Search Results - subject_exact:"Statistical inference"

Bayesian causal inference for credit default risk

Pitso, Sello Dalton; Michael, Taryn - 2026

Banks often assume that higher credit limits increase customer default risk because greater exposure appears to imply greater vulnerability. This reasoning, however, conflates correlation with causation. Whether increasing a customer's credit limit truly raises the likelihood of default remains...

Persistent link: https://ebvufind01.dmz1.zbw.eu/10015614384

Inference for an algorithmic fairness-accuracy frontier

Liu, Yiqi; Molinari, Francesca - 2025 - This draft: June 13, 2025

Algorithms are increasingly used to aid with high-stakes decision making. Yet, their predictive ability frequently exhibits systematic variation across population subgroups. To assess the trade-off between fairness and accuracy using finite data, we propose a debiased machine learning estimator...

Persistent link: https://ebvufind01.dmz1.zbw.eu/10015419993

An introduction to double/debiased machine learning

Ahrens, Achim; Chernozhukov, Victor; Hansen, Christian; … - 2026

This paper provides an introduction to Double/Debiased Machine Learning (DML). DML is a general approach to performing inference about a target parameter in the presence of nuisance functions: objects that are needed to identify the target parameter but are not of primary interest. Nuisance...

Persistent link: https://ebvufind01.dmz1.zbw.eu/10015616936

Estimating treatment effects with limited exogeneity : a machine learning approach to selection bias

Sun, Rui; Chen, Shiyi - 2026

This paper presents a novel method for estimating treatment effects in cases where prior knowledge of the exogeneity of the treatment variable is limited. We employ a machine learning technique, double selection via Lasso, to identify a robust set of control variables without requiring prior...

Persistent link: https://ebvufind01.dmz1.zbw.eu/10015633562

A practical guide to endogeneity correction using copulas

Qian, Yi; Koschmann, Anthony; Xie, Hui - 2026

Persistent link: https://ebvufind01.dmz1.zbw.eu/10015670274

Initial-condition-robust inference in autoregressive models

Andrews, Donald W. K.; Li, Ming; Zheng, Yapeng - 2026

Persistent link: https://ebvufind01.dmz1.zbw.eu/10015618889

An introduction to statistical inference for behavioral economics

Beleña, Leon; Escot Mangas, Lorenzo; Lazcano, Ana; … - 2026

Persistent link: https://ebvufind01.dmz1.zbw.eu/10015640885

Estimation and inference for the persistence of extremely high temperatures

Cai, Juan Juan; Lin, Yicong; Schaumburg, Julia; Wang, … - 2026

We propose a nonparametric framework for estimating the extremal index that captures the persistence of extreme observations. The framework provides unified and simple procedures for verifying the well-known local dependence condition D(ᵈ) (un), which characterizes the extremal index yet is...

Persistent link: https://ebvufind01.dmz1.zbw.eu/10015567815

Handling missing values in information systems research : a review of methods and assumptions

Peng, Jiaxu; Hahn, Jungpil; Huang, Ke-Wei - 2023

Persistent link: https://ebvufind01.dmz1.zbw.eu/10014323272

On local overidentification and efficiency gains in modern causal inference and data combination

Chen, Xiaohong; Xie, Haitian - 2026 - Revised version: March 1, 2026

Persistent link: https://ebvufind01.dmz1.zbw.eu/10015616461

Weak instrument bias in impulse response estimators

Lewis, Daniel J.; Mertens, Karel - 2026

Persistent link: https://ebvufind01.dmz1.zbw.eu/10015606655

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Weak instrument bias in impulse response estimators

Lewis, Daniel J.; Mertens, Karel - 2026

Book / Working Paper

Weak instrument bias in impulse response estimators

Lewis, Daniel J.; Mertens, Karel - 2026

Book / Working Paper

An alternative Bayesian data envelopment analysis approach for correcting bias of efficiency estimators

Zervopoulos, Panagiotis D.; Triantis, Konstantinos P.; … - 2023

Persistent link: https://ebvufind01.dmz1.zbw.eu/10014334850

Unified inference for predictive mean and quantile regressions via empirical likelihood

