Current Research

Monopolistic Competition and Stock Market Valuation over the Business Cycle

Abstract: The standard real business cycle (RBC) model with perfect competition implies that stock market valuations are closely tied to the capital stock. As such, the model has a hard time generating significant volatility in the stock market since the capital stock does not fluctuate too much over the business cycle. With monopolistic competition in the goods market, the stock market value does not only reflect the value of capital owned by corporations, but also the present value of pure economic profits that corporations will realize due to their market power. Additional volatility in the stock market can be generated by shocks that affect this present value of economic profits. I augment the RBC model with monopolistic competition and analyze the implications of this on the valuation of the stock market and its volatility. I consider the effects of aggregate productivity shocks, government expenditure shocks and mark-up shocks on market values and other macroeconomic aggregates. With reasonable parameters that replicate volatility of macroeconomic aggregates fairly well, the model can generate only a very small portion of the volatility in equity values.

The Case Against Constant Relative Risk Aversion and a Suggested Alternative (with Geoffrey Woglom)

Abstract: This paper reviews the paradoxes and implausible, strong results that follow from the assumption that preferences exhibit constant relative risk aversion. We then propose an alternative where preferences exhibit constant absolute risk aversion in relative wealth, where relative wealth is defined as wealth relative to a habit level of consumption. We show how these preferences are consistent with the empirical evidence on risk aversion, eliminate the implausible results, and can resolve the risk-free, equity premium asset pricing puzzles.

Land and Equity Valuation in Japan 1980-2002

Abstract: This paper studies the Japanese experience in the 1980's during which land and corporate market values significantly increased, which was followed by a sharp decline of both in the 90's. I use a growth model to determine how much of these asset price movements can be accounted for by the observed changes in fundamentals of the Japanese economy; in particular changes in productivity growth and government policy regarding land taxation. In the model, corporations issue land-collateralized debt to reduce their tax liabilities and the government follows a land tax policy that is countercyclical to land prices. These features substantially magnify the effect of small shocks by reducing the required return on land. With the model calibrated to Japanese data, I find that the observed changes in fundamentals can largely account for the movements in land values and partially for corporate market values, but only if these changes were expected to be highly persistent.

Oil Crisis, Energy-Saving Technological Change and the Stock Market Crash of 1973-74 (with Adrian Peralta-Alva)

Abstract: The market value of U.S. corporations was nearly halved following the oil crisis of October 1973. Real energy prices more than doubled by the end of the decade, increasing energy costs and spurring innovation in energy-saving technologies by corporations. This paper uses a neo-classical growth model to quantify the impact of the increase in energy prices on the market value of U.S. corporations. In the model, corporations adopt energy-saving technologies as a response to the energy price shock and the price of installed capital falls due to investment irreversibility. The model calibrated to match the subsequent decline in energy consumption in the U.S. generates a 24% decline in market valuation; accounting for nearly half of what is observed in the data.

Real Business Cycles and the Markov-Switch Model with Unobserved Components

Abstract: This paper incorporates the Markov-switch model of Hamilton (1989) into a real business cycle model. The growth of total factor productivity is modeled as the sum of two unobserved components: a transient component and a persistent component which switches between an "expansionary" and a "contractionary" regime. Agents observe only the total of these two components, and infer the likelihood of the current regime by Bayes' rule. I estimate the parameters of the model with maximum likelihood using US data. I then compute the likelihood of the expansionary vs. the contractionary regime and compare it to the business cycle turning points identified by the NBER. I also compare model's predictions on output and other aggregates with actual data. The model is largely consistent with US business cycle facts, and it offers an objective way to date business cycles. The model may be especially useful to analyze business cycles of countries where average growth rates have tended to fluctuate between decades.