Kleanthis Natsiopoulos and Nickolaos G. Tzeremes, "ARDL bounds test for Cointegration: Replicating the Pesaran et al. (2001) Results for the UK Earnings Equation Using R", Journal of Applied Econometrics, Vol. 37, No. 5, 2022, pp. 1079-1090. All data, code, figures, and auxiliary files are zipped and organized in nt-files.zip. Text files are in DOS format. Unix/Linux users should *not* use "unzip -a", because some files are binary. Everything included in the Supporting Information is organized according to the following structure. 1. figures (folder) It contains the figures that were used in the main paper and in the appendix. 2. data (folder) It contains the final datasets and raw data that can be used to fully reproduce the final datasets. More specifically: The raw data files: earn1.dat earn2.dat These were used for the narrow sense replication, and retrieved from the JAE Data Archive http://qed.econ.queensu.ca/jae/2001-v16.3/pesaran-shin-smith/ From the files earn1.dat and earn2.dat, we used the following variables: ERPR (average private sector earnings per employee (£)) PYNONG (the non-oil non-government GDP deflator) YPROM (output in the private, non-oil, non-manufacturing and public traded sectors at constant factor cost (£million, 1990) YMF (manufacturing output index adjusted for stock changes (1990=100)) EMF (employment in UK manufacturing sectors (thousands)) ENMF (employment in UK nonmanufacturing sectors (thousands)) ILOU (International Labour Office measure of unemployment (thousands)) WFEMP (total employment (thousands)) RPIX (the Retail Price Index excluding mortgage payments) UDEN (union density measured as union membership as a percentage of employment (constant from 1980:Q4)) EMPNIC (employers’ payments of National Insurance Contributions (£million)) NIS (national insurance surcharge accruals (£million)) OCR (employers’ other contributions (£million)) WFP (wage and salary bill (including forces’ pay) (£million)) TYEM (accruals of tax on employment income (including PAYE accruing on retirement)) EENIC (employees’ payments of National Insurance Contributions (£million)) The raw data files: AIIH-AIIH.csv (compulsory payments (£milion) ECG-G6NQ.csv (public sector employment central government (thousands)) ELA-G6NT.csv (public sector employment local government (thousands)) EMPNIC-CEAN.csv (employers’ payments of NICs (£million)) EMPSC-ROYK.csv (employers’ social contributions (£million)) GVA-ABMM.csv (gross value added at constant basic prices (£million)) LFSUR-MGSX.csv (unemployment rate) NIS-GTAY.csv (employers’ national insurance surcharge (£million)) PRXMIP-CHMK.csv (RPI excluding mortgage interest payments) PVGA-CGBV.csv (gross value added deflator) TradeUnionMembers.csv (trade union members (thousands) TYEM-DBBQ.csv (taxes on income from employment (£million)) WFJ-DYDC.csv (workforce jobs (thousands)) WFP-DTWL.csv (wages and salaries (incl. benefits in kind) (£million)) WRGTP-LOJU.csv (government trainees (thousands)) These were used for the wide sense replication, and retrieved from the Office for National Statistics (ONS) database https://www.ons.gov.uk/ The ready to use, clean dataset files: data_clean_narrow.csv (1970:Q1-1997:Q4) data_clean_wide.csv (1971:Q1-2019:Q4) These were created using the above raw data files. Each one contains the following 8 columns, while data_clean_wide.csv contains one more column, UnionR (union membership rate): time (linear time trend) w (real wage) Prod (labor productivity) UR (unemployment rate) Wedge (wedge effect) Union (union power) D7475 (income policies 1974:Q1-1975:Q4) D7579 (income policies 1975:Q1-1979:Q4) 3. appendix (folder) It contains the appendix.pdf and the files needed to reproduce it. Files in this folder: appendix.pdf (Contains all the information in the main paper plus some more details) appendix.Rnw (Sweave file which combines R code, data and figures to produce the appendix.pdf) jss.cls (LaTeX Document Class File) reph.bib (BibTeX file) 4. Code files data_preparation_narrow.R (R code that uses raw data and creates the final dataset for the narrow sense replication, data_clean_narrow.csv and also saves it in the data folder) data_preparation_wide.R (R code that uses raw data and creates the final dataset for the wide sense replication, data_clean_wide.csv and also saves it in the data folder. The file contains useful comments describing each step) narrow_replication.R (R code where every calculation regarding the narrow sense replication occurs. The file contains useful comments describing each step) wide_replication.R (R code where every calculation regarding the wide sense replication occurs. The file contains useful comments describing each step) functions.R (Custom functions that are used in narrow_replication.R and wide_replication.R, mainly for the desirable format of the tables) robustness_analysis.R (R code where the calculations for the section Robustness Analysis are done) 5. Execution In order to run the code inside the narrow_replication.R, the wide_replication.R or the robustness_analysis.R files, the working directory should be the path where these two files live (i.e. the nt-file folder). This way one can run step by step every calculation that appears in the main paper and in the appendix, or try to extend the present analysis by running the comment-out lines (some of theme are comment-out because they are time consuming). What these two files (narrow_replication.R and wide_replication.R) essentially do is: They load and run the files data_preparation_narrow.R and data_preparation_wide.R, that load the raw data, produce the clean datasets (data_clean_narrow.csv and data_clean_wide.csv) and save them in the data folder. Then they load the custom function from the file functions.R and the packages needed. Note that the packages should already exist locally. Use install.packages() in case that some packages do not already exist. The calculations follow the structure of the main paper and the appendix, with the same order that they appear, allowing the user to replicate each step and extend the present analysis in the future.