本文關(guān)鍵詞：空間非平穩(wěn)數(shù)據(jù)檢驗(yàn)及空間誤差修正模型的貝葉斯估計(jì)　出處：《新疆大學(xué)》2017年碩士論文　論文類型：學(xué)位論文

  更多相關(guān)文章： 空間非平穩(wěn) 兩步LM檢驗(yàn) 空間誤差修正模型 貝葉斯估計(jì)

【摘要】：隨著計(jì)量經(jīng)濟(jì)學(xué)的發(fā)展,特別是時(shí)間序列的單位根過程和協(xié)整理論的發(fā)展,給主流計(jì)量經(jīng)濟(jì)學(xué)的發(fā)展帶來一場(chǎng)革命,時(shí)間序列分析已經(jīng)建立了相對(duì)完善的理論分析框架,并在眾多經(jīng)濟(jì)領(lǐng)域取得很好的應(yīng)用.空間計(jì)量經(jīng)濟(jì)學(xué)作為計(jì)量經(jīng)濟(jì)學(xué)的一個(gè)分支,在處理橫截面數(shù)據(jù)和面板數(shù)據(jù)的空間相互作用和空間結(jié)構(gòu)變化方面發(fā)揮獨(dú)特優(yōu)勢(shì),并發(fā)展出了空間誤差模型、空間滯后模型和地理加權(quán)回歸模型等經(jīng)典模型來處理空間自相關(guān)性和空間異質(zhì)性.空間計(jì)量與地理信息系統(tǒng)(GIS)的結(jié)合廣泛應(yīng)用于房地產(chǎn)經(jīng)濟(jì)、環(huán)境和資源經(jīng)濟(jì)等領(lǐng)域.但是空間非平穩(wěn)計(jì)量經(jīng)濟(jì)學(xué)在空間計(jì)量經(jīng)濟(jì)學(xué)中的發(fā)展卻不夠完善。本文首先介紹時(shí)間序列的單位根和協(xié)整理論,然后討論關(guān)于非平穩(wěn)空間數(shù)據(jù)的研究,包括空間單位根和協(xié)整理論的定義及其檢驗(yàn)方法;空間單位根過程的數(shù)據(jù)生成方法及檢驗(yàn),以及空間誤差修正模型的不同形式和參數(shù)估計(jì);類似于時(shí)間序列的DF檢驗(yàn),空間非平穩(wěn)檢驗(yàn)的臨界值也被提出;Moran’s I是研究一個(gè)變量的集聚效應(yīng),本文也介紹關(guān)于兩個(gè)空間過程的相關(guān)性的研究.空間面板數(shù)據(jù)的單位根的研究已經(jīng)有成熟的理論,但空間截面數(shù)據(jù)的平穩(wěn)性研究仍需完善,所以本文的研究都是基于空間截面數(shù)據(jù)。本文創(chuàng)新在于用時(shí)間序列的方法檢驗(yàn)了空間非平穩(wěn)檢驗(yàn)臨界值的合理性,然后建議用兩步拉格朗日檢驗(yàn)法檢驗(yàn)空間數(shù)據(jù)的平穩(wěn)性;考慮到數(shù)據(jù)生成過程會(huì)對(duì)檢驗(yàn)結(jié)果造成影響,本文對(duì)兩類造成非平穩(wěn)的空間過程即含趨勢(shì)項(xiàng)的平穩(wěn)過程和含漂移項(xiàng)的隨機(jī)游走進(jìn)行檢驗(yàn)區(qū)分,通過模擬實(shí)驗(yàn)可以區(qū)分上述兩種不同非平穩(wěn)過程;鑒于工具變量法估計(jì)空間誤差修正模型時(shí)在參數(shù)邊界上誤差較大,本文使用貝葉斯方法對(duì)空間誤差修正模型進(jìn)行估計(jì),結(jié)果顯示貝葉斯方法整體上優(yōu)于工具變量法,即使在參數(shù)邊界上估計(jì)結(jié)果也比較好。
[Abstract]:With the development of econometrics, especially time series unit root process and the development of the theory, for the development of the mainstream of econometrics has brought a revolution to the time series analysis has established a relatively complete theoretical framework for analysis, and achieved very good application in many economic fields. Spatial econometrics is a branch of econometrics the advantages of interaction in the treatment of cross section and panel data of space and spatial structure change, and to develop the spatial lag model and spatial error model, geographically weighted regression model and classical model to deal with the spatial autocorrelation and spatial heterogeneity. The spatial econometric and geographic information system (GIS) combined with widely used in the real estate economy, environment and resources, economic and other fields. But the spatial non-stationary econometrics in spatial econometrics in development But it is not perfect. This paper first introduces the time series unit root and cointegration theory, and then discuss the research on non-stationary spatial data, including spatial definition of unit root and cointegration theory and test method; spatial data generation method of unit root process and inspection, and different forms of space and parameter error correction model estimation; DF test is similar to the time series the non critical value of stable test are also presented; "Moran s I is the agglomeration of a variable, this paper also introduces the research on the correlation between the two spatial process. Research on spatial panel data unit root has mature theory, but the stability of the space research section data still needs to be improved therefore, this study is based on cross-sectional data space. The innovation of this paper lies in using time series method to test the rationality of non smooth space check critical value, and then proposed the stationarity test of spatial data with the two step Lagrange test method; taking into account the data generation process will affect the test results, the paper on the two kinds of stationary process caused by non spatial smooth process including the trend and with random walk test to distinguish, through the simulation experiment can distinguish these two different kinds of non stationary process; given the estimated error correction model in the parameter space boundary error of instrumental variable method, this paper uses Bayesian methods to estimate the spatial error correction model, results show that Bayesian method is better than the method of instrumental variables, even if the bounds on the parameters estimation results are relatively good.
【學(xué)位授予單位】：新疆大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2017
【分類號(hào)】：O212.8

