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on Unemployment, Inequality and Poverty |
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Issue of 2017‒07‒02
five papers chosen by |
| By: | Richard V. Burkhauser; Nicolas Hérault; Stephen P. Jenkins; Roger Wilkins |
| Abstract: | Survey under-coverage of top incomes leads to bias in survey-based estimates of overall income inequality. Using income tax record data in combination with survey data is a potential approach to address the problem; we consider here the UK’s pioneering ‘SPI adjustment’ method that implements this idea. Since 1992, the principal income distribution series (reported annually in Households Below Average Income) has been based on household survey data in which the incomes of a small number of ‘very rich’ individuals are adjusted using information from ‘very rich’ individuals in personal income tax return data. We explain what the procedure involves, reveal the extent to which it addresses survey under-coverage of top incomes, and show how it affects estimates of overall income inequality. More generally, we assess whether the SPI adjustment is fit for purpose and consider whether variants of it could be employed by other countries. |
| JEL: | C81 D31 |
| Date: | 2017–06 |
| URL: | http://d.repec.org/n?u=RePEc:nbr:nberwo:23539&r=ltv |
| By: | David Neumark (University of California-Irvine); Ian Burn (University of California-Irvine); Patrick Button (Tulane University); Nanneh Chehras (University of California-Irvine) |
| Abstract: | We provide evidence from a field experiment — a correspondence study — on age discrimination in hiring for retail sales jobs. We collect experimental data in all 50 states and then relate measured age discrimination — the difference in callback rates between old and young applicants — to variation across states in antidiscrimination laws offering protections to older workers that are stronger than the federal age and disability discrimination laws. We do a similar analysis for nonexperimental data on differences across states in hiring rates of older versus younger workers. The experimental evidence points consistently to evidence of hiring discrimination against older men and, more so, against older women. However, the evidence on the relationship between hiring discrimination against older workers and state variation in age and disability discrimination laws is not so clear; at a minimum, there is not a compelling case that stronger state protections reduce hiring discrimination against older workers. In contrast, the non-experimental evidence suggests that stronger disability discrimination protections increase the relative hiring of older workers. |
| Date: | 2017–03 |
| URL: | http://d.repec.org/n?u=RePEc:mrr:papers:wp360&r=ltv |
| By: | Edward P. Lazear |
| Abstract: | Success, measured by earnings or education, of immigrants in the US varies dramatically by country of origin. For example, average educational attainment among immigrants ranges from 9 to 16 years, depending on source country. Perhaps surprisingly, immigrants from Algeria have higher educational attainment than those from Israel or Japan. Also true is that there is a strong inverse relation of attainment to number of immigrants from that country. These patterns result because in the US, immigrant slots are rationed. Selection from the top of the source country’s ability distribution is assumed and modeled. The main implications are that average immigrant attainment is inversely related to the number admitted from a source country and positively related to the population of that source country. The results are unequivocally supported by results from the American Community Survey. Additionally, a structural model that is more explicit in the assumptions and predictions fits the data well. |
| JEL: | F22 J01 J15 J61 M5 |
| Date: | 2017–06 |
| URL: | http://d.repec.org/n?u=RePEc:nbr:nberwo:23548&r=ltv |
| By: | Berggren, Niclas (Research Institute of Industrial Economics (IFN)); Ljunge, Martin (Research Institute of Industrial Economics (IFN)) |
| Abstract: | Religious beliefs and practices influence individual lives and societies in many ways. We study how religion affects self-assessed health, which in turn is important for both individual well-being and productivity. A religious background predicts worse health. As the previous literature has not been able to rule out reverse causality, we apply a novel method that does. The health of the children of immigrants in 30 European countries is related to different measures of religiosity in their mothers’ birth countries. Since religiosity in the mothers’ birth countries predicts children’s religiosity (through transmission in the family), we can use the former as a measure of the latter. Moreover, the children’s health arguably cannot affect the religiosity of their mothers’ home countries (measured several decades earlier). Furthermore, the negative relationship between religious background and health is robust to accounting for a range of individual and ancestral country characteristics, to excluding the most and least religious ancestral countries, and to accounting for systematic differences across ancestral continents. The negative relationship, which we also find in U.S. data, suggests that the positive correlations between health and religiosity in the earlier literature are not due to religion promoting health. |
| Keywords: | Health; Religion; Children of Immigrants |
| JEL: | I19 Z12 |
| Date: | 2017–06–21 |
| URL: | http://d.repec.org/n?u=RePEc:hhs:iuiwop:1173&r=ltv |
| By: | Simionescu, Mihaela; Zimmermann, Klaus F. |
| Abstract: | Internet or "big" data are increasingly measuring the relevant activities of individuals, households, firms and public agents in a timely way. The information set involves large numbers of observations and embraces flexible conceptual forms and experimental settings. Therefore, internet data are extremely useful to study a wide variety of human resource issues including forecasting, nowcasting, detecting health issues and well-being, capturing the matching process in various parts of individual life, and measuring complex processes where traditional data have known deficits. We focus here on the analysis of unemployment by means of internet activity data, a literature starting with the seminal article of Askitas and Zimmermann (2009a). The article provides insights and a brief overview of the current state of research. |
| Keywords: | big data,unemployment,internet,Google,internet penetration rate |
| JEL: | C22 C82 E17 E24 E37 |
| Date: | 2017 |
| URL: | http://d.repec.org/n?u=RePEc:zbw:glodps:81&r=ltv |