**21 Oct**2017

# Freelance Statistician / Econometrician / R Programmer for Academic Statistical Research

## Job Description

We would like to search for a Statistician / Econometrician / R programmer with good statistical/econometrician knowledge, modeling/modeling diagnostic experience, and statistical research experience, to develop the programs and consult on model and experiment design for our academic statistical research on hedge funds.

We would be analyzing the influencing factors that affect the performance, risk, and life cycle(hazard rate) of hedge funds using regression analysis (including multivariate regression, time series regression, Cox regression), difference-in-difference regression, heckman 2 stage model, Regression Discontinuity Designs, Natural experiment, and Randomized experiment. Doing causal inference and using identification strategies to setup appropriate experiment/tests that establish causal claims, and avoiding issues such as reverse causality, simultaneity, omitted variable, and endogeneity in general. The position’s responsibilities and qualifications are described below.

Work Period: From Immediately to 3 weeks-3 months

Pay: Total project pay is determined by your availability and hourly rate. We would do flat rate only for the entire project (the budget amount would not be a good reference because it depends on the freelancer).

**Responsibilities **

- Model Consultation and Model diagnostic: (if you have practical experience in this but do not have the R programming experience, please still apply)

-Consult on procedures for specifically detecting the presence of and treating the endogeneity issues of reverse causality, simultaneity, omitted variable, and endogeneity in general

-Consult on finding suitable identification strategies for establishing claim for causal relationship for what we are looking to test

-Consult on modeling design based on what we are looking to test and our data. –

-Consult on methodology or model diagnostic procedure that we should use to make sure our models/analysis/experiments are robust, and the model parameters are specified to our analysis, and properly adjusted for factors that may affect our model/results (such as to avoid multicollinearity, endogeneity, Heteroscedasticity, biase, distribution)

- Programming/model implementation/data processing:

-programming in R to code our models and variables, data processing, and various other programming, data, statistics related tasks.

- Models implementation: Replicating or applying models and procedures from reference papers to our research
- Description of procedures: Provide detailed and technical description of

the methodology used models and implementation

**Qualifications**

- Master’s or PhD’s degree in Statistics/Econometric that used R significantly
- Minimum 4 years of experience implementing programming using R (must), preferably statistical models
- Have experience in Causal inference and using identification strategies to setup appropriate experiment/tests that establish causal claims
- Have practical experience in implementing tests for detecting the presence of and methods for treating the endogeneity issues of reverse causality, simultaneity, omitted variable, and endogeneity in general
- Have experience in applying statistical methodologies procedures to ensure robustness (such as to avoid multicollinearity, endogeneity, Heteroscedasticity, biases) (having experience in model diagnostic procedures)
- Knowledgeable and years of practical experiences in basic and advanced statistical modeling, including many of the below statistical analysis methods, models, procedures
- Regression analysis
- o cross-sectional regression (t-statistic, chi square-statistic, F-statistic)
- o logistics regression (regular and conditional logit model)
- o Time series regression
- o Multivariate regression
- o Cox proportional hazard model (z-statistic) used for survival analysis

- AIC

- Regression analysis
- Experience in academic research would be preferred
- Very good English communications skills in oral and writing
- Weekly availability to be at least 25 hours from now to 01/03, prefer 40-60 hours/weekly availability

**Questions**

Do you have a Barchelor’s, Master’s, or Statistics degree in Statistics, Applied Mathematics, or closely related field? (please send a CV or resume with your application)

Could you describe your experience in Causal inference and using identification strategies to setup appropriate experiment/tests that establish causal claims?

Could you describe your experience in testing for and treating for the issues of reverse causality, simultaneity, omitted variable, endogeneity? (such as Hausman’s test, heckman correction – 2 stage model, 2 stage regression

Could you describe the extent of your statistical modeling experience? Please specify which models that you have had many years of working experience or academic research experience with

Number of years for R experience? and approximately how often have you used R those years (such as 30 hours/w)? Could you describe your R usage? Please include a more detailed description for the statistical programming usage

Could you send us a sample of a R script that you have written to allow us to evaluate your skill level?

What is your approx. weekly available hours that can dedicate to this work project up to 01/03?

To better determine the flat rate for the project, what is your usual rate charged for freelancing statistical and R programming work?