{"id":50494,"date":"2025-06-20T13:45:17","date_gmt":"2025-06-20T17:45:17","guid":{"rendered":"https:\/\/carleton.ca\/economics\/?page_id=50494"},"modified":"2025-06-20T13:51:10","modified_gmt":"2025-06-20T17:51:10","slug":"matt-webb-2","status":"publish","type":"page","link":"https:\/\/carleton.ca\/economics\/matt-webb-2\/","title":{"rendered":"Matt Webb"},"content":{"rendered":"\n<section class=\"w-screen px-6 cu-section cu-section--white ml-offset-center md:px-8 lg:px-14\">\n    <div class=\"space-y-6 cu-max-w-child-5xl  md:space-y-10 cu-prose-first-last\">\n\n            <div class=\"cu-textmedia flex flex-col lg:flex-row mx-auto gap-6 md:gap-10 my-6 md:my-12 first:mt-0 max-w-5xl\">\n        <div class=\"justify-start cu-textmedia-content cu-prose-first-last\" style=\"flex: 0 0 100%;\">\n            <header class=\"font-light prose-xl cu-pageheader md:prose-2xl cu-component-updated cu-prose-first-last\">\n                                    <h1 class=\"cu-prose-first-last font-semibold !mt-2 mb-4 md:mb-6 relative after:absolute after:h-px after:bottom-0 after:bg-cu-red after:left-px text-3xl md:text-4xl lg:text-5xl lg:leading-[3.5rem] pb-5 after:w-10 text-cu-black-700 not-prose\">\n                        Matt Webb\n                    <\/h1>\n                \n                                \n                                    \n\n<p>Research and Awards<\/p>\n\n\n                            <\/header>\n\n                    <\/div>\n\n            <\/div>\n\n    <\/div>\n<\/section>\n\n\n\n<p><strong>2021 SSHRC Insight Grant<\/strong><\/p>\n\n\n\n<p><em>Bootstrap Methods for Cluster Robust Inference<\/em><\/p>\n\n\n\n<p>Professor Matthew Webb is the primary applicant for this grant, alongside co-applicant James G. MacKinnon of Queen\u2019s University and they have received $88,750 for this project. Although the literature on cluster-robust inference has greatly expanded in recent years, there remain many statistical problems for empirical researchers. Often empirical researchers are interested in analyzing specific public policies to see if they achieved their goals. When these analyses are conducted with flawed statistical tools, the conclusions reached can also be flawed. Because there can be far too many false positives, policies that in reality had no effect can often be determined to be effective. These problems can be compounded if flawed analyses of current policies are used to develop new policies. Professors Webb and MacKinnon will improve the set of tools for inference with clustered data by writing four academic papers and a non-technical overview paper.<\/p>\n\n\n\n<p><strong>2021 CIHR Project Grant<\/strong><\/p>\n\n\n\n<p><em>Making the Most of Canada\u2019s \u201cNatural Laboratory\u201d: Advancing Difference-in-Differences Methods for Unpoolable Data<\/em><\/p>\n\n\n\n<p>Professor Matthew Webb is the co-investigator for this project, alongside principal investigator Erin Strumpf of McGill University, and they have received $371,971 for this project. DiD is an indispensable tool to estimate the effects of health policies and interventions, but no methods or \u201cbest practices\u201d currently exist for conducting DiD analyses when data cannot be pooled across jurisdictions. The overarching goal of this proposal is to develop methods to overcome this barrier, facilitating the use of DiD to estimate the impacts of health interventions. Professors Webb and Strumpf will validate these methods in a Canadian context using Canadian data, but we expect our work to be broadly transportable to other settings.<\/p>\n\n\n\n<p><strong>2019<\/strong>&nbsp;<strong>Research Achievement Award<\/strong><\/p>\n\n\n\n<p><em>Cluster Robust Inference With Binary Outcomes<\/em><\/p>\n\n\n\n<p>Professor Matthew Webb\u2018s project will develop statistical tools that will enable people to reliably analyze and compare public policies such as tax changes and subsidies.<\/p>\n\n\n\n<p>\u201cThese programs often change at the regional level, which makes statistical analysis difficult\u2014largely because the observations may not be statistically independent from one another.\u201d<\/p>\n","protected":false},"excerpt":{"rendered":"<p>2021 SSHRC Insight Grant Bootstrap Methods for Cluster Robust Inference Professor Matthew Webb is the primary applicant for this grant, alongside co-applicant James G. MacKinnon of Queen\u2019s University and they have received $88,750 for this project. Although the literature on cluster-robust inference has greatly expanded in recent years, there remain many statistical problems for empirical [&hellip;]<\/p>\n","protected":false},"author":313,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"_acf_changed":false,"_cu_dining_location_slug":"","footnotes":"","_links_to":"","_links_to_target":""},"cu_page_type":[478],"class_list":["post-50494","page","type-page","status-publish","hentry","cu_page_type-research-grants-and-awards"],"acf":{"cu_post_thumbnail":""},"_links":{"self":[{"href":"https:\/\/carleton.ca\/economics\/wp-json\/wp\/v2\/pages\/50494","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/carleton.ca\/economics\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/carleton.ca\/economics\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/carleton.ca\/economics\/wp-json\/wp\/v2\/users\/313"}],"replies":[{"embeddable":true,"href":"https:\/\/carleton.ca\/economics\/wp-json\/wp\/v2\/comments?post=50494"}],"version-history":[{"count":1,"href":"https:\/\/carleton.ca\/economics\/wp-json\/wp\/v2\/pages\/50494\/revisions"}],"predecessor-version":[{"id":50495,"href":"https:\/\/carleton.ca\/economics\/wp-json\/wp\/v2\/pages\/50494\/revisions\/50495"}],"wp:attachment":[{"href":"https:\/\/carleton.ca\/economics\/wp-json\/wp\/v2\/media?parent=50494"}],"wp:term":[{"taxonomy":"cu_page_type","embeddable":true,"href":"https:\/\/carleton.ca\/economics\/wp-json\/wp\/v2\/cu_page_type?post=50494"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}