Hi!
I'm Daniel, and I am attempting, for the first time, to use an instrument variable (IV) derived from the interaction between two variables. I'm employing 'ivreg2,' and I am not entirely certain if I am proceeding correctly. Let me provide you with some context.
I'm estimating the impact of a mother's education on infant mortality. To achieve this, I am leveraging a classroom construction program that had significant effects on women's education. Infant mortality is measured as the probability of having one deceased child, while exposure to the program is gauged by the interaction between 'treated_cohort' (1 if the cohort was affected) and the number of new classes constructed per 10,000 population in the vicinity (within 5 km) of the observations. Below is my sample:
Key: After confirming the significant effects of this program on women's education (years of education), I intend to employ two-stage least squares (2SLS) to estimate the impact of the educational advancements resulting from the classroom construction program on infant mortality. I'm utilizing the following equation:
So I'm intrumentalizing women's education using an interaction. First I would like to know if in terms of coding, and considering that is an interaction I'm doing it right. Second, I suspect this is not running well because of the following outcome message:
Warning: estimated covariance matrix of moment conditions not of full rank.
overidentification statistic not reported, and standard errors and
model tests should be interpreted with caution.
Possible causes:
number of clusters insufficient to calculate robust covariance matrix
singleton dummy variable (dummy with one 1 and N-1 0s or vice versa)
partial option may address problem.
Also, and more Importantly I get this at the end of the ivreg2 outcome:
It should be stressed that I don't have colinearity issues when I use reg and check the effect of the interaction on women's education, everything works pretty well. In conclusion, I'm certain I may have overlooked something, but I'm not sure what it is. I apologize if I've provided too many details, and I genuinely appreciate your assistance. I have tried to understand with help ivreg2 what happens but it's not very clear for me. Thank you in advance.
Daniel.
I'm Daniel, and I am attempting, for the first time, to use an instrument variable (IV) derived from the interaction between two variables. I'm employing 'ivreg2,' and I am not entirely certain if I am proceeding correctly. Let me provide you with some context.
I'm estimating the impact of a mother's education on infant mortality. To achieve this, I am leveraging a classroom construction program that had significant effects on women's education. Infant mortality is measured as the probability of having one deceased child, while exposure to the program is gauged by the interaction between 'treated_cohort' (1 if the cohort was affected) and the number of new classes constructed per 10,000 population in the vicinity (within 5 km) of the observations. Below is my sample:
Code:
* Example generated by -dataex-. For more info, type help dataex clear input float infant_mort byte education_years float(treatment_cohort newclassrooms) 0 0 . 32.692307 1 0 . 21.153847 0 0 . 0 0 0 1 32.692307 . 0 . 21.153847 . 13 1 21.153847 . 0 0 21.153847 . 0 . 32.692307 0 0 . 9.615385 . 0 . 21.153847 0 2 1 21.153847 1 4 . 21.153847 0 0 . 21.153847 0 0 . 32.692307 0 5 1 21.153847 0 0 1 0 . 0 0 19.23077 0 0 . 21.153847 . 7 1 11.538462 . 0 . 11.538462 0 9 . 21.153847 . 0 0 11.538462 0 0 . 21.153847 0 0 . 21.153847 0 0 1 21.153847 . 1 . 21.153847 1 0 . 11.538462 0 0 . 21.153847 . 5 1 11.538462 0 0 0 19.23077 0 0 . 32.692307 0 0 . 0 0 0 1 11.538462 1 0 1 21.153847 0 5 . 32.692307 end label values infant_mort infant_mort label def infant_mort 0 "all alive", modify label def infant_mort 1 "dead child", modify label values education_years V133 label values treatment_cohort treatedcohorts label def treatedcohorts 0 "pre", modify label def treatedcohorts 1 "post", modify
Code:
ivreg2 infant_mort (education_years=c.newclassrooms#treatment_cohort) newclassrooms i.ethnicity i.religion i.rural i.cohort i.commune4 i.survey2 if questionnaire=="women", cluster(id_geo)
Warning: estimated covariance matrix of moment conditions not of full rank.
overidentification statistic not reported, and standard errors and
model tests should be interpreted with caution.
Possible causes:
number of clusters insufficient to calculate robust covariance matrix
singleton dummy variable (dummy with one 1 and N-1 0s or vice versa)
partial option may address problem.
