The role of employment experience in explaining the gender wage gap - Michal Myck; Gillian Paull (Institute for Fiscal Studies (IFS), 2004)
The wage gap between male and female workers has narrowed in both the US and the UK over the past twenty five years. At the same time, employment rates for men and women have converged. This paper examines the relationship between these two facts by analysing the role played by labour market experience in explaining the narrowing gender wage gap. We analyse the relationships between male and female levels of experience and relative wages in the US and the UK over the period 1978 to 2000. The estimation procedure is based on pseudo panels created from cross-sectional data (Current Population Survey (CPS) for the US and Family Expenditure Survey (FES) for the UK). Possible biases from unobserved heterogeneity and the endogeneity of experience are addressed by using an `imputed' measure of experience based on grouped data and by estimating the wage regressions in first differences. Differences in levels of experience are found to explain 39 percent of the gender wage gap in the US and 37 percent in the UK, and failure to control for unobserved heterogeneity is found to understate the role played by total experience in explaining the gap. The gender wage gap has diminished over recent successive cohorts of workers. However, the evidence suggests that the improvements in relative female wages can't be attributed to changes in relative levels of experience. For each of the successive cohorts we examine, total experience increases the gender wage ratio by a constant 8 to 9 percentage points in the US and the UK. We find that the average experience for female workers relative to male workers has increased over successive cohorts. However, this has either been insufficient to lead to a noticeable effect on relative wages, or changes in the returns to experience have altered affecting female relative earnings unfavourably.
Keywords: J16; J41; C23; 330; gender wage gap; returns to experience; artificial panel data; Lohndifferenzierung; Geschlecht; Großbritannien