The rise of China and the security dilemma that it presents is viewed as inevitable by significant sections of the UK policy community. Central to this is China’s strong economic base, which has generated the diplomatic, informational, military and economic levers necessary for it to challenge the US-led ‘rules-based’ order designed to perpetuate Western power post-World War Two.
However, while China is a formidable adversary and should not be underestimated, we should not be blind to the weaknesses in China’s economic structure and risk overestimating its strengths and constraining ourselves conceptually. In particular, we should be cautious in using gross indicators to calculate relative power and economic growth, as in isolation these approaches can be misleading. This article compares competing methods of measuring power, before examining that while China is likely to overtake the US in terms of gross real GDP, this is not an effective metric for assessing relative power when used in isolation.
Despite economic headwinds, China will still overtake the US in terms of real GDP
Gross Domestic Product (GDP) is the market value of all “final goods and services produced in a specific period” in a country. Real GDP accounts for price inflation against the GDP of a chosen base year, therefore only rising output increases GDP, not inflation. This metric of real GDP benefits from being the most commonly used indicator of an economy’s overall size, growth and general health, meaning that there is significantly more data available for comparative analysis.
Although China has significant demographic, capital and productivity challenges, this is unlikely to prevent China from overtaking the US in real GDP. China has capitalised upon lower relative wage costs due to its large population, a central driver of its economic growth over the last 50 years. The 1978 economic reforms permitted private businesses while liberalising foreign trade and investment, since which China has experienced enormous economic growth, even compared to other rapidly growing “Asian Tiger” economies. From 1978 to the onset of the 2008 global financial crisis, China’s real GDP grew by a factor of 17.
The 2008 crisis reduced this breakneck growth, with China’s annual real GDP growth between 2015 and 2018 falling below 7% for the first time since 1991. This was compounded by further shocks from the recent Covid pandemic and the CCP’s “zero Covid” policy. Chinese policy post-2008 has increasingly relied upon state investment, improving technology and expanding domestic consumption of finished products. This transition from the previous export economic focus is assessed to be “hedging” against reduced exports due to increasing competition and international pressures such as tariffs. Nonetheless, China’s real GDP should still increase 5.7% annually to 2025 and 4.7% annually until 2030, according to Centre for Economics and Business Research (CEBR) forecasts. Although there are reasons to doubt these figures – including the provision of misleading data by the Chinese state, and upcoming shocks such as increased nearshoring of supply chains and property market debt bubbles – the overall trend is clear. Chinese real GDP is on course to overtake the US by 2030.
How can power be measured between states?
There are three main approaches to measuring power in international relations; control over actors, control over outcomes and control over resources. In the case of control over actors, power is usually defined as an actor’s ability to shape world politics following its interests. However, Nye argues that it is impossible to measure this ability systematically because it would require a comprehensive understanding of each actor’s influence and interest over a potentially infinite number of events. This means that the power over outcomes approach is issue-specific, with analysis not often transferable to other situations. Therefore, it is only useful for retrospective analysis and can often lead to nonsensical conclusions, for example, Vietnam being considered ‘more powerful’ than the US by forcing its withdrawal in 1973 and achieving its desired outcome.
In contrast, Dahl defines power over actors as the ability of “A to get B to do something” they would otherwise not do. Here, it is challenging to quantify to what extent A influenced B’s decision to do or not do something else. Furthermore, Hart argues that the use of coercive power, such as economic sanctions, does not always have the intended effect, and its effectiveness is dependent upon numerous other factors, such as the availability of domestic substitutes. This further complicates analysis, therefore most research compares resources, such as military assets and wealth. These assets allow for influence across most domains, leading to embedded views that unconsciously shape actors’ interests. For example, even if Mexico adopted an offensive realist foreign policy, it is highly unlikely to consider territorial expansion into the US due to its relative power resources. As such, the power over resources approach will be used for this analysis as its use of data produces more tangible conclusions than behavioural approaches, which assume accurate understanding of actors preferences.
