In April, disputes and chaos followed the sudden U.S. blanket tariffs threatened to pick the tightly woven structures produced globally. Now, about 300 million companies around the world are connected through an estimated 13 billion supply chains, and are now facing unprecedented uncertainty. But the current chaos is just the latest example of economic disruptions in the last fifty years. Since the beginning of the Covid pandemic in 2020, surprising bottlenecks in global supply chains have allowed academics to reassess how the economy works. Production slows and cargo shortages are exposed to delays in cargo changes that meet demand by hand sanitizer (special chemicals imported into the United States during the pandemic) and aircraft (due to shortages of important components in 2024). A global economic system in which commodities cross boundaries many times in continuous production and assembly stages. They also present traditional understandings on how best to measure growth and productivity.
Trade and technology have re-established global production, but based on the framework designed in the 1940s, economic statistics such as GDP growth and productivity are still being collected, for example, focusing primarily on economic demand and its current and past performance. They have no idea about the supply side or the economy’s ability to respond to stress. As a result, economists have described the output of developed economies as about one-fifth, which is “unmeasurable”. Disproportionate focus on industries that are easier to estimate, such as manufacturing, underestimate importance An industry that actually powers the modern economy.
In an unprecedented era of interconnectedness and turmoil, PolicyMakers need new tools to track the status of global production networks and capture forms of activity that were unimaginable when modern economic statistics were born. Overhaul requires more and better Data collection to fill gaps in knowledge, including indications of supply chain vulnerabilities and innovative technologies used to measure qualitative and intangible aspects of the economy that contribute to growth and inflation. A new framework that cannot fight standard statistics is more than just an academic issue; it is the only way for leaders to formulate reasonable economic policies in uncertain times.
The current international framework for measuring economic growth and productivity is the System of National Accounts (SNA), a set of statistical standards agreed every ten to 20 years by the official committee of statisticians led by the United Nations. It includes GDP, which economists and policy makers have long considered the best measure of economic progress.
The SNA was founded during World War II by American and British economists including John Maynard Keynes. As allies devoted their resources and production capacity to their war efforts, they needed to strike a balance between consumption and war production and designed SNA to measure domestic demand. The system occupied the founding of the years after the war, and every decade revised the structural changes of the economy, such as the rise in financial influence. The revision process is intentionally slow and gradually growing, and before any changes are adopted, consensus is required among the United Nations member states.
Today’s SNA is a complex measure of the mid-twentieth century economy where manufacturing dominated, production was conducted within the boundaries of individual countries, and broadband networks and data have not yet provided power for economic growth. The latest update to SNA has been modest and modernized. However, no patching around the edge will change the basic obsoleteness of the system built around the growth and productivity drivers of past eras. SNA can be performed on autopsy, but cannot be diagnosed or prescribed.
SNA has standardized measures of economic growth and achieved international comparisons for nearly a century. However, it has not kept pace with changes in economic activity caused by globalization and technological advances. Since the 1980s, the once national network manufacturing and service production has shifted to relying on global value chains. Global trade once meant to transport cars or refrigerators between countries, now requires highly professional components at every stage of production and assembly.
New business models thrive as the global economy becomes more detailed and entangled. Traditional integrated manufacturers that control the process from design to production and wholesale have given way to “factory-free commodity producers” of design, wholesale and retail. contract companies conducting manufacturing; and downstream "service" manufacturers focusing on sales related services and maintenance. In areas such as electronics and pharmaceuticals in the United States and the UK, contracted manufacturing accounts for about 15% to 20% of output, and bundled with products (for example, Rolls-Royce sells real-time monitoring services for its aircraft engines) has become a popular practice among large companies.
With the increase in specialization and labor division, these shifts have led to widespread economic growth, increasing productivity in the ever-expanding global market. But the trade-off has become clear: the goods have become cheaper and easier to obtain, And the quality is higher, but companies have relied too much on some overseas suppliers to obtain key components, making them more vulnerable to the global economic shock that has only become increasingly common. Traditional economic statistics are not designed for this complex interdependent network. The lack of reliable measurements in economic supply makes it difficult to capture the patterns and conditions of global production chains even in calm times.
