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The LM-MD Project

The LM-MD Project. A Hands-On Introduction Paul Cichello (PRMPR) John Giles (DECRG) Pierella Paci (PRMPR). Motivation. Labor is a vital asset of the poor. The return on that asset is critically important to individual’s well-being and the well-being of other household members

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The LM-MD Project

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  1. The LM-MD Project A Hands-On Introduction Paul Cichello (PRMPR) John Giles (DECRG) PierellaPaci (PRMPR)

  2. Motivation Labor is a vital asset of the poor. The return on that asset is critically important to individual’s well-being and the well-being of other household members Labor force surveys and studies of employment frequently focus on wage earners. It is not clear that this is appropriate in developing country settings. In many lower and middle income countries, a majority of the workforce is engaged in non-wage (i.e. home enterprise) work! Note: This is true for 7 of the 9 country datasets assembled to date.

  3. Labor Market Analyses Often Do not Include the Entire Workforce • Surveys have incomplete information • Some surveys make no attempt to capture employment in household enterprise work (or do it very poorly) • Some capture home enterprise work but not profits/earnings from this type of work • Surveys have information but analysts don’t use it • Quality of information • How to use it? Issues of comparability.

  4. Analysts’ Decisions are Understandable Survey design issues regarding accuracy of enterprise costs, benefits and/or profits Taking information as true, farm and non-farm profit data are subject to many choices, without clear “rules” Profits are often noisy, but what is reasonable noise? Sometimes, you can’t use data Rules for dividing enterprise profits are not clear In this project, we develop a consistent approach to assigning profits/income from household enterprises to laborers

  5. Analysts are Frequently Left with Unpleasant Choices Examine wage labor market only Focus on enterprise profits independent of other sectors Use household income/expenditures and household head characteristics Spend A LOT of time and resources to create imperfect measures of individual earnings for all employed members of the labor force

  6. LM-MD Project Create data set with individual level labor market variables for all workers, including non-wage workers. Employment status Characteristics of main job: sector, employment relationship, hours worked, earnings Characteristics of total labor effort: Total annual hours worked, total annual earnings, number of jobs worked Note: Excludes home production that is not part of family farm/non-farm enterprise Build on and link with existing Comparative Living Standards Project

  7. LM-MD Project Create individual level earnings variable for all employed individuals Divide farm enterprise profits among those who are engaged in working on the farm Divide on a per hours worked basis if possible Otherwise, divide per person Similarly, divide non-farm enterprise profits across non-wage non-farm workers.

  8. LM-MD Methodology- Harmonized? To the extent possible, the following are consistent across data sets: Variable definitions, Practical implementation of these definitions Methods of cleaning the data That said: Survey questionnaires often differ in minor to major ways Serious “data cleaning” issues frequently arose

  9. LM-MD Methodology- Harmonized? Our Choices: Consistency across time within country takes priority over consistency across countries Document general method in codebook Document all questions used and any major deviations from the norm in a README file for each data set Give special variable names for variables where construction differed significantly from Codebook

  10. LM-MD Project so Far Currently: 8 countries; 16 datasets Note: In these 8 countries, non-wage work represents between 35 and 83 percent of all employment. (over 49% for 6 of 8, over 78% or higher for 3 cos.) We are also nearly ready to release two survey rounds of data from Nicaragua.

  11. Does carefully assigning earnings from household enterprise activities matter? Cichello (2009) has examined whether trends in earnings inequality differ using the LM-MD approach from a more typical analysis based on wage income alone. • Used Gini, Theil-0 and Theil-1 • Compared change in inequality measure for wage workers to change in the full set of workers • In 8 of 24 comparisons, the sign was different • In 8 of 24 comparisons, the sign of the trend was the same but the size of the change was found to be different to an economically significant degree.

  12. Next Steps for the LM-MD? • Public good nature of the project • Difficulty of assembling comparable datasets even from surveys like the LSMS which are similar by design. • Is the LM-MD likely to meet immediate operational needs? Probably not, but we hope that it can provide guidance • Other regions possibly following guidelines laid out by the LM-MD (South Asia, East Asia).

  13. The LM-MD Website Full details of Methodology are available in the Codebook and Methodological Report, available at: http://go.worldbank.org/S0STAK6OC0

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