Housing Price and Rent Inflation after Hosting 2018 Winter Olympic Game in the city of Gangneung, Korea Chul Sohn Gangneung-Wonju National University, Dept. of Urban Planning and Real Estate, College of Social Science, Gangneung, Korea e-mail: csohn@gwnu.ac.kr Changrae Park Gangneung-Wonju National University, Dept. of Accounting, College of Social Science, Gangneung, Korea e-mail: pcr@gwnu.ac.kr Abstract The city of PyeongChang and the city of Gangneung are the host cities for 2018 Winter Olympic Game. The city of PyeongChang is the main Olympic city and most of snow sports will be held in the city while most of ice sports will be held in the city of Gangneung. This study analyzed how hosting the 2018 Winter Olympic Game influences the housing market situation of the city of Gangneung using difference-in-differences models. The results from estimating the difference-indifference models reveal that the sales prices of multi-family housing units of the city of Gangneung are increased approximately 18% in case of small sized units and 9% in case of medium sized units after the announcement of hosting the game compared with those of nearby city. Also the results show that the rent levels of the multi-family housing units has not statistically significantly increased since the announcement. Keywords: 2018 Winter Olympic Game, PyeongChang, Gangneung, Difference-in-Differences Model Research background and objective In this study, we analyzed the influences of hosting 2018 Winter Olympic Game on prices and rents of multi-family housing units in PyeongChang and Gangneung, Korea. The city of PyeongChang won the 2018 Winter Olympic Game in July 7, 2011. The city of PyeongChang tried three times to win the Winter Olympic Game. At the last trial, this city succeeded in hosting the game. The city of Gangneung is the neighboring the city of PyeongChang. The city of Gangneung is a coastal city while the city of
PyeongChang is the most famous mountain ski resort city in Korea. According to the plan of the Korea 2018 Winter Olympic Organizing Committee, all the snow sports will be held in PyeongChang and all the ice sports will be held in Gangneung. In Gangneung, there live approximately 220,000 people currently. However, in PyeongChang, only approximately 44,000 people live in 2013. PyeongChang s hosting of the Winter Olympic Game has been greatly welcomed by residents of two cities because people believe that investments in Olympic sports facilities and transportation infrastructure will boost the growth of regional economy. In fact, two cities and the Gangwon province to which these cities belong are less developed areas in Korea and have tourism based economy. For the residents of two cities, the major hindering factor of their tourism based economy is the poor rail infrastructure between these regions and the Capital region of Korea. Currently, there exist very efficient highway system between the Capital region and two cities. However, this highway system is usually highly congested during summer vacation season and sometimes becomes dangerous during winter season because of heavy snowfall. Thus the residents of two cities have wanted to have an efficient and safe rail system which connects these regions and the Capital region. This is because a rail system can provide congestion free and is less weather dependent. Figure 1. Locations for Olympic Sports Stadiums, Source: 2018 Winter Olympic Organizing Committee
Figure 2. Current Highway and Rail between Seoul and Gangneung In fact, there exists an old rail system between Gangneung and the Capital region. This rail system was built under Japanese Imperialist period when Japanese Imperialist colonized Korean peninsula. The purpose of this system was to transport the coal and iron mined to industrialized areas. It takes approximately 7 hours to get to the Capital region from Gangneung. However, if we use the highway system we can reach the capital region within 3 hours. The reason why people in two cities greatly welcome hosting of the game is that Korean government promised to build new efficient rail system if the city of PyeongChang won the game. Because of the decision made by IOC, the two cities will have a new efficient rail system and modern sports facilities which will be used by residents and tourists after the game. It can be expected that the future amenity benefits from improved transportation system and nearby sports stadiums will be gradually reflected in real estate markets of PyeongChang and Gangneung and, up to certain level, real estate prices increase. Also, there exists possibility that this increase in price levels could also increase the level of rents. This is because rent is usually leveraged to buy houses for investment purpose in Korea. This means that new house buyers with investment purpose can increase rent so that they can pay some amount of money for purchasement. The increase in housing costs has long been pointed out a major negative outcome from hosting mega games such as the 2018 Winter Olympic Game (Kontokosta, 2012; Kavetsos, 2012). In this study, we wanted to know whether the
announcement of hosting the 2018 Winter Olympic affects the price and rent levels of the multi-family housing units in the city of Gangneung as other hosting cities of mega games. Method, Data and Variables Method To investigate how the announcement of hosting the 2018 Winter Olympic affects the price and rent levels of the multi-family housing units in the city of Gangneung, following Wooldridge (2006), we used the Difference-in-Differences estimator which is explained in (1). In (2) devent is the dummy variable and has the value of 1 for after announcement period and dimpact is the dummy variable and has the value of 1 for treatment area that is the city of Gangneung. If we don t consider other factors when estimating (1), shows the changes in price or rent due to the announcement when compared with those of control area as (2). When we include other factors which are related with price or rent, is not the same with (2). However, interpretation of (2) can be done similarly (Wooldridge, 2006). where Devent: dummy for after announcement period, Devent: dummy for treatment area(gangenung) (1) (2) Data To estimate equation (1), we defined Gyo-Dong 1 of Gangneung, which is the most densely populated urban residential area as treatment area while we define Cheongok-Dong which is the most densely 1 Gyo-Dong consists of Gyo1-Dong and Gyo2-Dong.
