2016
DOI: 10.1111/ajps.12266
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Macro Implementation: Testing the Causal Paths from U.S. Macro Policy to Federal Incarceration

Abstract: Policy implementation is usually studied at the micro level by testing the short-term effects of a specific policy on the behavior of government actors and policy outcomes. This study adopts an alternative approach by examining macro implementation-the cumulative effect of aggregate public policies over time. I employ a variety of methodological techniques to test the influence of macro criminal justice policy on new admissions to federal prison via three mediators: case filings by federal prosecutors, convict… Show more

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Cited by 3 publications
(2 citation statements)
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“…By using lagged variables of immigration, the results are evidence of Granger causality whereby if variable (X) causes variable (Y), then a previous value of X should predict a subsequent value of Y (Granger, 1969). While Granger-causality tests are not proof of causality it does suggest “a temporal ordering that is consistent with a causal narrative” (Hall, 2017: 8).…”
Section: Resultsmentioning
confidence: 99%
“…By using lagged variables of immigration, the results are evidence of Granger causality whereby if variable (X) causes variable (Y), then a previous value of X should predict a subsequent value of Y (Granger, 1969). While Granger-causality tests are not proof of causality it does suggest “a temporal ordering that is consistent with a causal narrative” (Hall, 2017: 8).…”
Section: Resultsmentioning
confidence: 99%
“…Granger causality helps to determine whether this is true in the data. In short, for a relationship to be considered as signifying Granger causality, the independent variable should have a statistically significant relationship with the dependent variable, but the reverse p-value-a test of the reverse relationship with the dependent variable predicting the independent variable-should not indicate a p-value of less than 0.05 (Hall, 2017).…”
Section: The Frequency Of Coveragementioning
confidence: 99%