Back to Top

 Skip navigation

Chapter 10 Quality Adjusted Labour Input

Open in Excel:

The Quality Adjusted Labour Input (QALI) differs from conventional labour input as it weights the hours worked by the earnings of workers. The earnings of workers are stratified by economic sector and within the sector by age, education and gender thus enabling a more comprehensive examination of labour input. The objective is to distinguish between the contribution to productivity of an hour’s work by a surgeon compared to a worker in the retail trade. Producing the detailed time series required for this analysis over the entire nineteen years is challenging and entails additional estimation and aggregation. More details of the methodology followed can be found in the appendix.

In the section below, graphs are presented showing the growth in hours worked versus the quality adjusted labour input. Further graphs are also presented on labour composition, which attempt to measure the quality of labour input provided by the workforce. Considerable additional research work was necessary following on from the initial indicative estimates presented in the Productivity in Ireland 2017. However, the results are still considered to be experimental. Additional charts have also been included at the end of the chapter to illustrate how the labour composition could be incorporated into the main GVA analysis. These presentations could provide additional insight into the evolution of labour input in the economy.

X-axis labelQuality Adjusted Labour InputGrowth in Hours worked
200014.861040568492114.861040568492
20015.889647884528115.88964788452813
20020.6139427322471830.613942732247205
20032.990686364102372.99068636410231
200410.450917984134610.4509179841346
200512.609991388964513.510378407383
200612.7271746050111.1036207883505
20071.489670955798862.7745158051751
2008-14.9773348299623-14.2718022776645
2009-42.9118206074511-45.7061954674485
2010-38.2783996734829-43.9470126948123
2011-6.31783932039236-7.92982451956527
2012-10.0798374632626-8.26120876488238
20135.943184960908283.54852104994508
201416.070208811649615.8240477569401
20159.6535234010770914.4183418095141
201614.375409865060110.1645874452037
20178.497297366770598.87119700181236
201813.74636918872112.7190059677443
20190.4553433026055941.52855536347547

Get the data: PxStat PIA11

The chart above shows growth in hours worked and the QALI for the Construction sector, while the chart below shows QALI decomposed into Labour Composition, otherwise known as labour quality, and hours worked. It is evident from the graph above that both hours worked and QALI followed a similar pattern up until 2009. From 2009 to 2010, clear differences emerge between the two measures. In the depths of the recession, the fall in hours worked was greater than the fall in QALI. The hours measure fell more sharply as it does not account for the education or other quality indicators unlike the QALI measure. In fact, the gap between the two measures indicates that the majority of those who left the sector during the period were those who were on aggregate had a lower level of education or were less experienced when compared to the total workforce in the sector. This is also reflected in the Labour Composition in the graph below, with the increase in the Labour Composition recording results of 2.8% and 5.7% in 2009 and 2010. 

X-axis labelGrowth in HoursLabour CompositionQuality Adjusted Labour Input
200014.8610405684923.88578058618805E-1414.8610405684921
20015.88964788452813-2.08166817117217E-145.88964788452811
20020.613942732247205-2.21177243187043E-140.613942732247183
20032.990686364102316.48786580015326E-142.99068636410237
200410.45091798413466.10622663543836E-1410.4509179841346
200513.510378407383-0.90038701841841912.6099913889645
200611.10362078835051.6235538166595212.72717460501
20072.7745158051751-1.284844849376241.48967095579886
2008-14.2718022776645-0.705532552297752-14.9773348299623
2009-45.70619546744852.79437485999739-42.9118206074511
2010-43.94701269481235.66861302132938-38.2783996734829
2011-7.929824519565271.61198519917291-6.31783932039236
2012-8.26120876488238-1.81862869838026-10.0798374632626
20133.548521049945082.39466391096325.94318496090828
201415.82404775694010.24616105470951216.0702088116496
201514.4183418095141-4.764818408436989.65352340107709
201610.16458744520374.2108224198563614.3754098650601
20178.87119700181236-0.3738996350417798.49729736677059
201812.71900596774431.0273632209766913.746369188721
20191.52855536347547-1.073212060869880.455343302605594

Get the data: PxStat PIA11

The most recent year, 2019, saw a sharp decline in both QALI and hours worked in the sector, however a slight decrease in the labour composition also occurred, falling by 1.1%. This could be due to lower educated workers joining the workforce once again. As Construction activity picked up in 2019, demand for labourers and manual workers increased.

