Police performance measurement: an annotated bibliography

This study provides information to assist those involved in performance measurement in police organisations. The strategies used to identify the literature are described. Thematic sections cover; general overviews; methodological issues; performance management in other industries; national, international and cross-national studies; frameworks (e.g. Compstat; the Balanced Scorecard); criticisms (particularly unintended consequences); crime-specific measures; practitioner guides; performance evaluation of individual staff; police department plans and evaluations; annotated bibliographies in related areas, and; other literature. Our discussion offers two conclusions: the measures best aligned with performance are typically more expensive, while most operational data should only provide contextual information; the philosophy of open governance should be pursued to promote transparency, accountability and communication to improve police performance

Messing Up Texas?: A Re-Analysis of the Effects of Executions on Homicides

<div><p>Executions in Texas from 1994–2005 do not deter homicides, contrary to the results of Land et al. (2009). We find that using different models—based on pre-tests for unit roots that correct for earlier model misspecifications—one cannot reject the null hypothesis that executions do not lead to a change in homicides in Texas over this period. Using additional control variables, we show that variables such as the number of prisoners in Texas may drive the main drop in homicides over this period. Such conclusions however are highly sensitive to model specification decisions, calling into question the assumptions about fixed parameters and constant structural relationships. This means that using dynamic regressions to account for policy changes that may affect homicides need to be done with significant care and attention.</p></div

ARIMA transfer function models of Monthly Texas Homicides with additional covariates, 1994–2005.

<p>Standard errors in parentheses.</p

Changepoint model for monthly Texas homicides with covariates, 1986(3)–2009(8).

<p>First entry is the coefficient, second in parentheses are the standard errors, followed by the two-sided p-values.</p

Count of Post-Gregg executions by state as of 2009.

<p>Count of Post-Gregg executions by state as of 2009.</p

ADF and KPSS tests for unit roots in the Texas monthly homicides, 1994–2005.

<p>Critical values given the right-most columns.</p

Impulse Response Functions for One Execution for Models in Table 2.

<p>Responses are in solid lines with 68% or approximate one standard deviation confidence regions in dashed lines.</p

Texas homicides, first and seasonal differences and associated autocorrelation functions, 1994–2005.

<p>Texas homicides, first and seasonal differences and associated autocorrelation functions, 1994–2005.</p