File and Directory Structure of replication_package_GHKR\
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Describes how to get from cleaned, preprocessed administrative tax data to all tables, figures, and other statistics in 

"Consumption and saving patterns in Switzerland: new evidence based on administrative tax data"

Alain Galli, Louisa Hizli, Winfried Koeniger, Rina Rosenblatt-Wisch
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Note:
Items marked as *confidential* either contain confidential data or are directly linked to confidential data and therefore cannot be made available.

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- 00_data\
	- 01_output\
		Data created from raw administrative tax data *confidential*
	- 02_other\
		- 2022_GEOM_TK\
			Geographical data for heatmaps (Figure 5, Section 5.2)
		- geo_units\
			Swiss geographical units for heatmaps (Figure 5, Section 5.2)
		- HABE\
			Data from Household Budget Survey *confidential* (Figure 4, Section 4; Figure 6, Section 5.4; Table 17, Appendix A.3.2; Figure 10, Appendix A.3.3)
		- swiss_national_accounts\
			Data from Swiss National Accounts (Table 3, Section 4)
		- Data on stocks and bonds *confidential* (used to calculate net acquisition of financial wealth for budget constraint, see Section 3.1.2 and Appendix A.2.3)
		- lik.xlsx
			Landesindex der Konsumentenpreise (used to deflate, see Section 2)
		- ms_regionen_bfs.xlsx
			Regional units defined by the Swiss Federal Statistical Office for heatmaps (Figure 5, Section 5.2)
		- Wüstpartner price indices *confidential*
			Price indices (used to calculate net acquisition of real estate wealth in budget constraint, see Section 3.1.2 and Appendix A.2.3) 
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- 01_code\
	- 01_data_corrections.R
		R code to correct data (see Appendix A.1.1-A.1.3)
	- 02_make_figures.R
		R code to make figures 
		Figure 1, Section 3; Figure 2, Section 3.1.1; Figure 3, Section 3.3; Figure 4, Section 4; Figure 5, Section 5.2; Figure 8, Section 5.5; Figure 9, Appendix A.1.3; Figure 10, Section A.3.3
	- 03_make_tables.R
		R code to make tables 
		Table 1, Section 3.2; Table 2, Section 3.3; Table 3, Section 4; Table 4, Section 5.1; Table 5, Section 5.3; Table 6, Section 5.6; Table 7, Section 5.7
	- 04_robustness.R
		R code for robustness checks
		Figure 11, Appendix A.3.4; Figure 12, Appendix A.3.5
		Table 12, Appendix A.2.3; Table 16 and 17, Appendix A.3.2
	- 05_misc.R
		Miscellaneous analyses
		Figure 6, Section 5.4; Footnote 23, Section 5.4; Footnote 27, Appendix A.1.2
	- 06_general_reassessment_2020.R
		R code to check robustness w.r.t. general reassessment 2020
		Table 13 and 14, Appendix A.2.3
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- 02_figures\
	All figures are saved here
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- 03_apc\
	- functions\
		- apc_ie.do
			Function for instrinsic estimator for STATA
	- APC.do
		STATA code to estimate age-period-cohort effects
	- apc_consum_taxunit.R
		R code for age-period-cohort analyis for consumption in taxunits 
		Figure 7(a), (d), (g), Section 5.4
	- apc_consum_equivalized.R
		R code for age-period-cohort analyis for consumption in adult equivalent units 
		Figure 7(b), (e), (h), Section 5.4
	- apc_savingsrate.R
		R code for age-period-cohort analyis for the saving rate 
		Figure 7(c), (f), (i), Section 5.4
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- 04_covid_robustness
	- covid_data\
		Output of cleaning and preprocessing administrative tax data excluding covid years 2020-2022 *confidential*
	- covid_comparison.R
		R code to compare results with and without covid years 
		Table 15, Appendix A.3.1
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