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Business Practices in Small Firms in Developing Countries 2008-2014 (reproducible scripts)

2016 - RR_2008-2014_BPSFDC
David McKenzie, Christopher Woodruff
Created on June 18, 2020 Last modified June 18, 2020 Page views 66 Download 10 Metadata JSON
  • Project Description

Overview

Abstract
Management has a large effect on the productivity of medium and large firms. But does management matter in micro and small firms, where the majority of the labor force in developing countries works? We develop 26 questions that measure business practices in marketing, stock-keeping, record-keeping, and financial planning. These questions have been administered in surveys in Bangladesh, Chile, Ghana, Kenya, Mexico, Nigeria, and Sri Lanka. We show that variation in business practices explains as much of the variation in outcomes-sales, profits, and labor productivity and total factor productivity-in microenterprises as in larger enterprises. Panel data from three countries indicate that better business practices predict higher survival rates and faster sales growth. The association of business practices with firm outcomes is robust to including numerous measures of the owner's human capital. We find that owners with higher human capital, children of entrepreneurs, and firms with employees employ better business practices.
Keywords
business practices small enterprises productivity management
Authoring entity
Agency Name Role Affiliation Email
David McKenzie Primary investigator World Bank dmckenzie@worldbank.org
Christopher Woodruff Primary investigator University of Warwick
Sponsor / Funding agency
Name Abbreviation Role
Knowledge for Change Trust fund, World Bank KCP Financial support
Other Identifications/ Acknowledgments
Name Role
Miriam Bruhn, Nicholas Bloom, Raffaella Sadun, John Van Reenan, and participants at the AEA annual meeting, Bocconi, Collegio Carlo Alberto, and Warwick Provided comments
Anna Luisa Paffhausen Research Assistance
Topics
ID Topic Vocabulary Vocabulary URI
O12 Microeconomic Analyses of Economic Development JEL codes https://www.aeaweb.org/econlit/jelCodes.php
L26 Entrepreneurship JEL codes https://www.aeaweb.org/econlit/jelCodes.php
M20 Business Economics - General JEL codes https://www.aeaweb.org/econlit/jelCodes.php
O17 Formal and Informal Sectors - Shadow Economy - Institutional Arrangements JEL codes https://www.aeaweb.org/econlit/jelCodes.php
M53 Personnel Economic - Training JEL codes https://www.aeaweb.org/econlit/jelCodes.php
Language
English

