Levy Economics Institute of Bard College
ECON 529 – Research Methods I – Fall 2026
Instructor: J. Matias De Lucchi
E-mail: mdelucchi@levy.org
Meetings: Thursdays, 1:00–4:20 PM | Room 203
Office Hours: Wednesdays, 2:00–4:00 PM and by appointment
Course Description
The primary objective of this course is to provide the empirical tools needed to analyze economic data, evaluate economic hypotheses, and conduct applied research. This course examines the foundations of econometric methods and their application to macroeconomic debates and policy frameworks, with particular emphasis on time series analysis, empirical modeling, and the use of real-world data to investigate macroeconomic questions, evaluate competing theories, and assess alternative policy approaches. Students acquire the skills needed to select and apply appropriate econometric techniques to macroeconomic data, interpret and critically evaluate empirical findings in the context of macroeconomic debates, and develop the quantitative tools needed to strengthen and support their own research agendas.
Main References
Békés, G., & Kézdi, G. (2021). Data analysis for business, economics, and policy. Cambridge University Press.
Enders, W. (2022). Applied econometric time series (5th ed.). Wiley.
Evaluation
Course evaluation will be based on an in-class midterm exam, a final essay, assignments, and class participation.
Assignments will provide students with opportunities to apply the empirical methods covered in class to economic data and research questions. They may involve data collection and preparation, statistical and econometric analysis, coding, interpretation of results, and critical evaluation of empirical findings.
Unless otherwise indicated, assignments must be submitted by the specified deadline. Late submissions will be penalized.
The final essay will require students to apply the concepts and empirical methods developed throughout the course to an economic research question. Students are encouraged to use the final essay to develop or advance a project related to their own research agenda. Additional guidelines regarding the final essay will be provided during the semester.
Grading
Midterm Exam: 30% Final Essay: 30% Assignments: 30% Class Participation: 10%
Academic Honesty and Use of Generative AI
Students must be familiar with the guidelines regarding academic honesty described in the Student Handbook, including the program’s definition of plagiarism and the penalties associated with violations.
The use of generative AI tools is permitted and encouraged when they can support the research process, including for code generation, checking and correcting code, exploring alternative empirical approaches, clarifying statistical or econometric concepts, and improving the presentation of results.
However, AI-generated outputs should not be accepted at face value. Students are expected to critically evaluate and independently verify AI-generated code, calculations, interpretations, and factual claims, and to perform appropriate validation and robustness checks when necessary.
Students remain fully responsible for all work they submit, including the accuracy of their code, empirical results, interpretations, and conclusions. They should be able to explain the methods, code, and reasoning underlying their work, regardless of whether generative AI tools were used in preparing it.
AI-generated content may not be submitted as a substitute for a student’s own analysis or understanding. Any substantive use of generative AI in preparing an assignment or the final essay must be acknowledged.
Week 01 | Sep 03 — What Is Empirical Economic Research?
Key Topics
- Data and Research Design
- Data Collection and Data Quality
- Economic Data Sources
Suggested Readings
Békés & Kézdi (2021), Ch. 1
Mitchell, W., Wray, L. R., & Watts, M. (2019). Macroeconomics. Bloomsbury Academic. Chs. 2, 4–7
Discussion Topics
- Measuring and Constructing Macroeconomic Variables: GDP, Inflation, Unemployment, Real Wages, and the Rate of Profit
- When Empirical Research Goes Wrong: Errors, Data, and Replication
Discussion Readings
U.S. Bureau of Economic Analysis. (2015, December). Measuring the economy: A primer on GDP and the National Income and Product Accounts. U.S. Department of Commerce.
U.S. Bureau of Labor Statistics. (2024). Handbook of Methods: Consumer Price Index. U.S. Department of Labor. https://www.bls.gov/opub/hom/cpi/home.htm
U.S. Bureau of Labor Statistics. (2024). How the government measures unemployment. U.S. Department of Labor. https://www.bls.gov/cps/cps_htgm.htm
Retus, B. A., & Rouleau, M. (2025, April 22). Returns for domestic nonfinancial business. Survey of Current Business. U.S. Bureau of Economic Analysis.
Herndon, T., Ash, M., & Pollin, R. (2014). Does high public debt consistently stifle economic growth? A critique of Reinhart and Rogoff. Cambridge Journal of Economics, 38(2), 257–279.
Week 02 | Sep 10 — Preparing Data for Analysis
Key Topics
- Macroeconomic Data Structures
- Data Preparation
- Stocks and Flows
Suggested Readings
Békés & Kézdi (2021), Ch. 2
Discussion Topics
- Levels vs. Growth Rates: U.S. GDP Level vs. China’s GDP Growth
- Price Level vs. Inflation
Week 03 | Sep 17 — Exploratory Data Analysis and Probability
Key Topics
- Exploratory Data Analysis
- Conditional Probability
- Statistical Dependence
Suggested Readings
Békés & Kézdi (2021), Chs. 3–4
Discussion Topics
- Keynesian, Frequentist, and Bayesian Approaches to Probability and Inference
- Foley’s Statistical Equilibrium Approach and Laplace Distributions
Discussion Readings
Foley, D. K. (1994). A statistical equilibrium theory of markets. Journal of Economic Theory, 62(2), 321–345.
