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Decreases in stock market returns often lead to higher increases in volatility than increases in returns of the same magnitude, and it is common to incorporate these so-called leverage effects in GARCH and stochastic volatility models. Recent research has also found it useful to account for leverage in models of realized volatility, as well as in models of the continuous and jump components of realized volatility. This paper explores the use of smooth transition autoregressive (STAR) models for capturing leverage effects in multiple series of the continuous components of realized volatility. We find that the leverage effect is well captured by a common nonlinear factor driven by returns, even though the persistence in each country’s volatility is country specific. A three country model that incorporates both country specific persistence and a common leverage effect offers slight forecast improvements for mid-range horizons, relative to other models that do not allow for the common nonlinearity.

This paper examines real exchange rate responses to shocks in exchange rate determinants for fourteen Asian developing countries. The analysis is based on a panel structural vector error correction model, and the shocks are identified using sign and zero restrictions. We find that trade liberalization generates permanent depreciation, and higher government consumption causes persistent appreciation. Traded-sector productivity gains induce appreciation but their effects are not immediate and last only for a few years. Real exchange rate responses to unexpected monetary tightening are consistent with the long-run neutrality of money. The evidence suggests that trade liberalization and government consumption have a strong effect on real exchange rates, while the effects of traded-sector productivity shocks are much weaker.

This paper proposes two new weighting schemes that average forecasts using different estimation windows to account for structural change. We let the weights reflect the probability of each time point being the most-recent break point, and we use the reversed ordered Cusum test statistics to capture this intuition. The second weighting method simply imposes heavier weights on those forecasts that use more recent information. The proposed combination forecasts are evaluated using Monte Carlo techniques, and we compare them with forecasts based on other methods that try to account for structural change, including average forecasts weighted by past forecasting performance and techniques that first estimate a break point and then forecast using the post break data. Simulation results show that our proposed weighting methods often outperform the others in the presence of structural breaks. An empirical application based on a NAIRU Phillips curve model for the United States indicates that it is possible to outperform the random walk forecasting model when we employ forecasting methods that account for break uncertainty.

This paper proposes a new test for simultaneous intraday jumps in a panel of high frequency financial data. We utilize intraday first-high-low-last values of asset prices to construct estimates for the cross-variation of returns in a large panel of high frequency financial data, and then employ these estimates to provide a first-high-low-last price based test statistic to detect common large discrete movements (co-jumps). We study the finite sample behavior of our first-high-low-last price based test using Monte Carlo simulation, and find that it is more powerful than the Bollerslev et al (2008) return-based co-jump test. When applied to a panel of high frequency data from the Chinese mainland stock market, our first-high-low-last price based test identifies more common jumps than the return-based test in this emerging market.

The 2011 Clean Energy Act sought to align Australia's carbon pricing to the 2005 European Union Emission Trading Scheme (EU-ETS) by 2015, but this act was repealed in 2014. We estimate the hypothetical impact of Australia adopting an emissions trading policy in 2005, which corresponds with the establishment of the EU-ETS. We use a synthetic treatment approach that constructs a counterfactual measure of Australian carbon emissions that makes use of the time series properties of pre-2005 and post-2005 emissions in European countries. We find that Australian per-capita carbon emissions would have been lower by about 4.5% as a result of the policy -- a result that is robust to several variations of our methodology.

This paper proposes a new Bayesian approach for analysing moment condition models in

In the aftermath of the covid-19 pandemic, the prevention of further decline in aggregate employment and turning it around are high on the agenda of policymakers. To this end, it is imperative to have a disaggregated model of employment, given the unequal effects of covid-19 on employment in different sectors of the economy. In this paper we develop a multivariate time series model of employment in 19 sectors of the Australian economy. We provide the predictions of this model conditional on various scenarios that are based on the most recent quantitative information about sectoral employment in Australia. We estimate that the drop in total employment in the second quarter of 2020 will be in between 7 and 13 percentage points, compared to the second quarter of 2019. We also use this model to determine the long-run effect of a 1% increase in economic activity in any chosen sector on aggregate employment. Our findings point to manufacturing and construction sectors as those that might generate the largest positive spillovers for the rest of the economy. Moreover, we provide an interactive web-based app as well as an interactive spreadsheet that produce our model's 5-year forecasts based on any user-specified scenario for the current and following three quarters. As the covid-19 pandemic evolves and some restrictions are safely lifted or other restrictions become necessary, the sectoral employment multipliers together with the interactive tools produced here will provide useful information for policymakers.

