The creation of a system 29 April 2019 Antwerp, Belgium for social - - PowerPoint PPT Presentation

▶
the creation of a system
SMART_READER_LITE
LIVE PREVIEW

The creation of a system 29 April 2019 Antwerp, Belgium for social - - PowerPoint PPT Presentation

Oct 02, 2023 283 likes •459 views

The creation of a system 29 April 2019 Antwerp, Belgium for social impact evaluation in national policy making in Lithuania Aura iauskait THE NEED FOR A SYSTEM Tax and social insurance contribution reform Increased amount of State

slide-1
SLIDE 1

The creation of a system for social impact evaluation in national policy making in Lithuania

29 April 2019 Antwerp, Belgium

Aušra Čižauskaitė

slide-2
SLIDE 2

THE NEED FOR A SYSTEM

Tax and social insurance contribution reform Increased amount of State Supported Income; Introduction of disregarded income, universal child benefit; Changes in unemployment social insurance; Etc. European Commission: “What impact on poverty rate reduction and income inequality does Lithuania expect from the recent increase in adequacy of the social safety net (minimum income benefits; unemployment social insurance benefits; pensions)?“

But...No tool to evaluate ex-ante social impact

slide-3
SLIDE 3

PROJECT OVERVIEW

The project is aimed to develop a system that would help to

  • ptimize

Ministry's forecasting, decision-making and other related processes and would help to adopt decisions related with the Ministry's areas of activity. During this project, models conforming modern realities are being developed as well as methodologies describing them. Started in January 2018; A team of 6 members;

slide-4
SLIDE 4

THE SOCIAL IMPACT EVALUATION: GOALS

EUROMOD tax-benefit model use in the Ministry Disaggregated variables

Hypothetical household tool for Lithuania Administrative data/Calibrated database

Web-interface for public society

slide-5
SLIDE 5

ADAPTING HHoT ADD-ON FOR LITHUANIA

Add-on for families with children

Household types 2016 2017 1 adult 1 child 2.3 2.6 1 adult 2 children 1.5 1.6 2 adults 1 child 9.5 11.2 2 adults 2 children 11.8 10.5 2 adults 3 children 2.5 2.3 2 adults 1 student 1.7 1.4 1 adult 0 children 17.6 17.7 2 adults 0 children 23.4 23.6

slide-6
SLIDE 6

APPLICATION OF CALIBRATION ON MICRO DATA (1)

  • The Minisry‘s goal - representative ex-ante analysis.
  • EU-SILC data lag
  • Rapid employment and demographic changes in Lithuania

EUROMOD database LT_2017_a1 Based on UDB_v10-1 Year of collection 2017 Period of collection May-June 2017 Income reference period 2016 Sampling Stratified random sampling Unit of assessment Household and individual Coverage Private households Sample size 11127 individuals, 4 944 households Response rate 73.57 %

slide-7
SLIDE 7

APPLICATION OF CALIBRATION ON MICRO DATA (2)

50 100 150 200 250 300

2009 2010 2011 2012 2013 2014 2015 2016 2017 2018

NUMBER OF UNEMPLOYED PERSONS (THOUS.), 2009 2009-2018

slide-8
SLIDE 8

APPLICATION OF CALIBRATION ON MICRO DATA (3)

2500000 2600000 2700000 2800000 2900000 3000000 3100000 3200000 3300000

2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019

RESIDENT POPULATION AT THE BEGINNING OF OF THE YEAR, 2009-2019

slide-9
SLIDE 9

APPLICATION OF CALIBRATION ON MICRO DATA (4)

Re-weigthing used by Lefebure et al. (2007) Brewer at al. (2009), Kump and Navicke, 2014):

CONTROL VARIABLES:

  • Age structure (Eurostat)
  • Sex structure (Eurostat)
  • Unemployment rates (LFS data of 2015)
  • Level of urbanization (Statistics Lithuania)
  • Household composition* (Eurostat)
  • Bounded linear and logistic method, suggested by Deville and Särndal (1992)
  • Calibration at the household level, using integrative calibration in all cases when

controls are at individual level.

slide-10
SLIDE 10

Logistic method was chosen in

  • rder to avoid

negative values

LINEAR AND LOGISTIC PROCEDURES PRODUCE SIMILAR RESULTS (5)

slide-11
SLIDE 11

KERNEL DENSITY ESTIMATE (6)

slide-12
SLIDE 12

EXIT AND ENTRY WEIGHTS (7)

slide-13
SLIDE 13

DIFFERENCE (8)

slide-14
SLIDE 14

AT-RISK-OF-POVERTY AND INEQUALITY RATES

2017orig 2017cal 2018orig 2018cal 2019orig 2019cal

60% median HDI

Total 21.98 21.67 20.40 19.63 20.44 19.66

60% median HDI

0-15 years 23.41 23.25 19.17 17.95 18.91 17.69 16-24 years 26.44 25.36 24.73 23.02 24.65 22.62 25-49 years 15.93 15.54 14.42 13.58 14.27 13.36 50-64 years 18.63 18.29 17.90 17.41 18.08 17.61 65+ years 32.17 32.33 31.74 31.59 32.30 32.28 Gini 35.98 35.82 34.90 34.63 36.77 36.61 S80/S20 6.73 6.64 6.12 6.00 6.52 6.39

slide-15
SLIDE 15

QUESTIONS AND THINGS TO CONSIDER

  • 1. HYPOTHETICAL HOUSEHOLDS IN LITHUANIA:

Optimal number of household with children Hypothetical households characteristics Indicators using hypothetical households: methodology

  • 2. DATA CALIBRATION:

Methodological advice Control variables

  • 3. OTHER
slide-16
SLIDE 16