{"type":"script","doc_desc":{"producers":[{"name":"Reproducibility WBG","abbr":"DECDI","affiliation":"World Bank - Development Impact Department","role":"Verification and preparation of metadata"}],"prod_date":"2026-11-05","version":"1"},"project_desc":{"authoring_entity":[{"name":"Daniel Ayalew Ali","affiliation":"World Bank","email":"dali1@worldbank.org"},{"name":"Klaus W. Deininger","affiliation":"World Bank","email":"kdeininger@worldbank.org"},{"name":"Hari K. Nagarajan","affiliation":"IIM Ahmedabad","email":"hknagarajan@gmail.com"},{"name":"Abhiman Das","affiliation":"IIM Ahmedabad","email":"abhiman@iima.ac.in"},{"name":"Parth Hirpara","affiliation":"IIM Ahmedabad","email":"phd21parthh@iima.ac.in"}],"title_statement":{"title":"Reproducibility package for Digital Land Rights And Rural Credit Access: Lessons From Village Habitation (Abadi) \nLand Titling In India","idno":"RR_IND_2026_759"},"data_statement":"The reproducibility package relies on 2 types of data: Open and Restricted data. For the source, access type, file location, and citation of each dataset, refer to the Datasets section and the README file.","software":[{"name":"Stata","version":"19.5 MP"}],"scripts":[{"title":"Reproducibility package for Digital Land Rights And Rural Credit Access: Lessons From Village Habitation (Abadi) \nLand Titling In India","date":"2026-11","notes":"Computational reproducibility verified by Development Impact (DECDI) Analytics team, World Bank.","instructions":"See README in reproducibility package.","file_name":"RR_IND_2026_759","zip_package":"RR_IND_2026_759.zip","dependencies":"Stata dependencies are listed in the ado folder."}],"repository_uri":[{"name":"Reproducible Research Repository (World Bank)","uri":"https:\/\/reproducibility.worldbank.org"}],"production_date":"2026-11-05","abstract":"To test whether the overwhelming finding of zero credit effects from rural land titling in the literature can be attributed to a perception of registries as static document stores and a narrow focus on agricultural land, we explore India's SVAMITVA program. This program issued property cards at low cost to rural residential homesteads, the only asset for the 56% of rural households owning no agricultural land, in a way that is digitally integrated into national lending infrastructure. Heterogeneity-robust difference-in-differences estimates across 42,000 villages in Madhya Pradesh show property card issuance created sustained land and credit market activity from zero and reached remote communities as effectively as those near bank branches. This reframes an ideologically charged debate into an actionable agenda that views property registries as key digital public infrastructure, one that India's ongoing digitization and regulatory reforms are well-placed to advance.","geographic_units":[{"name":"India","code":"IND"}],"output":[{"type":"Working Paper","description":"Policy Research Working Paper (PRWP)","title":"Digital Land Rights And Rural Credit Access: Lessons From Village Habitation (Abadi) \nLand Titling In India"}],"language":[{"name":"English","code":"EN"}],"technology_requirements":"Run time ~ 5 hours","disclaimer":"The materials in the reproducibility packages are distributed as they were prepared by the staff of the International Bank for Reconstruction and Development\/The World Bank. The findings, interpretations, and conclusions expressed in this event do not necessarily reflect the views of the World Bank, the Executive Directors of the World Bank, or the governments they represent. The World Bank does not guarantee the accuracy of the materials included in the reproducibility package.","license":[{"name":"MIT License","uri":"https:\/\/opensource.org\/license\/mit"},{"name":"World Bank IGO