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Purpose – This paper examines potential correlates of the effectiveness of oleoresin capsicum (OC) or pepper spray and police officer satisfaction with its performance during use‐of‐force encounters. Design/methodology/approach – Based on surveys completed by police officers, superior officers, and substitute prosecutors, data on nearly 800 uses of OC by Dutch police forces occurring between June 1, 2001 and December 31, 2002 were obtained. Ordered and generalized ordered logistic regressions are used for the analysis. Findings – The paper shows that although OC was generally effective, it was less effective on suspects under the influence of drugs, violent suspects, minority suspects, and suspects who were warned before being exposed to OC. Officers with more job experience reported OC as being more effective than officers with less experience. OC reduced aggressiveness among suspects already aggressive, but it induced aggression among initially non‐aggressive subjects. The vast majority of officers were satisfied with OC's performance during the study period, although ratings were affected by its ability to ease arrests, incapacitate suspects, and reduce suspect aggressiveness. Research limitations/implications – The OC incidents on which the analysis is based are a subset of all actual uses, and thus may not be representative. Several of the regressors are based on officer perception, and may be subject to measurement error. Practical implications – The findings in this paper have implications for police policy, practice, and training, and officer and suspect safety. Originality/value – This is one of very few studies to use multiple‐regression to examine correlates of OC effectiveness and officer satisfaction, and it expands upon the prior literature by including additional measures of OC performance. The results should be of value to law enforcement agencies and officers using OC, and those considering its adoption.

The purpose of this paper is to examine the effect of police use of conducted energy devices (CEDs) on officer and suspect injuries while controlling for other types of force and resistance and other factors.

Data on 1,645 use‐of‐force incidents occurring between January 1, 2002 and July 2006 were obtained from two different law enforcement agencies. Logistic and generalized ordered logistic regressions are used to model the odds of injury and severity of injury.

The use of CEDs was associated with reduced odds of officer and suspect injury and the severity of suspect injury in one agency. In the other agency CED use was unrelated to the odds of injury; however, the use of pepper spray was associated with reduced odds of suspect injury. Among other findings, in both agencies the use of hands‐on tactics by police was associated with increased odds of officer and suspect injury, while the use of canines was associated with increased odds of suspect injury.

Although this research was carried out in two distinctly different law enforcement agencies with different histories of CED adoption, the fact that CED use was associated with reductions in injuries in one agency but not the other indicates the need for additional research on the impact of CED use in other settings

The analysis suggests that relative to other forms of force, the use of CEDs and pepper spray can reduce the risk of injury to both suspects and law enforcement officers. This information should prove useful to law enforcement agencies considering adopting CEDs and suggests that agencies should consider the use of these less lethal alternatives in place of hands‐on tactics against actively resistant suspects.

At the time of this writing there was no published independent research on the risks of injury associated with CED use in field settings. The findings reported herein will help inform the public debate on the utility of CEDs for law enforcement.

A whole series of food scandals indicates that misdirected incentives continue to be a source of food risks. Lacking market transparency and the opportunistic use of seemingly profitable opportunities to break the rules cause negative externalities and failure of markets. The purpose of this paper is to investigate the influence of mandatory transparency schemes on food businesses’ behavioural drivers and thus on compliance.

The authors use an adopted analytical framework developed by Hirschauer et al. (2012) as the theoretical background. The authors provide an empirical analysis of the effects of a disclosure system on businesses’ behavioural drivers in three urban parts of the German capital Berlin. The authors conducted a pen-and-paper survey among food businesses to collect data and used a generalized ordered logit regression model to analyse them.

The results show that the higher the businesses assess the possible negative effects of a negative smiley on sales, the higher the probability of compliance. Considering the immaterial behavioural drivers (protective factors) the authors find the statistical significant influence of a feeling of embarrassment in case of disclosure and the feeling of a fair evaluation on compliance. Thus, the study supports the expectation that disclosure policies affect behavioural drivers and have the potential to steer food businesses’ compliance.

The study supports the expectation that hygiene controls’ disclosure positively affects food businesses’ compliance. These findings should be taken into consideration in the ongoing discussion about disclosure. Nowadays, there is no mandatory transparency in Germany due to a strong opposition from businesses and their lobbying groups.

The authors conducted a pen-and-paper survey among food businesses in three urban districts of the German capital Berlin, namely, Pankow, Lichtenberg and Marzahn-Hellersdorf in 2014. The food authorities in these districts were the only ones in Germany that had introduced and run a mandatory disclosure system (smiley-system) for food businesses. The results of the inspections were published on the authorities’ homepages in the internet, and were displayed in businesses. Thus the data mirror the unique experiences of the only German food businesses that participated in a mandatory transparency scheme.

Micro, small and medium-sized enterprises (MSMEs) are the backbone of economic development for every economy. They contribute to local economic development through household wealth creation, employment generation and poverty reduction. Despite this pivotal role, MSMEs lack access to finance, and scholarship on the enabling role of financial inclusion on micro, small and medium-sized enterprises' performance is scant. The authors contribute to closing the knowledge gap by examining the enabling effect of financial inclusion on MSMEs using the FinScope MSME 2017 survey for the Kingdom of Eswatini. This paper aims to discuss the aforementioned objective.

