STATA Example Voter Turnout

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An example of how statistical analysis can help answer questions about voter turnout.

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STATA Example Voter Turnout

  1. 1. + Miguel Centellas Croft Visiting Assistant Professor of Political Science The University of Mississippi UNDERSTANDING Voter Turnout around the WORLD (A Brief Guide to Multivariate Regression)
  2. 2. + STEP 1: GET SOME DATA Find a source of data that is relevant to your research question. In our example, let’s look for a source that has data on voter turnout around the world—as well as other related data.
  3. 3. + Data from International IDEA Freely available on the web, along with background information.
  4. 4. + Data from International IDEA Freely available on the web, along with background information. You can download all the data. Or select specific countries, years, type of election, and other variables.
  5. 5. + STEP 2: CASE SELECTION You may use a number of criteria for case selection, but be sure you can justify your choices. In our case, let’s limit the cases to countries in Europe and the Americas—limiting it to countries that are rated as democracies (by Freedom House) and have not had a civil war recently (excludes most of the Balkans). We also limit our data to most recent legislative elections.
  6. 6. + Sample Selection: 51 Countries in Europe & the Americas Europe Albania • Austria • Belgium • Bulgaria • Czech Republic Denmark • Estonia • Finland • France • Germany Greece Hungary • Iceland • Ireland • Italy • Latvia • Lithuania Luxembourg • Malta • The Netherlands • Norway Poland • Portugal • Romania • Slovenia • Spain • Sweden Switzerland • United Kingdom The Americas Argentina • Bolivia • Brazil • Canada • Chile • Colombia Costa Rica • Dominican Republic • Ecuador • El Salvador Guatemala • Honduras • Jamaica • Mexico • Nicaragua Panama • Peru • Suriname • United States • Uruguay Venezuela
  7. 7. + Sample Selection: 51 Countries in Europe & the Americas Established Democracies Austria • Belgium • Canada • Colombia • Costa Rica Denmark • Finland • France • Germany • Iceland Ireland • Italy • Jamaica • Luxembourg • Malta The Netherlands • Norway • Sweden Switzerland United Kingdom • United States • Venezuela New Democracies Albania • Argentina • Bolivia • Brazil • Bulgaria • Chile Czech Republic • Dominican Republic • Ecuador El Salvador • Estonia • Greece • Guatemala • Honduras Hungary • Latvia • Lithuania • Mexico Nicaragua Panama • Peru • Poland • Portugal • Romania • Slovenia Spain • Suriname • Uruguay
  8. 8. + STEP 3A: SELECT THE DEPENDENT VARIABLE Your dependent variable is the object of your study, it is the thing you want to explain. In our case, we want to understand what causes changes in voter turnout across course selected countries.
  9. 9. + STEP 3B: OPERATIONALIZE THE DEPENDENT VARIABLEYou need to clearly specify how you will measure your dependent variable. In our case, we want to make sure that differences in voter turnout aren’t masked by differences in voter registration procedures. We want to know how many citizens vote. Fortunately, IDEA has a variable called Vote/VAP (percent of voting age population that voted).
  10. 10. + Voter Turnout in 51 Selected Countries Vote/VAP in Legislative Elections, 2004-2008 Venezuela Malta 0 20 40 60 80 100
  11. 11. + STEP 4: HYPOTHESES Use theory to develop testable hypotheses. Each hypothesis should link at least one INDEPENDENT variable with the dependent variable. In our case, let’s speculate about possible factors that may affect voter turnout.
  12. 12. + How Can We Explain Differences in Voter Turnout?  Hypothesis 1: Electoral System Voter turnout is a function of electoral systems. Proportional representation should drive up voter turnout because voters are less likely to “waste” votes.  Hypothesis 2: Level of Freedom Voter turnout is a function of civil & political liberties. Citizens will exercise their right to vote if they enjoy a wide range of civil rights and political liberties.  Hypothesis 3: Compulsory Voting Laws Voter turnout is a function of voting laws. Where voting is compulsory, citizens are more likely to vote.
  13. 13. + STEP 5: OPERATIONALIZE THE INDEPENDENT VARIABLES You also need to specify how you will measure your independent variables. In our case, we need to explain how we will measure changes along our three independent variables
  14. 14. + How Can We Explain Differences in Voter Turnout?  ELECTORAL SYSTEM Since we’re mostly interested in seeing if proportional representation increases voter turnout over first-past-the-post, let’s use a dummy variable (1=PR; 0=FPTP)1.  LEVEL OF FREEDOM One way to measure level of freedom is to use the Freedom House Index included in the IDEA dataset.2  COMPULSORY VOTING LAWS The IDEA dataset doesn’t include information on compulsory voting, but the website does have a list of countries with such laws. We can create a column in our spreadsheet for a dummy variable (1=compulsory voting law; 0=none). 1 Eight of our cases don’t use PR or FPTP electoral systems. 2 I transformed the FH scores so that 7 is now the highest level of freedom, and 1 is the lowest.
