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A new index to measure geopolitical fragmentation in global greenfield foreign direct investment

Global foreign direct investment flows are increasingly mirroring the world’s geopolitical divides. This column introduces a new index for FDI fragmentation that differentiates flows within and between three distinct blocs: a Western bloc, an Eastern bloc, and a neutral bloc of non-aligned nations. Being part of different geopolitical blocs reduces greenfield FDI flows between two countries by almost two-thirds, a shift not solely due to dwindling investments between China, Russia, and their Western counterparts, but also to a more widespread phenomenon reshaping the landscape of global investments.

‘Friendshoring’ or ‘nearshoring’ of production are much debated efforts to enhance the resilience of supply chains amidst geopolitical tensions. Any major reorganisation of global trade and value chain networks could be associated with shifts in global foreign direct investment (FDI). Though multiple contributions have looked at the implications of geopolitical fragmentation on trade (Aiyar et al. 2023a, Attinasi et al. 2023, Campos et al. 2023, Bosone et al. 2024), recently the impact of this fragmentation on FDI flows has gained prominence as well (IMF 2023, Casella et al. 2024, Gopinath et al. 2024, ECB 2024).

In this column, we explore trends in global greenfield FDI flows in the context of geopolitical fragmentation. Unlike previous analyses, we provide a continuous empirical measure that reveals how geopolitical alignments have influenced these flows over time. For our analysis, we leverage proprietary data on greenfield FDI flows from fDi Markets, data that give us insights into cross-border investments in new physical projects or expansions of existing investments. To analyse FDI fragmentation, we adopt a technical assumption that the world economy might exogenously fragment into three distinct blocs: a Western (US-centric) bloc, an Eastern (China-centric) bloc, and a neutral bloc comprising non-aligned countries. It is important to emphasise that this assumption – widely used in recent literature (ESCB 2024, Gopinath et al. 2024, Gopinath 2023, Aiyar et al. 2023, Felbermayr et al. 2023) – is highly simplifying, as FDI fragmentation can occur within countries of the same bloc as well. Therefore, this partitioning of the global economy into blocs should be regarded as a purely narrative device and is not intended to reflect any political stance. The classification we use is based on the geopolitical index developed by den Besten et al. (2023).

The effect of geopolitical fragmentation on the direction of FDI flows is ambiguous ex ante. On one hand, firms and policymakers might pursue friendshoring and/or nearshoring of production to make supply chains less vulnerable to geopolitical tensions or to protect their assets from potential future violations of property rights. On the other hand, firms might increase their investments in geopolitically distant countries – those with noticeably different stances on foreign policy issues – if they believe that future trade tensions could impede their access to local markets.

Descriptive analysis indicates that aggregate greenfield FDI flows are increasingly fragmenting along geopolitical fault lines. Western companies have been boosting investments in friendly (Western) countries, while reducing investments in geopolitically distant (Eastern) countries. Greenfield FDI flows within the Western bloc have been on the rise since 2016, while flows between the Eastern and Western blocs have declined (Figure 1). 1 The increase in greenfield investment by companies located in the Western bloc into friendly and neutral countries aligns with evidence from earnings call data, which shows a noticeable uptick in references to ‘friendshoring’, suggesting that Western companies are increasingly friendshoring or nearshoring their production capabilities.

Industrial policies could be another driver of the recent evolution of FDI flows. For example, the adoption of the Inflation Reduction Act (IRA) might have strengthened greenfield FDI inflows into the US and into IRA-related sectors, driven by IRA-related incentives for companies to shift their production to the US.

Figure 1 Global greenfield FDI flows

Figure 1 Global greenfield FDI flows
Figure 1 Global greenfield FDI flows
Note: Left: index Q1 2019 = 100; right: incidence of “shoring” terms. The latest observations are for the first quarter of 2024. Incidence of shoring terms refers to share of sentences containing at least one of the search phrases in all sentences made during an earnings call by a given firm. This firm-level exposure is averaged across all firms in each region and across days to arrive at a quarterly frequency. The terms considered were “friend shoring”, “friend-shoring”, ”nearshoring”, “near-shoring”, “onshoring”, “on-shoring”, “reshoring”, and “re-shoring”.
Sources: fDi Markets, NL Analytics, and ECB staff calculations.

Next, we turn to econometric analysis to control for potential confounding factors that could explain the time variation in FDI flows along geopolitical fault lines. We set up a gravity model and use specific dummy variables to capture FDI flows within or between geopolitical blocs (Figure 2). The ‘within’ dummy is assigned to FDI flows inside either the Western or Eastern bloc, while the ‘between’ dummy marks FDI flows occurring between the Western and Eastern blocs. The ‘other’ category, which serves as the residual (omitted) category, includes flows (1) between Western and neutral countries, (2) between Eastern and neutral countries, and (3) within the neutral bloc.

