This document presents an analysis of the relationship between political stability and economic growth in 10 countries from 2005-2014. The analysis finds:
1) Using a fixed effects regression model, higher political stability (as measured by the political stability index) is associated with higher GDP growth, as are higher investment rates.
2) Tests show the fixed effects model is preferred over the random effects or pooled models.
3) The addition of a dummy variable to distinguish more politically unstable countries from less unstable countries improves the model and shows GDP growth is lower, on average, in the more unstable countries.
This document discusses time series analysis and forecasting methods. It covers descriptive analysis techniques like index numbers and exponential smoothing to characterize patterns in time series data. It also covers inferential/forecasting methods like exponential smoothing, Holt's method, and regression models to predict future values in a time series. The learning objectives are to analyze time series data generated over time, present descriptive characterization methods, and present forecasting methods. Key concepts discussed include index numbers, exponential smoothing, time series components, measuring forecast accuracy, and autocorrelation.
Hero Motocorp is the world's largest two-wheeler manufacturing company. It conducted primary research through a questionnaire of 50 customers and secondary research using the company's annual reports. The questionnaire asked about customers' preferences for Hero and other brands, ownership of Hero vehicles, and satisfaction levels. It found that Hero's Splendor model is most popular and that customers rate Hero highly for fuel efficiency, mileage, and value. The document also analyzes Hero's shareholding patterns and provides financial analyses such as mean, median, mode, standard deviation, correlation, and regression related to the company's performance metrics.
Solutions manual for mathematics of finance canadian 8th edition by brown ibs...adelen11
This document contains solutions to exercises from a textbook on mathematics of finance. It provides answers to multiple choice and numerical problems related to simple and compound interest, effective rates of interest, present and future value of sums of money, and discounted cash flows. The solutions include calculations of interest earned on principal amounts over time at given rates, as well as determining unknown rates based on future or present values.
This document discusses a new approach to measuring the impact of foreign labor on native employment. It presents two natural experiments using data on H-2A visa workers and unemployment insurance records from North Carolina farms. The results section analyzes the effect of the recession on job referrals and native labor supply, finding that higher unemployment led to more job referrals but lower native employment, suggesting native workers withdrew from the labor market during economic downturns.
The document discusses cost benefit analyses of safety aspects and programs through two case studies. In the first case study of Ritrama manufacturing company, implementing a safety program including training, protective equipment, and a safety consultant led to a reduction in injuries from 14 to 5 recordable cases per year from 1995 to 2005. This decreased workers compensation costs and increased productivity. The second case study of mining company Anglo American saw a CEO implement a safety overhaul, reducing fatalities from 200 to zero. This increased profits from $20 billion to $35 billion in revenue while maintaining operating income. Overall, the document argues that safety programs have significant direct and indirect financial benefits that outweigh upfront costs.
This document contains an agenda, profile information for Sanofi, a large pharmaceutical company, background on their insulin drugs Lantus and Toujeo, methodology for data analysis, parameter estimates from regression models, findings and recommendations. Key findings include higher rebates and marketing program expenses being associated with higher net income for Lantus and Toujeo. Recommendations focus on reallocating resources between the two drugs.
Sheet1EgyptGDP by Expenditure2005 US $assumptionsYearYCGIXMconsump.docxmaoanderton
Sheet1EgyptGDP by Expenditure2005 US $assumptionsYearYCGIXMconsumption functionC=-20.4862982766+0.7460897862Y200078737.729587024359249.64476852068727.885739464114772.050070512318701.439762282822713.2907537555200181512.515401750161320.14166497139154.938252751614178.318154531519316.843630253422457.7263007577trend GDPRy=b=0.0449366764200284109.10396237862913.11581920269608.681548019114890.796453816617812.52306429221116.0129229523200386728.495429143964038.45466320599914.042190424114245.241694184719917.172763625621386.4158822964Import DemandM=Y200490302.410904929765505.324210443810219.402832902215062.944389646424588.468437457925073.7289655206200594456.32180659368828.574449917810505.54611219116613.541606264229555.835798517631047.1761602976Last 5 Years I/Y2006100973.80801124173280.255156930910832.567002848618828.680487085135839.555510440837807.25014606442007108092.58754227678448.702815302610853.00580853323303.261026347444184.732677089148697.1147849961Average X/Y 2000-20142008115850.57130333682468.862631922311084.468017679126904.537682077556892.991343073361500.28837141622009121295.54815456186997.952484219511701.700575548524458.670620090148636.545512291150499.32103758822010127481.62111044390561.662750439712228.920051973626409.362141840347185.293750957248903.61758476782011129951.22178650396646.473530784312691.844470412225854.165324178847773.639059688753014.9005985612012132810.148665824103875.04631698313090.473830644927909.894081772946675.394483525858740.66004710312013135600.392703195105792.35175105713543.886890700825226.460439558849428.986791371558391.29316949322014138533.933462906113520.54398606614333.703188862626394.252007270943224.867059992358939.4327792858projected2015144759.232830929108023.9023228282016151264.278476652112877.2518286452017158061.641358557117948.6963012062018165164.457336287123248.036274032019172586.452555608128785.5126872132020180341.969974099134571.826677975
Sheet1Y=XC=YXYx-xbary-ybar(x-xbar)(y-ybar)(x-xbar)^2787385925078737.729587024359249.6447685206-1547698.68024508-1154197.462231451786349889037.832395371204832.35C=-20.4862982766+0.7460897862815136132081512.515401750161320.1416649713-1544923.89443035-1152126.9653351779948478163.572386789839581.84841096291384109.10396237862913.1158192026-1542327.30586972-1150533.991180771774499990929.372378773518431.35867286403886728.495429143964038.4546632059-1539707.91440296-1149408.652336761769753598886.152370700461675.1903026550590302.410904929765505.3242104438-1536133.99892717-1147941.782789531763392401332.062359707662659.98944566882994456.32180659368828.5744499178-1531980.08802551-1144618.532550051753532800251.662346962990106.6410097473280100973.80801124173280.2551569309-1525462.60182086-1140166.851843041739281892322.382327036149554.0610809378449108092.58754227678448.7028153026-1518343.82228982-1134998.404184671723317815302.62305367962685.6711585182469115850.57130333682468.8626319223-1510585.83852876-1130978.244368051708439719626.52281869575563.6512129686998121295.54815456186997.9524842195.
