  In the past, the seed keywords for CPI prediction were often selected based
on empirical summaries of research and literature studies, which were prone to
select omitted and invalid variables. In this paper, we design a keyword
expansion technique for CPI prediction based on the cutting-edge NLP model,
PANGU. We improve the CPI prediction ability using the corresponding web search
index. Compared with the unsupervised pre-training and supervised downstream
fine-tuning natural language processing models such as BERT and NEZHA, the
PANGU model can be expanded to obtain more reliable CPI-generated keywords by
its excellent zero-sample learning capability without the limitation of the
downstream fine-tuning data set. Finally, this paper empirically tests the
keyword prediction ability obtained by this keyword expansion method with
historical CPI data.

General Economics;Economics