Econometrics and econometric modeling in Excel and R

2020 ◽  
Author(s):  
Lyudmila Babeshko ◽  
Irina Orlova
Keyword(s):  
Time Series ◽  
Stationary Time Series ◽  
Economic Research ◽  
Federal State ◽  
Practical Implementation ◽  
Time Series Models ◽  
Econometric Modeling ◽  
Software Environment ◽  
Multidimensional Time Series ◽  
State Educational

The textbook includes topics of modern econometrics, often used in economic research. Some aspects of multiple regression models related to the problem of multicollinearity and models with a discrete dependent variable are considered, including methods for their estimation, analysis, and application. A significant place is given to the analysis of models of one-dimensional and multidimensional time series. Modern ideas about the deterministic and stochastic nature of the trend are considered. Methods of statistical identification of the trend type are studied. Attention is paid to the evaluation, analysis, and practical implementation of Box — Jenkins stationary time series models, as well as multidimensional time series models: vector autoregressive models and vector error correction models. It includes basic econometric models for panel data that have been widely used in recent decades, as well as formal tests for selecting models based on their hierarchical structure. Each section provides examples of evaluating, analyzing, and testing models in the R software environment. Meets the requirements of the Federal state educational standards of higher education of the latest generation. It is addressed to master's students studying in the Field of Economics, the curriculum of which includes the disciplines Econometrics (advanced course)", "Econometric modeling", "Econometric research", and graduate students."

Econometrics and econometric modeling

2021 ◽  
Author(s):  
Lyudmila Babeshko ◽  
Mihail Bich ◽  
Irina Orlova
Keyword(s):  
Regression Models ◽  
Nonlinear Models ◽  
Federal State ◽  
Econometric Modeling ◽  
Software Environment ◽  
R Software ◽  
Wide Range ◽  
Multiple Regression Models ◽  
State Educational ◽  
Lag Structure

The textbook covers a wide range of issues related to econometric modeling. Regression models are the core of econometric modeling, so the issues of their evaluation, testing of assumptions, adjustment and verification are given a significant place. Various aspects of multiple regression models are included: multicollinearity, dummy variables, and lag structure of variables. Methods of linearization and estimation of nonlinear models are considered. An apparatus for evaluating systems of simultaneous and apparently unrelated equations is presented. Attention is paid to time series models. Detailed solutions of the examples in Excel and the R software environment are included. Meets the requirements of the federal state educational standards of higher education of the latest generation. For undergraduate and graduate students studying in the field of "Economics", the curriculum of which includes the disciplines "Econometrics"," Econometric Modeling","Econometric research".

scholarly journals Advantages Of A Time Series Analysis Using Wavelet Transform As Compared With A Fourier Analysis

2015 ◽  
Vol 23 (2) ◽  
pp. 30-36 ◽  
Author(s):  
Patrik Sleziak ◽  
Kamila Hlavčová ◽  
Ján Szolgay
Keyword(s):  
Time Series ◽  
Wavelet Transform ◽  
Time Series Analysis ◽  
Fourier Analysis ◽  
Stationary Time Series ◽  
Precipitation Time Series ◽  
Software Environment ◽  
R Software ◽  
Series Analysis ◽  
Average Annual Precipitation

Abstract The paper presents an analysis of changes in the structure of the average annual discharges, average annual air temperature, and average annual precipitation time series in Slovakia. Three time series with lengths of observation from 1961 to 2006 were analyzed. An introduction to spectral analysis with Fourier analysis (FA) is given. This method is used to determine significant periods of a time series. Later in this article a description of a wavelet transform (WT) is reviewed. This method is able to work with non-stationary time series and detect when significant periods are presented. Subsequently, models for the detection of potential changes in the structure of the time series analyzed were created with the aim of capturing changes in the cyclical components and the multiannual variability of the time series selected for Slovakia. Finally, some of the comparisons of the time series analyzed are discussed. The aim of the paper is to show the advantages of time series analysis using WT compared with FT. The results were processed in the R software environment.

scholarly journals The technology of organising the search activity of students of a technical university for the analysis of solutions to applied mathematical problems

2021 ◽  
Vol 27 (3) ◽  
pp. 189-194
Author(s):  
Nadezhda V. Sycheva ◽  
Alina O. Aleynikova
Keyword(s):  
Modern Society ◽  
Point Of View ◽  
Federal State ◽  
Practical Implementation ◽  
Search Activity ◽  
Mathematical Problems ◽  
Personal Qualities ◽  
Three Stages ◽  
Technical University ◽  
State Educational

The changes taking place in modern society and production naturally have an impact on the education system, making new requirements for it, which are associated not only with the professional qualities of a university graduate, but also with personal ones. These requirements are fixed in the federal state educational standards of higher education in the form of universal and professional competences. One of the directions that will contribute to the formation of personal qualities of a graduate is related to the training of students in search activities. We consider the issues of organising the search activity of students of a technical university in the process of studying higher mathematics. To do this, we have developed a technology for organising students' search activity based on the analysis of solutions to applied mathematical problems. We have identified three stages in the developed technology – preparatory, basic, and final. The goal of each stage is formulated both from the position of the student and from the position of the pedagogue. Also in the article we show an example of the practical implementation of the developed technology of organising the search activity of students of a technical university for the analysis of solutions to applied mathematical problems, which are reduced to calculating a certain integral. The proposed technology of organising students' search activities contributes to the development of their communication skills – students gain experience in preparing a report, presentation, public speaking, learn to answer additional questions, defend and argue their point of view.

scholarly journals Confidence Regions for Parameters in Stationary Time Series Models With Gaussian Noise

2022 ◽  
Vol 9 ◽  
Author(s):  
Xiuzhen Zhang ◽  
Riquan Zhang ◽  
Zhiping Lu
Keyword(s):  
Time Series ◽  
Empirical Likelihood ◽  
Long Memory ◽  
Score Function ◽  
Real Data ◽  
Confidence Regions ◽  
Stationary Time Series ◽  
Time Series Models ◽  
Finite Sample ◽  
Memory Time

This article develops two new empirical likelihood methods for long-memory time series models based on adjusted empirical likelihood and mean empirical likelihood. By application of Whittle likelihood, one obtains a score function that can be viewed as the estimating equation of the parameters of the long-memory time series model. An empirical likelihood ratio is obtained which is shown to be asymptotically chi-square distributed. It can be used to construct confidence regions. By adding pseudo samples, we simultaneously eliminate the non-definition of the original empirical likelihood and enhance the coverage probability. Finite sample properties of the empirical likelihood confidence regions are explored through Monte Carlo simulation, and some real data applications are carried out.

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