A New Class of Indirect Estimators and Bias Correction
In this paper we define a set of indirect estimators based on moment approximations of the auxilary estimators. We provide results that describe higher order asymptotic properties of these estimators. The introduction of these is motivated by reasons of analytical and computational facilitation. ...
Read more...
Analyzing Social Experiments as Implemented: A Reexamination of the Evidence From the HighScope Perry Preschool Program
Social experiments are powerful sources of information about the effectiveness of interventions. In practice, initial randomization plans are almost always compromised. Multiple hypotheses are frequently tested. "Signicant" effects are often reported with p-values that do not account fo...
Read more...
Bootstrap LM Test for the Box CoxTobit Model
Consistency of the maximum likelihood estimators for the parameters in the standard Tobit model rely heavily on the assumption of a normally distributed error term. The Box Cox transformation presents an obvious attempt to preserve normality when the data make this questionable. This paper sets o...
Read more...
Regression for nonnegative skewed dependent variables
Several options for estimation and prediction in regressions using nonnegative skewed dependent variables are compared. Often, Poisson regression outperforms competitors, even when its assumptions are violated and the correct model is one that justifies a competitor.
Non-linear DSGE Models and The Central Difference Kalman Filter
This paper introduces a Quasi Maximum Likelihood (QML) approach based on the Cen- tral Difference Kalman Filter (CDKF) to estimate non-linear DSGE models with potentially non-Gaussian shocks. We argue that this estimator can be expected to be consistent and asymptotically normal for DSGE models s...
Read more...
Non-linear DSGE Models and The Central Difference Kalman Filter
This paper introduces a Quasi Maximum Likelihood (QML) approach based on the Cen- tral Difference Kalman Filter (CDKF) to estimate non-linear DSGE models with potentially non-Gaussian shocks. We argue that this estimator can be expected to be consistent and asymptotically normal for DSGE models s...
Read more...
Short-Term Congestion Forecasting in Wholesale Power Markets
Short-term congestion forecasting is highly important for market participants in wholesale power markets that use Locational Marginal Prices (LMPs) to manage congestion. Accurate congestion forecasting facilitates market traders in bidding and trading activities and assists market operators in sy...
Read more...
|
|
|