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STATA: Data Analysis Software

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STATATime Series Analysis

Datasets Used in Tutorial

– Datasets in these tutorials are based on examples in:

Stock and Watson (2006) “Introduction to Econometrics”

– You can obtain all of the datasets used in these tutorials by downloading a STATA command file from http://www.stata.org.uk/download-examples.html

Outline

– Statistical Analysis• Time Series

– Managing Time Series Data– Dickey-Fuller Test

– ARIMA

– VAR

– ARCH

Outline

– Statistical Analysis• Time Series

– Managing Time Series Data» Open Dataset» Set Time Variable

» Graph Data

» Create Lags

» Create Leads

» Create Differences

Outline

– Statistical Analysis• Time Series

– Managing Time Series Data» Open Dataset

» Set Time Variable» Graph Data

» Create Lags

» Create Leads

» Create Differences

Outline

– Statistical Analysis• Time Series

– Managing Time Series Data» Open Dataset

» Set Time Variable

» Graph Data» Create Lags

» Create Leads

» Create Differences

Outline

– Statistical Analysis• Time Series

– Managing Time Series Data» Open Dataset

» Set Time Variable

» Graph Data

» Create Lags» Create Leads

» Create Differences

Outline

– Statistical Analysis• Time Series

– Managing Time Series Data» Open Dataset

» Set Time Variable

» Graph Data

» Create Lags

» Create Leads» Create Differences

Outline

– Statistical Analysis• Time Series

– Managing Time Series Data» Open Dataset

» Set Time Variable

» Graph Data

» Create Lags

» Create Leads

» Create Differences

Outline

– Statistical Analysis• Time Series

– Managing Time Series Data

– Dickey-Fuller Test– ARIMA

– VAR

– ARCH

Outline

– Statistical Analysis• Time Series

– Dickey-Fuller Test» DF Test on a variable» DF Test on differenced variable

Outline

– Statistical Analysis• Time Series

– Dickey-Fuller Test» DF Test on a variable

» DF Test on differenced variable

Outline

– Statistical Analysis• Time Series

– Managing Time Series Data

– Dickey-Fuller Test

– ARIMA– VAR

– ARCH

Outline

– Statistical Analysis• Time Series

– ARIMA» ARIMA Estimation» Partial Correlogram (PAC)

» Correlogram (AC)

» Info Criteria (AIC and BIC)

» Challenge

Outline

– Statistical Analysis• Time Series

– ARIMA» ARIMA Estimation

» Partial Correlogram (PAC)» Correlogram (AC)

» Info Criteria (AIC and BIC)

» Challenge

Outline

– Statistical Analysis• Time Series

– ARIMA» ARIMA Estimation

» Partial Correlogram (PAC)

» Correlogram (AC)» Info Criteria (AIC and BIC)

» Challenge

Outline

– Statistical Analysis• Time Series

– ARIMA» ARIMA Estimation

» Partial Correlogram (PAC)

» Correlogram (AC)

» Info Criteria (AIC and BIC)» Challenge

Outline

– Statistical Analysis• Time Series

– ARIMA» ARIMA Estimation

» Partial Correlogram (PAC)

» Correlogram (AC)

» Info Criteria (AIC and BIC)

» Challenge

ARIMA: Challenge

Challenge– Estimate ARIMA(2,0,2) for inflation

Method– Use current data– Generate inflation = (punew-L1.punew)/L1.punew– Run Dickey-Fuller on inflation– Use PAC and AC graphs– Use AIC and BIC tests on ARIMA(3,0,2)– Compare to AIC and BIC on ARIMA(2,0,2)

Outline

– Statistical Analysis• Time Series

– Managing Time Series Data

– Dickey-Fuller Test

– ARIMA

– VAR– ARCH

Outline

– Statistical Analysis• Time Series

– VAR» Declare Time Variable» VAR Regression (Dinflation vs Unemployment)

» Joint Significance Test

» VAR Forecast Calculations

» VAR Forecast Graphs

» Challenge

Outline

– Statistical Analysis• Time Series

– VAR» Declare Time Variable

» VAR Regression (Dinflation vs Unemployment)» Joint Significance Test

» VAR Forecast Calculations

» VAR Forecast Graphs

» Challenge

Outline

– Statistical Analysis• Time Series

– VAR» Declare Time Variable

» VAR Regression (Dinflation vs Unemployment)

» Joint Significance Test» VAR Forecast Calculations

» VAR Forecast Graphs

» Challenge

Outline

– Statistical Analysis• Time Series

– VAR» Declare Time Variable

» VAR Regression (Dinflation vs Unemployment)

» Joint Significance Test

» VAR Forecast Calculations» VAR Forecast Graphs

» Challenge

Outline

– Statistical Analysis• Time Series

– VAR» Declare Time Variable

» VAR Regression (Dinflation vs Unemployment)

» Joint Significance Test

» VAR Forecast Calculations

» VAR Forecast Graphs» Challenge

Outline

– Statistical Analysis• Time Series

– VAR» Declare Time Variable

» VAR Regression (Dinflation vs Unemployment)

» Joint Significance Test

» VAR Forecast Calculations

» VAR Forecast Graphs

» Challenge

VAR: Challenge

Challenge– Forecast unemployment using VAR with 4 lags

Method– Use current data– Run VAR with 4 lags– Forecast 20 steps ahead

Outline

– Statistical Analysis• Time Series

– Managing Time Series Data

– Dickey-Fuller Test

– ARIMA

– VAR

– ARCH

Outline

– Statistical Analysis• Time Series

– ARCH» ARCH Estimation» Conditional Variance

» Conditional St. Deviation

» Challenge

Outline

– Statistical Analysis• Time Series

– ARCH» ARCH Estimation

» Conditional Variance» Conditional St. Deviation

» Challenge

Outline

– Statistical Analysis• Time Series

– ARCH» ARCH Estimation

» Conditional Variance

» Conditional St. Deviation» Challenge

Outline

– Statistical Analysis• Time Series

– ARCH» ARCH Estimation

» Conditional Variance

» Conditional St. Deviation

» Challenge

GARCH: Challenge

Challenge– Estimate a GARCH(2,2) model

Method– Use current data– Run GARCH(2,2)– Save conditional variance

www.STATA.org.uk

– If you visit www.STATA.org.uk you can download tutorials on these other topics:

Data Management Statistical AnalysisImporting Data Summary Statistics

Graphs Linear Regressions

Presenting Output Panel Regressions

Merge or Drop Data Time Series Analysis

Instrumental Variables

Probit Analysis