Phillips-Ouliaris Cointegration Test

In this short tutorial in Eviews, we would explain the basic steps of conduting Phillips-Ouliaris Cointegration Test. To run Phillips-Ouliaris Cointegration Test in Eviews, we will need to ender the data as dated frequency and panel structure. Theoretically, the Phillips-Ouliaris Cointegration Test can found well explained in P. C. B. Phillips and S. Ouliaris (1990): Asymptotic Properties of Residual Based Tests for Cointegration. Econometrica 58, 165–193 which can be downloaded here.

Phillips-Ouliaris Cointegration Test

To run Phillips-Ouliaris Cointegration Test in Eviews, open Eviews and follow the steps below:

The following video tutorial explains the above steps to help replication be more convenient. If you would like to learn more about Applied Econometrics Research using Eviews, check our private and instructor led courses here.

Econometric Models Selection

In this simple outline on the issue of commonly raised douts on how to select an economic model, I would like to sum the issue in this 300 words article. Econometric Models Selection is one key problem for all. The model selection is based on the type of data and type of variables. Here, we mention an order following which helps an econometric model strategy development for us. We assume to use Panel data to develop econometric model selection strategy. Initially, to determine the right set of models, the nature of data structure for the panel data follows like this: A. Check data structure. 1. if N>T, then follows B series of steps. 2. If T>N, then follow the steps in C series.

If we assume the panel data has N sufficiently greater than T, then simple panel data or instrumental/GMM models for panel data can be achieved using the following order. This helps in Econometric Models selection looking into the key steps of the econometric analysis of the given panel data.

For Case 1, follow these steps.
B1. The first stepOLS
B2. RE/FE
B3. Hausman
B4. Assumptions of RE or FE from B3.
B5. Endogeneity Tests
B6. Instrumental Regression
B7. GMM if seens dynamics/autocorrelation in B4.

If the data at hands is such that T is sufficiently larger than N, the panel time series structure will be evidenced and hence our econometric models selection strategy will follow the following procedures. The unit roots and cointegration is for panel time series data which are also sometimes considered as longer time panel data or longer panel data. In such cases, the time series properties in estimators are heavily observed and hence the steps to select an econometric models selection strategy will include these.
For Case 2, follow these steps
C1. Unit Root
C2. Cointegration
C3. VECM


ARDL and Unit Root Testing using Eviews

ARDL Cointegration using Eviews 9

To estimate ARDL using Eviews 9 on Time Series Data, first open the data file/workfile, Click on your DV, press control key on keyboard, now left click to select all your IVs one by one, once selected then right click on any selected variables and open these as Equations. Once you get the Methods window in Eviews, go the methodology selection from Estimation Setting near to bottom, select ARDL from the list and click Okay. Now you cans elect the lags of DV and IV and any other options for the the methods. You can click on the OK button to get your estimates.

Augmented Dickey Fuller Unit Root Test using Eviews

Augmented Dickey Fuller Unit Root Test using Eviews We can test a time series variable for Unit Root Test following Augmented Dickey Fuller Approach in Eviews following the steps outlined below. First of all open the Eviews workfile or the Excel data in Eviews, then right click on any of the variables we would like to test for unit root based on Augmented Dickey Fuller Approach and click on Open. The series opens in spreadsheet in Eviews. We can click on View in the left upper corner of the new spreadsheet window in Eviews. Then we can click on Unit Root Test in this list that pops down by clicking on View tab. This opens the dialogue box as shown in the inserted screenshot from Eviews itself, we can see that it has mainly four sections. Main section is related to selecting the test type. The Eviews produces unit root test results following 6 methods. We will select the Augmented Dickey Fuller as test type. The we will select either the Level, Difference or Second Difference. Next we can select either to include intercept or both of trend and intercept or none. On the right side of the same window, we can either ask Eviews to use lags automatically or we can insert manually the maximum lags into the model to base our unit root test on. Once we select everything as per our assumed approach to test a series for unit root using Augmented Dickey Fuller Approach, we can click on OK to get the test results.

