M. Hashem Pesaran
- Published in print:
- 2015
- Published Online:
- March 2016
- ISBN:
- 9780198736912
- eISBN:
- 9780191800504
- Item type:
- chapter
- Publisher:
- Oxford University Press
- DOI:
- 10.1093/acprof:oso/9780198736912.003.0031
- Subject:
- Economics and Finance, Econometrics
This chapter reviews the theoretical literature on testing for unit roots and cointegration in panels where the time dimension (T) and the cross section dimension (N) are relatively large. The ...
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This chapter reviews the theoretical literature on testing for unit roots and cointegration in panels where the time dimension (T) and the cross section dimension (N) are relatively large. The discussions cover the model and hypotheses to test; first and second generation panel unit root tests; cross-unit cointegration; finite sample properties of panel unit root tests; residual-based approaches to panel cointegration; tests for multiple cointegration; and panel cointegration in the presence of cross section dependence. Exercises are provided at the end of the chapter.Less
This chapter reviews the theoretical literature on testing for unit roots and cointegration in panels where the time dimension (T) and the cross section dimension (N) are relatively large. The discussions cover the model and hypotheses to test; first and second generation panel unit root tests; cross-unit cointegration; finite sample properties of panel unit root tests; residual-based approaches to panel cointegration; tests for multiple cointegration; and panel cointegration in the presence of cross section dependence. Exercises are provided at the end of the chapter.
David McDowall, Richard McCleary, and Bradley J. Bartos
- Published in print:
- 2019
- Published Online:
- February 2021
- ISBN:
- 9780190943943
- eISBN:
- 9780190943981
- Item type:
- chapter
- Publisher:
- Oxford University Press
- DOI:
- 10.1093/oso/9780190943943.003.0005
- Subject:
- Sociology, Social Research and Statistics
Chapter 5 describes three sets of auxiliary methods that have emerged as add-on supplements to the traditional ARIMA model-building strategy. First, Bayesian information criteria (BIC) can be used to ...
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Chapter 5 describes three sets of auxiliary methods that have emerged as add-on supplements to the traditional ARIMA model-building strategy. First, Bayesian information criteria (BIC) can be used to inform incremental modeling decisions. BICs are also the basis for the Bayesian hypothesis tests introduced in Chapter 6. Second, unit root tests can be used to inform differencing decisions. Used appropriately, unit root tests guard against over-differencing. Finally, co-integration and error correction models have become a popular way of representing the behavior of two time series that follow a shared path. We use the principle of co-integration to define the ideal control time series. Put simply, a time series and its ideal counterfactual control time series are co-integrated up the time of the intervention. At that point, if the two time series diverge, the magnitude of their divergence is taken as the causal effect of the intervention.Less
Chapter 5 describes three sets of auxiliary methods that have emerged as add-on supplements to the traditional ARIMA model-building strategy. First, Bayesian information criteria (BIC) can be used to inform incremental modeling decisions. BICs are also the basis for the Bayesian hypothesis tests introduced in Chapter 6. Second, unit root tests can be used to inform differencing decisions. Used appropriately, unit root tests guard against over-differencing. Finally, co-integration and error correction models have become a popular way of representing the behavior of two time series that follow a shared path. We use the principle of co-integration to define the ideal control time series. Put simply, a time series and its ideal counterfactual control time series are co-integrated up the time of the intervention. At that point, if the two time series diverge, the magnitude of their divergence is taken as the causal effect of the intervention.
M. Hashem Pesaran
- Published in print:
- 2015
- Published Online:
- March 2016
- ISBN:
- 9780198736912
- eISBN:
- 9780191800504
- Item type:
- chapter
- Publisher:
- Oxford University Press
- DOI:
- 10.1093/acprof:oso/9780198736912.003.0015
- Subject:
- Economics and Finance, Econometrics
This chapter compares the properties of unit root processes with stationary processes, and considers alternative ways of testing for unit roots. The discussions cover difference stationary processes; ...
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This chapter compares the properties of unit root processes with stationary processes, and considers alternative ways of testing for unit roots. The discussions cover difference stationary processes; unit root and other related processes; trend-stationary versus first difference stationary processes; variance ratio tests; Dickey-Fuller unit root tests; other unit root tests; and long memory processes. Exercises are provided at the end of the chapter.Less
This chapter compares the properties of unit root processes with stationary processes, and considers alternative ways of testing for unit roots. The discussions cover difference stationary processes; unit root and other related processes; trend-stationary versus first difference stationary processes; variance ratio tests; Dickey-Fuller unit root tests; other unit root tests; and long memory processes. Exercises are provided at the end of the chapter.
Jeffrey S. Racine
- Published in print:
- 2019
- Published Online:
- January 2019
- ISBN:
- 9780190900663
- eISBN:
- 9780190933647
- Item type:
- chapter
- Publisher:
- Oxford University Press
- DOI:
- 10.1093/oso/9780190900663.003.0002
- Subject:
- Economics and Finance, Econometrics
This chapter outlines pitfalls of using standard inference procedures common in cross- sectional settings in time series settings and presents alternative procedures. It also addresses the issue of ...
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This chapter outlines pitfalls of using standard inference procedures common in cross- sectional settings in time series settings and presents alternative procedures. It also addresses the issue of spurious regression and cautions the reader against the unquestioning use of cross section tools in time series settings.Less
This chapter outlines pitfalls of using standard inference procedures common in cross- sectional settings in time series settings and presents alternative procedures. It also addresses the issue of spurious regression and cautions the reader against the unquestioning use of cross section tools in time series settings.