Also, and more Importantly I get this at the end of the ivreg2 outcome:
Code:
Instrumented: education_years
Included instruments: newclassrooms 2.ethnicity 3.ethnicity
4.ethnicity 5.ethnicity 6.ethnicity 10.ethnicity
11.ethnicity 2.religion 3.religion 4.religion 96.religion
2.rural 1977.cohort 1978.cohort 1979.cohort 1980.cohort
1981.cohort 1982.cohort 1983.cohort 1984.cohort
1985.cohort 1990.cohort 1991.cohort 1992.cohort
1993.cohort 1994.cohort 1995.cohort 1996.cohort
1997.cohort 1998.cohort 1999.cohort 2.commune4 3.commune4
4.commune4 5.commune4 6.commune4 7.commune4 8.commune4
9.commune4 10.commune4 11.commune4 12.commune4 13.commune4
14.commune4 15.commune4 16.commune4 17.commune4
18.commune4 19.commune4 20.commune4 21.commune4
22.commune4 23.commune4 24.commune4 25.commune4
26.commune4 27.commune4 28.commune4 29.commune4
30.commune4 31.commune4 32.commune4 33.commune4
34.commune4 35.commune4 36.commune4 37.commune4
38.commune4 39.commune4 40.commune4 41.commune4
42.commune4 43.commune4 44.commune4 45.commune4
46.commune4 47.commune4 48.commune4 49.commune4
50.commune4 51.commune4 52.commune4 53.commune4
54.commune4 55.commune4 56.commune4 57.commune4
58.commune4 59.commune4 60.commune4 61.commune4
62.commune4 63.commune4 64.commune4 65.commune4
66.commune4 67.commune4 68.commune4 69.commune4
70.commune4 71.commune4 72.commune4 73.commune4
74.commune4 75.commune4 76.commune4 77.commune4
78.commune4 79.commune4 80.commune4 81.commune4
82.commune4 83.commune4 84.commune4 85.commune4
86.commune4 87.commune4 88.commune4 89.commune4
90.commune4 91.commune4 92.commune4 93.commune4
94.commune4 95.commune4 96.commune4 97.commune4
98.commune4 99.commune4 100.commune4 101.commune4
102.commune4 103.commune4 104.commune4 105.commune4
106.commune4 107.commune4 108.commune4 109.commune4
110.commune4 111.commune4 112.commune4 113.commune4
114.commune4 115.commune4 116.commune4 117.commune4
118.commune4 119.commune4 120.commune4 121.commune4
122.commune4 123.commune4 124.commune4 125.commune4
126.commune4 127.commune4 128.commune4 129.commune4
130.commune4 131.commune4 132.commune4 133.commune4
134.commune4 135.commune4 136.commune4 137.commune4
138.commune4 139.commune4 140.commune4 141.commune4
142.commune4 143.commune4 144.commune4 145.commune4
146.commune4 147.commune4 148.commune4 149.commune4
150.commune4 151.commune4 152.commune4 153.commune4
154.commune4 155.commune4 156.commune4 157.commune4
158.commune4 159.commune4 160.commune4 161.commune4
162.commune4 163.commune4 164.commune4 165.commune4
166.commune4 167.commune4 168.commune4 169.commune4
170.commune4 171.commune4 172.commune4 173.commune4
174.commune4 175.commune4 176.commune4 177.commune4
178.commune4 179.commune4 180.commune4 181.commune4
182.commune4 183.commune4 184.commune4 185.commune4
186.commune4 187.commune4 188.commune4 189.commune4
190.commune4 191.commune4 192.commune4 193.commune4
194.commune4 195.commune4 196.commune4 197.commune4
198.commune4 199.commune4 200.commune4 201.commune4
202.commune4 203.commune4 204.commune4 205.commune4
206.commune4 207.commune4 208.commune4 209.commune4
210.commune4 211.commune4 212.commune4 213.commune4
214.commune4 215.commune4 216.commune4 217.commune4
218.commune4 219.commune4 220.commune4 221.commune4
222.commune4 223.commune4 224.commune4 225.commune4
226.commune4 227.commune4 228.commune4 229.commune4
230.commune4 231.commune4 232.commune4 233.commune4
234.commune4 235.commune4 236.commune4 237.commune4
238.commune4 239.commune4 240.commune4 241.commune4
242.commune4 243.commune4 244.commune4 245.commune4
246.commune4 247.commune4 248.commune4 249.commune4
250.commune4 251.commune4 252.commune4 253.commune4
254.commune4 255.commune4 256.commune4 257.commune4
258.commune4 259.commune4 260.commune4 261.commune4
262.commune4 263.commune4 264.commune4 265.commune4
266.commune4 267.commune4 268.commune4 269.commune4
270.commune4 271.commune4 272.commune4 273.commune4
274.commune4 275.commune4 276.commune4 277.commune4
278.commune4 279.commune4 280.commune4 281.commune4
282.commune4 283.commune4 284.commune4 285.commune4
286.commune4 287.commune4 288.commune4 289.commune4
290.commune4 291.commune4 292.commune4 293.commune4
294.commune4 295.commune4 296.commune4 297.commune4
298.commune4 299.commune4 300.commune4 301.commune4
302.commune4 303.commune4 304.commune4 305.commune4
306.commune4 307.commune4 308.commune4 309.commune4
310.commune4 311.commune4 312.commune4 313.commune4
314.commune4 315.commune4 316.commune4 317.commune4
318.commune4 319.commune4 320.commune4 321.commune4
322.commune4 323.commune4 324.commune4 325.commune4
326.commune4 327.commune4 328.commune4 329.commune4
330.commune4 331.commune4 332.commune4 333.commune4
334.commune4 335.commune4 336.commune4 337.commune4
338.commune4 339.commune4 340.commune4 341.commune4
342.commune4 343.commune4 344.commune4 345.commune4
346.commune4 347.commune4 348.commune4 349.commune4
350.commune4 351.commune4 352.commune4 353.commune4
354.commune4 355.commune4 356.commune4 357.commune4
358.commune4 359.commune4 360.commune4 361.commune4
362.commune4 363.commune4 364.commune4 365.commune4
366.commune4 367.commune4 368.commune4 369.commune4
370.commune4 371.commune4 372.commune4 373.commune4
374.commune4 375.commune4 376.commune4 377.commune4
378.commune4 379.commune4 380.commune4 381.commune4
382.commune4 383.commune4 384.commune4 385.commune4
386.commune4 387.commune4 388.commune4 2.survey2 3.survey2
4.survey2 5.survey2 6.survey2 7.survey2 8.survey2
Excluded instruments: 0b.treatment_cohort#c.newclassrooms
Dropped collinear: 1.treatment_cohort#c.newclassrooms (this are the treated why is it dropped??)
Daniel.
