Amr Data Analysis
franklee16/academic-research-skills
A skill your agent uses when stress-testing the LOGIC of an Academy of Management Review (AMR) theory manuscript — checking logical coherence, running thought experiments and counterfactuals…
A skill your agent uses when estimating and stress-testing results for a Journal of Public Policy & Marketing (JPP&M) manuscript — treatment effects from experiments, DiD/RDD/synthetic-control…
Install Jppm Data Analysis
$ npx skills add brycewang-stanford/Awesome-Journal-Skills --skill jppm-data-analysis -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install brycewang-stanford/Awesome-Journal-Skills jppm-data-analysis --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/brycewang-stanford/Awesome-Journal-Skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/Journal-of-Public-Policy-and-Marketing-Skills/skills/jppm-data-analysis .claude/skills/jppm-data-analysis && rm -rf skills-srcUse ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.
Claude Code skills documentation · loads skills from .claude/skills/
Install the "jppm-data-analysis" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/Journal-of-Public-Policy-and-Marketing-Skills/skills/jppm-data-analysis into .claude/skills/jppm-data-analysis/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "jppm-data-analysis", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/Journal-of-Public-Policy-and-Marketing-Skills/skills/jppm-data-analysisType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add brycewang-stanford/Awesome-Journal-Skills --skill jppm-data-analysis -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install brycewang-stanford/Awesome-Journal-Skills jppm-data-analysis --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/brycewang-stanford/Awesome-Journal-Skills.git skills-src && mkdir -p .agents/skills && cp -r skills-src/Journal-of-Public-Policy-and-Marketing-Skills/skills/jppm-data-analysis .agents/skills/jppm-data-analysis && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "jppm-data-analysis" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/Journal-of-Public-Policy-and-Marketing-Skills/skills/jppm-data-analysis into .agents/skills/jppm-data-analysis/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "jppm-data-analysis", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add brycewang-stanford/Awesome-Journal-Skills --skill jppm-data-analysis -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install brycewang-stanford/Awesome-Journal-Skills jppm-data-analysis --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/brycewang-stanford/Awesome-Journal-Skills.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/Journal-of-Public-Policy-and-Marketing-Skills/skills/jppm-data-analysis .cursor/skills/jppm-data-analysis && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "jppm-data-analysis" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/Journal-of-Public-Policy-and-Marketing-Skills/skills/jppm-data-analysis into .cursor/skills/jppm-data-analysis/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "jppm-data-analysis", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/brycewang-stanford/Awesome-Journal-Skills.git --path Journal-of-Public-Policy-and-Marketing-Skills/skills/jppm-data-analysis--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add brycewang-stanford/Awesome-Journal-Skills --skill jppm-data-analysis -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install brycewang-stanford/Awesome-Journal-Skills jppm-data-analysis --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/brycewang-stanford/Awesome-Journal-Skills.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/Journal-of-Public-Policy-and-Marketing-Skills/skills/jppm-data-analysis .gemini/skills/jppm-data-analysis && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "jppm-data-analysis" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/Journal-of-Public-Policy-and-Marketing-Skills/skills/jppm-data-analysis into .gemini/skills/jppm-data-analysis/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "jppm-data-analysis", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install brycewang-stanford/Awesome-Journal-Skills jppm-data-analysisInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add brycewang-stanford/Awesome-Journal-Skills --skill jppm-data-analysis -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/brycewang-stanford/Awesome-Journal-Skills.git skills-src && mkdir -p .github/skills && cp -r skills-src/Journal-of-Public-Policy-and-Marketing-Skills/skills/jppm-data-analysis .github/skills/jppm-data-analysis && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "jppm-data-analysis" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/Journal-of-Public-Policy-and-Marketing-Skills/skills/jppm-data-analysis into .github/skills/jppm-data-analysis/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "jppm-data-analysis", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add brycewang-stanford/Awesome-Journal-Skills --skill jppm-data-analysis -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install brycewang-stanford/Awesome-Journal-Skills jppm-data-analysis --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/brycewang-stanford/Awesome-Journal-Skills.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/Journal-of-Public-Policy-and-Marketing-Skills/skills/jppm-data-analysis .opencode/skills/jppm-data-analysis && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "jppm-data-analysis" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/Journal-of-Public-Policy-and-Marketing-Skills/skills/jppm-data-analysis into .opencode/skills/jppm-data-analysis/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "jppm-data-analysis", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
Facts
- Skill name
jppm-data-analysis- GitHub stars
- 1.2k
- Token cost
- ~1.8k tokens
- SKILL.md length
- 725 words
- Files
- 1
- Skills in repo
- 2,387
- Repo updated
- First seen
- Licence
- MIT
At a glance
A skill your agent uses when estimating and stress-testing results for a Journal of Public Policy & Marketing (JPP&M) manuscript — treatment effects from experiments, DiD/RDD/synthetic-control…
- Estimating and stress-testing results for a Journal of Public Policy & Marketing (JPP&M) manuscript — treatment effects from experiments
- SKILL.md covers When to trigger, Estimate for the decision, not…, The evaluation battery and Heterogeneity as welfare…, plus 5 more sections
- Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md
- DiD/RDD/synthetic-control policy evaluations
What it does
Jppm Data Analysis is an agent skill from brycewang-stanford/Awesome-Journal-Skills. Use when estimating and stress-testing results for a Journal of Public Policy & Marketing (JPP&M) manuscript — treatment effects from experiments, DiD/RDD/synthetic-control policy evaluations, subgroup analyses for vulnerable populations, and policy-interpretable reporting. Runs the analysis; it does not choose the design (jppm-methods).
