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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.

Several popular and academic pieces of late have expressed concerns regarding the sustainability of public defined benefit pension funds. Since the onset of the Great Recession, concern has increased. In this paper recent arguments are analyzed in the context of three related data sets: panel data on public sector pensions spanning 2001-2009, historic asset return data, and business cycle data. Findings generally indicate that while public sector plans have suffered a difficult decade, current anxieties may be somewhat overwrought. Several remedial policies are investigated. Remedial policies, such as improving plan administration, altering portfolio allocations, and increasing both employee and employer contributions, are observed to be more promising than either freezing or closing the funds.

This study aims at evaluating the technical efficiency (TE) of healthcare systems in the Arab region and exploring the key factors that affect the efficiency performance.

The study applies a two-stage Data Envelopment Analysis (DEA) approach to a sample of 20 Arab countries. In the first stage, a DEA model is used to calculate the TE scores of the examined healthcare systems in 2019 and 2010, following both the output and input orientations of efficiency. In the second stage, a censored Tobit model is estimated to investigate the determinants of healthcare efficiency.

DEA results of 2019 indicate that achievable efficiency gains of the Arab countries range from 0.4% to 16% under the output and input orientations, respectively. Six countries are efficient under both orientations. Although the average efficiency scores of the Arab countries have deteriorated between 2010 and 2019, Djibouti and Sudan had the greatest efficiency improvements between the two years. Bahrain, Mauritania, Morocco and Qatar proved to be efficient in 2010 and 2019 under the two orientations of efficiency and according to the two DEA specifications followed. The Tobit model reveals that corruption and government health expenditure tend to have an adverse impact on healthcare efficiency.

The author evaluates healthcare efficiency and healthcare's efficiency determinants in the Arab countries. Regardless Arab countries' diversity, these countries are facing common health challenges, including diminishing role of governments in healthcare financing; increased out-of-pocket healthcare spending; poor healthcare outputs and prevalence of health inequities resulting from weak governance institutions. Comparing the efficiency of healthcare systems between 2010 and 2019 gives insights on the potential impact of the Arab spring uprisings on healthcare efficiency. Moreover, examining the determinants of healthcare efficiency allows for better understanding of how to improve the efficiency of healthcare systems in the region.

The purpose of this study is to enhance understanding labour supply dynamics of the UK workers by examining whether and to what extent there is state dependence in the labour supply at both the extensive and intensive margins.

A dynamic two-tiered Tobit model is applied to the first seven waves of Understanding Society: the UK Household Longitudinal Study. The model used accounts for observed and unobserved individual heterogeneity and serially correlated transitory shocks to labour supply to draw inferences on state dependence.

The results show that both observed and unobserved individual heterogeneity contributes to observed inter-temporal persistence of the labour supply of the UK workers, and the persistence remains after these factors are controlled for, suggesting true state dependence at both the extensive and intensive margins of the labour supply. The study also finds that at both the margins, the state dependence of labour supply is larger for females than for males and that for both genders the state dependence is larger for people with low education, mature aged workers and people with long-standing illness or impairment. The results also show that estimates from a conventional Tobit model may produce misleading inferences regarding labour supply at the extensive and intensive margins.

This study adds to the international literature on labour supply dynamics by providing empirical evidence for both the extensive and intensive margins of labour supply, while previous studies tend to focus on the extensive margin of labour force participation only. Also, unlike earlier studies that often focus on females, this study compares labour supply dynamics between males and females. The study also compares the estimates from the more flexible two-tiered Tobit model with that from the conventional Tobit model.

The purpose of this paper is not only to gauge the extent of technical efficiency in 31 state road transport undertakings (SRTUs) operating in India but also to explore the most influential factors explaining its variations across SRTUs.

Three popular data envelopment analysis (DEA) models, namely CCR, BCC and Andersen and Petersen's super‐efficiency models, have been utilized to compute various efficiency scores for individual SRTUs. A censored Tobit analysis is conducted to see which factors significantly explain the inter‐SRTU variations in efficiency.

The key findings of the DEA analysis are only five SRTUs define the efficient frontier, and the remaining 26 inefficient undertakings have a scope of inputs reduction, albeit by the different magnitude; the extent of average overall technical inefficiency (OTIE) in these SRTUs is to the tune of 22.8 percent, indicating that the sample SRTUs are wasting about one‐fourth of their resources in the production operations; managerial inefficiency (as captured by the pure technical inefficiency) is a relatively more dominant source of OTIE; and operation in the zone of increasing returns‐to‐scale is a common feature for most of the undertakings. The multivariate regression analysis using Tobit analysis highlights that the occupancy ratio is the most significant determinant for all the efficiency measures, and bears a positive relationship with overall technical, pure technical and scale efficiencies. Further, scale efficiency is also impacted positively by the staff productivity.

The results of this paper can be applied from management's perspective. The managers can assess the relative efficiency of their SRTUs in the industry and take corrective measures to improve efficiency by altering input‐output mix.

This paper provides more robust estimates of relative efficiency of the SRTUs and highlights the key determinants of overall technical efficiency.

The aim of this paper is to study the technical and scale efficiency of a set of tax offices (Inland Revenue) in Greece during the period 2001‐2006.

The methodology used to estimate efficiency scores and Greek tax office ranking was the data envelopment analysis. In addition window analysis was used to detect efficiency trends and stability over time. Tobit analysis was applied to explain whether non‐discretionary factors play a role in tax office's performance.

The results underline that “scale size” and the structure of regional economy where tax offices operate are important factors affecting their efficiency.