Methods, software and scripts

Methods or algorithms applied
histogram, scatterplot, coefplot spearman correlation linear regression kernel-weighted local polynomial regression (lpoly) linear regression with large dummy-variable set (areg) principal components analysis (pca) standardized z-scores probit model (dprobit)
Software
Name Version
Stata 14
Scripts
File name
ReplicationFileBusinessPractices.do
Zip archive
Programs.zip
Description
Stata do file to replicate tables in paper using BusinessPracticesReplicationdata.dta
Authors
Date
2016-02-22
Format
Stata do file
software
Stata 14
Notes
See also Readme for Replication Files (ReadmeBusinessPractices.txt)
File name
Figure1recorder.grec
Zip archive
Programs.zip
Description
Stata graph editor file used in making Figure 1
Authors
Date
2014-12-03
Format
Stata 14 Graph recorder (text file)
software
Stata 14
File name
newFigure2recorder.grec
Zip archive
Programs.zip
Description
Stata graph editor file used in making Figure 2
Authors
Date
2015-01-24
Format
Stata 14 Graph recorder (text file)
software
Stata 14
File name
Figure2recorder.grec
Zip archive
Programs.zip
Description
Stata graph editor file used in making subfigures in Figure 4
Authors
Date
2015-01-29
Format
Stata 14 Graph recorder (text file)
software
Stata 14
File name
Figure4newcombiner.grec
Zip archive
Programs.zip
Description
Stata graph editor file using in making Figure 4
Authors
Date
2015-08-06
Format
Stata 14 Graph recorder (text file)
software
Stata 14
File name
newFigure5recorder.grec
Zip archive
Programs.zip
Description
Stata graph editor file using for Appendix Figure 1
Authors
Date
2015-01-29
Format
Stata 14 Graph recorder (text file)
software
Stata 14
File name
MergeDataKenya.do
Zip archive
Programs.zip
Description
Supplementary file showing how the data were constructed from the raw survey data files - File to name and label business practice data for Kenya
Authors
Date
2016-02-22
Format
Stata do file
software
Stata 14
File name
MExicoRenameVariables.do
Zip archive
Programs.zip
Description
Supplementary file showing how the data were constructed from the raw survey data files - File to name and label data from Mexico
Authors
Date
2015-08-05
Format
Stata do file
software
Stata 14
File name
NigeriaDataExtract.do
Zip archive
Programs.zip
Description
Supplementary file showing how the data were constructed from the raw survey data files - File to name and label data from Nigeria
Authors
Date
2016-02-22
Format
Stata do file
software
Stata 14
File name
CleanBangladesh.do
Zip archive
Programs.zip
Description
Supplementary file showing how the data were constructed from the raw survey data files - File to name and label data from Bangladesh
Authors
Date
2016-02-22
Format
Stata do file
software
Stata 14
File name
renameChile.do
Zip archive
Programs.zip
Description
Supplementary file showing how the data were constructed from the raw survey data files - File to name and label data from Chile
Authors
Date
2014-12-09
Format
Stata do file
software
Stata 14
File name
MergeDataSLKWomen.do
Zip archive
Programs.zip
Description
Supplementary file showing how the data were constructed from the raw survey data files - File to name and label data from Sri Lankan female sample
Authors
Date
2016-02-22
Format
Stata do file
software
Stata 14
File name
SriLanka_renameSMEvars.do
Zip archive
Programs.zip
Description
Supplementary file showing how the data were constructed from the raw survey data files - File to name and label SME data from Sri Lanka
Authors
Date
2014-12-01
Format
Stata do file
software
Stata 14
File name
Ghana_Renamev2.do
Zip archive
Programs.zip
Description
Supplementary file showing how the data were constructed from the raw survey data files - File to rename Ghana variables
Authors
Date
2015-01-24
Format
Stata do file
software
Stata 14
File name
SriLankaRenameVariables.do
Zip archive
Programs.zip
Description
Supplementary file showing how the data were constructed from the raw survey data files - File to rename other Sri Lankan data
Authors
Date
2015-01-24
Format
Stata do file
software
Stata 14

