We introduce nonnested hypotheses tests using indirect, simulation-based estimation procedures. We propose different test statistics and carefully examine the corresponding implicit mi hypotheses. A notion of indirect encompassing comes up naturally, which may be compared to the usual encompassing conditions. Then we show how these methods extend standard specification and overidentification tests.
This paper develops the statistical theory for testing and estimating multiple change points in regression models. The rate of convergence and limiting distribution for the estimated parameters are obtained. Several test statistics are proposed to determine the existence as well as the number of change points. A partial structural change model is considered. The authors study both fixed and shrinking magnitudes of shifts. In addition, the models allow for serially correlated disturbances (mixingales). An estimation strategy for which the location of the breaks need not be simultaneously determined is discussed. Instead, the authors' method successively estimates each break point.
Aaron S. Edlin, Mario Ephemerella, Walter P. Keller, Is Perfect Price Discrimination Really Efficient?: Welfare and Existence in General Equilibrium, Econometrica, Vol. 66, No. 4 (Jul., 1998), pp. 897-922
This paper attemps to identify, in a framework deliberately stripped of unnecessary technical- ities, some of the basic reasons why adaptive learning may or may not lead to stability and convergence to self-fulfilling expectations in large socioeconomic systems where no agent, or collection of agents, can act to manipulate macroeconomic outcomes. It is shown that if agents are somewhat uncertain about the local stability of the system, and are accordingly ready to extrapolate a large range of regularities (trends) that may show up in past small deviations from equilibrium, including divergent ones, the learning dynamics is locally divergent. On the other hand, if agents are fairly sure of the local stability of the system, and extrapolate only convergent trends out of small past deviations from equilibrium, one may get local stability. This “uncertainty principle” does show up in a wide variety of contexts: smooth or discontin- uous, finite or infinite memory learning rules, error learning, recursive least squares, Bayesian learning.
Issuers of initial public offerings (IPOs) can report earnings in excess of cash flows by taking positive accruals. This paper provides evidence that issuers with unusually high accruals in the IPO year experience poor stock return performance in the three years thereafter. IPO issuers in the most “aggressive” quartile of earnings managers have a three‐year aftermarket stock return of approximately 20 percent less than IPO issuers in the most “conservative” quartile. They also issue about 20 percent fewer seasoned equity offerings. These differences are statistically and economically significant in a variety of specifications.
ABSTRACT We propose a theory of securities market under‐ and overreactions based on two well‐known psychological biases: investor overconfidence about the precision of private information; and biased self‐attribution, which causes asymmetric shifts in investors' confidence as a function of their investment outcomes. We show that overconfidence implies negative long‐lag autocorrelations, excess volatility, and, when managerial actions are correlated with stock mispricing, public‐event‐based return predictability. Biased self‐attribution adds positive short‐lag autocorrelations (“momentum”), short‐run earnings “drift,” but negative correlation between future returns and long‐term past stock market and accounting performance. The theory also offers several untested implications and implications for corporate financial policy.