# RECORD 3b820e938ca4b455736f08f285e1b5bb43f7674a # TITLE: Determinants of Residential Real Estate Property Prices in Ethiopia: The Case of Bahir Dar City # YEAR: 2024.0 VENUE: International Journal of Business and Economics Research DOI: 10.11648/j.ijber.20241303.11 # AUTHORS: Tamirat Mekuria; Seid Yimam; Yohans Negashi # PAGES: 18 CANDIDATE TABLE PAGES (1-based): [14, 15] # ABSTRACT: The Ethiopian real estate industry has grown in the previous two decades, especially in the capital city of the country and regional capitals, including Bahir Dar. Real estate prices have doubled and even tripled in a few years because of different factors. Thus, the purpose of this study is to analyse the factors affecting residential real estate prices in Ethiopia, particularly in Bahir Dar City. For this purpose, the study used both purposive and stratified random sampling techniques. Descriptive and inferential statistics were used to analyze the data, and the ordinary least squares method was used to identify the factors that influence residential real estate prices. The hedonic regression model result reveals that R2 statistics (0.880) indicate that 88% of the variation in residential real estate prices can be explained by variation in the independent variables. Hedonic regression model results revealed that plot size, floor area, number of rooms, age of the house, external wall finishing material, ceiling finishing material, the direction of the house, distance of the property from the main road, and involvement of brokers in the transaction process, were major micro-factors that had a significant effect on residential real estate prices at the 5% level of significance. Furthermore, the interview results show that the challenges faced by real estate developers mostly include loans and aid issues, high-interest rates, mortgage restrictions, the financial capacity of real estate companies, delays in plan approvals, and rising costs of construction materials are among the major challenges affecting investment in real estate. The study suggests that the municipality of Bahir Dar City should provide an adequate supply of land to real estate developers, improve infrastructure development, and federal and regional governments should provide the credit lending mechanism by lowering interest rate especially for low-income class. ===== PAGE 1 (score 18, numeric-paren 2, table-words 1, var-words 14) ===== International Journal of Business and Economics Research 2024, Vol. 13, No. 3, pp. 46-63 https://doi.org/10.11648/j.ijber.20241303.11 *Corresponding author: Received: 14 April 2024; Accepted: 6 May 2024; Published: 24 May 2024 Copyright: Β© The Author(s), 2024. Published by Science Publishing Group. This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium, provided the original work is properly cited. Research Article Determinants of Residential Real Estate Property Prices in Ethiopia: The Case of Bahir Dar City Tamirat Mekonnen Mekuria1, * , Seid Hussen Yimam2 , Yohans Teshome Negashi3 1Department of Real Property Valuation, Institute of Land Administration, Oda Bultum University, Chiro, Ethiopia 2Department of Real Property Valuation, Institute of Land Administration, Bahir Dar University, Bahir Dar, Ethiopia 3Department of Real Property Valuation, College of Business and Economics, Dire Dawa University, Dire Dawa, Ethiopia Abstract The Ethiopian real estate industry has grown in the previous two decades, especially in the capital city of the country and regional capitals, including Bahir Dar. Real estate prices have doubled and even tripled in a few years because of different factors. Thus, the purpose of this study is to analyse the factors affecting residential real estate prices in Ethiopia, particularly in Bahir Dar City. For this purpose, the study used both purposive and stratified random sampling techniques. Descriptive and inferential statistics were used to analyze the data, and the ordinary least squares method was used to identify the factors that influence residential real estate prices. The hedonic regression model result reveals that R2 statistics (0.880) indicate that 88% of the variation in residential real estate prices can be explained by variation in the independent variables. Hedonic regression model results revealed that plot size, floor area, number of rooms, age of the house, external wall finishing material, ceiling finishing material, the direction of the house, distance of the property from the main road, and involvement of brokers in the transaction process, were major micro-factors that had a significant effect on residential real estate prices at the 5% level of significance. Furthermore, the interview results show that the challenges faced by real estate developers mostly include loans and aid issues, high-interest rates, mortgage