The challenge of resolving land use allocation and policy questions depends to a large degree on the conversion of data into information, and the effective integration of information into the decision process. Land evaluation is one of the fundamental means of generating information for land planning. Information products have however, been inconsistently and ineffectively used in the decision process. This thesis develops a decision centered approach to land evaluation as a response to this concern. Included in this development is a description of important theoretical concepts, as well as a practical demonstration of the use of decision support systems as a design approach. Initially, a conceptual model is introduced illustrating the technical and use components of information generation, as well as the adaptive design cycle. Various terms and techniques involved in the technical aspects of land evaluation are reviewed. Decision making concepts including decision structure, environment, analysis, and criteria are outlined. Three existing methods of land evaluation are then compared from a use or decision making perspective. Having completed a review of current approaches, Decision Support Systems are introduced as a logical progression towards a decision centered approach. Decision Support System design is demonstrated using a portion of the Central Fraser Valley Regional District as a case study area combined with an interactive microcomputer land planning tool (LANDPLAN). The demonstration emphasizes the advantages of the flexible, interactive capabilities of Decision Support Systems in aiding the decision process. Iterative design is also promoted with several needs identified if a more complete system is to be developed. In particular, data on strategic long term supply and demand factors is required, as well as continuous rating functions for assessing land performance. / Science, Faculty of / Resources, Environment and Sustainability (IRES), Institute for / Graduate

This diploma thesis deals with evaluation of the investment to purchase of a residential building in Brno-Řečkovice. The evaluation is based on the quantification of all costs and revenues associated with the long–term renting of apartments or selling them for short–term appreciation of invested funds. The important factor for achieving the desired return on investment is demand of the real estate market. The criteria that influence demand on the real estate market also influence the usual selling prices or rental revenues of residential units.

The doctoral thesis deals with the finding of a suitable approach for predicting the development of the residential real estate market, which would also be applicable in the practice of Experts and further develop the appraisal field. It has been found that a delayed multiple linear regression model appears to be appropriate, as confirmed by the verification of this model. The resulting model is also suitable for use in routine Expert practice, thanks to the simplicity of calculation without ownership of any computing program. Expert thanks to the created model is able to predict the development of the real estate market. The result is bound to the accuracy of the input data. All assumptions of regression models have been tested, optimal explanatory variables were selected based on backword regression. The doctoral thesis explains all input data, methods, tests, procedures and detailed modeling.

Riktvärdet på tomtmark har visat sig skilja mellan småhus på lantbruk och småhus på landsbygd. Detta uppmärksammades första gången av Lantmäteriet vid en jämförelse av taxeringen för lantbruk 2017 och småhus 2018. De har efter detta lyft problemet i arbetsgruppen som arbetar med förberedelsearbetet inför taxering. Syftet med studien är att undersöka om och i så fall hur skillnaderna i riktvärdet på tomtmark ser ut för småhus- respektive lantbruksenheter mellan taxeringarna 2017–2018 och 2020–2021. Studien går ut på att undersöka om det finns ett tydligt mönster eller om skillnaderna varierar mellan dessa olika taxeringsår. Studien avgränsades till Stockholms län och fokuserar på de värdeområden som 2017–2018 visade att tomtmarken hade fått ett högre riktvärde på lantbruksenheter än på småhusenheter, där skillnaden var minst 20 %. Studien omfattar även de värdeområden som 2020–2021 visade skillnaden på minst 20 % men som 2017–2018 hade en skillnad som var mindre än 20 %.Resultatet visade en relativt stor variation där några värdeområden fortfarande hade en skillnad på minst 20 %, några värdeområden hade denna gång inte någon skillnad alls och inågra andra värdeområden hade riktvärdena istället blivit högre på småhusenheter än på lantbruksenheter. Studien tar även upp hur förberedelsearbetet går till inför fastighetstaxering vad gäller småhus respektive lantbruk. Denna information är svår att läsa sig till på internet och i litteratur vilket gjort att den har tagits del av genom tre intervjuer med anställda på Skatteverket, Lantmäteriet och värderingsföretaget Svefa. / The guide value of plots of land have been shown to vary between small houses on farms and small houses in rural areas. This was first noticed by Lantmäteriet (the Swedish mapping, cadastral and land registration authority) when comparing the assessment of value for agriculture land in 2017 and single-family houses in 2018. The problem has been highlighted in the working group focusing on the preparation for assessment values. The purpose of this thesis is to investigate whether, and if so, what the differences in the guide value of plots of land look like for single-family and agricultural units between the assessments 2017–2018 and 2020–2021. The study is focused on whether there is a clear pattern or whether the differences vary between these different assessment years. The geographical area was chosen in the Stockholm County and focuses on the value areas that in 2017–2018 showed that the plot land had received a higher guide value of agricultural units than on single-family houses, where the difference was at least 20 %. The study also covers the value areas that in 2020-2021 showed differences of at least 20 % but which in 2017-2018 had a difference of less than 20 %.The result showed a fairly large variation where some value areas still had a difference of at least 20 %, some value areas had this time no difference at all, and some value areas had instead become higher for single-family units than for agricultural units. The study also addresses how the preparation work is done for property assessment in terms of single-family house and agricultural. This information is difficult to find on the internet and in literature, which has meant that it has been accessed through three interviews with employees at Skatteverket (the Swedish Tax Agency), Lantmäteriet and the valuation company Svefa.

