Persistent mispricing in a recently opened emerging index futures market: Arbitrageurs invited

The purpose of this study is to analyze the persistent, typically negative, mispricing in the new stock index futures market in Turkey, which has amounted to 5–8%, several multiples of transaction costs. The observations suggest that it is the outcome of a combination of practical difficulties of shorting in the spot stock market, behavioral effects, and insufficient arbitrage. The magnitude of the mispricing and the absence of arbitrage make behavioral effects more visible and provide a unique opportunity to examine extant behavioral hypotheses. Results confirm effects such as disposition and/or conservatism with the mispricing negatively related to past returns, but unrelated to future returns. Finally, an orderly weakening of the negative relation to past returns and behavioral effects is observed, suggesting that such effects will diminish as the market matures. © 2009 Wiley Periodicals, Inc. Jrl Fut Mark 29:218–243, 2009     

On adding over-identifying instrumental variables to simultaneous equations

Reducing the number of over-identifying instruments, or adding them to a structural equation, increases estimation dispersion. Added instruments should be insignificant under correct specification, with parameter estimates nearly unaffected, confirmed by Monte Carlo. Selecting instruments does not affect these results.     

Accommodating spatial correlation across choice alternatives in discrete choice models: an application to modeling residential location choice behavior

This paper presents a modeling methodology capable of accounting for spatial correlation across choice alternatives in discrete choice modeling applications. Many location choice (e.g., residential location, workplace location, destination location) modeling contexts involve choice sets where alternatives are spatially correlated with one another due to unobserved factors. In the presence of such spatial correlation, traditional discrete choice modeling methods that are often based on the assumption of independence among choice alternatives are not appropriate. In this paper, a Generalized Spatially Correlated Logit (GSCL) model that allows one to represent the degree of spatial correlation as a function of a multi-dimensional vector of attributes characterizing each pair of location choice alternatives is formulated and presented. The formulation of the GSCL model allows one to accommodate alternative correlation mechanisms rather than pre-imposing restrictive correlation assumptions on the location choice alternatives. The model is applied to the analysis of residential location choice behavior using a sample of households drawn from the 2000 San Francisco Bay Area Travel Survey (BATS) data set. Model estimation results obtained from the GSCL are compared against those obtained using the standard multinomial logit (MNL) model and the spatially correlated logit (SCL) model where only correlations across neighboring (or adjacent) alternatives are accommodated. Model findings suggest that there is significant spatial correlation across alternatives that do not share a common boundary, and that the GSCL offers the ability to more accurately capture spatial location choice behavior.