Replication Package for "Does Local Politics Drive Tropical Land-Use Change? Property-Level Evidence from the Amazon"

1 Does Local Politics Drive Tropical Land-Use Change? Property-Level Evidence from the Amazon Erik Katovich and Fanny Moffette The Economic Journal October 2025 Overview The code in this replication package constructs the analysis file from 11 data sources (MapBiomas, CAR, Terral Legal, INCRA, TSE, IBAMA, FINBRA, PGU, Banco Central, Census, Ipea) using Stata and R. The master do-file (MASTER_DOFILE.do) runs all of the do-files required to generate the data to replicate the 81 figures and 11 tables in the paper (main text and appendix). The replicator should expect the code to run for about 6 hours. Data Availability and Provenance Statements Statement about Rights • I certify that the authors of the manuscript have legitimate access to and permission to use the data used in this manuscript. • I certify that the authors of the manuscript have documented permission to redistribute/publish some of the data contained within this replication package. Please refer to Table 1 – Datasets list for details on which datasets are provided. Dara Availability Statatement • All data are publicly available. • Some data cannot be made publicly available. • No data can be made publicly available Summary of Availability As summarized in Table 1 below, this paper uses a combination of publicly available and restricted datasets. All publicly available data are included in the Data/Raw folder of this replication package. Restricted data on property boundaries with owners’ personal information, as well as data on environmental violations associated with specific properties or property 2 owners, were shared with the authors by the Gibbs Land Use and Environment Lab (GLUE) at University of Wisconsin-Madison. Our data use agreement with GLUE does not allow us to make these data publicly available. Furthermore, public sharing of these data is restricted under Brazilian law (Instrução Normativa nº 3/MMA of December 18th, 2014, Articles 3 and 4). We requested the following datasets from GLUE: • IBAMA environmental embargos linked with landholder ID numbers (CPF/CNPJ), covering states in the Brazilian Legal Amazon, from 2005-2020. • Property boundaries from the Cadastro Ambiental Rural, Terra Legal, and INCRA, including property holder names and ID numbers (CPF/CNPJ), covering states in the Brazilian Legal Amazon, intersected with annual data from MapBiomas (Version 5) to measure land use in hectares and land use transitions at 30mx30m resolution on each property between 2000-2020. Access procedures: Researchers seeking to replicate this analysis or pursue related research questions may contact the GLUE Lab (https://gibbslab.wisc.edu/index.html). Access requests should include (1) a description of the research project and intended use of the data, (2) documentation of IRB approval or equivalent ethical review, if applicable, and (3) acknowledgement of compliance with relevant Brazilian data protection laws regarding personally identifiable information. The data involved in this project are the result of years of significant effort by the GLUE Lab in collaboration with many partner institutions and organizations in Brazil. The GLUE Lab evaluates data requests on a case-by-case basis and requires a formal data use agreement that prohibits redistribution and requires secure data handling practices. Approval is not guaranteed, and the Lab's ability to share data depends on ongoing agreements with Brazilian data providers and may be subject to change. Note on Personal Identifiers This replication package contains Brazilian taxpayer identification numbers (CPFs) for political candidates and campaign donors. These identifiers serve as the essential link between electoral data and land registries. The