arXiv subjects
Publications and source records attributed to Gerard Keogh.
We examine the effect of a Hard Brexit on Irish Exports using the PPML Gravity Model and Irish Exports data at the micro level. We find a hard Brexit could reduce Irish national income by over 9 billion euro annually and the effect would be sustained mst in th etraditional sectors of Agriculture and Food production of the Irish economy
We describe the Time Series Multivariate Adaptive Regressions Splines (TSMARS) method. This method is useful for identifying nonlinear structure in a time series. We use TSMARS to model the annual change in the balance of trade for Ireland from 1970 to 2007. We compare the TSMARS estimate with long memory ARFIMA estimates and long-term parsimonious linear models. We show that the change in the balance of trade is nonlinear and possesses weakly long range effects. Moreover, we compare the period prior to the introduction of the Intrastat system in 1993 with the period from 1993 onward. Here we show that in the earlier period the series had a substantial linear signal embedded in it suggesting that estimation efforts in the earlier period may have resulted in an over-smoothed series.
We examine over 40,000 International Protection (IP) determinations for non-EEA nationals covering a 16 year period in Ireland. We reconfigure these individual outcomes into a set of over 23,000 matched pairs based on combination of direct matching and propensity score matching. A key feature of this approach is that it replicates the statistical features of an experimental set-up where observational data only are to hand. As a consequence we are able to identify those explanatory factors that in fact contribute to the grant of IP. This is a key innovation in the analysis of protection outcomes. We centre our study in the realm of International Relations studies on protection. We are particularly interested in whether immigration policy is a latent tool used to influence the odds of a grant of IP, specifically via the introduction of the Immigration Act 2004. Using both conditional maximum likelihood and mixed effects models we find this is not the case, this conclusion is both novel and profound in a matched pair context. On this basis we conclude there can be little justification for the perception that immigration policy is a latent tool affecting the protection process in Ireland.
This paper proposes a new bootstrap method to compute predictive intervals for nonlinear autoregressive time series model forecast. This method we call the splice boobstrap as it involves splicing the last p values of a given series to a suitably simulated series. This ensures that each simulated series will have the same set of p time series values in common, a necessary requirement for computing conditional predictive intervals. Using simulation studies we show the methods gives 90% intervals intervals that are similar to those expected from theory for simple linear and SETAR model driven by normal and non-normal noise. Furthermore, we apply the method to some economic data and demonstrate the intervals compare favourably with cross-validation based intervals.
The sharp decline in Ireland's economic performance in recent years has coincided with a recent fall in asylum applications. Simultaneously countries such as Switzerland are seeing increases in asylum numbers with evidence for greater numbers of Nigerian applicants, a group that have for some time been the largest nationality group applying in Ireland. A possible reason for this shift in asylum seeker preference is the general economic conditions here versus those in other European countries. In this paper we investigate whether this belief holds water. We model asylum applications as a function of GDP using a time varying parameter multiplicative growth model. Our results show there is an economic basis for asylum seeker preferences. We further show there is no regional basis for asylum seekers' expectation of a more favourable claim in the 'developed box' in central Europe as compared to countries on the so-called 'periphery'.