Both the ECB and the Fed implemented various unconventional measures in response to the last crisis. While the ECB's policies were based on direct lending to banks, the FED adopted large-scale asset purchases. According to the empirical evidence these policies had economically beneficial effects in the US and the Eurozone but these measures have also certain spillovers which scope and exact impacts are quite difficult to estimate. There have been already many papers focusing on cross-border impacts of the FED's policies, but far less studied the spillovers of the ECB's policies. This work provides a theoretical background concerning the unconventional monetary policies implemented by the ECB and the FED after 2008 and analyse the impacts of ECB's policies on six particular countries outside euro area. The Impulse Responses of output, inflation, domestic interest rate and exchange rate are analyzed via block-restricted VAR model. My results confirm that euro area monetary policy does have an impact on non-euro area countries, although the response of macroeconomic variables in analysed countries are heterogeneous and also differ in the period before and after September 2008. Countries seem to be indeed affected more by conventional monetary policies until September 2008, but the euro-area monetary policy spills over via unconventional policies after September 2008. Overall, the ECB's policies affect economic activity outside euro area, but does not have significant impact on inflation. Furthermore, the exchange rate just initially drops in response to monetary tightening, but this reaction usually does not last for more than four months.

This paper investigates the role of credit market sentiments and investor beliefs on credit cycle dynamics and their propagation to business cycle fluctuations. Using US data from 1968 to 2019, we show that credit market sentiments are indeed able to detect asymmetries in a small-scale macroeconomic model. By exploiting recent developments in behavioral finance on expectation formation in financial markets, we are able to identify an unexpected credit market news shock exhibiting different impacts in an optimistic and pessimistic credit market environment. While an unexpected movement in the optimistic regime leads to a rather low to muted impact on output and credit, we find a significant and persistent negative impact on those variables in the pessimistic regime. Therefore, this article departs from the current literature on the role of financial frictions for explaining business cycle behavior in macroeconomics and argues in line with recent theoretical contributions on the relevance of expectation formation and beliefs as source of cyclicity and instability in financial markets. / Series: Department of Economics Working Paper Series

This study aims to estimate the ratio of non-performing loans to total loans (NPL ratio), its determinants and its response to different macroeconomic shocks. As the last financial crises had negative impact on the economy of many countries of the world, we have to strive for preventive measures that would help us to fully or at least partly avoid future crises. It should be achieved by sound risk management practices of all financial institutions. Important part of these risk management practices shall be - among others - stress tests that would test the health of the institution under severe conditions and negative shocks. For this study the vector autoregression model (VAR methodology) is used to see the response of credit risk (in terms of NPL ratio) to macroeconomic shocks in the Czech Republic. The variables used for this study are quarterly time series data of the period from 2002 to 2011 (GDP, inflation rate, unemployment rate, koruna exchange rate (CZK/USD), and interest rate). For each of these variables the impulse response function was created, to show the impact of macroeconomic shocks and the speed of adjustment of NPL ratio to these shocks. Keywords: Financial Crises, Credit Risk Management, Non-performing loans, Macroeconomic Shocks, Czech Republic, VARs

This thesis examines dynamic relationships between inflation and monetary policy in a sample of African economies using quarterly data over the period 1980:01 to 2012:04. The literature on inflation dynamics and monetary policy focuses on developed economies, with little attention devoted to the African economies, which is potentially explained by the fact that in the past monetary policy played second fiddle because of fiscal policy dominance following episodes of high inflation and stabilization policies that occurred in the 1980's. This thesis fills an important gap in assessing African's monetary policy. The thesis predominantly uses the Vector-Autoregression (VAR) framework to examine the monetary policy frameworks of the African economies. The thesis finds that an interest rate shock on average explain a more significant proportion of the variance in the output gap and inflation than the exchange rate, in terms of analysing the decomposition of shocks to the economy. This shows a shift in the monetary policy focus away from exchange rate management to interest rate targeting as the African economies have become more market oriented. The monetary policy reveal strong asymmetric responses with respect to the macroeconomic variables when inflation exceeds its threshold value. The analysis suggests that monetary policy in the African economies is regime-dependent, propagated through the inflation thresholds, such that the authorities strongly implement policy changes when inflation goes beyond a certain threshold. The thesis reveals that by taking into account the prior belief of the monetary authorities, it helps produce better estimates of the performance of the monetary policy transmission mechanism, as it combines prior information with the sampling information which is contained in the data. The overall novelty of the thesis is that some African economies are adopting inflation targeting policies instead of exchange rate management. It is imperative that the subsequent inflation targeting frameworks will achieve monetary policy objectives for the African economies and the use of interest rate management should be continued.

