Week 1 Flashcards
(15 cards)
What is the difference between a Theoretical Model and an Empirical Model?
Theoretical models describe behaviours but may not always be feasible to replicate empirically, perhaps due to data limitations or aspects not related to real-world data.
Empirical (Econometric) models are simplified representations intended to capture the important features of certain observed phenomena using real-world data.
How are Economic Models typically represented?
By functional relationships, such as quantity demanded (Qd) as a function of price (P) and income (Y): Qd = f(P, Y).
What is the difference between Causation and Association?
Association is typically measured by something like a correlation coefficient, indicating a relationship between variables. Causation implies that a change in X causes a change in Y (ΔX causes ΔY).
What is the role of the Error Term in empirical models?
The error term is a random or unobserved component introduced to capture uncertainty, unpredictable elements, omitted variables, measurement error, or model misspecification.
What does Ceteris Paribus mean?
all other variables or factors are held constant
What are the main types of Economic Data?
Time Series
Cross-Section
Pooled Cross-Section
Panel Data (longitudinal)
Experimental
Observational
What is Time Series data?
Observations of a variable or variables over time. Examples: stock prices, GDP, CPI.
What is Cross-Section data?
A sample of units (individuals, households, firms, cities, etc.) at a given point in time.
What is Pooled Cross-Section data?
Combining two or more independent cross-sections in one dataset.
What is the difference between Cardinal and Ordinal Measurement in data?
Cardinal data is quantitative, where observations are measurements.
Ordinal data is qualitative, involving ranking or categories.
What is Ordinary Least Squares (OLS)?
OLS is a method (estimator) used to find the “best fit” line through a set of data points by minimizing the sum of the squared residuals (errors).
It provides estimates (coefficients with hats) for the unknown parameters (intercept and slope) of the linear regression model.
How does OLS work by minimizing residuals?
OLS calculates the difference between the actual Y value and the predicted Y value for each data point
To avoid positive and negative errors cancelling out, OLS squares each residual and sums them up
How is the total variation in the dependent variable explained in OLS?
The Total Sum of Squares (TSS), representing the total variation in Y, is decomposed into the Explained Sum of Squares (ESS), the part explained by the model, and the Residual Sum of Squares (RSS), the unexplained part. The relationship is TSS = ESS + RSS.
How do you interpret the slope coefficient in a simple linear regression model (Y = a + bX + u)?
The slope coefficient (b hat) represents the estimated change in the dependent variable (Y) for a one-unit increase in the explanatory variable (X).
What is the interpretation of the intercept in a simple linear regression model?
The intercept (a hat) is the predicted value of the dependent variable (Y) when the explanatory variable (X) is zero.
