This presentation comprises highlights from the publication OECD Competition Trends 2024 published in Paris on 6 March 2024 during the OECD Competition Open Day. The full publication can be accessed at oe.cd/comp-trends.
This document provides an overview of machine learning, including definitions, types, steps, and applications. It defines machine learning as a field that gives computers the ability to learn without being explicitly programmed. The document outlines the main types of machine learning as supervised learning, unsupervised learning, semi-supervised learning, and reinforcement learning. It also describes the typical steps in a machine learning process as gathering data, preparing data, choosing a model, training, evaluation, and prediction. Examples of machine learning applications discussed include prediction, image recognition, natural language processing, and personal assistants. Popular machine learning languages and packages are also listed.
Data-driven AI for Self-adaptive Information SystemsAndreas Metzger
Artificial Intelligence (AI) offers tremendous potential to benefit citizens, economy and society. From an industrial point of view, AI means algorithm-based and data-driven information systems that provide machines and people with digital capabilities such as perception, reasoning, learning and even autonomous decision making. AI thereby facilitates information systems to draw conclusions, learn, adapt and adjust parameters accordingly. With recent advances in special-purpose hardware and machine learning algorithms, AI is capable of capturing more and more complex problems. This keynote talk will explore the opportunities that AI offers in building self-adaptive information systems. On the one hand, it will present how ensembles of deep neural networks support proactive decision making for business process execution. On the other hand, it will present how reinforcement learning may be employed to build self-learning information systems. These systems learn from every interaction with their environment in order to dynamically improve themselves during operations. The talk closes with a critical look at the challenges entailed in delivering responsible AI-based information systems.
This knolx is about an introduction to machine learning, wherein we see the basics of various different algorithms. This knolx isn't a complete intro to ML but can be a good starting point for anyone who wants to start in ML. In the end, we will take a look at the demo wherein we will analyze the FIFA dataset going through the understanding of various data analysis techniques and use an ML algorithm to derive 5 players that are similar to each other.
Primer on the application of statistical significance testing for business research purposes.
1) How to use statistics to make more informed decisions (and when not to use).
2) Highlight differences between statistics in science vs business.
3) Highlight assumptions, limitations and best practices.
The document discusses requirements determination in systems analysis and design. It describes how requirements determination transforms high-level business needs into detailed system requirements through techniques like interviews, questionnaires, and joint application development sessions. Requirements elicitation aims to understand the current system and desired improvements, while requirements analysis strategies like root cause analysis and activity analysis help identify high-impact changes.
This document discusses data analytics and related concepts. It defines data and information, explaining that data becomes information when it is organized and analyzed to be useful. It then discusses how data is everywhere and the value of data analysis skills. The rest of the document outlines the methodology of data analytics, including data collection, management, cleaning, exploratory analysis, modeling, mining, and visualization. It provides examples of how data analytics is used in healthcare and travel to optimize processes and customer experiences.
Data refers to raw unorganized facts like numbers, text, images that are meaningless on their own. Information is processed data that has been organized into a meaningful form. Data is collected from various sources like surveys and census and is input using devices. Computers then process this data by manipulating, comparing, sorting and searching it. The output is information displayed on devices that is specific and meaningful to humans. Information depends on data but data does not depend on information.
Scipy 2011 Time Series Analysis in PythonWes McKinney
1) The document discusses statsmodels, a Python library for statistical modeling that implements standard statistical models. It includes tools for linear regression, descriptive statistics, statistical tests, time series analysis, and more.
2) The talk provides an overview of using statsmodels for time series analysis, including descriptive statistics, autoregressive moving average (ARMA) models, vector autoregression (VAR) models, and filtering tools.
3) The discussion highlights the development of statsmodels and the need for integrated statistical data structures and user interfaces to make Python more competitive with R for data analysis and statistics.
BigInsights and Text Analytics.
As enterprises seek to gain operational efficiencies and competitive advantage through greater use of analytics, much of the new information they need to analyze is found in text documents and, increasingly, in a wide variety of social media sites and portals. A critical step in gaining insights from this information is extracting core data from huge volumes of text. That data is then available for downstream analytic, mining and machine learning tools. AQL (Annotator Query Language) is a powerful declarative, rule-based language for the extraction of information from text documents.
Data Analytics For Beginners | Introduction To Data Analytics | Data Analytic...Edureka!
Data Analytics for R Course: https://www.edureka.co/r-for-analytics
This Edureka Tutorial on Data Analytics for Beginners will help you learn the various parameters you need to consider while performing data analysis.
