In this paper, we consider the stochastic Lotka-Volterra model with additive jump noises. We show some desired properties of the solution such as existence and uniqueness of positive strong solution, unique stationary distribution, and exponential ergodicity. After that, we investigate the maximum likelihood estimation for the drift coefficients based on continuous time observations. The likelihood function and explicit estimator are derived by using semimartingale theory. In addition, consistency and asymptotic normality of the estimator are proved. Finally, computer simulations are presented to illustrate our results.

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To accelerate global green and low-carbon development, China has proposed a “double carbon” target. It is particularly important to explore the carbon reduction effects of e-commerce transformation in cities to achieve sustainable development. Based on the quasi-natural experiment of the National E-Commerce Demonstration City (NEDC) pilot, 263 cities from 2008 to 2017 were selected as samples, and the propensity score matching difference-in-differences (PSM-DID) method was used to investigate the influence of NEDCs on urban carbon emissions in China and its underlying mechanism. The results show that NEDCs can significantly reduce urban carbon emissions; the carbon emission level of pilot cities was reduced by 9.45%. After passing a series of robustness tests, this conclusion remains valid. The policy effects of NEDCs on carbon emissions are heterogeneous across different regions and types of cities, with the policy effect being more significant in central and western cities and in resource-based cities. Further mechanism analysis shows that the NEDC policy reduces urban carbon emissions mainly through two channels, namely, green technology innovation and industrial structure upgrading. This study provides important policy implications for the implementation of e-commerce demonstration city construction according to local conditions and the realization of urban sustainable development under the double carbon goal.

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