This document discusses time series analysis and forecasting methods. It covers descriptive analysis techniques like index numbers and exponential smoothing to characterize patterns in time series data. It also covers inferential/forecasting methods like exponential smoothing, Holt's method, and regression models to predict future values in a time series. The learning objectives are to analyze time series data generated over time, present descriptive characterization methods, and present forecasting methods. Key concepts discussed include index numbers, exponential smoothing, time series components, measuring forecast accuracy, and autocorrelation.
Hero Motocorp is the world's largest two-wheeler manufacturing company. It conducted primary research through a questionnaire of 50 customers and secondary research using the company's annual reports. The questionnaire asked about customers' preferences for Hero and other brands, ownership of Hero vehicles, and satisfaction levels. It found that Hero's Splendor model is most popular and that customers rate Hero highly for fuel efficiency, mileage, and value. The document also analyzes Hero's shareholding patterns and provides financial analyses such as mean, median, mode, standard deviation, correlation, and regression related to the company's performance metrics.
Solutions manual for mathematics of finance canadian 8th edition by brown ibs...adelen11
This document contains solutions to exercises from a textbook on mathematics of finance. It provides answers to multiple choice and numerical problems related to simple and compound interest, effective rates of interest, present and future value of sums of money, and discounted cash flows. The solutions include calculations of interest earned on principal amounts over time at given rates, as well as determining unknown rates based on future or present values.
This document discusses a new approach to measuring the impact of foreign labor on native employment. It presents two natural experiments using data on H-2A visa workers and unemployment insurance records from North Carolina farms. The results section analyzes the effect of the recession on job referrals and native labor supply, finding that higher unemployment led to more job referrals but lower native employment, suggesting native workers withdrew from the labor market during economic downturns.
The document discusses cost benefit analyses of safety aspects and programs through two case studies. In the first case study of Ritrama manufacturing company, implementing a safety program including training, protective equipment, and a safety consultant led to a reduction in injuries from 14 to 5 recordable cases per year from 1995 to 2005. This decreased workers compensation costs and increased productivity. The second case study of mining company Anglo American saw a CEO implement a safety overhaul, reducing fatalities from 200 to zero. This increased profits from $20 billion to $35 billion in revenue while maintaining operating income. Overall, the document argues that safety programs have significant direct and indirect financial benefits that outweigh upfront costs.
This document contains an agenda, profile information for Sanofi, a large pharmaceutical company, background on their insulin drugs Lantus and Toujeo, methodology for data analysis, parameter estimates from regression models, findings and recommendations. Key findings include higher rebates and marketing program expenses being associated with higher net income for Lantus and Toujeo. Recommendations focus on reallocating resources between the two drugs.
