This study aims to investigate the direction of the relationship between financial deepening and economic growth after the completion of financial liberalization in Turkey. In order to do this, an unbalanced panel data set of 49 OECD and emerging countries for 1953-2005 period is examined with Granger causality and panel data estimation techniques. In the light of panel data analysis results, quarterly Turkish time series data for 1987-2006 period is examined by using Granger causality, cointegration and Vector Error Correction Model (VECM) procedures. Although the unbalanced panel data analysis reveals a relationship that is from financial deepening to economic growth, country specific Granger causality analysis employed with the panel data gives the opposite relationship for Turkey. Moreover, it is observed that quarterly time series data analysis mainly gives a relationship that is from economic growth to financial deepening.

In the first part of this thesis the prices of six non-ferrous metals (aluminum, copper, lead, nickel, tin, and zinc) are used to assess the forecasting performance of GARCH models. We find that the forecasting performances of GARCH, EGARCH, and TGARCH models are similar. However, we suggest the use of the GARCH model because it is more parsimonious and has a slightly better statistical performance than the other two. In the second part, the prices of six non-ferrous metals and the price of crude oil are used to examine the dynamic links between oil and metal returns by using the BEKK specification of the multivariate GARCH model and the Granger causality-in-variance tests. Results of our study agree with the previous studies in that the crude oil market volatility leads all non-ferrous metal markets. In order to move as far away from the effects of 9/11, daily data for the period December 12, 2003 &ndash / December 15, 2008 is used for the data analysis part of the thesis.

This study is concerned with the lead-lag relationship between Turkish spot equity and derivatives markets. In the study, the spot equity market is represented by the ISE-30 Index. In order to compare the structure of the two markets, the futures contract written on the ISE-30 Index, namely TURKDEX-ISE 30, is chosen to represent the derivatives market. The analysis is performed over the sample period beginning February 4, 2005 and ending on December 10, 2010 which actually covers the entire time span from the establishment of the TURKDEX market until the end of last year. This sample period is examined on the basis of 5-minute intervals during the trading day, enabling a more detailed and accurate evaluation of the lead-lag power of the markets. The main methods applied to examine the structure of information flow between the markets are co-integration and causality analyses. Different approaches of these basic methods are employed as well in order to provide robust results. An additional robustness check is provided through examining the relationship between the markets by using both raw and filtered prices. ARMA filtering is performed on the prices and these findings are compared to those obtained by raw prices in order to avoid the problem of infrequent trading. Outcomes of both raw and filtered price analyses reveal that in 2006, 2007 and 2009 the relationship between the markets is bi-directional, whereas in 2008 and 2010, futures market strictly leads the spot market. Filtered and raw analyses do not have a definitive conclusion regarding the lead-lag relationship in 2005. For this year, while the raw data support a bi-directional relationship, ARMA filtering indicates that the spot market leads the derivatives market.

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The performance of Internet-based services depends on many server-side, client-side, and network related factors. Often, the interaction among the factors or their effect on service performance is not known or well-understood. The complexity of these services makes it difficult to develop analytical models. Lack of models impedes network management tasks, such as predicting performance while planning for changes to service infrastructure, or diagnosing causes of poor performance. We posit that we can use statistical causal methods to model performance for Internet-based services and facilitate performance related network management tasks. Internet-based services are well-suited for statistical learning because the inherent variability in many factors that affect performance allows us to collect comprehensive datasets that cover service performance under a wide variety of conditions. These conditional distributions represent the functions that govern service performance and dependencies that are inherent in the service infrastructure. These functions and dependencies are accurate and can be used in lieu of analytical models to reason about system performance, such as predicting performance of a service when changing some factors, finding causes of poor performance, or isolating contribution of individual factors in observed performance. We present three systems, What-if Scenario Evaluator (WISE), How to Improve Performance (HIP), and Network Access Neutrality Observatory (NANO), that use statistical causal methods to facilitate network management tasks. WISE predicts performance for what-if configurations and deployment questions for content distribution networks. For this, WISE learns the causal dependency structure among the latency-causing factors, and when one or more factors is changed, WISE estimates effect on other factors using the dependency structure. HIP extends WISE and uses the causal dependency structure to invert the performance function, find causes of poor performance, and help answers questions about how to improve performance or achieve performance goals. NANO uses causal inference to quantify the impact of discrimination policies of ISPs on service performance. NANO is the only tool to date for detecting destination-based discrimination techniques that ISPs may use. We have evaluated these tools by application to large-scale Internet-based services and by experiments on wide-area Internet. WISE is actively used at Google for predicting network-level and browser-level response time for Web search for new datacenter deployments. We have used HIP to find causes of high-latency Web search transactions in Google, and identified many cases where high-latency transactions can be significantly mitigated with simple infrastructure changes. We have evaluated NANO using experiments on wide-area Internet and also made the tool publicly available to recruit users and deploy NANO at a global scale.

