These folders contain replication material for

"The Fertility Transition and Directed Technical Change towards Green Growth" by
Matthias Beulmann und Holger Strulik

Submission RED-D-24-00122R2

The codes provided were created using Matlab R2019b and Stata MP 14.2

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To generate Figure 1 and Figure F.1 and F.2 in the Appendix and the regression results from Tables A.1 -- A.5 in the Appendix: 

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HOW TO USE: 

1)	In each of the files OECD.do and NONOECD.do: 
	Insert the system path of the folder "Empirics" in line 27 between the quotation marks of the command "cd".
	Example: 	cd "C:\Replication\Empirics"
2)	Excute OECD.do and NONOECD.do (Computation time each: under 30 seconds)

All Tables and Figures are placed into the Folder "Output"

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The "Empirics" folder contains the following files:

OECD.do 		--> creates Tables A.1, A.2, A.4 and A.5 and Figures 1, F.1 and F.2 from dataset OECD_RAW_ANON.dta 
NON_OECD.do 		--> creates Table A.3 from data in folder Data\NONOECD
country_codes.do	--> script to assign numeric country identifier to observations based on various country labeling methods across datasets

Folder Data\OECD:
OECD_RAW_ANON.dta	--> anonymized fertility and school enrollment data from Madsen and Strulik (2022), merged with the other files in folder Data\OECD
carbon.xlsx		--> Carbon Emission Data from CDIAC http://cdiac.ess-dive.lbl.gov/ftp/ndp030/CSV-FILES/nation.1751_2014.csv
mpd2020.xlsx		--> GDP + Population Data from Maddison
pri.xlsx		--> Length of Primary Education from https://data.worldbank.org/indicator/SE.PRM.DURS
sec.xlsx		--> Length of Secondary Education https://data.worldbank.org/indicator/SE.SEC.DURS

Folder Data\NONOECD:
carbon.xlsx				--> Carbon Emissions from CIDAC via Gapminder
countries.xlsx				--> Information about countries, such as membership in OECD, landlocked status, etc. from Gapminder
crude_birth.xlsx			--> Crude Birth Rate from Gapminder
Education Index - Dataset - v1.xlsx	--> Years of Schooling from Gapminder, based on Lee-Lee (2016), Barro-Lee (2018) and UNDP (2018)
longrun_gdp_ppp.xlsx			--> GDP from Gapminder, combination of Maddison and PWT
total_population.xlsx			--> Population from Gapminder

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OECD DATA:

In case of the OECD data, we do not have permission to share the full raw data set. Instead, we provide 
an already merged quasi-raw data set that underwent a very limited amount of data cleaning/merging operations. 
These are (apart from renaming variables such as "Year" to "year" to make data compatible):

1) Import all excel files from Data\OECD into Stata
2) Import one more excel file (not provided) into Stata for which we do not have the permission to share it directly, containing information about school enrollment rates,
   fertility and mortality.
3) For Carbon data, construct Germanys observations from 1945 as the sum of East- and West-Germany.
4) Merge datasets based on country and year identifiers

This should enable anyone with (hypothetical) access to all the raw data to reproduce the file OECD_RAW_ANON.dta

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All dofiles were executed with Windows 11, Stata 14.2


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To generate Figures 2-6 and Figures A.1-A.5 in the Appendix:

The "Simulation" folder contains the following Matlab m-files:

- benchmark_model.m: main file that generates Figures 2-6 and A.1 to A.4
- banchmark_fun.m: function file containing the numerally solved equations
- us_data.mat: data file with targeted series in Figure 2
- case_2.m: main file that generates Figure A.5
- case_2_fun.m: function file for case_2.m

To generate the figures 2-6 and A.1 to A.4, run benmark_model.m
The number of the figure to be generated has to be specified in line 15

To generate figure A.5, run case_2.m