Obiettivi formativi Learning goals
The course provides a broad introduction to stochastic processes. In particular the aim is
- to give a rigorous introduction to the theory of stochastic processes,
- to discuss the most important stochastic processes in some depth with examples and applications,
- to give the flavour of more advanced work and applications,
- to apply these ideas to answer basic questions in several applied situations including biology, finance and search engine algorithms.
Knowledge and understanding
At the end of the course the students will be familiar with the basic concepts of the theory of stochastic processes in discrete and continuous time and will be able to apply various techniques to study stochastic models that appear in applications.
Applying knowledge and understanding
At the end of the course the students will have the tools to grasp and formalize, in the language of stochastic processes, phenomena that evolve in time and space. The students will have the tools to solve simple applied problems in new environments and broader contexts.
Making judgements
At the end of the course the students will have the tools to evaluate critically and choose between different stochastic models to model phenomena that evolve in time and space. The student will also acquire the necessary language skills to start reading academic books on the topic and research papers.
Communication skills
The students will acquire the intuition and the communication skills necessary to describe phenomena in the mathematical language of stochastic processes. In particular the student will also acquire the rationale behind the stochastic model studied (e.g. the ideas of Markovianity, transience, recurrence, equilibrium, stationarity, long and short-time behaviour...) that is necessary to communicate to specialist and non-specialist audiences.
Learning skills
The students will acquire the methodology and the language to study in a manner that may be largely autonomous and to apply the methodology to the subsequent studies in the area of statistics and finance.
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Obiettivi formativi Questo insegnamento può essere scelto dallo studente all'interno dei corsi della Sapienza, purché coerente con il percorso formativo.
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Obiettivi formativi The Role of International Organizations in Producing Official Statistics
Tentative syllabus
Learning goals
The main objective of this course is to introduce students to the statistical work of International Organizations and their contribution to the production of International Official Statistics. The differences between the statistical work of International Organizations and those of National Statistical Organizations, as well as the specific contribution of International Organizations to the global statistical system will be explained in detail.
Knowledge and understanding
The course is organized in two distinct parts: the first part of the course (12 lessons) will provide students with an introduction to the Global Statistical System, its key institutions and coordination mechanism, and the statistical work of International Organizations; the second part of the course (12 lessons) will familiarize students with the main statistical techniques used in international organizations for the production of official statistics, through hands-on practical training.
In particular, the first part of the course will describe:
1) How the international statistical system is organized: what are the main actors/Institutions involved, what are the key governance bodies, what are the key international statistical frameworks (SNA, BoP, IMTS, SEEA) and standards (including standards on international classifications; code-lists, flag systems) that guide the statistical work at national, regional and global levels; how international statistical standards are developed and implemented. Special focus on the System of National Accounts.
2) The statistical work of International Statistical Organizations: what are the key data sources and how the data flows from national to international organizations is structured; the main quality frameworks used at international level and how the quality of input data is assessed; the techniques used for data validation, editing and imputation; data discrepancies between national and international databases: how they can be explained and addressed; the data dissemination practices of international organizations, including the dissemination of microdata and the challenges it poses in terms of protection of data confidentiality.
3) The demand for new statistics resulting from the 2030 Agenda for Sustainable Development. The evolution of the concept of sustainable development and the ambition of the 2030 Agenda; The Global SDG Indicator Framework and its governance mechanisms; the role of the international Organizations as Custodian Agencies, the data flows between countries and International Organizations
The second part of the course will focus on the following six statistical techniques:
1. Theory and practice of index numbers
2. Composite indices for summarizing multidimensional phenomena
3. Time series and seasonal adjustment
4. Measuring latent variables
5. Measuring SDG progress
6. Using remote sensing data for estimating SDG indicators
Applying knowledge and understanding
At the end of the course, students will have the necessary instruments be start working in an international organization, having acquired an in-depth knowledge of the institutional, methodological, and technical aspect of its statistical work. Moreover, students will become familiar with the main statistics published in international databases; the compilation methodology and time series of selected SDG indicators; the main techniques used for the compilation of index numbers, latent variables, composite indices, trend indices and seasonally adjusted data.
Making judgements
At the end of the course, students will be able to apply their skills in analyzing and interpreting official statistics published by international organizations.
Communication skills
At the end of the course, students will acquire the ability of discussing statistical problems in an international environment and presenting oral and written reports of their practical analyses.
Learning skills
At the end of the course, students will be able to further improve their skills and knowledge of international official statistics by self-study and consultation of international organization databases, which will be helpful for future academic and professional activities.
