• Title/Summary/Keyword: Cointegration Method

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Cointegration based modeling and anomaly detection approaches using monitoring data of a suspension bridge

  • Ziyuan Fan;Qiao Huang;Yuan Ren;Qiaowei Ye;Weijie Chang;Yichao Wang
    • Smart Structures and Systems
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    • v.31 no.2
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    • pp.183-197
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    • 2023
  • For long-span bridges with a structural health monitoring (SHM) system, environmental temperature-driven responses are proved to be a main component in measurements. However, anomalous structural behavior may be hidden incomplicated recorded data. In order to receive reliable assessment of structural performance, it is important to study therelationship between temperature and monitoring data. This paper presents an application of the cointegration based methodology to detect anomalies that may be masked by temperature effects and then forecast the temperature-induced deflection (TID) of long-span suspension bridges. Firstly, temperature effects on girder deflection are analyzed with fieldmeasured data of a suspension bridge. Subsequently, the cointegration testing procedure is conducted. A threshold-based anomaly detection framework that eliminates the influence of environmental temperature is also proposed. The cointegrated residual series is extracted as the index to monitor anomaly events in bridges. Then, wavelet separation method is used to obtain TIDs from recorded data. Combining cointegration theory with autoregressive moving average (ARMA) model, TIDs for longspan bridges are modeled and forecasted. Finally, in-situ measurements of Xihoumen Bridge are adopted as an example to demonstrate the effectiveness of the cointegration based approach. In conclusion, the proposed method is practical for actual structures which ensures the efficient management and maintenance based on monitoring data.

An Estimation of Korea's Import Demand Function for Fisheries Using Cointegration Analysis (공적분분석을 이용한 우리나라 수산물 수입함수 추정)

  • 김기수;김우경
    • The Journal of Fisheries Business Administration
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    • v.29 no.2
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    • pp.97-110
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    • 1998
  • This paper tries to estimate Korea's import demand function for fisheries using cointegration analysis. The estimation function consists of one dependent variable-import quantity of fisheries(FTIW) and two independent variables-relative price(RP) between importable and domestic products and real income(GDP). As it has been empirically found out that almost all of time series of macro-variables such as GDP, price index are nonstationary, existing studies which ignore this fact need to be reexamined. Conventional econometric method can not analyze nonstationary time series in level. To perform the analysis, time series should be differenciated until stationarity is guaranteed. Unfortunately, the difference method removes the long run element of data, and so leads to difficulties of interpretation. But according to new developed econometric theory, cointegration approach could solve these problems. Therefore this paper proceeds the estimation on the basis of cointegration analysis, because the quartly variables from 1988 to 1997 used in the model is found out to be nonstationary. The estimation results show that all of the variables are statistically significant. Therefore Korea's import demand for fisheries has been strongly affected by the variation of real income and the relative price.

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Comovement and Forecast of won/dollar, yuan/dollar, yen/dollar: Application of Fractional Cointegration approach and Causal Analysis of Frequency Domain (한·중·일 환율 사이의 움직임 분석 - 분수공적분과 진동수영역의 인과성 -)

  • Jung, Sukwan;Won, DooHwan
    • International Area Studies Review
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    • v.21 no.2
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    • pp.3-20
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    • 2017
  • Traditional co-integration analysis method is known to be difficult to clearly determine the relationship between the cointegrated variables. This study utilizes a fractional cointegation method and a causal analysis of time and frequency domain among the exchange rates of Korea, China and Japan. The results show that even though traditional cointegration methods did not clarify the existence of cointegration, exchange rates were fractionally cointegrated. Causal analysis of time domain and frequency domain provided somewhat different results, but the yen/dollar was useful for forecasting won/dollar and yuan/dollar. Proper use of causal analysis of frequency domain and fractional cointegration emthods may provide useful information that can not be explained from the traditional method.

Online damage detection using pair cointegration method of time-varying displacement

  • Zhou, Cui;Li, Hong-Nan;Li, Dong-Sheng;Lin, You-Xin;Yi, Ting-Hua
    • Smart Structures and Systems
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    • v.12 no.3_4
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    • pp.309-325
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    • 2013
  • Environmental and operational variables are inevitable concerns by researchers and engineers when implementing the damage detection algorithm in practical projects, because the change of structural behavior could be masked by the conditions in a large extent. Thus, reliable damage detection methods should have a virtue of immunity from environmental and operational variables. In this paper, the pair cointegration method was presented as a novel way to remove the effect of environmental variables. At the beginning, the concept and procedure of this approach were introduced, and then the theoretical formulation and numerical simulations were put forward to illustrate the feasibility. The jump exceeding the control limit in the residual indicates the occurrence of damage, while the direction and magnitude imply the most potential damage location. In addition, the simulation results show that the proposed method has strong ability to resist the noise.

INFERENCE ON THE SEASONALLY COINTEGRATED MODEL WITH STRUCTURAL CHANGES

  • Song, Dae-Gun;Cho, Sin-Sup
    • Journal of the Korean Statistical Society
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    • v.36 no.4
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    • pp.501-522
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    • 2007
  • We propose an estimation procedure that can be used for detecting structural changes in the seasonal cointegrated vector autoregressive model. The asymptotic properties of the estimates and the test statistics for the parameter change are provided. A simulation example is presented to illustrate this method and its concept.

