Estimation with many instrumental variables

Using many valid instrumental variables has the potential to improve efficiency but makes the usual inference procedures inaccurate. We give corrected standard errors, an extension of Bekker (1994) to nonnormal disturbances, that adjust for many instruments. We find that this adujstment is useful in empirical work, simulations, and in the asymptotic theory. Use of the corrected standard errors in t-ratios leads to an asymptotic approximation order that is the same when the number of instrumental variables grow as when the number of instruments is fixed. We also give a version of the Kleibergen (2002) weak instrument statistic that is robust to many instruments.

Instrumental variables estimation with flexible distribution

Instrumental variables are often associated with low estimator precision. This paper explores efficiency gains which might be achievable using moment conditions which are nonlinear in the disturbances and are based on flexible parametric families for error distributions. We show that these estimators can achieve the semiparametric efficiency bound when the true error distribution is a member of the parametric family. Monte Carlo simulations demonstrate low efficiency loss in the case of normal error distributions and potentially significant efficiency improvements in the case of thick-tailed and/or skewed error distributions.

Instrumental variables estimation with flexible distributions

Instrumental variables are often associated with low estimator precision. This paper explores efficiency gains which might be achievable using moment conditions which are nonlinear in the disturbances and are based on flexible parametric families for error distributions. We show that these estimators can achieve the semiparametric efficiency bound when the true error distribution is a member of the parametric family. Monte Carlo simulations demonstrate low efficiency loss in the case of normal error distributions and potentially significant efficiency improvements in the case of thick-tailed and/or skewed error distributions

Construct-Validity of the Engagement with Challenge Measure for Adolescents: Structural- and Criterion-Validity Evidence

For adolescents, engaging with challenge is a key developmental task, hypothesized to support development of adult-like competencies (e.g., agency and self-direction; Larson, 2000). This study aimed to assess the construct-validity (structural- and concurrent-validity) of a new self-report measure assessing adolescents’ engagement with challenge to help researchers understand how different settings and the conditions in these settings support adolescents’ development. The sample consisted of 337 adolescents in 10 FFA programs along with the adult advisors in each program. Adolescents completed a questionnaire, which included the Engagement with Challenge measure and the following criterion variables: number of contests completed, participation frequency, and leadership roles. In addition to the self-reported criterion variables, the adult advisor evaluated Engagement with Challenge for each FFA student member in that program using a single item. The findings of this study provided strong evidence for the structural-validity of the engagement with challenge construct measured by the new scale, including having passed confirmatory factor analysis configural, weak, and strong invariance tests across four grade groupings. The findings also provided further evidence of construct-validity, as Engagement with Challenge correlated in the a priori hypothesized direction and magnitude. Suggestions for analysis with the new measure and for future research are presented

Construct-Validity of the Engagement with Challenge Measure for Adolescents: Structural- and Criterion-Validity Evidence

This is the published version.For adolescents, engaging with challenge is a key developmental task, hypothesized to support development of adult-like competencies (e.g., agency and self-direction; Larson, 2000). This study aimed to assess the construct-validity (structural- and concurrent-validity) of a new self-report measure assessing adolescents’ engagement with challenge to help researchers understand how different settings and the conditions in these settings support adolescents’ development. The sample consisted of 337 adolescents in 10 FFA programs along with the adult advisors in each program. Adolescents completed a questionnaire, which included the Engagement with Challenge measure and the following criterion variables: number of contests completed, participation frequency, and leadership roles. In addition to the self-reported criterion variables, the adult advisor evaluated Engagement with Challenge for each FFA student member in that program using a single item. The findings of this study provided strong evidence for the structural-validity of the engagement with challenge construct measured by the new scale, including having passed confirmatory factor analysis configural, weak, and strong invariance tests across four grade groupings. The findings also provided further evidence of construct-validity, as Engagement with Challenge correlated in the a priori hypothesized direction and magnitude. Suggestions for analysis with the new measure and for future research are presented

Youth Program Adult Leader\u27s Directive Assistance and Autonomy Support and Development of Adolescents’ Agency Capacity