Its SKILL.md is about 1.8k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.
It sits in Data & Analytics, covering Data analysis and Load testing. The repository describes itself as: Journal-specific Claude Code/Codex skill packs covering mainstream journals — AER, QJE, Nature, Cell, 管理世界, 经济研究 & 200+ more — your fast track to getting published. ｜ 覆盖主流期刊的… The licence is MIT.
When your agent uses it
- Estimating and stress-testing results for a Journal of Public Policy & Marketing (JPP&M) manuscript — treatment effects from experiments
- DiD/RDD/synthetic-control policy evaluations
- Subgroup analyses for vulnerable populations
- Policy-interpretable reporting
Example prompts
- “/jppm-data-analysis”
What it can do on your machine
Read from SKILL.md and the folder at commit 932eb23. It shows what the files ask for, not the result of running them.
Tool permissions
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
Runs code
No scripts in the folder and no shell commands in SKILL.md.
From the folder's file list and the shell code blocks in SKILL.md.
Network
No URLs in SKILL.md.
From URLs in SKILL.md, links to its own repository left out.
Credentials
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Context cost
Jppm Data Analysis loads about 1.8k tokens when it runs. Until then it costs about 90 tokens; SKILL.md has 725 words of instructions outside code blocks.
Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.
Safety
Auto-check passed
The automated check found no risky patterns in SKILL.md.
Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.
SKILL.md
The full file from brycewang-stanford/Awesome-Journal-Skills at commit 932eb23, republished under its MIT licence (© brycewang-stanford). 725 words, ~1,751 tokens.
Download SKILL.mdSave it as
.claude/skills/jppm-data-analysis/SKILL.md (or your agent's skills folder).- name
- jppm-data-analysis
- description
- Use when estimating and stress-testing results for a Journal of Public Policy & Marketing (JPP&M) manuscript — treatment effects from experiments, DiD/RDD/synthetic-control policy evaluations, subgroup analyses for vulnerable populations, and policy-interpretable reporting. Runs the analysis; it does not choose the design (jppm-methods).
Data Analysis (jppm-data-analysis)
When to trigger
- A DiD around a policy rollout needs modern estimators and a pre-trend defense
- An RDD's bandwidth, density, or placebo checks are unbuilt
- Experimental effects are significant but not yet expressed in units a regulator can use
- Subgroup results for vulnerable populations look like fishing rather than a plan
- A reviewer will ask "how big is this in the market, and for whom?" and you cannot answer
Estimate for the decision, not the asterisk
At JPP&M the estimate feeds a policy judgment, so the analysis has two jobs the sibling journals weigh less: (1) make the causal claim survive an econometrics-literate reviewer, and (2) express magnitudes in decision units — percentage points of prevalence, dollars per household, calories per purchase, share of consumers misled — with uncertainty attached. A p-value cannot tell an agency whether a warning is worth mandating; an effect of "−2.1 percentage points in purchase incidence, 95% CI [−3.4, −0.8], concentrated among households below median income" can. Every headline estimate should be convertible into the language of a regulatory impact analysis.
