Ireland’s economy and the rate of immigration in the 21st Century: The Polish and UK connection.


Ireland has a long history of population fluctuation, with emigration being the driving force of its changing demographic. This outward flow has been closely linked to economic factors, from the mass emigration during the Great Famine and towards the end of the 19th century (FitzGerald, n.d.), in the post-World War II era, to the more recent waves of departures during the bleak economy of the 1980s and after the global financial crisis of 2008 (Economic history of the Republic of Ireland, 2016). The exception was the 1970s, when negative net emigration was seen for the first time in Irish history.

However, it was not until the late 1990s that a significant influx of both returning Irish nationals and non-Irish immigrants placed Ireland as a country of net immigration. Rapid economic growth created a huge demand for labour (“Ireland”, 2009) and saw unemployment drop from 15.9 percent in 1993 to a historic low of 3.6 percent in 2001. After the 2004 EU enlargement, new highs were reached in overall immigration, as Ireland was one of just three countries that did not impose entry restrictions on the new EU accession states (Coleman, 2006). In 2007, Ireland had the third largest migration rate across the 27 EU member states (Focus-Migration: Ireland, n.d.). This rapid shift in demographics has been closely tied to the economic boom of the ‘Celtic Tiger’ and the subsequent decline in immigration seen after 2008 is linked to the global financial crisis and the severe economic recession experienced in Ireland. It would seem to be an accepted fact that there is a strong correlation between Ireland’s economy and the rate of immigration (Denny and O’Grada, 2013). The aim of this narrative is to determine how closely linked these elements are, and how reliable immigration rates are as an indicator of economic viability. To explore this, GDP and PPSN allocations from 2004 to 2015 were compared, along with unemployment data and population figures, to determine correlation.

The chosen dataset was PPSN Allocations to Foreign Nationals by Country and Year (CSO.ie, 2017) spanning the years 2004 to 2015. Personal Public Service Numbers (PPSN) are “the only relatively reliable source of immigration data divided by origin country between Census years” (Roeder, 2011). PPSN are required to work and to access social services, but allocations are not a complete record of immigration as not all immigrants or their dependants require one and it also does not account for asylum seekers or illegal immigrants. They also do not indicate when a person leaves the country. However, as immigrants must be normally resident in Ireland to obtain one and the data is grouped per year, it is likely that the numbers are strongly indicative of the actual immigration figures for that year. Figure 1 displays the entire primary dataset, showing emerging patterns which correlate with times of economic prosperity.

Figure 1


We tracked the PPSN to Irish Gross Domestic Product (GDP) (CSO, 2017), generally considered a good gauge of economic performance (Economic Indicators, 2003) over a ten year period and saw that there was indeed a correlation (Figure 2 & 3).


Figure 2: Global PPSN GDP Correlation


Figure 3: Line Chart Global PPSN GDP Correlation


Poland and the UK emerged as the biggest contributors to Irish immigration (Figure 4);


Figure 4: Top 10 PPSN Allocations


so it was decided to focus on these countries for the purposes of exploring the correlation between Ireland’s economy and the rate of immigration. PPSN allocations for Poland and UK only were plotted against the Irish GDP and both examples show a strong correlation during the height of the economic boom in Ireland. Interestingly, the UK seems to have had a much more consistent level of immigration to Ireland (possibly due to the common travel area, proximity, ease of travel and shared language), while data on Polish PPSN allocations could suggest a purely economic motivation for emigration to Ireland, as numbers peaked and then dropped off significantly during recession (Figure 5 & 6). The recovery in employment lagged behind the recovery in GDP, suggesting that while there was economic recovery, the financial gains weren’t being felt as widely as before.


