Abstract
Insurance consumption has been growing rapidly around the world, but there are few theories of insurance consumption in the literature. With data from China, we investigate the dynamics of nonlife insurance consumption for both the long run and short run in an integrated framework by employing the autoregressive distributed lag (ARDL) model developed by Pesaran et al. (2001). Our study focuses on two specific lines of nonlife insurance: personal accident insurance and automobile insurance, from which we discovered that the relationship between nonlife insurance consumption and its determinants is different across insurance lines and periods. The empirical findings of this article extend the results of previous works.
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