{"id":"https://openalex.org/W4402395811","doi":"https://doi.org/10.15826/vestnik.2024.23.3.027","title":"Forecasting The Economic Growth of Sverdlovsk Region: A Comparative Analysis of Machine Learning, Linear Regression and Autoregressive Models","display_name":"Forecasting The Economic Growth of Sverdlovsk Region: A Comparative Analysis of Machine Learning, Linear Regression and Autoregressive Models","publication_year":2024,"publication_date":"2024-01-01","ids":{"openalex":"https://openalex.org/W4402395811","doi":"https://doi.org/10.15826/vestnik.2024.23.3.027"},"language":"en","primary_location":{"id":"doi:10.15826/vestnik.2024.23.3.027","doi":"https://doi.org/10.15826/vestnik.2024.23.3.027","is_oa":true,"landing_page_url":"https://doi.org/10.15826/vestnik.2024.23.3.027","pdf_url":"https://journalaer.ru/fileadmin/user_upload/site_15934/2024/05_Balungu_Kumar.pdf","source":{"id":"https://openalex.org/S4210225054","display_name":"Journal of Applied Economic Research","issn_l":"2712-7435","issn":["2712-7435"],"is_oa":true,"is_in_doaj":true,"is_core":false,"listed_in":["doaj","russia-white-list-1"],"host_organization":"https://openalex.org/P4310312767","host_organization_name":"Ural Federal University","host_organization_lineage":["https://openalex.org/P4310312767"],"host_organization_lineage_names":["Ural Federal University"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Applied Economic Research","raw_type":"journal-article"},"volume":null,"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"diamond","oa_url":"https://journalaer.ru/fileadmin/user_upload/site_15934/2024/05_Balungu_Kumar.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5094126317","display_name":"Daniel Musafiri Balungu","orcid":"https://orcid.org/0009-0001-5098-7603","observed_orcids":["https://orcid.org/0009-0001-5098-7603"]},"institutions":[{"id":"https://openalex.org/I130823665","display_name":"Ural Federal University","ror":"https://ror.org/00hs7dr46","country_code":"RU","type":"education","lineage":["https://openalex.org/I130823665"]}],"countries":["RU"],"is_corresponding":false,"raw_author_name":"D. M. Balungu","raw_affiliation_strings":["Ural Federal University named after the First President of Russia B. N. Yeltsin , Yekaterinburg , Russia"],"raw_orcid":"https://orcid.org/0009-0001-5098-7603","affiliations":[{"raw_affiliation_string":"Ural Federal University named after the First President of Russia B. N. Yeltsin , Yekaterinburg , Russia","institution_ids":["https://openalex.org/I130823665"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5103081160","display_name":"Avinash Kumar","orcid":"https://orcid.org/0000-0001-6929-1852","observed_orcids":["https://orcid.org/0000-0001-6929-1852"]},"institutions":[{"id":"https://openalex.org/I130823665","display_name":"Ural Federal University","ror":"https://ror.org/00hs7dr46","country_code":"RU","type":"education","lineage":["https://openalex.org/I130823665"]}],"countries":["RU"],"is_corresponding":false,"raw_author_name":"A. Kumar","raw_affiliation_strings":["Department of Big Data Analytics and Video Analysis Methods , Institute of Radioelectronics and Information Technologies , Ural Federal University named after the first President of Russia B. N. Yeltsin , Yekaterinburg , Russia ( 620002 , Yekaterinburg , Mira street , 19","Ural Federal University named after the First President of Russia B. N. Yeltsin , Yekaterinburg , Russia"],"raw_orcid":"https://orcid.org/0000-0001-6929-1852","affiliations":[{"raw_affiliation_string":"Department of Big Data Analytics and Video Analysis Methods , Institute of Radioelectronics and Information Technologies , Ural Federal University named after the first President of Russia B. N. Yeltsin , Yekaterinburg , Russia ( 620002 , Yekaterinburg , Mira street , 19","institution_ids":["https://openalex.org/I130823665"]},{"raw_affiliation_string":"Ural Federal University named after the First President of Russia B. N. Yeltsin , Yekaterinburg , Russia","institution_ids":["https://openalex.org/I130823665"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I130823665"],"apc_list":null,"apc_paid":null,"fwci":3.3349,"has_fulltext":true,"cited_by_count":11,"citation_normalized_percentile":{"value":0.92348687,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":96,"max":99},"biblio":{"volume":"23","issue":"3","first_page":"674","last_page":"695"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11918","display_name":"Forecasting Techniques and Applications","score":0.9961000084877014,"subfield":{"id":"https://openalex.org/subfields/1803","display_name":"Management Science and Operations Research"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},"topics":[{"id":"https://openalex.org/T11918","display_name":"Forecasting Techniques and Applications","score":0.9961000084877014,"subfield":{"id":"https://openalex.org/subfields/1803","display_name":"Management Science and Operations Research"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T11326","display_name":"Stock Market Forecasting