Speech

IMF Managing Director’s Introductory Remarks to the G20 DGI Global Conference

June 13, 2023

Ladies, gentlemen, and distinguished guests

Welcome to the IMF, and welcome to the G20 Data Gaps Initiative Global Conference.

Let me start today by taking a step back to think about why data matters in our current context.

The Data Gaps Initiative was launched in 2009 by the G20 Finance Ministers and Central Bank Governors to close data gaps that were identified in the wake of the global financial crisis.

Fast forward to 2021 and – in the midst of the pandemic – the G20 initiated a new phase, covering climate change, household distributional information, data access, fintech and financial inclusion.

If we think back to that era of lockdowns and social distancing, it might seem remarkable to be thinking about future data needs at such a time of crisis.

But to me, it underlines the criticality data for policy decisions, especially in times of crisis and uncertainty that we have experienced recently.

Why? Because intuitively, we know that climate change is happening because we see the effects all around us. Winters are milder, and summers are hotter. Storms are more frequent and more violent.

We experience the digital finance revolution when we buy a coffee with an iPhone or send friends and family money through an app. And walking through most major cities will reveal stark inequalities.

But intuition and personal experience is not enough.

Policy advice must be based on hard data – and this is at the heart of decision-making for the IMF and our counterparts in central banks and finance ministries.

Just think – data tells us while global inequality has been declining since the 1990s, more than half of the countries and close to 90 percent of advanced economies have seen an increase within country income inequality.

Data tells us the number of registered mobile money agents has almost doubled worldwide between 2019 and 2021, mostly driven by increases in Africa and Asia.

And data tells us a single drought in Africa can lower a country’s medium-term economic growth potential by 1 percentage point.

In other words, data sharpens how we understand the economic and financial implications of the world around us—and is particularly important for tackling new and emerging issues like climate change, financial innovation and changes to wealth and income distributions.

But there are still gaps in our data. This impedes our ability to develop and monitor policies—from measures to incentivize cuts in emissions, to regulation that mitigates the risks of rapid financial innovation or helps boost financial inclusion.

What should be done? Let me point to three priorities.

First, I would echo the G20 in encouraging countries to go beyond gross domestic product in their national statistics.

The key aggregated data we publish each month, quarter, and year – such as GDP, government transfers, the Balance of Payments – are simply that: aggregates and averages. While they capture key elements of the economic story, they also conceal significant differences across household groups. What’s more, they don’t show a complete picture.

Here I would quote then-Senator Robert Kennedy, who said: "GDP does not allow for the health of our children, the quality of their education, or the joy of their play"

In other words, policymakers need official statistics that are broader, more detailed, and more frequent — including a range of household distributional income and wealth measures and climate indicators.

Take greenhouse gas emissions.

Countries regularly update their Paris Agreement climate action plans for cutting emissions, but official data on these reductions are usually published with low frequency and much delay—annually, with a lag of 12 to 24 months.

Given the urgent need to tackle climate change, tracking progress on a more regular timely basis would enable policy makers to understand the measures that work best, and where course corrections are needed.

Second, better data means investing in the infrastructure and capacity of collection agencies.

Enhancing data infrastructure involves establishing robust data collection systems, strengthening national statistical agencies, and integrating new indicators into existing frameworks.

Here, I congratulate the G20 for its leadership – and the work of the Data Gaps Initiative should serve as a pathfinder for other countries seeking to close their own gaps.

We must also give due credit to those countries that provide additional support to developing countries—including through the IMF’s ‘Data for Decisions’ Fund —as they build out their capacity to collect, analyze, and address these data gaps. This is a win-win as the international community benefits from the public good of better global assessments, while developing countries strengthen their statistical expertise and can harness stronger data.

That brings me to my final priority: filling data gaps requires collaboration and innovation.

From governments and international organizations to private sector entities and civil society, all players must work together to develop new methodologies, technologies, and partnerships to expand the availability and quality of data.

So, I am particularly pleased to see the current phase of the Data Gaps Initiative include a focus on data access.

The cross-border nature of many of today’s challenges underscores the importance of such collaboration in creating robust datasets that are internationally comparable—and so vital in addressing issues such as climate change or to understand how digital money is changing global finance.

But that’s only part of the story. As the revolution in data and analytics has gathered pace, the private sector is increasingly generating data that could be used to complement and improve official statistics—presenting an opportunity to fill data gaps.

At the same time all parties must be mindful of ethical standards and protecting personal information in order to maintain the trust that’s essential to stronger data sharing mechanisms.

Let me conclude.

The third phase of Data Gaps Initiative is an ambitious undertaking with a challenging timeline – but that reflects its importance and urgency.

It has the potential to deliver better data, leading to stronger insights and – ultimately – more effective policies across climate change, economic inclusion, and financial innovation.

At the IMF we are proud to serve as a partner to this Initiative, which complements our institutional efforts across data and statistics.

Most recently, a number of my colleagues have published a new book “Data for A Greener World” that presents a structured discussion on how to measure the economic and financial dimensions of climate change.

I hope it will serve as a foundation for our collective efforts to address climate data gaps, and that it will inspire fruitful and productive at this conference. I look forward to hearing the results of your discussions.

Thank you.

