Package 'realestatebr'

Description

Housing credit data from Brazilian housing finance system (SFH) including SBPE flows, financed units, and home equity loans.

Retrieve this dataset with get_dataset() using the name "abecip".

abecip <- get_dataset("abecip")
abecip_units <- get_dataset("abecip", table = "units")

Details

• Source: ABECIP - Associação Brasileira das Entidades de Crédito Imobiliário

• URL: https://www.abecip.org.br

• Geography: Brazil

• Frequency: monthly

• Coverage: 1982-present (varies by category)

• Tables: "sbpe", "units", "cgi" (default: "sbpe")

Column names translated from Portuguese to English following standard patterns.

Table "sbpe" (SBPE Monetary Flows)

Monetary flows from SBPE (Sistema Brasileiro de Poupança e Empréstimo). This is the default table. Coverage: January 1982-present.

date

Reference month.

sbpe_inflow

Deposits into SBPE savings accounts during the month (R$ million; historical values in the currency of the period).

sbpe_outflow

Withdrawals from SBPE savings accounts during the month (R$ million).

sbpe_netflow

Net savings flow: inflow minus outflow (R$ million).

sbpe_netflow_pct

Net flow as a share of the SBPE savings stock.

sbpe_yield

Interest credited to SBPE savings accounts (R$ million).

sbpe_stock

End-of-month SBPE savings stock (R$ million).

rural_inflow

Deposits into rural savings accounts during the month (R$ million).

rural_outflow

Withdrawals from rural savings accounts during the month (R$ million).

rural_netflow

Net rural savings flow: inflow minus outflow (R$ million).

rural_netflow_pct

Net rural flow as a share of the rural savings stock.

rural_yield

Interest credited to rural savings accounts (R$ million).

rural_stock

End-of-month rural savings stock (R$ million).

total_stock

Combined SBPE and rural savings stock (R$ million).

total_netflow

Combined SBPE and rural net savings flow (R$ million).

Table "units" (Financed Units)

Number of units financed by SBPE, split by construction and acquisition. Coverage: January 2002-present.

date

Reference month.

units_construction

Number of units financed for construction.

units_acquisition

Number of units financed for acquisition.

units_total

Total number of financed units.

currency_construction

Value of construction financing (R$ million).

currency_acquisition

Value of acquisition financing (R$ million).

currency_total

Total value of financing (R$ million).

Table "cgi" (Home Equity Loans (CGI))

Summary data on home equity loans including default rates and average terms. Coverage: January 2017-present.

year

Reference year.

date

Reference month.

new_contracts

Number of new home equity loan contracts signed in the month.

stock_contracts

Number of outstanding contracts at the end of the month.

loan

Value of new loans granted in the month (R$).

outstanding_balance

Outstanding loan balance at the end of the month (R$).

average_term

Average contract term (months).

default_rate

Share of loans in default (percent).

Source

ABECIP - Associação Brasileira das Entidades de Crédito Imobiliário

See Also

get_dataset(), list_datasets(), get_dataset_info()

Other datasets: abrainc, bcb_realestate, bcb_series, fgv_ibre, rppi, rppi_bis, secovi

Description

Primary real estate market indicators including launches, sales, and business conditions from 66+ partnered developers.

Retrieve this dataset with get_dataset() using the name "abrainc".

abrainc <- get_dataset("abrainc")
abrainc_radar <- get_dataset("abrainc", table = "radar")

Details

• Source: ABRAINC/FIPE

• URL: https://www.fipe.org.br/pt-br/indices/abrainc

• Geography: Brazil (major cities)

• Frequency: quarterly

• Coverage: 2014-present

• Tables: "indicator", "radar", "leading" (default: "indicator")

Social Housing (MCMV) refers to Minha Casa Minha Vida and Casa Verde Amarela programs.

Table "indicator" (Market Indicators)

Broad numbers of launches, sales, supply in the primary market. This is the default table.

date

Reference month.

year

Reference year.

category

Indicator group (e.g. new_units, sold, delivered).

variable

Market segment: total, market_rate, or social_housing (MCMV and related programs).

value

Number of units.

variable_label

Human-readable label for variable.

