상가 임대차계약의 옵션가치 추정에 관한 연구 = (A)study on the lease option model of retail real estate|RISS 상세보기

다국어 초록 (Multilingual Abstract)

Ⅰ. Introduction
These days, investors are increasingly interested in profitable real estate in the Korean real estate market. Retail real estate is such an item, and investors or developers who value the nature of cash flow are becoming more interested in turning rental business and retail real estate into financial products. The change in the nature of real estate investment implies that real estate is indeed an investment item like other financial products, so investors or developers need to check the risk of investing in real estate market. That is, one needs an index in order to come up with an objective investment decision, and the amount of rent will become ever more important as an index for measuring the profitability of commercial real estate when leasing becomes more prevalent in Korean real estate market in the future.
Rent in retail real estate is decided locally and individually based on the retail environment of the commercial trade area where the target customers exist, so the economic power of commercial trade area greatly affects in the amount of rent. The change in the economic power of commercial trade area results in the increase or decrease in retail rental, prompts new commercial trade areas or marts to compete against the existing commercial establishment, and brings changes in the consumers’ standing. Changes in public transportation, introduction of large wholesale or retail stores, introduction or transfer of public agencies or big businesses, and increase in income and accompanying change in consumption pattern are some of the factors which may bring changes to market power. The start of city restructuring and diversification of consumer taste have resulted in the intense and complex usage of land in Seoul, thereby increasing the economic power of commercial trade area.
Despite the importance of the economic power of commercial trade area, researches on concrete factors which affect the economic power of commercial trade area have been neglected thus far. Depending on the individual background of retail rental, predicting the operation and resale profits and coming up with a strategy have become an important issue. Thus, this study will discuss variables that affect the rental price of individual store and their importance by utilizing data on retail real estate in Seoul. In addition, this study will predict the option price based on an option price model and rental price index.
Lease options is the combination of rental contract, financial tool and checks every revision interval whether situation have changed favorable to decision maker or not. This paper main goal of this study to develop the Lease Option Model of Retail Real Estate by the data mining method controlling the market characteristics which are influential on the level of rent and to establish the retail building rent forecast model which is connected with the macro economic variables.
Ⅱ. Trend of research
Because it is hard to obtain rental data in retail real estate, and retail real estate requires more complex professional knowledge than residential real estate, there have not been many studies how retail real estate goes about setting its rental price. Studies that deal with factors which affect commercial rental price were geared towards how spatial factors of retail real estate affected rental price until 1980s, but they have progressed to investigating how non spatial factors, such as the nature of consumers or image of shopping centers, affect the rental price since 1990s.
According to studies on rental price or retail real estate, stores located in a huge shopping mall is more competitive than stores located in a small shopping center (Eton & Lipsepy; 1982, Mulligan;1983); and Ghosh (1986) reports that landowners or low level retailers benefit from the availability of multi purpose shopping. Moreover, the lease term, percentage rent, or name value of franchise affect the rental value of each store (Benjamin, Boyle & Sirmans; 1990); and the size or age of shopping center or nature of core leasees may decide the rental price as well. (Sirmans & Guidry; 1993) Also, stores which are traditionally known to draw a sizable volume of traffic often end up paying less for rent. (The Center for Advanced Land Use Studies; 1975 & Anderson; 1985)
Many studies used the rental price of retail real estate and nature of the market or economic power of the primary commercial trade area as an explanatory variable, but studies which deal with variables on the economic power of commercial trade area are extremely limited. The buying power of commercial trade area is known to be important in determining the amount of retail sales and setting rental price (Ingene and Lusch; 1980, Okoruwa et al.; 1994); and the image of core leasees or characteristics of the population are some of the variables that reflect the economic power of the commercial trade area. (William and Marvin L; 2001)
Ⅲ. The research model and data
1. Theoretical model and variables
(1) Theoretical model
In this study, a commercial trade area means a spatial and local area, and includes all the concepts which oversee the most practical place of trading for consumers as well as businesses. In general, the commercial trade area is determined by the nature of stores, physical obstacles, competitions within the location, driving distance, and other elements. According to the Central Place Theory, high level goods and service industry influences low level goods and service industry. That is, a high level goods and service industry often affects the rented price of retail real estate for an area close to the industry.
