Skill UI

This skill guides authors through the rigorous requirements of American Economic Journal: Economic Policy. It helps evaluate whether an applied economics manuscript meets the journal's high bar, focusing specifically on the joint criteria of sound causal identification (DiD, IV, RDD) and clear, impactful policy relevance. Use it to re-frame arguments and check against best practices for policy evaluation.

This guide provides stringent methodological standards for establishing credible causal claims in empirical policy manuscripts. It covers advanced econometric techniques—including Difference-in-Differences (DiD), Instrumental Variables (IV), Regression Discontinuity Design (RDD), and Randomized Controlled Trials (RCT)—required to move beyond mere correlation and prove that the observed effect is genuinely caused by the policy intervention.

A comprehensive strategy guide for authors submitting policy-evaluation papers to top economics journals. It details how expert referees evaluate manuscripts, focusing on four critical areas: policy interest, causal credibility, welfare reading, and robustness. This tool helps authors proactively anticipate and strengthen potential weaknesses before submission or during revision, significantly increasing the paper's chances of acceptance.

This guide helps academics determine if their manuscript aligns with the scope of China Industrial Economics, or if it should be redirected to more specialized journals (e.g., Economic Research, Management World). It provides criteria based on empirical rigor, policy quasi-experiments, and specific research focus (industry, enterprise, environment).

A comprehensive guide detailing advanced econometric methods for establishing causal relationships in policy evaluations. It covers techniques such as Difference-in-Differences (DID), Instrumental Variables (IV), Regression Discontinuity Design (RDD), and structural modeling. The core focus is bridging the gap between econometric rigor and policy legibility, ensuring that the causal mechanism is explicit in the main text while maintaining formal defense in the appendix.

A comprehensive guide for establishing robust causal links in environmental economics. It covers advanced econometric techniques for policy evaluation, including staggered Difference-in-Differences (DiD), Instrumental Variables (IV), and Regression Discontinuity Designs (RDD). It specifically addresses challenges in non-market valuation, such as spatial sorting, hypothetical bias, and separating weather shocks from long-term climate trends, ensuring the recovered parameter is welfare-relevant.

A guide for advanced data analysis in policy evaluation, extending beyond standard causal estimates. It emphasizes rigorous reporting of cost-benefit ratios, distributional consequences (who gains and who pays), robust heterogeneity testing, and honest uncertainty quantification necessary for high-level policy academic journals. Essential for turning effect sizes into decision-relevant policy narratives.

A comprehensive guide to defending causal claims in policy and program evaluation, adhering to rigorous econometric standards (e.g., JPAM). It covers advanced methods such as RCT, Difference-in-Differences (DiD), Regression Discontinuity (RDD), Instrumental Variables (IV), and Synthetic Control. This guide emphasizes stating the estimand, defending identification assumptions, and robustly ruling out alternative causal explanations, rather than just writing estimation code.

A comprehensive guide for authors submitting policy evaluation manuscripts to academic journals. It outlines the rigorous standards required to ensure full research reproducibility, detailing the process of archiving data and code in public repositories, creating master scripts, and providing documentation for restricted administrative data access.

This guide provides an advanced framework for conducting rigorous causal inference and policy evaluation, essential for academic journals. It covers state-of-the-art methods including DiD, RDD, Synthetic Control, and experimental analysis. The core focus is moving beyond simple p-values to estimate effect magnitudes in tangible 'decision units' (e.g., dollars per household, percentage points). It mandates comprehensive stress-testing, including pre-trend checks, placebo outcomes, and detailed subgroup heterogeneity analysis, ensuring results are immediately actionable by regulators.

Provides comprehensive methodological guidelines for designing rigorous studies in public policy and marketing. The framework covers both prospective (e.g., realistic experiments) and retrospective (e.g., DiD, RDD) evaluation designs, emphasizing the necessity of establishing a strong counterfactual basis and ensuring policy relevance in data collection and analysis.

A comprehensive guide and heuristic tool for assessing whether an academic manuscript is suitable for high-level public administration and policy journals, specifically referencing Public Administration and Policy Review. It details required scope, suitable methodologies (e.g., policy evaluation, case studies, mixed methods), structural requirements (anonymity, abstract formatting), and common rejection pitfalls to guide authors toward rigorous academic writing.