我國經(jīng)濟(jì)增長率動(dòng)態(tài)波動(dòng)機(jī)制研究
發(fā)布時(shí)間：2018-07-23 20:08
【摘要】：經(jīng)濟(jì)增長率的動(dòng)態(tài)波動(dòng)機(jī)制是宏觀經(jīng)濟(jì)學(xué)中的熱議話題。許多學(xué)者都對(duì)這一問題進(jìn)行了詳細(xì)探究。早期的研究通過使用自回歸序列和協(xié)整檢驗(yàn)來刻畫經(jīng)濟(jì)增長率的變化特征。然而，隨著經(jīng)濟(jì)理論建模的不斷發(fā)展，簡(jiǎn)單的自回歸序列已無法充分地反映經(jīng)濟(jì)增長率的變化機(jī)制，因此更多的非線性模型被引入用以刻畫經(jīng)濟(jì)增長率的波動(dòng)機(jī)制。近年來，越來越多的學(xué)者認(rèn)為：經(jīng)濟(jì)系統(tǒng)的結(jié)構(gòu)在不同的水平位置上存在著差異，而隨著經(jīng)濟(jì)系統(tǒng)結(jié)構(gòu)的改變，系統(tǒng)中各變量的作用機(jī)制也可能存在著相應(yīng)的變化。早期，許多研究使用區(qū)制轉(zhuǎn)移的方法對(duì)經(jīng)濟(jì)增長率的區(qū)間進(jìn)行了劃分，但由于樣本規(guī)模較小，劃分區(qū)間后卻難以對(duì)經(jīng)濟(jì)系統(tǒng)中變量的作用機(jī)制予以刻畫。因此，本文將在以往研究的基礎(chǔ)上，使用更廣義的時(shí)變估計(jì)方法，從動(dòng)態(tài)的角度刻畫經(jīng)濟(jì)增長率的波動(dòng)機(jī)制，并直接給出在變化的同時(shí)系統(tǒng)中各變量間作用機(jī)制的改變。 本文秉承了以往的研究思路，通過GDP增長率，通貨膨脹增長率，M2增長率以及PPI增長率建立了經(jīng)典的VAR經(jīng)濟(jì)模型。文中首先基于季度數(shù)據(jù)探討了VAR均值方程中GDP增長率對(duì)系統(tǒng)中各變量的沖擊反映，這一階段的結(jié)論大體上與以往大量的研究相吻合。只有在建立模型前的序列檢驗(yàn)上與以往研究略有不同，我們?cè)趯?duì)數(shù)據(jù)進(jìn)行平穩(wěn)性檢驗(yàn)時(shí)發(fā)現(xiàn)，CPI增長率序列并不平穩(wěn)，我們認(rèn)為，這是樣本區(qū)間差異造成的，我們的數(shù)據(jù)起始于1996年4季度，截止于2012年3季度，共16年整，當(dāng)數(shù)據(jù)剔除1996年前三個(gè)季度后，CPI增長率數(shù)據(jù)便體現(xiàn)出非平穩(wěn)特征，表現(xiàn)為差分平穩(wěn)序列。并且，它與GDP增長率序列存在著長期協(xié)整關(guān)系，因此這并不影響我們建立VAR模型。 隨后我們?cè)诨A(chǔ)研究的結(jié)果上，進(jìn)一步加入了本文的研究要素，通過蒙特卡洛模擬法獲取了樣本的后驗(yàn)分布，并進(jìn)一步引入了隨機(jī)波動(dòng)予以刻畫時(shí)變特征，建立了時(shí)變向量自回歸模型（TVP-VAR）�？紤]到在每個(gè)樣本點(diǎn)給出時(shí)變估計(jì)方程并沒有意義，因此本文選取了時(shí)變方程的兩種經(jīng)典沖擊反應(yīng)函數(shù)來刻畫變量間作用機(jī)制的時(shí)變特征。 實(shí)證研究結(jié)果表明，TVP-VAR模型對(duì)時(shí)點(diǎn)信息的捕捉能力要顯著優(yōu)于傳統(tǒng)的VAR均值方程。此外，我們發(fā)現(xiàn)：在樣本期間內(nèi)，通貨膨脹與經(jīng)濟(jì)增長間的作用機(jī)制可能發(fā)生過結(jié)構(gòu)性的改變。以往的文獻(xiàn)以及我們對(duì)2001年3季度和2006年3季度時(shí)點(diǎn)信息的研究都表明通貨膨脹在短期內(nèi)會(huì)促進(jìn)經(jīng)濟(jì)增長，而后將對(duì)經(jīng)濟(jì)增長表現(xiàn)出抑制作用。然而在刻畫2011年3季度的時(shí)點(diǎn)沖擊反應(yīng)函數(shù)時(shí)我們發(fā)現(xiàn)，通貨膨脹僅對(duì)經(jīng)濟(jì)增長表現(xiàn)出抑制作用，即二者間的作用機(jī)制發(fā)生了改變。最后，我們還認(rèn)為：當(dāng)經(jīng)濟(jì)增長率處于較高水平時(shí)，無論是控制通貨膨脹，，改變貨幣供給量，或是改變投資規(guī)模都會(huì)對(duì)經(jīng)濟(jì)增長產(chǎn)生較為強(qiáng)烈的沖擊，而當(dāng)經(jīng)濟(jì)增長率處于低位水平時(shí)，相應(yīng)的刺激效果遠(yuǎn)不如前者顯著。
[Abstract]:The dynamic fluctuation mechanism of economic growth rate is a hot topic in macroeconomics. Many scholars have studied the problem in detail. Early studies used autoregressive sequences and cointegration tests to characterize the changing characteristics of economic growth rates. However, with the development of economic theory modeling, simple autoregressive series can not fully reflect the changing mechanism of economic growth rate, so more nonlinear models are introduced to describe the fluctuation mechanism of economic growth rate. In recent years, more and more scholars think that the structure of the economic system is different at different levels, and with the change of the structure of the economic system, the action mechanism of the variables in the system may also have corresponding changes. In the early years, many studies used the method of district