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Impact of Population Relocation to City Commerce: Micro-Level Estimation with Validated Agent-Based Model

SeHoon Lee, Jeong Hee Hong, Jang Won Bae and Il-Chul Moon
Journal of Artificial Societies and Social Simulation 18 (2) 5

Abstract: To reduce overpopulation around Seoul, Korea, the government implemented a relocation policy of public officers by moving the government complex. This implies that there will be a negative impact on the suburban area that originally hosted the complex, but we do not know the magnitude of the impact. Therefore, this paper presents a micro-level estimation of the impact on the city commerce with an agent-based model. This model is calibrated by the micro-level population census data, the time-use data, and the geographic data. Agent behavior is formally specified to illustrate the daily activities of diverse population types, and particularly the model observes how many agents pass by commercial buildings of interest. With the described model, we performed a virtual experiment that examines the strengths of factors in negatively influencing the city commerce. After the experiment, we statistically validated the model with the survey data from the real world, which resulted in relatively high correlation between the real world and the simulations.

Housing Market Agent-Based Simulation with Loan-To-Value and Debt-To-Income

Tae-Sub Yun and Il-Chul Moon
Journal of Artificial Societies and Social Simulation 23 (4) 5

Abstract: This paper introduces an agent-based model of a housing market with macro-prudential policy experiments. Specifically, the simulation model is used to examine the effects of a policy setting on loan-to-value (LTV) and debt-to-income (DTI), which are policy instruments several governments use to regulate the housing market. The simulation model illustrates the interactions among the households, the house suppliers, and the real estate brokers. We model each household in the population as either seller or buyer, and some of households may behave as speculators in the housing market. To better understand the impact of the policies, we used the real-world observations from the Korean housing market, which include various economic conditions, policy variables, and Korean census data. Our baseline model is quantitatively validated to the price index and the transaction volume of the past Korean housing market. After validation, we show the empirical effectiveness of setting LTV and DTI towards house prices, transaction volumes, and the amount of households' mortgages. Furthermore, we investigate the simulation results for the owner-occupier rate of households. These investigations provide the policy analyses in Korea's housing market, and other governments with LTV and DTI regulations.