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KLEMS

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In the section below, the focus is on the KLEMS (Capital, Labour, Energy, Materials and Services) methodology for measuring productivity. The data sources used and the issues that had to be overcome as well as the use of Domar Aggregation in estimating MFP are examined. In addition, some KLEMS based analysis on key industries in the Irish Economy will be presented. KLEMS is a framework where changes in productivity are measured in terms of Gross Output as opposed to Gross Value Added (which is used in the core productivity accounts presented in Chapters 2 - 7).  Gross Output is broken out into contributions from Energy, Materials and Services, in addition to the factor inputs of Capital, Labour and Multifactor productivity. Energy, Materials and Services are classified as intermediate inputs and the KLEMS framework critically produces indicators of their contribution to productivity.  The framework can also provide useful information on the interaction between different industries.

           How KLEMS estimates differ from the GVA based estimates of productivity:

EnergyMaterialsServicesCapital ServicesLabour InputMultifactor ProductivityGross Output
20000.1515592443425340.1903229134746971.117151185081455.642219076438031.79248065454005-5.647041357147973.24669171672878
2001-0.6727965953637590.520089523795223-2.562126585416334.519268371638780.446000220334022-7.99782901757297-5.74739408258503
2002-0.1505060932254550.3060734235505171.274400913049882.840746828945640.164760495069909-2.216940120172242.21853544721825
20030.26965087014997-0.214807717907208-0.2703534078985821.704534497881130.115797285063632-1.99246189980187-0.38764037251292
20041.190583786417111.939277631601537.548256389542370.6737207058331541.082534272645460.61849825318119313.0528710392208
2005-0.617930051292924-0.726578409101628-3.611496851781981.805587378558091.87605221635431-0.905264746116809-2.17963046338094
2006-1.195591010318623.1201250813548410.52425061476992.7994355806171.05538297592943-0.91321037585755115.390392866495
20071.44287516662416-0.432397131332690.09731258265890212.879973666763611.704033650919062.805495665413098.49729360104613
2008-0.614309962344548-1.784878858016027.718005808042891.215830025888610.181051234081738-5.320197500364731.39550074728793
20090.9558324807992450.412611335348044-3.01222845512563-1.25517755649691-3.9472963599476-1.93938357970775-8.78564213513061
2010-1.16010288480079-1.58513959557620.995315483503036-2.34208897397791.455650816894821.1481818788225-1.48818327513453
2011-0.3503522165366170.07297195303208794.08896563984832-0.960489883727854-0.004035606201229140.1279772496385062.97503713605321
2012-0.08868493663384150.7036623467109510.0901543699423714-0.5655573450611850.204891021135759-0.36928651926787-0.0248210631738148
20130.7111454558352020.614630789702261-7.182717596648521.494387225770880.667471400273689-2.66793442143503-6.36301714650152
2014-0.688380154475695-0.712911945543003-1.078440620030650.707184160667450.5754661795523772.426162648356891.22908026852736
20150.4493347927215210.4114756818120893.366224772711273.699646827013760.7161371539449910.2746931782437548.91751240644739
2016-0.07723226009445621.157278886728327.742021910901981.14875829298720.2147629642780570.86218979743392411.047779592235
2017-0.4758681728064550.1545790516344861.496272656967942.534160795539180.68216298952753-3.681805740732570.709501580130115
20180.1472028043410690.04150456206681042.574621847672971.12137553912328-0.02124993888861712.25120009596226.1146549102777

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The chart above depicts Gross Output in the Wholesale & Retail Sector broken down by its contribution from the KLEMS inputs. It is compared with its GVA counterpart below.

