class: center, middle, inverse, title-slide # How bad weather excludes marginal voters
from turning out for election ## Paper presentation at the 2021 DPSA meeting ### Søren Damsbo-Svendsen
sdas
@ifs.ku.dk
### Kasper Møller Hansen
kmh
@ifs.ku.dk
### Department of Political Science
University of Copenhagen ### 28 October 2021 --- # Turnout and weather <br>**RQ: Does bad weather on Election Day cause voters to stay home and not turn out for election?**<br> -- <br> > "It's __*a myth* that the weather matters for turnout__. If the weather is bad, maybe a few voters stay home. But today's weather is probably of little importance.".right[*Jørgen Elklit, 2005, Ritzau* (translated)] <br> -- <br> > "There are lots of things that affect turnout, but the weather does not seem to be one of them. In the Danish context, we have tried and tried to show that when it rains, people will stay at home. But the __Danes turn out no matter if it rains__ or snows".right[*Kasper M. Hansen, 2015, DR Nyheder* (translated)] --- # Why is this important? -- <br> - Frequent references in the **media** -- - Electoral turnout is a key __indicator of health and legitimacy__ of democracy -- - Small weather effects are not necessarily important *per se* - if they affect all citizens the same - → small overall reduction in turnout -- - (However, global **climate change** will make unpleasant Election day weather more likely, so it should not be dismissed) -- - Much more important: If **marginal voter groups** are more susceptible, the weather can induce **inequalities** in democratic representation --- # Contribution -- - We show that **existing research is highly mixed** in terms of design and results -- - We provide better evidence to the matter through several __methodological advantages__ -- - Validated **individual-level data** [handful of previous studies] - (Almost) **complete electorate** (with huge N) [first study] - **Panel data** with repeated measurements [first study] -- ## Key results - Rainfall ("**bad weather**") reduces probability of voting (1.1 pp per cm rain) -- - Sunshine ("**nice weather**") increases it -- - **Young (marginal) voters** are roughly five times more susceptible to weather effects --- # Theoretical background <br> - **Cost of voting** -- - Also potential __mood__ effects -- - __Meta-analysis__ of 30 studies: Average effect -0.76 percentage points per cm of rainfall --- # Marginal voters - "*those whose decisions to turn out are sensitive to exogenous factors*" (Fowler 2015: 205) -- - If the weather disproportionately reduces turnout in marginal voter groups, it **can be a major issue** for democratic representation -- - We focus on **young voters** in their (early) twenties who have (1) left their childhood home and (2) not yet established a solid voting habit -- .pull-left[ <img src="data:image/png;base64,#media/turnout_by_age.png" width="1000px" style="display: block; margin: auto;" /> ] .pull-right[ <br><br><br> .center['The rollercoaster ride of turnout and age' (descriptive turnout by age at KV13-KV17)] ] ??? Fowler, A. (2015) Regular voters, marginal voters and the election effects of turnout. *The European Political Science Association* 3(2): 205-219. The figure shows descriptive turnout rates by voter age on Election Day binned in years (18-80) and pooled across the 2013 and 2017 elections. N=7,855,649. --- # Data - Validated __voter records__ for all* eligible Danish voters at municipal elections of 2013 and 2017 .footnote[*Excluding ~1% and ~9% in non-participating municipalities, ~3% early voting, and elderly voters above age 80.] -- - 4,459,145 eligible __in-person voters__ (age 18-80) -- - Home coordinates → __individual weather exposure__ from validated DMI data __↓__ ??? ~73% eligible at both elections --- # Data - Validated __voter records__ for all* eligible Danish voters at municipal elections of 2013 and 2017 - 4,459,145 eligible __in-person voters__ (age 18-80) - Home coordinates → __individual weather exposure__ from validated DMI data __↓__ <div class="figure" style="text-align: center"> <img src="data:image/png;base64,#media/weather-stations.png" alt="Individual weather exposure from 166 DMI weather stations" width="1000px" /> <p class="caption">Individual weather exposure from 166 DMI weather stations</p> </div> ??? ~73% eligible at both elections --- # Estimation <br> - __OLS regression__ of turnout (1/0) on rainfall, sunshine, and temperature with FEs -- - Two strategies: - (1) **pooled model**: Municipality and election fixed effects -- - (2) **panel model**: Municipality, election, and __voter fixed effects__ -- - Additional __controls__: (individual) age, gender, (municipal) population size, share of non-Western immigrants, and closeness of the election --- # Results - **Rainfall** *does* decrease probability of voting (i.e., turnout) -- - Our best estimate is __-1.1 pp per cm of rainfall__ (avg: -0.76 pp per cm) -- - The rainfall effect grows with rainfall levels (i.e., is **non-linear**) -- - __Sunshine__ boosts turnout (mixed results for temperature) -- - Very strong weather effects on __young (marginal) voters ↓__ <img src="data:image/png;base64,#media/interaction_age3_panel.png" width="65%" height="65%" style="display: block; margin: auto;" /> --- class: center, middle # Thank you for your attention! <br> <img src="data:image/png;base64,#media/rain-election.png" width="50%" style="display: block; margin: auto;" /> <span style="color:grey;font-size:9pt;">Edward Linsmier—Getty Images 2014, time.com/3554884/2014-election-weather-forecast</span> --- # Appendix <img src="data:image/png;base64,#media/weather-turnout-table.png" width="65%" style="display: block; margin: auto;" /> --- # Appendix <img src="data:image/png;base64,#media/curvelinear_marginal-effects_panel.png" width="1000px" style="display: block; margin: auto;" /> --- # Appendix <img src="data:image/png;base64,#media/interaction_age3_panel.png" width="1000px" style="display: block; margin: auto;" /> --- # Appendix <img src="data:image/png;base64,#media/interaction_age3_pool.png" width="1000px" style="display: block; margin: auto;" />