自2002年，澳門政府開放賭權後，博彩業成為澳門重要的經濟命脈，伴隨著澳門經濟迅速發展，澳門住宅價格亦因此高速飛漲。故此，本研究係以澳門為主要研究對象，探討自澳門政府批出三份博彩經營權後，總體經濟、博彩業與澳門主住宅市間之關係。選取二零零一年第一季至二零一四年第四季之季資料，運用單根檢定、因果關係檢定與共整合檢定等研究方法進行實證分析，檢定變數間的因果關係是否有長短期均衡關係與是否有領先落後的效果。 根據實證結果顯示，存款利率、外來投資金額、外地僱員及飯店入住率領先住宅價格之變動，所得及博彩稅收與住宅價格則呈現雙向因果關係，而外來投資金額、外地僱員、飯店入住率皆屬於博彩旅遊相關之變數，顯示博彩業蓬勃發展能推動澳門住宅價格，使房價高漲。此外，博彩稅收、外來投資金額、外地僱員及飯店入住率皆對所得具有單向影響，故此，可推斷博彩業開放後為澳門帶來巨大的經濟衝擊。另一方面，澳門經濟發展高度依賴博彩業，中小企業亦因租金持續高漲、人力資源短缺等問題，面臨極大的成本壓力，嚴重排擠中小企業生存空間。 / In the year of 2002, after the gambling are allowing by the government in Macau, gambling has already become a pillar industry. Accompanying with the rapid development of economy, housing price has risen at high speed in Macau. Therefore, this paper aims to investigate the research of interactive relationship between the real estate market, macroeconomic and gambling industry variables on the basis of Granger causality test since the gambling concession was granted out to three companies. Our sample period starts from Q1 of 2001 to Q4 of 2014 with quarterly data. The research uses ADF Test, Granger Causality Test, and Cointegration Test model that we verify the relationship between macroeconomic variables and the real estate prices. The paper hopes to find out that whether the long-term steady changes between the real estate market and macroeconomic variables will be a leading or lagging effect. The empirical result shows that, deposits rate, foreign direct investment (FDI), non-resident workers (NRW) and hotel occupancy rate (HOR), are in the lead of variation of housing price, income and tax revenue from gaming presents a causal relationship with housing price. FDI, NRW and HOR belong to the variations of the gambling industry which reveal flourishing gambling industry cam promote the housing price in Macau. Moreover, tax revenue from gaming, FDI, NRW and HOR leads income. Thus, it can infer after the gambling are allowed, it brings a great impact on the economy in Macau. On the other hand, the economy of Macau too dependent on gambling. Medium-sized and small enterprises face lot of cost pressure such as the raising rent and short of hands, so that excluding vivo sphere of medium-sized and enterprises.

This dissertation consists of three essays that apply both economic theory and econometric methods to understand design and dynamics of institutions. In particular, it studies how institutions aggregate information and deal with uncertainty and attempts to derive implications for optimal institution design. Here is a brief summary of the essays. In many economic, political and social situations where the environment changes in a random fashion necessitating costly action we face a choice of both the timing of the action as well as choosing the optimal action. In particular, if the stochastic environment possesses the property that the next environmental change becomes either more or less likely as more time passes since the last change (in other words the hazard rate of environmental change is not constant over time), then the timing of the action takes on special importance. In the first essay, joint with Maxwell B Stinchcombe, we model and solve a dynamic decision problem in a semi-Markov environment. We find that if the arrival times for state changes do not follow a memoryless process, time since the last observed change of state, in addition to the current state, becomes a crucial variable in the decision. We characterize the optimal policy and the optimal timing of executing that policy in the differentiable case by a set of first order conditions of a relatively simple form. They show that both in the case of increasing and decreasing hazard rates, the optimal response may be to wait before executing a policy change. The intuitive explanation of the result has to do with the fact that waiting reveals information about the likelihood of the next change occurring, hence waiting is valuable when actions are costly. This result helps shed new light on the structure of optimal decisions in many interesting problems of institution design, including the fact that constitutions often have built-in delay mechanisms to slow the pace of legislative change. Our model results could be used to characterize optimal timing rules for constitutional amendments. The paper also contributes to generalize the methodology of semi-Markov decision theory by formulating a dynamic programming set-up that looks to solve the timing-of-action problem whereas the existing literature looks to optimize over a much more limited set of policies where the action can only be taken at the instant when the state changes. In the second essay, we extend our research to situations, where the current choice of action influences the future path of the stochastic process, and apply it to the legal framework surrounding environmental issues, particularly to the ‘Precautionary Principle' as applied to climate change legislation. We represent scientific uncertainty about environmental degradation using the concept of 'ambiguity' and show that ambiguity aversion generates a 'precautionary effect'. As a result, justification is provided for the Precautionary Principle that is different from the ones provided by expected utility theory. This essay serves both as an application of the general theoretical results derived in the first essay and also stands alone as an analysis of a substantive question about environmental law. Prediction markets have attracted public attention in recent years for making accurate predictions about election outcomes, product sales, film box office and myriad other variables of interest and many believe that they will soon become a very important decision support system in a wide variety of areas including governance, law and industry. For successful design of these markets, a thorough understanding of the theoretical and empirical foundations of such markets is necessary. But the information aggregation process in these markets is not fully understood yet. There remains a number of open questions. The third essay, joint with Robert Lieli, attempts to analyze the direction and timing of information flow between prices, polls, and media coverage of events traded on prediction markets. Specifically, we examine the race between Barack Obama and Hillary Clinton in the 2008 Democratic primaries for presidential nomination. Substantively, we ask the following question: (i) Do prediction market prices have information that is not reflected in viii contemporaneous polls and media stories? (ii) Conversely, do prices react to information that appears to be news for pollsters or is prominently featured by the media? Quantitatively, we construct time series variables that reflect the "pollster's surprise" in each primary election, measured as the difference between actual vote share and vote share predicted by the latest poll before the primary, as well as indices that describe the extent of media coverage received by the candidates. We carry out Granger Causality tests between the day-to-day percentage change in the price of the "Obama wins nomination" security and these information variables. Some key results from our exercise can be summarized as follows. There seems to be mutual (two-way) Granger causality between prediction market prices and the surprise element in the primaries. There is also evidence of one-way Granger causality in the short run from price changes towards media news indices. These results suggest that prediction market prices anticipate at least some of the discrepancy between the actual outcome and the latest round of polls before the election. Nevertheless, prices also seem to be driven partly by election results, suggesting that there is an element of the pollster’s surprise that is genuine news for the market as well. / text