  15. 15. + STEP 5: DESCRIPTIVE STATISTICS Simply looking at the data may provide some evidence to support a hypothesis. In our case, let’s see if it looks like voter turnout is driven by either of our three dependent variables: electoral system, level of freedom, or compulsory voting laws.
  16. 16. + Voter Turnout in 51 Selected Countries Vote/VAP in Legislative Elections, 2004-2008 USA Jamaica CanadaFrance UK Chile Ireland Malta 0 20 40 60 80 100
  17. 17. + Voter Turnout and Level of Freedom Vote/VAP & FH Index 0 20 40 60 80 100 3.5 4 4.5 5 5.5 6 6.5 7
  18. 18. + Voter Turnout and Level of Freedom Vote/VAP and Freedom House Index Scores Peru Switzerland USA Venezuela 0 20 40 60 80 100 3.5 4 4.5 5 5.5 6 6.5 7 Expected Unexpected Outlier
  19. 19. + Voter Turnout and Compulsory Voting 0 20 40 60 80 100 Voter Turnout in Countries with Compulsory Voting 0 20 40 60 80 100 Voter Turnout in Countries without Compulsory Voting Average = 69% (STDEV = 13.7%) Average = 62% (STDEV = 16.7%)
  20. 20. + After Descriptive Statistics: What Explains Differences in Voter Turnout?  It seems PR electoral systems tend to have higher voter turnout. Although some PR countries had low voter turnout, all the FPTP countries had relatively low voter turnout.  It seems like there’s a tendency for countries with high levels of freedom to have higher voter turnout. But there are some interesting exceptions.  On average, countries with compulsory voting laws have higher voter turnout. But the range is too wide to be certain.
  21. 21. + STEP 6: REGRESSION ANALYSIS Regression analysis allows us to look at multiple variables simultaneously, to see if they have any effect on our dependent variable. In our case, let’s dump our dataset into STATA, a statistical package and run some regressions.
  22. 22. Regression Analysis Output in STATA Command Goodness of fit Statistical Significance Coefficients
  23. 23. + All You Need to Know to Interpret A Regression Analysis Output  Goodness of Fit (Adjusted R-Squared) How well a model fits a set of observations, or how much variation in the data is explained by the model. By itself, the R-Squared (R2) value is meaningless. What matters is whether a particular model has a larger R2 value than another (larger is better).  Correlation Coefficient The “slope” of the relationship between the dependent and independent variable. Every unit increase on the independent variable produces an increase equal to the coefficient.  Statistical Significance (p value) Linear regression executes a t-test for each variable. The p value represents the probability that we can trust the coefficient. A p value of 0.05 means we have a 95% confidence the coefficient is accurate.
  24. 24. + Regression Estimates for Voter Turnout Table 1. Determinants of Voter Turnout in Legislative Elections in 51 selected Latin American and European countries, 2004-2008 Independent Variables Model 1 Model 2 Model 3 Model 4 Proportional Representation * 14.711 (6.999) – – 14.365 (7.366) Freedom House Score – * 5.363 (2.461) – ** 7.373 (2.411) Compulsory Voting – – 6.571 (4.724) * 9.687 (4.551) Constant 50.662 30.115 0.850 0.848 Adjusted R-Squared 0.069 0.069 0.019 0.225 Number of Observations 47 51 49 45 Note: Coefficients reflect percentage change in voter turnout; *p < 0.05, **p < 0.01 Table 2. Determinants of Voter Turnout in Legislative Elections in 51 selected Latin American and European countries, 2004-2008
  25. 25. + STEP 6B: CHECK FOR INTERVENING EFFECTS This is an optional step, but it never hurts to run additional models that check for intervening effects. But these should be guided by theory. In our case, let’s check for regional effects, whether new democracies behave differently, and whether spoiled votes made a difference.
  26. 26. + Regression Estimates for Voter Turnout Number of Observations 47 51 49 45 Note: Coefficients reflect percentage change in voter turnout; *p < 0.05, **p < 0.01 Table 2. Determinants of Voter Turnout in Legislative Elections in 51 selected Latin American and European countries, 2004-2008 Independent Variables Model 5 Model 6 Model 7 Model 8 Proportional Representation 6.907 (10.343) 6.907 (10.343) 13.937 (7.903) 10.583 (10.197) Freedom House Score * 7.174 (3.423) * 7.174 (3.423) ** 7.476 (2.520) ** 10.125 (3.045) Compulsory Voting 10.588 (5.640) 10.588 (5.640) * 9.540 (4.693) 8.568 (4.994) Latin America -1.641 (7.296) – – – Europe – 1.641 (7.296) – – New Democracy – – 7.949 (4.867) – Spoiled Votes – – – 0.585 (0.352) Constant 9.923 8.282 0.171 -15.210 Adjusted R-Squared 0.173 0.173 0.206 0.205 Number of Observations 43 43 45 40 Note: Coefficients reflect percentage change in voter turnout; *p < 0.05, **p < 0.01
  27. 27. + After Regression Analysis: What Explains Differences in Voter Turnout?  By itself, PR does have a positive effect on voter turnout. But in multivariate analysis, it has no statistically significant effect.  By itself, a country’s FH score does have a positive effect on voter turnout. This variable also is consistently significant in multivariate models.  By itself, compulsory voting has no effect on voter turnout. However, it does have a significant, positive effect on voter turnout in new democracies.
  28. 28. + WHAT DID WE LEARN? Voters are more likely to turn out to vote when civil liberties and political rights are protected. (None of this was evident from descriptive statistics alone.)
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