ADEC 7320 Econometrics

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
Every Fall, Every Spring, Every Summer

Catalog details

Prerequisites
ADEC7301/ADAN7301 or ADEC7310/ADAN7309 or ADAN7310/ADEC7309

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
4.08 / 5 · Very Good
176 responses
Instructor rating
4.18 / 5 · Very Good
176 responses
Terms evaluated
13
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 Sharma3.34.04.34.04.84.54.84.310+ hrs/week4 of 7
Spring 2026Piyush Chandra3.13.14.14.34.84.44.13.010+ hrs/week8 of 10
Fall 2025Arvind Sharma4.54.44.34.25.04.84.84.37–9 hrs/week6 of 8
Fall 2025Piyush Chandra3.03.23.94.04.84.24.23.810+ hrs/week10 of 16
Summer 2025Arvind Sharma4.35.04.54.84.84.85.04.010+ hrs/week4 of 7
Fall 2024Arvind Sharma5.05.05.05.05.05.05.04.7—3 of 6
Fall 2024Gustavo Vicentini4.64.63.93.94.74.74.74.67–9 hrs/week7 of 9
Fall 2024Razvan Veliche4.54.34.54.64.84.34.84.0—8 of 11
Summer 2024Arvind Sharma4.54.64.54.64.94.34.73.610+ hrs/week10 of 13
Spring 2024Arvind Sharma5.05.05.05.04.55.05.05.0—2 of 3
Spring 2024Gustavo Vicentini4.24.04.74.74.84.44.84.810+ hrs/week7 of 10
Spring 2024Razvan Veliche4.44.43.84.24.63.84.44.010+ hrs/week5 of 8
Fall 2023Arvind Sharma—————————3 of 8
Fall 2023Gustavo Vicentini—————————15 of 19
Fall 2023Razvan Veliche—————————6 of 8
Summer 2023Arvind Sharma—————————5 of 5
Spring 2023Arvind Sharma4.34.44.44.64.64.64.73.910+ hrs/week7 of 11
Spring 2023Gustavo Vicentini4.84.74.74.84.74.84.84.77–9 hrs/week6 of 9
Spring 2023Razvan Veliche3.53.84.04.05.04.04.04.010+ hrs/week4 of 8
Fall 2022Gustavo Vicentini3.93.94.64.64.74.34.64.77–9 hrs/week18 of 22
Summer 2022Haydar Evren4.34.85.05.04.85.04.83.37–9 hrs/week4 of 9
Spring 2022Gustavo Vicentini3.74.04.64.04.44.24.24.3—6 of 17
Spring 2022Razvan Veliche3.54.03.73.74.74.04.03.87–9 hrs/week6 of 16
Fall 2021Gustavo Vicentini4.24.14.64.64.04.74.74.44–6 hrs/week9 of 26
Fall 2021Nathaniel Bastian3.64.54.44.45.04.64.44.410+ hrs/week9 of 17
Fall 2021Razvan Veliche3.33.83.53.54.04.04.53.37–9 hrs/week4 of 10

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, Summer 2023, Spring 2023 · Official rating 4.62/5
  • Gustavo Vicentini
    Fall 2024, Spring 2024, Fall 2023, Spring 2023, Fall 2022, Spring 2022, Fall 2021 · Official rating 4.12/5
  • Haydar Evren
    Summer 2022 · Official rating 4.75/5
  • Nathaniel Bastian
    Fall 2021 · Official rating 4.50/5
  • Piyush Chandra
    Spring 2026, Fall 2025 · Official rating 3.17/5
  • Razvan Veliche
    Fall 2024, Spring 2024, Fall 2023, Spring 2023, Spring 2022, Fall 2021 · Official rating 4.12/5