The evaluation battery
| Design | Core estimate | The checks reviewers expect |
|---|---|---|
| DiD (staggered adoption) | group-time ATTs (Callaway–Sant'Anna, Sun–Abraham) | event-study plot; Goodman-Bacon decomposition; honest-DiD sensitivity to pre-trend violations |
| Canonical 2×2 DiD | TWFE with clustered SEs | pre-trend test; placebo outcomes; composition stability |
| RDD | local polynomial at the cutoff (rdrobust) | McCrary density test; bandwidth sensitivity; covariate smoothness; donut variants |
| Synthetic control | treated-vs-synthetic gap | pre-period fit; in-space and in-time placebos; leave-one-out donors |
| Experiment | ANOVA/OLS on manipulated conditions | randomization/balance check; effect sizes with CIs; multiple-outcome corrections |
Inference discipline: cluster at the policy-assignment level (state, market), and when treated clusters are few, use wild-cluster bootstrap or randomization inference rather than pretending N is large.
Heterogeneity as welfare analysis
Subgroup effects are not garnish here — they are often the finding. Pre-specify the policy-relevant splits (income, literacy/numeracy, age, race/ethnicity where the policy debate concerns targeting, prior usage of the harmful product), report them all rather than the flattering subset, and correct for the family of tests. An intervention with a null average effect that protects the most-exposed decile is a policy success; a positive average driven entirely by the already-safe is a policy failure. Interactions need probing (simple effects at policy-meaningful levels), and null subgroup effects deserve equivalence-style interpretation, not silence.
Translating estimates into policy terms
- Rescale to the affected population: effect × exposed base = market-level consequence (with CI carried through).
- Benchmark against instruments: compare the effect to what taxation, education, or existing labels achieve.
- Report the compliance-adjusted effect: an ITT under partial firm compliance understates the mandate's potential; show both ITT and, where instruments allow, the complier-adjusted estimate.
- Bound the unintended consequences: quantify substitution and boomerang outcomes, even (especially) when noisy.
Show full SKILL.md (276 more words)Show less
Execution bridge (StatsPAI / Stata MCP)
Run the battery, don't just enumerate it. Full map:
execution-with-mcp. JPP&M lives on policy evaluation and policy-realistic experiments; the counterfactual checks and welfare-relevant subgroup corrections are where reviewers concentrate fire.
detect_design→recommend→ fit withas_handle=true→audit_resultto enumerate what the design still owes.- Staggered policy adoption:
callaway_santanna/sun_abraham, thenbacon_decompositionandhonest_did_from_resultfor the pre-trend sensitivity a policy audience needs. - Cutoff-assigned exposure:
rdrobust+mccrary_test(firms sort around thresholds — test it, don't assert it). - Experiments and subgroup families: randomization inference plus
romano_wolf/benjamini_hochbergacross the vulnerable-population splits. - Inference with few treated clusters:
wild_cluster_bootstrap; spatial policy spillovers →conley. - Exhibits from the handle:
etable/did_summary_to_latexandplot_from_result, so table numbers never drift from the fitted model.
Keep the decisive counterfactual evidence in the body and the exhaustive battery in the web appendix; a worked end-to-end run lives in the JF execution walkthrough.
Checklist
- Headline effects reported in decision units with CIs, not asterisks
- DiD uses heterogeneity-robust estimators; event study + sensitivity to pre-trend violations shown
- RDD shows density, bandwidth, and placebo checks; synthetic control shows placebos
- SEs clustered at the assignment level; small-cluster inference handled honestly
- Vulnerable-population subgroups pre-specified, all reported, family-corrected
- Market-level rescaling and instrument benchmarking included
- Unintended-consequence outcomes estimated or explicitly bounded
Anti-patterns
- TWFE autopilot: a staggered rollout estimated with plain two-way fixed effects, no diagnostics
- Eyeball parallel trends: a raw-trends plot standing in for a sensitivity analysis
- Subgroup roulette: the one significant split reported, the pre-specified family hidden
- Unitless effects: standardized betas a regulator cannot map to any decision
- Cherry-dropped clusters: excluding inconvenient states/markets without a stated rule
- Silent substitution: claiming success while consumers shifted to an equally harmful alternative
Output format
【Design & estimator】DiD (CS/SA) / RDD / synthetic control / experiment (+ inference choice)
【Headline estimate】effect in decision units + CI
【Counterfactual checks】pre-trends/sensitivity, density/placebos — status of each
【Heterogeneity】pre-specified subgroups, corrected; who is protected vs. missed
【Policy translation】market-level magnitude + benchmark vs. alternative instruments
【Unintended effects】substitution/boomerang estimates or bounds
【Next skill】jppm-contribution-framing© brycewang-stanford, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
Files
Just SKILL.md in Journal-of-Public-Policy-and-Marketing-Skills/skills/jppm-data-analysis of brycewang-stanford/Awesome-Journal-Skills.