This thesis examines the effects of monetary policy shocks on the housing market. To this end, TVP-VAR model with dynamic dimension selection and stochastic volatility is estimated using monthly data for the United States over the period 1999-2017. Moreover, the model features estimating the optimal value of the Bayesian shrinkage coefficient in a time-varying manner. Since the sample covers the Zero Lower Bound period, Wu-Xia shadow rate is employed to measure the stance of monetary policy. To assess the link between housing variables and monetary policy, impulse responses and forecast error variance decompositions are provided. However, due to the time-varying nature of the model, they are estimated only for selected time periods that correspond both to the events that most likely influenced the path of macroeconomic and financial variables and to periods of low economic uncertainty. The main results are threefold. First, the model suggests that monetary policy shocks can contribute to developments in house prices. Second, the stimulative monetary policy positively affects residential investment and negatively affects mortgage rates, however, the effects are not significant due to the large confidence bands of the impulse responses. Third, higher values of the shrinkage hyperparameter are crucial for...

Depuis l’article séminal de Baks et Kramer (1999), le concept de la liquidité globale est souvent revenu au cœur de l’actualité, car les facteurs de son développement ont été considérés comme ayant indirectement participé aux développements des déséquilibres précédents la crise financière de 2008. Face à ces enjeux, la littérature s’est largement concentrée sur l’approche de la stabilité financière dans les pays émetteurs. Contrairement à cette approche, les recherches développées dans cette thèse se concentrent la perspective des pays destinataires de la liquidité globale, en particulier les pays émergents. Ainsi pour répondre à la problématique principale de l’identification des effets de reports de la liquidité globale, cette thèse propose une analyse en trois chapitres du phénomène. Premièrement, à travers une généralisation de l’analyse de la problématique de la stabilité financière dans les pays émergents. Deuxièmement, en analysant comment le comportement d’accumulation des pays destinataires affecte les conditions de la liquidité globale dans les pays émetteurs. Troisièmement, en analysant au niveau national le comportement des autorités monétaires pour prémunir leurs économies des effets de l’expansion de la liquidité globale. / Since the seminal paper by Baks and Kramer (1999), the concept of global liquidity catch once again the attention because the factors of its expansion are considered in the literature as having contributed to the development of vulnerabilities prior to the global financial crisis. Given the importance of global liquidity issues, the literature has largely focused on the financial stability approach in the issuing countries. Contrary to this approach, the research developed in this Ph.D. thesis relies principally on the receiving countries perspective, particularly the emerging countries. Accordingly, in order to answer our main problematic regarding the identification of global liquidity spillovers into the receiving countries, this thesis proposes a three chapters analysis of the phenomenon. First, we focus on a generalization of the financial stability concerns into the emerging countries. Second, we analyze how the reserve accumulation behavior in the receiving countries affects the global liquidity conditions in the main issuing country. Third, we center on the monetary authorities behavior in order to isolate their economies from the effects of the global liquidity expansion.

<p dir="ltr">In this thesis, we delve into the exploration of several nonparametric and semiparametric econometric models within the Bayesian framework, highlighting their applicability across a broad spectrum of microeconomic and macroeconomic issues. Positioned in the big data era, where data collection and storage expand at an unprecedented rate, the complexity of economic questions we aim to address is similarly escalating. This dual challenge ne- cessitates leveraging increasingly large datasets, thereby underscoring the critical need for designing flexible Bayesian priors and developing scalable, efficient algorithms tailored for high-dimensional datasets.</p><p dir="ltr">The initial two chapters, Chapter 2 and 3, are dedicated to crafting Bayesian priors suited for environments laden with a vast array of variables. These priors, alongside their corresponding algorithms, are optimized for computational efficiency, scalability to extensive datasets, and, ideally, distributability. We aim for these priors to accommodate varying levels of dataset sparsity. Chapter 2 assesses nonparametric additive models, employing a smoothing prior alongside a band matrix for each additive component. Utilizing the Bayesian backfitting algorithm significantly alleviates the computational load. In Chapter 3, we address multiple linear regression settings by adopting a flexible scale mixture of normal priors for coefficient parameters, thus allowing data-driven determination of the necessary amount of shrinkage. The use of a conjugate prior enables a closed-form solution for the posterior, markedly enhancing computational speed.</p><p dir="ltr">The subsequent chapters, Chapter 4 and 5, pivot towards time series dataset model- ing and Bayesian algorithms. A semiparametric modeling approach dissects the stochastic volatility in macro time series into persistent and transitory components, the latter addi- tional component addressing outliers. Utilizing a Dirichlet process mixture prior for the transitory part and a collapsed Gibbs sampling algorithm, we devise a method capable of efficiently processing over 10,000 observations and 200 variables. Chapter 4 introduces a simple univariate model, while Chapter 5 presents comprehensive Bayesian VARs. Our al- gorithms, more efficient and effective in managing outliers than existing ones, are adept at handling extensive macro datasets with hundreds of variables.</p>

