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Chapter 6: Political trust in Europe

The purpose of this chapter is to use data from the European Social Survey 2010 to develop a two-level model for political trust in Europe with explanatory variables at the individual level and country level, and to interpret the findings.

People’s trust in central institutions in a society is important to the state of democracy as well as to the functioning of broader social and economic processes. High levels of political trust signify institutions that function effectively and facilitate social and economic exchange. Trust also reduces the need for control and supervision, which saves money for the government as well as for firms and other actors in the private sector (Listhaug & Ringdal 2008).

Political trust can be explained by a combination of individual, cultural and institutional factors. Trust in political institutions is the result of early-life socialization and interpersonal trust, and a consequence of the performance of the institutions themselves (Mishler & Rose 2001). For a deeper understanding of political trust, see Kenneth Newton’s ESS EduNet module on Social and Political trust.

Page 1

Preparing the data

Please start with the data file you downloaded and modified in Chapter 5. If you have deliberately skipped Chapter 5, you will have to do the following:

  1. Download data, follow these instructions

    ESS Multilevel Data is an online service that makes it possible to download ESS survey data together with data for countries and regions. You are now going to visit this site and create and download the data you need to do the exercises in chapter 6.

    We recommend you to keep the instructions on this page open in one browser window, and to open the ESS MD in another window. This enables you to switch between windows, and it will definitely be useful for those of you who are not able to memorize a whole page at one glance.

    It will be useful for your later searches for data to spend some time on ESS MD and to familiarize yourself with the resource. In order to keep the pace up, however, you can also start with these stepwise instructions:

    1. Click this link and open ESS MD in a new window.
    2. There are two gateways into the data. Please select the one called ‘ESS Multilevel Download’.
    3. If you are a registered user of ESS data, please enter your e-mail address. If you are not already registered, you will have to fill in a short form. Registration is free and fast.
    4. You will need data from Round 5 of the ESS, and you will need to download respondents from all the countries. Please tick for all the Round 5 countries and click ‘Next’.
    5. The tree shows all the available levels: a) country b) region (ess region, nuts1, nuts2 and nuts3) and c) individual (the ESS respondents). You will need data for individuals and countries for Chapters 5 and 6.
    6. Start with the individual level variables. Click the ‘+’ in front of ‘ESS5e02 - Individual level’.
      1. Click the ‘+’ in front of the variable group ‘Media and social trust’ and tick the variable:
        - ‘Most people can be trusted or you can’t be too careful’
      2. Click the ‘+’ in front of the variable group ‘Politics’ and tick the variables:
        - ‘Trust in country’s parliament’
        - ‘Trust in the legal system’
        - ‘Trust in the police’
        - ‘Trust in politicians’
        - ‘Trust in political parties’
        - ‘Satisfaction with present state of economy in country’
        - ‘Satisfaction with the national government’
        - ‘Satisfaction with the way democracy works in country’
      3. Click the ‘+’ in front of the variable group ‘Subjective well-being, social exclusion, religion...’ and tick the variables:
        - ‘How happy are you’
        - ‘How often people meet socially with friends, relatives or colleagues’
      4. Click the ‘+’ in front of the variable group ‘Gender, Year of birth and Household grid’ and tick the variables:
        - ‘Gender’
        - ‘Age of respondent’
      5. Click the ‘+’ in front of the variable group ‘Socio-demographics’ and tick the variables:
        - ‘Interviewer code, lives with husband/wife/partner’
        - ‘Interviewer code, lives with husband/wife/partner’ (there are two variables with similar labels)
        - ‘Highest level of education, ES - ISCED’
        - ‘Years of full-time education completed’
        - ‘Household’s total net income, all sources’
        - ‘Feeling about household’s current net income’
    7. Proceed with the country level variables. Click the ‘+’ in front of ‘Country level’.
      1. Click the ‘+’ in front of the variable group ‘Demography’, the ‘+’ in front of the group ‘Population size’ and tick the variable
        - ‘Population size 2008’
      2. Click the ‘+’ in front of the variable group ‘Economy’, the ‘+’ in front of the group ‘National economic accounts’ and tick the variable
        - ‘GDP per capita 2008’
      3. Click the ‘+’ in front of the variable group ‘Economy’, the ‘+’ in front of the group ‘Gini coefficient’ and tick the variable
        - ‘Gini coefficient after taxes - Total population 2005’
      4. Click the ‘+’ in front of the variable group ‘Economy’, the ‘+’ in front of the group ‘Social expenditure’ and tick the variable
        - ‘Social expenditure as a percentage of GDP 2005’
      5. Click the ‘+’ in front of the variable group ‘Composite measures’, the ‘+’ in front of the group ‘Human development index’ and tick the variable
        - ‘Human development index, HDR 2007’
      6. Click the ‘+’ in front of the variable group ‘Composite measures’, the ‘+’ in front of the group ‘Multidimensional poverty index’ and tick the variable
        - ‘Multidimensional poverty index, 2011’
      7. Click the ‘+’ in front of the variable group ‘Composite measures’, the ‘+’ in front of the group ‘Gender empowerment measure' and tick the variable
        - ‘Gender empowerment measure 2009’
      8. Click the ‘+’ in front of the variable group ‘Composite measures’, the ‘+’ in front of the group ‘Freedom in the world’ and tick the variables
        - ‘Freedom in the world - Political rights 2008’
        - ‘Freedom in the world - Civil liberties 2008’
        - ‘Freedom in the world - Status 2008’
      9. Click the ‘+’ in front of the variable group ‘Health’, the ‘+’ in front of the group ‘Life expectancy’ and tick the variable
        - ‘Life expectancy at birth (years) both sexes 2008’
      10. Click the ‘+’ in front of the variable group ‘Health’, the ‘+’ in front of the group ‘Health expenditure’ and tick the variables
        - ‘General government expenditure on health as a % of total government expenditure 2007’
        - ‘Per capita total expenditure on health 2007’
      11. Click the ‘+’ in front of the variable group ‘Crime’, the ‘+’ in front of the group ‘Corruption Perceptions Index’ and tick the variable
        - ‘Transparency International - Corruption Perceptions Index 2008’
    8. Select your preferred data format in the drop-down box at the top right-hand corner of the page and click ‘Download’. Save the file to your computer.
    9. If you find theese steps a bit too tedious, you may follow this link, select the preferred data format and download the file.
    1. Users of SPSS: Please click here, select the syntax and copy it into your syntax.

