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Real Estate Research - samenvatting/transcript alle colleges

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Real Estate Research Master Real Estate Studies RUG Transcript van alle colleges

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Estudio
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Subido en
23 de noviembre de 2021
Número de páginas
149
Escrito en
2020/2021
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Resumen

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Real Estate Research 2020/2021
WEEK 1
Lecture 1 – Introduction
Monday 1 February 2021 – Daniele Mantegazzi

To do:
- Book ‘Real Estate Modelling and Forecasting by Chris Brooks and Sotiris Tsolacos
(2010). This book introduces and explains a broad range of quantitative techniques
that are relevant for the analysis of real estate data. The authors do an excellent job
of illustrating the practical application of the concepts to real estate
- 6 articles:
› DeMaris, A. (1995). A Tutorial in Logistic Regression. Journal of Marriage and the
Family, 57(4), 956-968.
› Gerking, S.D., and Weirick, W.N. (1983). Compensating Differentials. The Review of
Economics and Statistics, 65,
483-487.
› Koster, H.R.A, Van Ommeren, J., and Rietveld, P. (2014). Is the sky the limit? High-
rise buildings and office rents.
Journal of Economic Geography, 14, 125-153.
› Kuiper, N.M., Van Duijn, M., and Van der Vlist, A.J. (2020). Do urban redevelopment
projects create jobs? Evidence
from the Dutch National Restoration Fund. Working paper.
› Schafer, J.L., and Graham, J.W. (2002). Missing Data: Our View of the State of the
Art. Psychological Methods, 7(2),
147-177.
› Serrano, C., and Hoesli, M. (2010). Are Securitized Real Estate Returns more
Predictable than Stock Returns? Journal
of Real Estate Finance and Economics, 41, 170-192.
- Econometrics academy = for every methodology a video on methodology itself, a
technical perspective and an example how to use it in real life in stata. Watch the
first 3 video’s! First 2 on method, 3rd stata. On the site are the ppt slides and data
used in stata available. You can replicate what is shown in stata video.
- Perusall
- Group assignment

,Lecture 2 – Conceptual model building (example public housing)
Monday 1 February 2021 – Arno van der Vlist

Classes
- Substance and conceptual framework
- Statistical methods at work = real world applications
- Integrity/ethics in research = list assumptions: what is the implicit assumption you
make? include bookkeeping, what data do you include and what do you exclude?

Principles of Teaching (1)
- Learning is a consequence of [your] thinking, not [my] teaching!
- It happens when people reflect on and choose a new behavior (Harvard Business
Review Special, Winter 2020).
- Learning strategy: Aspiration, Self-Awareness, Curiosity, Beginners’mind (the more
mistakes you make, the more you learn)




There are 2 main ways of doing academic research, and a third combination:
1. Deductive approach= start from theory. Example: maximize income. On the basis of
assumptions, you start writing hypothesis using data to test for these. This is the
quantitative approach.
2. Inductive approach = observe a pattern in the data, in case studies. I don’t know if
any literature is there on this aspect. There is no theory and no testing procedure.
Then you start collecting empirical regularities using qualitative methods to enrich
theory.
3. Abduction approach = paper Heckman, 2017. Writing on abducting economics.
Bottom line of this paper is that deductive or inductive are no opposites or
better/worse. But we need an abductive approach. This is searching. Taking pieces of
theory, confront it with empirical regularities. A combination of deductive and
inductive.

,Course units
For RER
Substance: Appraisal & Automated valuation Methodology: Modelling & Forecasting
For ASA
Substance: no specific focus – but micro Methodology: Modelling but not forecasting

Today’s Learning Objective is conceptual model building.
Apply quantitative methods to real world problems:
A. From a societal problem to a research problem
B. Towards a conceptual model
C. How to explore data <–> conceptual model building

Households’ waiting time for public housing Topic:
Topic: Waiting lists for public housing. The time on a waiting list depends on the location. A
waiting list of zero means that you are not eligible for public housing or the supply might be
higher than the demand (which is not the case). The demand is high when the price is low,
and low supply. That’s why we expect a positive waiting time. Before starting research, you
need a sort of understanding of the problem and in this case the role of the institutions.

Societal questions may relate to:
- Efficiency of public rental housing → a public housing unit is given to the household
that deserves it best. The fundamental problem is that houses are offered to the
houses to a price lower than the amount they are willing to pay. The maximum rent
makes it inefficient.
- Equity/Distributional issues in housing → how is public housing allocated to different
households? Different households refer to differences in income, education, and
household type, is there an equal distribution? No because you need to be eligible.

A. From a societal problem to a research problem
› How do households choose a public rental unit?
› What is households’ willingness to pay for public rental housing?
› How can we identify the Marginal Willingness to Pay MWP for public housing
characteristics X?

B. Towards a conceptual model
Unregulated rental housing = no price regulations. So no waiting and high monthly rent.
Hotizontal H = amount of housing, quantity. Vertical R = rent, the price of the house.
A large house = a lot of rent, the opposite for small.
The blue line is the demand curve. When the price is low, there is a lot of demand and the
other way around. Price go down, demand goes up.
The other line is the supply curve, it’s upward sloping: when prices are high, the quantity
will go up.

, Regulated rental housing in NL, why? And what happens? The supply curve is fixed in
quantity.
Why waiting? R* is the optimal rent, where supply equals demand.




This graph is used as a simple visualization from the research problem




The costs are a combination of waiting time and the rents. Large grey house which is cheap
and a unit which is smaller and more expensive. Is it true that waiting times vary between
those houses? If yes, we can identify how households pay in rent and waiting time = building
the conceptual framework.

Formally:
Utility framework for households with housing h and other good o:
Budget restriction:
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