The document provides an overview of modeling and forecasting techniques using EViews software. It discusses the main forecasting steps, which include preparing and processing data, estimating linear equations and pool data equations, univariate time series modeling and forecasting, and using error correction models for long-term and short-term prediction. The document uses examples of consumer price index data to demonstrate preparing data, identifying appropriate time series models like ARMA, and generating forecasts using Box-Jenkins and Holt-Winters exponential smoothing methods.
The Outcome of our Square Pi Digital Investment is a What If? Metric Map, Key to Stakeholder Investments https://www.slideshare.net/slideshow/comments-on-square-pi-key-to-the-investmentpdf/267325383
20120612 07 - Portail qualimétrie mis en oeuvre chez Schneider SquoringLeClubQualiteLogicielle
Schneider Electric uses a software qualimetry approach called SQuORE (Source Code Quality Indicators) to measure and improve source code quality. SQuORE provides a quality model, analysis model, and technical debt metric to evaluate code. It utilizes static analysis tools and stores results in a centralized database for reporting. SQuORE is being progressively deployed across Schneider Electric projects, with over 30% of software now impacted. Feedback from users emphasizes making configurations easy to use and tailoring evaluations to specific project needs.
Managerial Accounting Tools for Business Decision Making Canadian 5th Edition...EmmanuelCamerons
This document provides an assignment classification table and characteristics for a chapter in a managerial accounting textbook. The table outlines the key study objectives covered in the chapter, self-study questions, brief exercises, do it review exercises, problems, and a Bloom's taxonomy table correlating the objectives with the exercises. It also includes a table describing characteristics of assigned problems such as difficulty level and time allotted. The document provides resources and guidance for students to learn about classifying costs, calculating cost of goods manufactured, and preparing financial statements for a manufacturer.
Muhammad Ismail Sheikh has developed several software and hardware projects during his graduate studies at Ryerson University in Electrical and Computer Engineering. Some of his software projects include developing parallel image matching and queuing model simulation Android applications, and an ECG monitoring system. His hardware projects involve analyzing a DC motor, designing a data acquisition system, and building a linear waveform generator and decimal counter. He has also won or placed in several engineering competitions through innovative designs.
This document describes Hanan Naser's research estimating and forecasting Bahrain's quarterly GDP using simple regression and factor models. It finds that a simple regression model augmented with intercept correction provided the most reliable estimates. Several models were able to shorten the lag in official GDP estimates by one week. The research adapts forecasting techniques used for developed countries to the case of Bahrain as an oil-producing developing country.
The Digital Twin For Production OptimizationYokogawa1
Digitalization is fundamental to the development of Repsol’s strategy for the future. To meet emerging challenges, the business units have developed an ambitious program comprising multiple projects. Within Repsol’s Industrial Business, development of a refinery digital twin leads the digitalization program. The digital twin allows the business to maximize production while optimizing energy consumption. This session will explore the digital twin project objectives to improve the accuracy and scope of the Refinery LP model that the Programming and Planning departments use to make decisions regarding crude feedstock purchasing and refinery unit operations. It will also report on the context of the business goals achieved, the technology and architecture developed, and the connectivity deployed to communicate results. It will conclude with a description of how enhancements to existing technology work with new technologies to improve value.
In this presentation we report about ongoing research to extend Value-Based Analysis to Project Selection within a Portfolio of related projects. We define a new value –based indicator, “Project Value to Portfolio Value” (PV2PV) to asses the added value of a new project to the value of the firm’s actual portfolio of projects. The PV2PV indicator allows us to establish the modified ranking of the individual projects of the portfolio should a new incoming project be included in the firm’s portfolio of standing projects. When a new project is included in the portfolio the entire portfolio has to be reprogrammed since it will be affected in terms of their risks, capital costs and cash flows. We will evaluate a new incoming project in terms of the total value added to the portfolio in terms of the PV2PV indicator. An additional advantage of this new indicator is that it can be used as well in the continuous monitoring and evaluation of a given project portfolio.
The Outcome of our Square Pi Digital Investment is a What If? Metric Map, Key to Stakeholder Investments https://www.slideshare.net/slideshow/comments-on-square-pi-key-to-the-investmentpdf/267325383
20120612 07 - Portail qualimétrie mis en oeuvre chez Schneider SquoringLeClubQualiteLogicielle
Schneider Electric uses a software qualimetry approach called SQuORE (Source Code Quality Indicators) to measure and improve source code quality. SQuORE provides a quality model, analysis model, and technical debt metric to evaluate code. It utilizes static analysis tools and stores results in a centralized database for reporting. SQuORE is being progressively deployed across Schneider Electric projects, with over 30% of software now impacted. Feedback from users emphasizes making configurations easy to use and tailoring evaluations to specific project needs.
Managerial Accounting Tools for Business Decision Making Canadian 5th Edition...EmmanuelCamerons
This document provides an assignment classification table and characteristics for a chapter in a managerial accounting textbook. The table outlines the key study objectives covered in the chapter, self-study questions, brief exercises, do it review exercises, problems, and a Bloom's taxonomy table correlating the objectives with the exercises. It also includes a table describing characteristics of assigned problems such as difficulty level and time allotted. The document provides resources and guidance for students to learn about classifying costs, calculating cost of goods manufactured, and preparing financial statements for a manufacturer.
Muhammad Ismail Sheikh has developed several software and hardware projects during his graduate studies at Ryerson University in Electrical and Computer Engineering. Some of his software projects include developing parallel image matching and queuing model simulation Android applications, and an ECG monitoring system. His hardware projects involve analyzing a DC motor, designing a data acquisition system, and building a linear waveform generator and decimal counter. He has also won or placed in several engineering competitions through innovative designs.
This document describes Hanan Naser's research estimating and forecasting Bahrain's quarterly GDP using simple regression and factor models. It finds that a simple regression model augmented with intercept correction provided the most reliable estimates. Several models were able to shorten the lag in official GDP estimates by one week. The research adapts forecasting techniques used for developed countries to the case of Bahrain as an oil-producing developing country.
The Digital Twin For Production OptimizationYokogawa1
Digitalization is fundamental to the development of Repsol’s strategy for the future. To meet emerging challenges, the business units have developed an ambitious program comprising multiple projects. Within Repsol’s Industrial Business, development of a refinery digital twin leads the digitalization program. The digital twin allows the business to maximize production while optimizing energy consumption. This session will explore the digital twin project objectives to improve the accuracy and scope of the Refinery LP model that the Programming and Planning departments use to make decisions regarding crude feedstock purchasing and refinery unit operations. It will also report on the context of the business goals achieved, the technology and architecture developed, and the connectivity deployed to communicate results. It will conclude with a description of how enhancements to existing technology work with new technologies to improve value.