Sheet1EgyptGDP by Expenditure2005 US $assumptionsYearYCGIXMconsump.docxmaoanderton
Sheet1EgyptGDP by Expenditure2005 US $assumptionsYearYCGIXMconsumption functionC=-20.4862982766+0.7460897862Y200078737.729587024359249.64476852068727.885739464114772.050070512318701.439762282822713.2907537555200181512.515401750161320.14166497139154.938252751614178.318154531519316.843630253422457.7263007577trend GDPRy=b=0.0449366764200284109.10396237862913.11581920269608.681548019114890.796453816617812.52306429221116.0129229523200386728.495429143964038.45466320599914.042190424114245.241694184719917.172763625621386.4158822964Import DemandM=Y200490302.410904929765505.324210443810219.402832902215062.944389646424588.468437457925073.7289655206200594456.32180659368828.574449917810505.54611219116613.541606264229555.835798517631047.1761602976Last 5 Years I/Y2006100973.80801124173280.255156930910832.567002848618828.680487085135839.555510440837807.25014606442007108092.58754227678448.702815302610853.00580853323303.261026347444184.732677089148697.1147849961Average X/Y 2000-20142008115850.57130333682468.862631922311084.468017679126904.537682077556892.991343073361500.28837141622009121295.54815456186997.952484219511701.700575548524458.670620090148636.545512291150499.32103758822010127481.62111044390561.662750439712228.920051973626409.362141840347185.293750957248903.61758476782011129951.22178650396646.473530784312691.844470412225854.165324178847773.639059688753014.9005985612012132810.148665824103875.04631698313090.473830644927909.894081772946675.394483525858740.66004710312013135600.392703195105792.35175105713543.886890700825226.460439558849428.986791371558391.29316949322014138533.933462906113520.54398606614333.703188862626394.252007270943224.867059992358939.4327792858projected2015144759.232830929108023.9023228282016151264.278476652112877.2518286452017158061.641358557117948.6963012062018165164.457336287123248.036274032019172586.452555608128785.5126872132020180341.969974099134571.826677975
Sheet1Y=XC=YXYx-xbary-ybar(x-xbar)(y-ybar)(x-xbar)^2787385925078737.729587024359249.6447685206-1547698.68024508-1154197.462231451786349889037.832395371204832.35C=-20.4862982766+0.7460897862815136132081512.515401750161320.1416649713-1544923.89443035-1152126.9653351779948478163.572386789839581.84841096291384109.10396237862913.1158192026-1542327.30586972-1150533.991180771774499990929.372378773518431.35867286403886728.495429143964038.4546632059-1539707.91440296-1149408.652336761769753598886.152370700461675.1903026550590302.410904929765505.3242104438-1536133.99892717-1147941.782789531763392401332.062359707662659.98944566882994456.32180659368828.5744499178-1531980.08802551-1144618.532550051753532800251.662346962990106.6410097473280100973.80801124173280.2551569309-1525462.60182086-1140166.851843041739281892322.382327036149554.0610809378449108092.58754227678448.7028153026-1518343.82228982-1134998.404184671723317815302.62305367962685.6711585182469115850.57130333682468.8626319223-1510585.83852876-1130978.244368051708439719626.52281869575563.6512129686998121295.54815456186997.9524842195.
ACCT608: Investment Analysis of Sheng Siong GroupAlvin J. Lin
The document analyzes Sheng Siong Group as an investment opportunity. It provides three scenarios for the company's performance and finds that the base case scenario would yield a 30.1% return on investment, higher than a 9.3% return from an A-grade bond. The analysis also shows Sheng Siong has higher profitability and return on equity than Dairy Farm International based on financial metrics. Overall the document recommends buying shares in Sheng Siong Group.
This document summarizes population, economic, and budget trends in Vermont from 2008 to 2015 using data from various sources. It shows that while the population and median income grew modestly, health care costs increased significantly. State spending grew at an average annual rate of 5.45%, much higher than the underlying economic growth rate of around 3%. If spending had grown at 3% annually instead, the state would not have a budget deficit. The document proposes focusing reforms and efficiencies to control spending growth to 3% annually going forward.
Estimation of Import Regression for CanadaGeray Gerayli
1) The document estimates import regression models for Canada from 1975-2014 to analyze the relationship between imports, GDP, and real exchange rate.
2) Eight multiple regression models are estimated with different specifications of the dependent and independent variables. The best-fitting model is Model 5, which uses the natural log of imports as the dependent variable and GDP and the natural log of real exchange rate as independent variables.
3) Model 5 has individually and jointly statistically significant coefficients, the expected negative relationship between imports and real exchange rate, and the lowest AIC and BIC values, indicating it is the preferred specification according to the data analysis in the document.
The document analyzes the future performance of PRAN AMCL LTD using a linear regression model. It finds that:
1) The regression equation indicates profit is influenced by various variables like sales, salary, advertisement etc.
2) There is a very high positive relationship (R=0.813) among the variables but the relationship is not statistically significant.
3) Sales has the most influence on profit but the relationship is also not statistically significant.
4) Analysis of historical profit data from 1999-2013 finds the company has a average annual growth rate of 3.49% and acceleration rate of 3.76%, suggesting future performance will be promising if this trend continues.
The document discusses a company called 3DP that is considering two options - launching a new 3D printer product or selling the patent license. It provides information on the estimated costs of product development and market potential for the product. It also provides details on a potential offer from another company to purchase the patent license. The document asks two questions: 1) Calculate the expected monetary value of the two options and recommend the decision based on financial considerations. 2) Calculate the exchange rate change needed to change the recommended decision and its probability.
This document contains numerical examples related to time value of money calculations. It includes calculations for:
- Present and future value of a single payment
- Present and future value of an annuity
- Net present value
- Internal rate of return
- Multiple internal rates of return
- Reinvestment rate assumptions
The examples demonstrate time value of money principles and calculations for a variety of cash flow patterns over different time periods. Trial and error or spreadsheet tools are suggested to solve the examples.