The Role of international Organizations in Producing Official Statistics
Outline of the course
Theory and Practice of the International Statistical System (12 lessons)
1st lesson
1. Introduction: what is official statistics?
a. Official statistics at national level: the Statistics Law
b. The National Statistical Office and its coordinating role of the National Statistical System
c. Other data producers at national level
d. International organizations as producers of official statistics
2. The International Statistical System: an overview
e. The UN Statistical System
f. Non-UN Statistical Organizations
g. Statistical and Policy Organizations (independence of statistics from political influence)
h. Coordination across international/regional organizations: allocation of responsibilities
3. Data Governance for the global statistical system
a. The UN Statistical Commission and its subsidiary bodies
b. The Regional Statistical Commissions
c. Statistics governance of UN Organizations
d. The Committee of the Chief Statisticians of the UN System
e. The Committee for the Coordination of the Statistical System (CCSA)
2nd lesson
4. International Statistical Standards: Main International Classifications, Code lists and Flags
a. International Family of Classifications
b. Main economic classifications: ISIC; CPC; HS; COICOP; COFOG.
c. Classifications by statistical domain: e.g., Land Cover & Land Use Classification.
d. Country/Area Codes for Statistical Use; Regional groupings.
e. SDMX Observation status codes and flags
3rd lesson
5. International Statistical Frameworks
a. Main International Statistical Frameworks
System of National Accounts
International Merchandise Trade Statistics
Balance of Payments
System of Environmental Economic Accounting
b. How International Statistical Frameworks have been developed and how they continue to evolve.
4th lesson
6. Introduction to the System of National Accounts
a. Overview of national accounts
b. Economic actors and transactions
c. GDP: Production approach
d. GDP: Expenditure approach
e. GDP: Income approach
f. National accounts criticism and challenges
5th lesson
7. Data sources of International Organizations
a. National Statistics System (NSO, line ministries) and other national data providers (NGOs, Research Institutions, private sector, citizens, etc.)
i. Questionnaire design for secondary data collections from National Institutions
b. Direct data collection
ii. Internationally led surveys (LSMS-WB; MICS-UNICEF; DHS-USAID; LFS-ILO).
iii. Questionnaire design for primary data collections (from households; farms, businesses)
c. Geospatial data
d. Big data
6th lesson
8. Statistics Principles and Quality Frameworks
a. UN Fundamental Principles of Official Statistics
b. UN National Quality Assurance Framework
c. IMF Data Quality Assurance Frameworks
d. Principles Governing (International) Statistical Activities (CCSA)
e. Statistical Quality Assurance Framework of International Organizations (UN Statistical Quality Assurance Framework; European Statistics Code of Practice - CoP).
7th lesson
9. Quality Assessments
a. EUROSTAT Survey Manager Checklist and Quality Indicators
b. UN Self-assessment checklist
c. IMF General Data Diss. System (e-GDDS), Special Data Diss. Standard (SDDS)
d. OECD Global Assessment
e. UNECE Global Assessments and Sector Reviews
f. EUROSTAT Peer Review
8th lesson
10. Data editing and Imputation of macro data
a. Data availability at international level: the Statistical Capacity Index
b. Methods and sources for the validation of country data
c. System of editing rules
d. Editing procedures: macro-editing and selective editing
e. Overview of main imputation methods
9th lesson
11. Discrepancies between national and international data
a. Type of data discrepancies
b. Consequences of data discrepancies
c. Possible solutions to resolve data discrepancies.
12. Data validation and country ownership
a. Validation of data disseminated and/or methods of data production.
b. Principles of data validation: IAEG-SDG guidelines of global data flows
c. Different modalities of data validation
10th lesson
13. Data dissemination and key data users
a. Defining user requirements for planning purposes: users-producers’ consultations
b. Relevant information for different type of data users:
a. Central Government/ Ministries
b. Regional/local government
c. Public and media
d. Businesses
e. Academia and Research Institutions
f. Other International Organizations
c. Dissemination of data and metadata
d. Main international statistical databases (WB WDI; OECD.Stat; FAOSTAT)
e. User consultations
f. What should IOs disseminate? Only data and statistics (historical time series) or also statistical analysis (and forecasts)?
11th lesson
14. Protection of data confidentiality and Microdata dissemination
a. Principle of data confidentiality
b. Informed consent of respondent
c. Dissemination of microdata set
d. Anonymisation & Statistical disclosure control
e. Terms of use for microdata dissemination
12th lesson
15. The 2030 Agenda for Sustainable Development and Its Monitoring Framework
a. The evolution of the concept of sustainable development
b. The key differences between the MDGs and the SDGs.
