[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-123852-en":3,"doc-seo-123852-105":30,"detail-sidebar-cat-0-en-105":91},{"code":4,"msg":5,"data":6},0,"success",{"doc_id":7,"user_id":8,"nickname":9,"user_avatar":10,"doc_module":4,"category_id":11,"category_name":12,"doc_title":13,"doc_description":14,"doc_content":15,"file_id":16,"file_url":17,"file_type":18,"file_size":19,"view_count":4,"is_deleted":4,"is_public":20,"is_downloadable":20,"audit_status":20,"page_count":21,"language":22,"language_code":23,"site_id":24,"html_lang":23,"table_of_contents":25,"faqs":26,"seo_title":27,"seo_description":14,"update_tm":28,"read_time":29},123852,549758252649,"Ivy","https://ap-avatar.wpscdn.com/avatar/8000253669c5317157?_k=1778319167496531819",8,"Research & Report","Application of machine learning methods in forecasting economic growth and inflation of Vietnam","Inflation and economic growth are central indicators that shape macroeconomic stability and policy decisions. This study builds forecasting models for Vietnam’s economic growth and inflation by applying machine learning algorithms, including KNN and multi-layer perceptron (MLP), and compares their predictive accuracy with traditional approaches such as VAR and LASSO. Models are estimated using data from 1996 to 2021, and performance is evaluated using RMSE, MAE, and MSE. Results indicate the MLP-based forecasts achieve the highest accuracy across all metrics.","Electronic Journal of Applied Statistical Analysis EJASA, Electron. J. App. Stat. Anal.  \n[http://siba-ese.unisalento.it/index.php/ejasa/index](http://siba-ese.unisalento.it/index.php/ejasa/index)  \ne-ISSN: 2070-5948  \nDOI: 10.1285/i20705948v17n1p191  \nApplication of machine learning methods in forecasting economic growth and inflation of Vietnam  \nBy Tran, Le  \n15 March 2024  \nThis work is copyrighted by Universit`a del Salento, and is licensed under a Creative Commons Attribuzione-Non commerciale-Non opere derivate 3 .0 Italia License.  \nFor more information see:  \n[http://creativecommons.org/licenses/by-nc-nd/3.0/it/](http://creativecommons.org/licenses/by-nc-nd/3.0/it/)  \nElectronic Journal of Applied Statistical Analysis Vol. 17, Issue 01, March 2024, 191-205  \nDOI: 10.1285/i20705948v17n1p191  \nApplication of machine learning methods in forecasting economic growth and inflation of Vietnam  \nPhuoc Tran a and Hoang Anh Le * b  \na Faculty of Finance and Accounting, Ho Chi Minh City University of Food Industry, 140 Le  \nTrong Tan street, Tan Phu District, Ho Chi Minh city, Vietnam  \nb Institute for Research Science and Banking Technology, Ho Chi Minh University of Banking,  \n36 Ton That Dam street, District 1, Ho Chi Minh city, Vietnam  \n15 March 2024  \nInflation and economic growth are two crucial indicators for any country in the world. In light of the importance of these two economic indicators, the forecast of economic growth and inflation has become a significant topic that national governments have traditionally prioritized. This study aims to apply popular machine learning algorithms such as KNN and MLP to build models for predicting economic growth and inflation. We also provide a comparison of the predictive accuracy between these machine learning algorithmsand traditional forecasting models such as VAR and LASSO. Specifically, we employ techniques such as VAR, LASSO, KNN, and multi-layer perceptron (MLP) to construct forecasting models for Vietnam’s economic growth and inflation using data collected from 1996 to 2021 . The accuracy of the models is assessed using three indices: RMSE, MAE, and MSE. The empirical results show that according to all three indicators, RMSE, MAE, and MSE, the forecasting models of economic growth and inflation by the MLP model are the most accurate. Based on the results, we have concluded that the MLP model is a valuable tool for future forecasting because it can describe the nonlinear relationships between variables in the model and visually map them.  \nkeywords: VAR, LASSO, KNN, MLP.  \n* Corresponding authors: anhlh [vnc@hub.edu.vn](vnc@hub.edu.vn)  \n➞Universit`a del Salento ISSN: 2070-5948  \n[http://siba-ese.unisalento.it/index.php/ejasa/index](http://siba-ese.unisalento.it/index.php/ejasa/index)  \n192 Tran, Le  \n1 Introduction  \nEconomic growth and inflation are two critical indicators of any economy in the world. Economic growth reflects the development of a country, helping to enhance its status and to attract investment into that country. Economic growth has an impact on implementing social policies, changing the structure of economic sectors, forming new industries, and generating a large number of new employment for locals. Contrary to economic growth, high inflation causes macroeconomic instability by affecting consumption, investment, saving, and many other aspects of an economy. Furthermore, high inflation in a country reduces public trust in that country’s national currency. Although they are considered two macroeconomic indicators that deeply affect socio-economic life, inflation and economic growth have a connection. This relationship has been indicated in many theories and empirical studies. Specifically, Keynes’ theory shows that countries have to accept a certain inflation level to boost the economy in the short term. However, this positive relationship does not exist forever. When inflation exceeds a threshold, economic growth decreases (Stockman, 1981; Ocran and Biekpe","cbCaiuEh8KzWwD4D","https://ap.wps.com/l/cbCaiuEh8KzWwD4D","pdf",1099159,1,16,"English","en",105,"# Introduction\n## Background and importance\n## Relationship between inflation and growth\n## Forecasting approaches and motivation\n# Methods and evaluation","[{\"question\":\"What machine learning methods are used to forecast Vietnam’s economic growth and inflation?