Submitted by Ary Cera Zanetta Neto Zanetta (ary.zanetta@brasil-capital.com) on 2014-08-19T19:21:54Z No. of bitstreams: 1 Efeitos de Choques Globais na Economia Brasileira_ Uma Análise a Partir do GVAR.pdf: 1085836 bytes, checksum: 25e953aa352fed09b5b828362226aab9 (MD5) / Rejected by JOANA MARTORINI (joana.martorini@fgv.br), reason: A ficha catalográfica não está valida, por gentileza aguardar o envio da ficha correta pala biblioteca digital. on 2014-08-19T19:29:14Z (GMT) / Submitted by Ary Cera Zanetta Neto Zanetta (ary.zanetta@brasil-capital.com) on 2014-08-19T20:33:33Z No. of bitstreams: 1 Efeitos de Choques Globais na Economia Brasileira_ Uma Análise a Partir do GVAR.pdf: 1085836 bytes, checksum: 25e953aa352fed09b5b828362226aab9 (MD5) / Approved for entry into archive by JOANA MARTORINI (joana.martorini@fgv.br) on 2014-08-20T16:30:59Z (GMT) No. of bitstreams: 1 Efeitos de Choques Globais na Economia Brasileira_ Uma Análise a Partir do GVAR.pdf: 1085836 bytes, checksum: 25e953aa352fed09b5b828362226aab9 (MD5) / Made available in DSpace on 2014-08-20T19:02:31Z (GMT). No. of bitstreams: 1 Efeitos de Choques Globais na Economia Brasileira_ Uma Análise a Partir do GVAR.pdf: 1085836 bytes, checksum: 25e953aa352fed09b5b828362226aab9 (MD5) Previous issue date: 2014-08-05 / O objetivo deste estudo é avaliar a propagação de choques econômicos de alguns países sobre o crescimento econômico brasileiro, com principal destaque para China, Estados Unidos da América (EUA) e Argentina, que são os principais parceiros comerciais do Brasil. O aumento do comércio com a China tornou o Brasil muito mais vulnerável a choques no PIB chinês e menos vulnerável, do que no passado recente, a choques no PIB americano, enquanto que a influência da Argentina manteve-se estável. Foi aplicada a metodologia Vetor Autorregressivo Global (Global Var – GVAR), introduzida por Pesaran, Schuermann e Weiner (2004), Garratt, Lee, Pesaran e Shin (2006) e Dées, Di Mauro, Pesaran e Smith (2007), para analisar os canais de comércio e a transmissão de choques entre o resto do mundo e o Brasil. Usando dados trimestrais a partir de 1990 até o final de 2013, foi possível constatar que o aumento da relevância da economia Chinesa na balança comercial Brasileira exerce pressão sobre o crescimento econômico do Brasil. Em suma, a China tornou-se mais relevante para o crescimento econômico do Brasil do que os EUA e a Argentina. / The objective of this study is to evaluate the impact of variations in the Gross Domestic Product (GDP) of countries and economic blocks over Brazilian economic growth, with emphasis on China, United States of America (USA) and Argentina, which are the main commercial partners of Brazil. The increase in trading with China has made Brazil more vulnerable to shocks in Chinese GDP and less vulnerable, than in the recent past, to shocks in American GDP, and stability in the case of Argentina. It has been applied the methodology Global Vector Autorregressive (Global Var – GVAR), introduced, explained and expanded by Pesaran, Schuermann and Weiner (2004), Garratt, Lee, Pesaran and Shin (2006) and Dées, Di Mauro, Pesaran and Smith (2007) to analyze the trading channels and the transmission of shocks between the rest of the world and Brazil (specially with China, USA and Argentina). Using a sample from the first quarter of 1990 to the third quarter of 2013 it is possible to see that the increase of relevance of the Chinese economy on the Brazil trade balance increased the relevance of the Chinese economy over the Brazilian economy. Therefore, the conclusions of this work indicate a considerable vulnerability of the Brazilian economy to the Chinese economic cycle and, in a lower degree than in the past, to the American and Argentinian economies.