X-axis labelLabour InputCapital ServicesMultifactor ProductivityGVA Growth
20003.120166091643148.4511306607008-8.680780328367962.89051642397598
20010.685900649519747.58596225014522-12.7900399953909-4.51817709572595
20020.2876902861885994.11111168198568-3.100966190824011.29783577735028
20030.2002141404140782.55086516125469-3.00607567233942-0.254996370670646
20041.985293687785341.12185646743431-0.7006512532090612.40649890201059
20053.173817249256362.83743954939909-0.5540444042832045.45721239437225
20061.982128298523544.659084098560010.3762680684082747.01748046549182
20073.124032823863264.873643264046584.9437396654563712.9414157533662
20080.3310612731979722.40988880828144-7.73649258821819-4.99554250673878
2009-7.50330632102928-2.44837838759916-2.96521230703992-12.9168970156684
20103.13047279148346-4.098299142736422.007974201081531.04014784982858
2011-0.00842935310102778-1.752746295411730.149434991109538-1.61174065740322
20120.44474358210963-1.02867108072252-0.788078816939276-1.37200631555217
20131.364293700848772.38770743515049-3.017820409146050.734180726853206
20141.091738841203021.181396227717174.674424728064226.9475597969844
20151.429489727830255.926923211544741.421542716346478.77795565572146
20160.4445017885575152.089275274390612.436884051578544.97066111452666
20171.481205398009844.60619122270763-7.0446531165336-0.957256495816128
2018-0.04407894571746192.087029626652654.185496024498096.22844670543328

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The main difference between the KLEMS and GVA models of productivity is the inclusion of intermediate inputs in a more detailed series that estimates MFP based on gross output rather than on GVA in any given industry. The two charts above compare the KLEMS and GVA models of productivity for Wholesale & Retail. The KLEMS model offers a more detailed analysis in terms of what is driving growth and productivity in the industry. In addition to capital, energy, materials and services are also driving economic activity in this sector in the KLEMS model. This is not apparent in the GVA model of Wholesale & Retail and it has a relatively large MFP. In the GVA model, MFP is simply the difference between changes in GVA and changes in the primary factors of production. In fact, MFP measures the unobservable drivers of productivity and is sometimes known as the Solow residual. The KLEMS model minimises the MFP estimate where MFP = Output – Capital – Labour – Intermediate Inputs whereas the GVA model excludes these intermediate inputs and, in many instances, results in larger MFP. In theory, the inclusion of the additional intermediate consumption units in the KLEMS model should yield a more accurate MFP estimate as it minimises the Solow residual by including more explanatory variables. In practice, the inclusion of intermediate inputs makes the KLEMS model more prone to data quality issues and for this reason the KLEMS MFP estimates are considered experimental. The gross output series in the KLEMS model is much more volatile than the GVA model by nature, as the KLEMS series uses a gross measure for output while the GVA is a net measure.

In terms of the data sources, both KLEMS and GVA extract their capital services estimates from the CSO’s Capital Stock estimates and Labour estimates from the Labour Force Survey (LFS). The addition of intermediate consumption estimates from the Supply & Use Tables (SUT) was necessary for estimating MFP on a gross output basis in the KLEMS model. The Supply and Use tables are not intentionally designed for productivity analysis in National Accounts and incorporating these into the KLEMS analysis may have also contributed to volatility and certainly highlighted several data gaps that necessitated further estimation and additional adjustments. These issues emphasise that the GVA estimates are the more robust and consistent estimates for productivity analysis and the KLEMS is considered experimental.

Data Sources

In relation to data sources, as indicated above Capital and Labour inputs are sourced from the CSO’s Capital Stock publication and Labour Force Survey (LFS) which are also used throughout the publication in all productivity presentations. The intermediate inputs are obtained from the Supply & Use tables and used together with Capital and Labour inputs to estimate productivity on a Gross Output basis. The Supply and Use Tables provide a detailed picture of the transactions in goods and services by industries and consumers across the Irish economy in a single year. They highlight the inter-industry flows that lie behind the National Accounts main aggregates. The supply table contains estimates of the supply of goods and services (products) by domestic industries as well as imports of goods and services while the use table contains estimates of the use of products by domestic industry and by the final demand sectors (Final Demand comprises consumption by households, government, non-profit organisations serving households (NPISH), gross fixed capital formation (GFCF) and exports). The Supply & Use tables are broken down by NACE Rev. 2.0 into an A21 sector economy.  The incorporating of these inputs with Capital and Labour generated a series of issues ranging from data source issues to methodological issues that impacted the KLEMS estimates. 