In this paper we estimate the short-term and long-term relationship between stock prices and exchange rates for the sample of US and Asian markets during the period 2004 – 2014. Monetary variables include money supply, interest rates, foreign exchange rates, and the consumer price index. All the data are monthly indices and have been examined using multivariate co integration analysis and Granger causality analysis. The empirical analysis employed provides evidence of a positive co-integrating short- run relationship between these variable with Granger causality found to run from stock prices to the exchange rate during the sample period in Japan. For US, significant relationships were not been established. The results for Japan confirm the conclusion of other studies that stock returns are significant predictors of short – run exchange rate movements especially in period of financial crisis. We also apply LS model in order to estimate a linear regression. / Στην εργασία αυτή θα εκτιμηθεί η βραχυπρόθεσμη και μακροπρόθεσμη σχέση μεταξύ των τιμών των μετοχών και των συναλλαγματικών ισοτιμιών για το δείγμα των αμερικανικών και ασιατικών αγορών κατά την περίοδο 2004-2014. Νομισματικές μεταβλητές περιλαμβάνουν την προσφορά χρήματος, τα επιτόκια, τις συναλλαγματικές ισοτιμίες και τον δείκτη τιμών καταναλωτή. Όλα τα στοιχεία είναι μηνιαία και έχουν εξεταστεί σύμφωνα με πολυπαραγοντική ανάλυση και την ανάλυση της αιτιότητας. Η εμπειρική ανάλυση που χρησιμοποιείται παρέχει απόδειξη της θετικής σχέσης μεταξύ αυτών των μεταβλητών με Granger αιτιότητα από τις τιμές των μετοχών προς την συναλλαγματική ισοτιμία κατά τη διάρκεια της περιόδου του δείγματος στην Ιαπωνία. Για την Αμερική, σημαντικές σχέσεις δεν έχουν τεκμηριωθεί. Τα αποτελέσματα για την Ιαπωνία επιβεβαιώνουν το συμπέρασμα άλλων μελέτών ότι οι αποδόσεις των μετοχών είναι σημαντικοί παράγοντες πρόβλεψης των βραχυπροθεσμων διακυμανσεων των συναλλαγματικών ισοτιμιών,ιδίως σε περίοδο οικονομικής κρίσης. Μπορούμε επίσης να εφαρμόσουμε το μοντέλο LS, προκειμένου να εκτιμηθεί μια γραμμική παλινδρόμηση.