This chapter introduces multiple regression analysis. Multiple regression allows modeling the relationship between a dependent variable (Y) and two or more independent variables (X1, X2, etc). The key assumptions and outputs of multiple regression are discussed, including the multiple regression equation, R-squared, adjusted R-squared, standard error, and hypothesis testing of individual regression coefficients. An example illustrates estimating a multiple regression model to examine factors influencing weekly pie sales.
Javier Garcia - Verdugo Sanchez - Six Sigma Training - W4 The Binary Logistic...J. García - Verdugo
The document discusses binary logistic regression and provides an example. It analyzes data from a study of 100 men investigating the relationship between age and risk of coronary heart disease. Logistic regression is used to estimate the effect of age on the probability of disease. The analysis finds that for each one year increase in age, the odds of disease increase by 13% (odds ratio of 1.13).
This document analyzes the relationship between US GDP performance and government current expenditure from 1999 to 2009. Regression analysis shows a strong positive linear relationship between the two variables, with current expenditure explaining 85.4% of the variation in GDP over the period. Both GDP and current expenditure showed an increasing trend over time. The regression coefficients, F-test, and correlation coefficient provide strong statistical evidence that increases in government current expenditure are positively associated with increases in US GDP during this period.
This document discusses applying financial statistics to analyze Turkey's economy. It provides data on Turkey's GDP, economic size, and per capita income. It then examines the correlation between GDP per capita and three independent variables: domestic credit, broad money, and services value added. The document estimates a linear regression equation relating GDP to these three variables and performs hypothesis testing to evaluate the model. It finds the model is statistically significant and the independent variables domestic credit and broad money significantly impact GDP, but services does not.
This chapter discusses various factors used in engineering economy to analyze cash flows over time under conditions of interest. It introduces the single-payment compound amount factor (SPCAF) and single-payment present worth factor (SPPWF) for analyzing single payments compounded over time. It also discusses the uniform series present worth factor (USPWF) and capital recovery factor (CRF) for analyzing uniform series of cash flows. Examples are provided to illustrate the calculation of future and present values using these factors under simple and compound interest conditions. Arithmetic and geometric gradient factors are also introduced for cash flows that regularly increase or decrease by a constant amount or percentage.
Banco ABC Brasil had strong financial results in 4Q07. Net income increased 154.6% compared to 4Q06 to R$50.7 million. The credit portfolio grew 71% to R$4,992.2 million with high credit quality maintained. Business segments all saw growth in 4Q07 compared to prior periods. Expenses were well controlled while profitability and efficiency metrics improved. The bank ended 2007 with net income up 93.8% and a solid capital and ratings position supported by its controlling shareholder ABC Banking Corporation.
U.S. Manufacturing Job Gains and Imports, 2001-2011: An AnalysisAaron S. Robertson
The document analyzes the relationship between manufacturing job gains and imports in the United States from 2001-2011. A regression analysis found a moderate negative correlation (r=-0.750) between the two variables, with higher manufacturing job gains associated with lower import levels. The p-value of 0.0078 leads to a rejection of the null hypothesis that there is no correlation, indicating there is a statistically significant correlation between manufacturing jobs and imports over the period studied.
Tesla and Toyota were analyzed through 3 year valuation models and sensitivity analyses. Tesla was found to be overvalued at its current stock price, while Toyota was found to be undervalued. Both companies were also assessed on various financial metrics such as growth rates, profitability, and liquidity. A regression analysis showed a moderate positive correlation between automotive industry sales and total nonfarm payrolls.
Statistics assignment about data driven management scienceRahatulAshafeen
The document describes two linear regression models created to analyze sales and profit before tax data for Abhinav Technologies over 20 years.
The first model for predicting sales had an R^2 of 0.996, indicating the model explained 99.6% of the variability in sales based on material, other incomes, personnel, and interest payments. Only interest payments were not a statistically significant predictor.
The second model for predicting profit before tax had an R^2 of 0.934, showing the model explained 93.4% of the variability in profit based on the same predictor variables. Material and interest payments were not statistically significant for this model.
This document provides solutions to end-of-chapter problems from the 8th edition of the textbook "Engineering Economy" by Leland Blank and Anthony Tarquin. It includes solutions to over 50 problems involving time value of money calculations using factors, arithmetic gradients, geometric gradients, and determining interest rates. The solutions demonstrate applications of present worth, future worth, annual worth, payment, and rate of return formulas.
ACCT608: Investment Analysis of Sheng Siong GroupAlvin J. Lin
The document analyzes Sheng Siong Group as an investment opportunity. It provides three scenarios for the company's performance and finds that the base case scenario would yield a 30.1% return on investment, higher than a 9.3% return from an A-grade bond. The analysis also shows Sheng Siong has higher profitability and return on equity than Dairy Farm International based on financial metrics. Overall the document recommends buying shares in Sheng Siong Group.
