Factors Determining the Continuous Price Appreciation of Condominium Units in Addis Ababa

Factors Determining the Continuous Price Appreciation of Condominium Units in Addis Ababa
Factors Determining the Continuous Price Appreciation
of Condominium Units in Addis Ababa
Hemen Melesse
Lecturer, Department of Land and Real Property Valuation, Dire Dawa University, Dire Dawa, Ethiopia
Email: hemenmelesse7@gmail.com
The rapid growth rate of Addis Ababa’s population has resulted in a growing demand for
residential housing. Hence, the Ethiopian government reacted to launch condominium program
to improve the housing problems of the poor. However, the continuous appreciation of this
condominium transaction price and unaffordability of the units for the poor were some of the
challenges to this housing program after transfer. This study aimed to explore the major factors
responsible for price appreciation correlated to the demand. Descriptive research method and
mixed research approach have employed on three pilot study areas through, purposive selection
focusing on two municipal districts in Addis Ababa. Both primary and secondary sources of data
were used by means of questionnaires, interviews and a review of relevant documents. The OLS
estimators have resulted highly statistically significant for the expected variables of year, area
and location in determining the price suggesting further contributing factors from the actual
findings. Actual findings thus identified; lack of information, illegitimate role of brokers and
monopolistic housing supply as major determinants. Finally, this study has recommended
passing regulations and directives can minimize the incremental rate of the condominium
transaction price considering all the challenging factors of the sector having clear and reasonable
valuation methods.
Keywords: Condominium, Determinant factors, Housing Demand, Price Appreciation, Transaction, Poor
INTRODUCTION
Housing is one of the necessities for human survival, due
to the stagnant nature of the property; effective housing
delivery has been difficult for governments to fulfill the
need of their residents. Thus, it is considered as one of the
sectors that serve as a tool to address poverty and bring
sustainable development (UN-HABITAT, 2003). In
accommodating some section of the society, Governments
have housed some of their own employees like their
Armed forces and University Teachers.
After time being, the growing population became the
strongest underlying reason for huge demand in
accommodation and real estate properties across the
developing countries. According to (John-Paul (founder
and head of small starter Africa), “Africa is the hottest
property market in the world”). Sub Saharan Africa’s
largest cities are currently some of the fastest- growing
urban areas in the world. This is already creating
shortages and a considerable impact on property prices
(K., Frank, 2017). Other than the demographic issues,
interest rates, the economy, government policies and
subsidies also determine a real estate market (Sisay, Z.,
2014).
Since Ethiopia could not cope with the fast-increased need
for the last four decades, the Ethiopian government
involved in the supply of vertical communal housing called
a condominium. This has initiated by Addis Ababa City
Administration with a new site expansion and
redevelopment approach (MoWUD, 2006), aimed at
affordability-based supply and owner-occupied
condominium units considered to address the insufficient
housing and improved lifestyle of the pro-poor urban
dwellers. According to (UN-HABITAT, 2010), this program
has first contributed to progress towards an improved
housing market by legalizing housing supply, stop illegal
development and increased the number of official property
titles on land in Addis Ababa.
Research Article
Vol. 4(1), pp. 064-078, June, 2020. © www.premierpublishers.org. ISSN: 1936-868X
World Journal of Civil Engineering and Construction Technology

Melesse H. 65
In other way, the middle-class communities have faced
problems associated with the absence of sufficient land
provision that excluded from collateral valuation for land
and necessary construction instruments supply like,
cements and metals limited below the required level.
Moreover, buildings under construction were always taking
too long and construction capacity of the country was
limited to meet the required level of demand, poor
borrowing capacity and as a result of lower per capita
income and their earning capability, the low and middle
income earners have been wiped out from the loan market
(Zerayehu, S. and Kagnew, W., 2015).
Following to the intolerable fact of the down payment and
interested overdue along the poor, the Government has
permitted transfer to the third person assuming; if
beneficiaries had the financial capacity to meet their
mortgage obligations. However, this has led to the
unexpected and unforeseen active transaction of the
property synergic by high-value rent and sell; that lead to
high space demand and uncontrolled price appreciation.
Several studies have also examined and investigated on
the Problems and prospects of housing development and
Property management in Ethiopia. As (Abraham, 2007),
concluded that in this transaction there is unless, an
accumulated demand for residential housing and
otherwise, the low supply of residential housing had
pushed prices. According to Addis Ababa city
development office, in 2011 above 52 percent of the total
population of Addis Ababa, earns below the least scale of
the salary of the civil servant. This becomes a constraint to
the low and middle-income residents to pay the down
payment. Correspondingly, (Bereket and Nigatu, 2015) in
their study found out that some households could afford
with less than a quarter of their income, some might not
possibly afford housing-while others had the ability to
afford more than quarter and even more without hardship
on the transaction.
Because of the above inspection, limited researches were
conducted to identify the determinants of house price more
particularly on condominium transaction. Instead, most of
the present studies mainly assessed Governments’
transfer price, affordability, transparency and other social
phenomena. Thus, this study intended to fill the knowledge
gap associated with identifying factors who are
responsible for the incremental sale price in Addis Ababa
condominium housing transaction, with regard to the
consecutive socio-economic problems. Specifically, the
study aims:
o To identify market contributing factors of the
condominium units.
o To evaluate factors to the price appreciation in
condominium housings
o To assess the demand shift factors of housing to
condominium properties
o To compare condominium housing transactions with
other real estate transaction
RESEARCH METHODOLOGY
Addis Ababa is the capital city of Ethiopia, the seat of the
African Union (AU) and the United Nations Economic
Commissions for Africa (UNECA). It is situated between
8055' and 9005' North Latitude and 380 40' and 380 50'
East Longitude in the central plateau of Ethiopia. Addis
Ababa is a chartered city having three layers of
government: city government, sub-city administrations,
and district (Woreda) administrations. The city
administration divide Addis Ababa into 10 sub cities and
one hundred seventeen woreda administrations.
Currently Addis Ababa became a just one center for CBD
and Polycentric or located multi small centers. Expansion
is behind the demand of housing and the provision of
public condominiums and other industrial developments
on the level of parks. Since the government has introduced
national condominium housing program in 2005, Addis
Ababa city Administration has transferred 175,000 units by
13 years (Yared, T., 2018).
Map 1: Location Map of Addis Ababa and the selected
Bole and Lideta sub cities
MATERIALS AND METHODS
Condominium housing has mainly and firstly, tested in
Addis Ababa city both functionally and economically of the
city could not manageably address the increasing amount
of demand for housing due to the growing population. The
study also tried to select Addis Ababa as a potential
information area regarding to institutions such as
Economic ministry, National Bank, Housing Administration
and Real estate agencies. Detailed selection has