Methods","score":0.0020000000949949026,"subfield":{"id":"https://openalex.org/subfields/1803","display_name":"Management Science and Operations Research"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T12667","display_name":"Economic and Technological Developments in Russia","score":0.0010000000474974513,"subfield":{"id":"https://openalex.org/subfields/3303","display_name":"Development"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/economic-growth-forecasting","display_name":"economic growth forecasting","score":0.9229999780654907},{"id":"https://openalex.org/keywords/regional-gross-domestic-product","display_name":"regional gross domestic product","score":0.8759999871253967},{"id":"https://openalex.org/keywords/sverdlovsk-oblast","display_name":"Sverdlovsk Oblast","score":0.9940000176429749},{"id":"https://openalex.org/keywords/random-forest","display_name":"random forest","score":0.8759999871253967},{"id":"https://openalex.org/keywords/sarimax","display_name":"SARIMAX","score":0.9750000238418579},{"id":"https://openalex.org/keywords/autoregressive-models","display_name":"autoregressive models","score":0.9470000267028809},{"id":"https://openalex.org/keywords/linear-regression","display_name":"linear regression","score":0.953000009059906},{"id":"https://openalex.org/keywords/machine-learning-forecasting","display_name":"machine learning forecasting","score":0.7250000238418579},{"id":"https://openalex.org/keywords/macroeconomic-indicators","display_name":"macroeconomic indicators","score":0.8619999885559082},{"id":"https://openalex.org/keywords/regional-economic-development","display_name":"regional economic development","score":0.6110000014305115}],"concepts":[{"id":"https://openalex.org/C159877910","wikidata":"https://www.wikidata.org/wiki/Q2202883","display_name":"Autoregressive model","level":2,"score":0.8051935434341431},{"id":"https://openalex.org/C149782125","wikidata":"https://www.wikidata.org/wiki/Q160039","display_name":"Econometrics","level":1,"score":0.6242461204528809},{"id":"https://openalex.org/C152877465","wikidata":"https://www.wikidata.org/wiki/Q208042","display_name":"Regression analysis","level":2,"score":0.5293957591056824},{"id":"https://openalex.org/C48921125","wikidata":"https://www.wikidata.org/wiki/Q10861030","display_name":"Linear regression","level":2,"score":0.5209394693374634},{"id":"https://openalex.org/C24338571","wikidata":"https://www.wikidata.org/wiki/Q2566298","display_name":"Autoregressive integrated moving average","level":3,"score":0.4659501016139984},{"id":"https://openalex.org/C83546350","wikidata":"https://www.wikidata.org/wiki/Q1139051","display_name":"Regression","level":2,"score":0.4320516884326935},{"id":"https://openalex.org/C151406439","wikidata":"https://www.wikidata.org/wiki/Q186588","display_name":"Time series","level":2,"score":0.4156121015548706},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.3922361135482788},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.38127899169921875},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.29067736864089966},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2811952829360962},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.2561897933483124}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.15826/vestnik.2024.23.3.027","doi":"https://doi.org/10.15826/vestnik.2024.23.3.027","is_oa":true,"landing_page_url":"https://doi.org/10.15826/vestnik.2024.23.3.027","pdf_url":"https://journalaer.ru/fileadmin/user_upload/site_15934/2024/05_Balungu_Kumar.pdf","source":{"id":"https://openalex.org/S4210225054","display_name":"Journal of Applied Economic Research","issn_l":"2712-7435","issn":["2712-7435"],"is_oa":true,"is_in_doaj":true,"is_core":false,"listed_in":["doaj","russia-white-list-1"],"host_organization":"https://openalex.org/P4310312767","host_organization_name":"Ural Federal University","host_organization_lineage":["https://openalex.org/P4310312767"],"host_organization_lineage_names":["Ural Federal University"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Applied Economic Research","raw_type":"journal-article"},{"id":"pmh:oai:elar.urfu.ru:10995/148443","doi":null,"is_oa":true,"landing_page_url":"https://journalaer.ru/en/archive/journal/302/article/2748/","pdf_url":null,"source":{"id":"https://openalex.org/S4306401523","display_name":"Electronic scientific archive of UrFU (Ural Federal University)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I130823665","host_organization_name":"Ural Federal University","host_organization_lineage":["https://openalex.org/I130823665"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":null,"raw_type":"info:eu-repo/semantics/article"},{"id":"pmh:oai:RePEc:aiy:jnjaer:v:23:y:2024:i:3:p:674-695","doi":null,"is_oa":false,"landing_page_url":"https://journalaer.ru//fileadmin/user_upload/site_15934/2024/05_Balungu_Kumar.pdf","pdf_url":"https://journalaer.ru//fileadmin/user_upload/site_15934/2024/05_Balungu_Kumar.pdf","source":{"id":"https://openalex.org/S4306401271","display_name":"RePEc: Research Papers in Economics","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I77793887","host_organization_name":"Federal