Table "radar" (Business Radar)

0-10 standardized index for general business conditions.

date

Reference month.

year

Reference year.

category

Radar dimension (e.g. macro, credit, demand).

variable

Indicator within the dimension (e.g. confidence, activity, interest).

source

Source of the underlying series (e.g. FGV, BCB).

value

Standardized 0-10 score.

avg_category

Average score of the category over the full sample.

avg_year_category

Average score of the category in the year.

avg_year_variable

Average score of the variable in the year.

ma3

3-month moving average of value.

ma6

6-month moving average of value.

variable_label

Human-readable label for variable.

Table "leading" (Leading Indicator)

Building permits in São Paulo as real estate leading indicator.

date

Reference month.

year

Reference year.

variable

Series identifier: leading_index, leading_index_12m, or alvaras_total (building permits).

zone

São Paulo city zone (Total, Centro, Zona Norte, and others).

value

Series value; index points, percent change, or permit counts depending on variable.

variable_label

Human-readable label for variable.

Source

ABRAINC/FIPE

See Also

get_dataset(), list_datasets(), get_dataset_info()

Other datasets: abecip, bcb_realestate, bcb_series, fgv_ibre, rppi, rppi_bis, secovi

Description

List of main Brazilian real estate players listed on B3.

Usage

b3_real_estate

Format

b3_real_estate

A tibble with 38 rows and 3 columns:

symbol

Stock ticker.

name

Full company name.

name_short

A shorter version of the company name.

Source

B3

Description

A table with metadata for BCB economic series. Use with get_dataset("bcb_series"). The hierarchy column controls which series are returned by default: pass table = "core" for the most relevant real estate series, or a broader level for more macroeconomic context (see get_dataset).

Usage

bcb_metadata

Format

bcb_metadata

A data frame with 140 rows and 11 columns:

code_bcb

Numeric code identifying the series.

bcb_category

Category of the series.

name_simplified

Simplified name of the series.

name_pt

Full name of the series in Portuguese.

name

Full name of the series in English.

unit

Unit of the series.

frequency

Frequency of the series.

first_value

Date of the first available observation.

last_value

Date of the last available observation.

source

Source of the series.

hierarchy

Integer relevance tier: 1 = core real estate credit series; 2 = primary (key macro series such as SELIC, IPCA, INCC); 3 = secondary (broader macro context); 4 = tertiary (less relevant or discontinued series).

Source

Brazilian Central Bank (BCB)

Description

Comprehensive real estate credit and market data from Brazilian Central Bank.

Retrieve this dataset with get_dataset() using the name "bcb_realestate".

bcb_realestate <- get_dataset("bcb_realestate")
bcb_realestate_accounting <- get_dataset("bcb_realestate", table = "accounting")

Details

• Source: Banco Central do Brasil

• URL: https://dadosabertos.bcb.gov.br/dataset/informacoes-do-mercado-imobiliario

• Geography: Brazil (by state)

• Frequency: monthly

• Coverage: 2001-present (varies by category)

• Tables: "accounting", "application", "indices", "sources", "units" (default: "all")

Complex multi-level series structure; v1-v5 columns contain series components.

Columns

All tables share the structure below; the table argument filters which series are returned.

date

End-of-month reference date (last day of the month).

category

Top-level series grouping (e.g. credito, contabil, direcionamento, fontes, imoveis).

type

Series subtype within the category (e.g. estoque, contratacao, financiamento).

v1

Series identifier component 1; meaning varies by series (e.g. carteira, borrower type, region).

v2

Series identifier component 2 (e.g. br, pf, pj).

v3

Series identifier component 3 (e.g. credit line such as sfh, fgts, home-equity).

v4

Series identifier component 4 (often a state abbreviation or credit line).

v5

Series identifier component 5 (often a state abbreviation or br).

series_info

Full underscore-separated series identifier; together with date it uniquely identifies an observation.

value

Series value; unit varies by series (R$, units, or percent).

year

Reference year.

month

Reference month (1-12).

abbrev_state

Two-letter state abbreviation, or BR for the national aggregate.

