Brazil

Brazil (2009)

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This page summarizes Enterprise Surveys data for Brazil. The graphs below provide an overview of the sample and highlight the biggest obstacles experienced by private sector firms in Brazil. The 12 tables below the graphs summarize key factual indicators at the country and regional levels for each of the business environment topics. A few subjective indicators are also available.

 

NUMBER OF FIRMS SURVEYED

1,802

Business owners and top managers in 1,802 firms were interviewed from May 2008 through June 2009.

Characteristics of Firms Surveyed

Textiles: 168 Garments: 162 Leather Products: 131 Chemicals & Chemical Products: 137 Machinery & Equipment: 161 Motor Vehicles: 107 Food: 166 Other Services: 125 IT & IT Services: 110 Retail: 84 Other Manufacturing: 278 Furniture: 173 Textiles: 168 Garments: 162 Leather Products: 131 Chemicals & Chemical Products: 137 Food: 166 Other Services: 125 IT & IT Services: 110 Food: 166 Food: 166 Textiles: 168 Textiles: 168 Garments: 162 Garments: 162 Leather Products: 131 Leather Products: 131 Chemicals & Chemical Products: 137 Chemicals & Chemical Products: 137 Machinery & Equipment: 161 Machinery & Equipment: 161 Motor Vehicles: 107 Motor Vehicles: 107 Furniture: 173 Furniture: 173 Other Manufacturing: 278 Other Manufacturing: 278 Retail: 84 Retail: 84 IT & IT Services: 110 IT & IT Services: 110 Other Services: 125 Other Services: 125 Small (5-19): 678 Large (100+): 374 Medium (20-99): 750 Small (5-19): 678 Large (100+): 374 Medium (20-99): 750 Small (5-19): 678 Small (5-19): 678 Medium (20-99): 750 Medium (20-99): 750 Large (100+): 374 Large (100+): 374 Sao Paulo: 441 Rio Grande do Sul: 196 Minas Gerais: 179 Santa Catarina: 177 Rio de Janeiro: 167 Maranhao: 3 Paraiba: 14 Brasilia DF: 38 Pernambuco: 45 Amazonas: 50 Mato Grosso: 55 Goias: 82 Ceara: 92 Bahia: 99 Parana: 164 Sao Paulo: 441 Rio Grande do Sul: 196 Minas Gerais: 179 Maranhao: 3 Paraiba: 14 Brasilia DF: 38 Pernambuco: 45 Amazonas: 50 Mato Grosso: 55 Sao Paulo: 441 Sao Paulo: 441 Rio Grande do Sul: 196 Rio Grande do Sul: 196 Minas Gerais: 179 Minas Gerais: 179 Santa Catarina: 177 Santa Catarina: 177 Rio de Janeiro: 167 Rio de Janeiro: 167 Parana: 164 Parana: 164 Bahia: 99 Bahia: 99 Ceara: 92 Ceara: 92 Goias: 82 Goias: 82 Mato Grosso: 55 Mato Grosso: 55 Amazonas: 50 Amazonas: 50 Pernambuco: 45 Pernambuco: 45 Brasilia DF: 38 Brasilia DF: 38 Paraiba: 14 Paraiba: 14 Maranhao: 3 Maranhao: 3

NUMBER OF FIRMS SURVEYED

1,802

After being presented with a list of 15 business environment obstacles, business owners and top managers in 1,802 firms were asked to choose the biggest obstacle to their business.

Ranking of the Top Business Environment Obstacle for Firms

Customs and trade regulations: 2.6 Political instability: 3.0 Corruption: 3.3 Crime, theft and disorder: 6.6 Tax administration: 6.7 Labor regulations: 7.4 Access to finance: 7.5 Practices of the informal sector: 12.4 Inadequately educated workforce: 12.6 Tax rates: 33.5

ECONOMY OVERVIEW

Country Highlights summarize the key findings from the Enterprise Survey

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Country Profiles provide key investment climate indicators for a country with benchmarks against their respective regional and income groups

Brazil Country Profile

Brazil Country Profile

921.2KB pdf file

REGION:
Latin America & Caribbean
INCOME CATEGORY:
Upper middle income
POPULATION:
202,033,670
GNI PER CAPITA (US $):
11,760

Resources

Custom Data Set

Custom Data Set

Generate a Custom Data Set for Brazil including standard errors, indicator values by firm subgroups, historical data and comparable countries.

