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Abstract
This paper tests the proposition that public opinion can be measurably influenced by sunlight. Specifically, it hypothesizes that sunlight should boost Presidential approval ratings because sunlight generally makes people happy and optimistic. Analysis reveals that, in spring and winter, survey respondents are indeed more likely to indicate approval of the President on sunny days than on cloudy days, even after controlling for demographic, ideological, and geographic predictors of approval. This paper is organized into three sections. The first draws on academic literature from sociology, economics, psychology, psychiatry, and political science to explain how sunlight should affect survey response. Section 2 describes the data employed to test the proposition that sunlight boosts Presidential approval. Results and conclusions are discussed in Section 3.
Notes
The author owes a debt of gratitude Douglas Dion, Michael Lewis-Beck, Arthur Miller, Douglas Madsen, Tom Rice, Jae-On Kim, Scott Cody, and two anonymous reviewers for their comments and critiques of earlier versions of this manuscript. The author would also like to thank Fred Boehmke and Jeffrey Stout for generously providing the author unfettered access to the University of Iowa Political Science Collaboratory.
1 0 = no, 1 = yes. If the respondent answers with ‘don’t know’, the surveyor asks once, “overall, do you approve or disapprove of the way George W. Bush is handling his job as president?”
2 2005 is used as the year for this study because it is the last year for which the National Renewable Energy Laboratory compiled hourly sunlight measures.
3 Like most surveys conducted by the Pew Research Center for the People and Press, these surveys were nationally administered through a random digit sample of U.S. phone numbers. Both listed and unlisted numbers could be selected. Among landlines, only the last two digits were randomized. The remainder of the landline phone numbers placed in the interviewing sample on the basis of area code, telephone exchange, and bank number. Exchanges were represented such that the number of telephone numbers randomly sampled from within a given county was proportional to that county's share of telephone numbers in the U.S. Only banks of telephone numbers containing three or more listed residential numbers are selected. These phone numbers were released to interviewers as a smaller random sample of this larger sample in order to ensure a regionally representative sample. The cellular phone sample was drawn through systematically sampling wireless banks. Again, a random smaller sample of this larger sample of phone numbers was released to interviewers in such a way that the sample was representative both geographically and of large and small wireless companies. Finally, landline and cell phone numbers were sampled at a ratio of approximately three to one to ensure diversity of demographics and geographic response. When making contact with a respondent on a landline phone, interviewers ask to speak with “the youngest male, 18 years of age or older, who is not at home.” If no such male is home, the interviewer asks for a female instead. This helps surveys reach more younger people, who are often undersampled due to their lifestyles. When cell phones are called, interviewers simply ask if the respondent is 18 to determine eligibility. Seven attempts were made to complete interviews at each sampled telephone number, with calls staggered by time of day and day of week. Sample data are weighted for analysis. The landline sample was weighted by household size because people within larger households are less likely to be sampled. Landline and cell phone samples are weighted to account for the greater probability of people being selected from both sample. The sample was also weighted using population parameters obtained from the U.S. Census Bureau. Population parameters were compared with sample data to construct weights. Final weights were derived using an iterative technique to simultaneously balance the distributions of all weighting parameters. The March survey was administered on March 17–21, 2005, with a sampling error of ±3 points (C.I. 95%), a response rate of 21.3%, and a final N of 1,504. The June survey was administered on June 8-12, 2005, with a sampling error of ±2.9% (C.I. 95%), a response rate of 28.8%, and a final N of 1,464. The October survey was administered on October 6–10, 2005, with a sampling error of ±3 points (95% C.I.), a response rate of 21.7%, and a final N of 1,500. The December survey as administered on December 7-11, 2005, with a sampling error of ±3 points (95% C.I.) , a response rate of 26.8% and a final N of 1,501 respondents. Cases with missing data were dropped from analysis.
4 Details are omitted due to space considerations, but are available at http://www.nrel.gov/docs/fy07osti/41364.pdf.
5 “In politics TODAY, do you consider yourself a Republican, Democrat, or Independent?” Two dummy variables, Republican and Democrat, are created from responses.
6 “In general, would you describe your political views as…” 1 = Very Conservative; 2 = Conservative; 3 = Moderate; 4 = Liberal; 5 = Very Liberal.
7 Furnished by the Bureau of Labor Statistics.
8 “Last year, that is in 2004, what was your total family income from all sources, before taxes? Just stop me when I get to the right category”: 1 = Less than $10,000; 2 = $10,000 to under $20,000; 3 = $20,000 to under $30,000; 4 = $30,000 to under $40,000; 5 = $40,000 to under $50,000; 6 = $50,000 to under $75,000; 7 = $75,000 to under $100,000; 8 = $100,000 to under $150,000; 9 = $150,000 or more.
9 “Aside from weddings and funerals, how often do you attend religious services…” more than once a week (6), once a week (5), once or twice a month (4), a few times a year (3), seldom (2), or never (1)?
10 In June, October, and December, respondents were asked if they “followed” “news about the current situation in Iraq.” In March, only one half of respondents were asked this question, and so in its place their response to “protests and political changes in Lebanon” is substituted. 1 = Not at all; 2 = Not too closely; 3 = Fairly closely; 4 = Not at all closely.
11 While Latinos are not monolithic in their partisan dispositions (Cuban Americans in particular buck the trend in their stalwart support of the Republican Party), many scholars regard Latino to be a viable identity for the purposes of analysis (eg, CitationKenski & Tisinger, 2006; CitationLeal et al., 2005).
12 Whites represent the omitted category. Asians are included in the omitted category because too few were present in some surveys to facilitate a viable dummy variable of their own. Analysis was also conducted with these cases excluded from regression and had no substantive effect upon outcomes.
13 “What is the last grade or class that you completed in school?” (options are not read aloud) 1 = None, or Grades 1–8; 2 = High school incomplete (Grades 9–11); 3 = High school graduate (Grade 12 or GED certificate); 4 = Business, Technical, or vocational school AFTER high school; 5 = Some college, no 4-year degree; 6 = College graduate (B.S., B.A., or other 4-year degree); 7 = Postgraduate training or professional schooling after college (e.g., toward a master's Degree or Ph.D.; law or medical school).
14 South: AL, AR, DE, FL, GA, KY, LA, MD, MS, NC, OK, SC, TN, TX, VA, and WV; Midwest: IA, IL, IN, KS, MI, MN, MO, NE, OH, SD, and WI; Northeast: CT, DC, MS, ME, NH, NJ, NY, PA, RI, and VT.
15 All variables other than sunlight held at mean values.