World J. Civ. Engin. Constr, Techn. 66
employed on the action areas under 2 sub cities that were
mainly practiced in their several typology and bases of
inner-city development and mostly offering agricultural
land for a new expansion.
Bole and Lideta subcity; specifically, Bole Gerji, Bole
summit II and lideta condominiums. Bole Gerji was a
relatively small pilot project on a brown-field site and led
by GTZ with (G+2) typology in 2008. Bole summit; the first
grand project built on the edge of the city in 2014 (G+4)
typology and Lideta was an inner-city upgrading project
that was the first project to use a ground floor plus seven
storeys (G+7) condominium typology.
Figure 1: Common Spaces in Lideta condominium
Figure 2: Gerji condominium site
Figure 3: Summit condominium
Purposive Sampling method has employed on the primary
data collection method to select respondents.
Questionnaire survey, interview and discussions. Two
types of questionnaire has provided, one for the target
population of household in the selected condominium units
and other to the selected institutions. Structured interview
as well as key informants interview has provided to get
clear issues and address the question on both the dwellers
and professionals to share their first-hand knowledge and
experience on the market encounter. Moreover, Focused
group discussion has made between the major housing
Administration officials.
Secondary data for the study mainly used on macro-
economic indices in Addis Ababa from the period 2009 –
2019. These macro-economic indices were seen
according to inflation rate on the consecutive years, the
increased rate of price and condominiums interest rate.
Most of the information pertaining were obtained from
previous survey, literature and annual reports from various
institutions such as; Growth and Transformation Plan,
National bank report, registration contracts and transaction
contracts.
As a result, and analysis stage, triangulation method has
used to analyze the data from different sources. This has
employed by organizing the data through the identical
ideas from the quantitative and qualitative documents to
make the study more reliable, this data had refined by
analyzing the data using Statistical Package for Social
Science (SPSS), STATA version 15.0 for Windows (Stata
Corp. College Station, TX, USA). Moreover, multiple
regression analysis (MRA) techniques have used as
multiple factors in calculating the analysis separately to
quantify the impact of numerous influences upon a single
dependent variable. Every single factor has calculated by
its average index respect to a few levels of influence under
respondents’ opinions. The index will then treated as
influencing the level of the factors.
Model Specification
Multiple Regression can incorporate general functional
form relationships as well as it allows for much more
flexibility. The method of ordinary least squares (OLS)
regression model employed. Based on the sampled data,
the study employed over quantitative method on both
response and control variables. Thus, there was data of 37
sold condominium residential units taken from the three
condominium sites with their full information and analyzed
by using the multicolleniarity test using linear regression
analysis among the following factor variables
Equation 1: Log (House Price) = 𝛽0 + 𝛽1 𝐿𝑜𝑐𝑎𝑡𝑖𝑜𝑛 +
𝛽2 𝑁𝑢𝑚𝑏𝑒𝑟 𝑜𝑓 𝑏𝑒𝑑𝑟𝑜𝑜𝑚𝑠 + 𝛽3 𝑌𝑒𝑎𝑟 +
𝛽4 𝐼𝑛𝑡𝑒𝑟𝑛𝑎𝑙𝐹𝑙𝑜𝑜𝑟𝐴𝑟𝑒𝑎 + 𝛽5 𝑆𝑡𝑜𝑟𝑒𝑦𝑇𝑦𝑝𝑒 +
𝛽6 𝐼𝑛𝑓𝑙𝑎𝑡𝑖𝑜𝑛 + 𝛽7 𝐼𝑛𝑡𝑒𝑟𝑒𝑠𝑡𝑟𝑎𝑡𝑒 + 𝑒
Source: Reference: (Gujarati , 2004)
RESULTS AND DISCUSSION
Pilot survey
Demographic features occupants
The main determinants of demand in the housing market
relate with demographic factors. However, factors such as
income, availability of credit, and customer preferences
are also important. Demographic factors include the size
of the market because the more the consumers, the higher
the demand, as well as the rate of marriages, divorces and

Melesse H. 67
deaths, which provide an idea of the population growth.
This growth is the strongest underlying reason for huge
demand for accommodation and real estate properties
across the developing countries (K., Frank, 2017).
Similarly, (Sisay, Z., 2014) and (D.B. Animansa and G.,
Danimi, 2014) in their findings, the other demographic
factors are family size, Age, migration and life-cycle stage
are the supportive factors for the demand of living in
condominiums. Furthermore, there are various
demographic and socioeconomic changes of the city
during the last decades influencing to create the
condominium property market. Particularly, well-educated,
middle-income earning people who migrated to the city for
various reasons have raised the demand for low-rise
condominiums while foreigners and the affluent ones have
raised the demand for high-rise condominium property
considering the security, convenience and location.
According to this study in the income category, above 29%
of the respondents were civil servants, 63% of them work
in private organizations and self- employed and nearly 8%
were with other sources of income.
Figure 1: Pie chart of occupation
Figure 5: Pie chart of income level
From the questionnaire survey, occupation specified about
6.5% from relocation, 21.5% purchase and 69% from rent
and others. As the number of rooms inspection showed
that, about 22.6 % of respondents lived in a studio, 35.5%
in 1 bedroom, 22.5% in 2bed rooms and 19.4% in 3
bedroom units. This shows more of the people prefer a 1
bedroom unit indicating small family size (i.e. a new
bridegroom and no child), about 29% had no child or
family, 53.8% were from 1- 4 children and the rest of 17.2%
of the household had up to 7 families with large in size. On
the final variable amenities, the total respondents about
70% were accessible to amenities and the rest 30% were
in lack of amenities.
Table 1: Demographic characteristics of condominium
housing respondents
s/no Variables Variable category Percentage
(%)
1. Income
Civil servant 29.0
Private 63
Other 8
Total 100.0
2. Education level
Illiterate 24.7
High
school/certificate
2.2
Degree and above 73.1
Total 100.0
3.
Occupation
Relocation 6.5
Purchase 21.5
Rent 68.8
Lottery 1.1
Others 2.1
Total 100.0
4.
Number of
bedrooms
Studio 22.6
1bed room 35.5
2bed room 22.6
3bed room 19.4
Total 100.0
5.
Family size
no child/family 29.0
1-4 53.8
4-7 17.2
Total 100.0
6. Amenities
No 30.1
Yes 69.9
Total 100.0
According to the government officials’ perspective,
Condominium program aimed at targeting lower-income
groups but the current occupation was from better income
individuals with higher prices. Evaluations showed that this
price was more than twice the transfer one. It does not
compare with the income of dwellers and the construction
cost.
Figure 6: Chart on Condominium transfer, rent and
average resale price change on a one-bedroom unit from
2009 - 2019
Source: (allaboutEthio.com by Mengistu, T., 2018)
(ezega.com by Samson B. 2015)

