Der Risikobegriff bezieht sich auf die Wahrscheinlichkeit eines Schadens aufgrund einer Gefährdungsexposition, in der Finanzwelt meist finanzielle Verluste. Viele Risiken der globalen Finanzwirtschaft sind unbekannt. „Wir wissen es, wenn wir es sehen“, um Potter Stewart (1964) zu paraphrasieren. Der Financial Risk Meter (FRM) soll Aufschluss über die Entstehung systemischer Risiken geben. Durch Verwendung von Quantilregressionstechniken ist der FRM nicht nur ein Maß für finanzielle Risiken. Er bietet durch seine Netzwerktopologie einen tiefen Einblick in die Spill-over-Effekte, die sich als systemische Risikoereignisse manifestieren können. Das FRM-Framework wird in verschiedenen Märkten und Regionen entwickelt. Die FRM-Daten werden für Risiko-Prognose sowie für Portfoliooptimierung genutzt. In Kapitel 1 wird der FRM vorgestellt und auf die Aktienmärkte in den USA und Europa, sowie auch auf die Zinsmärkte und Credit-Default-Swaps angewendet. Der FRM wird dann verwendet, um wirtschaftliche Rezessionen zu prognostizieren. In Kapitel 2 wird der FRM auf den Markt der Kryptowährungen angewendet, um das erste Risikomaß für diese neue Anlageklasse zu generieren. Die errechneten FRM-Daten zu Abhängigkeiten, Spillover-Effekten und Netzwerkaufbau werden dann verwendet, um Tail-Risk-optimierte Portfolios zu erstellen. Der Portfoliooptimierungsansatz wird in Kapitel 3 weitergeführt, in dem der FRM auf die sogenannten Emerging Markets (EM)-Finanzinstitute angewendet wird, mit zwei Zielen. Einerseits gibt der FRM für EM spezifische Spillover-Abhängigkeiten bei Tail-Risk-Ereignissen innerhalb von Sektoren von Finanzinstituten an, zeigt aber auch Abhängigkeiten zwischen den Ländern. Die FRM-Daten werden dann wieder mit Portfoliomanagementansätzen kombiniert. In Kapitel 4 entwickelt den FRM for China ist, eines der ersten systemischen Risikomaße in der Region, zeigt aber auch Methoden zur Erkennung von Spill-Over-Kanälen in Nachbarländer und zwischen Sektoren. / The concept of risk deals with the exposure to danger, in the world of finance the danger of financial losses. In a globalised financial economy, many risks are unknown. "We know it when we see it", to paraphrase Justice Potter Stewart (1964). The Financial Risk Meter (FRM) sheds light on the emergence of systemic risk. Using of quantile regression techniques, it is a meter for financial risk, and its network topology offers insight into the spill-over effects risking systemic risk events. In this thesis, the FRM framework in various markets and regions is developed and the FRM data is used for risk now- and forecasting, and for portfolio optimization approaches. In Chapter 1 the FRM is presented and applied to equity markets in the US and Europe, but also interest rate and credit-default swap markets. The FRM is then used to now-cast and predict economic recessions. In Chapter 2 the FRM is applied to cryptocurrencies, to generate the first risk meter in this nascent asset class. The generated FRM data concerning dependencies, spill-over effects and network set-up are then used to create tail-risk optimised portfolios. In Chapter 3 the FRM is applied to the global market Emerging Market (EM) financial institutions. The FRM for EM gives specific spill-over dependencies in tail-risk events within sectors of financial institutions, but also shows inter-country dependencies between the EM regions. The FRM data is then combined with portfolio management approaches to create tail-risk sensitive portfolios of EM Financial institutions with aim to minimize risk clusters in a portfolio context. In Chapter 4 the Financial Risk Meter for China is developed as the first systemic risk meter in the region, but also derives methods to detect spill-over channels to neighbouring countries within and between financial industry sectors.

No description available.

No description available.

No description available.

