I am plotting event study coefficients by running coefplot after reghdfe. Coefplot is a very nice community-contributed command for plotting regression results. This has worked pretty well, but I have a problem when I interact event study leads/lags with a categorical variable and try to plot coefficients from those interactions.
(Conceptually, my specification is doing what's explained in Example 1.2 in this UCLA IDRE tutorial on interactions in Stata, but interacting a group category with event study leads and lags instead of with a female indicator.)
I would like to look for heterogeneous treatment effects, between the two levels of this categorical variable, mcareimpactwq2. The variable indicating treatment is called first_it. This is my main regression:
Code:
reghdfe mort_res_pt0 i.mcareimpactwq2#i.treat_prelead_10_100 i.mcareimpactwq2#i.F(9/2).first_it ///
zero_lead1 i.mcareimpactwq2#i.L(0/20).first_it i.mcareimpactwq2#i.treat_postlag ///
i.mcareimpactwq2 ///
state*t_trend ///
$lincontrols $sqcontrols ///
if firstyear>1964 /*include treateds after 1964 and never-treateds */ ///
[aw=pop_icpsr0], absorb(fips year) cluster(fips)
forvalue i = 1/2 {
coefplot, omitted keep( `i'*mcare*#1*first_it zero_lead1 ) vertical xlabel(,angle(90)) /*xlabel(10 "0" 5 "-5" 15 "5" 20 "10" 25 "15" 30 "20")*/ xline(10) yline(0) ///
xtitle("Years from Treatment") ytitle("Effect on Mortality" "OLS Estimate and 95CI") ///
caption("Run on quartile `i' of Blue Cross Uninsured Rate")
graph export "output/23_18_heterog_fullinteract/reg05_qis`i'.png", as(png) replaceThis produces the desired graph for 2.mcareimpact#1*first_it (i.e., the coefficients for the group mcareimpact=2) but not for 1b.mcareimpact#1*first_it. (Obviously, the plot in the second graph is not interpretable because the labels are so long. I am keeping these long labels for now in order to diagnose why coefplot isn't behaving as I thought it would.)
Array Array
All the interaction coefficients for 2.mcareimpact appear, but none of the coefficients for 1b.mcareimpact# appear. I check to make sure the names of the stored values are compatible with my code:
Code:
. reghdfe, coeflegend noheader
(Std. Err. adjusted for 943 clusters in fips)
-----------------------------------------------------------------------------------------------
mort_res_pt0 | Coef. Legend
------------------------------+----------------------------------------------------------------
mcareimpactwq2#|
treat_prelead_10_100 |
1 1 | -.1309679 _b[1b.mcareimpactwq2#1.treat_prelead_10_100]
2 1 | .0781197 _b[2.mcareimpactwq2#1.treat_prelead_10_100]
|
mcareimpactwq2#F9.first_it |
1 1 | -.0113029 _b[1b.mcareimpactwq2#1F9.first_it]
2 1 | -.287819 _b[2.mcareimpactwq2#1F9.first_it]
|
mcareimpactwq2#F8.first_it |
1 1 | .1529969 _b[1b.mcareimpactwq2#1F8.first_it]
2 1 | -.0102849 _b[2.mcareimpactwq2#1F8.first_it]
|
mcareimpactwq2#F7.first_it |
1 1 | -.0435848 _b[1b.mcareimpactwq2#1F7.first_it]
2 1 | -.1261294 _b[2.mcareimpactwq2#1F7.first_it]
|
... etc..The names look like they are compatible with my code: coefplot should get the coefficients I want. So I don't know why coefplot doesn't plot the 1bmedicareimpactwq2 coefficients.
