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.