Tighten JOSS paper summary and impact section

Author: vahid-ahmadi

paper-preview.html

@@ -394,7 +394,7 @@ <h2>Contents</h2>
 
   <article class="paper-body">
 <h1 id="summary">Summary</h1>
-<p>The <code>policyengine</code> Python package <span class="citation" data-cites="policyengine_py">(PolicyEngine Contributors 2026)</span> is an open-source analysis layer for tax-benefit microsimulation. It provides a common interface for running policy simulations and analyzing distributional impacts across the US and UK. It delegates country-specific tax-benefit calculations to dedicated country packages (<code>policyengine-us</code> and <code>policyengine-uk</code>) while providing shared abstractions for simulations, datasets, parametric reforms, and output analysis. Recent releases also provide version-pinned reproducibility by certifying compatible combinations of country models, microdata, and dataset artifacts. The package also powers an interactive web application at <a href="https://policyengine.org">policyengine.org</a>.</p>
+<p>The <code>policyengine</code> Python package <span class="citation" data-cites="policyengine_py">(PolicyEngine Contributors 2026)</span> is open-source software for analyzing how tax and benefit policies affect household incomes and government budgets in the US and UK. It gives analysts a common workflow for running simulations on representative microdata or custom households and for comparing current law with proposed reforms. Country-specific rules live in dedicated packages (<code>policyengine-us</code> and <code>policyengine-uk</code>), while <code>policyengine</code> provides shared tools for datasets, reforms, outputs, and reproducible release bundles. The package also powers the interactive web application at <a href="https://policyengine.org">policyengine.org</a>.</p>
 
 <h1 id="statement-of-need">Statement of Need</h1>
 <p>Tax-benefit microsimulation models are standard tools for evaluating the distributional impacts of fiscal policy. Governments, think tanks, and researchers use them to estimate how policy reforms affect household incomes, poverty rates, and government budgets. In practice, however, analysts often work across separate layers: statutory rules, representative microdata, reform definitions, and distributional outputs live in different tools and interfaces. Reproducing a baseline-versus-reform workflow, or carrying the same analysis pattern from one country model to another, therefore often requires bespoke scripts and project-specific conventions. Historical replication is especially difficult when policy rules, the analysis layer, and representative microdata are versioned independently and the analyst must reconstruct which combination produced a published estimate.</p>
@@ -498,14 +498,12 @@ <h1 id="software-design">Software Design</h1>
 <p>A UK reproduction script that runs a population-level analysis is available at <code>examples/paper_repro_uk.py</code>.</p>
 