Cai, Zongwu; Chen, Yifeng; Hong, Seok Young; Tsvetanov, … - 2026

Persistent link: https://ebvufind01.dmz1.zbw.eu/10015619835

Model averaging and double machine learning

Ahrens, Achim; Hansen, Christian; Schaffer, Mark E.; … - 2025

Persistent link: https://ebvufind01.dmz1.zbw.eu/10015372755

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Model averaging and double machine learning

Ahrens, Achim; Hansen, Christian; Schaffer, Mark E.; … - 2024

Book / Working Paper

A robust inference for predictive expectile regression : an IVX-based approach

Cai, Zongwu; Long, Wei - 2026

Persistent link: https://ebvufind01.dmz1.zbw.eu/10015619847

Subsampling inference for nonparametric extremal conditional quantiles

Kurisu, Daisuke; Otsu, Taisuke - 2025

This paper proposes a subsampling inference method for extreme conditional quantiles based on a self-normalized version of a local estimator for conditional quantiles, such as the local linear quantile regression estimator. The proposed method circumvents difficulty of estimating nuisance...

Persistent link: https://ebvufind01.dmz1.zbw.eu/10015374601

Extreme value inference for heterogeneous heavy-tailed data : a derandomization theory

Daouia, Abdelaati; Hachem, Joseph; Stupfler, Gilles - 2026

Persistent link: https://ebvufind01.dmz1.zbw.eu/10015625395

Bootstrap inference for group factor models

Gonçalves, Sílvia; Koh, Julia; Perron, Benoit - 2025

Persistent link: https://ebvufind01.dmz1.zbw.eu/10015339830

Causal inference on regression discontinuity designs by high-dimensional methods

Arai, Yoichi; Seo, Myung Hwan; Otsu, Taisuke - 2026

Persistent link: https://ebvufind01.dmz1.zbw.eu/10015626459

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Causal inference on regression discontinuity designs by high-dimensional methods

Arai, Yoici; Otsu, Taisuke; Seo, Myung Hwan - 2019

Book / Working Paper

Causal inference and data fusion in econometrics

Hünermund, Paul; Bareinboim, Elias - 2025

Persistent link: https://ebvufind01.dmz1.zbw.eu/10015357822

Harnessing genetic variants for local average treatment effect estimation

Bia, Michela; Menta, Giorgia; Huber, Martin; … - 2026

When multiple instruments are available, conventional instrumental variable estimators aggregate across potentially heterogeneous margins of compliance and may yield effects that lack a clear economic interpretation. The problem is compounded when some instruments violate the exclusion...

Persistent link: https://ebvufind01.dmz1.zbw.eu/10015638521

On the nuisance of control variables in causal regression analysis

Hünermund, Paul; Louw, Beyers - 2025

Persistent link: https://ebvufind01.dmz1.zbw.eu/10015187574

Quantile selection in the gender pay gap

Batbayar, Egshiglen; Breunig, Christoph; Haan, Peter; … - 2026

We propose a new approach to estimate selection-corrected quantiles of the gender wage gap. Our method employs instrumental variables that explain variation in the latent variable but, conditional on the latent process, do not directly affect selection. We provide semiparametric identification...

Persistent link: https://ebvufind01.dmz1.zbw.eu/10015640929

Double robust inference for continuous updating GMM

Kleibergen, Frank; Zhan, Zhaoguo - 2025

We propose the double robust Lagrange multiplier (DRLM) statistic for testing hypotheses specified on the minimizer of the population continuous updating objective function. The (bounding) χ2 limiting distribution of the DRLM statistic is robust to both misspecification and weak identification,...

Persistent link: https://ebvufind01.dmz1.zbw.eu/10015190343

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Double robust inference for continuous updating GMM

Kleibergen, Frank - 2021

Book / Working Paper

Forecasting China bond default with severe class-imbalanced data : a simple learning model with causal inference

Peng, Mike W.; Stern, Elisheva R.; Hu, Hanwen - 2025

Persistent link: https://ebvufind01.dmz1.zbw.eu/10015195157

Is inference conditional on not rejecting a pre-test less reliable than unconditional inference?

Chaisemartin, Clément de; D'Haultfœuille, Xavier - 2026

Assume that an estimator is asymptotically normal for a target parameter under some conditions. Suppose also that one can test these conditions, and one conducts inference for the target only if the pre-test is not rejected. Does such pre-testing undermine inference? We show that if the tested...