I try a simplified version:
Code:
reghdfe mort_res_pt0 i.mcareimpactwq2#i.F(2).first_it ///
i.mcareimpactwq2 ///
if firstyear>1964 /*include treateds after 1964 and never-treateds */ ///
[aw=pop_icpsr0], absorb(fips year) cluster(fips)
coefplot, nolabels vertical xlabel(,angle(90))As you can see, it plots the estimate for 2.mcareimpactwq2#F2.first_it, but not for 1bmcareimpactwq2#F2.first_it. Here are the regression results and stored values. There you can see that Stata does in fact have stored estimates for both of these:
Code:
note: 2.mcareimpactwq2 omitted because of collinearity
HDFE Linear regression Number of obs = 62,137
Absorbing 2 HDFE groups F( 2, 1106) = 0.42
Statistics robust to heteroskedasticity Prob > F = 0.6577
R-squared = 0.6761
Adj R-squared = 0.6699
Within R-sq. = 0.0000
Number of clusters (fips) = 1,107 Root MSE = 1.5525
(Std. Err. adjusted for 1,107 clusters in fips)
--------------------------------------------------------------------------------------------
| Robust
mort_res_pt0 | Coef. Std. Err. t P>|t| [95% Conf. Interval]
---------------------------+----------------------------------------------------------------
mcareimpactwq2#F2.first_it |
1 1 | .1030809 .1801463 0.57 0.567 -.2503861 .4565479
2 1 | -.0973199 .116785 -0.83 0.405 -.326465 .1318252
|
2.mcareimpactwq2 | 0 (omitted)
_cons | 9.656954 .0005526 1.7e+04 0.000 9.65587 9.658039
--------------------------------------------------------------------------------------------
Absorbed degrees of freedom:
-----------------------------------------------------+
Absorbed FE | Categories - Redundant = Num. Coefs |
-------------+---------------------------------------|
fips | 1107 1107 0 *|
year | 69 0 69 |
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation
.
end of do-fileCode:
. mat list e(b)
e(b)[1,7]
1b.mcareim~2# 1b.mcareim~2# 2o.mcareim~2# 2.mcareimp~2# 1b. 2o.
0bF2.firs~it 1F2.first_it 0bF2.firs~it 1F2.first_it mcareimpac~2 mcareimpac~2 _cons
y1 0 .1030809 0 -.09731989 0 0 9.6569545Code:
. reghdfe, coeflegend noheader
(Std. Err. adjusted for 1,107 clusters in fips)
--------------------------------------------------------------------------------------------
mort_res_pt0 | Coef. Legend
---------------------------+----------------------------------------------------------------
mcareimpactwq2#F2.first_it |
1 1 | .1030809 _b[1b.mcareimpactwq2#1F2.first_it]
2 1 | -.0973199 _b[2.mcareimpactwq2#1F2.first_it]
|
2.mcareimpactwq2 | 0 _b[2o.mcareimpactwq2]
_cons | 9.656954 _b[_cons]
--------------------------------------------------------------------------------------------
Absorbed degrees of freedom:
-----------------------------------------------------+
Absorbed FE | Categories - Redundant = Num. Coefs |
-------------+---------------------------------------|
fips | 1107 1107 0 *|
year | 69 0 69 |
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computationThanks,
Nate
Code:
* Example generated by -dataex-. To install: ssc install dataex
clear
input float mort_res_pt0 byte(mcareimpactwq2 first_it) float firstyear double fips float year double pop_icpsr0
. . 0 . 36 1962 .
. . 0 . 36 1963 .
. . 0 . 36 1964 .
. . 0 . 36 1965 .
. . 0 . 36 1966 .
. . 0 . 36 1967 .
. . 0 . 36 1968 .
. . 0 . 36 1969 .
. . 0 . 36 1970 .
. . 0 . 36 1971 .
. . 0 . 36 1972 .
. . 0 . 36 1973 .
. . 0 . 36 1974 .
. . 0 . 36 1975 .
