Relative factor endowments, foreign direct investment and tax planning of multinational firms: an empirical investigation into cross-country data

ABSTRACT

This paper studies the impact of relative endowments of skilled labour and physical capital on the location choices of multinational firms (MNEs). We demonstrate potential methodological issues and possible solutions related to the identification of vertical MNE activity when using aggregate country-level data. To support our analysis, we introduce data matching and various assumptions with respect to the degree of profit shifting activities of MNEs that we apply to study unilateral inward foreign direct investment (FDI) across Estonia, Latvia, and Lithuania. Our choice of data is motivated by various legislation gaps, taxation specificities, and growing equity stocks in sectors related to profit shifting in the aforementioned economies. Ultimately, we highlight the importance of international tax differences and the growing discrepancy between real and reported cross-country FDI data.

KEYWORDS:

• Foreign direct investment
• profit shifting
• Estonia
• Latvia
• Lithuania

JEL:

• F23: P33

Acknowledgements

We are thankful to Krzysztof Szczygielski, Stefano Bolatto, Sarhad Hamza, and three anonymous referees for their comments and suggestions on the earlier drafts of the paper. Gurshev acknowledges financial assistance from the University of Warsaw, and host assistance from the University of Bologna.

Disclosure statement

No potential conflict of interest was reported by the authors.

Notes

1 This refers to, inter alia, Belize, Cyprus, Malaysia, Mauritius, Panama, and Singapore. Destinations that were frequently found to be major locations of the abovementioned accounting activities in the studies of Hines and Rice (1994), Davies et al. (2018), and Damgaard et al. (2019).

2 As Davies et al. (2018) note, the implementation of the arm’s length principle alone is not sufficient to completely deter profit shifting as there are ways with which the final price can be determined. Hence, the existing methodological legislative flexibility still leaves a lot of room for MNEs to prove that the declared intra-group price is correct to national tax authorities.

3 Due to the existing lack of up-to-date firm-level studies using data from either Latvia or Lithuania, there is no certainty about whether any of incoming FDI in financial or insurance sectors is completely real.

4 For example, according to Bank of Russia (2021), between 2009 and 2019 firms with residence in Cyprus maintained FDI stocks valued at around $128.3 billion (current dollars, annual average), while firms from the closest real investor economy – Germany, had only $13.5 billion.

5 We acknowledge that this approach ignores the existence of multi-stage profit shifting. Nevertheless, given the available data, we can at least demonstrate that such a setup can yield sensible empirical results.

6 The use of stock data is dictated by the following facts: first, unlike affiliate sales, bilateral FDI stock data are significantly more widespread and readily available for a large group of economies. As a result, cross-comparison, and panel data analysis can be applied to a great extent. Second, unlike flow data (net FDI), which are a sum of equity and debt instruments, stock data contains only the reported real capital equity owned by foreign affiliates in a given host economy.

7 Damgaard et al. (2019) construct cross-country FDI positions using IMF’s Coordinated Direct Investment Survey (CDIS) that reports basic annual equity ownership across 100–105 economies together with the OECD FDI Statistics database that specifies how much inward FDI is conducted into SPE and non-SPE entities. Then, the ultimate owner economy is identified using firm-level corporate ownership information from Orbis.

8 While the current (2023) EU blacklist treats Russia and Costa Rica as non-cooperative tax jurisdictions, between 2009 and 2019 both countries were not considered as such. Hence, our analysis does not account for this change.

9 In all fairness, because the employed estimator drops observations that are either singletons or separated by fixed effects, our results never feature the complete number of observations, more details are in Correia et al. (2020).

10 Here we refer to the two types FDI data we use from Damgaard et al. (2019): i) total FDI (this includes both real- and SPE-related transactions, and similar to the data we observe using national sources), and ii) non-SPE FDI (genuine value of real equity only).

11 This also includes cases where the use of robust standard errors in OLS are not able to completely mitigate concerns about heteroskedasticity and will lead to incorrect inference from the regression analysis.

12 The estimated parameter remains significant at the 5% level only in case when we use Damgaard’s total FDI stock data (single determinant case). In the other instances, it is insignificant (national data) and weakly significant (non-SPE FDI stocks only), see Table B2 for details (Appendix).

13 These additional results are available upon request from the authors.

Additional information

Notes on contributors

Andrzej Cieślik

Prof. Andrzej Cieślik is a full professor of economics at the Faculty of Economic Sciences, University of Warsaw.

Oleg Gurshev

Dr. Oleg Gurshev is a PhD student at the Faculty of Economic Sciences, University of Warsaw.