In this presentation we report about ongoing research to extend Value-Based Analysis to Project Selection within a Portfolio of related projects. We define a new value –based indicator, “Project Value to Portfolio Value” (PV2PV) to asses the added value of a new project to the value of the firm’s actual portfolio of projects. The PV2PV indicator allows us to establish the modified ranking of the individual projects of the portfolio should a new incoming project be included in the firm’s portfolio of standing projects. When a new project is included in the portfolio the entire portfolio has to be reprogrammed since it will be affected in terms of their risks, capital costs and cash flows. We will evaluate a new incoming project in terms of the total value added to the portfolio in terms of the PV2PV indicator. An additional advantage of this new indicator is that it can be used as well in the continuous monitoring and evaluation of a given project portfolio.
Dear students get fully solved assignments
Send your semester & Specialization name to our mail id :
“ help.mbaassignments@gmail.com ”
or
Call us at : 08263069601
Moving toward Portal Prosperity and Remote Building will increase your personal prosperity as well as industrial engineering competence and intellectual property ownership... an overview of Productivity and Maintenance of Intellectual Property and Asset Management Systems, A Major Shift in Management by the Morning Star is highlighted in Part III
This document discusses how segmentation would be implemented in a project to classify pixels in microscopy images as belonging to LDL particles or the background. It proposes using a convolutional neural network trained on a dataset of microscopy images and corresponding manually created segmentation masks. To address the small size of the original dataset, data augmentation is applied by mirror flipping the images, tripling the size of the dataset. Further augmentation by rotating images was considered but abandoned due to the computational expense of training on a much larger dataset. The segmentation method aims to classify each pixel rather than ignore spatial information about objects.
The presentation describes Elements of cost and classification, cost estimation approaches and method, break even analysis, steps and limitation with examples
How Will Knowledge Graphs Improve Clinical Reporting WorkflowsNeo4j
This document discusses GSK's goal of improving clinical reporting workflows using knowledge graphs. It describes GSK's current clinical data flow as involving numerous handoffs, transformations and integrations between different data standards and domains. GSK envisions a "Google Translate" for clinical data using a clinical knowledge graph that connects different data domains and allows for greater automation, analytics and accelerated decision making. The document outlines GSK's phased approach to testing the feasibility of building a clinical knowledge graph MVP using Neo4j to ingest, enrich, analyze and report on clinical trial data in graph form.
Information and Communication Technology (ICT) is not limited to software development, mobile apps and ICT service management but percolates into all kind of products with the so-called Internet of Things.
ICT depends on software where defects are common. Developing software is knowledge acquisition, not civil engineering. Thus knowledge might be missing and consequently leading to defects and failures to perform. In turn, operating ICT products involves connecting ICT services with human interaction, and is error-prone as well. There is much value in delivering software without defects. However, up to now there exists no agreed method of measuring defects in ICT. UML sequence diagrams is a software model that describes data movements between actors and objects and allows for automated measurements using ISO/IEC 19761 COSMIC. Can we also use it for defect measurements that allows applying standard Six Sigma techniques to ICT by measuring both functional size and defect density in the same model? It allows sizing of functionality and defects even if no code is available. ISO/IEC 19761 measurements are linear, thus fitting to sprints in agile development as well as for using statistical tools from Six Sigma.(IT Confidence 2014, Tokyo (Japan))
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This document provides instructions and questions for an assignment on cost and managerial accounting concepts. It asks the student to:
1. Analyze supply chain management and value chain analysis concepts for a furniture company called KVK Industries to help control costs.
2. Prepare schedules of cost of goods manufactured and an income statement for KVK Industries using provided inventory, cost and sales data.
3. Calculate total and unit costs for different output levels of Product M using estimated variable costs and fixed costs.
4. Calculate operating income for two promotional options for Product N and advise which option to choose.
It also provides additional questions involving job order costing calculations for overhead application rates and total/unit costs for
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This document provides instructions and questions for an assignment on cost and managerial accounting concepts. It asks the student to:
1. Analyze supply chain management and value chain analysis concepts for a furniture company to control costs, including constructing a schedule of cost of goods manufactured and income statement.
2. Calculate output levels, unit costs, and operating income for one of the company's products under different promotional scenarios.
3. Compute overhead rates and total/unit costs for a job order costing case study involving two production departments.
4. Briefly discuss advantages and disadvantages of activity-based costing.
The assignment is divided into two parts worth a total of 100 marks and includes quantitative problems, short
Driving Innovation with Kanban at Jaguar Land RoverLeanKit
Find out how Kanban is accelerating product design and development at Jaguar Land Rover.
Watch the recorded webinar here: https://vimeo.com/172780037
Hamish McMinn, Automotive and IT Project Manager, will explain how Kanban is improving time, cost and quality across new vehicle development projects at Jaguar Land Rover.
You'll learn:
-Why new product development provides rich opportunities for continuous process improvement.
-Benefits and challenges of transferring agile software techniques to hardware design and development.
-How to visualize work, focus on flow and increase cross-functional collaboration using LeanKit.
Hamish will share learnings from the initial pilot project, and how Kanban is now being scaled across multiple engineering teams.
Mainframes handle 30 billion business transactions each day and 87% of all credit card transactions*, they are not traditionally associated with flexible, fail-fast development approaches. Can we bring the practices of agile, CI/CD and fully automated deployments to applications running on a mainframe? During our talk, we'll tell you a story about test automation; redefining the smallest testable unit of a program. And we'll discuss our learnings from introducing continuous integration and agile practices to the world of insurance and mainframes.
*9 Mainframe statistics that may surprise you
1. Which of the following is INCORRECT regarding the process capab.docxjackiewalcutt
1. Which of the following is INCORRECT regarding the process capability index Cpk
Productivity can be improved by
Increasing inputs while holding outputs steady
Decreasing outputs while holding inputs steady
Increasing inputs and outputs in the same proportion
Increasing outputs while holding inputs steady
2. Productivity can be improved by
Increasing inputs while holding outputs steady
Decreasing outputs while holding inputs steady
Increasing inputs and outputs in the same proportion
Increasing outputs while holding inputs steady
3. Which of the following statements is INCORRECT regarding critical paths?
The path that takes the longest time to complete in a project is the critical path.
Activities on the critical path must have zero slack time.
Some non-critical activities may have zero slack time.
For any project, the (expected) project completion time is equal to the (expected) time duration of the project’s critical path.