Key challenges in applying the power as resources approach
This method faces three key challenges. First, the extent to which national actors can control or employ resources in their country. For example, the structure of fiefdoms – and corruption – in the Chinese system slows coordination and misallocates resources which challenges the control and employment of the state’s huge resources towards its goals.
Second, it requires accurate and replicable data on resources and trends within a country. The highly centralised CCP policy making and target setting for five year plans incentivises regional and local leaders to inflate such data internally. This provides challenges for internal decision making, even before we consider how China manipulates and likely exaggerates publicly released data on its economy and currency to maintain the perception of high growth – which in turn complicates this analysis.
China manipulates and likely exaggerates publicly released data on its economy and currency
Finally, the focus on national power diminishes the role of non-state actors in determining outcomes and makes the effects of interdependence harder to assess. The stated aim of the CCP to reshape the Western-dominated ‘rules-based order’ contributes to China’s complicated relationship with non-state actors, who are not viewed as having sovereignty over China unless it is to support their imposition of the Middle Kingdom’s tributary expectations on other states. Non-state actors are often used for leverage and to conduct ‘lawfare’ on other actors but ignored when used against China.
Despite these challenges, this approach is the only reliable method that allows forward-looking analysis from available data that can generally be corroborated. This is unlike the subjective assumptions used for power over outcomes or power over actors approaches which are often issue-specific about how actor W was influenced at X time to do Y thing or achieve Z outcome. They also are backwards-looking and therefore hard to apply to another context or the future as the data isn’t available and coerced actors will respond and adapt to previous events.
Net vs. Gross Metrics
While Chinese real GDP is a source of power, it is counteracted by a number of significant economic costs. Beckley argues that power is a function of net resources, this lies in contrast to most scholars who measure power in gross terms. Using net resources mitigates some effects of nonmaterial influences by discounting costs (such as increased transfer payments to provide welfare for an ageing population). Utilising a net approach would account for the significant economic costs that China faces which counteract its large GDP, for example; an increasingly ageing population (contributing to a significantly declining working population); male-dominated demographics; overexploitation damaging much of its arable land; industrialisation and pollution causing substantial water scarcity and negative health externalities; huge welfare and internal security burdens; and increasing infrastructure and education costs.
Spending money will always increase GDP even if THE money is wasted, as seen with China’s ineffective infrastructure investments.
Moreover, GDP counts production costs as output; therefore, spending money will always increase GDP even if money is wasted, as seen with China’s ineffective infrastructure investments. GDP also counts security spending as economic output, so investment in productivity-enhancing research can equate to the same value as expenditure on methods of domestic political persecution. GDP therefore fails to fully account for the economic costs of domestic instability and international conflict, as illustrated by how GDP usually rises when a country mobilises for war. Throughout most of human history, “production, welfare and security” have consumed “nearly all” of every country’s resources and limited power projection abroad. For example, when measured in net terms, actors with greater resources have won “70% of disputes and nearly 80% of wars” over the last 200 years.
Commonly used economic metrics, such as real GDP (a gross indicator), are not the sole determinants of relative national power. Understanding whether a country is more powerful or influential than another is complex, consisting of large amounts of data and intangible factors such as unconscious perceptions. Individual gross economic metrics cannot fully illustrate the power resources of an actor, and economic size is only one of several dimensions of national power, generally conceptualised as Diplomatic, Informational, Military and Economic (DIME) levers. Thus, while one metric is insufficient, the grouping of gross metrics can show how powerful actors are in relation to each other.
Power Conversion Problems
Further to this, and reinforcing the case for a more holistic understanding of national power resources, GDP cannot all be leveraged as power, with some expenditure giving no increase in capability or revenue to the state through taxation. This presents challenges in assessing a state’s power resources using a single metric, even before we consider how they can convert resources into power or influence. For example, since 2015 UK real GDP has included sex work, despite brothels being illegal and the industry returning no tax revenue. Although estimates of its GDP are based on significant assumptions from limited data, the industry is calculated to add £5 billion annually to UK GDP. As such, real GDP does not effectively measure relative power resources because it is usually calculated simply by adding up all government, business, and citizen expenditures in a given period.
