• 제목/요약/키워드: Seasonal adjustment

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A New Estimator for Seasonal Autoregressive Process

  • So, Beong-Soo
    • Journal of the Korean Statistical Society
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    • 제30권1호
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    • pp.31-39
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    • 2001
  • For estimating parameters of possibly nonlinear and/or non-stationary seasonal autoregressive(AR) processes, we introduce a new instrumental variable method which use the direction vector of the regressors in the same period as an instrument. On the basis of the new estimator, we propose new seasonal random walk tests whose limiting null distributions are standard normal regardless of the period of seasonality and types of mean adjustments. Monte-Carlo simulation shows that he powers of he proposed tests are better than those of the tests based on ordinary least squares estimator(OLSE).

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Seasonal Adjustment on Chain-Linking (연쇄가중법 도입에 따른 계절변동조정)

  • Jeon, Gyeong-Bae
    • Communications for Statistical Applications and Methods
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    • 제16권1호
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    • pp.41-50
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    • 2009
  • Chain-linking is a method for aggregating volume measures which would improve the quality of estimates of economic growth over the present fixed base in Korea. There is a risk that choice of chain-linking techniques such annual overlap, one-quarter overlap or over-the-year overlap may create an artificial seasonality to the volume series. The empirical results on Korean GDP suggest that the use of the annual overlap is recommended. And conducting seasonal adjustment after chain-linking to produce the chain-linked seasonally adjusted GDP is more appropriated in Korea.

New seasonal moving average filters for X-13-ARIMA (X-13-ARIMA에서의 새로운 계절이동평균필터 개발 연구)

  • Shim, Kyuho;Kang, Gunseog
    • The Korean Journal of Applied Statistics
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    • 제29권1호
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    • pp.231-242
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    • 2016
  • X-13-ARIMA (a popular time series analysis software) provides $3{\times}3$, $3{\times}5$, $3{\times}9$, $3{\times}15$ moving average filters for seasonal adjustment. However, there has been questions on their performance and the need for new filters is a constant topic due to Korean economic time series often containing higher irregularity and more various seasonality than other countries. In this study, two newly developed seasonal moving average filters, $3{\times}7$ and $3{\times}11$, are introduced. New filters were implemented in X-13-ARIMA and applied to 15 economic time series to demonstrate their suitability and reliability. The result shows that some series are more stable when using new seasonal moving average filters. More accurate time series analyses would be possible if newly proposed filters are used together with existing filters.

A Comparison of Seasonal Adjustment Methods: An Application of X-13A-S Program on X-12 Filter and SEATS (X-13A-S 프로그램을 이용한 계절조정방법 분석 - X-12 필터와 SEATS 방법의 비교 -)

  • Lee, Hahn-Shik
    • The Korean Journal of Applied Statistics
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    • 제23권6호
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    • pp.997-1021
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    • 2010
  • This paper compares the two most widely used seasonal adjustment methods: the X-12-ARIMA and TRAMO-SEATS procedures. The basic features of these methods are discussed and compared in both their theoretical and empirical aspects. In doing so, the X-13A-S program is used to reevaluate their applicability to Korean macroeconomic data by considering possible structural breaks in the series. The finding is that both methods provide very reliable and stable estimates of seasonal factors and seasonally adjusted data. As for the empirical comparisons, TRAMO-SEATS appears to outperform X-12-ARIMA, although the results are somewhat mixed depending on the comparison criteria used and on the series under analysis. In particular, the performance of TRAMO-SEATS turns out to compare more favorably when seasonal adjustment is carried out to each sub-samples (by taking possible structural breaks into account) than when the whole sample period is used. The result suggests that as the model-based TRAMO-SEATS has a considerable theoretical appeal, some features of TRAMO-SEATS should further be incorporated into X-12-ARIMA until a standard and integrated procedure is reached by combining the theoretical coherence of TRAMO-SEATS and the empirical usefulness of X-12-ARIMA.

Development of a Daily Electricity Business Index by using the Electricity Daily Data of the Manufacturing Sector (제조업 일별 전력 사용량을 활용한 일일전력경기지수(DEBI) 개발)

  • Oh, Seunghwan;Park, Sungkeun
    • Journal of the Korean Operations Research and Management Science Society
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    • 제41권3호
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    • pp.59-74
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    • 2016
  • Electricity sales are directly measured from individual consumers, which could minimize the time gap between data collection and public announcement. Furthermore, industrial electricity sales are highly linked with production and output. Therefore, industrial electricity consumption can be used to track production and output in real time. By using the high-frequency data of industrial electricity sales, this study develops the daily electricity business index (DEBI) to capture the daily economic status. The steps used to formulate DEBI are as follows: (1)selection of the explanatory variables and period, (2) amendment of the seasonal adjustment to eliminate daily temperature and effective day effects, (3) estimation of the weighted value via variables by using PCA, (4) calculation of DEBI and commencement of validation tests. Our empirical analysis and the Hodrick-Prescott filter analysis show that DEBI is highly related to existing economic indices.

