DOI: 10.5061/dryad.76hdr7sv8
title: Degraded Pastures in Brasil: dataset used in econometric models

description: Degraded pasture restoration is the major liability in Brazilian
 agriculture but could be the main asset. Here we show the technical
 inefficiency of livestock activity in Brazil is around 19% in which
 degraded pastures being the main factor of diseconomy of scale. On the
 other hand, the recovery of 12 million hectares of degraded pastures could
 generate an additional production of 16.9 million bovines. There is a
 large regional concentration of degraded pastures, which would facilitate
 the targeting of Technical Assistance and Rural Extension (ATER) and Rural
 Credit efforts to foster pasture recovery, as these two factors have a
 significant impact in reducing inefficiency. 1% of Brazilian
 municipalities concentrate 25% of degraded pastures that could generate
 almost 30% of the total increment of the additional herd via pasture
 recovery.  At the municipality level, even if most of the
 degraded pastures were allocated to forest recovery in order to comply
 with the Forest Code, an increase of 9 M of cattle would be possible due
 to the recovery of degraded pastures that would exceed the minimum
 necessary to comply with the environmental law. Redirecting investment
 credits, especially for resources with controlled interest rate. Degraded
 pasturelands are the new frontier that could boost livestock activities
 and avoid deforestation in Brazil.
description: All econometric models -
 Stochastic Frontier for estimating livestock efficiency, and SEM and
 Robust Regression models for estimating regional stocking rates - were
 estimated using variables collected from the Agricultural Census 2017. It
 is the most recent Brazilian census, conducted by the Brazilian Institute
 of Geography and Statistics. The census covered the entire national
 territory, covering the 5.03 million rural properties in 5,563
 municipalities, 26 states and the Federal District, with data reported
 from October 1, 2016 to September 30, 2017, and published in 2019. The
 census adopted the collection and content premises suggested by the World
 Programme for the Census of Agriculture 2020 , implemented by the Food and
 Agriculture Organization - FAO, and the International Standard Industrial
 Classification of all Economic Activities - ISIC - Revision 4. The census
 is divided into 13 themes with 137 interactive tables that allow advanced
 data selection and information combination.  Each table has 1 or more
 variables that can be combined with a series of search criteria, including
 producer profile, production type, geographical level, etc. The search
 results can be downloaded in 7 formats (different extensions). The census
 did not provide microdata - producer-level responses. The most detailed
 territorial level is the municipality. We also used data from The Rural
 Credit Data Matrix (RCDM) which is an online platform of the Brazilian
 Central Bank (CBB) that allows access to information on the value and
 number of rural credit contracts signed by the official credit system,
 allowing search combined with different criteria, including month and year
 of operation, municipality, economic activity group, purpose (investment,
 costs etc.), product (pasture, milk, soybeans etc.), credit program and
 subprogram, sources of resources etc. The time series is updated monthly
 and covers the period from January 1, 2013 to the present, and generates
 results for free donwload in 4 formats
 (extensions). 
description: Dataset - in original websites - are mostly available exclusively
 in Portuguese, and there is no official English version. In order to
 ensure greater transparency about the data used as well as to assist users
 with limited knowledge in Portuguese, we provided in the Supplemental
 Material a comprehensive guide on how to access and download the data,
 including links to all variables used in our models.
 Dataset is in Excel Spreadsheet.