Datasets

Datasets
BusinessPracticesReplicationdata
WLD_2008-2014_BPSFDC_V01_M Data access type: Public
Stata 14 [.dta] data file
Bangladesh survey data
The survey was conducted between March and May 2010 as part of a World Bank project intended to investigate the differences between formal and informal firms in Bangladesh (McKenzie, 2010). The data consists of 1725 enterprises, selected from a sample frame formed by a census of 55,817 firms in the randomly selected areas in urban parts of the 19 old districts. The sample was stratified by firm size (in terms of full-time employment) and broad industry (manufacturing, trade or services. Oversampling of firms with 10-99 full-time workers was done to ensure sufficient sample sizes of these firms. Only one round of this survey was taken.
Chile survey data
The data consist of the follow-up survey from individuals owning enterprises in the control group of Mart?nez et al. (2013). The original sample consists of beneficiaries of Chile's anti-poverty program (Chile Solidario) who applied to a government microenterpreneurship support program in 2010, and who were located in the metropolitan area of Santiago. 566 individuals were assigned to the control group. The followup survey, which measured business practices, took place between October and November 2011. We use the sample of 158 individuals in the control group who were found to be running enterprises in this followup survey. Only one round of business practice data are available, and we use time-invariant characteristics of the business owners from the baseline survey coupled with the outcome and business practice data from the follow-up survey.
Ghana survey data
The sample consists of 335 applicants to a business plan competition in Accra and Kumasi, described in Fafchamps and Woodruff (2014). Baseline data were collected in 2010, and then two rounds of follow-up surveys were collected in July-August 2011, and August-September 2012, approximately one and two years after the baseline. 257 individuals were surveyed in the first follow-up, and 279 in the second follow-up. The survey did not collect detailed survival data, and so we only use the time dimension of this data for examining the persistence of business practices over time.
Kenya survey data
The sample comes from an ongoing evaluation of a business training program for women in four counties of Kenya: Kakamega and Kisii in the Western region, and Embu and Kitui in the Eastern region. In each county a census was taken of market centers, and then a screening was done to select a sample in which the business did not have more than 3 employees; the business had profits in the past week between 0 and 4000 Kenyan Shillings (KSH) (1 US Dollar averaged approximately 85 KSH over the survey period); sales in the past week less than or equal to 50,000 KSH; and the individual had at least one year of schooling (Diwan et al, 2014). The survey is therefore representative of microenterprises of this size run by women in these four counties. The baseline survey took place between June and November 2013, and consisted of 3,537 individuals. The survey is missing responses on business practices F5-F8 (financial statements) in the baseline, because the question only allowed for one response, rather than a yes/no for each type of financial statement (70.2% report not having any accounting statement prepared).A follow-up survey was conducted one year later, with survival data collected for 3,446 individuals and follow-up business practices data for 2,860 individuals.
Mexico survey data
This survey is the baseline of a randomized-controlled trial to evaluate the impact of 'Mujeres Moviendo a Mexico', a large-scale business training program for female micro-entrepreneurs funded by INADEM ('Instituto Nacional del Emprendedor Mexicano') and implemented by the NGO Crea Comunidades de Emprendedores Sociales. The survey was conducted in 2014 and consists of a representative sample of female-run firms with 5 or fewer employees and less than 4 million Mexican pesos in annual turnover operating in eight urban areas in Mexico: Aguascalientes, Dolores Hidalgo, Irapuato, Le?n, Mexico City, Quer?taro, San Juan del R?o and Toluca. The data are described further in Calderon et al. (2015). The data consists of 10,275 individuals. The business practice questions asked did not include R2 (keeping a record of every purchase and sale.
Nigeria survey data
The sample consists of applicants to a nationwide business plan competition, described in McKenzie (2014). The first round data consist of 1725 individuals surveyed between November 2012 and April 2013 who were operating businesses at that time. The sample consists of applicants who had been selected for a business plan training workshop, or had scores close to the threshold for being selected. A second followup survey was conducted between October 2013 and February 2014, allowing measurement of survival over a 1 year horizon, and of the stability of business practices. The business practice questions asked did not include F5-F8 (financial statements).
Sri Lanka survey data
The business practice questions were asked in three separate surveys undertaken in Sri Lanka, and we use the data from all three. The first sample comes from the Sri Lankan Longitudinal Survey of Enterprises (SLLSE), a long-term panel survey of microenterprises designed by the authors in collaboration with Suresh de Mel (de Mel et al, 2010, 2013). The baseline survey was intended to be a representative survey of male microenterprises with 2 or fewer employees in the Colombo, Kandy, and Galle-Matara areas of Sri Lanka, and was conducted between April and October 2008. This gives 1562 individuals with business practice scores. These enterprises were then subsequently re-interviewed in 10 additional follow-up rounds, in April and October of 2009, 2010, 2011 and 2012, and in April of 2013 and 2014. This enables us to examine survival over periods of as long as 5.5 years. The second sample consists of a representative sample of current female business owners operating in greater Colombo and greater Kandy areas, who had monthly profits of 5,000 Rs or less (US$43). These 628 women were first interviewed in January 2009, and form the current enterprise sample for a business training intervention described in de Mel et al. (2014). Four rounds of follow-up surveys were conducted in September 2009, January 2010, September 2010, and June 2011. We use the January 2010 follow-up to measure the one-year survival rates and stability of business practices over a one-year horizon. The third sample consist of small and medium enterprises that were a booster sample to the baseline of the SLLSE, which were surveyed in order to generate a larger sample of firms of this size (de Mel et al, 2010). The baseline sample consisted of 610 of these firms, but did not ask business practice questions. We use the 471 firms that were reinterviewed and still surviving in April 2009.
Geographic locations
Location Code Type
Bangladesh BGD Country
Chile CHL Country
Ghana GHA Country
Kenya KEN Country
Mexico MEX Country
Nigeria NGA Country
Sri Lanka LKA Country
Confidentiality
The published materials do not contain confidential information.
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