      * This syntax prepares data for chapter 6 in the EduNet module 'Multilevel models'.
      * Data downloaded from ESS MD (edition 2 of the ESS 5, http://ess.nsd.uib.no/ess/essmd/).

      Open the file you downloaded above.

      *Please remember to change the path to the location where your dataset is and, later, to write the path to the location where you would like to save your work.

      GET FILE='c:\data\ESSMDw5e2.sav'.

      * Compute age centred.

      compute agec = agea - 48.
      var labels agec 'Age centred: age- 48'.

      * Compute centered age squared.

      compute agec2 = agec*agec.
      var labels agec2 'Age centred squared'.

      * Compute dummy variable, female.

      compute female = gndr-1.
      var label female 'Female gender from gndr'.

      * eisced has seven values, recode to three levels.

      fre eduyrs.
      recode eisced (1,2=1)(3,4=2)(5,6,7=3)into edlev3.
      var labels edlev3 'Education in three level from eisced'.
      value labels edlev3 1 'Primary' 2 'Secondary' 3 'Tertiary'.

      * Create dummy indicators for the three levels of education.

      recode edlev3 (1=1)(2,3=0)intro primed.
      recode edlev3 (2=1)(1,3=0)intro seced.
      recode edlev3 (3=1)(1,2=0)intro terted.
      var labels primed 'Primary education, Edlev=1'.
      var labels seced 'Secondary education, Edlev=2'.
      var labels terted 'Tertiary education, Edlev=3'.

      * Recode hincfel - Feeling about household's current income.

      recode hincfel (1,2=1)(3,4=0)into copeinc.
      var labels copeinc 'Living comfortably or coping on present income'.

