The long-run impact of monetary policy uncertainty and banking stability on inward FDI in EU countries

Abstract

In the present paper, we assess the long-run relationship between FDI inflows and the financial environment in 16 EU countries. For this purpose, we use a cointegration technique for heterogeneous panels and the FMOLS and DOLS estimators, over the period 2001–2015. We show that financial conditions are important for FDI inflows. More precisely, the monetary uncertainty, calculated as the difference between the recorded and the forecasted interest rate values, negatively affects the FDI inflows. In addition, the banking stability, measured through different Z-score specifications, positively influences the foreign investment. However, this result is influenced by the way the Z-score is calculated. We further report a positive relationship between the business cycle and the FDI entrance. The robustness analyses based on alternative specifications of monetary uncertainty and banking stability confirm our findings. These results are also supported by a PMG estimation. Therefore, authorities must pay special attention to monetary policy predictability and to banking stability in order to facilitate the investors’ access to finance and their investment decision.

Introduction

The stock of foreign direct investment (FDI) as percentage in GDP has continuously increased in the European Union (EU) countries during the last decades, supporting thus the theory of their higher economic integration. However, the FDI inflows started to decrease just before the outburst of the recent financial crisis, and they did not recover as expected up to now. In addition, the credit market does not function very well, even if the monetary conditions were relaxed over the last years.¹ In this context, a better understanding of the relationship between FDI inflows and the financial environment of the host economies is absolutely necessary.

We posit that the traditional inward FDI determinants, as the structure, the size and the institutional quality of the host economy, which are put into question nowadays,² cannot explain the fluctuations in FDI inflows on a long-time horizon. The role of this category of determinants is usually investigated in relation with the stock of investment, given their reduced variability. However, FDI inflows have fluctuated a lot during the last years, and these fluctuations could be explained by the change in the financial environment characterizing the host countries, and in particular by the access to finance and by the financial costs associated with investment. Indeed, for an international investor it is important to know if the business will benefit from financial support abroad, and if the financial costs can be anticipated and sustained. A sound banking system can ensure the access to finance, and the predictability of the monetary policy offers information about the financial costs generated by borrowed funds. At the same time, the FDI inflows might influence in their turn the banking activity and the conduct of the monetary policy.

Therefore, our purpose is to investigate the long-run relationship between FDI inflows as percentage in GDP, monetary policy uncertainty and banking stability for a panel of 16 EU countries over the period 2001–2015, using the Organization for Economic Co-operation and Development (OECD) statistics. However, the uncertainty and instability tend to increase during economic downturn periods, and both FDI inflows and financial conditions are likely to be driven by the business cycle. Consequently, in order to isolate the effect of the financial environment on FDI inflows, we introduce in our long-run relationship the economic growth rate.

The FDI determinants literature is very extensive. According to Eicher et al. (2012), the FDI determinants can be grouped in elements associated with the attractiveness of the national economy, the economic performance, and the quality of host countries economic policies. The first category of factors is related to the size of the host market (Botrić and Škuflić, 2006), the human resources quality and labor market characteristics (Castellani et al., 2016, Siedschlag et al., 2013, Villaverde and Maza, 2015), the institutional quality and reforms (Morisset and Pirnia, 2000, Wernick et al., 2009, Walsh and Yu, 2010, Tintin, 2013, Bokpin, 2017), and the proximity to research excellence centers (Siedschlag et al., 2013). The economic performance is assessed through investment’s profitability (Gwenhamo, 2011), trade integration (Clausing, 2000, Lehmann, 2002, Anwar and Nguyen, 2011), employment (Andersen and Hainaut, 1998), international agreements (Neumayer et al., 2016), financial market development (Agbloyor et al., 2013) and economic growth (Wernick et al., 2009, Tang et al., 2014). The third category covers elements associated with the quality of macroeconomic policies, namely the fiscal and the monetary policies. The effect of fiscal policy on inward FDI is assessed through fiscal incentives and competition (Haaparanta, 1996; Hines, 1999; Morisset and Pirnia, 2000; Ramb and Weichenrieder, 2005; Egger et al., 2008; Arbatli, 2011; Rădulescu and Druica, 2014; Albulescu and Ianc, 2016). The monetary policy effectiveness is associated with the performance of the exchange rate regime (Bénassy-Quéré et al., 2001; Aubin et al., 2006; Choi and Jeon, 2007; Ahmad et al., 2017) and with lower inflation and interest rates (Coskun, 2001, Dabla-Norris et al., 2010). Only few studies underline the importance of macroeconomic stabilization (Wint and Williams, 2002, Albulescu and Ianc, 2016, Chenaf-Nicet and Rougier, 2016), of systemic financial stability (Albulescu et al., 2010), and of uncertainty (Tang et al., 2014) in influencing FDI inflows. However, no previous papers investigate the long-run relationship between monetary uncertainty, banking stability and FDI inflows in the EU countries.