Figure 2 Categorisation of FDI flows along geopolitical blocs

Figure 2 Categorisation of FDI flows along geopolitical blocs
Figure 2 Categorisation of FDI flows along geopolitical blocs
Sources: Authors’ own depiction. Classification of blocs following den Besten et al. (2023). 

Our regression analysis also incorporates several control variables, such as traditional time-invariant gravity variables (geographical distance, common language, common legal background, and former colonial relationship), a dummy for preferential trade agreements, another for intra-EU investment, and fixed effects for source-time and destination-time. The model is similar to that of Gopinath et al. (2024). However, instead of estimating a panel over the entire horizon, we run regressions using a rolling window of 12 quarters, spanning Q1 2003 to Q1 2024 (similar to the gravity model for trade in ESCB 2024, which employs a period-by-period estimation). The key advantage of this approach is that it provides a continuous measure of how fragmentation has affected FDI over time. The dependent variable is the estimated cumulative FDI flows in USD between two countries, covering both the extensive and intensive margins of greenfield FDI.

Our findings suggest that FDI flows between countries within the same bloc (whether Eastern or Western) have historically been higher than those in the ‘other’ category. Figure 3 reports the evolution of regression coefficients of dummies for FDI between and within geopolitical blocs over time. 2 Since 2005, the ‘within’ dummies have been positive (Figure 3). Conversely, throughout the entire sample period, the coefficients for the ‘between’ dummies were generally smaller, and occasionally even negative or not significantly different from zero. In recent years, the ‘between’ coefficients have declined further while the ‘within’ dummies have remained broadly stable, resulting in a growing gap between the two.

Figure 3 FDI fragmentation index and coefficients of within and between dummies

Figure 3 FDI fragmentation index and coefficients of within and between dummies
Figure 3 FDI fragmentation index and coefficients of within and between dummies
Notes: Between and within denote regression coefficients of dummies for FDI between and within geopolitical blocs, respectively, compared to FDI flows that fall into the other category. Estimations are carried out in rolling windows of 12 quarters between 2003Q1 and 2024Q1. Vertical bars denote the respective standard errors around the point estimate. The FDI fragmentation index is calculated as exp(within)/exp(between).
Source: Authors’ calculations.

We introduce an index for geopolitical fragmentation in FDI flows (the FDI fragmentation index) based on the ratio of the ‘within’ and ‘between’ coefficients. The index suggests that, in the three years up to Q1 2024, FDI flows within geopolitical blocs were nearly three times higher than between blocs, irrespective of factors such as economic size or geographical distance. 3 A few years ago, the index indicates that the ratio was lower than two and sometimes approaching a value of one, suggesting that geopolitical alignment was much less important in explaining global FDI flows at the time.

We build a set of alternative indices for geopolitical FDI fragmentation to assess whether the recent decline in FDI flows between the Eastern and Western blocs has been driven mainly by flows involving China or Russia. To this end, we isolate specific country pairs that are part of the ‘between’ category to determine their impact on the observed increase in the fragmentation index. One regression excludes FDI flows between China and its main Western investment counterparts – the US, Japan, the EU, and Taiwan – to assess whether the observed increase in the fragmentation index might be driven by a rebalancing of FDI flows formerly directed towards China. Another specification excludes FDI flows between Russia and its key Western counterparts – the US, the EU, Japan, and South Korea – considering that geopolitical shifts following Russia’s invasion of Ukraine could be driving the aggregate fragmentation index. However, the alternative fragmentation indices reveal very similar dynamics to the baseline, suggesting that recent trends in FDI flows between the Eastern and Western blocs are not driven primarily by flows involving China or Russia and their major Western counterparts, but rather reflect a broader phenomenon (Figure 4). 4

Figure 4 FDI fragmentation index: Robustness

Figure 4 FDI fragmentation index: Robustness
Figure 4 FDI fragmentation index: Robustness
Notes: Estimations are carried out in rolling windows of 12 quarters between 2003Q1 and 2024Q1. The FDI fragmentation index is calculated as exp(within)/exp(between). Excluded main China flows are FDI flows between China and the US, Japan, Taiwan, and the EU, respectively. Excluded main Russia flows are FDI flows between Russia and the US, the EU, Japan, and South Korea, respectively.
Source: Authors’ calculations.

Our findings corroborate earlier research that greenfield FDI is increasingly influenced by geopolitical divides. Descriptive evidence suggests that greenfield FDI has either remained steady or intensified within geopolitical blocs and has recently decreased between them. This is supported by econometric analysis using a gravity model, which shows that FDI flows within geopolitical blocs were almost three times higher than those between blocs in the three years leading up to Q1 2024, regardless of country-specific characteristics such as economic size or distance. These developments in the global greenfield FDI network might foreshadow a reconfiguration of global trade and value chain networks becoming increasingly fragmented along geopolitical lines.

Source : VOXeu

GLOBAL BUSINESS AND FINANCE MAGAZINE

GLOBAL BUSINESS AND FINANCE MAGAZINE

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