Rider","uri":"https:\/\/github.com\/worldbank\/metadata-editor\/blob\/main\/WB-IGO-RIDER.md"}],"contacts":[{"name":"Daniel Ayalew Ali","affiliation":"World Bank","email":"dali1@worldbank.org"},{"name":"Reproducibility WBG","affiliation":"World Bank","email":"reproducibility@worldbank.org"}],"datasets":[{"name":"SVAMITVA Program Data","note":"Village-level drone-flying dates, map handover dates, and property-card preparation\/distribution counts and dates, for Gujarat, Madhya Pradesh, and Maharashtra. Data for Madhya Pradesh and Gujarat come from the public SVAMITVA website; data for Maharashtra were obtained from the National Informatics Centre (NIC) by the order of the Joint Secretary of MoPR, as that state's figures are not published on the website. Access by state: (1) Madhya Pradesh and Gujarat \u2014 publicly available from the SVAMITVA website: https:\/\/svamitva.nic.in\/svamitva_hindi\/; extract dated 11-11-2025. Follow the data use policy of the SVAMITVA website. (2) Maharashtra \u2014 confidential. Under MoPR Work Order No. M-11015\/192\/2023-Governance (13 October 2025), all data, reports, and deliverables are MoPR property. IIM-A may not disclose confidential information or use MoPR's name or logo without prior written approval. To access Maharashtra data, contact MoPR's secretary office: secy-mopr@nic.in; contact information at https:\/\/panchayat.gov.in\/en\/whos-who\/. Contact details of NIC: nic-mopr@nic.in; website: https:\/\/panchayat.gov.in\/en\/whoswho\/nic\/. File location: DataManipulation\/Data\/Raw_Svamitva\/NIC _SVAMITVA-11-11-2025_GJ+MP+MH.xlsx.O","access_type":"Data access was granted directly to the study authors by the data owners\/managers. It was obtained with a custom data license that does not allow for redistribution and it is not included in the reproducibility package.","license":"Custom License","citation":"Authors' compilation. 2025. SVAMITVA Program Data [dataset]. Compiled from: Government of India, Ministry of Panchayati Raj (MoPR) and National Informatics Centre (NIC), Joint Secretary of MoPR. Accessed November 2025."},{"name":"Madhya Pradesh Land Records \u2014 Khasra, Mutations, and Mortgage Data","note":"Madhya Pradesh village-level administrative land records comprising three files: (1) Khasra_all_sheets.csv \u2014 the official land parcel register (khasra), annually from FY2019, available separately for agricultural and residential parcels. (2) mutation_all_files.csv \u2014 land transactions (mutations), half-yearly from 2020, available separately for agricultural and residential parcels. (3) mortgage_all_files.csv \u2014 parcels charged by banks as loan collateral and amounts lent, quarterly from 2018, available separately for agricultural and residential parcels. Since July 1, 2023, these records have been connected to the Reserve Bank of India's Unified Lending Interface (ULI), and property cards are linked to the state's digital Revenue Court Management System (RCMS) for foreclosure processing under the SARFAESI Act. Data obtained on the order of MoPR from Madhya Pradesh Land Records Management Society (MPLRS). Access is confidential: the information is intended solely for the designated recipient(s) for the specified purpose(s) and may include personal data, which must be handled, processed, and protected to ensure its confidentiality, security, and privacy. To access the data, contact MPLRS, Bhopal; Office of Commissioner Land Records, Gwalior; Madhya Pradesh, India; Email: mp-lrs@mp.gov.in. MP Bhulekh Portal: https:\/\/webgis2.mpbhulekh.gov.in\/#\/home?lang=en. File locations: DataManipulation\/Data\/Raw_Khasra_Mutations_Mortgage\/Khasra_all_sheets.csv; \nmutation_all_files.csv; mortgage_all_files.csv.","access_type":"Data access was granted directly to the study authors by the data owners\/managers. It was obtained with a custom data license that does not allow for redistribution and it is not included in the reproducibility package.","license":"Custom License","uri":"https:\/\/webgis2.mpbhulekh.gov.in\/#\/home?lang=en","citation":"Government of Madhya Pradesh. 