CPFs in this package are historical public records collected from Brazil's Superior Electoral Court (Tribunal Superior Eleitoral - TSE) prior to 2022. At the time of data collection, all candidates and donors knowingly consented to public disclosure of this information. A recent Brazilian judicial ruling has restricted publication of candidate CPFs for current and future elections, and the TSE has removed candidate CPFs from their data transparency platform. However, we are not aware of any legal requirement for retroactive removal of historical candidate CPFs, and Brazilian public data repositories continue to make candidate CPFs available for research purposes. 3 For GDPR-Compliant Researchers: We acknowledge that the presence of these identifiers may create administrative constraints for researchers operating under European data protection regulations. However, given that these historical data remain publicly available in open repositories, were obtained with the informed consent of public figures, and are important for replicability and transparency, we have opted to retain them in this package. This decision has been reviewed and approved by the journal's Data Editor. Researchers who cannot use data containing these identifiers may contact the corresponding author to discuss alternative arrangements, such as access to a redacted version of the package. 4 Table 1 Datasets list Data Source Years Raw & Analysis Level Data - name Provided Deforestation & Land Use MapBiomas 2000-2019 Property dataset_Part1_Katovich_and_Moffette_2021_07_09.txt No dataset_Part3_Katovich_and_Moffette_2021_07_26.txt No dataset_Part4_Katovich_and_Moffette_2021_07_29_revised.txt No dataset_all_amazon_biome_properties_mapbiomas8pt0_variables.csv No dataset_all_amazon_biome_properties_natveg_to_farm_vars.csv No Municipality MapBiomas_Transitions.csv Yes Municipal_Deforestation_2000_to_2020_PRODES.csv Yes Land Registries CAR 2011-2020 Property dataset_Part1_Katovich_and_Moffette_2021_07_09.txt dataset_all_amazon_biome_properties_propertyha.csv dataset_all_amazon_biome_properties_ownerids_v2.csv No Terral Legal 2014-2017 Property INCRA 2016-2020 Property Elections (Candidates) TSE 2000-2016 Individual Elections_Candidates.dta Yes Elections (Donors) TSE 2004-2016 Individual ReceitaCandidato_2004.CSV Yes ReceitaComitê_2004.CSV Yes receitas_candidatos_2008_brasil.csv Yes receitas_comites_2008_brasil.csv Yes receitas_candidatos_2012_brasil.txt Yes receitas_comites_2012_brasil.txt Yes receitas_partidos_2012_brasil.txt Yes receitas_candidatos_prestacao_contas_final_2016_brasil.txt Yes receitas_partidos_prestacao_contas_final_2016_brasil.txt Yes Candidates_Donations_MunicipalityLevel_withMunicCodes.dta Yes 5 Environmental Violations IBAMA 2005-2020 Property dataset_Part2_Katovich_and_Moffette_2021_07_22.txt No dataset_all_amazon_biome_properties_embargo_variables.csv No Municipality dataset_Part6_Katovich_and_Moffette_2022_01_31.txt No Public Finances FINBRA SICONFI 2000-2020 Municipality municipio_despesas_funcao.csv Yes PublicFinances_1998_2017.dta Yes Federal Matching Grants PGU 1996-2022 Municipality 20220204_Convenios.csv Yes Rural Credit Banco Central 2004-2017 Municipality credit.dta Yes Municipality Characteristics IBGE 2000-2021 Municipality Population_Complete_Panel.dta Yes municipal_population_to2021.csv Yes Ipea 2000 Census_IPEA_forMerging.dta Yes Other datasets IBGE - Municipality brazil_geographical_codes.dta Yes IBGE - Municipality Legal_Amazon_Percentage.csv Yes IBGE - Municipality AmazoniaLegal_Maranhao.csv Yes Moffette et al. (2021) - Municipality Complementary dataset.dta Yes Region_Municipality_List.dta Yes 6 Software Requirements • Stata SE (version 18) – All required packages are stored locally in 3-replicationpackage/Code/ado, unless otherwise noted. – gtools and colrspace require