Despite the limitations related to the data set, the empirical work suggests that future research may need to concentrate on the dynamic factors i.e. characteristics of the regional where the tax office is situated which could play a significant role in a tax office performance.

The analysis provides information on tailor‐made political and administrative measures that can lead to improvements in the general infrastructure behind the tax office system in Greece.

Considering that the emerging results needed to be evaluated and considered with a sceptical eye, the present study simply highlights the importance of the information (without sensationalizing it) from the policymakers' perspective and in so doing perhaps provide an additional information resource on which they can base their decisions and policies.

The purpose of this paper is to find ways to develop more efficient mass transit systems across the USA and, thus, make the best use of state/federal/municipal government funds and taxpayers’ monies. This paper conducts benchmarking studies. In doing so, this paper identifies the best-in class mass transit practices that every regional mass transit system can emulate.

The continuous underutilization of a mass transit system can increase public scrutiny concerning the increased investment in mass transit services. To defuse such scrutiny, this paper analyzes the past (in year 2011) performances of 515 mass transit agencies in the USA using data envelopment analysis (DEA). Also, to identify which factors influences those performances, the authors paired DEA scores for transit efficiency at the state level against a set of independent variables using a special form of regression analysis called Tobit regression.

The authors found that the greater population density of the service area, the greater number of riders can be served in a short amount of distance and time. Also, the authors discovered that the transportation mode of mass transit services could affect mass transit efficiency. On the other hand, the authors found no evidence indicating that the public ownership or private operation of transit systems could make any differences in the transit efficiency.

This paper is one of the few that assessed the performance of mass transit systems in comparison to their peers using a large-scale data and identify the leading causes of mass transit inefficiency. Thus, this paper helps transit authorities in handling juggling acts of protecting the conflicting interests of government policy makers against the general public and, then, make sensible future investment decisions.

This paper aims to examine the level of Islamic social reporting (ISR) disclosure of Islamic banking in Gulf Cooperative Council (GCC) countries using a checklist based on Accounting and Auditing Organization for Islamic Financial Institution (AAOIFI) standards.

A quantitative method – Tobit Model – is adopted in this study. The unweighted disclosure method used to measure the ISR disclosure checklist consist of 51 items in Islamic banks (IBs) in the GCC countries. The stakeholder theory and legitimacy theory are used to investigate the possible banking performance factors affecting the accounting practices such as ISR disclosure in IBs.

The findings show that the ISR disclosure index is linked to the IBs’ performance indicators in GCC countries. The result indicates both Islamic banking profitability and age establish positive and statistically significant relationship with ISR disclosure while leverage establishes significant negative relationship with ISR disclosure. This implies that Islamic banking profitability, leverage, and age are essential bank performance indicators that make ISR disclosure worthy of doing even in the presence of Islamic bank stakeholders in GCC countries. This finding linked compliance with the mandatory disclosure recommendations of AAOIFI Standard No. 7, as well as voluntary disclosure.

This study used cross sectional data for the year 2019, which is considered more recent despite its being a year data analysis. However, future research should consider mix method as well as more analysis tools provided their number of observations are sufficient enough.

The study identifies the factors that may enhance Islamic financial institutions, including Islamic banking in GCC countries, to comply with ISR disclosure. The application of this study supports Accounting standards setters to consider standards that support ISR disclosure in Islamic banking in different countries.

To the best of the authors’ knowledge, this study is novel in exploring the level of ISR disclosure in Islamic banking in GCC countries by using a checklist based on AAOIFI standard No. 7 and establishes the relationship between ISR disclosure index and IBs profitability, leverage, as well as age of Islamic banking in operation.

The purpose of this study is to investigate gender-based punishment bias in the type and severity of punishments imposed on a male-dominated profession using the accounting profession as a proxy.

Data were hand-collected from the population of certified public accountants disciplined for violations of the Code of Professional Conduct. Disciplinary actions were obtained from the American Institute of Certified Public Accountant’s website. A total of 404 observations were obtained for the study over a five-year period from January 2009 through June 2015, comprising the population of the captured infractions committed during this time frame.

Women are punished more harshly than men for equivalent infractions; the disparity in punishment between women and men increases with the severity of the infraction.

This paper answers the call by Wren (2006) for an increased examination of workplace punishment’s relationship to gender using real-world scenarios and data. This study provides empirical evidence of the gender-based punishment bias, which calls into question the neutrality of workplace punishment as executed by a male-dominated profession.

The purpose of this paper is to assess the benefits to firms arising from their geographical concentration; paying particular attention to the impact of specialized employees, information and knowledge spillovers and a collective reputation.

The authors have taken into account two main approaches: a cluster one, where location may increase firms’ competitiveness; and the resource-based view, where internal resources are the key for firms’ success. Empirical evidence has been gathered from the Ham cluster in Spain combining secondary and primary data. The authors undertook a Tobit regression model since the dependent variable is limited.

The authors observe that firms with human resources tend to benefit more from cluster externalities. On contrary, R&D and advertising investments induce firms to isolate themselves from crowded areas and prevent any local leakage.

It would be interesting to better understand the role that human resources play; undertake a longitudinal analysis; and take into account the resources of other proximate firms.

Local advantages depends the maturity of the industry by reducing the attractiveness of cluster locations through greater competition in the input and final markets; while internal resources may improve a firm's ability to absorb these externalities, they may also create leakage that benefits neighbouring firms.

It combines two approaches evaluating the moderating influence of internal resources on local externalities. It also offers new empirical evidence from a low-tech industry.