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A Dynamic Causality Analysis of Oliver Flounder Producer Price by Region using the Panel VAR Model

패널 VAR 모형을 이용한 지역별 양식넙치 산지가격의 동태적 인과관계 분석

  • Jeon, Yong-Han (Division of Economics, College of Humanities & Social Sciences, Pukyong National University) ;
  • Nam, Jong-Oh (Division of Economics, College of Humanities & Social Sciences, Pukyong National University)
  • 전용한 (부경대학교 인문사회과학대학 경제학부) ;
  • 남종오 (부경대학교 인문사회과학대학 경제학부)
  • Received : 2020.12.16
  • Accepted : 2021.03.23
  • Published : 2021.03.31

Abstract

The purpose of this study is to identify the leading price between Jeju and Wando's oliver flounder producer price and to analyze the dynamic effect of the regional producer price using the panel VAR model. In the process of analysis, it was confirmed that there are unit roots in the monthly data of Jeju and Wando's oliver flounder producer price. So, in order to avoid spurious regression, the rate change of producer price which carries out log difference was used in the analysis. As a result of the analysis, first, the panel Granger causality test showed that the influence of the change rate of producer price in oliver flounder in Jeju was slightly larger than that in Wando, but it was found that each region all leads the change rate of the producer price in oliver flounder. Second, the panel VAR estimation showed that the rate change of producer price in Jeju and Wando a month ago had a statistically significant effect on the change rate of producer price of each region. Third, the impulse response analysis indicated that other regions are affected a little more than the same region in case of the occurrence of the impact on the error terms of the change rate of produce price in Jeju and Wando oliver flounder. Fourth, the variance decomposition analysis showed that the change rate of producer price in the two regions was higher explained by Jeju compared to Wando. In conclusion, it is expected that the above results can not only be useful as basic data for the stabilization of oliver flounder producer price and the establishment of policies for easing volatility but can also help the oliver flounder industry operate its business.

