Matteo Picchio, Claudia Pigini, Stefano Staffolani, and Alina
Verashchagina, "If not Now, When? The Timing of Childbirth and Labor
Market Outcomes", Journal of Applied Econometrics, Vol. 36, No. 6,
2021, pp. 663-685.

The data used in the article are the AD-SILC, which is the combination
of the administrative data on labor market contracts from the National
Social Insurance Agency (INPS) and the IT-SILC database gathered by
the Italian National Institute of Statistics (ISTAT). The AD-SILC data
is a confidential data source administered by the Italian Ministry of
Economics and Finance and the Giacomo Brodolini Foundation.

Requests for permission to use this data source should be directed to
Ottavio Ricchi (Dipartimento del Tesoro,  Ministero dell'Economia e
delle Finanze, e-mail: ottavio.ricchi [AT] mef.gov.it) and Manuelita
Mancini (Giacomo Brodolini Foundation, e-mail:
mancini [AT] fondazionebrodolini.eu).

The data are made up of several datasets both from the IT-SILC side
and the INPS side. The construction of our final sample can be rebuilt
following the Stata do files provided into the zipped folder
stata-files-ppsv.zip. This folder contains 5 Stata do files and one
Stata dataset containing regional indicators extracted from ISTAT and
used in this step. The Stata do files numbered from 1 to 3 clean and
merge the different datasets and should be run from 1 to 3. The Stata
do file numbered 4 runs the OLS estimates and draws the descriptive
graphs reported in online Appendix A. Finally, the Stata do file
numbered 5 prepares the dataset to be converted into a Matlab dataset.
The estimation results presented and discussed in Section 5 of the
article and in online Appendixes C-F are obtained by estimating the
model by maximum likelihood in Matlab.

The Matlab codes to load the dataset, set up the regressors and the
outcome variables, and launch the maximum likelihood estimates
(actually we minimize minus the loglikelihood using the Matlab
minimizer fminunc) of the final models are in the zipped folder
matlab-files-ppsv.zip. This folder contains four numbered subfolders.
The number of the subfolder corresponds to the model estimates as
reported in the different columns of Table 4 in the article. We
include in these subfolders the (minus) log-likelihood functions,
named function_f.m. We minimized them using analytical derivatives
automatically calculated by the external Matlab toolbox ADiMat Version
0.4-r9 (C.H. Bischof, H.M. Buecker, B. Lang, A. Rasch, A. Vehreschild:
Combining Source Transformation and Operator Overloading Techniques to
Compute Derivatives for MATLAB Programs, Conference proceeding,
Proceedings of the Second IEEE International Workshop on Source Code
Analysis and Manipulation (SCAM 2002), IEEE Computer Society, 2002)


Please address any questions to:

Matteo Picchio
Department of Economics and Social Sciences
Marche Polytechnic University
Piazzale Martelli 8
60121 Ancona
Italy
E-mail: matteopicchio [AT] gmail.com
Tel: +39 0712207176