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NAEC Innovation LAB Workshops and Seminars

 

 

The NAEC Innovation LAB is developing innovative projects drawing on talents from across Directorates and mixing different skills, including as part of the OECD Smartdata Framework. As a platform for collaboration with wider communities, the LAB is helping develop links and make use of expertise and data outside the Organisation, including in national governments, academic institutions, think-tanks and the private sector.

1-3 July 2019 - Fundamentals of Machine Learning for Economists

Michal Andrle, Senior Economist at the IMF Research Department

The course will be a set of lectures and example applications (Matlab/Python code examples will be provided) based on a course that Michal and his colleagues gave at the IMF (programme).

The course aims to provide an in-depth overview of the main concepts and techniques of machine learning. It is aimed both at those who are interested in understanding or eventually applying these statistical techniques and those with some or no experience of machine learning, aiming to give a stronger underlying framework and set out the breadth of issues. In addition, he will cover “causal inference”, which is of particular interest at the OECD given our efforts to identify the impact of policy on outcomes. This will draw on the very recent literature in this area and will focus on the idea of acknowledging specification/model searching in statistical inference and the concept of “principled” model search using adaptive ML approaches (lasso, random forests).

17 April 2019 - NAEC masterclasses

NAEC and its partners held master classes with some of the world’s leading practitioners on complexity, network analysis and agent-based modelling

>> Agenda (pdf) >> Watch the webcast - am / pm

Complexity Economics

Led by Alan Kirman, Chief Advisor for NAEC, CAMS-EHESS, Paris

=> Complexity and Economics (pdf)

Elena Rovenskaya, Programme Director, Advanced Systems Analysis, IIASA

=> Towards a Systems Perspective on National Well-being (pdf)

Agent-Based Modelling

Led by Robert Axtell, Chair of the Department of Computational Social Science at George Mason University, and Santa Fe Institute

Networks and Systemic Risk

Led by Thomas Hurd, Professor of Mathematics, McMaster University, Toronto

=> Introduction to Financial Networks and Systemic Risk (pdf)

Macroeconomics

Led by Matheus Grasselli, Professor of Mathematics, McMaster University and the Fields Institute, Toronto

=> An Introduction to Stock-flow Consistent Models in Macroeconomics (pdf)

8 April 2019 - Causal Machine Learning: Heterogeneous Impacts of a Welfare Experiment

A presentation, organised by the NAEC Innovation LAB and the Centre of Entrepreneurship, SME, Regions and Cities, by Anthony Strittmatter, Professor for Econometrics at the Swiss Institute for Empirical Economic Research (SEW-HSG), University of St. Gallen in Switzerland

Abstract: Recent studies have proposed causal machine learning (CML) methods to estimate conditional average treatment effects (CATEs). In this study, I investigate whether CML methods add value compared to conventional CATE estimators by re-evaluating Connecticut’s Jobs First welfare experiment. This experiment entails a mix of positive and negative work incentives. Previous studies show that it is hard to tackle the effect heterogeneity of Jobs First by means of CATEs. I report evidence that CML methods can provide support for the theoretical labor supply predictions. Furthermore, I document reasons why some conventional CATE estimators fail and discuss the limitations of CML methods.

12 February 2019 - Why Big Data Needs Small Data

Professor Roberto Rigobon, Professor of Applied Economics at the MIT Sloan School of Management

A discussion on how to combine big and small data to construct better national statistics in the context of MIT and Harvard’s Billion Prices project. Professor Rigobon will talk about the advantages and the limitations of using big data technique for economic measurement and the possible extension to our area of expertise, measuring competition with prices in services sectors and the links with policy regulations. He will illustrate with concrete examples the IT architecture put in place to collect unstructured data from the web and online retail platforms, such as Walmart and Amazon, the process designed to transform these data into a structured dataset suitable for the daily measurement of CPI inflation in a set of countries. From his experience, we will consider the feasibility of replicating such an approach in the context of the NAEC Innovation LAB and discuss future collaboration.

>> Watch the webcast

7 February 2019 - Brainstorm on Big Data

Big data has the potential to shed new light on policy questions but also requires researchers to approach problems in a different way. The OECD’s Smart Data Strategy is addressing a range of issues around big data and the use of new sources of data. The NAEC Innovation LAB can help in developing applications of big data to policy questions.

A discussion bringing together several OECD directorates to look at how big data could be used to bring new policy insights and how, practically, we can develop some projects that would show this and provide a stronger foundation for working with such data in the future. The aim is to identify the most promising policy questions where big data could be applied in the OECD, what the approach might be and what sources of data would be required.

24 January 2019 - Development Co-operation Directorate (DCD) FLITS Project

Frans Lammersen, Senior Policy Analyst, OECD Development Co-operation Directorate, and colleagues

Discussion about the DCD FLITS project, which aims to break down silos between different DCD communities (i.e. policy, statistics and evaluation).  Through the use of a so-called intelligent reader tool or semantic analysis, the project will contribute to efforts to create the ONE Sight for developing, accessing and sharing information and knowledge on OECD’s work-in-progress and the NAEC Innovation LAB for diversifying and strengthening the OECD’s analytical tools.

