Management & Information Systems Review (경영과정보연구)

Daehan Academy of Management Information Systems (대한경영정보학회)
권호 표지

A Study on Income and Price Elasticities of Tourism Demand in Korea

한국관광수요의 소득 및 가격탄력성에 대한 연구

  • Lee, Kyung-Hee (Dept. of Tourism Administration, Kangwon National University) ;
  • Kim, Kyung-Soo (Dept. of Accounting, Kangwon National University)
  • Received : 2017.07.17
  • Accepted : 2017.11.08
  • Published : 2017.11.30
Download PDF
⟨ Previous Next ⟩

Abstract

This study examined the income and price elasticities of tourism demand model by using the ARDL models. This paper used the ARDL & ARDL-RECM model based on the annual number of tourists arrivals, GDP and CPI including tourists from the US, Japan and China entering Korea. First, the income elasticity of the US was inelastic and insensitive necessities for long-run US tourists in the ARDL model. China's income elasticity was elastically sensitive luxuries. Second, the US and China's own price elasticities were very elastic to tourism demand in both models. Third, the US's cross price elasticity showed the relationship between inelastic positive substitutes and inelastic negative complements in China in ARDL model. The cross price elasticities of the US and China showed inelastic positive substitutes in the ARDL-RECM model. Fourth, the coefficients of the error correction term were such that the actual sign and the expected sign of the US and China coincided with the negative sign in the ARDL-RECM model. Therefore, first, it can be established in a tourist policy or tourism strategy through income elasticity. Second, we can improve the quality and differentiation of products, recognizing that Korea's tourism price is more elastic than other markets through price elasticity.

본 연구는 ARDL 모형을 이용하여 관광수요모형의 소득탄력성과 가격탄력성을 분석하고자 하였다. 한국으로 입국하는 미국, 일본 및 중국 등의 관광객 입국자수, GDP 및 CPI의 연별 IMF 자료를 바탕으로 설정된 ARDL과 ARDL-RECM 모형을 이용하였다. 첫째, ARDL 모형결과, 미국의 소득탄력성은 비탄력적으로 둔감하였으므로 장거리 미국관광객들에게는 필수재(necessities), 중국의 소득탄력성은 탄력적으로 민감하여 사치재(luxuries)로 구분되었다. 둘째, ARDL과 ARDL-RECM 모형결과, 미국과 중국의 자체가격탄력성이 매우 탄력적이고 민감하였다. 셋째, ARDL 모형결과, 미국의 대체가격탄력성이 비탄력적 대체재(substitutes), 중국은 비탄력적 보완재(complements)의 관계가 존재하고, ARDL-RECM 모형결과에서 미국과 중국의 대체가격탄력성은 비탄력적 대체재의 관계를 보여주었다. 넷째, ECM의 계수값은 미국과 중국의 실제와 기대부호가 음(-)의 값으로 일치하여 단기관계와 전기의 불균형에서 다음 기의 균형으로 조정해 가는 속도를 추정하였다. 이러한 모형에서 미국과 중국의 경우 설명력이 높고 적합도가 높으나, 자기상관이 약간 존재하였다. 본 연구의 결과는 한국정부에 의해 실행된 소득, 자체가격, 대체가격 및 정책이 미국, 일본 및 중국에서 한국으로의 관광수요를 성공적으로 설명하고 있다. 따라서 소득탄력성을 통해 관광정책 또는 관광전략을 수립할 수 있고 가격탄력성을 통해 한국의 관광가격이 타시장에 비해 탄력적임을 인식하여 관광서비스의 질과 상품의 차별화를 더욱 개선시킬 수 있다.

