Master's thesis is focused on the problem of the economic impacts of floods on the property market in Prague. Aim of this work is to clarify whether the floods affect the price of real estate and to what extent. Hypothesis is that floods affect the price of property in flood plains. This effect is determined by the hedonic price model (HPM) for the analysis of secondary data. The theoretical part explains the risk of flooding and floodplains mapping. This section further explains the whole hedonic model and reviewed studies provide a research procedure outside the Czech Republic region. The practical part deals with the exploratory analysis, regression analysis and hedonic price modeling based on the implicit price of flooding. Finding of the thesis is the fact that property prices in Prague are affected by the Q100 flood plains resulting in positive and negative impact confirmed by a log-log weighted least squares regression model. It is shown that implicit price of flooding far exceeds the cost of building flood protection measures in Prague.

The aim of this thesis is to examine the influence of selected characteristics of sold flats (2007-2012) in Prague on the selling price. The analysis is made on group of similar flats of size 3+1 and 3+kk. Data consist of 1185 observations. I am using the hedonic price method to investigate the influence of selected variables. The results indicate that with rise in availability by 1% the price of flat decrease by 0, 13%, with rise of its size the price rise by 0,92%. The price of flats rise by 13% when the cooperative ownership change to personal ownership The change of construction materials from panel to bricks rise the price of flat by 23%, the reconstruction of bathroom rise the price by 5,7%. Other finding is that overall reconstruction rises the price by 11%. Garage increase the price by 24%. Finally the hypothesis that flat in the ground floor is negatively viewed and the price of flat decrease by 2, 5%.

The diploma thesis "Critical analysis of the housing stock and prediction of its devel-opment" provides comprehensive information of the residential market development in the context of demographic, political and economic factors. This thesis explores the possibility of involvement of methodological ways to improve market transparency in the housing and its development and research. Analysis of residential market contained in the first few chapters is based on predicting the market in terms of optimistic, pessimistic and realistic market devel-opment assuming the interaction of certain macroeconomic and microeconomic conditions according to the scenario.

The impact of geographical choices is crucial for both individuals and businesses to assess. Generally, companies are favored by being in accessible areas, which pushes up the demand and price for space. This phenomenon is referred to as a bid-rent theory. Infrastructure like roads and public transport contributes to accessibility. Earlier studies have shown that property prices are affected by all public means of transport but seems to be mostly affected by the accessibility to metro stations. With a quantitative research method, the aim of this master thesis is to explore how commercial property transaction prices are affected by the proximity to public transport specified on metro stations in Stockholm. Our study is performed on 123 officebuildings, and all observations are within the timeline of 2015 to 2021, in both the inner and outer city. The aim is also to explore the difference between those areas. In this study, a hedonic price model is used, where price/sqm is the dependent variable: y = m + β1x1 + … + βnxn + ε 10 independent variables are used, all arguably related to determine a price for a commercial office property. The variables Metro and I/O are in focus and considered our main variables to examine, Metro represents the distance to metro stations and I/O is a dummy for inner and outer city. In total, 7 models are presented in the results, with different combinations of independent variables. All models contribute to discussion, however, the model that we consider gives the most relevant results has a degree of explanation R2 of 46,7%. This model gives us significant results on both independent variables in focus, and the model itself. A large factor that interrupted better results was the limitations on observations. The interpretation of the model for offices in the inner city showed that the dependent variable changed 0,667 units when the independent variable I/O changed 1 unit. Moreover, when the distance to metro stations increased with 1 unit the dependent variable decreased with 0,0454 units per km. Furthermore, within the inner city the distance to metro stations tends to have less significance, to clarify the reason why, is yet to be discovered. / Valet av geografisk placering är något som både privatpersoner och företag påverkas av. Generellt sett är det ekonomiskt fördelaktigt för företag att placera sig i lättillgängliga områden, vilket i sin tur bidrar till en högre efterfrågan och högre hyror i vissa områden. Infrastruktur såsom vägar och kollektivtrafik bidrar till ökad tillgänglighet. Tidigare studier visar att närhet till kollektivtrafik, oavsett trafik-slag, har en effekt på priset. Dock verkar priset påverkas främst av tillgängligheten till tunnelbana. Med en kvantitativ forskningsmetod är syftet med denna masteruppsats att undersöka hur kommersiella fastighetspriser påverkas av närhet till kollektivtrafik, med en inriktning på tunnelbanestationer i Stockholms län. Vår studie grundar sig på 123 kontorsfastigheter och samtliga transaktioner är utförda mellan år 2015–2021, i både innerstad och ytterstad. Syftet är därför också att undersöka vilken skillnad det finns mellan dessa områden. I studien används en hedonisk prismodell, där vår beroende variabel är pris/kvm: y = m + β1x1 + … + βnxn + ε 10 oberoende variabler, som i någon mån kan förklara priset, har använts i analysen. Bland dessa har vi haft störst fokus på variablerna för avstånd till tunnelbanestation Metro samt dummy-variabeln för innerstad/ytterstad I/O. Totalt sett redovisas 7 modeller med olika kombinationer av oberoende variabler. Samtliga modeller bidrar till diskussion, men den modell vi anser ger oss mest relevant information har en förklaringsgrad R2 på 46,7% och visar signifikans på modellen i sin helhet samt våra oberoende variabler i fokus. Tolkningen av modellen för kontorsfastigheter i innerstaden visade att den beroende variabeln steg 0,667 enheter när den oberoende variabeln I/O ändrades med 1 enhet. Samt visade det sig att när avståndet ökade till tunnelbanestationer med 1 enhet så minskade den beroende variabeln med 0,0454 enheter per kilometer. Dessutom, tenderar avståndet till unnelbanestationer i innerstad, att ha mindre påverkan på priset. Orsaken till detta, framgår inte i denna studie.

