Kevin Albertson

Payment by results and social impact bonds in the criminal justice sector: new challenges for the concept of evidence-based policy?

Payment by results allows the government to pay a provider of services on the basis of the outcomes their service achieves rather than the inputs or outputs the provider delivers. Social impact bonds (SIBs) are a form of payment by results which allow the financing of social outcomes via private investment. It is suggested that payment by results and SIBs will drive greater efficiency, innovation and impact in tackling social problems through focusing reward on outcomes and providing minimal prescription as to how these outcomes should be achieved. It is suggested that this may be achieved while also reducing risk for government. Here we set out the challenges likely to arise in developing payment by results models and SIBs in the criminal justice system of England and Wales. These include the uncertainty arising from defining outcomes, estimating the potential impact of interventions, measuring and attributing change, valuing benefits, demonstrating a fiscal return and getting interventions to scale. We conclude that, to a government trying to deliver ‘more for less’, payment by results may offer an attractive solution in some parts of the public sector. However, the case for this approach in the criminal justice sector, where the evidence base is contested and potential savings difficult to quantify and realize, is not yet proven.

Social innovation, an answer to contemporary societal challenges? Locating the concept in theory and practice

Social innovation discourses see in social challenges opportunities to make societies more sustainable and cohesive through inclusive practices, coproduction and pro-active grassroots initiatives. In this paper we are concerned first that the concept has been stretched in so many directions that it is at breaking point. We illustrate this by documenting the varied uses of social innovation in different academic and policy discourses. Second, we assume that, if social innovation is to be a useful concept for policy-makers, then it must tell us something about what adjustments are needed to develop an effective political economy that is social innovation ready. Finally, we argue that what is needed is more theoretical and empirical work to help social innovation to develop into an effective policy tool.

Forecasting the outbreak of moorland wildfires in the English Peak District

Warmer, drier summers brought by climate change increase the potential risk of wildfires on the moorland of the Peak District of northern England. Fires are costly to fight, damage the ecosystem, harm water catchments, cause erosion scars and disrupt transport. Fires release carbon dioxide to the atmosphere. Accurate forecasts of the timing of fires help deployment of fire fighting resources. A probit model is used to assess the chance of fires at different times of the year, days of the week and under various weather conditions. Current and past rainfall damp fire risk. The likelihood of fire increases with maximum temperature. Dry spells or recent fire activity also signal extra fire hazard. Certain days are fire prone due to visitors and some months of the year are more risky reflecting the changing flammability of moorland vegetation. The model back-predicts earlier fires during a hot dry summer. The impact of climate change on fire incidence is not straightforward. Risks may be reduced if wetter winters and earlier onset of spring add to plant moisture content. Yet a warm spring increases biomass and potential fuel load in summer. Climate change may cause the timing of moorland wildfires to shift from a damper and more verdant spring to drought-stressed summer.

Forecasting the behaviour of manufacturing inventory

Forecasting levels of stocks held by manufacturing industry is problematic. Stocks are the most volatile component of GDP. The data itself is subject to chronic revision. Yet, forecasting inventory changes in the supply chain is crucial for firms trying to manage output. The paper reports a successful approach to forecasting UK manufacturing stock behaviour sponsored by a leading European metals manufacturer. The model exploits the seasonality of stock build-ups and run-downs. (Existing econometric approaches rely on seasonally adjusted data.) The forecasting performance of our model is compared to alternative time series approaches. Use of raw, unadjusted data implies markedly different specifications from those in the established literature. In particular, we find no significant evidence of a structural break in UK stockholding behaviour in our sample period and the absence of cointegration between stocks and output suggests the conventional error correction approach is spurious, as well as giving poor forecasts.

