Neuroeconomics: Why Economics Needs Brains

Neuroeconomics uses knowledge about brain mechanisms to inform economic theory. It opens up the “black box” of the brain, much as organizational economics opened up the theory of the firm. Neuroscientists use many tools—including brain imaging, behavior of patients with brain damage, animal behavior and recording single neuron activity. The key insight for economics is that the brain is composed of multiple systems which interact. Controlled systems (“executive function”) interrupt automatic ones. Brain evidence complicates standard assumptions about basic preference, to include homeostasis and other kinds of state‐dependence, and shows emotional activation in ambiguous choice and strategic interaction.     

DYNAMIC ASSET ALLOCATION AND CONSUMPTION CHOICE IN INCOMPLETE MARKETS*

We study the optimal investment and consumption problem of a CRRA investor when the drift and volatility of the stock are driven by a correlated factor. The myopic and non‐myopic components of the optimal portfolio process are characterised in terms of the market price of traded and non‐traded risk of the minimax martingale measure. We find that the optimal policies depend crucially on the nature of the agent, aggressive versus conservative, and the market incompleteness, improving versus deteriorating investment opportunities. Furthermore, we show that the original problem cannot be decomposed into a pure consumption and a pure terminal wealth problem, unless the market is complete.     

The price adjustment and lead-lag relations between stock returns: microstructure evidence from the Taiwan stock market

This paper investigates the price adjustment and lead-lag relations between returns on five size-based portfolios in the Taiwan stock market. It finds evidence that the price adjustment of small-stock portfolios is not slower than that of large-stock portfolios. Additionally, limited evidence supports a positive leading role of large-stock portfolio returns over small-stock portfolio returns. These two findings are substantially different from the results of previous research on developed markets.     

Do interventions in foreign exchange markets modify investors' expectations? The experience of Japan between 1992 and 2004

The purpose of this paper is to analyze the impact of the Bank of Japan's official interventions on the JPY/USD parity during the period 1992–2004. The novelty of our approach is to combine two recent advances of the empirical literature on foreign exchange interventions: (i) drawing on over-the-counter option prices to characterize more precisely the distribution of market expectations; (ii) redefining interventions in terms of events as they tend to come in clusters. Moreover, in order to deal with the features of the data (small sample size, non-standard distribution), we use bootstrap tests.We show that interventions have a significant impact on the mean expectation (the forward rate). The results are more ambiguous for variance. Additionally, we find that the effect of interventions on skewness is significant, robust to different definitions of skewness, and consistent with the direction of interventions. On the contrary, our results clearly show that kurtosis is not affected by interventions. We finally show that: (i) coordination increases effectiveness of interventions; (ii) results are not altered when controlling for other economic and political news.     

Understanding the Economic Factors Influencing Farm Policy Preferences

A survey conducted in Mississippi, Texas, Indiana, and Nebraska elicited producers' preferences for various farm policy changes. This permitted examination of the diversity of preferences that single-state studies have not allowed. Five policy choices, including deficiency payments, loan programs, crop insurance, export programs, and disaster payments were examined. Logit model results predicting producer preferences for each of the five dichotomous policy choices are reported. Explanatory variables based on expected utility theory such as risk aversion, price and yield variability, and price–yield correlation are significant in various models.