Source

Banco Central do Brasil

See Also

get_dataset(), list_datasets(), get_dataset_info()

Other datasets: abecip, abrainc, bcb_series, fgv_ibre, rppi, rppi_bis, secovi

Description

General economic and real estate related time series from Brazilian Central Bank.

Retrieve this dataset with get_dataset() using the name "bcb_series".

bcb_series <- get_dataset("bcb_series")
bcb_series_primary <- get_dataset("bcb_series", table = "primary")

Details

• Source: Banco Central do Brasil - SGS

• URL: https://www3.bcb.gov.br/sgspub

• Geography: Brazil

• Frequency: varies (daily/monthly/quarterly)

• Coverage: varies by series

• Tables: "core", "primary", "secondary", "tertiary", "full" (default: "core")

Metadata available in both Portuguese and English.

Columns

All tables share the structure below; the table argument filters which series are returned.

date

Reference date (frequency varies by series).

code_bcb

Numeric code of the series in the BCB SGS system.

name_simplified

Short series identifier; see the bundled bcb_metadata table for full names and units.

value

Series value.

Source

Banco Central do Brasil - SGS

See Also

get_dataset(), list_datasets(), get_dataset_info()

Other datasets: abecip, abrainc, bcb_realestate, fgv_ibre, rppi, rppi_bis, secovi

Description

Drops every dataset memoised during the current R session. Useful when iterating during development or to force re-fetch without restarting R.

Usage

clear_session_cache()

Value

NULL, invisibly.

Examples

clear_session_cache()

Description

A table with official IBGE identifiers for all Brazilian cities.

Usage

dim_city

Format

An object of class tbl_df (inherits from tbl, data.frame) with 5570 rows and 9 columns.

Details

A tibble with 5,570 rows and 9 columns:

code_muni

7-digit IBGE code identifying the city.

name_muni

Name of the city.

code_state

2-digit IBGE code identifying the state.

abbrev_state

Two-letter state abbreviation (e.g. "SP").

name_state

Name of the state.

code_region

1-digit IBGE code identifying the region.

name_region

Name of the region.

year

Reference year of the IBGE territorial division (2020).

name_simplified

Simplified version of the city name for easier subsetting.

Source

IBGE (Brazilian Institute of Geography and Statistics)

Description

Real estate market indicators from Fundação Getulio Vargas IBRE.

Retrieve this dataset with get_dataset() using the name "fgv_ibre".

fgv_ibre <- get_dataset("fgv_ibre")

Details

• Source: FGV IBRE

• URL: https://portalibre.fgv.br

• Geography: Brazil

• Frequency: monthly

• Coverage: 2010-present

Technical economic terms; standard translations applied.

Columns

date

Reference month.

name_simplified

Short series identifier (e.g. incc_brasil_di, ivar_brazil, ic_cst).

value

Series value.

name_series

Full series name in Portuguese.

code_series

FGV series code.

unit

Unit of the series (index, percent, or indicator).

source

FGV survey of origin (e.g. FGV-INCC, FGV-SONDA).

Source

FGV IBRE

See Also

get_dataset(), list_datasets(), get_dataset_info()

Other datasets: abecip, abrainc, bcb_realestate, bcb_series, rppi, rppi_bis, secovi

Description

Unified interface for accessing all realestatebr datasets. Resolves data from the package's GitHub release assets when possible (fast, pre-processed, updated weekly by CI) and falls back to a fresh download from the original source. Repeated calls within one R session are served from an in-memory memo to avoid redundant network traffic.

Usage

get_dataset(
  name,
  table = NULL,
  source = "auto",
  date_start = NULL,
  date_end = NULL,
  ...
)

Arguments

Value

A tibble or named list, depending on the dataset. Use get_dataset_info to inspect the expected structure.

See Also

list_datasets for available datasets, get_dataset_info for dataset details, clear_session_cache to drop the in-session memo. For table and column documentation of each dataset, see the dataset help topics: abecip, abrainc, bcb_realestate, bcb_series, fgv_ibre, rppi, rppi_bis, secovi.