restrictions, the financial capacity of real estate companies, delays in plan approvals, and rising costs of construction materials are among the major challenges affecting investment in real estate. The study suggests that the municipality of Bahir Dar City should provide an adequate supply of land to real estate developers, improve infrastructure development, and federal and regional governments should provide the credit lending mechanism by lowering interest rate especially for low-income class. Keywords Hedonic Regression Model, Micro-Factors, Property Prices, Residential Real Estate ===== PAGE 14 (score 43, numeric-paren 0, table-words 15, var-words 11) ===== International Journal of Business and Economics Research http://www.sciencepg.com/journal/ijber 59 Coefficientsa Model Unstandardized Coeffi- cients Standardized Coefficients T Sig. B Std. Error Beta Broker involvement in the transaction process .468 .202 .126 2.320 .023* External wall finishing material .383 .183 .138 2.089 .040* Floor finishing material .035 .025 .083 1.391 .168 Ceiling finishing material .023 .023 .054 1.008 .013* Direction of the house (East=1 Non-East=0) .456 .160 .150 .285 .036* Land grade -.009 .011 -.048 -.865 .389 Accessible road type -.001 .008 -.005 -.094 .925 Log_ Floor Area in square meter .601 .175 .307 3.441 .001* Log_ Gross plot size in square meter .335 .110 .258 3.052 .003* Log_ Age of the House in years -.187 .054 -.250 -3.434 .001* Log_ Number of rooms .148 .066 .131 2.240 .028* Log_ Distance of the property from the main road in meter -.097 .031 -.191 -3.115 .002* Dependent Variable: Log_ Residential Real Estate Price * Statistically significant at 0.05 Source: Regression model result, 2024 Table 9 shows the value of each coefficient. This model confirmed that structural factors (building characteristics), age of the property, gross plot size, floor area, number of rooms, external wall finishing material, ceiling finishing ma- terial, and direction of the house are statistically significant in affecting the price of residential real estate. Also, based on locational attributes, the distance from the property to the main road is statistically significant. In addition to these fac- tors, the brokers’ involvement in the transaction is statistical- ly significant. Table 9 shows that the coefficients of these variables have a p-value of less than 0.05. The hedonic regression model shows variables that were significant in the overall model, that is, age of the property (t = -3.434, p-value = 0.001), gross plot area (plot size) (t = 3.052, p-value = 0.003), distance of the property from the main road (t = -3.115, p-value = 0.002), a broker involved in the transaction (t = 2.320, p-value = 0.023), ceiling finishing material (t = 1.008, p-value = 0.013), the direction of the house (t = 0.285, p-value = 0.036), external wall finishing material (t = 2.089, p-value = 0.040), and a number of rooms (t = 2.240, p-value = 0.028). The results of the regression model indicate that the prices of residential real estate are influenced by building characteristics. In addition, these bro- kers’ involvement in the transaction also influenced residen- tial real estate prices. However, the land grade, accessible road type, and floor finishing material, are not significant variables. The p-value of those variables is greater than 5%, so these variables have no significant effect on the sales price of residential real estate properties. Therefore, from the above Table 9, 14.539 is the intercept of this linear relationship, which indicates if the independent variables were all rated as zero, residential real estate prices rising would be 14.539. According to the regression result, the age of the property and distance of the property from the main road has a negative relationship with the sales price of residential real estate. According to different literatures, old- er houses are often associated with a lower house price com- pared to newer houses. In the current study, we found that the age of a house has a significant effect on the price of res- idential real estate. The sign of building age is negative, indi- cating that the older the house is, the lower the house price. This study's results show that a relatively new house with good quality has a higher price than an old or low-quality house. A 1-year increase in the age of the house leads to a decrease in the price of residential real estate by (18.7%), ceteris paribus. The property near the main road has a higher price than the property far from the main road. The property is far from the main road; at a distance of one meter, the sales price of the residential real estate will decrease by (9.7%). The re- ===== PAGE 15 (score 28, numeric-paren 0, table-words 8, var-words 10) ===== International Journal of Business