4. Suppose a project team has arrived at the following time estimates for an activity: a = 4 days, m = 6 days, and b = 8 days. What is the variance involved in this activity?
0.111
0.250
0.444
0.694
5. Suppose you are asked to determine the Lower Control Limit for a p-chart for quality control purposes. Samples are taken from the production line. The fraction defective is 0.008 and the standard deviation is 0.002 based on the samples. Set z = 3. Which of the following is the LCL of the p-chart?
0.001
0.002
0.006
0.013
6. The least squares method is to find out the intercept and the slope of a regression line that minimizes the sum of the squared differences between
observed values of the independent variable and predicted values of the independent variable
observed values of the independent variable and predicted values of the dependent variable
observed values of the dependent variable and predicted values of the dependent variable
None of the three is correct.
7. Which of the following statements is INCORRECT regarding corporate missions?
They reflect a company's purpose.
They indicate what a company intends to contribute to society.
They are formulated after strategies are known.
They define a company's reason for existence.
8. Given forecast errors of -2, 5, 10, and -3, what is the mean absolute deviation (MAD)?
2.5
3
4
5
9. Which of the following best describes the process focus strategy?
Appropriate for high-volume, low-variety production
Equipment or processes are arranged based on the progressive steps by which a product is made.
Also known as flow shop
Appropriate for low-volume, high-variety production
10. According to the definition of design quality,
Quality is the degree of excellence at an acceptable price
Quality depends on how well the product fits consumer preferences
Even though quality cannot be defined, you know what it is
Quality is the degree to which a specific product conforms to design specifications
11. Which of the f ...
The document is an agenda for the Neo4j GraphDay event in Italy on October 11, 2022. The agenda includes sessions on Neo4j use cases from ENEL, CERVED and SOGEI. There will also be a panel discussion with these companies and Neo4j. The day will cover the latest Neo4j product news, professional services, and basic Neo4j training. Key speakers include Riccardo Ciarlo from Neo4j and Marco Bessi who will discuss when connected data is critical.
Managerial Accounting Tools for Business Decision Making 6th Edition Weygandt...nenoliruzu
This document provides an assignment classification table and answers to questions for a chapter on process costing. It includes:
- A table that classifies learning objectives, questions, exercises and problems by level of difficulty and time required.
- Answers to 22 questions on topics like the flow of costs in process cost systems, preparing production cost reports, computing equivalent units, and more.
- Solutions to 7 brief exercises involving journal entries, computing equivalent units and unit costs, and preparing production cost reports.
The document provides information and examples to help understand key concepts in process costing systems, from classifying assignments to solving specific accounting problems.
HIS 2017 Peter Ladkin- Rigorous-Assurance Points in Software Developmentjamieayre
Almost fifty years ago, a dependability crisis in software was noted by an international meeting of computer scientists in Garmisch-Partenkirchen. Stored-program computers were just a couple of decades old. We are now approaching the seventieth anniversary of stored-program computers, and they are ubiquitous. In the half-century since the Garmisch meeting, the technology of software dependability has advanced immeasurably. But much of it remains unused in everyday software development. Like most engineered artifacts, software is built to some purpose. That purpose belongs to the “documentation” of the artifact, as do assurances that the built object is fit for the purpose. The dependability of the software depends essentially upon its purpose, and thereby its documentation. A number of us are concerned that standards for critical software development, for example IEC 61508-3, lag years, even decades, behind the state of the art. In 2010, with the help of some eminent colleagues, I formulated a collection of 26 points at which objective properties of the software and documentation could be rigorously assured using industrially-mature techniques, and often were not. None of them appeared in IEC 61508-3. After seven years of discussion, including further research on industrial maturity commissioned from Bernd Sieker, the German National Committee for functional safety of computer-based systems formulated a proposal to be presented to the IEC for a standards document based on those assurance points. I introduce those techniques in this talk.
Dear students get fully solved assignments
Send your semester & Specialization name to our mail id :
“ help.mbaassignments@gmail.com ”
or
Call us at : 08263069601
Moving toward Portal Prosperity and Remote Building will increase your personal prosperity as well as industrial engineering competence and intellectual property ownership... an overview of Productivity and Maintenance of Intellectual Property and Asset Management Systems, A Major Shift in Management by the Morning Star is highlighted in Part III
This document discusses how segmentation would be implemented in a project to classify pixels in microscopy images as belonging to LDL particles or the background. It proposes using a convolutional neural network trained on a dataset of microscopy images and corresponding manually created segmentation masks. To address the small size of the original dataset, data augmentation is applied by mirror flipping the images, tripling the size of the dataset. Further augmentation by rotating images was considered but abandoned due to the computational expense of training on a much larger dataset. The segmentation method aims to classify each pixel rather than ignore spatial information about objects.
The presentation describes Elements of cost and classification, cost estimation approaches and method, break even analysis, steps and limitation with examples
How Will Knowledge Graphs Improve Clinical Reporting WorkflowsNeo4j
This document discusses GSK's goal of improving clinical reporting workflows using knowledge graphs. It describes GSK's current clinical data flow as involving numerous handoffs, transformations and integrations between different data standards and domains. GSK envisions a "Google Translate" for clinical data using a clinical knowledge graph that connects different data domains and allows for greater automation, analytics and accelerated decision making. The document outlines GSK's phased approach to testing the feasibility of building a clinical knowledge graph MVP using Neo4j to ingest, enrich, analyze and report on clinical trial data in graph form.
Information and Communication Technology (ICT) is not limited to software development, mobile apps and ICT service management but percolates into all kind of products with the so-called Internet of Things.
ICT depends on software where defects are common. Developing software is knowledge acquisition, not civil engineering. Thus knowledge might be missing and consequently leading to defects and failures to perform. In turn, operating ICT products involves connecting ICT services with human interaction, and is error-prone as well. There is much value in delivering software without defects. However, up to now there exists no agreed method of measuring defects in ICT. UML sequence diagrams is a software model that describes data movements between actors and objects and allows for automated measurements using ISO/IEC 19761 COSMIC. Can we also use it for defect measurements that allows applying standard Six Sigma techniques to ICT by measuring both functional size and defect density in the same model? It allows sizing of functionality and defects even if no code is available. ISO/IEC 19761 measurements are linear, thus fitting to sprints in agile development as well as for using statistical tools from Six Sigma.(IT Confidence 2014, Tokyo (Japan))
حل واجب be310 & 00966597837185 @ مهندس أحمد حلول واجبات الجامعة العربية المفتوحةحل واجبات عمل ابحاث
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This document provides instructions and questions for an assignment on cost and managerial accounting concepts. It asks the student to:
1. Analyze supply chain management and value chain analysis concepts for a furniture company called KVK Industries to help control costs.