\",\"answer\":\"The study applies KNN and a multi-layer perceptron (MLP) to construct forecasting models.\"},{\"question\":\"Which traditional forecasting models are compared against machine learning methods?\",\"answer\":\"The comparison includes VAR and LASSO as traditional forecasting models.\"},{\"question\":\"How is forecasting accuracy evaluated in the study?\",\"answer\":\"Accuracy is assessed using RMSE, MAE, and MSE on data spanning 1996 to 2021.\"}]","Application of machine learning methods in forecasting economic growth and inflation of Vietnam | PDF",1785818894,40,{"code":4,"msg":31,"data":32},"ok",{"site_id":24,"language":23,"slug":33,"title":13,"keywords":34,"description":14,"schema_data":35,"social_meta":86,"head_meta":88,"extra_data":90,"updated_unix":28},"application-of-machine-learning-methods-in-forecasting-economic-growth-and-inflation-of-vietnam","",{"@graph":36,"@context":85},[37,54,68],{"@type":38,"itemListElement":39},"BreadcrumbList",[40,44,48,51],{"item":41,"name":42,"@type":43,"position":20},"https://docshare.wps.com","Home","ListItem",{"item":45,"name":46,"@type":43,"position":47},"https://docshare.wps.com/document/","Document",2,{"item":49,"name":12,"@type":43,"position":50},"https://docshare.wps.com/document/research-report/",3,{"item":52,"name":13,"@type":43,"position":53},"https://docshare.wps.com/document/application-of-machine-learning-methods-in-forecasting-economic-growth-and-inflation-of-vietnam/123852/",4,{"url":52,"name":13,"@type":55,"author":56,"headline":13,"publisher":58,"fileFormat":61,"inLanguage":23,"description":14,"dateModified":62,"datePublished":62,"encodingFormat":61,"isAccessibleForFree":63,"interactionStatistic":64},"DigitalDocument",{"name":9,"@type":57},"Person",{"url":41,"name":59,"@type":60},"DocShare","Organization","application/pdf","2026-08-04",true,{"@type":65,"interactionType":66,"userInteractionCount":4},"InteractionCounter",{"@type":67},"ViewAction",{"@type":69,"mainEntity":70},"FAQPage",[71,77,81],{"name":72,"@type":73,"acceptedAnswer":74},"What machine learning methods are used to forecast Vietnam’s economic growth and inflation?","Question",{"text":75,"@type":76},"The study applies KNN and a multi-layer perceptron (MLP) to construct forecasting models.","Answer",{"name":78,"@type":73,"acceptedAnswer":79},"Which traditional forecasting models are compared against machine learning methods?",{"text":80,"@type":76},"The comparison includes VAR and LASSO as traditional forecasting models.",{"name":82,"@type":73,"acceptedAnswer":83},"How is forecasting accuracy evaluated in the study?",{"text":84,"@type":76},"Accuracy is assessed using RMSE, MAE, and MSE on data spanning 1996 to 2021.","https://schema.org",{"og:url":52,"og:type":87,"og:title":13,"og:site_name":59,"og:description":14},"article",{"robots":89,"canonical":52},"index,follow",{"doc_id":7,"site_id":24},{"code":4,"msg":5,"data":92},[93,97,101,105,110,115,119,122,127,130,134],{"id":20,"doc_module":4,"doc_module_name":46,"category_name":94,"show_sort_weight":95,"slug":96},"Story & Novel",90,"story-novel",{"id":47,"doc_module":4,"doc_module_name":46,"category_name":98,"show_sort_weight":99,"slug":100},"Literature",80,"literature",{"id":53,"doc_module":4,"doc_module_name":46,"category_name":102,"show_sort_weight":103,"slug":104},"Exam",70,"exam",{"id":106,"doc_module":4,"doc_module_name":46,"category_name":107,"show_sort_weight":108,"slug":109},5,"Comic",60,"comic",{"id":111,"doc_module":4,"doc_module_name":46,"category_name":112,"show_sort_weight":113,"slug":114},6,"Technology",50,"technology",{"id":116,"doc_module":4,"doc_module_name":46,"category_name":117,"show_sort_weight":29,"slug":118},7,"Healthcare","healthcare",{"id":11,"doc_module":4,"doc_module_name":46,"category_name":12,"show_sort_weight":120,"slug":121},30,"research-report",{"id":123,"doc_module":4,"doc_module_name":46,"category_name":124,"show_sort_weight":125,"slug":126},9,"Religion & Spirituality",20,"religion-spirituality",{"id":125,"doc_module":4,"doc_module_name":46,"category_name":128,"show_sort_weight":125,"slug":129},"World Cup","world-cup",{"id":131,"doc_module":4,"doc_module_name":46,"category_name":132,"show_sort_weight":131,"slug":133},10,"Lifestyle","lifestyle",{"id":135,"doc_module":4,"doc_module_name":46,"category_name":136,"show_sort_weight":106,"slug":137},19,"General","general"]