Replication Data for: A Bounds Approach to Inference Using the Long Run Multiplier
<|begin_of_text|><|start_header_id|>system<|end_header_id|> You are a research archivist expert in dataset metadata. Answer the question truthfully.  <|eot_id|><|start_header_id|>user<|end_header_id|> Here is the Description of a dataset. Description:'Pesaran, Shin, and Smith (2001) (PSS) proposed a bounds procedure for testing for the existence of long run cointegrating relationships between a unit root dependent variable y and a set of weakly exogenous regressors X when the analyst does not know whether the independent variables are stationary, unit root, or mutually cointegrated processes. This procedure recognizes the analyst's uncertainty over the nature of the regressors but not the dependent variable. When the analyst is uncertain whether y is a stationary or unit root process, the test statistics proposed by PSS are uninformative for inference on the existence of a long run relationship between y and X. We propose the LRM test statistic as a means of testing for long run relationships without knowing whether the series are stationary or unit roots. Using stochastic simulations' . Please return only a json list of at most 3 Keywords corresponding to the Description:.<|eot_id|><|start_header_id|>assistant<|end_header_id|> {"Answer" : ["Stationary","Time Series Analysis","Unit Root"]} <|eot_id|>
 Here is the Description of a dataset. Description:'Pesaran, Shin, and Smith (2001) (PSS) proposed a bounds procedure for testing for the existence of long run cointegrating relationships between a unit root dependent variable y and a set of weakly exogenous regressors X when the analyst does not know whether the independent variables are stationary, unit root, or mutually cointegrated processes. This procedure recognizes the analyst's uncertainty over the nature of the regressors but not the dependent variable. When the analyst is uncertain whether y is a stationary or unit root process, the test statistics proposed by PSS are uninformative for inference on the existence of a long run relationship between y and X. We propose the LRM test statistic as a means of testing for long run relationships without knowing whether the series are stationary or unit roots. Using stochastic simulations' . Please return only a json list of at most 3 Keywords corresponding to the Description:.
Pesaran, Shin, and Smith (2001) (PSS) proposed a bounds procedure for testing for the existence of long run cointegrating relationships between a unit root dependent variable y and a set of weakly exogenous regressors X when the analyst does not know whether the independent variables are stationary, unit root, or mutually cointegrated processes. This procedure recognizes the analyst's uncertainty over the nature of the regressors but not the dependent variable. When the analyst is uncertain whether y is a stationary or unit root process, the test statistics proposed by PSS are uninformative for inference on the existence of a long run relationship between y and X. We propose the LRM test statistic as a means of testing for long run relationships without knowing whether the series are stationary or unit roots. Using stochastic simulations
Stationary; Time Series Analysis; Unit Root