      * Recode hinctnta into hinc4.

      do if (cntry='BE').
      recode hinctnta (1 thru 5=1)(6,7=2)(8,9,10=3)(77,88,99=4)into hinc4.
      end if.
      do if (cntry='BG').
      recode hinctnta (1=1)(2 thru 6=2)(7,8,9,10=3)(77,88,99=4)into hinc4.
      end if.
      do if (cntry='CH').
      recode hinctnta (1 thru 4=1)(5,6,7=2)(8,9,10=3)(77,88,99=4)into hinc4.
      end if.
      do if (cntry='CZ').
      recode hinctnta (1 thru 3=1)(4,5,6=2)(7 thru 10=3)(77,88,99=4)into hinc4.
      end if.
      do if (cntry='CY').
      recode hinctnta (1 thru 2=1)(3,4,5=2)(6 thru 10=3)(77,88,99=4)into hinc4.
      end if.
      do if (cntry='DE').
      recode hinctnta (1 thru 3=1)(4,5,6=2)(7 thru 10=3)(77,88,99=4)into hinc4.
      end if.
      do if (cntry='DK').
      recode hinctnta (1 thru 4=1)(5,6,7=2)(8,9,10=3)(77,88,99=4)into hinc4.
      end if.
      do if (cntry='EE').
      recode hinctnta (1 thru 4=1)(5,6,7=2)(8,9,10=3)(77,88,99=4)into hinc4.
      end if.
      do if (cntry='ES').
      recode hinctnta (1 thru 3=1)(4,5,6=2)(7 thru 10=3)(77,88,99=4)into hinc4.
      end if.
      do if (cntry='FI').
      recode hinctnta (1 thru 4=1)(5,6,7=2)(8,9,10=3)(77,88,99=4)into hinc4.
      end if.
      do if (cntry='FR').
      recode hinctnta (1 thru 3=1)(4,5,6=2)(7,8,9,10=3)(77,88,99=4)into hinc4.
      end if.
      do if (cntry='GB').
      recode hinctnta (1 thru 3=1)(4,5,6,7=2)(8,9,10=3)(77,88,99=4)into hinc4.
      end if.
      do if (cntry='GR').
      recode hinctnta (1 thru 4=1)(5,6,7=2)(8,9,10=3)(77,88,99=4)into hinc4.
      end if.
      do if (cntry='HR').
      recode hinctnta (1 thru 3=1)(4,5,6=2)(7,8,9,10=3)(77,88,99=4)into hinc4.
      end if.
      do if (cntry='HU').
      recode hinctnta (1 thru 3=1)(4,5,6=2)(7,8,9,10=3)(77,88,99=4)into hinc4.
      end if.
      do if (cntry='IE').
      recode hinctnta (1,2=1)(3,4,5=2)(6,7,8,9,10=3)(77,88,99=4)into hinc4.
      end if.
      do if (cntry='IL').
      recode hinctnta (1 thru 4=1)(5,6=2)(7,8,9,10=3)(77,88,99=4)into hinc4.
      end if.
      do if (cntry='NL').
      recode hinctnta (1 thru 4=1)(5,6,7=2)(8,9,10=3)(77,88,99=4)into hinc4.
      end if.
      do if (cntry='NO').
      recode hinctnta (1 thru 3=1)(4,5,6=2)(7,8,9,10=3)(77,88,99=4)into hinc4.
      end if.
      do if (cntry='PL').
      recode hinctnta (1 thru 3=1)(4,5,6=2)(7,8,9,10=3)(77,88,99=4)into hinc4.
      end if.
      do if (cntry='RU').
      recode hinctnta (1 thru 3=1)(4,5,6=2)(7,8,9,10=3)(77,88,99=4)into hinc4.
      end if.
      do if (cntry='SE').
      recode hinctnta (1 thru 4=1)(5,6,7,8=2)(9,10=3)(77,88,99=4)into hinc4.
      end if.
      do if (cntry='SI').
      recode hinctnta (1 thru 3=1)(4,5,6=2)(7,8,9,10=3)(77,88,99=4)into hinc4.
      end if.
      do if (cntry='SK').
      recode hinctnta (1 thru 4=1)(5,6,7=2)(8,9,10=3)(77,88,99=4)into hinc4.
      end if.
      do if (cntry='TR').
      recode hinctnta (1,2=1)(3,4,5=2)(6,7,8,9,10=3)(77,88,99=4)into hinc4.
      end if.
      do if (cntry='UA').
      recode hinctnta (1,2=1)(3,4,5=2)(6,7,8,9,10=3)(77,88,99=4)into hinc4.
      end if.
      var labels hinc4 'Household income in 3 cat + missing from hinctnta'.
      value labels hinc4 1 'Low' 2 'Medium' 3 'High' 4 'Missing'.

