Lifecycle variation, errors-in-variables bias and nonlinearities in intergenerational income transmission: new evidence from Canada

Chen, Wen‐Hao; Ostrovsky, Yuri; Piraino, Patrizio

doi:10.1016/j.labeco.2016.09.008

Cited by 45 publications

(60 citation statements)

References 30 publications

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“…Earnings are comprised of wages and salaries, while income also includes business income, investment income, private and public transfers and irregular income such as redundancies (Summerfield et al, 2016). Potential explanations for the results from this study being inconsistent with past literature are that, since children's income is measured during their late twenties and early thirties, self-employed children may not yet have started their own business, or the accrual of wealth and investment income may be a more important source of income later in the life cycle for children from affluent backgrounds (Chen et al, 2017). The IGE estimate is also larger for earnings than for individual income; however the difference is less marked.…”

Section: (Ii) Rank Correlationscontrasting

confidence: 97%

“…11 Studies estimating the rank correlation include Chetty et al (2014a,b), Dahl and DeLeire (2008) and Mazumder (2015) for the USA; Corak et al (2014) for Canada, Sweden and the USA; Chen et al (2017) for Canada; Nybom and Stuhler (2016) for Sweden; and Gregg et al (2017) for the UK. To the authors' knowledge, there have been no studies that estimate the rank correlation using Australian data.…”

Section: (Ii) Rank Correlationmentioning

confidence: 99%

“…() for Canada, Sweden and the USA; Chen et al . () for Canada; Nybom and Stuhler () for Sweden; and Gregg et al . () for the UK.…”

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confidence: 98%

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Direct Measures of Intergenerational Income Mobility for Australia

Murray¹,

Clark

Mendolia³

et al. 2018

Economic Record

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We present the first Australian estimates of intergenerational mobility that draw on direct observations of income from two generations. Using panel data for three birth cohorts of young adults from the Household, Income and Labour Dynamics Australia Survey, the estimated intergenerational income elasticity is 0.28. Correcting for attenuation bias raises this to 0.41. We estimate the rank correlation to be 0.27. We show that Australia has greater mobility than the USA, and this is not sensitive to methodological choices. We also show that spousal selection and family structure may be important determinants of income persistence across generations.

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Section: (Ii) Rank Correlationscontrasting

confidence: 97%

Section: (Ii) Rank Correlationmentioning

confidence: 99%

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Direct Measures of Intergenerational Income Mobility for Australia

Murray¹,

Clark

Mendolia³

et al. 2018

Economic Record

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“…Future analyzes could evaluate: (1) 1971, 1973, 1975, 1976, 1978, 1980, 1981National Longitudinal Survey Zimmerman (1992) 1977-1996, 1998, 2000 Panel Study of Income Dynamics ) 1979-2000Cross National Equivalent File Vogel (2006 1980 N/A Behrman and Taubman (1985) cited in Corak (2006) 1980National Longitudinal Survey Grawe (2004 1993-1996, 2001-2008, 2003-2006 Intergenerational Income Data Chen, Ostrovsky, and Piraino (2017) 1995 Administrative data and Canadian income tax Corak and Heisz (1999) Jantti, Bratsberg, Roed et al (2006) 1996, 1998, 2000, 2002, 2004 Statistics Sweden's administrative data Bratberg, Davis, Mazumder et al (2017) …”

Section: Final Considerationsmentioning

confidence: 99%

A meta-analysis of the association between income inequality and intergenerational mobility

Amaral¹,

Yen²,

Wang³

2018

Preprint

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Our aim is to provide an overview of associations between income inequality and intergenerational mobility in the United States, Canada, and eight European countries (Denmark, Finland, France, Germany, Italy, Norway, Sweden, and the United Kingdom). We analyze whether this correlation is observed across and within countries over time. Developed countries have been experiencing increases in inequality in recent decades, mostly due to a steep concentration of income at the top of the distribution. We investigate Great Gatsby curves and perform meta-regression analyses based upon several papers on this topic. Results suggest that countries with high levels of inequality tend to have lower levels of mobility. Intergenerational income elasticities have stronger associations with the Gini coefficient, compared to associations with the top one percent income share. Once models are controlled for methodological variables, country indicators, and paper indicators, correlations of mobility with the Gini coefficient lose significance, but not with the top one percent income share. This result is an indication that recent increases in inequality at the top of the distribution (captured by the top one percent income share) might be negatively affecting mobility on a greater magnitude, compared to variations across the income distribution (captured by the Gini coefficient).

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“…This table is not meant to offer a comprehensive survey, but rather a list of the recent influential studies. The sources are: Chen, Ostrovsky and Piraino (2017), Connolly, Corak and Haeck (2019), Corak (2019), Deutscher and Mazumder (2019), http://EqualChances.org (2019), Fairbrother and Mahadevan (2016), Huang, Perales and Western (2016), Leigh (2007), Mendolia and Siminski (2016) and Murray et al (2018). …”

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confidence: 99%

Intergenerational Mobility: What Do We Care About? What Should We Care About?

Corak¹

2020

Australian Economic Review

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Inequality threatens intergenerational income mobility, but different types of inequality threaten mobility in different ways, raising distinct policy challenges. This is why empirical researchers should be agnostic in the choice of statistics they use to measure intergenerational mobility. I argue that Australia is on the whole characterised by a good deal of intergenerational mobility, but that a full picture requires judicious international comparisons across different dimensions of mobility citizens care about, mobility not just of incomes, but also of position and direction, particularly the scope for upward mobility.

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Lifecycle variation, errors-in-variables bias and nonlinearities in intergenerational income transmission: new evidence from Canada

Cited by 45 publications

References 30 publications

Direct Measures of Intergenerational Income Mobility for Australia

Direct Measures of Intergenerational Income Mobility for Australia

A meta-analysis of the association between income inequality and intergenerational mobility

Intergenerational Mobility: What Do We Care About? What Should We Care About?

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