The Demand and Supply Factor to House Price
As (D.N. Dwivedi, 2010) inspected that, the main
determinants of demand for housing are demographic but
other factors like income, price of housing, cost, consumer
preference, investor preference, price of substitutes and
price of complements, all play a role. According to
(Arvanities, Y., 2013), More than often, studies on housing
markets tend to focus on the demand side, and in
particular the mortgage market. The real estate developers
have a higher capacity to execute projects as well as to
bring well-built units at reasonable costs into the market is
a key determinant of housing supply. Real estate
developers in East African countries found to lack
experience, which usually comes with a lack of record of
accomplishment thus making financing more difficult. This
often induces a degree of execution risk. Lack of access
to finance for developers means they must resort largely
to pre-sales in order to sector cash flow. Any delay in
payments, or difficulties to sell on plans puts developers in
a difficult position to keep projects within expected time
schedules as well as within budget.
Accordingly, condominium units in the city showed that
selling price ranges from 15,625$ – 93,750$ and about 72
% of the dweller purchased a unit by 15,625$ – 40,625$,
about 20% from 43,750$ - 78,125$ were purchased, the
rest 8% could have purchased above 78,125$ - 93,750$.
The units were rented from 94$ - 469$, above 60% of the
units from 94$ - 188$, about 35% from 188$-313$, the rest
4.5% were rented the unit from 10,000$-15,000$. The third
category, relocated ones shown that government’s sell
price is based on the integrated units that have transferred
including the 12th round transfer price in 2019 counting the
6.5% interest rate.
Based on the interview results, there were also differences
between the transfer price and the current transaction, For
example as the price of transfer for 20/80 studio typology
in which one small room as a dining, living, and bed, was
transferred for 5,156$ but they would have sold up to
46,875$. Another 10/90 typology with an amount of 2,500$
would have sold up to 25,000$ which was about 10 times
that of the transfer price. It does not compare with the
income of dwellers and the construction cost. On these
transactions, the highest benefit was for the lucky lottery
winners than people relocated because they were savers
from earlier that made it easy for them to pay the loan.
Therefore, from the result, the relocated ones were more
sellers than the lucky lottery ones.
Table 2: The transfer price (cost) of condominium housing units by the Government from year 2012 - 2019
Item 2012-2016 (7thth - 9th round) 2016-2018 (10th-11th round) 2019 (12th round)
Down
payment
Monthly
Payment
Total
Payment
Down
payment
Monthly
Payment
Total
Payment
Down
payment
Monthly
Payment
Total
Payment
Studio 348 - 1510 617 22.5 3086.46 - 82.7 -
One bedroom 604 - 2740 1170 43.6 5850.8 - 114.6 -
Two bedroom 1201 - 5607.8 2199 90.9 10,982.3 - 146.5 -
Three bedroom 1460 - 6849.3 3179 131.9 15,894 - 159.2 -
Source: (AAHAA, 2018)
According to Housing Administration, not the demand but
housing supply is the reason to the rise in price, and other
real estate developers holding a wider area afterward they
sell the land with added price, this made the price to
increase. Even the main accelerators on the supply and
demand space market may be mainly the bank and the
dwellers used for these units and there stands
disequilibrium between demand and supply. Moreover,
The reason for this problem was not only the construction
price but also variety costs were added including waste
costs such as corruption cost, mismanagement cost, delay
cost, etc. so the current condominium demand volume
shift factors were corruption, mismanagement, wastage of
materials, delay of construction, labor and bank interest.
About 50% of each officer respondents from different
offices said that government finance and inflation were the
reason for the transaction price and instability. Therefore,
dweller's income + selling price + government finance
were the factors for customer demand. Moreover, about
78% of the professionals agreed with the demand for rental
units and inflation factors on the resale price by shifting
demand towards these condominiums. This shift was due
to brokers’ involvement in getting benefits on the
condominium properties, government flexible
management and lack of control. Land value and
dynamics of raw materials price for construction were also
the reason for the fluctuation.
Marketability Factor
Demand is the buyer’s intentions and plans with respect to
the purchase of a product with a specific time. The law of
demand has also stated that a relative price of one good
rise, fewer goods would have bought. In the case of real
estate; housing price confides in the law of supply and
demand. When demand for property remains high but
scarce in quantity, prices skyrocket. However, real estate
trends focus on the business and structural changes
affecting the industry, this is from the case of the
neighboring country Kenya (Muli, 2012). These factors
were affecting to influence the demand upturn of housing
in the short run, such as the shift from D0 to D1 there by
either a price or quantity adjustment or both. For the price

