Monitoring International Labor Standards Quality of Information: Summary of a Workshop (2003) / Chapter Skim
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2. Challenges in Measuring Labor Market Conditions Across Countries
2. Challenges in Measuring Labor Market Conditions Across Countries
Pages 8-16
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From page 8... ...
Rama presented their results a database of labor market information on 121 countries, classified into seven broad groups.1 The database includes information on most "larger" countries, as well as countries with relatively good data and those with which Rama and Artecona were personally familiar. Because the boundaries of many nations have changed over The seven groups include the industrial or developed countries and six geographic regions defined by The World Bank: Sub-Saharan Africa; East Asia and the Pacific Islands; Eastern Europe and Central Asia; Latin America and the Caribbean; the Middle East and North Africa; and the South Asian region.
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From page 9... ...
The database does not include information on the share of the informal sector in the total labor force because there was no clear definition of what constitutes informal employment. Artecona said they drew on a wide variety of cross-country and country-specific sources, including unpublished statistical information gathered during their research for the World Bank.
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From page 10... ...
LFRFEM Female participation rate, in percentage of the female population aged 15 to 64.
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From page 11... ...
For example, Rama said that one variable for which it was difficult to find data was severance pay after two years of uninterrupted private employment. Across world regions, the database provided good coverage for Latin America and South Asia, but "much worse" coverage of labor market information for Sub-Saharan Africa, the Middle East, and North Africa.
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From page 12... ...
12 QUALITY OFINFORMATION TABLE 2-2 Coverage by Variable and Region in the Draft Database of Labor Market Indicators Across Countries (as of ~uly 2002) Region Countries LFTALL LFTAGR LFTIND LFRALL LFRMLE 212 164 162 140 140 114 77 74 74 65 99 74 59 105 105 223 175 153 153 138 196 147 144 126 126 174 131 126 102 102 49 35 35 30 31 AFR EAP ECA INL LAC MNA SAS 23 12 18 23 21 19 LFRFE1~/ 140 74 105 138 126 105 30 ALL 121 1067 803 753 730 707 718 UNTFST HRSWRK WGEAGR WGEIND PRDIND WGEGC AFR 23 10 17 15 97 87 37 EAP 12 13 26 13 71 59 22 ECA 18 13 25 51 66 34 20 INL 23 48 91 16 150 155 33 LAC 21 33 38 15 119 118 25 MNA 19 13 7 7 84 83 17 SAS 5 3 8 26 27 28 13 ALL 121 133 212 143 614 564 167 SSCONT SSCVGE SSREVN UNBRPL UNBDUR SVCPAY AFR 23 38 24 34 4 4 13 EAP 12 27 19 17 4 8 3 ECA 18 24 14 37 13 17 3 INL 23 46 9 107 49 56 0 LAC 21 56 58 81 8 20 12 MNA 19 43 23 25 7 14 17 SAS 5 9 8 0 1 1 22 ALL 121 243 155 301 86 120 70 EMPGGT EMPPSR ILOCNV CHLDLB FORCLB ABOLF: AFR 23 41 24 105 253 253 253 EAP 12 27 15 85 126 126 126 ECA 18 19 25 98 178 159 178 INL 23 42 26 252 253 253 253 LAC 21 35 17 150 231 231 231 MNA 19 26 17 106 208 208 208 SAS 5 10 8 46 55 55 55 ALL 121 200 132 842 1304 1285 1304
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From page 13... ...
LABOR MARKET CONDITIONSACROSS COUNTRIES case of 'MLE LFRFEM EMTALL EMTIND UNRALL UNRMLE UNRFEM 40 15 31 16 5 5 74 51 59 55 31 31 05 59 58 28 16 16 38 187 183 155 193 157 26 53 56 78 61 61 05 36 21 31 14 14 30 21 18 25 18 18 718 422 426 388 338 302 FIND WGEGOV WGEMIN MATLVE ANNLVE ACCDNT SSTYPE 37 41 52 28 30 34 22 26 22 10 35 19 20 33 32 14 21 18 33 102 69 43 56 46 25 64 75 29 50 42 7 30 37 18 23 29 3 5 14 9 6 8 67 301 301 151 221 196 BDUR SVCPAY TUMMBR TUCVGE STKNBR STKWRK STKHRS 3 67 7 30 28 30 3 56 5 40 33 31 3 43 4 18 17 18 0 181 50 63 66 88 2 75 10 46 46 39 17 42 0 11 11 11 22 23 0 27 27 27 70 487 76 235 228 244 RCLB ABOLFL EQLREM DISCRM ORGNZE BRGAIN 253 26 178 253 231 253 26 160 253 231 208 208 55 55 304 1286 253 26 160 253 231 253 26 178 253 231 253 26 178 253 231 208 208 208 55 55 55 286 1304 1304 13
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From page 14... ...
DISCUSSION Responding to Rama and Artecona's presentation, Yale economist T.N. Srinivasan commended "their valiant effort in putting together a data set." However, he was not persuaded that the database would allow researchers to analyze the interaction between labor market policies and institutions on the one hand and economic growth, poverty, and inequality on the other hand.
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From page 15... ...
As a result, selecting the best sources may affect in a nonrandom way the number of cells filled in the final data set. Srinivasan highlighted another problem: The data set does not include the informal sector, which accounts for the major share of employment in many developing countries.
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From page 16... ...
In addition, he said, there are so many different sources of measurement error, in so many different directions, that "our sense is that it can be treated as random error." Although the database does not provide an indicator of the relative shares of employment in the formal and informal sectors for each country, Rama noted that some of the variables in the database do provide information on informal employment, such as labor force levels, labor force participation rates, unemployment rates, and work hours. In addition, one of the variables the average wage of casual agricultural workers refers exclusively to the informal sector.
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