The study examines the effect of inflation, investment, life expectancy and literacy rate on per capita GDP across 20 countries using ordinary least squares regression. Initially, the regression results show inflation, investment and literacy rate have a negative effect, while life expectancy has a positive effect on per capita GDP. Sri Lanka, USA and Japan are identified as potential outliers based on their high residuals. Running the regression after removing these outliers improves the model fit and explanatory power of the variables. Diagnostic tests find no evidence of misspecification or heteroskedasticity, validating the OLS estimates.
Aleksey Narko
II year Management
Econometrics Final Project
I took the data set about the wealth of nations and in particular the dependence between the population and total wealth of the country (nation).
Source: http://data.worldbank.org/data-catalog/wealth-of-nations
2011 WSB-NLU
Professor: Jacek Leskow
Aleksey Narko
II year Management
Econometrics Final Project
I took the data set about the wealth of nations and in particular the dependence between the population and total wealth of the country (nation).
Source: http://data.worldbank.org/data-catalog/wealth-of-nations
2011 WSB-NLU
Professor: Jacek Leskow
Multiple Linear Regression II and ANOVA IJames Neill
Explains advanced use of multiple linear regression, including residuals, interactions and analysis of change, then introduces the principles of ANOVA starting with explanation of t-tests.
Multiple Linear Regression II and ANOVA IJames Neill
Explains advanced use of multiple linear regression, including residuals, interactions and analysis of change, then introduces the principles of ANOVA starting with explanation of t-tests.
Easily share what happened during the past month with a beautiful presentation from Venngage. Bring attention to your accomplishments with graphs, charts, and engaging icons. With a presentation from Venngage your audience will be on the edge of their seats.
Easily share your biggest accomplishments with your audience using graphs, charts, and engaging icons. With a presentation from Venngage your audience will be on the edge of their seats.
Easily share what happened during the past year with a beautiful presentation from Venngage. Bring attention to your accomplishments with graphs, charts, and engaging icons. With a presentation from Venngage your audience will be on the edge of their seats.
The name of Athens, connected to the name of its patron goddess Athena, originates from an earlier Pre-
Greek language.
The etiological myth explaining how Athens acquired this name through the legendary contest between Poseidon and Athena was described by Herodotus, Apollodorus, Ovid, Plutarch, Pausanias and others.
Plato, in his dialogue Cratylus, offers his own etymology of Athena's name connecting it to the phrase ἁ θεονόα or hē theoû nóēsis (ἡ θεοῦ νόησις, 'the mind of god')
http://inarocket.com
Learn BEM fundamentals as fast as possible. What is BEM (Block, element, modifier), BEM syntax, how it works with a real example, etc.
The colours that dresses your brand are playing an important role in how they support this personality that you want to portray. Don’t panic when a colour speaks one thing, but in the relation to the brand it delivers a slightly different response.
Check out these examples of how brands used in conveying their message through branding and banner advertisement.
Read more http://www.bannersnack.com/blog/color-banner-design-inspiration/
How NOT to Run Your Company – Lessons LearnedWeekdone.com
The Internet is full of articles on „How to succeed“ and „How to build a great company“ But while following those guidelines we often forget that there's a lot you just can't do.
Learning from your own mistakes is good, but it's even better when you can learn from the mistakes of others.
Everyone's favorite billionaire and Republican presidential hopeful Donald Trump has said “Watch, listen, and learn. You can’t know it all yourself. Anyone who thinks they do is destined for mediocrity.”
Enjoy the slides and a sense of humor is advised.
Tips from Calvin and Hobbes on how to be a good customerFreshdesk Inc.
What could a careless, mischievous six year old possibly teach you about being a good customer? Well, not much really, but he can surely tell you a lot about what you should NOT do.
Here are a few things you can learn from Calvin about being a good customer.
For more tips on customer support, head over to the Freshdesk blog - http://blog.freshdesk.com/
Lightning Talk #9: How UX and Data Storytelling Can Shape Policy by Mika Aldabaux singapore
How can we take UX and Data Storytelling out of the tech context and use them to change the way government behaves?