Submitted by Denis Nakazawa (denisnak@hotmail.com) on 2013-06-12T10:02:00Z No. of bitstreams: 1 Fatores Determinantes do Preço de Imóveis (Denis)_vf (pos-banca).pdf: 582940 bytes, checksum: a0fa5f51d08621702a0529597eb29f5f (MD5) / Este estudo tem como objetivo determinar os principais fatores macroeconômicos que influenciam a formação do preço de imóveis, tomando como base o mercado imobiliário residencial da cidade de São Paulo entre os anos de 2001 e 2012. Para capturar o efeito endógeno do PIB, da taxa de juros e da bolsa de valores sobre o preço de imóveis, optou-se por um modelo VAR. Concluiu-se que, dentre as variáveis, o PIB foi o fator mais preponderante na formação do preço, chegando a ter um impacto quase três vezes superior à taxa de juros. Não foram encontradas evidências estatísticas significativas do efeito da bolsa sobre o preço dos imóveis. Constatou-se ainda que choques no PIB e na taxa de juros demoram, no mínimo, um ano para começarem a refletir sobre o preço. Essas conclusões foram mais robustas no período anterior à crise imobiliária americana de 2008. / This article aims to identify the main economic determinants of house prices, based on the Sao Paulo residential market between the years 2001 and 2012. A VAR model was used to capture the endogenous dynamic among GNP, interest rate, equity and house prices. Among the variables, GNP was the most preponderant factor, having an impact almost three times superior than interest rate. No significant statistical evidence was found relating equity to housing price. Furthermore, house prices took at least one year to respond to shocks in the GNP and interest rate. These conclusions were more robust in the period previous to the American subprime mortgage crises of 2008.

This paper presents VAR results on the recent economic history of the U.S and focuses on the dependence of U.S. macrofinancial variables on international capital flows. Both gross and net flows are included in the analysis. The results indicate that cross-border funding has affected the build-up in the U.S. housing market irrespective of how these flows are defined and measured. Both the savings glut hypothesis and the banking glut hypothesis are supported by these findings. However, net banking flows appear to explain the higher volatility in the increase in house prices as well as the mortgage loan boom. (authors' abstract) / Series: Department of Economics Working Paper Series

This study aims to analyse the precrisis period on the oil markets with a primary objective of assessing the role of speculation in the commodity's price development and its volatility. First it depicts the rapidly increasing speculative activity on the futures market together with the parallel oil price surge. The speculation is initially proxied by non-commercial traders' positions and subsequently quantified by Working's T-index. The paper then uses speculative traders' positions and both spot and futures prices to test for Granger causality within the framework of VAR models. For the sake of consistency it also evaluates causal links between speculation and inventories level. Further the study investigates the speculation impact on volatility of oil prices by employing various approaches in volatility quantification including GARCH models. Contrary to expectations we find that the speculatio's impact on both prices and their volatility is rather insignificant. In the last chapter we therefore seek for an explanation of the oil price developments by examining the market fundamentals. The interaction of supply and demand finally gives substantial evidence for understanding the price developments in the precrisis period.

Cette thèse analyse la faisabilité d'une union monétaire en Asie de l'Est dans une vision dynamique et utilise les outils appropriés qui correspondent à l'histoire de l'économie régionale de la région. A partir de la littérature de la ZMO, nous testons quatre critères où chaqu'un d'eux sera traiter dans un chapitre. Dans le premier chapitre, nous présentons un fait stylisé pour différents arrangements financiers régionaux. Suite à la littérature existence, nous testons la dynamique de l'intégration financière par le biais de l'interdépendance des marchés boursiers. Le deuxième chapitre présente des perspectives à long terme des taux de change en Asie de l'Est avec une recommandation de la politique de ciblage d'inflation comme une politique monétaire régionale. L'adoption de cette politique assure un équilibre interne et maintient la stabilité de la compétitivité par la stabilité du taux de change. Nous étudions la synchronisation des cycles à l'Asie de l'Est au troisième chapitre. Une nouvelle mesure de la synchronisation des cycles économiques fondés sur l'analyse spectrale a été introduite. Notre méthodologie empirique renforce ceux des chapitres précédents qui prouvent une intégration économique croissante dans la région essentiellement durant cette dernière décennie. Le dernier chapitre examine la réaction d'un choc externe et un choc monétaire aux différents dates pour certaines économies de l'Asie de l'Est. / This thesis analyzes the feasibility of a monetary union in East Asia in a dynamic view and employ the appropriate tools which are close to the specific way of the regional economy trajectory in the region. Starting from OCA literature, we test four main criteria in four separate chapter. In the first chapter, we present a stylized fact for different regional financial arrangement. Following existence literature, we test dynamic of financial integration through stock market index interdependence proxy. The second Chapter presents long term perspective of exchange rate in East Asia with a recommendation of Inflation Targeting policy as a common regional monetary policy. The adoption of such policy insures an internal equilibrium and maintains stability of competitiveness through the stability of exchange rate. We investigate in the third Chapter business cycles synchronization in East Asia. A new measure of business cycle synchronization based on spectral analysis has been introduced. Our empirical methodology reinforces previous chapter finds of a clear economic integration in the region for the last decade. The last Chapter thoroughly investigates the reaction of an external shock and a monetary shock at different period for some East Asia economies.