installation every time from SSC. – Csdid2 and csdid require moremata to be uninstalled and reinstalled every time, followed by net install csdid and csdid2 from “https://raw.githubusercontent.com/ friosavila/stpackages/main” – ftools (version 2.49.1 08aug2023) – reghdfe (version 6.12.3 08aug2023) – coefplot (version 1.8.8 22aug2025 Ben Jann) – grstyle (version 1.1.1 15sep2020 Ben Jann) – csdid (v1.81 by pedro Sant'Anna. Compatibility checks *! v1.8 by FRA. Trim) – drdid (Ver 1.71 bug with weights) – gtools (version 1.10.1 05Dec2022 Mauricio Caceres Bravo) – colorpalette (version 1.2.7 23may2024 Ben Jann) – linepallette (version 1.0.1 27dec2018 Ben Jann) – grc1leg2 (version 2.26 (4Nov2023), by Mead Over *! Enhanced version of -grc1legversion 1.0.5 02jun2010, by Vince Wiggins) – estout (version 3.31 26apr2022 Ben Jann) – csdid2 (v1.3 Allows for Reg2 and drimp2: hdidregress compatible *! v1.21 Allows for treatvar *! v1.2 Allows for Anticipation *! v1.13 Cluster Corrections for RCS and RC *! v1.12 Adds Option for CSname *! v1.11 Corrects For missing in cluster *! v1.1 adds Rolling *! v1 Wrapper for CSDID2-Mata version) • R 3.4.3 – geobr (version 1.9.1) – ggplot2 ( version 3.5.1) – sf (version 1.0-17) – sp (version 2.1-4) – dplyr (version 1.1.1) – rio (version 1.2.3) – geosphere (version 1.5-20) – foreign (version 0.8-84) – spData (version 2.3.4) – ptinpoly (version 2.8) – data.table(version 1.14.8) – viridis (version 0.6.5) – gridExtra (version 2.3) – the file “Mapping_Deforestation_CloseElections.R” will install all dependencies (latest version). 7 Controlled Randomness • Seed is set at line 17 of program MASTER_DOFILE.do • Sortseed is set at line 18 of program MASTER_DOFILE.do • Since “clear all” is used in each do-file, the seed is deleted from memory. The same seed and sortseed are reset in all subsequent do-files to allow results to be reproduced. Memory and Runtime Requirements Approximate time needed to reproduce the analyses on a standard 2025 desktop machine with 16GB computer memory: • <10 minutes • 10-60 minutes • 1-2 hours • 2-8 hours • 8-24 hours • 1-3 days • 3-14 days • > 14 days • Not feasible to run on a desktop machine, as described below. Details The code was last run on a 12th Gen Intel-based laptop (i7-1255U, 1.70 GHz) with Windows 11 OS. Docker testing was performed using Docker Desktop with the dataeditors/stata18_5-se:2025-02-26 container image. 8 Instructions to Replicators Data Setup Download the data files referenced above. Each should be stored in Data/Raw, in the format that you download them in. Critical step: all confidential data files stored in Folder 4-confidential-data-not-forpublication/Raw must be copied and pasted into 3-replication-package/Data/Raw for the package to run. Running the Code The replication package runs in a Docker container to ensure reproducibility across different computing environments. Prerequisites: Docker Desktop installed (download at https://www.docker.com/products/dockerdesktop) Valid Stata SE 18 license file (stata.lic) PowerShell (Windows), Terminal (Mac/Linux), or equivalent command-line interface Steps: 1. Edit the Docker execution script: • Open DockerFile.txt in the main replication package folder • Modify line 1 to point to where you've saved the replication package • Modify the $STATALIC path to point to your Stata license file location 2. Run the container: • Open PowerShell (Windows) or Terminal (Mac/Linux) • Copy and paste the entire contents of DockerFile.txt into your terminal • Press Enter to execute 3. Review results: • Output log: Code/MASTER_DOFILE.log • Results (Figures, Tables, etc.) are stored in subfolders within Results 9 Note: The container automatically installs platform-specific dependencies (gtools, colrspace, csdid, csdid2) from SSC and Github. An active internet connection is required