Examples

abecip_data <- get_dataset("abecip")

sbpe_data <- get_dataset("abecip", table = "sbpe")

bcb_recent <- get_dataset("bcb_series", date_start = as.Date("2020-01-01"))

Description

Returns detailed metadata for a single dataset, including available tables and source information.

Usage

get_dataset_info(name)

Arguments

Value

A named list with the following elements:

metadata

Title, description, geography, frequency, and coverage.

categories

Available tables/subtables and their descriptions.

source_info

Source organization and URL.

technical_info

Cached file names and translation notes.

Examples

info <- get_dataset_info("abecip")
str(info)

Description

Returns a tibble describing all datasets available in the realestatebr package. Optionally filter by category, source organization, or geographic coverage.

Usage

list_datasets(category = NULL, source = NULL, geography = NULL)

Arguments

Value

A tibble with one row per dataset and the following columns:

name

Dataset identifier used with get_dataset.

title

English dataset name.

title_pt

Portuguese dataset name.

description

Brief description.

source

Data source organization.

geography

Geographic coverage.

frequency

Update frequency.

coverage

Time period covered.

available_tables

Comma-separated table names for multi-table datasets.

See Also

get_dataset for retrieving data, get_dataset_info for detailed metadata on a single dataset.

Examples

list_datasets()

list_datasets(source = "BCB")

Description

Comprehensive collection of all Brazilian residential property price indices.

Retrieve this dataset with get_dataset() using the name "rppi".

rppi <- get_dataset("rppi")
rppi_ivgr <- get_dataset("rppi", table = "ivgr")

Details

• Source: Multiple (FIPE/ZAP, IVGR, IGMI, IQA, IQAIW, IVAR, SECOVI-SP)

• Geography: Brazil

• Frequency: monthly

• Coverage: varies by index

• Tables: "fipezap", "ivgr", "igmi", "iqa", "iqaiw", "ivar", "secovi_sp", "sale", "rent", "all" (default: "fipezap")

Index methodologies vary by source; base periods normalized where possible.

Table "fipezap" (FIPE-ZAP Index)

FIPE-ZAP residential property price index. This is the default table. Coverage: Major cities.

date

Reference month.

name_muni

City name or aggregate (e.g. Índice Fipezap).

market

Market segment: residential or commercial.

rent_sale

Transaction type: sale or rent.

variable

Measure: index, chg, acum12m, price_m2, or yield.

rooms

Number of bedrooms (total, 1, 2, 3, or 4).

value

Value of the measure.

Table "ivgr" (IVGR - Índice de Valores Gerais Residenciais)

General residential values index. Coverage: National.

date

Reference month.

name_geo

Geographic area (Brazil).

index

Price index level.

chg

Month-on-month change of the index.

acum12m

Accumulated 12-month change of the index.

Table "igmi" (IGMI - Índice Geral do Mercado Imobiliário)

General real estate market index. Coverage: São Paulo.

date

Reference month.

name_muni

City name or national aggregate.

index

Price index level.

chg

Month-on-month change of the index.

acum12m

Accumulated 12-month change of the index.

Table "iqa" (IQA - Índice QuintoAndar)

QuintoAndar rent price index. Coverage: Major cities.

date

Reference month.

name_muni

City name.

index

Rent index level.

chg

Month-on-month change of the index.

acum12m

Accumulated 12-month change of the index.

Table "iqaiw" (IQAIW - Índice QuintoAndar ImovelWeb)

QuintoAndar ImovelWeb hedonic rent price index. Coverage: Major cities (6 cities).

date

Reference month.

name_muni

City name.

rooms

Number of bedrooms (total, 1, 2, 3, or 4).

index

Rent index level.

chg

Month-on-month change of the index.

acum12m

Accumulated 12-month change of the index.

Table "ivar" (IVAR - Índice de Valores de Aluguéis Residenciais)

Residential rent values index. Coverage: National.

date

Reference month.

name_muni

City name or national aggregate.

index

Rent index level.

chg

Month-on-month change of the index.

acum12m

Accumulated 12-month change of the index.