2025. \"Madhya Pradesh Land Records [dataset]. https:\/\/webgis2.mpbhulekh.gov.in\/#\/home?lang=en."},{"name":"Maharashtra Plot-Level Loans ","note":"Plot-level loans secured against property cards in Maharashtra, including Plot Survey Number (CTS), Bank Name, loan amount (Rs.), Mutation number, mutation date, and Inward Number from 2020 to as of November 2025; lender type generated using bank name. Data is confidential, provided by officials of Land Records. To access, contact the Office of Settlement Commissioner and Director of Land Records, Maharashtra. Source portal: https:\/\/bhumiabhilekh.maharashtra.gov.in\/?districtId=37. File location: DataManipulation\/Data\/Plot_Level_Loans\/Maharashtra_SVAMITVA Loan Mortgauge Sheet_25_11_2025.xlsx.","access_type":"Data access was granted directly to the study authors by the data owners\/managers. It was obtained with a custom data license that does not allow for redistribution and it is not included in the reproducibility package.","license":"Custom License","uri":"https:\/\/bhumiabhilekh.maharashtra.gov.in\/?districtId=37","citation":"Government of Maharashtra. 2025. \"Maharashtra Plot-Level Loans [dataset]. https:\/\/bhumiabhilekh.maharashtra.gov.in\/?districtId=37. "},{"name":"Madhya Pradesh Plot-Level Loans ","note":"Plot-level loans secured against property cards in Madhya Pradesh, including plot number, block number, area, owner name, caste category, loan open date, bank name, branch name, IFSC code, and loan amount (Rs.) from 2020 to as of November 2025. Further derived variables include lender type (generated using bank name), borrower gender (using name of owner), and urban\/rural status (using bank branch address and IFSC code). Data is confidential, provided by officials of Land Records from MPLRS. To access, contact MPLRS, Bhopal; Office of Commissioner Land Records, Madhya Pradesh. Source portal: https:\/\/webgis2.mpbhulekh.gov.in\/#\/home?lang=en. File location: DataManipulation\/Data\/Plot_Level_Loans\/Plot_Loan_Data_04-11-2025 fromMP_Gender&Urban-Rural.xlsx.","access_type":"Data access was granted directly to the study authors by the data owners\/managers. It was obtained with a custom data license that does not allow for redistribution and it is not included in the reproducibility package.","license":"Custom License","uri":"https:\/\/webgis2.mpbhulekh.gov.in\/#\/home?lang=en","citation":"Government of Madhya Pradesh. 2025. Madhya Pradesh Plot-Level Loans [dataset]. https:\/\/webgis2.mpbhulekh.gov.in\/#\/home?lang=en. "},{"name":"RBI Bank Branch Data \u2014 2023 Vintage ","note":"All India scheduled commercial bank (SCB) branch addresses, bank\/branch identifiers, and population-group classification (rural\/semi-urban\/urban\/metropolitan) as of 2023. Constructed from the RBI Master Office File (MOF) and linked to India Post pincode and locality information and the Local Government Directory (LGD). Main construction steps: extract preliminary pincodes from RBI branch addresses; validate or correct against India Post records; link pincodes to postal localities; match localities to LGD villages using administrative information (state, district, sub-district). Latitude and longitude attached from India Post pincode directory. Exact, fuzzy, and manual matching used to resolve spelling differences, ambiguous localities, and cases where several villages or branches share a pincode. The coordinates generally represent the relevant postal area or locality rather than the precise bank building. Replication