The insurance function of contracts

One of the central problems in contract law is to define the frontier between legal and illegal breaches of promises. The distinction between good and bad faith is perhaps the conceptual tool most commonly used to tell one from the other. Lawyers spend a lot of energy trying to frame better definitions of the concepts of good and bad faith based on principles of ethics or justice, but often pay much less attention to theories dealing with the incentives that can engender good faith behavior in contractual relationships. By describing the economics of what Stiglitz defined as “explicit” and “implicit” insurance, I highlight the “insurance function” hidden in any promise with basically no mathematical notation. My aim is to render the subject intelligible and useful to lawyers with little familiarity with economics.

Bounds for the probability distribution function of the linear ACD process

This paper derives both lower and upper bounds for the probability distribution function of stationary ACD(p, q) processes. For the purpose of illustration, I specialize the results to the main parent distributions in duration analysis. Simulations show that the lower bound is much tighter than the upper bound.

Non-emptiness of the alpha-core

We prove non-emptiness of the alpha-core for balanced games with non-ordered preferences, extending and generalizing in several aspects the results of Scarf (1971), Border (1984), Florenzano (1989), Yannelis (1991) and Kajii (1992). In particular we answer an open question in Kajii (1992) regarding the applicability of the non-emptiness results to models with infinite dimensional strategy spaces. We provide two models with Knightian and voting preferences for which the results of Scarf (1971) and Kajii (1992) cannot be applied while our non-emptiness result applies.

Aggregate vs disaggregate data analysis: a paradox in the estimation of money demand function of Japan under the low interest rate policy

We investigate the issue of whether there was a stable money demand function for Japan in 1990's using both aggregate and disaggregate time series data. The aggregate data appears to support the contention that there was no stable money demand function. The disaggregate data shows that there was a stable money demand function. Neither was there any indication of the presence of liquidity trapo Possible sources of discrepancy are explored and the diametrically opposite results between the aggregate and disaggregate analysis are attributed to the neglected heterogeneity among micro units. We also conduct simulation analysis to show that when heterogeneity among micro units is present. The prediction of aggregate outcomes, using aggregate data is less accurate than the prediction based on micro equations. Moreover. policy evaluation based on aggregate data can be grossly misleading.