The Unassuming Economist

Source: Peterson Institute of International Economics

While a lot of research conducted from 2021 until March of 2022 suggests that labor markets in the US reached record high levels of tightness as job openings and quits rose, recent evidence collected by the Peterson Institute indicates the possibility of a potential cool down. The underlying argument driving this idea is that the sharp spike in nominal wages in 2021 could have been a result of some post-pandemic factors that shaped expectations of longer-run inflation which ultimately got dragged until 2022. So even though labor force participation rates in the US in April 2022 remained at 3.6%, 0.1% higher than the corresponding pre-pandemic level, the authors argue that this shortfall in employment is driven by a labor supply shortage as demand is robust.

The article also touches upon related issues like rising nominal wages that are beginning to plateau now and a somewhat alarming drop in real wages.

Read the full article to know more.

From a new paper by Davide Furceri, Prakash Loungani, Jonathan D. Ostry, and Pietro Pizzuto:

“This paper provides evidence on the impact of major epidemics from the past two decades on income distribution. The pandemics in our sample, even though much smaller in scale than COVID-19, have led to increases in the Gini coefficient, raised the income share of higher income deciles, and lowered the employment-to-population ratio for those with basic education compared to those with higher education. We provide some evidence that the distributional consequences from the current pandemic may be larger than those flowing from the historical pandemics in our sample, and larger than those following typical recessions and financial crises.”

Source: VoxEU CEPR

Abstract: Since the beginning of the pandemic, labour market indicators have been sending different signals about the degree of slack in the US labour market. This column uses time-series and cross-section data to show that firm-side unemployment (figure underneath) – a measure that ties together the unemployment rate with the vacancy and quits rate – predicts wage inflation better than the unemployment rate or the employment ratio, and that firm-side unemployment currently experienced in the US corresponds to a degree of tightness previously associated with sub 2% unemployment. The findings suggest that labour markets in the US are extremely tight and will likely contribute to inflationary pressures for some time to come.

Figure: Actual unemployment rate versus firm-side estimated unemployment rate

Ironically, in the big data age of today, a significant barrier to women’s inclusion in formal economies is made up of the lack of sex-disaggregated data at the high level. Within this, the lack of more granular data to base models and policies on, the lack of data on related services like internet access, use of bank accounts, feature phones and smartphones, or even inclusion in the national identification process is hard to come by.

In a recent blog detailing ideas for their new project, Strengthening Gender Statistics, officials from the World Bank Group write about challenges to accessing quality gendered data and how to tackle them. They try to understand the vast variety of challenges by grouping them into three categories- challenges to data production, analysis, and dissemination.

Read also:

Making Women and Girls Visible: Gender Data Gaps and Why They Matter (2018), UN Women

Closing gender data gaps in the world of work- role of the 19th ICLS standards (2020), ILO

Source: Ideas for India

In a recent column for the Ideas for India blog, development economist Jean Dreze writes about the perils of experimental policymaking. While data-based policy design is quite the rage now with randomized control trials (RCTs) being used to gather evidence on “what works” and then scaling up whatever does, Dreze writes how a more comprehensive approach to policymaking would be one where insights from data are interspersed with a sound mix of understanding the issues, value judgments, and deliberation on inclusivity.

He makes a case for this argument by discussing an experiment conducted in the Indian state of Bihar during 2012-13 to study a new financial management system in the Mahatma Gandhi National Rural Employment Guarantee Act (Banerjee, Duflo, Imbert, Mathew, and Pande (2020). From delivering counter-productive results in the form of reducing, not enhancing, the baseline expenditure on this scheme to delays in workers’ payments and the lack of significant differences between outputs of the treatment and control groups, this article draws attention to the challenges associated with hasty rollouts of interventions and subsequent conclusions based on them without negating the learnings. It concludes with some best practices for engaging with governments, conducting experiments at scale, and ensuring that the “do no harm” principle of RCTs stays put.