Show Table: Table 8.1: KLEMS Decomposition: 2018

 KLEMS  - The Challenges

The KLEMS estimates created required a data series of Supply and Use Tables (SUTs) for the entire period 2000 – 2018. The existing series of SUTs are not complete for this entire period and are also presented in line with earlier standards and earlier classifications. In fact, 2000 - 2018 witnessed the reclassification of economic activity from NACE Rev. 1.1 to NACE Rev. 2.0 and the change from European System of Accounts (ESA) 1995 to ESA 2010. The production of a single consistent presentation of the input data for Energy, Materials and Services from the Supply and Use tables for the entire 18 years was therefore challenging due to gaps in the data series for some years. Accordingly, in this publication the estimates reflect a re-evaluation of our KLEMS estimates and entailed several steps to ensure data quality and consistency between the KLEMS and GVA frameworks and the analysis presented. The series is nevertheless considered experimental.

Details on Methodology - Domar Aggregation

Domar Aggregation or Domar Weights are used to combine the twenty one sector industry-level, gross output-based MFP to higher-level aggregates. Domar aggregation imposes a relationship between the value-added MFP and the gross output MFP [see appendix]. It states that an industry’s value-added MFP is equal to its respective gross output MFP multiplied by its Domar weighting. This weighting is the ratio of its gross output to aggregated value added in the twenty one sector Irish economy. The advantage of the Domar methodology of estimating MFP is that it imposes a direct relationship between the value-added MFP estimate and the gross output MFP estimate, resulting in consistency between the GVA and Gross Output MFP estimates and near perfect positive correlations. The sum of the Domar weights are greater than 1 as the sum of each industry’s output will be greater than the sum of value-added in each industry. The economic rationale for this is that industries interact by using each other’s output as intermediate consumption, thus contributing to productivity and gross output in the aggregate economy.

EnergyMaterialsServicesCapital ServicesLabour InputMultifactor ProductivityGross Output
20005.782142748557821.869607239264951.534854541047324.01439943075315-3.493895008618911.8487798745933911.5558888255977
20011.489518590517011.104287743898431.240113168124694.327508023355112.98394779964952-3.14262000559398.00275531995086
2002-2.801187986541546.278315883280092.675187829662525.619393276428120.741377539242672-5.600228068347326.91285847372454
2003-1.87508191476868-4.85498185138175-2.724091917643365.486074009069272.66096732461888-7.94823369720262-9.25534804730826
20047.62322263882065-0.9031973874601960.7341815345525893.012264625835570.6150142474399821.629682524110312.7111681832989
200522.74634010914441.549294952807834.71799618584153.11962531425871-0.880155289586435-4.6438261926632426.6092750798028
20062.651960898904521.5497612271815216.75006709146742.09491580837619-2.61211561749022-2.60438629666817.8302031117714
2007-11.6738288858841-3.29019413165153-4.29097002738582.89150792672741.27862089736814-7.46888403930008-22.553748260126
200844.00880705313581.345358275882452.135557454820381.460886316207180.954422496031932-14.134895384056335.7701362120215
2009-3.04235361181237-2.04039211897925-3.218986841236840.1445528423942410.940344558345005-5.22677877569823-12.4436139469874
2010-17.42223264801942.58840427035015-0.16284234903332-1.27726587835268-4.5706536282768.06282526717995-12.7817649661513
2011-14.940269123705-0.957277269325592-4.31085203644529-2.48381005485172-2.37849094444474-3.19616142494144-28.2668608537138
201232.138808099491.335669264576454.079005095003130.0550982308839354-2.34383796626958-6.0744671087293229.1902756149547
2013-0.232458732133210.8183419340178320.5586217075069091.829701130440672.187847601086-6.96680041967722-1.80474677875901
2014-9.5733818067248710.06370450941065.325616822023880.758231017161518-0.0329492135021954-0.1579681347094926.38325319365943
2015-3.75254521844666-2.411409642678032.062963941368791.8683869574355-0.885567275540834-1.79927394608475-4.91744518394598
2016-12.5374183680831-1.88994270101939-6.941825463441542.789282769991360.0856958645047576-5.5857904147094-24.0799983127573
201722.93394201514849.9673735765232127.23420655879980.4668641244857260.823036165364494-11.781402065245349.6440203750764
2018-14.2477814740814-4.32132868254523-11.10525923153283.304126732491040.8232521138132585.6484786976932-19.8985118441619

