Valid Wald Inference with Many Weak Instruments

This paper proposes three novel test procedures that yield valid inference in an environment with many weak instrumental variables (MWIV). It is observed that the t statistic of the jackknife instrumental variable estimator (JIVE) has an asymptotic distribution that is identical to the two-stage-least squares (TSLS) t statistic in the just-identified environment. Consequently, test procedures that were valid for TSLS t are also valid for the JIVE t. Two such procedures, i.e., VtF and conditional Wald, are adapted directly. By exploiting a feature of MWIV environments, a third, more powerful, one-sided VtF-based test procedure can be obtained

Design-Based Multi-Way Clustering

This paper extends the design-based framework to settings with multi-way cluster dependence, and shows how multi-way clustering can be justified when clustered assignment and clustered sampling occurs on different dimensions, or when either sampling or assignment is multi-way clustered. Unlike one-way clustering, the plug-in variance estimator in multi-way clustering is no longer conservative, so valid inference either requires an assumption on the correlation of treatment effects or a more conservative variance estimator. Simulations suggest that the plug-in variance estimator is usually robust, and the conservative variance estimator is often too conservative

Sensitivity Analysis for Linear Estimands

We propose a novel sensitivity analysis framework for linear estimands when identification failure can be viewed as seeing the wrong distribution of outcomes. Our family of assumptions bounds the density ratio between the observed and true conditional outcome distribution. This framework links naturally to selection models, generalizes existing assumptions for the Regression Discontinuity (RD) and Inverse Propensity Weighting (IPW) estimand, and provides a novel nonparametric perspective on violations of identification assumptions for ordinary least squares (OLS). Our sharp partial identification results extend existing results for IPW to cover other estimands and assumptions that allow even unbounded likelihood ratios, yielding a simple and unified characterization of bounds under assumptions like the c-dependence assumption of Masten and Poirier (2018). The sharp bounds can be written as a simple closed form moment of the data, the nuisance functions estimated in the primary analysis, and the conditional outcome quantile function. We find our method does well in simulations even when targeting a discontinuous and nearly infinite bound.Comment: Preliminary and incomplet

Robust Conditional Wald Inference for Over-Identified IV

For the over-identified linear instrumental variables model, researchers commonly report the 2SLS estimate along with the robust standard error and seek to conduct inference with these quantities. If errors are homoskedastic, one can control the degree of inferential distortion using the first-stage F critical values from Stock and Yogo (2005), or use the robust-to-weak instruments Conditional Wald critical values of Moreira (2003). If errors are non-homoskedastic, these methods do not apply. We derive the generalization of Conditional Wald critical values that is robust to non-homoskedastic errors (e.g., heteroskedasticity or clustered variance structures), which can also be applied to nonlinear weakly-identified models (e.g. weakly-identified GMM)

Tax Risk, Corporate Governance, and the Valuation of Tax Avoidance Across Philippine Firms: How Do Investors Value Corporate Tax Avoidance?

Tax avoidance has traditionally been thought to enhance firm value because it generates cash savings for reinvestment or distribution to shareholders. More recent literature, however, suggests that tax avoidance valuation may not be so simple. Desai and Dharmapala (2009) introduced the “agency perspective” on tax avoidance, arguing that investors consider the risk of tax avoidance as opening opportunities for managers to extract rents from their firms. Positive tax avoidance value would therefore be conditional on good corporate governance quality. Drake et al. (2017) introduced yet another dimension—tax risk—to the valuation of tax avoidance, arguing that tax avoidance that comes with less variability in tax outcomes (i.e., comes with lower tax risk) should be preferred to those that come with more because investors prefer stable earnings over risky earnings. This policy brief discusses our findings on how public investors in the Philippines value corporate tax avoidance in the contexts of tax risk and corporate governance quality, and policies that can be implemented to enhance firm transparency, increase tax revenues, and raise firm valuations

Sensitivity of Policy Relevant Treatment Parameters to Violations of Monotonicity