populated area in the city of Donghae, the neighboring city of Gangneung as control area. According to the plan of Korea 2018 Winter Olympic Organizing Committee, the Gyo-Dong area will host most of stadiums for ice sports. We choose Cheongok-Dong as a control area because this is typical and representative residential area of neighboring city which is not directly impacted by hosting the 2018 Winter Olympic Game. Figure 3. Location of Gyodong Figure 4. Distance between Gydong and Cheongokdong
The data sets for estimating equation (1) come from Real Estate Transaction Price Database managed by Korea Ministry of Land Infrastructure and Transport. This database records every price and rent information reported from individual real estate transactions. It also records approximate date of transaction agreement made and story of real estate units in case of multi-family housing units. For this analysis, we include the sales transaction information from Jan., 2010 to Dec., 2012 and rental agreement information from Nov., 2010 to Dec., 2012. Because the decision for PyeongChang was made July 7, 2011, we have approximately 18 months before the event and 18 months after the event in case of sales transaction data set. During this period, total 2,286 cases of sales transaction were made and total 1,411 cases of rental transactions were made. In case of rental transaction, in Korea, usually a house owner receives one time two year security deposit from a tenant without any monthly payment or receives the partial amount of the two year deposit and monthly payment at the same time. The house owners usually use the deposit for investments of personal consumptions or save it to the bank and receive interest from the bank. Also, in Korea, multi-family housing units are grouped into three size class: small (below 65 sq. m), medium (between 65 and 85 sq. m), large (over 85 sq. m). Because the control area, Chungok-Dong has only small number of large class units, we used the samples from small class and medium class to estimate Difference-in-Differences estimators. Also in case of rent samples, if we focus on the small and medium size classes, the number of samples is substantially reduced. Thus, for the rent samples, we integrate small and medium size classes and estimate just one Difference-in-Differences estimator. Variables Table 1. shows the definitions of variables used to estimate (1) for each size classes. In Table 1. njunsei means two year rent of a multi-family housing unit. When a tenant pays the one time deposit for two years and monthly payment at the same time, we converted the monthly payment to equivalent amount of two year deposit and summed with the original deposit. Table 2. and Table 3. show the summary statistics of the samples used for this analysis
Table 1. Definition of Variables Variables Ln(price) Ln(nJunsei) size Log of Price Log of njunsei Size in sq. m Definition Age Aptunit Dstory Devent Dimpact Age of House The number of housing units in the multi-family housing complex 1 if the unit is located in the first floor, 0 if not 1 if sold (rent agreement made) after July 7, 2011, 0 if not 1 if located in Gangneung, 0 if not Table 2. Summary Statistics: Sales Variable Obs Mean Std. Dev. Min Max price 1744 8924.604 4744.797 1600 24200 size 1744 65.65336 17.28365 27.75 84.99 age 1744 15.25573 6.42258 1 29 aptunit 1744 511.7787 304.295 58 1019 dstory 1744 0.110665 0.313807 0 1 dstep 1744 0.904243 0.294342 0 1 Table 3. Summary Statistics: Rent Variable Obs Mean Std. Dev. Min Max njunsei 544 7122.349 3356.278 1300 19000 size 544 66.50217 16.55058 27.75 84.99 age 544 13.92463 5.880941 2 29 aptunit 544 538.2206 282.2915 58 1019 dstory 544 0.123162 0.328925 0 1
