Get 20M+ Full-Text Papers For Less Than $1.50/day. Start a 14-Day Trial for You or Your Team.

Learn More →

Constructing independent evidence from regression and instrumental variables with an application to the effect of violent conflict on altruism and risk preference

Constructing independent evidence from regression and instrumental variables with an application... To provide an unbiased estimate, a regression analysis depends, among other things, on there being no unmeasured confounding. Often, unmeasured confounding is thought to be possible, but not severe; leading to a secondary instrumental variables (IV) analysis. However, these two analyses are correlated. It is unclear how much independent evidence is provided by the IV analysis. We resolve this redundancy using a new estimator, which extracts the part of the regression estimator uncorrelated to the IV-based 2SLS estimator. We apply our approach to analyze the effect of exposure to violent conflict on preferences for altruistic behavior, time and risk. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Biostatistics & Epidemiology Taylor & Francis

Constructing independent evidence from regression and instrumental variables with an application to the effect of violent conflict on altruism and risk preference

Karmakar, Bikram; Small, Dylan S.
Biostatistics & Epidemiology , Volume OnlineFirst: 21 – Aug 18, 2022
Download PDF

Constructing independent evidence from regression and instrumental variables with an application to the effect of violent conflict on altruism and risk preference

Abstract

To provide an unbiased estimate, a regression analysis depends, among other things, on there being no unmeasured confounding. Often, unmeasured confounding is thought to be possible, but not severe; leading to a secondary instrumental variables (IV) analysis. However, these two analyses are correlated. It is unclear how much independent evidence is provided by the IV analysis. We resolve this redundancy using a new estimator, which extracts the part of the regression estimator uncorrelated...
Loading next page...
 
/lp/taylor-francis/constructing-independent-evidence-from-regression-and-instrumental-CKVHumywVy
Publisher
Taylor & Francis
Copyright
© 2022 International Biometric Society – Chinese Region
ISSN
2470-9379
eISSN
2470-9360
DOI
10.1080/24709360.2022.2109910
Publisher site
See Article on Publisher Site

Abstract

To provide an unbiased estimate, a regression analysis depends, among other things, on there being no unmeasured confounding. Often, unmeasured confounding is thought to be possible, but not severe; leading to a secondary instrumental variables (IV) analysis. However, these two analyses are correlated. It is unclear how much independent evidence is provided by the IV analysis. We resolve this redundancy using a new estimator, which extracts the part of the regression estimator uncorrelated to the IV-based 2SLS estimator. We apply our approach to analyze the effect of exposure to violent conflict on preferences for altruistic behavior, time and risk.

Journal

Biostatistics & Epidemiology – Taylor & Francis

Published: Aug 18, 2022

Keywords: Independent pieces of evidence; instrumental variables; preferences; sensitivity analysis; unmeasured confounding

References

  • Long-term consequences of Vietnam-era conscription: new estimates using social security data
  • Does fiscal decentralization affect the effectiveness of intergovernmental grants? European regional policy and Spanish autonomous regions
  • Consumer spending and the economic stimulus payments of 2008
  • Instrumental variable methods in comparative safety and effectiveness research
  • Information frictions in trade
  • Effectiveness of chemotherapy for advanced lung cancer in the elderly: instrumental variable and propensity analysis
  • Risk of death in elderly users of conventional vs. atypical antipsychotic medications
  • Evidence factors in observational studies
  • Testing hypotheses in order
  • From violence to voting: war and political participation in Uganda
  • War and local collective action in Sierra Leone
  • Violent conflict and behavior: a field experiment in Burundi
  • Seeds of distrust: conflict in Uganda
  • Ethnicity and power in Burundi and Rwanda: different paths to mass violence
  • Estimating causal effects of treatments in randomized and nonrandomized studies
  • Causal inference, path analysis and recursive structural equation models
  • Identification of causal effects using instrumental variables
  • Sensitivity analysis for instrumental variables regression with overidentifying restrictions
  • Errors in variables
  • Alternative tests of independence between stochastic regressors and disturbances
  • Specification tests in econometrics
  • A heteroskedasticity-consistent covariance matrix estimator and a direct test for heteroskedasticity
  • The exact sampling distribution of ordinary least squares and two-stage least squares estimators
  • Can we make smart choices between OLS and contaminated IV methods
  • Smoking and lung cancer: recent evidence and a discussion of some questions
  • Assessing sensitivity to an unobserved binary covariate in an observational study with binary outcome
  • Sensitivity analysis for certain permutation inferences in matched observational studies
  • Bounding disagreements about treatment effects: a case study of sentencing and recidivism
  • Sensitivity analysis for trend tests: application to the risk of radiation exposure
  • Sensitivity analyses comparing outcomes only existing in a subset selected post-randomization, conditional on covariates, with application to HIV vaccine trials
  • Bayesian sensitivity analysis for unmeasured confounding in observational studies
  • The sensitivity of linear regression coefficients' confidence limits to the omission of a confounder
  • Calibrating sensitivity analyses to observed covariates in observational studies
  • An introduction to sensitivity analysis for unobserved confounding in nonexperimental prevention research
  • Sensitivity analysis without assumptions
  • Alternative approximations to the distributions of instrumental variable estimators
  • Asymptotic and finite sample distribution theory for IV estimators and tests in partially identified structural equations
  • Instrumental variables regression with weak instruments
  • A new specification test for the validity of instrumental variables
  • CCeak identification in generalized method of moments
  • In search of homo economicus: behavioral experiments in 15 small-scale societies
  • Anomalies: the endowment effect, loss aversion, and status quo bias
  • Estimators of the parameters of a single equation in a complete set of stochastic equations