The rate of new business startups has fallen drastically over the last thirty-five
years, a trend that accelerated after the year 2000. Other measures of business
dynamism, such as the job reallocation rate, are consistent with this trend. This
has raised serious concern, given the effect that young, high-growth firms have been
shown to have on employment, and may also have on innovation and growth. The
timing of this decline coincides with the start of a steady increase in both the life expectancy and average age of the workforce. I document that an individual's propen-
sity to select into entrepreneurship follows a 'hump shape' as they age. To account
for both individual behavior and aggregate trends, I construct a life cycle model of
entrepreneurial choice, studying a number of channels that link demographic forces
to entrepreneurial selection. I find that demographic channels can account for a
large portion of the recent decline in startup activity. This model predicts that
entrepreneurial activity will continue to decline as the pool of potential entrepreneurs
continue to age. I conclude with a discussion of the potential policy tools that will affect
individual's life cycle risk attitudes and the predicted effects that such measures
will have on the rate of new business startups.
with Alan M. Taylor
Population aging has been linked to global declines in interest rates. A similar trend
shows that equity risk premia are on the rise. An existing literature can explain part
of the decline in the trend in safe rates using demographics, but has no mechanism to
speak to trends in relative asset prices. We calibrate a heterogeneous agent life-cycle
model with equity markets, showing that this demographic channel can simultaneously
account for both the majority of a downward trend in the risk free rate, while also
increasing premium attached to risky assets. This is because the life cycle savings
dynamics that have been well documented exert less pressure on risky assets as older
households shift away from risk. Under reasonable calibrations we find declines in
the safe rate that are considerably larger than most existing estimates between the
years 1990 and 2017. We are also able to account for most of the rise in the equity risk
premium. Projecting forward to 2050 we show that persistent demographic forces will
continue push the risk free rate further into negative territory, while the equity risk
premium remains elevated.
The currency union effect on trade has been a contentious topic, with a wide range of estimates on the true size of gains.
One fundamental issue underlying many estimates is the lack of a accurate control group against which to compare outcomes, making
it hard to understand the degree to which makes existing estimates even harder to interpret from the perspective of policy makers.
Estimates of gains within the eurozone tend to be smaller, while the sovereign debt crisis in Europe caused many to question the long
term viability of the union. It is crucial for the public debate over the costs and benefits of eurozone membership to bring more clarity
to our understanding of the benefits from trade that such a union provides to its members. I propose a novel approach to this literature
that applies inverse propensity score weighting as well as local projections to study both the traditional static estimates of trade as well
as forecasts of the effect of currency unions on trade over time. I find that the static effect of currency unions on trade are in general still
quite large for currency unions in general, but quite small for the emu. However, I find the puzzling result that the currency union effect on trade
for the euro declined over the period from implementation until the recession in 2008. Since the expected effect should be fixed over time this suggests
a deeper understanding of the simultaneous policy changes that take place over the period that may bias static effects upwards.
Stuck in the Middle with You: Structural Change and Inequality
with Andrew Padovani
When industries grow at different rates how do labor market frictions, coupled with age specific life cycle occupational choices, affect
the distribution of wages and wealth?
Age compositions of industries and occupations suggest that younger workers are more flexible in allocating toward industries with rapid wage growh.
This can be explained in a life cycle model with fixed cost of reallocating labor, which in turn generates Kuznets curves when trends in wage growth different
between two industries.
Aging and Asset Prices in the Long Run
with Alan M. Taylor
How has the age structure of a population affected returns on safe and risky assets in long run historical data?