Measuring inequality

McGregor, Thomas; Smith, Brooke M.; Wills, Samuel

doi:10.1093/oxrep/grz015

Cited by 29 publications

(21 citation statements)

References 77 publications

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“…We use our methods to analyze admissions data from a selective U.K. university on applicants who have cleared an initial exam-based elimination round. We first provide evidence in support of our identifying assumption; we then apply our methods to show that male applicants face a higher admission standard than females, 1 whereas standards faced by private school applicants are possibly slightly higher than those faced by state school applicants. In contrast, the application success rates are very similar across gender and type of school attended by the candidate, both before and after controlling for key covariates, thereby illustrating the crux of our approach.…”

Section: Introductionmentioning

confidence: 77%

Are University Admissions Academically Fair?

Bhattacharya

Kanaya

Stevens

2017

The Review of Economics and Statistics

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Admission practices at high-profile universities are often criticized for undermining academic merit. Popular tests for detecting such biases suffer from omitted characteristic bias. We develop a bounds-based test to circumvent this problem. We assume that students who are better qualified on observables would, on average, appear academically stronger to admission officers based on unobservables. This assumption reveals the sign of differences in admission standards across demographic groups that are robust to omitted characteristics. Applying our methods to admissions data from a British university, we find higher admission standards for men and slightly higher ones for private school applicants, despite equal admission success probability across gender and school background.

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Section: Introductionmentioning

confidence: 77%

Are University Admissions Academically Fair?

Bhattacharya

Kanaya

Stevens

2017

The Review of Economics and Statistics

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“…Inequality measures: In order to proxy income inequality within countries, we use the Gini coefficient as provided by Hammar and Waldenström (2017) and focus on net yearly labour earnings, meaning after taxes and employee social security deductions. The advantage of using net earnings is that we automatically control for taxes and get an impression of the effect of financial crises on the resources that people can dispose of (McGregor, Smith, & Wills, 2019).…”

Section: Operationalizationmentioning

confidence: 99%

Casino Capitalism? The Impact of Financial Crises on Inequality, 1970 to 2016

Rübsam

Schneider

2020

Preprint

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The ways in which countries have reacted to financial crises varies considerably. While income inequality has grown in more than half of the EU member states after the Great Recession, some countries such as the United States have experienced a significant increase in wealth inequality. A number of countries, by contrast, was able to keep these inequities at bay. We argue in this paper that the impact of financial crises on inequality differ between the type and severity of these economic shocks and that sovereign debt and exchange rate rather than banking crises increase the economic inequities. The paper also examines the extent to which fiscal constraints of governments and membership in the Eurozone mediate these effects. We examine the diverse income and wealth inequality effects to more than 50 financial crises across the OECD member states from 1970 to 2010. The empirical evidence gathered so far supports our conjecture of different distributive effects of varying types of crises.

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“…Moreover, each inequality statistic embeds, explicitly or implicitly, value judgement about the relative importance of individual income earners along the income distribution. Inequality statistics are, contrary to their promise, "not purely statistical" (McGregor et al, 2019).…”

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confidence: 96%

“…Similarly, the Gini coefficient weighs more heavily incomes close to the center of the distribution than in the tails (Cowell, 2011). Economists typically focus only on one indicator, either because of practicality (the Gini is the most readily available indicator) or because they are making explicit assumptions about social welfare function (see Jenkins and Van Kerm, 2011;McGregor et al, 2019;andRavallion, 2014, and2018, for an introduction).…”

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confidence: 99%

Measuring Income Inequality and Implications for Economic Transmission Channels

Blotevogel¹,

Imamoglu²,

Moriyama³

et al. 2020

IMF Working Papers

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We study the channels that theoretically transmit the effects of inequality to economic growth, unlike much of the existing literature that focuses on the direct linkage. The role of inequality in these transmission channels is difficult to pin down and varies with the particular inequality indicator chosen. We run our analyses with six methodologically distinct inequality measures (Gini coefficients and Top10 income shares). Methodological differences within the set of Gini coefficients and the Top10 income shares exert a first-order impact on the estimated relationships, which is generally larger than the effect of switching between Gini and Top10 income shares. For a given inequality indicator, we find that the transmission channels can react in opposite directions, with the net effect on growth difficult to determine. Finally, we emphasize two additional but so far underappreciated empirical complications: (i) estimated relationships change over time; and (ii) fragile countries create significant but counterintuitive empirical associations that may obscure structural relationships.

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Measuring inequality

Cited by 29 publications

References 77 publications

Are University Admissions Academically Fair?

Are University Admissions Academically Fair?

Casino Capitalism? The Impact of Financial Crises on Inequality, 1970 to 2016

Measuring Income Inequality and Implications for Economic Transmission Channels

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