X-axis labelQuality Adjusted Labour InputGrowth in Hours worked
20003.903571940747093.90357194074705
2001-0.0515045439860208-0.0515045439860431
20020.879220999083060.87922099908306
20035.12938185161265.1293818516126
2004-4.91639792083593-4.91639792083592
20054.491223044366865.79227536065816
20066.202200710108685.29770383688874
20076.688574916363138.46039946696336
2008-5.39329701931949-6.32123501487903
2009-4.39514591187105-3.58597971036063
2010-7.3956732997556-3.38884547537586
2011-6.35263396396219-5.79292413483833
20122.529095920521832.13209692920316
201310.83901546151019.98388656653161
20147.227861493415847.78947987623588
20153.934774317105652.2144386190408
20164.956054023998925.56662202128879
20173.008706130786065.09815213059417
20188.550984875228868.14909622798117
20195.482202205592482.26248251135562

Get the data:  PxStat PIA11

The chart above compares growth in hours worked and QALI in the Accommodation and Food sector. It is clear from the graph above that both hours worked and QALI followed a similar pattern over the period. Between 2009 and 2010, a gap emerges between the two measures, with the fall in QALI greater than the drop in hours worked. This was suggestive of a small number of higher educated people leaving the sector and is reflected in the negative Labour Composition growth of -4.0%. However, slight increases occurred in Labour Composition during 2012 and 2013, as the sector recovered, which is highlighted in the chart below.

X-axis LabelGrowth in HoursLabour CompositionQuality Adjusted Labour Input
20003.903571940747054.23272528138341E-143.90357194074709
2001-0.05150454398604312.2215302514228E-14-0.0515045439860208
20020.8792209990830600.87922099908306
20035.129381851612605.1293818516126
2004-4.91639792083592-1.17961196366423E-14-4.91639792083593
20055.79227536065816-1.30105231629134.49122304436686
20065.297703836888740.904496873219946.20220071010868
20078.46039946696336-1.771824550600236.68857491636313
2008-6.321235014879030.927937995559544-5.39329701931949
2009-3.58597971036063-0.809166201510426-4.39514591187105
2010-3.38884547537586-4.00682782437974-7.3956732997556
2011-5.79292413483833-0.559709829123856-6.35263396396219
20122.132096929203160.3969989913186682.52909592052183
20139.983886566531610.85512889497850110.8390154615101
20147.78947987623588-0.5616183828200417.22786149341584
20152.21443861904081.720335698064843.93477431710565
20165.56662202128879-0.6105679972898644.95605402399892
20175.09815213059417-2.08944599980813.00870613078606
20188.149096227981170.4018886472476928.55098487522886
20192.262482511355623.219719694236865.48220220559248

Get the data: PxStat PIA11

In recent years the Labour Composition has been increasing and decreasing in line with trends in the economy, however a sizeable increase in Labour Composition occurred in 2019 of 3.2%. This is also evident in chart 10.3, where the fall in hours was greater than the fall in QALI. The increased Labour Composition may be due to higher educated workers joining the sector.

