Departmental retreat: Employment Policy Department Employment Impact Assessment Methodologies: From Input Output to DySAM 5 September 2
Integration of Employment in Public Investment Programmes in Infrastructure PROGRAMMING AND BUDGETING PROCESS Tools & Methodologies for impact assessment to analyse economic growth, household income and consumption, employment, multiplier effects, balance of payment, etc. 3. Negotiation, arbitration and finalisation of budget proposals 2. Preparation and priority setting of programmes Ministry of Planning/Finance Employment Investment Unit 4- Political process and approval of the budget. Macroeconomic framework Programme formulation guidance I Preparation, impact assessment and approval of programme proposals Investments in Public Works Sector Investments in Education & Health Sectors Investments in Environment Protection Sector Investments in Agriculture Sector Investments in decentralisation & regional development Tools & Methodologies for Capacity Building and sectoral analysis of major technical options using the 3 criteria: (i) unit cost, (ii) employment and incomes, (iii) foreign exchange: local expenditure vs. import (in the preparation, selection and prioritisation of programmes)
Evolution The (Dy)SAM is the result of a natural evolution of analytical EIA tools developed and used by Emp/Invest during the last 3 years It is based and adds up on previous used tools, which have shown their effectiveness, but also certain limitations the (Dy)SAM intends to overcome
Production I N P U T O U T P U T Social transfers Institutions Wages Consumption Transfers Taxes Subsidies/credits Social transfers Enterprises Households Government
Expanded and extended SAM Activities Expansion Construction SAM Monetary values Employment satellite Employment satellite Real values
DYSAM Time dimension 2 29 28 Static: One specific year
Dynamic SAM Static SAM: Snapshot of the economy Dynamic SAM: consistent evolution of the economic structure over time (incl. income and techn. coefficients) To create a dynamic SAM, need for forward looking projections of key macro & financial variables, derived from macro SAM and flow of funds
What is the outcome of it? Impact analysis of: on targets: Public investment: e.g. infrastructure Social transfers/prot. Private investment Sectors/sect. policies Ex ante Ex post Workers Households Formal/informal Rural/Urban Gender/youth Skill level Green jobs Decile/quintile Rural/urban Heads of HH Gender Direct, indirect and induced employment effect Direct, indirect and induced employment effect
Who will use the DySAM? CMEA: Infrastructure investment Public Works: Construction satellite account Finances: Climate change/green jobs Planning: Climate change, growth and employment (youth emp) Bank of Indonesia: Climate change & remittances (social fin.) Manpower: FDI and employment BPS: Hosting and up dating DySAM ILO projects: Trade and employment, green jobs Proposals on regional DySAMs UNWTO: Tourism satellite account
