Real-World Application and Analysis of the Wheaton Macroeconomic Model

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This report analyzes the Wheaton Model, a macroeconomic model used to determine newly constructed stock, asset prices, and rental prices in the real estate market. It explores the model's application, particularly in the housing market, and how it links information from asset ownership and leasable space markets. The report discusses the model's use by academics, investment managers, and governments for policy development and investment decisions. It highlights the model's ability to account for market fluctuations, its applicability in different settings, and compares the thought processes of practitioners and academics regarding the model. The report also addresses how axiomatic assumptions influence the model's real-world applicability and how the real world either confirms or breaks the model. The Wheaton model is essential for understanding the correlation between real estate assets and their use, making it valuable across property management, development, and valuation sectors. The report concludes by emphasizing the model's benefits for market development, despite its associated challenges.
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Running head: WHEATON MODEL 1
Wheaton Model
Name
Institution
WHEATON MODEL
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Introduction
The model known as Wheaton graphically determines newly constructed stock, asset
price, rental price, as well as the total number of stock in the market (a real estate market).
Wheaton model is one of the standard macroeconomic models (Bajari et al. 2013). This model is
currently one of the best documented as well as the most appropriate model of the real estate.
This paper discusses in detail how this model known as Wheaton can be put on use in the real
world. This paper is separated into different section. The first part discusses how axiomatic
assumptions affect the real-world applicability of this model. The second part illustrates how the
world either breaks or confirms the model. Finally, there is a comparison of the thought process
of practitioners and academic.
Application
The investment and academics managers can use the model to link information that is
generated from the markets for asset ownership claims and leasable space. The former is called
the space market, while the latter is called the Capital market. Initially, it was difficult for
academics to incorporate the two markets analytically (Norman et al. 2017). But for now, they
can apply the Wheaton Model to integrate the two markets analytically. The model divides the
space of the real estate into two different markets: the real estate assets and real estate space. The
real estate space represents a market determines the rent level and the housing stock while the
real estate assets is a market that determines the level of construction and the price level (Giglio
et al. 2016). Wheaton model can also be used to account for the housing market. The model can
be applied to demonstrate how the various kinds of exogenous stock can influence the property
market. For example, the model can be used to account for the yearly fluctuations for the housing
market price as well as construction in the United States. The model adopts the approach of a
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stock-flow explicitly to study the impact of different variables, such as household income, rental
price, housing stock, among others on the construction level and housing price. A research study
conducted by various researchers confirmed that Wheaton models are in line with reality
(Glaeser, & Nathanson, 2017). Therefore, the government can use the model to develop
appropriate, affordable housing. This policy can help the government to achieve the well-set
goals. This model can also be applied by the investors in making their decisions in determining
the level of price and purchasing real assets (Steiner, 2010). The information and data derived
from the housing market can be used by the investors to make vital decisions on whether the
investments will bring value in the long run. Also, this model can be used to offers a framework
that demonstrates the correlation between real estate assets and real estate use (Diedrichs et al.
2016).
To summarize, this model can be applied in a different sector of the economy namely
property management, property development as well as property valuation. Finally, this model
was initially developed in the United States to account for the housing market. Research shows
that it can be applied in the China market to account for their housing market development. The
model can be implemented in different settings, on condition that market segmentation is an
essential ingredient (Au, 2017). The researchers also confirmed that the model could be used by
the Western economies to account for the features of their markets.
Illustration of how the world either breaks or confirms the Wheaton model
The real world confirms the model in that most of the countries uses the model to account
for their housing market. For example, the United States developed the model to consider for its
housing market. It is also true that China can also use the model to enhance its housing market.
How the axiomatic assumptions of Wheaton Model affect its actual world applicability
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The axiomatic assumptions affect the application of the model in that they enable the
theory to lose its strength and some of the premises may be incorrect. The assumptions may fail
to provide facts about the information provided by the Wheaton model. They also contain no
proof in the system that they are defining. It is also difficult to find out whether axiomatic
assumptions are the facts. In comparison to the Wheaton model, the axiomatic assumptions will
fail to provide clear facts relating to the housing markets.
Comparison of the thought process of practitioners and academics
Academics such as academics managers thought that the model is more useful since it
links information generated from the markets for asset ownership claims and leasable space.
Academic researchers find Wheaton model to be very important for both empirical and
theoretical analysis. This information from the housing market can be used for the decision-
making process, while practitioners generally do not select to exposit it. This is because of the
difficulty associated with the graphical determination of values of equilibrium of the endogenous
variables used during the calculation. Practitioners are only aware of supply and demands
because most of the books contain the discussion, but few books contain the discussion of
demand and supply curves. This makes the model to be difficult to many of the practitioner
because it uses demand-supply analysis.
Conclusion
This paper discussed the application of the Wheaton model in the real world. It is true
that this model was developed in the United States to account for its housing market. Researchers
found out that this model can now be applied in the China market since it performed well in the
United States housing market (Aten et al. 2018). Wheaton model is essential to both the
investments and academics managers as they can use the model in linking information from
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different markets for examples markets for asset ownership claims and leasable space. The
government can use this model to develop appropriate policies such as price fluctuation policies.
Although there are some challenges associated with the model, researchers found out that this
model can offer more benefits to a country in terms of market development.
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References
Aten, J. D., Boan, D., Davis, E. B., & Schruba, A. N. (2018). The Humanitarian Disaster
Institute: A training model for graduate-level psychology and counseling
programs. Journal of Psychology and Christianity, 37(1), 80-86.
Au, A. (2017). The sociological study of stress: an analysis and critique of the stress process
model. European Journal of Mental Health, 1(12), 53-72.
Bajari, P., Chan, P., Krueger, D., & Miller, D. (2013). A dynamic model of housing demand:
Estimation and policy implications. International Economic Review, 54(2), 409-442.
Diedrichs, D. R., Phelps, K., & Isihara, P. A. (2016). Quantifying communication effects in
disaster response logistics: A multiple network system dynamics model. Journal of
Humanitarian Logistics and Supply Chain Management, 6(1), 24-45.
Giglio, S., Maggiori, M., & Stroebel, J. (2016). Nobubble condition: Modelfree tests in housing
markets. Econometrica, 84(3), 1047-1091.
Glaeser, E. L., & Nathanson, C. G. (2017). An extrapolative model of house price
dynamics. Journal of Financial Economics, 126(1), 147-170.
Norman, L. M., Sankey, J. B., Dean, D., Caster, J., DeLong, S., DeLong, W., & Pelletier, J. D.
(2017). Quantifying geomorphic change at ephemeral stream restoration sites using a
coupled-model approach. Geomorphology, 283, 1-16.
Steiner, E. (2010). Estimating a stock-flow model for the Swiss housing market. Swiss Journal of
Economics and Statistics, 146(3), 601-627.
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