Assessment of Degradation Rate Coefficient and Temperature Correction Factor by Seasonal Variation of Concentration and Temperature in Livestock Wastewater Treatment in Field Scale (현장수준의 축산폐수처리에 있어서 계절별 농도 및 온도변화에 따른 분해반응계수 및 온도보정계수의 산정)

  • 박석환
    • Journal of Environmental Health Sciences
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    • 제22권2호
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    • pp.90-95
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    • 1996
  • This study was performed to calculate the degration rate coefficient, operating parameters to meet the effluent standards, and the temperature adjustment coefficients to each parameter of pollution by seasonal variation of concentration and temperature of influent in livestock wastewater treatment by sequencing batch reactor process in field scale. The followings are the conclusions that were derived from this study. 1. In the field, temperature of livestock wastewater in reactor was 20.3$\circ$C in summer and 6.0$\circ$C in winter. The ratio of BOD:TKN: T-P in influent was 100:80:7. BOD loadings in winter and spring were 0.26 and 0.43 kg $BOD/m^3$ day, respectively. Those in summer and fall were 0.25 and 0.13 kg $BOD/m^3$ day, respectively. 2. The degradation rate coefficient for TKN was larger in summer and fall in which temperature was high than that in which temperature was high than that in winter and spring in which concentration was high. On the contrary, the phosphorus uptake rate was larger in winter and spring than that in summer and fall. 3. The hydraulic retention time in winter and spring was longer than that in summer and fall. Especially, in order to meet the standard for TKN of 120 mg/l in winter in which temperature of wastewater was 6.0$\circ$C, as the MLSS concentration was increased from 4, 000 to 7, 000 mg/l, the hydraulic retention time was increased from 212 to 121 hours. But, in order to shorten that less than 121 hours for the economical wastewater treatment, countermeasure to increase temperature of wastewater in the reactor should be considered. 4. the temperature adjustment coefficients for BOD, $COD_{Mn}$, TKN and T-P were 1.0241, 1.0225, 1.0541 and 1.0495, respectively. Namely, the treatment of TKN was most sensitively affected by temperature. For the purpose of the effective removal of nitrogen and phosphorus which are sensitive to temperature, it is necessary to keep the temperature of livestock wastewater more than 20$\circ$C which is the temperature of it in summer.

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Functional Forecasting of Seasonality (계절변동의 함수적 예측)

  • Lee, Geung-Hee
    • The Korean Journal of Applied Statistics
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    • 제28권5호
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    • pp.885-893
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    • 2015
  • It is important to improve the forecasting accuracy of one-year-ahead seasonal factors in order to produce seasonally adjusted series of the following year. In this paper, seasonal factors of 8 monthly Korean economic time series are examined and forecast based on the functional principal component regression. One-year-ahead forecasts of seasonal factors from the functional principal component regression are compared with other forecasting methods based on mean absolute error (MAE) and mean absolute percentage error (MAPE). Forecasting seasonal factors via the functional principal component regression performs better than other comparable methods.

Study for the Changes of Annual and Seasonal Mean Temperature Using Adjusted Temperature Data in the Republic of Korea (고품질의 기온자료를 이용한 연.계절평균기온의 변화에 관한 연구)

  • Park, Chang-Yong;Choi, Young-Eun
    • Journal of the Korean Geographical Society
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    • 제46권1호
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    • pp.20-35
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    • 2011
  • This study suggested the systematic steps for quality control, construction of the climatological reference series and homogeneity test and adjustment of temperature series in the Republic of Korea. It also attempted to evaluate more accurate magnitude of change using adjusted temperature data. All erroneous values produced by quality control were detected by internal inconsistency check. The method selected for homogeneity test in this study well defined fairly correct signals of station relocations. Therefore, this method might be regarded as the appropriate one to test homogeneity of temperature series of the Republic of Korea. The increase of temperature of the Republic of Korea after the adjustment were bigger than before the adjustment of annual and seasonal mean temperature. Adjusted temperature data produced by these steps will enable to evaluate more accurate characteristics and magnitude of climate change.

Development of a Method to Estimate the Seasonal Heating Load for Plastic Greenhouses (플라스틱 온실의 기간난방부하 산정 방법 개발)

  • Nam, Sang Woon;Shin, Hyun Ho
    • Journal of The Korean Society of Agricultural Engineers
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    • 제57권5호
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    • pp.37-42
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    • 2015
  • In order to provide fundamental data for the creation of environmental design criteria for horticultural facilities, we developed a method to easily calculate the seasonal heating load applying heating degree-hour while taking into account heating load reductions due to solar radiation in the daytime, and reviewed through greenhouse heating experiments. Heating experiments and measuring meteorological environments were carried out in three greenhouses located at Buyeo, Cheonan, and Buan, and we derived reduction factors of seasonal heating load according to hours of sunshine. Daily mean hours of sunshine during the experiment period in each of the greenhouse was 4.0 to 8.3 hours, and the reduction factor of seasonal heating load was 0.64 to 0.85, has been shown to decrease linearly with the increase in hours of sunshine. A method to estimate the seasonal heating load for greenhouses was developed using the reduction factor of seasonal heating load derived from the greenhouse heating experiment, including the adjustment factor of seasonal heating load according to hours of sunshine. The developed method was validated through heating experiments in a greenhouse located at Cheonan. Greenhouse seasonal heating loads calculated by the method developed in this study were analyzed to show the estimate error of 1.2 to 5.0%. It showed that the accuracy increased 2.3 times more than when using the heating load reduction factor of 0.75 applied uniformly in previous studies. Thus, the calculation method of seasonal heating load for greenhouses considering hours of sunshine developed in this study could be utilized for energy estimation, management planning, and economic evaluation in greenhouse design.

Smooth Tests for Seasonality (평활 계절성 검정)

  • Lee, Geung-Hee
    • The Korean Journal of Applied Statistics
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    • 제24권1호
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    • pp.45-59
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    • 2011
  • When using X-12-ARIMA for seasonal adjustment, we usually check whether the series has stable seasonality or not via D8 F-tests, Kruskal-Wallis test, and the spectral diagnostics. In this paper, we develop several smooth tests for seasonality based on a Fourier series to improve the spectral diagnostics of X-12-ARIMA. A simulation study is conducted to compare five smooth tests for seasonality and X-12-ARIMA's D8 F-test an Kruskal-Wallis test. The simulation study shows that smooth tests for seasonality performed well compared with D8 F-tests and a Kruskal-Wallis test.