Net zero greenhouse gas emissions by 2050, the UK’s current target, requires bridging a dramatic energy transition and eliminating all other net sources of emissions while ensuring a just transition. Key components like renewable electricity generation and electric vehicles are well developed, but many issues remain. Public support for a green economy may wane if the economic costs are too high or seen as unfair. Therefore, although renewable energy is cheaper than fossil fuels, it is essential to maintain employment, real per capita growth and reduced inequality. Decarbonizing the UK economy requires an integrated sequential approach and need not be delayed while dealing with the aftermath of the COVID-19 pandemic, energy crisis and resulting inflation.

The least squares Monte Carlo method has become a standard approach in the insurance and financial industries for evaluating a company’s exposure to market risk. However, the non-linear regression of simulated responses on risk factors poses a challenge in this procedure. This article presents a novel approach to address this issue by employing an a-priori segmentation of responses. Using a K-means algorithm, we identify clusters of responses that are then locally regressed on their corresponding risk factors. The global regression function is obtained by combining the local models with logistic regression. We demonstrate the effectiveness of the proposed local least squares Monte Carlo method through two case studies. The first case study investigates butterfly and bull trap options within a Heston stochastic volatility model, while the second case study examines the exposure to risks in a participating life insurance scenario.

Using daily data on vaccinations, disease spread and measures of social interaction from Google Mobility reports aggregated at the country level for 112 countries, we present estimates of behavioural responses to the global rollout of COVID-19 vaccines. We first estimate correlates of the timing and intensity of the vaccination rollout, finding that countries which vaccinated more of their population earlier strongly tended to be richer, whereas measures of the state of pandemic or its death toll up to the time of the initial vaccine rollout had little predictive ability after controlling for income. Estimates of models of social distancing and disease spread suggest that countries which vaccinated more quickly also experienced decreases in some measures of social distancing, yet also lower incidence of disease, and in these countries, policy-makers relaxed social distancing measures relative to countries which rolled out vaccinations more slowly.

The Institute is a world leader in macroeconomic modelling and forecasting. It has produced quarterly economic forecasts for around sixty years, supported by macroeconomic models. The aim of the original builders of macroeconomic models was to transform understanding of how economies worked and use that knowledge to improve economic policy. In the early years, when computers were rare, macroeconomic modelling was a new frontier and Institute economists were among the first to produce a working model of the UK economy. It is remarkable how quickly models were being used to produce forecasts, assess policy and influence the international macroeconomic research agenda. The models built at the Institute were mainstream in the sense that they followed the contents of standard macroeconomic textbooks, developed with the subject, and fitted the facts as they were known at the time. There were continual improvements in understanding as the subject developed in response to new ideas and developments in the global economy. This article celebrates the development of macroeconomic modelling at the Institute and the contribution it has made to public life.

This paper introduces a special issue of the Review on how the National Institute Global Econometric Model (NiGEM) is being used to navigate uncertain times. NiGEM is the leading global macroeconomic model, used by both policy-makers and the private sector across the globe for economic forecasting, scenario building and stress testing. The paper summarises the main features of NiGEM and describes some standard model simulations to illustrate how the model responds to monetary, fiscal and technology shocks.

There is a strong case for boosting public investment in many countries based on identified country-specific structural weaknesses and the relatively low levels of such investment. This paper analyses the potential macroeconomic benefits of increased public investment using simulations on NiGEM. The results suggest that the supply-side benefits from raising potential output are likely to lead to more favourable macroeconomic outcomes than those from using many other standard fiscal instruments, although it takes many years for the full effect on potential output to accumulate. Variant model simulations also suggest that a fiscal stimulus will be more effective in the short term the less it is offset by monetary policy, making well-targeted policy initiatives especially effective when policy interest rates are at the zero lower bound. Globalisation implies that spillover effects from collective action are larger than in the past, boosting multipliers relative to the case where countries take individual action, particularly in the first two years after the policy change. Such spillovers are likely to be particularly important in small open European economies, especially those strongly integrated in European value chains.

This paper develops and illustrates the application of a procedure to evaluate and compare the cost effectiveness of alternative crop insurance products for cotton in terms of their effect on expected producer net returns and the variation of net returns. Farm unit-level cotton yields and state-level price distributions are estimated by a multivariate nonnormal parametric modeling procedure and used to simulate the net returns to alternative crop insurance products over a 10-year planning horizon. The ranking of alternative insurance products using third-degree stochastic dominance is presented for Texas cotton producers.

A previous study showed that imposing economic restrictions improves the forecasting ability of food demand systems, thus warranting their use even when they are rejected in-sample. This article evaluates whether this result is due to economic restrictions enhancing degrees of freedom or containing nonsample information. Results indicate that restrictions improve forecasting ability even when they are not derived from economic theory, but theoretical restrictions forecast best.

In this paper, we present an econometric analysis of the effects of a price floor on price dynamics and price volatility. A price floor (implemented as a part of government pricing policy) provides a censoring mechanism for price determination. We specify and estimate a dynamic Tobit model under time-varying volatility. The model is applied to analyze the effects of a price support program on price dynamics and price volatility in the U.S. American cheese market. The econometric analysis provides useful insights on price dynamics in the presence of a government-determined price floor.