Checklist of empirical robustness tests for finance/economics papers
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Systematic checklist of robustness tests for empirical research. Use this to ensure comprehensive testing before submission.
| 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 |
| 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 |
| 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 |
| 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 |
| 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 |
For difference-in-differences designs:
For instrumental variables:
At minimum, most papers should include:
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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