metadata: authors: 0: author: Mulabdic,Alen
1: author: Nayyar,Gaurav
count: United States,World
docna: 0: docna: Is the U.S. Friend-Shoring, Nearshoring, or
            Reshoring ? Evidence from Greenfield Investment Announcements
docty: Policy Research Working Paper
abstracts: cdata!: This paper examines the evolution of
            greenfield investment announcements&#x2014;both domestic
            and international&#x2014;for US multinational companies
            in response to recent global shocks. The results indicate an
            intensification of reshoring and nearshoring activities by
            US companies, especially following the Russian
            Federation&#x2019;s invasion of Ukraine. This shift is
            estimated to have doubled the number of direct jobs
            associated with greenfield investment announcements in the
            US and its neighboring countries. The paper finds no
            evidence that US companies are adopting a friend-shoring
            strategy by investing more in military allies. The paper
            suggests that US supply chains are likely to become less
            global and more regional as these investments become operational.
display_title: Is the U.S. Friend-Shoring,
            Nearshoring, or Reshoring ? Evidence from Greenfield
            Investment Announcements
listing_relative_url: /research/2024/12/34438589/friend-shoring-nearshoring-or-reshoring-evidence-greenfield-investment-announcements
topicv3: Private Sector Development m1326060 1921,Economic Growth m1326241 471,Trade m1326924 698,Jobs m1503931 2670
publishtoextweb_dt: 2024-12-19T00:00:00Z
dois: 10.1596/1813-9450-11006
origu: Off of Sr VP Dev Econ/Chief Econ (DECVP)
no_of_pages: 24
author_keys: 0: author_key: 1259324
1: author_key: 808820
model_extractions: Policy Research Working Paper 11006 Is the U.S. Friend-Shoring, Nearshoring, or Reshoring? Evidence from Greenfield Investment Announcements _Alen Mulabdic Gaurav Nayyar_ Prosperity Vertical & Prospects Group December 2024 A verified reproducibility package for this paper is available at http://reproducibility.worldbank.org, click **here** for direct access.
Policy Research Working Paper 11006

# **Abstract**

This paper examines the evolution of greenfield investment announcements—both domestic and international—for US multinational companies in response to recent global shocks. The results indicate an intensification of reshoring and nearshoring activities by US companies, especially following the Russian Federation’s invasion of Ukraine. This shift is estimated to have doubled the number of direct jobs associated with greenfield investment announcements in the US and its neighboring countries. The paper finds no evidence that US companies are adopting a friend-shoring strategy by investing more in military allies. The paper suggests that US supply chains are likely to become less global and more regional as these investments become operational.

This paper is a product of the Office of the Chief Economist, Prosperity Vertical and the Prospects Group, Development Economics . It is part of a larger effort by the World Bank to provide open access to its research and make a contribution to development policy discussions around the world. Policy Research Working Papers are also posted on the Web at http:// www.worldbank.org/prwp. The authors may be contacted at amulabdic@worldbank.org and gnayyar@worldbank.org. A verified reproducibility package for this paper is available at http://reproducibility.worldbank.org, click **here** for direct access.

<!-- Start of picture text --> TRANSPARENT<br>ANALYSIS<br>G<br>R E<br>N<br>S<br>I P<br>Y E<br>K A<br>C A<br>R P<br>LI R<br>O E<br>O C<br>W R<br>H<br>S<br>P<br><!-- End of picture text --> _The Policy Research Working Paper Series disseminates the findings of work in progress to encourage the exchange of ideas about development issues. An objective of the series is to get the findings out quickly, even if the presentations are less than fully polished. The papers carry the names of the authors and should be cited accordingly. The findings, interpretations, and conclusions expressed in this paper are entirely those of the authors. They do not necessarily represent the views of the International Bank for Reconstruction and Development/World Bank and its affiliated organizations, or those of the Executive Directors of the World Bank or the governments they represent._ Produced by the Research Support Team
# **Is the U.S. Friend-Shoring, Nearshoring, or Reshoring?**

_Evidence from Greenfield Investment Announcements_<sup>☆</sup> Alen Mulabdic (World Bank) Gaurav Nayyar (World Bank) _Keywords_ : Foreign direct investment, reshoring, friend-shoring, nearshoring, home-bias _JEL Codes_ : F2; F21; F23; F52; F6

