APPLIED ECONOMETRICS

James Morley

COURSE OUTLINE

• Time Series

• Basic Models

• Inference

• Forecasting

• Structural Analysis

• Advanced Models

PART I: “TIME SERIES”

OUTLINE

•Macroeconomic Data

• Serial Correlation

• Trends and Breaks

•Methodology

READINGS AND MATERIALS

• Stock and Watson, C. 12

• Hansen, JEP

• Hoover, Ch.5

• Sims, JEP

• EViews and GAUSS lite

TIME SERIES?

TIME SERIES?

• collection of observations for a variable (e.g., aggregate output) over time

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MACRO DATA

• Aggregate (Normality)

• FRED, BEA, SourceOECD, ABS

• Literature focuses on US data

• Look at the data!!

KEY SERIES (I)

• Real GDP, Components, Population

• Inflation (GDP Deflator, PCE Deflator, CPI)

• Unemployment Rate

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KEY SERIES (II)

•Deficits/Debt

• Interest Rates

• Exchange Rates

• Stock Returns

DATA ISSUES

• Seasonality

• Revisions

•Measurement Error

• Chain Weighting

• Frequency

• Serial Correlation

SERIAL CORRELATION

• persistence in time series

WHY DOES SERIAL CORRELATION MATTER?

• less independent information

•more potential for forecasting

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