Using `ivreg2` (Instrumental Variables)

The manual 2SLS from the previous exercise produces correct coefficients but incorrect standard errors, because Stata doesn’t know that CA_hat is an estimated variable. Now we’ll use the user-written ivreg2 command, which handles both stages simultaneously, properly adjusts the standard errors, and automatically reports key diagnostic statistics (weak instrument F-stat, overidentification test).

• Using Michler_JEEM.dta (maize only), run ivreg2 with wardNGO as the instrument for CA, including the same controls as Exercise 1 (lnbasal lntop lnseed lnaream2 pdate pdate2 i.year) and clustering at rc. Use the first option to display the first-stage results. Store as iv.

1. Adapt the table code from Exercise 1 to add a third column for ivreg2 and export to Overleaf.

2. Create a coefplot comparing the CA coefficient across OLS, manual 2SLS, and ivreg2 and export to Overleaf:

* coefficient plot comparing OLS, Manual, and IV
	coefplot        (ols, label("OLS")) ///
	                (manual, label("Manual 2SLS")) ///
	                (iv, label("IV (2SLS)")), ///
	                    keep(CA CA_hat) xline(0) ///
	                    title("Effect of CA on Maize Yield: " ///
	                    "OLS vs Manual vs IV") ///
	                    xtitle("Coefficient on CA and CA_hat") ///
	                    graphregion(color(white))
	graph export    "$answ/13-iv-coefplot.png", replace

3. Is the coefficient on CA from ivreg2 identical to the one you found manually in Exercise 1?

4. Are the standard errors the same? Why or why not?