system transfer to divide the region of economic growth rate, but because of the small sample size, it is difficult to describe the mechanism of the variables in the economic system after dividing the interval. Therefore, on the basis of previous studies, this paper uses a more generalized time-varying estimation method to describe the fluctuation mechanism of economic growth rate from a dynamic point of view, and directly gives the change of the interaction mechanism between variables in the system while the change is taking place. In this paper, the classical VAR economic model is established by means of GDP growth rate, inflation growth rate M _ 2 growth rate and PPI growth rate. In this paper, based on the quarterly data, the impact of the GDP growth rate on the variables in the VAR mean equation is discussed. The conclusion of this stage is consistent with a lot of previous studies. Only in the model before the series test and previous research slightly different, we in the data when the stationary test found that the CPI growth rate series is not stable, we believe that this is the result of sample interval differences, Our data started in the fourth quarter of 1996 and ended in the third quarter of 2012 for a total of 16 years. Moreover, there is a long-term cointegration relationship with GDP growth rate series, so this does not affect the establishment of VAR model. Then we add the research elements to the results of basic research, obtain the posterior distribution of samples by Monte Carlo simulation method, and further introduce random waves to characterize the time-varying characteristics. A time-varying vector autoregressive model (TVP-VAR) is established. Considering that it is not meaningful to give the time-varying estimation equation at each sample point, two classical impulse response functions of the time-varying equation are selected to characterize the time-varying characteristics of the interaction mechanism between variables. The empirical results show that TVP-VAR model is superior to the traditional VAR mean equation in capturing time point information. In addition, we find that during the sample period, the mechanism of inflation and economic growth may have undergone structural changes. Previous literature and our studies of time points in the third quarter of 2001 and the third quarter of 2006 have shown that inflation promotes economic growth in the short term and then suppresses it. However, in describing the time point shock response function in the third quarter of 2011, we find that inflation only suppresses economic growth, that is, the mechanism of action between the two has changed. Finally, we also believe that when the economic growth rate is at a relatively high level, whether it is controlling inflation, changing the amount of money supply, or changing the scale of investment, it will have a stronger impact on economic growth. And when the economic growth rate is low, the corresponding stimulus effect is far less significant than the former.