This document summarizes population, economic, and budget trends in Vermont from 2008 to 2015 using data from various sources. It shows that while the population and median income grew modestly, health care costs increased significantly. State spending grew at an average annual rate of 5.45%, much higher than the underlying economic growth rate of around 3%. If spending had grown at 3% annually instead, the state would not have a budget deficit. The document proposes focusing reforms and efficiencies to control spending growth to 3% annually going forward.
Estimation of Import Regression for CanadaGeray Gerayli
1) The document estimates import regression models for Canada from 1975-2014 to analyze the relationship between imports, GDP, and real exchange rate.
2) Eight multiple regression models are estimated with different specifications of the dependent and independent variables. The best-fitting model is Model 5, which uses the natural log of imports as the dependent variable and GDP and the natural log of real exchange rate as independent variables.
3) Model 5 has individually and jointly statistically significant coefficients, the expected negative relationship between imports and real exchange rate, and the lowest AIC and BIC values, indicating it is the preferred specification according to the data analysis in the document.
The document analyzes the future performance of PRAN AMCL LTD using a linear regression model. It finds that:
1) The regression equation indicates profit is influenced by various variables like sales, salary, advertisement etc.
2) There is a very high positive relationship (R=0.813) among the variables but the relationship is not statistically significant.
3) Sales has the most influence on profit but the relationship is also not statistically significant.
4) Analysis of historical profit data from 1999-2013 finds the company has a average annual growth rate of 3.49% and acceleration rate of 3.76%, suggesting future performance will be promising if this trend continues.
The document discusses a company called 3DP that is considering two options - launching a new 3D printer product or selling the patent license. It provides information on the estimated costs of product development and market potential for the product. It also provides details on a potential offer from another company to purchase the patent license. The document asks two questions: 1) Calculate the expected monetary value of the two options and recommend the decision based on financial considerations. 2) Calculate the exchange rate change needed to change the recommended decision and its probability.
This document contains numerical examples related to time value of money calculations. It includes calculations for:
- Present and future value of a single payment
- Present and future value of an annuity
- Net present value
- Internal rate of return
- Multiple internal rates of return
- Reinvestment rate assumptions
The examples demonstrate time value of money principles and calculations for a variety of cash flow patterns over different time periods. Trial and error or spreadsheet tools are suggested to solve the examples.
This chapter introduces multiple regression analysis. Multiple regression allows modeling the relationship between a dependent variable (Y) and two or more independent variables (X1, X2, etc). The key assumptions and outputs of multiple regression are discussed, including the multiple regression equation, R-squared, adjusted R-squared, standard error, and hypothesis testing of individual regression coefficients. An example illustrates estimating a multiple regression model to examine factors influencing weekly pie sales.
Javier Garcia - Verdugo Sanchez - Six Sigma Training - W4 The Binary Logistic...J. García - Verdugo
The document discusses binary logistic regression and provides an example. It analyzes data from a study of 100 men investigating the relationship between age and risk of coronary heart disease. Logistic regression is used to estimate the effect of age on the probability of disease. The analysis finds that for each one year increase in age, the odds of disease increase by 13% (odds ratio of 1.13).
This document analyzes the relationship between US GDP performance and government current expenditure from 1999 to 2009. Regression analysis shows a strong positive linear relationship between the two variables, with current expenditure explaining 85.4% of the variation in GDP over the period. Both GDP and current expenditure showed an increasing trend over time. The regression coefficients, F-test, and correlation coefficient provide strong statistical evidence that increases in government current expenditure are positively associated with increases in US GDP during this period.
This document discusses applying financial statistics to analyze Turkey's economy. It provides data on Turkey's GDP, economic size, and per capita income. It then examines the correlation between GDP per capita and three independent variables: domestic credit, broad money, and services value added. The document estimates a linear regression equation relating GDP to these three variables and performs hypothesis testing to evaluate the model. It finds the model is statistically significant and the independent variables domestic credit and broad money significantly impact GDP, but services does not.
This chapter discusses various factors used in engineering economy to analyze cash flows over time under conditions of interest. It introduces the single-payment compound amount factor (SPCAF) and single-payment present worth factor (SPPWF) for analyzing single payments compounded over time. It also discusses the uniform series present worth factor (USPWF) and capital recovery factor (CRF) for analyzing uniform series of cash flows. Examples are provided to illustrate the calculation of future and present values using these factors under simple and compound interest conditions. Arithmetic and geometric gradient factors are also introduced for cash flows that regularly increase or decrease by a constant amount or percentage.
Banco ABC Brasil had strong financial results in 4Q07. Net income increased 154.6% compared to 4Q06 to R$50.7 million. The credit portfolio grew 71% to R$4,992.2 million with high credit quality maintained. Business segments all saw growth in 4Q07 compared to prior periods. Expenses were well controlled while profitability and efficiency metrics improved. The bank ended 2007 with net income up 93.8% and a solid capital and ratings position supported by its controlling shareholder ABC Banking Corporation.