requires the same versions of the RBI, India Post, and LGD source files, the matching and correction records, and manual review decisions; source files and administrative boundaries may change over time. Data sources used in construction: RBI Master Office File (MOF): https:\/\/dbieold.rbi.org.in\/DBIE\/dbie.rbi?site=publications; India Post (All India Pincode Directory): https:\/\/www.indiapost.gov.in\/; Local Government Directory (LGD) All-Village Directory: https:\/\/lgdirectory.gov.in\/downloadDirectory.do. File locations: DataManipulation\/Data\/Raw_BankBranch\/MOF_PINCODE_Corrected(12_23)_07_04_2026.dta; MP_BankBranch.csv.","access_type":"Data is publicly available and included in the reproducibility package.","license":"Open Data","uri":"https:\/\/dbieold.rbi.org.in\/DBIE\/dbie.rbi?site=publications","citation":"Authors' compilation. 2026. \"RBI Bank Branch Data, 2023 Vintage [dataset]. Compiled from: Reserve Bank of India, Master Office File (MOF), India Post, All India Pincode Directory and Local Government Directory (LGD). https:\/\/dbieold.rbi.org.in\/DBIE\/dbie.rbi?site=publications"},{"name":"RBI Bank Branch Data \u2014 2026 Vintage ","note":"All India scheduled commercial bank (SCB) branch addresses, bank\/branch identifiers, and population-group classification (rural\/semi-urban\/urban\/metropolitan) as of 2026. Based on the RBI Master Office File (MOF) and the RBI CISBI (Central Information System for Banking Infrastructure) master branch dataset. Geographic coordinates obtained via the Google Maps Geocoding API, with manual cross-checks for low-confidence matches. The 2026 branch data, the existing geocoded branch data, and the 2023 vintage are compared to identify: the current set of bank branches in Madhya Pradesh; unmatched branches across datasets; branches present in the 2023 data but not in the 2026 list. Python scripts geocode three complementary groups using the Google Maps API: (i) the current 2026 Madhya Pradesh branch list, (ii) branches from the 2023 geocoded list unmatched to the 2026 list, and (iii) branches present only in the older 2023 list without geocodes. For each branch, the scripts construct a search address and submit it to the Google Maps Geocoding API; the API returns latitude, longitude, match status, and place type. Records with no result are retried using a shorter address. Coordinates are visually reviewed; suspected anomalies are checked through manual online searches and corrected where necessary. Third-party Google Maps Geocoding API usage terms apply to the geocoded coordinates. Download: https:\/\/dbieold.rbi.org.in\/DBIE\/dbie.rbi?site=publications. File location: DataManipulation\/Data\/Raw_BankBranch\/Bank Branch Data MASTER_CISBI_Data_RBI_06_04_2026.xlsx.","access_type":"Data is publicly available and included in the reproducibility package.","license":"Open Data","uri":"https:\/\/dbieold.rbi.org.in\/DBIE\/dbie.rbi?site=publications","citation":"Authors' compilation. 2026. \"RBI Bank Branch Data, 2026 Vintage [dataset]. Compiled from: Reserve Bank of India, Master Office File (MOF) and CISBI. https:\/\/dbieold.rbi.org.in\/DBIE\/dbie.rbi?site=publications"},{"name":"Census of India 2011 ","note":"State\/district\/sub-district\/village hierarchy, population, literacy, and scheduled-tribe shares. Source: Census of India, 2011, Registrar General and Census Commissioner, Government of India. Data accessed in 2026. Download: https:\/\/censusindia.gov.in\/census.website\/data\/population-finder. Follow the data use policy at https:\/\/censusindia.gov.in\/census.website\/en\/node\/286. File location: DataManipulation\/Data\/Raw_Census\/Census2011-IndiaStateDistSbDistVill-0000.xlsx.","access_type":"Data is publicly available and included in the reproducibility package.","license":"Open Data","uri":"https:\/\/censusindia.gov.in\/census.website\/data\/population-finder","citation":"Office of the Registrar General and Census Commissioner. 