Estimating Latent Group Structure in Time-Varying Coefficient Panel Data Models

This paper studies the estimation of latent group structures in heterogeneous time-varying coefficient panel data models. While allowing the coefficient functions to vary over cross sections provides a good way to model cross-sectional heterogeneity, it reduces the degree of freedom and leads to poor estimation accuracy when the time-series length is short. On the other hand, in a lot of empirical studies, it is not uncommon to find that heterogeneous coefficients exhibit group structures where coefficients belonging to the same group are similar or identical. This paper aims to provide an easy and straightforward approach for estimating the underlying latent groups. This approach is based on the hierarchical agglomerative clustering (HAC) of kernel estimates of the heterogeneous time-varying coefficients when the number of groups is known. We establish the consistency of this clustering method and also propose a generalised information criterion for estimating the number of groups when it is unknown. Simulation studies are carried out to examine the finite sample properties of the proposed clustering method as well as the post-clustering estimation of the group-specific time-varying coefficients. The simulation results show that our methods give comparable performance as the penalised-sieve-estimation-based classifier-LASSO approach by Su et al. (2018), but are computationally easier. An application to a panel study of economic growth is also provided

Molecular Ecology and Natural History of Simian Foamy Virus Infection in Wild-Living Chimpanzees

Identifying microbial pathogens with zoonotic potential in wild-living primates can be important to human health, as evidenced by human immunodeficiency viruses types 1 and 2 (HIV-1 and HIV-2) and Ebola virus. Simian foamy viruses (SFVs) are ancient retroviruses that infect Old and New World monkeys and apes. Although not known to cause disease, these viruses are of public health interest because they have the potential to infect humans and thus provide a more general indication of zoonotic exposure risks. Surprisingly, no information exists concerning the prevalence, geographic distribution, and genetic diversity of SFVs in wild-living monkeys and apes. Here, we report the first comprehensive survey of SFVcpz infection in free-ranging chimpanzees (Pan troglodytes) using newly developed, fecal-based assays. Chimpanzee fecal samples (n = 724) were collected at 25 field sites throughout equatorial Africa and tested for SFVcpz-specific antibodies (n = 706) or viral nucleic acids (n = 392). SFVcpz infection was documented at all field sites, with prevalence rates ranging from 44% to 100%. In two habituated communities, adult chimpanzees had significantly higher SFVcpz infection rates than infants and juveniles, indicating predominantly horizontal rather than vertical transmission routes. Some chimpanzees were co-infected with simian immunodeficiency virus (SIVcpz); however, there was no evidence that SFVcpz and SIVcpz were epidemiologically linked. SFVcpz nucleic acids were recovered from 177 fecal samples, all of which contained SFVcpz RNA and not DNA. Phylogenetic analysis of partial gag (616 bp), pol-RT (717 bp), and pol-IN (425 bp) sequences identified a diverse group of viruses, which could be subdivided into four distinct SFVcpz lineages according to their chimpanzee subspecies of origin. Within these lineages, there was evidence of frequent superinfection and viral recombination. One chimpanzee was infected by a foamy virus from a Cercopithecus monkey species, indicating cross-species transmission of SFVs in the wild. These data indicate that SFVcpz (i) is widely distributed among all chimpanzee subspecies; (ii) is shed in fecal samples as viral RNA; (iii) is transmitted predominantly by horizontal routes; (iv) is prone to superinfection and recombination; (v) has co-evolved with its natural host; and (vi) represents a sensitive marker of population structure that may be useful for chimpanzee taxonomy and conservation strategies