The following are the topics covered in this session:
Introduction To Data Analytics
Statistics
Data Cleaning and Manipulation
Data Visualization
Machine Learning
Roles, Responsibilities and Salary of Data Analyst
Need of R
Hands-On
Statistics for Data Science: https://youtu.be/oT87O0VQRi8
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E-governance refers to the use of information technologies by government agencies to improve access to government services and information. China has made notable progress in developing e-governance since 1999 with projects like the Government Online Project and Golden Bridge Project, which aim to provide online services and information exchange. However, China still faces challenges in fully realizing e-governance goals due to insufficient infrastructure in some areas and a lack of sufficient funding and internet penetration nationwide.
Business Analytics, "Second Edition teaches the fundamental concepts of the emerging field of business analytics and provides vital tools in understanding how data analysis works in today s organizations. Students will learn to apply basic business analytics principles, communicate with analytics professionals, and effectively use and interpret analytic models to make better business decisions. Included access to commercial grade analytics software gives students real-world experience and career-focused value. Author James Evans takes a balanced, holistic approach and looks at business analytics from descriptive, and predictive perspectives.
The document discusses the physical and logical design aspects of system design. Physical design involves graphical representation of internal and external system entities and data flows. It includes user interface, data, and process design to specify how data is input, processed and output. Logical design provides an abstract representation of system processes and data flows using models and diagrams to describe what tasks the system performs without specifying how.
Machine learning is the study of algorithms and statistical models that allow computer systems to perform tasks without being explicitly programmed. It builds mathematical models from sample data to make predictions or decisions. There are four main types of machine learning: supervised learning, unsupervised learning, semi-supervised learning, and reinforcement learning. Machine learning has various applications including web search, computational biology, finance, e-commerce, robotics, and social networks. Key elements of machine learning systems include representation, evaluation, and optimization techniques.
Summary of statistical tools used in spssSubodh Khanal
This document provides an overview of statistical analysis tools that can be used to analyze data, including when to use frequencies, descriptive statistics, chi-square tests, Fisher's exact test, one sample t-tests, paired sample t-tests, and independent sample t-tests. It gives examples of different variable types and scales, and outlines the assumptions and requirements for each statistical test.
Group members and an introduction to information systems are provided. Key concepts around data, information, and knowledge are defined. The document discusses the types of information systems used in organizations and how systems are developed. It also provides definitions for important terms like data, information, organization, and systems development.
This document summarizes common statistical models used in simulation. It discusses queueing systems, inventory and supply chain models, reliability and maintainability models, and models for limited data. Queueing models use exponential, normal, and truncated normal distributions. Inventory models use Poisson, negative binomial, and geometric distributions. Reliability models use exponential, gamma, Weibull, and normal distributions to model time to failure. Models for limited data include uniform, triangular, beta, Bernoulli, binomial, and hyper-exponential distributions.
The document discusses various aspects of term weighting which is important for text retrieval systems, including term frequency, document frequency, inverse document frequency, and how they are used to calculate TF-IDF weights for terms. It also covers stoplists, stemming, and the bag-of-words model which represents text as vectors of word occurrences without considering word order. Term weighting schemes play a major role in the similarity measures used by information retrieval systems to determine document relevance.
The document discusses software process models. It describes the waterfall model, which is a generic process framework for software engineering that defines five framework activities: communication, planning, modeling, construction, and deployment. It also discusses umbrella activities that are applied throughout the process, such as project tracking and control. The waterfall model prescribes distinct activities, actions, tasks, milestones, and work products for software development. However, process models need to be adapted to meet the needs of specific projects.
Information retrieval 10 tf idf and bag of wordsVaibhav Khanna
The bag-of-words model is a simplifying representation used in natural language processing and information retrieval (IR). In this model, a text (such as a sentence or a document) is represented as the bag (multiset) of its words, disregarding grammar and even word order but keeping multiplicity.
This presentation by the OECD secretariat was made during the discussion “The Future of Effective Leniency Programmes: Advancing detection and deterrence” held at the 137th meeting of the OECD Working Party No. 3 on Co-operation and Enforcement on 13 June 2023. More papers and presentations on the topic can be found out at oe.cd/felp.
This presentation by Gaetano LAPENTA, OECD Competition Division, was made during the discussion “The Relationship between FDI Screening and Merger Control Reviews” held at the 139th meeting of the OECD Competition Committee on 30 November 2022. More papers and presentations on the topic can be found out at https://oe.cd/cinf
This presentation by Paulo Burnier (OECD Competition Expert) was delivered during a workshop on mergers held in the framework of the 2021 Virtual African Competition Forum on 29 June 2021.