This paper investigates international responses of key macroeconomic variables, particularly real exchange rates, to simultaneous shocks to productivity in the traded sector in eight Asian emerging and developing countries. We use panel estimation techniques to construct component submodels in a thirty country global vector autoregressive (GVAR) model. The GVAR approach can account for interaction among all countries and capture many potential international transmission channels. We identify the shocks by using sign restricted impulse responses. We find that increases in traded-sector productivity in Asian developing countries lead to a real appreciation of the domestic currencies, in line with the Balassa-Samuelson hypothesis. Inflation also increases in many Asian developing countries. After the shocks, nontraded sector productivity in the US and other developed countries increases, suggesting that there is a compositional shift in their production, away from the traded goods toward the nontraded goods. This allows productivity in the nontraded sector to increase. Further, the traded sector productivity shocks in Asia stimulate international trade in most countries.

BackgroundBiopsy remains the gold standard for determining fibrosis stage in patients with primary biliary cholangitis (PBC), but it is unavailable for most patients. We used data from the 11 US health systems in the FibrOtic Liver Disease Consortium to explore a combination of biochemical markers and electronic health record (EHR)-based diagnosis/procedure codes (DPCs) to identify the presence of cirrhosis in PBC patients.MethodsHistological fibrosis staging data were obtained from liver biopsies. Variables considered for the model included demographics (age, gender, race, ethnicity), total bilirubin, alkaline phosphatase, albumin, aspartate aminotransferase (AST) to platelet ratio index (APRI), Fibrosis 4 (FIB4) index, AST to alanine aminotransferase (ALT) ratio, and >100 DPCs associated with cirrhosis/decompensated cirrhosis, categorized into ten clusters. Using least absolute shrinkage and selection operator regression (LASSO), we derived and validated cutoffs for identifying cirrhosis.ResultsAmong 4328 PBC patients, 1350 (32%) had biopsy data; 121 (9%) were staged F4 (cirrhosis). DPC clusters (including codes related to cirrhosis and hepatocellular carcinoma diagnoses/procedures), Hispanic ethnicity, ALP, AST/ALT ratio, and total bilirubin were retained in the final model (AUROC=0.86 and 0.83 on learning and testing data, respectively); this model with two cutoffs divided patients into three categories (no cirrhosis, indeterminate, and cirrhosis) with specificities of 81.8% (for no cirrhosis) and 80.3% (for cirrhosis). A model excluding DPCs retained ALP, AST/ALT ratio, total bilirubin, Hispanic ethnicity, and gender (AUROC=0.81 and 0.78 on learning and testing data, respectively).ConclusionAn algorithm using laboratory results and DPCs can categorize a majority of PBC patients as cirrhotic or noncirrhotic with high accuracy (with a small remaining group of patients' cirrhosis status indeterminate). In the absence of biopsy data, this EHR-based model can be used to identify cirrhosis in cohorts of PBC patients for research and/or clinical follow-up.

Alzheimer's Disease Neuroimaging Initiative., [Objective] To study the neuropathologic correlates of cholinergic basal forebrain (BF) atrophy as determined using antemortem MRI in the Alzheimer disease (AD) spectrum., [Methods] We determined associations between BF volume from antemortem MRI brain scans and postmortem assessment of neuropathologic features, including neuritic plaques, neurofibrillary tangles (NFTs), Lewy body (LB) pathology, and TDP-43, in 64 cases of the Alzheimer's Disease Neuroimaging Initiative cohort. For comparison, we assessed neuropathologic features associated with hippocampal and parahippocampal gyrus atrophy. In addition to region of interest–based analysis, we determined the association of neuropathologic features with whole brain gray matter volume using regionally unbiased voxel-based volumetry., [Results] BF atrophy was associated with Thal amyloid phases (95% confidence interval [CI] −0.49 to −0.01, p = 0.049) and presence of LB pathology (95% CI −0.54 to −0.06, p = 0.015), as well as with the degree of LB pathology within the nucleus basalis Meynert (95% CI −0.54 to −0.07, p = 0.025). These effects were no longer significant after false discovery rate (FDR) correction. Hippocampal atrophy was significantly associated with the presence of TDP-43 pathology (95% CI −0.61 to −0.17, p = 0.003; surviving FDR correction), in addition to dentate gyrus NFT load (95% CI −0.49 to −0.01, p = 0.044; uncorrected). Voxel-based analysis confirmed spatially restricted effects of Thal phases and presence of LB pathology on BF volume., [Conclusions] These findings indicate that neuropathologic correlates of regional atrophy differ substantially between different brain regions that are typically involved in AD-related neurodegeneration, including different susceptibilities to common comorbid pathologies., M.J.G. is supported by the “Miguel Servet” program [CP19/00031] of the Spanish Instituto de Salud Carlos III (ISCIII-FEDER).