Phillips Perron Unit Root Test using Eviews

Phillips Perron (PP) Unit Root Test using Eviews We can test a time series variable for Unit Root Test following Phillips Perron (PP) Approach in Eviews following the steps outlined below. First of all open the Eviews workfile or the Excel data in Eviews, then right click on any of the variables we would like to test for unit root based on Phillips Perron (PP) Approach and click on Open. The series opens in spreadsheet in Eviews. We can click on View in the left upper corner of the new spreadsheet window in Eviews. Then we can click on Unit Root Test in this list that pops down by clicking on View tab. This opens the dialogue box as shown in the inserted screenshot from Eviews itself, we can see that it has mainly four sections. Main section is related to selecting the test type. The Eviews produces unit root test results following 6 methods. We will select the Phillips Perron (PP) as test type. The we will select either the Level, Difference or Second Difference. Next we can select either to include intercept or both of trend and intercept or none. On the right side of the same window, we can either ask Eviews to use lags automatically or we can insert manually the maximum lags into the model to base our unit root test on. Once we select everything as per our assumed approach to test a series for unit root using Phillips Perron (PP) Approach, we can click on OK to get the test results.

KPSS Unit Root Test using Eviews

KPSS Unit Root Test using Eviews We can test a time series variable for Unit Root Test following Kwiatkowski-Phillips-Schmidt-Shin Approach in Eviews following the steps outlined below. First of all open the Eviews workfile or the Excel data in Eviews, then right click on any of the variables we would like to test for unit root based on KPSS Approach and click on Open. The series opens in spreadsheet in Eviews. We can click on View in the left upper corner of the new spreadsheet window in Eviews. Then we can click on Unit Root Test in this list that pops down by clicking on View tab. This opens the dialogue box as shown in the inserted screenshot from Eviews itself, we can see that it has mainly four sections. Main section is related to selecting the test type. The Eviews produces unit root test results following 6 methods. We will select the KPSS as test type. The we will select either the Level, Difference or Second Difference. Next we can select either to include intercept or both of trend and intercept or none. On the right side of the same window, we can either ask Eviews to use lags automatically or we can insert manually the maximum lags into the model to base our unit root test on. Once we select everything as per our assumed approach to test a series for unit root using KPSS Approach, we can click on OK to get the test results.

Ng-Perron Unit Root Test using Eviews

We can test a time series variable for Unit Root Test following Ng-Perron Approach in Eviews following the steps outlined below. First of all open the Eviews workfile or the Excel data in Eviews, then right click on any of the variables we would like to test for unit root based on Ng-Perron Approach and click on Open. The series opens in spreadsheet in Eviews. We can click on View in the left upper corner of the new spreadsheet window in Eviews. Then we can click on Unit Root Test in this list that pops down by clicking on View tab. This opens the dialogue box as shown in the inserted screenshot from Eviews itself, we can see that it has mainly four sections. Main section is related to selecting the test type. The Eviews produces unit root test results following 6 methods. We will select the Ng-Perron as test type. The we will select either the Level, Difference or Second Difference. Next we can select either to include intercept or both of trend and intercept or none. On the right side of the same window, we can either ask Eviews to use lags automatically or we can insert manually the maximum lags into the model to base our unit root test on. Once we select everything as per our assumed approach to test a series for unit root using Ng-Perron Approach, we can click on OK to get the test results.

List of Best Econometrics Books

Most of the times, we need to select a book to understand econometrics more easily. In the following, I have shared my personally recommended set of best books for econometrics which I have been reading frequently. These books on econometrics have helped me develop a strong understanding of some core issues in developing econometric skills for research and data analytics, both for academic and professional research for freelance projects.