This thesis aims to explore the time variation of liquidity and transaction prices in the Swedishcommercial real estate market. The purpose is to contribute with insights about price dynamics and liquidity on the Swedish commercial real estate transaction market. A price index was therefore estimated based on the output of a hedonic regression model. The model controls for different locations, segments and years and further includes variables controlling for size, portfolio transactions and investor nationality. The regression model is based on transaction data provided by Cushman & Wakefield which consists of 10 194 observations over a 20-year period between the years 2003-2023. Further the relationship between transaction prices and liquidity was investigated. The liquidity measure used is turnover rate which was calculated for each year based on data from Statistics Sweden (SCB). Granger causality tests were conducted for different geographic aggregation levels to explore if liquidity can predict transaction prices and vice versa. The results show that market liquidity in terms of turnover rate in city and regional locations can be used to forecast the development of transaction prices and therefore“leads” the price development. The test results, in combination with a correlation analysis that showed strong correlation between prices and previous year’s turnover rates, suggests evidence of a sequential relationship between the variables. For the nation as a whole and for the rural location, the results of the causality tests were insignificant and the hypothesis that there does not exist a Granger causality between price and turnover could not be rejected. It was also concluded that since liquidity leads prices, information about turnover rates can be used to help forecast property cycles in the short term. / Detta examensarbete syftar till att undersöka sambandet mellan likviditet och transaktionspriser på den svenska kommersiella fastighetsmarknaden. Syftet är att bidra med insikter om prisdynamik och likviditet på den svenska kommersiella fastighetstransaktionsmarknaden. Ett prisindex estimerades baserat på en hedonisk regressionsmodell. Modellen estimerar transaktionspriser för olika geografiska delmarknader, segment och år och inkluderar vidare variabler som kontrollerar för storlek, portföljtransaktioner och investerarnationalitet. Regressionsmodellen är baserad på transaktionsdata från Cushman & Wakefield som består av 10 194 observationer under en 20-årsperiod mellan åren 2003 och 2023. Vidare undersöktes sambandet mellan transaktionspriser och likviditet. Likviditetsmåttet som används är omsättningsandel som beräknats för respektive år baserat på data från SCB. Test av Grangerkausalitet genomfördes för olika geografiska delmarknader för att undersöka om likviditet kanprediktera transaktionspriser och vice versa. Resultaten visar att marknadslikviditet i form avomsättningsandel i storstäder och regioner kan användas för att prognostisera utvecklingen avtransaktionspriser och därmed "leder" prisutvecklingen. Testresultaten, i kombination med enkorrelationsanalys som visade på en stark korrelation mellan priser och föregående årsomsättningsandelar, tyder på att det finns ett sekventiellt samband mellan variablerna. För landet som helhet och för landsbygden gav kausalitetstesterna inget signifikant resultat och hypotesen att inget kausalitetssamband existerar mellan likviditet och priser kunde därmed inte förkastas. En annan slutsats som drogs var att eftersom likviditet leder priserna kan information om omsättningsförändring användas för att prognostisera fastighetscykler på kort sikt.

