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Insights and lessons from Hungarian quantitative evaluations. Balázs Váradi. Budapest Institute for Policy Analysis. www.ujszechenyiterv.gov.hu | Budapest 26 September 2013. Outline of the talk. Introduction , disclaimers

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Insights and lessonsfromHungarianquantitativeevaluations

Balázs Váradi

Budapest Institute for Policy Analysis

www.ujszechenyiterv.gov.hu | Budapest 26 September 2013


Outline of thetalk

  • Introduction, disclaimers

  • Three quantitative, quasi ex post impact assessments (on allocated grants!)

  • Tentativegeneralinsights and lessonsforthenextprogrammingperiodin Hungary and beyond

www.budapestinstitute.eu


The Budapest Institute – in brief

  • Established in 2008 by four economists

  • Independent research and analysis to support public policy making

  • Policy expertise in:

    • employment policy

    • social policy

    • education policy

    • SME development, and

    • better regulation

www.budapestinstitute.eu


Disclaimers

„Generals always fight the last war”

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Impact assessments by BI in 2012-2013

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Impact assessmentsby BI: main findings

Alas, detailsmostlyinHungarian. Forsome, youcandownload English summariesfrom: http://www.nfu.hu/programme_evaluation_2007_2013

orcontactus: [email protected]

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Impact of programmeparticipation (e.g. on probability of reemployment , on productivity)

Compareobservedoutcometo „Whatif?”

Comparetocounterfactual

Selectcontrolgroupbymatching (propensityscore) ordiff-in-diff

Control group with same observed characteristics(e.g. age, sex, education, employment history, location, sector, firm size, etc.)

The method: impactanalysis

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E.g. Impact of SROP 1.1.1

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Do not forget about the ex post evaluation of the programmes of the previous period when the pressure of ex ante evaluation fades (soon), decent ex post evaluation just starts to become possible from 2015 onwards.

Donotlet 2007-2013 programmeresultsbecomeunsustainable and crumble (e.g. financingthenewoutpatient service locations).

Lessonsfor 2014-2020 I

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Planmonitoring, datacollection and evenprogramme design (e.g. whereappropriate, randomizeselection) better, sothatreliableex post evaluationinthefuturebecomes (1) possible (2) cheap. A stitchintimesavesnine.

Be conservative: buildonwhatworks. Whereeveryoufoundsignificantpositiveeffects (e.g. employability, ambulatorycare), comparethosewiththealternatives (CB analysis) ifyoucan, makeadjustmentsbasedontheevaluations, and carryon.

Lessonsfor 2014-2020 II

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Concentrate more on long-term effects, and generally put much more weight on well-chosen impact and outcome indicators rather than on output and process ones.

Considercarefullytheequityeffectsof programme design.

Be very-verydistrustful of unconditionaltransferstofirms.

Lessonsfor 2014-2020 III

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Thankyouforyourattention

[email protected]

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