I can help you conduct econometric analysis using R and write report
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Project Details
Why Hire Me?
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With 7+ years of experience in applied data analytics, I specialize in econometric modeling using R. From lm() and plm to forecast and tseries, I use the right combination of packages to execute regression, panel, and time-series models. I deliver plagiarism-free reports in APA, Harvard, or IEEE format with detailed interpretations and actionable insights.
Key Strengths:
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Econometric expertise tailored to both academic research and business questions
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Deep experience with R libraries like
lmtest,plm,forecast,ggplot2, andtseries -
End-to-end project coverage: data cleaning, modeling, diagnostics, reporting
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Clear output with robust checks for heteroskedasticity, autocorrelation, and multicollinearity
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Fully formatted reports with R Markdown integration for reproducibility
What I Need to Start Your Work
To deliver precise and useful econometric analysis using R, I will require the following:
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Project Overview
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Objectives and questions your econometric analysis is expected to address
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Intended purpose (e.g., thesis, policy recommendation, investment insight)
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Dataset & Description
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File in
.csv,.xlsx, or.RDataformat -
Summary of variables, data source, and preprocessing details (if any)
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Model Preferences
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Type of models to apply (e.g., OLS, fixed/random effects, ARIMA, GARCH)
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Any specific packages or functions to use (e.g.,
plm,urca,dynlm)
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Report Requirements
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Word count, report structure, formatting style (APA/Harvard/IEEE)
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Charts, tables, and narrative expectations for final output
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Timelines & Communication
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Delivery deadline and key milestones
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Preferred mode and frequency of communication for updates
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Portfolio
Housing Prices and Air Quality: Econometric Evidence from U.S. Metropolitan Areas Using R
Used fixed-effects panel regression in R to assess the relationship between property prices and air pollution levels across 30 U.S. cities. Findings guided green zoning and tax rebate policies.
Impact of Minimum Wage Changes on Part-Time Employment: A Time Series Analysis in R
Implemented ARDL models in R to explore how changes in state-level minimum wages affect part-time employment rates. Insights shaped labor market advocacy strategies.
Determinants of Residential Electricity Demand: A U.S. Panel Data Approach Using R
Used panel regression in R to analyze the effects of income, weather, and appliance usage on electricity consumption across 48 U.S. states. Findings guided energy subsidy policies and infrastructure planning.
Process






