demonstrate the causal impact of FDI penetration on manufacturing TFP in Chile. Rather than using a services reform indicator, the authors exploit the issue of whether the extent to which Chile’s accumulated net real FDI inflows in services, i.e. stock, had any significant impact on domestic firm performance. Their multiplicative form of FDI stock and Chile’s input coefficients relies on a firm‐level dependence indicator of services input as opposed to using input coefficients from input‐output tables as done in other firm‐level studies. They find a positive impact of services FDI on TFP for Chilean manufacturing industries, which in fact can explain 7 percent of its contribution to total TFP increase in Chile. Using Indonesian firm‐level data, Duggan _et al_ . (2013) provide evidence that services reform using the OECD’s regulatory restrictiveness index in FDI for Indonesia showed a positive contribution to manufacturing firm TFP. In this study the authors construct an input reliance variable using Indonesian input‐output tables.

Most of these studies have been conducted using country‐specific firm‐level data for mainly developing economies, while no study to date has taken up a multiple country approach or used a developing economy, not to mention the European Union (EU) as a central point.<sup>4</sup> Of course, a focus on developing countries is logical if one thinks of the fact that many of these economies still have restrictive services policies in place which make their sectors still relatively locked. From this perspective, concentrating on the potential welfare gains for poorer countries is therefore important. Yet, it is somewhat surprising that although much debate on potential productivity gains in Europe has been allocated to its divergent services sector performance, which implies that levels of restrictions significantly differ across European countries as can be seen in Figure 2, no comprehensive study on the EU’s services sector and its effect on the wider downstream economy has until now been undertaken. This paper therefore performs a first step to fill that gap and takes the European market as a point in case. In sum, this is the first study to perform firm‐level analysis with a multiple country dimension using developed economies.

In particular, our study contributes to the existing literature as hitherto discussed in the following ways. First, we augment all the previous country‐specific papers by using firm‐level data that spans multiple (European) countries so as to have a consistent cross‐country (almost balanced) panel sample for both goods and services firms. This is important as it could provide us with close estimates of the real economic potential of future reforms across the entire European landscape rather than concentrating specifically on one country and / or on the manufacturing sector only. These are two valuable additions in our paper that have so far not been exploited. Previous firm‐level works related to our topic only takes up one country and only the manufacturing sector. Our rich data set allows for changing this tradition by not only concentrating on multiple countries, but also by taking into account all other downstream services sectors at a disaggregated level that are present in European economies.

Second, we exploit alternative TFP estimates which have been developed over recent years and have been applied individually in each previous study and never together.<sup>5</sup> The productivity literature has presented several estimates of how to construct a credible TFP indicators with estimation strategies from Olley and Pakes (2003) and Levinsohn and Petrin (2008) as the most commonly used ones.<sup>6</sup> This recent literature has also brought forward new TFP measures such as the one by Ackerberg _et al_ . (2006;

> 4 A study by Bourlès _et al_ . (2013) and Barone and Cingano (2011) do seek to explain downstream TFP through services linkages as explained above in a multiple developed country setting. However, both papers use industry‐ level data as opposed to firm‐level data which our paper takes as a starting point.

> 5 Apart from Fernades and Paunov (2012) which show the results of three different types of TFPs.

> 6 Duggan _et al_ . (2013) use a TFP computation following Aw _et al_ . (2001).

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