The economics of ageing is the study of economic decision‐making by individuals and government aimed at fostering well‐being in old age. These decisions include preparing for old age and dealing with the risks of old age. The risks are substantial. Using the life‐cycle model, this article considers the risks for well‐being that people face in retirement and the role of government and private insurance in meeting those risks. The perspective of the life‐cycle model is also used to consider the gender gap in wealth on retirement.

This is a history of the global economy, starting with the appearance of Homo sapiens and ending with the 21st century with a final chapter that attempts to look into the future. It belongs to the new genre of histories of the human species or H. sapiens from the time the species emerged: other recent examples are the books by Blainey (2000), Harari (2014) and Rutherford (2016).1 The book by White differs from the others in that it uses the concepts and tools of the discipline of economic history to enlighten our understanding of the history of global economic activity. I shall use my understanding of growth economics and the analysis of globalization to evaluate what the discipline of economic history adds to our understanding of global history.

We investigate the effect of the global financial crisis (GFC) on household willingness to take risk. A model incorporating experienced returns as a determinant of risk tolerance is specified, with time‐varying weights on past stock returns capturing changes during the crisis. Results show that households became more myopic during the GFC, placing greater weight on more recent stock returns when evaluating financial risk attitudes. Households have been more sensitive to financial shocks during the GFC and post‐GFC periods, with the change in sensitivity found to be uniform over the life cycle and other household characteristics, but differing by income.

Uncertainty has been a pretty hot topic among academics and economists working in policy circles since the global financial crisis. I believe we now know a lot more about its effects on the business cycles of a variety of countries than we knew before the crisis. Uncertainty tends to be recessionary, it exerts stronger effects when the economy is already experiencing difficulties from an aggregate standpoint, or when financial markets operate less smoothly, and it tends to harm macroeconomic policies’ effectiveness. In spite of the impressive amount of knowledge accumulated so far, gaps in the literature are still present. First, we do not know much about how long term rates respond to uncertainty shocks. While dynamic stochastic general equilibrium models approximated at third order offer predictions on how the term structure responds to uncertainty shocks, the literature has not yet produced many model‐free reduced‐form types of regressions on the link between uncertainty and long rates. This is a big hole, given the relevance of long rates on consumption and investment decisions. Second, we need to sharpen our understanding of monetary policy risk management. Uncertainty is clearly relevant from a policy standpoint. But do policymakers systematically monitor uncertainty? Moreover, do they disagree on the economic outlook, and if so, does this influence their decisions? Third, we need proxies for uncertainty for a broader set of countries than the G7. For example, how does uncertainty evolve in a country like New Zealand as opposed to, say, the United States? This special issue addresses all these questions. The first paper, ‘Yield curve and financial uncertainty: Evidence based on US data’, estimates the response of the US yield curve to a jump in financial uncertainty. I address this question by conducting a local projection analysis with US monthly data from 1962–2018. I find both ends of the yield curve respond negatively and significantly. The response of the short end of the yield curve is stronger than that of the long end, that is, a financial uncertainty shock causes a temporary steepening of the yield curve. This result is consistent, among other interpretations, with medium‐term expectations of a recovery in real activity after a financial uncertainty shock.

How do short‐ and long‐term interest rates respond to a jump in financial uncertainty? We address this question by conducting a local projections analysis with US monthly data, period: 1962–2018. The state‐of‐the‐art financial uncertainty measure proposed by Ludvigson, Ma and Ng (2019) is found to predict movements in interest rates at different maturities. In particular, an increase in financial uncertainty is found to trigger a negative and significant response of both short‐ and long‐term interest rates. The response of the short end of the yield curve (i.e., of short‐term interest rates) is found to be stronger than that of the long end (i.e., of long‐term ones). In other words, a financial uncertainty shock causes a temporary steepening of the yield curve. This result is consistent, among other interpretations, with medium‐term expectations of a recovery in real activity after a financial uncertainty shock.

In this paper, we discuss a number of key methodological and data issues presented to researchers in determining base funding requirements for Australian schools. In particular, we outline the commonly used ‘reference school’‐ based approach to determining a benchmark level of school effectiveness and efficiency, and discuss some of its limitations. In contrast to this method, we present a new approach to estimating base funding requirements that, aided by the use of more granular data, provides a more robust approach to understanding and measuring school effectiveness and efficiency.

This issue of the policy forum focuses on a theme that has become dominant on the policymakers’ agenda since the global financial crisis: How to conduct monetary and fiscal policies in an environment characterised by low interest rates and concerns over fiscal sustainability.

This article discusses recent research on the macroeconomic effects of fiscal policy—the theme of the 2018 edition of the Melbourne Institute Macroeconomic Policy Meeting. We review recent research findings on the effects of fiscal multipliers in normal times, during booms/busts, and in the presence of the zero lower bound. Studies on the effects of fiscal policy in open economy settings as well as contributions on the fiscal‐monetary policy mix are also considered. We conclude by outlining a few research avenues that are particularly relevant from a policy standpoint.

Stochastic mortality models have a wide range of applications. They are particularly important for analysing Chinese mortality, which is subject to rapid and uncertain changes. However, owing to data‐related problems, stochastic modelling of Chinese mortality has not been given adequate attention. We attempt to use a Bayesian approach to model the evolution of Chinese mortality over time, taking into account all of the problems associated with the data set. We build on the Gaussian state space formulation of the Lee–Carter model, introducing new features to handle the missing data points, to acknowledge the fact that the data are obtained from different sources and to mitigate the erratic behaviour of the parameter estimates that arises from the data limitations. The approach proposed yields stochastic mortality forecasts that are in line with both the trend and the variation of the historical observations. We further use simulated pseudodata sets with resembling limitations to validate the approach. The validation result confirms our approach's success in dealing with the limitations of the Chinese mortality data.

We prove that a subtle but substantial bias exists in a common measure of the conditional dependence of present outcomes on streaks of past outcomes in sequential data. The magnitude of this streak selection bias generally decreases as the sequence gets longer, but increases in streak length, and remains substantial for a range of sequence lengths often used in empirical work. We observe that the canonical study in the influential hot hand fallacy literature, along with replications, are vulnerable to the bias. Upon correcting for the bias, we find that the longstanding conclusions of the canonical study are reversed.

This article investigates the role of welfare receipt in shaping norms regarding work and welfare using unique Australian data from the Youth in Focus Project. We begin by incorporating welfare into a theoretical model of the transmission of work-welfare norms across generations. Consistent with the predictions of this model, we find evidence that youths' attitudes toward work and welfare may be influenced by socialization within their families. Young people are more likely to oppose generous social benefits and to believe that social inequality stems from individual characteristics if (i) their mothers support these views; (ii) their mothers were employed while they were growing up; and (iii) their families never received welfare. Finally, youths' work-welfare norms appear to be unrelated to their neighbors' welfare receipt suggesting that socialization occurs primarily within families rather than within neighborhoods.