 <h1 id="research-impact-statement">Research Impact Statement</h1>
-<p><strong>Government use.</strong> Co-author Nikhil Woodruff served as an Innovation Fellow with the 10DS data science team at 10 Downing Street, adapting PolicyEngine for government policy analysis <span class="citation" data-cites="no10fellowship2026">(Woodruff 2026)</span>. HM Treasury registered PolicyEngine in the UK Algorithmic Transparency Recording Standard as an algorithmic tool their Personal Tax, Welfare and Pensions team evaluates <span class="citation" data-cites="hmt2024atrs">(HM Treasury 2024)</span>. The U.S. Congress Joint Economic Committee built an immigration fiscal impact calculator using PolicyEngine's microsimulation model <span class="citation" data-cites="jec2026immigration">(Joint Economic Committee 2026)</span>.</p>
-<p><strong>Congressional and parliamentary citation.</strong> In the US, members of Congress cited PolicyEngine analyses when introducing the Young Adult Tax Credit Act <span class="citation" data-cites="mcgarvey2024yatc">(Office of Representative Morgan McGarvey 2024)</span>, the End Child Poverty Act <span class="citation" data-cites="tlaib2023endchildpoverty">(Office of Representative Rashida Tlaib 2023)</span>, and the Keep Your Pay Act <span class="citation" data-cites="pe_keepyourpay">(Office of Senator Cory Booker 2026)</span>. In the UK, Baroness Altmann cited Commons Library research using PolicyEngine during House of Lords debate on the National Insurance Contributions (Employer Pensions Contributions) Bill <span class="citation" data-cites="hansard2026nic">(House of Lords 2026)</span>.</p>
-<p><strong>Institutional use.</strong> Under a memorandum of understanding with the Federal Reserve Bank of Atlanta, PolicyEngine runs three-way comparisons of its calculations against TAXSIM and the Atlanta Fed's Policy Rules Database <span class="citation" data-cites="atlanta_fed_prd">(Federal Reserve Bank of Atlanta 2021)</span>. Co-author Max Ghenis and Jason DeBacker (University of South Carolina) presented the Enhanced CPS methodology at the 117th Annual Conference on Taxation of the National Tax Association <span class="citation" data-cites="ghenis2024nta">(Ghenis and DeBacker 2024)</span>.</p>
-<p><strong>Academic research.</strong> The Better Government Lab (Georgetown McCourt School / University of Michigan Ford School) collaborated with PolicyEngine on benefits eligibility research <span class="citation" data-cites="pe_bgl">(Ghenis 2024b)</span>. Matt Unrath (University of Southern California) uses PolicyEngine in a study of effective marginal and average tax rates facing American families, which the US Department of Health and Human Services funds through the Institute for Research on Poverty <span class="citation" data-cites="pe_usc">(Institute for Research on Poverty 2025)</span>. The Beeck Center at Georgetown University featured PolicyEngine in research on rules-as-code for US public benefits <span class="citation" data-cites="beeck2023rac beeck2025ai">(Kennan et al. 2023, 2025)</span>. Youngman et al. <span class="citation" data-cites="youngman2026carbon">(2026)</span>, at the Institute for New Economic Thinking, Oxford, cite PolicyEngine UK's microdata methodology in an agent-based macroeconomic model for the UK's Seventh Carbon Budget.</p>
-<p><strong>Policy research.</strong> In the US, the Niskanen Center used PolicyEngine to estimate the cost and distributional impacts of Child Tax Credit reform options <span class="citation" data-cites="mccabe2024ctc">(McCabe and Sargeant 2024)</span>. DC Councilmember Zachary Parker cited PolicyEngine's analysis when introducing the District Child Tax Credit Amendment Act of 2023 <span class="citation" data-cites="pe_dctc">(Council of the District of Columbia 2023)</span>. In the UK, the National Institute of Economic and Social Research (NIESR) used PolicyEngine in their UK Living Standards Review 2025 <span class="citation" data-cites="niesr2025living">(Mosley et al. 2025)</span>, and the Institute of Economic Affairs published PolicyEngine-based analyses of employer National Insurance contributions and 2025&ndash;2026 tax changes <span class="citation" data-cites="woodruff2024nic woodruff2025tax">(Woodruff 2024, 2025)</span>.</p>
+<p><strong>Government and legislative use.</strong> Co-author Nikhil Woodruff served as an Innovation Fellow with the 10DS data science team at 10 Downing Street, adapting PolicyEngine for government policy analysis <span class="citation" data-cites="no10fellowship2026">(Woodruff 2026)</span>. HM Treasury registered PolicyEngine in the UK Algorithmic Transparency Recording Standard as a tool their Personal Tax, Welfare and Pensions team evaluates <span class="citation" data-cites="hmt2024atrs">(HM Treasury 2024)</span>, and the U.S. Congress Joint Economic Committee built an immigration fiscal impact calculator on top of PolicyEngine's microsimulation model <span class="citation" data-cites="jec2026immigration">(Joint Economic Committee 2026)</span>. In the US, members of Congress cited PolicyEngine analyses when introducing the Young Adult Tax Credit Act, the End Child Poverty Act, and the Keep Your Pay Act <span class="citation" data-cites="mcgarvey2024yatc tlaib2023endchildpoverty pe_keepyourpay">(Office of Representative Morgan McGarvey 2024; Office of Representative Rashida Tlaib 2023; Office of Senator Cory Booker 2026)</span>. In the UK, Baroness Altmann cited Commons Library research using PolicyEngine during House of Lords debate on employer pension contributions <span class="citation" data-cites="hansard2026nic">(House of Lords 2026)</span>.</p>
+<p><strong>Institutional and academic use.</strong> Under a memorandum of understanding with the Federal Reserve Bank of Atlanta, PolicyEngine runs three-way comparisons against TAXSIM and the Atlanta Fed's Policy Rules Database <span class="citation" data-cites="atlanta_fed_prd">(Federal Reserve Bank of Atlanta 2021)</span>. Co-author Max Ghenis and Jason DeBacker presented the Enhanced CPS methodology at the 117th Annual Conference on Taxation of the National Tax Association <span class="citation" data-cites="ghenis2024nta">(Ghenis and DeBacker 2024)</span>. PolicyEngine has also been used or discussed in work by the Better Government Lab, the Beeck Center at Georgetown University, Matt Unrath at the University of Southern California, and Youngman et al. at the Institute for New Economic Thinking, Oxford <span class="citation" data-cites="pe_bgl beeck2023rac beeck2025ai pe_usc youngman2026carbon">(Ghenis 2024b; Kennan et al. 2023, 2025; Institute for Research on Poverty 2025; Youngman et al. 2026)</span>.</p>
+<p><strong>Policy research use.</strong> In the US, the Niskanen Center used PolicyEngine to estimate the cost and distributional impacts of Child Tax Credit reform options, and DC Councilmember Zachary Parker cited PolicyEngine's analysis when introducing the District Child Tax Credit Amendment Act of 2023 <span class="citation" data-cites="mccabe2024ctc pe_dctc">(McCabe and Sargeant 2024; Council of the District of Columbia 2023)</span>. In the UK, the National Institute of Economic and Social Research used PolicyEngine in their UK Living Standards Review 2025, and the Institute of Economic Affairs published PolicyEngine-based analyses of employer National Insurance contributions and 2025&ndash;2026 tax changes <span class="citation" data-cites="niesr2025living woodruff2024nic woodruff2025tax">(Mosley et al. 2025; Woodruff 2024, 2025)</span>.</p>
 