Foreign Direct Investment (FDI) in the United States, which predominately occurs in the manufacturing sector, remains critically important for a strong regional and local economy, due to the resulting increase in employment, wages, and tax revenue. Traditionally, local economic development strategies have focused on attracting external manufacturing plants or facilities as the primary route to economic growth, through the expansion of the tax base and/or an increase in employment. In comparison, Sustainable Local Economic Development (SLED) emphasizes the establishment of a minimum standard of living for all and an increase in this standard over time; a reduction in the steady growth in inequality among people; a reduction in spatial inequality; and the promotion and encouragement of sustainable resource use and production (Blakely & Leigh, 2010). These essential SLED principles motivate this study, which will seek to develop a better understanding of whether and how FDI contributes to SLED in terms of its spatial patterns and its impact on middle class earnings. By selecting Georgia as a case study area, this research specifically examines whether and how the location of manufacturing FDI has reduced (or increased) spatial inequality at the intra-state and intra-metropolitan levels. It also identifies whether and how manufacturing FDI has reduced (or increased) inequality among people, focusing on its impact on middle class earnings. This study finds a strong spatial concentration of manufacturing FDI employment in metropolitan areas, particularly in a large metropolitan area, at the intra-state spatial pattern analysis. The results of panel regression analysis suggest that presence of agglomeration economies in metropolitan areas has positively influenced the location of manufacturing FDI jobs. The study also finds a suburbanization pattern of manufacturing FDI employment in the intra-metropolitan spatial pattern analysis. This intra-metropolitan suburbanization of FDI in manufacturing jobs is associated with loss of urban industrial land in the central areas within a large metropolitan area. These uneven distribution patterns of manufacturing FDI jobs indicate increased spatial inequality at both intra-state and intra-metropolitan levels, but the implications of this finding are mixed. Using individual earnings data from the American Community Survey Public Use Microdata Sample files, this study also conducts a quantile regression to estimate the earnings distribution effects that a concentration of manufacturing FDI may have on different earnings groups. The findings both from place-of-work and place-of-residence earnings analysis suggest that manufacturing FDI generally has reduced inequality among people. The concentration of manufacturing FDI in a certain area show the largest distribution effects on area workers in the lower earnings group and residents in the middle earnings group.

住宅市場是典型的不完全訊息市場，每個市場參與者並不知道潛在交易對象的所在位置、偏好，與保留價格。不完全訊息意涵著，交易者必須透過搜尋才能找到交易對象，因而必須支付搜尋成本，也會形成搜尋市場。不論是住宅交易的買方或者賣方，都可以選擇是自行搜尋交易對象，或者透過仲介業者來協助交易的達成。然而，仲介業者對於住宅搜尋市場之影響，目前仍存在著許多問題是尚待釐清的，而拍賣市場在台灣所扮演的重要性愈來愈高，其市場機制的價格效果也是值得關注的問題： 一、跨區購屋、定錨行為與仲介服務效果 買賣房屋幾乎必然會有議價過程，雙方的議價能力除了受到市場條件的影響外，賣方對於本身所蓋或者所擁有的房屋及附近地區市場等資訊都較買方為多，因此賣方處於較有利的地位。因此，本研究的第一個研究問題即是：就購屋者彼此之間，在地購屋者是否比跨區購屋者具有訊息優勢？參考價格偏誤是否存在？具有訊息優勢的仲介服務能否改善購屋者的搜尋成本與參考價格偏誤？本研究實證結果顯示，基於搜尋成本較高的原因，跨鄉鎮市區的跨區購屋者相對於未跨區者需要多支付3.8%的價格貼水。其次，參考價格愈高的地區，其購屋者會因為定錨效果或參考點偏誤而多支付1%的價格貼水，此外，高價格分配信念的購屋者，平均會支付4.9%的價格貼水。第三，地價上漲率較高地區的購屋者，會誤用自身地區的外推性預期，以為遷入地區也有同等的價格增值空間，而多支付約11.4%的價格貼水。最後，購屋者若尋求仲介服務亦能改善其出價能力，約可降低2.9%的價格貼水，然而，仲介服務在改善搜尋成本與定錨的效果方面則不顯著。 二、仲介服務對於價格分散之影響 本研究利用搜尋成本與價格分散的觀點，檢視具有訊息優勢的仲介服務業者是否真能提高住宅市場的價格搜尋效率。以台北地區的住宅市場資料，指出仲介服務的存在的確可以提高購屋者的搜尋能力。價格分散的估計與檢定結果則顯示：第一，購屋者成交價價格分散小於訂價價格分散；第二，透過仲介服務搜尋者訂價價格分散未顯著異於自行搜尋者的訂價價格分散，可是透過仲介服務搜尋者的成交價價格分散則顯著小於自行搜尋者的成交價價格分散，同時透過仲介服務的價格收斂比率較高。