Moving beyond traditional FDI determinants, and building upon previous studies, this paper has two primary contributions to the literature. First, we focus on the role of financial environment in sustaining FDI inflows. Different from previous works (i.e. Agbloyor et al., 2013, Tang et al., 2014), we focus on the conditions which influence the access of multinational companies to finance, namely the banking stability and the monetary policy uncertainty, without considering the role of the financial development of host countries, an element with a small variability during the analyzed period. While the banking stability is measured through different Z-score specifications for the national banking systems, we assess the monetary uncertainty comparing the level of the short-term interest rates and their forecasted values, using OECD data (OECD Economic Outlook). According to the OECD definition, the short-term interest rates are generally averages of daily rates, or 3-month money market rates where available. Comparing the recorded level of interest rates and their forecasted values is a common approach to assess the monetary uncertainty.³ However, money market rates do not differ much across the Euro area countries. Moreover, their forecasted values are the same for the Euro area members. Thus, a small variability appears when we use this statistic as a proxy for the monetary uncertainty. Therefore, we use a set of robustness analyses to check the validity of our findings. On the one hand, we use both 1-year and 2-years forecasts. On the other hand, we use the level and the forecasted values of long-term interest rates as a new measure for the monetary uncertainty. Indeed, there is a large variability between the EU countries regarding the uncertainty computed using long-term rates. However, in this case, the uncertainty is related to government bond yields, which are influenced by the sovereign risk. Thus, in this case, the uncertainty is also associated with the quality of the macroeconomic policies. Finally, we use the slope of the yield curve (the difference between the long- and short-term interest rates) as a measure of uncertainty. Woodford (2010) shows that interest rate spreads reflect liquidity conditions within the financial system, and a high spread can be associated with inconsistent expectations. Hence, economic agents became interested in financial investment with a short maturity. Therefore, an inverted yield curve might be viewed as an indicator announcing an economic downturn.

The second contribution of the present paper relies in the employed empirical approach. Different from other studies that perform panel data analyses and use simple regressions without addressing any endogeneity issues (exceptions are Ahmed and Zlate, 2014, Tang et al., 2014, Ahmad et al., 2017), we show that our variables are not stationary in level. Thus, we address the long-run relationship within a cointegration framework, which takes into account the potential endogeneity of the involved variables by using adequate models, as the fully modified ordinary least square (FMOLS) estimator and the dynamic ordinary least square (DOLS) estimator. In particular, we use the cointegration analysis for heterogeneous panels, as proposed by Pedroni, 1999, Pedroni, 2001. Given the structure of our sample (old and new EU members), the probability to have a heterogeneous panel is high. Further, for robustness purposes, we use the Pool Mean Group (PMG) estimator (Pesaran et al., 1999). Given the multitude of FDI inflows’ determinants, this estimator helps us to address both reverse causation and omitted variable bias. Moreover, the structure of our sample offers good reasons to expect a similar relationship for the long-run equilibrium across groups.

The remainder of the paper is structured as follows. Section 2 presents a brief review of the literature on the role of financial environment in sustaining FDI inflows. Section 3 describes the data and the methodology. Section 4 shows the main empirical findings while Section 5 is dedicated to robustness checks. The last section concludes.