基于經(jīng)濟(jì)景氣指數(shù)對(duì)我國(guó)經(jīng)濟(jì)周期波動(dòng)轉(zhuǎn)折點(diǎn)的識(shí)別[1]

王金明1，2 劉旭陽(yáng)2

（1.吉林大學(xué)數(shù)量經(jīng)濟(jì)研究中心，吉林，長(zhǎng)春，130012；2.吉林大學(xué)商學(xué)院，吉林，長(zhǎng)春，130012）

摘要：本文利用NBER傳統(tǒng)方法和動(dòng)態(tài)因子模型計(jì)算景氣指數(shù)，并基于B-B法獲得轉(zhuǎn)折點(diǎn)信息，作為經(jīng)濟(jì)周期波動(dòng)基準(zhǔn)日期的參考。兩個(gè)景氣指數(shù)及其轉(zhuǎn)折點(diǎn)日期信息十分接近，共同反映出我國(guó)經(jīng)濟(jì)周期波動(dòng)態(tài)勢(shì)，通過(guò)對(duì)比存在差異的峰谷點(diǎn)信息，發(fā)現(xiàn)SW景氣指數(shù)確定的峰谷點(diǎn)更準(zhǔn)確，暫定為我國(guó)經(jīng)濟(jì)周期波動(dòng)的基準(zhǔn)日期?；诖耍疚膶⑽覈?guó)21世紀(jì)這段時(shí)期劃分為四輪經(jīng)濟(jì)周期，前兩輪經(jīng)濟(jì)周期表現(xiàn)出上升階段長(zhǎng)、下降階段短的非對(duì)稱特征，而后兩輪經(jīng)濟(jì)周期出現(xiàn)了上升階段短而下降階段長(zhǎng)的非對(duì)稱特征，我國(guó)經(jīng)濟(jì)目前正處于第四輪經(jīng)濟(jì)周期的收縮階段。同時(shí)，本文考察了馬爾可夫轉(zhuǎn)換（MS）方法在我國(guó)經(jīng)濟(jì)周期轉(zhuǎn)折點(diǎn)識(shí)別研究中的適用性，發(fā)現(xiàn)MS方法并不適合作為判斷我國(guó)經(jīng)濟(jì)周期轉(zhuǎn)折點(diǎn)信息的方法。

關(guān)鍵詞：經(jīng)濟(jì)周期 景氣指數(shù) 轉(zhuǎn)折點(diǎn) 動(dòng)態(tài)因子模型

Identifying the Turning Points of China’s Business Cycles Based on Economic Climate Index

Abstract：This paper calculates climate indexes by both the traditional method of NBER and dynamic factor model （DFMs），and obtains the information of the turning points from the indexes respectively based on Bry-Boschan Method （B-B），which is taken as a reference of business cycle fluctuation. The two climate indexes and relevant information of the turning points are close，they reflect the trend of Chinese business cycle fluctuation. Comparing the peaks and troughs which are different，this paper finds that SW climate index is more precise，so the turning points of the SW index are identified as the reference dates of Chinese business cycles. Based on the index，there exist four business cycles since 2000. We find that the first two business cycles have the asymmetry character of long expansion stage and short contraction stage，while the recent two business cycles have an opposite asymmetry character and China’s economy is still in a contraction stage now. This paper also investigates whether Markov Switching （MS） model can be used to identify China’s cyclical turning points. Unfortunately，this paper concludes that MS approach is not a good choice to decide China’s cyclical turning points.

Key Words：Business Cycle Climate Index Turning Points Dynamic Factor Model