U.S. Manufacturing Job Gains and Imports, 2001-2011: An AnalysisAaron S. Robertson
The document analyzes the relationship between manufacturing job gains and imports in the United States from 2001-2011. A regression analysis found a moderate negative correlation (r=-0.750) between the two variables, with higher manufacturing job gains associated with lower import levels. The p-value of 0.0078 leads to a rejection of the null hypothesis that there is no correlation, indicating there is a statistically significant correlation between manufacturing jobs and imports over the period studied.
Tesla and Toyota were analyzed through 3 year valuation models and sensitivity analyses. Tesla was found to be overvalued at its current stock price, while Toyota was found to be undervalued. Both companies were also assessed on various financial metrics such as growth rates, profitability, and liquidity. A regression analysis showed a moderate positive correlation between automotive industry sales and total nonfarm payrolls.
Statistics assignment about data driven management scienceRahatulAshafeen
The document describes two linear regression models created to analyze sales and profit before tax data for Abhinav Technologies over 20 years.
The first model for predicting sales had an R^2 of 0.996, indicating the model explained 99.6% of the variability in sales based on material, other incomes, personnel, and interest payments. Only interest payments were not a statistically significant predictor.
The second model for predicting profit before tax had an R^2 of 0.934, showing the model explained 93.4% of the variability in profit based on the same predictor variables. Material and interest payments were not statistically significant for this model.
This document provides solutions to end-of-chapter problems from the 8th edition of the textbook "Engineering Economy" by Leland Blank and Anthony Tarquin. It includes solutions to over 50 problems involving time value of money calculations using factors, arithmetic gradients, geometric gradients, and determining interest rates. The solutions demonstrate applications of present worth, future worth, annual worth, payment, and rate of return formulas.
Similar to The impact of political stability on economic growth (20)
13 Jun 24 ILC Retirement Income Summit - slides.pptxILC- UK
ILC's Retirement Income Summit was hosted by M&G and supported by Canada Life. The event brought together key policymakers, influencers and experts to help identify policy priorities for the next Government and ensure more of us have access to a decent income in retirement.
Contributors included:
Jo Blanden, Professor in Economics, University of Surrey
Clive Bolton, CEO, Life Insurance M&G Plc
Jim Boyd, CEO, Equity Release Council
Molly Broome, Economist, Resolution Foundation
Nida Broughton, Co-Director of Economic Policy, Behavioural Insights Team
Jonathan Cribb, Associate Director and Head of Retirement, Savings, and Ageing, Institute for Fiscal Studies
Joanna Elson CBE, Chief Executive Officer, Independent Age
Tom Evans, Managing Director of Retirement, Canada Life
Steve Groves, Chair, Key Retirement Group
Tish Hanifan, Founder and Joint Chair of the Society of Later life Advisers
Sue Lewis, ILC Trustee
Siobhan Lough, Senior Consultant, Hymans Robertson
Mick McAteer, Co-Director, The Financial Inclusion Centre
Stuart McDonald MBE, Head of Longevity and Democratic Insights, LCP
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3. We selected the top 10 countries which seem
to have the lowest political stability rate
globally.
-.4-.2
0
.2
AFG BDI YEMCAF COD IRQ LBN PAK SDN UKR
Names of the countries
Growth of GDP per capita ave_grGDP
-3-2-1
0
AFG BDI CAF COD IRQ LBN PAK SDN UKR YEM
Names of the countries
Political Stability Index averagePSI
Data:
Time span : 2005-2014
Source:http://www.theglobaleconomy.
com/rankings/transparency_corruption
5. Variable name : Description :
Growth GDP Growth of GDP per capita
Trade “ the openness ” (%GDP)
Debt The central Government debt(%GDP)
grL Growth of Labor force (%)
GFCF Gross Fixed Capital Formation(investments)% GDP
PSI Political Stability Index
6. Should we add it in the model?
-.4-.2
0
.2
0 50 100 150 200 250
The central goverment debt as % GDP
As we notice no
correlation between
the dependent and
independent
variable, we don’t
add Debt2.
7. _cons -.022388 .0326614 -0.69 0.495 -.0873388 .0425628
PSI -.005904 .0118178 -0.50 0.619 -.029405 .0175969
trade -.00006 .0002871 -0.21 0.835 -.0006309 .0005109
Debt .000227 .0001757 1.29 0.200 -.0001223 .0005763
grL -.7999446 .5073365 -1.58 0.119 -1.808839 .2089497
GFCF .002364 .0007654 3.09 0.003 .0008418 .0038861
growthGDP Coef. Std. Err. t P>|t| [95% Conf. Interval]
Total .353566467 89 .003972657 Root MSE = .06003
Adj R-squared = 0.0928
Residual .302735757 84 .003603997 R-squared = 0.1438
Model .050830711 5 .010166142 Prob > F = 0.0210
F(5, 84) = 2.82
Source SS df MS Number of obs = 90
. reg growthGDP GFCF grL Debt trade PSI
Observations=90
R2=0,1438
Prob>F=0,0210 (the probability of estimating
wrong is 0,0210)
8. Autocorrelation
_cons -.001642 .0068771 -0.24 0.812 -.0153334 .0120493
laggeduhat .0992124 .1156011 0.86 0.393 -.1309317 .3293566
uhat Coef. Std. Err. t P>|t| [95% Conf. Interval]
Total .297295455 79 .003763234 Root MSE = .06145
Adj R-squared = -0.0033
Residual .294514334 78 .003775825 R-squared = 0.0094
Model .002781121 1 .002781121 Prob > F = 0.3934
F(1, 78) = 0.74
Source SS df MS Number of obs = 80
. reg uhat laggeduhat
-.4-.3-.2-.1
0
.1
Residuals
-.4 -.3 -.2 -.1 0 .1
laggeduhat
P>|t|=0,393
There is no autocorrelation.