成本法為估價三大方法之一，其中折舊率之掌握至今仍無定論，Malpezzi et al.（1987）、Smith（2004）指出，由於土地無實體損壞及功能性退化，故利用特徵價格法分析折舊時，分析主體包含土地，將造成折舊的低估，而國內先前研究亦指出，分析主體包含土地，可能是使其分析結果不合常理的原因。本研究採特徵價格法，以台南市透天建物為對象，實證結果與Malpezzi等之論點一致，即不包含土地之價格函數，確有較高的折舊率，且呈現凸向原點之折舊型態。不動產價格模型亦顯示，建物壽命前期價格逐年下跌，但至後期將反轉向上，反應出土地之再開發價值。 此外，依不動產估價技術規則之規定，求取建物價格時似乎未考慮外部性退化之價值減損，或將其視為與剩餘經濟耐用年數相關。然而Colwell and Trefzger（1994）指出負面外部性將同時影響土地與建物，本文實證結果發現，外部性退化除對土地價格造成影響外，事實上對建物價格亦產生價格減損效果。此外，外部性特徵對於建物價格之影響視兩者距離相鄰程度而定，故不應將外部性退化視為與屋齡相關，而於考量後推估建物剩餘經濟耐用年數。 / In this paper, we verify that estimated depreciation rate is higher when the land price has been extracted from single-family house prices in Tainan, and the depreciation pattern of building is convex to the origin. We also find that property prices will decrease in the early years and then turn to increase; this phenomenon may testify the benefit in land redevelopment. Moreover, this study shows that external obsolescence would reduce not only the land price but also the building price when the surrounding is unattractive, and the decreasing figures caused by external obsolescence shouldn’t base on house age, but distance between house and unattractive objects.

行動電話基地台設施近年來已逐漸成為一另類「鄰避設施」，然而其對於周遭不動產價值減損程度如何，國內尚缺乏相關研究。本文首先採用問卷調查法以瞭解居民對於行動電話基地台的相關看法及居民認知行動電話基地台對於住宅價格的影響程度；其次運用特徵價格法對於實際不動產成交價格資料，以迴歸分析方式驗證行動電話基地台對周遭住宅價格是否有影響及其影響程度。 研究結果發現無論問卷調查或特徵價格實證分析皆顯示行動電話基地台對周遭住宅價格影響是負面的，問卷調查的受訪者普遍對基地台設施存有負面觀感，且有高達54.4﹪的受訪者認為該設施對周遭住宅價格的負面影響程度在10﹪以上；而在特徵價格實證分析方面，研究地區內房屋所在樓層較高者（七樓以上）相較於較低者（七樓以下），其住宅價格更容易受到行動電話基地台設施的負面影響，而住宅價格因距離行動電話基地台遠近因素所受到折損程度平均約為2.35﹪，惟行動電話基地台設施之可視性因素對住宅價格的影響並不顯著。 / The cellular phone towers has become another NIMBY, although the absence of domestic research for how detract from real estate's value. The article first use the Questionnaire Investigation method’s way to realize that people’s opinion of cellular phone towers and cognition of the effective level of cellular phone towers on house’s price ; secondly use Hedonic Price Method on real estate's value, by using Regression Analysis’s way to prove the impact of cellular phone towers on house’s price . In which we found no matter Questionnaire Investigation or Regression Analysis both announces that the effective level of cellular phone towers on house’s price is negative, there are up to 54.4% of subjects involved in the survey though that the negative influence is above 10% ; on Hedonic Price Method’s way, the house whereabouts higher stairs on the area of researchs, its price is more easy effected by cellular phone towers than the lower one. And the house's price is effected by the distance of cellular phone towers that the average of detractive level is about 2.35%.Only the effect on cellular phone towers of the cause of visual by house price was not broad.

