Table 1.
Overconfidence and news exposure (binary measures)
Oct./Nov. | Nov./Dec. | Pooled | ||||
False | Mainstream | False | Mainstream | False | Mainstream | |
Overconfidence | 0.0609** | −0.0450 | 0.0003 | −0.0007 | 0.0569*** | −0.0415 |
(0.0231) | (0.0505) | (0.0003) | (0.0006) | (0.0186) | (0.0411) | |
Constant | −0.0815* | 0.4645*** | −0.0225 | 0.3735*** | −0.0715* | 0.4419*** |
(0.0354) | (0.1010) | (0.0498) | (0.1199) | (0.0298) | (0.0799) | |
Control variables | ||||||
0.17 | 0.11 | 0.08 | 0.17 | 0.11 | 0.11 | |
N | 1,780 | 1,780 | 767 | 767 | 2,547 | 2,547 |
Cell entries are OLS coefficients estimated using survey weights. The overconfidence measure subtracts the respondent’s actual percentile from their self-rated percentile and is rescaled to range from −1 to 1. False news exposure is coded as one if the respondent visited any such domain and zero otherwise. Mainstream news exposure is coded as one if the respondent visited any such domain and zero otherwise. All models include controls for Democrat, Republican, college education, gender, non-White racial background, age, and media diet slant. *, **, *** (two-sided).