【相似文獻(xiàn)】

相關(guān)期刊論文 前10條

1 劉廣迎;李翔;;基于協(xié)整和誤差修正模型的電力需求分析[J];煤炭技術(shù);2009年11期

2 白雪梅,趙松山;協(xié)整及誤差修正模型[J];數(shù)量經(jīng)濟(jì)技術(shù)經(jīng)濟(jì)研究;1998年08期

3 劉學(xué)武,劉安;單根、共積與誤差修正模型——理論、方法和應(yīng)用[J];預(yù)測(cè);2000年03期

4 吳容容;;誤差修正模型在匯率與貿(mào)易傳導(dǎo)機(jī)制上的實(shí)證運(yùn)用[J];西南科技大學(xué)學(xué)報(bào)(哲學(xué)社會(huì)科學(xué)版);2011年06期

5 梁海龍;王新娟;;基于誤差修正模型的我國股市聯(lián)動(dòng)性分析[J];中國證券期貨;2012年07期

6 楊世東;黃萍;;協(xié)整分析與誤差修正模型——安徽省城鎮(zhèn)居民人均年消費(fèi)與收入的實(shí)證研究[J];市場(chǎng)周刊.理論研究;2006年02期

7 吳爽;;我國農(nóng)村消費(fèi)和收入的誤差修正模型分析[J];江西農(nóng)業(yè)學(xué)報(bào);2006年06期

8 李中才;王廣成;婁美珍;;中國生態(tài)足跡與經(jīng)濟(jì)增長的協(xié)整、誤差修正模型及預(yù)測(cè)[J];系統(tǒng)工程;2007年08期

9 羅漢武;李f ;;社會(huì)用電量與經(jīng)濟(jì)增長的協(xié)整檢驗(yàn)和誤差修正[J];統(tǒng)計(jì)與決策;2009年17期

10 劉慶廣;;江蘇經(jīng)濟(jì)增長與港口物流發(fā)展的關(guān)系——基于誤差修正模型的實(shí)證分析[J];價(jià)值工程;2012年22期

相關(guān)會(huì)議論文 前3條

1 施滸立;趙彥;;誤差設(shè)計(jì)新理念與方法[A];中國電子學(xué)會(huì)電子機(jī)械工程分會(huì)2007年機(jī)械電子學(xué)學(xué)術(shù)會(huì)議論文集[C];2007年

2 崔建華;牛e，

本文編號(hào)：1343064