Fifth Statistical Forum

November 16-17, 2017

The International Monetary Fund will hold the Fifth Statistical Forum at its headquarters in Washington DC on November 16-17, 2017. The Forum is a platform for policymakers, academics, researchers, and compilers of economic and financial data to come together to discuss cutting-edge issues in macroeconomic and financial statistics and to build support for statistical improvements.

The theme of this year’s Statistical Forum is “ Measuring the Digital Economy”. Digitalization has transformed the way we work, consume, and engage with one another. Against a backdrop of slow growth of GDP and productivity, concerns that existing macroeconomic statistics may not fully capture the gains from digital and digitally-enabled products and activities have become a topic of much discussion and debate. The Forum will include empirical or conceptual papers that foster progress on understanding the implications of digitalization for macroeconomic and financial statistics and developing strategies to fill the measurement gaps.

The Forum is open to the public and registration is required. To register for the Forum please use the registration link .

Please note that registration will close on Monday, October 23, 2017 24H00 EST. Registered attendees will be required to present photo identification on entering the IMF at 1900 Pennsylvania Avenue, N.W., Washington D.C. For questions regarding the Forum, please send an email to STAForum@imf.org.

Please note that Forum participants are expected to cover their own travel and accommodation expenses and make their own arrangements.

 

 

Draft Agenda

Thursday, November 16, 2017 (Day 1)

Introductory Remarks

Opening Remarks

Keynote speech

Session I: Does GDP still tell us what we need to know?

The "digital economy" has given households access to many new, free, or low cost products. It has also allowed households to make more intensive use of assets that they already own via participation in the sharing economy and to substitute home production for market production. For producers, data has become a new kind of factor of production, and access to open-source software, cloud computing services, and increased opportunities for globalized production have allowed cost savings or tax savings. Do existing macroeconomic statistics still provide a full picture of changes in production, consumption and inflation, and if not, how can the new data needs be addressed?

Session II: Framing the Conceptual Issues

What do we mean by “the digital economy” for purposes of macroeconomic and financial statistics? The existing conceptual framework for GDP offers logical coherence and is well-suited for analyzing key macroeconomic questions involving employment and government revenue, but digitalization has made the well-known limitations of GDP as a measure of well-being or total production more fundamental. What are the main conceptual issues, and what are the prospects for addressing them?

Session III: Economic Effects of Digitalization

To frame the context of the measurement discussion, we step back and consider how digitalization has changed the economy. For example, winner-take-all dynamics created by network effects have contributed to growing inequality, new ways of transacting have boosted economic activity, and the growth of ecommerce and the sharing economy may have contributed to deflationary pressures.

Session IV: How Big is the Digital Economy?

The overall importance of possible errors in measuring the digital economy depends, in part, on its size. What do we know about the actual size and growth of key parts of the digital economy, such as B2C e-commerce, the sharing economy and international trade in digital services? How the size and structure of the digital economy vary across developing, emerging and advanced economies? Is there a good way to capture international trade in digital and digitally-enabled services? How has the use of mobile money and other kinds of e-money spread?

Session V: State of play in national macroeconomic and financial statistics in capturing of the Digital Economy.

What are statistical agencies around the world doing to measure digital products or activity in national accounts, price statistics, labor statistics, balance of payments statistics and financial statistics? What are the innovations in data collection, compilation or reporting? How are Big Data techniques being used to measure the digital economy in macroeconomic and financial statistics? What do statistical agencies and other data compilers see as the main emerging challenges and opportunities?

Friday, November 17, 2017 (Day 2)

Session VI: Deflators for digital products: are they contributing to mismeasurement of productivity, growth and inflation?

Under-adjustment for quality change in the deflators for ICT products has long been an issue in the measurement of GDP volume change, and the challenges may have grown, as hard-to-measure software has increased in importance and new kinds of digitally-intermediated services have appeared in the “sharing economy.” What does the latest research show about the deflators for ICT equipment, software and new kinds of digital products, and what are the implications for the measurement of inflation/deflation, growth and productivity?

Session VII: Digitalization and Consumer Welfare

Free and new digital products are widely consumed throughout the world, and in developing countries mobile money and other Fintech innovations have notably expanded access to financial services for formerly unbanked households. GDP statistics may therefore not fully reflect growth in consumer welfare made possible by digitalization. What are the welfare effects of digitalization and how can we measure them?

Closing Panel

What lessons can we take away concerning the conceptual and compilation issues, size of the digital economy, and economic effects of digitalization, country experiences and potential policy implications of digital economy? The conclusions of the individual sessions will be discussed, aiming at agreeing on the way forward for statistics, to better serve economic analysis and policy-making. What practical steps can be taken to better measure the impact of the digital economy on output, productivity, prices, employment and welfare? What can macroeconomic statistics do to better inform the society of the impact of digitalization?

Closing Remarks