A match made in Maastricht: The average treatment effect of the EMU on trade

Open Economies Review

Why do estimates of the European Monetary Union (EMU) effect on trade vary so greatly? Rose (2017) shows that the largest factor determining the size of EMU trade estimates is the choice of sample, with studies using only European or rich countries finding smaller impacts than those using more complete trade datasets. I push this question one step further, asking instead: what is the appropriate comparison group with which to study the euro's trade impact? Using a first stage estimation of selection into the EMU and a robust propensity score weighting estimator, I extend the work of Millimet and Tchernis (2009) to a larger dataset of countries and years, showing that gravity estimates of the euro effect on trade are smaller when sample truncation and weighting brings the differences in observable characteristics between EMU and non- EMU pairs close to zero. Utilizing a Poisson pseudo-maximum likelihood approach, I find that estimates using this more robust estimator reflect the same pattern, but with significantly less initial upward bias. My work suggests that policy analysis in trade should be more careful to consider the comparability of "treated" and "control" observations, and more readily utilize propensity score methods as a data driven approach to rebalancing samples when differences across these groups are large.

Many unions, one estimate? Disaggregating the currency union effect on trade

Emerging Markets Finance and Trade

A large literature estimates the impact of currency unions on trade. Often ignored in these estimates are the dramatic differences in the characteristics of countries adopting common currencies, hidden by aggregation into a single currency union effect. I show that currency unions have substantial differences in their observable characteristics, relative to non-unions, making them a poor comparison group for estimation of policy treatment. Further, these differences are heterogeneous across individual currency unions, making one aggregate estimate likely inappropriate. Using inverse propensity score methods, I find that adjusting these gravity equation estimates to account these differences, both via weighting and via sample adjustment, meaningfully impacts the estimated policy effects. I find a wide range of currency union effects across individual, disaggregated, currency unions. My results suggest that future work on currency unions, and other macroeconomic policies, should be careful to check for such underlying heterogeneity when estimating policy effects.

Growing older and growing apart? Population age structure and trade

Journal of Economic Studies

This paper explores the empirical relationship between population age structure and bilateral trade. I include age structure in both log and PPML formulations of the gravity equation of trade. I study relative age effects, using differences in the demographic structure of each country-pair. I find that a relatively larger share of population in working age increases bilateral exports. This is robust to various estimation models, as well as to changes in the method of specifying the demographic controls. Old-age shares have a negative, but less robustly estimated impact on trade. Estimating instead the balance of trade between trading partners produces similar results, with positive effects of age structure peaking later in working life. Global populations are poised to undergo a massive transition. Trade a crucial way that the demographic deficits of one country may be offset by the dividends of another as comparative advantages shift along with the size and strength of their underlying workforce. My work is among the first to quantify the effect of relative age structure between two countries and their bilateral trade flows. Focusing for the on aggregate flows, relative age shares, and PPML estimates of the trade relationship, this paper provides the most comprehensive picture to date on how age structure affects trade.

Population age structure and secular stagnation: Evidence from long run data

Journal of the Economics of Ageing

A large literature has reopened the secular stagnation hypothesis, first proposed near the end of the great depression as a warning for anemic growth resulting from long run trends in population aging. In this paper, I explore the relationship between population age structure and growth in: investment, consumption and output, in a long run panel of advanced economies. The evidence is largely consistent with proposed channels for secular stagnation. Investment growth, in its level and as a fraction of GDP, appears much stronger in young populations, while facing demographic headwinds in older economies. Consumption and output growth are positively associated with late career workers, with a negative relationship coming from both young and old dependents. Consistent with the recent secular stagnation literature, interest rate channels appear to have strong interactions with population age structures. I find that for investment and output growth, estimated impacts of age-structure are more pronounced in low interest rate environments, with high rates mitigating some of their effect.


The age for austerity? Population age structure and fiscal consolidation multipliers

Journal of Macroeconomics

Advanced economies face two important trends: population aging and rising debt. In the coming years, it will be critical to understand how policies undertaken by governments interact with their changing age structures. In a panel of advanced economies, I show that fiscal deficit consolidation multipliers are highly sensitive to changes in population age. The demographic transmission of fiscal shocks differs between spending cuts and tax hikes, with important variation within working age and across dependent groups. Tax increases lead to weaker output response in relatively young economies, strengthening as population weights move to middle age, and falling again with large shares of retirees. Output response to spending, on the other hand, shows little change with demographics. The transmission of both policies to fiscal deficits suggests significant age dependence, with important impacts on multipliers when constructed as the ratio of cumulative output and deficit effects. Projecting forward, my estimates expect smaller multipliers as the baby boomer cohort fully retires, with demographics accommodating both tax and spending consolidations in terms of stronger deficit improvements, with tax policy displaying weaker output response.

Okay boomer... Excess money growth, inflation, and population aging

Macroeconomic Dynamics

What determines the strength of the relationship between money growth and inflation? A large literature suggests that it has weakened since the 1980s, without a definitive explanation of the cause. I explore how population age structure explains changes in the pass through of money growth rates to inflation. I show that the quantity theory of money holds over long time horizons, with sizable estimates of the impact of money growth on inflation in the short to medium term. Various measures of population age structure have significant impact on the strength of this relationship. These demographics account for an increase in the transmission of money growth to prices in the 1970s and a weakening throughout the great moderation. The baby boomer cohort, now in the age groups around retirement, may exert upward pressure on this money transmission to prices at present, with ambiguous implications in the future as low fertility and rising longevity persist.

Working Papers:

The Savings Glut of the Old: Population Aging, the Risk Premium, and the Murder-Suicide of the Rentier

with Alan M. Taylor

Under Review

Population aging has been linked to a global savings glut and a decline in safe real interest rates. Conversely, risky real returns have not fallen as much, if at all, with equity risk premia on the rise. An existing literature can explain changes in safe rates using demographics. We go further to account for divergent returns on different assets as well as the underlying surge in the wealth-income ratio and its asset composition. Empirical evidence from historical panel data shows that demographic shifts are correlated with asset returns and risk premia. We build a heterogeneous agent life-cycle model with two assets (a safe bond and equity) and with aggregate risk. Aging demographics can help to simultaneously explain three key trends: the rising wealth-income ratio, the falling risk free rate, and an increasing risk premium. The shifts exert less pressure on risky returns as high-wealth elderly reallocate away from equities: aging makes retirement saving a "crowded trade" but more so for bonds. Projecting our model to 2050, aging pushes the safe rate below zero, but the risk premium remains elevated, as post-boomer demographics push asset returns to unprecedented and persistently low levels.

An Aging Dynamo: Demographic Change and the Decline of Entrepreneurial Activity in the United States

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.