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The above chart shows Gross Output in the Electricity, Gas & Steam sector broken out by the KLEMS inputs. The chart shows that the trend in this sector is mostly explained by changes in energy inputs, MFP and changes in Services. Gross Output is quite stable between 2000 and 2004 where growth remains below 20%. The trend shows growth until 2007 where it sharply decreases by 23% coming into the recessionary period. It is important to note that Gross Output increases by 36% in 2008 at the start of the economic downturn which is largely driven by an increase in Energy Inputs of 44%, despite a negative MFP of 14%. This may suggest an increase in demand for electricity or energy inputs during a financial shock however it is important to consider factors that affect the intermediate costs of producing electricity, which are in turn reflected in our analysis using the KLEMS model.

X-axis labelBrent Crude (right axis)Electricity Energy Input (left axis)Transport Energy Services Input (left axis)
200046.960922971390121.888044769025377.0111367185909
2001-14.80656271038955.417485018074250.175016605156473
20022.37479958770495-12.8261498217652-4.79024998970367
200314.3123651831718-8.5793745884997464.891348194494
200428.301931944044430.135291472711736.4197638248266
200535.202733038162562.512994208319720.1185629429366
200618.31801867369447.81983334431988-11.7842495048436
200710.661023729874-57.410538427306739.0187010269032
200829.3792507304015101.27439650225468.9278560172933
2009-45.5614663628721-7.933135684003845.75142498872002
201025.2502835940454-51.122910260296-3.79288187182479
201133.282235586745-65.8340035308288-28.5155896623529
20120.78650991200134983.255929230301348.6849636572435
2013-2.82223091831196-0.639890212753792-11.1557897786641
2014-9.53680063783037-37.51883408800899.1654225784916
2015-63.5652208086162-18.2248089460924-14.0406492258456
2016-17.362635428763-100.505297912027-25.0082021615085
201721.111173122863387.952655227231-32.9328808323353
201826.7301185902436-84.014053908144711.665219565901

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Using an annual dataset from the Federal Reserve of Economic Data (FRED) on Brent Crude Oil prices, it was found that there were high positive correlations of 79% and 77% respectively between Energy inputs in Transport & Storage and Electricity, Gas & Steam and Oil Prices ($ per barrel) during the period the years of 2000-2018. The chart above presents growth in energy input in Electricity, Gas & Steam and Transport & Storage against oil prices (on the secondary axis). Oil Prices increased by 13% in 2008 and this may be what is driving the large change in Energy inputs in 2008 in both sectors, as oil or products indexed to oil prices such as gas, are key inputs or materials used in electricity generation and is also an important energy resource for transport in Ireland. Oil prices are also used as an index for electricity prices. Oil was a costly resource for intermediate consumption during 2008 and this may be what is contributing to the increase in intermediate consumption in 2008 for both sectors. Gross Output growth in Electricity, Gas & Steam then peaked at 50% in 2017 which is largely driven by increases in Energy inputs and Services inputs. The estimates for 2018 suggest that the decline in output of 20% is largely down to decreases in energy inputs and services inputs.

