Good morning, good afternoon, and good evening to all.
I would like to start by thanking Anil Arora for the invitation to join you. I have enjoyed collaborating with Anil as Chair of the Group on Economic Statistics in its efforts to develop a transformative agenda for economic statistics, based on a sustained dialogue between statisticians and economists in the public and private sectors. I fully support this agenda, which seeks to allow the statistical system to be more agile and responsive to user demands and promotes an update of the system of economic statistics that produces increasingly broader measures of progress.
My interaction with the members of the FOC Group has deepened my appreciation for your work as Chief Statisticians of the national and international statistical systems. My 25 years with the IMF have taught me how essential your role is, but also how difficult it is, and I fear that e economists often fail to give you the credit that you have earned.
Let me try upfront therefore, to rectify that in some small way. My friend and colleague, Stefan Schweinfest, informs me that, in response to the COVID19 pandemic, you have adopted new business models that emphasize the production of new more timely and frequently experimental statistics through the use of new alternative data sources and partnerships with public and private institutions. These new business models, I am told, take a holistic, coherent and integrated approach across statistical domains in order to provide a complete assessment of the impact of the crisis on the economy, the environment and the society. In this era of sustainable development, this is precisely what we need, and I congratulate you for this initiative. Once again, the statistics profession has shown itself to be ahead of the economics profession.
I have been asked to make a brief 15-minute introduction on the data needs for undertaking policy analysis on globalization from a UN economist perspective with a focus on where I see data gaps and the role of the national statistical offices in closing these data gaps.
The first point I’d like to make here is that as our national economies become increasingly integrated and more complex global production arrangements emerge, the compilation of economic statistics poses a rising challenge.
Globalization is a process that encompasses economic, technological, and social developments. With the increasing global fragmentation of the production of goods and services, our national economies—small, medium or large—have more intertwined. This economic globalization is characterized by the growing international trade, foreign direct investments and other international capital flows. Multinational enterprises dominate this arena with dynamic and fast-changing operations as they continuously seek to maximize profits and minimize tax payments.
Traditional policy research has focused on the short-term and structural monitoring of international trade in goods and services, foreign investments and other financial capital flows and stocks, and the integration of domestic enterprises into global value chains through international trade and investment. The monitoring also covers the consequences of globalization on economic growth, prices, employment, labour productivity, wages and innovation. This policy research is supported by econometric and CGE models using a coherent set of time-series of short-term, quarterly and annual national accounts, trade statistics, business statistics, investment and financial statistics and the structural relationships of (multi country) input-output tables and integrated economic accounts.
What we are missing in all of this is the qualitative element. Globalization is in many respects the principal driver of economic development on the global stage but it is itself subject to the influence and impact of the observed global mega trends of technological innovation, urbanization, demographic change, rising inequality, and environmental degradation and climate change.
The recently established UN Network of Economist is taking a more holistic view whereby globalization has to be understood in the context of sustainable development, and its impact must be assessed across the three dimensions of sustainable development—the social and the environmental alongside the economic—and under the influence of these megatrends. We need information—official statistics, indicators and data from different sources—that will allow us to make that assessment and establish the evidence base for effective policy. Let me spend a few moments looking at each of these megatrends in turn and the challenges they pose for economic statistics.
The widespread deployment of new technologies, especially digital technologies, is transforming labour markets, societal structures, and affects all aspects of human life and development. This rapid technological change has had a major effect on the rapid pace of globalization that has defined the global structure of production and employment. The rapidly declining cost of advanced technology has large effects on competitiveness and production which are not easily captured in the standard data on international trade and investment. And yet, this phenomenon will have major consequences for firms involved in global value chains that are not able to keep up and remain technologically competitive. It will also affect the distribution of the benefits of globalization, and consequently the inequitable distribution of income and wealth among countries, and within them as well.
