Inflation Expectations over the Life Cycle under Rational Inattention
by Jessica Schultz
Abstract
This paper explores how people track inflation over their lifetimes while facing tradeoffs between attention and certainty. It first employs a flexible modification of the Recursive Least Squares Learning approach from Malmendier and Nagel (MN) (2016) to find that households place weight on each inflation observation in a hump-shaped pattern over age when using past observations to set expectations about the future. This finding departs from MN, which models a strictly increasing weighting scheme with age. This paper then uses these findings to motivate a theory of Rational Inattention (RI) in inflation: as households age and accumulate wealth, their knowledge of the inflation rate becomes more important in their financial decisions–so they pay more attention to inflation. Consequently, as they decumulate wealth during their retirement, they have less reason to track inflation as accurately.
This paper subsequently formalizes this theory in a two-period RI model in which inflation-driven uncertainty in the interest rate between a working period and a retirement period can be reduced at a cost; this reduction in uncertainty occurs through observing an endogenously chosen signal that is correlated with the interest rate. It finds that as wealth increases before retirement, the optimal choice of signal precision increases as well. These findings help explain the hump-shaped weighting scheme for inflation observations in the empirical section, assuming changes in these weights over age are related in part to changes in household wealth. Ultimately, these findings suggest that monetary policy that focuses on long-term inflation stability or accounts for this heterogeneity may be most effective in anchoring consumer inflation expectations and increasing consumer welfare.
Professor Francesco Bianchi, Faculty Advisor
Professor Michelle Connolly, Faculty Advisor
JEL Codes: E2, E21, E31
Immigrant Workers in a Changing Labor Environment: A study on how technology is reshaping immigrant earnings
By Grace Peterson
This research determines how automation affects immigrant wages in the US and how closely this impact follows the skills-biased technical change (SBTC) hypothesis. The present study addresses this question using American Community Survey (ACS) data from 2012 to 2016 and a job automation probability index to explain technological change. This research leverages OLS regressions to evaluate real wage drivers, grouping data by year, immigration status, and education level. According to the SBTC hypothesis, high skill immigrant wages should be less negatively affected by technological change than low skill immigrant wages. Univariate analysis suggests that the SBTC hypothesis is even stronger for US = immigrants than native-borns, as high skill immigrants have a lower average probability than low skill immigrants of having their jobs automated, and the difference in effect on high versus low skilled workers is larger for immigrant than native-borns. However, multivariate analysis asserts that technological change affects low skill immigrants’ wages less than high skilled individuals’ wages, which counters the SBTC hypothesis.
Advisors: Professor Grace Kim | JEL Codes: J15, J24, J31, J61, E24
Multi-Variable Regression Analysis For the Prediction of Equity Returns Over 10 Year Periods
by Arjun Singh Jaswal
Abstract
The use of 5 variables is examined in order to forecast ex ante the total return from holding equities over 10 year periods. The 5 variables are a moving average of Campbell and Shiller’s P/E ratio, Robert B. Barsky and J. Bradford De Long’s log price predictor, a function of James Tobin’s q, the rate of change of GDP over 30 years and the rate of change of cash flow over 10 years. The significance of these variables is explained by considering them individually, simultaneously and finally under the architecture suggested by David Hirshleifer.
Professor Edward Tower, Faculty Advisor
JEL Codes: C3, E22
Assessing the Performance of Actively Managed Global Funds
by Luyuan Fan
Abstract
It has been widely debated whether managed funds outperform their index counterparts. Many scholars have carried out empirical testing for U.S. managed funds, but few have examined global funds. This study compares the total returns and risk-adjusted returns for 29 largest global funds with that of a basket of Vanguard indexes over 5 two-year periods from January 1997 to December 2006. We discover that the global funds outperform the basket of indexes before expenses. Also, the global funds outperform the indexes by an increasing amount in later periods than in earlier ones, implying accumulated experience and improved fund management skills of fund managers over time. Moreover, the average of the return differentials in favor of global funds in five periods is lower than the return differential over the entire 10-year period, indicating fund managers’ superior style-picking skills. After expenses, the indexes win on average, because most global funds have high expense ratios (of up to 2 %.) However, low cost global funds, such as the Vanguard Global Equity, make an exception.
Professor Edward Tower, Faculty Advisor
JEL Codes: E22,
The Value of Unsolicited Buy Recommendations to Investors: Can Investors Trade Profitably Based on E-mail Spam?
by Angela Nicole Aldrich
Abstract
This paper explores the possibility of trading profitably based on information contained in email spam messages advertising certain stock trades. Through careful analysis of a basket of sixteen stocks that were recommended to my advisor and myself via unsolicited email spam, I conclude that the most effective way for investors to trade these stocks is to short-sell immediately upon initial receipt of a recommendation to buy.
Professor Bjorn Eraker, Faculty Advisor
JEL Codes: E2, G11,