Economy profile

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Survey Design Strata

Ex Post Groupings

Include Statistics:
Indicator Brazil Latin America & Caribbean All Countries 2  
Bribery incidence (percent of firms experiencing at least one bribe payment request) Percent of firms experiencing at least one bribe payment request during 6 transactions dealing with utilities access, permits, licences, and taxes.

11.7 10.4 17.9  
Bribery depth (% of public transactions where a gift or informal payment was requested) Bribery depth is the percentage of transactions (out of 6 transactions dealing with utilities access, permits, licences, and taxes) where a gift or informal payment was requested.

8.4 7.1 13.9  
Percent of firms expected to give gifts in meetings with tax officials Percent of firms expected to give gifts or an informal payment in meetings with tax officials.

8.3 6.4 13.0  
Percent of firms expected to give gifts to secure government contract Percent of establishments that consider that firms with characteristics similar to theirs are making informal payments or giving gifts to public officials to secure government contract.

32.9 20.3 28.4  
Value of gift expected to secure a government contract (% of contract value) Percentage of the contract value expected as a gift to secure a government contract. Only firms that have confirmed that they have secured or attempted to secure a government contract in the last 12 months were required to answer this question.

0.4 1.2 1.7  
Percent of firms expected to give gifts to get an operating license Percent of firms expected to give gifts or an informal payment to get an operating license.

9.9 7.8 14.5  
Percent of firms expected to give gifts to get an import license Percent of firms expected to give gifts or an informal payment to get an import license.

1.2 6.3 15.0  
Percent of firms expected to give gifts to get a construction permit Percent of firms expected to give gifts or an informal payment to get a construction permit.

9.4 15.2 23.9  
Percent of firms expected to give gifts to get an electrical connection Percent of firms expected to give gifts or an informal payment to get an electrical connection.

4.6 3.9 16.5  
Percent of firms expected to give gifts to get a water connection Percent of firms expected to give gifts or an informal payment to get a water connection.

6.7 11.2 16.5  
Percent of firms expected to give gifts to public officials "to get things done" Percent of establishments that consider that firms with characteristics similar to theirs are making informal payments or giving gifts to public officials to "get things done” with regard to customs, taxes, licenses, regulations, services, etc.

12.5 11.3 21.5  
Percent of firms identifying corruption as a major constraint Percent of firms identifying corruption as a major constraint. The computation of the indicator is based on the rating of the obstacle as a potential constraint to the current operations of the establishment.

68.8 43.9 31.9  
Percent of firms identifying the courts system as a major constraint Percent of firms identifying the courts system as a major constraint. The computation of the indicator is based on the rating of the obstacle as a potential constraint to the current operations of the establishment.

45.4 28.4 14.3  

Update: In August 2014, Enterprise Surveys re-issued the Brazil 2009 raw dataset and the resulting indicators. Corrections were made to the sampling weights which had been incorrectly mapped to the various cells in the sample design. The correction does not impact the underlying survey responses.

  • Notes

    * This indicator is computed using data from manufacturing firms only.

    Additional Notes

    1. Most surveys were administered using the Enterprise Surveys Global Methodology as outlined in the Methodology page, while some others did not strictly adhere to the Enterprise Surveys Global Methodology. For example, for surveys which do not follow the Global Methodology, the Universe under consideration may have consisted of only manufacturing firms or the questionnaire used may have been different from the standard global questionnaire. Data users should exercise caution when comparing raw data and point estimates between surveys that did and did not adhere to the Enterprise Surveys Global Methodology. For surveys which did not adhere to the Global Methodology plus Afghanistan 2008, any inference from one of these surveys is representative only for the data sample itself.
    2. Regional and "all countries" averages of indicators are computed by taking a simple average of country-level point estimates. For each economy, only the latest available year of survey data is used in this computation. Only surveys, posted during the years 2010-2016, and adhering to the Enterprise Surveys Global Methodology are used to compute these regional and "all countries" averages.
    3. Descriptions of firm subgroup levels, e.g. how the ex post groupings are constructed, are provided in the Indicator Descriptions (PDF, 710KB) document.
    4. Statistics derived from less than or equal to five firms are displayed with an "n.a." to maintain confidentiality and should be distinguished from ".." which indicates missing values. Also note for three growth-related indicators under the "Performance" topic, these indicators are not computed when they are derived from less than 30 firms.
    5. Standard errors are labeled "n.c.", meaning not computed, for the following:

           1) indicators for all surveys that were not conducted using the Enterprise Surveys Global Methodology and

           2) for indicator breakdowns by ex post groupings: exporter or ownership type, and gender of the top manager.
    6. Please cite our data as follows:

      Enterprise Surveys (http://www.enterprisesurveys.org), The World Bank.