The digital technology megatrend also interacts closely with the existing global patterns of inequality. With the globalization and digitalization, our economies are increasingly interconnected through digital networks. Developed countries with more advanced national innovation systems that lead research and development, and with firms and customers that can rapidly buy and use technologies, are the first to reap the immediate benefits of discoveries and progress. For developing countries, catching-up to and keeping up with countries closer to the technological frontiers depends on their ability to access, adapt and deploy these new technologies. Policy in this area must aim at building an enabling infrastructure and regulatory environment, and promoting risk-taking, investment, and a culture that embraces these new technologies. To inform such policy we need data and information that enable us to understand the capacities of countries to build up such national innovation systems, and to make good use of available technologies. This evidence base will also allow us to anticipate where developments in globalization, and in frontier technologies risk leaving groups of people, or countries, behind, and to formulate policy interventions that can address this.
In the context of the COVID pandemic, it was necessary to understand the interlinkages of local small, medium and large enterprises in global value chains and to analyze the cascading regional and local economic effects of significant domestic, regional and global value chains in order to monitor the impact of the sharp drop in demand for supply chain related industries like the automotive, aeronautic, textiles, construction, and tourism.
Turning now to urbanization, the role of cities in connecting the rest of the world has been changing rapidly with the introduction of digital networks between cities and among urban and rural areas. Cities and urban areas are critical economic and transportation nodes in a complex, multi‐layer, and often global network, in which the traditional roles, the regional and international boundaries will lose importance.. Digital inclusion is imperative for our economies and urban and rural communities to grow and prosper. Urbanization and rural development can be a powerful driver of this inclusion, and are therefore critical for our overall sustainable development.
International discussions about the global demographic trends have shifted from a predominant emphasis on population growth to paying greater attention to the implications of slower population growth and “population ageing”. This produces rising old-age dependency ratios that require adaptation of global labour markets, pension, health care, and social systems to insure adequate support and sustainability. In the absence of such global reforms, there is increasing fiscal pressure on pension and health care systems, as well pressures on families in societies where public transfers are limited, and adult children are expected to care for older parents and grandparents. Longer-term policy planning depends heavily on the availability of disaggregated population data that enable a differentiated analysis of these trends.
Domestic and international migration and the related remittance flows are an important consideration in our interconnected global economy. The reliance on migrant workers in specific industries in our economies has again come to the fore with the COVID crisis where the sharp downturn in our national economies led to massive movement of domestic and international workers to their home communities and countries.
Climate change and environmental degradation cannot be turned around in the short term and have already experienced significant and possibly irreversible changes. There needs to be a particular focus on decoupling environmental degradation and resource use from economic growth. With the assistance of alternative indicators of development (for example, Inclusive Wealth Index, Human Development Index) and mainstreaming the discourse of natural capital and ecosystem services into discussions about development, it will be possible to more precisely frame the kind of transformational change and decoupling that is required and identify the most effective policy options..
Way Forward TP13 Allow me to end by turning to the evolving statistical needs of global and national policy makers in meeting globalization’s challenges and the attendant need for an economic statistics system that is responsive and provides timely and relevant information for policy makers.
I like to suggest the following for your consideration and further discussions today:
I would like to start by thanking Anil Arora for the invitation to join you. I have enjoyed collaborating with Anil as Chair of the Group on Economic Statistics in its efforts to develop a transformative agenda for economic statistics, based on a sustained dialogue between statisticians and economists in the public and private sectors. I fully support this agenda, which seeks to allow the statistical system to be more agile and responsive to user demands and promotes an update of the system of economic statistics that produces increasingly broader measures of progress.
My interaction with the members of the FOC Group has deepened my appreciation for your work as Chief Statisticians of the national and international statistical systems. My 25 years with the IMF have taught me how essential your role is, but also how difficult it is, and I fear that e economists often fail to give you the credit that you have earned.
Let me try upfront therefore, to rectify that in some small way. My friend and colleague, Stefan Schweinfest, informs me that, in response to the COVID19 pandemic, you have adopted new business models that emphasize the production of new more timely and frequently experimental statistics through the use of new alternative data sources and partnerships with public and private institutions. These new business models, I am told, take a holistic, coherent and integrated approach across statistical domains in order to provide a complete assessment of the impact of the crisis on the economy, the environment and the society. In this era of sustainable development, this is precisely what we need, and I congratulate you for this initiative. Once again, the statistics profession has shown itself to be ahead of the economics profession.
