Forest vegetation carbon dynamics are widely considered as basic indicators of the capacity of a forest ecosystem for carbon sequestration and carbon exchange with the atmosphere and the ability of the forest ecosystem to function as a carbon sink or source. Forest management practices such as harvesting, afforestation, and reforestation are the most important factors that influence forest carbon dynamics. Therefore,elucidation of the effects of human silvicultural activities on forest ecosystem dynamics will provide a valuable insight into ways of expanding the size of the carbon pool and improving the ecological environment of China. Previous studies have attempted to identify the factors that affect forest carbon sequestration ; however, most of these investigations focused on a single factor and did not consider the interactions occurring between multiple factors. In addition, most previous studies were conducted on a small scale, and no investigations conducted at a regional or larger scale examined the influence of interactions occurring between multiple factors on forest carbon sequestration. Forest dynamic models represent a valuable tool for resolving this problem; however, existing models do not adequately reflect the interactive effects of multiple factors such as forest management practices, climate change, and other human-induced disturbances on forest carbon storage. In the present study, we used a vector autoregression (VAR) model that included seven parameters (factors) (timber output, forest-tending area, area affected by forest diseases and/or pests, fire-affected area, reforestation area, annual total precipitation, and annual average temperature) to simulate forest carbon storage dynamics in Shanxi Province. The results of variable stationary and cointegration analyses revealed that the investigated variables exhibited a single whole-sequence order at the 5% significance level ; in addition,they showed long-term stable equilibrium. Hence,we applied each variable to the VAR model and used the model stationary test to show that all the characteristic roots of the VAR model were <1,i.e., these roots fell within the unit circle. Our results indicate that the VAR model system is stable and meets the prerequisites for identifying the effects of multiple factors on forest vegetation carbon storage dynamics. Finally,we used impulse response and variance decomposition analyses to show that forest pests and timber output had significant negative impacts on carbon storage and contributed to a high degree of 5.61% and 4.52%, respectively. Forest tending and artificial reforestation had weakly negative effects on carbon storage, whereas forest fires, precipitation, and temperature had no significant effects on carbon storage. Taken together, our findings verify the suitability of the VAR model for identifying the effects of multiple factors on forest ecosystem carbon storage dynamics. Therefore, in future studies, this model can be used to analyze factors that influence forest vegetation carbon storage at a provincial scale.