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La douleur est une expérience perceptive comportant de nombreuses dimensions. Ces dimensions de douleur sont inter-reliées et recrutent des réseaux neuronaux qui traitent les informations correspondantes. L’élucidation de l'architecture fonctionnelle qui supporte les différents aspects perceptifs de l'expérience est donc une étape fondamentale pour notre compréhension du rôle fonctionnel des différentes régions de la matrice cérébrale de la douleur dans les circuits corticaux qui sous tendent l'expérience subjective de la douleur. Parmi les diverses régions du cerveau impliquées dans le traitement de l'information nociceptive, le cortex somatosensoriel primaire et secondaire (S1 et S2) sont les principales régions généralement associées au traitement de l'aspect sensori-discriminatif de la douleur. Toutefois, l'organisation fonctionnelle dans ces régions somato-sensorielles n’est pas complètement claire et relativement peu d'études ont examiné directement l'intégration de l'information entre les régions somatiques sensorielles. Ainsi, plusieurs questions demeurent concernant la relation hiérarchique entre S1 et S2, ainsi que le rôle fonctionnel des connexions inter-hémisphériques des régions somatiques sensorielles homologues. De même, le traitement en série ou en parallèle au sein du système somatosensoriel constitue un autre élément de questionnement qui nécessite un examen plus approfondi. Le but de la présente étude était de tester un certain nombre d'hypothèses sur la causalité dans les interactions fonctionnelle entre S1 et S2, alors que les sujets recevaient des chocs électriques douloureux. Nous avons mis en place une méthode de modélisation de la connectivité, qui utilise une description de causalité de la dynamique du système, afin d'étudier les interactions entre les sites d'activation définie par un ensemble de données provenant d'une étude d'imagerie fonctionnelle. Notre paradigme est constitué de 3 session expérimentales en utilisant des chocs électriques à trois différents niveaux d’intensité, soit modérément douloureux (niveau 3), soit légèrement douloureux (niveau 2), soit complètement non douloureux (niveau 1). Par conséquent, notre paradigme nous a permis d'étudier comment l'intensité du stimulus est codé dans notre réseau d'intérêt, et comment la connectivité des différentes régions est modulée dans les conditions de stimulation différentes. Nos résultats sont en faveur du mode sériel de traitement de l’information somatosensorielle nociceptive avec un apport prédominant de la voie thalamocorticale vers S1 controlatérale au site de stimulation. Nos résultats impliquent que l'information se propage de S1 controlatéral à travers notre réseau d'intérêt composé des cortex S1 bilatéraux et S2. Notre analyse indique que la connexion S1→S2 est renforcée par la douleur, ce qui suggère que S2 est plus élevé dans la hiérarchie du traitement de la douleur que S1, conformément aux conclusions précédentes neurophysiologiques et de magnétoencéphalographie. Enfin, notre analyse fournit des preuves de l'entrée de l'information somatosensorielle dans l'hémisphère controlatéral au côté de stimulation, avec des connexions inter-hémisphériques responsable du transfert de l'information à l'hémisphère ipsilatéral. / Pain is a perceptual experience comprising many dimensions. These pain dimensions interrelate with each other and recruit neuronal networks that process the corresponding information. Elucidating the functional architecture that supports different perceptual aspects of the experience is thus, a fundamental step to our understanding of the functional role of different regions in the cerebral pain matrix that are involved in the cortical circuitry underlying the subjective experience of pain. Among various brain regions involved in the processing of nociceptive information, primary and secondary somatosensory cortices (S1 and S2) are the main areas generally associated with the processing of sensory-discriminative aspect of pain. However the functional organization in these somatosensory areas is not completely clear and relatively few studies have directly examined the integration of information among somatic sensory regions. Thus, several questions remain regarding the hierarchical relationship between S1 and S2, as well as the functional role of the inter-hemispheric connections of the homologous somatic sensory areas. Likewise, the question of serial or parallel processing within the somatosensory system is another questionable issue that requires further investigation. The purpose of the present study was to test a number of causal hypotheses regarding the functional interactions between S1 and S2, while subjects were receiving painful electric shocks. We implemented a connectivity modeling approach, which utilizes a causal description of system dynamics, in order to study the interactions among activation sites defined by a data set derived from a functional imaging study. Our paradigm consists of 3 experimental scans using electric shock stimuli, with the stimulus intensity changing from moderately painful (level 3), to slightly painful (level 2), and to completely non-painful (level 1) during the final scan. Therefore our paradigm allowed us to investigate how stimulus intensity is encoded within our network of interest, and how the connectivity of the different regions is modulated across the different stimulus conditions. Our result is in favor of serial mode of somatosensory processing with thalamocortical input to S1 contralateral to stimulation site. Thus our results implicates that pain information is propogated from S1 contralateral through our network of interest comprising of bilateral S1 and S2. Our analysis indicates that S1→S2 connection is modulated by pain, which suggests that S2 is higher on the hierarchy of pain processing than S1, in accordance with previous neurophysiological and MEG findings. Lastly, our analysis provides evidence for the entrance of somatosensory information into the hemisphere contralateral to the stimulation side, with inter-hemispheric connections responsible for the transfer of information to the ipsilateral hemisphere.