1998 Fiscal Year Final Research Report Summary
Economic Time Series and Seasonal Adjustment Methods
| Project/Area Number |
09630024
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| Research Category |
Grant-in-Aid for Scientific Research (C)
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| Allocation Type | Single-year Grants |
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| Section | 一般 |
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| Research Field |
Economic statistics
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| Research Institution | The University of Tokyo |
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Principal Investigator |
KUNITOMO Naoto Faculty of Economics, The University of Tokyo, Professor., 大学院・経済学研究科, 教授 (10153313)
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| Co-Investigator(Kenkyū-buntansha) |
SATO Seisho Institute of Statistical Mathematics, Research Associate., 統計数理研究所, 助手 (60280525)
YAJIMA Yoshihiro Faculty of Economics, The University of Tokyo, Professor., 大学院・経済学研究科, 教授 (70134814)
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| Project Period (FY) |
1997 – 1998
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| Keywords | Economic Time Series / Seasonal Adjustment / X-12-ARIMA / DECOMP / Spectrul Analysis / Missing Observations |
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| Research Abstract |
The main purpose of this project was to re-examine the existing statistical methods often used in making the published economic time series data from the central and local governments in Japan. In particular we have investigated the X-12-ARIMA method recently developed by the U.S.Census office and the DECOMP method developed by Professor Kitagawa of the Institute of Statistical Mathematics.
First we have inverstigated the major improvements in the X-12-ARIMA method, which is a revised version of the Census X-11 method. Since the X-11 method has been commonly used among Japanese governrment officials, the meaning of improvements have been the central issues in our study. We found that we can often get stable time series data sets by using the X-12-ARIMA methods, but also found that it really depends on the selection of the seasonal ARIMA models used in the program. Another issue has been whether we should use the trading day adjustments and the Leap year adjustments in order to make the
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official time series. Since the time seresi cycles behind the trading day effects and the Leap year effects are not seasonal (i.e. 12 months cycles), it has been still controversial if we use these options in the X-12-ARIMA program. We also have investigated the spectral properties of the residuals from the X-12-ARIMA program and the DECOMP program. We found that the estimated spectrum from the X-12-ARIiMA residuals often are smooth while the estimated spectrum from the DECOMP residuals have sometimes dips in the seasonal cycles. We have tried to investigated if this phenomenon is the result of the optimal properties of the DECOMP program in the sense of MSE.This problem was pointed out by the classical study on the seasonal adjustment methods by Grether and Nerlove and we have done some Simulation studies. However, we could not have reach a firm conclusion on this issue. Given our investigations, we have an impression that we need more study on these two seasonal adjustment programs from the theoretical side as well as the practical side in the Japanese governments.
In conclusion, we have acomplished the most important objectives of this project. Three members participated in this project has written some papers and also stimulated a large number of researchers in the related fields and some statisticians in the Japanese governments We thank The Ministry of Education, Science and Culture for giving the generous support to research project. Less
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