Showcasing the truth is the highest goal of data storytelling. Because the design of a chart can affect the interpretation of data in a major way, one must wield visual tools with care and deliberation. Using quantitative facts to evoke an emotional response is best achieved with the combination of UX and data storytelling.
Clickbait: A Guide To Writing Un-Ignorable HeadlinesVenngage
We looked at some of the top performing content on social media, from some of the top publications on the web. From this, we were able to figure out the recipe for crafting a click-worthy title. Here is what we learned...
Visit us at gykantler.com for more information.
The concept of a “brand” is no longer taboo at B2B companies. In fact, strong B2B brands outperform weaker ones by as much as 20%, according to recent research by McKinsey. Yet it’s not easy for ROI-obsessed marketers to justify spending money on their brand, which can be difficult to track. As a result, your brand is too often left either underfunded or on the back-burner altogether.
We’re going to help you solve this. In this presentation you’ll learn:
- How your brand can boost demand generation and other key performance indicators
- The elements of a B2B brand and how those are different from traditional consumer branding
- How to elevate your brand through B2B marketing channels and brand advocates
- Metrics to track the impact of your brand
Dispatches From The New Economy: The Five Faces Of The On-Demand EconomyIntuit Inc.
From people determined to be their own boss, to those embracing the flexibility to do something they love, to workers finding a replacement for a traditional job – people working in the on-demand economy are just about as diverse as the labor market itself. A new report from Intuit Inc. and Emergent Research shows that there are a broad range of motivations – and differing levels of satisfaction – among five distinct groups of on-demand workers:
The Business Builders – primarily driven by the desire to be their own boss. They represent 22 percent of on-demand workers.
The Career Freelancers – happily building a career through independent work. They represent 20 percent of on-demand workers.
The Side Giggers – looking to find financial stability by supplementing existing income. They represent 26 percent of on-demand workers.
The Passionistas – looking for the flexibility to do something they love. They represent 18 percent of on-demand workers.
The Substituters – replacing a traditional job that is no longer available. They represent 14 percent of on-demand workers.
Methodology
A total of 4,622 workers who find work opportunities via the platforms provided by the participating partner companies completed an online survey between September 11 and October 1, 2015. The results were weighted to reflect the proportion of workers in each of the following segments: Drivers/Delivery, Online Talent Marketplaces and Field Service/Onsite Talent. The weights were developed using earlier survey work that sized the on-demand economy. The largest weighted share of on-demand worker respondents from any single company is 16%, with most partner companies providing less than 10% of the respondents.
10 Engagement Lessons Learned From 1 Million Survey AnswersD B
Officevibe released a research report called The State of Employee Engagement based on 1,200,000 survey answers from employees in 157 countries. After analyzing the data, we discovered some truly shocking statistics about the state of engagement across the world.
This actionable webinar will show you how you can keep your employees happy and productive.
See the recording of the webinar:
http://bit.ly/2gjJg3o
Get all the free bonuses and extra tips:
http://bit.ly/2g7Q3xM
Content by Officevibe, the simplest tool for a greater workplace.
What happens when the digital tools and platforms we make and use for communication and entertainment are hijacked for terrorism, violence against the vulnerable and nefarious transactions? What role do designers and developers play? Are we complicit as creators of these technologies and products? Should we police them or fight back? As Portfolio Lead for Northern Lab, Northern Trust's internal innovation startup focused on client and partner experience, Antonio will share a mix of provocative scenarios torn from today's headlines and compelling stories where activism and technology facilitated peace—and war.
As a call-to-action for designers and developers to engage in projects capable of transformational change, he'll explore the question: How might technology foster new experiences to better accelerate social activism and make the world a smarter, safer place?
A Study on the Short Run Relationship b/w Major Economic Indicators of US Eco...aurkoiitk
The objective of this study
was to develop an economic indicator system for the US
economy that will help to forecast the turning points in the
aggregate level of economic activity. Our primary concern
is to study the short run relationship between the major
economic indicators of US economy (eg: GDP, Money
Supply, Unemployment Rate, Inflation rate, Federal Fund
Rate, Exchange Rate, Government Expenditure &
Receipt, Crude Oil Price, Net Import & Export).