此乃表示，仲介服務業者並未運用其訊息優勢協助賣方進行較有效率的訂價，但是能有效地協助買賣雙方透過配對與議價活動，大幅地降低成交價的價格分散程度。此外，進一步比較國內相關研究結果，目前台北市的住宅市場訊息效率已較過去有顯著的改善，特別是透過仲介服務的改善效果更為明顯。 三、不對稱的仲介服務價格效果 過去有關仲介服務對於交易價格影響的實證結果卻出現許多分歧而不一致的現象，本研究認為過去相關文獻的差異，可能源自以普通最小平方迴歸的方式來估計仲介服務的價格效果時，會忽略住宅價格條件分配的差異。以分量迴歸估計後發現，仲介服務係數在各價格分量呈現很大的差異且顯著，仲介服務的價格效果，在0.10分量約有4.4%的溢價，而 0.75分量以上則約有-5.6%的折價現象。因此，本研究嘗試以高低價格分量的不對稱訂價策略，作為仲介服務價格效果不一致的現象的檢視觀點，並得到實證上的支持。 四、搜尋與拍賣市場機制選擇及拍賣市場績效之再檢視 拍賣市場為購屋者的重要次級市場之一，因此拍賣市場的績效就顯得愈來愈重要。本研究考慮了購屋者的搜尋成本對於市場機制自我選擇偏誤的影響，重新檢視拍賣市場的績效。本研究實證結果顯示，在未考慮自我選擇偏誤下，拍賣市場機制的估計係數為-22.6%，且達1%統計顯著水準。但是，在控制買方與物件的自我選擇偏誤後，我國拍賣市場與搜尋市場間並無顯著的價格差異存在，因而本研究對於過去國內相關文獻認為拍賣市場一定比搜尋市場折價較多的說法，提出了相當的質疑。惟此三年間我國北部地區拍賣市場的拍定率從10%快速成長到30%，而市場條件的快速變化，很可能會造成較大的拍賣價格變異。因此在後續研究上，可以比較拍定率差異較大的時間進行比較研究，以了解本研究結果之穩定度。 / This dissertation employs search theory and behavior theory to study four relative essays. The first essay is to test three questions using a unique data base in the viewpoint of search cost and Anchoring behavior: First, is there anchoring effect or reference price bias on home-purchasing behavior? Second, is there any extrapolative expectation effect of reference price change on homebuyers? Third, can homebuyers reduce price premium from their high search cost or perceived bias? Those answers can help us understand if we can get alternative interpretation to housing price dispersion and if government should provide housing information service. Empirically, we find that out-of-town/district buyers pay a statistically significant price premium in the Taipei area. We also find some evidence consistent with the price premium being driven by high search costs, anchoring effect and extrapolative expectation from heuristics. Finally, homebuyers can lower price premium through real estate brokers in the market. The second essay is to examine the efficiency of housing and brokerage markets in view of price dispersion. We find brokerage service enhance the search ability of homebuyers. We use listing price prices as the prices before search and the actual transaction prices as the price after search, and we also separate the sample into search by homebuyers and search by broker. We find that search by broker decreases the price dispersion compared to search by homebuyers. The third essay is try to explain a number of past and recent studies provided conflicting empirical answers to the effect of real estate brokerage service on housing price. We employ quantile regression to capture the behavior at each quantile of conditional house price distribution and to test the asymmetric effects of brokerage service. An important findings of this paper is that the price effects of real estate brokerage service are significant heterogeneous across the conditional price distribution. The contribution of this paper to the prior literature is to provide empirical evidence by showing that broker might have a positive, negative, or zero impact on the housing prices. The final essay is to discuss the decision making behavior of housing markets mechanism choice. Real estate auction market has been one of main market mechanisms of home purchase. Therefore, the performance of real estate auctions is a very important issue. This article reviews the price premium or discount of real estate auctions by correcting the self-selectivity bias in a view of homebuyers’ search cost. The empirical result shows that the availability of an auction as an alternative has the result of high search cost buyers attending auctions. Next, after accounting for the endogenous nature of this choice and controlling for property and buyer characteristics, prices of properties sold at auction were not lower than those of comparable properties sold in a search market. It is questionable to say the performance of real estate auctions is inferior to that of negotiated sales at Taiwan.