The aim is to determine the price of a building selected for different purposes, using itemized budget and methods for valuation of property under applicable laws. Explain basic concepts in property valuation, explain their rationale, show the procedure of formation value by different pricing methods and selected construction object to demonstrate their use.

Thesis deals with appreciation of real estate investment before sale. Theoretical part of the thesis is describing basic concepts from the field of valuation of property and basic concepts of investment. There were also summarized basic types of investments, evaluation methods and financial expenses related to investment. Practical part of the thesis is focused on specific property, where were realized construction work. First of all were researched financial expenses of construction work, i.e. investment cost. The property was evaluated by three hypothetical variants of investment. Calculation of expenses related to borrowed capital followed. At the end of the thesis, the survey data were evaluated and compared.

Värdering av förvaltningsfastigheter är komplext. Det finns många olika metoder att använda sig av i värderingsprocessen kring förvaltningsfastigheter, vilket skapar en osäkerhet kring vad som är det korrekta värdet. Osäkerhet är ett bestående problem som alltid kommer att finnas i värderingsprocessen. Med anledning av att det alltid finns risker och utmaningar i vä rderingsprocesser är syftet med denna studie att undersöka, med utgångspunkt i två företag, vad ett företag som följer IFRS 13 och ett som följe r K3 har för värderingsprocesser. Syftet är också att unders öka utmaningar och risker i värderingsprocessen. Tidigare forskning menar att vä rderingsprocessen ä r komplex f ör den baseras på uppskattningar om framtiden, samtidigt är det av stor vikt att värde ringen blir så tydlig och korrekt som möjligt. Studien grundas p å en kvalitativ metod i form av semistrukturerade intervjuer, vilket innebär att intervjuerna bygger på teman. Teman i denna studie kommer att vara extern och intern värdering, värderingsprocess, risker och utmaningar. Genom intervjuerna uppkommer det empiriska materialet som sedan kopplas mot den teoretiska referensramen. Studien kommer att bestå av fem intervjuer och samtliga personer som intervjuas har en nära koppling till vä rdering av fastigheter. Alla intervjuer har skett på respektive företags kontor i Sundsvall. Exempel på frågor som ställs till intervjupersonen är, “Hur påverkas värderingen av konjunkturen?” och “Hur skiljer värderingen av fastigheter sig intern och exter nt?”. Resultatet av studien visar att det finns olika faktorer som påverkar vä rderingsprocessen, s åsom vakansrisken, hyresintäkter och driftkostnader. Det finns också en risk oavsett vilken värderingsmetod som företagen väljer att använda sig av. Nettonu värdesmetoden grundar sig till stor del på hyresintäkter vilket innebär att vakansrisken är en stor risk. Precis som nettonuvärdesmetoden är kassaflödesmetoden beroende av hyresintäkter. Andra risker med kassaflödesmetoden är att kostnaderna som är kopplade till fastigheten. Ortsprismetoden är en metod som många fastighetsbolag använder samtidigt som den kan vara problematisk, exempelvis på en marknad där det verkar ett fåtal aktörer kan det vara svårt att använda ortsprismetoden. / The valuation of an investment property is a complex process. There are many different methods for valuation that an assessor can use to valuate a property. This can create a risk of what the fair value should be. This study will analyze valuation of prope rties based on two companies. One of the companies is obligated to comply with IFRS 13 and the other company complies with K3. We will investigate, and analyze, which method for valuation the companies use and how they use the methods. We will also investi gate and analyze the risks and challenges the methods have. Previous research believes that the process of valuation is so complex because the valuation is based on estimates of the future. At the same time it is of great importance that the valuation beco mes as accurate as possible. The study is based on a quantitative method. The study will use semi structured interviews, which means that the interviews are based on different themes. The themes in this study are going to be extern and intern valuation the process of valuation and the risks and challenges. The empirical material of the study is a result of the interviews and these findings will be compared to the theoretical frame of reference. Five different interviews will take place. The persons int erviewed all have a close connection to the process of valuation of properties. The interviews have taken place at the offices of the companies in Sundsvall. An example of the questions asked at the interviews isis“ How does the economic situation in the country affect the process of valuation?” and,and,“ How does the process of valuation of properties differ internally and externally?” The results of this study shows that there are different factors affecting the process of valuation. These factors are the risk of vacancy, rental income and operating costs. There is a risk regardless of the method of valuation that the company uses. Net present value is largely based on the rental income which means that the risk o f vacancy is a major risk. The cashflow method is, like net present value, very dependent on rental income. Another risk with this method is the running costs of the real estate. The local price method is a method which many companies use even though this method can be highly problematic. Especially if there are only a few companies active in one area.