Modelling the Great Lakes Freeze: forecasting and seasonality in the market for ferrous scrap

Abstract The paper offers a methodology for modelling seasonality in a volatile commodity market. It gives a practical example of the way seasonal factors can be incorporated into industrial forecasts. Recycled ferrous scrap is a widely traded commodity used in the steel and foundry industries. This paper considers the problems of forecasting scrap prices in the US market. Scrap prices display seasonal behaviour as a result of weather and patterns of industrial production. We consider various ways of modelling this seasonality, use of seasonal vector autoregression, the concept of seasonal integration and the use of dummy variables. A seasonal vector autoregression (VAR) is developed. Here the quarterly series is decomposed into four annual series, one for each quarter. We regress each of these resultant series on its own lags and lags of other series, so developing a periodic autoregressive model. A series of tests enables us to determine the type of seasonality exhibited by the data. The simplest form of seasonal adjustment using seasonal dummy variables turns out to be the best for forecasting US scrap prices. Use of the test procedure suggests that employing seasonal dummies is the correct specification in this case. Inclusion of seasonal effects usually improves the estimation and forecasting performance of time series models. Comparison of a range of alternative forecasting models suggests a periodic autoregression only forecasts satisfactorily in the short run. ARIMA models with seasonal dummies show the best performance. A long lag length is necessary to capture long run cyclical effects.

Is payment by results the most efficient way to address the challenges faced by the criminal justice sector

In recent years the UK government has emphasized evidence-based policy, as a part of which the Payment by Results (PbR) approach has increasingly been promoted. Payment by Results allows the government to pay a provider of services on the basis of specified outcomes achieved rather than the inputs or outputs delivered. Linked to PbR is the innovative source of funding social interventions know as Social Impact Bonds (SIBs). We discuss the potential benefits of PbR and survey its use across the UK public sector. Then, concentrating in particular on the Criminal Justice System (CJS) we outline three methodological challenges to the implementation of PbR: gaming, measuring outcomes and identifying fiscal benefits. We then identify a number of challenges to the implementation of PbR. We conclude that PbR has a place in commissioning services, but that its role in the CJS is likely to be limited and unlikely to succeed as a socially efficient means of attracting new sources of funding. We finish by considering two alternatives to PbR: justice reinvestment and personalization.

Justice Reinvestment: Can it Deliver More for Less?

Recent years have seen high levels of public spending on criminal justice but to relatively little effect. Prison numbers have risen sharply and public confidence in the criminal justice system remains relatively low. Although crime has fallen there is limited evidence to suggest that this is because of increased criminal justice activity. Justice reinvestment (JR) is a concept that has been widely touted as an approach that might help UK authorities deliver more for less at a time when public sector spending is being cut. It has been used widely in the USA with seemingly promising results. Although elements of JR have been tried in the UK, a full-scale implementation has yet to be attempted. Such an attempt will have to give careful consideration to a variety of practical implementation challenges and methodological issues which range from the potential unification and devolution of criminal justice budgets, to the transferability of a predominantly USA-originating evidence base to the UK. This article identifies a number of such issues and attempts to set out an agenda for academic discourse on JR.

Crime and Economics : An Introduction

The economics of crime is an area of growing activity and concern, increasingly influential both to the study of crime and criminal justice and to the formulation of crime reduction and criminal justice policy. As well as providing an overview of the relationship between economics and crime, this book poses key questions such as: What is the impact of the labour market and poverty on crime? Can society decrease criminal activity from a basis of economic disincentives? What forms of crime reduction and methods of reducing re-offending are most cost beneficial? Can illicit organised crime and illicit drug markets be understood better through the application of economic analysis? For those interested in economic methods, but without previous economic training, this book also provides an accessible overview of key areas such as cost-benefit analysis, econometrics and the debate around how to estimate the costs of crime.

Justice reinvestment : can the criminal justice system deliver more for less?

1. Introduction, 2. Rising prison numbers: the key challenge for criminal justice policy, 3. Justice Reinvestment overview, 4. A new approach to criminal justice policy, 5. Justice mapping, 6. Justice Reinvestment and evidence-based policy, 7. The economics of criminal justice policy, 8. New ways of financing criminal justice interventions: Payment by results and Social Impact Bonds, 9. Conclusion.

Could economics solve the prison crisis

This article considers important developments over the last decade which have laid the foundations for a new approach to criminal justice policy; an approach in which economic analysis is central. These developments include aspects of the policy debate on sentencing; the government’s commitment to evidence-based policy; investment in the economics profession across government; and the rise of the Justice Reinvestment movement. While many of the opportunities presented for economic analysis of sentencing policy have not yet been exploited, there is reason to believe that they will be over the next few years. Various reasons are discussed including the current economic situation, which makes increasingly untenable the continuing commitment of government to increasing prison capacity without consideration of more efficient alternatives. The article concludes by suggesting some steps that the new government might take to ensure that the benefits of an economically efficient approach to criminal justice policy are realized.