Figure 5: UK PPSN and Irish GDP


Figure 6: Polish PPSN and Irish GDP


GDP may not be an effective methodology of economic growth in Ireland (OECD, 2017 ). In 2016, Nobel Prize winning economist, Paul Krugman called Ireland’s rapidly growing GDP figures “Leprechaun economics” (Deen & Doyle, 2016). Therefore, we decided to look at other indicators of economic growth such as unemployment levels. Initially, we compared (Figure 7 Ireland’s GDP and unemployment levels), Ireland’s unemployment figures with domestic GDP which indicated that in 2012, we had the highest rate of unemployment at 14.7% whilst experiencing a 0.9% growth in GDP. In 2008, unemployment levels where at a lower 6.1% whilst GDP was in a negative value at -3, demonstrating unemployment as a lagging but real life indicator of changing economic conditions.


Figure 7: Ireland’s GDP and Unemployment Levels


A further comparison of Ireland’s unemployment levels with immigrant numbers (Figure 8) demonstrated a sharp reduction in immigrants from the UK and Poland in line with Irish unemployment records.


Figure 8: A Comparison of Irish Unemployment Levels and UK and Polish Immigrants to Ireland: 2004-2014


If unemployment records for 2007 are compared to the GDP of Ireland, UK and Poland, all three countries experienced a drop in GDP while Ireland and the UK experienced a negative value recession (Figure 9).


Figure 9: Comparison of unemployment with GDP


Figure 9 shows that Ireland’s negative GDP and subsequent growing unemployment were a strong indicator of reduced UK and possibly Polish immigrant levels than the GDP levels of their home countries. In fact, (Figure 1) immigration into Ireland fell from all over the world in line with Ireland’s worsening economic crisis. This is contrary to the views of Krings et al (2009) who argued that it was misplaced and simplistic to assume that immigrants, especially Polish immigrants, left Ireland ‘when times are getting tough’.

Figures from the Central Statistics Office challenge Krings et al (2009) perspective with numbers showing a significant decline in PPSN applications post Celtic Tiger Ireland (Figure 3 &10). On the other hand, in 2006, in the height of the boom, 63,276 Polish immigrants were living in Ireland and this number increased by 93.7% to 122,585 when Ireland was in the midst of an economic recession (Figure 10) leading to a net increase of Polish residents in Ireland at a time of highest unemployment levels and negative GDP.


Figure 10:Polish Immigrants in Ireland: Pre and Post Celtic Tiger


Whilst the Polish population significantly increased since 2004, it’s been established that new immigrant levels greatly decreased. It could be argued that a stable Polish immigrant population remained in Ireland despite an economic decline. In this same timespan, Ireland’s second largest immigrant population, the UK, remained relatively stable pre and post Celtic Tiger, though new immigrants decreased by nearly 6,000 (Figure 11). It could be argued the Polish immigrant made a connection with Irish society beyond monetary gain. In fact, according to the Polish Embassy in Ireland, the Polish population has continued to expand in Ireland.


Figure 11: PPSN Poland & Uk and Polish and UK population in Ireland


It’s clear that immigration rates, if classified by annual new immigration are a strong indicator of economic viability and are aligned to both unemployment levels and to a lesser extent GDP in Ireland. However, if immigrant classification also includes figures from the previous decade, it is noted that the Polish immigrant population increased despite a marked Irish economic decline and a strong Polish GDP (Figure 12).


Figure 12: Polish Population Continues to Grow


Therefore, there is some evidence that immigration populations are influenced by other factors as well as economic viability.

A critique of this investigation must take into account the measurement indicators used. There was a global criticism of Irish inflated GDP values in 2015 which reduced its credibility as a measure of the Irish economy. Furthermore, research indicates that net migration has more of a correlation with the country’s economy than immigration figures alone (Bernskiold et al, 2015). (Figure 13) demonstrates an increase in net migration in 2014 approaching the Celtic Tiger figures of 2003.


Figure 13: Net Migration Trends in Ireland: 2001-2014


Further research would need to use a broader variety of economic and immigration/migration values to get a more holistic perspective on the links between the Irish economy and immigration both generally or specific to the UK and Poland.

