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Generation of Panel statistics using small enterprise mall (commercial district) big data and analysis of the impact of COVID-19 : Focusing on Chungcheongbuk-do
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소상공인 상가(상권) 빅데이터를 이용한 패널 통계작성과 COVID-19의 영향분석 : 충청북도를 중심으로

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Type
Academic journal
Author
Kim, JoungGu (청주대학교)
Journal
Chungbuk Research Institute 지역정책연구 Vol.33 No.2 KCI Accredited Journals
Published
2022.8
Pages
159 - 194 (36page)

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Generation of Panel statistics using small enterprise mall (commercial district) big data and analysis of the impact of COVID-19 : Focusing on Chungcheongbuk-do
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In this study, small enterprise panel statistics were prepared using small enterprise big data from 2016Q1 to 2022Q1 provided by SEMS(Small Enterprise and Market Service) through the public data platform (DATA.GO.KR). In addition, static analysis and dynamic analysis using these statistics were performed. Statistics using big data were compiled by city·gun·gu·eup·myeon·dong, quarterly, and industry in Chungbuk.
As a preliminary work to conduct static analysis, the number and closure rates of businesses closed during 2019Q4 and 2021Q2 were calculated. For dynamic analysis, a breakpoint unit root test was conducted to analyze whether COVID-19 had an effect on the structural change in the number of small enterprises in city·gun·gu, anddistricts in Chungcheongbuk-do.
First, as a result of statistical aggregation of big data, the number of small enterprises in Chungbuk in 2022Q1 was 87,717, accounting for 4% of the nation’s 2,208,968 establishments. By industry, the retail industry accounted for the largest share at 35.2%, followed by the food and beverage industry at 33.2% and the living service industry at 17.2%. Characteristics of the time series change from 2016Q1 to 2022Q1 were a sharp increase that deviates from the existing trend after 2019Q1, a sharp decline that deviates from the existing trend after Q4 2020, and a recovery of the existing trend after Q3 2021. As a result of comparative static analysis, it was found that during the analysis period, the closure rate of cities, guns, and gu with dense population was high, and Cheongju occupies 65.8% of the closed businesses.
By industry, tourism/leisure/entertainment had the highest closure rate at 41.7%. As a result of the dynamic analysis, structural changes occurred in the 4 districts of Cheongju, Chungju, and Danyang-gun due to COVID-19, and it was analyzed that the effects of constantbreak, trendbreak, and breakdum variables were different depending on the region.

Contents

Ⅰ. 서론
Ⅱ. 선행 연구 검토
Ⅲ. 빅데이터 통계작성 방법 및 모형설정
Ⅳ. 실증분석 결과
Ⅴ. 결론
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