This paper proposes a new Bayesian approach for analysing moment condition models in the situation where the data may be contaminated by outliers. The approach builds upon the foundations developed by Schennach (2005) who proposed the Bayesian exponentially tilted empirical likelihood (BETEL) method, justified by the fact that an empirical likelihood (EL) can be interpreted as the nonparametric limit of a Bayesian procedure when the implied probabilities are obtained from maximizing entropy subject to some given moment constraints. Considering the impact that outliers are thought to have on the estimation of population moments, we develop a new robust BETEL (RBETEL) inferential methodology to deal with this potential problem. We show how the BETEL methods are linked to the recent work of Bissiri, Holmes and Walker (2016) who propose a general framework to update prior belief via a loss function. A controlled simulation experiment is conducted to investigate the performance of the RBETEL method. We find that the proposed methodology produces reliable posterior inference for the fundamental relationships that are embedded in the majority of the data, even when outliers are present. The method is also illustrated in an empirical study relating brain weight to body weight using a dataset containing sixty-five different land animal species.

PurposeThe purpose of this article is to evaluate optic nerve head (ONH) characteristics in an ethnically diverse cohort of young U.S. adults.MethodsIn this study, 409 myopes and 206 nonmyopes (median age 22 years) completed measures including biometry and spectral domain optical coherence tomography from enface (ovality and torsion) and cross-sectional (tilt and crescent width) scans. Associated factors were evaluated using multivariable models.ResultsIn myopic versus nonmyopic right eyes, median tilt (6.0° vs. 2.4°; P < 0.0001) and frequency of crescents (49% vs. 10%; P < 0.0001) were higher in myopes. Right eyes with crescents had higher median tilts (8.8° [myopic], 9.0° [nonmyopic]) than those without crescent (2.5° [myopic], 2.1° [nonmyopic]), irrespective of refractive group (both P < 0.0001). Torsion was similar between groups, with a slight difference in ovality (0.89 vs. 0.91; P < 0.03). Data in the left eyes were similar, and modeling was done only for the right myopic eyes. Multivariable models showed that an increased tilt was associated with ethnicity (P < 0.001), the presence of crescent (P < 0.001), and smaller ONH diameter (P < 0.0031), with interactions between ethnicity and crescent (P = 0.002). Specifically, ONH tilt was significantly higher in Asian eyes without crescent (P < 0.0001 for all comparisons), and crescent width was associated with increased tilt in non-Asian eyes (P < 0.02). Crescent width was associated with ethnicity (greatest in Asians) and disc tilt. Interactions were observed between tilt and ethnicity, whereby tilt had a greater effect on crescent width in non-Asian eyes, and crescent width was associated with increased tilt in non-Asian eyes.ConclusionsThe data clarify the influence of ethnicity and myopia on ONH characteristics in young adults and may inform future studies of biomechanical properties or of retinal pathology of the myopic eye.

Objectives:To estimate a regional progression pattern of amyloid deposition from cross-sectional amyloid-sensitive PET data and evaluate its potential for in vivo staging of an individual's amyloid pathology.Methods:Multiregional analysis of florbetapir (18F-AV45)–PET data was used to determine individual amyloid distribution profiles in a sample of 667 participants from the Alzheimer's Disease Neuroimaging Initiative cohort, including cognitively normal older individuals (CN) as well as patients with mild cognitive impairment and Alzheimer disease (AD) dementia. The frequency of regional amyloid positivity across CN individuals was used to construct a 4-stage model of progressing amyloid pathology, and individual distribution profiles were used to evaluate the consistency of this hierarchical stage model across the full cohort.Results:According to a 4-stage model, amyloid deposition begins in temporobasal and frontomedial areas, and successively affects the remaining associative neocortex, primary sensory-motor areas and the medial temporal lobe, and finally the striatum. Amyloid deposition in these brain regions showed a highly consistent hierarchical nesting across participants, where only 2% exhibited distribution profiles that deviated from the staging scheme. The earliest in vivo amyloid stages were mostly missed by conventional dichotomous classification approaches based on global florbetapir-PET signal, but were associated with significantly reduced CSF Aβ42 levels. Advanced in vivo amyloid stages were most frequent in patients with AD and correlated with cognitive impairment in individuals without dementia.Conclusions:The highly consistent regional hierarchy of PET-evidenced amyloid deposition across participants resembles neuropathologic observations and suggests a predictable regional sequence that may be used to stage an individual's progress of amyloid pathology in vivo.

