Estimating de facto Population Using Spatial Statistics

Lee， Gunhak; Kamyoung Kim

Recently, demand for statistics of the potential service population is increasing for the analysis of trade area for small business establishment and the investigation of regional industrial demands. The census is not appropriate for estimating a timely potential service population because the census survey is usually implemented at a regular long interval. Mobile telecommunications big data collected from individual’s mobile phone enables to overcome the shortcomings of the census and presents the real-time dynamics of regional population distribution and flow. This research attempts to estimate a de facto population as potential service demand of the region using a mobile telecommunications big data and spatial statistics. For doing this, we first examined the distribution of the ‘service population’ of Daegu metropolitan city in terms of gender, age, and temporal periods, which is provided by a commercial mobile telecom company. Then, we estimated a de facto population by census output area using OLS and spatial regression models based on a number of explanatory variables regarding population, social, and economic characteristics of the region. The empirical results show that a potential service population can be significantly estimated using regional statistical data and the spatial regression model with an explicit consideration of spatial dependency of population is the best fit for de facto population estimation. The estimation error is smallest in the level of the census output area and de facto population by age group is more accurately estimated than other population categories. For the spatial distribution of the estimation error, over-estimation has often occurred in central areas of the city and under-estimation has appeared in outer areas of the city. This might be led by the regional differentiation of mobile-phone usage and mobility.

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REFERENCES (16)
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* 2021년 이후 발행 논문의 참고문헌은 현재 구축 중입니다.

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