> ☆ We are grateful to Amat Adarov, Mirco Balatti, Jakob de Haan, Ayhan M. Kose, Aart Kraay, Michele Ruta, Kersten Stamm and seminar participants at the World Bank for comments and conversations. The findings, interpretations, and conclusions expressed in this paper are entirely those of the authors. They do not necessarily represent the views of the International Bank for Reconstruction and Development/World Bank and its affiliated organizations, or those of the Executive Directors of the World Bank or the governments they represent. The authors may be contacted at amulabdic@worldbank.org and gnayyar@worldbank.org.
# **1. Introduction**

Are multinationals likely to reverse 30 years of globalization? Will global value chains that have benefited some developing countries become increasingly regional? How are businesses reacting to friend-shoring requests by policy makers? The reconfiguration of global value chains can have significant economic implications for the world. For instance, Cerdeiro et al. (2021) estimate that technological decoupling can lead to GDP losses of 5 percent for many countries. At the same time, Brenton et al. (2022) predict that reshoring production to high-income countries and China could drive 52 million people in developing countries into extreme poverty.

Rising geopolitical tensions between the US and China, the Russian Federation’s invasion of Ukraine, and the Covid-19-related supply chain disruptions have led some policy makers and businesses to revisit the benefits of globalization. These events have also highlighted the risks associated with overdependence on countries that are not considered strategic allies. For instance, US Secretary of the Treasury Janet Yellen called US firms to increase friend-shoring with the aim of having production spread across countries “ _[...]that have strong adherence to a set of norms and values about how to operate in the global economy and about how to run the global economic system_ ” to reduce trade partners’ geopolitical leverage from market positions in critical raw materials, technologies, or products that could disrupt the US economy.<sup>1</sup> Recent work shows that FDI is increasingly concentrated among countries with similar UN voting patterns (Aiyar et al., 2023; IMF, 2023).<sup>2</sup> In the specific case of the US, Alfaro and Chor (2023) document an increase in greenfield FDI

> 1 - <u>https://home.treasury.gov/news/press releases/jy0714#:~:text=We%20cannot%20allow%20countries%20to,work%20better%20for%20American %20workers.</u>

> 2 Aiyar et al. (2023) estimate a gravity model using the information on Ideal Point Distances (IPD) developed by Bailey et al. (2017) to show that “geopolitical distance” is an important determinant of FDI during the 2003-2021 period.

2
by US multinationals in Mexico in recent years, particularly in the automobile and electronics sectors. However, these studies only provide anecdotal evidence of reshoring.

The recent Infrastructure Investment and Jobs Act (IIJA) and the Inflation Reduction Act (IRA) have also increased the incentives to relocate production to the US through a combination of tax credits and grants requiring domestic or North American content. For instance, the IRA Section 45X MPTC Advanced Manufacturing Tax Credit applies to components for wind, solar, and battery projects manufactured in the US. To be eligible for the domestic content bonus credit, energy projects and facilities are subject to a domestic content requirement of 40 percent until 2025, which increases to 55 for facilities for which construction begins after 2026.<sup>3</sup> According to Secretary of Energy Jennifer M. Granholm, the rationale for these local content requirements is driven by the aim of “[...] strengthening American manufacturing and enhancing our national security with products stamped ‘Made in the USA.’”<sup>4</sup> To our knowledge, this is the first paper to formally analyze the extent of reshoring by US multinationals, complementing the recent trade literature on the consequences of supply chain disruptions. The paper offers novel insights about the future of US supply chains using information on announcements of greenfield investment projects from the Financial Times fDi Markets database, including projects within the US. The database provides realtime information on cross-border greenfield investments gathered from various sources, including the Financial Times newswire, industry organizations, investment agencies, and company reports. As a result, unlike other data on investments, this information is forwardlooking as it captures announcements about new projects and expansions. Furthermore, unlike other studies, the data allow us to leverage information on domestic investment projects between US states to assess reshoring activities.

> 3 <u>https://www.irs.gov/pub/irs-drop/n-23-38.pdf</u>

> 4 - <u>https://home.treasury.gov/news/press releases/jy1477</u>

3
First, we analyze the pattern of US investment over time through an event study approach that investigates whether the coefficients on distance, border, NATO, and same country variables have changed. We find limited evidence of nearshoring or friend-shoring as the coefficients of the dummy variables for border and NATO appear relatively stable over time. However, the data suggest an intensification in reshoring activities among US companies. Specifically, the same country dummy, which captures how much companies headquartered in the US are investing domestically, became positive and statistically significantly different in 2020 and further increased in magnitude in 2023.