Open the folder on GitHubat commit 932eb23
Compare with similar skills
Jppm Data Analysis next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Jppm Data Analysis this skillbrycewang-stanford/Awesome-Journal-Skills | 1.2k | — | ~1.8k | Automated safety check: Pass | MIT | |
| Amr Data Analysisfranklee16/academic-research-skills | 223 | 1 repos | ~1.5k | Automated safety check: Pass | None | |
| Amr Theory Developmentfranklee16/academic-research-skills | 223 | 1 repos | ~1.4k | Automated safety check: Pass | None | |
| Isr Methodsfranklee16/academic-research-skills | 223 | 1 repos | ~1.1k | Automated safety check: Pass | None | |
| Jcr Methodsfranklee16/academic-research-skills | 223 | 1 repos | ~1.2k | Automated safety check: Pass | None | |
| Jme Data Analysisfranklee16/academic-research-skills | 223 | 1 repos | ~885 | Automated safety check: Pass | None |
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Questions about Jppm Data Analysis
What does Jppm Data Analysis do?
A skill your agent uses when estimating and stress-testing results for a Journal of Public Policy & Marketing (JPP&M) manuscript — treatment effects from experiments, DiD/RDD/synthetic-control…. Jppm Data Analysis is an agent skill from brycewang-stanford/Awesome-Journal-Skills. Use when estimating and stress-testing results for a Journal of Public Policy & Marketing (JPP&M) manuscript — treatment effects from experiments, DiD/RDD/synthetic-control policy evaluations, subgroup analyses for vulnerable populations, and policy-interpretable reporting.
When should I use Jppm Data Analysis?
Jppm Data Analysis fits situations like: estimating and stress-testing results for a Journal of Public Policy & Marketing (JPP&M) manuscript — treatment effects from experiments; diD/RDD/synthetic-control policy evaluations; subgroup analyses for vulnerable populations; policy-interpretable reporting.
How do I install Jppm Data Analysis in Claude Code?
Run `npx skills add brycewang-stanford/Awesome-Journal-Skills --skill jppm-data-analysis -a claude-code`. Or copy the skill folder (Journal-of-Public-Policy-and-Marketing-Skills/skills/jppm-data-analysis in brycewang-stanford/Awesome-Journal-Skills) into .claude/skills/jppm-data-analysis in your project. Claude Code loads it when a task matches its description.
How do I install Jppm Data Analysis in Codex?
Run `npx skills add brycewang-stanford/Awesome-Journal-Skills --skill jppm-data-analysis -a codex`. Or copy the skill folder (Journal-of-Public-Policy-and-Marketing-Skills/skills/jppm-data-analysis in brycewang-stanford/Awesome-Journal-Skills) into .agents/skills/jppm-data-analysis in your project. Codex loads it when a task matches its description.
Can I use Jppm Data Analysis in Cursor, Gemini CLI or GitHub Copilot?
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add brycewang-stanford/Awesome-Journal-Skills --skill jppm-data-analysis -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/jppm-data-analysis, .gemini/skills/jppm-data-analysis, .github/skills/jppm-data-analysis and .opencode/skills/jppm-data-analysis in your project.
What does Jppm Data Analysis need to run?
SKILL.md names no scripts, command-line tools or credentials: Jppm Data Analysis is instructions for the agent only.
Does Jppm Data Analysis access the network?
SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.
Is Jppm Data Analysis safe to install?
Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.
What licence does Jppm Data Analysis use?
Jppm Data Analysis is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
How many tokens does Jppm Data Analysis use?
About 1.8k tokens (SKILL.md is roughly 7k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.
What are the alternatives to Jppm Data Analysis?
Skills that share tags, products or a category with Jppm Data Analysis: Amr Data Analysis (franklee16/academic-research-skills, 223 stars), Amr Theory Development (franklee16/academic-research-skills, 223 stars), Isr Methods (franklee16/academic-research-skills, 223 stars) and Jcr Methods (franklee16/academic-research-skills, 223 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Jppm Data Analysis?
brycewang-stanford (a GitHub user) maintains it in brycewang-stanford/Awesome-Journal-Skills, which has 1,219 GitHub stars. The repository holds 2,387 skills in this directory. The repository was last updated on September 27, 2026.
Source: brycewang-stanford/Awesome-Journal-Skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.