Fandamental Statistics and Data Science Stock_price_analysis_OESON_P1.pptxyabotenoffice
Fandamental Statistics and Data Science.
The scope of this project was to create a statistical report that compiles real- time data on stock prices for prominent US corporations such as Microsoft, Apple and Tesla in order to analyse the performance of their stock, by performing a descriptive and regression analysis.
InstructionsView CAAE Stormwater video Too Big for Our Ditches.docxdirkrplav
Instructions:
View CAAE Stormwater video "Too Big for Our Ditches"
http://www.ncsu.edu/wq/videos/stormwater%20video/SWvideo.html
Explain how impermeable surfaces in the urban environment impact the stream network in a river basin. Why is watershed management an important consideration in urban planning? Unload you essay (200-400 words).
Neal.LarryBUS457A7.docx
Question 1
Problem:
It is not certain about the relationship between age, Y, as a function of systolic blood pressure.
Goal:
To establish the relationship between age Y, as a function of systolic blood pressure.
Finding/Conclusion:
Based on the available data, the relationship is obtained and shown below:
Regression Analysis: Age versus SBP
Analysis of Variance
Source DF Adj SS Adj MS F-Value P-Value
Regression 1 2933 2933.1 21.33 0.000
SBP 1 2933 2933.1 21.33 0.000
Error 28 3850 137.5
Lack-of-Fit 21 2849 135.7 0.95 0.575
Pure Error 7 1002 143.1
Total 29 6783
Model Summary
S R-sq R-sq(adj) R-sq(pred)
11.7265 43.24% 41.21% 3.85%
Coefficients
Term Coef SE Coef T-Value P-Value VIF
Constant -18.3 13.9 -1.32 0.198
SBP 0.4454 0.0964 4.62 0.000 1.00
Regression Equation
Age = -18.3 + 0.4454 SBP
It is found that there is an outlier in the dataset, which significantly affect the regression equation. As a result, the outlier is removed, and the regression analysis is run again.
Regression Analysis: Age versus SBP
Analysis of Variance
Source DF Adj SS Adj MS F-Value P-Value
Regression 1 4828.5 4828.47 66.81 0.000
SBP 1 4828.5 4828.47 66.81 0.000
Error 27 1951.4 72.27
Lack-of-Fit 20 949.9 47.49 0.33 0.975
Pure Error 7 1001.5 143.07
Total 28 6779.9
Model Summary
S R-sq R-sq(adj) R-sq(pred)
8.50139 71.22% 70.15% 66.89%
Coefficients
Term Coef SE Coef T-Value P-Value VIF
Constant -59.9 12.9 -4.63 0.000
SBP 0.7502 0.0918 8.17 0.000 1.00
Regression Equation
Age = -59.9 + 0.7502 SBP
The p-value for the model is 0.000, which implies that the model is significant in the prediction of Age. The R-square of the model is 70.2%, implies that 70.2% of variation in age can be explained by the model
Recommendation:
The regression model Age = -59.9 +0.7502 SBP can be used to predict the Age, such that over 70% of variation in Age can be explained by the model.
Question 2
Problem:
It is not sure that whether the factors X1 to X4 which represents four different success factors have any influences on the annual savings as a result of CRM implementation.
Goal:
To determine which of the success factors are most significant in the prediction of a successful CRM program, and develop the corresponding model for the prediction of CRM savings.
Finding/Conclusion:
Based on the available da.
A tool-agnostic overview of how to analyse and explore data in a systematic way. This talk covers metadata generation, univariate analysis, and the basics of bivariate analysis.
The talk also provides examples of natural power law distributions (scale-free networks.)
2024.06.01 Introducing a competency framework for languag learning materials ...Sandy Millin
http://sandymillin.wordpress.com/iateflwebinar2024
Published classroom materials form the basis of syllabuses, drive teacher professional development, and have a potentially huge influence on learners, teachers and education systems. All teachers also create their own materials, whether a few sentences on a blackboard, a highly-structured fully-realised online course, or anything in between. Despite this, the knowledge and skills needed to create effective language learning materials are rarely part of teacher training, and are mostly learnt by trial and error.