during the initial run. Structure of Folder Manual edits to Tables and Figures • TB6 + TB7: manually removed digits after the decimal point for two coefficients • Table 1: manually removed zeros and replaced with missing values for donors for their personal characteristics. • Table B2 – bring data from Table 1 for columns 1 and 2. • Table B4 – Sample sizes in bottom row of table are computed in Municipal_Descriptives_Table_B4.do (lines 120-136) and manually added to table. • Figure 5, 6, and A3 have manual edits for aesthetics. MASTER_DOFILE.do ado 16 Data_Cleaning\Municipal_MapBiomas_Cleaning.do Input: - Raw\MapBiomas_Transitions.csv - Intermediate\Legal_Amazon_Municipalities_List.dta Output: - Intermediate\MapBiomas_NatVeg3.dta - Intermediate\MapBiomas_Pasture.dta - Intermediate\MapBiomas_soy.dta - Intermediate\MapBiomas_Deforestation_to_Pasture.dta - Intermediate\MapBiomas_Deforestation_to_Soy.dta - Intermediate\MapBiomas_Pasture_to_Soy.dta Data_Cleaning\Municipal_RuralCredit_Cleaning.do Input: - Raw\credit.dta Output: - Intermediate\Rural_Credit_Panel_2004_2017.dta Data_Cleaning\Municipal_Convenios_Cleaning.do Input: - Raw\20220204_Convenios.csv - Raw\brazil_geographical_codes.dta - Intermediate\Legal_Amazon_Municipalities_List.dta Output: - Intermediate\Municipal_Grants_Panel_LegalAmazon.dta 17 Data_Cleaning\Municipal_DataPrep_Revised.do Input: - Raw\municipio_despesas_funcao.csv - Raw\PublicFinances_1998_2017.dta - Raw\brazil_geographical_codes.dta - Raw\Complementary dataset.dta - Raw\dataset_Part6_Katovich_and_Moffette_2022_01_31.txt - Raw\municipal_population_to2021.csv - Intermediate\Municipal_Grants_Panel_LegalAmazon.dta - Intermediate\Rural_Credit_Panel_2004_2017.dta - Intermediate\MapBiomas_NatVeg3.dta - Intermediate\MapBiomas_Pasture.dta - Intermediate\MapBiomas_soy.dta - Intermediate\MapBiomas_Deforestation_to_Pasture.dta - Intermediate\MapBiomas_Deforestation_to_Soy.dta - Intermediate\MapBiomas_Pasture_to_Soy.dta - Intermediate\Census_IPEA_2000Descriptives.dta - Intermediate\Legal_Amazon_Municipalities_List.dta - Intermediate\Candidates_GLUE_PRODES_Embargos_MapBiomas_Legal_Amz.dta - Intermediate\Donors_withCandidateOutcomes_CPFs_Iteration3_Legal_Amz.dta - Intermediate\Donors_withCandidateOutcomes_Names_Iteration3_Legal_Amz.dta - Intermediate\Candidate_Year_Donations_CompleteIndividualData.dta - Intermediate\Landowning_Mayoral_Candidates_List_Amazon_only.dta 18 Output: - Intermediate\Agriculture_and_Environment_Spending_2004_to_2020.dta - Intermediate\Agriculture_and_Environment_Spending_2000_to_2003.dta - Intermediate\Agriculture_and_Environment_Spending_2000_to_2020.dta - Intermediate\AmazonBiome_List.dta - Intermediate\AmazonBiome_List_numeric.dta - Intermediate\Municipality_Level_Embargo_Counts.dta - Intermediate\Municipality_Outcomes_Panel3a.dta - Intermediate\Municipality_Level_AnnualOutcomes_Processed3a.dta - Intermediate\Municipality_MandateLevel_Outcomes_Processed3a.dta - Intermediate\Landowning_Mayoral_Candidates_List_Amazon_only.dta - Intermediate\Candidate_Donations_Landowners_CPFs.dta - Clean\Municipality_Data_Clean.dta Data_Cleaning\Municipal_DataPrep_Yearly.do Input: - Intermediate\Municipality_Outcomes_Panel3a.dta - Intermediate\Legal_Amazon_Municipalities_List.dta - Intermediate\Candidate_Year_Donations_CompleteIndividualData.dta - Raw\brazil_geographical_codes.dta - Intermediate\Landowning_Mayoral_Candidates_List_Amazon_only.dta - Intermediate\Candidate_Donations_Landowners_CPFs.dta Output: - Intermediate\Municipality_Level_AnnualOutcomes_Processed.dta - Intermediate\Municipality_MandateLevel_Outcomes_Processed_Yearly.dta - Clean\Municipality_Panel_Outcomes_and_LandowningCandidates_Yearly.dta 19 Descriptives\Landowner_Share_of_Politicians.do Input: - Intermediate\Candidate_Year_Donations_CompleteIndividualData.dta - Raw\brazil_geographical_codes.dta - Intermediate\GLUE_PRODES_CPFLevel_Iteration3.dta - Intermediate\Legal_Amazon_Municipalities_List.dta Output: - Intermediate\Landowner_PoliticianShare_2000.csv - Intermediate\Landowner_PoliticianShare_2004.csv - Intermediate\Landowner_PoliticianShare_2008.csv - Intermediate\Landowner_PoliticianShare_2012.csv - Intermediate\Landowner_PoliticianShare_2016.csv Mapping_Deforestation_CloseElections.R Input: - Raw\AmazoniaLegal_Maranhao.csv - Intermediate\Close_Elections_Per_Municipality.csv - Intermediate\Landowner_PoliticianShare_2000.csv - Intermediate\Landowner_PoliticianShare_2004.csv - Intermediate\Landowner_PoliticianShare_2008.csv - Intermediate\Landowner_PoliticianShare_2012.csv - Intermediate\Landowner_PoliticianShare_2016.csv Output: - Figures\Landowner_Intensity_2000_Map.png - Figures\Landowner_Intensity_2004_Map.png - Figures\Landowner_Intensity_2008_Map.png - Figures\Landowner_Intensity_2012_Map.png - Figures\Landowner_Intensity_2016_Map.png - Figures\Close_Elections_Map.png (Figure A1) 20 Data_Cleaning\All_Properties_DataPrep_and_ Descriptives.do Input: - Intermediate\Candidates_GLUE_PRODES_Embargos_MapBiomas_Amazon_only.dta - Intermediate\Donations_2016.dta - Intermediate\Donations_2004.dta - Intermediate\Donations_2008.dta - Intermediate\Donations_2012.dta - Raw\brazil_geographical_codes.dta - Intermediate\AmazonBiome_List_numeric.dta - Intermediate\GLUE_PRODES_Embargos_MapBiomas_CPFLevel_Amazon_only.dta - Raw\dataset_all_amazon_biome_properties_propertyha.csv - Raw\dataset_all_amazon_biome_properties_embargo_variables.csv - Raw\ dataset_all_amazon_biome_properties_natveg_to_farm_vars.csv - Raw\dataset_all_amazon_biome_properties_ownerids_v2.csv - Raw\dataset_all_amazon_biome_properties_mapbiomas8pt0_variables.csv Output: - Intermediate\Candidate_PropertyIDs_List.dta - Intermediate\Donors_PropertyIDs_List2.dta - Intermediate\All_Properties_PropertyArea.dta - Intermediate\All_Properties_Embargoes.dta - Intermediate\All_Properties_NatVeg_to_Farming.dta - Intermediate\All_Properties_OwnerIDs.dta - Clean\All_Properties_and_Mayors_PropertyArea_for_Figure_1.dta - Clean\All_Properties_and_Mayors_Deforestation_for_Figure_2.dta - Intermediate\AllProperties_for_Table_B2.dta - Clean\All_Properties_and_Donors_PropertyArea_for_Figure_1.dta - Clean\All_Properties_and_Donors_Deforestation_for_Figure_2.dta 21 Data_Cleaning\DataPrep_for_Table1.do Input: Clean\Elections_and_Defor_Donors_Database_Iteration3_Amazon_only.dta - Intermediate\AmazonBiome_List_numeric.dta - Raw \Elections_Candidates.dta - Intermediate\Candidate_Year_Donations_CompleteIndividualData.dta - Raw\brazil_geographical_codes.dta - Intermediate\Candidates_GLUE_PRODES_Embargos_MapBiomas_Legal_Amz.dta - Intermediate\Donations_2016.dta - Intermediate\Donations_2004.dta - Intermediate\Donations_2008.dta - Intermediate\Donations_2012.dta - Intermediate\GLUE_PRODES_Embargos_MapBiomas_CPFLevel_Amazon_only.dta - Intermediate\Elections_Candidates_Mayors_Unique.dta - Intermediate\Successful_Donors_List_2004_2016_Replication.dta 22 Output: - Intermediate\Successful_Donors_List_2004_2016_Replication.dta - Intermediate\Donors_to_Successful_Candidates_Total_2004_to_2016_Replication.dta - Intermediate\Elections_Candidates_Mayors_Unique.dta - Intermediate\Descriptive_Statistics_all_candidates_total.dta - Intermediate\Descriptive_Statistics_all_candidates_land.dta - Intermediate\Descriptive_Statistics_winning_candidates_total.dta - Intermediate\Descriptive_Statistics_winning_candidates_land.dta - Intermediate\Runner_Up_List_V3.dta - Intermediate\Descriptive_Statistics_runnerup_candidates_total.dta - Intermediate\Descriptive_Statistics_runnerup_candidates_land.dta - Intermediate\Descriptive_Statistics_Candidates_Combined.dta - Intermediate\Descriptive_Statistics_all_donors_total.dta - Intermediate\Descriptive_Statistics_all_donors_land.dta - Intermediate\Descriptive_Statistics_runnerup_donors_total.dta - Intermediate\Descriptive_Statistics_runnerup_donors_land.dta - Intermediate\Descriptive_Statistics_winning_donors_total.dta - Intermediate\Descriptive_Statistics_winning_donors_land.dta 23 Descriptives\All_Candidates_and_Donors_ Landholding.do Input: - Intermediate\Candidate_Year_Donations_CompleteIndividualData.dta - Raw\brazil_geographical_codes.dta - Intermediate\Candidate_PropertyIDs_List.dta - Intermediate\AmazonBiome_List_numeric.dta - Intermediate\Donations_2016.dta - Intermediate\Donations_2004.dta - Intermediate\Donations_2008.dta - Intermediate\Donations_2012.dta - Intermediate\Donors_PropertyIDs_List2.dta Output: - Intermediate\Landholding_Candidates_for_TableB3.dta - Intermediate\Landholding_Donors_for_TableB3.dta - Intermediate\Parties_Landholding_Donations.dta 24 Descriptives\Figure_A3.do Input: - Intermediate\Candidate_Year_Donations_CompleteIndividualData.dta - Raw\brazil_geographical_codes.dta - Intermediate\Candidate_PropertyIDs_List.dta - Raw\Region_Municipality_List - Intermediate\Donations_2016.dta - Intermediate\Donations_2004.dta - Intermediate\Donations_2008.dta - Intermediate\Donations_2012.dta - Intermediate\Donors_PropertyIDs_List2.dta Output: - Intermediate\Parties_Landholding_Candidates.dta - Figures\FA4.gph Descriptives\Table_B3.do Input: -Intermediate\Landholding_Candidates_for_TableB3.dta Output: - Tables\TB3.tex Descriptives\Municipal_Descriptives_Table_B4.do Input: - Raw\Candidates_Donations_MunicipalityLevel_withMunicCodes.dta - Intermediate\Census_IPEA_2000Descriptives.dta - Intermediate\Population_Complete_2000.dta - Intermediate\Legal_Amazon_Percentage_Municipalities.dta - Intermediate\Close_Elections_Panel_2000_to_2016.dta - Intermediate\Municipal_Deforestation_2000_to_2020_PRODES.dta - Intermediate\Legal_Amazon_Municipalities_List - Intermediate\AmazonBiome_List_numeric.dta Output: - Tables\TB4.tex 25 Descriptives\All_Properties_Descriptives_Table_B2.do Input: - Intermediate\AllProperties_for_Table_B2.dta Output: - Tables\TB2.tex Descriptives\Mean_Outcome_Graphs.do Input: - Clean\Elections_and_Defor_Donors_Database_Iteration3_Amazon_only.dta - Intermediate\AmazonBiome_List_numeric.dta Output: - Figures\FA4.png - Figures\FA5.png Descriptives\Pre_Post_Donations_ DescriptiveStatistics.do Input: - Clean\Elections_and_Defor_Donors_Database_Iteration3_Amazon_only.dta - Raw\Region_Municipality_List.dta Output: - Log\Pre_Post_Donations_descriptives.smcl 32 Output: - Tables\TB6.tex - Numbers\CoeffEstPastureT0.tex - Numbers\CoeffEstPastureT6.tex - Numbers\BaselineDVMeanPasture.tex - Numbers\BaselineDVMeanSoy.tex - Numbers\CoeffEstSoyT3.tex - Numbers\EffectSoyHa.tex - Numbers\CoeffEstSoyT5.tex - Numbers\PercIncrSoyMandate.tex - Numbers\TotHaSoyIncrease6years.tex - Numbers\CoeffEstDeforT3.tex - Tables\TB7.tex - Numbers\CandidateBaselineDVMeanD4.tex - Tables\TB8.tex - Tables\TB9.tex - Tables\TB10.tex - Numbers\MunCoeffEstAgPromoMoreThan25perc.tex - Numbers\MunCoeffEstCreditMoreThan50perc.tex - Numbers\MunCoeffEstCreditMoreThan25perc.tex - Numbers\MunCoeffEstSoyMoreThan25perc.tex - Numbers\MunCoeffEstSoyHaMoreThan25perc.tex - Numbers\MunCoeffEstDeforMoreThan25perc.tex - Numbers\MunCoeffEstD4HaMoreThan25perc.tex - Numbers\MunCoeffEstEmbargoMoreThan25perc.tex 33 Analysis\Results_Figures_C41_to_C61.do Input: - Clean\Municipality_Data_Clean.dta - Intermediate\AmazonBiome_List_numeric.dta - Clean\Municipality_Panel_Outcomes_and_LandowningCandidates_Yearly.dta Output: - Figures\FC41.pdf to Figures\FC61.pdf 34 Data References Banco Central do Brasil, Matriz de Dados do Crédito Rural - Crédito Concedido. Accessed in August 2021, URL: https://www.bcb.gov.br/estabilidadefinanceira/micrrural Base dos Dados, municipio_despesas_por_funcao, Sistema de Informações Contábeis e Fiscais