REIT Stock Repurchases: Completion Rates, Long - Run Returns, and the Straddle Hypothesis

This study of real estate investment trusts (REITs) analyzes three possible explanations for the stock price reaction to a repurchase announcement and the subsequent repurchase behavior of managers under each hypothesis. Two of the hypotheses, the signaling hypothesis and the exchange option hypothesis, are established in the existing literature; the third hypothesis is a modification of the exchange option hypothesis. The exchange option hypothesis is extended to allow for additional flexibility in management decisions. This extended exchange option hypothesis is termed the ‘‘straddle’’ hypothesis because it provides management with both a call and put option. The empirical analyses show the straddle hypothesis is a more robust explanation of changes in shares outstanding in the postannouncement period than the alternative explanations.

Reducing Reparameterization Gradient Variance

Optimization with noisy gradients has become ubiquitous in statistics and machine learning. Reparameterization gradients, or gradient estimates computed via the "reparameterization trick," represent a class of noisy gradients often used in Monte Carlo variational inference (MCVI). However, when these gradient estimators are too noisy, the optimization procedure can be slow or fail to converge. One way to reduce noise is to use more samples for the gradient estimate, but this can be computationally expensive. Instead, we view the noisy gradient as a random variable, and form an inexpensive approximation of the generating procedure for the gradient sample. This approximation has high correlation with the noisy gradient by construction, making it a useful control variate for variance reduction. We demonstrate our approach on non-conjugate multi-level hierarchical models and a Bayesian neural net where we observed gradient variance reductions of multiple orders of magnitude (20-2,000x)

Valuing Catastrophic Citrus Losses

Courts are often required to estimate changes in welfare to agricultural operations from catastrophic events. For example, courts must assign damages in lawsuits, such as with pesticide drift cases, or determine "just compensation" when the government takes private land for public use, as with the removal of dairy farms from environmentally sensitive land or destruction of canker-contaminated citrus trees. In economics, the traditional method of quantifying producer losses is estimating changes in producer welfare, but courts rarely use this method. Instead, they turn to substitute valuation methods that may not fully capture welfare changes, such as changes in land value, tree replacement value, and total revenue. This study examines various measures for valuing the back-to-back catastrophic freezes that occurred in the Florida citrus industry in the 1980s. We first use the traditional method to determine the welfare change due to a freeze (1) for a citrus grove that loses one crop and is able to return to full production the next year, and (2) the lower measure of welfare loss due to a citrus grove that loses all of its trees and is abandoned or is replanted. The lower measure is used to simulate the legal doctrine of avoidable consequences. These measures are then compared to substitute valuation measures that have been used by courts to determine welfare changes. For case 1, total revenue overestimates losses by 35.6%. For case 2, total revenue overestimates losses by 55.3%, tree replacement value underestimates losses by 93.6%, and changes in land value underestimates losses by 13.2%.citrus, perennial crops, catastrophic loss, damages, freeze, Crop Production/Industries,

Valuing Catastrophic Losses for Perennial Agricultural Crops

Courts are often required to estimate changes in welfare to agricultural operations from catastrophic events. For example, courts must assign damages in lawsuits, such as with pesticide drift cases, or determine 'just compensation' when the government takes private land for public use, as with the removal of dairy farms from environmentally sensitive land or destruction of canker-contaminated citrus trees. In economics, the traditional method of estimating changes in producer welfare is the computation of lost producer surplus, but courts rarely use this method. Instead, they turn to substitute valuation methods that may not fully capture welfare change, such as changes in land value, tree replacement value, and total revenue. This study examines various measures for valuing the back-to-back catastrophic freezes that occurred in the Florida citrus industry in the 1980s. We first use the traditional method to determine the welfare change due to a freeze (1) for a citrus grove that loses one crop and is able to return to full production the next year (simulating destruction of annual crops), and (2)the lower measure of welfare loss due to a citrus grove that loses all of its trees and is abandoned or is replanted. The lower measure is used to simulate the legal doctrine of avoidable consequences. These measures are then compared to substitute valuation measures that have been used by courts to determine welfare changes. For case 1, total revenue overestimated losses by 35.6%. For case 2, total revenue overestimates losses by 55.3%, tree replacement value underestimates losses by 93.6%, and changes in land value underestimates losses by 13.2%.citrus, perennial crops, catastrophic loss, damages, freeze, Crop Production/Industries,

Approximate Inference for Constructing Astronomical Catalogs from Images

We present a new, fully generative model for constructing astronomical catalogs from optical telescope image sets. Each pixel intensity is treated as a random variable with parameters that depend on the latent properties of stars and galaxies. These latent properties are themselves modeled as random. We compare two procedures for posterior inference. One procedure is based on Markov chain Monte Carlo (MCMC) while the other is based on variational inference (VI). The MCMC procedure excels at quantifying uncertainty, while the VI procedure is 1000 times faster. On a supercomputer, the VI procedure efficiently uses 665,000 CPU cores to construct an astronomical catalog from 50 terabytes of images in 14.6 minutes, demonstrating the scaling characteristics necessary to construct catalogs for upcoming astronomical surveys.Comment: accepted to the Annals of Applied Statistic

A Rapid, Scalable Method for the Isolation, Functional Study, and Analysis of Cell-Derived Extracellular Matrix

The extracellular matrix (ECM) is recognized as a diverse, dynamic, and complex environment that is involved in multiple cell-physiological and pathological processes. However, the isolation of ECM, from tissues or cell culture, is complicated by the insoluble and cross-linked nature of the assembled ECM and by the potential contamination of ECM extracts with cell surface and intracellular proteins. Here, we describe a method for use with cultured cells that is rapid and reliably removes cells to isolate a cell-derived ECM for downstream experimentation. Through use of this method, the isolated ECM and its components can be visualized by in situ immunofluorescence microscopy. The dynamics of specific ECM proteins can be tracked by tracing the deposition of a tagged protein using fluorescence microscopy, both before and after the removal of cells. Alternatively, the isolated ECM can be extracted for biochemical analysis, such as sodium dodecyl sulphate-polyacrylamide gel electrophoresis (SDS-PAGE) and immunoblotting. At larger scales, a full proteomics analysis of the isolated ECM by mass spectrometry can be conducted. By conducting ECM isolation under sterile conditions, sterile ECM layers can be obtained for functional or phenotypic studies with any cell of interest. The method can be applied to any adherent cell type, is relatively easy to perform, and can be linked to a wide repertoire of experimental designs