      * Recode hinc4 into dummies.

      recode hinc4 (1=1)(2,3,4=0)into lowinc.
      recode hinc4 (2=1)(1,3,4=0)into medinc.
      recode hinc4 (3=1)(1,2,4=0)into highinc.
      recode hinc4 (4=1)(1,2,3=0)into missinc.
      var labels lowinc 'Low household income, hinc4=1'.
      var labels medinc 'Medium householdincome, hinc4=2'.
      var labels highinc 'High household income, hinc4=3'.
      var labels missinc 'Missing income, hinc4=4'.

      * Recode iscpart2 into cohab, living with husband, wife, partner or cohabiting.

      recode icpart2 (1=1)(2=0)into cohab.
      var labels cohab 'Living with husband wife partner or cohabiting'.

      * Recode schmeet into social, meeting socially.

      recode sclmeet (1,2,3,4,5=0)(6,7=1)into social.
      var labels social 'Meet sdeveral times a week with friends, relatives collegues'.

      * Recode cntry into welstate.

      RECODE cntry ('SE', 'NO', 'DK', 'FI' =1) ('IE', 'GB'=2) ('NL','LU', 'DE'=3)('CH', 'BE','AT', 'FR'=3)('ES','IL','IT', 'GR', 'TR','PT', 'CY'=4) ('RU', 'EE', 'BG','CZ','PL','HR', 'HU','LV','RO','SI','SK','UA'=5) INTO welstate .
      var labels welstate 'Welfare state classification based on Ferrera'.
      value labels welstate 1 'Nordic' 2 'Liberal' 3 'Continental' 4 'Southern' 5 'Eastern'.

      *Save the changes.

      SAVE OUTFILE='c:\data\Multilevel.sav'
      /COMPRESSED.
    2. Click here to open a Stata syntax that will modify the file

      * This syntax prepares data for chapter 6 in the EduNet module 'Multilevel models'.
      * Data downloaded from ESS MD (edition 2 of the ESS 5, http://ess.nsd.uib.no/ess/essmd/).

      Open the file you downloaded above.

      *Please remember to change the path to the location where your dataset is and, later, to write the path to the location where you would like to save your work.

      use "C:\data\Multilevel.dta", clear

      * Compute age centred.

      generate agec = agea - 48
      label variable agec "Age centered_ age- 48"

      * Compute centered age squared.

      generate agec2 = agec*agec
      label variable agec2 "Age centered squared"

      * Compute dummy variable, female.

      gen female = gndr-1
      label variable female "Female gnder from gndr"

      * eisced has seven values, recode to three levels.

      fre eduyrs.
      recode eisced (1,2=1)(3,4=2)(5,6,7=3)into edlev3.
      var labels edlev3 'Education in three level from eisced'.
      value labels edlev3 1 'Primary' 2 'Secondary' 3 'Tertiary'.