Knowledge and skills frameworks, generally called competency frameworks, for ELT teachers, trainers and managers have existed for a few years now. However, until I created one for my MA dissertation, there wasn’t one drawing together what we need to know and do to be able to effectively produce language learning materials.
This webinar will introduce you to my framework, highlighting the key competencies I identified from my research. It will also show how anybody involved in language teaching (any language, not just English!), teacher training, managing schools or developing language learning materials can benefit from using the framework.
Unit 8 - Information and Communication Technology (Paper I).pdfThiyagu K
This slides describes the basic concepts of ICT, basics of Email, Emerging Technology and Digital Initiatives in Education. This presentations aligns with the UGC Paper I syllabus.
Introduction to AI for Nonprofits with Tapp NetworkTechSoup
Dive into the world of AI! Experts Jon Hill and Tareq Monaur will guide you through AI's role in enhancing nonprofit websites and basic marketing strategies, making it easy to understand and apply.
Executive Directors Chat Leveraging AI for Diversity, Equity, and InclusionTechSoup
Let’s explore the intersection of technology and equity in the final session of our DEI series. Discover how AI tools, like ChatGPT, can be used to support and enhance your nonprofit's DEI initiatives. Participants will gain insights into practical AI applications and get tips for leveraging technology to advance their DEI goals.
Normal Labour/ Stages of Labour/ Mechanism of LabourWasim Ak
Normal labor is also termed spontaneous labor, defined as the natural physiological process through which the fetus, placenta, and membranes are expelled from the uterus through the birth canal at term (37 to 42 weeks
Read| The latest issue of The Challenger is here! We are thrilled to announce that our school paper has qualified for the NATIONAL SCHOOLS PRESS CONFERENCE (NSPC) 2024. Thank you for your unwavering support and trust. Dive into the stories that made us stand out!
Thinking of getting a dog? Be aware that breeds like Pit Bulls, Rottweilers, and German Shepherds can be loyal and dangerous. Proper training and socialization are crucial to preventing aggressive behaviors. Ensure safety by understanding their needs and always supervising interactions. Stay safe, and enjoy your furry friends!
The simplified electron and muon model, Oscillating Spacetime: The Foundation...RitikBhardwaj56
Discover the Simplified Electron and Muon Model: A New Wave-Based Approach to Understanding Particles delves into a groundbreaking theory that presents electrons and muons as rotating soliton waves within oscillating spacetime. Geared towards students, researchers, and science buffs, this book breaks down complex ideas into simple explanations. It covers topics such as electron waves, temporal dynamics, and the implications of this model on particle physics. With clear illustrations and easy-to-follow explanations, readers will gain a new outlook on the universe's fundamental nature.
This slide is special for master students (MIBS & MIFB) in UUM. Also useful for readers who are interested in the topic of contemporary Islamic banking.
A Strategic Approach: GenAI in EducationPeter Windle
Artificial Intelligence (AI) technologies such as Generative AI, Image Generators and Large Language Models have had a dramatic impact on teaching, learning and assessment over the past 18 months. The most immediate threat AI posed was to Academic Integrity with Higher Education Institutes (HEIs) focusing their efforts on combating the use of GenAI in assessment. Guidelines were developed for staff and students, policies put in place too. Innovative educators have forged paths in the use of Generative AI for teaching, learning and assessments leading to pockets of transformation springing up across HEIs, often with little or no top-down guidance, support or direction.
This Gasta posits a strategic approach to integrating AI into HEIs to prepare staff, students and the curriculum for an evolving world and workplace. We will highlight the advantages of working with these technologies beyond the realm of teaching, learning and assessment by considering prompt engineering skills, industry impact, curriculum changes, and the need for staff upskilling. In contrast, not engaging strategically with Generative AI poses risks, including falling behind peers, missed opportunities and failing to ensure our graduates remain employable. The rapid evolution of AI technologies necessitates a proactive and strategic approach if we are to remain relevant.
How to Build a Module in Odoo 17 Using the Scaffold MethodCeline George
Odoo provides an option for creating a module by using a single line command. By using this command the user can make a whole structure of a module. It is very easy for a beginner to make a module. There is no need to make each file manually. This slide will show how to create a module using the scaffold method.
