3 Connecting FDI and FATS statistics

3.2 Pass-through analyses

Another way of combining FDI and FATS statistics is the analysis of micro-data, linking inward and outward datasets. For the following example the FDI microdataset is taken as a basis for applying FATS concepts.8

Domestic FDI entities are divided in three groups:

1. Inward investment only, foreign control

2. Inward and outward investment, foreign control 3. Outward investment, domestic control

8 A similar exercise was performed in OeNB 2016, chapter 1.4.

The three groups are plotted in the centre column of figure 8.1.

The idea of this analysis is to show the flow of control to, through and from Austria. The metric used is the number of FDI entities. Inward FDI entities consist of “Inward FDI adjusted” and “Pass through”, outward FDI entities are in the “Pass through” and “Outward FDI adjusted” classes. “Pass through” is of specific interest because both directions, inward and outward, are combined in this group.

Figure 8.1: Pass through analysis 2014, No. of units

Taking the perspective of controlling regions (left column), several things regarding the control of the group “Inward FDI adjusted” are notable. Euro-pean investors, regardless of EU membership, have a fairly even split between controlling Austrian units in group 1 (“Inward FDI adjusted”) and group 2 (“Pass through”), whereas investors from overseas have a clear majority of their Austrian units in group 2 (“Pass through”). Obviously these investors typically do not solely use domestic subsidiaries to conduct business in Austria, but to a large degree for managing or financing other enterprises via Aus-tria. The target regions (right column) of group 2 (“Pass through”) are mainly CESEE and other European countries. The overseas regions are dominated by group 3 (“Outward FDI adjusted”), Austrian controlled, domestic investors.

Combining these findings one could conclude that overseas MNEs typically use Austrian affiliates for operations in Austria and as a hub to other European

countries. For European investors on the other hand, it is more likely that Austria is the final destination of their engagement. As a result overseas regions as a target group are in many cases controlled by genuine Austrian investors.

4 References

Greul, Cernohous, Dell’mour 2010: Die neue Auslandsunternehmenseinhei-ten-Statistik. Statistische Nachrichten 1/2010 und Statistiken Q1/10, Wien.

IMF 2009: Balance of Payments and International Investment Position Manu-al; Sixth Edition (BPM6); Washington.

OECD 2008: Benchmark Definition of Foreign Direct Investment; Fourth Edi-tion (BD4); OECD.

OeNB 2016: Direktinvestitionen 2014 – Österreichische Direktinvestitionen im Ausland und ausländische Direktinvestitionen in Österreich – Stand per Ende 2014; Statistiken Sonderheft; Wien Dezember 2016.

STATISTIK AUSTRIA 2016: Pressemitteilung 11.372-183/16, Auslandsunter-nehmen 2014; Wien.

STATISTIK AUSTRIA 2011: Standard-Dokumentation, Metainformationen zur Auslandsunternehmenseinheitenstatistik („Foreign Affiliates Statistics – FATS“); Wien.

UNCTAD 2016; World Investment Report 2016; Reforming International In-vestment Governance; New York and Geneva.

FATS- und FDI-Statistiken: Enge Verknüpfungen, unterschiedlicher Fokus Statistiken zu ausländischen Direktinvestitionen (FDI) und Statistiken zu Aus-landsunternehmen (FATS) sind eng miteinander verbunden, da beide den grenz-überschreitenden Einfluss der Eigentumsstrukturen von Unternehmen messen.

Während sich die Grundgesamtheiten überlappen und beide einen stark integrierten Entstehungsprozess aufweisen, werden jeweils unterschiedliche Fragestellungen beantwortet. FDI-Statistiken verfolgen die finanziellen Entwicklungen von grenz-überschreitenden Investitionen, FATS statistiken wiederum beleuchten Sachver-halte der Realwirtschaft. Für diese Unterschiede in den Berechnungsverfahren und in den Indikatoren von Entstehungsprozessen existieren gute Gründe. Diese Arbeit beginnt mit einem historischen Überblick, insbesondere hinsichtlich der Imple-mentierung beider Statistiken in Österreich, wobei im Anschluss die Unterschiede zwischen FDI und FATS im Detail erläutert werden. Trotz der unterschiedlichen Methoden kann ein Zusammenbringen von Aspekten beider Statistiken einen Nut-zen generieren. Deshalb wird schlussendlich ein FDI-Mikrodatenset mit Berech-nungsmethoden und Indikatoren der FATS-Methodologie verbunden, wodurch womöglich neue Einblicke in grenzüberschreitende Strukturen von österreichi-schen Unternehmen gewonnen werden können.

JEL code: F2


Gábor Hunya

FDI inflow to 22 CESEE countries increased in 2016 to its highest level since 2008.

The recovery was most robust in the Central European EU Member States while in Russia a large foreign acquisition made a one-time contribution. Also greenfield investment activities increased, albeit more modestly than FDI inflows. Manufac-turing and financial services have attracted the largest amounts of FDI, but there are also numerous greenfield projects in the advanced services sectors.

1 General features of FDI in the CESEE since the global financial crisis

The inflow of foreign direct investment (FDI) had long been considered a main driver of economic growth in the countries of Central, East and Southeast Europe (CESEE). The aim of this chapter is to check the existence of any meaningful trend in the development of FDI and its contribution to economic development in 2013–2016. The analysis is imbedded into longer trends fol-lowing the global financial crisis.

