{"id":9076,"date":"2025-12-15T20:27:03","date_gmt":"2025-12-15T23:27:03","guid":{"rendered":"https:\/\/aaep.org.ar\/?p=9076"},"modified":"2025-12-15T20:27:05","modified_gmt":"2025-12-15T23:27:05","slug":"estimating-closeness-of-competition-from-market-share-data-and-an-application-on-the-online-travel-agency-market","status":"publish","type":"post","link":"https:\/\/aaep.org.ar\/?p=9076","title":{"rendered":"Estimating closeness of competition from market share data and an application on the online travel agency market"},"content":{"rendered":"<iframe loading=\"lazy\" class=\"wonderplugin-pdf-iframe\" src=\"https:\/\/aaep.org.ar\/wp-content\/plugins\/wonderplugin-pdf-embed\/pdfjslight\/web\/viewer.html?v=2&file=https:\/\/aaep.org.ar\/works\/works2025\/18.pdf\" width=\"100%\" height=\"600px\" style=\"border:0;\"><\/iframe>\n\n\n\n<p><\/p>\n\n\n\n<p><\/p>\n","protected":false},"excerpt":{"rendered":"<p>Understanding the closeness of competition between competitors is of interest for market analysts and antitrust practitioners . The diversion ratio is a central statistic to summarize it. We present an empirical method to estimate diversion ratios from market share data using transition matrix estimates. The method can help understand the closeness of competition going beyond restrictive market-share based diversion ratios with little data requirements. The method is used to calculate counterfactuals and estimate the effect of international online travel agencies platforms exit from the Russian market in March, 2022. The counterfactual allows one to explain market changes over time from consumer substitution patterns, firm repositioning and income effects. Our results indicate that market relevance before the restrictions did not predict gains from competitor restrictions.<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"_coblocks_attr":"","_coblocks_dimensions":"","_coblocks_responsive_height":"","_coblocks_accordion_ie_support":"","footnotes":""},"categories":[29],"tags":[33],"class_list":["post-9076","post","type-post","status-publish","format-standard","hentry","category-anales","tag-aaep-anales-2025"],"acf":[],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v27.5 - https:\/\/yoast.com\/product\/yoast-seo-wordpress\/ -->\n<title>Estimating closeness of competition from market share data and an application on the online travel agency market - Asociaci\u00f3n Argentina de Econom\u00eda Pol\u00edtica<\/title>\n<meta name=\"robots\" content=\"noindex, follow\" \/>\n<meta property=\"og:locale\" content=\"es_ES\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Estimating closeness of competition from market share data and an application on the online travel agency market - Asociaci\u00f3n Argentina de Econom\u00eda Pol\u00edtica\" \/>\n<meta property=\"og:description\" content=\"Understanding the closeness of competition between competitors is of interest for market analysts and antitrust practitioners . The diversion ratio is a central statistic to summarize it. We present an empirical method to estimate diversion ratios from market share data using transition matrix estimates. The method can help understand the closeness of competition going beyond restrictive market-share based diversion ratios with little data requirements. The method is used to calculate counterfactuals and estimate the effect of international online travel agencies platforms exit from the Russian market in March, 2022. The counterfactual allows one to explain market changes over time from consumer substitution patterns, firm repositioning and income effects. Our results indicate that market relevance before the restrictions did not predict gains from competitor restrictions.\" \/>\n<meta property=\"og:url\" content=\"https:\/\/aaep.org.ar\/?p=9076\" \/>\n<meta property=\"og:site_name\" content=\"Asociaci\u00f3n Argentina de Econom\u00eda Pol\u00edtica\" \/>\n<meta property=\"article:published_time\" content=\"2025-12-15T23:27:03+00:00\" \/>\n<meta property=\"article:modified_time\" content=\"2025-12-15T23:27:05+00:00\" \/>\n<meta name=\"author\" content=\"aaepolitica\" \/>\n<meta name=\"twitter:card\" content=\"summary_large_image\" \/>\n<meta name=\"twitter:creator\" content=\"@aaepoficial\" \/>\n<meta name=\"twitter:site\" content=\"@aaepoficial\" \/>\n<meta name=\"twitter:label1\" content=\"Escrito por\" \/>\n\t<meta name=\"twitter:data1\" content=\"aaepolitica\" \/>\n<script type=\"application\/ld+json\" class=\"yoast-schema-graph\">{\"@context\":\"https:\\\/\\\/schema.org\",\"@graph\":[{\"@type\":\"Article\",\"@id\":\"https:\\\/\\\/aaep.org.ar\\\/?p=9076#article\",\"isPartOf\":{\"@id\":\"https:\\\/\\\/aaep.org.ar\\\/?p=9076\"},\"author\":{\"name\":\"aaepolitica\",\"@id\":\"https:\\\/\\\/aaep.org.ar\\\/#\\\/schema\\\/person\\\/7150b747ba20875259c74b2cd177316c\"},\"headline\":\"Estimating closeness of competition from market share data and an application on the online travel agency market\",\"datePublished\":\"2025-12-15T23:27:03+00:00\",\"dateModified\":\"2025-12-15T23:27:05+00:00\",\"mainEntityOfPage\":{\"@id\":\"https:\\\/\\\/aaep.org.ar\\\/?p=9076\"},\"wordCount\":32,\"publisher\":{\"@id\":\"https:\\\/\\\/aaep.org.ar\\\/#organization\"},\"keywords\":[\"AAEP Anales 2025\"],\"articleSection\":[\"Anales\"],\"inLanguage\":\"es\"},{\"@type\":\"WebPage\",\"@id\":\"https:\\\/\\\/aaep.org.ar\\\/?p=9076\",\"url\":\"https:\\\/\\\/aaep.org.ar\\\/?p=9076\",\"name\":\"Estimating closeness of competition from market share data and an application on the online travel agency market - 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