Therefore, these statistics are also inappropriate in the face of technological advances. Traditional firm measures (such as GDP) cannot account for the impact of cost savings and productivity growth infrastructure (such as cloud services on growth). For example, they also underestimated the value of data to large companies, calculating only the cost of building a data center, rather than the tangible productivity achieved by data collection and use. Furthermore, statisticians cannot reach consensus on how to document the value of widely used free digital services, such as open source software.
Central banks and researchers have begun to establish broad measures of supply chain pressure, such as the Fed's Global Supply Chain Pressure Index, as this pressure has played a major role in driving inflation in the global economy since the pandemic. However, statisticians (and therefore decision makers) still lack sufficient metrics to measure the risk of providing a chain for a particular product (even a high-profile product like the iPhone). They also don’t have the tools or expertise to understand how digitalization and artificial intelligence can reshape business models and trade. In short, they attempted to develop policies without useful statistical guidelines for current and future production in today's economy.
It is not impossible to develop statistics on global production networks. Academic experts in the field, such as Vasco Carvalho, an economist at the University of Cambridge, have explained how tax and payment data can be used to understand and track product flows Element. However, a truly effective update to economic statistics must go beyond the new business model that maps production networks and technology implementations. It must also focus on capturing the economic resilience and future potential of the economy while better detailing its current production model.
The economic concept known as comprehensive wealth is key to this reimagining. Integrated Wealth broadly describes a country's balance sheet, including traditional production capacity, such as the status of buildings and equipment owned by a business and its national infrastructure, from roads to ports. Crucially, it should also consider communication networks and their potential barriers and vulnerabilities, as well as other intangible infrastructures, including government and private sector data, and “digital public infrastructure,” meaning hardware, such as cloud servers and telecommunications networks; data and identity verification Systems that digitize public services and store all economic and official statistics required by businesses and governments); and applications, including payment systems and government services. The digital stack is full of its own bottlenecks and vulnerabilities that any government related to national security and resilience needs to be able to quantify these risks.
The national balance sheet requires a certain amount of human capital to quantify how the skills and health of the labor force promotes productivity and income. It should also take into account a country’s natural capital: While some natural resources that can make economic activity (such as rare earths and other critical minerals required in cutting-edge technologies) are partially valued by the current statistical framework, more comprehensive accounts must also consider underestimated resources such as the provision of leisure services and national parks that provide leisure quality and biodiversity to promote agricultural productivity.
Finally, a true comprehensive statistical account should include the Nobel Prize winners Daron Acemoglu, Simon Johnson and James Robinson, among others, who believe that a country’s legal and government agencies contribute to its prosperity through confidence in the rule of law, contract security and economic freedom. The available indicators do not distinguish between the productivity of “mining” institutions that dissuade private investment and personal skills at the expense of a wider population, and institutions provide stable countries that allow all to thrive in their work or business.
Transforming from economic surveys conducted by traditional consumers and businesses to novel data sources would be a cultural revolution for traditionally cautious statisticians. Collect the amount of data needed to build a more complete country’s productivity and its economic vulnerability Since the 2008 global financial crisis, most countries have strengthened their government budgets globally and their resources have steadily lowered. It also requires international efforts to build consensus on definitions and data standards. But as the response rate to official statistical surveys declines, businesses and individuals are increasingly suffering from “investigation fatigue”, profound changes are both necessary and inevitable.
The revolution in data collection and technology that requires new statistical paradigms will be useful in creating it. From tracking payments and tax numbers required to produce global networks to employers’ salary figures, information collected from store scanner systems, and many new sources of sensor and satellite data, many basic data already exist or can be collected. Pilot data programs such as the Human Economic Index could help statisticians track the adoption and use of artificial intelligence in society, a defined technological shift that is currently invisible in economic statistics.
Global production networks are under tremendous pressure. Policymakers correctly hope that their statistical systems can provide useful information about their economic situation. Just as the imperatives of war led to the development of SNA in the 1940s, the new urgency of the world impacted by trade wars, geopolitical instability and supply required a modern statistical framework. Without it, a true mastery of the nature of the global economy will remain elusive - the world will remain in the dark.
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