I have been asked to make a brief 15-minute introduction on the data needs for undertaking policy analysis on globalization from a UN economist perspective with a focus on where I see data gaps and the role of the national statistical offices in closing these data gaps.
The first point I’d like to make here is that as our national economies become increasingly integrated and more complex global production arrangements emerge, the compilation of economic statistics poses a rising challenge.
Globalization is a process that encompasses economic, technological, and social developments. With the increasing global fragmentation of the production of goods and services, our national economies—small, medium or large—have more intertwined. This economic globalization is characterized by the growing international trade, foreign direct investments and other international capital flows. Multinational enterprises dominate this arena with dynamic and fast-changing operations as they continuously seek to maximize profits and minimize tax payments.
Traditional policy research has focused on the short-term and structural monitoring of international trade in goods and services, foreign investments and other financial capital flows and stocks, and the integration of domestic enterprises into global value chains through international trade and investment. The monitoring also covers the consequences of globalization on economic growth, prices, employment, labour productivity, wages and innovation. This policy research is supported by econometric and CGE models using a coherent set of time-series of short-term, quarterly and annual national accounts, trade statistics, business statistics, investment and financial statistics and the structural relationships of (multi country) input-output tables and integrated economic accounts.
What we are missing in all of this is the qualitative element. Globalization is in many respects the principal driver of economic development on the global stage but it is itself subject to the influence and impact of the observed global mega trends of technological innovation, urbanization, demographic change, rising inequality, and environmental degradation and climate change.
The recently established UN Network of Economist is taking a more holistic view whereby globalization has to be understood in the context of sustainable development, and its impact must be assessed across the three dimensions of sustainable development—the social and the environmental alongside the economic—and under the influence of these megatrends. We need information—official statistics, indicators and data from different sources—that will allow us to make that assessment and establish the evidence base for effective policy. Let me spend a few moments looking at each of these megatrends in turn and the challenges they pose for economic statistics.
The widespread deployment of new technologies, especially digital technologies, is transforming labour markets, societal structures, and affects all aspects of human life and development. This rapid technological change has had a major effect on the rapid pace of globalization that has defined the global structure of production and employment. The rapidly declining cost of advanced technology has large effects on competitiveness and production which are not easily captured in the standard data on international trade and investment. And yet, this phenomenon will have major consequences for firms involved in global value chains that are not able to keep up and remain technologically competitive. It will also affect the distribution of the benefits of globalization, and consequently the inequitable distribution of income and wealth among countries, and within them as well.
The digital technology megatrend also interacts closely with the existing global patterns of inequality. With the globalization and digitalization, our economies are increasingly interconnected through digital networks. Developed countries with more advanced national innovation systems that lead research and development, and with firms and customers that can rapidly buy and use technologies, are the first to reap the immediate benefits of discoveries and progress. For developing countries, catching-up to and keeping up with countries closer to the technological frontiers depends on their ability to access, adapt and deploy these new technologies. Policy in this area must aim at building an enabling infrastructure and regulatory environment, and promoting risk-taking, investment, and a culture that embraces these new technologies. To inform such policy we need data and information that enable us to understand the capacities of countries to build up such national innovation systems, and to make good use of available technologies. This evidence base will also allow us to anticipate where developments in globalization, and in frontier technologies risk leaving groups of people, or countries, behind, and to formulate policy interventions that can address this.
In the context of the COVID pandemic, it was necessary to understand the interlinkages of local small, medium and large enterprises in global value chains and to analyze the cascading regional and local economic effects of significant domestic, regional and global value chains in order to monitor the impact of the sharp drop in demand for supply chain related industries like the automotive, aeronautic, textiles, construction, and tourism.
