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Analysis on Real Discount Rate for Prediction Accuracy Improvement of Economic Investment Effect

경제적 투자효과의 예측 정확도 향상을 위한 실질할인율 분석

  • Lee, Chijoo (Graduated School of Engineering Mastership, Pohang University of Science and Technology) ;
  • Lee, Eul-Bum (Graduated School of Engineering Mastership, Pohang University of Science and Technology)
  • 이치주 (포항공과학교 엔지니어링 대학원) ;
  • 이을범 (포항공과학교 엔지니어링 대학원)
  • Received : 2014.07.16
  • Accepted : 2015.01.06
  • Published : 2015.01.31

Abstract

The expected economic effect by investment was divided by square of real discount rate annually for change to present value. Thus, the impact of real discount rate on economic analysis is larger than other factors. The existing general method for prediction of real discount rate is application of average data during past certain period. This study proposed prediction method of real discount rate for accuracy improvement. First, the economic variables which impact on interest rate of business loan and consumer price of real discount rate were determined. The variables which impact on interest rate of business loan were selected to call rate and exchange rate. The variable which impact on consumer price index was selected to producer price index. Next, the effect relation was analyzed between real discount rate and selected variables. The significant effect relation were analyzed to exit. Lastly, the real discount rate was predicted from 2008 to 2010 based on related economic variables. The accuracy of prediction result was compared with actual data and average data. The real discount rate based on actual data, predicted data, and average data were analyzed to -1.58%, -0.22%, and 6.06%, respectively. Though the proposed method in this study was not considered special condition such as financial crisis, the prediction accuracy was much higher than result based on average data.

투자에 의해 기대되는 경제적 효과는 실질할인율의 자승으로 매년 나누어서 현재가치로 전환된다. 따라서 실질할인율이 경제성 분석결과에 미치는 영향은 다른 요인들보다 크다. 실질할인율을 예측하는 기존의 일반적인 방법은 과거 특정기간의 평균값을 적용하는 것이다. 본 연구에서는 실질할인율의 예측 정확도를 향상시키기 위한 방법을 제안하였다. 먼저 실질할인율을 구성하는 기업대출 이자율과 소비자 물가지수에 영향을 미치는 경제변수들을 도출하였다. 기업대출 이자율에 영향을 주는 변수들로는 콜 금리와 환율, 소비자 물가지수에 영향을 주는 경제변수는 생산자 물가지수를 선정하였다. 다음으로 실질할인율과 선정된 변수들과의 영향관계를 검정하였다. 영향관계가 존재하는 것으로 분석되었다. 마지막으로 관련된 경제 변수들을 기반으로 2008년부터 2010년까지의 실질할인율을 예측하였다. 예측 결과의 정확도는 실측값과 평균값의 결과와 비교되었다. 실측값이 적용된 실질할인율은 -1.58%였으며, 예측 값은 -0.22%, 평균값은 6.06%으로 분석되었다. 본 연구에서 제안한 방법은 금융위기와 같은 특수 상황을 고려하지 않은 것이지만, 평균값보다 예측 정확도가 크게 우수한 것으로 분석되었다.

Keywords

References

  1. Kim, B., and Jung, Y. (2012). "Stochastic analysis for Rel Rate Interest of Building Life Cycle Cost (LCC) with Monte-Carlo Simulation", Proceedings of the Korea Institute of Building Construction the Spring Conference, 12(1), pp. 161-164.
  2. Kim, B., and Jung, Y. (2014). "A Study on Development of the Probabilistic LCC Analysis (P-LCCA) Model to Building by using Forecast Simulation", Journal of Architectural Institute of Korea, 30(3), pp. 115-122. https://doi.org/10.5659/JAIK_SC.2014.30.3.115
  3. Kim, J., Jung, Y., and Son. J. (2010). "A Study on Reliability Analysis Model of the Repair and Replacement Cycle of a Building Which Utilizes Monte Carlo Simulation", Journal of the Korea Institute of Building Construction, 10(2), pp. 41-50. https://doi.org/10.5345/JKIC.2010.10.2.041
  4. Kim, M., and Kang, K. (2005). "The Long-term Relation Analysis between PPI and CPI in Korea", Journal of money & finance, 19(2), pp. 170-206.
  5. Choi, M., and Lee, E. (1999). "LCCA Method of Construction Industry and Application Method", Construction Economy Research Institute of Korea (CERIK).
  6. Hong, C., and Cho, W. (2010). "A Study on the Lead-Lag Relationship between Call, KOSPI and Won/Dollar Spot Markets", Journal of Korean Industrial Economics and Business, 2(1), pp. 1-21.
  7. Hur, N., Jung, J., and Kim, S. (2009). "A Study on Air Demand Forecasting Using Multivariate Time Series Models", Journal of the Korean Statistical Society, 22(5), pp. 1007-1017. https://doi.org/10.5351/KJAS.2009.22.5.1007
  8. Jang, S. W. (2014). "Analysis of Dynamic Relationship between Changes in Domestic and Overseas Orders and Insolvency of Construction Companies", Korean Journal of Construction Engineering and management, KICEM, 15(2), pp. 87-94. https://doi.org/10.6106/KJCEM.2014.15.2.087
  9. Jun, H. M. (2012). "Analysis on the determinants of bank profitability in Korea", Dissertation of Master degree, Soongsil University.
  10. Lee, H., Park, J., Song, D., and Lim, K. (2005). "Time Series Analysis of Financial Economy using EVIEWS", Kyungmoon Publishers.
  11. Lee, C., and Lee. G. (2010). "Relation Analysis Between REITs and Construction Business, Real Estate Business, and Stock MArket", Korean Journal of Construction Engineering and management, KICEM, 11(5), pp. 41-52. https://doi.org/10.6106/KJCEM.2010.11.5.41
  12. Lee, H. S. (2007). "A Study on the Influence of Macroeconomic Factors upon the Housing Transation and Jeonse Rental Index". Dissertation of Ph.D degree, Kyungwon Univeristy.
  13. The Bank of Korea. (2011). "Economic Statistics System", .

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