Conclusion It can do a lot, macro, meso, micro but not all e.g. monet. policy, project monitoring Helpful analytical tool for policy advise: Evaluation of effectiveness of past policies Decision making on future policies & mix of policies Targeting of specific groups (of workers) or indicators (e.g. MDG) Bring employment considerations into decision making process of various Ministries Potential for Social Dialogue Way forward: Extension & expansion Issues: technological change, green jobs/climate change, social protection, sectoral disaggregation Method: Provincial/local DySAMs, dynamic investment Training: ILO staff, local constituents, trainers of trainer
Christoph Ernst ernst@ilo.org
Additional material
Comparative Table Static SAM Method Deman driven multiplier framework on accounting platform (input output + social transfer) SAM + time series (dynamique), some behaviours Data required high: SNA, FoF, LFS, HS very high: same as static SAM + time series for macro variables Level of analysis Macro meso micro + interlinkages Macro meso micro + interlinkages Applicability Inputs required Data, skilled staff, simple software + hardware Data, skilled staff, dynamic software Costs Construction 3 w/m international, 3 5 w/m national consultant 2 6 w/m international, 4 7 w/m national consultant Period implementation Construction: 6 months, Training: 2 days 4 weeks Construction: /2 6 months, Training: 2 days 4 weeks Strengths full socio economic circle, micro meso macro, techno choices, employment account SAM+ dynamic + some behaviours Weaknesses Technical coefficient fix, strong assumptions Data and skill requirements, still fixed prices Challenges Starting costs: Financial resources + national commitment Starting costs: Financial resources + national commitment Ex post impact evaluation, ex ante simulation: public investment, spending, policies, exogenous shocks Ex post impact evaluation, ex ante simulation: public investment, spending, policies, exogenous shocks DySAM
< x 4 ( A Co ) A r Co c > <x4 ( I t xco) Co c > <x4 ( Tr Co) Co c > <x4 ( TC- TR) ( C o ) C o r > <x4 ( CoA) Co r A c > <x4 ( FL A) FL r A c > <x4 ( Fk A) A c> < x 4 ( ( wcu A) ) A c > < x 4 ( T r A ) A c> <x4 ( TC- TR) ( A ) A r > < x 4 ( I h F L ) ih r F L c > <x4 ( wcu FL) FL c> < x 4 ( T r F L ) FL c> <x4 ( TC- TR) ( F L ) F L r > <x4 ( I h Fk) ih r > <x4 t ( icr Fk) > <x4 t ( wcu FK) > <x4 t ( Tr Fk) > <x4 ( T c - T r ) ( F k) > <x4 ( CoI H) Co r I H c > <x4 ( I h I h) I h r I h c > <x4 ( I Cr I h) I h c > <x4 ( I g I h) I h c > < x 4 ( C c ih ) ih c> < x 4 ( ( w C u ih ) ) ih c > < x 4 ( T r ih ) ih c> <x4 ( Tc- Tr ) ( ih ) ih r > <x4 ( I h I C r ) I h r > < x 4 t ( I C r I C r ) > < x 4 t ( I g I C r ) > <x4 t ( Cc ic r ) > < x4 t ( wcu ic r ) > <x4 t ( Tr ic r ) > <x4 ( T c - T r ) ( i C r ) > <x4 ( Co I G ) C o r > <x4 ( I h I g ) I