Stefania Albanesi,
Giacomo De Giorgi, Jaromir Nosal, VOX: Mortgage default during the Great
Recession came from real estate investors, not subprime credit holders. The Global Crisis narrative has suggested that an
expansion of subprime credit was the reason for rising mortgage defaults,
leading to the large-scale recession in 2007-09. Taking a closer look at the
characteristics of subprime credit holders over the period, this column argues
that the growth in
mortgage defaults did not occur predominantly amongst subprime credit holders.
Instead, it was real estate investors that played a critical role in the rise
in mortgage debt, specifically among the middle and the top of the credit score
distribution.
Youssef Benzarti,
Dorian Carloni, NBER: Who Really Benefits from Consumption Tax Cuts? Evidence
from a Large VAT Reform in France. In this paper we evaluate the incidence of a large cut in value-added
taxes (VAT) for French sit-down restaurants. In contrast to previous studies
that focus on prices only, we estimate its effect on four groups: workers, firm
owners, consumers and suppliers of material goods. Using a difference-in-differences strategy on
firm-level data we find that: (1) the effect on consumers was limited, (2)
employees and sellers of material goods shared 25 and 16 percent of the total
benefit, and (3) the reform mostly benefited owners of sit-down restaurants,
who pocketed 41 percent of the tax cut.
Brad Hershbein,
Lisa B. Kahn, Harvard Business Review: Drastically Changed the Skills Employers
Want. Previous research has suggested that a primary driver
of this job polarization is something called routine-biased technological
change (RBTC). In recent research we investigate how the demand for skills
changed over the Great Recession (2007-09). Using nearly all electronically
posted job vacancies in 2007 and 2010–2015 collected by the analytics company
Burning Glass Technologies, as well as geographic differences in economic
conditions, we establish a new fact: the skill requirements of job ads increased in metro areas that
suffered larger employment shocks in the Great Recession, relative to the same
areas before the shock and to other areas that experienced smaller shocks.
Our estimates imply that ads posted in a hard-hit metro area are about 5
percentage points (16%) more likely to contain education and experience
requirements and about 2–3 percentage points (8‒12%) more likely to include
requirements for analytical and computer skills.
Anne Boschini,
Kristin Gunnarsson, Jesper Roine, IZA: Women in Top Incomes: Evidence from
Sweden 1974–2013. Using a large, register-based panel data set
we study gender differences in top incomes in Sweden over the period 1974–2013.
We find that, while women
are still a minority of the top decile group, and make up a smaller share the
higher up in the distribution we move, their presence has steadily increased in
all top groups over the past four decades. Top income women are
wealthier and rely more on capital incomes, but the difference, relative to
men, has decreased since the 1970s. Over this period capital incomes have in
general become more important in the top, but the share of working-rich women
has gone up, while the opposite is true for men.
Jamie Cullen, The
Atlantic: When Working From Home Doesn’t Work. The expectation was that information technology would flatten the
so-called Allen Curve. But Ben Waber, a visiting scientist at MIT, recently
found that it hasn’t. The
communications tools that were supposed to erase distance, it turns out, are
used largely among people who see one another face-to-face. In one study
of software developers, Waber, working alongside researchers from IBM, found
that workers in the same office traded an average of 38 communications about
each potential trouble spot they confronted, versus roughly eight
communications between workers in different locations.
The Optimizing
Government Project: This Project draws
together researchers from across the University of Pennsylvania and the
Philadelphia area to collaborate on studying the implementation of machine
learning by government. The project aims to assess the technical, legal, ethical, and political
challenges associated with machine learning in government, promoting
collaboration between government, the private sector, and the academy.
No comments:
Post a Comment