Real GDP also assumes that the state can efficiently use all these economic resources. China’s attempts to grow ‘value-added services’ over traditional manufactured goods for export have been challenging due to state policies constraining innovation. This reform agenda has stalled the further liberalisation required for a more innovative knowledge-based economy which would threaten the interests of entrenched elites, despite the recent pandemic demonstrating the vulnerability of manufactured goods to disruption. Additional investment in upskilling the population and improving the mobility of skilled labour will increase productivity. However, most of China’s policies to increase competitiveness have been externally focused due to the reduced political risk associated with these policies. These include decreasing tariffs through diplomatic and economic coercion or increasing foreign investment. Therefore, although the Chinese economy is very large, the state is not able to harness it as effectively due to constraints on innovation and the associated political risks.
Even if real GDP were to accurately calculate a state’s power resources, further power conversion problems arise. Some actors are better at converting their resources into influence, so power conversion is the capacity to convert potential power (measured by resources) into realised power (measured by outcomes or the changed behaviour of others. Money is essential and some key capabilities are not visible from conventional metrics. For example, China’s high real GDP does not directly correlate to its technological research or innovation capacity – these rely on cultivated systems of skills, processes, networks, funding and testing and cannot be bought off the shelf. Money is essential and the most fungible resource to convert into power and influence, but the process is not a simple transaction. Implementation and development time is essential to procure and develop a state’s military capabilities. A state military ‘bought’ or hired overnight would be brittle and lacking the organisational systems, culture and training needed to deliver the desired strategic effect. Furthermore, some key power resources in the information age are not directly visible from conventional metrics. For example, China’s high real GDP does not directly correlate to its technological research or innovation capacity. The Chinese paradigm has relied heavily upon adapting existing intellectual property to develop its economy at pace in the past. Therefore, to predict outcomes accurately, rigorous analysis must consider how skilled an actor is at power conversion as well as account for its power resources.
Using military power resources in isolation to measure relative power is also flawed. The USSR reached its military peak in the 1980s despite its economy being in a “death spiral”, demonstrating that military power is often a lagging indicator. The CINC is the most commonly used metric incorporating six categories, focusing on military spending, energy consumption, iron and steel production, urban population, total population, and military personnel numbers to measure military power. However, these are again gross indicators that inflate the capabilities of large, populous nations such as China, which has already overtaken the US in this metric. These metrics, such as total troop numbers, do not accurately measure military capability, which is more complex than simply comparing statistics, especially in the 21st century with expanding technology and production dependencies.
The USSR reached its military peak in the 1980s despite its economy being in a “death spiral”
Therefore, taking one metric as evidence that one actor will overtake another in terms of relative power is inaccurate and exacerbated by using gross indicators. Ultimately, extrapolating whether leading economies will be overtaken in terms of power or even economic capability from a single gross metric, will not lead to any’ inevitable’ conclusion.
Conclusion
This article has illustrated the limitations of gross and isolated metrics being extrapolated for strategic analysis of actors’ relative power. While China will likely overtake the US in terms of real GDP by 2030, this does not necessarily mean it will inevitably overtake the US in terms of net power. China will soon face increasing macroeconomic costs from an ageing population, declining working population and increasing environmental degradation. These factors will eventually lead to wage inflation, increased welfare costs and increased resource costs that must be considered against its rising real GDP.
China also faces costs shared with most developed nations, including the US, such as increasing capital depreciation and increasing demand for greater capital investment to maintain the same level of employment and economic competitiveness. This will further erode net real GDP growth even before non-domestic policies and factors are considered, such as nearshoring, property market debt bubbles, tariffs, increasing animosity against China globally post-Covid, and other potential macroeconomic shocks and trends are considered.
This analysis has highlighted the requirement for future research into calculating net power resources between the US and China for more effective analysis. Relying only on flawed metrics such as real GDP will lead to poor policy formulation and a greater risk of miscalculation among the great powers.
Charlie Bradbury
Charlie is a Venture Strategist at Monitor Deloitte working in the Defence and Security sectors. He is also an Army Reserve infantry officer and guest lecturer at Lancaster University Security Institute.