h r > <x4 t ( I Cr I g ) > < x 4 t ( I g I g ) > <x4 t ( isu I g ) > <x4 t ( Cc ig ) > <x4 t ( ( wcu ig ) ) > <x4 t ( Tr ig ) > <x4 ( T c - T r ) ( ig ) > < x 4 t ( I g I T x ) > <x4 t ( Tr it x ) > <x4 ( T c - T r ) it x > <x4 ( A is u ) A r > <x4 t ( ( wcu is u ) ) > <x4 t ( Tr is u ) > <x4 ( T c - T r ) is u > <x4 ( Co Cc ) Co r > <x4 t ( ( wcu C c ) ) > <x4 t ( Tr cc) > <x4 ( T c - T r ) cc> <x4 ( ( Co W C u ) ) C o r > <x4 ( FL W C u ) F L r > <x4 t ( FK wcu ) > <x4 ( I h wcu ) I h r > <x4 t ( icr wcu ) > <x4 t ( ig wcu ) > <x4 t ( ( itx wcu ) ) > <x4 t ( ( Cc wcu ) ) > <x4 t ( Tr wcu ) > <x4 ( T c - T r ) wcu > <x4 ( Co TC) Co r > <x4 ( A Tc) A r > <x4 ( FL Tc) FL r > <x4 t ( Fk Tc) > <x4 ( I h Tc) I h r > <x4 t ( icr Tc) > <x4 t ( ig Tc) > <x4 t ( itx Tc) > <x4 t ( isu Tc) > <x4 t ( cc Tc) > <x4 t ( wcu Tc) > Variable Map Dynamic SAM for Indonesia 2-28 (Producer Prices) 2/4 Matrix Column Row Scalar Dimension # # 7 4 Factor (F) Institutions (i) 2 3 4 5 6 7 8 9 2 24 24 6 a 24 b ACCOUNT 8 Label Co A FL FK ih icr ig itx isu Cc wcu TC mco wtr Commodity 24 Co (Co A) (Co ih) (Co ig) (Co Cc)) (Co wcu) (Co TC) (Co mco) Activity 2 24 A (A Co) (A isu) (A TC) Factor Labor 3 6 FL (FL A) (FL wcu) (FL TC) (FL wtr)) Factor Capital 4 FK (Fk A) (Fk wcu) (Fk TC) (Fk wtr) Household 5 ih (ih FL) (ih Fk) (ih ih) (ih icr) (ih ig) (ih wcu) (ih TC) (ih wtr) Corporate 6 icr (icr Fk) (icr ih) (icr icr) (icr ig) (icr wcu) (icr TC) (icr wtr) Government 7 ig (ig ih) (ig icr) (ig ig) (ig itx) (ig wcu) (ig TC) (ig wtr) Tax 8 itx (itx Co) (itx wcu) (itx TC) (itx wtr) Subsidy 9 isu (isu ig) (isu TC) Capital A/C Cc (cc ih) (cc icr) (cc ig) (cc wcu) (cc TC) (cc wtr) World Cosolidated Current A/C wcu (wcu A) (wcu FL) (wcu Fk) (wcu ih) (wcu icr) (wcu ig) (wcu isu) (wcu Cc) (wcu TC) (deleteed) Total Row/Col 2 TR (TR Co) (TR A) (TR FL) (TR Fk) (TR ih) (TR icr) (TR ig) (TR itx) (TR isu) (TR Cc) (TR wcu) (TR mco) (TR wtr) Balance Bal (TC-TR) Co (TC-TR) A (TC-TR) FL (TC-TR) Fk (TC-TR) ih (TC-TR) icr (TC-TR) ig (TC-TR) itx (TC-TR) isu (TC-TR) Cc (TC-TR) wcu Import World Transfer a b 24 mco wtr (mco A) (wtr FL) (wtr Fk) (mco ih) (wtr ih) (wtr icr) (mco ig) (wtr ig) (wtr isu) (mco cc) (mco TC) (wtr TC) Consolidated # = a + b
What is a DySAM? A. Dynamic, 2. Social Accounting Matrix, 3. with extension on employment, 4. with expansion on construction sector, 5. with technology choices It is a social accounting system reflecting the socioeconomic structure of the economy It considers changes over time (linkages and employment multipliers) It includes, to some extent, behaviours of socioeconomic actors
Employment Satellite Account Mozambique Agricultura Silvicultua Pesca Industria mineira TOTAL 749 88 33 89 Sexo Homem 626 62 3 88 Mulher 285 26 2 Area residencial Urbano 4662 7 75 47 Rural 2829 7 55 42 Região Norte 55 24 2 Centro 796 62 7 8 Sul 4884 2 23 59 Provincias Niassa 333 6 3. Cabo Delgado 224 48 Maputo province 878 38 2 2 Idade 5 9 26 24 36 7 2 24 247 3 58 5 6 64 783 4 9 4 Nivel educacional Nenhum 6799 52 8 7 Primário (o ciclo) 874 85 56 Primário (2o ciclo) 522 25 44 6 Secundário e mais 43 2