EnergyMaterialsServicesCapital ServicesLabour InputMultifactor ProductivityGross Output
20003.312817161806343.6994082871983410.68884612223121.840098221104332.15811806098406-3.1615973750420718.5376904782822
20010.00675375802831960.771467409843759.270229065639012.100208318550414.38271548575248-5.4932923643999511.038081673414
2002-0.1682224461123840.3908620629231571.846993938423282.903446493357671.39703260579932-1.733469609194524.63664304519653
20033.881096458401541.091726434368025.173060510780920.892219088728763-0.3312278351793510.9390642980300811.64593895513
20042.72433477398309-0.2095726897712345.990161072189451.195289859759321.383537197858831.7475806903706612.8313309043901
20051.72770540816933-0.2792672286373152.326982683666731.912540522565390.928130198501814-0.3013853324214756.31470625184448
2006-0.8877410758507921.56945139797357.257101222911251.39183951813473-0.3142436144719281.7760895630367910.7924970117335
20073.56271155007593-0.9136272442424181.837827565526772.632051511141730.64524175236421-0.7653507627547936.99885437211143
200812.759644122307-0.09916754430177239.086414878912920.821436821241387-0.4712734887915-5.6470419205554316.4500128688126
20090.7961866501318013.36884706209002-5.07426115302860.683144882420460.207974774574546-6.73476258629969-6.75287037011146
2010-0.6566799676886072.487797939762115.08152781381444-0.659751419064928-3.670651762168642.250102431322754.83234503597713
2011-5.59681930431315-3.38043358568783-12.7482134280556-2.835264084009650.178110155174382-1.36759464284113-25.750214889733
201212.51192398655743.2154611630114515.55820980278130.399458626475582-1.14477204552143-3.1148028421690227.4254786911354
2013-2.673208442134730.480698440879297-5.703395945213790.558910026682129-0.247202333734707-0.969796245319564-8.55399449884136
20142.16569248975304-0.3045065820787521.625460139409970.07720405763147470.5536739834364621.123606096997645.24113018514984
2015-2.43102015293782.550388732971392.000170418609581.13358988671621.36642895728544-1.137444679668693.48211316297613
2016-4.319639666168890.287679190472990.3553596221831873.23772255864480.371486041292013-0.76075383471052-0.828146088286413
2017-5.55041072336763-0.14377704221286-0.4524969795655361.921748123505630.4832545166873620.93698987894722-2.80469222600581
20182.020917479327671.195027752642933.22305568796431.713629943250111.30055337101637-0.5013436332049548.95184060099643

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The above chart shows Gross Output in the Transport & Storage sector broken out by the KLEMS inputs. Changes in Gross Output growth are explained mostly by changes in Services Input as well as Energy input and MFP. Gross Output declines between 2000 and 2003 and remains below 20% until 2009 where it declined by 12% only to grow by 5% in 2010 and sharply decline again by 26% in 2011. The spike in Gross Output in 2012 of 27% and decline of 9% in 2013 brought about the end of the post-recession period of volatility in this industry between 2008 and 2013. The recovery period brought about significant changes in fiscal decisions that may have created volatility in intermediate consumption because of changes in public expenditure and policy reform in transport development in Ireland. The latter years of 2014 -2017 experienced a steady decline in Gross Output caused by a decline in Energy Input and MFP with Gross Output returning to a positive growth rate of 9% in 2018.

EnergyMaterialsServicesCapital ServicesLabour InputMultifactor ProductivityGross Output
20000.7236060264333331.795876811842815.863250470366858.122200783655022.0776849336625-4.9882248136316813.5943942123288
20010.07129638527615830.8161747314308644.563175476475324.554627560558521.194737218360380.40434741747794911.6043587895792
20020.2980846777290.607385003940446-1.020455653118996.327988996213870.263421757982251-5.504207377478770.972217405267804
2003-0.700087131395873-1.630688546410820.6001557545852152.645906009336920.628654763342925-3.72625913772692-2.18231828826855
20040.0247769780488537-1.61334321191577-2.161980568896674.266035281878732.389167827375311.358251630325644.26290793681609
2005-0.714347941672411-1.69975444471792-5.7822122164541418.73747909345842.55600341430255-12.12224062772430.974927277192199
2006-0.3139589548069680.574837875027878-3.293073709437472.374775710256182.1413068677756-13.9006052734599-12.4167174846447
20071.339615962534593.2558522938117117.32584101807771.41337377214672.399788195552867.8102273039877333.5446985461113
20083.12297571205079-2.023250485447730.7514925238056-0.639049467128511-0.169916306255718-5.4125179864785225.629733990546
2009-1.2403050813797116.381186322572-3.062436314358481.7369776909215-2.60749758801838-10.21045301381740.997472015919628
2010-0.686033012604474-2.39722784053648-10.42629852890963.28224632582406-1.29049056436458-0.746116618286073-12.2639202388771
2011-0.442656685290135-5.11744634593671-17.06905160154874.1257754341680.984674596204912-8.95746617362568-26.4761707760283
20120.1081335629793138.34065659659994-1.122085606066473.03514562785946-0.391991977435165-6.343543881087423.62631432284965
20130.2628340132389118.58144150227459-1.993669080463073.597819250897361.37504574354017-0.02253316047944611.8009382690085
2014-0.077937534821816-2.90922720673819-1.7015199760133312.1901802466461.73350216855122-6.594147098802722.64085059882119
20150.224622588484087-2.18036452899773-0.8092590929356276.435737251764830.8767366612582970.4034422958682014.95091517544206
20160.5071639139763027.22929804706929.224333168443522.187841122926771.32611606119484-1.7915654963760918.6831868172345
2017-0.525199569890349-2.17895428023743-1.92373416535611.564793028024111.336386771646183.534904134129851.80819591831626
20180.2007170288332181.61718536552482.763663026012265.10989660500481.8809579155434-2.757532708153188.8148872327653