1. STUDYING THE EFFECT OF INFLATION, INVESTMENT, LIFE EXPECTANCY AND LITERACY RATE ON PER CAPITA GDP GUIDE: PROF. SAMARJIT DAS REPORT BY: UDAY THARAR MSQE 1 ST YEAR QE0703 INDIAN STATISTICAL INSTITUTE
2. DATA Country GDP PC ($) Inflation (%) Investment ratio (%) Life Expectancy (years) Literacy Rates (%) (PCI) (I) (INV) (LE) (LIT) India 1348 9.8 25 61.3 51.2 China 2604 9.3 40 68.9 80.9 Sri Lanka 3277 11.8 25 72.2 90.1 USA 26397 3.2 16 76.2 99 UK 18620 5.1 16 76.7 99 Russia 4828 148.9 25 65.7 98.7 Pakistan 2154 9.2 19 62.3 37.1 Bangladesh 1331 6.4 17 56.4 37.3 Australia 19285 3.7 23 78.1 99 Canada 21459 2.9 19 79 99 France 20510 2.8 18 78.7 99 Germany 19675 3 21 76.3 99 Japan 21581 1.4 29 79.8 99 Kenya 1404 13 19 53.6 77 Argentina 8937 255.6 18 72.4 96 Zimbabwe 2196 20.9 22 49 84.7 Indonesia 3740 8.8 38 63.5 83.2 Korea 10656 6.7 37 71.5 97.9 Norway 21346 3 23 77.5 99 Thailand 7104 5 43 69.5 93.5
4. THE METHOD USED IS OLS WITH PER CAPITA GDP AS THE EXPLAINED VARIABLE AND INFLATION, INVESTMENT RATIO, LIFE EXPECTANCY AND LITERACY RATE AS EXPLANATORY VARIABLES. We now provide a brief explanation of the explanatory variables-- ANALYSIS
5.
6.
7. REGRESSION RESULTS Dependent Variable: PCI Method: Least Squares Sample: 1 20 Included observations: 20 Variable Coefficient Std. Error t-Statistic Prob. I -38.4496 13.3138 -2.888 0.0113 INV -392.582 98.1917 -3.9981 0.0012 LE 571.6545 119.109 4.7994 0.0002 LIT 156.2885 54.5576 2.8647 0.0118 C -31508 6827.77 -4.6147 0.0003 R-squared 0.883177 Mean dependent var 10923 Adjusted R-squared 0.852024 S.D. dependent var 8981.6 S.E. of regression 3455.021 Akaike info criterion 19.345 Sum squared resid 1.79E+08 Schwarz criterion 19.594 Log likelihood -188.454 F-statistic 28.35 Durbin-Watson stat 2.4797 Prob(F-statistic) 0.000001
10. RESIDUAL ANALYSIS THE RESIDUAL TABLE AND GRAPH INDICATE THE PRESENCE OF SOME OUTLIERS.THE OBSERVATIONS 3, 4 & 13 HAVE HIGHER RESIDUALS THAN THE OTHERS. THESE COUNTRIES ARE SRI LANKA, USA AND JAPAN RESPECTIVELY. THOUGH ANALYSING THE RESIDUALS IS NOT A VERY GOOD INDICATOR OF OUTLIERS BUT BY LOOKING AT THE INDIVIDUAL OBSERVATIONS ONE CAN GET THE INTUITION THAT THESE COULD BE OUTLIERS SINCE SRI LANKA HAS HIGH LITERACY AND LIFE EXPECTANCY RATES INSPITE OF BEING A LOW PER CAPITA INCOME COUNTRY AND THE REMAINING 2 HAVE A HIGH PER CAPITA INCOME AS COMPARED TO THE OTHER COUNTRIES. THESE DIFFERENCES COULD BE DUE TO DIFFERENT NATIONAL POLICIES THAT THEIR GOVERNMENTS FOLLOW. WE WILL RUN ANOTHER REGRESSION AFTER DELETING THESE.