Second, we implement a triple-difference approach comparing US investments to EU investments over time to identify differences in their patterns following the beginning of the US-China trade war, the Covid-19 pandemic, and the Russian invasion of Ukraine. This approach allows us to control for all source country-time, destination country-time, and country-pair unobservable characteristics. The results confirm that US companies intensified their reshoring activities. In addition, we find that, compared to EU firms, US companies also increased nearshoring following the Covid-19 shock. The estimates indicate that US investment in neighboring countries and within the US states doubled during the post Russia’s invasion of Ukraine period, with slightly larger effects for US investment in the US.

Finally, we exploit the richness of the fDi Markets database to assess the impact of the shocks on direct job creation associated with greenfield investment announcements. This allows us to determine whether the increase in investment announcements is associated with job creation in the US or if these investments are likely leading to jobless growth in the manufacturing sector with highly automated factories. The results suggest that recent investments are associated with job creation in both the US and neighboring countries. For example, following the invasion of Ukraine, the number of direct jobs in greenfield investment announcements were more than double in the US and its neighbors. These results combined with the ones for investment, may suggest that more labor-intensive projects are being directed to Mexico.

4
This paper contributes to different strands of the literature. First, it contributes to the recent literature on the economic effects of the US-China trade tensions by expanding the analysis to investment, jobs, and more recent shocks. Several studies investigate the impact of tariff increases on trade, prices, and welfare (Alfaro and Chor, 2023; Amiti et al., 2019; Fajgelbaum et al., 2020; Flaaen et al., 2020; Freund et al., 2024; Gopinath et al., 2024). Second, the paper contributes to the literature that analyzes the effects of shocks on the reshaping of global value chains (Antràs, 2020; Freund et al., 2022; Javorcik, 2020). Third, it documents the importance of shocks in influencing FDI decisions (Aiyar et al., 2023; Alfaro and Chen, 2018; Crescenzi et al., 2021; Harding and Javorcik, 2011; Kox and Rojas‐ Romagosa, 2020). In addition, to the best of our knowledge, this is the first paper that quantifies the home bias in greenfield investment. Home bias has been documented in goods trade (e.g., Anderson and Yotov, 2010; McCallum, 1995) and more recently in government procurement (e.g., García-Santana and Santamaría, 2023; Herz and VarelaIrimia, 2020; Mulabdic and Rotunno, 2022; Rickard and Kono, 2014).

The paper is organized as follows. The next section describes the empirical strategy and data. Section 3 presents our results. Section 4 presents a series of robustness tests, while section 5 extends the analysis to jobs. Section 6 concludes.

# **2. Empirical methodology and data**

This section describes the empirical strategy and data used to analyze changes in greenfield investment patterns following the start of US-China trade tensions, the Covid-19 pandemic, and Russia’s invasion of Ukraine.

# _2.1. Empirical strategy I: Event study approach_

As a first exercise, we implement an event study approach and estimate a gravity-like equation and investigate whether the coefficients on distance, border, NATO, and same country variables have changed over time. Specifically, we rely on the following event study specification: 5
where F is the log of greenfield investment plus one from the US to country in month in a specific year. is a row vector of gravity variables, which include an indicator II jj variable equal to one if country is a member of the North Atlantic Treaty Organization tt GG ZZ (NATO), the log of the population-weighted distance between the US and country , an jj indicator variable equal to one if country is the US, a dummy variable equal to one if jj country is an English speaking country, as well as the log of country _j_ ’s GDP and jj population in the previous year, and time fixed effects . jj jj αα The indicator variable for N N alliance is used as a proxy for the importance of “friends” or strategic military allies. A positive coefficient that increases over time, especially after the Russian invasion of Ukraine, would suggest an intensification of friend-shoring in nations that provide higher security to US businesses. The coefficients on and B capture the sensitivity of investment announcements to physical proximity to the FFD ttyyD yy US. Larger negative coefficients for or larger positive coefficients for B yyBBy in recent years would indicate an intensification of nearshoring activity by US companies. FFD ttyyD yy yyBBy Finally, the coefficient on the dummy variable identifies the home bias of the greenfield investment from the US, reflecting the extent to which investment within SSyySSyy DDBBccDDtty US national borders differs from investment to other countries, capturing the importance of reshoring. Additionally, we also include controls for population and GDP to account for destination market size and economic conditions.