2. Prepare schedules of cost of goods manufactured and an income statement for KVK Industries using provided inventory, cost and sales data.
3. Calculate total and unit costs for different output levels of Product M using estimated variable costs and fixed costs.
4. Calculate operating income for two promotional options for Product N and advise which option to choose.
It also provides additional questions involving job order costing calculations for overhead application rates and total/unit costs for
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This document provides instructions and questions for an assignment on cost and managerial accounting concepts. It asks the student to:
1. Analyze supply chain management and value chain analysis concepts for a furniture company to control costs, including constructing a schedule of cost of goods manufactured and income statement.
2. Calculate output levels, unit costs, and operating income for one of the company's products under different promotional scenarios.
3. Compute overhead rates and total/unit costs for a job order costing case study involving two production departments.
4. Briefly discuss advantages and disadvantages of activity-based costing.
The assignment is divided into two parts worth a total of 100 marks and includes quantitative problems, short
Driving Innovation with Kanban at Jaguar Land RoverLeanKit
Find out how Kanban is accelerating product design and development at Jaguar Land Rover.
Watch the recorded webinar here: https://vimeo.com/172780037
Hamish McMinn, Automotive and IT Project Manager, will explain how Kanban is improving time, cost and quality across new vehicle development projects at Jaguar Land Rover.
You'll learn:
-Why new product development provides rich opportunities for continuous process improvement.
-Benefits and challenges of transferring agile software techniques to hardware design and development.
-How to visualize work, focus on flow and increase cross-functional collaboration using LeanKit.
Hamish will share learnings from the initial pilot project, and how Kanban is now being scaled across multiple engineering teams.
Mainframes handle 30 billion business transactions each day and 87% of all credit card transactions*, they are not traditionally associated with flexible, fail-fast development approaches. Can we bring the practices of agile, CI/CD and fully automated deployments to applications running on a mainframe? During our talk, we'll tell you a story about test automation; redefining the smallest testable unit of a program. And we'll discuss our learnings from introducing continuous integration and agile practices to the world of insurance and mainframes.
*9 Mainframe statistics that may surprise you
1. Which of the following is INCORRECT regarding the process capab.docxjackiewalcutt
1. Which of the following is INCORRECT regarding the process capability index Cpk
Productivity can be improved by
Increasing inputs while holding outputs steady
Decreasing outputs while holding inputs steady
Increasing inputs and outputs in the same proportion
Increasing outputs while holding inputs steady
2. Productivity can be improved by
Increasing inputs while holding outputs steady
Decreasing outputs while holding inputs steady
Increasing inputs and outputs in the same proportion
Increasing outputs while holding inputs steady
3. Which of the following statements is INCORRECT regarding critical paths?
The path that takes the longest time to complete in a project is the critical path.
Activities on the critical path must have zero slack time.
Some non-critical activities may have zero slack time.
For any project, the (expected) project completion time is equal to the (expected) time duration of the project’s critical path.
4. Suppose a project team has arrived at the following time estimates for an activity: a = 4 days, m = 6 days, and b = 8 days. What is the variance involved in this activity?
0.111
0.250
0.444
0.694
5. Suppose you are asked to determine the Lower Control Limit for a p-chart for quality control purposes. Samples are taken from the production line. The fraction defective is 0.008 and the standard deviation is 0.002 based on the samples. Set z = 3. Which of the following is the LCL of the p-chart?
0.001
0.002
0.006
0.013
6. The least squares method is to find out the intercept and the slope of a regression line that minimizes the sum of the squared differences between
observed values of the independent variable and predicted values of the independent variable
observed values of the independent variable and predicted values of the dependent variable
observed values of the dependent variable and predicted values of the dependent variable
None of the three is correct.
7. Which of the following statements is INCORRECT regarding corporate missions?
They reflect a company's purpose.
They indicate what a company intends to contribute to society.
They are formulated after strategies are known.
They define a company's reason for existence.
8. Given forecast errors of -2, 5, 10, and -3, what is the mean absolute deviation (MAD)?
2.5
3
4
5
9. Which of the following best describes the process focus strategy?
Appropriate for high-volume, low-variety production
Equipment or processes are arranged based on the progressive steps by which a product is made.
Also known as flow shop
Appropriate for low-volume, high-variety production
10. According to the definition of design quality,
Quality is the degree of excellence at an acceptable price
Quality depends on how well the product fits consumer preferences
Even though quality cannot be defined, you know what it is
Quality is the degree to which a specific product conforms to design specifications
11. Which of the f ...
The document is an agenda for the Neo4j GraphDay event in Italy on October 11, 2022. The agenda includes sessions on Neo4j use cases from ENEL, CERVED and SOGEI. There will also be a panel discussion with these companies and Neo4j. The day will cover the latest Neo4j product news, professional services, and basic Neo4j training. Key speakers include Riccardo Ciarlo from Neo4j and Marco Bessi who will discuss when connected data is critical.
Managerial Accounting Tools for Business Decision Making 6th Edition Weygandt...nenoliruzu
This document provides an assignment classification table and answers to questions for a chapter on process costing. It includes:
- A table that classifies learning objectives, questions, exercises and problems by level of difficulty and time required.
- Answers to 22 questions on topics like the flow of costs in process cost systems, preparing production cost reports, computing equivalent units, and more.
- Solutions to 7 brief exercises involving journal entries, computing equivalent units and unit costs, and preparing production cost reports.
The document provides information and examples to help understand key concepts in process costing systems, from classifying assignments to solving specific accounting problems.
HIS 2017 Peter Ladkin- Rigorous-Assurance Points in Software Developmentjamieayre
Almost fifty years ago, a dependability crisis in software was noted by an international meeting of computer scientists in Garmisch-Partenkirchen. Stored-program computers were just a couple of decades old. We are now approaching the seventieth anniversary of stored-program computers, and they are ubiquitous. In the half-century since the Garmisch meeting, the technology of software dependability has advanced immeasurably. But much of it remains unused in everyday software development. Like most engineered artifacts, software is built to some purpose. That purpose belongs to the “documentation” of the artifact, as do assurances that the built object is fit for the purpose. The dependability of the software depends essentially upon its purpose, and thereby its documentation. A number of us are concerned that standards for critical software development, for example IEC 61508-3, lag years, even decades, behind the state of the art. In 2010, with the help of some eminent colleagues, I formulated a collection of 26 points at which objective properties of the software and documentation could be rigorously assured using industrially-mature techniques, and often were not. None of them appeared in IEC 61508-3. After seven years of discussion, including further research on industrial maturity commissioned from Bernd Sieker, the German National Committee for functional safety of computer-based systems formulated a proposal to be presented to the IEC for a standards document based on those assurance points. I introduce those techniques in this talk.