Results Table 4. to Table 5. show estimation results from the Difference-in-Differences estimators of sales samples and Table 6. shows results from rent samples. The t and P-value of Table 4., Table 5., and Table 6. are based on heteroskedasticity consistent estimator. The results of F-test show that estimated results are statistically acceptable. In case of sales samples, the results from estimating the differenceindifference models reveal that the sales prices of multi-family housing units of the city of Gangneung are increased approximately up to 18% in case of small sized units and 9% in case of medium sized units. However, Table 6. shows that rent levels are not impacted by the announcement of hosting 2018 Winter Olympic Game. Table 4. Sales Price Estimation Result: Small Size Sample (less than or equal to 60 sq. m) lnprice Coef. t P> t size 0.039006 33.14 0 age -0.01413-6 0 aptunit 0.000194 6.69 0 dstory -0.06412-3.58 0 devent 0.146666 9.09 0 dimpact 0.156081 6.52 0 devent*dimpact 0.184062 7.23 0 _cons 6.601553 64.31 0 Number of obs = 938 F( 7, 930) = 1190.25 Prob > F = 0.0000 R-squared = 0.8801 Root MSE =.18429 The increase in housing prices of Kyo-Dong can be explained as the results of reflection of anticipated increase in amenity level in this area. The finding that the rent levels are not affected by the announcement is somewhat unexpected if we consider the fact that rent can be leveraged to buy new houses whose prices are inflating.
Table 5. Sales Price Estimation Result: Medium Size Sample (between 60 sq. m and 85 sq. m) lnprice Coef. t P> t size 0.012455 9.16 0 age -0.03888-35.93 0 aptunit 0.000177 7.92 0 dstory -0.1086-4.57 0 devent 0.119528 7.2 0 dimpact 0.088761 6 0 devent*dimpact 0.094383 3.83 0 _cons 8.660625 74.31 0 Number of obs = 806 F( 7, 798) = 431.88 Prob > F = 0.0000 R-squared = 0.7764 Root MSE =.1609 Table 7. Rent Estimation Result: Small and Medium Size Sample (less than or equal to 85 sq. m) lnnjunsei Coef. t P> t size 0.016093 18.74 0 age -0.02098-6.97 0 aptunit 0.000261 6.03 0 dstory 0.038392 0.96 0.337 devent 0.096874 2.06 0.04 dimpact 0.317944 6.63 0 devent*dimpact -0.04111-0.76 0.449 _cons 7.568305 70.09 0 Number of obs = 544 F( 7, 536) = 225.87 Prob > F = 0.0000 R-squared = 0.7294 Root MSE =.27324
Conclusion This study analyzed how hosting the 2018 Winter Olympic Game influences the housing market situation of the city of Gangneung using difference-in-differences models. The results from estimating the difference-indifference models reveal that the sales prices of multi-family housing units of the city of Gangneung are increased approximately 18% in case of small sized units and 9% in case of medium sized units. Also the results show that the rent levels of the multi-family housing units has not statistically significantly increased since the announcement of hosting the 2018 Winter Olympic Game. The finding that the sales prices of small size multi-family housing units are inflated relatively higher than those of medium size units tells us that 2018 Winter Olympic acts as a mechanism to reduce the affordable housing stocks for low income family in the city of Gangneung. References Dehring, C. A., C. A. Depken and M. R. Ward. 2007. The Impact of Stadium Announcements on Residential Property Values: Evidence from a Natural Experiment in Dallas-Fort Worth. Contemporary Economic Policy 25 (4): 627-638. Kavetsos, G. 2012. The Impact of the London Olympics Announcement on Property Prices. Urban Studies 49 (7): 1453-1470. Kontokosta, C. 2012. The Price of Victory: The Impact of the Olympic Games on Residential Real Estate Markets. Urban Studies 49 (5): 961-978. Tu, C. C. 2005. How Does a New Sports Stadium Affect Housing Values? The Case of FedEx Field. Land Economics 81 (3): 379-395. Wooldridge, Jeffrey M. (2006) Introductory Econometrics. Mason, Ohio : Thomson.