9. Multicollinearity
Gross Fixed
Capital
Formtion(investments)
%GDP
Growth of
Labor
Force(percent)
The
central
goverment
debt as %
GDP
The
openess
(%GDP)
Political
Stability
Index
0
20
40
60
0 20 40 60
0
.05
.1
0 .05 .1
0
100
200
0 100 200
0
50
100
150
0 50 100 150
-3
-2
-1
0
-3 -2 -1 0
PSI -0.0625 -0.4437 -0.0850 0.3939 1.0000
trade 0.1126 -0.0104 0.3025 1.0000
Debt -0.1845 0.2418 1.0000
grL -0.1403 1.0000
GFCF 1.0000
GFCF grL Debt trade PSI
. pwcorr GFCF grL Debt trade PSI
There is no
multicollinearity
between the
independent
variables.
10. Heteroscedasticity
Breusch-Pagan Test
p= 0,5481 > 0,05 accept Ho there is no
heteroscedasticity
Prob > chi2 = 0.5481
chi2(1) = 0.36
Variables: fitted values of uhat
Ho: Constant variance
Breusch-Pagan / Cook-Weisberg test for heteroskedasticity
. hettest
17. As we examine the graph ,we notice that there are no
observations up in the right corner and therefore no
observations have to be deleted.
34 5
6
7 8
9
101314151617181920232425262728 29
30
333435363738394043
44
454647 48
49
5053545556
575859
60
63646566676869707374757677 78
79
808384 85
86
8788899093949596
97
98
99100
0
.1.2.3.4.5
Leverage
0 .1 .2 .3 .4 .5
Normalized residual squared
2
3
4
5
67
8910
12
13
14
15
16
17
18
19
20
22232425
26
27
28 29
30
32
33
34
35
36
37
38
39
40
42
4344
45
46
47 48
49 50
525354
55
56
57
58
59
60
62
63646566
67686970
727374
75
7677
7879
80
82
83
84
85
86
87
88
89
90
92
9394
95
96
97
9899
100
0
.05
.1
.15
.2
Leverage
0 .1 .2 .3 .4 .5
Normalized residual squared
18. A dummy variable is one that takes the value 0 or 1 to indicate the
absence or presence of some categorical effect that may be expected to
shift the outcome.
As the subject of our research focuses on Political Stability ,we have
chosen to enforce our model with a dummy which will separate our
countries to UNSTABLE(A) and VERY UNSTABLE (B) during 2005-2014.
19. So now, we have reached a spot , where we are able to add our
dummy variable to our model. Hence, using our final regression:
As we see ,the dummy
variable is statistically
significant ( p>|z|)
=0.025 expressing
affection on our
dependent variable,
which is the growthGDP.
Averagely, countries A
have 0.510388 more
growth than countries B.
F test that all u_i=0: F(9, 74) = 3.07 Prob > F = 0.0036
rho .59177723 (fraction of variance due to u_i)
sigma_e .0544578
sigma_u .0655678
_cons .10478 .0686549 1.53 0.131 -.0320179 .2415778
dummyPSI .0510388 .0223395 2.28 0.025 .0065264 .0955512
PSI .0175713 .0231657 0.76 0.451 -.0285874 .06373
trade -.0005202 .0005851 -0.89 0.377 -.001686 .0006456
Debt .0002788 .0003094 0.90 0.370 -.0003376 .0008953
grL -3.080095 .7935516 -3.88 0.000 -4.661281 -1.498909
GFCF .0017297 .0011287 1.53 0.130 -.0005194 .0039788
growthGDP Coef. Std. Err. t P>|t| [95% Conf. Interval]
corr(u_i, Xb) = -0.8048 Prob > F = 0.0006
F(6,74) = 4.50
overall = 0.0324 max = 9
between = 0.0228 avg = 9.0
within = 0.2674 min = 9
R-sq: Obs per group:
Group variable: country Number of groups = 10
Fixed-effects (within) regression Number of obs = 90
. xtreg growthGDP GFCF grL Debt trade PSI dummyPSI,fe
20. GFCF ( Fixed Investments) : Positive effect ( statisticly insignificant)
In accordance with Magnus Blomstrom,Robert E.Lipsey Mario
Zejan(August 1993)
Employment : Negative effect
In contrast to Steven Kapsos (December 2005)
Debt : Positive effect ( statistically insignificant )
In accordance with Christina Checherita Westpha, Phillip Rother(
Octomber 2012)
PSI : Positive effect
In accordance with Ari Aisen, Francisco Jose Veiga (January 2011)
Trade : Negative effect ( statistically insignificant )
In contrast to Oscar Afonso (May 2001)