Melesse H. 69
stayed the same, the supply of housing would increase.
That is, supply SH0 would have increased by HS. If the
construction cost increase, CCo-CC1 developers find their
business less profitable and they were more selective in
their ventures. Some developers may also leave then the
quantity decreased, which eventually decreases the
supply then prices tend to rise.
According to (D.N. Dwivedi, 2010) states, market needs an
easy to enter and exit, perfect competition and higher
interest rates that the majority of customers do not affect
by the higher interest rate; but as a result of the existed
monopoly, the only seller could maximize profit especially
for the stockbrokers. Monopoly pricing was practiced as a
low level of output but higher profit. The result of the study
has realized that current Addis Ababa condominiums were
lower in quality but higher in demand and transaction that
even would be able to change the behavior of the rich and
the poor.
Among the open-ended questionnaire answers, more than
50% of the professionals agreed with consumer taste as a
factor for affecting the demand, about 75% of respondent
officials agreed with consumer expectation and more than
72% of them strongly agreed with that of material costs.
Eccentrically, about 90% of these officials agreed on the
disequilibrium of supply and demand to the condominium
units. Of the sample respondents, about 78% agreed with
the demand for rental units and inflation factors on the
resale price by shifting demand towards these
condominiums.
Condominium Marketability and Active transaction, when
compared to other real estates, looks more active.
According to the questioner survey, more than 87% of
respondents agreed on higher housing demand and small
in a number of available units and unaffordability of the
present housing price, mainly on the apartments.
However, these professional respondents agreed on the
buyers and sellers get imperfect information about the
other private or cooperative real estate types from the
quality or construction level, ownership right and market
facts.
Locational Factor
Location is the main decisive factor that the distance from
home to work, schools, shops, hospitals and important
factors that make up a good location in connectivity/
accessibility, utilities, existing and upcoming
developments and social infrastructure. Thirdly,
infrastructure quality of life namely transportation,
neighbors, recreational areas, water supply, sewerage,
power, phone-connectivity, waste disposal and amenities:
from the social infrastructure, playgrounds, adequate
parking space and security are an important part of home
life. These are the Determinants of Transaction Value
Factors on Condominium Properties (Lonappan, J., 2013)
studied that there is a great deal of diversity among
neighborhood structures with in metropolitan areas; in
turn, it has a higher impact on the valuation of structural
attributes on the preference of customers.
As (Aluko, O., 2011) and (J, Jayalath, 2016) revealed that,
neighboring factors has s a higher impact on the valuation
of properties on the preference of customers. Community
attributes has related to availability of schools, universities,
religious palaces, court ordered service and so on, are
affecting the market value of the condominium properties.
Moreover, availability of institutional facilities, social
organizations and recreational facilities are community
factors that affect market value of a property.
Most of the dwellers in Gerji site are large families with
children that get their very need proximity to the almost
amenities were fulfilled such as; (schools (3-5min), clinic
(3-5 min), recreation (3-15min) adult walk. Moreover, it is
restricted from high transport modes so better to live there
and have better economic activity in a neighborhood. On
the Summit site, most of the living units have occupied by
single dwellers. Dwellers take the time of average 1 hour-
2:30 on their way to work, of 30 min- 2 hours for other
social services. This is as far as what they need in
inefficient infrastructure and the Lideta site from the
dwellers above 50% are doctors from the Black Lion,
largest Hospitals in the city and the country and merchants
from the Merkato, the largest market from the city and
country. As a CBD Lideta is accessible for any need,
therefore, the units were more valuable, noisy and higher
crime levels compared to the others.
Map 2. Location of Lideta condominium near to a CBD
and main centers
According to these housing unit conditions as a preference
(LIKE MOST) to condominium units, the largest population
approximately 47% has preferred the unit based on
Location factor (i.e. proximity and accessibility). The
second largest liked from the unit was about 18.3% of
households, were selected by the availability of utilities.
The third population share 34.7% were completely
dissatisfied with their unit conditions and the rest chose the
unit by its amount of space and number of rooms. On the
contrary, the second variable, (LIKE LEAST) showed the
largest share is 61.7% of the respondents’ informed poor
drainage as the least feature about their unit. Almost

38.3% of households disliked the scarce to enough space,
poor quality, lack of utilities, poor drainage, and Location
(far from centers).
As stated by the findings in (J. Kahr and M. C. Thomsett,
2005) analysis, traffic patterns, location of regional and
local jobs, transportation issues (public as well as auto-
based transportation patterns), and the proximity from the
site to schools, shopping, and other local amenities are
main factors affecting housing market. The shape of the
market is not also likely to be round, but is more likely to
follow development and roadway factors, location of jobs,
and the competitive factors existence of competing or
planned apartments within that realistic market area.
In this Study, one of the most features choose to live was
neighborhood, and the result showed that; from the
positive (BEST FEATURES) above 31% of the
respondents preferred their quarter with its access to
utilities. The 19.4% population prefer proximity to social
services and the rest 23% were by the familiarity of the
area and closeness to their work. In the contrary, (WORST
FEATURES) 29% of the population had seen their
neighborhood as poor access to jobs and social services,
about 34.4% for its poor infrastructure and (17.2%) for poor
drainage and most of all about 10.8% of the respondents’
distress with the crime level of their neighborhood.
Table 3: Characteristics of condominium dwelling units and conditions
s/no Variables Variable categories No of respondents Percentage (%)
1.
LIKE MOST
Amount of space number of rooms 8 8.6
Quality of unit 4 4.3
Location 44 47.3
Utilities 17 18.3
Other 2 2.2
Completely dissatisfied 15 16.1
All 3 3.2
Total 93 100.0
2.
LIKE LEAST
Not enough space or rooms 17 18.3
Poor quality 9 9.7
Utilities 5 5.4
Poor drainage 28 30.1
Location 11 11.8
All 19 20.4
Completely satisfied 4 4.3
Total 93 100.0
3.
UNIT COND
Good 28 30.1
Fair 63 67.7
Bad 2 2.2
Total 93 100.0
4. BESTFEATURE Proximity to work 10 10.8
Access to utilities 29 31.2
Familiarity to area 12 12.9
Proximity to social services 18 19.4
Nothing 11 11.8
Everything 13 14.0
Total 93 100.0
5. WORSTFEATURE Poor drainage 16 17.2
Poor infrastructure 16 17.2
Poor neighborhood 3 3.2
Poor access to jobs, social services 27 29.0
High crime level 10 10.8
Completely satisfactory 11 11.8
All 10 10.8
Total 93 100.0
Challenges on the condominium Transaction price
management after transfer
Based on the officials’ response from the open-ended
questionnaire, perceptions flowed that; on the inner city
there was no means of housing to the low and middle-
income individuals and even the delay to supply perceived
as the demand shift to the existed units. Corresponding to
the economy of the society, there were no better
alternatives to have a house that is the reason with the
higher demand. Furthermore, the government constructed
condominiums delay with different complications
exacerbate the selected problem mainly for low and
middle-income citizens.

