Publications by authors named "Kaizhi Yu"

In the realm of time series data analysis, information criteria constructed on the basis of likelihood functions serve as crucial instruments for determining the appropriate lag order. However, the intricate structure of random coefficient integer-valued time series models, which are founded on thinning operators, complicates the establishment of likelihood functions. Consequently, employing information criteria such as AIC and BIC for model selection becomes problematic.

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This paper presents a first-order integer-valued autoregressive time series model featuring observation-driven parameters that may adhere to a particular random distribution. We derive the ergodicity of the model as well as the theoretical properties of point estimation, interval estimation, and parameter testing. The properties are verified through numerical simulations.

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A new integer-valued moving average model is introduced. The assumption of independent counting series in the model is relaxed to allow dependence between them, leading to the overdispersion in the model. Statistical properties were established for this new integer-valued moving average model with dependent counting series.

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The continuously increasing carbon emissions have become a significant hurdle for global sustainable development. Technological progress is considered essential for controlling carbon emissions. However, previous literature has analyzed technological progress as a whole, largely ignoring its spatial spillovers.

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No study has been conducted linking Chinese migrants' subjective well-being (SWB) with urban inequality. This paper presents the effects of income and inequality on their SWB using a total of 128,000 answers to a survey question about "happiness". We find evidence for a satiation point above which higher income is no longer associated with greater well-being.

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