This document discusses various aspects of financial ratio analysis, including:
1) Calculating and analyzing key ratios such as the current ratio, inventory turnover, days sales outstanding, and profitability ratios for a company.
2) Using the DuPont analysis and extended DuPont equation to break down return on equity.
3) The potential limitations and qualitative factors to consider when evaluating a company's ratios and future performance.
The document provides an overview of key financial statements (balance sheet, income statement, statement of cash flows) and concepts (accounting income vs cash flow, EVA, taxes). It includes examples from a company called D'Leon that recently expanded its operations. The expansion increased D'Leon's sales but resulted in negative net income, cash flow, and EVA in 2002 compared to 2001. D'Leon financed the expansion using external debt.
This document provides an overview of financial management. It discusses career opportunities in finance including money/capital markets and investments. The responsibilities of financial staff are to maximize stock value through forecasting, planning, decisions on investments/financing, coordinating/controlling transactions, and managing risk. Forms of business include sole proprietorships, partnerships, and corporations. Corporations have the goal of shareholder wealth maximization through stock price increases. Agency relationships exist between shareholders/managers and shareholders/creditors.
Strategic supply chain management operates at the highest level and involves long-term decisions about product development, customers, manufacturing, inventory, suppliers, and logistics that align with overall corporate strategy. These strategic decisions determine the overall direction of the company's supply chain and are refined at tactical and operational levels. The goal is to deliver customer orders accurately and on time while minimizing costs to optimize the supply chain.
This chapter discusses political risk faced by multinational corporations and strategies to manage risk. It examines how companies evaluate macro-level country risks and micro-level industry and sector risks. The chapter presents a framework to assess three dimensions of political risk: transfer risks relating to movement of capital and payments; operational risks relating to constraints on local operations; and ownership control risks relating to restrictions on ownership and control. It also discusses quantitative and qualitative techniques used to analyze risk, as well as integrative, protective, and proactive strategies companies employ to mitigate risk and develop productive government relations. Finally, it addresses challenges in managing alliances and joint ventures.
The document discusses key findings about the oil and gas industry and energy transitions from an IEA analysis. It finds that:
1) The oil and gas industry faces the challenge of balancing short-term returns with its long-term license to operate as societies demand reductions in emissions alongside energy.
2) No company will be unaffected by clean energy transitions, so every part of the industry needs to consider how to respond.
3) So far, investment by oil and gas companies outside their core business has been less than 1% of total capital expenditure.
Presentation of the Guidelines 2016_ English.pptxMamdouh Mohamed
This document provides guidelines for emerging oil and gas producing countries on good governance practices. It discusses establishing a strategic vision for the petroleum sector that is aligned with the national development plan. Key recommendations include conducting public consultations to set priorities, planning for long-term success, and reassessing objectives every 3-5 years. It also addresses attracting qualified investors through transparent licensing processes, collecting geological data to reduce risk, and establishing clear prequalification criteria for bidders. Frontier areas may require different licensing formats than more prospective acreage to generate investor interest.
Political risk analysis evaluates risks faced by governments, investors, and corporations from political instability and policy changes. It assesses risks from shifts in political power, conflicts, corruption, and other events. Political risk includes risks from a country's political system, economic system, legal framework, social stability, corruption, and security issues. Many actors underestimate political risks and rely too heavily on economic analysis rather than specialized political risk assessments. A thorough political risk analysis examines a country's government, policy process, political culture, and both domestic and external actors and public opinion. It also considers factors like governance, rule of law, and challenges to state authority from opposition groups or international actors.
Political risk analysis evaluates risks faced by governments, investors, and corporations from political instability and policy changes. It assesses risks from shifts in political power, conflicts, corruption, and other events. Political risk includes risks from a country's political system, economic system, legal framework, social stability, corruption, and security issues. Many actors underestimate political risks and rely too heavily on economic analysis rather than specialized political risk assessments. A thorough political risk analysis examines a country's government, policy process, political culture, actors, and public opinion to evaluate potential risks.
Peru has a National Civil Defense System (SINADECI) that coordinates disaster risk reduction (DRR) efforts. The National Institute of Civil Defense (INDECI) leads SINADECI and implements the National Plan for Disaster Prevention and Response. Key aspects of Peru's DRR system include its legal framework, institutional structures at national and sub-national levels, and sectoral incorporation of DRR into policies. Regional cooperation on DRR occurs through participation in initiatives like the Andean Strategy. Strengths include participation of all sectors in SINADECI, while weaknesses include need for improved coordination between actors and implementation of DRR plans.
The document discusses potential topics for an energy chapter in the Transatlantic Trade and Investment Partnership (TTIP) agreement between the EU and US. It notes that while an energy chapter could increase energy security and trade, it may also face opposition and have negative environmental impacts if it leads to increased fossil fuel production and use. Any energy chapter would need to ensure the EU's energy transition goals are not undermined and promote cooperation on renewable energy and efficiency. Key issues that could be addressed include reducing barriers to trade in green technologies, developing common emission reduction policies, and transatlantic collaboration on sustainable energy areas like smart grids and energy storage. Overall, the document analyzes both benefits and risks that would need to be weighed in considering
The document discusses heteroskedasticity in regression analysis. It defines heteroskedasticity as unequal variance of the error terms, unlike homoskedasticity which assumes equal variance. This can affect statistical tests by underestimating standard errors. The document outlines various tests to detect heteroskedasticity including graphical tests and formal tests like Breusch-Pagan. It also discusses resolving heteroskedasticity using generalized least squares and weighted least squares to produce efficient estimates.
This document provides an overview of the EViews command language and programming. It describes the four main components of the EViews command language: commands, functions, object views and procs, and object data members. It provides examples of common commands like wfopen, series, and equation. It also discusses functions, object views and procs, data members, and basic programming concepts in EViews like variables, control structures like if/else and for loops, and program arguments.
The document provides guidance on defining a product for export market analysis. It discusses defining the core, actual, and augmented elements of a product. The core product is the basic problem-solving benefit. The actual product encompasses physical attributes, and the augmented product includes additional services. Understanding these elements aids in segmentation, positioning and identifying competitors. It also explains how to determine a product's Harmonized System (HS) code for international trade and national tariff line (NTL) codes for specific countries to aid market research.