Keywords

References

  1. 김미경(2015), "21세기 관광산업진흥을 위한 관광벤처사업 활성화 방안," 경영과 정보연구, 34(3), 197-213.
  2. 김미숙(2015), "경영자보상이 투자와 이익조정에 미치는 영향에 관한 연구," 경영과 정보연구, 34(3), 179-196.
  3. 김한주(2015), "실현율을 이용한 관광 수요 예측 - 부산 송도케이블카 설치를 중심으로 -," 경영과 정보연구, 34(1), 179-190.
  4. 모수원.김창범(2001), "한국인 해외관광객의 추정과 예측," 관광학연구, 25(1), 117-134.
  5. 모수원.이광배(2004), "아웃바운드 관광수요의 변화," 산업경제연구, 17(6), 2287-2297.
  6. 박진석(2009), "일본인 한국관광수요의 결정요인에 관한 연구," 관광학연구, 33(2), 287-302.
  7. 변상우(2015), "관광지 선택 동기가 관광지 이미지, 재방문의도에 미치는 영향에 관한 연구 -감천문화마을을 중심으로 - ," 경영과 정보연구, 34(3), 197-213.
  8. 오현주.김상혁(2013), "거시 환경의 변화에 따른 국적별 외래 관광객 수요에 관한 연구," 관광레저연구, 25(4), 5-20.
  9. 유병철.오지영(2011), "환율변동에 따른 우리 나라의 장.단기 비대칭 해외관광수요 분석," 시장경제연구, 40(2), 47-77.
  10. 이강욱(1999), 한국 관광계량 모형(KTRI-99) 구축, 문화체육관광부.
  11. 이경희.김경수(2015), "인바운드 국제관광지출의 탄력성과 구조적 변화," 무역연구, 11(4), 461-483.
  12. 이경희.김경수(2016), "금융위기하에서 한국과 주요 선진국간의 국제적 경기변동성 추정," 무역연구, 12(4), 333-355.
  13. 이성훈(2015), "오차수정모형을 이용한 일본인의 방한 관광수요 분석," 한국엔터테인먼트산업학회지, 9(1), 169-176.
  14. 이종원(2007), 계량경제학, 3판, 박영사.
  15. 이종호(2015), "전시컨벤션 참관객 만족도와 참여업체 성과인식에 관한 연구 - 부산국제관광전을 중심으로 - ," 경영과 정보연구, 34(2), 171-191.
  16. 지성권(2010), "경영자보상의 하방경직성에 영향을 미치는 요인," 경영과 정보연구, 29(4), 333-357.
  17. 최영문.김사헌(1998), "단변량 시계열 관광 수요 예측모형의 적정성 비교평가 내국인 해외관광객수 실측치와 예측치의 비교," 관광학연구, 21(2), 111-128.
  18. Allsop, J.(2004), Premium pricing, paper presented at Future Foundation Changing Lives Conference, December.
  19. Breusch, T.(1978), Testing for autocorrelation in dynamic linear models, Journal of Australian Economic Papers, 17, 334-355. https://doi.org/10.1111/j.1467-8454.1978.tb00635.x
  20. Chow, G. C.(1960), Test of equality between sets of coefficients in two linear regressions, Econometrica, 28, 591-605. https://doi.org/10.2307/1910133
  21. Davidson, J., D. F. Hendry, F. Saba, and S. Yeo(1978), Econometric modelling of the aggregate time series relationships between consumers expenditure and income in the United Kingdom, Economic Journal, 88, 661-692. https://doi.org/10.2307/2231972
  22. Engle, R. F. and C. W. J. Granger(1987), Cointegration and error correction: Representation, estimation and testing, Econometrica, 55, 251-276. https://doi.org/10.2307/1913236
  23. Fama, E. F.(1965), The behavior of stock market prices, Journal of Business, 38, 34-105. https://doi.org/10.1086/294743
  24. Gilbert, C.(1986), Professor Hendry's methodology, Oxford Bulletin of Economics and Statistics, 48, 283-307.
  25. Godfrey, L. G.(1978), Testing for higher order serial correlation in regression equations when the regressors contain lagged dependent variables, Econometrica, 46, 1303-1310. https://doi.org/10.2307/1913830
  26. Granger, C. W. J. and R. Joyeux(1980), An introduction to long-memory time series models and fractional differencing, Journal of Time Series Analysis, 1, 15-29. https://doi.org/10.1111/j.1467-9892.1980.tb00297.x
  27. Greene, W. H.(1993), Econometric Analysis (2nd), New York, NY: Macmillian Publishing.
  28. Hendry, D. F.(1995), Dynamic Econometrics: Advanced Text in Econometrics, Oxford, UK: Oxford University Press.
  29. Hendry, D. F. and T. von Ungern- Sternberg(1981), Liquidity and inflation effects on consumers expenditure, In Essays on the Theory and Measurement of Consumer Behaviour, edited by Deaton, A. S., Cambridge. UK: Cambridge University Press.
  30. Huang, H. and C. Xu(1999), Financial institutions and the financial crisis, European Economic Review, 43, 903-914. https://doi.org/10.1016/S0014-2921(98)00103-2
  31. Hurst, H.(1951), Long-term storage capacity of reservoirs, Transactions of the American Society of Civil Engineers, 116, 770-799.
  32. International Monetary Fund(IMF)(1999), International Financial Statistics Yearbook. Washington, DC: International Monetary Fund.
  33. Jarque, C. M. and A. K. Bera(1980), Efficient tests for normality, homoskedasticity and serial independence of regression residuals, Economics Letters, 6, 255-259. https://doi.org/10.1016/0165-1765(80)90024-5