高密度發展的都市型態已成為世界各國為追求永續發展的都市規劃方式。對政策規劃者來說，他們關心的議題之一為高密度都市發展後房價的變動是否會影響居民對住的福利水準，過去文獻之實證研究亦發現高密度發展將產生房價上漲或下跌的效果，此引發本研究欲得知高密度指標對台北市房價將如何影響之動機。然而高密度都市發展政策的實施對各所得階層居民的影響為何若以普通最小平方迴歸分析將無法得知，所以本研究以分量迴歸進行分析，增加變數的可解釋能力。 因此本研究以台北市十二個行政區為空間範圍，利用民國九十三年至九十六年間共1268筆房屋交易實例案例，作為實證研究之樣本。主題變數方面以容積率、是否為住宅大樓及人口密度來分析各變數對房價之影響。藉由普通最小平方迴歸及分量迴歸分析結果發現，高密度之都市發展將造成住宅平均價格下跌，對中低總價住宅亦產生價格下跌的效果，因此高密度都市發展型態將增加居民福利水準，增進都市整體效益。 / Nowadays, most nations in the world has thought of the urban form of high density development as a mean to pursue sustainable development. For policy planner, what they care is whether high density development would influence residents about the variation of welfare for living. Literatures of past empirical research also show that high density development will have the effects of rising or falling on housing prices, which leads to the motive of this study and also leads to a better understanding of how high density indicators would impact housing prices in Taipei City. However, what’s the impact for every income class through the implication of this urban development policy is impossible to know if we use OLS models, therefore, our study adopts Quantile Regression to enhance the interpretable abilities for every variable. Accordingly, our study uses 1268 property-trading-records from 2004 to 2007 as samples, which all locate within 12 districts in Taipei City. We use floorage ratio, residential building and population density as main variables to analyze their impacts on housing prices. The result shows that high density development will both lead to falling of average housing prices and middle and low housing prices. Consequently, the urban form of high density development will enhance the level of residents’ welfare and improve the benefits for all urban area.

長期以來，不動產估價相關研究皆著重在估價理論與技術的改進，以使最後估值能更為精確。然而實際上，估價人員的行為才是影響價格評定的本質因素；尤其國內、外對於市場比較法的相關研究，皆發現估價人員有偏離理論規範的現象。故本文第一部份是分析估價人員系統行為偏誤問題；第二部分探討特徵價格模型的偏誤，並應用分量迴歸改進不同高低價格的估價模型準確度；第三部分比較估價師個別估價與大量估價模型之偏誤與差異；為提升客觀估價方法，第四部分探討以估價師估值樣本產生最可能價格與機率的方式。本研究藉由估價師估價行為與大量估價模型不同面向的研究，重新檢視市場比較法的各種偏誤現象。 一、市場比較法估價之系統行為偏誤 市場比較法是估價人員最常使用的方法，但在估價過程中主觀判斷部分相對較多也最易引起爭議。過去市場比較法研究著重在估價理論與技術改進，以減少主觀判斷造成的隨機偏誤，然而，研究指出行為偏誤造成的系統偏誤，其持續性的偏誤對於估價偏誤有重要影響。過去探討估價行為的研究，受限於資料樣本取得，幾乎都是以問卷或實驗得到結果，而非實證結果。本文則是以實際估價報告書進行實證分析，以鄒檢定(Chow Test)及似無相關檢定(Seemingly Unrelated Regression)，發現勘估標的估值與比較標的市場成交值兩模型係數有顯著差異，表示估價人員估值模型起始點高於市場成交值模型，估價人員對於使用類型有高估現象，對於面積估計有低估現象，支持估價人員有系統行為偏誤。此外，也發現評估不同市場時，行為偏誤程度亦不同，估價人員於評估拍賣價格時，因估價經驗與比較案例較少，較傾向參考比較案例，行為偏誤亦較小，僅面積係數有差異；但於評估正常市場價格時，估價行為偏誤較大，區位、使用類型及面積係數皆有差異。 二、不同高低價格不動產估價模型之偏誤改進－分量迴歸模型之應用 隨著國內不動產市場M型化推案趨勢，非典型住宅（如：高總價豪宅和低總價小套房）類型逐漸增多，對於此類型產品的估價精準度也需要提升。從過去研究發現，最小平方迴歸估計忽略各特徵屬性對價格條件分配的差異。本研究乃以分量迴歸方法建立住宅大量估價模型，藉以瞭解住宅特徵對於不同價格分量的差異，實證結果發現以最小平方迴歸模型估計相較於分量迴歸，對於一樓、頂樓、車位、區位等變數有高估或低估的情形。比較估值模型預測精確度，本文透過30次重複實驗，發現分量迴歸對於兩側尾端樣本有較佳的預測能力。從實證方法而言，本文改進以最小平方迴歸模型對兩尾端價格高估或低估問題；就實務應用方面，隨著不動產產品差異度增加，以及新版巴塞爾協定（Basel Ⅱ）實施對不動產價值更新的需求，分量迴歸模型可提升兩尾端估計精確度，並提供住宅大量估價系統另一種資產重估方法。 