We analyze how the impact of a change in the sovereign debt-to-GDP ratio on economic growth depends on the level of debt, the stress level on the financial market and the membership in a monetary union. A dynamic growth model is put forward demonstrating that debt affects macroeconomic activity in a non-linear manner due to amplifications from the financial sector. Employing dynamic country-specific and dynamic panel threshold regression methods, we study the non-linear relation between the growth rate and the debt-to-GDP ratio using quarterly data for sixteen industrialized countries for the period 1981Q1-2013Q2. We find that the debt-to-GDP ratio has impaired economic growth primarily during times of high financial stress and only for countries of the European Monetary Union and not for the stand-alone countries in our sample. A high debt-to-GDP ratio by itself does not seem to necessarily negatively affect growth if financial markets are calm. (authors' abstract)

This thesis is concerned with volatility estimation using financial panels and bias-reduction in non-linear dynamic panels in the presence of dependence. Traditional GARCH-type volatility models require large time-series for accurate estimation. This makes it impossible to analyse some interesting datasets which do not have a large enough history of observations. This study contributes to the literature by introducing the GARCH Panel model, which exploits both time-series and cross-section information, in order to make up for this lack of time-series variation. It is shown that this approach leads to gains both in- and out-of-sample, but suffers from the well-known incidental parameter issue and therefore, cannot deal with short data either. As a response, a bias-correction approach valid for a general variety of models beyond GARCH is proposed. This extends the analytical bias-reduction literature to cross-section dependence and is a theoretical contribution to the panel data literature. In the final chapter, these two contributions are combined in order to develop a new approach to volatility estimation in short panels. Simulation analysis reveals that this approach is capable of removing a substantial portion of the bias even when only 150-200 observations are available. This is in stark contrast with the standard methods which require 1,000-1,500 observations for accurate estimation. This approach is used to model monthly hedge fund volatility, which is another novel contribution, as it has hitherto been impossible to analyse hedge fund volatility, due to their typically short histories. The analysis reveals that hedge funds exhibit variation in their volatility characteristics both across and within investment strategies. Moreover, the sample distributions of fund volatilities are asymmetric, have large right tails and react to major economic events such as the recent credit crunch episode.

The thesis aims at identifying the reasons behind the heterogeneous inflation performance of countries across Central and Eastern Europe. The impact of a large number of variables is being assessed in a dynamic panel data model covering 20 countries over the period 2003-2013. The empirical results suggest that cross-country differences in inflation are attributed to the structure of the economy, to the capital deepening effects and openness. Along with the structural factors, cyclical positions also prove to be of particular importance in explaining inflation across the region, since during the last decade most of the Central and Eastern European countries have experienced fast GDP growth, a credit boom and increased domestic demand that in turn fueled inflation.

Recentemente, importantes questionamentos emergiram na literatura sobre repasse cambial. Mais especificamente, foi dada crescente atenção à hipótese de Taylor (2000) de que o pass-through se reduziu em diversos países como conseqüência do ambiente de inflação mais baixa. Esta dissertação investiga o tema através da aplicação de painéis dinâmicos para um conjunto de economias desenvolvidas. Deste modo, são estimados modelos de efeito fixo e Arellano-Bond em janelas fixas (rolling windows), que apontam para uma redução substancial na transmissão do câmbio para a inflação. A análise de potenciais determinantes macroeconômicos dessa queda indica que o ambiente inflacionário foi o principal elemento por trás do fato, sobretudo nos anos oitenta e noventa, em que o processo de desinflação foi mais intenso. Por outro lado, os anos dois mil apresentam um coeficiente de pass-through bastante baixo e estável, visto que o cenário de inflação baixa já estava consolidado para o conjunto de economias analisadas. / Recently, economists have become more interested in studying exchange rate pass-through. More specifically, increasing attention has been given to Taylors (2000) hypothesis that the passthrough has declined in several countries as a result of a lower inflation environment. This dissertation examines this issue through the application of dynamic panels for a number of developed economies. Panel data models are estimated here using fixed effects and Arellano- Bond estimators in rolling windows. The results point to a substantial reduction in the transmission of exchange rate to inflation. The analysis of potential macroeconomic determinants of this decline indicates that the inflationary environment was the main factor behind this fact, mainly in the eighties and nineties when the disinflation process was more intense worldwide. On the other hand, in the first decade of this century the pass-through coefficient was fairly low and stable, perhaps because the scenario of low inflation was already a longstanding reality to the economies analyzed in the present study.