Persistent link: https://ebvufind01.dmz1.zbw.eu/10015644454

Robust inference on income inequality : t-statistic based approach

Ibragimov, Rustam; Kattuman, Paul A.; Skrobotov, Anton - 2025

Persistent link: https://ebvufind01.dmz1.zbw.eu/10015196609

Improved spatial dependence-robust inference via pre-whitening

Conley, Timothy G.; Kelly, Morgan; Kozbur, Damian - 2026

This paper presents a method to improve existing spatial dependence-robust inference procedures for spatial data. Our method involves augmenting a regression specification with functions of locations that reduce spatial correlation in regression scores and serves as a pre-whitener, followed by...

Persistent link: https://ebvufind01.dmz1.zbw.eu/10015644690

Recent applications of generalized instrumental variable models

Kim, Dongwoo - 2025

Persistent link: https://ebvufind01.dmz1.zbw.eu/10015325824

Hierarchical risk parity variants for cryptocurrency portfolios : denoising, detoning, tail dependence, embeddings, and statistical inference, 2020-2026

Matys, Alan; Rodriguez, Federico Martin; Delfau, Emiliano - 2026

We extend the 2025 conference study on Hierarchical Risk Parity (HRP) by addressing its two stated methodological follow-ups (Marchenko-Pastur denoising and spectral detoning) and by evaluating a broader cross-section of portfolio construction choices on a survivorshipbias-corrected,...

Persistent link: https://ebvufind01.dmz1.zbw.eu/10015656467

Inference for high-dimensional local projection

Gao, Jiti; Liu, Fei; Peng, Bin - 2026

Persistent link: https://ebvufind01.dmz1.zbw.eu/10015650641

Interacting treatments with endogenous takeup

Kormos, Máté; Lieli, Robert P.; Huber, Martin - 2025

Persistent link: https://ebvufind01.dmz1.zbw.eu/10015463300

On causal inference with model-based outcomes

Arkhangelsky, Dmitry; Yanagimoto, Kazuharu; Zohar, Tom - 2026

We study the estimation of causal effects on group-level parameters identified from microdata (e.g., child penalties). We demonstrate that standard one-step methods (such as pooled OLS and IV regressions) are generally inconsistent due to an endogenous weighting bias, where the policy affects...

Persistent link: https://ebvufind01.dmz1.zbw.eu/10015650738

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On causal inference with modelbased outcomes

Arkhangelsky, Dmitry; Yanagimoto, Kazuharu; Zohar, Tom - 2026

Book / Working Paper

On causal inference with model-based outcomes

Arkhangelsky, Dmitry; Yanagimoto, Kazuharu; Zohar, Tom - 2025

Book / Working Paper

How diversification shapes full-fledged Islamic bank Stability? : A causal inference approach

Haddou, Samira; Boughrara, Adel - 2025

Persistent link: https://ebvufind01.dmz1.zbw.eu/10015466453

From perfect to practical : partial identification methods for causal inference in strategic management research

Frake, Justin; Gibbs, Anthony; Goldfarb, Brent; … - 2025

Persistent link: https://ebvufind01.dmz1.zbw.eu/10015467450

Two-way clustering with non-exchangeable data

Jochmans, Koen - 2026 - This version: January 20, 2026

Persistent link: https://ebvufind01.dmz1.zbw.eu/10015575634

Revisiting the macroeconomic determinants of non-performing loans with a deep learning technique with causal inference : evidence from Türkiye

Raşid Bakır, Muhammed; Atalay Çetin, Mümin; … - 2025

This study revisits the macroeconomic determinants of non-performing loans using a deep neural network (DNN). We present the proposed DNN as a methodological framework that combines deep learning techniques and causal inference methods. We employ a rigorous triple-validation methodology that...

Persistent link: https://ebvufind01.dmz1.zbw.eu/10015471266

Estimation of DSGE models by non-Gaussian vector autoregressions

Martinoli, Mario; Di Francesco, Damiano; Moneta, Alessio; … - 2026

We propose a new impulse response matching procedure for estimating the parameters of dynamic stochastic general equilibrium models from observed macroeconomic time series. The estimator is based on an indirect inference framework in which the auxiliary model is a structural vector...