2011. Census of India 2011 [dataset]. https:\/\/censusindia.gov.in\/census.website\/data\/population-finder. ","license_uri":" https:\/\/censusindia.gov.in\/census.website\/en\/node\/286"},{"name":"Madhya Pradesh PESA Scheduled Tribal Area Villages","note":"Village-level PESA (Panchayats Extension to Scheduled Areas) scheduled-tribal-area classification (ScheduledAreaPESA\/ispesavillage flags) for Madhya Pradesh's 19 PESA districts: Alirajpur, Barwani, Betul, Balaghat, Chhindwara, Dhar, Dindori, Jhabua, Khandwa, Khargone, Mandla, Ratlam, Shahdol, Sheopur, Sidhi, Umaria, Hoshangabad, Burhanpur, and Anooppur. Source: PESA Portal, The Provisions of the Panchayats Act, 1996; Ministry of Panchayati Raj, Government of India. Extracted June 19, 2026 from https:\/\/egramswaraj.gov.in\/pesaDashboardView.do. Extraction procedure: (1) Navigate to https:\/\/egramswaraj.gov.in\/getStateWisePesaVillageCount.do; (2) select a state to open the GP-wise village list at https:\/\/egramswaraj.gov.in\/getStateWisePesaVillage.do; (3) open the browser developer console (F12), select the Console tab; if pasting is blocked, type 'allow pasting' and press Enter; (4) paste and run the provided JavaScript snippet to extract the DataTable and download as CSV; (5) update the output filename for each state before running. Follow the data use policy of the PESA Portal. File location: DataManipulation\/Data\/Raw_PESA\/MP_PESA_Villages_All_12407.csv.","access_type":"Data is publicly available and included in the reproducibility package.","license":"Open Data","uri":"https:\/\/egramswaraj.gov.in\/pesaDashboardView.do","citation":"Ministry of Panchayati Raj. 2026. Madhya Pradesh PESA Scheduled Tribal Area Villages [dataset]. https:\/\/egramswaraj.gov.in\\\/pesaDashboardView.do. Accessed June 2026."},{"name":"Economic Census","note":"Village-level data for Madhya Pradesh and Maharashtra from the Socioeconomic High-resolution Rural-Urban Geographic Database (SHRUG), India Data Lab. Three files used: (1) shrid.csv \u2014 village shapefiles and area, used for spatial matching of bank branches to villages; (2) ec13_shrid (Economic Census) \u2014 village-level firm and employment counts; (3) secc_rural_shrid.dta (SECC, rural) \u2014 scheduled-caste\\\/tribe shares, land ownership, income sources and thresholds, and housing characteristics. Data accessed in 2026. Download: https:\/\/devdatalab.org\/shrug. Citation: Asher, S., T. Lunt, R. Matsuura, and P. Novosad (2021). Follow the data use policy of the SHRUG open data platform. File locations: DataManipulation\/Data\/SHRUG_EconomicCensus\/shrid.csv; ec13_shrid; secc_rural_shrid.dta.","access_type":"Data is publicly available and included in the reproducibility package.","license":"Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)","uri":"https:\/\/devdatalab.org\/shrug","citation":"Asher, S., T. Lunt, R. Matsuura, and P. Novosad. 2021. Development Research at High Geographic Resolution: An Analysis of Night-Lights, Firms, and Poverty in India Using the Shrug Open Data Platform","license_uri":"https:\/\/creativecommons.org\/licenses\/by-nc-sa\/4.0\/"},{"name":"Village-wise Identifiers","note":"Village-wise identifiers including LGD code, Census 2011 code, and Gram Panchayat (GP) code. Source: Local Government Directory (LGD), Ministry of Panchayati Raj, Government of India. Data accessed in 2026. Download: https:\/\/lgdirectory.gov.in\/downloadDirectory.do. Follow the data use policy of the LGD website. File location: DataManipulation\/Data\/LGD_VillageCode\/villageofSpecificState2026_03_30_21_22_35_073.xlsx.","access_type":"Data is publicly available and included in the reproducibility package.","license":"Open Data","uri":"https:\/\/lgdirectory.gov.in\/downloadDirectory.do","citation":"Ministry of Panchayati Raj. 2026. Village-wise Identifiers [dataset]. https:\/\/lgdirectory.gov.in\/downloadDirectory.do. Accessed 2026."