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Debate on the use of lagged dependent variables has a long history in political science. The latest contribution to this discussion is Wilkins (2018, Political Science Research and Methods, 6, 393–411), which advocates the use of an ADL(2,1) model when there is serial dependence in the outcome and disturbance. While this specification does offer some insurance against serially correlated disturbances, this is never the best (linear unbiased estimator) approach and should not be pursued as a general strategy. First, this strategy is only appropriate when the data-generating process (DGP) actually implies a more parsimonious model. Second, when this is not the DGP—e.g., lags of the predictors have independent effects—this strategy mischaracterizes the dynamic process. We clarify this issue and detail a Wald test that can be used to evaluate the appropriateness of the Wilkins approach. In general, we argue that researchers need to always: (i) ensure models are dynamically complete and (ii) test whether more restrictive models are appropriate. [ABSTRACT FROM AUTHOR]

Are sanctions and sanctions threats costly for the sanctioning state? The costs of sanctions for the sender are an important feature of many theories developed to explain the use and utility of economic sanctions. Despite the prominence of this assumption in existing research, there are only a handful of studies that have endeavored to analyze or estimate the economic consequences of sanctions for sender states. This paper builds a theoretical framework that connects the costs of sanctions for sender firms with a phenomenon that can be observed, stock market data. Sanctions and sanctions threats should create market uncertainty that is reflected in stock price volatility for firms with commercial interests in targeted states. Comparisons are made using stock price data for firms within sectors at the same point in time, within sectors over time, and across sectors over time. The stock prices for firms with commercial interests in targeted states are more volatile than stock prices for comparable firms without commercial interests in targeted states. These spells of uncertainty not only reflect the costs of sanctions and sanctions threats for firms caused by interruptions in commercial activities but represent important costs for firms in-and-of themselves. [ABSTRACT FROM AUTHOR]

A fundamental challenge facing applied time‐series analysts is how to draw inferences about long‐run relationships (LRR) when we are uncertain whether the data contain unit roots. Unit root tests are notoriously unreliable and often leave analysts uncertain, but popular extant methods hinge on correct classification. Webb, Linn, and Lebo (WLL; 2019) develop a framework for inference based on critical value bounds for hypothesis tests on the long‐run multiplier (LRM) that eschews unit root tests and incorporates the uncertainty inherent in identifying the dynamic properties of the data into inferences about LRRs. We show how the WLL bounds procedure can be applied to any fully specified regression model to solve this fundamental challenge, extend the results of WLL by presenting a general set of critical value bounds to be used in applied work, and demonstrate the empirical relevance of the LRM bounds procedure in two applications. [ABSTRACT FROM AUTHOR]

How do economic sanctions affect presidential approval? Competing claims have been made about the domestic political consequences of economic sanctions. One claim is that sanctions are unpopular because they have negative economic consequences; another claim is that sanctions are popular because they project an image of strength; and another claim is that sanctions are neither popular nor unpopular because the public is uninformed about international affairs. These arguments imply competing identification restrictions. I test these competing models using a Bayesian Structural Vector Autoregression (B-SVAR) model. The results show that sanctions have a moderate negative effect on presidential approval. I use these findings as a basis for a broader set of auxiliary analyses. Despite received wisdom, sanctions imposed for different reasons against different target states do not produce disparate effects on public opinion. These analyses resolve an important empirical dilemma that weighs on a range of theoretical perspectives in the sanctions literature and highlights fruitful avenues for future research. [ABSTRACT FROM AUTHOR]