Developing a capacity for exercising agency is an important developmental task of adolescence. Many organized youth programs provide adolescents opportunities to build their capacity to exercise agency. The researchers tested hypotheses that adult youth program leader\u27s directive assistance and autonomy support would promote adolescents’ capacity for agency. They surveyed 441 high school adolescents and 11 adult advisors from 10 Future Farmers of America chapters twice over 2 years. Adolescents self‐reported on their capacity for agency and advisors reported on each adolescent\u27s capacity. Directive assistance and autonomy support correlated with the capacity for agency within both time points. Only autonomy support predicted adolescents’ capacity for agency over time. Implications of leader\u27s support for adolescents’ capacity for exercising agency are discussed

Double machine learning for treatment and causal parameters

Most modern supervised statistical/machine learning (ML) methods are explicitly designed to solve prediction problems very well. Achieving this goal does not imply that these methods automatically deliver good estimators of causal parameters. Examples of such parameters include individual regression coefficients, average treatment effects, average lifts, and demand or supply elasticities. In fact, estimators of such causal parameters obtained via naively plugging ML estimators into estimating equations for such parameters can behave very poorly. For example, the resulting estimators may formally have inferior rates of convergence with respect to the sample size n caused by regularization bias. Fortunately, this regularization bias can be removed by solving auxiliary prediction problems via ML tools. Specifically, we can form an efficient score for the target low-dimensional parameter by combining auxiliary and main ML predictions. The efficient score may then be used to build an efficient estimator of the target parameter which typically will converge at the fastest possible 1/Í n rate and be approximately unbiased and normal, allowing simple construction of valid confidence intervals for parameters of interest. The resulting method thus could be called a "double ML" method because it relies on estimating primary and auxiliary predictive models. Such double ML estimators achieve the fastest rates of convergence and exhibit robust good behavior with respect to a broader class of probability distributions than naive "single" ML estimators. In order to avoid overfitting, following [3], our construction also makes use of the K-fold sample splitting, which we call cross-fitting. The use of sample splitting allows us to use a very broad set of ML predictive methods in solving the auxiliary and main prediction problems, such as random forests, lasso, ridge, deep neural nets, boosted trees, as well as various hybrids and aggregates of these methods (e.g. a hybrid of a random forest and lasso). We illustrate the application of the general theory through application to the leading cases of estimation and inference on the main parameter in a partially linear regression model and estimation and inference on average treatment effects and average treatment effects on the treated under conditional random assignment of the treatment. These applications cover randomized control trials as a special case. We then use the methods in an empirical application which estimates the effect of 401(k) eligibility on accumulated financial assets

Effects of Perceptual and Conceptual Cues in a Response Switching Task

ABSTRACT In the directed response switching (DRS) task, participants kept two conflicting responses active, choosing between responses on each trial. The primary response was word naming, whereas the secondary response was a generic verbal response, "bam." In previous versions of DRS, we used color as the sole cue for the correct response, potentially allowing people to make decisions about correct responses without fully encoding the stimuli. In the present experiment, we varied perceptual (color) and conceptual (group membership) cues to examine the effect of more complex cues on decision making. We also manipulated the ease of detecting the primary response and secondary response cues. Using response times as the dependent measure, we found a three-way interaction: Altering the nature of the cues lead to dramatic changes in cognitive control performance. Conceptual input exaggerated both the task and discrimination effects, relative to perceptual input. DESIG

High-resolution Near-Infrared Images and Models of the Circumstellar Disk in HH 30

We present Hubble Space Telescope (HST) Near-Infrared Camera and Multi-object Spectrometer (NICMOS) observations of the reflection nebulosity associated with the T Tauri star HH 30. The images show the scattered light pattern characteristic of a highly inclined, optically thick disk with a prominent dustlane whose width decreases with increasing wavelength. The reflected nebulosity exhibits a lateral asymmetry in the upper lobe on the opposite side to that reported in previously published Wide Field Planetary Camera 2 (WFPC2) images. The radiation transfer model which most closely reproduces the data has a flared accretion disk with dust grains larger than standard interstellar medium grains by a factor of approximately 2.1. A single hotspot on the stellar surface provides the necessary asymmetry to fit the images and is consistent with previous modeling of the light curve and images. Photometric analysis results in an estimated extinction of Av>~80; however, since the photometry measures only scattered light rather than direct stellar flux, this a lower limit. The radiative transfer models require an extinction of Av = 7,900.Comment: Accepted for publication in Ap.