隨著社會經濟結構的轉型，目前台灣已邁向服務業為主的社會型態。為應該服務業及商業所需的辦公空間，因此辦公大樓陸續的興建。隨著近年來不動產的投資興盛，辦公大樓成為了外資或者保值的投資選擇。而判斷辦公大樓價值的標準即為該大樓所能創造的收益為何。辦公大樓的收益為租金，因此了解影響租金組成的因素，能夠提供我們在進行投資決策時一個參考的依據。但過去已有許多租金影響因素之研究，是以本研究擬從不同的觀點切入來探討租金的成因。 近十年來，國內許多豪宅或者知名的辦公大樓引進入物業管理的方式，取代了過去由管理委員會主導的管理模式。物業管理的興起，乃是人們對於住宅安全以及管理品質引申需求。對於物業管理的研究，國內目前仍著重在管理績效的衡量以及利用電腦提升物業管理效率的部分，鮮有探討辦公大樓租金與物業管理之間的關連。是以，本研究以台北市六行政區的辦公大樓為標的，利用特徵價格模型(Hedonic Price Model)和BOX-COX轉換，從物業管理的觀點來探討辦公大樓租金的影響因素。 / In Taiwan, business has become the main economic activity. The more prosperous business is, the more office spaces are requested. To understand the composition of office rent, hedonic price model is used as an analysis tool frequently. The varieties, such as age, distance of MRT, or standard floor, are usually used as the hedonic varieties. When property management is getting popular in the decade, there are few research use property management as varieties. To understand if the difference of property management style would affect the office rent, this essay used Box-Cox translation and Semi-Log regression to analyze the relationship between property management and office rent.

