The Unassuming Economist

From a NBER paper by Rebecca Diamond and Enrico Moretti:

“Income differences across US cities are well documented, but little is known about the level of standard of living in each city—defined as the amount of market-based consumption that residents are able to afford. In this paper we provide estimates of the standard of living by commuting zone for households in a given income or education group, and we study how they relate to local cost of living. Using a novel dataset, we observe debit and credit card transactions, check and ACH payments, and cash withdrawals of 5% of US households in 2014 and use it to measure mean consumption expenditures by commuting zone and income group. To measure local prices, we build income-specific consumer price indices by commuting zone. We uncover vast geographical differences in material standard of living for a given income level. Low-income residents in the most affordable commuting zone enjoy a level of consumption that is 74% higher than that of low-income residents in the most expensive commuting zone.

We then endogenize income and estimate the standard of living that low-skill and high-skill households can expect in each US commuting zone, accounting for geographical variation in both costs of living and expected income. We find that for college graduates, there is essentially no relationship between consumption and cost of living, suggesting that college graduates living in cities with high costs of living—including the most expensive coastal cities—enjoy a standard of living on average similar to college graduates with the same observable characteristics living in cities with low cost of living—including the least expensive Rust Belt cities. By contrast, we find a significant negative relationship between consumption and cost of living for high school graduates and high school drop-outs, indicating that expensive cities offer a lower standard of living than more affordable cities. The differences are quantitatively large: High school drop-outs moving from the most to the least affordable commuting zone would experience a 26.9% decline in consumption.”

On December 7th, 2021, the World Inequality Lab released the World Inequality Report 2022, authored by the Lab’s co-director and economist Lucas Chancel and economists Thomas Piketty, Emmanuel Saez, and Gabriel Zucman. Through the course of its 10 chapters, the report covers insights on themes like changing global economic inequality, the rise of multimillionaires, the disproportionate burden of labor income discrimination on women, carbon inequalities, tax justice, and sustainability. Some notable statistics from the report yield the following results:

1. Income inequality: Globally, the richest 10% of the population currently earns 52% of the global income, whereas the poorest half of the population earns 8% of it. On average, an individual from the top 10% of the global income distribution earns €87,200 (USD122,100) per year, whereas an individual from the poorest half of the global income distribution makes €2,800 (USD3,920) per year.
2. Wealth inequality: The poorest half of the global population barely owns any wealth at all, possessing just 2% of the total. In contrast, the richest 10% of the global population own 76% of all wealth. On average, the poorest half of the population owns PPP €2,900 per adult, i.e. USD4,100 and the top 10% own €550,900 (or USD771,300) on average.
3. Regional variations in inequality: In Europe, the top 10% income share is around 36%, whereas in MENA it reaches 58%. In between these two levels, we see a diversity of patterns. In East Asia, the top 10% makes 43% of total income and in Latin America, 55%. Moreover, while some countries have experienced spectacular increases in inequality (including the US, Russia and India) others like European countries and China have only experienced a little rise.
4. Nations have become richer, but governments have grown poorer: Private wealth has grown immensely but the share of the public sector in total national wealth is close or euqal to 0 in rich countries.
5. Gender inequalities in labor income: Women’s share of total incomes from work (labor income) neared 30% in 1990 and stands at less than 35% today

The report also includes excerpts from Thomas Piketty’s upcoming book titled, ‘A brief history of inequality‘, slated for release in 2022 in the concluding chapter.

Click here to access the full report.

From the IMF’s latest report on Albania:

“Enhanced surveillance of the fast-growing real estate market is needed. Housing price growth has averaged 11 percent annually since 2018, driven by prices in Tirana and coastal areas. Mortgages account for 64 percent of household loans and construction loans account for 13 percent of total loans to enterprises. Staff encouraged the authorities to address data gaps in the real estate market and develop indicators to closely monitor the potential impact of the sector on financial stability.”

Abstract of this National Bureau for Economic Research (NBER) working paper (2021) by Jean-Felix Brouillette, Charles I. Jones, and Peter J. Klenow of Standford University:

“We construct a measure of consumption-equivalent welfare for Black and White Americans. Our statistic incorporates life expectancy, consumption, leisure, and inequality, with mortality rates playing a key role quantitatively. According to our estimates, welfare for Black Americans was 43% of that for White Americans in 1984 and rose to 60% by 2019. Going back further in time (albeit with more limited data), the gap was even larger, with Black welfare equal to just 28% of White welfare in 1940. On the one hand, there has been remarkable progress for Black Americans: the level of their consumption-equivalent welfare increased by a factor of 28 between 1940 and 2019 when aggregate consumption per person rose a more modest 5-fold. On the other hand, despite this remarkable progress, the welfare gap in 2019 remains disconcertingly large. Mortality from COVID-19 has temporarily reversed a decade of progress, lowering Black welfare by 17% while reducing White welfare by 10%.”

Click here to read the full paper.

New Paper by Frank Schorfheide & Dongho Song

“We resuscitated the mixed-frequency vector autoregression (MF-VAR) developed in Schorfheide
and Song (2015, JBES) to generate macroeconomic forecasts for the U.S. during the COVID-19
pandemic in real time. The model combines eleven time series observed at two frequencies:
quarterly and monthly. We deliberately did not modify the model specification in view of the
COVID-19 outbreak, except for the exclusion of crisis observations from the estimation sample.
We compare the MF-VAR forecasts to the median forecast from the Survey of Professional
Forecasters (SPF). While the MF-VAR performed poorly during 2020:Q2, subsequent forecasts
were at par with the SPF forecasts. We show that excluding a few months of extreme
observations is a promising way of handling VAR estimation going forward, as an alternative of a
sophisticated modeling of outliers.”

Read more here.