Reserve Bank of St. Louis","host_organization_lineage":["https://openalex.org/I77793887"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"article"}],"best_oa_location":{"id":"doi:10.15826/vestnik.2024.23.3.027","doi":"https://doi.org/10.15826/vestnik.2024.23.3.027","is_oa":true,"landing_page_url":"https://doi.org/10.15826/vestnik.2024.23.3.027","pdf_url":"https://journalaer.ru/fileadmin/user_upload/site_15934/2024/05_Balungu_Kumar.pdf","source":{"id":"https://openalex.org/S4210225054","display_name":"Journal of Applied Economic Research","issn_l":"2712-7435","issn":["2712-7435"],"is_oa":true,"is_in_doaj":true,"is_core":false,"listed_in":["doaj","russia-white-list-1"],"host_organization":"https://openalex.org/P4310312767","host_organization_name":"Ural Federal University","host_organization_lineage":["https://openalex.org/P4310312767"],"host_organization_lineage_names":["Ural Federal University"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Applied Economic Research","raw_type":"journal-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/8","display_name":"Decent work and economic growth","score":0.6452000141143799},{"id":"https://metadata.un.org/sdg/9","display_name":"Industry, innovation and infrastructure","score":0.428600013256073}],"study_designs":[],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4402395811.pdf","grobid_xml":"https://content.openalex.org/works/W4402395811.grobid-xml"},"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W2358302315","https://openalex.org/W4412822305","https://openalex.org/W3092453270","https://openalex.org/W4405376177","https://openalex.org/W6929158793","https://openalex.org/W4415104213","https://openalex.org/W4401450603","https://openalex.org/W7141779516","https://openalex.org/W4414617289","https://openalex.org/W7163645552"],"abstract_inverted_index":{"The":[0,65,104,156],"relevance":[1],"of":[2,45,58,67,75,83,86,99,152,159,166,192,205,217,234,239,251,264],"accurate":[3],"economic":[4,59,125,197,223,243,265,276],"forecasting":[5,77,172,198],"cannot":[6],"be":[7],"overstated":[8],"in":[9,16,79,90,123,171,196,210,221,242,255,272],"today's":[10],"rapidly":[11,274],"changing":[12],"global":[13],"economy.":[14],"Decision-makers":[15],"both":[17],"the":[18,43,56,73,81,84,87,96,116,144,163,167,177,189,202,215,231,237,246,260],"public":[19],"and":[20,37,137,248,262],"private":[21],"sectors":[22],"rely":[23],"heavily":[24],"on":[25,95,236],"reliable":[26],"forecasts":[27,60],"to":[28,54,71,118,142,176,230],"make":[29],"informed":[30,270],"decisions":[31],"about":[32],"resource":[33],"allocation,":[34],"investment":[35],"strategies,":[36],"policy":[38],"development.":[39],"In":[40],"this":[41,68,108,160,227],"context,":[42],"importance":[44],"leveraging":[46,128],"advanced":[47,207],"analytical":[48,208],"techniques,":[49],"such":[50],"as":[51],"machine":[52,101,112,193,218],"learning,":[53],"improve":[55],"accuracy":[57,261],"has":[61],"become":[62],"increasingly":[63],"apparent.":[64],"purpose":[66],"study":[69,109,161,228],"is":[70,110],"explore":[72],"use":[74],"different":[76,153],"models":[78,114,122,220],"predicting":[80,124,222],"dynamics":[82],"GRP":[85,135,173],"Sverdlovsk":[88],"region":[89],"Russia,":[91],"with":[92],"a":[93,129,148,273],"focus":[94],"potential":[97,117,203],"benefits":[98,204],"integrating":[100],"learning":[102,113,194,219],"techniques.":[103],"central":[105],"hypothesis":[106],"underlying":[107],"that":[111,132],"have":[115],"outperform":[119],"traditional":[120,178],"autoregressive":[121],"growth.":[126],"By":[127,213],"rich":[130],"dataset":[131],"includes":[133],"yearly":[134],"data":[136],"macroeconomic":[138],"indicators":[139,224],"from":[140],"2005":[141],"2022,":[143],"research":[145],"procedure":[146],"involved":[147],"comprehensive":[149],"comparative":[150],"analysis":[151],"modeling":[154],"approaches.":[155],"main":[157],"findings":[158,253],"highlight":[162],"superior":[164],"performance":[165],"random":[168],"forest":[169],"model":[170],"growth":[174],"compared":[175],"SARIMAX":[179],"model.":[180],"These":[181],"results":[182],"not":[183],"only":[184],"provide":[185],"valuable":[186],"insights":[187],"into":[188],"predictive":[190],"power":[191],"algorithms":[195],"but":[199],"also":[200],"underscore":[201],"adopting":[206],"techniques":[209],"decision-making":[211,271],"processes.":[212],"demonstrating":[214],"superiority":[216],"like":[225],"GRP,":[226],"contributes":[229],"growing":[232],"body":[233],"literature":[235],"application":[238],"data-driven":[240],"approaches":[241],"analysis.":[244],"Ultimately,":[245],"theoretical":[247],"practical":[249],"significance":[250],"these":[252],"lies":[254],"their":[256],"implications":[257],"for":[258],"improving":[259],"reliability":[263],"forecasts,":[266],"thereby":[267],"enabling":[268],"more":[269],"evolving":[275],"landscape.":[277]},"counts_by_year":[{"year":2026,"cited_by_count":8},{"year":2025,"cited_by_count":3}],"updated_date":"2026-10-30T12:39:25.321706","created_date":"2024-09-11T00:00:00"}