},{"name":"CORS (Continuously Operating Reference Stations) Geolocations \u2014 Madhya Pradesh","note":"Village-wise geolocations of Continuously Operating Reference Stations (CORS) in Madhya Pradesh as of April 2024. Obtained from the National Informatics Centre (NIC) on the order of the Joint Secretary, Ministry of Panchayati Raj (MoPR). Maintained by the Office of the Surveyor General of India, Survey of India. Access is confidential: under MoPR Work Order No. M-11015\/192\/2023-Governance (13 October 2025), all data, reports, and deliverables are MoPR property. IIM-A may not disclose confidential information or use MoPR's name or logo without prior written approval. To access, contact MoPR's secretary office: secy-mopr@nic.in; https:\/\/panchayat.gov.in\/en\/whos-who\/. NIC contact: nic-mopr@nic.in; https:\/\/panchayat.gov.in\/en\/whoswho\/nic\/. Alternatively, request from the Office of the Surveyor General of India, Dehradun, India. File location: DataManipulation\/Data\/GIS\/XLS\/MP_Villages_CORS_distance.xlsx.","access_type":"Data access was granted directly to the study authors by the data owners\/managers. It was obtained with a custom data license that does not allow for redistribution and it is not included in the reproducibility package.","license":"Custom License","uri":"https:\/\/panchayat.gov.in\/en\/whos-who\/","citation":"Authors' compilation. 2024. CORS Geolocations [dataset]. Compiled from: National Informatics Centre (NIC), Ministry of Panchayati Raj, Office of the Surveyor General of India. Accessed April 2024"},{"name":"GIS-Derived Village-Level Measures ","note":"Authors' compilation of five village-level GIS measures for Madhya Pradesh, extracted from remote sensing products using Google Earth Engine (GEE) scripts, plus one derived spatial matching output. All files located in DataManipulation\/Data\/GIS\/XLS\/. (1) village_builtup_timeseries_2016_2025_MP.csv: built-up area time series 2016-2025 per village. Source: World Settlement Footprint (WSF) Evolution\/Tracker products. GEE script: https:\/\/code.earthengine.google.com\/79aac8309fc6948d816b47475704b989. (2) village_builtup_WSF2019_MP.csv: built-up area per village from the WSF 2019 layer. Source: World Settlement Footprint (WSF) 2019, a global 10m-resolution binary raster mask produced by the German Aerospace Center (DLR) using multitemporal Sentinel-1 (SAR) and Sentinel-2 (optical) imagery; pixel value 255 indicates human settlement. GEE script: https:\/\/code.earthengine.google.com\/018a0bcd3a20e8d0077acb9ca97db79b. (3) village_forest_2018_MP.csv: forest cover per village. Source: Hansen Global Forest Change dataset, version 1.6 (2018), produced by the University of Maryland at 30m resolution from Landsat 7 ETM+ and Landsat 8 OLI imagery; provides annual forest loss from 2001-2018 and baseline tree canopy cover for 2000. GEE script: https:\/\/code.earthengine.google.com\/c1f2842187ba69e2982467096ed4da9a. (4) village_rice_winter_2018_MP.csv: winter (rabi) rice area per village. Source: Chen, X. et al. (2023), \"High-Resolution Distribution Dataset of Paddy Rice in India (2018),\" Figshare, doi:10.6084\/m9.figshare.24228619. GEE script: https:\/\/code.earthengine.google.com\/c5c7835ef1d1e94776b5cfd0cabcfb30. (5) village_rice_2018_MP.csv: Kharif (monsoon) season rice area per village. Source: Multi-temporal Sentinel-1 C-band SAR backscatter in VV and VH polarizations. GEE script: https:\/\/code.earthengine.google.com\/77ea033260c043769f93915c78c051e4. (6) villages_branch_counts.csv: Madhya Pradesh village-level number of bank branches within successive distance bands (2, 5, 10, and 25 km). Constructed by spatially matching geocoded RBI bank branch locations (see RBI Bank Branch Data entries) to village shapefiles from SHRUG using a Python script that counts branches within each distance band. Village boundaries and Census 2011 village codes sourced from SHRUG (https:\/\/devdatalab.org\/shrug).