14-16 January 2019 - 10 Years After the Crisis - Modelling Meets Policy Making

The 2008 financial crisis posed unprecedented challenges to practitioners and policy makers around the world. Researchers responded in tandem by re-examining the approaches to model financial markets and their interactions with the real economy. Agent-based models, networks, dynamical systems, and mean-field games became part of the emerging research area of systemic risk alongside more traditional economic models.

In a joint OECD NAEC-Fields Institute workshop in Toronto, leading academic experts and policy makers reflected on the lessons learned over the past 10 years and discussed recent advances in modelling of the financial system with the aim of a sustainable, inclusive and stable economy.

=> Summary of conference (pdf)

The first day of the workshop featured mini-courses targeted towards graduate students, postdoctoral fellows and other young researchers

Complexity Economics
Alan Kirman, NAEC Initiative

Agent-Based Models in Economics

Blake LeBaron, Brandeis International Business School
Alissa Kleinnijenhuis, University of Oxford

Asset Price Bubbles: Economics, Mathematics, and Statistics

Matheus Grasselli, McMaster University

Networks and Systemic Risk
Thomas Hurd, McMaster University

Blockchains and Distributed Ledgers in Retrospective and Perspective

Alex Lipton, Co-Founder and CTO, Silamoney and MIT

29 November 2018 - Machine learning and interpretability

Marcin Detyniecki, Head of Data Science and R&D, AXA Data Innovation Lab

Discussion on machine learning and interpretability, which is key to convincing policymakers to use the results of machine learning.

>> Watch the webcast

15 November 2018 - Agent-based modelling/networks

Eleonora MavroediOECD Economics Department

A discussion on the use of agent-based modelling/networks, drawing on her participation in the Sante Fe Institute Complex System Summer School and on-going projects.

23 October 2018 - Policy Experiments

Andy Haldane, Chief Economist and Executive Director of Monetary Analysis and Statistics at the Bank of England

His seminar on "Policy Experiments (pdf)" endorsed the work of the NAEC Innovation LAB.


As a scientific method, economists have gone from telling stories, to using empirics to developing models. All still have an important role in the policy domain – indeed, the role of each is being reshaped and improved by new data and new technologies. The missing ingredient, at least for macro-economic policy purpose so far, has been experimental methods. These hold great promise for the future, as recent examples in the monetary policy and regulatory policy domain illustrate.

>> Watch the webcast

27 June 2018 - Modelling housing using Agant Based Modelling (ABM)

Marc Hinterschweiger and Arzu Uluc (Bank of England) and Adrián Carro of the Institute for New Economic Thinking (INET)

The Bank of England/Oxford team led an in-depth discussion of their work using ABM to model the housing market at the Bank of England which went into depth on the design, calibration and simulation of their model.

>> Watch the webcast

7 June 2018 - Semantics

Neil Thompson (MIT)

Neil Thompson presented his paper on “Science Is Shaped by Wikipedia: Evidence From a Randomized Control Trial” with a focus on the technical aspects of his work on semantic analysis and discussed the use of AI-based techniques in economics. Caroline Paunov, of the OECD Science, Technology and Innovation Directorate, introduced the seminar by providing a short discussion of the relevance of semantics for work conducted in the OECD context and giving concrete examples of applications in the field of science, technology and innovation policy analysis.

31 May 2018 - presentation by DataIKU

The pilot OECD Smart Data Science Platform

The Collaborative Data Science platform from DataIku complements the existing ‘smart data sandbox’ with data science features made easy to access and use by analysts (machine learning, text mining, policy simulation or exploration of large data). It was selected by a panel of OECD experts as part of 2017 call for tender ‘data services and solutions’. DataIKU presented the platform and illustrated its value with several examples relevant in the OECD context. Analysts were also invited to present their potential uses of the project and 10 projects were selected for pilot.

20 October 2017 - Financial markets, network analysis and ABMs

A technical workshop on methodologies and tools for understanding financial markets with Rick Bookstaber, one of the world’s leading risk managers, and Jean-Philippe Bouchaud, Capital Fund Management and École Polytechnique.
>>  Watch the webcast

ABM background paper (pdf)
Presentation - JP Bouchaud (pdf)
Presentation - R Bookstaber (pdf)

29 September 2017 - New perspectives on the labour market: Policy applications using agent-based modelling (ABM)

In a session on macro-economic insights on labour markets using ABM Jean-Philippe Bouchaud (Capital Fund Management and École Polytechnique) discussed a methodology, inspired by statistical physics, that helps in understanding large macro-economic fluctuations. A session on Micro insights on the Labour Markets Using ABM, with Gérard Ballot, Université Paris 2 Panthéon-Assas, and Jean-Daniel Kant, Université Pierre et Marie Curie (UMPC), reviewed French Labour Laws using a model of the recent French labour market (An agent-based approach to evaluate the impact of economic dismissals facilitation on the French labor market).

>> Watch the webcast (OECD only)

ABM background paper (pdf)
Annotated agenda (pdf)
Presentation ABM - J-P Bouchaud / Presentation ABM - A Mourougane / Presentation ABM - G Ballot et JD Kant / Presentation ABM - P Fialho