do Setor Público Brasileiro (SICONFI). Accessed in November 2020, URL: https://basedosdados.org/dataset/5a3dec52-8740-460e-b31d0e0347979da0?table=ee51f2d3-c5fb-4ff3-a6e2-fe4bbdcc46c8 Brazilian Ministry of the Environment (Ibama), Embargoes and Infractions, Accessed in November 2020. Accessed in June 2021, URL: https://servicos.ibama.gov.br/ctf/publico/areasembargadas/ConsultaPublica AreasEmbargadas.php Gibbs Land Use and Environment Lab, Harmonized Identified Property Records with Land-Use and Environmental Violations (2000-2020), Proprietary Dataset. Instituto Brasileiro de Geografia e Estatística, Códigos dos municípios IBGE. Accessed in November 2019, URL: https://www.ibge.gov.br/explica/codigos-dosmunicipios.php Instituto Brasileiro de Geografia e Estatística, Estimativas da População. Accessed in May 2020, URL: https://www.ibge.gov.br/estatisticas/sociais/populacao/9103-estimativasde-populacao.html Instituto Brasileiro de Geografia e Estatística, Municípios da Amazônia Legal – XLSX. Accessed in November 2019, URL: https://www.ibge.gov.br/geociencias/cartas-e-mapas/mapasregionais/15819-amazonia-legal.html Instituto de Pesquisa Econômica Aplicada, Finanças Publicas - Despesas por função, IPEAdata. Accessed in November 2020, URL: http://www.ipeadata.gov.br/Default.aspx Instituto Nacional de Colonização e Reforma Agrária (INCRA), Certificado de Cadastro do Imóvel Rural (CCIR). Accessed in June 2021, URL: https://www.gov.br/incra/pt-br/assuntos/governanca-fundiaria/cadastroimovel-rural Instituto Nacional de Pesquisas Espaciais (INPE), PRODES: Brazil Amazon Forest monitoring - Municipal_Deforestation_2000_to_2020_PRODES.csv. Accessed in November 2019, URL: http://www.obt.inpe.br/prodes/dashboard/prodesrates.html 35 MapBiomas, Statistics – Coverage and Transitions Legal Amazon, Collection 5, Brazilian Annual Land Use and Land Cover Mapping Project. Accessed in June 2021, URL: https://brasil.mapbiomas.org/en/estatisticas/ Ministério do Desenvolvimento Agrário e Agricultura Familiar (MDA), Terra Legal. Accessed in June 2021, URL: https://www.gov.br/mda/pt-br Moffette, F., Skidmore, M., & Gibbs, H. K., Complementary dataset.dta (2021). Environmental policies that shape productivity: Evidence from cattle ranching in the Amazon. Journal of Environmental Economics and Management, 109, 102490. URL: https://doi.org/10.1016/j.jeem.2021.102490 Procuradoria Geral da Uniao, Sistema de Gestão de Convênios e Contratos de Repasse do Governo Federal (SICONV) – Convênios, Consulta de Convênios e Acordos, Portal da Transparência do Governo Federal. Accessed in August 2021, URL: https://portaldatransparencia.gov.br/convenios/consulta?ordenarPor=orgao &direcao=desc Sistema de Informações Contábeis e Fiscais do Setor Público Brasileiro (Siconfi), FINBRA (Finanças Municipais) - Dados Contábeis dos Municípios. Accessed in November 2020, URL: https://www.gov.br/tesouronacional/pt-br/estados-emunicipios/dados-consolidados/finbra-financas-municipais Sistema Nacional de Cadastro Ambiental Rural (SICAR), SICAR, Base de Downloads. Accessed in June 2021, URL: http://www.car.gov.br/publico/imoveis/index Tribunal Supremo Eleitoral, Candidatos - 2000, 2004, 2008, 2012, 2016, Portal de Dados Abertos do TSE. Accessed in November 2019, URL: https://dadosabertos.tse.jus.br/dataset Tribunal Supremo Eleitoral, Prestação de Contas Eleitorais – 2004, 2008, 2012, 2016, Portal de Dados Abertos do TSE. Accessed in November 2019, URL: https://dadosabertos.tse.jus.br/dataset Tribunal Supremo Eleitoral, Resultados – 2000 2004, 2008, 2012, 2016, Portal de Dados Abertos do TSE. Accessed in November 2019, URL: https://dadosabertos.tse.jus.br/dataset Vilhuber, L., Connolly, M., Koren, M., Llull, J., & Morrow, P. (2020). A template README for social science replication packages. Zenodo. URL: https://doi.org/10.5281/zenodo.4319999