Possible scenarios: Public spending trillion of Rupiah on:. Labour based road construction 2. Capital based road construction 3. Subsidies to enterprises in garment industry
INJECTION AREA # # 2 3 4 5 6 7 8 9 Account Co A FL FK ih icr ig itx isu Capital Cc wcu TC Dimension # 24 24 6 8 Commodity (24) Co <s3 (Co A)> <s3 (Co ih)> <s3 (Co ig)> <s3 FSPC (Co Cc)> <s3 (Co wcu)> <s3 (Co Tc)> Activity (24) A <s3 (A Co)> <s3 (A isu)> <s3 (A Tc)> Factor Labor (6) Factor Capital () FL FK <s3 (FL A)> <s3 (Fk A)> INJECTION AREA <s3 (FL wtr)> <s3 (Fk wtr)> <s3 (FL Tc)> <s3 (Fk Tc)> Household () ih <s3 (ih FL)> <s3 (ih Fk)> <s3 (ih ih)> <s3 (ih icr)> <s3 (ih ig)> <s3 (ih wtr)> <s3 (ih Tc)> Corporate () icr <s3 (icr Fk)> <s3 (icr ih)> <s3 (icr icr)> <s3 (icr ig)> <s3 (icr wtr)> <s3 (icr Tc)> Governmen t () ig <s3 (ig ih)> <s3 (ig icr)> <s3 (ig ig)> <s3 (ig itx)> <s3 (ig wtr)> <s3 (ig Tc)> Tax () itx <s3 (Itx Co)> <s3 (itx wtr)> <s3 (itx Tc)> Subsidy () isu <s3 (isu ig)> <s3 (isu Tc)> Capital A/C () Cc <s3 (Cc ih)> <s3 (Cc icr)> <s3 (Cc ig)> <s3 (Cc wtr)> <s3 (cc Tc)> RoW Consol idated () wcu <s3 (wcu A)> <s3 (wtr FL)> <s3 (wtr FK)> <s3 (wcu ih)> <s3 (wtr icr)> <s3 (wcu ig)> <s3 (wtr isu)> <s3 (wcu Cc)> <s3 (wcu Tc)> Total Row/Col TR <s3 (Tr Co)> <s3 (Tr A)> <s3 (Tr FL)> <s3 (Tr Fk)> <s3 (Tr ih)> <s3 (Tr icr)> <s3 (Tr ig)> <s3 (Tr itx)> <s3 (Tr isu)> <s3 (Tr Cc)> <s3 (Tr wcu)> Note: FSPC = Part of the FSP which went into infrastructure/construction investment
Employment account after simulation (incl. multipliers) Cap. Road Lab. Road Garment male 8 25 8 rural female 2 5 2 total 4 4 2 male 4 7 urban female 6 3 2 total 2 3 3 6 29 years 2 25 3 Over 29 years 25 2 Total 3 5 5
Or the other way around: calculating back from target Scenario? male rural female total male urban female total 6 29 years Million Over 29 years Total Trillion Rupiah Labour based road construction.7 Capital based road construction.5 Garment industry.3 What is the most (cost ) effective public spending to create million jobs for the youth?
SIMULATION SCENARIO DYNAMIC SAM 28 NORMAL GROWTH Forecast NORMAL GROWTH Forecast + FISCAL STIMULUS OUTPUT OUTPUT 2 Difference = IMPACT OF FISCAL STIMULUS
In billion Rp Projection for 29 Time (Year) 2 2 22 23 24 25 26 27 28 Projected 29 [c Construction r5] Rp 23,39.89 Rp 273,84.25 Rp 294,978.3 Rp 348,392.5 Rp 393,896.44 Rp 487,66.69 Rp 572,677.69 Rp 677,833.75 Rp 886,423. Rp,5,35.9 Annual increase 8.2% 8.2% 8.% 3.6% 23.68% 7.55% 8.36% 3.77% Average Percentage increase 8.47% Annual Average Percentage increase in construction capital formation until 28 is 8.47% From that data, we could have the projection for 29 which is Rp,5.3 billion In 29, there is fiscal stimulus which is Rp 2.2 trillion to the infrastructure sector.