and Economics Research http://www.sciencepg.com/journal/ijber 60 gression result reveals that keeping other explanatory varia- bles constant, an addition of 1 square meter to the plot size leads to a change in the price of residential real estate by (33.5%). This result is consistent with the findings of (Guntermann et al., 2015, and Gu, 2018), that residential properties with a larger plot size have a higher price than those with a smaller plot size. The OLS regression suggests that with an addition of floor size by 1 square meter, the price of residential real estate increases by (60.1%). As the number of rooms increased by one room, the price of resi- dential real estate increased by (14.8%). Many experts agree that real estate brokers play an im- portant role in the real estate industry. However, their find- ings demonstrate that even if real estate agents play a signifi- cant role in the market by contacting buyers and sellers, they may monopolize the market and take advantage of clients, especially in areas where there are flaws in the market. Simi- lar findings were obtained from this study in Bahir Dar City, where the majority of real estate deals involve brokers, who do a fantastic job of connecting the two sides. Brokers, how- ever, charge more than they did and have a significant im- pact on price increases. This occurs when there is an infor- mation asymmetry, and as a result, both parties are asked to pay more for their perceived advantages. This is in line with the findings of the study by Marete (2011), who also claims that home buyers who acquired their property through an agent or broker are subjected to additional demands by form- ing a conspiracy with one or both participants. According to this study, there will be a 46.8% change in the sales price of residential real estate with broker engagement. The material from which the ceiling finishing material of the building is made also determines the price of residential real estate. Many studies support the idea that real estate with better quality and a long-lasting ceiling-finishing material has better value. As depicted in Table 9, those properties finished through gypsum and painting has a better selling price than those properties finished through plastic. The ex- pected price change in residential real estate with ceilings finished with gypsum is increased by 2.3% compared to plas- tic ceiling finishing material types. This result is consistent with the finding of [3], which states that the construction material, which directly affects the cost of construction, has a significant effect on the price of real estate. The price of res- idential real estate with quartz paint external wall finishes increase by 38.3% compared to plaster with cement external wall types. The direction of the house has a statistically significant ef- fect on the residential real estate price. According to the re- gression results, the house located in the east direction has a higher price difference than the house located in the non-east direction. As depicted in coefficient Table 9, those buildings located in the east direction have a better selling price than those located in the non-east direction. The expected price difference in residential real estate located in the east aspect increases by 45.6% compared to residential real estate locat- ed in the non-east aspect. The amount to which each variable influences the price of residential real estate in the area is shown by the standard coefficient (Beta) value of the explanatory (independent) variable. It is presented in Table 9 above. It gives a picture of how influential or important the independent factors are about the price of residential real estate. The influence of the variable increases with beta magnitude. So, based on the analysis's findings, the brokers’ role in the deal, the direction of the house, and floor area have the greatest impact on the residential real estate property price in the study area. From the above Table 9, therefore, the model is thus as in- dicated below; πΏπ‘œπ‘”βˆ’π‘…π‘…πΈπ‘ƒ= 14.593 + 0.468(𝐡𝑅) + 0.383(πΈπ‘ŠπΉπ‘€) + 0.023(𝐢𝐹𝑀) + 0.456(𝐷𝐻) + 0.601(πΏπ‘œπ‘”βˆ’πΉπΏπ΄) + 0.335(πΏπ‘œπ‘”βˆ’πΊπ‘ƒπ΄) βˆ’0.187(πΏπ‘œπ‘”βˆ’π΄π‘”π‘’ ) + 0.148(πΏπ‘œπ‘”βˆ’π‘π‘…) βˆ’0.097(πΏπ‘œπ‘”βˆ’π·π‘€π‘…) + π‘’π‘Ÿπ‘Ÿπ‘œπ‘Ÿπ‘  Table 10. Summary of Hypothesis Testing. S.N Hypothesis Sig (P-Value) Level of Signif- icance Conclusion 1 H1: There is significant relationship between age of the house and prices of residential real estate property 0.001 0.05 Accepted 2 H2: There is significant relationship between number of rooms and prices of residential real estate property 0.028 0.05 Accepted 3 H3: There is significant relationship between floor area and prices of residen- tial real estate property 0.001 0.05 Accepted 4 H4: There is significant