  34. Jarque, C. M. and A. K. Bera(1987), A test for normality of observations and regression residuals, International Statistical Reviews, 55, 163-172. https://doi.org/10.2307/1403192
  35. Johansen, S.(1988), A statistical analysis of cointegration vectors, Journal of Economic Dynamics and Control, 12, 231-254. https://doi.org/10.1016/0165-1889(88)90041-3
  36. Johansen, S. and K. Juselius(1990), Maximum likelihood estimation and inference on cointegration-with application to the demand for money, Oxford Bulletin of Economics and Statistics, 52, 169-210.
  37. Kim, S. and H. Song(1998), An empirical analysis of demand for Korean tourism: A cointegration and error correction approach, Tourism Analysis, 3, 25-41.
  38. Kotler, P., G. Armstrong, S. H. Ang, S. M. Leong, C. T. Tan and O. H. Yau(2009), Principles of marketing: A global perspective, Singapore, Pearson.
  39. Kulendran, N. and M. L. King(1997), Forecasting international quarterly tourist flows using error correction and time series models, International Journal of Forecasting, 13, 319-327. https://doi.org/10.1016/S0169-2070(97)00020-4
  40. Kulendran, N. and S. F. Witt(2001), Cointegration versus least squares regression, Annals of Tourism Research, 28, 291-311. https://doi.org/10.1016/S0160-7383(00)00031-1
  41. Lo, A. W.(1991), Long-term memory in stock market prices, Econometric Theory, 7, 1-21. https://doi.org/10.1017/S0266466600004217
  42. Lo, A. W. and C. Mackinlay(1988), Stock market prices do not follow random walks: Evidence from a simple specification test, Review of Financial Studies, 1, 41-66. https://doi.org/10.1093/rfs/1.1.41
  43. MacKinnon, J. G.(1996), Numerical distribution functions for unit root and cointegration tests, Journal of Applied Econometrics, 11, 601-618. https://doi.org/10.1002/(SICI)1099-1255(199611)11:6<601::AID-JAE417>3.0.CO;2-T
  44. Mandelbrot, B.(1963), The variation of certain speculative prices, Journal of Business, 36, 394-419. https://doi.org/10.1086/294632
  45. Mervar, A. and J. E. Payne(2007), Analysis of foreign tourism demand for Croatian destinations: Long-run elasticity estimates, Tourism Economics, 13, 407-420. https://doi.org/10.5367/000000007781497764
  46. Mizon, G. E. and J. F. Richard(1986), The encompassing principle and its application to testing non-nested hypotheses, Econometrica, 54, 657-78. https://doi.org/10.2307/1911313
  47. Narayan, P. K.(2004), Fiji's tourism demand: The ARDL approach to cointegration, Tourism Economics, 10, 193-206. https://doi.org/10.5367/000000004323142425
  48. Pesaran, M. H., Y. Shin, and R. J. Smith(2001), Bounds testing approaches to the analysis of level relationships, Journal of Applied Econometrics, 16, 289-326. https://doi.org/10.1002/jae.616
  49. Pesaran, B. and M. H. Pesaran(2009), Time series econometrics: Using Microfit 5.0, Oxford and New York, NY: Oxford University Press.
  50. Ramsey, J. B.(1969), Test for specification errors in classical linear test squares regression analysis, Journal of the Royal Statistical Society, Series B, 31, 350-371.
  51. Song, H., P. Romilly, and X. Liu(2000), An empirical study of UK outbound tourism demand, Applied Economics, 32, 611-624. https://doi.org/10.1080/000368400322516
  52. Thomas, R. L.(1997), Modern Econometrics: An Introduction, Harlow, UK: Addison- Wesley.
  53. White, H.(1980), A heteroskedasticityconsistent covariance matrix estimator and a direct test of heteroskedasticity, Econometrica, 48, 817-838. https://doi.org/10.2307/1912934
  54. Witt, S. F. and C. A. Witt(1992), Modeling and Forecasting Demand in Tourism, London: Academic Press.
  55. Witt, S. F. and C. A. Witt(1995), Forecasting tourism demand: A review of empirical research, International Journal of Forecasting, 11, 447-475. https://doi.org/10.1016/0169-2070(95)00591-7
  56. Yeoman, I.(2008), Tomorrow's tourist: Scenarios & trends, edited by Page, S. J.. Advances in tourism research, Oxford: Elsevier.
  57. Zellner, A.(1988), Bayesian analysis in econometrics, Journal of Econometrics, 37, 27-50. https://doi.org/10.1016/0304-4076(88)90072-3