In addition, the special image of retail real estate or core leasees, or the economic power of commercial trade area may increase the amount of sales in retail real estate, and the increase will be reflected in rental price of retail real estate. The model also explains the recent accumulation of retail stores at the center of a shopping district, and the crowding phenomenon which allows the consumers to visit many stores in single visit, thereby saving the cost of traveling, but the phenomenon differs in scale and pattern depending on the local characteristics. (Dipasqual Wheaton; 1996)
The accumulation of retail stores arises depending on the hierarchy or kind of retail products, such as convenience goods or shopping goods. (McDonald; 1999) The structure or characteristic of commercial trade area always changes. In general, the structure or characteristic of commercial trade area changing according to the physical conditions, such as type of residence, or road construction, or investment in new buildings. Factors describing the characteristics of commercial trade area include the size, shape, local population, nature of the population (age, gender, income, and so on), potential expense, degree of market penetration, degree of market dominance, absorption power of client, approachability of store, and transportation. Factors determining the economic power of commercial trade area include the price of real estate, population, housing, industry, and real estate development. The index describing the economic power of commercial trade area include the number of population, household, population density, population spread according to age, population increase rate, weekly population index, income, and buying power for each product. The economic power of such commercial trade area differs depending on the type of real estate, so it is using the index for the economic power of commercial trade area for residence, where the index includes the rate of home ownership, single housing, apartment, duplex housing, and other types of housing. Moreover, the economic power index of commercial trade area related to industry includes the number of businesses, number of employees, spread of employees per industry, increase of sales amount in wholesale and retail businesses, and degree of concentration within 1㎢ for wholesale, retail, and restaurant businesses. The economic power index of commercial trade area related to the real estate price includes the premium of store, rent of store, deposit money for the rent of house, and rental price of office. Lastly, the economic power index of commercial power related to real estate development includes the viability of the area to turn it into a commercial area next to a subway station, commercial area through rezoning, part of land planning, business building, administrative town, residential and commercial building, project of expanding or repairing a road, and redevelopment project.
Thus, based on the basic theory in the formation of a commercial trade area, this study has considered the average premium or deposit of the retail real estate within the commercial trade area, population of the trade area, the number or types of housing within the trade area, and the number, types, or members of businesses within the trade area to determine the rental price of retail real estate per pyeong (3.3058㎡). The average rental price of commercial trade area according to this model is the function of effective buying power, where the effective buying power is determined by the size of population and income within the trade area.
RENTji=j(LRPj, POPj, HOUSEj, INDUSTRYj) (1)
That is, this study intends to propose in details the economic variables of commercial trade area which affect the rental price of retail real estate. This study used a multiple regression analysis (least squares) to examine the relationship between the rental price of retail real estate in Seoul and the various descriptive variables.
(2) Definition of variables
Main variables directly or indirectly related to equation (1) above have following definitions. Variables related to the economic power or rental price of economic trade area are many when they are viewed macroscopically or microscopically, but this study limited them to four.
1) The premium or deposit of commercial trade area
The center has high land price, so the price of housing, deposit for renting housing, rental price of office, and rental price of retail real estate are set at higher price. Higher average deposit and premium for retail real estate within commercial trade area lead to higher rental price per pyeong. Among them, the average premium of commercial trade area represents the present and future economic power index of commercial trade area, so this study included deposit and premium as important variables.
Premium is also interpreted as the index which reflects the present and future possibility of the relevant commercial trade area. Premium means the amount being paid by new leasee to the existing leasee for certain rights attached to the business, facilities, or ground being transferred. There are premiums for business, facility, or ground, but they are all added into one when dealing with retail real estate.
Firstly, premium for business arises from the successful efforts of present leasee to enliven the business of the store or commercial area, and it awards the leasee for the build up of royal clients, reputation of the store, and the sole right to a franchise and resulting superior standing in the market. Secondly, premium for facility is formed when the existing leasee asks for the cost for the facility she invested, such as interior, sign, or equipment, at the start of her business from new leasee who happens to engage in the same type of business as the existing leasee. Thirdly, premium for ground is reward for good business due to the store location. Lastly, other premiums include the amount new leasee pays to the existing leasee for any other rights besides business, facility, or ground.
2) Population
Population is the basic unit of demand for goods or services. The demand here means the valid demand for goods or services, and it is included in this study as a major variable because the object among the population is determined by the types of goods or services. Fixed and floating population is directly related to the amount of sale in retail real estate. Thus, the valuation of retail real estate is proportionally related to the number of people passing through the area. That is, the concentration of population or change in the background population determines the value of the consumption center. Also, the increase of population and accompanying changes in environments are very important in consumption activities. Variables representing income, such as occupation, education level, and spending, are important variables which affect the retail sales of store. Especially, the characteristics of population within commercial trade area represent the quality of commercial trade area. In this respect, in the consumer market of food or clothing, the total population size is an important index which determines the volume of demand for the products.