本文是探討管理浮動匯率時期（1978年第三季至1993年第三季），台灣地區經常帳盈餘發生的原因，同時考慮匯率因素、貨幣市場及商品與勞務市場吸納的情況。利用兩個向量自迴歸模型，分別納入：(1)匯率、利率、經常帳、消費節約及貨幣供給，(2)匯率、利率、經常帳、財政盈餘及貨幣供給，藉由因果關係檢定、預測誤差分解、及衝擊反應，分析經常帳失衡的原因。 　　實証結果指出：台灣地區經常帳盈餘，深受匯率、財政盈餘及消費節約的影響，這個結論與我國低估幣值與出口拓展的政策一致。且經常帳盈餘並不能夠顯著的影響貨幣供給，這個結論與央行沖銷的措施一致，其目的無非是要隔離國外部門影響國內貨幣。足見自由化的匯率政策，不但讓匯率反應出合理的水準值，同時可追求獨立的貨幣政策，配合著獎勵投資、消費及增加公共支出，增加國內吸納，藉以減少鉅幅的經常帳盈餘。

本篇論文擴充Ang et al. (2007)之基本架構,分別建構台灣各式月資料與季資料的物價指數預測模型,並進行預測以及實證分析。我們用以衡量通貨膨脹率的指標為 CPI 年增率與核心CPI 年增率。我們比較貨幣模型、成本加成模型、6 種不同設定的菲力浦曲線模型、3 種期限結構模型、隨機漫步模型、 AO 模型、ARIMA 模型、VAR 模型、主計處(DGBAS)、中經院(CIER) 及台經院(TIER) 之預測。藉由此研究,我們可以完整評估出文獻上常用之各式月資料及季資料預測模型的優劣。 我們實證結果顯示,在月資料預測模型樣本外預測績效表現方面, ARIMA 模 型對 2 種通貨膨脹率指標的樣本外預測能力表現最好。至於季資料預測模型樣本外預測績效表現, ARIMA 模型對未來核心 CPI 年增率的樣本外預測能力表現最好; 然而,對於 CPI 年增率為預測目標的預測模型則不存在最佳的模型。此外,實證分析中我們也發現本研究所建構的模型預測表現仍遜於主計處的預測,但部份模型的樣本外預測能力表現則比中經院與台經院的預測為佳。 / This paper compares the forecasting performance of inflation in Taiwan. We conduct various inflation forecasting methods (models) for two inflation measures(CPI growth rate and core-CPI growth rate) by using monthly and quarterly data. Besides the models of Ang et al. (2007), we also consider some macroeconomic models for comparison. We compare some Monetary models, Mark-up models, six variants of Phillips curve models, three variants of term structure models, a Random walk model, an AO model, an ARIMA model, and a VAR model. We also compare the forecast ability of these model with three different survey forecasts (the DGBAS, CIER, and TIER surveys). We summarized our findings as follows. The best monthly forecasting model for both inflation measures is ARIMA model. For quarterly core-CPI inflation, ARIMA model is also the best model; however, when comparing the quarterly forecasts for CPI inflation, there does not exist the best one. Besides, we also found that the DGBAS survey outperforms all of our forecasting methods/models, but some of our forecasting models are better than the CIER and TIER surveys in terms of MAE.

After many decades, macroeconomic effects of fiscal policy have returned to the centre of the economic policy debate. Both automatic fiscal stabilizers and discretionary fiscal stimuli have been used to support aggregate demand during the recent global economic crisis with a subsequent need for large-scale fiscal consolidations. In this context, a proper assessment of the size of automatic fiscal stabilizers and fiscal multipliers represents a key input for fiscal policymaking. This dissertation provides a quantitative analysis of the interactions between fiscal policy and real economy in the Czech Republic. The impact of real economy developments on public finances is assessed based on the methods of the OECD, the European Commission and the ESCB for the identification of general government structural balances, i.e. balances adjusted for effects of the economic cycle and net of one-off and other temporary transactions. I find that the underlying fiscal position, as approximated by the government structural balance, was mostly below the level stabilising the debt-to-GDP ratio since mid-1990s. An indistinct improvement in the structural balance can be identified in the period 2004--2007, which was subsequently reversed by the adverse structural impact of the world economic crisis. At the same time, dynamics of unadjusted fiscal balance was largely determined by one-off transactions in the past. The effects of fiscal policy on real economy are analysed using the structural VAR approach. I find that an increase in government spending has a temporary positive effect on output that peaks after one to two years with a multiplier of around 0.6. Tax multiplier appears to be small and, in contrast to standard Keynesian assumptions, positive. Government spending is supportive to private consumption, contradicting the hypothesis of Ricardian equivalence, but it crowds out private investment in the short run. The results should be interpreted with caution, as the analysis is complicated by rapidly changing economic environment in the period of the economic transition, relatively short available time series and a large number of one-off fiscal transactions.

