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Diff- inDiff 2

Diff- inDiff 2. 1. Are exports from i to j, the same as imports in i from j? Should they be?. . gen test= xij-mji (14 missing values generated) . sum test, detail test -------------------------------------------------------------

kennedy-howe
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Diff- inDiff 2

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  1. Diff-inDiff 2

  2. 1. Are exports from i to j, the same as imports in i from j? Should they be? . gen test=xij-mji (14 missing values generated) . sum test, detail test ------------------------------------------------------------- Percentiles Smallest 1% -2058.9 -8174.801 5% -565.3003 -8159 10% -226.45 -7875.398 Obs 10150 25% -45.79004 -7844.6 Sum of Wgt. 10150 50% -4.5 Mean 13.0583 Largest Std. Dev. 799.2009 75% 4.95 10998.57 90% 149.63 11075.08 Variance 638722 95% 521.5001 11454 Skewness 4.147469 99% 3113 15071.91 Kurtosis 68.47176

  3. 2. If you estimate the gravity equation, what part of the variation in bilateral trade is explained by this simple regression? . regltrade lrgdp1 lrgdp2 ldist1, cluster(pairid) Linear regression Number of obs = 10138 F( 3, 230) = 775.09 Prob > F = 0.0000 R-squared = 0.8840 Root MSE = .72859 (Std. Err. adjusted for 231 clusters in pairid) ------------------------------------------------------------------------------ | Robust ltrade | Coef. Std. Err. t P>|t| [95% Conf. Interval] -------------+---------------------------------------------------------------- lrgdp1 | .7751556 .0272591 28.44 0.000 .7214461 .8288651 lrgdp2 | .8136234 .0266388 30.54 0.000 .7611361 .8661107 ldist1 | -.7900897 .03726 -21.20 0.000 -.8635043 -.7166752 _cons | -4.046405 .3929865 -10.30 0.000 -4.820719 -3.272091 ------------------------------------------------------------------------------ . end of do-file

  4. Difference in Difference Estimate of the effect of the Euro on Trade: Basic Specification • Who are our treatment group? • Who are our control group? • When is the Treatment Period and When is the Post Period? • Why are we leaving in the controls? (two reasons) • What is the identification assumption? • What is our parameter of interest?

  5. DiD Estimate • . regltrade euro after euro_after lrgdp1 lrgdp2 ldist1, cluster(pairid) • Linear regression Number of obs = 10138 • F( 6, 230) = 566.84 • Prob > F = 0.0000 • R-squared = 0.8848 • Root MSE = .72625 • (Std. Err. adjusted for 231 clusters in pairid) • ------------------------------------------------------------------------------ • | Robust • ltrade | Coef. Std. Err. t P>|t| [95% Conf. Interval] • -------------+---------------------------------------------------------------- • euro | -.0712745 .0953126 -0.75 0.455 -.259072 .116523 • after | -.1566864 .0327201 -4.79 0.000 -.2211558 -.092217 • euro_after | .4343633 .0594883 7.30 0.000 .3171517 .5515749 • lrgdp1 | .7774377 .0276147 28.15 0.000 .7230276 .8318479 • lrgdp2 | .8145928 .0269346 30.24 0.000 .7615226 .867663 • ldist1 | -.7935692 .0395425 -20.07 0.000 -.8714812 -.7156573 • _cons | -4.020708 .4189466 -9.60 0.000 -4.846172 -3.195245 • ------------------------------------------------------------------------------ • . • end of do-file

  6. What does our DiD estimator look like graphically?

  7. How do the results change when we add controls?How about when we also add time FE? Why do we drop the after dummy?How about when we also include pair FE?Why do we now exclude the Euro Dummy? Language, and border dummies etc?What do we learn from this? Does this help with the identification assumption?

  8. Estimating Year-by-Year interactions? • We must exclude one of the year interactions. Why? • Suppose we excluded 1960, the first year. What do the coefficients on each years interaction (Bt) tell us? • If we are to believe the parallel trends assumption, what would we like to see?

  9. What do we see?

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