Keywords

References

  1. 강영준 (2016), "패널 벡터자기회귀에 대한 이론 연구와 처리효과분석을 이용한 실증 연구", 박사학위논문, 고려대학교, 1-84.
  2. 강희찬.황상연 (2016), "R&D 투자와 환경쿠즈네츠 곡선 가설: CO2 사례 분석", 자원.환경경제연구, 25 (1), 89-112.
  3. 김홍기 (2005), "외국인 직접투자의 기술혁신 효과에 대한 실증분석", 과학기술정책연구원, 1-34.
  4. 남종오.정민주 (2017), "제주 양식넙치의 월별 산지가격 예측 및 예측력 비교", 해양정책연구, 32 (2), 1-22. https://doi.org/10.35372/KMIOPR.2017.32.2.001
  5. 박건준 (2016), "국내 주택시장에서의 매매가격과 거래량 간의 동적관계 분석", 석사학위논문, 경희대학교, 1-55.
  6. 손진곤.남종오 (2016), "중량별 제주 넙치 산지가격의 선도가격 추정 및 시장가격 충격에 대한 동태적 영향 분석", 수산해양교육연구, 28 (1), 198-210. https://doi.org/10.13000/JFMSE.2016.28.1.198
  7. 송유철.원용걸 (2011), "동아시아 국가들의 실질환율, 순수출 및 경제성장간의 상호관계 비교연구: 시계열 및 패널자료 인과관계 분석", KIF working paper, 1-47.
  8. 옥영수.김상태.고봉현 (2007), "양식 넙치의 가격변동 및 예측에 관한 연구", 수산경영론집, 38 (2), 41-62.
  9. 은석 (2015), "교육 및 사회정책이 출산율 고양효과에 대한 비교 연구: System-GMM을 활용한 26개국 18년간의 패널 자료 분석 결과를 중심으로", 보건사회연구, 35 (2), 5-31. https://doi.org/10.15709/HSWR.2015.35.2.5
  10. 이연정.이윤정.윤성민 (2019), "전력소비와 경제성장: 지역패널자료를 이용한 동태적 인과관계 분석", 한국지역개발학회지 31 (3), 185-206.
  11. 이용희 (2018), "패널 VAR 모형을 이용한 주택 관련 거시건전성정책의 효과에 관한 연구 -수도권 아파트가격을 중심으로-", 박사학위논문, 수원대학교, 1-146.
  12. 이헌동.안병일 (2016), "넙치 관측사업 효과분석 : 가격안정 및 시장효율성 개선효과, 산지-도매가격간 인과성 분석을 중심으로", 수산경영론집, 47 (1), 1-20 https://doi.org/10.12939/fba.2016.47.1.001
  13. 최봉호 (2014), "전략적 수출촉진정책과 비교우위 동태화의 관계에 대한 패널분석 - 한국의 중기술산업 중심 -", 무역통상학회지, 14 (3), 55-71.
  14. 한국해양수산개발원 (2011), "넙치 양식 동향 및 지역별 생산성 비교", KMI 월간동향, 17-22.
  15. Abidin, N. Z., Yussof, I. and Karim, Z. A. (2020), "Total Factor Productivity Shock and Economic Growth in Selected ASEAN+3 Countries: A New Evidence Using a Panel VAR," International Journal of Business and Society, 21 (3), 1366-1383. https://doi.org/10.33736/ijbs.3355.2020
  16. Abrigo, M. R. M. and Love, I. (2015), "Estimation of Panel Vector Autoregression in Stata," Stata Journal, 16 (3), 778-804. https://doi.org/10.1177/1536867x1601600314
  17. Andrews, D. and Lu, B. (2001), "Consistent Model and Moment Selection Procedures for GMM Estimation with application to dynamic panel data models," Journal of Econometrics, 101 (1), 123-164. https://doi.org/10.1016/S0304-4076(00)00077-4
  18. Arellano, M. and Bond, S. (1991), "Some Tests of Specification for Panel Data: Monte Carlo Evidence and an Application to Employment Equations," Review of Economic Studies, 58 (2), 277-297. https://doi.org/10.2307/2297968
  19. Arellano, M. and Bover, O. (1995), "Another Look at the Instrumental Variable Estimation of Errorcomponents Models," Journal of Econometrics, 68 (1), 29-51. https://doi.org/10.1016/0304-4076(94)01642-D
  20. Blundell, R. and Bond, S. (1998), "Initial Conditions and Moment Restrictions in Dynamic Panel Data Models," Journal of Econometrics, 87 (1), 115-143. https://doi.org/10.1016/S0304-4076(98)00009-8
  21. Canova. and Ciccarelli, M. (2013), "Panel vector autoregressive models: a survey," ECB Working Paper, 1507, 1-53.
  22. Hamilton, J. D. (1994), "Time Series Analysis," Princeton University Press, 291-350.
  23. Hayakawa, K. (2009), "First Difference or Forward Orthogonal Deviation- Which Transformation Should be Used in Dynamic Panel Data Models?: A Simulation Study," Economics Bulletin, 29 (3), 2008-2017.
  24. Holtz-Eakin, D., Newey, W. and Rosen, H. S. (1988), "Estimating Vector Autoregressions with Panel Data," Econometrica, 56 (6), 1371-1395. https://doi.org/10.2307/1913103
  25. Im, K. S., Pesaran, M. H., and Shin, Y. C. (2003), "Testing for Unit Roots in Heterogeneous Panels," Journal of Econometrics, 115 (1), 53-74. https://doi.org/10.1016/S0304-4076(03)00092-7
  26. Levin, A., Lin, C. F. and Chu, C. S. J. (2002), "Unit Root Tests in Panel Data:Asymptotic and Finite Sample Properties," Journal of Econometrics, 108 (1), 1-24. https://doi.org/10.1016/S0304-4076(01)00098-7
  27. Lutkepohl, H. (2005), "New Introduction to Multiple Time Series Analysis," Springer, 9-231.
  28. Nickell, S. (1981), "Biases in Dynamic Models with Fixed Effects," Econometrica, 49 (6), 1417-1426. https://doi.org/10.2307/1911408
  29. StataCorp LLC. (2019), "Stata Longitudinal-data/Panel data Reference Manual Release 16," 553-588.
  30. Zouaouia, H. and Zoghlami, F. (2020), "On the income diversification and bank market power nexus in the MENA countries: Evidence from a GMM panel-VAR approach," Research in International Business and Finance, 52, 1-19.
  31. 국가통계포털 (2020), "생산자물가지수", 2020년 10월 11일 접속 (http://kosis.kr).
  32. 한국해양수산개발원 수산업관측센터 (2021), "연도별.중량별 넙치 생산량", 2021년 3월 6일 접속(www.foc.re.kr).
  33. 한국해양수산개발원 수산업관측센터 (2021), "월별 넙치 산지가격 및 넙치 생산량", 2021년 3월 6일 접속(www.foc.re.kr).
  34. 동아일보, https://www.donga.com/news/Society/article/all/20191022/98006600/1
  35. 서울경제, https://www.sedaily.com/NewsVIew/1Z08WG7CNH
  36. 완도신문, http://www.wandonews.com/news/articleView.html?idxno=213310
  37. 한국일보, https://www.hankookilbo.com/News/Read/201907291643060891