. 2 0 . 1001 1927 19458.199999999983
. 2 0 . 1001 1928 19536.79999999999
. 2 0 . 1001 1929 19615.399999999994
. 2 0 . 1001 1930 19694
. 2 0 . 1001 1931 19822.29999999999
. 2 0 . 1001 1932 19950.600000000006
. 2 0 . 1001 1933 20078.899999999994
. 2 0 . 1001 1934 20207.199999999983
. 2 0 . 1001 1935 20335.5
. 2 0 . 1001 1936 20463.79999999999
10.635146 2 0 . 1001 1937 20592.100000000006
9.217969 2 0 . 1001 1938 20720.399999999994
9.640889 2 0 . 1001 1939 20848.699999999983
10.916718 2 0 . 1001 1940 20977
10.725726 2 0 . 1001 1941 20697.899999999907
8.913354 2 0 . 1001 1942 20418.79999999993
9.583062 2 0 . 1001 1943 20139.699999999953
10.12054 2 0 . 1001 1944 19860.599999999977
9.294487 2 0 . 1001 1945 19581.5
7.771054 2 0 . 1001 1946 19302.399999999907
9.987752 2 0 . 1001 1947 19023.29999999993
10.830017 2 0 . 1001 1948 18744.199999999953
10.127213 2 0 . 1001 1949 18465.099999999977
11.327394 2 0 . 1001 1950 18186
9.703256 2 0 . 1001 1951 18241.29999999999
10.657718 2 0 . 1001 1952 18296.59999999999
9.481307 2 0 . 1001 1953 18351.899999999994
9.724456 2 0 . 1001 1954 18407.199999999997
9.803656 2 0 . 1001 1955 18462.5
9.072352 2 0 . 1001 1956 18517.79999999999
10.122166 2 0 . 1001 1957 18573.09999999999
10.736295 2 0 . 1001 1958 18628.399999999994
8.403047 2 0 . 1001 1959 18683.699999999997
9.552271 2 0 . 1001 1960 18739
9.217497 2 0 . 1001 1961 19311.100000000093
9.807275 2 0 . 1001 1962 19883.199999999953
12.368433 2 0 . 1001 1963 20455.300000000047
11.55635 2 0 . 1001 1964 21027.40000000014
10.231718 2 0 . 1001 1965 21599.5
9.381371 2 0 . 1001 1966 22171.600000000093
9.321262 2 0 . 1001 1967 22743.699999999953
9.692998 2 0 . 1001 1968 23315.800000000047
8.018808 2 0 . 1001 1969 23819
8.272171 2 0 . 1001 1970 24661
8.979336 2 0 . 1001 1971 25503
7.585801 2 0 . 1001 1972 27156
9.032439 2 0 . 1001 1973 28453
7.552715 2 0 . 1001 1974 29261
6.595773 2 0 . 1001 1975 29716
7.828181 2 0 . 1001 1976 29892
7.354631 2 0 . 1001 1977 30457
7.124583 2 0 . 1001 1978 30879
7.020281 2 0 . 1001 1979 32050
6.859733 2 0 . 1001 1980 32217
7.097077 2 0 . 1001 1981 31985
6.523503 2 0 . 1001 1982 32038
8.328914 2 0 . 1001 1983 32057
9.088079 2 0 . 1001 1984 32130
8.062515 2 0 . 1001 1985 32248
8.542332 2 0 . 1001 1986 32895
8.386942 2 0 . 1001 1987 33266
8.23498 2 0 . 1001 1988 33637
. 2 0 . 1001 1989 33996
. 2 0 . 1001 1990 34353
. 2 0 . 1001 1991 35010
. 2 0 . 1001 1992 35985
. 2 0 . 1001 1993 36953
. 2 0 . 1001 1994 38186
. 2 0 . 1001 1995 39112
. 2 0 . 1001 1996 40207
. 2 0 . 1001 1997 41238
. 2 0 . 1001 1998 42106
. 2 0 . 1001 1999 42963
. 2 0 . 1001 2000 44021
. 2 0 . 1001 2001 44889
8.451502 2 0 . 1001 2002 45909
8.5470085 2 0 . 1001 2003 46800
7.794732 2 0 . 1001 2004 48366
9.139222 2 0 . 1001 2005 49676
8.9035225 2 0 . 1001 2006 51328
7.747352 2 0 . 1001 2007 52405
. 2 0 1956 1003 1927 26021.300000000047
. 2 0 1956 1003 1928 26777.199999999953
. 2 0 1956 1003 1929 27533.09999999986
. 2 0 1956 1003 1930 28289
. 2 0 1956 1003 1931 28692.5
end
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