The document provides an introduction to using Trade Map indicators to conduct market scanning and select target export markets. It discusses key concepts like identifying target markets, comparing markets across criteria like size, growth, and competition using standardized scores. Trade Map is introduced as an online tool that provides trade data indicators needed for market scanning, like market size, growth rates, unit values, and competition levels. The document emphasizes benchmarking growth rates and interpreting unit values to better understand market dynamics. It also highlights limitations of mirror trade data and demonstrates how to assign scores to criteria in a market scan analysis to identify the most attractive markets.
This document provides guidance on conducting market research to gather trade information. It outlines the steps to systematically organize research, including identifying relevant sources, recording findings, analyzing information, and understanding market implications. Key sources of trade information discussed include institutional websites, international market research companies, and tools like CBI's Market Intelligence Platform. The document emphasizes a structured approach to research using frameworks like the 9Ps to comprehensively gather and record up-to-date, reliable intelligence on target markets.
1. Elemental Economics - Introduction to mining.pdfNeal Brewster
After this first you should: Understand the nature of mining; have an awareness of the industry’s boundaries, corporate structure and size; appreciation the complex motivations and objectives of the industries’ various participants; know how mineral reserves are defined and estimated, and how they evolve over time.
Economic Risk Factor Update: June 2024 [SlideShare]Commonwealth
May’s reports showed signs of continued economic growth, said Sam Millette, director, fixed income, in his latest Economic Risk Factor Update.
For more market updates, subscribe to The Independent Market Observer at https://blog.commonwealth.com/independent-market-observer.
2. Elemental Economics - Mineral demand.pdfNeal Brewster
After this second you should be able to: Explain the main determinants of demand for any mineral product, and their relative importance; recognise and explain how demand for any product is likely to change with economic activity; recognise and explain the roles of technology and relative prices in influencing demand; be able to explain the differences between the rates of growth of demand for different products.
Lecture slide titled Fraud Risk Mitigation, Webinar Lecture Delivered at the Society for West African Internal Audit Practitioners (SWAIAP) on Wednesday, November 8, 2023.
Independent Study - College of Wooster Research (2023-2024) FDI, Culture, Glo...AntoniaOwensDetwiler
"Does Foreign Direct Investment Negatively Affect Preservation of Culture in the Global South? Case Studies in Thailand and Cambodia."
Do elements of globalization, such as Foreign Direct Investment (FDI), negatively affect the ability of countries in the Global South to preserve their culture? This research aims to answer this question by employing a cross-sectional comparative case study analysis utilizing methods of difference. Thailand and Cambodia are compared as they are in the same region and have a similar culture. The metric of difference between Thailand and Cambodia is their ability to preserve their culture. This ability is operationalized by their respective attitudes towards FDI; Thailand imposes stringent regulations and limitations on FDI while Cambodia does not hesitate to accept most FDI and imposes fewer limitations. The evidence from this study suggests that FDI from globally influential countries with high gross domestic products (GDPs) (e.g. China, U.S.) challenges the ability of countries with lower GDPs (e.g. Cambodia) to protect their culture. Furthermore, the ability, or lack thereof, of the receiving countries to protect their culture is amplified by the existence and implementation of restrictive FDI policies imposed by their governments.
My study abroad in Bali, Indonesia, inspired this research topic as I noticed how globalization is changing the culture of its people. I learned their language and way of life which helped me understand the beauty and importance of cultural preservation. I believe we could all benefit from learning new perspectives as they could help us ideate solutions to contemporary issues and empathize with others.
How Does CRISIL Evaluate Lenders in India for Credit RatingsShaheen Kumar
CRISIL evaluates lenders in India by analyzing financial performance, loan portfolio quality, risk management practices, capital adequacy, market position, and adherence to regulatory requirements. This comprehensive assessment ensures a thorough evaluation of creditworthiness and financial strength. Each criterion is meticulously examined to provide credible and reliable ratings.
Falcon stands out as a top-tier P2P Invoice Discounting platform in India, bridging esteemed blue-chip companies and eager investors. Our goal is to transform the investment landscape in India by establishing a comprehensive destination for borrowers and investors with diverse profiles and needs, all while minimizing risk. What sets Falcon apart is the elimination of intermediaries such as commercial banks and depository institutions, allowing investors to enjoy higher yields.
In a tight labour market, job-seekers gain bargaining power and leverage it into greater job quality—at least, that’s the conventional wisdom.
Michael, LMIC Economist, presented findings that reveal a weakened relationship between labour market tightness and job quality indicators following the pandemic. Labour market tightness coincided with growth in real wages for only a portion of workers: those in low-wage jobs requiring little education. Several factors—including labour market composition, worker and employer behaviour, and labour market practices—have contributed to the absence of worker benefits. These will be investigated further in future work.