X-axis labelQuality Adjusted Labour InputGrowth in Hours worked
20001.378055493005671.37805549300569
2001-0.364729004237724-0.364729004237779
2002-5.03472345966735-5.03472345966736
2003-2.36507127826972-2.36507127826965
2004-2.42413480289804-2.42413480289809
2005-3.33734600678219-1.48959508790703
20064.46572926556405-1.24917541957007
2007-2.466669982743750.461572882542558
2008-3.96265562939314-4.92976253539502
2009-11.0092760891469-9.15553753749053
2010-12.6601186871633-18.6957271302619
20117.15914574203665-0.575227042616755
2012-2.98042266410033-0.801428280146415
20136.081812517662714.82327317539062
20146.954142496412083.95318111497855
20156.495933756316076.2188508189336
20162.86232503700714.87225790156163
20173.819846329815820.393618782408611
20181.08468951837452-0.0448202352173111
20191.049075947469451.77020631254178

Get the data: PxStat PIA11

The chart above shows the growth in the QALI and hours worked in the Manufacturing sector. Like the two sectors discussed previously, both measures follow a similar pattern over the period, albeit with a small spike in QALI in 2006. This spike is reflected in the Labour Composition of 5.7% in the chart below, with many lower skilled leaving the sector, when jobs were plentiful during the boom years. A Labour Composition gap of 7.7% emerged between the two measures in 2011, with hours worked of the lower skilled falling faster than those of the higher skilled workers.. This sector employs a mix of lower and higher skilled workers, with the foreign MNEs typically employing the higher earners. However, it was the lower skilled workers, typically from domestic owned companies, who appeared to be the first to go when the recession occurred with foreign-owned entities less impacted.

X-axis LabelGrowth in HoursLabour CompositionQuality Adjusted Labour Input
20001.37805549300569-2.18575157973078E-141.37805549300567
2001-0.3647290042377795.57279916657549E-14-0.364729004237724
2002-5.034723459667361.17961196366423E-14-5.03472345966735
2003-2.36507127826965-6.83481049534862E-14-2.36507127826972
2004-2.424134802898094.54497550705923E-14-2.42413480289804
2005-1.48959508790703-1.84775091887516-3.33734600678219
2006-1.249175419570075.714904685134124.46572926556405
20070.461572882542558-2.9282428652863-2.46666998274375
2008-4.929762535395020.967106906001881-3.96265562939314
2009-9.15553753749053-1.85373855165635-11.0092760891469
2010-18.69572713026196.03560844309855-12.6601186871633
2011-0.5752270426167557.73437278465347.15914574203665
2012-0.801428280146415-2.17899438395392-2.98042266410033
20134.823273175390621.258539342272096.08181251766271
20143.953181114978553.000961381433536.95414249641208
20156.21885081893360.2770829373824746.49593375631607
20164.87225790156163-2.009932864554532.8623250370071
20170.3936187824086113.426227547407213.81984632981582
2018-0.04482023521731111.129509753591831.08468951837452
20191.77020631254178-0.7211303650723281.04907594746945

Get the data: PxStat PIA11

Between 2013 and 2015, growth in QALI exceeded growth in hours as the economy recovered and the lower skilled left the sector, perhaps in search of a premium in competing industries. In 2019, Labour Composition decreased, suggesting it is the lower educated who are joining the sector.

X-axis labelQuality Adjusted Labour InputGrowth in Hours worked
20004.005848302924493.91198794088393
20012.670767493463642.58807119238353
20020.6069452179360280.554497917347374
20030.8689312028904480.916605143437386
20042.698465037180432.72368589124087
20053.924732179999365.21727836602579
20063.381791121317154.28559126995682
20072.571566142877583.53678084162263
2008-1.66262515436711-1.7659444861751
2009-9.58001091267832-9.92108649467303
2010-9.51521230504231-9.29542474102229
2011-0.223433796455351-1.28035817947935
2012-0.66847352077677-0.471671707702352
20133.8757626140963.22817151054518
20142.127147032847873.43894111831455
20154.259459134425064.32246969657164
20163.175529068162563.21579058965096
20174.191796286977543.63781871007337
20183.516310859920153.51470658160178
20192.496503488102262.24811605911466

Get the data: PxStat PIA11

The chart above shows the situation in terms of growth in Quality Adjusted Labour Input and hours worked across the economy. During the early years between 2005 and 2007 when the economy was booming, and opportunities were abundant, the growth in hours outstripped growth in QALI and it was the longest period of negative Labour Composition growth. Lower skilled workers were in high demand at a time when consumer demand for goods and services was at a high.