Melesse H. 71
The lower-income level of the society plus higher land
value and scarcity influences the price of rent in the city.
Land tenure issues, a supply of land and its incremental
price brought a narrow opportunity to the individuals to
build their homes with a medium potential. Therefore,
currently, the prime choice to occupy with middle income
as a real estate remains these condominium units. The
society with a misunderstanding and a less adaptation on
an integrated residential building moreover the selected
units associations were self – administrative, this became
a bottleneck to the management and administration.
People with many homes tend to occupy the units and
marriage conditions (they made fraud using marriage and
separation), lottery view cases moreover the system of
thrift for the units and corruption were the main deceptive
activities on the dynamic market exercise.
Therefore, the current housing transaction in Addis
Ababa was very unhealthy and unsound. The role of
brokers was very high mainly on price variation and
dynamics, which means they made a big role in making
fluctuations as their wish in order to increase their
commission acting for sale by harrying the purchaser and
the seller in between. Based on the gradational difference
of the condominium transaction price, boosted the higher
the rate day-to-day and has created market instability.
Challenges used to address condominium housing
problem-related factors
According to the transaction offices on the sub-cities, the
site planning problems and sanitary problems were the
main causes of the disagreement between dwellers and
their neighbors. Another management problem was the
fraud of selling the units in a mortgage way before the five
years (within the prohibited period) illegally. In order to gain
additional profit dwellers, use illegal construction on the
units. In construction, the quality construction material is
critical because the building must get proper strength, in
bole site materials were obviously not as a requirement.
There was no quality work of construction according to its
durability and quality; that was very poor. Furthermore,
there were wastages in both material and funding that
expose to the scarcity of finance. Government finance
does not allocate in a proper way for the targeted area
seen through the quality, the scheduled time, how fast it
goes and evadable information about it. Generally, about
50% of each officer respondents from different offices said
that land value and dynamics of raw materials price for
construction were the reason for the fluctuation.
Quality, supply, and finance were the main encumber in
one way or another, more of the poor especially the pro-
poor was not advantageous and there was a gap with the
granted occupation for the deserved community than that
of individuals with one or more houses. Very few affluent
were the only homeowners and monopolized the market in
a disposable way. It was too much to afford, high price and
low quality regarding these material usages and even they
have a design problem. Moreover, there were a number of
factors that determine condominium market one was the
cost of purchase; it has to be some legal frameworks about
the condominium sale price, but the ups and downs
coordinated by illegal brokers. It yields a cause to the
gentrification of the poor for the reason that of the value of
high price on the CBD (central business district).
Analysis in an Econometric Setting
For convenience in analyzing the ratio variables, the
econometric model has set up in an analysis pattern based
on secondary data of the 37 sold residential units on the
selected sample condominium sites in Addis Ababa from
the year 2015 - 2019 G.C.
The determinants of condominium housing prices were
analyzed by identifying factors influencing the unit's
transaction, its demand and price appreciation by using
multiple linear regression models. This was done based on
the relationship established between housing price
(dependent variable) and the independent variables. In
line with the continuous character of the data consists;
Time, money, inflation and interest rate and in order to
define the dependent and independent variables
appropriately was encountered regression equations
where the dependent variable appears in a logarithmic
form (log-level). It is the percentage increase in price the
same increase in one percent explaining the variation as a
function of house price with certain explanatory variables
data set such as the amount of bed, internal floor area (per
Square meter), story type and location.
In addition, after running the OLS regression the
association between explanatory variables checked by
using variance inflation factor (VIF), which shows how the
variance of the estimate is inflated because of the
presence of Multi-collinearity. But there is no serious
problem of Multi-collinearity since all values of VIF were
below ten (on average 2.22) and assumed minimum
because the value of VIF less than 10 does not bring a
serious problem of Multi-collinearity.
Table 4: Variance inflation factor of independent variables
that tests the Multicollinearity
VIF
Variable VIF 1/VIF
No of bedrooms 3.52 0.284032
Internal floor area 3.28 0.304643
Year 2.29 0.437501
Interest rate 2.01 0.496657
Inflation 1.87 0.534151
Storey Type 1.31 0.764431
Location 1.27 0.785222
Mean VIF 2.22

Heteroscedasticity test was performed using Breusch-
pagan/Cook-Weisberg, and it suggested there is
homoscedasticity, which means there is no problem of
heteroscedasticity. The null that the errors have constant
variance is accepted. In addition, error terms are normality
distributed as the normal probability plot for residuals
approaches to the normality line.
The 𝐹-statistic ratio was highly significant at less than a 1%
probability level. This showed that the main (alternate)
hypothesis formulated, that is, “there is significant
variability of housing price under different variables” has
accepted. The coefficient of multiple determination (R2)
was 0.8816 which implies that 88.16% of the variations in
housing prices were explained by the independent
variables includes in the model. The F-ratio was significant
at a 1% probability indicating the goodness of the model.
The significant factors influencing housing prices were
Year, inflation, location, interest rate and internal floor area
per m2.
Table 5: The probability for F-test, the R2 and adjusted R2
Source SS df MS
Model 6.23909617 7 .891299453
Residual .838297261 29 .028906802
Total 7.07739343 36 .196594262
Interpreting the Regression Coefficient Estimate
Results
Equation 2: ln (House Price) = β0 + β1 (year)+ β2
(inflation)+ β3 (storey type) + β4 (location)+ β5 (no of
bed) + β6 (interest rate) + β7 (internal floor area (sqm)+
Ei
The dependent variable, house price is a function of
intercept (constant) plus the chosen variables. Based on
the outputs, the coefficients standing on β0 value of 13, -
0.15 of β1 standing for year, β2 value of 0.016 for inflation,
β3 value to -0.12 for story type, β4 of -0.05 for location, β5
0.018 value for number of bed, 0.09 for interest rate and
0.017 for internal floor area.
Table 6: The P-value and the Coefficients Affecting the Log Price
Price Coef. Std. Err. t P>|t| [95% Conf. Interval]
Year -.1492735 .046349 -3.22 0.003 -.2440678 -.0544792
Inflation .0418829 .0161126 2.60 0.015 .0089289 .0748369
StoreyType -.1249561 .065114 -1.92 0.065 -.2581292 .0082171
Location -.0506518 .0124516 -4.07 0.000 -.0761182 -.0251855
Noofbedrooms .0180066 .1049311 0.17 0.865 -.1966016 .2326148
Interestrate .0096362 .0038005 2.54 0.017 .0018633 .0174092
Internalfloorareamsq .017006 .0024972 6.81 0.000 .0118986 .0221133
_cons 13.00366 .2184784 59.52 0.000 12.55682 13.4505
Interpreting the Beta (β) in Log-Level Regression
If time is lagged by 1 year from the base year 2019, house
price eased by 15% or over time it is increasing at a higher
level and statistically significant. From the model result,
inflation is statistically significant at the 5% probability
level. The estimated coefficient of inflation implies that as
inflation increased by 1% the house price increase by
4.1%. On the other hand, floor level (story type) has a
negative effect on housing price and it is statistically
significant at less than a 10% probability level. The longer
the housing located from the CBD, 1km longer has 5 birrs
(0.15$) increase the transport cost reduce the house price,
which is negatively affecting and highly statistically
significant. A number of bed of the livable area is no longer
statistically significant. Because the number of beds is
accounting for the internal floor area and vice versa,
whereas the internal floor area increase in 1m2 rises the
house price by 1.7% and highly statistically significant. The
interest rate based on their types has affected the selling
price of the condominium unit positively and statistically
significant.
As a result, almost six variables are statistically significant
at different probability levels. Therefore considering these
variables are one of the most important things but also to
look at other determinants that are affecting the current
condominium residential unit price from the empirical
analysis view cooperatively.
Number of obs = 37
F(7, 29) = 30.83
Prob > F = 0.0000
R-squared = 0.8816
Adj R-squared = 0.8530
Root MSE = .17002
Equation 3: ln (House Price) = 13 - 0.15 (year) + 0.041 (inflation) – 0.12 (storey type) - 0.05 (location)
(0.2) (0.046) (0.016) (0.06) (0.012)
+ 0.018 (no of bed) +0.009 (interest rate) + 0.017 (internal floor area (sqm)
(0.1) (0.0038) (0.002)

