Good afternoon,
I was advised to create a new thread on a previous one ( https://www.statalist.org/forums/for...interpretation).
I will reiterate the background information- any help would be greatly appreciated.
My topic regards a legislation's impact on disability in the workplace and concerns a 5 quarter longitudinal dataset whereby the legislation is enforced at the start of quarter 5. The use of logGRSSWK (the log of gross weekly wage- my dependent variable) only details information for 2 points: quarter 1 and quarter 5 (for which I acknowledge the analysis' profound limitations). Moreover, an important thing to also note is that a time trend was initially absent: the majority of variables ended in the number of the quarter they referred to (i.e GRSSWK1 = Gross weekly wage in quarter 1), although this was somewhat resolved via:
Nevertheless, I established a preliminary DID:
(where DIS= 1 if disabled, 0 if non-disabled; ACT = 1 if post-legislation, 0 if otherwise; ACTDIS = ACT *DIS)
However, this restricts analysis to those in employment and, to ensure the pre- and post- compositions didn't change to undertake the DID, I ensured all observations were in employment quarters 1 and 5 (further limiting the validity of results).
Therefore, my main question is: is the Heckman selection model still applicable given this limited background and, if so, does the required code vary due to this context?
Any help would be greatly appreciated, thank you.
I was advised to create a new thread on a previous one ( https://www.statalist.org/forums/for...interpretation).
I will reiterate the background information- any help would be greatly appreciated.
My topic regards a legislation's impact on disability in the workplace and concerns a 5 quarter longitudinal dataset whereby the legislation is enforced at the start of quarter 5. The use of logGRSSWK (the log of gross weekly wage- my dependent variable) only details information for 2 points: quarter 1 and quarter 5 (for which I acknowledge the analysis' profound limitations). Moreover, an important thing to also note is that a time trend was initially absent: the majority of variables ended in the number of the quarter they referred to (i.e GRSSWK1 = Gross weekly wage in quarter 1), although this was somewhat resolved via:
Code:
gen id = _n reshape long GRSSWK d_DIS DISCURR AGES URESMC REGWKR MARSTA HIQUAL8 HDPCH19 Inde07m GRSSWK2 TPEN091 STATR SKSBN91 FTPTWK , i(id) j(quarter)
HTML Code:
reg logGRSSWK ACT DIS ACTDIS i.SEX i.ETH i.AGES i.RES_NEW i.REGWKR_NEW i.HDPCH19 i.IND i.MARSTA i.HIQUAL i.SKSBN91 i.FTPTWK, vce(robust) Linear regression Number of obs = 3,836 F(74, 3761) = 67.98 Prob > F = 0.0000 R-squared = 0.5729 Root MSE = .53276 -------------------------------------------------------------------------------------------------------- | Robust logGRSSWK | Coef. Std. Err. t P>|t| [95% Conf. Interval] ---------------------------------------+---------------------------------------------------------------- ACT | .1165873 .0193822 6.02 0.000 .0785866 .1545879 DIS | -.033673 .0392651 -0.86 0.391 -.1106559 .04331 ACTDIS | -.0090192 .0517852 -0.17 0.862 -.110549 .0925106
However, this restricts analysis to those in employment and, to ensure the pre- and post- compositions didn't change to undertake the DID, I ensured all observations were in employment quarters 1 and 5 (further limiting the validity of results).
Therefore, my main question is: is the Heckman selection model still applicable given this limited background and, if so, does the required code vary due to this context?
Any help would be greatly appreciated, thank you.