      * Create dummy indicators for the three levels of education.

      recode edlev3 (1=1) (2/3=0), gen(primed)
      recode edlev3 (2=1) (1/3=0), gen(seced)
      recode edlev3 (3=1) (1/2=0), gen(terted)
      label variable primed "Primary education, Edlev=1"
      label variable seced "Secondary education, Edlev=2"
      label variable terted "Tertiary education, Edlev=3"

      * Recode hincfel - Feeling about household's current income.

      recode hincfel (1/2=1) (3/4=0), gen(copeinc)
      label var copeinc "Living comfortably or coping on present income"

      * Recode hinctnta into hinc4.

      recode hinctnta (1/5=1) (6/7=2) (8/10=3) (.a .b .c . =4) if cntry == "BE", gen (hincBE)
      gen hinc4 = hincBE
      drop hincBE


      recode hinctnta (1=1) (2/6=2) (7/10=3) (.a .b .c . =4) if cntry == "BG", gen (hincBG)
      replace hinc4 = hincBG if hinc4 ==.
      drop hincBG


      recode hinctnta (1/4=1) (5/7=2) (8/10=3) (.a .b .c . =4) if cntry == "CH", gen (hincCH)
      replace hinc4 = hincCH if hinc4 ==.
      drop hincCH


      recode hinctnta (1/3=1) (4/6=2) (7/10=3) (.a .b .c . =4) if cntry == "CZ", gen (hincCZ)
      replace hinc4 = hincCZ if hinc4 ==.
      drop hincCZ


      recode hinctnta (1/2=1) (3/5=2) (6/10=3) (.a .b .c . =4) if cntry == "CY", gen (hincCY)
      replace hinc4 = hincCY if hinc4 ==.
      drop hincCY


      recode hinctnta (1/3=1) (4/6=2) (7/10=3) (.a .b .c . =4) if cntry == "DE", gen (hincDE)
      replace hinc4 = hincDE if hinc4 ==.
      drop hincDE


      recode hinctnta (1/4=1) (5/7=2) (8/10=3) (.a .b .c . =4) if cntry == "DK", gen (hincDK)
      replace hinc4 = hincDK if hinc4 ==.
      drop hincDK


      recode hinctnta (1/4=1) (5/7=2) (8/10=3) (.a .b .c . =4) if cntry == "EE", gen (hincEE)
      replace hinc4 = hincEE if hinc4 ==.
      drop hincEE


      recode hinctnta (1/3=1) (4/6=2) (7/10=3) (.a .b .c . =4) if cntry == "ES", gen (hincES)
      replace hinc4 = hincES if hinc4 ==.
      drop hincES


      recode hinctnta (1/4=1) (5/7=2) (8/10=3) (.a .b .c . =4) if cntry == "FI", gen (hincFI)
      replace hinc4 = hincFI if hinc4 ==.
      drop hincFI


      recode hinctnta (1/3=1) (4/6=2) (7/10=3) (.a .b .c . =4) if cntry == "FR", gen (hincFR)
      replace hinc4 = hincFR if hinc4 ==.
      drop hincFR


      recode hinctnta (1/3=1) (4/7=2) (8/10=3) (.a .b .c . =4) if cntry == "GB", gen (hincGB)
      replace hinc4 = hincGB if hinc4 ==.
      drop hincGB


      recode hinctnta (1/4=1) (5/7=2) (8/10=3) (.a .b .c . =4) if cntry == "GR", gen (hincGR)
      replace hinc4 = hincGR if hinc4 ==.
      drop hincGR


      recode hinctnta (1/3=1) (4/6=2) (7/10=3) (.a .b .c . =4) if cntry == "HR", gen (hincHR)
      replace hinc4 = hincHR if hinc4 ==.
      drop hincHR


      recode hinctnta (1/3=1) (4/6=2) (7/10=3) (.a .b .c . =4) if cntry == "HU", gen (hincHU)
      replace hinc4 = hincHU if hinc4 ==.
      drop hincHU


      recode hinctnta (1/2=1) (3/5=2) (6/10=3) (.a .b .c . =4) if cntry == "IE", gen (hincIE)
      replace hinc4 = hincIE if hinc4 ==.
      drop hincIE


      recode hinctnta (1/4=1) (5/6=2) (7/10=3) (.a .b .c . =4) if cntry == "IL", gen (hincIL)
      replace hinc4 = hincIL if hinc4 ==.
      drop hincIL


      recode hinctnta (1/4=1) (5/7=2) (8/10=3) (.a .b .c . =4) if cntry == "NL", gen (hincNL)
      replace hinc4 = hincNL if hinc4 ==.
      drop hincNL