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The chart above shows Gross Output in the Professional, Scientific, Admin & Support Services sector broken out into the KLEMS inputs between 2000 and 2018. This sector covers 13 NACE activities and the largest areas within this broad genre of services include Research & Development, Architecture & Engineering Activities and Legal & Accounting Services. As expected, changes in Gross Output in this sector are largely explained by changes in Services Input as well as changes in MFP and Materials Input.  The decline in Gross Output between 2000 and 2003 was associated with the collapse of the dotcom bubble in 2003 when Gross Output declined by 2%. Gross Output grows to 4% in 2004 however it again declines between then and 2006 where it takes a sharp decline of 12%. The large positive Gross Output growth rate of 34% and 26% in 2007 and 2008 respectively are followed by a gradual declining trend and a decrease of 26% is recorded in 2011. This decline was likely caused by the economic recession period as high skilled industries are likely to witness a gradual decline in output rather than a sudden drop which was seen in industries like Construction and Accommodation & Food. Gross Output growth recovers after 2011 and peaks at 19% in 2016. This recovery in Gross Output is largely explained by increases in Materials input and Capital input.

EnergyMaterialsServicesCapital ServicesLabour InputMultifactor ProductivityGross Output
20000.5744061674552682.9103936164598114.16277660493085.883904726396041.617283251317512.2570007978573727.4057651644168
2001-0.531448737296064-1.88536327785223-13.6188829810199.49625702363460.871158364756152-16.523135916857-22.1914155246335
20020.8355705705797921.7116750078386328.83758402317332.54363679370663-0.21963624905244-8.2024769834540325.5063531627919
2003-0.263347944469899-0.387641164015773-7.75887219426856-0.671061498324951.18801265806506-1.84345347271025-9.73636361572438
2004-0.03693609649644010.0117674677808908-0.120593844415557-1.550956563333222.266824414871928.159775610292568.72988098870016
20050.2674675595076581.4109790969957522.58924735388392.97520017091630.722081010970046-6.848099543259521.1168756490142
2006-0.005921294331296691.429964423726147.152294425551034.765935803208130.7025625772854630.54312861957419614.5879645550137
20070.2364763105673810.0124382723436528-10.19923902737865.774521342193251.36686833738548-5.45447991378161-8.2634146786705
2008-0.325873822418081-1.24911007956566-3.67327124985322.523248485189810.922767602303822-4.45528448185698-6.25752354620029
20090.3587745275658080.902127761376929-0.2144853532066250.161766426037270.775236391533534-4.43702000842633-2.45360025511942
2010-0.17851006548982-0.849408721691175-5.02324255014585-5.78738858415855-7.1610573344184217.0692304940253-1.93037676187848
20110.0301560127700768-0.05674772133908262.81370713258438-2.643715471641280.236815444561926-2.73529950732179-2.35508411038577
2012-0.1213717702093660.172367538000577-0.8100276351377430.296573625890972-0.0733647044464375-9.97673893518438-10.5125618810864
20130.5248153441974560.76777180922146710.84208129611013.167688869013140.796394806912466-11.0317632887025.06698883675267
2014-0.164528482082154-0.185897751458396-5.3778597097691710.36093729844450.545563817351981-9.90567429935496-4.72745912686816
20150.3663145176796540.6226614592262278.478530232469723.004859040429370.2764265127021743.2396888815628415.98848064407
2016-0.302121669632383-0.484737067741156-6.100870104087086.362047780757541.24101152815797-7.40314404694145-6.68781357948655
20170.1637929562144961.113328055980314.12740796116166.40649467951186-0.666945523605653-4.1128820863738217.0311960428888
20180.1722159424674750.5569651198377876.22805830230194.996399337724090.161641403172688-4.098634284678948.016645820825