Melesse H. 73
CONCLUSION
According to the response from the survey, the transaction
price from the cost quality and location perspective found
very contrary where it has fluctuated and higher in price.
Results from the survey concluded that the main factors
that influence the rise of house price i) higher rate housing
supply, ii) corruption, iii) mismanagement cost, iv)
wastage of materials, v) delay of construction, labor and
bank interest costs vi) government finance and vii) inflation
were the reason for the transaction price instability. viii)
Brokers’ involvement of getting benefit on the
condominium properties, ix) government flexible
management and lack of control and x) locational
difference are the least.
Collected data from respondents were adopted into a
tabulated format based on the survey category of variables
and per each respondent for both theoretical and
econometric description. Results from Multiple regression
Analysis showed that almost all the listed variables that are
expecting to affect the Housing unit price found of
statistically significant, but it suggests to look also on
further determinants. The role of brokers on the price is
also very high on the price variation and dynamics, which
means they have a big role in making the fluctuation.
Moreover the lack of knowledge, imprudence, and mainly
forced to sell including the mediator agents and even the
supplier (Governments’) Grand Projects shifted the
demand. This would have made the demand monopoly
towards condominiums.
In comparison between the selected condominium sites
and their adjacent Apartments, there was no such
difference but higher transaction, demand and incremental
value towards condominium that is less liquid, and stability
along with Apartment residential. Private apartments now
in the city are higher in quality than the condominiums but
from the cost of their construction and the perspective of
people, they have no such transaction practice like the
condominiums. The legal framework is another factor that
has prevented the private market from growing; many
problems like delays and awareness were not solved
because of the lack of approved and clear proclamation on
real estate development.
ACKNOWLEDGMENTS
First, I would like to thank God almighty for giving me the
strength, ability and opportunity to undertake this study
and complete it satisfactorily. My genuine
acknowledgment goes to my advisor, Dr. Achamyeleh
Gashu for his positive attitude to help and encourage me
to be industrious on the process of the Research
preparation. In my journey towards this research, I found a
teacher and a pillar of heartfelt support at the path, Ato
Hailemariam Behailu. Without his guidance, this paper
would not have been possible. I would also like to express
my Gratitude to Ato Gebreegziabher Fentahun.
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https://allaboutethio.com/12th-round-20-80-three-
bedroom-condominium-winners-list [Accessed 02
2019]
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development in Ethiopia", Property Management.
Emerald Group Publishing Limited, Volume 25, pp. 27-
53.
Aluko, O., (2011). The effects of location and
neighborhood attributes on housing values in
metropolitan Lagos. Ethiopian journal of Environmental
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analysis of demand for condominium properties in
colombo. African journal of Estate and Property
Management , pp. 56-61.
Arvanities, Y. (2013). African Housing Dyamics: Lessons
from the Kenyan Market. Africa Economic Brief.
Bereket, R. and Nigatu, R. (2015). “Housing and Poverty
in southern Ethiopia: Examining Affordability of
Condominium Houses in Hawassa city”, Economics,
and sociology. pp. 155-169,
D.N. Dwivedi (2010). “Monopoly pricing and substitute in
managerial Economics,” 8th edition. s.l.:s.n.
D. N., Gujarati (2004). “Basic Econometrics,” 4th Edition,
Ed. New York: McGraw-Hill
Jayalath, J. (2016). Determinants of Market Value for
Condominium Properties: Case Study in Dehiwala,
Colombo. Conference of Business Management, pp.
892-907.
Kahr, J. and M. C. Thomsett (2005). Real Estate Market
Valuation and Analysis. Canada
Frank, K. (2017). “African property market investment”.
Africa Report
Lonappan, J. (2013). An evaluation of factors influencing
cutomer's home buying decison. Parplex - Indian
Journal of Research, Volume 2, pp. 158-160.
Mengistu, T. (2018), “allaboutEthio.com,” [Online]
Available at https://allaboutethio.com/ [Accessed 10
2018]
MoWUD (2006). “Integrated Housing Development
Program Volume II, GTZ low-cost Housing Project,”
Addis Ababa: Ministry of Works and Urban
Development(Government).
Muli (2012). “Effects of Economic Factors on the
performance of Real Estate in Kenya”
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https://www.ezega.com/News/
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UN-HABITAT (2003). “Rental Housing- An Essential
Option for the Urban Poor in Developing Countries,”
Nairobi, Kenya: UN-HABITAT.
UN-HABITAT (2010). “The Ethiopia case of Condominium
Housing: The Integrated Housing Development
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Nairobi, Kenya: UN-HABITAT.

