# The Factors Impact the Number of Private Car Ownership of China

Topics: Regression analysis, Autocorrelation, Statistics Pages: 10 (1459 words) Published: February 6, 2013
The Factors Impact the Number of Private Car Ownership of China

Demi Huang

1. Problem Introduction and Research Significance
From 1990s, sales volume of vehicles in China increase swiftly. Number of private car ownership also increase rapidly from 1995. Car market is making a great contribution to domestic economy in China. According to the statistic data (1995-2010) make a time serious sample. Analysis the impact of domestic average wage, residents’ deposits, money supply, Engel coefficient, price index and the quantity of car production on the number of private car ownership. Then conclude and give recommendations to keep China car market growth.

2. Model specification

where,
numco is number of private car ownership (10 thousand),
avgw is average wage (in Chinese Yuan),
rsdps is residents’ deposits (100 million Yuan),
ms is money supply (100 million Yuan),
engle is Engle coefficient,
pi is price index,
q is quantity of car output (10 thousand).
3. Obtain data
Obtain the data we need from website of National Bureau of Statistics of China. http://www.stats.gov.cn/tjsj/
Built a time serious sample as follow table shows:
(Sample size n=16)
|year |numco |avgw | |Method: Least Squares | | | |Date: 11/16/12 Time: 00:52 | | | |Sample: 1 16 | | | | |Included observations: 16 | | | | | | | | | | | | | | | |Variable |Coefficient |Std. Error |t-Statistic |Prob.   | | | | | | | | | | | | | |C |-1829.927 |574.5195 |-3.185142 |0.0111 | |AVGW |-0.002268 |0.040144 |-0.056500 |0.9562 | |RSDPS |-0.006983 |0.005868 |-1.190077 |0.2645 | |MS |0.011283 |0.004930 |2.288765 |0.0479 | |ENGLE |26.88898 |10.08886 |2.665216 |0.0258 | |PI |0.927345 |7.874427 |0.117767 |0.9088 | |Q |0.316694 |0.775447 |0.408402 |0.6925 | | | | | | | | | | | | | |R-squared |0.998995 |    Mean dependent var |1749.633 | |Adjusted R-squared |0.998325 |    S.D. dependent var |1692.257 | |S.E. of regression |69.25438 |    Akaike info criterion |11.61309 | |Sum squared resid |43165.52 |    Schwarz criterion |11.95109 | |Log likelihood |-85.90468 |    Hannan-Quinn criter. |11.63039 | |F-statistic |1491.219 |    Durbin-Watson stat |2.396667 | |Prob(F-statistic) |0.000000 | | | | | | | | | | | | | | | |

n=16...