由於過去數年間金融業者對於授信品質控管的鬆散，產生國內數量及金額龐大的不良債權，資產管理公司也在此時先後成立，不良資產市場亦因而逐漸熱絡，在整體不動產市場占有一席之地。 從過去文獻可得知影響不動產價格之因素數量眾多，但過去較重視實質屬性對於不動產價格之影響，而較忽略非實質因素對於處分價格的影響，其中有關討論時間因素之研究更為稀少；然而由於不良資產同時包含了一般不動產的特徵屬性（如土地、建物面積及區位）與不良資產專有的特徵屬性（如債務人屬性、處分時間），因此進一步研究影響不良資產處分價格之因素便相對重要。 本研究目的主要在於探討影響不良資產處分時間因素對於不良資產處分價格之影響，以供投資人或公司更重視時間因素對於處分不良資產所產生的成本與效益，作為相關單位評估與處分價格之參考。 因此，本文首先探討影響不良資產處分價格之因素種類，並透過特徵價格法建置不良資產特徵價格模型，並進行實證分析，分析探討時間以及相關因素對於不良資產價格的影響關係與程度。 實證結果顯示處分時間、區位、土地面積、建物面積、利率與債務人屬性對於不良資產處分價格有正向的影響力，唯利率因素雖顯著但與假設不符，本研究認為與投資人之行為與心態有關，或因買方之資金成本隨利率提高而增加。 另特別就處分時間因素而言，實證結果顯示當不良資產處分時間越長，價格越高，因此，應合理延長標的物之市場曝光期，以提高資產的處分價格。雖然延長處分時間，相對機會成本亦增加，但投資人或金融機構應在法務流程上更有彈性，以利不良資產的回收。因此藉由本文之研究成果，希冀提供金融機構或資產管理公司處分不良資產時，應謹慎考量處分時間與處分價格間的得失權宜，擬定最適處分策略。 / Due to the loosening credit in the past few years, Taiwan’s non-performing loans, both in terms of volume and amount, burgeoned, resulting in rapid growth of establishments of asset management companies. NPLs consequently became one asset class that was highly sought after in the overall real estate market in Taiwan. From past literatures we understand that there are various factors affecting real estate prices. However, most studies focused on the physical attributes of the underlying real estate, rather than non-physical attributes’ effect on real estate prices. Even more rare are studies that focus on the impact of time. Since non-performing loans encompass both performing real estates’ attributes (land and building area, and location) and non-performing real estates’ attributes (characteristics of debtors and days on market), further study on such factors that affect the real estate prices should be warranted. This paper is to probe the effects of days on market on non-performing loans’ prices. This paper should help investors (including asset management companies) understand the importance of time in regards to its effect on the cost and benefits when disposing NPLs. Therefore, this paper first explores the different factors that affect the prices of NPLs by using Hedonic price method to build models to determine the prices, and then uses real examples to analyze the relationship and magnitude of time and other factors’ impact on NPLs’ prices. Empirical data suggests that days on market, location, land area, building area, interest rate, and borrower types all have positive impact on the prices of NPLs. Interest rate, although showed positive relationship, did not fit the hypothesis, which is probably due to investors’ behavior or mindset or increase in cost of funding as interest rate rises. Specifically for days on market, empirical results manifest that the longer the time on market, the higher the resolution price is. Therefore, it is recommended to reasonably lengthen the days on market to achieve higher resolution price. Although the increase in days on market will increase the opportunity cost, investors and financial institutions should be able to enjoy more flexibility in the legal process, thereby resulting in better recovery. Finally, through the research of this paper, financial institutions and AMCs should carefully consider the cost/benefit between time on market and resolution prices to achieve optimal resolution strategy.

Over the last decades, economics as a field has experienced a profound transformation from theoretical work toward an emphasis on empirical research (Hamermesh, 2013). One common constraint of empirical studies is the access to data, the quality of the data and the time span it covers. In general, applied studies rely on surveys, administrative or private sector data. These data are limited and rarely have universal or near universal population coverage. The growth of the internet has made available a vast amount of digital information. These big digital data are generated through social networks, sensors, and online platforms. These data account for an increasing part of the economic activity yet for economists, the availability of these big data also raises many new challenges related to the techniques needed to collect, manage, and derive knowledge from them. The data are in general unstructured, complex, voluminous and the traditional software used for economic research are not always effective in dealing with these types of data. Machine learning is a branch of computer science that uses statistics to deal with big data. The objective of this dissertation is to reconcile machine learning and economics. It uses threes case studies to demonstrate how data freely available online can be harvested and used in economics. The dissertation uses web scraping to collect large volume of unstructured data online. It uses machine learning methods to derive information from the unstructured data and show how this information can be used to answer economic questions or address econometric issues. The first essay shows how machine learning can be used to derive sentiments from reviews and using the sentiments as a measure for quality it examines an old economic theory: Price competition in oligopolistic markets. The essay confirms the economic theory that agents compete for price. It also confirms that the quality measure derived from sentiment analysis of the reviews is a valid proxy for quality and influences price. The second essay uses a random forest algorithm to show that reviews can be harnessed to predict consumers’ preferences. The third essay shows how properties description can be used to address an old but still actual problem in hedonic pricing models: the Omitted Variable Bias. Using the Least Absolute Shrinkage and Selection Operator (LASSO) it shows that pricing errors in hedonic models can be reduced by including the description of the properties in the models.