X-axis LabelGrowth in HoursLabour CompositionQuality Adjusted Labour Input
20003.911987940883930.0938603620405554.00584830292449
20012.588071192383530.08269630108010682.67076749346364
20020.5544979173473740.05244730058865450.606945217936028
20030.916605143437386-0.04767394054693790.868931202890448
20042.72368589124087-0.02522085406043642.69846503718043
20055.21727836602579-1.292546186026423.92473217999936
20064.28559126995682-0.9038001486396713.38179112131715
20073.53678084162263-0.9652146987450472.57156614287758
2008-1.76594448617510.103319331807987-1.66262515436711
2009-9.921086494673030.34107558199471-9.58001091267832
2010-9.29542474102229-0.219787564020013-9.51521230504231
2011-1.280358179479351.056924383024-0.223433796455351
2012-0.471671707702352-0.196801813074417-0.66847352077677
20133.228171510545180.6475911035508233.875762614096
20143.43894111831455-1.311794085466682.12714703284787
20154.32246969657164-0.06301056214658434.25945913442506
20163.21579058965096-0.0402615214884053.17552906816256
20173.637818710073370.5539775769041764.19179628697754
20183.514706581601780.00160427831836233.51631085992015
20192.248116059114660.2483874289876032.49650348810226

Get the data: PxStat PIA11

As the economy collapsed between 2009 and 2011 and the fall in hours was greater than QALI, employees with lower levels of education or those who were less experienced lost their jobs. This resulted in the positive Labour Composition effect of 1.1% in 2011 and was due to the recessionary effects on the economy with house building stalling, falling demand for business and personal services and lower levels of discretionary spending. Since the recession, growth has recovered and both QALI and hours have grown at a similar rate in recent years. The latter years are characterised by marginal increases in the quality of the labour force.

GVA Analysis with Labour Composition

The two charts below are presented for illustrative purposes and show how labour composition can be included in GVA analysis. In the charts below, the labour input is split between the Labour Composition and the growth in hours worked. This distinction allows users to see the impact that each of the components have in different stages of the economic cycle. A table is also provided below to show how the Labour Composition relates to the factor inputs.

Table 10.1: Total Economy GVA Growth and Input Contributions 2000-2019

X-axis labelLabour InputCapital InputMulti-factor ProductivityGVA GrowthLabour Composition
200011.95384495902022.56072718873659-8.072328135838166.442244011918683.12562356976163E-14
20014.758663461249221.75742199773358-3.376776661439793.13930879754299-1.68192707931234E-14
20020.4851514813894361.096434739114340.2480427309215521.82962895142531-1.74779277521642E-14
20032.31141259155931.197020631340072.555588535821646.064021758721055.01427862273423E-14
20047.902972288608970.8733215328328680.7741823510667189.55047617250864.6175216340894E-14
200510.13196806147422.47279858008893-1.9680350275559.96149571472373-0.675235899284373
20068.227781611039123.16380339524894-8.030658699427634.563979481304091.20305317444366
20072.180669916221312.94462569991937-3.163631125625730.951822519234562-1.00984197128039
2008-13.14524086156620.001200353905576017.87427685563302-5.91960416639756-0.649840514369948
2009-45.706195450829011.1199057680251-31.79191482280642.79437485999739
2010-43.947012709912208.01226796913753-30.26613171944535.66861302132938
2011-7.929824522051460-8.9319909055906-15.24983022846911.61198519917291
2012-8.2612087530539408.09537868944336-1.98445876199084-1.81862869838026
20133.264631355323040.2299321509184693.170525031590338.868173934205682.20308539637384
201412.342239588728-1.01851389354893-4.918632557286336.597090707609120.19199756971643
201510.4120816588371.50531333983499-2.042315050479456.43420727230311-3.44087267588939
20167.375140126278672.43605368021-2.6640501221080510.20239856956213.05525488518151
20176.115558166328442.779508789898023.8891533588924812.5264642345203-0.257756080598683
20188.384881796556214.50021822261732-2.4211415652941711.14123772934550.677279275466095
20191.016799199407385.938025101660820.9983545837915847.23927529978323-0.71390358507655