During transition, FDI was expected to provide much-needed capital and knowledge, as well as access to technology and markets. The three main regions of transition countries developed along different trajectories. Those countries that have become EU members (EU-CEE) have attracted significant amounts of both market-seeking and efficiency-seeking FDI and have benefited from the expected positive impacts. While most of the EU-CEE countries have been integrated into multinational production networks via FDI, this has scarcely occurred in the former Soviet Union (Commonwealth of Independent States – CIS + Ukraine) and the Western Balkans (WB; see table 9.1 for the members of country groups). In the CIS countries and Ukraine, unfavourable legal and business conditions have restricted the scope of FDI. Inflows have been domi-nated by the local oligarchy’s capital transfers, while genuine foreign capital has played only a limited role. In the Western Balkans, FDI has been mainly con-fined to domestic market-oriented sectors, leaving unutilised scope for export-oriented FDI in manufacturing and services.

FDI boomed until the financial crisis and foreign investment enterprises became dominant in several EU-CEE and WB countries, contributing to com-petitiveness and growth. Since 2009, investments have declined all across Europe, including cross-border investments. EU-CEE and WB economies had to rebalance their balance of payments to adjust to lower capital inflows. In the EU-CEE countries, external financing has shifted from private capital to

EU funds. FDI inflows have not only been much smaller than they were before the crisis, but they have also fluctuated wildly from one year to another, losing their connection with economic growth or changes in the business environ-ment. The interpretation of FDI flow data by the standard location factors has thus become increasingly difficult.

The content and structure of FDI data have also changed a lot despite switch-ing the methodology to the IMF Balance of Payments Manual 6 based on the directional principle. Inflow of real investment capital is hard to define because capital relations between subsidiaries and parent companies have become more complex: capital reserves, losses and profits are shifted around within multina-tional conglomerates in various forms of FDI and income; pass-through funds and restructuring of financial assets registered as inflow and simultaneous out-flow of FDI distort the statistics.1 Further, tax optimisation by multinational enterprises is one of the main factors determining the economic sector and the immediate home country of the investment. As to sectors, investors often organise subsidiaries into holding companies, which provide room to balance profits and losses over various fields of activity. Tax regimes direct the loca-tion choice for multinaloca-tional headquarters. Holdings are often registered in the Netherlands or in Luxembourg, two countries that provide favourable condi-tions for headquarters; or in Cyprus and in Caribbean islands, which have the lowest corporate tax rates worldwide. Domestic companies may also flee from high taxes and insecure property rights to tax havens, and return as foreign direct investors in their country of origin (roundtripping, characteristic of Rus-sia, first of all).

Despite all these distortions, FDI-related analysis and academic research have continued to use FDI data reported in the balance of payments on the assumption that these data reflect at least in part the contribution of foreign capital to domestic investments. In the analysis below, 2016 FDI inflow data are partly estimated and also 2015 data can be subject to further revisions (table 9.1). As a further source, greenfield FDI statistics are used to trace the location choice of new investment projects.

1 Table 9.1 includes two series of data for Hungary, the only country for which data are available; negative FDI inflow figures for Slovakia may have a similar reason.

Table 9.1: FDI inflow in CESEE countries, 2013–2016, EUR million

2013 2014 2015 2016

Bulgaria 1384 1161 1692 683

Croatia 694 2256 199 1300*

Czech Republic 2769 4141 419 6104

Estonia 565 455 117 787

Hungary 2529 5818 –13108 –4703

Hungary ex. 1926 4989 2056 4226

Latvia 680 590 600 114

Lithuania 353 –18 785 300*

Poland 2730 10755 12138 12000*

Romania 2713 2421 3461 4081

Slovakia –455 –386 –176 3000*

Slovenia –114 791 1465 831

EU-CEE 13848 27983 7592 24497

EU-CEE HU ex. 13244 27154 22756 33426

Albania 945 869 890 983

Bosnia and

Herzegovina 208 399 244 258

Kosovo 280 151 309 216

Macedonia 252 205 217 358

Montenegro 337 375 630 205

Serbia 1546 1505 2116 2000*

Western Balkans 3568 3503 4406 4020

Belarus 1690 1418 1521 1000*

Kazakhstan 7769 6326 3619 8196

Moldova 183 151 164 97

Russia 33622 20873 10327 20000*

Ukraine 3389 310 2670 2871

CIS-4 + Ukraine 46653 29079 18301 32164

CESEE (HU ex.) 63465 59736 45567 69610

Remarks: Data are based on the IMF BPM6 directional principle unless otherwise stated; data exclude Special Purpose Entities (SPEs), if reported. For explanations see https://oenb.at/en/


* Estimate, based on three quarters of the year or annual asset/liability data.

Hungary ex. – excluding capital in transit and company assets restructuring.

For Albania and Kosovo, asset/liability data are used; Montenegro does not identify reverse in-vestments, thus data based on directional and asset/liability principle are identical.

Moldova reports based on BPM5.

Data for Ukraine exclude the occupied territories of Crimea and Sevastopol since 2014.

Source: wiiw FDI Database based on direct investment statistics and balance of payments statis-tics of respective National Banks; author’s estimates.

In document Gnan | Kr onberger (Hg.) Schwerpunkt Außenwirtschaft 2016/2017 44pt (Page 174-180)