Canonical Higher-Order Kernels for Density Derivative Estimation

In this note we present r th order kernel density derivative estimators using canonical higher-order kernels. These canonical rescalings uncouple the choice of kernel and scale factor. This approach is useful for selection of the order of the kernel in a data-driven procedure as well as for visual comparison of kernel estimates.Derivative Estimation, AMISE

Normal Reference Bandwidths for the General Order, Multivariate Kernel Density Derivative Estimator

This note derives the general form of the approximate mean integrated squared error for the q-variate, th-order kernel density r th derivative estimator. This formula allows for normal reference rule-of-thumb bandwidths to be derived. We give tables for some of the most common cases in the literature.Derivative Estimation, Smoothing, AMISE

Imposing Economic Constraints in Nonparametric Regression: Survey, Implementation and Extension

Economic conditions such as convexity, homogeneity, homotheticity, and monotonicity are all important assumptions or consequences of assumptions of economic functionals to be estimated. Recent research has seen a renewed interest in imposing constraints in nonparametric regression. We survey the available methods in the literature, discuss the challenges that present themselves when empirically implementing these methods and extend an existing method to handle general nonlinear constraints. A heuristic discussion on the empirical implementation for methods that use sequential quadratic programming is provided for the reader and simulated and empirical evidence on the distinction between constrained and unconstrained nonparametric regression surfaces is covered.identification, concavity, Hessian, constraint weighted bootstrapping, earnings function

Are any growth theories linear? Why we should care about what the evidence tells us

Recent research on macroeconomic growth has been focused on resolving several key issues, two of which, specification uncertainty of the growth process and variable uncertainty, have received much attention in the recent literature. The standard procedure has been to assume a linear growth process and then to proceed with investigating the relevant variables that determine growth across countries. However, a more appropriate approach would be to recognize that a misspecified model may lead one to conclude that a variable is relevant when in fact it is not. This paper takes a step in this direction by considering conditional variable uncertainty with full blown specification uncertainty. We use recently developed nonparametric model selection techniques to deal with nonlinearities and competing growth theories. We show how one can interpret our results and use them to motivate more intriguing specifications within the traditional studies that use Bayesian Model Averaging or other model selection criteria. We find that the inclusion of nonlinearities is necessary for determining the empirically relevant variables that dictate growth and that nonlinearities are especially important in uncovering key mechanism of the growth process.Growth Nonlinearities, Irrelevant Variables, Least Squares Cross Validation, Bayesian Model Averaging, Parameter Heterogeneity

Working Class Judges

In recent years, a steady chorus of dignitaries has decried the low pay of federal judges and suggested that the federal judiciary is on the brink of losing its best and its brightest. The persistent nature of these claims should give us pause. Scott Baker\u27s recent study empirically evaluates these claims by examining the relationship between judicial salaries and the work habits and voting patterns of federal appellate judges. If large pay disparities are indeed eroding the quality of the federal bench, Baker theorizes this likely results in more ideological voting, fewer dissents, longer delays in issuing opinions, and a self-selection of judges who are intent on maximizing their influence within the federal judiciary. To test these hypotheses, Baker undertook the formidable task of assembling the requisite datasets, which he then posted on the Internet for other researchers to use. Along with the ingenuity of his research design, we applaud Baker\u27s industry and transparency. Thanks to his efforts, there is now an empirical literature surrounding the debate over federal judicial pay. At the end of his inquiry, Baker concludes that higher judicial salaries would have virtually no effect on the performance of federal appellate judges. The purpose of this Reply is to qualify Baker\u27s interpretation of his results, at least with regard to judges located in the Top Five legal markets of New York, Chicago, Los Angeles, San Francisco, and Washington, D.C. In his original analysis, Baker relies upon the average law firm partnership compensation, adjusted for years in practice and region, to estimate the forgone income - and hence opportunity costs - of each federal judge. Baker explicitly anticipated the possibility that this variable would understate the opportunity cost in large legal markets; thus, he included a Top Five variable plus an interaction term, which captures the effect of forgone earnings when a judge is located in one of the nation\u27s five largest legal markets. Baker\u27s discussion, however, does not formally address the significance of the interaction term, which requires some additional steps to properly interpret. Based on our reanalysis of Baker\u27s specifications, it appears that judges in the largest legal markets often behave differently than their smaller market counterparts. Specifically, the lower judicial salaries in Top Five markets strongly correlate with behavior Baker characterizes as ideological or influence-motivated. Conversely, while lower judicial salaries in small markets correlate with longer delays in issuing opinions, the exact opposite effect describes the behavior of judges in Top Five metropolitan areas. Our brief Reply proceeds as follows. Part I provides our reanalysis of Baker\u27s data. Part II establishes an additional comparative context that allows us to speculate why Top Five legal markets may foster a more intense tradeoff of influence versus remuneration. Indeed, as we note, the real or perceived financial tradeoffs are so enormous - and conspicuous - in Top Five markets that federal judges may feel they have been lumped together with a large, faceless working class. We conclude by suggesting that the debate over judicial salaries is rooted in the more general problem of greater income disparity within the American legal profession