Effects of Movements in Stock Prices and Real Estate Prices on Money Demand: Cross Country Study (주가 및 부동산가격이 화폐수요에 미치는 부의 효과: 국가 간 비교분석)

  • Chang, Byoung-Ky
    • International Area Studies Review
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    • v.15 no.1
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    • pp.219-240
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    • 2011
  • The main purpose of this study is to analyze the effects of stock price and real estate price on the money demand. We investigated the demand for money for 25 money units of 10 countries. To estimate the money demand functions, Johansen's cointegration and ARDL-bounds test were employed. Additionally, Stock and Watson's DOLS method was applied to estimate long-run cointegration vectors. According to the results of cointegration test, stock price and real estate price are crucial in the long-run equilibrium relationship. There were no cointegration relationships among money demand, real income, interest rate, and exchange rate in 12 money unit models. However, by including stock price and real estate price on the tested models, we could find strong cointegration relationships, using ARDL-bounds test. The results of DOLS confirm that stock price and real estate price are effective factors influencing on money demands. Especially, the coefficient of real estate price is statistically significant in the 19 out of 20 money unit models. However, the direction and magnitude of coefficients of asset prices are different across countries and money units.

Estimation of Seasonal Cointegration under Conditional Heteroskedasticity

  • Seong, Byeongchan
    • Communications for Statistical Applications and Methods
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    • v.22 no.6
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    • pp.615-624
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    • 2015
  • We consider the estimation of seasonal cointegration in the presence of conditional heteroskedasticity (CH) using a feasible generalized least squares method. We capture cointegrating relationships and time-varying volatility for long-run and short-run dynamics in the same model. This procedure can be easily implemented using common methods such as ordinary least squares and generalized least squares. The maximum likelihood (ML) estimation method is computationally difficult and may not be feasible for larger models. The simulation results indicate that the proposed method is superior to the ML method when CH exists. In order to illustrate the proposed method, an empirical example is presented to model a seasonally cointegrated times series under CH.

The Speculative Efficiency of Frozen Shrimp Futures Market (새우 선물시장의 투기 효율성에 관한 연구)

  • Kang, Seok-Kyu
    • The Journal of Fisheries Business Administration
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    • v.38 no.2
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    • pp.63-78
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    • 2007
  • The objective of this study is to examine the speculative efficiency of shrimp futures market. Testing for the speculative efficiency hypothesis is carried out using Johansen's the maximum-likelihood cointegration method and Fama(1984) regressison model. Analysis data are obtained Kansai Commodities Exchange in Osaka and are daily data of frozen shrimp futures and cash prices for all trading days in the time period from September 6, 2002, frozen shrimp futures is introduced, to May 10, 2007. The empirical results are summarized as follows:First, there exists the cointegrating relationship between realized spot India 16/20, Indonesia 16/20, vietnam 16/20 prices and futures prices of the 14 day to maturity. Second, shrimp futures contract prices do not behave as unbiased predictor s of future spot shrimp prices. This indicates that the shrimp futures market is inefficient.

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GMM Estimation for Seasonal Cointegration

  • Park, Suk-Kyung;Cho, Sin-Sup;Seon, Byeong-Chan
    • The Korean Journal of Applied Statistics
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    • v.24 no.2
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    • pp.227-237
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    • 2011
  • This paper considers a generalized method of moments(GMM) estimation for seasonal cointegration as the extension of Kleibergen (1999). We propose two iterative methods for the estimation according to whether parameters in the model are simultaneously estimated or not. It is shown that the GMM estimator coincides in form to a maximum likelihood estimator or a feasible two-step estimator. In addition, we derive its asymptotic distribution that takes the same form as that in Ahn and Reinsel (1994).

The Impact of Trade Openness on Economic Growth in China: An Empirical Analysis

  • Hye, Qazi Muhammad Adnan;Wizarat, Shahida;Lau, Wee-Yeap
    • The Journal of Asian Finance, Economics and Business
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    • v.3 no.3
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    • pp.27-37
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    • 2016
  • This study uses an endogenous economic growth model to determine the long run relationship between trade openness and economic growth in China by using the data 1975-2009.It contributes to the literature by developing trade openness index. An autoregressive distributed lag approach to cointegration and rolling regression method are employed. This study tests the link between trade openness and economic growth in the case of China by using the framework of endogenous economic growth model. This study also employs the rolling window regression method in order to examine the stability of coefficients throughout the sample span. The autoregressive distributed lag (ARDL) cointegration technique and rolling regression method are used. The empirical findings indicate that trade openness (i.e. Both individual trade indicator and composite trade openness index) are positively related to economic growth in the long run and short run. Our results indicate that trade openness as measured by individual trade indicator and composite trade openness index are positively related to economic growth in the long run and short run. However, results from the rolling window suggest that trade openness is negatively linked to economic growth only for a number of years.