【摘要】：從改革開放到現(xiàn)在,我國(guó)的年度數(shù)據(jù)只有30多個(gè)。對(duì)于很多經(jīng)濟(jì)研究來(lái)說(shuō)這樣的數(shù)據(jù)量是遠(yuǎn)遠(yuǎn)不夠的,所以對(duì)于季度、月度等子年度時(shí)間序列的研究顯得特別重要。子年度數(shù)據(jù)所包含的信息會(huì)受到季節(jié)性的影響,很多經(jīng)濟(jì)時(shí)間序列之間的動(dòng)態(tài)關(guān)系由于受到季節(jié)因素的干擾變得模糊不清,如果存在很強(qiáng)的季節(jié)影響,時(shí)間序列的真實(shí)關(guān)系可能會(huì)被掩蓋,經(jīng)季節(jié)調(diào)整的數(shù)據(jù)可以消除季節(jié)性因素的影響,反映經(jīng)濟(jì)序列的真實(shí)情況,所以對(duì)于子年度數(shù)據(jù)季節(jié)調(diào)整方法的研究有重要的理論意義與應(yīng)用價(jià)值。文章首先介紹了對(duì)CPI進(jìn)行季節(jié)調(diào)整的背景及意義,并從國(guó)內(nèi)外兩個(gè)角度分別詳細(xì)列舉了前人對(duì)季節(jié)調(diào)整的研究情況。在總結(jié)國(guó)內(nèi)外學(xué)者對(duì)季節(jié)調(diào)整研究?jī)?nèi)容的基礎(chǔ)上,提出CPI存在季節(jié)性的問(wèn)題,并使用X-13A-S模型對(duì)CPI進(jìn)行季節(jié)調(diào)整,此模型是美國(guó)普查局正在研究并將進(jìn)行實(shí)施的最新成果。雖然對(duì)季節(jié)調(diào)整的文獻(xiàn)數(shù)量非常多,但是具體到最新的X-13A-S模型,前人的研究并不充分,需要后人進(jìn)行更詳細(xì)的補(bǔ)充。由于X-13A-S包括X-12-ARIMA模型和TRAMO-SEATS模型的功能,所以理論介紹包含對(duì)X-12-ARIMA模型和TRAMO-SEATS模型的介紹以及X-13A-S對(duì)他們的繼承和發(fā)展。在理論介紹的基礎(chǔ)上文章將X-13A-S模型應(yīng)用于CPI的季節(jié)調(diào)整,并將春節(jié)因素引入其中。在得到季節(jié)調(diào)整模型后,文章使用譜圖對(duì)其調(diào)整效果進(jìn)行檢測(cè)。從得到的圖形中,可以看出經(jīng)過(guò)季節(jié)調(diào)整后的序列已經(jīng)不再包含季節(jié)性和交易日效應(yīng),說(shuō)明模型的調(diào)整效果很好。當(dāng)然,采用X-13A-S模型進(jìn)行季節(jié)調(diào)整的實(shí)證過(guò)程并不是沒(méi)有任何瑕疵的,之后文章指出了在進(jìn)行季節(jié)調(diào)整時(shí)存在的缺陷,以期以后的研究者可以加以改進(jìn)。文章的最后對(duì)我國(guó)的季節(jié)調(diào)整給出了幾點(diǎn)展望,也指出了未來(lái)一段時(shí)期內(nèi)我國(guó)季節(jié)調(diào)整的目標(biāo)和方向。文章的創(chuàng)新之處主要體現(xiàn)在兩個(gè)方面：第一,首次使用Win Genhol軟件將春節(jié)變量引入模型,為以后對(duì)移動(dòng)假日的引入提供了參考,使得移動(dòng)假日的調(diào)整變得更容易；第二,文章首次對(duì)X-13A-S進(jìn)行了詳細(xì)系統(tǒng)的描述,然后將其應(yīng)用于對(duì)CPI的季節(jié)調(diào)整,并且得到了很好的調(diào)整效果。
[Abstract]:Since the reform and opening up to the present, China's annual data only more than 30. This amount of data is far from enough for many economic studies, so the study of the monthly equivalent annual time series is particularly important for the quarter. The information contained in the sub-annual data is affected by seasonality, and the dynamic relationship between many economic time series is blurred by the interference of seasonal factors, if there is a strong seasonal effect, The true relationship of the time series may be masked. Seasonally adjusted data can eliminate the effects of seasonal factors and reflect the true state of the economic series. Therefore, the study of seasonal adjustment method of sub-annual data has important theoretical significance and application value. This paper first introduces the background and significance of seasonal adjustment of CPI, and enumerates in detail the previous researches on seasonal adjustment from two angles at home and abroad. On the basis of summarizing the domestic and foreign scholars' research on seasonal adjustment, this paper puts forward that CPI has seasonal problems, and uses X-13A-S model to adjust CPI seasonally. This model is the latest achievement that the US Census Bureau is studying and will implement. Although the number of seasonally adjusted literature is very large, but to the latest X-13A-S model, previous studies are not sufficient, and need to be supplemented in more detail. Because X-13A-S includes the functions of X-12-ARIMA model and TRAMO-SEATS model, the theoretical introduction includes the introduction of X-12-ARIMA model and TRAMO-SEATS model, as well as the inheritance and development of X-13A-S to them. Based on the theoretical introduction, the paper applies the X-13A-S model to the seasonal adjustment of CPI, and introduces the Spring Festival factors into it. After getting the seasonal adjustment model, the adjustment effect is detected by spectrum diagram. From the figure obtained we can see that the seasonally adjusted series no longer contain seasonal and trading day effects which shows that the adjustment effect of the model is very good. Of course, the empirical process of seasonal adjustment using X-13A-S model is not without any defects, and then the paper points out the defects in the process of seasonal adjustment, so that the future researchers can improve it. At the end of this paper, some prospects of seasonal adjustment in China are given, and the aim and direction of seasonal adjustment in the future are also pointed out. The innovation of this paper is mainly reflected in two aspects: first, the introduction of Spring Festival variables into the model by using Win Genhol software for the first time, which provides a reference for the introduction of mobile holidays in the future and makes the adjustment of mobile holidays easier; second, In this paper, X-13A-S is described in detail for the first time, then it is applied to the seasonal adjustment of CPI, and a good adjustment effect is obtained.
【學(xué)位授予單位】：天津財(cái)經(jīng)大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2014
【分類號(hào)】：F726;F224

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