\nFile location: DataManipulation\/Data\/GIS\/XLS\/village_builtup_timeseries_2016_2025_MP.csv, village_builtup_WSF2019_MP.csv, village_forest_2018_MP.csv, village_rice_winter_2018_MP.csv, village_rice_2018_MP.csv, villages_branch_counts.csv","access_type":"Data is publicly available and included in the reproducibility package.","license":"Custom License","citation":"Authors' compilation. 2026. GIS-Derived Village-Level Measures [dataset]. Compiled from: World Settlement Footprint (WSF) Evolution\/Tracker products, German Aerospace Center (DLR), World Settlement Footprint (WSF) 2019, Hansen Global Forest Change dataset v1.6, University of Maryland, Chen, X. et al. (2023), High-Resolution Distribution Dataset of Paddy Rice in India (2018), Figshare; doi:10.6084\/m9.figshare.24228619, Sentinel-1 C-band SAR backscatter, RBI Bank Branch Data, Asher et al. (2021), India Data Lab. "}],"reproduction_instructions":"To reproduce the findings in this paper, a replicator must:\n1. Secure Access to Data: Access the datasets not included in the package. See the Datasets section for more details.\n2. Open the master do file `main.do`, update the directory on line 7 and run the code\n\nSince some of the data is restricted , the package includes the outputs produced by the authors, which can be used to review the results presented in the paper.","technology_environment":"Paper exhibits were reproduced on a computer with the following specifications:\n\u2022 OS: Windows 11 Enterprise\n\u2022 Processor: Intel(R) Xeon(R) Gold 5218 CPU @ 2.30GHz (2.30 GHz) (2 processors)\n\u2022 Memory available: 16 GB"},"datacite":{"creators":[{"givenName":"Daniel Ayalew","familyName":"Ali","nameType":"Personal","affiliation":[{"name":"World Bank","affiliationIdentifier":"https:\/\/ror.org\/00ae7jd04","affiliationIdentifierScheme":"ROR","schemeUri":"https:\/\/ror.org"}]},{"givenName":"Klaus W.","familyName":"Deininger","nameType":"Personal","affiliation":[{"name":"World Bank","affiliationIdentifier":"https:\/\/ror.org\/00ae7jd04","affiliationIdentifierScheme":"ROR","schemeUri":"https:\/\/ror.org"}]},{"givenName":"Hari K.","familyName":"Nagarajan","nameType":"Personal","affiliation":[{"name":"IIM Ahmedabad","affiliationIdentifier":"https:\/\/ror.org\/02egcpy68","affiliationIdentifierScheme":"ROR","schemeUri":"https:\/\/ror.org"}]},{"givenName":"Abhiman","familyName":"Das","nameType":"Personal","affiliation":[{"name":"IIM Ahmedabad","affiliationIdentifier":"https:\/\/ror.org\/02egcpy68","affiliationIdentifierScheme":"ROR","schemeUri":"https:\/\/ror.org"}]},{"givenName":"Parth","familyName":"Hirpara","nameType":"Personal","affiliation":[{"name":"IIM Ahmedabad","affiliationIdentifier":"https:\/\/ror.org\/02egcpy68","affiliationIdentifierScheme":"ROR","schemeUri":"https:\/\/ror.org"}]}],"titles":[{"lang":"en","title":"Reproducibility package for Digital Land Rights And Rural Credit Access: Lessons From Village Habitation (Abadi) \nLand Titling In India"},{"title":"RR_IND_2026_759","titleType":"Other"}],"publisher":"World Bank","publicationYear":"2026","types":{"resourceType":"Reproducibility package","resourceTypeGeneral":"Other"},"url":"https:\/\/reproducibility.worldbank.org\/index.php\/catalog\/study\/RR_IND_2026_759","language":"en"},"tags":[{"tag":"DOI"},{"tag":"Open Code"},{"tag":"Restricted Data"}],"schematype":"script"}