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A popular practice of community‐policing is police attendance at community meetings. Given the prevalence of this co‐productive activity, research needs to understand the potential variation in police‐community interactions occurring in or reported in community meetings. Developing reliable and valid measurement techniques to characterize interactions occurring at police‐community meetings has strategic planning value for police and community practitioners and scholarly theoretical value. Two observational coding (issue‐specific and global) and sampling (continuous and periodic) strategies are contrasted. Methodological trade‐offs regarding validity, utility, strategic planning value, and theory‐testing value of the different methods are detailed. It is concluded that global measures of police‐community interactions and periodic observations of police‐community meetings can help with understanding variation in police‐community meetings and implementation effectiveness of co‐productive strategies. Yet, to validly understand the cause and effects of police‐community co‐production on building community and public safety, issue‐specific coding strategies and continuous observations of community meetings are necessary.

I survey applications of Markov switching models to the asset pricing and portfolio choice literatures. In particular, I discuss the potential that Markov switching models have to fit financial time series and at the same time provide powerful tools to test hypotheses formulated in the light of financial theories, and to generate positive economic value, as measured by risk-adjusted performances, in dynamic asset allocation applications. The chapter also reviews the role of Markov switching dynamics in modern asset pricing models in which the no-arbitrage principle is used to characterize the properties of the fundamental pricing measure in the presence of regimes.

I review the burgeoning literature on applications of Markov regime switching models in empirical finance. In particular, distinct attention is devoted to the ability of Markov Switching models to fit the data, filter unknown regimes and states on the basis of the data, to allow a powerful tool to test hypotheses formulated in light of financial theories, and to their forecasting performance with reference to both point and density predictions. The review covers papers concerning a multiplicity of sub-fields in financial economics, ranging from empirical analyses of stock returns, the term structure of default-free interest rates, the dynamics of exchange rates, as well as the joint process of stock and bond returns.

This paper investigates forecasting US Treasury bond and Dollar Eurocurrency rates using the stochastic unit root (STUR) model of Leybourne et al. (1996), and the stochastic cointegration (SC) model of Harris et al. (2002, 2006). Both models have time-varying parameter representations and are conceptually attractive for modelling interest rates as both allow for conditional heteroscedasticity. I find that for many of the series considered STUR and SC models generate statistically significant gains in out-of-sample forecasting accuracy relative to simple orthodox models. The results obtained highlight the usefulness of these extensions and raise some issues for future research.

Long-term interest rates of small open economies (SOE) correlate strongly with the USA long-term rate. Can central banks in those countries decouple from the United States? An estimated Dynamic Stochastic General Equilibrium (DSGE) model for the UK (vis-á-vis the USA) establishes three structural empirical results: (1) Comovement arises due to nominal fluctuations, not through real rates or term premia; (2) the cause of comovement is the central bank of the SOE accommodating foreign inflation trends, rather than systematically curbing them; and (3) SOE may find themselves much more affected by changes in USA inflation trends than the United States itself. All three results are shown to be intuitive and backed by off-model evidence.

Most criminal justice scholars agree that the past three decades have witnessed a punitive shift in criminal justice policy, public opinion, and political rhetoric. Have these political trends also left their mark on policy approaches to due process rights? The provision of counsel to indigent defendants is a signature issue in debates over due process rights. The Supreme Court expanded dramatically the circumstances under which states were required to provide counsel in the 1960s and 1970s, though decisions about the implementation of this mandate were left to individual states. We examine the evolution of indigent defense policy, at the state and local level, over the past three decades, and ask two questions: First, did policies evolve in the directions expected by reform advocates? Second, to the extent that policies developed differently across states, how can we account for those differences? We find that refomers' optimistic projections about structure and funding have not been realized, and that adoption of progressive policies has been uneven across states. Most importantly, we find evidence that the politics of ideology and racial conflict have played a significant role in states' indigent defense policy over the past three decades.

This paper investigates the relationship between institutional ownership and idiosyncratic volatility in Chinese and the USA stock markets and explores the potential explanations.

In this paper, the authors use the panel data regressions and the dynamic tests of two-way Granger causality in the panel VAR model to examine the relationship between institutional ownership and idiosyncratic volatility in Chinese and the USA stock markets.

The authors find that the institutional ownership in the Chinese (the USA) stock market is significantly and positively (negatively) related to idiosyncratic volatility through various tests. This paper indicates that institutional investors in the USA are more prudent and risk-averse, while the Chinese institutional investors are not because of high risk-bearing capacity.

This paper deepens the authors’ understanding on the relationship between institutional ownership and idiosyncratic volatility and in the USA and the Chinese stock markets. This paper explains the opposite relationships between institutional ownership and idiosyncratic volatility in the stock markets in China and USA.