Table "secovi_sp" (SECOVI-SP Index)

São Paulo real estate syndicate index. Coverage: São Paulo.

date

Reference month.

name_muni

City name (São Paulo).

index

Rent index level.

chg

Month-on-month change of the index.

acum12m

Accumulated 12-month change of the index.

Table "sale" (Stacked Sale Indices)

Harmonized combination of all sale-related indices with source column.

source

Index source: IVG-R, IGMI-R, or FipeZap.

date

Reference month.

name_muni

City name or aggregate (e.g. Brazil).

index

Price index level (each source has its own base period).

chg

Month-on-month change of the index.

acum12m

Accumulated 12-month change of the index.

Table "rent" (Stacked Rent Indices)

Harmonized combination of all rent-related indices with source column.

source

Index source: IVAR, IQAIW, or FipeZap.

date

Reference month.

name_muni

City name or aggregate (e.g. Brazil).

index

Rent index level (each source has its own base period).

chg

Month-on-month change of the index.

acum12m

Accumulated 12-month change of the index.

Table "all" (All Indices Combined)

Complete stacked dataset with transaction_type indicator.

source

Index source (e.g. IVG-R, IGMI-R, IVAR, IQAIW, FipeZap).

date

Reference month.

name_muni

City name or aggregate (e.g. Brazil).

index

Index level (each source has its own base period).

chg

Month-on-month change of the index.

acum12m

Accumulated 12-month change of the index.

transaction_type

Transaction type: sale or rent.

Source

Multiple (FIPE/ZAP, IVGR, IGMI, IQA, IQAIW, IVAR, SECOVI-SP)

See Also

get_dataset(), list_datasets(), get_dataset_info()

Other datasets: abecip, abrainc, bcb_realestate, bcb_series, fgv_ibre, rppi_bis, secovi

Description

International residential property price indices from Bank for International Settlements.

Retrieve this dataset with get_dataset() using the name "rppi_bis".

rppi_bis <- get_dataset("rppi_bis")
rppi_bis_detailed_monthly <- get_dataset("rppi_bis", table = "detailed_monthly")

Details

• Source: Bank for International Settlements

• URL: https://data.bis.org/topics/RPP

• Geography: International (60+ countries including Brazil)

• Frequency: quarterly

• Coverage: 1970-present (varies by country)

• Tables: "selected", "detailed_monthly", "detailed_quarterly", "detailed_annual", "detailed_halfyearly" (default: "selected")

International data; minimal translation needed.

Table "selected" (Selected Series)

Core RPPI series for major countries. This is the default table.

date

Reference quarter (first day of the quarter).

ref_area_code

Country or area code (aggregates use BIS codes such as 4T).

ref_area_name

Country or area name.

unit

Measure: index (2010 = 100) or yoy_chg (year-on-year change, percent).

unit_name

Full description of the unit of measure.

is_nominal

1 for nominal series, 0 for CPI-deflated (real) series.

series_code

BIS series identifier.

value

Series value.

Table "detailed_monthly" (Detailed Monthly)

Monthly detailed RPPI data.

date

Reference period.

year

Reference year.

series_code

BIS series identifier.

ref_area_code

Country or area code.

ref_area_name

Country or area name.

re_type_code

Property type code.

re_type_name

Property type (e.g. all types, new or existing dwellings).

re_vintage_code

Property vintage code.

re_vintage_name

Property vintage (new versus existing).

compiling_org_code

Compiling organisation code.

compiling_org_name

Compiling organisation.

priced_unit_code

Priced unit code.

priced_unit_name

Priced unit (e.g. dwelling, square metre).

seas_adjust_code

Seasonal adjustment code.

seas_adjust_name

Seasonal adjustment description.

availability_code

Series availability code.

availability_name

Series availability description.

unit_code

Unit of measure code.

unit_name

Unit of measure description.

unit_mult_code

Unit multiplier code.

unit_mult_name

Unit multiplier description.

value

Series value.

Frequency-specific period columns (month, quarter, or semester) and a few metadata columns vary slightly across the detailed tables.

