• KDI Journal of Economic Policy
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• v.37 no.4
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• pp.1-20
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• 2015

We examine the validity of popular exchange rate models such as the purchasing power parity (PPP) hypothesis and the monetary model for Korean won/US dollar exchange rate. Various specification tests demonstrate that Korean data are more favorable for both models based on time-varying cointegration coefficients as compared to those based on constant cointegration coefficients. When the abilities to predict future exchange rates between those models based on time-varying cointegration coefficients are compared, an in-sample analysis shows that the time-varying PPP (monetary model) has better predictive power over horizons shorter (longer) than one year. Results from an out-of-sample analysis indicate that the time-varying PPP outperforms models based on constant cointegration coefficients when predicting future exchange rate changes in the long run.

• International Area Studies Review
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• v.21 no.1
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• pp.201-219
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• 2017

This paper analyzes the economic effects of the S&T Innovation, R&D, human resources and investment on the economic growth using 18 countries. We have obtained the somewhat mixed results on the existence of unit root roots in variables. While most of Pedroni cointegration tests show that there are no panel cointegration among the variables, Kao cointegration test shows that there is the panel cointegration among the variables such as GDP, human capital, R&D investment and patent. Kao cointegration test result shows that human capital, R&D investment, patent economic growth seem to have the panel cointegration or the long-run relationship among them as a whole. The estimation results of individual OLS and panel estimation show that the human capital, R&D investment and technology innovation or patent had positively significant effects on economic growth or GDP.

• Journal of the Korean Data and Information Science Society
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• v.16 no.3
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• pp.695-703
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• 2005

This paper extends the maximum likelihood seasonal cointegration procedure developed by Johansen and Schaumburg (1999) for daily time series. The finite sample distribution of the associated rank test for dally data is also presented.

• Communications for Statistical Applications and Methods
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• v.16 no.4
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• pp.707-711
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• 2009

We propose new cointegration tests using signs of the regressors as instrumental variable. Our tests have the asymptotic standard normal distribution and are free from the dimension of regressors under the null hypothesis of no cointegration. A Monte-Carlo simulation shows that the proposed tests have a stable size and an improved power. Particulary, the tests have better power for small numbers of observations.

• Communications for Statistical Applications and Methods
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• v.15 no.3
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• pp.411-420
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• 2008

This paper considers a feasible two-step estimator for seasonal cointegration as the extension of $Br{\ddot{u}}ggeman$ and $L{\ddot{u}}tkepohl$ (2005). It is shown that the reducedrank maximum likelihood(ML) estimator for seasonal cointegration can still produce occasional outliers as that for non-seasonal cointegration even though the sizes of them are not extreme as those in non-seasonal cointegration. The ML estimator(MLE) is compared with the two-step estimator in a small Monte Carlo simulation study and we find that the two-step estimator can be an attractive alternative to the MLE, especially, in a small sample.

• International Area Studies Review
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• v.20 no.3
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• pp.3-22
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• 2016

This paper uses Dynamic OLS(DOLS) approach to estimate the long-run energy demand functions. The results are compared with those of standard cointegration approach. Cointegration tests verify that there is a cointegration among energy consumption, real GDP, and energy price in China. Johansen approach and DOLS approach are more appropriate to estimate for the long-run energy demand function than Engle-Granger Cointegration approach. DOLS provided significant negative sign of price while Engle-Granger did not. Based on the DOLS results, the elasticities of real GDP and energy price on energy consumption are 0.83 and -0.45 respectively, and their statistical significances are high.

• 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.

• KDI Journal of Economic Policy
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• v.31 no.2
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• pp.1-13
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• 2009

The monetary model suggests that nominal exchange rates between two countries will be determined by important macroeconomic variables. The existence of a cointegrating relationship among these fundamental variables is the backbone of the monetary model. In a recent paper, Rapach and Wohar (2002, Journal of International Economics) advance the literature by testing for linear cointegration in the monetary model using a century of data to increase power. They find evidence of cointegration in five or six of ten countries. We extend their work to the nonlinear framework by performing threshold cointegration tests that allow for asymmetric adjustments in two regimes. Asymmetric adjustments in exchange rates can occur, for example, if transactions costs are present or if policy makers react asymmetrically to changing fundamentals. Moreover, whereas Rapach and Wohar (2002) found it necessary to exclude the relative output variable in some cases to maintain the validity of their cointegration tests, we can include this variable as a stationary covariate to increase power. Overall, using their same long-span data, we find more support for cointegration in a nonlinear framework.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.8
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• pp.13-19
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• 2021

To provide empirical evidence on the impact of export instability on economic growth in developing countries, this study estimated the neoclassical production function using data of the Jordanian economy for the period 1995-2019. Real exports, real capital, and export instability were the independent variables in the production function. To determine the appropriate methodology for estimating the production function, the study conducted some preliminary tests, including the Augmented-Dickey Fuller (ADF), on the study data. The results of this test indicated that all study variables were stationary at first difference. Therefore, the Johanson cointegration test was applied to determine that there was cointegration between the study variables since the results of the former test indicated that there was one cointegration vector between these variables. The cointegration equation revealed a positive and statistically significant impact of real capital, real exports, and an indicator of export instability on economic growth. The most important policy implications for these results would be reducing the geographical concentration of exports through the expansion of free trade agreements (FTA) to enhance the positive impact of the instability of exports on economic growth. Moreover, the study recommends strengthening export-oriented actions to achieve higher levels of economic growth.

• The Journal of Asian Finance, Economics and Business
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• v.9 no.2
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• pp.141-149
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• 2022

Despite the importance of the insurance business for financial and economic development, few studies have looked at the factors that influence its growth. This research adds to the body of knowledge by empirically examining the impact of numerous factors on the development of the insurance business in 15 Middle East and North African (MENA) countries from 2000 to 2017. The study looks at macroeconomic, demographic, and institutional factors as potential drivers of the insurance industry's growth, with the insurance premium as a percentage of GDP as the dependent variable. All variables are stationary at the first difference, according to the IPS panel unit root test. The Pedroni residual cointegration test, Kao residual cointegration test, and Johansen-Fisher panel cointegration tests are then used to look for long-run associations. The cointegration tests strongly suggest that the insurance premium and the various variables have long-run correlations. Findings from the Fully-Modified OLS imply that GDP per capita, gross capital formation, and the KOF economic globalization index have a positive long-term impact on the insurance business. The insurance business is also driven by combating corruption and the rule of law. The population and regulatory quality, on the other hand, have no significant impact.