Mostly Harmless Econometrics: An Empiricist's Companion
Mostly Harmless Econometrics: An Empiricist's Companion (Paperback)
by Joshua D. Angrist (shelved 11 times as econometrics)
Basic Econometrics 4th Economy Edition
Basic Econometrics 4th Economy Edition
by Damodar N. Gujarati (shelved 9 times as econometrics)
Introductory Econometrics: A Modern Approach
Introductory Econometrics: A Modern Approach (Hardcover)
by Jeffrey M. Wooldridge (shelved 8 times as econometrics)
Econometric Analysis
Econometric Analysis (Hardcover)
by William H. Greene (shelved 8 times as econometrics)
Econometrics
Econometrics (Hardcover)
by Fumio Hayashi (shelved 7 times as econometrics)
A Guide To Econometrics
A Guide To Econometrics (Paperback)
by Peter E. Kennedy (shelved 5 times as econometrics)
A Guide to Modern Econometrics
A Guide to Modern Econometrics (Paperback)
by Marno Verbeek (shelved 4 times as econometrics)
The Econometrics of Financial Markets
The Econometrics of Financial Markets (Hardcover)
by John Y. Campbell (shelved 4 times as econometrics)
Time Series Analysis
Time Series Analysis (Hardcover)
by James D. Hamilton
Econometric Analysis of Cross Section and Panel Data
Econometric Analysis of Cross Section and Panel Data (Hardcover)
by Jeffrey M. Wooldridge (shelved 4 times as econometrics)
Applied Time Series Econometrics
Applied Time Series Econometrics (Paperback)
by Helmut Luetkepohl (Editor) (shelved 3 times as econometrics)
Bayesian Econometrics
Bayesian Econometrics (Paperback)
by Gary L. Koop (shelved 3 times as econometrics)
Advanced Econometrics
Advanced Econometrics (Hardcover)
by Takeshi Amemiya (shelved 3 times as econometrics)
Schaum's Outline of Statistics and Econometrics
Schaum's Outline of Statistics and Econometrics (Paperback)
by Dominick Salvatore (shelved 3 times as econometrics)
A Course in Econometrics
A Course in Econometrics (Hardcover)
by Arthur S. Goldberger (shelved 3 times as econometrics)
Econometric Theory and Methods
Econometric Theory and Methods (Hardcover)
by James G. MacKinnon (shelved 3 times as econometrics)
Introduction to Econometrics
Introduction to Econometrics (Paperback)
by Christopher Dougherty (shelved 3 times as econometrics)
Microeconometrics Using Stata
Microeconometrics Using Stata (Paperback)
by A. Colin Cameron (shelved 2 times as econometrics)
Computational Methods in Statistics and Econometrics
Computational Methods in Statistics and Econometrics (Hardcover)
by Hisashi Tanizaki (shelved 2 times as econometrics)
Nonparametric Econometrics
Nonparametric Econometrics (Paperback)
by Adrian Pagan (shelved 2 times as econometrics)
Econometric Methods
Econometric Methods (Hardcover)
by Jack Johnston (shelved 2 times as econometrics)
Introduction to Modern Bayesian Econometrics
Introduction to Modern Bayesian Econometrics (Hardcover)
by Tony Lancaster (shelved 2 times as econometrics)
Econometrics
Econometrics (Paperback)
by Badi H. Baltagi (shelved 2 times as econometrics)
Using Eviews for Principles of Econometrics
Using Eviews for Principles of Econometrics (Paperback)
by R. Carter Hill (shelved 2 times as econometrics)
Limited-Dependent and Qualitative Variables in Econometrics
Limited-Dependent and Qualitative Variables in Econometrics (Paperback)
by G.S. Maddala (shelved 2 times as econometrics)
The Practice of Econometrics: Classic and Contemporary
The Practice of Econometrics: Classic and Contemporary (Hardcover)
by Ernst R. Berndt (shelved 2 times as econometrics)
Financial Econometrics: Problems, Models, and Methods
Financial Econometrics: Problems, Models, and Methods (Hardcover)
by Christian Gourieroux (shelved 2 times as econometrics)
Estimation and Inference in Econometrics
Estimation and Inference in Econometrics (Hardcover)
by Russell Davidson (shelved 2 times as econometrics)
Analysis of Panel Data
Analysis of Panel Data (Paperback)
by Cheng Hsiao (shelved 2 times as econometrics)
Microeconometrics: Methods and Applications
Microeconometrics: Methods and Applications (Hardcover)
by A. Colin Cameron (shelved 2 times as econometrics)
Introduction to Econometrics (Addison-Wesley Series in Economics)
Introduction to Econometrics (Addison-Wesley Series in Economics)
by James H. Stock (shelved 2 times as econometrics)
Principles of Econometrics
Principles of Econometrics (Hardcover)
by R. Carter Hill (shelved 2 times as econometrics)
Learning and Practicing Econometrics
Learning and Practicing Econometrics (Hardcover)
by William E. Griffiths (shelved 2 times as econometrics)
Econometric Models And Economic Forecasts
Econometric Models And Economic Forecasts
by Robert S. Pindyck (shelved 2 times as econometrics)
Analysis of Financial Time Series
Analysis of Financial Time Series (Hardcover)
by Ruey S. Tsay (shelved 2 times as econometrics)
Poverty Dynamics: Interdisciplinary Perspectives
Poverty Dynamics: Interdisciplinary Perspectives (Hardcover)
by Tony Addison (Editor) (shelved 1 time as econometrics)
Student Solutions Manual To Introductory Econometrics
Student Solutions Manual To Introductory Econometrics
by Jeffrey M. Wooldridge (shelved 1 time as econometrics)
Econometric Methods
Econometric Methods (Hardcover)
by Manoranjan Dutta (shelved 1 time as econometrics)
Evolutionary Dynamics And Extensive Form Games
Evolutionary Dynamics And Extensive Form Games (Hardcover)
by Ross Cressman (shelved 1 time as econometrics)
Theory of econometrics
Theory of econometrics
by A. Koutsoyiannis (shelved 1 time as econometrics)
Mastering 'Metrics: The Path from Cause to Effect
Mastering 'Metrics: The Path from Cause to Effect (Hardcover)
by Joshua Angrist (shelved 1 time as econometrics)
Data Analysis Using Regression and Multilevel/Hierarchical Models
Data Analysis Using Regression and Multilevel/Hierarchical Models (Paperback)
by Andrew Gelman (shelved 1 time as econometrics)
Extending the Linear Model with R: Generalized Linear, Mixed Effects and Nonparametric Regression Models
Extending the Linear Model with R: Generalized Linear, Mixed Effects and Nonparametric Regression Models (Hardcover)
by Julian James Faraway (shelved 1 time as econometrics)
Probability and Statistics
Probability and Statistics (Paperback)
by Morris H. DeGroot (shelved 1 time as econometrics)
Introduction to Bayesian Econometrics
Introduction to Bayesian Econometrics (Hardcover)
by Edward Greenberg (shelved 1 time as econometrics)
Introductory Econometrics with Applications
Introductory Econometrics with Applications (Hardcover)
by Ramu Ramanathan (shelved 1 time as econometrics)
Mastering 'Metrics: The Path from Cause to Effect
Mastering 'Metrics: The Path from Cause to Effect (Kindle Edition)
by Joshua D. Angrist (shelved 1 time as econometrics)
Mathematical Statistics and Data Analysis
Mathematical Statistics and Data Analysis (Hardcover)
by John A. Rice (shelved 1 time as econometrics)
Doing Bayesian Data Analysis: A Tutorial Introduction with R and BUGS
Doing Bayesian Data Analysis: A Tutorial Introduction with R and BUGS (Hardcover)
by John Kruschke (shelved 1 time as econometrics)
Bayesian Data Analysis
Bayesian Data Analysis (Hardcover)
by Andrew Gelman (shelved 1 time as econometrics)

