In Korea, macroeconomic changes and demographic changes are underway, such as low interest rates for more than 10 years, prolonged low birth rates, an increase in the elderly population, and population concentration in large cities. In addition, consumption patterns are rapidly changing due to the increase in non-face-to-face online commerce triggered by COVID-19 and the emergence of unmanned stores. Despite these changes in macroeconomics, consumption patterns, and demographic structure, there is still a lack of research that presents investment standards or investment plans for neighborhood shopping malls that are closely related to our lives.
Therefore, this study provides information on market analysis criteria and successful bid rate formation factors for rational investment decision-making to owners and investors of neighborhood shopping malls, thereby making a reasonable decision to establish real estate policy, investment decision-making and management activities for neighborhood shopping malls. It aims to provide a framework for decision-making.
As a proxy variable for the price of neighborhood shopping malls, the successful bid rate for neighborhood shopping malls in Seoul and Gyeonggi-do auction markets was selected. As explanatory variables for this, interest rate, economic growth rate, and consumer price index were selected among macroeconomic variables. As changes in consumption patterns are expected to affect the rate of drop in neighborhood shopping malls, the online-only mall transaction amount was selected as a new variable. Population size, 1-2 person households, and economically active population were selected as demographic variables.
The spatial scope of this study selected Seoul and Gyeonggi-do, and quarterly time series data from the first quarter of 2005 to the fourth quarter of 2022 were used. Since macroeconomic variables, consumption type variables, and demographic variables used in the analysis have the characteristics of time-series data, VECM (Vector Error Correction Model), which is suitable for multi-time series analysis, was used.
The analysis results and implications of the changes in the successful bid price ratio of neighborhood shopping malls in this study can be summarized as follows.
First, as a result of shock response analysis of each variable on the successful bid price of neighborhood shopping malls in Seoul, the interest rate, economic growth rate, consumer price index, population growth rate, 1-2 person household growth rate, and economically active population growth rate all showed a positive (+) response. Only the online sales growth rate showed a negative (-) response. Variables other than the online sales growth rate were found to have an effect with differences in degree.
As a result of variance decomposition of prediction errors, the main influencing factors were analyzed in the order of 1-2 person household growth rate, consumer price index, interest rate, economic growth rate, economically active population growth rate, population growth rate, and online-only transaction amount. 1-2 person household growth rate shows the number of independent unmarried young people or the number of elderly people who are separated from their households. As they emerge as major customers, they have become an important factor in determining the successful bid price rate of neighborhood shopping malls, and are judged to be a factor in increasing the successful bid price ratio of neighborhood shopping malls. Therefore, when making an investment decision on neighborhood shopping malls, it is necessary to consider the growth rate of 1-2 person households and the regional characteristics of population outflows and inflows.
Second, as a result of shock response analysis of each variable on the successful bid price of neighborhood shopping malls in Gyeonggi-do, the interest rate, economic growth rate, consumer price index, population growth rate, and economically active population growth rate showed a positive (+) response, and online sales growth rate, 1-2 person household growth rate showed a negative (-) response.
As a result of the variance decomposition of prediction errors, the main influencing factors were analyzed in the order of online sales growth rate, population growth rate, interest rate, economic growth rate, consumer price index, economically active population growth rate, and 1-2 person household growth rate. The growth rate of online sales is growing rapidly thanks to the popularization of SNS and smartphones. Seoul is a densely populated city with high accessibility to neighborhood shopping malls, but Gyeonggi-do has low population density, so accessibility to neighborhood shopping malls is low, and demand for online purchases seems to be higher. This growth rate of online sales is a factor that can decrease the successful bid price rate of neighborhood shopping malls in Gyeonggi-do, and should be considered first when making investment decisions.
Third, for the baby boom generation and early retirees to secure funds for retirement and living, neighborhood shopping malls that can generate investment and rental income are expected to be good investment destinations. In addition, demand for indirect investment products such as real estate REITs and FUNDs, which are alternative investment products, is expected to increase, so the above variables should be reviewed in advance when investing.
Finally, in summarizing, it is necessary to consider the characteristic variables of each region in advance, along with the review of demographic variables in Seoul and consumption patterns and macroeconomic variables in Gyeonggi-do.