Introduction to Computational Economics Using Fortran: A Comprehensive Guide

Introduction to Computational Economics Using Fortran

by Roberto Pedace

4.6 out of 5

Language	:	English
File size	:	17583 KB
Text-to-Speech	:	Enabled
Screen Reader	:	Supported
Enhanced typesetting	:	Enabled
Print length	:	585 pages
Lending	:	Enabled
X-Ray for textbooks	:	Enabled

FREE

Computational economics is a rapidly growing field that combines economic theory with computational methods to solve complex economic problems. Fortran is a powerful programming language that is widely used in scientific computing and is particularly well-suited for computational economics.

This guide provides a comprehensive to computational economics using Fortran. It covers essential concepts, numerical methods, simulation techniques, optimization algorithms, econometrics, data analysis, and machine learning applications.

Essential Concepts

The first part of this guide provides an overview of essential concepts in computational economics, including:

* The role of computation in economics * Different types of computational models * Numerical representation of economic data * Data structures and algorithms

Numerical Methods

The second part of this guide covers numerical methods for solving economic problems, including:

* Root finding * Linear algebra * Numerical integration * Differential equations * Optimization

Simulation Techniques

The third part of this guide introduces simulation techniques for modeling economic systems, including:

* Monte Carlo simulation * Agent-based modeling * Dynamic programming

Optimization Algorithms

The fourth part of this guide covers optimization algorithms for solving economic problems, including:

* Linear programming * Nonlinear programming * Integer programming * Heuristic algorithms

Econometrics

The fifth part of this guide provides an overview of econometrics, the branch of statistics that is concerned with the application of statistical methods to economic data. Topics covered include:

* Regression analysis * Time series analysis * Forecasting

Data Analysis

The sixth part of this guide covers data analysis techniques for exploring and visualizing economic data, including:

* Data visualization * Data cleaning * Data mining

Machine Learning Applications

The seventh part of this guide introduces machine learning applications in computational economics, including:

* Supervised learning * Unsupervised learning * Reinforcement learning

This guide provides a comprehensive to computational economics using Fortran. It covers essential concepts, numerical methods, simulation techniques, optimization algorithms, econometrics, data analysis, and machine learning applications. By following the steps outlined in this guide, you will be able to develop and implement computational models to solve complex economic problems.

Introduction to Computational Economics Using Fortran

by Roberto Pedace

4.6 out of 5

Language	:	English
File size	:	17583 KB
Text-to-Speech	:	Enabled
Screen Reader	:	Supported
Enhanced typesetting	:	Enabled
Print length	:	585 pages
Lending	:	Enabled
X-Ray for textbooks	:	Enabled

FREE