Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: A Class of Semiparametric Models with Homogeneous Structure for Panel
  Data Analysis   Stimulated by the analysis of a dataset from China about Covid-19, we propose
a class of semiparametric models for panel data analysis. The proposed models
account for both homogeneity and heterogeneity among the individuals of a panel
data. They strike a nice balance between parsimony and risk of
misspecification. Although stimulated by the analysis of a particular dataset,
the proposed models apply to very broad range of panel data analysis, they are
powerful in exploring nonlinear dynamic patterns of impacts of covariates or
transformed covariates. An estimation procedure is presented, and its
asymptotic properties are established. Intensive simulation studies are also
conducted to demonstrate how well the estimation procedure works and the risk
of ignoring homogeneity or heterogeneity among individuals in panel data
analysis. Finally, we apply the proposed models and estimation procedure to the
Covid-19 data from China, and reveal some interesting dynamic patterns of the
impacts of some important factors.

21
The categories of this paper are: adap-org
11
The categories of this paper are: hep-lat
10
The categories of this paper are: q-bio
37
The categories of this paper are: supr-con
36
The categories of this paper are: cmp-lg
29
The categories of this paper are: funct-an
2
The categories of this paper are: math
4
The categories of this paper are: cond-mat
18
The categories of this paper are: econ
19
The categories of this paper are: eess
35
The categories of this paper are: mtrl-th
6
The categories of this paper are: astro-ph
27
The categories of this paper are: comp-gas
32
The categories of this paper are: atom-ph
26
The categories of this paper are: bayes-an
24
The categories of this paper are: dg-ga