Cointegration, Unit Root and ARDL

Assume we have three variables. X1, X2 and X3. In all of the following three cases, we can to test all of X variables for unit root by at least two to three different tests. I personally recommend using ADF and KPSS to test the opposite null hypotheses. ADF's null is unit root series and KPSS is stationary series. Case 1. If all variables are I(0), we can use VAR as Johansen-Juselieus Cointegration Pre-condition is not satisfied. Case 2. If Two variables are I(1) but only one is I(0), or Two are I(0) and one is I(1), then ARDL from Pesaran (2001) is a feasible approach. Case 3. If at least one variable is I(2) and others are either I(0) or I(1) or mixed, the Toda-Yamamoto Causality can be applied after estimated the VAR. Note also, Toda-Yamamoto is a causality test not a test of short run or long run relationship and I usually assume Granger type causality by Toda-Yamamoto or Granger Causality itself has no dependent on VECM or Cointegration.

So in nutshell, If you variables all I(0), you can use VAR. If your all variables are I(1) or I(2), use JJ and Granger Causality. If all variables are mixed I(1) and I(0) but none is I(2), use ARDL and you can also use Granger Causality after running a VAR. If you have mixed order I(0), I(1) and I(2), use Toda Yamamoto Causality Test.

Step By Step Instructions for running ARDL in Eviews.

The steps to conduct ARDL cointegration test in Eviews are:

  1. Open your time series in Eviews
  2. Dfuller and KPSS your variables to check no variable is I(2)
  3. Single click on Dependent Variable (DV)
  4. Press Ctrl Key on keyboard, and click one on all Independent variables (IV) one by one
  5. Once DV and IV are are selected, Righ click on them
  6. A small caption open, Click on Open As Equation
  7. Another selection window appear, select maximum lags for DV and IV
  8. Click on Ok go get the ARDL estimates.

The screenshot will explain the required steps in simple to understand instructions.

Cointegration, Unit Root and ARDL

Cointegration, Unit Root and ARDL

We will share the complete the silenced one minute video tutorial in next part of this tutorial.