三、大量估價與個別估價之差異分析 不動產估價研究可分為個別估價與大量估價兩類，過去有關個別估價研究多為估價行為或估價方法改進，而大量估價研究則多是運用數量方法建立模型，由於兩者建構方式不同，欲同時進行兩者實證比較並不容易。本文藉由相同勘估標的，取得估價師個別估價資料，與資料庫建立的自動估價系統，進行案例選取、權重調整及最後估值三階段的比較分析。經本文差異比較發現，前二個階段的比較結果，皆是自動估價系統優於個別估價，從估價行為觀點，顯示自動估價系統具有較客觀且符合估價理論程序優點。然而第三階段的估值比較，發現自動估價系統的表現並不如預期，此結果與過去研究結論不同，分析兩者差異值大的案例，發現資料庫樣本較少地區以及非典型住宅類型（面積過大或過小），是造成個別估價估值與自動估價系統估值差異大的原因，顯示自動估價系統有其適用限制，未來若增加資料庫樣本或次市場模型，兩者估值差異將可獲得改善。 四、不動產估值認知與估值機率 本章以估價師估值資料為樣本，藉由蒙地卡羅模擬估值機率模型，其模擬結果可客觀估計最可能價格（the most probable price）與機率。由於資料樣本來自於專業估價師的判斷，估值分配代表的是估價師所估計的可能估值結果；相較於過去僅以單一估值決定資產價值，藉由多位專業估價師所判斷結果而建立的估值區間與最可能價格及機率，應該是更具客觀性且接近市場價值，而且估值機率的呈現將有助於估價報告書使用者評估存在於資產價值的上方（upside risk）及下方風險（downside risk）。 / In the real estate appraisal research, appraisers and mass appraisal are the two methods most often used in the sales comparison approach. Past studies focused on appraisers behavior and mass appraisal model, lack of compared the difference by appraisers for the same objects as well as mass. The first essay reviews the behavior literature regarding real estate appraisers and summarizes the two hypotheses for departure from normative models. The study is based on appraisers’ reports analyzes for the appraisal valuation and the market transaction by hedonic price models. Among the 112 appraisal reports of the transaction data of 230 comparables and the valuations of 224 subjects, the results reveal the effect of the variables on the appraisal valuation are not consistent with those of the market transaction. In addition, comparing the appraisers’ behavior on the general market with the auction market, the result found is the differences between the valuation models and the transaction models are less than the models on the auction market. The empirical evidences support the two hypotheses and can be explained plausibly by the appraisers’ behavioral contention. The second essay analize the current domestic trend of residential types, it is easy to find that high-priced dwelling units and low-priced dwelling units keep gaining popularity. Thus, the estimation of these two types of residences should be more precise. Since ordinary least square regression can not signify the variation caused by different quantile functions of a conditional distribution, this study estimates the housing price by quantile regression. We compare the models by using ordinary least square regression and quantile regression. The empirical results show that the distributions of some variables, such as first floor, top floor, parking lot, location, are different between two models. These are easily to be underestimated or overestimated when ordinary least square regression is applied. Based on thirty repeated experiments using random sampling, the results of hit rate and mean absolute percentage error show that quantile regression estimates more accurately on two-tailed distribution. For mass appraisal application, a quantile regression advances the estimate on two-tailed price and provides a new method on assets reevaluation of banks.

