Minimum Wages in Kenya Mabel Andalón - Index of - IZA

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The first and the fourth columns in Table 10 report the simple correlation between the level of wages and minimum wages, for agricultural and general order minimum wages. Such correlation is found to be positive and statistically significant for agricultural activities, however, it may well be driven by reverse causality: higher wages determine higher minimum wages. Columns (2) and (4) in Table 10 examine the correlation between wages and minimum wages controlling for a number of individual and job characteristics that explain the level of wages across occupations. Once these effects are taken into account, the minimum wage is no longer significant in explaining the level of wages for the average worker. Yet, minimum wages may be relevant for explaining the wage level of workers of certain types, particularly those whose wages are more likely to be close to the minimum wage. To account for such possibility, we add interactions between the minimum wage level and individual characteristics of workers (age, gender, education level, and whether formal or informal). We report the results in columns (3) and (6) of Table 10. Given that minimum wages vary only by occupation, in agriculture, the level effect of the minimum wage is absorbed by the inclusion of occupation effects. The coefficients on the interactions between the minimum wage and the personal characteristics indicate whether minimum wages affect some workers more than others. The only coefficient that is statistically significant is the interaction with age. The negative sign suggests that in agriculture, minimum wages exert a stronger upward push on wages for the adult population than for younger workers. The level effect of the minimum wage can be recovered for workers in urban areas because minimum wages vary by location within occupation. Its coefficient suggests that minimum wages exert an upward push on the wages of less educated workers The results also suggest that minimum wages exert a higher push on the wages of women, thereby contributing to reduce the gender earnings gap. 14
VI. Minimum Wages and Employment Evidence on the effect of minimum wages on employment in Kenya is scarce. To our knowledge, only one study studied this issue and concluded that minimum wages reduce employment (Omolo and Omitti, 2004). Their conclusions are based on an estimated negative correlation between changes in the minimum wage and changes in employment using aggregate data. However, a negative correlation does not establish causality. It could well be, for example, that the causality goes in the opposite direction, that is, periods of low employment growth, and in general poor output growth, lead to lower increases in the minimum wage. Given the problems associated with using aggregate time series data, the economic literature relies on repeated cross sectional or longitudinal data at the individual level to estimate the effect of minimum wages on employment. Unfortunately, there is not much labor market micro data available in Kenya. To our knowledge, in the last 10 years there was only one labor force survey that covered urban areas. Nonetheless, the presence of a large number of minimum wages levels across occupations and locations provides important cross sectional variation that we can exploit with the 98/99 ILFS data to relate employment to the multiple minimum wages. Figure 8 relates the ratio of the minimum, for each occupation-location pair, to the median wage for all salaried workers with the share of formal salaried employment, the share of informal salaried and the share of self-employment in total employment for each location-occupation pair. We restrict the analysis to urban areas since the wage analysis suggests that these are the areas where minimum wages are more likely to be binding and also because in urban areas we can exploit the occupation-location variation. Total employment includes salaried, self-employment, unpaid work and apprentices. The number of data points in these figures is constrained by: (i) the number of occupation- location pairs for which a minimum wage is defined and (ii) the number of occupation location pairs for which a sufficiently large number of observations are available in the 15
Page 1 and 2: DISCUSSION PAPER SERIES IZA DP No.
Page 3 and 4: IZA Discussion Paper No. 3390 March
Page 5 and 6: in employment in the uncovered sect
Page 7 and 8: Employment Act (CAP 229). The objec
Page 9 and 10: In the analysis that follows the te
Page 11 and 12: implies that all non-clearly assign
Page 13 and 14: the average wage. Based on this lat
Page 15: In contrast, there appears to be a
Page 19 and 20: larger -but of similar magnitude--
Page 21 and 22: the effect of minimum wages on pove
Page 23 and 24: Fields, Gary and Ravi Kanbur. 2007.
Page 25 and 26: 160 140 120 100 80 60 40 1991 1992
Page 27 and 28: Figure 3: Minimum Wage level (relat
Page 29 and 30: Figure 6: Minimum Wages in General
Page 31 and 32: Table 1: Gazetted Monthly Basic Min
Page 33 and 34: Table 3. Descriptive Statistics Var
Page 35 and 36: Table 5: Minimum Wages Variables by
Page 37 and 38: Table7: Minimum Wage Variables by A
Page 39 and 40: Table 9: Minimum Wages relative to
Page 41 and 42: Table 11: Structure of Employment a

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