Total Impact on Job creation 29: Economy Wide, Construction by Type and Crops JOB CREATION Employment Increase (Growth) Share ME Factor(*) ME Persons (*) ME Share Total Economy Wide 287,6 (.26%) %.2 292,8 % a RoadLI r2 25,722 (9%) 9.%.6 29,837.2% a RoadKI r2 8,539 (9%) 3.%.6 9,95 3.4% a Irrig r2 4,85 (9%).7%.6 5,627.9% a ConstRest r2,25 (9%) 3.9%.6 2,95 4.4% a Crops r5 8,95 (.22) 28.5%.8 65,24 22.3% Note: ME = Manpower Equivalence (full employment)
Intra Account Impact on Job creation 29: Economy Wide, Construction by Type and Crops JOB CREATION Employment Share ME Persons (*) Increase Total Economy Wide 3,83.% 6,79 a RoadLI r2 25,62 22.5% 29,698 a RoadKI r2 8,499 7.5% 9,859 a Irrig r2 4,829 4.2% 5,62 a ConstRest r2,73 9.7% 2,845 a Crops r5 2,34 2.%,84 Note: Intra account effect = production coefficient
Employment Shares by Location and Gender Urban Male Urban Female Rural Male Rural Female Total Urban Total Rural Total 28 Economy wide 25.4% 5.6% 36.9% 22.% 4.% 59.%.% Construction 46.9%.6% 5.8%.8% 48.4% 5.6%.%
Net cost of the construction fiscal stimulus package in 29 (Billion IDR) Injection Fiscal stimulus package Effect on Government Income Net Cost Fiscal Stimulus Package,825. 2,288.58 8,526.42
In billion Rp Top Ten Increase in Final output of Production Activity Account No Element of sector account Projected 29 Projected + Fiscal Increase in total % Increase in Stimulus Output total Output a Irrig r5 Rp47,6.72 Rp422,66.47 Rp4,564.75.9% 2 a RoadLI r5 Rp45,35.59 Rp46,722.5 Rp,586.45.9% 3 a ConstRest r5 Rp74,62.42 Rp76,52.8 Rp,98.66.9% 4 a RoadKI r5 Rp332,669.78 Rp336,36.3 Rp3,636.34.9% 5 a MiningQuarry r5 Rp64,664.4 Rp65,33.9 Rp639.5.99% 6 a ForestHunt r5 Rp45,384.4 Rp45,655.2 Rp27.82.6% 7 a Wood r5 Rp4,248.47 Rp4,792.2 Rp543.73.39% 8 a RealEstate BusinessSrv r5 Rp29,.69 Rp29,65.28 Rp963.59.33% 9 a BankInsuranceSrv r5 Rp288,96.88 Rp288,949.94 Rp853.6.3% a TradeSrv r5 Rp822,734.38 Rp825,36.88 Rp2,42.5.29% In total, the fiscal stimulus in construction sector of 29 will increase the final output in Labour Factor account for Rp 32.68 billion The five production activity element that have the highest % increase are: Irrigation, Road Labour intensive, Road Capital Intensive, and also mining quarry.
Top Ten Increase in employment creation No Element of sector account Projected 29 for total Projected + Fiscal Stimulus Employment Creation due Employment employment for total employment to Fiscak Stimulus Growth a Irrig c5 6,78 68,468 6,687.9% 2 a RoadLI c5 3,345,936 3,382,5 36,574.9% 3 a RoadKI c5,54,772,66,32,53.9% 4 a ConstRest c5,392,4,47,33 5,27.9% 5 a MiningQuarry c5,4,287,4,22 9,925.99% 6 a ForestHunt c5 735,429 739,88 4,388.6% 7 a Wood c5,66,89,666,625 6,437.39% 8 a RealEstate BusinessSrv c5 86,399 89,77 2,679.33% 9 a BankInsuranceSrv c5 72,677 722,8 2,34.3% a TradeSrv c5 8,24,584 8,77,28 52,634.29% In total, the fiscal stimulus in construction sector of 29 will increase the employment creation by 327,793 workers. Elements of activity account with the biggest increase: Irrigation, Road Labour Intensive as well as Capital intensive and also Rest of the construction, which is the construction sector itself.
Summary findings In 29, Rp 2.2 trillion of Fiscal Stimulus in Construction sector will increase the employment creation by.3%. In 29, Fiscal Stimulus in Construction sector will induce the economic growth in term of the increase the total output by.3 %.
Unit Injection in (A A) Account: Total Impact and its Decomposition