本文的研究目的為分析台灣菸品消費的特性。本文選擇採取分量迴歸法作為研究方法，探討在0.05、0.2、0.4、0.6、0.8和0.95的菸品消費分量下，吸菸家戶的菸品消費特性效果為何。資料來源為行政院家庭收支調查報告。 研究結果指出，在0.2到0.8分量的菸品消費量下，菸品的價格彈性為-0.161到-0.231之間。然而，在0.05分量的菸品消費量下，菸品的價格彈性為-0.363，而當位於0.95分量的菸品消費量時，菸品的消費彈性大幅的提升至-0.701。這代表著提高菸品稅或是菸品健康福利捐的政策是可以有效減少吸菸行為的。 更近一步探討，在0.95分量的菸品消費下，菸品的消費彈性大幅的提升至-0.701，對於此現象可能的解釋為，對於較高菸品消費量的家戶大部分為吸菸成癮者，當價格上漲時，消費者會選擇改變吸菸習慣例如戒菸或購買較便宜的香菸。 而值得一提的是，對於吸菸成癮的消費者而言，也存在一定機率會選擇購買非法的走私香菸，而走私香菸不但無法增加我國菸品稅收收入，也無法達成抑制我國吸菸率的政策目標。因此，政府在推動菸品控管政策時，須將菸品消費者的消費特性列入考量，同時也必須加強查緝非法菸品走私的行為，才能更有效達成政策目標。 / The research purpose of the paper was to analyze the characteristics of cigarette consumptions in Taiwan. The paper had adopted quantile regression as research method to discuss the effect of smoking households’ consumption characteristics to the cigarette consumptions in Taiwan at 0.05, 0.2, 0.4, 0.6, 0.8, and 0.95 quantile. Data for the research was sourced from the “Report on the Survey of Family Income & Expenditure”, conducted by the Executive Yuan, R.O.C. The results showed up that the price elasticities of cigarettes were estimated about -0.161 to -0.231 from 0.2 to 0.8 quantile of cigarettes consumption. However, the price elasticity of cigarettes was -0.363 in 0.05 quantile and raised significantly to -0.701 in 0.95 quantile. Indicating the policy of implementing cigarette tax or “Health and Welfare Surcharge on Tobacco Products” would decrease the smoking behavior effectively. Furthermore, the price elasticity changed to -0.701 in 0.95 quantile, a possible explanation for this phenomenon was that households with higher cigarette consumption were highly addicted to smoking, when the cigarette price increased, they would try to change smoking habit such as buying cheaper cigarettes or quit smoking. However, it is worth noticed that there existed risks of price sensitive smokers seek out measures to purchase less expensive cigarettes when they were highly relied on cigarettes, such as smuggled cigarettes, which may decrease future cessation efforts, and also lose the tax revenue from cigarette excise tax. Therefore, government should also take the consumption characteristics of smoking households into account and also enhance the prevention of illegal consumption behaviors when implementing the tobacco control policy.

The treatment of owner-occupied housing (OOH) is probably the most important unresolved issue in inflation measurement. How -- and whether -- it is included in the Consumer Price Index (CPI) affects inflation expectations, the measured level of real interest rates, and the behavior of governments, central banks and market participants. We show that none of the existing treatments of OOH are fit for purpose. Hence we propose a new simplified user cost method with better properties. Using a micro-level dataset, we then compare the empirical behavior of eight different treatments of OOH. Our preferred user cost approach pushes up the CPI during housing booms (by 2 percentage points or more). Our findings relate to the following important debates in macroeconomics: the behavior of the Phillips curve in the US during the global financial crisis, and the response of monetary policy to housing booms, secular stagnation, and globalization. / Series: Department of Economics Working Paper Series