Persistent link: https://ebvufind01.dmz1.zbw.eu/10015667205

The choice of control variables in empirical management research : how causal diagrams can inform the decision

Hünermund, Paul; Louw, Beyers; Rönkkö, Mikko - 2025

Persistent link: https://ebvufind01.dmz1.zbw.eu/10015439049

Causal inference for social network formation

Kasy, Maximilian; Linos, Elizabeth; Mobasseri, Sanaz - 2026

This paper develops a framework for identification, estimation, and inference on the causal mechanisms driving endogenous social network formation. Identification is challenging because of unobserved confounders and reverse causality; inference is complicated by questions of equilibrium and...

Persistent link: https://ebvufind01.dmz1.zbw.eu/10015670159

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Causal inference for social network formation

Kasy, Maximilian; Linos, Elizabeth; Mobasseri, Sanaz - 2026

Book / Working Paper

Causal inference for social network formation

Kasy, Maximilian; Linos, Elizabeth; Mobasseri, Sanaz - 2026

Book / Working Paper

Coupling LSTM neural networks and state-space models through analytically tractable inference

Vuong, Van-Dai; Nguyen, Luong-Ha; Goulet, James-A. - 2025

Persistent link: https://ebvufind01.dmz1.zbw.eu/10015440244

Causal state-dependent local projections

David, Joel M.; Giacomini, Raffaella; Jiao, Xiyu; Wang, … - 2026

Persistent link: https://ebvufind01.dmz1.zbw.eu/10015665864

Moran's I lasso for models with spatially correlated data

Barde, Sylvain; Cherodian, Rowan; Tchuente, Guy - 2025

Persistent link: https://ebvufind01.dmz1.zbw.eu/10015459769

Likelihood-free inference for multivariate generalized pareto models

Aka, Samira; Kratz, Marie; Naveau, Philippe - 2026

Persistent link: https://ebvufind01.dmz1.zbw.eu/10015677538

Inference in a stationary/nonstationary autoregressive time-varying-parameter model

Andrews, Donald W. K.; Li, Ming - 2025

This paper considers nonparametric estimation and inference in first-order autoregressive (AR(1)) models with deterministically time-varying parameters. A key feature of the proposed approach is to allow for time-varying stationarity in some time periods, time-varying nonstationarity (i.e., unit...

Persistent link: https://ebvufind01.dmz1.zbw.eu/10015460575

Robust inference for time series quantile regression : a dependent wild bootstrap-based approach

Cai, Zongwu; Long, Wei - 2026

Persistent link: https://ebvufind01.dmz1.zbw.eu/10015673652

The role of storage in commodity markets : indirect inference based on grain data

Gouel, Christophe; Legrand, Nicolas - 2025

We develop an indirect inference approach relying on a linear supply and demand model serving as an auxiliary model to provide the first full empirical test of the rational expectations commodity storage model. We build a rich storage model that incorporates a supply response and four structural...

Persistent link: https://ebvufind01.dmz1.zbw.eu/10015425389

Testing models with fat tails via indirect inference

Minford, Patrick; Meenagh, David - 2026

Fat tails can in principle undermine the power of the standard indirect inference test. We examine this issue with Monte Carlo experiments, first for a New Keynesian model solved by the nonlinear algorithm method of Fair and Taylor. Here we find that the standard test has its usual high power,...

Persistent link: https://ebvufind01.dmz1.zbw.eu/10015672849

Vis inertiae and statistical inference : a review of Difference-in-Differences methods employed in economics and other subjects

Bosco, Bruno Paolo; Maranzano, Paolo - 2025

Difference in Differences (DiD) is a useful statistical technique employed by researchers to estimate the effects of exogenous events on the outcome of some response variables in random samples of treated units (i.e., units exposed to the event) ideally drawn from an infinite population. The...

Persistent link: https://ebvufind01.dmz1.zbw.eu/10015562085

Role-reversed auxiliary calibration for treatment effects under selection on potential outcomes

Hoshino, Takahiro; Shinoda, Kazuhiko; Otsu, Taisuke - 2026

Persistent link: https://ebvufind01.dmz1.zbw.eu/10015676166

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Role-reversed auxiliary calibration for treatment effects under selection on potential outcomes

Hoshino, Takahiro; Shinoda, Kazuhiko; Otsu, Taisuke - 2026

Book / Working Paper