# _2.2. Empirical strategy II: Triple-difference approach_

In a second exercise, we take advantage of the investment data, which allow us to compare US and EU investment flows—the only economies for which we have internal investment. We implement a triple-difference approach and compare the coefficients for distance, 6
<!-- Start of picture text --> = fp + 6<br>+ 0<br><!-- End of picture text --> <!-- Start of picture text --> + oo<br><!-- End of picture text -->
Second, as we observe investment from both the EU and the US, we can include destination country-time fixed effects j to control for any pull factors such as business-friendly reforms in destination markets . Finally, we include country-pair fixed effects to control αα for any time-invariant characteristics determining bilateral investment between and . jj DD jj

# _2.3. Data_

Information on bilateral investment comes from the Financial Times fDi Markets database. The data cover cross-border greenfield investment announcements, including new projects and the expansion of existing projects, at a monthly frequency. In addition to the number of projects, the database provides information on the value of investments. An important feature of the database is that it also tracks US inter-state investments, which allows us to study the impact of recent shocks on reshoring activity by US multinationals.<sup>5</sup> The fDi Markets data have been used extensively in recent research projects and for surveillance purposes by policy institutions, showing that the data tracks well official FDI flows (Aiyar et al., 2023; Alfaro and Chor, 2023; IMF, 2023; Toews and Vézina, 2022; UNCTAD, 2023). The data also cover information on the number of jobs associated with greenfield investment announcements. Toews and Vézina (2022) show that, in the case Mozambique, fDi Markets data is correlated with census data across different sectors, cities, and time but underestimates the total number of jobs created.

The greenfield investment data is combined with standard gravity variables from the CEPII’s gravity database. These variables include the bilateral geographical distance and information on whether countries share the same language, border, or colonial history. Finally, we also construct an indicator variable to capture if country-pairs are part of the

> 5 An important caveat is that the data does not cover intra-US state greenfield investments, which may account for a large share of greenfield investment at the state level.

8
North Atlantic Treaty Organization (NATO).<sup>6</sup> The final sample covers EU and US investment between January 2015 and December 2022 to 156 destination markets.

A first inspection of US investment data in Figure 1 shows no indication of permanent shifts in nearshoring or friend-shoring following the trade tension with China (2018-19), the Covid-19 pandemic (2020-21), and the Russian invasion of Ukraine (2022-23).<sup>7</sup> The share of greenfield foreign direct investment in neighboring and NATO countries declined by a few percentage points when comparing the 2015-17 and 2022-23 periods (Figure 1). However, reshoring activity by US multinationals intensified following the Covid-19 pandemic, with the share of greenfield investment in the US increasing from 46 percent to 56 percent, between the 2015-17 and 2020-21 periods. This evidence corroborates the anecdotal evidence of US manufacturers starting to bring back factories to the US.<sup>8</sup> These investments are likely to have an impact on trade flows once they become operational.

> 6 List of NATO countries: Belgium (1949), Canada (1949), Denmark (1949), France (1949) Iceland (1949), Italy (1949), Luxembourg (1949), Netherlands (1949), Norway (1949), Portugal (1949), United Kingdom (1949), United states (1949), Greece (1952), Türkiye (1952), Germany (1955), Spain (1982), Czechia (1999), Hungary (1999), Poland (1999), Bulgaria (2004), Estonia (2004), Latvia (2004), Lithuania (2004), Romania (2004), Slovak Republic (2004), Slovenia (2004), Albania (2009), Croatia (2009), Montenegro (2017), and North Macedonia (2020). We assume that the EU is a NATO member even if some of the EU countries are not part of the alliance.

> 7 These results are similar to Aiyar et al. (2023) that show no impact of geopolitical distance for advanced economies.

> 8 See for instance Bloomberg “US Manufacturers ‘Pumped Up’ About Supply-Chain Reshoring Trend” (November 2, 2022) <u>https://www.bloomberg.com/news/articles/2022-11-02/us-manufacturers-pumped-upabout-supply-chain-reshoring-trend</u> and the Wall Street Journal “U.S. Companies on Pace to Bring Home Record Number of Overseas Jobs” (August 23, 2022) <u>https://www.wsj.com/articles/u-s-companies-on-paceto-bring-home-record-number-of-overseas-jobs-11660968061.</u>