21. Is fixed investment the key of economic growth?
http://www.nber.org/papers/w4436.pdf
The employment intensity of growth: Trends and macroeconomic
determinants
http://www.oit.org/wcmsp5/groups/public/---ed_emp/---emp_elm/documents/publication/wcms_143163.pdf
The impact of high government debt on economic growth and its
channels: An empirical investigation for the euro area
http://www.sciencedirect.com/science/article/pii/S0014292112000876
How Does Political Instability Affect Economic Growth?
https://www.imf.org/external/pubs/ft/wp/2011/wp1112.pdf
The impact of international trade on economic growth
http://wps.fep.up.pt/wps/wp106.pdf
22.
23.
24. 0
204060
0
204060
0
204060
-.4 -.2 0 .2 -.4 -.2 0 .2
-.4 -.2 0 .2 -.4 -.2 0 .2
AFG BDI CAF COD
IRQ LBN PAK SDN
UKR YEM
Density
kdensity growthGDP
normal growthGDP
Density
Growth of GDP per capita
Graphs by Names of the countries
25. 0
.1.2.3
0
.1.2.3
0
.1.2.3
0 50 100 150 0 50 100 150
0 50 100 150 0 50 100 150
AFG BDI CAF COD
IRQ LBN PAK SDN
UKR YEM
Density
kdensity trade
normal trade
Density
The "openess" (%GDP)
Graphs by Names of the countries
26. 0
.05
.1
0
.05
.1
0
.05
.1
0 100 200 300 0 100 200 300
0 100 200 300 0 100 200 300
AFG BDI CAF COD
IRQ LBN PAK SDN
UKR YEM
Density
kdensity Debt
normal Debt
Density
The central goverment debt as % GDP
Graphs by Names of the countries
27. 0
100200300400
0
100200300400
0
100200300400
-.05 0 .05 .1 -.05 0 .05 .1
-.05 0 .05 .1 -.05 0 .05 .1
AFG BDI CAF COD
IRQ LBN PAK SDN
UKR YEM
Density
kdensity grL
normal grL
Density
Growth of Labor Force(percent)
Graphs by Names of the countries
28. 0
.2.4
0
.2.4
0
.2.4
0 20 40 60 0 20 40 60
0 20 40 60 0 20 40 60
AFG BDI CAF COD
IRQ LBN PAK SDN
UKR YEM
Density
kdensity GFCF
normal GFCF
Density
Gross Fixed Capital Formtion(investments) %GDP
Graphs by Names of the countries
29. 024602460246
-3 -2 -1 0
-3 -2 -1 0 -3 -2 -1 0 -3 -2 -1 0
AFG BDI CAF COD
IRQ LBN PAK SDN
UKR YEM Total
Density
kdensity PSI
normal PSI
Density
Political Stability Index
Graphs by Names of the countries
59. -.4-.2
0
.2-.4-.2
0
.2-.4-.2
0
.2
0 50 100 150 0 50 100 150
0 50 100 150 0 50 100 150
AFG BDI CAF COD
IRQ LBN PAK SDN
UKR YEM
The "openess" (%GDP)
Graphs by Names of the countries
60. -.4-.2
0
.2-.4-.2
0
.2-.4-.2
0
.2
0 100 200 0 100 200
0 100 200 0 100 200
AFG BDI CAF COD
IRQ LBN PAK SDN
UKR YEM
The central goverment debt as % GDP
Graphs by Names of the countries
61. -.4-.2
0
.2-.4-.2
0
.2-.4-.2
0
.2
-.02 0 .02 .04 .06 -.02 0 .02 .04 .06
-.02 0 .02 .04 .06 -.02 0 .02 .04 .06
AFG BDI CAF COD
IRQ LBN PAK SDN
UKR YEM
Growth of Labor Force(percent)
Graphs by Names of the countries
62. -.4-.2
0
.2-.4-.2
0
.2-.4-.2
0
.2
0 20 40 60 0 20 40 60
0 20 40 60 0 20 40 60
AFG BDI CAF COD
IRQ LBN PAK SDN
UKR YEM
Gross Fixed Capital Formtion(investments) %GDP
Graphs by Names of the countries
63. -.4-.2
0
.2-.4-.2
0
.2-.4-.2
0
.2
-3 -2 -1 0 -3 -2 -1 0
-3 -2 -1 0 -3 -2 -1 0
AFG BDI CAF COD
IRQ LBN PAK SDN
UKR YEM
Political Stability Index
Graphs by Names of the countries