In this thesis, I investigate economic and policy implications of corporate debt financing. In the first chapter, I examine whether or not leverage has a negative effect on corporate investment due to a debt overhang problem. Existing empirical studies face a challenging endogeneity problem inherent in the investment-leverage relationship, the source of which is the firm's anticipation of its growth opportunities. I develop a novel approach to control for this problem by using analysts' earnings forecasts as an anticipation measure. I show that anticipations influence the investment-leverage relationship in that firms that do anticipate future growth opportunities suffer less from debt overhang. In the second chapter, I extend Chapter One's analysis to a dynamic setting. I first establish that there is a stable long-term relationship between investment and leverage, and then disentangle the short-term dynamics of leverage and investment and find that the deviation of leverage from its benchmark path has a negative impact on the change in investment. I also employ dynamic panel models to estimate the causal dynamic effects of leverage on investment. The estimations show that the impact is negative for recent leverage, but positive for leverage in the more distant past. Also, the effects of leverage are attenuated when the investment uncertainties are further controlled. This suggests that the firm's response to investment uncertainties might explain dynamic effects of leverage on investment. In Chapter Three, I investigate the effects of the U.S. Chapter 11 bankruptcy-reorganization law on firm operating performance, and adopt matching methods to account for self-selection and heterogeneity in firms' pre-filing characteristics. Matching methods entail the selection of a control group of non-bankrupt firms that are comparable to Chapter 11 filing firms in a wide range of pre-filing characteristics that affect filing decisions. Comparing the operating performances of the two groups, I find that filing firms' net cash flows, but not operating incomes, improve significantly during bankruptcy. Furthermore, firms reduce their leverage levels and incur lower interest expenses after bankruptcy. The results suggest that the reduction in interest expenses contributes to the improvement in firms' net cash flows during bankruptcy.

This dissertation evaluates the empirical relation between the value-added tax (VAT) and the level of aggregate consumption. Furthermore, it develops a theoretical framework and an empirical analysis to study the impact of the VAT, as a form of taxing consumption, on capital accumulation, productivity growth, and overall economic growth. While recent theoretical work shows that the VAT may boost capital accumulation and growth by encouraging more savings, we find that the net impact of consumption taxes on growth and its sources is theoretically ambiguous, and depends on the interaction between utility parameters, the interest rate, and the tax structure. Moreover, we develop a theoretical model to study the tax design problem in order to rationalize the observed variation in effective VAT rates over time in our sample. This framework considers both equity and efficiency as important factors determining optimal tax structure, and we identify conditions under which taxes could be evolving or constant over time. Empirically, we use a panel of 15 European Union countries and employ the recently developed GMM dynamic panel techniques. After controlling for the potential biases associated with persistence, endogeneity, simultaneity, measurement error, omitted variables, and unobserved country-specific effects, we find that (i) the VAT exerts a negative impact on the level of aggregate consumption, (ii) the VAT affects physical capital accumulation positively, which feeds through to overall GDP growth, and (iii) productivity growth seems to be a less relevant channel for the VAT to influence economic growth.

