Modeling And Advanced Techniques In Modern Economics PDF
Preview Modeling And Advanced Techniques In Modern Economics
Modeling Advanced and Techniques Modern in Economics B1948 Governing Asia TTTThhhhiiiissss ppppaaaaggggeeee iiiinnnntttteeeennnnttttiiiioooonnnnaaaallllllllyyyy lllleeeefffftttt bbbbllllaaaannnnkkkk BB11994488__11--AAookkii..iinndddd 66 99//2222//22001144 44::2244::5577 PPMM Modeling Advanced and Techniques Modern in Economics Editors Çağdaş Hakan Aladağ Hacettepe University, Turkey Nihan Potas Ankara Hacı Bayram Veli University, Turkey World Scientific NEW JERSEY • LONDON • SINGAPORE • BEIJING • SHANGHAI • HONG KONG • TAIPEI • CHENNAI • TOKYO Published by World Scientific Publishing Europe Ltd. 57 Shelton Street, Covent Garden, London WC2H 9HE Head office: 5 Toh Tuck Link, Singapore 596224 USA office: 27 Warren Street, Suite 401-402, Hackensack, NJ 07601 Library of Congress Cataloging-in-Publication Data Names: Aladağ, Çağdaş Hakan, editor. | Potas, Nihan, editor. Title: Modeling and advanced techniques in modern economics / editors, Çağdaş Hakan Aladağ, Hacettepe University, Turkey, Nihan Potas, Ankara Hacı Bayram Veli University, Turkey. Description: New Jersey : World Scientific, [2022] | Includes bibliographical references and index. Identifiers: LCCN 2022000600 | ISBN 9781800611740 (hardcover) | ISBN 9781800611757 (ebook) | ISBN 9781800611764 (ebook other) Subjects: LCSH: Econometric models. | Economics--Mathematical models. Classification: LCC HB141 .M586 2022 | DDC 330.01/5195--dc23/eng/20220118 LC record available at https://lccn.loc.gov/2022000600 British Library Cataloguing-in-Publication Data A catalogue record for this book is available from the British Library. Copyright © 2022 by World Scientific Publishing Europe Ltd. All rights reserved. This book, or parts thereof, may not be reproduced in any form or by any means, electronic or mechanical, including photocopying, recording or any information storage and retrieval system now known or to be invented, without written permission from the Publisher. For photocopying of material in this volume, please pay a copying fee through the Copyright Clearance Center, Inc., 222 Rosewood Drive, Danvers, MA 01923, USA. In this case permission to photocopy is not required from the publisher. For any available supplementary material, please visit https://www.worldscientific.com/worldscibooks/10.1142/Q0346#t=suppl Desk Editor: Soundararajan Raghuraman Typeset by Stallion Press Email: [email protected] Printed in Singapore SSoouunnddaarraarraajjaann -- QQ00334466 -- MMooddeelliinngg aanndd AAddvvaanncceedd TTeecchhnniiqquueess..iinndddd 11 1144//77//22002222 99::5599::0044 aamm July15,2022 6:50 ModelingandAdvancedTechniques... 9inx6in b4501-fm pagev To my mother Rezzan Alada˘g and my father Hikmet Feridun Alada˘g C¸a˘gda¸s Hakan Alada˘g To my mother Prof. Dr. S¸efika S¸ule Er¸cetin, my sister Dr. S¸uay Nilhan A¸cıkalın and my beloved children Mihri and Uraz for their eternal love Nihan Potas v B1948 Governing Asia TTTThhhhiiiissss ppppaaaaggggeeee iiiinnnntttteeeennnnttttiiiioooonnnnaaaallllllllyyyy lllleeeefffftttt bbbbllllaaaannnnkkkk BB11994488__11--AAookkii..iinndddd 66 99//2222//22001144 44::2244::5577 PPMM July15,2022 6:50 ModelingandAdvancedTechniques... 9inx6in b4501-fm pagevii (cid:2)c 2022 World Scientific Publishing Europe Ltd. https://doi.org/10.1142/9781800611757 fmatter Preface While the global economy stumbles under a pandemic crisis, under- standing macroeconomic variables has become more vital not only for the governments and economy bureaucracies but also for firms and individuals. Thus, each of us needs to understand the impact of exogenous shocks on the global economy. Statistical thinking is one of the leading ways of improvement in this thinking. For statistical thinking, data that can be worked on and then, in order to make clear, understandable and explanatory results, statistical inference are required. The way to shape and see the future is to collect data correctly, analyze it correctly and interpret the results correctly. There are two main elements at the base of this approach. These are Statistics and Economics. The aim of this book, briefly, is to introduce new approaches that can be used to shape and forecast the future by combining the two disciplines mentioned. In this day and age, data is a vital asset for any organization, regardless of industry or size. The world is built upon data. It is not only data but also having the right kind of knowledge is critically important today. In order to obtain the right kind of knowledge from data, the process of analyzing data is very crucial for indi- viduals, organizations or governments. This is why the concept of Data Science is so popular today. Nowadays, many researchers and practitioners from various fields are studying advanced data analy- sis techniques. One of these fields is Economics. For example, time series analysis is very important for economics. Time series, which vii July15,2022 6:50 ModelingandAdvancedTechniques... 