Expert Econometrician for Quantile Regression Modelling

This project seeks a highly qualified professional with extensive experience in econometrics and statistical regression modeling, particularly utilizing STATA software (as an alternate, R/RStudio can also be used). The project involves a comprehensive analysis of employee wage data using quantile regression and decomposition techniques. Objectives: 1. Sample Selection Corrected Conditional Quantile Regression & Decompositions: - Evaluate the impact of various employee characteristics on their wages across different employment types, employing sample selection correction for conditional quantile regression. - Decompose the gender wage gap using a Sample Selection Adjusted conditional quantile regression with Melly's Machado-Mata Decomposition. 2. Unconditional Quantile Regression & Centered Regressions for Wage Gap Decomposition: - Analyze how employee characteristics affect their wages across employment types using unconditional quantile regression and centered regression for influence function analysis. - Utilize this information to decompose the wage gap between genders and across employment types. - Incorporate Sample Selection Adjustment methodology into both models. 3. Mixed Effects Quantile Regression Model Application: - Employ mixed effects quantile regression models to assess the impact of employee characteristics on their wages within various employment types. 4. Quantile Regression Coefficient Modelling Framework Analysis: - Leverage the R-based Quantile Regression Coefficient Modelling Framework to investigate the influence of employee characteristics on wages across employment types. Required Skills & Qualifications: • In-depth knowledge of econometrics and statistical regression modeling (quantile regression, sample selection models, decomposition methods) • Advanced proficiency in STATA (or R) software for econometric analysis • Strong coding skills, particularly for implementing custom methodologies absent from pre-packaged software Additional Information: • A detailed document containing the project objectives, variable descriptions, and relevant research papers is attached. • Each of the above objectives is to be finished stage-wise. I highly value your expertise in this domain and welcome your advice on the project. I eagerly await your bid and potential collaboration to conduct this wage gap analysis successfully.