In this thesis, I investigate economic and policy implications of corporate debt financing. In the first chapter, I examine whether or not leverage has a negative effect on corporate investment due to a debt overhang problem. Existing empirical studies face a challenging endogeneity problem inherent in the investment-leverage relationship, the source of which is the firm's anticipation of its growth opportunities. I develop a novel approach to control for this problem by using analysts' earnings forecasts as an anticipation measure. I show that anticipations influence the investment-leverage relationship in that firms that do anticipate future growth opportunities suffer less from debt overhang. In the second chapter, I extend Chapter One's analysis to a dynamic setting. I first establish that there is a stable long-term relationship between investment and leverage, and then disentangle the short-term dynamics of leverage and investment and find that the deviation of leverage from its benchmark path has a negative impact on the change in investment. I also employ dynamic panel models to estimate the causal dynamic effects of leverage on investment. The estimations show that the impact is negative for recent leverage, but positive for leverage in the more distant past. Also, the effects of leverage are attenuated when the investment uncertainties are further controlled. This suggests that the firm's response to investment uncertainties might explain dynamic effects of leverage on investment. In Chapter Three, I investigate the effects of the U.S. Chapter 11 bankruptcy-reorganization law on firm operating performance, and adopt matching methods to account for self-selection and heterogeneity in firms' pre-filing characteristics. Matching methods entail the selection of a control group of non-bankrupt firms that are comparable to Chapter 11 filing firms in a wide range of pre-filing characteristics that affect filing decisions. Comparing the operating performances of the two groups, I find that filing firms' net cash flows, but not operating incomes, improve significantly during bankruptcy. Furthermore, firms reduce their leverage levels and incur lower interest expenses after bankruptcy. The results suggest that the reduction in interest expenses contributes to the improvement in firms' net cash flows during bankruptcy.

This thesis explores the impact of sectoral competition on inflation in Turkey. To this end, panel data analyses investigating the determinants of deviation of sectoral price inflation from the consumer price inflation, and the resulting effect of the changes in the level of sectoral competition on this deviation measure are conducted in both static and dynamic frameworks. The empirical analyses covers the 1995-2001 period and 62 manufacturing sectors classified according to International Standard of Industrial Classification (ISIC) Rev. 2 at 4-digit level. The findings of the empirical analyses are particularly important for the assessment of the theoretical foundations and empirical basis of the recent proposals favoring enhancement of competition with disinflationary motives. The static analyses suggest that sectoral concentration is insignificant in explaining deviations of sectoral inflation from consumer inflation, while dynamic analyses suggest enhancing competition may lead to higher levels of sectoral inflation. The interpretation of the results indicates that enhancing competition may not be a viable tool for disinflationary purposes in Turkey.

In this dissertation we proposed two generalizations of the Second-Order Least Squares (SLS) approach in two popular dynamic econometrics models. The first one is the regression model with time varying nonlinear mean function and autoregressive conditionally heteroskedastic (ARCH) disturbances. The second one is a linear dynamic panel data model. We used a semiparametric framework in both models where the SLS approach is based only on the first two conditional moments of response variable given the explanatory variables. There is no need to specify the distribution of the error components in both models. For the ARCH model under the assumption of strong-mixing process with finite moments of some order, we established the strong consistency and asymptotic normality of the SLS estimator. It is shown that the optimal SLS estimator, which makes use of the additional information inherent in the conditional skewness and kurtosis of the process, is superior to the commonly used quasi-MLE, and the efficiency gain is significant when the underlying distribution is asymmetric. Moreover, our large scale simulation studies showed that the optimal SLSE behaves better than the corresponding estimating function estimator in finite sample situation. The practical usefulness of the optimal SLSE was tested by an empirical example on the U.K. Inflation. For the linear dynamic panel data model, we showed that the SLS estimator is consistent and asymptotically normal for large N and finite T under fairly general regularity conditions. Moreover, we showed that the optimal SLS estimator reaches a semiparametric efficiency bound. A specification test was developed for the first time to be used whenever the SLS is applied to real data. Our Monte Carlo simulations showed that the optimal SLS estimator performs satisfactorily in finite sample situations compared to the first-differenced GMM and the random effects pseudo ML estimators. The results apply under stationary/nonstationary process and wih/out exogenous regressors. The performance of the optimal SLS is robust under near-unit root case. Finally, the practical usefulness of the optimal SLSE was examined by an empirical study on the U.S. airfares.

This paper discusses capital structure theories, with special attention to partial-adjustment model. Strategic waiting theory of IPO firms and its relation to market timing theory are also discussed. Two empirical tests related to capital structure theory are included. First one is a test on the relation between a firm’s strategic waiting behavior in IPO market and its stock return. Second one is on the relation of a firm’s strategic waiting behavior in IPO market and its subsequent capital structure decision.