9inx6in b4501-fm pageviii viii Modeling and Advanced Techniques in Modern Economics is a collection of data points collected at constant time intervals, is one of the most important data types. People have tried to forecast time series by different methods for a long time. Forecasting is so essential since the prediction of future events is a critical input for many types of planning decision-making processes, with real-world applications in all areas. With the development of technology and algorithms, time series forecasting approaches are developing. Thus, it is possible to reach more accurate predictions of the future by using advanced forecasting approaches. In this manner, some chap- tersofthisbookareintendedtobeavaluablesourceofrecentknowl- edge on advanced time series forecasting techniques. These chapters include applications of efficient, recent forecasting approaches. The readers can also findusefulinformation on advanced time series fore- casting techniques, such as artificial neural networks, deep learning, machine learning and chaotic time series. In addition to these time series applications, some chapters introduce some other recent data analysis methods such as fiducialmethod,a novel approach based on inverseGaussiandistributionandweightedsuperpositionattraction– repulsion algorithm. Trends in econometric analysis, especially in financial time series analysis, are moving toward artificial intelligence. Machine learn- ing becomes handier when dealing with complex structures as their computational capacities increase. Moreover, in classical time series analysis, univariate or multivariate, linear time series methods may not capture these complex structures. Nowadays, deep neural net- works are a popular tool in forecasting and classification. Neural networks are flexible and can be used in both regression and clas- sification. They have good performance in predicting nonlinear and non-stationary time series. The learning algorithms used in financial time series or econometrics are not restricted to neural networks. In classification support vector machines, tree type algorithms and k-nearest neighbors are some of the most popular algorithms. In the regression part support vector regression, ridge regression, Elastic- Net regression and Lasso regression can be mentioned as some of the popular algorithms. In light of these, in some chapters of this book, the authors provide information on econometric and financial mod- els as well as commonly used financial and economic variables and mention sources of relevant data. The readers can also find useful information about the financial and econometric models, stochastic July15,2022 6:50 ModelingandAdvancedTechniques... 9inx6in b4501-fm pageix Preface ix financial models, machine learning and application of the models to financial and macroeconomic data. Readers can also find useful information about the effect of the economy through theoretical, comparative and applied studies on agent-based models, nonlinear economic systems, evolutionary eco- nomics,econophysics,chaostheory,fractalanalysis,neuroeconomics, fuzzy systems and network theory. Economic agents, be they banks, firms, households, consumers or investors, act with strategic behavior and foresight by considering outcomes that might result from behavior they might undertake. Furthermore,theycontinuallyadjusttheirmarketoperations,buying decisions,pricesandforecaststothesituationsthattheseoperations, decisions, prices and forecasts together create. These topics add a layer of complexity to economics not found in the natural sciences. The editors would also like to express their sincere thanks to all authors for their valuable contributions. We believe that this book is a very useful resource for the readers.
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