The data visualisations clearly show that during the mid 2000s Ireland’s economic situation had a huge effect on the rate of immigration. The subsequent decline in the rate of new immigrant arrivals is also clearly in line with the economic crash of the late 2000s. However, that did not result in mass emigration of those who had already become established in Ireland, as shown by the overall increased population of those from the UK and especially Poland. It would suggest that once established, immigrants were less likely to leave the country purely for economic reasons. It is possible the reasons are more social than economic and could make for interesting further study. There is a strong possibility that as Ireland begins a slow recovery, the rates of new immigration will rise again, and as new information is released from the latest census, these developments will be able to be tracked more closely.

Written and produced collaboratively by: Alison De Paor, Emma Healy, Patricia O’Sullivan & Bernadette Smart



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Crowdsourced Spatial Projection Project 6010

Evolving from the humanitarian crisis in Haiti in 2010, Humanitarian OpenStreetMaps (HOTOSM) uses open source data  and volunteer collaborative efforts to create maps in support of navigation, logistics and tracking during crises, especially in under-developed and unmapped areas of the globe. MapSwipe is a mobile application developed by MSF as a complimentary preliminary mapping tool. I engaged with both projects and also with OpenStreetMaps (OSM) in my hometown as part of this assignment and will reflect on this from a practical and a critical standpoint.

Mapping in a known area is relatively straightforward as the satellite imagery is generally good and there is a confidence in having familiarity with the area. Although major roads and other features were already present and labelled, I was able to add minor roads and buildings such as the primary school, parish hall, water treatment plant and also points of interest. This allowed me to become familiar with the interface; how to add lines, points and areas and how to classify and tag items. It is possible to switch between layers and compare modern satellite and aerial imagery with older ordnance survey maps, which would be useful for studying the changes over time. Compared to a Google map of the same area, OSM had a lot more detail, in some areas, though obviously it did not have the street view ability of the former. Because of the wiki-like nature of OSM, any changes or additions will remain until another contributor reviews or deletes them. This opens up the possibility of vandalism. Another issue involves identification of individual residences, as in,  the possibility of a contributor labeling a house, not by its street address and number, but by the occupant’s surname (as is commonly done in more rural areas), which could lead to a residence being targeted for criminal activity. As OSM is non-proprietary, anyone can export the map for use off-line or to create a custom map, as long as OSM is credited correctly using its Creative Commons (CC-BY-SA) license.

OSM Screenshot


Google Screenshot







Using HOTOSM task manager, I was able to complete 5 tiles in 3 different projects and validate 3 further tiles. However, it took a lot of trial-and-error and several uncompleted tiles to become familiar and at ease with the interface, and previous experience using OSM, while of benefit, did not adequately prepare me for these tasks, even though I completed all the tutorials and read instructions carefully. The video tutorials did not work, though I was able to read the transcripts and written instructions. I added roads and buildings using iD editor but did not attempt using JOSM as it was beyond my expertise. Given the importance of the work, and the very real nature of what HOTOSM is attempting to do and the possible negative effects of incorrect contributions, I was much more hesitant and unsure of my efforts. The tiles vary hugely in terms of complexity, with some being  densely populated areas with different road networks and others being very sparsely populated or devoid  of both buildings or roads. Cloud cover and lower-quality resolution imagery also created issues, though there were different layers to switch between if one was compromised and often the pink border line denoting the boundary of the mapping area or tile disappeared, which meant saving and uploading what I had done and going back a few stages and reloading everything.