9
<!-- Start of picture text --> 6<br>5<br>£<br>g 4<br>z<br>ao<br>i)<br>‘Ss<br>§2<br>=<br>wn<br>0<br>2015-17 2018-19 2020-21 2022-23<br>(Trade War) (Covid-19) (Invasion of Ukraine)<br>(08) USA HE NATO countries =~ Neighboring countries<br><!-- End of picture text -->
<!-- Start of picture text -->
1.5 |<br>: 1<br>am<br>=: ! |<br>2015 «2016 «= 2017) 9.2018 )9=—2019 20202021 92022 = 2023<br>e I(Same country) e I(NATO) e I (Border)<br><!-- End of picture text -->
multinationals increased investment in the US during the Covid-19 pandemic, with further increases following Russia’s invasion of Ukraine.

# _3.2. Evolution of the determinants of US investment flows: Triple difference_

One potential issue with the event study approach is that the results could be driven by unobservable characteristics such as global trends or country-specific shocks. For instance, nearshoring of production may be happening, but given that future economic prospects in Asia may be improving, an analysis for the US only would not capture this trend. Also, the reshoring results could be driven by exceptionally favorable investment conditions in the US. Thus, we employ a triple-difference approach where we compare US investment to EU27 investment over time. This specification allows us to control both for source- and destination-time fixed effects as well as county-pair fixed effects.

Table 1 reports the estimates from equation (2). Results point to strong evidence of nearshoring for the US FDI compared to the EU. The border dummy increased both in terms of magnitude and statistical significance following the outset of the Covid-19 pandemic (column 2). Estimates from column (3) show that the border coefficient decreased slightly after Russia’s invasion of Ukraine from 0.804 to 0.643. This translates to investment being 90 percent higher in neighboring countries compared to others.<sup>10</sup> This large effect and absence of significance during the trade war period, can be explained by the uncertainty related to the North American Free Trade Agreement (NAFTA) and subsequent ratification of the United States–Mexico–Canada Agreement (USMCA), which came into effect on July 1, 2020, and stimulated US investment in Canada and Mexico.

The triple-difference approach confirms the intensification of reshoring activity by US companies which intensified over time. The coefficient of the same country dummy variables for the US in the post-invasion of Ukraine period is 0.795. This implies that,

> 10 exp(0.643) −1 = 0.902.

12
everything else being equal, the value of investment between US states in the post-shock period, compared to the EU, is more than double than investment between the US and other countries.<sup>11</sup> Similarly to the event study approach, we do not find evidence of an increase in nearshoring, proxied by distance, or friend-shoring, proxied by NATO. If anything, investment by US multinationals in countries that are military allies of the US decreased over time.

> 11 (0.795) −1 = 1.214. yye

13
# _Table 1: Triple difference_

||(1)<br>|(2)<br>ln(FDI)<br>|(3)<br>|
|---|---|---|---|
||Trade War|Covid-19|Invasion of Ukraine|
|**I(t>Event) x I(US) x ...**||||
|... x I(Same country)|0.583*|0.781**|0.795***|
||(0.337)|(0.306)|(0.281)|
|... x I(Border)|0.233|0.804**|0.643**|
||(0.417)|(0.336)|(0.300)|
|... x ln(distance)|0.236**|0.034|0.078|
||(0.117)|(0.090)|(0.077)|
|... x I(NATO)|-0.067|-0.371*|-0.485***|
||(0.218)|(0.200)|(0.165)|
|... x I(Common language)|-0.099|-0.192**|-0.186**|
||(0.116)|(0.089)|(0.081)|
|**I(t>Event) x ...**||||
|... x I(Same country)|-0.516*|-0.490*|-0.486**|
||(0.311)|(0.256)|(0.237)|
|... x I(Border)|-0.251|-0.238|-0.257|
||(0.233)|(0.183)|(0.164)|
|... x ln(distance)|-0.311***|-0.105|-0.116*|
||(0.086)|(0.070)|(0.060)|
|... x I(Common language)|0.141|0.143*|0.089|
||(0.110)|(0.084)|(0.075)|
|Observations|20,088|27,540|34,992|
|R-squared|0.865|0.863|0.862|

Note: The regression includes source country-time, host country-time, and source country-host country fixed effects. The sample covers bilateral US and EU investment. In column (1), the sample covers the period from January 2015 to February 2020 (Trade War); in column (2), from January 2015 to January 2022 (COVID19); and in column (3), from January 2015 to December 2023 (Invasion of Ukraine). Robust standard errors, clustered at the source-time level, are reported in parentheses. *** p<0.01, ** p<0.05, * p<0.1

# **4. Robustness analysis**

This section presents a series of robustness checks. First, to handle the zero investment flows, we use the Poisson pseudo maximum likelihood (PPML) estimator. Second, to exclude that our results are driven by phantom investment in small countries, we estimate the baseline regressions on the sample of countries with a population greater than 1 million.