Appendix I: Introduction—to the book Data for A Greener World

Serkan Arslanalp, Kristina Kostial, Gabriel Quirós-Romero

Climate change is already confronting all of us and will do even more so in the coming years and decades. Global warming is bound to affect basic living conditions, productivity and growth, fiscal positions and debt trajectories, asset valuations. It will raise financial stability risks, redistribute income across the globe, and influence trade patterns and exchange rate valuations.

We need to get ahead of these challenges. But policymakers and investors alike face a lack of reliable and comparable data for researching the specifics of damaging economic activity, tracking the transition to a low-carbon economy. And while there are over 200 frameworks, standards, and other forms of guidance on sustainability reporting and climate-related disclosures across 40 countries, they lack consistency and comparability.

Harmonized and reliable data are necessary to enhance analyses and could also help unlock action by both the public and private sectors. Policymakers could then better monitor the transition and design appropriate macro policies. In turn, the private sector could better assess climate exposures and facilitate the flow of capital toward climate-sustainable investments.

Extensive work is underway to fill data gaps on both macro and micro levels. On the macro side, the IMF launched the Climate Change Indicators Dashboard in April 2021, which provides timely and standardized climate change-related experimental indicators. It improves the frequency and timeliness of climate change data, bringing their publication at par with the general pattern in macroeconomic statistics. Equally important, it aims to ensure a common methodology to make data comparable across countries. On the micro side, the Network for Greening the Financial System has identified and prioritized data needs, which also serve as a framework for the new G20 Data Gaps Initiative which sets climate data as priority.

This book build on these and other initiatives and efforts across the world. It is the first attempt to present a structured discussion of measurement issues related to key macroeconomic, financial, and cross-border dimensions of climate change. Involving seven international organizations—the European Central Bank (ECB), Eurostat, the International Energy Agency (IEA), International Monetary Fund (IMF), the Organisation for Economic Co-operation and Development (OECD), the World Bank (WB), and the World Trade Organization (WTO)—the books aims to leverages each institution’s leadership in relevant statistical methodologies.

The book is aimed at informing policymakers, economists, statisticians, academics, and the private sector for whom climate data have become a critical need. It combines theory and analysis with real world examples, explained by leading practitioners and experts. We hope the readers will find the book to be an inspiration for further analysis.

Chapter 1 presents estimates of quarterly greenhouse gas emissions by economic activity, developed in a partnership between Eurostat, IEA, IMF, OECD, and the UNSD. It outlines the underlying methodology used to prepare the estimates, presents possible applications, and explores avenues for future work.

Chapter 2 shifts the focus from emissions by production to emissions by consumption—with international trade being the missing link. Based on work pioneered by the OECD, it describes the sources and methods used to estimate the carbon dioxide emissions embodied in international trade, and then final domestic demand. The estimates are based on global input–output tables to account for global production networks and value chains and can be used for structural decomposition analysis to reveal the drivers of emissions in final demand.

Chapter 3 turns to fiscal policies geared toward protecting the environment. It reviews the definitions and measurement of environmental taxes and expenditures, shows how they have changed in recent decades, and discusses way to improve their measurement, including through green budget tagging.

Chapter 4 is aimed at central banks, based on work by the ECB. It discusses physical risk indicators that could be used for analyses and climate stress testing and highlights new data sources and methodologies borrowed from geographers, climate scientists, and disaster management experts at the intersection of climate and financial analysis.

Chapters 5, 6, and 7 turn to transition risks, particularly for tracking the impact of mitigation policies. Chapter 5 provides an overview of approaches for measuring carbon pricing. It summarizes the World Bank’s indicators for direct carbon pricing, as outlined in its Carbon Pricing Dashboard, and outlines underlying methodologies and limitations. The chapter also presents the World Bank’s framework for combining direct and indirect carbon pricing into a single metric of total carbon pricing.

Chapter 6 describes the IMF’s methodology for measuring fossil fuel subsidies at the global and country levels and quantifies the impacts of reform. It involves an extensive compilation of country-level data on sectoral fuel consumption; fuel prices; supply costs; climate, local air pollution, and broader externalities associated with fuel use; and general consumer taxes. A spreadsheet tool for estimating the environmental, fiscal, and economic impacts of fuel-price reform is also briefly discussed.

Chapter 7 presents an experimental indicator—the carbon footprint of bank loans—to quantify the exposure of a country’s banking sector to climate transition risks. It presents the results of the indicator for a range of emerging and advanced economies and discusses how to overcome data limitations related to the indicator in the context of the broader climate information architecture.

Chapter 8 and 9 turn to cross-border aspects of climate data. Chapter 8 presents two measures of carbon emissions associated with Foreign Direct Investment (FDI) in host economies from capital formation financed by FDI (e.g., constructing new plants and equipment), and from direct and indirect carbon emissions from the production of foreign-owned firms.

Finally, Chapter 9 discusses how to estimate trade in low-carbon technology (LCT) products, such as solar panels and wind turbines. It discusses recent trends in LCT trade, provides an overview of barriers to trade in LCTs, and discusses policy uses and applications of the experimental indicators, which could inform international negotiations on trade policy and climate finance.

The common thread running throughout the book is that there are practical approaches to close climate data gaps using already existing data sources, and that close cooperation across institutions and fields of expertise is of the essence. Many indicators presented in this book are available on the IMF’s Climate Change Indicators Dashboard and can be replicated by other countries, including emerging and developing economies. We thus hope that our book will help policymakers and practitioners to improve their understanding of the impact of climate change on their economies and ultimately accelerate policy action toward a greener world.