ADAN 7320 Regression Models

This course focuses on the application of statistical tools used to estimate economic relationships. The course begins with a discussion of the linear regression model, and examination of common problems encountered when applying this approach, including serial correlation, heteroscedasticity, and multicollinearity. Models with lagged variables are considered, as is estimation with instrumental variables, two-stage least squares, models with limited dependent variables, and basic time-series techniques.

Course overview

Department
Advancing Studies
School
ADV
Credits
3
Level
Graduate
Offered
Periodically

Catalog details

Prerequisites
ADEC7301/ADAN7301

Catalog text is imported from the reviewed Boston College course snapshot. Confirm eligibility in EagleApps.

Course evaluations

Response-weighted averages from Boston College’s official course evaluations (Avalanche/Blue).

Course rating
4.35 / 5 · Very Good
45 responses
Instructor rating
4.38 / 5 · Very Good
45 responses
Terms evaluated
9
Most recent: Spring 2026

Scales: overall ratings run from 1 (poor) to 5 (excellent); agreement questions from 1 (strongly disagree) to 5 (strongly agree); weekly effort from 1 (up to 1 hour) to 5 (10 or more hours).

Evaluations by term and instructor
TermInstructorCourse overallInstructor overallWell organizedClear learning objectivesIntellectually challengingHelpful assignmentsApplicable beyond courseAttendance necessaryWeekly effortResponses
Spring 2026Arvind Sharma5.04.85.05.05.05.05.04.810+ hrs/week5 of 5
Spring 2026Piyush Chandra4.54.55.04.55.05.05.03.57–9 hrs/week2 of 4
Fall 2025Arvind Sharma4.04.35.04.74.74.74.74.77–9 hrs/week3 of 3
Fall 2025Piyush Chandra3.83.34.54.34.54.54.33.8—5 of 5
Summer 2025Arvind Sharma5.05.05.05.05.05.05.05.010+ hrs/week3 of 3
Fall 2024Arvind Sharma4.54.55.05.05.04.54.54.0—2 of 2
Fall 2024Gustavo Vicentini5.05.05.05.05.05.05.05.07–9 hrs/week1 of 2
Fall 2024Razvan Veliche4.04.04.34.04.04.04.03.84–6 hrs/week4 of 4
Summer 2024Arvind Sharma4.44.74.74.74.94.64.63.810+ hrs/week7 of 8
Spring 2024Arvind Sharma4.04.04.54.54.54.04.53.0—2 of 4
Spring 2024Razvan Veliche4.04.34.74.74.74.74.73.34–6 hrs/week3 of 3
Fall 2023Arvind Sharma—————————2 of 3
Fall 2023Gustavo Vicentini—————————2 of 3
Spring 2023Gustavo Vicentini4.55.05.05.04.55.05.05.0—2 of 2
Fall 2022Gustavo Vicentini4.04.04.04.04.04.05.05.01–3 hrs/week1 of 2
Fall 2022Razvan Veliche2.02.03.03.05.04.03.04.07–9 hrs/week1 of 2

Data freshness

Course and evaluation data last updated 2026-10-09. Source details and limitations are documented in Data Sources and Methodology.

Instructors

  • Arvind Sharma
    Spring 2026, Fall 2025, Summer 2025, Fall 2024, Summer 2024, Spring 2024, Fall 2023 · Official rating 4.67/5
  • Gustavo Vicentini
    Fall 2024, Fall 2023, Spring 2023, Fall 2022 · Official rating 4.83/5
  • Piyush Chandra
    Spring 2026, Fall 2025 · Official rating 3.61/5
  • Razvan Veliche
    Fall 2024, Spring 2024, Fall 2022 · Official rating 3.87/5