This paper studies the All Ordinaries Index in Australia, and its futures contract known as the Share Price Index. We use a new form of smooth transition model to account for a variety of nonlinearities caused by transaction costs and other market/data imperfections, and given the recent interest in the effects of market automation on price discovery, we focus on how the nonlinear properties of the basis and returns have changed, now that floor trading in the futures contract has been replaced by electronic trading.

We develop nonlinear leading indicator models for GDP growth, with the interest rate spread and growth in M2 as leading indicators. Since policy makers are typically interested in whether or not a recession is imminent, we evaluate these models according to their ability to predict the probability of a recession. Using data for the United States, we find that conditional on the spread, the marginal contribution of M2 growth in predicting recessions is negligible.

This paper studies the relationship between international trade and output fluctuations. We find evidence that the business cycles of countries that are more open to international trade are more likely to be synchronized with the business cycles of their major trading partners. A detailed study of the South Korean case shows that while business cycles are related to openness, the diversification of export destinations seems to weaken these links. We find no relationship between openness and output volatility.

PurposeHigh-quality optical coherence tomography (OCT) macular scans make it possible to distinguish a range of normal and diseased states by characterising foveal pit shape. Existing mathematical models lack the flexibility to capture all known pit variations and thus characterise the pit with limited accuracy. This study aimed to develop a new model that provides a more robust characterisation of individual foveal pit variations.MethodsA Sloped Piecemeal Gaussian (SPG) model, consisting of a linear combination of a tilted line and a piecemeal Gaussian function (two halves of a Gaussian connected by a separate straight line), was developed to fit retinal thickness data with the flexibility to characterise different degrees of pit asymmetry and pit bottom flatness. It fitted the raw pit data between the two rims of the fovea to improve accuracy. The model was tested on 3488 macular scans from both eyes of 581 young adults (376 myopes and 206 non-myopes, mean (S.D.) age 21.9 (1.4)years). Estimates for retinal thickness, wall height and slope, pit depth and width were derived from the best-fitting model curve. Ten variations of Gaussian and Difference of Gaussian models were fitted to the same scans and compared with the SPG model for goodness of fit (by Root mean square error, RMSE), model complexity (by the Bayesian Information Criteria) and model fidelity.ResultsThe SPG model produced excellent goodness of fit (mean RMSE=4.25 and 3.89μm; 95% CI: 4.20, 4.30 and 3.86, 3.93 for fitting horizontal and vertical profiles respectively). The SPG model showed pit asymmetry, with average nasal walls 17.6 (11.6)μm higher and 0.96 (0.61)° steeper than temporal walls and average superior walls 7.0 (12.2)μm higher and 0.41 (0.65)° steeper than the inferior walls. The SPG model also revealed a continuum of human foveal shapes, from round bottoms to extended flat bottoms (up to 563μm). 49.1% of foveal profiles were best fitted with a flat bottom >30μm wide. Compared with the other tested models, the SPG was the preferred model overall based on the Bayesian Information Criteria.ConclusionsThe SPG is a new parsimonious mathematical model that improves upon other models by accounting for wall asymmetry and flat pit bottoms, providing an excellent fit and more faithful characterisation of typical foveal pit shapes and their known variations. This new model may be helpful in distinguishing normal foveal shape variations by refractive status as well by other characteristics such as sex, ethnicity and age.