1. Modeling and
forecasting on EVIEWS
TRAINING PROVIDED BY NASREDDINE DRIDI 2021
STATISTICAL ENGINEER
DIRECTOR OF MACROECONOMIC FORECASTS
2. Main forecasting steps
I. Preparing and processing the required data
II. Elaboration of linear equations (sectoral value added, production, intermediate
consumption) and exploiting them for forecasting
III. Estimate the pool data equations (IPI idustrual sectoriel production indicator)
IV. Estimate the equations system
V. Time Series: Univariate Modeling (CPI) and Forecasting
VI. Targeting ECModels for long-term and short-term prediction
NASREDDINE DRIDI : TRAINING 2021 2
3. I. Preparing and processing the required data
Date Variable1 Variable2
D1 V11 V21
D2 V12 V22
D3 V13 V31
D4 V14 V41
Date Individu Variable1 Variable2
D1 1 V111 V211
D2 1 V112 V212
D3 1 V113 V311
D1 2 V121 V221
D2 2 V122 V222
D3 2 V123 V223
D1 3 V131 V231
D2 3 V132 V232
D3 3 V133 V233
Data for estimate Pool Data
Data for estimate Time series
NASREDDINE DRIDI : TRAINING 2021 3
4. I. Preparing and processing the
required data
NASREDDINE DRIDI : TRAINING 2021 4
5. I. Preparing and processing the
required data
NASREDDINE DRIDI : TRAINING 2021 5
6. I. Preparing and processing the
required data
For Annual Data : 1983 : 2021
For semestriel Data : 1983S1 : 2021S2
For trimestriel Data : 1983T1 : 2021T2
For mensuel Data : start date 1983:1 End date 2021:12
For weekly Data : nombre of month : nombre of day : year exp: 08:10:1983
NASREDDINE DRIDI : TRAINING 2021 6
7. I. Preparing and processing the
required data
Exemple
NASREDDINE DRIDI : TRAINING 2021 7
8. I. Preparing and processing the
required data
Import Data : Proc/Import/Read text-lotus-Excel
NASREDDINE DRIDI : TRAINING 2021 8
9. I. Preparing and processing the
required data
Import Data : Proc/Import/Read text-lotus-Excel
NASREDDINE DRIDI : TRAINING 2021 9
10. I. Preparing and processing the
required data
Convert data from annual to quarterly : TMM Money market rate
NASREDDINE DRIDI : TRAINING 2021 10
11. I. Preparing and processing the
required data
Convert data from annual to quarterly
NASREDDINE DRIDI : TRAINING 2021 11
12. I. Preparing and processing the
required data
Convert data from ammual to quarterly
NASREDDINE DRIDI : TRAINING 2021 12
13. I. Preparing and processing the
required data
Convert data from ammual to quarterly
NASREDDINE DRIDI : TRAINING 2021 13
البيانات تحويل
إلى السنوية
أي ربعية
من تحويل
األقل التكرار
التكرار إلى
األعلى
14. I. Preparing and processing the
required data
Convert data from ammual to quarterly
NASREDDINE DRIDI : TRAINING 2021 14
15. I. Preparing and processing the
required data
Generate a new variable
NASREDDINE DRIDI : TRAINING 2021 15
16. II. Estmation of linear equations
Estimate Equation: Quick/Estimate Equation
NASREDDINE DRIDI : TRAINING 2021 16
17. II. Estmation of linear equations : Multiple regression
Estimate Equation: Resids
NASREDDINE DRIDI : TRAINING 2021 17
18. II. Estmation of linear equations : Multiple regression
Residual Test: Pas d’autocorrelation des résidus
NASREDDINE DRIDI : TRAINING 2021 18
19. II. Estmation of linear equations : Multiple regression
white Test: Pas d’autocorrelation des résidus P-value>5% we accepte the homoscedasticity
hypothesis H0
NASREDDINE DRIDI : TRAINING 2021 19
20. II. Estmation of linear equations : Multiple regression
Breush-Godfrey Test: Pas d’autocorrelation des résidus
P-value>5% we don’t reject the no correlation
hypothesis H0
NASREDDINE DRIDI : TRAINING 2021 20
21. II. Estmation of linear equations : Multiple regression
Test of Multicollinearity :
NASREDDINE DRIDI : TRAINING 2021 21
22. II. Estmation of linear equations : Multiple regression
Test of Multicollinearity :
NASREDDINE DRIDI : TRAINING 2021 22
23. II. Estmation of linear equations : Multiple regression
Test of Multicollinearity : No multicolinearity منخفض المتعدد الخطي التداخل
NASREDDINE DRIDI : TRAINING 2021 23
24. II. Estmation of linear equations : Multiple regression
Reset test of Ramsey: H0 :the model is well specified vs H1 : the model is incorrectly specified
P-value>5% we don’t reject the H0 hypothesis
NASREDDINE DRIDI : TRAINING 2021 24
25. II. Estmation of linear equations : Multiple regression
Stability test of Chow: H0 :the model is stable vs H1 : the model is not stable
P-value<5% 2001 is a brekpoint
NASREDDINE DRIDI : TRAINING 2021 25
26. II. Estmation of linear equations : Multiple regression
Forecast quality:
NASREDDINE DRIDI : TRAINING 2021 26
27. III. Estimate the pool data equations (IPI idustrual
sectoriel production indicator)
Create a pool data project
NASREDDINE DRIDI : TRAINING 2021 27
28. III. Estimate the pool data equations (IPI idustrual
sectoriel production indicator)
Create a pool data project
we must introduce the individual
codes
NASREDDINE DRIDI : TRAINING 2021 28
29. III. Estimate the pool data equations (IPI idustrual
sectoriel production indicator)
Create a pool data project
NASREDDINE DRIDI : TRAINING 2021 29
30. III. Estimate the pool data equations (IPI idustrual
sectoriel production indicator)
Import pool data
NASREDDINE DRIDI : TRAINING 2021 30
31. III. Estimate the pool data equations (IPI idustrual
sectoriel production indicator)
Import pool data
NASREDDINE DRIDI : TRAINING 2021 31
32. III. Estimate the pool data equations (IPI idustrual
sectoriel production indicator)
Import pool data
NASREDDINE DRIDI : TRAINING 2021 32
33. III. Estimate the pool data equations (IPI idustrual
sectoriel production indicator)
Data representation
NASREDDINE DRIDI : TRAINING 2021 33
34. III. Estimate the pool data equations (IPI idustrual
sectoriel production indicator)
Unit Root Test
NASREDDINE DRIDI : TRAINING 2021 34
35. III. Estimate the pool data equations (IPI idustrual
sectoriel production indicator)
Descriptive Statistics
NASREDDINE DRIDI : TRAINING 2021 35
36. III. Estimate the pool data equations (IPI idustrual
sectoriel production indicator)
𝑦𝑖𝑡 = ∁ + 𝛼𝑖 + 𝛽𝑖𝑡𝑋𝑖𝑡 + 𝜀𝑖𝑡
cte Indivual effect Vector of estimators Vector of variables residue
Random individual effect:
𝑦𝑖𝑡 = ∁ + 𝛽𝑖𝑡𝑋𝑖𝑡 + 𝛼𝑖 + 𝜀𝑖𝑡
𝑈𝑖𝑡 = 𝛼𝑖 + 𝜀𝑖𝑡
Fixe individual effect:
𝑦𝑖𝑡 = ∁ + 𝛼𝑖 + 𝛽𝑖𝑡𝑋𝑖𝑡 + 𝜀𝑖𝑡
NASREDDINE DRIDI : TRAINING 2021 36
37. III. Estimate the pool data equations (IPI idustrual
sectoriel production indicator)
Pool Estimation
Estimation
Pool
Random Individual effect
NASREDDINE DRIDI : TRAINING 2021 37
38. III. Estimate the pool data equations (IPI idustrual
sectoriel production indicator)
Pool Estimation : Random Individual Effect
NASREDDINE DRIDI : TRAINING 2021 38
39. III. Estimate the pool data equations (IPI idustrual
sectoriel production indicator)
Pool Estimation : Fixed Individual Effect
NASREDDINE DRIDI : TRAINING 2021 39
40. III. Estimate the pool data equations (IPI idustrual
sectoriel production indicator)
Hausman Test: Random Individual Effect
NASREDDINE DRIDI : TRAINING 2021 40
We accept H0: Random
individuel effect
41. III. Estimate the pool data equations (IPI idustrual
sectoriel production indicator)
Random Individual Effect
NASREDDINE DRIDI : TRAINING 2021 41
42. III. Estimate the pool data equations (IPI idustrual
sectoriel production indicator)
Make system : Fixed Individual Effect
NASREDDINE DRIDI : TRAINING 2021 42