 <h1 id="acknowledgements">Acknowledgements</h1>
-<p>Arnold Ventures <span class="citation" data-cites="arnold_ventures">(Arnold Ventures 2023)</span>, NEO Philanthropy <span class="citation" data-cites="neo_philanthropy">(Ghenis 2024a)</span>, the Gerald Huff Fund for Humanity, and the National Science Foundation (NSF POSE Phase I, Award 2518372) <span class="citation" data-cites="nsf_pose">(National Science Foundation 2025)</span> funded this work in the US. The Nuffield Foundation has funded the UK work since September 2024 <span class="citation" data-cites="nuffield2024grant">(Nuffield Foundation 2024)</span>. These funders had no involvement in the design, development, or content of this software or paper.</p>
+<p>Arnold Ventures <span class="citation" data-cites="arnold_ventures">(Arnold Ventures 2023)</span>, NEO Philanthropy <span class="citation" data-cites="neo_philanthropy">(Ghenis 2024a)</span>, the Gerald Huff Fund for Humanity, and the National Science Foundation (NSF POSE Phase I, Award 2518372) <span class="citation" data-cites="nsf_pose">(National Science Foundation 2025)</span> funded this work in the US. The Nuffield Foundation has funded the UK work since September 2024 <span class="citation" data-cites="nuffield2024grant">(Nuffield Foundation 2024)</span>. These funders had no involvement in the design, development, or content of this software or paper. All authors are employed by PolicyEngine and may benefit reputationally from the software's adoption; this relationship is disclosed here as a potential conflict of interest.</p>
 <p>We thank all PolicyEngine contributors and the OpenFisca community for the microsimulation framework from which PolicyEngine was forked <span class="citation" data-cites="openfisca">(OpenFisca Contributors 2024)</span>. We acknowledge the US Census Bureau for providing access to the Current Population Survey, and the UK Data Service and the Department for Work and Pensions for providing access to the Family Resources Survey.</p>
 
 <h1 id="ai-usage-disclosure">AI Usage Disclosure</h1>