robustness
Checklist of empirical robustness tests for finance/economics papers
Install / Use
npx skills add brycewang-stanford/Auto-Empirical-Research-Skills --skill robustnessInstalls into whichever agent you are using.
SKILL.md
Installable skill definition
Quality Score
Category
Finance & AccountingSupported Platforms
Our assessment of robustness
robustness scores 84/100 on our quality scale, 27th of 45 Finance & Accounting skills we index.
Its SKILL.md is 5.3 KB long, well organised into 12 sections with 1 code example: a solid amount of guidance for an agent.
With 4,360 GitHub stars, it is one of the more widely adopted skills in the catalogue.
Maintenance, license and trust
- The repository was last updated 3 days ago, so robustness is actively maintained.
- No license is declared. By default that means all rights are reserved: you can read it, but reusing or redistributing it is not clearly permitted. Ask the author before building on it commercially.
- Its trust signals score 88/100, with 1 caution from licensing, adoption, age or documentation. These come from repository metadata, not a code audit — read the skill file before letting an agent act on it.
robustness compared with similar skills
All 4 of these similar skills score higher than robustness; compare them before choosing.
| Skill | Score | Stars | Updated | Format |
|---|---|---|---|---|
| robustness (this skill)by brycewang-stanford | 84 | 4.4k | 3d ago | SKILL.md |
| algorithmic-artby anthropics | 100 | 177.9k | 4d ago | SKILL.md |
| pptxby anthropics | 100 | 177.9k | 4d ago | SKILL.md |
| designby nextlevelbuilder | 100 | 130.2k | 5d ago | SKILL.md |
| ui-ux-pro-maxby nextlevelbuilder | 100 | 130.2k | 5d ago | SKILL.md |
Frequently asked questions
- How do I install robustness?
- Run
npx skills add brycewang-stanford/Auto-Empirical-Research-Skills --skill robustness. The install tabs above show the steps for each supported agent. - Which AI agents does robustness work with?
- It is written for Universal, as a SKILL.md file. Other agents that read the same format can often use it too.
- Is robustness safe to use?
- It declares no license and scores 88/100 on trust signals. Skills are instructions an agent will follow, so read the file before installing it and do not approve commands you do not understand.
- Is robustness still maintained?
- The repository was last updated 3 days ago, so robustness is actively maintained.
Skill content
View source on GitHubname: robustness description: Checklist of empirical robustness tests for finance/economics papers
Robustness Test Checklist
Systematic checklist of robustness tests for empirical research. Use this to ensure comprehensive testing before submission.
Core Robustness Categories
1. Alternative Samples
| Test | Description | When to Use | |------|-------------|-------------| | Exclude outliers | Winsorize/trim at different levels (0.5%, 2%, 5%) | Always | | Drop financial firms | Exclude SIC 6000-6999 | If not already excluded | | Drop regulated industries | Exclude utilities, telecoms | Industry-specific effects | | Different time periods | Split sample pre/post crisis, early/late | Results may be period-specific | | Geographic subsamples | By region, state, country | External validity | | Size subsamples | Small vs. large firms | Heterogeneous effects | | Balanced panel | Require continuous observations | Survivorship concerns |
2. Alternative Specifications
| Test | Description | When to Use | |------|-------------|-------------| | Different fixed effects | Firm, industry×year, state×year | Control for unobservables | | Additional controls | Add variables referees might suggest | Omitted variable concerns | | Drop controls | Verify not over-controlling | Mediator concerns | | Different clustering | Firm, industry, state, two-way | Inference robustness | | Different standard errors | Bootstrap, Newey-West, Driscoll-Kraay | Serial/cross-sectional correlation | | Nonlinear specifications | Quadratic terms, splines | Linearity assumption | | Log vs. level | Transform dependent variable | Skewed distributions |
3. Alternative Measures
| Test | Description | When to Use | |------|-------------|-------------| | Alternative dependent variable | Different proxy for same concept | Measurement concerns | | Alternative treatment measure | Continuous vs. binary, different threshold | Treatment definition | | Alternative control measures | Different proxies for size, leverage, etc. | Standard practice | | Scaled differently | By assets, sales, employees | Scaling choice matters |
4. Identification Tests
| Test | Description | When to Use | |------|-------------|-------------| | Placebo/Falsification | | | | Placebo timing | Fake treatment 1-3 years before actual | DiD parallel trends | | Placebo outcome | Effect on outcome that shouldn't be affected | Specificity of mechanism | | Placebo treatment | Random assignment of treatment | Rule out spurious correlation | | Pre-trends | | | | Event study plot | Coefficient for each pre/post period | Visual parallel trends | | Joint F-test | Test pre-period coefficients = 0 | Statistical parallel trends | | Endogeneity | | | | Instrumental variables | Find exogenous variation | Selection concerns | | Heckman selection | Model selection explicitly | Sample selection | | Propensity score matching | Match treated/control | Observable selection | | Entropy balancing | Reweight to balance covariates | Covariate imbalance | | Regression discontinuity | If threshold exists | Sharp identification |
5. Inference Robustness
| Test | Description | When to Use | |------|-------------|-------------| | Wild cluster bootstrap | Small number of clusters | <50 clusters | | Randomization inference | Permutation-based p-values | Few treated units | | Conley standard errors | Spatial correlation | Geographic data | | Multiple hypothesis correction | Bonferroni, FDR | Many outcomes tested |
DiD-Specific Tests
For difference-in-differences designs:
- [ ] Event study with pre-treatment coefficients
- [ ] Parallel trends test (formal)
- [ ] Bacon decomposition (staggered treatment)
- [ ] Callaway-Sant'Anna or Sun-Abraham estimator (heterogeneous treatment effects)
- [ ] Placebo treatment timing
- [ ] Vary treatment window
- [ ] Triple-difference if possible
- [ ] Exclude always-treated or never-treated
IV-Specific Tests
For instrumental variables:
- [ ] First-stage F-statistic (>10, prefer >100)
- [ ] Weak instrument robust inference (Anderson-Rubin)
- [ ] Overidentification test (if multiple IVs)
- [ ] Exclusion restriction discussion
- [ ] Reduced form results
- [ ] Compare OLS vs. IV magnitudes
Quick Commands
- "robustness checklist" - Full checklist for current paper
- "DiD robustness" - DiD-specific tests only
- "what tests for [method]" - Tests for specific identification strategy
- "referee-proof" - Most commonly requested tests
- "prioritize tests" - Rank by importance for your setting
Referee-Proof Minimum
At minimum, most papers should include:
- Sample robustness: Exclude outliers, alternative time periods
- Specification robustness: Alternative fixed effects, controls
- Measurement robustness: Alternative variable definitions
- Inference robustness: Alternative clustering
- Identification test: At least one placebo or pre-trend test
Reporting Template
For robustness tables:
Table X: Robustness Tests
Panel A: Alternative Samples
(1) Baseline
(2) Exclude financial firms
(3) Exclude 2008-2009
(4) Winsorize at 5%
Panel B: Alternative Specifications
(5) Add industry×year FE
(6) Control for firm age
(7) Cluster by industry
Panel C: Alternative Measures
(8) Alternative dependent variable
(9) Continuous treatment measure
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Trust signals
From repository metadata: license, adoption, age and documentation. Not a code audit — see the Safety scan above for what the skill file itself contains.
