1. [3 points] Suppose a global pandemic happens and people stop going to bars, to school, to church, etc. Using our formula for a reservation match quality from the search model of dating/marriage, describe what you would expect to happen to the quality of relationships as a result. 2. [4 points] In our economic model of fertility, agents maximize utility from child services and adult goods subject to a budget constraint. Use this model to discuss what will happen to the amount of child services consumed if men's wages decline. Be sure to pay attention to both the quality and quantity components of child services. 3. [10 points] Below is a snapshot of Table 2 from Bailey (2010). You may need to refer to the paper (including the table notes) to answer the question. TABLE 2CHANGES IN BIRTH CONTROL PiLL USE IN STATES WITH SALES BANS, 1965 t0 1970 DV: 1 = Ever used the birth control pill (1) (2 3) 4) Sales ban 0.057 0.072 0.073 0.077 [0.020] [0.022] 0.023] [0.022] Sales ban x 1(1970) 0.043 0.040 0.058 0.0061 10.029] [0.030] [0.024] [0.023] Observations 6,950 6,950 6,754 6,712 Log likelihood 4,203.19 4,201.65 3,700.85 3,676.13 Additional covariates R R RACEI RACEIK Legal variablesP PX PX, AD PX, AD PX, AD TABLE 2CHANGES IN BiIrTH CoNTROL PiLL USE IN STATES WITH SALES BANs, 1965 10 1970 DV: 1 = Ever used the birth control pill (n (2) (3) 4) Sales ban 0.057 -0.072 0.073 0.077 [0.020] [0.022] [0.023] [0.022] Sales ban x 1(1970) 0.043 0.040 0.058 0.0061 [0.029] [0.030] [0.024] [0.023] Observations 6,950 6.950 6,754 6,712 Log likelihood 4,203.19 4.,201.65 3,700.85 3,676.13 Additional covariates R R RACEI RACEIK Legal variablesP PX PX, AD PX, AD PX, AD a. Interpret the coefficient on \"Sales ban\" in column (4). b. Is this coefficient statistically different from zero at the 5% significance level? How can you tell? c. How would you describe this paper's identification strategy? That is, what is Bailey doing to try to identify the causal effect of the Pill on married women's fertility? d. Give one explanation for the decline in fertility in the 1960s and 1970s (the end of the Baby Boom) other than changes to contraception/abortion access. 4. [13 points] a. Below is a snapshot of Figure 5 from Kearney and Levine (2014). How does this figure b. 16 and Pregnant/Teen Mom Ratings relate to the paper's identification strategy? B 5 + New Orleans + * # Birmingham 4 +* +* + + +* # lonesboro 3 * * * +* * : % . 2 # San Antonio * : s '0 P + . 4 Houston o \" . \""' * * & & # Austin 2 * - 0' * apt +% o + + + * * v & u * . ' \"4 - *, '~.. "' * & . * % R 'r" . U5 o", .o " o * - e o see s > +* +* + * 4t = * & oy 0e & 0 0.2 0.4 06 o8 i 12 14 i6 i8 MTV Shows, 2008/2009 In Table 3 of the paper, the authors estimate a regression where the dependent variable is the log of the tweet rate for the term \"birth control,\" and the key independent variable is the log of the tweet rate for the term \"16 and pregnant.\" The coefficient from this regression is 0.077. Interpret this coefficient. Can we reject the null hypothesis that the coefficient is zero at the 5% significance level? c. Now consider the following equation from the paper. The dependent variable is the log of the conception rate (births minus nine months) in market area j and quartert. The second through the eighth terms are interactions between 16 & Pregnant ratings and indicators for the quarters relative to the debut of the show (so for example, preQ3 is an indicator for the quarter three periods before the show debuts). In(B;) = fo + ai(RATE16P;*preQ3;) + ax(RATE16P;*preQ2;) + a;(RATE16P;*preQ1;) + BIRATEI6P, *postO1,) + PRATE16P,*postQ2;) + Ps(RATEI6P,*post(3,) + BRATE16PE*postQ4+;) + BUy + 31 + 0; + & Suppose we can reject the null hypothesis that a1 = a2 = a3 = 0. How would this affect your thinking about whether the paper has a credible identification strategy? d. Suppose that our estimate of B1=-0.05. How would you interpret this result? (Note: 16 & Pregnant ratings are measured as Nielsen points.) e. The term &; represents market-area fixed effects. Why is it important to include these fixed effects