The step by step instruction of run ARDL using Stata can be:

  1. Open your data in Stata
  2. Tsset your data with the time variable
  3. Dfuller and KPSS your variables
  4. There should be no I(2) in the variables.
  5. Findit ardl code
  6. or scc install ardl
  7. Once installed, run the code as: ardl dv ivs, lags(#) ec
  8. ## should be replaced with a number of lags.

Why to Select Econometrics Specialists?

All econometrics specialists well aware of the theories of economics related to consumer behaviour, market structure and macroeconomic systems. The econometrics specialists usually work within these domains of economic thinking and plays with the data tools on daily basis. The problems and recent issues are well in their lines of duty because they are the main force within the organizations and teams to define the system for the evaluation and prediction of the future uncertain events to a greater extent. With this simple background, econometrics specialists usually work within the quality agreements and deadlines for each project and hence our econometrics specialists offer 100% gauranteed satisfaction for each project to each client.

Econometrics Specialists, ranked among the top 1% freelancers in Elance.com, Freelancer.com, Odesk.com, Guru.com and Fiverr.com have completed projects in the following areas. See more specific details about the projects detals and reviews for each project at our workplace here. The list is compiled for reference only to show you what kind of freelance skills have been acquired by the for your convinience.

  1. Stata programming for econometric analysis
  2. Econometric Analysis
  3. Time Series Analysis for Economic Data using Eviews
  4. Econometric Analysis using Eviews
  5. Forecasting using Stata
  6. Forecasting using R
  7. Forecastiing using Excel
  8. SSA using JavaScript
  9. Sales Forecasting
  10. Panel Data Analysis
  11. Pricing System Analytics and using Nonlinear Regression Models in Stata
  12. Selecting of Instruments and GMM Regression using Stata Loops
  13. Stata Programming for Healthcare Analytics
  14. Healthcare Analytics for Insurance Premiums through Logistic Regression/Odds Ratio/Marginal
  15. Education Research, Qualitative Data Analysis using Nvivo10
  16. PhD Econometrics Supervision in Econometrics for Healthcare
  17. Data Analysis using R for Public Health Research
  18. Developing PHP based Chi-Square tests using A/B Test Approach in WebAnalytics
  19. Teaching Econometrics using Stata to PhD class
  20. Political Economy and Financial RiskMetrics using Stata
  21. Testing Endogeneity in Panel Data using Stata
  22. Developing a do file for Dynamic Analysis of Data using Correlation and Regression across industries.
  23. Solving custom questions in Econometrics using Stata
  24. Solving custom questions in Econometrics using Eviews
  25. Statistical Analysis of Education data using SPSS
  26. Application of SEM using Stata to Marketing Survey
  27. Application of SEM using Stata to Students Admissions and Droppout Data
  28. Application of SEM using AMOS/SPSS and SEM using Stata for Business Research
  29. Qualitative Analysis of HR Interviews using Nvivo10
  30. Teaching Qualitative Analysis using Nvivo10 to PhD in Organizational Management and HR
  31. Developing Econometric Toolbox using Stata
  32. Econometric Analysis of Brain Drain data using Eviews and Stata
  33. Analysis of Corporate Governance and Financial Performance using Stata for Panel Data (Note, this has been ordered by more than 10 PhD candidates and all have completed their thesis with highest achievements).
  34. Analysis of HR data using SPSS and application of Exploratory Factor Analysis and Confirmatory Factor Analysis/SEM
  35. Partial Least Square using SmartPLS
  36. Moderation SEM using WarpPLS
  37. ANOVA using SPSS for Web Analytics

Econometrics Specialists Skills and Experience

Econometrics Specialists are fully committed to complete each project. Our committment is fully supported by our academic and professional experience and the technical skills in Econometrics and Statistics with Stata, Eviews, SPSS, R, Nvivo10/11, Python, Matlab, Minitab, SAS, RATS, Gretl and HLM. In the following, we can only sum up our experience in the keywords for you.

  1. Assistant Professor in Econometrics and Statistics
  2. Assistant Professor in Economics
  3. Assistant Professor in Research Methods
  4. Assistant Professor in Quantitative Techniques
  5. Professionally trained in Stata, SPSS, R, Matlab, Minitab, RATS, SAS, Excel for Econometrics, Eviews
  6. Professionally trained in Research Methods, Writing Styles, Idea Generation and Publication Management
  7. Professional trainer in Data Analysis using Stata, SPSS and Eviews
  8. Freelance Econometrics Specialist since 2009
  9. Completed more than 500 projects specifically as Econometrics Specialist