Yared T. (2018). “Addis Fortune.com” [Online]
Available at: https://addisfortune.net/columns/smaller
players on the age of condo shops escalate[Accessed
03 2019].
Zerayehu S. and Kagnew W. (2015). “Performance,
Challenges and Prospects of Real Estate Financing in
Addis Ababa: Micro- and Macro economic
Implications”, American Journal of Economic, Finance
and Management, pp. 1-9.
APPENDIX
Table 7: Sale data on condominium units from lideta, Gerji and Summit
Table Appendix 1: condominiums……………………………………………
Respondent
code
Tenure type
(owner/ or
lessee
Internal
floor
area
(msq)
No of
bed
rooms
Common
area share
(in msq) &
price Eth.
Birr
Location/
edge,
middle,
corner,
front to
road,
back from
the road
Workplace
distance
Public
place /
playground
/ resting
place
Crime
Frequency/
annum
Economic
activity
status in
neighbor-
hood
distance
from
noise
1 condominium 44.6 1bed 4th
floor
920,000
Summit
2016
2 hours 1hour 2 no Better
2 condominium 72 2bed 4th
floor
1.3mill
Summit
2018
1-2 hours 2-3 hours 2-3 Not much A few
3 condominium 44.6 1bed 2nd
floor
1mill
Summit
2017
1 hour 30 min-1
hour
no Not much Better
4 5-10 min 5 min 5 Very high Noisy
floor
1.3mill
Lideta
2017
30 min 1 hour 2-3 Good Far from
noise
6 condominium 72 2bed 3rd
floor
1.4mill
Summit
2018
2 hours 30 min-1`
hour
no A few
7 condominium 64 2bed 2nd
floor
1.4mill
Street
side
summit
2018
1 hour 30 min- 2
hours
no A few
8 Condominium 47 1bed 1.1mill summit 30 min 3-10 min no Very good Far from
noise
9 condominium 116 2bed 1st
floor
2.5 mill
Gerji GTZ 2:30 30-1 hour 1-2 Low
10 condominium 76 2bed 1.3mill summit 5min 3-10 min 5-6 Very good Noisy
11 condominium 62 2bed 1.3mill lideta 10 min 10-20 min 5 Very good Noisy
floor
1.3
Lideta 30min 10 min 3 Very good Noisy
floor
1.25mill
Lideta 45 min 10 min No Very good Far from
noise
14 condominium 47 studio 4th
650,000
Gerji 30 min 3-5 min 3 Very good Noisy
floor
2,800,000
Lideta
Apr
19/2018
30min 10-20 min 2 Very good Noisy
16 condominium 26 studio 3rd
floor
550,000
Lideta
mar 16/
2017
finishing
1:30 1:30 No Low Far from
noise
17 condominium 31 studio 1st
floor
500,000
Summit
mar 27/
2017
1:30 30-45 min 1-2 Low Far from
noise
18 Condominium 72 2bed 1.3 mill Summit
mar
3/2017
30 min 5-15 min No Very good Noisy
19 condominium 29 1bed 530,000 Lideta
feb2017
>2hours 30 min-1
hour
No Low Far from
noise

Melesse H. 75
floor
820,000
Summit
finishing
Oct
04/2017
30min 15- 20 min No Low Far from
noise
floor
800,000
Summit
finishing
Sep
15/2017
1 hour 20 min No Good Far from
noise
floor
780,000
Summit
finishing
Sep4/2017
1hour 30-1hour No Low Far from
noise
23 condominium 46.5 1bed 3rd
floor
740,000
Sep 4/
2015
Summit
finishing
2 hour 45 min-
1:30
No Low Far from
noise
floor
750,000
Aug 3/2017
Summit
finishing
2-2:30
hours
30 min-
1:30
2-3 Low Far from
noise
25 condominium 47 1bed Ground
floor
850,000
Summit
finishing
Jul 21/2017
30 min 15 min-
1hour
1 A few Far from
noise
floor
800,000
Summit
finishing
Jul22/2017
30 min 1hour-
2hours
1 Low Far from
noise
floor
720,000
Summit
finishing
Jul 21/2015
1:30 hour 30 min-
1hour
No Low Far from
noise
floor
1.3 mill
Summit
finishing
Sep
20/2017
1 hour 10 min No A few Far from
noise
floor
900,000
Summit
finishing
Sep
15/2017
2hours 30 min-
1:30
1-2 A few Far from
noise
floor
1.45 mill
Summit
finishing
Jan/2018
3 min 3-7 min No Very good Far from
noise
31 condominium 48 studio 1.1 mill Gerji
finishing
Aug/2017
20 min 10 min 1 Very good Far from
noise
32 condominium 74 2bed 1.6mill Aug/2017
Gerji
finishing
5 min 5-10 min 1 Very good Far from
noise
33 Condominium 62.4 1bed 1.8mill Aug/2017
Gerji
finishing
20-30 min 5 min No Very good Noisy
34 Condominium 84 3bed 2.6mill
1st
floor
Lideta
Mar/2018
2-2:30
hours
2 hours No Low Far from
noise
35 Condominium 84 3bed 1.6mill
1st
floor
Summit
aug/2018
5 min 5 min-10
min
5-6 Very good A few
36 condominium 52 1bed 1.4mill
2nd
floor
Gerji
sep/2016
1:30 15-30 min No Very good Far from
noise
37 condominium 72 2bed 1.8mill
2nd
floor
Gerji
sep/2018
15 min 5- 10 min No Very good Far from
noise