      recode hinctnta (1/3=1) (4/6=2) (7/10=3) (.a .b .c . =4) if cntry == "NO", gen (hincNO)
      replace hinc4 = hincNO if hinc4 ==.
      drop hincNO


      recode hinctnta (1/3=1) (4/6=2) (7/10=3) (.a .b .c . =4) if cntry == "PL", gen (hincPL)
      replace hinc4 = hincPL if hinc4 ==.
      drop hincPL


      recode hinctnta (1/3=1) (4/6=2) (7/10=3) (.a .b .c . =4) if cntry == "RU", gen (hincRU)
      replace hinc4 = hincRU if hinc4 ==.
      drop hincRU


      recode hinctnta (1/4=1) (5/8=2) (9/10=3) (.a .b .c . =4) if cntry == "SE", gen (hincSE)
      replace hinc4 = hincSE if hinc4 ==.
      drop hincSE


      recode hinctnta (1/3=1) (4/6=2) (7/10=3) (.a .b .c . =4) if cntry == "SI", gen (hincSI)
      replace hinc4 = hincSI if hinc4 ==.
      drop hincSI


      recode hinctnta (1/4=1) (5/7=2) (8/10=3) (.a .b .c . =4) if cntry == "SK", gen (hincSK)
      replace hinc4 = hincSK if hinc4 ==.
      drop hincSK


      recode hinctnta (1/2=1) (3/5=2) (6/10=3) (.a .b .c . =4) if cntry == "UA", gen (hincUA)
      replace hinc4 = hincUA if hinc4 ==.
      drop hincUA


      label var hinc4 "Household income in 3 cat + missing from hinctnta"
      label define hinc4 1 'Low' 2 'Medium' 3 'High' 4 'Missing'
      label values hinc4 hinc4

      * Recode hinc4 into dummies.

      recode hinc4 (1=1) (2/4=0), gen (lowinc)
      recode hinc4 (2=1) (1 3/4=0), gen (medinc)
      recode hinc4 (3=1) (1/2 4=0), gen (highinc)
      recode hinc4 (4=1) (1/3=0), gen (missinc)
      lab var lowinc "Low household income, hinc4=1"
      lab var medinc "Medium household income, hinc4=2"
      lab var highinc "High household income, hinc4=3"
      lab var missinc "Missing income, hinc4=4"

      * Recode iscpart2 into cohab, living with husband, wife, partner or cohabiting.

      recode icpart2 (1=1) (2=0), gen (cohab)
      lab var cohab "Living with husband wife partner or cohabiting"

      * Recode schmeet into social, meeting socially.

      recode sclmeet (1/5=0) (6/7=1), gen (social)
      lab var social "Meet sdeveral times a week with friends, relatives collegues"

      * Recode cntry into welstate.

      encode cntry, gen (cntry_num)
      *
      recode cntry_num (23 19 7 10 = 1)(16 12=2) (18 6=3)(3 1 11=3)(9 17 13 21 4 = 4)(22 8 2 5 20 14 15 24 25 26=5),
      *
      gen(welstate)
      lab var welstate "Welfare state classification based on Ferrera"
      * Define a label group*
      label define welstate 1 'Nordic' 2 'Liberal' 3 'Continental' 4 'Southern' 5 'Eastern'
      *Assign the label group to the variable*
      label value welstate welstate

      *Save the changes.

      SAVE "c:\data\Multilevel.dta", replace
      /COMPRESSED.

The dependent variable

All rounds of the ESS include the following set of questions on trust in institutions:

Using this card, please tell me on a scale from 0-10 how much you personally trust each of the institutions I read out; 0 means you do not trust an institution at all, and 10 means you have complete trust. Firstly, trust in...
... the country's parliament (B4)
... the legal system (B5)
... the police (B6)
... politicians (B7).
... political parties (B8)
... the European Parliament (B9)
... the United Nations (B10)

The explanatory variables

The variables are either already present in the file or were created in Chapter 5/the syntax above. We want to have the following variables available for the analysis:

Demographic variables: age, age squared, centred age, gender as female.