43. III. Estimate the pool data equations (IPI idustrual
sectoriel production indicator)
Pool Estimation : Fixe Individual Effect
NASREDDINE DRIDI : TRAINING 2021 43
44. III. Estimate the pool data equations (IPI idustrual
sectoriel production indicator)
IPI forecasting
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45. IV. Time Series: Univariate Modeling (CPI) and
Forecasting
Exemple : Consumption price Index (CPI)
View/Correlogram
Existance of Unit root
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46. IV. Time Series: Univariate Modeling (CPI) and
Forecasting
Exemple : Consumption price Index (CPI)
View/Correlogram
NASREDDINE DRIDI : TRAINING 2021 46
47. IV. Time Series: Univariate Modeling (CPI) and
Forecasting
Exemple : Consumption price Index (CPI)
View/Correlogram
Unit Root
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48. IV. Time Series: Univariate Modeling (CPI) and
Forecasting
Exemple : Consumption price Index (CPI)
View/Correlogram
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49. IV. Time Series: Univariate Modeling (CPI) and
Forecasting
Exemple : Consumption price Index (CPI)
Process is identified from the functions of autocorrelation and partial autocorrelation
AR(p) process : the partial
autocorrélation of ordre p+1 is null
MA(q) process : The partial
autocorrélation of ordre q+1 is null
The possible process are AR(1),
MA(1), ARMA(1,1)
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50. IV. Time Series: Univariate Modeling (CPI) and
Forecasting
Exemple : Consumption price Index (CPI)
Estimation of ARMA(1,1) process
the
component
is not
significant
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51. IV. Time Series: Univariate Modeling (CPI) and
Forecasting
Exemple : Consumption price Index (CPI)
Estimation of AR(1) process
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52. IV. Time Series: Univariate Modeling (CPI) and
Forecasting
Exemple : Consumption price Index (CPI)
Make Risidual Test : unit Root Test
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53. IV. Time Series: Univariate Modeling (CPI) and
Forecasting
Exemple : Consumption price Index (CPI)
Make Risidual Test : unit Root Test
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We rejet H0 hypothesis:
Resid are stationnary
54. IV. Time Series: Univariate Modeling (CPI) and
Forecasting
Exemple : Consumption price Index (CPI)
Forecast : Box-jenkins
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55. IV. Time Series: Univariate Modeling (CPI) and
Forecasting
Exemple : Consumption price Index (CPI)
Forecast
NASREDDINE DRIDI : TRAINING 2021 55
56. IV. Time Series: Univariate Modeling (CPI) and
Forecasting
Exemple : Consumption price Index (CPI)
Forecast : Non parametric method :Lissage expononciel Double: Holt –winters non saisonnière
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57. IV. Time Series: Univariate Modeling (CPI) and
Forecasting
Exemple : Consumption price Index (CPI)
Forecast : Non parametric method :Lissage expononciel Double: Holt –winters non saisonnière
IPC 2020
ECModel 6,5
Box-Jenkis 4,48
Holt-winters 6,68
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58. V. Time series: multivariate study
Causality Test : CPI-M3-NEER
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59. V. Time series: multivariate study
Causality Test : View/Granger Causality
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We accept the
hypothesis of
causality from
M3 to IPC
60. V. Time series: multivariate study
Model VAR: Objects/New Objecs/VAR
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61. V. Time series: multivariate study
Vector Autoregression Estimate
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62. V. Time series: multivariate study
View/Lag Structure/Block Exogeneity Tests
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NEER
Exogenous
variable
63. V. Time series: multivariate study
Model VAR: VAR Specification
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64. VI. Targeting ECModels for long-term and short-term
prediction
Data Base
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65. VI. Targeting ECModels for long-term and short-term
prediction
Modeling 3 equations with ECModels : 1.producer price index 2.PCI 3.private consumption
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66. VI. Targeting ECModels for long-term and short-term
prediction
Cointegration Test : Test de johanson
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67. VI. Targeting ECModels for long-term and short-term
prediction
Cointegration Test : Test de johanson
Existence of at least two cointegration relations
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68. VI. Targeting ECModels for long-term and short-term
prediction
Cointegration Test : Estimation of VECM(1) Model
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𝐷 𝑌𝑡 = 𝐷 𝑋𝑡 + σ(𝑌𝑡−1 − 𝑋𝑡−1)
𝜎 < 0
𝐷 𝑌𝑡 = 𝐷 𝑋𝑡 + σ𝜀𝑡−1
69. VI. Targeting ECModels for long-term and short-term
prediction
Cointegration Test : Estimation of VECM(1) Model
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the long-
term
relation
the Short-term
relation
the return to long-term
equilibrium takes 14 month
70. VI. Targeting ECModels for long-term and short-term
prediction
Cointegration Test : Test of Ljung-Box
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71. VI. Targeting ECModels for long-term and short-term
prediction
Cointegration Test : Test of Ljung-Box
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72. VI. Targeting ECModels for long-term and short-term
prediction
Estimate ECModel : Cointegration Price Idex equation
Force de rappelle
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73. VI. Targeting ECModels for long-term and short-term
prediction
Estimate ECModel : Cointegration real wage equation
Force de rappelle
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74. VI. Targeting ECModels for long-term and short-term
prediction
simultaneous equation system
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75. VI. Targeting ECModels for long-term and short-term
prediction
simultaneous equation system
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76. VI. Targeting ECModels for long-term and short-term
prediction
simultaneous equation system : exp Production Function CES
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Bloc à estimer pour chaque secteur.
Stock de capital du secteur i:
ki
t = yi
t ― s (cki
t ― pyi
t) + (s―1) gki.t + k0
Emploi total dans le secteur i:
li
t = yi
t + s (wi
t ― pyi
t) + (s ― 1)gli.t + l0
Prix de la valeur ajoutée du secteur i:
pyi
t = π0 (cki
t ― gki.t) + (1― π0) (wi
t ― gli.t) + py0
77. VI. Targeting ECModels for long-term and short-term
prediction
simultaneous equation system : The estimators
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78. VI. Targeting ECModels for long-term and short-term
prediction
simultaneous equation system : All variables of Model
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Inflation
Forecast
79. VI. Targeting ECModels for long-term and short-term
prediction
choice of hypothesis
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