This dissertation presents three empirical studies on topics in labor market and globalcommodity prices. The first chapter analyzes how consumption, spending and labor market
decisions vary across the life-cycle, and their implications for the aggregate economy. The
second chapter discovers the dynamic adjustments of 49 world commodity prices in response to
innovations in the nominal and real shocks, and the third chapter reveals how commodity prices
are affected by information from the news in high-frequency trading.
The first chapter studies the effect of aging on service consumption quantity and pricein the United States. In particular, I ask, do older households consume more service goods?
Can aging explain the rise of service price? I investigate the impact of age profile on service consumption and service price in the U.S. using household survey data and metropolitan statistical
areas (MSAs) level variations, respectively. The results show that after controlling for household
income, as people age, they consume progressively more health insurance and medical services
and less food away from home. Furthermore, there is a positive correlation between service price
and old-age dependency ratio1 in the long run across MSAs. I then build a two-period two-sector
OLG model with an education entry cost to explain these results. In this model, age affects
service price through two channels: 1) on the demand side, labor markets with older populations
tend to demand more services; 2) on the supply side, the education friction would cause worker
mobility from the service sector to the manufacturing sector, which further increases the service
price.
The second chapter is a group project with Professor Hyeongwoo Kim. We studydynamic adjustments of 49 world commodity prices in response to innovations in the nominal
exchange rate and the world real GDP. After we estimate the dynamic elasticity of the prices
with respect to these shocks, we obtain the kernel density of our estimates to establish stylized
facts on the adjustment process of the commodity price toward a new equilibrium path. Our
empirical findings imply, on average, that the law of one price holds in the long-run, whereas the
substantial degree of short-run price rigidity was observed in response to the nominal exchange
rate shock. The real GDP shock tends to generate substantial price
fluctuations in the short-run
because adjustments of the supply can be limited, but have much weaker effects in the long-
run as the supply eventually counterbalances the increase in the demand. Overall, we report
persistent long-lasting effects of the nominal exchange rate shock on commodity prices relative
to those of the real GDP shock.
The third chapter is a group project with Yifei Sheng and Zijing Zhu. To uncover thenews impact on the price of WTI crude oil futures, the third chapter applies supervised and
unsupervised machine learning algorithms to conduct news sentiment and topic analysis. With
the assumption that the crude oil futures market is efficient enough to respond quickly to new
information, this chapter obtains high-frequency prices and news from the Bloomberg terminal.
Using results from logistic regression and K-means clustering, this chapter defines the positive
score and topic for each news article as inputs for the final logistic regression. The regression
results show that the "World Crude Oil" news is more positively correlated with price increase
than other topics. Moreover, the "WTI Crude Oil" news has the highest correlation with the
price increase as the positive score increases.