Objective:To comprehensively assess neurobiological effects of the protective APOE2 allele in the aged brain using a cross-sectional multimodal neuroimaging approach.Methods:Multimodal neuroimaging data were obtained from a total of 572 older individuals without dementia (cognitively normal and mild cognitive impairment) enrolled in the Alzheimer's Disease Neuroimaging Initiative and included assessments of regional amyloid load with AV45-PET, glucose metabolism with fluorodeoxyglucose-PET, and gray matter volume with structural MRI. Imaging indexes of APOE2 carriers were contrasted to risk-neutral APOE3 homozygotes, and analyses were controlled for age, sex, education, and clinical diagnosis. Additional models examined genotype-specific effects of age on the imaging markers.Results:In region-of-interest–based analyses, APOE2 carriers had significantly less precuneal amyloid pathology and did not show the typical age-related increase in amyloid load, although the age × genotype interaction was only trend-level significant. In contrast, parietal metabolism and hippocampal volume did not differ between APOE2 and APOE3 genotypes, and both groups showed comparable negative effects of age on these markers. The amyloid specificity of APOE2-related brain changes was corroborated in 2 complementary analyses: spatially unbiased voxel-wise analyses showing widespread reductions in amyloid deposition but no differences in gray matter volume or metabolism and an analysis of CSF-based biomarkers showing a significant effect on amyloid but not on tau pathology.Conclusions:Regarding the range of Alzheimer disease biomarkers considered in the present study, the APOE2 allele appears to have a relatively selective effect on reduced accumulation of amyloid pathology in the aged brain.

Weight changes are common in aging and Alzheimer's disease (AD) and postmortem findings suggest a relation between lower body mass index (BMI) and increased AD brain pathology. In the current multicenter study, we tested whether lower BMI is associated with higher core AD brain pathology as assessed by cerebrospinal fluid (CSF)-based biological markers of AD in 751 living subjects: 308 patients with AD, 296 subjects with amnestic mild cognitive impairment (MCI), and 147 elderly healthy controls (HC). Based upon a priori cutoff values on CSF concentration of total tau and beta-amyloid (Aβ(1-42)), subjects were binarized into a group with abnormal CSF biomarker signature (CSF+) and those without (CSF-). Results showed that BMI was significantly lower in the CSF+ when compared with the CSF- group (F = 27.7, df = 746, p0.001). There was no interaction between CSF signature and diagnosis or apolipoprotein E (ApoE) genotype. In conclusion, lower BMI is indicative of AD pathology as assessed with CSF-based biomarkers in demented and nondemented elderly subjects.

Transportation has consistently been the largest barrier for homeless students to overcome to staying in school. With family homelessness on the rise nationally, the provision of transportation services for homeless students is an important protection of the right to public education for homeless youth, and an effort to provide students with the most stable and academically supportive option. This study aims to investigate the successes and continuing challenges in homeless student transportation services at the city-scale (Los Angeles County) in order to contribute to a national discourse on prevention of further hardship for a growing number of youth. Secondary data analysis describes the context of the issue, while surveys and interviews with school district employees reveal the solutions born of these factors and explore the dynamics of coordination and the actors involved. Public transportation is the most cited mode of transportation for children and youth to school. Frequent residential mobility and difficulty getting in touch with parents are the biggest challenges to transportation coordination. District Liaisons interact with multiple agencies in the coordination of transportation, through communication, collaboration and conducting outreach. Although the survey responses are promising in what they communicate about educational access, recommendations for improving conditions are outlined.

Social enterprises are diverse in their mission, business structures and industry orientations. Like all businesses, social enterprises face a range of strategic and operational challenges and utilize a range of strategies to access resources in support of their venture. This exploratory study examined the strategic management issues faced by Australian social enterprises and the ways in which they respond to these. The research was based on a comprehensive literature review and semi-structured interviews with 11 representatives of eight social enterprises based in Victoria and Queensland. The sample included mature social enterprises and those within two years of start-up. In addition to the research report, the outputs of the project include a series of six short documentaries, which are available on YouTube at http://www.youtube.com/user/SocialEnterpriseQUT#p/u. The research reported on here suggests that social enterprises are sophisticated in utilizing processes of network bricolage (Baker et al. 2003) to mobilize resources in support of their goals. Access to network resources can be both enabling and constraining as social enterprises mature. In terms of the use of formal business planning strategies, all participating social enterprises had utilized these either at the outset or the point of maturation of their business operations. These planning activities were used to support internal operations, to provide a mechanism for managing collective entrepreneurship, and to communicate to external stakeholders about the legitimacy and performance of the social enterprises. Further research is required to assess the impacts of such planning activities, and the ways in which they are used over time. Business structures and governance arrangements varied amongst participating enterprises according to: mission and values; capital needs; and the experiences and culture of founding organizations and individuals. In different ways, participants indicated that business structures and governance arrangements are important ways of conferring legitimacy on social enterprise, by signifying responsible business practice and strong social purpose to both external and internal stakeholders. Almost all participants in the study described ongoing tensions in balancing social purpose and business objectives. It is not clear, however, whether these tensions were problematic (in the sense of eroding mission or business opportunities) or productive (in the sense of strengthening mission and business practices through iterative processes of reflection and action). Longitudinal research on the ways in which social enterprises negotiate mission fulfillment and business sustainability would enhance our knowledge in this area. Finally, despite growing emphasis on measuring social impact amongst institutions, including governments and philanthropy, that influence the operating environment of social enterprise, relatively little priority was placed on this activity. The participants in our study noted the complexities of effectively measuring social impact, as well as the operational difficulties of undertaking such measurement within the day to day realities of running small to medium businesses. It is clear that impact measurement remains a vexed issue for a number of our respondents. This study suggests that both the value and practicality of social impact measurement require further debate and critically informed evidence, if impact measurement is to benefit social enterprises and the communities they serve.

