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Ziemowit Bednarek Ph.D., Business Administration, Finance (Candidate) Expected graduation: 2010
Email: bednarek@haas.berkeley.edu
Address: 545 Student Services Building Haas School of Business University of California Berkeley, CA 94720
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Curriculum Vitae: PDF
Research interests: Asset pricing, Macroeconomics, Productivity measurement
Publications and working papers:
"The Technology Gap and Consumption Predictability", 2009 (job market paper)
This paper finds a new consumption growth predictor linked to macroeconomic
fundamentals: the technology gap, the difference in
productivity between new and existing capital. I construct a representative firm
business cycle model, in which the technology
gap generates specific patterns of short- and long-run consumption growth and
consumption growth volatility. Intuitively, a high
technology gap acts as an economic shock that lowers consumption in the short
term, but increases consumption in the long term due to
a
higher future productivity level. I use quality-adjusted price indexes of
durable investment goods to create a proxy for the
technology gap. Consistent with the model, I find empirical evidence that a high
technology gap predicts: (i) economic troughs in the
short run, (ii) strong consumption growth at longer horizons, (iii) high
consumption growth volatility, and (iv) high risk-free rate.
The technology gap is thus a powerful consumption growth predictor with a strong
economic foundation.
"Long-run Consumption Risk and Expected Returns", 2007
This paper tests the existing durable consumption-based asset pricing model of
Yogo (2006). Consumption risk is measured by the
covariance between asset returns and future durable consumption growth, rather
than contemporaneous growth, as in the original
model. I present empirical evidence that excess returns on Fama-French
portfolios are correlated more with future than
contemporaneous durable consumption growth. Because of that, the estimate of
risk aversion decreases from over 200 in the original
model to below 10 in my version of the model. I also find that the altered
consumption risk measure increases the explanatory power of the model.
I approximate the original model to estimate it in the simple OLS framework.
Cross-sectional R2
is highest when the consumption growth is
sampled over six to eight quarters ahead. This result is robust to different
sets of test assets.
"Equity Volatility and Credit Yield Spreads", 2006
"Venture Capital Distributions and Stock Returns", 2006
"Closed Credit Portfolio Migration Model", Warsaw School of Economics Research Journal, 35:29-43, 2003