Table 8: Apartment Sale data from Lideta, Gerji and Summit
R.
code
Tenure type
(owner/ or
lessee
Internal floor
area (msq) No of bed rooms Year/
Location/ edge, middle,
corner, front to road,
back from the road
Price in
Ethiopian
Birr
1. 1. Apartment 75 m2 2 bed+ 2 bath 2017 Modern kitchen summit 1,900,000
2. 2 Apartment 76 m2 2017 summit 1,600,000
3. 3 Apartment 74 m2 2bed+1 bath 2017 Summit, 3rd floor 1,600,000
4. 4 Apartment 74 m2 3bed+2 bath 2017 Summit, 1st floor 1,600,000
5. 5 Apartment 105 m2 3bed+2kitchen+2bath 2017 summit 2,000,000
6. 6 Apartment 47 m2 1bed+1bath 2019 Summit, ground 1,400,000
7. 7 Apartment 53 m2 2 bed+1bath 2019 Summit, 1st floor 1,700,000
8. 8 Apartment 63 m2 2bed+2bath 2019 Summit, 4th floor 2,300,000
9. 9 Apartment 90 m2 3bed+2bath 2019 Summit, 4th floor 2,500,000
10. 10 Apartment 112m2 3bed+2bath 2019 Gerji 2,900,000
11. 11 Apartment 90 m2 2bed 2019 Gerji 1,900,000
12. 12 Apartment 100 m2 3bed+2bath 2018 Gerji 2,200,000
13. 13 Apartment 18 bed+19bath 2019 Gerji 22,000,000
14. 14 Apartment 3bed+2bath 2017 summit 1,600,000
15. 15 Apartment 105 m2 3bed+2bath 2018 Summit, well furnished 2,000,000
16. 16 Apartment 3bed+2bath 2018 Summit 1,250,000
Questionnaire for the dwellers
1. Your level of education: (A) Secondary school (B) Diploma and certificate (D) First degree and above
2. Your income from:_____________________________________
3. How do you get the house?
a. Relocation b. buy c. rent d. other explain
1. If buy
3.1.1. How much did you purchase?_________________
3.1.2. When did you purchase? The year? Month?_______________________
2. If you rented
3.2.1. How much do you pay monthly?_____________________________
3.2.2. How many rooms the houses contain?_______________________
3.2.3. Have you ever had same rent experience before? Where and how much? With how many rooms?
_____________________________
4. Do you have children or other family with you?
a. Yes b. No
5. If you have children (other family), how many? __________
Section II. Tenure and shelter history
6. Now I would like to get some information on your housing arrangements
5.1.What do you like most about this unit /LIKE MOST/
Amount of space number of rooms
Quality of unit
Location
Utilities –availability of water, electricity etc
Other
Nothing, completely dissatisfied

Melesse H. 77
5.2 What do you like least about this unit /LIKE LEAST/
Not enough space or rooms for household
Poor quality of unit
Utilities- water, electricity etc not available
Poor drainage
Location
Other ……………………..
Nothing, everything is satisfactory
5.3. What do you think about the condition of your unit /UNIT COND/
In good condition
In fair condition
In poor condition
Section III. Neighborhood, location and access characteristics
Now I would like to ask your opinion about the neighborhood in general _______________________________________
_______________________________________________________________________________________________
6. Which amenities do the household use, how long does it take to get there, how much does it cost? /AMENITIES/
time Cost/birr/ Mode of transportation /min/ week year
A Work/household head/
B shopping
C school
D Hospital or clinic
E Other …………………….
Mode of transportation codes
Walk
taxi
City bus
other …………
7. What feature do you like most about this neighborhood? /BESTFEATURE/
Proximity to work
Access to utilities
Familiarity to area
Proximity to social services
8. What feature do you like least about this neighborhood? /WORSTFEATURE/
Poor drainage
Poor infrastructure
Poor neighborhood
Poor access to jobs, social services
High crime level
Other ……………….
2 Closed ended questionnaire for the selected sample respondents of:
For the following questions, please put (X) mark in the box corresponding to your preferred response using the
scale below:
SA: Strongly Agree A: Agree UD: Undecided D: Disagree SD: Strongly Disagree
1. What do you think the factors to the current demand for condominium housing, and the factors for that demand?
No Critical factors to the current demand for condominium Scale
SA A UD D SD
1. Demographic issues related with the migration for job and education
2. Higher shortage of housing and the need for shelter
3. Newly introduced housing alternative for low and middle income groups
4. Income of the customer( affordability)
5. The amount of the price of the particular housing

2. How do you see the current condominium transaction price and its marketability?
No factors for current condominium higher transaction frequency and active marketability Scale
SA A UD D SD
1. Third person; the brokers and other agents and their advertisements liaises in between
transactions
2. Higher housing demand and small in number of existed housing
3. Un affordability of the existing housing price mainly on the apartments or no vacancy
3. How do you estimate the condominium re sale price related with the transfer value?
No The current condominium re sale price relation to the transfer value Scale
SA A UD D SD
1. The transfer value rises the price for the transaction based on the higher inflation rate in
affecting the condominium construction
2. The demand pull inflation that is affecting those who receive the fixed nominal incomes
and help those who receive flexible nominal incomes
3. The rate of interest and higher dept on the transferring process
4. Because condominiums are an income generation areas or a non-investment
transactions because of transactions on the transfer of existing assets unlike other private
houses and these mere transfer doesn’t create new capital
5. Based on the mere transfer and the higher demand of the space market to transact
affects the condominium price
6. Flexible transfer and valuation system
4. What do you think the factors to the current demand for condominium housing, and the factors for that demand?
No the factors of preference and highly liquid of condominium housing than alternative
apartment
Scale
SA A UD D SD
1. Listed prices; from all over the real estate the condominium value is lower in price
2. Extra infrastructures that are fulfilled around the condominium than other apartments (like
public transport, school for children and other commercial uses for the dwellers)
3. Because of lack of comparable or substitution effect, there is no better alternative than
the condominium units
4. Imperfect information, about other real estates and more information for condominiums
among the home seekers and buyers
5. Transaction volume; if the current transaction volume among the condominium
influences the demand towards
6. Brokerage services, giving information that could shift the demand towards the
condominium and make it more liquid
7. Interest rates and economic conditions
5. Who are the accelerators on the supply and demand space market on these housing types?
No Factors in accelerating the supply and demand space market on condominium
transaction and price
Scale
SA A UD D SD
1. Demographic issues
2. Brokers
3. Inflation prediction
4. Lack of control
5. Flexible management
6. What do you think the solution in avoiding the speculation and uncontrolled incremental value of condominium unit?
________________________________________________________________________________________
Accepted 10 June 2020
Citation: Melesse H (2020). Factors Determining the Continuous Price Appreciation of Condominium Units in Addis
Ababa. World Journal of Civil Engineering and Construction Technology, 4(1): 064-078.
Copyright: © 2020 Melesse H. This is an open-access article distributed under the terms of the Creative Commons
Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original
author and source are cited.

Factors Determining the Continuous Price Appreciation of Condominium Units in Addis Ababa

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