Esta tesis se ocupa de los problemas de la estimación econométrica con muestras pequeñas, en los contextos del los VARs monetarios y de la investigación empírica del crecimiento. Primero, demuestra cómo mejorar el análisis con VAR estructural en presencia de muestra pequeña. El primer capítulo adapta la especificación con prior intercambiable (exchangeable prior) al contexto del VAR y obtiene nuevos resultados sobre la transmisión monetaria en nuevos miembros de la Unión Europea. El segundo capítulo propone un prior sobre las tasas de crecimiento iniciales de las variables modeladas. Este prior resulta en la corrección del sesgo clásico de la muestra pequeña en series temporales y reconcilia puntos de vista Bayesiano y clásico sobre la estimación de modelos de series temporales. El tercer capítulo estudia el efecto del error de medición de la renta nacional sobre resultados empíricos de crecimiento económico, y demuestra que los procedimientos econométricos robustos a incertidumbre acerca del modelo son muy sensibles al error de medición en los datos. / This thesis deals with the problems of econometric estimation with small samples, in the contexts of monetary VARs and growth empirics. First, it shows how to improve structural VAR analysis on short datasets. The first chapter adapts the exchangeable prior specification to the VAR context, and obtains new findings about monetary transmission in New Member States. The second chapter proposes a prior on initial growth rates of modeled variables, which tackles the Classical small-sample bias in time series, and reconciles Bayesian and Classical points of view on time series estimation. The third chapter studies the effect of measurement error in income data on growth empirics, and shows that econometric procedures which are robust to model uncertainty are very sensitive to measurement error of the plausible size and properties.

本研究之宗旨在於探究中國大陸對亞洲區域內國家的金融市場影響程度之變化。由過去的各國股市日報酬率資料間相關程度與政策改變間的影響結果，來觀察是否未來在兩岸政策更開放下會使中國大陸對台灣的影響程度上升，進而使國際間投資組合的風險分散效果下降。本研究自DataStream選取台灣、香港、中國大陸、泰國、印尼、新加坡、馬來西亞、菲律賓、日本以及美國等十國的股價指數日資料，以對數轉換為日報酬率後年化加以分析。選取時間自1991年7月15日(中國大陸上海證券交易所股價指數公開後)至2008年12月31日。本研究選用的方法為使用風險值(VaR; Value at Risk)的概念來取代傳統的標準差，衡量以該十國所分別組成的各投資組合風險值變動情形；以及由風險值所衍生出的Diversification Benefit與Incremental VaR的結果。發現到僅由亞洲區域國家內組成的投資組合風險分散效果逐漸下降；且效果並不如有納入區域外國家(如美國)的投資組合。接著本研究將Gaussian Copula模型放入VaR中以增加對極端值的捕捉能力，結果發現本研究所選用的指數加權移動平均法所求得之相關係數已可有效反應出各國之間的相依程度，即加入Copula的效果有限。另外藉由Copula所求得之相關係數顯示，台灣、香港對中國大陸之間的相依程度已逐漸上升，並開始出現超越美國之現象，其中又以2005年為上升趨勢的起點。最後本研究以向量自我迴歸模型(VARs)來驗證2005年前後中國大陸股市對其他亞洲區域國家的影響力是否存在結構性的改變；並再佐以變異數拆解之方法來觀察2005年前後各國家之間自發性衝擊對彼此之間的影響程度變化。研究結果發現，透過VARs可證明中國大陸對亞洲區域各國的影響力在2005年後轉變為顯著；僅對美國不存在此一現象。另外變異數拆解的結果也顯示各國之間的相依程度在2005年後有明顯的上升，中國大陸對各國的影響程度亦然。透過本研究之結論，在未來兩岸將簽訂金融監理備忘錄使整合關係提升的環境下，需提醒投資人整合關係的上升將使得以之為標的之投資組合風險分散效果下降，需作為投資策略之考量。 / The object of this research is to find out the trend of dependence and correlation between China and other Asian countries. Based on past information about the relationship between equity markets’ correlation and changes in policies, this research can make suggestions to the foreseeable future of Taiwan and China whose relationship will be more solid due to new policy. The data of this research are gathered from DataStream, which includes Taiwan, Hong Kong, China, Thailand, Indonesia, Singapore, Malaysia, Philippines, Japan and United States. Selected from 1991/07/15 (when the Shanghai SE Composite went public) to 2008/12/31, this research calculates the annualized daily return using natural logarithms of two consecutive daily index prices. This research uses Value at Risk (VaR) to measure the risk exposure of portfolios formed by ten countries, and extends to the use of Diversification Benefit and Incremental VaR. The results found out that the diversification effects of portfolio which includes only Asian countries are decreasing and inferior to the effects when cross region countries are included. The second study of this research is to combine Gaussian Copula Model with VaR to capture the effects of extreme values. Empirical results found out that the VaR using Exponentially Weighted Moving Average method is good enough for analyzing Asian stock markets. The correlation in Copula model suggests that the dependence between Taiwan and China had increased since 2005 and has the increasing trend which might overwhelm the dependence between Taiwan and United States. Final research is about using Vector Autoregressions Model (VARs) to testify is there exist any structural change of dependence before and after 2005, and using Variance Decomposition to observe the relationships between these ten countries. The results found out that there exist structural change in 2005, the post-2005 periods shows that for Asian countries the effect from China are significant and greater than pre-2005 periods.