Cash transfers following the birth of a first child can have large and long-lasting effects on that child’s outcomes. Andrew C. Barr and two co-authors made use of natural experiment—the January 1 birthdate cut-off for U.S. child-related tax benefits. Children born in December of previous year are eligible for tax deduction, while children born just a couple of weeks later, in January, are not eligible. As a result, families with otherwise similar children receiving substantially different refunds during the first year of life—roughly $1,300, or 10 percent of income for the average low-income single-child.
Using the careful data connection strategy, authors showed that this transfer in infancy increases young adult earnings by at least 1 to 2 percent, with larger effects for males. Baseline estimates indicate that eligibility for additional resources during the first year of life generates a $319 increase in average annual earnings between age 23 and 25 and a $456 increase between ages 26 and 28. These effects persist to older ages, with 2-3 percent increases at ages 29-31 and 32-34. These estimated effects are larger than those generated by the in-kind support programs. According to calculations, additional tax receipts associated with the increased earnings in adulthood, exceed the amount of the initial transfer, implying a negative net cost to the federal government.
The observed earnings effects appear to be explained by earlier human capital effects. the North Carolina education data showed substantial increases in test scores, reductions in behavioural problems, and a greater likelihood of high school graduation during childhood and adolescence. This chart shows effect of cash transfer eligibility on student outcome index, constructed as the mean of normalized test scores in grade 3-8, high school graduation, and any suspension in middle or high school. Birthdates to the left of the dotted line represent those where the child’s family could have received additional resources from child-related tax benefits in the following year (if eligible based on income).
More than century ago Henry Ford made an unusual offer. He guaranteed pay $5 per day (around $150 per day in today’s dollars) for eight hours of assembly line work for all workers at his production plant. At the time the offer was surprising and created a lot of hype. It was quite generous, roughly doubled workers’ pay. It went against common wisdom—labour is abundant, you could fire and replace workers in no time. Ford had his own views, based on the issue he faced. Ford standardised products and production processes at plants. The workers were not, turnover was high, and quality of products varied. Generous wage offer aimed at reducing workers turnover and maintaining this hidden human capital. Arguably, it paid off in a long run.
Century later economists got data to confirm Ford’s intuition and quantify the hidden cost of worker turnover. Recent article in Management Science “The Hidden Cost of Worker Turnover: Attributing Product Reliability to the Turnover of Factory Workers” combined data on weekly workers turnover at major electronic producer plant, and data on field failures of their electronic products. Result? For Each percentage point increase in the weekly rate of workers quitting from an assembly line, field failures increase by 0.74%–0.79%. These extra failures could total to striking 10.2% in the high-turnover weeks following paydays. The associated costs amount to hundreds of millions of U.S. dollars.
The issue seems to be even worse in new sectors economy, knowledge based. Search Cloud provider Sinequa published findings from a survey of 1,000 IT managers at large organizations in the UK and US to explore the impact the Great Resignation has on employee experience, productivity, and organizational risk. It showed that 64% felt that their organization already has experienced loss of knowledge due to people leaving the company. There is a concern that turnover could have a cumulative effect—56% of surveyed managers agreed it will hurt the organization’s ability to onboard new employees. Hidden human capital is not that visible, highly underappreciated, and could be quite costly to replace.
If data are not persuasive enough, here is a nice meme on newbie dealing with legacy products.
COVID-19 can undermine life-long perspectives of young people. Students globally lost eight months of learning and the impact varies widely from staggering 12 months in South Asia and Latin America and Caribbean to modest 4 months in North America and Europe and Central Asia. Recent McKinsey study identifies three archetypes of countries: 🚩 Most affected countries with moderate levels of pre-COVID-19 learning and significant delays in education, where students may be nine to 15 months behind. 🚩 Prepandemic-challenged countries, with very low levels of pre-COVID-19 learning, where losses were daunting but not so dramatic in absolute terms, about three to eight months 🚩 Least affected are high-performing countries, with relatively high levels of pre-COVID-19 performance, where losses were limited to one to five months.
Lower levels of learning translate into lower future earnings potential for students and lower economic productivity for nations (📉 losing 1 percent of global GDP annually, according to McKinsey estimates). By using scenario modelling UNDP came to similar conclusions. The study shows how governments can make choices today that have the greatest potential to boost progress in the future. School systems can respond across multiple horizons to help students get back on track: ⭐Resilience, 🔁Reenrollment, 🔼Recovery, and 💡Reimagining.