3) Housing
Housing takes up an important part of national economy. Housing is a part of stock, a fixed capital, and it takes up a portion of political means in creating wealth. Housing is closely related to the industry of locale. Like a luxury vehicle, housing is also a symbol of prestige one occupies in the society. A large portion of individual wealth is spent on the purchase or maintenance of housing, and the state or type of possession of housing directly or indirectly represents the social position or income level of the resident. The type of ownership, size of possession, and location of the residence are used as variables representing the income of individual along with the source and amount of income and occupation. Thus, this study used the resident of apartment and ownership of housing as well as the average amount of vehicle and residential tax as proxy variables to represent the income level of the area.
4) Industry
The source of demand for real estate is a part of the business activity in the area. Changes in hiring practice of economically active population for each industry greatly affect the market, and they are followed by changes in the consumption patterns. That is, people working in the secondary or tertiary industry maintain the westernized life style, so they contribute greatly in increasing the demand for consumer goods including durable consumer goods. In this case, department stores with the concentration of sales businesses or discount stores with restaurants will suitably cater to the population as well as the food court, entertainment district, hotel, cram school, or theater.
2. Data
The data set used for this study consists of 50,000 data for retail real estate rental in Seoul Metropolitan Area and the 2002 Annual Statistics Report of Seoul. (2003) Monthly rental per pyeong was assigned as a response variable, and items of population, industry, and housing were assigned as explanatory variables. The monthly rental, deposit, and premium per pyeong in Seoul area came from the monthly rental of retail real estate properties, which were on the market from December 1st of 2004 to December 31st of the same year. The explanatory variables chosen were deposit per pyeong, premium per pyeong, area scale, population density, total population size, gender ratio, median age, the number of household, own housing, leased housing, housing with month to month rent, single housing, number of housing, apartment, duplex housing, the rate of home ownership, number of businesses, number of employees, number of manufacturers, number of employees in manufacturing industry, number of businesses in the tertiary industry, number of people in the tertiary industry, number of businesses in service industry, number of wholesalers or retailers, number of restaurants or hotels, number of IT businesses, number of cultural businesses, number of welfare recipients, number of people who receive help from governmental agencies, number of registered vehicles and number of people receiving governmental. The data which were used in this study are summarized in the followings:
Ⅳ. Conclusion
This study described in details how certain variables related to the economic power of commercial trade area affect the determination of rent in retail real estate. For the empirical model, this study established a data set utilizing the rent of retail real estate within Seoul and the Annual Statistical Report of Seoul. This study selected significant variables among 36 variables related to the economic power of commercial trade area using statistical data mining. More precisely, this researcher used variables deciding the rent within economic trade area, such as the population, housing, and industry.
According to the analysis which determined factors affecting the rent of commercial real estate, premium per pyeong, area scale, ratio of duplex housing, number of employees, number of people working in the tertiary industry, number of people working in manufacturing sector, number of restaurants and hotels, number of people receiving governmental preference, number of welfare recipients, number of registered vehicles were found to be significant.
(2) When this study observed the statistic of the optimal model based on the 10 explanatory variables, each P value for every explanatory variable was found to be below 0.05, so the finding was significant with 95% reliability. Also, both the adjusted coefficient of determination (adjR2) at 0.522 and the value of F at 42.63 were rather high when compared to the results from previous studies.
(3) The residual analysis, influence evaluation, and multi collinearity analysis were performed as parts of the regression analysis, and the Durbin-Watson value of residue was found to be 0.917, thereby satisfying the independence of residue. Also, the distribution of residue was close to normal, so the result satisfied the normalization.
In the option pricing model, the price of call option for lease contract was high when the rent of store was high, whereas the price of put option was high when the rent index was low. The result implies that one must consider, along with the real estate dealings, investing in real estate related financial products based on the rent index of store to hedge the market risk resulting from the volatility of underlying asset or option price according to the rent price of commercial trade area.
(5) Other studies mostly confined themselves by discussing limited variables representing the economic power of commercial trade area, such as the rent vacancy rate within the trade area, competitive nature of the trade area, and number of household receiving governmental aid, but this study prides itself for building a retail rent decision model with more detailed data, such as the population, housing, and industry of commercial trade area. Accordingly, this study, through an empirical analysis, has proved that the rent of retail real estate in Seoul is affected by the population, income, present state of industry, deposit, and premium. Thus, this study has proven that one must consider the economic power of commercial trade area when building a rent decision model for commercial real estate. Moreover, this study finds it necessary to build variables and models for each type of commercial trade area in the future.

