This chapter examines how key issues in the design and implementation of UK QE were addressed not by the Monetary Policy Committee but by the executive managers of the Bank of England. It also discusses accountability for the probably huge budgetary costs of the QE programme.

This chapter documents how the Bank of England’s thinking on the various transmission channels of QE changed over time through an analysis of quotes from policymakers and members of Bank staff.

This chapter shows how QE has had material consequences for fiscal policy in the UK since 2009 and also leads to potential conflicts in times of QT. It looks to international precedent for lessons on how to manage these fiscal interactions.

Chapter 9 examines how mental models shape attitudes toward artificial intelligence (AI), a rapidly emerging yet relatively unpoliticized technology. Initially, individuals with and without an Economist Mental Model (EMM) show no strong divergence in their baseline assessments of AI’s risks and benefits, likely reflecting the technology’s novelty. However, two survey experiments reveal that EMM-oriented respondents adapt their views more readily when presented with economic information about AI’s impacts on productivity, wages, or inequality. By contrast, those with Alternative Mental Models (AMMs) remain largely unmoved by the same data. In a second experiment using a conjoint design, EMM-oriented participants systematically adjust their support for AI adoption in hypothetical firms, raising support when gains outweigh losses and reducing it when the scenario shows net harms. Conversely, individuals with AMMs maintain fixed views. This responsiveness underscores the role of economic thinking in evaluating AI’s trade-offs and shaping policy preferences.

This chapter reviews the recent history of quantitative easing and tightening in the US, focusing on the impact on financial markets.

This chapter describes the period between the late eighteenth and early nineteenth century where the Bank of England used excess reserve creation (in the form of banknote issuance) to help fund a burgeoning fiscal deficit.

Chapter 6 examines zero-sum thinking (ZST) – the idea that one party’s gain must be another’s loss – and contrasts it with the Economist Mental Model (EMM), which recognizes that economic interactions can be positive-sum. Historically adaptive in static, resource-scarce settings, ZST becomes counterproductive in modern, dynamic economies built on cooperation and specialization. Using survey data from the US, the chapter differentiates between generic ZST (a broad tendency to see life as win-lose) and policy-specific ZST, which can reveal partisan divides. Democrats often display zero-sum views about redistribution, whereas Republicans do so regarding immigration or trade. Crucially, people with higher economic knowledge – those more aligned with the EMM – show markedly lower generic ZST and are less inclined toward protectionist policies than those with lower economic knowledge – aligned with Alternative Mental Models (AMMs).

In 2011, Italy narrowly avoided financial collapse, prompting the formation of a technocratic government tasked with enacting sweeping reforms. Although these measures stabilized public finances, they drew fierce opposition and highlighted a broader pattern of public skepticism toward expert advice. Similar dynamics unfolded during the 2016 Brexit referendum, when voters dismissed economic forecasts, and in Donald Trump’s election, where nationalist rhetoric overshadowed warnings on protectionism. These events highlight a persistent gap between how economists and the general public evaluate policy trade-offs, often producing outcomes economists view as welfare-reducing. This book explores how mental models, particularly the Economist Mental Model (EMM), shape individual political decisions and explains why populist solutions gain traction despite longer-term harms. Through diverse cases – from Brexit and US protectionism to price controls – it argues that wider adoption of the EMM could enhance support for welfare-enhancing policies, a crucial insight in an era of heightened populist sentiment.

Chapter 8 investigates how mental models shape individuals’ responses to policy information and partisan cues. Through a survey experiment in Italy involving hypothetical price controls on olive oil, the chapter shows that people with high economic knowledge – the Economist Mental Model – are far more influenced by cost–benefit data, reducing their support for price controls by 20 percentage points once presented with evidence of net societal losses. Meanwhile, those with lower economic knowledge respond more to partisan cues, increasing their support by about 6 points when party leaders endorse the policy. Notably, both groups share similar baseline preferences in the absence of new information, indicating that economic knowledge – not preexisting ideology – drives these contrasting reactions. The chapter further reveals that high-knowledge participants are 25 percentage points more likely to calculate the policy’s true societal impact, illustrating the distinctive role of economic reasoning in integrating and acting on new policy information.