14
Table 2 presents the robustness tests for the value of investment. Columns (1) to (3) present the results of estimating equation (2) with a PPML estimator. The results for reshoring and nearshoring are robust to the inclusion of zeros. The results show that investment in the US and neighboring countries has increased over time, particularly following the Covid-19 and Russia’s invasion of Ukraine. The estimated effects are larger than those in Table 2, with investment in the US increasing by a factor of six, while investment in neighboring countries increasing fourfold.

Columns (4) to (6) present the results of the baseline specifications estimated using the sub-sample of countries with a population greater than 1 million. This smaller sample excludes small countries such as the Bahamas and Cayman Islands, which may attract investment without having strong economic fundamentals. The results are qualitatively and quantitively similar to those presented in Table 1. The nearshoring and reshoring activities start with Covid-19 and accelerate with the invasion of Ukraine in the case of reshoring.

15
_Table 2: Robustness PPML and small countries_

||(1)|(2)<br>PPML|(3)|(4)<br>Small|(5)<br>countries ex|(6)<br>cluded|
|---|---|---|---|---|---|---|
|||FDI|||ln(FDI)||
||Trade War|Covid-19|Invasion of<br>Ukraine|Trade War|Covid-19|Invasion of<br>Ukraine|
|**I(t>Event) x I(US) x ...**|||||||
|... x I(Same country)|1.172|1.389**|1.832***|0.613|0.888**|1.087***|
||(0.785)|(0.676)|(0.702)|(0.489)|(0.397)|(0.362)|
|... x I(Border)|0.562|1.084*|1.396**|0.264|0.923**|0.904**|
||(0.650)|(0.651)|(0.651)|(0.537)|(0.419)|(0.372)|
|... x ln(distance)|0.236|0.241|0.377|0.243|0.010|0.135|
||(0.346)|(0.319)|(0.342)|(0.201)|(0.142)|(0.125)|
|... x I(NATO)|-0.430|-0.370|-0.539|-0.066|-0.517**|-0.676***|
||(0.412)|(0.394)|(0.341)|(0.244)|(0.237)|(0.200)|
|... x I(Common language)|-0.299|-0.377**|-0.374**|-0.063|-0.159|-0.165*|
||(0.184)|(0.174)|(0.175)|(0.134)|(0.101)|(0.093)|
|**I(t>Event) x ...**|||||||
|... x I(Same country)|-0.453|-0.451|-0.724|-0.531|-0.632**|-0.775***|
||(0.600)|(0.524)|(0.514)|(0.386)|(0.305)|(0.281)|
|... x I(Border)|-0.246|-0.254|-0.540|-0.279|-0.325|-0.418**|
||(0.470)|(0.474)|(0.457)|(0.275)|(0.216)|(0.194)|
|... x ln(distance)|0.115|0.138|0.102|-0.318***|-0.108|-0.155**|
||(0.171)|(0.197)|(0.210)|(0.116)|(0.087)|(0.076)|
|... x I(Common language)|0.068|0.009|-0.112|0.129|0.133|0.057|
||(0.239)|(0.219)|(0.219)|(0.118)|(0.097)|(0.090)|
|Observations|7,622|10,006|12,678|15,996|21,930|27,864|
|R-squared||||0.861|0.860|0.859|

Note: The regression includes source country-time, host country-time, and source country-host country fixed effects. The sample covers bilateral US and EU investment. In columns (1) and (4), the sample covers the period from January 2015 to February 2020 (Trade War); in columns (2) and (5), from January 2015 to January 2022 (Covid-19); and in columns (3) and (6), from January 2015 to December 2023 (Invasion of Ukraine). Robust standard errors, clustered at the source-time level, are reported in parentheses.

*** p<0.01, ** p<0.05, * p<0.1

# **5. Extensions to jobs**

This section expands the analysis to assess the impact of recent shocks on estimated jobs created directly through greenfield investment projects. Given the identified reshoring trend, we test for similar trends using information on the number jobs in the US associated 16
with these investments. If a small number of capital-intensive projects drives the investment results, we would expect a limited impact on direct job creation associated with greenfield investment in the US or neighboring countries.

