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
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