Foreign Direct Investment in Ireland 2019

Figure 5.1 shows the series of both Exports and FDI Inward in Ireland over the period described. Both indicators have grown significantly over this time period.

Figures 5.2 and 5.3 present FDI and Exports data in terms of the percentage changes from one year to the next. This process removes autocorrelation in the data and gives a better visual for comparison of covariance. 

Figure 5.3 utilises the remaining FDI series calculated in Chapter 4. This series was stripped of the effects of Pass Through, Intangible Assets and aircraft. In getting rid of any potential white noise, it may improve the result of any causal research into the relationship between the two indicators.

In Figure 5.4, the data is aggregated at a firm level for the time period shown and presented by quarter in order to increase the number of overall observations and increase the variance in the series. This data was also differenced; the figures shown are the differences from the current quarters and their predecessors. This method helps reduce autocorrelation in the series and also provides a better visual to look at covariance between the two variables over time. This firm level data has been stripped of Pass Through using the Finnish method referenced in the pass-through chapter (Leino et al, 2014).

One problem for analysing Irish FDI and Goods Export data, is that there are a number of firms established here that predominantly trade in services. Therefore, in Figure 5.5, any firm which has less than a €2 million valuation of aggregate goods Exports over the total period shown was removed from the analysis.

Figure 5.6 illustrates this aggregated firm level FDI data lagged for two years against the Goods Export data. This two-year lag reflects the fact that the period whereby investment begins to pay off for firms may be on a time delay. If a firm invests significantly in an economy, depending on their current level of operations there, it may take a long time for that investment to manifest itself in an increase in production capacity. In preliminary results, for various different types of regression models, this two-year lag proved to have the most significant correlation with exports.