本文關(guān)鍵詞： 混頻數(shù)據(jù) 非線性格蘭杰非因果性檢驗(yàn) 向量自回歸模型 典型相關(guān)分析　出處：《數(shù)量經(jīng)濟(jì)技術(shù)經(jīng)濟(jì)研究》2017年05期 　論文類型：期刊論文

【摘要】：研究目標(biāo):提出一種針對混頻數(shù)據(jù)非線性格蘭杰因果關(guān)系檢驗(yàn)的方法。研究方法:在混頻向量自回歸模型(MFVAR)的基礎(chǔ)上提出構(gòu)造Wald統(tǒng)計(jì)量,通過模擬實(shí)驗(yàn)和實(shí)證研究考察統(tǒng)計(jì)量的性質(zhì)。研究發(fā)現(xiàn):模擬實(shí)驗(yàn)結(jié)果表明該檢驗(yàn)相對于其他混頻檢驗(yàn)和低頻檢驗(yàn)具有更優(yōu)的性質(zhì),并且對檢驗(yàn)式誤設(shè)具有穩(wěn)健性。進(jìn)一步針對中國經(jīng)濟(jì)增長與消費(fèi)者信心因果關(guān)系的實(shí)證研究證明,混頻檢驗(yàn)與低頻檢驗(yàn)得出的結(jié)論有很大差異,混頻檢驗(yàn)得出的結(jié)論更符合經(jīng)濟(jì)理論。研究創(chuàng)新:利用自助法修正統(tǒng)計(jì)量在有限樣本下產(chǎn)生的水平扭曲,利用典型相關(guān)分析實(shí)現(xiàn)了數(shù)據(jù)降維。研究價(jià)值:在檢驗(yàn)不同頻率變量之間的非線性格蘭杰因果關(guān)系時(shí)避免了信息損失和虛增。
[Abstract]:Research objective: to propose a method to test the nonlinear Granger causality of mixing data. Research methods: on the basis of mixing vector autoregressive model (MFVARA), we propose the construction of Wald statistics. The properties of statistics are investigated through simulation experiments and empirical studies. The results of simulation experiments show that this test has better properties than other mixing tests and low frequency tests. Furthermore, the empirical study on the causality between economic growth and consumer confidence in China proves that the conclusions of mixed frequency test and low frequency test are very different. The results of mixing test are more in line with economic theory. Research innovation: using self-help method to correct the horizontal distortion of statistics in a limited sample. Data dimension reduction is realized by canonical correlation analysis. Research value: information loss and false increase are avoided in testing nonlinear Granger causality between different frequency variables.
【作者單位】： 天津財(cái)經(jīng)大學(xué)統(tǒng)計(jì)系;天津財(cái)經(jīng)大學(xué)金融系;
【分類號(hào)】：F124.1;F126.1;F224.0

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本文編號(hào)：1517166