This dissertation investigates the financial health of municipalities in the United States, their margins of response to fiscal shocks, and their exposure and response to climate risk stemming from hurricanes. In Chapter 1, we construct a novel data set on the fiscal position of municipalities in the United States and document a secular decline in their financial health. Our data combines financial data from the Annual Comprehensive Financial Reports (ACFRs) of municipalities along with Census data of their revenue and expenditure cash flows. We find that a large share of municipalities operate with a negative net position---akin to a negative book equity position in the corporate context. We find that most of the decline originates from the accumulation of legacy obligations, i.e., pensions and other post-employment benefits (OPEBs); this is recognized by municipal bond markets through higher credit spreads. While accounting values from the ACFRs are informative, they are based on book valuations which potentially convey limited information about the economic value of assets and liabilities. Thus, we turn to the market valuation of local governments' equity by estimating an SDF that matches the valuation of a wide range of assets in the economy to prices future tax and expenditure claims. Using market prices for tax and expenditure claims, and market valuations of liability positions we find that the market values of equity are highly correlated with the book values. The negative equity position---in terms of book and market values---for some local governments suggests the presence of implicit insurance by the state and federal governments. The deteriorating fiscal position of municipalities across the United States raises questions about fiscal adjustment mechanisms municipalities have at their disposal and the general equilibrium effects of any adjustment taken. In Chapter 2, we utilize quasi-experimental variation in the year of property tax assessments in the state of Connecticut to provide causal evidence of the fiscal adjustment following a large decline in property values after the Great Financial Crisis. We find that local governments adjust tax rates to maintain stable tax revenues; there is no change in public employment levels and limited adjustments of public services. Our micro data on people's location further allows us to causally estimate the migration elasticity to a change in property tax rates. We find evidence of inter-state migration in response to an increase in property tax rates; and no statistically significant response of intra-state migration. Detailed property and location choice data reveal the elasticity of migration with regard to the property tax bill. An increase in the property tax bill by ten percent leads to an average increase in the migration propensity by about 1.5%. Finally, in Chapter 3, I investigate the investment component of local economic growth in municipalities after hurricanes. Using hand collected and web-scraped statutory property tax rate data in the U.S., I find that municipalities respond to hurricane impact by raising tax rates. I find the hike in tax rates is persistent for 3-4 years after hurricane impact. The response is four times larger for major hurricanes compared to minor hurricanes. However, the increase in tax rates is not expected to be large enough to cause significant out-migration after the average hurricane. I supplement these findings with a novel data set of firm facility-level hurricane impact. I find that firms initially decrease investment in the quarter following hurricane impact and increase it in the final quarters of the second year after impact. Taken together, this chapter presents a novel set of stylized facts on government and firm mitigation investment response to hurricane disasters. In particular, the precarious fiscal health of municipalities coupled with increasing costs of mitigating and managing climate risk poses serious questions about optimal policy in assisting local governments vulnerable to climate change.