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국문 초록 (Abstract)

본 논문은 통계적 데이터마이닝(Data mining)을 통하여 소매부동산의 임대료에 영향을 미칠 수 있는 시장상황 변수를 추출하고 이를 바탕으로 상가 임대차계약의 옵션 가치를 추정하는데 그 목적이 있다.
분석대상 자료는 크게 횡단면자료와 종단면자료로 구분하여 사용하였다. 종단면자료는 1995년 1월부터 2004년 12월까지의 전국의 상가임대료지수, 소비자물가지수, 부동산임대 및 가격지수(주택의 매매 및 전세 지수, 오피스 임대료, 이자율(3년만기 회사채 수익률)이다. 횡단면자료는 2004년 12월의 서울시 지역에 있는 소매부동산의 50,000개의 호가임대료를 반응변수로 사용하고 설명변수는 총 36개의 변수로 동별 평균 보증금, 동별 평균 권리금, 면적 , 인구밀도, 총인구, 남자, 여자, 성비, 중위연령, 가구수, 자가 가구, 전세가구, 월세가구, 기타, 단독세대, 주택수, 단독주택, 아파트, 연립세대, 기타, 주택보급률, 총 사업자수, 총 종사자수, 제조업체수, 제조업 종사자수, 3차산업 종사자수, 서비스업체수, 도소매 업체수, 음식숙박업체수, IT 업체수, 문화산업 업체수, 생활보호대상자, 장애인 등록수, 승용자 등록대수를 사용하였다. 또한 건물별 임대료 모형에서는 서울시 위치한 4,990개의 소매부동산을 2004년 12월 1개월 동안에 시장조사를 통하여 자료를 구축하였다. 평당 월세를 반응변수로 하고 설명변수는 총 16개이며, 설명변수에는 은행입점여부, 지하철역과의 이격거리, 건축연면적, 주차대수, 총승강기 대수, 경과년수, 지상층수, 지하층수, 전용률, 소유자수(1999 , 2002), 준공년도, 관리비, 경과년수, 임대료(보증금)가 해당된다.
본 연구는 이론적으로는 실물옵션이론, 지대이론과 밀접한 관련을 가지고 있다. 상가 임대차계약의 옵션가치는 상가임대료와 상가임대료결정에 영향을 주는 설명변수가 변화됨에 따라 차이가 나타났다. 상가 임대차계약의 옵션가치는 일반경제, 상권의 경제, 건물의 속성에 의해 영향을 받는다. 상가 임대차계약의 옵션가치는 시장임대료와 상점의 매출액, 그리고 임대차기간 의해 차이가 발생한다.
실증적으로 분석한 결과, 상가임대료 지수의 장기시계열은 점진적으로 상승추세를 띠고 있고 있으며 2003년 이후에는 급속도로 상승하고 있다. 상가임대료지수는 1997년 이전에는 분산이 컸으나 시간이 흐름에 따라 감소했다. 1995년부터 2004년까지의 자료를 근거로 한 상가임대료의 변동성은 2%미만이었다. 소매부동산의 임대료의 시계열상의 추이는 소비자물가지수, 사무실 임대료와는 동행하고 이자율과는 반대의 방향으로 움직이는 것을 알 수 있었다. 소매부동산의 임대료 구조에서는 평당 월임대료, 평당 권리금, 평당 보증금 사이에 정(+)의 상관관계가 존재하였다. 평당 보증금이 높은 지역은 전통적으로 상권력이 높은 지역이었으며 월임대료가 높은 지역은 최근 상권력이 확대되는 지역들이었다. 상권내의 소매부동산 임대료에 영향을 미치는 주요 시장변수는 산업, 인구, 주택이다. 특히, 평당 권리금, 총종사자수, 3차산업총사자수, 음식숙박업체수, 정부특혜수령자, 연면적, 관리비, 지상층수, 지하철과의 이격거리 변수는 회귀분석에서 베타값이 높게 나와 소매부동산임대료를 산정함에 있어 상대적으로 비중 있는 설명변수로 분석되었다. 이항모형을 이용한 상가 임대차계약의 옵션가치를 추정할 경우에는 상가의 매출액의 산정과 적정한 시장임대료의 산정이 상가임대차계약의 현금흐름과 옵션가격을 추정하는 것이 제일 중요하다.

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본 논문은 통계적 데이터마이닝(Data mining)을 통하여 소매부동산의 임대료에 영향을 미칠 수 있는 시장상황 변수를 추출하고 이를 바탕으로 상가 임대차계약의 옵션 가치를 추정하는데 그 목...

목차 (Table of Contents)