Understanding Equation Balance in Time Series Regression: An Extension
<|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:'Most contributors to a recent Political Analysis symposium on time series analysis suggest that in order to maintain equation balance, one cannot combine stationary, integrated and/or fractionally integrated variables with general error correction models (GECMs) and the equivalent autoregressive distributed lag (ADL) models. This definition of equation balance implicates most previous uses of these models in political science and circumscribes their use moving forward. The claim thus is of real consequence and worthy of empirical substantiation, which the contributors did not provide. Here we address the issue. First, we highlight the difference between estimating unbalanced equations and mixing orders of integration, the former of which clearly is a problem and the latter of which is not, at least not necessarily. Second, we assess som' . 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" : ["time series, equation balance, gecm, ecm, adl"]} <|eot_id|>
 Here is the Description of a dataset. Description:'Most contributors to a recent Political Analysis symposium on time series analysis suggest that in order to maintain equation balance, one cannot combine stationary, integrated and/or fractionally integrated variables with general error correction models (GECMs) and the equivalent autoregressive distributed lag (ADL) models. This definition of equation balance implicates most previous uses of these models in political science and circumscribes their use moving forward. The claim thus is of real consequence and worthy of empirical substantiation, which the contributors did not provide. Here we address the issue. First, we highlight the difference between estimating unbalanced equations and mixing orders of integration, the former of which clearly is a problem and the latter of which is not, at least not necessarily. Second, we assess som' . Please return only a json list of at most 3 Keywords corresponding to the Description:.
Most contributors to a recent Political Analysis symposium on time series analysis suggest that in order to maintain equation balance, one cannot combine stationary, integrated and/or fractionally integrated variables with general error correction models (GECMs) and the equivalent autoregressive distributed lag (ADL) models. This definition of equation balance implicates most previous uses of these models in political science and circumscribes their use moving forward. The claim thus is of real consequence and worthy of empirical substantiation, which the contributors did not provide. Here we address the issue. First, we highlight the difference between estimating unbalanced equations and mixing orders of integration, the former of which clearly is a problem and the latter of which is not, at least not necessarily. Second, we assess som
time series, equation balance, gecm, ecm, adl