Table "detailed_quarterly" (Detailed Quarterly)

Quarterly detailed RPPI data.

date

Reference period.

year

Reference year.

series_code

BIS series identifier.

ref_area_code

Country or area code.

ref_area_name

Country or area name.

re_type_code

Property type code.

re_type_name

Property type (e.g. all types, new or existing dwellings).

re_vintage_code

Property vintage code.

re_vintage_name

Property vintage (new versus existing).

compiling_org_code

Compiling organisation code.

compiling_org_name

Compiling organisation.

priced_unit_code

Priced unit code.

priced_unit_name

Priced unit (e.g. dwelling, square metre).

seas_adjust_code

Seasonal adjustment code.

seas_adjust_name

Seasonal adjustment description.

availability_code

Series availability code.

availability_name

Series availability description.

unit_code

Unit of measure code.

unit_name

Unit of measure description.

unit_mult_code

Unit multiplier code.

unit_mult_name

Unit multiplier description.

value

Series value.

Table "detailed_annual" (Detailed Annual)

Annual detailed RPPI data.

date

Reference period.

year

Reference year.

series_code

BIS series identifier.

ref_area_code

Country or area code.

ref_area_name

Country or area name.

re_type_code

Property type code.

re_type_name

Property type (e.g. all types, new or existing dwellings).

re_vintage_code

Property vintage code.

re_vintage_name

Property vintage (new versus existing).

compiling_org_code

Compiling organisation code.

compiling_org_name

Compiling organisation.

priced_unit_code

Priced unit code.

priced_unit_name

Priced unit (e.g. dwelling, square metre).

seas_adjust_code

Seasonal adjustment code.

seas_adjust_name

Seasonal adjustment description.

availability_code

Series availability code.

availability_name

Series availability description.

unit_code

Unit of measure code.

unit_name

Unit of measure description.

unit_mult_code

Unit multiplier code.

unit_mult_name

Unit multiplier description.

value

Series value.

Table "detailed_halfyearly" (Detailed Half-yearly)

Half-yearly detailed RPPI data.

date

Reference period.

year

Reference year.

series_code

BIS series identifier.

ref_area_code

Country or area code.

ref_area_name

Country or area name.

re_type_code

Property type code.

re_type_name

Property type (e.g. all types, new or existing dwellings).

re_vintage_code

Property vintage code.

re_vintage_name

Property vintage (new versus existing).

compiling_org_code

Compiling organisation code.

compiling_org_name

Compiling organisation.

priced_unit_code

Priced unit code.

priced_unit_name

Priced unit (e.g. dwelling, square metre).

seas_adjust_code

Seasonal adjustment code.

seas_adjust_name

Seasonal adjustment description.

availability_code

Series availability code.

availability_name

Series availability description.

unit_code

Unit of measure code.

unit_name

Unit of measure description.

unit_mult_code

Unit multiplier code.

unit_mult_name

Unit multiplier description.

value

Series value.

Source

Bank for International Settlements

See Also

get_dataset(), list_datasets(), get_dataset_info()

Other datasets: abecip, abrainc, bcb_realestate, bcb_series, fgv_ibre, rppi, secovi

Description

São Paulo real estate market indicators including condominium fees, rentals, launches, and sales.

Retrieve this dataset with get_dataset() using the name "secovi".

secovi <- get_dataset("secovi")
secovi_condo <- get_dataset("secovi", table = "condo")

Details

• Source: SECOVI-SP - Sindicato da Habitação

• URL: https://www.secovi.com.br

• Geography: São Paulo

• Frequency: monthly

• Coverage: 2004-present (varies by category)

• Tables: "condo", "rent", "launch", "sale" (default: "all")

Regional classifications specific to São Paulo metropolitan area.

Columns

All tables share the structure below; the table argument filters which series are returned.

date

Reference month.

category

Market segment: condo, rent, launch, or sale.

variable

Indicator within the category (e.g. icon, default_condominio, acao_locaticia).

name

Breakdown dimension of the indicator (region, property type, or total).

value

Indicator value; unit varies by variable.

Source

SECOVI-SP - Sindicato da Habitação

See Also

get_dataset(), list_datasets(), get_dataset_info()

Other datasets: abecip, abrainc, bcb_realestate, bcb_series, fgv_ibre, rppi, rppi_bis