Identification of the covariance structure of earnings using the GMM estimator

Doris, Aedín; O’Neill, Donal; Sweetman, Olive

doi:10.1007/s10888-012-9216-5

Cited by 17 publications

(17 citation statements)

References 43 publications

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“…Nevertheless, in Section VI we 3 The relative performance of levels versus growthbased generalised method of moments estimates has not previously been examined to our knowledge. Doris et al (2010) look at the performance only of levelsbased estimates, and their wage model does not allow for either heterogeneous growth or purely transitory shocks. Likewise, Hryshko (2012) focuses only on the performance of growth-based estimation, while Manovskii et al (2015) look at levels-versus growth-based estimation but only in relation to reconciling differences in estimates of persistent and transitory shocks.…”

Section: Introductionmentioning

confidence: 99%

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The Drivers of Life‐Cycle Wage Inequality in Australia

Freestone

2018

Economic Record

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Why does wage inequality rise with age? Using panel data on male wages, we explore the relative importance of unobserved worker heterogeneity versus random wage shocks in explaining this life‐cycle trend in Australia. While we find significant heterogeneity in wage levels (via differences in starting wages), we find no evidence of systematic heterogeneity in wage growth. Instead, highly persistent wage shocks are found to account entirely for the rise in wage inequality with age. We also find evidence that the upward trend in wage inequality since the early 2000s reflects an increase in permanent rather than transitory wage inequality.

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Section: Introductionmentioning

confidence: 99%

“…Doris et al . () look at the performance only of levels‐based estimates, and their wage model does not allow for either heterogeneous growth or purely transitory shocks. Likewise, Hryshko () focuses only on the performance of growth‐based estimation, while Manovskii et al .…”

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confidence: 99%

The Drivers of Life‐Cycle Wage Inequality in Australia

Freestone

2018

Economic Record

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“…This causes problems in identification, since both the transitory and the permanent components reflect relatively permanent earnings inequality, making it difficult to distinguish them from one another, especially, if panel length is short. Doris et al (2010) gives Monte Carlo evidence on the ranges of parameter values that lead to biased estimates. According to Tables 2a and 3 in their paper, a model estimated using eight panel years of observations and ρ = .8 is sufficient to give unbiased results.…”

Section: Identificationmentioning

confidence: 99%

Earnings dynamics of men and women in Finland: permanent inequality versus earnings instability

Kässi

2013

Empir Econ

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I decompose the variance of earnings of Finnish male and female workers to its permanent and transitory components and study their evolution between the years 1998 and 2007. I find that the increasing earnings inequality of men and women is driven by both transitory and permanent components of earnings. In addition, I find considerable differences in earnings dynamics between men and women that have been largely neglected in previous studies of earnings dynamics. The inequality among men is dominated by the permanent component. Conversely, permanent and transitory components are of comparable magnitudes to women. As a corollary, men face more stable income paths but with larger permanent earnings differences. Women, on the other hand, face more instable earnings profiles but have smaller permanent differences in earnings.The correlation between initial earnings inequality and the growth in earnings inequality is found to be positive for both sexes, implying a divergence of earnings profiles towards end of the working career. In addition, earnings instability has risen for both sexes.JEL codes: J31, J62

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“…Reliable inference on flexible models earnings dynamics requires access to data with both a high number of observations and a long time frame, as Doris et al . () emphasized. We can allow the variance of both permanent and transitory shocks to vary flexibly with workers’ age—an essential feature emphasized in Blundell et al .…”

Section: Introductionmentioning

confidence: 97%

Modelling Earnings Dynamics and Inequality: Foreign Workers and Inequality Trends in Luxembourg, 1988–2009

Sologon

Kerm

2017

Journal of the Royal Statistical Society Series A: Statistics in Society

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Summary. The paper exploits large-scale administrative data to analyse trends in male earnings inequality in Luxembourg during 20 years of rapid economic growth, industrial redevelopment and massive inflow of foreign workers. A detailed error components model is estimated to identify persistent and transitory components of (the trends of) log-earnings variance and to disentangle the contributions to it of native, immigrant and cross-border workers. The model is flexible and allows for a high degree of individual, age, time and cohort heterogeneity. We observe a surprising stability in overall earnings inequality as a result of more complex underlying changes, with marked increases in persistent inequality (except among natives), a growing contribution of foreigners and a decrease in earnings instability (primarily for natives).

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Identification of the covariance structure of earnings using the GMM estimator

Cited by 17 publications

References 43 publications

The Drivers of Life‐Cycle Wage Inequality in Australia

The Drivers of Life‐Cycle Wage Inequality in Australia

Earnings dynamics of men and women in Finland: permanent inequality versus earnings instability

Modelling Earnings Dynamics and Inequality: Foreign Workers and Inequality Trends in Luxembourg, 1988–2009

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