Turning now to urbanization, the role of cities in connecting the rest of the world has been changing rapidly with the introduction of digital networks between cities and among urban and rural areas. Cities and urban areas are critical economic and transportation nodes in a complex, multi‐layer, and often global network, in which the traditional roles, the regional and international boundaries will lose importance.. Digital inclusion is imperative for our economies and urban and rural communities to grow and prosper. Urbanization and rural development can be a powerful driver of this inclusion, and are therefore critical for our overall sustainable development.
International discussions about the global demographic trends have shifted from a predominant emphasis on population growth to paying greater attention to the implications of slower population growth and “population ageing”. This produces rising old-age dependency ratios that require adaptation of global labour markets, pension, health care, and social systems to insure adequate support and sustainability. In the absence of such global reforms, there is increasing fiscal pressure on pension and health care systems, as well pressures on families in societies where public transfers are limited, and adult children are expected to care for older parents and grandparents. Longer-term policy planning depends heavily on the availability of disaggregated population data that enable a differentiated analysis of these trends.
Domestic and international migration and the related remittance flows are an important consideration in our interconnected global economy. The reliance on migrant workers in specific industries in our economies has again come to the fore with the COVID crisis where the sharp downturn in our national economies led to massive movement of domestic and international workers to their home communities and countries.
Climate change and environmental degradation cannot be turned around in the short term and have already experienced significant and possibly irreversible changes. There needs to be a particular focus on decoupling environmental degradation and resource use from economic growth. With the assistance of alternative indicators of development (for example, Inclusive Wealth Index, Human Development Index) and mainstreaming the discourse of natural capital and ecosystem services into discussions about development, it will be possible to more precisely frame the kind of transformational change and decoupling that is required and identify the most effective policy options..
Way Forward TP13 Allow me to end by turning to the evolving statistical needs of global and national policy makers in meeting globalization’s challenges and the attendant need for an economic statistics system that is responsive and provides timely and relevant information for policy makers.
I like to suggest the following for your consideration and further discussions today:
- With the shift toward evidence-based policy making for sustainable development, economic statistics need to be situated within a broader framework that is integrated across statistical domains—we need this in order to provide a complete assessment of the impact of any development or policy on the economy, the environment and the society (the three pillars of sustainable development). This speaks to the pressing need for a broader set of metrics to measure development, beyond-GDP as you will. The virtually instantaneous spread of the COVID pandemic and its economic and social impact was due to the interconnectedness of our economies and societies—this only accentuates the pressing need for a more integrated and holistic measure of progress.
- As we move into the pivotal post-Covid recovery phase, NSOs may adopt a new business model that produces new (more timely and more frequent) experimental statistics through the use of new alternative data sources and partnerships with public and private institutions.
- In the new business model, the integration of statistical registers of businesses, persons, buildings, land, etc. will prove to be a critical statistical infrastructure for micro data linking (MLD) to produce timely, accurate and relevant statistics on small, medium and large businesses, households and communities. These statistics will address issues of health, education, employment, production, technological innovation, inequality, demographic change and climate change at granular geographical levels of regions, cities and local communities
- Communication with the users and policy makers was key during the crisis to identify what type of information was needed and to communicate the quality of the information provided. Open and transparent communication ensured the continuous trust in the NSOs. This communication could also be pursued at international level by convening joint meetings of the UN Network of economists with the UN Network of statisticians. Other international organisations such IMF, World Bank, OECD, WTO and ILO should join these user producer dialogues.
- The innovative data solutions established in recent months may, and perhaps should, be considered a new normal. Countries have adopted various data solutions to ensure continuity of their statistical programmes using new data. New data sources, including administrative data, web scraped data, open data, and Big Data, were exploited through public and private partnerships to access data for the public good during the crisis.
- A common statistical challenge could be determined by the international statistical community to inform the impact of globalisation during the COVID crisis building on the emerging new business model for national and international statistics systems. This challenge should adopt a centralized location to document and share the wealth of experience and lessons learned to further strengthen the new business model. Regional Commissions like UNECE should play in important role in setting and coordinating this statistical challenge.
File date:
Monday, June 22, 2020