11. REGRESSION RESULTS AFTER DELETING THE OUTLIERS Dependent Variable: PCI Method: Least Squares Sample: 1 17 Included observations: 17 Variable Coefficient Std. Error t-Statistic Prob. I -36.57134 6.271489 -5.831365 0.0001 INV -360.7367 47.65338 -7.570013 0.0000 LE 553.5307 56.83341 9.739529 0.0000 LIT 149.2246 25.52452 5.846322 0.0001 C -30431.88 3279.835 -9.278479 0.0000 R-squared 0.972098 Mean dependent var 9835.118 Adjusted R-squared 0.962798 S.D. dependent var 8295.732 S.E. of regression 1600.071 Akaike info criterion 17.83341 Sum squared resid 30722718 Schwarz criterion 18.07847 Log likelihood -146.584 F-statistic 104.5204 Durbin-Watson stat 1.23126 Prob(F-statistic) 0.00000
12. COMPARISON BETWEEN THE TWO EQUATIONS Variable Coefficient Std. Error Prob. of t- statistic NEW OLD NEW OLD NEW OLD C -30431.88 -31508.03 3279.84 6827.771 0.0000 0.0003 I -36.57134 -38.44955 6.27149 13.31378 0.0001 0.0113 INV -360.7367 -392.5823 47.6534 98.19166 0.0000 0.0012 LE 553.5307 571.6545 56.8334 119.1089 0.0000 0.0002 LIT 149.2246 156.2885 25.5245 54.55759 0.0001 0.0118 OLD R-squared = 0.883177 NEW R-squared = 0.97208
13.
14. WE WILL NOW CHECK IF OUR OLS ESTIMATES ARE VALID OR NOT BY CHECKING IF SOME OF THE STANDARD CLRM ASSUMPTIONS ARE VIOLATED. FOR THIS WE CARRY OUT A FEW TESTING EXERCISES. Estimated Equation: PCI = - 30431.88104 - 36.57134273*I - 360.736706*INV + 553.5306553*LE + 149.2245611*LIT Thus while Inflation and Investment are inversely related with PCI, Life Expectancy and Literacy Rate influence it positively.
15. JARQUE-BERA NORMALITY TEST ON THE RESIDUALS The test is to check for normality of the disturbance terms. The null hypothesis of the test is that the error terms or the residuals are N(0, σ ²). This test actually tests for the joint null hypothesis that the skewness E( ) is zero and the kurtosis E( ) is equal to 3 , which holds if the s are N(0, σ ²) distributed. Under the null hypothesis the test statistic involved (for large n) has a χ 2 distribution.
16. The Null Hypothesis cannot be rejected both at 5% & 1% level of significance. So we conclude that the residuals are indeed normally distributed. However, the Jarque-Bera test is an asymptotic test. Our sample size is only 17 so the validity of the test is under suspect.
17. THE RAMSEY RESET TEST The Ramsey Reset Test is a test for Functional Specification. It checks for any functional mis-specification. As suggested by Ramsey, the Null Hypothesis of a zero u vector is based on an augmented regression on the powers of the estimated or predicted values of the dependent variable namely y ² , y ³ , …. and testing whether the coefficients are significant or not. This test has been done by taking the no. of fitted items as 1.
18. RESULTS We can see that the coefficients of higher powers are indeed zero as suggested by the Probability value. Thus we can assert that our Regression has a Linear Specification . F-statistic 0.213322 Probability 0.653176 Log likelihood ratio 0.326523 Probability 0.567714 Dependent Variable: PCI Method: Least Squares Sample: 1 17 Included observations: 17 Variable Coefficient Std. Error t-Statistic Prob. I -25.19922 25.46244 -0.989662 0.3436 INV -252.5063 239.4612 -1.054477 0.3143 LE 436.2553 260.6334 1.673827 0.1223 LIT 117.1873 74.22027 1.578913 0.1427 C -24374.78 13546.16 -1.799387 0.0994 FITTED^2 1.01E-05 2.18E-05 0.461868 0.6532 R-squared 0.972629 Mean dependent var 9835.118 Adjusted R-squared 0.960188 S.D. dependent var 8295.732 S.E. of regression 1655.246 Akaike info criterion 17.93185 Sum squared resid 30138250 Schwarz criterion 18.22593 Log likelihood -146.4207 F-statistic 78.17742 Durbin-Watson stat 1.147307 Prob(F-statistic) 0.00000
19. WHITE HETEROSKEDASTICITY TEST Heteroskedasticity refers to the situation in which the variance of the error term in the regression equation is not constant but varies with the independent variable. In the presence of Heteroskedasticity, the Ordinary Least Square estimates, although still unbiased are no longer efficient. We refer to the WHITE HETEROSKEDASTICITY TEST for the detection of Heteroskedasticity, wherein one simply computes an auxiliary regression of the squared OLS residuals on a constant and all nonredundant variables in the set consisting of the regressors, their squares and their cross products.
