After the publication of the Government’s ‘Levelling Up’ White Paper, this paper reviews the role of institutions and governance structures across English regions in tackling spatial inequality and low productivity. It considers the recent history and changing roles of local and regional organisations and the overarching policy frameworks that oversee them as a key element of tackling spatial inequality and low productivity. Specifically, the paper looks at the frequent changes to institutional arrangements supporting economic development and the process of allocating competitive funds to local and regional bodies.

Brexit has both increased the momentum towards Scottish independence and complicated what it could mean in practice, especially if Scotland rejoins the European Union (EU). EU accession would re-open the flow of goods, people, services and capital between Scotland and other EU member-states; a corollary of this, however, would be new restrictions on movement between Scotland and its non-EU neighbours. Effective border management entails a variety of ‘at the border’ and ‘behind the border’ processes. As much as these would require dedicated infrastructure and trained personnel, they would ultimately depend upon reliable data/information and good communication among myriad agencies, including on the other side of the border. Fundamentally, the nature and form of the border controls would be determined largely by the relationship that an independent Scotland had with the remainder of the UK—and, principally, on the relationship that the UK develops with the EU.

Trade issues lie at the heart of the two biggest constitutional challenges the UK has faced in decades: Brexit and Scottish independence. Brexit has demonstrated the economic importance of borders and led to renewed calls for Scottish independence. While there are a range of possible trading arrangements an independent Scotland could pursue, all of them involve economically significant change. In this paper, we describe Scottish trade patterns and review the range of options that a newly independent Scotland might have for its trading arrangements. We then model the relative economic importance of these different potential trading arrangements.

A recent contribution to research on age and well-being asserts that the impact of age on happiness is ‘u-shaped’ virtually everywhere. I evaluate that finding for European countries, considering whether it is robust to alternative methodological approaches. The analysis excludes control variables that are affected by age (noting that those variables are not antecedents of age) and explores the relationship via models that do not impose a quadratic functional form. The article shows that these alternative approaches do not produce a u-shape ‘everywhere’: u-shapes are evident for some countries, but for others, the pattern is quite different.

We examine the start date of the Great Recession across OECD countries. The Sahm Rule identifies the start of recession in the US to the beginning of 2008 but in most other OECD countries it identifies the start after that identified by two successive falls in quarterly GDP. We establish our own rule for predicting recession using the fear of unemployment series to predict recession. We show a 10-point rise in the series compared to its previous 12 month low predicted the onset of the Great Recession in both the United States and Europe.

Populist responses to matters of social concern are considered in a framework like that of Acemoglu and Robinson’s ‘narrow corridor’ that supports liberty and justice. We discuss the risk that such responses could result in a country being pushed out of this narrow corridor—and, if so, with what long-run consequences. We conclude that a political system of ‘checks and balances’ can play a key role in keeping the society within the narrow corridor; but it is incumbent on the existing political system to confront the issues of populist concern so as to come up with creative solutions.

Climate change and weather shocks have multi-faceted impacts on food systems with important implications for economic policy. Combining a longitudinal household survey with high-resolution climate data, we demonstrate that both climate and weather shocks increase food insecurity; cash assistance and participation in Ethiopia’s Productive Safety Net Programme have reduced food insecurity; but food assistance has been ineffective. Importantly, households with savings, and those that stored their harvest to sell at higher prices rather than for home use, suffered less from food insecurity, yet both strategies are harder for the poorest and most food insecure households to adopt. Our paper provides micro-founded evidence needed to design policies that both improve agricultural yields in the context of a changing climate and target households’ abilities to cope with shocks that put upwards pressure on food prices.

Both the physical and transition-related impacts of climate change pose substantial macroeconomic risks. Yet, markets still lack credible estimates of how climate change will affect debt sustainability, sovereign creditworthiness and the public finances of major economies. We present a taxonomy for tracing the physical and transition impacts of climate change through to impacts on sovereign risk. We then apply the taxonomy to the UK’s potential transition to net zero. Meeting internationally agreed climate targets will require an unprecedented structural transformation of the global economy over the next two or three decades. The changing landscape of risks warrants new risk management and hedging strategies to contain climate risk and minimise the impact of asset stranding and asset devaluation. Yet, conditional on action being taken early, the opportunities from managing a net zero transition would substantially outweigh the costs.

Climate change is one of the most serious risks facing humanity. Temperature rises can lead to catastrophic climate and natural events that threaten livelihoods. From rising sea levels to flooding, bush fires, extreme temperatures and droughts, the economic and human cost is too large to ignore. More than 190 world leaders got together in Glasgow during November 2021 at the UN’s COP26 climate change summit to discuss progress on the Paris Agreement (COP21) and to agree on new measures to limit global warming. In Paris, countries agreed to limit global warming to well below 2° and aim for 1.5° as well as to adapt to the impacts of a changing climate and raise the necessary funding to deliver on these aims. However, actions to date were not nearly enough as highlighted by the IPCC (2018) special report. The world is still on track to reach warming above 3° by 2100. As evident from figure 1, global temperatures have been on a steadily increasing path since the start of the 20th century and this process has substantially accelerated since the beginning of the 1980s. This has been unevenly distributed, with temperatures in the Northern hemisphere being a full 1°C higher than for the 1961–1990 average, whilst temperatures in the Southern hemisphere have increased by almost 0.5°C.

