The Deadline for Submission of the Chapters to the Project is March 15th, 2022.
Our books are published by the publishers that are indexed in the SSCI, Scopus and Web of Science.
BEYOND THE MAINSTREAM ECONOMETRIC MODELS
In recent years, there is an increasing polemic about the accuracy of the mainstream econometric models. The main objective of the econometric models is to analyze an economic issue within the frame of a quantitative model and to make estimations. However, to make the analyses under many assumptions and to disregard a lot of factors keep the models apart from the real world. Most of the time, the mainstream econometrists are being criticized since they somehow fit the data to the model.
In today’s technologically advanced world, every agent in the economy is connected, which create a big network. This situation enables to reach a wide range of data, called big data. Traditional methods are not adequate to build realistic models based on big data.
This book project, entitled “Beyond the Mainstream Econometric Models”, aims to bring studies that particularly employ the new econometric models based on Machine Learning, Agent Based Computational Models, Neural Networks, Prediction Methods, Lasso and Ridge Regressions in order to achieve more accurate economic outcomes. Accordingly, there will be three sections in the book. In the first section the studies on microeconomics applications, in the second section the studies on macroeconomics applications, and finally, in the last section financial sector applications will be considered.
Asst. Prof. Hale Kırer Silva Lecuna
Main Themes of the Book Project
- Machine Learning
- Deep Learning
- Agent-Based Computational Models
- New Econometric Models for Big Data
- Neural Networks
- Prediction Methods
- K-Nearest Neighbor regression (KNN)
- Radial Basis Functions (RBF)
- Multi-Layer Perceptron (MLP)
- Bayesian Neural Network (BNN)
- Generalized Regression Neural Networks (GRNN)
- CART regression trees (CART)
- Support Vector Regression (SVR)
- Gaussian Processes (GP)
- Lasso Regression
- Ridge Regression
Recommended Topics for Applications
- Economic Decision-Making
- Market Structure
- Energy Economics
- Policy Recommendations
- Business Cycles
- Recession Forecasting
- Forecasting of Growth Rate and Unemployment Rates
- Asset Pricing
- Stock Market Simulations
- Risk Analysis
The target audiences of this book are academics, scholars and researchers who are interested in heterodox economic analyses.