Socioeconomic variables: years of education, level of education, evaluation of current income.

Years of education (eduyrs) can be used directly, although the variable is not the best indicator of educational attainment in the ESS. It also has some problematic high values. The best indicator of education is eisced, which we recoded into three levels: primary, secondary and tertiary. We also created dummy indicators for the three levels.

SPSS syntax

* Chapter 6 Political trust.
* Data downloaded from ESS MD.

*Open the file you downloaded and modyfied.
*Please remember to change the path to the location where your dataset is and, later, to write the path to the location where you would like to save your work.

GET FILE='c:\data\Multilevel.sav'.

* Dependent variable: poltrust: trust in electoral system.

fre trstprl trstplt trstprt.
compute poltrust = mean.3 (trstprl, trstplt, trstprt).
var labels poltrust 'Trust in the electoral system, mean of trstprl trstplt trstprt'.
fre poltrust.
corr trstprl trstplt trstprt with poltrust.

*Demographic variables: age, gender.

desc agec agec2.
fre female gndr.

* Education.

fre eduyrs eisced edlev3 primed seced terted.

* Evaluation of current income.
* hincfel - Feeling about household's current income.

fre copeinc hincfel.

* System performance: satisfaction with the economy, with the government and with democracy may be used in their original form.

fre stfeco stfgov stfdem.

* social or interpersonal trust may be used in its original form.

fre ppltrst.

* A variable counting the number of missing codes for the set of variables.

count nmiss = poltrust agec agec2 female seced terted copeinc stfeco stfgov stfdem ppltrst (missing).
var labels nmiss 'Number of missing for model variables'.
fre nmiss.

*Save the changes you have made.
*Please remember to change the path to the location where you would like to save the dataset.

SAVE OUTFILE='c:\data\Multilevel.sav'
/COMPRESSED.
Stata syntax

* Chapter 6 Political trust*
* Data downloaded from ESS MD*

*Open the file you downloaded and modyfied*
*Please remember to change the path to the location where your dataset is and, later, to write the path to the location where you would like to save your work*

use "C:\Users\par\Desktop\Multilevel.dta", clear

* Dependent variable: poltrust: trust in electoral system*

tab1 trstprl trstplt trstprt.
by ESS5_id, sort: egen mean_trstprl=mean(trstprl)
by ESS5_id, sort: egen mean_trstplt=mean(trstplt)
by ESS5_id, sort: egen mean_trstprt=mean(trstprt)
gen poltrust = (mean_trstprl + mean_trstplt + mean_trstprt)/3
lab var poltrust "Trust in the electoral system, mean of trstprl trstplt trstprt"
tab poltrust.
corr poltrust trstprl trstplt trstprt
*In order to run the Perason r's correlation you need to use the pwcorr command:*
pwcorr poltrust trstprl trstplt trstprt, sig obs

*Demographic variables: age, gender*

sum agec agec2.
tab1 female gndr.

* Education*

tab1 eduyrs eisced edlev3 primed seced terted.

* Evaluation of current income*
* hincfel - Feeling about household's current income*

tab1 copeinc hincfel.

* System performance: satisfaction with the economy, with the government and with democracy may be used in their original form*

tab1 stfeco stfgov stfdem.

* social or interpersonal trust may be used in its original form*

tab ppltrst.

* A variable counting the number of missing codes for the set of variables*

* In order to look at the distribution of missing values across observations you need to innstall the function rmiss2. Start by typing findit rmiss2 and install the small program in your version of Stata*

findit rmiss2
egen nmiss=rmiss2 (poltrust agec agec2 female seced terted copeinc stfeco stfgov stfdem ppltrst)
lab var nmiss "Number of missing for model variables"
tab nmiss.

*Save the changes you have made*
*Please remember to change the path to the location where you would like to save the dataset*

save "c:\data\Multilevel.dta", replace
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Developing the model

Complete the steps in the modelling process and develop a final model for interpretation with explanatory variables at both levels. Summarize the main results.

