Identification and Estimation of Triangular Simultaneous Equations Models Without Additivity

This paper investigates identification and inference in a nonparametric structural model with instrumental variables and non-additive errors. We allow for non-additive errors because the unobserved heterogeneity in marginal returns that often motivates concerns about endogeneity of choices requires objective functions that are non-additive in observed and unobserved components. We formulate several independence and monotonicity conditions that are sufficient for identification of a number of objects of interest, including the average conditional response, the average structural function, as well as the full structural response function. For inference we propose a two-step series estimator. The first step consists of estimating the conditional distribution of the endogenous regressor given the instrument. In the second step the estimated conditional distribution function is used as a regressor in a nonlinear control function approach. We establish rates of convergence, asymptotic normality, and give a consistent asymptotic variance estimator.

Feedback control of unstable cellular solidification fronts

We present a numerical and experimental study of feedback control of unstable cellular patterns in directional solidification (DS). The sample, a dilute binary alloy, solidifies in a 2D geometry under a control scheme which applies local heating close to the cell tips which protrude ahead of the other. For the experiments, we use a real-time image processing algorithm to track cell tips, coupled with a movable laser spot array device, to heat locally. We show, numerically and experimentally, that spacings well below the threshold for a period-doubling instability can be stabilized. As predicted by the numerical calculations, cellular arrays become stable, and the spacing becomes uniform through feedback control which is maintained with minimal heating.Comment: 4 pages, 4 figures, 1 tabl

A New Robust and Most Powerful Test in the Presence of Local Misspeci cation

This paper proposes a new test that is consistent, achieves correct asymptotic size and is locally most powerful under local misspecification, and when any square-root-of-n-estimator of the nuisance parameters is used. The new test can be seen as an extension of the Bera and Yoon (1993) procedure that deals with non-ML estimation, while preserving its optimality properties. Similarly, the proposed test extends Neyman's (1959) C(a) test to handle locally misspecified alternatives. A Monte Carlo study investigates the finite sample performance in terms of size, power and robustness to misspecification

Rancho Seco--Decommissioning Update

The Rancho Seco Nuclear Generating Station ceased operation in June of 1989 and entered an extended period of SAFSTOR to allow funds to accumulate for dismantlement. Incremental dismantlement was begun in 1997 of steam systems and based on the successful completion of work, the Sacramento Municipal Utility District (SMUD) board of directors approved full decommissioning in July 1999. A schedule has been developed for completion of decommissioning by 2008, allowing decommissioning funds to accumulate until they are needed. Systems removal began in the Auxiliary Building in October of 1999 and in the Reactor Building in January of 2000. Systems dismantlement continues in the Reactor Building and should be completed by the end of 2003. System removal is near completion in the Auxiliary Building with removal of the final liquid waste tanks in progress. The spent fuel has been moved to dry storage in an onsite ISFSI, with completion on August 21, 2002. The spent fuel racks are currently being removed from the pool, packaged and shipped, and then the pool will be cleaned. Also in the last year the reactor coolant pumps and primary piping were removed and shipped. Characterization and planning work for the reactor vessel and internals is also in progress with various cut-up and/or disposal options being evaluated. In the year ahead the remaining systems in the Reactor Building will be removed, packaged and sent for disposal, including the pressurizer. Work will be started on embedded and underground piping and the large outdoor tanks. Building survey and decontamination will begin. RFP's for removal of the vessel and internals and the steam generators are planned to fix the cost of those components. If the costs are consistent with current estimates the work will go forward. If they are not, hardened SAFSTOR/entombment may be considered

Rancho Seco-Planning for Large Components

The Rancho Seco Nuclear Generating Station ceased operation in June of 1989 and entered an extended period of Safestor to allow funds to accumulate for dismantlement. Incremental dismantlement was begun in 1997 of steam systems and based on the successful work to date, the Sacramento Municipal Utility District (SMUD) board of directors approved full decommissioning in July 1999. A schedule has been developed for completion of decommissioning by 2008, allowing decommissioning funds to accumulate until they are needed. Systems removal began in the Auxiliary Building in October of 1999 and in the Reactor Building in January of 2000. Systems dismantlement continues in the Reactor Building and the Auxiliary Building and should be completed by mid 2003. The Spent Fuel is currently being moved to dry storage in an onsite ISFSI, with completion scheduled for late 2002. The personnel resources on site are currently assigned to support both the dry fuel project and the dismantlement of the facility. Once fuel movement is complete more resources will be provided for dismantlement. Characterization of major components other than the vessel is complete and planning for their removal is in progress with various cut-up and/or shipping options being evaluated. Planning for the vessel and internals removal is being performed. The relatively slow pace of the work allows careful evaluation of cost-effective options as they become available in the industry

Confidence Intervals for Diffusion Index Forecasts and Inference for Factor-Augmented Regressions

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/73839/1/j.1468-0262.2006.00696.x.pd