empirical-design

To generate an empirical research design from literature notes, the Skill converts your ingested wiki of papers, variables, and datasets into a structured plan covering research questions through expected tables. It grounds key judgments by citing specific wiki pages.

An identification strategy in econometrics isolates causal effects from confounding factors. This Skill builds one by mapping your wiki's mechanisms and baseline models into a concrete plan that explicitly describes endogeneity risks and robustness checks.

To document data gaps during econometric study planning, the Skill flags missing local information transparently. It avoids pretending insufficient data can support an identified plan and lists specific gaps when local datasets fall short.

Yes, you can use this for empirical workflows in accounting, finance, management, and economics. It produces a workflow-aware blueprint spanning baseline models, mechanism checks, heterogeneity analysis, and expected tables for these fields.

To structure a robustness testing plan for a research proposal, the Skill transforms your wiki context into an executable empirical blueprint. It defines mechanism checks, heterogeneity analysis, and identification strategies, then archives the output to a dated wiki file.

The best way to connect literature reviews to variable construction is by cross-referencing specific wiki pages like [[耐心资本]]. This Skill distinguishes literature precedent from project proposals, linking ingested papers directly to variable definitions and data samples.