The forms social enterprises can take and the industries they operate in are so many and various that it has always been a challenge to define, find and count social enterprises. In 2009 Social Traders partnered with the Australian Centre for Philanthropy and Nonprofit Studies (ACPNS) at Queensland University of Technology to define social enterprise and, for the first time in Australia, to identify and map the social enterprise sector: its scope, its variety of forms, its reasons for trading, its financial dimensions, and the individuals and communities social enterprises aim to benefit.

In this paper, we consider the introduction of Markov-switching (MS) processes to both the permanent and transitory components of the Beveridge-Nelson (BN) decomposition. This new class of MS models within the context of BN decomposition provides an alternative framework in the study of business cycle asymmetry. Our approach incorporates Markov switching into a BN decomposition formulated in a single source of error state-space form, allowing regime switches in the long-run multiplier as well as in the short-run parameters.

This paper proposes neural network based measures of predictability in conditional mean, and then uses them to construct nonlinear analogues to autocorrelograms and partial autocorrelograms. In contrast to other measures of nonlinear dependence that rely on nonparametric estimation of densities or multivariate integration, our autocorrelograms are simple to calculate and appear to work well in relatively small samples.

Given that it is quite impractical to use standard model selection criteria in a nonlinear modeling context, the builders of nonlinear models often choose lag length by setting it equal to the lag length chosen for a linear autoregression of the data. This paper studies the performance of this procedure in a variety of circumstances, and then proposes some new and simple model selection procedures, based on linear approximations of the nonlinear forms. The idea here is to apply standard selection criteria to these linear approximations, rather than to autoregressions that make no provision for nonlinear behavior. A simulation study compares the properties of these proposed procedures with the properties of linear selection procedures.

The Australian community radio sector has played an important role in the social movement of media democratization, both locally and more broadly, however, little attention has been paid to this sector as a social movement. This research maps the organizational history of Brisbane community radio station, 4ZZZ, to examine the impacts of institutionalism on the station, viewed as a social movement organization (SMO). It argues that while SMOs typically move from an oppositional position of protest to one that is increasingly institutional, this does not necessarily dilute the effectiveness of SMOs over time. Refereed/Peer-reviewed

There is a nexus where radio and prisons meet that is yet to be explored to its full potential,both in practice and in academia. This article consolidates two separate bodies of knowledge,examining ‘prisoners’ radio’ (usually broadcast to the general public on community radio or the Internet) and ‘prison radio’ (broadcast to a prison audience within a prison setting), to propose a theoretical framework that incorporates both. It draws on two case studies from the United Kingdom and Australia and is informed by the seminal work of alternative media theorists Clemencia Rodriguez, John Downing and Chris Atton. Refereed/Peer-reviewed

This article examines the connections between prisoners' radio and community, drawing on a case study of an annual Indigenous prisoners' radio project from Melbourne, Australia called Beyond the Bars, coordinated by community radio station 3CR. It demonstrates that an important aspect of prisoners' radio is its ability, as a media form, to sustain relationships between those inside and outside of incarceration, and as a result maintain community connections. The success of Beyond the Bars as a whole can be attributed in part to the special relationship forged between the local Indigenous community and the radio station itself, which has featured over 30 years of Indigenous broadcasting. Refereed/Peer-reviewed

Defining prisoners' radio programming is no easy task. The most important element to note is that programming broadcasts outside of prison. Prison radio does exist inside prison confines; however, this research focuses on programs that broadcast to the wider community, as it is this connection to the “outside world” that strengthens the empowering nature of prisoners' engagement in media production. This article connects prisoners' radio production with notions of active citizenship. While the concept of citizenship is highly relevant to alternative media practice, the issues are compounded when we consider prisoners because of their tenuous position as citizens. Refereed/Peer-reviewed