This paper proposes a method in an environment with heterogeneous treatment effects to bound policy relevant treatment parameters (PRTP) without the monotonicity assumption that the instrumental variable works in the same direction for all individuals. While the procedure applies to all PRTP objects, this paper provides a detailed analysis for local average treatment effects in counterfactual environments (LATE*) that does not yet have a procedure for sensitivity analysis to monotonicity violations. The bounding framework uses the proportion of defiers relative to compliers as a sensitivity parameter and yields an identified set that is an interval. The bounds are sharp for binary outcomes. The method is illustrated in an example where the same sex instrument is used to find the effect of having a third child on labor force participation. I find that bounds are informative only for small violations in monotonicity

A Comment on The Common-Probability Auction Puzzle (2023)

Ngangoué and Schotter (2023) investigate common-probability auctions. By running an experiment, they find that, in contrast to the substantial overbidding found in common-value auctions, bidding in strategically equivalent common-probability auctions is consistent with the Nash equilibrium. We reproduce their results in R, conduct robustness checks on how their sample was constructed, and consider possible heterogeneity. We confirm their documented qualitative results

Three-Dimensional Analysis of the In Vivo Motion of Implantable Cardioverter Defibrillator Leads

Better understanding of the lead curvature, movement and their spatial distribution may be beneficial in developing lead testing methods, guiding implantations and improving life expectancy of implanted leads. Objective The aim of this two-phase study was to develop and test a novel biplane cine-fluoroscopy-based method to evaluate input parameters for bending stress in leads based on their in vivo 3D motion using precisely determined spatial distributions of lead curvatures. Potential tensile, compressive or torque forces were not subjects of this study. Methods A method to measure lead curvature and curvature evolution was initially tested in a phantom study. In the second phase using this model 51 patients with implanted ICD leads were included. A biplane cine-fluoroscopy recording of the intracardiac region of the lead was performed. The lead centerline and its motion were reconstructed in 3D and used to define lead curvature and curvature changes. The maximum absolute curvature C-max during a cardiac cycle, the maximum curvature amplitude C-amp and the maximum curvature C-max@amp at the location of C-amp were calculated. These parameters can be used to characterize fatigue stress in a lead under cyclical bending. Results The medians of C-amp and C-max@amp were 0.18 cm(-1) and 0.42 cm(-1), respectively. The median location of C-max was in the atrium whereas the median location of C-amp occurred close to where the transit through the tricuspid valve can be assumed. Increased curvatures were found for higher slack grades. Conclusion Our results suggest that reconstruction of 3D ICD lead motion is feasible using biplane cine-fluoroscopy. Lead curvatures can be computed with high accuracy and the results can be implemented to improve lead design and testing

Tax risk, corporate governance, and the valuation of tax avoidance across Philippine firms: How do investors value corporate tax avoidance?

Corporate tax avoidance has traditionally been thought to enhance firm value because it generates cash tax savings. Recent literature on tax risk and the agency perspective on tax avoidance, however, suggests that the value of tax avoidance diminishes in certain situations. In tax risk literature, the value of tax avoidance has been observed to diminish when it entails higher tax risk. Investors discount the value of tax avoidance when it produces uncertain tax outcomes. In the literature on the agency perspective on tax avoidance, the value of tax avoidance has been observed at zero to negative when strong corporate governance is absent. Investors assign tax avoidance no value, or even negative value in some cases, when there is a lack of strong corporate governance to prevent rent extraction and protect tax savings. In this study, we examine the effect of tax avoidance on firm value while considering tax risk and corporate governance for non-utility, non-financial, and non-PEZA firms listed on the Philippine Stock Exchange from 2012 to 2019. We employ a two-step generalized method of moments estimation technique using two measures of tax avoidance, two measures of tax risk, and one measure of corporate governance quality to examine any relation between firm value and the set of factors consisting of tax avoidance, tax risk, and corporate governance quality. Consistent with agency theory, we find that investors negatively value tax avoidance. We conclude that for Philippine investors, negative concerns about agency costs arising from tax avoidance activities overshadow positive expectations about their benefits. Furthermore, we ascertain that good corporate governance alleviates the negative valuation of tax avoidance