International Perspective on Advanced Vehicle Technology Deployment Global NCAP
This document summarizes the work of the Towards Zero Foundation (TZF) and Global NCAP in promoting vehicle safety standards internationally. It discusses TZF's support for emerging market NCAP programs in Latin America and Southeast Asia which have increased availability of higher safety rated vehicles. It also outlines TZF campaigns like Stop the Crash Partnership to promote lifesaving technologies like ESC, and calls for all countries to adopt UN vehicle safety regulations to meet the UN's goal of 100% of new vehicles meeting high safety standards by 2030.
This document summarizes statistics on global merger control and competition enforcement from 2015-2019. It finds that most jurisdictions have mandatory pre-merger notification regimes. Over this period, there were over 30,000 merger notifications but fewer than 2,000 prohibition decisions. Merger control budgets increased for most jurisdictions but fines increased more sharply, in some cases exceeding agency budgets by hundreds of times. Common blocked sectors were retail, technology, and transportation. Most decisions were clearances while clearances with remedies and prohibitions each made up under 7% of total decisions.
This document provides an overview and analysis of global competition enforcement trends from 2015 to 2019 based on data from 56 jurisdictions. It finds that total competition budgets increased over the period to reach 1.155 billion euros in 2019. On average, competition agencies had 207 staff and made 10,768 enforcement decisions annually. Cartel enforcement remained active with 449 cartel decisions per year, while abuse of dominance decisions and merger reviews also continued at high levels. Total fines imposed increased substantially over the period, reaching on average over 1 billion euros annually. The report aims to support informed policymaking and improving global competition law and policy.
Rothschild & Co reported results for full-year 2019:
- Group revenue declined 5% to €1,872 million due to lower revenue in Global Advisory.
- Net income attributable to shareholders fell 15% to €243 million, impacted by lower revenue and higher staff costs.
- Assets under management in Wealth & Asset Management increased 17% to €76.0 billion due to strong net new assets.
Higher cost of finance exacerbates a climate investment trap in developing ec...Nadia Ameli
Finance is vital for the green energy transition, but access to low cost finance is uneven as the cost of capital differs substantially between regions. This study shows how modelled decarbonisation pathways for developing economies are disproportionately impacted by different weighted average cost of capital (WACC) assumptions. For example, representing regionally-specific WACC values indicates 35% lower green electricity production in Africa for a cost-optimal 2 °C pathway than when regional considerations are ignored. Moreover, policy interventions lowering WACC values for low-carbon and high-carbon technologies by 2050 would allow Africa to reach net-zero emissions approximately 10 years earlier than when the cost of capital reduction is not considered. A climate investment trap arises for developing economies when climate-related investments remain chronically insufficient. Current finance frameworks present barriers to these finance flows and radical changes are needed so that capital is more equitably distributed.
On 28 April 2021, Shardul Agrawala, Head, Environment and Economy Integration Division, OECD Environment Directorate, presented the OECD report "The Economic Benefits of Air Quality Improvements in Arctic Council Countries".
Presentation from the OECD Workshop “Climate transition scenarios: integrating models into risk assessment under uncertainty and the cost of delayed action” (6 July 2022) - Session 1, Stéphane Dees, and Annabelle De Gaye, Banque de France
BCG has launched its Telco Sustainability Index, designed to capture the four dimensions most relevant to a telco’s environmental strategy. The index tracks the company’s commitment to sustainability, its emissions intensity and that of its upstream and downstream partners, its elimination of waste, and its customer enablement.
This presentation comprises key figures included in the publication OECD COmpetition Trends 2020 released on 26 February 2020 during the OECD Competition Open Day in Paris. The full publication can be found at oe.cd/comp-trends.
- Volkswagen is facing challenges transforming to electric and digital platforms but sees these changes as opportunities to reduce costs and gain market share. The company is investing heavily in dedicated electric vehicle platforms and a new software organization to lead its transformation and better position itself in the increasingly software-defined automotive industry. This strategy aims to make Volkswagen's electric vehicles cost competitive with internal combustion engines and establish Volkswagen as a leading automotive software company.
This document analyzes the Greek economic outlook and provides forecasts through 2020. It discusses three main challenges: consumption needs to shift to investment, fiscal consolidation targets require €14 billion in additional measures, and liquidity must be maintained. Alternative macroeconomic scenarios are modeled. Greek SMEs are important, generating most value and employment, though performance varies greatly. Emerging trends and opportunities in the changing Greek landscape are also examined.