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The above chart shows Gross Output in the Financial & Insurance Activities sector broken out by the KLEMS inputs. The changes in Gross Output growth between 2000 and 2018 can largely be explained by changes in Services Input as well as MFP. The volatility in Gross Output between 2000 and 2018 is largely associated with fluctuations in Services Input as well as changes in MFP. The volatility in Gross Output between 2000 and 2003 can be attributed to the collapse of the dotcom bubble and this leads into a period of increasing Gross Output up until the collapse of the sector in 2007. This was largely down to a decrease in Services Input as well as MFP. Gross Output was slow to recover in the Financial Services and Insurance sector as this period was characterised by what was termed a Balance Sheet recession where a period of asset inflation was followed by a crash in these same asset values. Many bubbles were present in the market as many assets were overpriced and price increases were not driven by fundamentals leading to the collapse of many financial instruments as bubbles burst in 2008.  The recovery period saw drastic changes in financial regulation as the Central Bank moved towards adopting and implementing macroprudential policies and this may be responsible for the slow and steady recovery in gross output in Financial Services & Insurance. The period between 2011 and 2018 is associated with volatility in Gross Output as the industry recovered from the decline in Gross Output during the recessionary period after 2007.

EnergyMaterialsServicesCapital ServicesLabour InputMultifactor ProductivityGross Output
2000-0.01840718660571-0.169441691079357-0.04909987357726391.381635493574661.29954806599159-2.87387377513226-0.429638966828338
2001-1.44333377541352.284084903756751.478753021275060.950931248857473-0.0172490896810282-0.05841036536701693.19477594342773
20020.141799889329522-0.230577696068411-0.1832799147392690.5466530194497930.301048877493829-1.00419102966752-0.428546854202052
2003-0.0107916587073907-0.8598499731861272.051286996746590.01771130977465741.785288177221840.8740162928095113.85766114465908
20040.4361800494359433.820697787756412.3473984954078-0.202925099949937-1.643896662181122.545367981773517.30282255224261
2005-0.43858488624863-7.91218899211642-0.7725657533505990.1880876310590622.23021017978005-2.43884184410241-9.14388366497895
20060.052532612236944-0.06184866136194611.567443325591730.28183130953252.10578093489275-2.88848937380871.05725014708329
20070.2282438111532422.041429118368082.169971486852420.26044784842053.464074762382980.01287888612982328.17704591330705
20080.02350121694142935.096943893458044.630102443566560.0772918932718543-2.366304049498341.609640398567439.07117579630697
20091.83116180195682-7.76709105893874-0.318689597391632-0.0910603099120693-1.47389608381494-2.96830679849448-10.787882046595
2010-2.07735798465379-7.10094183991663-1.811755952728460.0570860149009748-1.55488173455874-0.710246960072175-13.1980984570288
20110.506319840286583-11.20759783451862.4225656381595-0.151425206178256-2.97806159196446-4.73962008784396-16.1478192420591
20120.5380106484881354.73237320607577-0.434504826563265-0.4258608588801850.992911701990217-1.906328870429283.49660100068139
20130.00800857088215004-3.47455661836922-6.176450575974210.003468768596944434.99256525736467-1.28870577281847-5.93567037031813
20140.7779554673323253.68825600067363.283142322301770.1079870901180513.73140326891111-0.70184859771439310.8868955516225
2015-0.50411942965169-1.33096986837183-5.123204321462540.4595490826657911.146259188939670.660105624593797-4.69237972328681
2016-0.4838059485081531.67051850402822.967604981288180.2167191370453292.908089787249030.4882241149624977.76735057606509
2017-0.7809172387059820.6485978473073791.152206454391760.1045473973076292.480924223498660.659275553300194.26463423709964
20180.339642285117430.5894802283381881.894957960555520.6237891599445443.907224579167091.151847392507188.50694160562995

