The model picks at least one variable in each of the key pre-identified categories (table 2). This suggests that there is empirical validity that country-level measures of performance corresponding to these categories have a relevance to assessing the investment climate. This broadly validates approaches like the Doing Business and Competitiveness indicators.

One surprise is the relative absence of indicators linked with infrastructure (only one indicator of transport connectivity) and financial services. In the specific context of the data used for the estimation, this may be explained by the fact that large investments (FDI captured in the database are presumably the decision of large investors) may be able to internalize these types of constraints. Another point of note is that the FDI data sample (unlike the trade data one) includes services and goods sectors and that we cannot exclude that results would vary in a specification differentiating goods and services sectors.

Natural resources rents pose a specific conundrum as they may influence market readiness for investments in opposite directions. Resource rents are obviously specific to resource sectors and play positively on FDI prospects in these sectors. They also impact other sectors, with a mix of potentially positive and negative effects. Resource windfall through induced demand effect, potential Dutch disease and resource curse effects that should favor non-trade sectors and thus favor market seeking FDI. However, these effects also come at the expense of efficiency in other productive sectors thus detracting potential investment in these. Resource-curse effects may negatively affect the overall attractiveness of investing in a country.

Because of the importance of investments that are linked to extractive industries (in poorer countries in particular), we ran a specification of the model omitting investments in the resource-based sectors (mining and oil sectors). We find that that results are robust to the omission maintaining an overall good fit for the model, and with most variables being stable to the specification. The model also assigns the same significance to rent variables in both specifications. Taken together these results suggest that the drivers of investments are not determined by investment behavior in the extractive sectors and that the presence of extractive resources do have a significant impact on investments in the rest of economic sectors.<sup>22</sup> Turning to the variables that are associated with extractive rents, results find that resource rents as share of the overall economy tend to have a depressing effect on the likelihood of investment. However, this is not the case for oil reserves which are on the contrary linked with higher likelihood of investment.

As would be expected, demand size dimensions are linked to investment decisions, and have higher magnitude of the coefficients (positive for Final consumption expenditure as % of GDP) as is the involvement of government in markets (negative for General government final consumption expenditure as % of GDP) which suggests that this factor having more relevance than others. Interestingly, the coefficient for industry value added coefficient is also higher. We take this variable as an indication of technological development capacity, which thus would suggest that more sophisticated markets offer more possibilities for economic returns than less sophisticated ones.

Finally, there is generally a positive signaling effect created by other investments (measured by the stock of FDI). While it is intuitive to think of realized investments as indeed signaling the availability of economic opportunities, and in line with the literature findings (see e.g., Walsh and Yu, 2010). The

> 22 However, this does not imply that dimensions that matter for the extractive sector are identical to those associated with non-extractive sectors.

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