Measured health output in the UK declined sharply during the Covid-19 pandemic, despite the evident large increase in some National Health Service (NHS) activities such as critical care, and the new test and trace and vaccination programmes. We explain the measurement methods applied to public services that produced the published decline, in the context of the inherent difficulties of defining and measuring health output and productivity; and describe the changes in practice that had to take place in NHS hospitals. We also discuss, on the basis of these changes including increased use of technology, the likely outlook for healthcare productivity. We conclude that within NHS England capacity, constraints have contributed to substantial falls in non-Covid-19 healthcare output and argue that increased capacity in the social infrastructure of the health service is essential to enable higher productivity in an uncertain environment.

In 2020–2021, the world has been gripped by a pandemic that no living person has ever known. The coronavirus pandemic is undoubtedly the greatest challenge the world has faced in over a generation. The imperative of statistical modelling is not only to manage the short-run crisis for the health services, but also to explain the pandemic’s course and establish the effectiveness of different policies, both non-pharmaceutical and with vaccines. This difficult task has been undertaken by the epidemiologists and others in the face of measurement data problems, behavioural complications and endogeneity issues. This paper proposes a simple taxonomy of the alternative different models and suggests how they may be used together to overcome limitations. This perspective may have important implications for how policy-makers cope with future waves or strains in the current pandemic, or future pandemics.

An often overlooked strategy for fighting the COVID-19 pandemic is group testing. Its main advantage is that it can scale, enabling the regular testing of the whole population. We argue that another advantage is that it can induce social distancing. Using a simple model, we show that if a group tests positive and its members are in close social proximity, then they will rationally choose not to meet. The driving force is the uncertainty about who has the virus and the fact that the group cares about its collective welfare. We therefore propose identifying socially connected groups, such as colleagues, friends and neighbours, and testing them regularly.

This article shows how new time series models can be used to track the progress of an epidemic, forecast key variables and evaluate the effects of policies. The univariate framework of Harvey and Kattuman (2020, Harvard Data Science Review, Special Issue 1—COVID-19, https://hdsr.mitpress.mit.edu/pub/ozgjx0yn) is extended to model the relationship between two or more series and the role of common trends is discussed. Data on daily deaths from COVID-19 in Italy and the UK provides an example of leading indicators when there is a balanced growth. When growth is not balanced, the model can be extended by including a non-stationary component in one of the series. The viability of this model is investigated by examining the relationship between new cases and deaths in the Florida second wave of summer 2020. The balanced growth framework is then used as the basis for policy evaluation by showing how some variables can serve as control groups for a target variable. This approach is used to investigate the consequences of Sweden’s soft lockdown coronavirus policy in the spring of 2020.

Can smart containment policies crowd out private efforts at social distancing? We analyse this question from the perspective of network formation theory. We focus in particular on the role of externalities in social distancing choices. We also look at how these choices are affected by factors such as the agents’ risk perception, the speed of the policy intervention, the structure of the underlying network and the presence of strategic complementarities. We argue that crowding out is a problem when the probability that an outbreak may spread undetected is relatively high (either because testing is too infrequent or because tests are highly inaccurate). This is also the case where the choice of relaxing social distancing generates the largest negative externalities. Simulations on a real-world network suggest that crowding out is more likely to occur when, in the absence of interventions, face-to-face contacts are perceived to carry relatively high risk.

Based on evidence gathered from a newly built large macroeconomic dataset (MD) for the UK, labelled UK-MD and comparable to similar datasets for the United States and Canada, it seems the most promising avenue for forecasting during the pandemic is to allow for general forms of nonlinearity by using machine learning (ML) methods. But not all nonlinear ML methods are alike. For instance, some do not allow to extrapolate (like regular trees and forests) and some do (when complemented with linear dynamic components). This and other crucial aspects of ML-based forecasting in unprecedented times are studied in an extensive pseudo-out-of-sample exercise.

Nowcasting, that is, forecasting the current economic conditions, is a key ingredient for decision making, but it is complex, even more so for a small open economy, due to the higher volatility of its GDP. In this paper, we review the required steps, taking Luxembourg as an example. We consider both standard and alternative indicators, used as inputs in several nowcasting methods, including various factor and machine learning models. Overall, mixed frequency dynamic factor models and neural networks perform well, both in absolute terms and in relative terms with respect to a benchmark autoregressive model. The gains are larger during problematic times, such as the financial crisis and the recent Covid period.

A major part of the 2010–15 UK government's education reforms in England was a focus on the curriculum that pupils study from ages 14–16. Most high profile was the introduction of the English Baccalaureate (EBacc) performance measure for schools, incentivising study of “subjects the Russell Group identifies as key for university study” (Gibb, 2011). However, there does not appear to be good quantitative evidence about the importance of studying such a set of subjects, per se. This paper sets out to analyse this question, considering whether otherwise similar young people who study specific sets of subjects (full set for EBacc-eligibility, two or more sciences, foreign languages, applied subjects) to age 16 have different probabilities of entering university, and specifically a high-status university. It compares results from regression modelling and propensity score matching, taking advantage of rich survey data from a recent cohort of young people in England. We find that conditional differences in university entry attributable to subject choice are, at most, small.

None of the existing models for the future trade policy relationship between the UK and the EU come with a predetermined foreign and security policy relationship. This article assesses how the future EU-UK foreign and security policy relationship might be organised post-Brexit. It provides evaluation of the current EU-UK interrelationship in the fields of the EU's Common Foreign and Security Policy (CFSP) and Common Security and Defence Policy (CSDP) and assesses the degree to which the UK is presently integrated into EU decision-making and implementation. It highlights that the UK needs to determine the degree to which it wants autonomy or even divergence from existing EU policies. The article concludes by rehearsing the costs and benefits of three possible future relationships between the UK and EU foreign, security and defence policy: integrated, associated or detached.