Another issue I documented was that of differences between what was shown on the Bing aerial imagery and the custom imagery. In the top screenshot using Bing, there are two buildings clearly shown towards the right, while in the one below, there are none. Also, the outlines of the two smaller buildings towards the left are offset in the Bing photo. As all the surrounding tiles were aligned using the custom imagery, I was hesitant to use what I saw using Bing. I could not determine which was the newer imagery, as it is possible the buildings on the right were either newly added or recently demolished. I spent a lot of time zooming in and out but there was no way to tell for sure. I checked the other imagery sources but they were of lower quality. Following the ‘Where does this image come from?’ link did not help me nor did searching the FAQ for the history and date of the images, though it is possible I overlooked something. I watched a tutorial on how to adjust offset imagery and attempted it but adjusting it to align with one source over another adjusted the surrounding tiles also and I was uncomfortable with that. I was very conscious of doing anything to change other people’s work. I imagine that using satellite as opposed to aerial imagery is more accurate and less prone to discrepancies but I found that particular experience frustrating and  time-consuming and was somewhat conflicted regarding the accuracy of my contributions. Further reading on the subject suggests that there are efforts to involve people with local knowledge who can verify and correct contributions as needed, but the sheer scope and scale of the various projects means that will not be always possible, especially in the case of a natural disaster where the need for accuracy is immediate and life-threatening.

Screenshot using Bing Aerial Imagery



Screenshot using Custom Imagery





MapSwipe was easy to navigate and use and I understand the benefits of having large swathes of land pre-identified for more intensive mapping. There is a gamefied element to the app which provides a certain reward or gratification from its use and as there are only 3 instructions for identifying a tile, it did not cause the same conflictions as HOTOSM. There were some glitches regarding tiles not loading and also cloud cover or low-resolution images making it impossible to identify features but by using the double tap ‘maybe’ option, it was not a major issue. It is easy to envision this being used by people when they have some spare time and it does not require anywhere near the same levels of concentration or ability as more intensive mapping. It is visually interesting and could appeal to younger users. However, some people might have reservations about whether gamefication belongs on the same platform as real people facing serious humanitarian issues.



While engaging in mapping projects for HOTOSM and MapSwipe, many questions arose regarding open-source versus proprietary data, possible abuse of collected data and the ethical implications of so-called ‘armchair activism’, as well as questions around attribution.

As Serge Wroclawski says in his blog “Place is a shared resource, and when you give all that power to a single entity, you are giving them the power not only to tell you about your location, but to shape it.”(“Why the world needs OpenStreetMap — Emacsen’s Blog,” n.d.) He points to Google as an example of a company that utilises and monetises user data and also controls what exactly gets displayed on the maps it creates. OpenStreetMaps seems to be the antithesis of this as a ‘neutral and transparent’ non-profit organisation. Recent attempts by Google to mimic the user generated content model  of OSM would seem to be a testament to this usefulness. However, unlike Google, all data and the source code itself can be copied, distributed, adapted and transmitted, as long as OSM is credited under its Creative Commons Attribution ShareAlike (CC BY-SA) license. Bing, Yahoo and a number of other bodies such as regional governmental GIS agencies have allowed use of aerial and satellite imagery to aid in the mapping effort, though why a corporation like Microsoft would choose to give away this valuable resource is open to debate.


It is hard to deny the humanitarian objectives and aims of HOTOSM and MapSwipe, and the very real benefits it provides in times of crisis. It is also possible to envision the information being abused, such as for unethical drug testing by pharmaceutical companies, by human traffickers, terrorist organisations or by governments themselves. The real and immediate benefits would seem to outweigh these worst-case scenarios however. Another concern is one surrounding the ‘us-versus-them’ mentality and disassociation of swiping through an app on a mobile phone or outlining huts on a laptop in the comfort of one’s home, miles removed from the actual scenario. However, personally speaking, the more I engaged with the mapping, the more aware I became of the reality of what I was doing. I believe it can provide a valuable insight to how life is for people in other areas of the world. Also, as one of the objectives is to engage and involve people ‘on the ground’, it is a collaboration in the true sense of the word. The more data there is, the more people will want to contribute and the more useful the maps will become.

As part of my research into English Language resources available to migrants in Cork, I would definitely be open to using OSM to create a custom map with locations of facilities and organisations that could be of benefit. Another possible use would be to highlight the journey or origin of migrants who want to tell their story.

Websites and Readings