Working Class Judges

In recent years, a steady chorus of dignitaries has decried the low pay of federal judges and suggested that the federal judiciary is on the brink of losing its best and its brightest. The persistent nature of these claims should give us pause. Scott Baker\u27s recent study empirically evaluates these claims by examining the relationship between judicial salaries and the work habits and voting patterns of federal appellate judges. If large pay disparities are indeed eroding the quality of the federal bench, Baker theorizes this likely results in more ideological voting, fewer dissents, longer delays in issuing opinions, and a self-selection of judges who are intent on maximizing their influence within the federal judiciary. To test these hypotheses, Baker undertook the formidable task of assembling the requisite datasets, which he then posted on the Internet for other researchers to use. Along with the ingenuity of his research design, we applaud Baker\u27s industry and transparency. Thanks to his efforts, there is now an empirical literature surrounding the debate over federal judicial pay. At the end of his inquiry, Baker concludes that higher judicial salaries would have virtually no effect on the performance of federal appellate judges. The purpose of this Reply is to qualify Baker\u27s interpretation of his results, at least with regard to judges located in the Top Five legal markets of New York, Chicago, Los Angeles, San Francisco, and Washington, D.C. In his original analysis, Baker relies upon the average law firm partnership compensation, adjusted for years in practice and region, to estimate the forgone income - and hence opportunity costs - of each federal judge. Baker explicitly anticipated the possibility that this variable would understate the opportunity cost in large legal markets; thus, he included a Top Five variable plus an interaction term, which captures the effect of forgone earnings when a judge is located in one of the nation\u27s five largest legal markets. Baker\u27s discussion, however, does not formally address the significance of the interaction term, which requires some additional steps to properly interpret. Based on our reanalysis of Baker\u27s specifications, it appears that judges in the largest legal markets often behave differently than their smaller market counterparts. Specifically, the lower judicial salaries in Top Five markets strongly correlate with behavior Baker characterizes as ideological or influence-motivated. Conversely, while lower judicial salaries in small markets correlate with longer delays in issuing opinions, the exact opposite effect describes the behavior of judges in Top Five metropolitan areas. Our brief Reply proceeds as follows. Part I provides our reanalysis of Baker\u27s data. Part II establishes an additional comparative context that allows us to speculate why Top Five legal markets may foster a more intense tradeoff of influence versus remuneration. Indeed, as we note, the real or perceived financial tradeoffs are so enormous - and conspicuous - in Top Five markets that federal judges may feel they have been lumped together with a large, faceless working class. We conclude by suggesting that the debate over judicial salaries is rooted in the more general problem of greater income disparity within the American legal profession

