Dear Statalist,
I would like to ask for some help regarding the use of -estadd-. I run a dynamic panel regression and use -lincom- to produce an estimate and standard error of a linear combination of some coefficients. After using -estadd- to store scalars and -esttab- to produce a regression table, the standard error appears finely on the table, but the scalar for the coefficient does not. Can anyone give me a clue why this is such a case? Thank you!
My code is:
eststo: qui xtreg qoq_consumerloan L(1/4).qoq_consumerloan L(0/4).MaP ///
L.TA_r L.LR L.CR L.FC ///
qoq_rgdp REER qoq_polrate creditgap i.flood i.crisis qr*, fe cluster(ficode)
lincom MaP + L1.MaP + L2.MaP + L3.MaP + L4.MaP
estadd scalar se = r(se)
estadd scalar coeff = r(estimate)
esttab , stats (coeff se, fmt(%9.3f %9.3f))
The regression table I get is (Please note that the number for "coeff" from estadd command does not appear on the table:
I would like to ask for some help regarding the use of -estadd-. I run a dynamic panel regression and use -lincom- to produce an estimate and standard error of a linear combination of some coefficients. After using -estadd- to store scalars and -esttab- to produce a regression table, the standard error appears finely on the table, but the scalar for the coefficient does not. Can anyone give me a clue why this is such a case? Thank you!
My code is:
eststo: qui xtreg qoq_consumerloan L(1/4).qoq_consumerloan L(0/4).MaP ///
L.TA_r L.LR L.CR L.FC ///
qoq_rgdp REER qoq_polrate creditgap i.flood i.crisis qr*, fe cluster(ficode)
lincom MaP + L1.MaP + L2.MaP + L3.MaP + L4.MaP
estadd scalar se = r(se)
estadd scalar coeff = r(estimate)
esttab , stats (coeff se, fmt(%9.3f %9.3f))
The regression table I get is (Please note that the number for "coeff" from estadd command does not appear on the table:
| (1) | |
| qoq_consum~n | |
| L.qoq_cons~n | 0.299* |
| (2.35) | |
| L2.qoq_con~n | 0.119 |
| (2.07) | |
| L3.qoq_con~n | 0.198** |
| (3.47) | |
| L4.qoq_con~n | -0.00717 |
| (-0.21) | |
| MaP | -0.000168 |
| (-0.02) | |
| L.MaP | 0.0167 |
| (1.72) | |
| L2.MaP | -0.00746 |
| (-1.43) | |
| L3.MaP | 0.0117 |
| (2.02) | |
| L4.MaP | 0.000335 |
| (0.04) | |
| L.TA_r | -0.0207 |
| (-0.81) | |
| L.LR | -0.000000277 |
| (-0.48) | |
| L.CR | -0.000000737 |
| (-0.65) | |
| L.FC | -0.0252 |
| (-0.63) | |
| qoq_rgdp | 0.112 |
| (0.74) | |
| REER | -0.00143 |
| (-0.90) | |
| qoq_polrate | 0.000571 |
| (0.05) | |
| creditgap | 0.000584 |
| (1.32) | |
| 0.flood | 0 |
| (.) | |
| 1.flood | -0.0127 |
| (-0.78) | |
| 0.crisis | 0 |
| (.) | |
| 1.crisis | -0.00907 |
| (-0.66) | |
| qr2 | 0.0123 |
| (1.50) | |
| qr3 | 0.0250*** |
| (4.72) | |
| qr4 | 0.0349*** |
| (4.14) | |
| _cons | 0.327 |
| (0.93) | |
| coeff | |
| se | 0.018 |
| t statistics | in parentheses |
| * p<0.05, ** | p<0.01, *** p<0.001 |