c. Separation between the Political (definition of Goals and Targets) and the Statistical process (definition of the SDG indicator framework)
d. Governance of Global SDG monitoring
e. Role of the international Organizations as Custodian Agencies
f. Data flows between countries and International Organizations
Statistical Techniques (12 lessons)
(1 lesson methodological introduction; 1 lesson laboratory)
13th -14th lessons
1. Theory and Practice of Index numbers
a. Methodology (Problems in constructing index numbers; Methods of constructing index numbers; Laspeyer’s, Paasche’s, Marshall-Edge worth’s and Fisher’s ideal index numbers; Test of Consistency; Chain Base Index Numbers; Shifting of Base year)
b. Calculation of the Consumer Price index
15th – 16th lessons
2. Composite indices for summarizing multidimensional phenomena
a. Methodology (Pros and cons in the use of composite indices; Pre-requisites for the compilation of composite indices; Steps in the production of composite indices; Criteria for choosing the ‘best’ method)
b. Calculation of the Human Development Index
17th-– 18th lessons
3. Time series and seasonal adjustment
a. Methodology (The components of a time series; The causes of seasonality; Why to adjust for seasonality; Decomposition models; Official software procedures for seasonal adjustment)
b. The use of RJDemetra+: Illustrative example
19th-– 20th lessons
4. Measuring latent variables
a. The Rasch model
b. The calculation of the Food insecurity Experience Scale (SDG indicator 2.1.2)
21st – 22nd lessons
5. Measuring SDG progress
a. Methodology
b. Calculating the distance from the SDG target
c. Calculating the likelihood of achieving the SDG target by 2030
23rd – 24th lessons
6. Using remote sensing data for estimating SDG indicators
a. Combining remote sensing and survey data for producing global estimates of land cover
b. The Mountain Green Cover Indicator (SDG indicator 15.4.1)
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Obiettivi formativi Learning goals
The primary goal of the course on “Sample Surveys” is that student should learn the main problems and methods in sampling from finite populations. They should be able to formalize and plan the whole process of data collection and analysis in observational studies.
In more detail, students should be able to plan a sample survey, to choose a sampling design, to plan the data collection, as well as to analyze real data and to estimate quantities of interest.
Knowledge and understanding
After attending the course the students know and understand the main methodologies in planning a sample survey, as well as in dealing with non-sampling sources of error, such as nonresponses and missing values, measurement errors, list imperfections. Furthermore, students should be able to analyze real data and to estimate quantities of interests, such as means and proportions.
Applying knowledge and understanding
At the end of the course the students are able to formalize and plan the whole process of data collection and analysis in observational studies. They should be able to manage the most important (i) sampling designs and (ii) point and interval estimators, as well as the main methodologies to deal with missing values, measurement errors, list imperfections. Moreover, they should be able to apply the methods to the data and to interpret the results.
Making judgements
Students develop critical skills through the application of sampling and estimation methodologies to a wide range of contexts.
They also develop the critical sense through the comparison of different solutions and the analysis of results.
Communication skills
Students, through their study, should acquire the technical-scientific language of the discipline, to be used in their activity.
Learning skills
Students who pass the exam have learned a method of analysis to be used in the data collection and analysis from finite populations."
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Obiettivi formativi Learning goals
The primary learning goal of this course is that of exposing students to the body of econometric techniques that are customised to economics applications. The aim of the course is to review this body of techniques, to demonstrate their use in hands-on style, drawing on as wide a range of example as possible, and to interpret each set of results in ways that are most useful to read and represent economic phenomena.
Knowledge and understanding.
The course is supposed to broaden students' knowledge of the various econometric techniques that appear in the economics literature, their properties and the way these are applied to data in order to verify economic theory.
Applying knowledge and understanding.
Upon successful completion of the course, students will be able to carry out a wide range of tasks in empirical economics, such as recognising the most suitable approaches to analyse the data at hand in order to capture and model its regularities, and intelligibly convey its messages to both economists and broader audiences.
Making judgements.
The course develops in a way to spurs students on researching empirical evidence of competing economic theories by respecting the nature of convenient data.
Communication skills.
Through study and hands-on sessions, students will acquire the terminology characterising the discipline, which they are required to use in both written and oral dissemination.
Learning skills.
Students who complete the course successfully will be acquainted with a method of analysis enabling them to endeavour the main economic issues from an empirical point of view.
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Obiettivi formativi Learning goals
Knowledge at an intermediate and advanced level of the main issues in official statistics with special attention to data quality
Knowledge and understanding
Knowledge and understanding of statistical methods within the topics of official statistics in an changing environment
Applying knowledge and understanding
Ability to apply statistical methods for official statistics problems with emphasis on the data quality process
Making judgements
Ability of choosing appropriate methods in different problems in official statistics with emphasis on the data quality process
Communication skills
Ability of communicating results of the analyses in official statistics with emphasis on the data quality process
Learning skills
Students acquire skills useful to approach more advanced topics in official statistics and data quality management
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Obiettivi formativi Learning goals
Students will be introduced to the following topics
1. The Monetary, banking and financial statistics.
Why Bank of Italy collects statistics and what collects. Application: recent developments of the banks.
2. The financial accountsThe financial accounts structure.Household wealth after Piketty: an international comparison.The financial structure of the companies.
3. The balance of payments and international investment positionThe Italian balance of payments: the structure and recent developments.The procedure on excessive macroeconomic imbalances in Europe.Funds held abroad by the families.
4. The sample surveys of the Bank of ItalyThe survey on Household Income: recent results and a long-term look.The survey on inflation and growth expectations.
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Obiettivi formativi Goals. With this activity (based on internships) students merge their academic knowledge with practical skills.
They also develop independent judgement and communication skills.
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