Get the data: PxStat PIA09 (GVA and Input Contributions),  PxStat PIA11 (Labour Composition and Hours)

The chart above shows the factor inputs in the Construction sector. During the recessionary period between 2009 and 2010, the impact of Labour Composition can be seen. The contribution of the Labour Composition to overall GVA growth increased by 3% and 6% in 2009 and 2010 respectively, while growth in hours fell sharply. Since 2015, the Labour Composition contribution has increased on average by 1.0%, indicating for that these years, higher skilled workers have joined the labour market in the sector. Over the entire period, Labour Composition has been a significant factor, particularly in explaining GVA growth in the Construction sector.

X-axis labelLabour InputCapital InputMulti-factor ProductivityGVA GrowthLabour Composition
20002.001491304747653.76777954277522.022837584364517.840130230861050.0480217989736923
20011.313281815467323.30658625668655-0.9260299101973323.735801284429570.0419631224730318
20020.273549083122133.866563515425021.7409523761945.906938671538590.0258736967974376
20030.4459968805239583.26359878196431-2.414504756311481.2718939724497-0.0231969337270819
20041.357325314546233.511545747908210.2054123920076015.06171485990391-0.0125685945581303
20052.649032982591455.39899165635474-1.488356002441535.90338824698138-0.656280389523278
20062.212722340751473.20693147840826-0.4853534652819074.46765324394714-0.466647109930678
20071.850069940281282.857532565613923.316409951658167.51911413898902-0.504898318564347
2008-0.9577084127775711.99147106294119-3.36888252301756-2.279087651051050.0560322218028966
2009-5.534262477889021.15927546230653-2.41914265959109-6.603868074555290.190261600618293
2010-4.9834815263080.8179686361055796.11455398529221.83120815086762-0.117832944222155
2011-0.643415373784160.6979047857577360.2937539035803610.8793770297231010.531133714169164
2012-0.2291196034952541.39206961271894-3.18863528076662-2.12128386873738-0.0955985971944475
20131.54267627583451.13124388610123-1.558189637863931.425200894092050.309470370020249
20141.593774408156683.832779236087412.535876056210587.35447981978506-0.607949880669607
20151.7276966843056837.3465848492346-16.196552061201922.8525440698088-0.0251854025295358
20161.139752332027583.11202185637144-2.757598009554411.47990654223439-0.0142696366102242
20171.288322029764643.895406824356741.834265597991967.214183864334280.196189412220955
20181.196593152768030.6274113907060477.337598816386969.162149541571920.000546181710874374
20190.7452805421133166.04496132788678-1.508030100650975.364555524032170.0823437546830486

Get the data: PxStat PIA09 (GVA and Input Contributions),  PxStat PIA11 (Labour Composition and Hours)

The chart above shows the factor inputs in the total economy. Similar to the Construction sector, the Labour Composition is presented for illustrative purposes. Unlike the Construction sector, however, the impact of Labour Composition is not particularly evident in the chart. As the total economy encompasses both foreign and domestic dominated sectors, some sectors such as Construction suffered badly during the crisis, while other foreign dominated sectors, such as Manufacturing were not as heavily impacted. This resulted in an overall balancing out of Labour Composition effects in the economy.


Go to the next chapter: Summary