Table 3 reports the results of estimating equation (2), where the dependent variable is the number of jobs created by the announced investment projects instead of the value of projects. All specifications include source-time, destination-time, source-destination fixed effects to control for country-specific time-varying shocks as well as country-pair time invariant characteristics.

Results in column (1) show no increase in the number of jobs associated with greenfield announcements in the US, Canada, or Mexico following the beginning of the trade war. This could be the effect of the high uncertainty created by the renegotiation of the North American Free Trade Agreement (NAFTA), which diminished after the ratification of the United States–Mexico–Canada Agreement (USMCA) in March 2020. The border and same country variables become significant in columns (2) and (3) following the Covid-19 and Russia’s invasion of Ukraine shocks.

The number of jobs associated with greenfield announcements doubled following Russia’s invasion of Ukraine both in the US and neighboring countries. These effects are similar to those observed for investment value, as presented in Table 1, but slightly stronger for neighboring countries, which could be indicative of more labor intensive projects being directed to Mexico. This evidence suggests that contrary to widespread belief, US multinationals are not merely repatriating factories but are also bringing back some jobs.

17
_Table 3: Number of jobs_

||(1)<br>|(2)<br>ln(Jobs)<br>|(3)<br>|
|---|---|---|---|
||Trade War|Covid-19|Invasion of Ukraine|
|**I(t>Event) x I(US) x ...**||||
|... x I(Same country)|0.469|0.697**|0.723**|
||(0.439)|(0.353)|(0.322)|
|... x I(Border)|0.424|0.917**|0.723**|
||(0.454)|(0.352)|(0.317)|
|... x ln(distance)|0.374**|0.151|0.193*|
||(0.151)|(0.113)|(0.098)|
|... x I(NATO)|0.147|-0.229|-0.367*|
||(0.306)|(0.251)|(0.217)|
|... x I(Common language)|-0.180|-0.267***|-0.262***|
||(0.130)|(0.100)|(0.091)|
|**I(t>Event) x ...**||||
|... x I(Same country)|-0.439|-0.421|-0.589**|
||(0.364)|(0.303)|(0.282)|
|... x I(Border)|-0.438|-0.367*|-0.374*|
||(0.276)|(0.214)|(0.198)|
|... x ln(distance)|-0.457***|-0.187**|-0.193**|
||(0.107)|(0.086)|(0.075)|
|... x I(Common language)|0.195|0.186*|0.124|
||(0.135)|(0.101)|(0.090)|
|Observations|20,088|27,540|34,992|
|R-squared|0.863|0.863|0.862|

Note: The regression includes source country-time, host country-time, and source country-host country fixed effects. The sample covers bilateral US and EU investment. The sample covers bilateral US and EU investment. In column (1), the sample covers the period from January 2015 to February 2020 (Trade War); in column (2), from January 2015 to January 2022 (COVID-19); and in column (3), from January 2015 to December 2023 (Invasion of Ukraine). Robust standard errors, clustered at the source-time level, are reported in parentheses. *** p<0.01, ** p<0.05, * p<0.1 18
# **6. Conclusion**

This paper uses data on monthly greenfield investment announcements from 2015 to 2023 to study how US-China trade tensions, the Covid-19 pandemic, and the Russian invasion of Ukraine are reshaping US investment. The paper shows that US multinationals reacted to recent shocks by mainly reshoring their activities. When comparing US multinationals to their EU counterparts, we find that investment patterns differed following the recent shocks. The evidence indicates that the reshoring trend by US multinationals started with the Covid-19 shock and accelerated with the Russia’s invasion of Ukraine. An increase in greenfield investment in neighboring countries has accompanied this reshoring trend. Furthermore, the results suggest that reshoring and nearshoring of investment projects is also associated with the reshoring and nearshoring of jobs.

These findings are particularly important for developing countries as a retreat from globalization by US multinational corporations could negatively affect their growth prospects. FDI has played an important in providing capital to, and fostering productivity growth, in developing countries (e.g., Alfaro and Chauvin, 2020; Smarzynska Javorcik, 2004). The linkages between multinational enterprises and domestic firms, especially in global value chains, have been associated with knowledge and technology spillovers (e.g., Dasgupta, 2012; Sinani and Meyer, 2004), which play a fundamental role in income convergence across countries.

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