l'impact de l'urbanisation, de l'adaptation de la structure industrielle, du prix de l'énergie et de l'exportation sur les intensités énergétiques agrégés et désagrégés des provinces. Dans le chapitre 3, nous étudions les facteurs qui expliquent la transition énergétique vers des combustibles propres des ménages ruraux. Dans le chapitre 4, nous examinons les effets conjoints des risques environnementaux, du revenu individuel, des politiques de santé sur l'état de santé des adultes chinois. En particulier, nos résultats empiriques suggèrent d’intégrer le développement urbain dans la stratégie d'économies d'énergie; de considérer des substitutions/complémentarités complexes parmi les sources d'énergie et entre l'énergie et l’alimentation pour les ménages ruraux; d’aligner les politiques environnementales, énergétiques et alimentaires avec les politiques de santé. / With the purpose of coping with the intertwined challenges of energy depletion, environmental degradation and public health concerns in the Chinese-specific context in response to sustainable development, we focus on investigating China’s energy, environment and health policies. In chapter 1, we provide an overview of China’s energy, environment and health policies over the past 20 years in order to know about the future policy directions to which the government has not given a sufficient attention. In the following three chapters, we provide a series of empirical studies so as to derive some useful policy implications. In chapter 2, we investigate the impact of urbanization, industrial structure adjustment, energy price and export on provincial aggregate and disaggregate energy intensities. In chapter 3, we study the factors explaining the switches from dirty to clean fuel sources in rural households. In chapter 4, we examine the joint effects of environmental hazards, individual income and health policies on the health status of Chinese adults. Our empirical findings particularly suggest integrating urban development into the strategy of energy saving; considering the complex substitutions/complementarities among energy sources and between energy and food for rural households; aligning the environment, energy and food policies with health policies.

La plupart des études en gestion sur la performance des entreprises sont centréessur l'explication de la relation entre les facteurs internes ou des caractéristiquesintrinsèques de l'entreprise (niveau d'endettement, diversification des produits, lastratégie concurrentielle, etc.) et son performance. Cette thèse vise à déterminerquels sont les facteurs de risque exogènes qui ont un impact sur la performance desentreprises en République Dominicaine? Ces facteurs, affectent-ils différemment lesmicro, petites et moyennes entreprises en fonction de leur secteur d'activité. Quelest le risque pour chacun des plus représentatifs sous-secteurs des entreprisesDominicaines? Nous avons constaté que les facteurs de risque les plusstatistiquement significatifs sont les dépenses de consommation des ménages, letaux d'intérêt des banques commerciales, l'investissement total, le taux de changede DOP à USD et le déficit de la balance commerciale. La composition etl'importance des facteurs varient considérablement en fonction de la taille desentreprises et le sous-secteur auquel ils appartiennent. Les grandes entreprises sonten moyenne moins risqué que des moyennes, petites et micro entreprises, n’importequel que soit le sous-secteur auquel ils appartiennent. / Many of the management studies on the performance of the company are focusedon explaining the relationship between the internal factors or intrinsic characteristicsof the firm (debt level, diversification of products, competitive strategy, etc.) and itsperformance. This thesis seeks to determine, what are the exogenous risk factorsthat impact the performance of all companies in the Dominican Republic? Thesefactors differentially affect the micro, small and medium enterprises according to theirbusiness sector. What is the risk on each of the most representative sub-sectors ofthe Dominican companies? We found that the most statistically significant riskfactors are the household consumption expenditure, the interest rate of commercialbanks, the total investment, the DOP to USD exchange rate and the deficit on thetrade balance. The composition and importance of the factors significantly variesdepending on the size of the company and the sub-sector to which it belongs. Also,large firms are on average less risky than medium, small and micro regardless of thesub-sector they belong. / Muchos de los estudios de gestión sobre el performance de la empresa se enfocanen explicar la relación que existe entre los factores o características intrínsecas de laempresa (nivel de endeudamiento, diversificación de productos, estrategiacompetitiva, etc.) y el performance de la misma. Esta tesis busca determinar¿cuáles son los factores exógenos de riesgo que impactan el performance de lasempresas de la República Dominicana? Si estos factores afectan de forma diferentea la micro, pequeña y mediana empresa según su actividad empresarial. ¿Cuál es elriesgo que tiene cada uno de los sub-sectores más representativos de las empresasdominicanas? Encontramos que los factores de riesgo estadísticamente mássignificativos son el consumo de los hogares, la tasa de interés de los bancoscomerciales, la inversión total, la tasa de cambio de DOP a USD y el déficit en labalanza comercial. La importancia y composición de los factores varíasignificativamente según el tamaño de la empresa y el sub-sector al que pertenece.También, en promedio, las empresas grandes tienen menos riesgos que lasmedianas, pequeñas y micro sin importar al sub-sector que pertenezcan.