The Unassuming Economist

From Raj Chetty’s (Harvard University) Testimony Before the House Financial Services Committee:

“Stable housing in high-opportunity neighborhoods can provide a critical foundation for a variety of outcomes such as future earnings, health, and education. Failing to meet our children’s basic housing needs serves to worsen already-stark racial and economic disparities and bar generations from growing up and joining the middle class.

Today, we have an unprecedented opportunity to expand access to neighborhoods that research shows are foundational to children’s and families’ long-term success. Well-designed expansions of the Housing Choice Voucher program, public housing investments, the Housing Tax Credit, and place-based investments could significantly increase housing supply and access to opportunity. Such investments can give all children an opportunity to grow-up in communities that will support their long-term success.

More broadly, to achieve long-term mobility for all children in the United States, we must reduce historic patterns of segregation that have limited access to opportunity-rich neighborhoods, particularly for Black and Hispanic Americans. Equally important, we must also increase opportunity in communities that do not presently see such outcomes. Expanding access to affordable housing can be valuable on both fronts. We must continue to deploy our resources towards increasing options for low- and middle-income families living in areas currently offering high levels of opportunity, and simultaneously to maintain and expand high-quality housing options and community development efforts in areas that currently offer lower levels of opportunity. These strategies will help ensure that all families have a true choice about where to live, reduce the present bifurcation between ‘high’ and ‘low; opportunity areas across the country, and give all children – irrespective of their race, ethnicity, or family income – a chance of achieving the American Dream.”

Policymaking and research on perhaps some of the most pressing social issues in the contemporary world today, like poverty, inequality, access to resources, and related matters, is both blessed and plagued with the idea that additional evidence on people’s identities and information sets can radically transform the rate of success or failure of policies. 

Among other things, one such question has also been the irony of demand for redistributive and poverty alleviation programs not rising commensurately or even remotely as much with the ever-rising level of inequalities in the world. Many studies have attempted to explain this phenomenon by presenting the idea that poor people often have only limited knowledge about their relative deprivation viz other people in the economy. They also believe their income levels to approximately coincide with the average income level of the country, thus convincing themselves of the non-usefulness of any redistribution programs. 

This study, by Hoy and Mager, empirically tests some of these theories using randomized surveys and churns out some insightful observations. It redefines the idea of ‘benchmarking’ incomes for designing redistribution programs and explains the importance of information sets in shaping poor people’s preferences for accepting aid. 

Click here to read more.

From https://voxeu.org/

By Elena Bobeica, Gabriel Pérez-Quirós, Gerhard Rünstler, Georg Strasserposted on 31 October 2021 

“The recent decade has shown that forecasters need to continuously adapt their tools to cope with increasing macroeconomic complexity. Just like the global crisis, the current Covid-19 pandemic highlights once again that forecasters cannot be content with just assessing the single most likely future outcome – such as a single number for future GDP growth in a certain year. Instead, a characterisation of all possible outcomes (i.e. the entire distribution) is necessary to understand the likelihood and nature of extreme events.

This is key for central bank forecasters as well, as pointed out by ECB Executive Board member Philip Lane in his opening remarks at the 11th Conference on Forecasting Techniques. Central banks rely heavily on forecasts to design their policy and need robust techniques to navigate through turbulent times. They not only ensure price stability and are thus directly interested in the most likely future inflation path, but in the process also contribute to the understanding, managing, and handling of macro-economic risks and thus need to grasp the likelihood of extreme events (see also the discussion in Greenspan 2004).”

Continue reading here.

From a new CESifo working paper by Kajal Lahiri & Cheng Yang

“We forecast New York state tax revenues with a mixed-frequency model using a number of machine learning techniques. We found boosting with two dynamic factors extracted from a select list of New York and U.S. leading indicators did best in terms of correctly updating revenues for the fiscal year in direct multi-step out-of-sample forecasts. These forecasts were found to be informationally efficient over 18 monthly horizons. In addition to boosting with factors, we also studied the advisability of restricting boosting to select the most recent macro variables to capture abrupt structural changes. Since the COVID-19 pandemic upended all government budgets, our boosted forecasts were used to monitor revenues in real time for the fiscal year 2021. Our estimates showed a drastic year-over-year decline in real revenues by over 16% in May 2020, followed by several upward nowcast revisions that led to a recovery to -1% in March 2021, which was close to the actual annual value of -1.6%.”

From VoxEU.ORG

Expectations data indicate the US is entering recession about now

By Alex Bryson, David Blanchflower 21 October 2021

“With the mass rollout of COVID-19 vaccinations and the attendant decline in COVID-related deaths in most advanced economies, and with many economic indices turning positive, it looks like most economies are on the road to recovery although the data paint a confusing picture. 

For example, in the spring of 2020, wage growth jumped sharply at the same time unemployment was rising. This was in both the US and the UK. Since then, unemployment has been falling while wage growth remains high. This implies the wage curve slopes up, which seems unlikely. But other metrics are telling a different story, most notably those capturing consumer and business sentiment.

Two series – from The Conference Board on business conditions, employment and income six months hence, and from the University of Michigan on the financial situation in a year and business conditions a year and five years hence – tell the same story: sentiment peaked in spring or early summer. And it has been falling precipitously since (Blanchflower and Bryson 2021a). This is true for the US as a whole and for the eight largest states for which The Conference Board collect data.”

Continue reading here.