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Lecture 14 summary
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Summary of 9 pages for the course EKN 320 at UP (Lecture 14 summary)
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Lecture 14Relationships between economics time series:
regression analysis
Econometrics:
- Empirical estimation of economic relationships
o Concerned with measuring economic relationships
- Econometric approach → utilised to measure and to test empirically certain
relationships among economic variables
o Economic theory → embodied in an econometric model
▪ Indicates relationship between variables
▪ These must represent reality as accurately as possible
o Facts → summarised by relevant data
▪ Events in real world relating to phenomenon under investigation
▪ Most likely would need to adjust or refine the data series using
various adjustments
• Seasonal/cyclical adjustments, extrapolation, interpolation,
merging of different data sources
• Set of adjusted data = refined data
o Statistical theory → refined in econometric techniques
▪ Estimate the econometric model using econometric techniques
▪ Extensions of classical statistical theory, particularly statistical
inference → use sample information to infer certain characteristics of
population
- Purpose of econometrics:
o Structural analysis = “scientific” purpose of econometrics
▪ Understanding real-world phenomena by quantitatively measuring,
testing and validating economic relationships
o Forecasts = basis for action
▪ E.g. → sales forecasts of motor vehicle sales = how many cars/parts
to import
▪ E.g → effect of interest rate hikes this far and predicted effect =
should still hike interest rates?
o Policy evaluation = used by policy makers
▪ Simulate alternative policies and look at forecasts for relevant
variables under each alternative
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, Basic concepts:
- Quantitative data vs qualitative data:
o Quantitative
▪ Numeric values
▪ Immediately usbale data
o Qualitative
▪ May be assigned numeric values → dummy variable
• E.g male and female → 1 for male and 0 for female
- Time series (TS) data vs cross-sectional (CS) data:
o TS → measures particular variable during successive time periods or at
different dates
▪ E.g. daily, weekly, quarterly or annually
o CS → measures information for different individual economic agents
(different countries, different households, etc.) at the same period
- Equation components:
o 𝐶 = 𝛽0 + 𝛽1 𝑌 → consumption function in simplest Keynesian form
▪ 𝐶 → total private consumption/household expenditure (dep.
variable)
▪ 𝛽0 → autonomous comsumption
• Parameter/coefficient of equation
▪ 𝛽1 → marignal propensity to consume (△ 𝐶/△ 𝑌)
• Parameter/coefficient of equation
▪ 𝑌 → total income (indep. variable)
▪ 𝐶 = 𝑓(𝑌) → C is a funtion of Y
• Variation in C may be expklained by varition in Y
o Dependent variable → being explained by the equation
▪ Falls on the left of the equals sign
o Independent variable → used to explain the dependent variable
▪ Falls on the right of the equals sign
o Causality → direction of cause between two variables
▪ Y is used to determind C but C is needed to compute Y
o Endogenous variable
▪ Explained by the model/theory
o Exogenous variable
▪ Determined outside the system/model
▪ Used to explain the model, but are not explained by the model
o Variable example:
▪ 𝐶 = 𝐶(𝑌) → total private consumption spending
▪ 𝐼 = 𝐼(𝑟) → total fixed investment
▪ 𝑋 = 𝑋(𝑌, 𝑟) → net exports
▪ 𝑌 = 𝐶 + 𝐼 + ∆𝑖𝑛𝑣 + 𝐺0 + 𝑋
• 𝑌 → total income/production
• 𝐺0 → government spending
• ∆𝑖𝑛𝑣 → changes in inventory (inventory investment)
• 𝑟 → interest rate
▪ 𝐶, 𝐼, 𝑋 𝑎𝑛𝑑 𝑌 → endogenous
▪ ∆𝑖𝑛𝑣, 𝑟 𝑎𝑛𝑑 𝐺0 → exogenous
Notes can only be purchased through the following details:
gorgataylor@gmail.com or 0829369077 2
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