22. SORTED DATA Country GDP PC Inflation Investment ratio Life Expectancy Literacy Rates (PCI) (I) (INV) (LE) (LIT) Zimbabwe 2196.0 20.9 22.0 49.0 84.7 Kenya 1404.0 13.0 19.0 53.6 77.0 Bangladesh 1331.0 6.4 17.0 56.4 37.3 India 1348.0 9.8 25.0 61.3 51.2 Pakistan 2154.0 9.2 19.0 62.3 37.1 Indonesia 3740.0 8.8 38.0 63.5 83.2 Russia 4828.0 148.9 25.0 65.7 98.7 China 2604.0 9.3 40.0 68.9 80.9 Thailand 7104.0 5.0 43.0 69.5 93.5 Korea 10656.0 6.7 37.0 71.5 97.9 Argentina 8937.0 255.6 18.0 72.4 96.0 Germany 19675.0 3.0 21.0 76.3 99.0 UK 18620.0 5.1 16.0 76.7 99.0 Norway 21346.0 3.0 23.0 77.5 99.0 Australia 19285.0 3.7 23.0 78.1 99.0 France 20510.0 2.8 18.0 78.7 99.0 Canada 21459.0 2.9 19.0 79.0 99.0
23.
24. PARAMETER STABILITY TESTS THE CUSUM TEST SINCE THE CUMULATIVE SUM IS INSIDE THE AREA BETWEEN,THE TWO CRITICAL LINES,WE CAN SAY THAT THE PARAMETERS ARE CONSTANT IN TERMS OF INTERCEPT. THE CUSUMSQ TEST HERE WE CAN SAY THAT THE PARAMETERS ARE CONSTANT IN TERMS OF VARIANCE.
25. THE RECURSIVE RESIDUALS TEST THE RESIDUALS ARE INSIDE THE STANDARD ERROR BANDS. IT SUGGESTS THAT THE PARAMETERS ARE STABLE.
26.
27. Chow Forecast Test: Forecast from 15 to 17 F-statistic 1.476388 Probability 0.285454 Log likelihood ratio 6.80347 Probability 0.078433 Dependent Variable: PCI Method: Least Squares Sample: 1 14 Included observations: 14 Variable Coefficient Std. Error t-Statistic Prob. I -34.69875 6.000098 -5.783031 0.0003 INV -394.0349 58.12046 -6.779625 0.0001 LE 534.8819 54.46534 9.820593 0.0000 LIT 144.0358 24.30871 5.925275 0.0002 C -28332.41 3331.343 -8.504801 0.0000 R-squared 0.978415 Mean dependent var 9149.357 Adjusted R-squared 0.968821 S.D. dependent var 8565.987 S.E. of regression 1512.535 Akaike info criterion 17.75341 Sum squared resid 20589850 Schwarz criterion 17.98165 Log likelihood -119.2739 F-statistic 101.9883 Durbin-Watson stat 1.396911 Prob(F-statistic) 0.0000
28. From the statistical table under F distribution, we see that: F 3,9,0.05 = 3.86 F 3,9,0.01 = 6.99 From the table the Chow F-statistic obtained is F(3,9) = 1.476388 Thus the value of the F-statistic obtained is less than the tabular value at both 5% and 1% level of significance. We therefore accept the Null Hypothesis of parameter constancy at both 5% and 1% level of significance.
29.
30. We have obtained the following results: From the results obtained above we see that in our model the VIF of all the estimated coefficients are close to 1. Thus we conclude that the model is free from multicollinearity or in other words, the explanatory variables are uncorrelated. Regressors VIF I 1.123 INV 1.105 LEX 1.781 LIT 1.911