Determining the culturability of the rumen bacterial microbiome

The goal of the Hungate1000 project is to generate a reference set of rumen microbial genome sequences. Toward this goal we have carried out a meta-analysis using information from culture collections, scientific literature, and the NCBI and RDP databases and linked this with a comparative study of several rumen 16S rRNA gene-based surveys. In this way we have attempted to capture a snapshot of rumen bacterial diversity to examine the culturable fraction of the rumen bacterial microbiome. Our analyses have revealed that for cultured rumen bacteria, there are many genera without a reference genome sequence. Our examination of culture-independent studies highlights that there are few novel but many uncultured taxa within the rumen bacterial microbiome. Taken together these results have allowed us to compile a list of cultured rumen isolates that are representative of abundant, novel and core bacterial species in the rumen. In addition, we have identified taxa, particularly within the phylum Bacteroidetes, where further cultivation efforts are clearly required. This information is being used to guide the isolation efforts and selection of bacteria from the rumen microbiota for sequencing through the Hungate1000

Utilizing pHluorin-Tagged Receptors to Monitor Subcellular Localization and Trafficking

Understanding membrane protein trafficking, assembly, and expression requires an approach that differentiates between those residing in intracellular organelles and those localized on the plasma membrane. Traditional fluorescence-based measurements lack the capability to distinguish membrane proteins residing in different organelles. Cutting edge methodologies transcend traditional methods by coupling pH-sensitive fluorophores with total internal reflection fluorescence microscopy (TIRFM). TIRF illumination excites the sample up to approximately 150 nm from the glass-sample interface, thus decreasing background, increasing the signal to noise ratio, and enhancing resolution. The excitation volume in TIRFM encompasses the plasma membrane and nearby organelles such as the peripheral ER. Superecliptic pHluorin (SEP) is a pH sensitive version of GFP. Genetically encoding SEP into the extracellular domain of a membrane protein of interest positions the fluorophore on the luminal side of the ER and in the extracellular region of the cell. SEP is fluorescent when the pH is greater than 6, but remains in an off state at lower pH values. Therefore, receptors tagged with SEP fluoresce when residing in the endoplasmic reticulum (ER) or upon insertion in the plasma membrane (PM) but not when confined to a trafficking vesicle or other organelles such as the Golgi. The extracellular pH can be adjusted to dictate the fluorescence of receptors on the plasma membrane. The difference in fluorescence between TIRF images at neutral and acidic extracellular pH for the same cell corresponds to a relative number of receptors on the plasma membrane. This allows a simultaneous measurement of intracellular and plasma membrane resident receptors. Single vesicle insertion events can also be measured when the extracellular pH is neutral, corresponding to a low pH trafficking vesicle fusing with the plasma membrane and transitioning into a fluorescent state. This versatile technique can be exploited to study localization, expression, and trafficking of membrane proteins

Tradeoffs Between Inflation and Output-Gap Variances in an Optimizing-Agent Model

We demonstrate the existence of a monetary policy tradeoff between price-inflation variability and output-gap variability in an optimizing-agent model with staggered nominal wage and price contracts. This variance tradeoff is absent only in the special case in which prices are sticky and wages are perfectly flexible. When the model is calibrated to exhibit an empirically reasonable degreee of nominal wage inertia, strict inflation targeting induces substantial output-gap volatility.monetary policy tradeoff; price-inflation variability; output-gap variability;

Pharmacological chaperoning of nAChRs: A therapeutic target for Parkinson's disease

Chronic exposure to nicotine results in an upregulation of neuronal nicotinic acetylcholine receptors (nAChRs) at the cellular plasma membrane. nAChR upregulation occurs via nicotine-mediated pharmacological receptor chaperoning and is thought to contribute to the addictive properties of tobacco as well as relapse following smoking cessation. At the subcellular level, pharmacological chaperoning by nicotine and nicotinic ligands causes profound changes in the structure and function of the endoplasmic reticulum (ER), ER exit sites, the Golgi apparatus and secretory vesicles of cells. Chaperoning-induced changes in cell physiology exert an overall inhibitory effect on the ER stress/unfolded protein response. Cell autonomous factors such as the repertoire of nAChR subtypes expressed by neurons and the pharmacological properties of nicotinic ligands (full or partial agonist versus competitive antagonist) govern the efficiency of receptor chaperoning and upregulation. Together, these findings are beginning to pave the way for developing pharmacological chaperones to treat Parkinson's disease and nicotine addiction