The study used the re-centered influence function regression framework to estimate unconditional quantile regressions and the generalized ordered logit model to analyze the data.

The findings from the unconditional quantile regression revealed that small changes in access to bank accounts, saving for business, formal saving, stokvel and informal saving at the 50th and 75th percentiles have a positive and statistically significant effect on microenterprises' annual turnover profit. Conversely, small changes in formal insurance have a mixed effect on annual turnover profit. At the 10th and 25th percentiles, a small increment in insurance reduces annual turnover profit but increases microenterprise annual turnover profit at the 75th percentile. Meanwhile, the evidence from the generalized ordered logit model showed that financial inclusion reduces the likelihood of microenterprises being classified as least developed and increased the chances of microenterprises falling into emerging and developed business categories.

This study makes use of a cross-sectional survey dataset, as a result, it does not infer causal relationships over the long term, but rather an association between the independent and dependent variables.

Overall, formal and informal financial inclusion enhances the annual turnover profit for microenterprises, particularly at the 50th and 75th percentiles in the Kingdom of Eswatini. The authors recommend a specialized institution such as a micro, small and medium-sized partial credit guarantee scheme to improve the quality and affordability of credit for microenterprises, and a mix of financial and non-financial supports depending on the development stage to boost a sustainable microenterprises' sector.

The study uses two advanced cross-sectional techniques, the recentered influence function framework and the generalized ordered logit model to analyze the data. The paper is original and contributes to the discussion of the role of financial inclusion in enabling microenterprises' success in Africa, using the FinScope 2017 survey of microenterprises in Eswatini as a case study.

The peer review history for this article is available at: https://publons.com/publon/10.1108/IJSE-10-2020-0689.

The R environment for statistical computing and graphics (R Development Core Team, 2008) offers practitioners a rich set of statistical methods ranging from random number generation and optimization methods through regression, panel data, and time series methods, by way of illustration. The standard R distribution (base R) comes preloaded with a rich variety of functionality useful for applied econometricians. This functionality is enhanced by user-supplied packages made available via R servers that are mirrored around the world. Of interest in this chapter are methods for estimating nonparametric and semiparametric models. We summarize many of the facilities in R and consider some tools that might be of interest to those wishing to work with nonparametric methods who want to avoid resorting to programming in C or Fortran but need the speed of compiled code as opposed to interpreted code such as Gauss or Matlab by way of example. We encourage those working in the field to strongly consider implementing their methods in the R environment thereby making their work accessible to the widest possible audience via an open collaborative forum.

There is a growing literature in nonparametric econometrics in the recent two decades. Given the space limitation, it is impossible to survey all the important recent developments in nonparametric econometrics. Therefore, we choose to limit our focus on the following areas. In Section 2, we review the recent developments of nonparametric estimation and testing of regression functions with mixed discrete and continuous covariates. We discuss nonparametric estimation and testing of econometric models for nonstationary data in Section 3. Section 4 is devoted to surveying the literature of nonparametric instrumental variable (IV) models. We review nonparametric estimation of quantile regression models in Section 5. In Sections 2–5, we also point out some open research problems, which might be useful for graduate students to review the important research papers in this field and to search for their own research interests, particularly dissertation topics for doctoral students. Finally, in Section 6 we highlight some important research areas that are not covered in this paper due to space limitation. We plan to write a separate survey paper to discuss some of the omitted topics.

We formulate generalized maximum entropy estimators for the general linear model and the censored regression model when there is first order spatial autoregression in the dependent variable. Monte Carlo experiments are provided to compare the performance of spatial entropy estimators relative to classical estimators. Finally, the estimators are applied to an illustrative model allocating agricultural disaster payments.

Branching is one of the crucial strategic non-price actions for banks. Previous studies on the impact of state ownership upon banks focus on bank lending behavior. This paper aims to offer a novel investigation of how state ownership affects bank branching behavior by examining state-controlled commercial banks (SCCBs) in the context of the largest developing and transitional country China.

The two-part model (TPM) is applied to analyze the branching decision process. In the first stage, the dependent variable is the choice of bank branching dynamics and in the second stage the dependent variable is the number of new branches or the number of closed branches. For robustness check, the ordered probit selection model allowing for interdependence of the two stage decisions is also employed.

Using a unique dataset of bank branches in China, this paper finds that the branching decisions of Chinese SCCBs are driven by both profit motivated factors including population size, population density, income level, financial development and banking competition and politically motivated factors as represented with the proportion of SOEs. As a comparison, branching decisions of joint-stock banks in China are fully determined by profit motivated factors.

First, this study is the first to explore the effect of state ownership on bank branching decisions, providing a new insight on the literature regarding to the impact of state ownership on bank decisions. Second, this study explores the potential effect of politically motivated factors on bank branching decisions, filling the gap in bank branching literature. Third, this study can contribute to bank branching literature by enriching the limited understanding of how SCCBs make branching decisions. Lastly, this study applies novel empirical strategies to analyze bank branching decisions, including the TPM and the ordered probit selection model.