【學(xué)位授予單位】：吉林大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2013
【分類號(hào)】：F224;F124.1
本文編號(hào)：2140510
[Abstract]:The dynamic fluctuation mechanism of economic growth rate is a hot topic in macroeconomics. Many scholars have studied the problem in detail. Early studies used autoregressive sequences and cointegration tests to characterize the changing characteristics of economic growth rates. However, with the development of economic theory modeling, simple autoregressive series can not fully reflect the changing mechanism of economic growth rate, so more nonlinear models are introduced to describe the fluctuation mechanism of economic growth rate. In recent years, more and more scholars think that the structure of the economic system is different at different levels, and with the change of the structure of the economic system, the action mechanism of the variables in the system may also have corresponding changes. In the early years, many studies used the method of district system transfer to divide the region of economic growth rate, but because of the small sample size, it is difficult to describe the mechanism of the variables in the economic system after dividing the interval. Therefore, on the basis of previous studies, this paper uses a more generalized time-varying estimation method to describe the fluctuation mechanism of economic growth rate from a dynamic point of view, and directly gives the change of the interaction mechanism between variables in the system while the change is taking place. In this paper, the classical VAR economic model is established by means of GDP growth rate, inflation growth rate M _ 2 growth rate and PPI growth rate. In this paper, based on the quarterly data, the impact of the GDP growth rate on the variables in the VAR mean equation is discussed. The conclusion of this stage is consistent with a lot of previous studies. Only in the model before the series test and previous research slightly different, we in the data when the stationary test found that the CPI growth rate series is not stable, we believe that this is the result of sample interval differences, Our data started in the fourth quarter of 1996 and ended in the third quarter of 2012 for a total of 16 years. Moreover, there is a long-term cointegration relationship with GDP growth rate series, so this does not affect the establishment of VAR model. Then we add the research elements to the results of basic research, obtain the posterior distribution of samples by Monte Carlo simulation method, and further introduce random waves to characterize the time-varying characteristics. A time-varying vector autoregressive model (TVP-VAR) is established. Considering that it is not meaningful to give the time-varying estimation equation at each sample point, two classical impulse response functions of the time-varying equation are selected to characterize the time-varying characteristics of the interaction mechanism between variables. The empirical results show that TVP-VAR model is superior to the traditional VAR mean equation in capturing time point information. In addition, we find that during the sample period, the mechanism of inflation and economic growth may have undergone structural changes. Previous literature and our studies of time points in the third quarter of 2001 and the third quarter of 2006 have shown that inflation promotes economic growth in the short term and then suppresses it. However, in describing the time point shock response function in the third quarter of 2011, we find that inflation only suppresses economic growth, that is, the mechanism of action between the two has changed. Finally, we also believe that when the economic growth rate is at a relatively high level, whether it is controlling inflation, changing the amount of money supply, or changing the scale of investment, it will have a stronger impact on economic growth. And when the economic growth rate is low, the corresponding stimulus effect is far less significant than the former.
【學(xué)位授予單位】：吉林大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2013
【分類號(hào)】：F224;F124.1
【參考文獻(xiàn)】
相關(guān)期刊論文 前10條
1 劉金全,王大勇;經(jīng)濟(jì)增長的階段性假說和波動(dòng)性溢出效應(yīng)檢驗(yàn)[J];財(cái)經(jīng)研究;2003年05期
2 范智;對(duì)我國1978～1994年的通貨膨脹與經(jīng)濟(jì)增長之間關(guān)系的探討[J];當(dāng)代財(cái)經(jīng);1997年05期
3 陳朝旭;;我國通貨膨脹與經(jīng)濟(jì)增長關(guān)系研究[J];當(dāng)代經(jīng)濟(jì)研究;2011年05期
4 劉金全;鄭挺國;;我國經(jīng)濟(jì)周期階段性劃分與經(jīng)濟(jì)增長走勢(shì)分析[J];中國工業(yè)經(jīng)濟(jì);2008年01期
5 莫力科;喬雪;;城市住宅價(jià)格與宏觀經(jīng)濟(jì)變量的關(guān)系分析——基于VAR模型的實(shí)證研究[J];工程管理學(xué)報(bào);2011年04期
6 張兵;;中美經(jīng)濟(jì)周期的同步性及其傳導(dǎo)機(jī)制分析[J];世界經(jīng)濟(jì)研究;2006年10期
7 宋健;;超額貨幣、經(jīng)濟(jì)增長與通貨膨脹——基于1979～2007年中國宏觀經(jīng)濟(jì)數(shù)據(jù)的實(shí)證研究[J];廣東金融學(xué)院學(xué)報(bào);2010年02期
8 左大培;;中國的經(jīng)濟(jì)增長與通貨膨脹[J];經(jīng)濟(jì)學(xué)動(dòng)態(tài);2008年06期
9 劉金全,范劍青;中國經(jīng)濟(jì)周期的非對(duì)稱性和相關(guān)性研究[J];經(jīng)濟(jì)研究;2001年05期
10 劉樹成;中國經(jīng)濟(jì)波動(dòng)的新軌跡[J];經(jīng)濟(jì)研究;2003年03期
相關(guān)碩士學(xué)位論文 前1條
1 鄭進(jìn)城;貝葉斯經(jīng)濟(jì)時(shí)間序列預(yù)測(cè)模型及其應(yīng)用研究[D];湖南大學(xué);2005年
本文編號(hào)：2140510
本文鏈接：http://sikaile.net/jingjilunwen/zhongguojingjilunwen/2140510.html
最近更新
教材專著