Diese Arbeit stellt Modelle und Methoden vor, die für robuste Statistiken und ihre Anwendungen in verschiedenen Bereichen entwickelt wurden. Kapitel 2 stellt einen neuartigen Partitionierungs-Clustering-Algorithmus vor, der auf Expectiles basiert. Der Algorithmus bildet Cluster, die sich an das Endverhalten der Clusterverteilungen anpassen und sie dadurch robuster machen. Das Kapitel stellt feste Tau-Clustering- und adaptive Tau-Clustering-Schemata und ihre Anwendungen im Kryptowährungsmarkt und in der Bildsegmentierung vor. In Kapitel 3 wird ein faktorerweitertes dynamisches Modell vorgeschlagen, um das Tail-Verhalten hochdimensionaler Zeitreihen zu analysieren. Dieses Modell extrahiert latente Faktoren, die durch Extremereignisse verursacht werden, und untersucht ihre Wechselwirkung mit makroökonomischen Variablen mithilfe des VAR-Modells. Diese Methodik ermöglicht Impuls-Antwort-Analysen, Out-of-Sample-Vorhersagen und die Untersuchung von Netzwerkeffekten. Die empirische Studie stellt den signifikanten Einfluss von durch finanzielle Extremereignisse bedingten Faktoren auf makroökonomische Variablen während verschiedener Wirtschaftsperioden dar. Kapitel 4 ist eine Pilotanalyse zu Non Fungible Tokens (NFTs), insbesondere CryptoPunks. Der Autor untersucht die Clusterbildung zwischen digitalen Assets mithilfe verschiedener Visualisierungstechniken. Die durch CNN- und UMAP-Regression identifizierten Cluster werden mit Preisen und Merkmalen von CryptoPunks in Verbindung gebracht. Kapitel 5 stellt die Konstruktion eines Preisindex namens Digital Art Index (DAI) für den NFT-Kunstmarkt vor. Der Index wird mithilfe hedonischer Regression in Kombination mit robusten Schätzern für die Top-10-Liquid-NFT-Kunstsammlungen erstellt. Es schlägt innovative Verfahren vor, nämlich Huberisierung und DCS-t-Filterung, um abweichende Preisbeobachtungen zu verarbeiten und einen robusten Index zu erstellen. Darüber hinaus werden Preisdeterminanten des NFT-Marktes analysiert. / This thesis provides models and methodologies developed on robust statistics and their applications in various domains. Chapter 2 presents a novel partitioning clustering algorithm based on expectiles. The algorithm forms clusters that adapt to the tail behavior of the cluster distributions, making them more robust. The chapter introduces fixed tau-clustering and adaptive tau-clustering schemes and their applications in crypto-currency market and image segmentation. In Chapter 3 a factor augmented dynamic model is proposed to analyse tail behavior of high-dimensional time series. This model extracts latent factors driven by tail events and examines their interaction with macroeconomic variables using VAR model. This methodology enables impulse-response analysis, out-of-sample predictions, and the study of network effects. The empirical study presents significant impact of financial tail event driven factors on macroeconomic variables during different economic periods. Chapter 4 is a pilot analysis on Non Fungible Tokens (NFTs) specifically CryptoPunks. The author investigates clustering among digital assets using various visualization techniques. The clusters identified through regression CNN and UMAP are associated with prices and traits of CryptoPunks. Chapter 5 introduces the construction of a price index called the Digital Art Index (DAI) for the NFT art market. The index is created using hedonic regression combined with robust estimators on the top 10 liquid NFT art collections. It proposes innovative procedures, namely Huberization and DCS-t filtering, to handle outlying price observations and create a robust index. Furthermore, it analyzes price determinants of the NFT market.