relationship between proximity to the main road and prices of residential real estate property 0.002 0.05 Accepted 5 H5: There is significant relationship between gross plot area and prices of resi- 0.003 0.05 Accepted ===== PAGE 16 (score 15, numeric-paren 0, table-words 1, var-words 12) ===== International Journal of Business and Economics Research http://www.sciencepg.com/journal/ijber 61 S.N Hypothesis Sig (P-Value) Level of Signif- icance Conclusion dential real estate property 6 H6: There is significant relationship between broker involvement in the trans- action and prices of residential real estate property 0.023 0.05 Accepted 7 H7: There is significant relationship between external wall finishing materials and prices of residential real estate property 0.040 0.05 Accepted 8 H8: There is significant relationship between floor finishing materials and pric- es of residential real estate property 0.168 0.05 Reject 9 H9: There is significant relationship between ceiling finishing materials and prices of residential real estate property 0.013 0.05 Accepted 10 H10: There is significant relationship between direction of the house and prices of residential real estate property 0.036 0.05 Accepted 11 H11: There is significant relationship between land grade and prices of residen- tial real estate property 0.389 0.05 Reject 12 H12: There is significant relationship between accessible road type and prices of residential real estate property 0.925 0.05 Reject Source: Researcher, 2024 5. Conclusion and Recommendations Conclusions The framework of price determinants for the research area was also developed using 12 variables that were discovered and categorized into the known residential real estate price determinants. To determine the price of residential real estate in the study area of Bahir Dar City, information on the varia- bles taken into account was requested from property owners, real estate developers, and brokers. Findings from the correlation analysis result showed the price of residential real estate has a positive relationship with the ten explanatory variables: gross plot area, floor area, number of rooms, external wall finishing materials, floor finishing materials, ceiling finishing materials, the direction of the house, brokers involvement in the transaction process, land grade, and accessible road type. It was found that the price of residential real estate has a negative relationship with the age of the house, and its proximity to the main road. According to the findings of the regression model result, gross plot size, floor area, number of rooms, age of the house, proximity to the main road, the direction of the houses, ex- ternal wall finishing material, ceiling finishing materials, and broker involved in the transaction process were identified as statistically significant factors in residential real estate prices at 5% level of significance. In general, the coefficients of the regression results show that factors like gross plot area, floor area, number of rooms, age of the house, distance from the property to the main road, the direction of the house, external wall finishing material, ceiling finishing materials, and brokers’ involvement in the transaction process have major influence on the prices of residential real estate. Recommendations This study has identified the significant factors that affect the price of residential real estate properties, and describe the challenges that real estate developers confront in Bahir Dar City. Thus, the study has forwarded the following recom- mendations in light of conclusions that have been presented thus far: 1) The real estate developers should invest in quality finishes and analyze the target market to understand the size of plots and the size of houses they most likely prefer. 2) This study suggests that the government should concen- trate on providing sufficient land to real estate develop- ers to restrict the increase in property prices and make housing affordable for the middle and lower-income classes in the city. 3) The paper also urges governments to actively pursue data collection and analysis of housing market trends. The information available was quite limited but crucial for making policy decisions, particularly in court. 4) Since the current real estate prices seem to exclusively target the upper class and the diaspora, the government should develop a system, such as a price index for resi- dential real estate sectors that would allow it to monitor the real estate price increase. 5) The government should improve infrastructure develop- ments that will improve the real estate sector's capacity to develop affordable residential real estate for their clients. 6) Finally, the government should controlling high cost of construction brought about by acquisition cost of both