between FDI and growth is instead negative (but not statistically significant and close to zero) when credit to the private sector is 25 percentage points below the sample mean.

When we interact FDI with education, we find that the correlation between FDI and growth is positive and statistical significance when schooling is at the sample mean (column 3 of Table 1) and becomes much larger as schooling increases. The point estimates imply that, when education is at its sample mean, a one standard deviation increase in FDI is associated with a 1.1 percentage points increase in GDP growth. When Education is 3 months above its sample mean, the correlation between FDI and growth increases to 1.8 percentage points. The correlation between FDI and growth becomes negative, albeit not statistically significant, when schooling is about three months below the sample mean (panel b of Figure 1).

The last three columns of Table 1 estimate the same models of columns 1-3 using data for 1975-94. There are two notable differences with respect to the results for 1970-89: (i) the direct effect of FDI turns negative (albeit not statistically significant) in the regression of column 4 and (ii) the interaction between FDI and education is no longer statistically significant (column 6 of Table 1, and bottom right panel of Figure 1).

There are two potential factors that may drive these changes: the different time span and the slightly larger country sample of columns 4-6. To probe further, we estimate the same models of Table 1 with data for 1990-2009 and 1995-2014 but with exactly the same sample of countries used in Table 1. Specifically, columns 1-3 of Table 2 use the same sample of countries of the corresponding columns of Table 1 and columns 4-6 of Table 2 use the same countries used in columns 4-6 of Table 1.

When we estimate the model for 1990-2009, we find that FDI flows are never significantly correlated with GDP growth, no matter the state of local conditions (columns 1-3 of Table 2). When we focus on 1995-2014, instead, we find that FDI flows are not significantly correlated with growth in the model without interaction (column 4). However, the main effect of FDI becomes larger (by a factor of 10) and statistically significant when the interaction effects are included in the model (columns 5 and 6). Moreover, the interactive effects are now statistically significant and negative. These latter results indicate that there is a positive and statistically significant correlation between FDI and growth for countries with average levels of education or financial depth, but that this correlation becomes _negative_ in countries with high levels of education or a deep financial sector (illustrated in panels a and b in Figure 2). For instance, the point estimates of columns 5 and 6 imply that a one standard deviation increase in FDI is associated with a 1.6 percentage point increase in GDP growth (average GDP growth in this sub-sample is 2.7%), when financial depth or education is at its sample mean. However, the correlation between FDI and growth becomes negative and statistically significant when financial depth is twice the sample mean (the point estimate implies a decrease in growth of about half a percentage point; panel c of Figure 2). We find the same result for the level of education (panel d of Figure 2).

This is the _opposite_ of what was found by Alfaro et al. (2010) and Borensztein et al. (1998) and of what we also find when we use data for the 1970s and 1980s. The role of local factors has clearly evolved over time.

To show that we did not cherry-pick the estimation periods of Tables 1 and 2, we estimate 8