Qingyuan Zhao,Trevor Hastie
Qingyuan Zhao
The fields of machine learning and causal inference have developed many concepts, tools, and theory that are potentially useful for each other. Through exploring the possibility of extracting causal interpretations from black-box machine-tr...
Heterogeneity in Expectations, Risk Tolerance, and Household Stock Shares: The Attenuation Puzzle [0.03%]
期望、风险管理能力和家庭股票份额的异质性：风险管理能力悖论
John Ameriks,Gábor Kézdi,Minjoon Lee et al.
John Ameriks et al.
This paper jointly estimates the relationship between stock share and expectations and risk preferences. The survey allows individual-level, quantitative estimates of risk tolerance and of the perceived mean and variance of stock returns. T...
John M Abowd,Kevin L McKinney,Ian M Schmutte
John M Abowd
We evaluate the bias from endogenous job mobility in fixed-effects estimates of worker- and firm-specific earnings heterogeneity using longitudinally linked employer-employee data from the LEHD infrastructure file system of the U.S. Census ...
Censored Quantile Instrumental Variable Estimates of the Price Elasticity of Expenditure on Medical Care [0.03%]
医疗保健支出价格弹性的审查分位数工具变量估计值
Amanda Kowalski
Amanda Kowalski
Efforts to control medical care costs depend critically on how individuals respond to prices. I estimate the price elasticity of expenditure on medical care using a censored quantile instrumental variable (CQIV) estimator. CQIV allows estim...
Yongli Zhang,Xiaotong Shen
Yongli Zhang
Many procedures have been developed to deal with the high-dimensional problem that is emerging in various business and economics areas. To evaluate and compare these procedures, modeling uncertainty caused by model selection and parameter e...
Zhibiao Zhao
Zhibiao Zhao
For non-stationary processes, the time-varying correlation structure provides useful insights into the underlying model dynamics. We study estimation and inferences for local autocorrelation process in locally stationary time series. Our co...
Feature Screening for Ultrahigh Dimensional Categorical Data with Applications [0.03%]
超高维分类数据的特征筛选及其应用
Danyang Huang,Runze Li,Hansheng Wang
Danyang Huang
Ultrahigh dimensional data with both categorical responses and categorical covariates are frequently encountered in the analysis of big data, for which feature screening has become an indispensable statistical tool. We propose a Pearson chi...
Mian Huang,Runze Li,Hansheng Wang et al.
Mian Huang et al.
When the functional data are not homogeneous, e.g., there exist multiple classes of functional curves in the dataset, traditional estimation methods may fail. In this paper, we propose a new estimation procedure for the Mixture of Gaussian ...
Mehmet Caner,Hao Helen Zhang
Mehmet Caner
Model selection and estimation are crucial parts of econometrics. This paper introduces a new technique that can simultaneously estimate and select the model in generalized method of moments (GMM) context. The GMM is particularly powerful f...
Measurement error in earnings data: Using a mixture model approach to combine survey and register data [0.03%]
基于混合模型方法结合调查数据与注册数据来衡量收入数据中的测量误差
Erik Meijer,Susann Rohwedder,Tom Wansbeek
Erik Meijer
Survey data on earnings tend to contain measurement error. Administrative data are superior in principle, but they are worthless in case of a mismatch. We develop methods for prediction in mixture factor analysis models that combine both da...