The essay deals with what previous research exists within real estate valuation with artificial intelligence as well as the traditional real estate valuation process. Furthermore, it explains how the traditional property valuation process works and then further research on property valuation with artificial intelligence. Consequently, a few behavioral economics theories and the technology acceptance model are explained. Overall, it is being investigated whether they can make the real estate valuation process for commercial real estate more reliable and objective with the help of artificial intelligence. The choice to only investigate commercial properties is based on the expectation that a delimitation to a smaller research area will result in more precise answers. Furthermore, five interviews have been conducted with respondents to contribute with in-depth knowledge of the subject in question. The information that the respondents have contributed supports and mainly agrees with the developed theory. Advantages that have been identified in the paper are that artificial intelligence contributes to making the valuation process more objective and reliable, which in turn opens up more time for property valuers to analyze the values ​​presented. The respondents and their respective companies show a positive attitude and openness to working with AI. Artificial intelligence also means that valuers can take into account more value-influencing factors when making valuations. Something that should be taken into account in the respondents' answers is that there is a risk that the respondents are somewhat biased as AI is a technology that could potentially affect their work. The study mainly shows that the valuation process can become more efficient, objective and reliable if sufficient input data and comparison objects are available. An additional criterion that must be met is that there is a sufficiently well-developed AI system and an openness to AI among all actors in the industry. / Uppsatsen behandlar vilken tidigare forskning som finns inom fastighetsvärdering med artificiell intelligens samt den traditionella fastighetsvärderingsprocessen. Vidare förklaras hur den traditionella fastighetsvärderingsprocessen går till för att sedan forska vidare om fastighetsvärdering med artificiell intelligens. Följaktligen redogörs ett fåtal beteendeekonomiska teorier samt technology acceptance model. Sammantaget undersöks det om de går att göra fastighetsvärderingsprocessen för kommersiella fastigheter mer tillförlitlig och objektiv med hjälp av artificiell intelligens. Valet att enbart undersöka kommersiella fastigheter grundar sig i förväntan av att en avgränsning till ett mindre forskningsområde ska resultera i mer precisa svar. Vidare har fem intervjuer genomförts med respondenter för att bidra med ingående kunskap om ämnet i fråga. Informationen som respondenterna har bidragit med stödjer och stämmer huvudsakligen överens med den framtagna teorin. Fördelar som har identifierats i uppsatsen är att artificiell intelligens bidrar med att göra värderingsprocessen mer objektiv och tillförlitlig, vilket i sin tur öppnar upp mer tid för fastighetsvärderare att analysera de värden som presenteras. Respondenterna samt deras respektive företag visar en positiv inställning och öppenhet till att arbeta med AI. Artificiell intelligens innebär även att värderare kan beakta fler värdepåverkande faktorer vid värderingar. Något som bör beaktas i respondenternas svar är att det finns en risk att respondenterna är något partiska då AI är en teknik som eventuellt kan påverka deras arbeten. Studien visar huvudsakligen att värderingsprocessen kan bli mer effektiv, objektiv och tillförlitlig ifall tillräckligt med indata och jämförelseobjekt finns tillgängligt. Ett ytterligare kriterium som är tvungen att uppfyllas är att det finns ett tillräckligt väl utvecklat AI system samt en öppenhet för AI bland samtliga aktörer inom branschen.

Der Immobiliensektor trägt maßgeblich zur Treibhausgasemission bei und muss daher in den kommenden Jahren wesentlich verändert werden, um die notwendigen Einsparungen zu erzielen. Im Rahmen dieses Beitrags werden erste Untersuchungen dargestellt, den Wohnimmobilienmarkt mittels verschiedener Geosensoren zu erfassen, um aus den visuell erfassbaren Eigenschaften sowie geometrischen Informationen von Gebäuden Aussagen zu energetischen Zuständen von Immobilien zu tätigen. Dazu ist im Zuge eines Kooperationsprojekts der TU Dresden, der TU Clausthal, dem Fraunhofer IOSB-INA sowie der Geoinformationsbehörde des Kreises Lippe und dem Gutachterausschuss für Grundstückswerte im Kreis Lippe und in der Stadt Detmold eine Messkampagne durchgeführt worden. Im Rahmen dieser Messkampagne wurde eine Begehung durch Immobilienexperten sowie eine terrestrische und drohnenbasierte Erfassung mit RGB-Bildern, Laserscanning und Wärmebildern eines Quartiers durchgeführt. Die erfassten Eigenschaften von Immobilien werden in diesem Beitrag qualitativ diskutiert, um das mögliche Potenzial für eine automatisierte Bewertung des energetischen Zustands abzuschätzen. Durch empirische Untersuchungen sollen darüber hinaus die Werteinflüsse von energetischen Sanierungen auf die Verkehrswerte der Immobilien quantifiziert werden. Diese Information kann genutzt werden, um in etwaigen Förderprogrammen die Differenz zwischen den zu tätigenden Investitionen und dem dadurch hervorgerufenen Wertzuwachs zu fördern. In der vorliegenden Untersuchung kann gezeigt werden, dass Einschätzungen von Immobilienexperten zur Qualität von Immobilien zu guten Ergebnissen führen. Die genutzten Sensoren sind geeignet, Qualitäten und Schwächen von Immobilien aufzudecken, jedoch müssen die zeitlichen Konfigurationen der Aufnahmen optimiert werden.