Gerrard, B. (1995). Probability, uncertainty and behaviour: A Keynesian approach. In S. Dow & J. Hillard (Eds.), Keynes, knowledge and uncertainty (pp. 177–196). Edward Elgar.
Week 04 | Sep 24 — Generalizing from Data
Key Topics
- Statistical Inference
- Statistical Estimation
- Hypothesis Testing
Suggested Readings
Békés & Kézdi (2021), Chs. 5–6
Week 05 | Oct 01 — Simple Regression
Key Topics
- Simple Linear Regression
- Model Specification
- Regression Diagnostics and Interpretation
Suggested Readings
Békés & Kézdi (2021), Chs. 7–8
Discussion Topics
- Estimating Keynes’ Marginal Propensity to Consume
- The Phillips Curve Debate
- Correlation vs. Causation: The Quantity Theory of Money
Discussion Readings
Phillips, A. W. (1958). The relation between unemployment and the rate of change of money wage rates in the United Kingdom, 1861–1957. Economica, 25(100), 283–299.
McCandless, G. T., Jr., & Weber, W. E. (1995). Some monetary facts. Federal Reserve Bank of Minneapolis Quarterly Review, 19(3), 2–11.
Week 06 | Oct 08 — Multiple Regression
Key Topics
- Multiple Linear Regression
- Model Specification
- Regression Diagnostics and Interpretation
Suggested Readings
Békés & Kézdi (2021), Chs. 9–10
Discussion Topic
- Estimating Cost-Push Inflation
Recommended Reading
Lavoie, M. (2022). Post-Keynesian economics: New foundations (2nd ed., Section 8.1.1: The Rejection of the Accelerationist Thesis). Edward Elgar Publishing.
Week 07 | Oct 15 — No Class / Fall Break
Week 08 | Oct 22 — Midterm Exam
Week 09 | Oct 29 — Introduction to Time Series Analysis
Key Topics
- Time Series Data and Stochastic Processes
- Trends, Cycles, and Stationarity
- Time Series Regression and Serial Correlation
Suggested Readings
Békés & Kézdi (2021), Chs. 11–12
Enders (2022), Chs. 1–2
Week 10 | Nov 05 — Unit Roots and Cointegration
Key Topics
- Unit Root Processes
- Long-Run Relationships: Cointegration
- Short-Run Dynamics: Error Correction Models
Suggested Readings
Enders (2022), Chs. 4 & 6
Discussion Topics
- The Term Structure of Interest Rates and Monetary Policy Transmission
- The Normal Rate of Profit
Discussion Reading
Zacharias, A. (2001). Testing profit rate equalization in the U.S. manufacturing sector: 1947–1998 (Working Paper No. 321). The Jerome Levy Economics Institute.
Week 11 | Nov 12 — VAR and Dynamic Systems
Key Topics
- Vector Autoregressions
- Granger Causality
- Impulse Response Analysis
Suggested Readings
Enders (2022), Ch. 5
Discussion Topic
- Kaldor’s Endogenous Money Hypothesis and Granger Causality
Discussion Reading
Kaldor, N. (1970). The new monetarism. Lloyds Bank Review, 97, 1–18.
Week 12 | Nov 19 — State-Space Models and Unobserved Components
Key Topics
- State-Space Models
- Kalman Filter
- Time-Varying Parameters
Suggested Reading
EViews. (2025). State space models and the Kalman filter. EViews User’s Guide. https://help.eviews.com/content/sspace-State_Space_Models_and_the_Kalman_Filter.html
Discussion Topic
- Can We Measure the Natural Rate of Interest?
Discussion Readings
Laubach, T., & Williams, J. C. (2003). Measuring the natural rate of interest. Review of Economics and Statistics, 85(4), 1063–1070.
Kalecki, M. (1968). Trend and business cycles reconsidered. The Economic Journal, 78(310), 263–276.
Week 13 | Nov 26 — No Class / Thanksgiving
Week 14 | Dec 03 — Volatility and Nonlinear Models
Key Topics
- Time-Varying Volatility
- Threshold Models
- Regime-Switching Models
Suggested Readings
Enders (2022), Chs. 3 & 7
Discussion Topic
- Minsky’s Nonlinear Dynamics
Discussion Reading
Minsky, H. P. (1978). The financial instability hypothesis: A restatement. Thames Papers in Political Economy. Hyman P. Minsky Archive, Bard Digital Commons.