• Proceedings of the Korean Operations and Management Science Society Conference
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• 1994.10a
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• pp.99-99
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• 1994

• Proceedings of the Korean Institute of Building Construction Conference
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• 2015.11a
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• pp.192-193
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• 2015

Construction Cycle Trend Survey, which survey total value of orders and realized amounts monthly, is a valuable statistics that used to quick grasp or forecast the trend of domestic construction business. In recent periodical survey quality diagnoses, few professional users named a problem that Construction Cycle Trend Survey could not get together with the current state of the construction industry. This study examined weather Construction Cycle Trend Survey reflects the economic sentiment of construction business or not. Paired t test was performed between Construction Cycle Trend Survey and Construction Business Survey Index (CBSI), and significant differences were verified.

• International Area Studies Review
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• v.21 no.4
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• pp.159-172
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• 2017

In a typical trend-cycle decomposition of GDP, the trend component is usually assumed to follow a random walk process. This paper considers an ARIMA trend and assesses the validity of the ARIMA trend model. I construct univariate and bivariate unobserved-components(UC) models, allowing the ARIMA trend. Estimation results using U.S. data are favorable to the ARIMA trend models. I, also, compare the forecasting performance of the UC models. Dynamic pseudo-out-of-sample forecasting exercises are implemented with recursive estimations. I find that the bivariate model outperforms the univariate model, the smoothed estimates of trend and cycle components deliver smaller forecasting errors compared to the filtered estimates, and, most importantly, allowing for the ARIMA trend can lead to statistically significant gains in forecast accuracy, providing support for the ARIMA trend model. It is worthy of notice that trend shocks play the main source of the output fluctuation if the ARIMA trend is allowed in the UC model.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1993.04a
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• pp.437-437
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• 1993

• KDI Journal of Economic Policy
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• v.31 no.2
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• pp.47-85
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• 2009

With a relatively simple quantitative method, this study comprehensively analyzes the characteristics related to business cycles represented by macroeconomic variables of Korea since 1970. This empirical analysis deals with roughly following three topics: How to identify cyclical component with respect to trend; with what characteristics and how the economic variables of each sector move with in the phases of business cycle, and; whether there are signs of a structural change in the phases of business cycle. Section 2 discusses how to identify trends and cycle components, the basis assumption for the analysis of business cycle. Like the Korean economy, where a relatively high growth rate has been maintained, it is appropriate to determine its economic recession based on the fall in the growth trend, not in the absolute level of real output. And, it is necessary to apply the concept of growth cycle against a traditional concept of business cycle. Accordingly the setting of growth trend is of preliminary importance in identifying cyclical fluctuations. The analysis of Korea's GDP data since 1970, the decomposition of trends and cycles through the Band-pass filter is found to appropriately identify the actual phases of busyness cycle. Section 3 analyzes what particular relationship various economic variables have with output fluctuations during the phases of economic cycle, using the corss-correlation coefficients and prediction contribution. Section 4 monitors the stability of the phases of Korea's business cycle and quantitatively verifies whether there is a structural break, and then reviews the characteristics of variations in each sector. And, stylized facts observed through these studies are summarized in the conclusion. The macroeconomic stability of Korea, in particular, is found to continue to improve since 1970, except for the financial crisis period. Not only that, it is found that its volatility of economic growth rate as well as inflation have been reduced gradually. Meanwhile, until recently since 2000, the volatility in domestic demand has remained stable, while that in exports and imports has been increased slightly. But, in an over all perspective, Korea's business cycle variation is on the decline due to shorter response period to shocks and the formation of complementary relationship among economic sectors.

• The Korean Journal of Applied Statistics
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• v.27 no.3
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• pp.431-444
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• 2014

We introduce the empirical model decomposition (EMD) to decompose a time series into a set of components in the time-frequency domain. By using EMD, we also extract cycle and trend components from major Korean macroeconomic indices and forecast the indices with the components combined. In order to evaluate their efficiencies, we investigate volatility, autocorrelation, persistence, Granger causality, nonstationarity, and forecasting performance. They are then compared with those by Hodrick-Prescott filter which is the most commonly used method.

• Wind and Structures
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• v.38 no.5
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• pp.381-398
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• 2024

This study presents a mode analysis of 3D turbulent velocity data around a square-section building model to identify the dynamic system for Kármán-type vortex shedding. Proper orthogonal decomposition (POD) was first performed to extract the significant 3D modes. Magnitude-squared coherence was then applied to detect the phase consistency between the modes, which were roughly divided into three groups. Group 1 (modes 1-4) depicted the main vortex shedding on the wake of the building, with mode 2 being controlled by the inflow fluctuation. Group 2 exhibited complex wake vortexes and single-sided vortex phenomena, while Group 3 exhibited more complicated phenomena, including flow separation. Subsequently, a third-order polynomial regression model was used to fit the dynamics system of modes 1, 3, and 4, which revealed average trend of the state trajectory. The two limit cycles of the regression model depicted the two rotation directions of Kármán-type vortex. Furthermore, two characteristic periods were identified from the trajectory generated by the regression model, which indicates fast and slow motions of the wake vortex. This study provides valuable insights into 3D mode morphology and dynamics of Kármán-type vortex shedding that helps to improve design and efficiency of structures in turbulent flow.

• The Journal of the Korea Contents Association
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• v.17 no.9
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• pp.300-309
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• 2017

This paper examines the cyclical fluctuation of 'construction orders' and 'construction investment' using HP filter, Bandpass filter and Beveridge-Nelson decomposition methods. The main results are as follows. As a result of the analysis of the cyclical fluctuation of construction orders, it was analyzed that there were about 7 cyclical fluctuations from 1976 to the first quarter of 2017. Construction orders for cyclical fluctuations peaked in the second quarter of 2015 and turned to a downward trend. On the other hand, construction investment has experienced about 6 cycles of fluctuations during the same period, and it has been rising continuously since the bottom of 3Q12. This is consistent with the general theory that construction orders precede construction investments. In addition, the comparison of the construction orders, construction investment, and GDP amplitude shows that the GDP amplitude is the smallest and stable, and the construction orders have the greatest variation in amplitude. Therefore, construction orders should be adjusted by government policy depending on economic fluctuations.

• KDI Journal of Economic Policy
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• v.34 no.4
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• pp.117-156
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• 2012

This paper decomposes and estimates trend/cyclical components of some key macro variables-GDP, inflation, and interest rate, using a simple DSGE model along with flexible trend specification. The extracted cyclical components of output and interest rate are similar to HP-filtered counterparts, despite some differences in persistence and volatility, while inflation resembles that from BK filtering. This implies that the usual practice of applying a single filtering method to the data of interest may be problematic. When the baseline model is extended to incorporate consumption habit and price indexation, habit turns out to be important in explaining the persistence of business cycles. Comparison of several alternative models shows that the usual practice of estimation of DSGE model using filtered data leads to biased results. Finally, various sensitivity analyses illustrate that (1) allowing for correlation between structural cyclical shocks and trend shocks and (2) including irregular components (in inflation rate) may deliver interesting/important implication for gap estimates.