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 The chart above depicts Gross Output in the Accommodation & Food Services sector decomposed by the KLEMS inputs. Growth in Gross Output and productivity in this sector are largely associated with changes in Materials consumed in the production process. The series depicts an increasing trend in Gross Output between 2006 and 2008 which is largely driven by changes in Materials and Labour. The industry experienced a sharp decline in Gross Output after the economic crisis in 2008.  The following years of 2009-2011 saw a continued decline in Gross Output which was largely driven by decreases in materials input and labour. This period also saw lower levels of overall activity and discretionary consumption as many household budgets were impacted by the events of 2008. This may have resulted in lower levels of demand for Accommodation & Food services. The recovery period resulted in volatility in this industry, which is seen in the alternating increases and decreases in Gross Output between 2012 and 2016, which is caused by volatility in materials consumed in the production process. The industry’s return to steady growth in 2016 was largely down to a steady increase in labour input as the industry experienced an increase in demand due to improving household and corporate budgets.

EnergyMaterialsServicesCapital ServicesLabour InputMultifactor ProductivityGross Output
2000-0.0233005678044371-0.540092533268886-2.125521969578574.490714882987210.243697541894854-4.7402081349141-2.69471078068393
20010.174430767553941.952845373602036.864409251077563.476337455353230.463975622528774-2.8300724044398810.1019260656757
20020.0666873900544334-0.43013246577579511.76538155106822.342194336128970.2995328933991560.42743079957101314.471094504446
20030.0741587903965297-2.54732820883557-7.2184903734541.24626189306527-1.05037524832524-4.15732832166734-13.6531014688203
20040.266953139498596-3.27199816427412-10.90516463925031.67181397930133-0.4849733655560762.42993885598199-10.2934301942986
20050.2492690081317450.81191486616964316.26774405947951.884700940185170.9680473689329840.64498520997469120.8266614528738
20060.4632408092874411.055044905270726.156453580689312.262504852290230.4118879286083261.8095662155646112.1586982917106
2007-0.007224322940113590.33394691676907-10.33555855140022.61596327942025-0.05649422424332183.82378359804934-3.62558330434496
20080.593020148374228-1.553686802194820.98782186280242.129712002609260.429220701293438-2.0781906103789320.5078973025056
2009-0.4281982420525512.49358011112345-0.08849502183944451.46073290185551-0.012468984200649-1.215448085487082.20970267939924
2010-0.1130369946332554.0092448885970121.22480010187441.29922740999068-1.650430224295971.4756139466966826.2454191282295
2011-0.0661607491451089-1.78013394867976-3.774225299402051.480742438659540.386497327712506-1.98443954825607-5.73771977911093
20120.07337433086130160.040405808100585128.97398398848382.529598681051590.152868289235479-3.7299112126267828.040319885106
20130.5388425504516151.35149872652999-3.733384236492292.192301853524540.449812765256294-0.51605687686510.283014782405047
2014-0.0530483952517063-0.16711815766946812.70677009859262.54075257298438-0.00304879880566196-0.038099004501931914.9862083153482
2015-0.01196291852332910.08229511287897621.444487782880734.31825262476360.170706339649625-0.7966911680317335.20708777361787
2016-0.133919753655603-0.480964215326521-7.478832536839515.135878944745130.524377179495299-2.38668875783311-4.82014913941431
2017-0.04423525173548720.06989709392712282.3220068565494519.35239273794040.731259721373194-14.4561507435087.97517041454669
20180.05275453460112750.44936414570940912.05989626087770.6289043260171810.0652172268700266.5456232379985519.801759732074

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The chart above decomposes Gross Output in the Information & Communications sector into its KLEMS inputs. Gross Output in this industry is quite volatile which is a consequence of extreme fluctuations in consumption of services in the production process. The dot-com bubble collapse in 2003 is followed by an increase of output up until 2005. The fluctuations between 2007 and 2013 where Gross Output fluctuates between positive and negative changes in growth is a result of fluctuations in services.   A change in the fluctuating trend in gross output occurs between 2016 and 2018 where gross output increases steadily in 2017 and 2018, possibly suggesting a return to a steady and predictable trend in economic activity in this industry.


Go to the next chapter: Quality Adjusted Labour Input