This document summarizes the OECD's analysis of G-20 countries' growth strategies. It discusses the OECD's role in assessing the strategies and quantifying their potential economic impacts. The OECD found over 950 policy commitments in the strategies, spanning areas like investment, employment, competition and trade. Using economic modeling, the OECD estimates these commitments could increase G-20 GDP by 1.8% by 2018, though there is uncertainty in such forecasts. Next steps include finalizing the strategies, monitoring their implementation, and further OECD analysis of fiscal policy impacts.
The Greek economy experienced a crisis characterized by high growth based on consumption and borrowing, which led to reduced competitiveness and twin deficits. As the global financial crisis hit, Greece could no longer finance its deficits and debt, requiring bailouts totaling €245 billion from Eurozone countries and the IMF. This came with austerity measures including spending cuts and tax increases amounting to over 10% of GDP. The recession caused a 25% decline in GDP and tripling of unemployment by 2013. Structural reforms aimed to boost competitiveness and fiscal adjustments reduced deficits, though deflation and depressed demand prolonged the recession.
Analysis of the World Economic Forum Global Competitiveness Report 2017/18 by Dr. Balraj Kistow, Lecturer and Programme Director at the Arthur Lok Jack Graduate School of Business
The document provides an overview of TIM Brasil's business as of April 2020. It discusses TIM's market positioning in Brazil as the country transitions to increased mobile internet and data usage. TIM has transformed its customer base from primarily prepaid to incorporating more postpaid subscribers. The presentation also outlines TIM's portfolio of mobile and home broadband products and services to address evolving customer needs.
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4. 1. Competition staff and nominal budgets
continued growing but real budgets in 2022 decreased.
4
Real competition budget
0
5
10
15
20
25
30
35
40
2015 2016 2017 2018 2019 2020 2021 2022
Real
competition
budget
EUR
Millions
Asia-Pacific Europe Middle East and Africa Americas
Although nominal budgets increased 10%
in 2022, real budget decreased 2.6%
Competition staff
5. 2. Leniency applications increased in all regions
for the first time since 2015
5
Total number of leniency applications
0
100
200
300
400
500
600
2015 2016 2017 2018 2019 2020 2021 2022
All Asia-Pacific Europe Americas Middle East and Africa
6. 3. But cartel decisions decreased, mostly in Europe
6
Average number of cartel decisions
0
5
10
15
20
25
30
2015 2016 2017 2018 2019 2020 2021 2022
Avg
cartel
decisions
Asia-Pacific Middle East and Africa Americas Europe
7. 4. Abuse of dominance investigations and decisions
also declined
7
Average abuse of dominance investigations (left) and decisions
(right)
0
2
4
6
8
10
12
2015 2016 2017 2018 2019 2020 2021 2022
0.0
0.5
1.0
1.5
2.0
2.5
3.0
2015 2016 2017 2018 2019 2020 2021 2022
All OECD Non-OECD
8. 5. As a result, fines imposed decreased in 2022
8
Average fines imposed per jurisdiction by type of infringement
0
20
40
60
80
100
120
2015 2016 2017 2018 2019 2020 2021 2022
Avg
fines
in
EUR
Millions
Cartel Abuse of dominance
9. 6. There was a drop in merger notifications
9
Average merger notifications by region
0
50
100
150
200
250
300
350
2015 2016 2017 2018 2019 2020 2021 2022
Americas Asia-Pacific Europe Middle East and Africa
10. 7. The intervention rate increased significantly in OECD
jurisdictions (as CAs approved more mergers with remedies)
10
Average merger intervention rate
0%
1%
2%
3%
4%
5%
6%
7%
8%
9%
2015 2016 2017 2018 2019 2020 2021 2022
All OECD Non-OECD
The total number of mergers
cleared with remedies in
phase I and II increased 56%.
It went from 169 mergers in
2021 to 263 in 2022.
12. 9. Horizontal theories of harm are the most common in
prohibition decisions
12
Total prohibitions, by theory of harm and whether it relied on a single
or multiple theories of harm, 2015-2022
139
16 16
34
20 23
4
0
20
40
60
80
100
120
140
160
180
200
Horizontal (unilateral) Horizontal (coordinated) Vertical Conglomerate
Total
prohibitions
Single TOH Multiple TOH
13. 10. The industries with most prohibitions between 2015-22
were manufacturing, retail trade and transportation
13
Total prohibitions, by industry (NAICS), 2015-2022
59
28
20 19
16 15
10 9 8 7 5 4 4 2 2 2 2 1 1 1
0
10
20
30
40
50
60
70
Total
prohibitions
14. PREVIOUS OECD COMPETITION TRENDS REPORTS
Full publications available at oe.cd/comp-trends
2020 2021 2022 2023