  1. The first step is to estimate the null model and compute the intraclass correlation.
  2. The second step is to develop the full level 1 model, normally the individual level model.
  3. The third step is to develop the final model with level 2 explanatory variables.
SPSS solution
** The null model.
mixed poltrust with agec agec2 female seced terted copeinc stfeco stfgov stfdem ppltrst
/fixed =
/method = ml
/random = intercept | subject(cntry)
/print = solution.

** Full individual level model.
mixed poltrust with agec agec2 female seced terted copeinc stfeco stfgov stfdem ppltrst
/fixed = agec agec2 female seced terted copeinc stfeco stfgov stfdem ppltrst
/method = ml
/random = intercept | subject(cntry)
/print = solution.

** Models with country level variables HDI + CPI **.
mixed poltrust with agec agec2 female seced terted copeinc stfeco stfgov stfdem ppltrst c_hdihdr_2009 c_ticpi_2008
/fixed = agec agec2 female seced terted copeinc stfeco stfgov stfdem ppltrst c_hdihdr_2009 c_ticpi_2008
/method = ml
/random = intercept | subject(cntry)
/print = solution.
Stata solution
** The null model
xtmixed poltrust || cntry: , mle variance, if nmiss==0

** Full individual level model
xtmixed poltrust agec agec2 female seced terted copeinc stfeco stfgov stfdem ppltrst || cntry: , mle variance, if nmiss==0
** Models with country level variables HDI + CPI
xtmixed poltrust agec agec2 female seced terted copeinc stfeco stfgov stfdem ppltrst c_hdihdr_2009 c_ticpi_2008 || cntry: , mle variance, if nmiss==0
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Summary of the main results

First, the null model indicates that about 25 per cent of the variation in political trust stems from variation between countries. It is obvious that a multilevel model is needed. The full individual level model with age, gender, levels of education, assessment of income, satisfaction with the economy, with the government, with democracy, and social trust explains about 38 per cent of the individual variance and 86 per cent of the country level variance. Thus, most of the differences between the countries can be explained by differences in the composition of the individual level variables. Adding the Human Development Index and the Corruption Perception Index increases the explanation of the country level variation to 95 per cent. The increase is entirely due to the CPI.

The demographics and levels of education have moderate effects on political trust. Trust increases with age, women trust political institutions slightly more than men, and those with university level education show more political trust than people with only primary education. Of the performance variables, satisfaction with the government and satisfaction with democracy are the most important ones in relation to political trust. Social trust is important in that the difference between low and high social trust means a difference of one point in political trust. The CPI is by far the most important country level variable. An increase of one point on the CPI, i.e. one point less corrupt, increases political trust by 0.2 points. That means that the maximal effect of the CPI is 7*0.218 = 1.53.

Table 6.1. Estimates of random parameters and explained variances from three models
Explained variance Null model Full individual model + HDI and CPI
Individual level variance 3.934 2.432 2.432
Between-country variance 1.281 0.177 0.067
Explained individual level variance 0.000 0.382
Explained country level variance 0.000 0.862 0.948
Intraclass correlation ICC 0.246

Table 6.2. Estimates of fixed parameters
Variable names B S.e. t Sig.
Intercept 1.156 1.811 0.639 0.529
agec Age in years, centred 0.002 0.000 4.083 0.000
agec2 Age centred squared 0.000 0.000 8.616 0.000
female Female gender 0.055 0.015 3.715 0.000
Primary education (reference category) 0.000
seced Secondary education 0.019 0.020 0.934 0.351
Terted Tertiary education 0.135 0.021 6.472 0.000
Copeinc Coping well on present income 0.037 0.018 2.078 0.038
stfeco Satisfied with the state of the economy 0.090 0.005 19.434 0.000
stfgov Satisfied with the government 0.326 0.004 73.205 0.000
stfdem Satisfied with democracy 0.183 0.004 44.334 0.000
ppltrst Most people can be trusted 0.105 0.003 30.786 0.000
c_hdihdr_2009 Human Development Index -2.448 2.309 -1.060 0.299
c_ticpi_2008 Corruption Perception Index (high=clean) 0.218 0.056 3.889 0.001
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