This thesis provides four contributions to the literature on the productivity- internationalization nexus by considering some recent developments in the literature. A well-established stylized fact is reported by this literature, which is that exporters are more productive and larger than non-exporters, and two hypotheses attempt to explain this finding. The first, often referred to as the self-selection hypothesis, suggests that more productive firms select themselves into export markets, while the learning-by-exporting hypothesis highlights the role of learning from exporting. In this thesis, first, the self-selection hypothesis is revisited, and it is shown that evidence against self-selection exists in some UK industries. Second, it is demon- strated that some UK firms experience rising marginal costs, although both tra- ditional and new trade theories assume constant marginal cost. It is then shown that the evidence against self-selection that we report can be best explained by the existence of increasing, rather than constant, marginal costs. Third, the learning by exporting hypothesis is tested empirically for UK firms. Highlighting the importance of the scale effect in total factor productivity growth, it is shown that any learning by exporting effects are predominantly attributable to a change in scale efficiency. Unlike Melitz (2003), some recent studies consider some other strategies to access foreign markets, such as foreign direct investment, and cross-border mergers. Finally, following this new branch of the literature, the productivity-internationalization nexus is examined by utilizing a two-country oligopolistic model. It is shown that more productive firm might prefer greenfield investment over cross-border merger, which contradicts the findings provided by the relevant literature.

This study examines empirically the transition, persistence, and loan demand in the rural credit market using panel data. The data was collected for seven rounds (1994-2009) from 15 villages in Ethiopia. The sample size is about 1500 households for each round. . Chapter one examines the determinants of simultaneous borrowing and lending. We also investigate why some households in rural Ethiopia simultaneously borrow and lend. Who are these households? Panel logit model is estimated for the sub-sample of borrowers and lenders. The result suggests that households that simultaneously borrows and lends are relatively better-off households. The probability of being a simultaneous borrower and lender is higher for households with strong village level networks. Moreover, households that are affected by common shock are more likely to be a simultaneous borrower and lender. Chapter two examines the dynamics and persistence in the rural credit markets in Ethiopia. It also examines the determinants of dynamics and persistence in borrowing and lending. Duration, dynamic probit, and dynamic multinomial logit models are estimated. We control for unobserved heterogeneity and initial condition. The result reveals the existence of positive duration dependence in both only borrowing households and simultaneously lending and borrowing households. The longer the duration as a borrower, the more likely to exit from borrowing. The longer the duration out of borrowing, the more likely to re-enter to borrowing. Off-farm work, fertilizer use, household size, and storing crop are an important determinant of the probability of exit from borrowing. There is also true state dependence in lending, borrowing, and simultaneously borrowing and lending households. This means the probability of being a borrower in the current period is highly correlated with being in the same state in the previous period. Poverty status, flood, labor sharing, membership in mutual help association, total oxen owned, storing crop, off-farm activities, and fertilizer use are an important determinant of the probability of being a borrower. Chapter three examines the determinants of demand for credit in rural Ethiopia. Bias due to data truncation, variation of the interest rate, and using loan data from a single source are the challenges in estimating demand for credit in the context of rural credit market. This study captures data truncation by estimating a panel Tobit model. The variation in the interest rate is also controlled by using village dummies and their interaction with the source of the loan. Total loan obtained from multiple sources is used as a dependent variable. The result reveals that initial endowment proxied by the value of assets, household size, the age of the head of the households, transitory income, and real per capita consumption are the most important determinants of demand for credit.

Connus sous le nom de Systèmes d’Alerte Avancés, ou Early Warning Systems (EWS), les modèles de prévision des crises financières sont appelés à jouer un rôle déterminant dans l’orientation des politiques économiques tant au niveau microéconomique qu’au niveau macroéconomique et international. Or,dans le sillage de la crise financière mondiale, des questions majeures se posent sur leur réelle capacité prédictive. Deux principales problématiques émergent dans le cadre de cette littérature : comment évaluer les capacités prédictives des EWS et comment les améliorer ?Cette thèse d’économétrie appliquée vise à proposer (i) une méthode d’évaluation systématique des capacités prédictives des EWS et (ii) de nouvelles spécifications d’EWS visant à améliorer leurs performances. Ce travail comporte quatre chapitres. Le premier propose un test original d’évaluation des prévisions par intervalles de confiance fondé sur l’hypothèse de distribution binomiale du processus de violations. Le deuxième chapitre propose une stratégie d’évaluation économétrique des capacités prédictives des EWS. Nous montrons que cette évaluation doit être fondée sur la détermination d’un seuil optimal sur les probabilités prévues d’apparition des crises ainsi que sur la comparaison des modèles.Le troisième chapitre révèle que la dynamique des crises (la persistance) est un élément essentiel de la spécification économétrique des EWS. Les résultats montrent en particulier que les modèles de type logit dynamiques présentent de bien meilleurs capacités prédictives que les modèles statiques et que les modèles de type Markoviens. Enfin, dans le quatrième chapitre nous proposons un modèle original de type probit dynamique multivarié qui permet d’analyser les schémas de causalité intervenant entre différents types crises (bancaires, de change et de dette). L’illustration empirique montre clairement que le passage à une modélisation trivariée améliore sensiblement les prévisions pour les pays qui connaissent les trois types de crises. / Known as Early Warning Systems (EWS), financial crises forecasting models play a key role in definingeconomic policies at microeconomic, macroeconomic and international level. However, in the wake ofthe global financial crisis, numerous questions with respect to their forecasting abilities have been raised,as very few signals were drawn prior to the starting of the turmoil. Two questions arise in this context:how to evaluate EWS forecasting abilities and how to improve them?The broad goal of this applied econometrics dissertation is hence (i) to propose a systematic model-free evaluation methodology for the forecasting abilities of EWS as well as (ii) to introduce new EWSspecifications with improved out-of-sample performance. This work has been concretized in four chapters.The first chapter introduces a new approach to evaluate interval forecasts which relies on the binomialdistributional assumption of the violations series. The second chapter proposes an econometric evaluationmethodology of the forecasting abilities of an EWS. We show that adequate evaluation must take intoaccount the cut-off both in the optimal crisis forecast step and in the model comparison step. The thirdchapter points out that crisis dynamics (persistence) is essential for the econometric specification of anEWS. Indeed, dynamic logit models lead to better out-of-sample forecasting probabilities than those oftheir main competitors (static model and Markov-switching one). Finally, a multivariate dynamic probitEWS is proposed in the fourth chapter to take into account the causality between different types of crises(banking, currency, sovereign debt). The empirical application shows that the trivariate model improvesforecasts for countries that underwent the three types of crises.