Debiased/Double Machine Learning for Instrumental Variable Quantile Regressions

In this study, we investigate estimation and inference on a low-dimensional causal parameter in the presence of high-dimensional controls in an instrumental variable quantile regression. Our proposed econometric procedure builds on the Neyman-type orthogonal moment conditions of a previous study Chernozhukov, Hansen and Wuthrich (2018) and is thus relatively insensitive to the estimation of the nuisance parameters. The Monte Carlo experiments show that the estimator copes well with high-dimensional controls. We also apply the procedure to empirically reinvestigate the quantile treatment effect of 401(k) participation on accumulated wealth.Comment: 19 page

Meta-analysis of genome-wide association studies identifies eight new loci for type 2 diabetes in east Asians

We conducted a three-stage genetic study to identify susceptibility loci for type 2 diabetes (T2D) in east Asian populations. We followed our stage 1 meta-analysis of eight T2D genome-wide association studies (6,952 cases with T2D and 11,865 controls) with a stage 2 in silico replication analysis (5,843 cases and 4,574 controls) and a stage 3 de novo replication analysis (12,284 cases and 13,172 controls). The combined analysis identified eight new T2D loci reaching genome-wide significance, which mapped in or near GLIS3, PEPD, FITM2-R3HDML-HNF4A, KCNK16, MAEA, GCC1-PAX4, PSMD6 and ZFAND3. GLIS3, which is involved in pancreatic beta cell development and insulin gene expression1,2, is known for its association with fasting glucose levels3,4. The evidence of an association with T2D for PEPD5 and HNF4A6,7 has been shown in previous studies. KCNK16 may regulate glucose-dependent insulin secretion in the pancreas. These findings, derived from an east Asian population, provide new perspectives on the etiology of T2D

Debiased/Double Machine Learning for Instrumental Variable Quantile Regressions

In this study, we investigate the estimation and inference on a low-dimensional causal parameter in the presence of high-dimensional controls in an instrumental variable quantile regression. Our proposed econometric procedure builds on the Neyman-type orthogonal moment conditions of a previous study (Chernozhukov et al. 2018) and is thus relatively insensitive to the estimation of the nuisance parameters. The Monte Carlo experiments show that the estimator copes well with high-dimensional controls. We also apply the procedure to empirically reinvestigate the quantile treatment effect of 401(k) participation on accumulated wealth

Stress history influence on sedimentary rock porosity estimates: Implications for geological CO2 storage in Northern Taiwan

We established a stress-history-dependent porosity model of potential target rocks for CO2 geosequestration based on rock sample porosity measurements under various effective stresses (5 - 120 MPa). The measured samples were collected from shallow boreholes (< 300 m depth) drilled at the frontal fold in northern Taiwan. The lithology, density, and the stress-history-dependent porosity derived from shallow boreholes enabled us to predict the porosity-depth relationship of given rock formations at (burial depths of approximately 3170 - 3470 m) potential sites for CO2 geosequestration located near the Taoyuan Tableland coastline. Our results indicate that the porosity of samples derived from laboratory tests under atmospheric pressure is significantly greater than the porosity measured under stress caused by sediment burial. It is therefore strongly recommended that CO2 storage capacity assessment not be estimated from the porosity measured under atmospheric pressure. Neglecting the stress history effect on the porosity of compacted and uplifted rocks may induce a percentage error of 7.7% at a depth of approximately 1000 m, where the thickness of the eroded, formerly overlying formation is 2.5 km in a synthetic case. The CO2 injection pressure effect on the porosity was also evaluated using the stress-history-dependent porosity model. As expected, the pore pressure buildup during CO2 injection will induce an increase in the rock porosity. For example, a large injection pressure of 13 MPa at a depth of approximately 1000 m will increase the rock porosity by a percentage error of 6.7%. Our results have implications for CO2 storage capacity injection pressure estimates

Meta-analysis of genome-wide association studies identifies eight new loci for type 2 diabetes in east Asians

We conducted a three-stage genetic study to identify susceptibility loci for type 2 diabetes (T2D) in east Asian populations. We followed our stage 1 meta-analysis of eight T2D genome-wide association studies (6,952 cases with T2D and 11,865 controls) with a stage 2 in silico replication analysis (5,843 cases and 4,574 controls) and a stage 3 de novo replication analysis (12,284 cases and 13,172 controls). The combined analysis identified eight new T2D loci reaching genome-wide significance, which mapped in or near GLIS3, PEPD, FITM2-R3HDML-HNF4A, KCNK16, MAEA, GCC1-PAX4, PSMD6 and ZFAND3. GLIS3, which is involved in pancreatic beta cell development and insulin gene expression, is known for its association with fasting glucose levels. The evidence of an association with T2D for PEPD and HNF4A has been shown in previous studies. KCNK16 may regulate glucose-dependent insulin secretion in the pancreas. These findings, derived from an east Asian population, provide new perspectives on the etiology of T2D

Genome-wide trans-ancestry meta-analysis provides insight into the genetic architecture of type 2 diabetes susceptibility

To access publisher's full text version of this article click on the hyperlink at the bottom of the pageTo further understanding of the genetic basis of type 2 diabetes (T2D) susceptibility, we aggregated published meta-analyses of genome-wide association studies (GWAS), including 26,488 cases and 83,964 controls of European, east Asian, south Asian and Mexican and Mexican American ancestry. We observed a significant excess in the directional consistency of T2D risk alleles across ancestry groups, even at SNPs demonstrating only weak evidence of association. By following up the strongest signals of association from the trans-ethnic meta-analysis in an additional 21,491 cases and 55,647 controls of European ancestry, we identified seven new T2D susceptibility loci. Furthermore, we observed considerable improvements in the fine-mapping resolution of common variant association signals at several T2D susceptibility loci. These observations highlight the benefits of trans-ethnic GWAS for the discovery and characterization of complex trait loci and emphasize an exciting opportunity to extend insight into the genetic architecture and pathogenesis of human diseases across populations of diverse ancestry.Canadian Institutes of Health Research Medical Research Council UK G0601261 Mexico Convocatoria SSA/IMMS/ISSSTE-CONACYT 2012-2 clave 150352 IMSS R-2011-785-018 CONACYT Salud-2007-C01-71068 US National Institutes of Health DK062370 HG000376 DK085584 DK085545 DK073541 DK085501 Wellcome Trust WT098017 WT090532 WT090367 WT098381 WT081682 WT085475info:eu-repo/grantAgreement/EC/FP7/20141