English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

When parameters are weakly identified, bounds on the parameters may provide avaluable source of information. Existing weak identification estimation andinference results are unable to combine weak identification with bounds. Withina class of minimum distance models, this paper proposes identification-robustinference that incorporates information from bounds when parameters are weaklyidentified. The inference is based on limit theory that combines weakidentification theory with parameter-on-the-boundary theory. This paperdemonstrates the role of the bounds and identification-robust inference in twoexample factor models. This paper also demonstrates the identification-robustinference in an empirical application, a factor model for parental investmentsin children.

Weak Identification with Bounds in a Class of Minimum Distance Models