García-Peñalosa, Petit and van Ypersele (2023). "Can workers still climb the social ladder as middling jobs become scarce? Evidence from two British cohorts". Labour Economics.

Abstract: The increase in employment polarization observed in several high-income economies has coincided with a reduction in inter-generational mobility. This paper argues that the disappearance of middling jobs can drive changes in mobility, notably by removing a stepping stone towards high-paying occupations for those from less well-off family backgrounds. Using data from two British cohorts who entered the labour market at two points in time with very different degrees of employment polarization, we examine how parental income affects both entry occupations and occupational upgrading over careers. We find that transitions across occupations are key to mobility and that the impact of parental income has grown over time. At regional level, using a shift-share IV-strategy, we show that the impact of parental income has increased the most in regions experiencing the greatest increase in polarisation. This indicates that the disappearance of middling jobs played a role in the observed decline in mobility.

Data Availability Statements

All data used to support the findings of this study have been deposited in _data/. The raw data are provided by UKDATA and require an authorization.

Dataset list

This list contains the final datasets used in the main.Rmd notebook. Original data are available in _data/_raw/. Cleaned data in csv format are available in _data/_clean/. Cleaning of data are performed with scripts in _script/_cleaner/. Aggregation of the cleaned data are performed with the script _script/project_data.R.

DATA FILE	SOURCE	NOTES	PROVIDED
_data/classification_isco88.csv	UKDATA	As per terms of use	No
_data/cohort_acthist.csv	UKDATA	As per terms of use	No
_data/cohort_data.csv	UKDATA	As per terms of use	No
_data/first_job.csv	UKDATA	As per terms of use	No
_data/series-180322.csv	ONS	As per terms of use	Yes

Computational requirements

Software requirements (R Session info)

R version 4.2.2 (2022-10-31 ucrt) Platform: x86_64-w64-mingw32/x64 (64-bit) Running under: Windows 10 x64 (build 22621)

Matrix products: default

locale: [1] LC_COLLATE=English_United States.utf8 LC_CTYPE=English_United States.utf8
[3] LC_MONETARY=English_United States.utf8 LC_NUMERIC=C
[5] LC_TIME=English_United States.utf8

attached base packages: [1] grid stats graphics grDevices utils datasets methods base

other attached packages: [1] effects_4.2-2 carData_3.0-5 nnet_7.3-18 knitr_1.42 kableExtra_1.3.4
[6] texreg_1.38.6 gridExtra_2.3 ggpubr_0.5.0 RColorBrewer_1.1-3 ggrepel_0.9.3
[11] ggplot2_3.4.0 zoo_1.8-11 lubridate_1.9.1 stringr_1.5.0 data.table_1.14.6 [16] tidyselect_1.2.0 tidyr_1.3.0 reshape2_1.4.4 dplyr_1.1.0 readr_2.1.3
[21] haven_2.5.1 foreign_0.8-84

loaded via a namespace (and not attached): [1] Rcpp_1.0.10 svglite_2.1.1 lattice_0.20-45 digest_0.6.31 utf8_1.2.3 R6_2.5.1
[7] plyr_1.8.8 backports_1.4.1 survey_4.1-1 evaluate_0.20 httr_1.4.4 pillar_1.8.1
[13] rlang_1.0.6 minqa_1.2.5 rstudioapi_0.14 nloptr_2.0.3 car_3.1-1 Matrix_1.5-1
[19] rmarkdown_2.20 splines_4.2.2 lme4_1.1-31 webshot_0.5.4 munsell_0.5.0 broom_1.0.3
[25] compiler_4.2.2 xfun_0.37 pkgconfig_2.0.3 systemfonts_1.0.4 mitools_2.4 htmltools_0.5.4
[31] insight_0.19.0 tibble_3.1.8 fansi_1.0.4 viridisLite_0.4.1 tzdb_0.3.0 withr_2.5.0
[37] MASS_7.3-58.1 DBI_1.1.3 nlme_3.1-160 gtable_0.3.1 lifecycle_1.0.3 magrittr_2.0.3
[43] scales_1.2.1 cli_3.6.0 stringi_1.7.12 ggsignif_0.6.4 xml2_1.3.3 ellipsis_0.3.2
[49] generics_0.1.3 vctrs_0.5.2 boot_1.3-28 tools_4.2.2 forcats_1.0.0 glue_1.6.2
[55] purrr_1.0.1 hms_1.1.2 survival_3.4-0 abind_1.4-5 fastmap_1.1.0 yaml_2.3.7
[61] timechange_0.2.0 colorspace_2.1-0 rstatix_0.7.2 rvest_1.0.3

• the file _script/init.R will install all dependencies (latest version), and should be run once prior to running other programs.

Descriptions of programs

• Scripts in _script/_cleaner/ clean all the data used in the analysis from _data/_raw/.
• The script project_data.R generates the final datasets used in the analysis.
• Notebook main.Rmd generates all graphs and tables of this study.

Device specifications

The code was last run on a laptop with Processor 12th Gen Intel(R) Core(TM) i7-1265U and Windows 11 Enterprise Version 22H2 (OS build 22621.1848).

Instructions

• Get access to the same datasets from UKDATA.
• Download them and organize them in the folder _data, see _data/README.md for more details.
• Run all the scripts _script/ to clean the data.
• Run main.Rmd to generates all graphs and tables of this study.

List of directories and files

Each directory contains a README file describing each file and subdirectory.

DATA FILE	DESCRIPTION
_data	All the data (raw, cleaned and final datasets)
_function	All the functions
_graphic	All the graphics
_script	All the scripts
_tabular	All the tabulars
main.Rmd	Main notebook (R code)

Acknowledgements

Structure of this file was copied from the Template README and Guidance of The Review of Economic Studies.