Japan’s aging and shrinking population could lower the natural rate of interest and, together with low inflation expectations, challenge the Bank of Japan’s efforts to reflate the economy. This paper uses a semi-structural model to estimate the impact of demographics on the natural rate in Japan. We find that demographic change has a significantly negative impact on the natural rate by lowering trend potential growth. We also find that the negative impact has been increasing over time amid stronger demographic headwinds. These findings highlight the importance of boosting potential growth to offset the negative demographic impact and lift the natural rate in Japan.

This issue of Finance & Development discusses link between demographics and economic well-being. In the coming decades, demographics is expected to be more favorable to economic well-being in the less developed regions than in the more developed regions. The age structure of a population reflects mainly its fertility and mortality history. In high-mortality populations, improved survival tends to occur disproportionately among children. The “demographic dividend” refers to the process through which a changing age structure can spur economic growth. It depends, of course, on several complex factors, including the nature and pace of demographic change, the operation of labor and capital markets, macroeconomic management and trade policies, governance, and human capital accumulation. Population aging is the dominant demographic trend of the twenty-first century—a reflection of increasing longevity, declining fertility, and the progression of large cohorts to older ages. Barring a change in current trends, the industrial world’s working-age population will decline over the next generation, and China’s working-age population will decline as well. At the same time, trends toward increased labor force participation of women have played out with, for example, more women than men now working in the United States.

The rapid aging and shrinking of Japan’s population will dominate economic policy making in coming decades—impelling a fresh look at the objectives and tools of Abenomics. Six years of Abenomics have yielded some important results, but achieving sustained high growth and durable reflation, while also tackling debt sustainability and a shifting global economic landscape, will require strengthened policies.

This paper uses case studies to explore the nature and extent of past IMF engagement on social spending issues and to draw lessons for future engagement.

The six-volume set LNCS 12742, 12743, 12744, 12745, 12746, and 12747 constitutes the proceedings of the 21st International Conference on Computational Science, ICCS 2021, held in Krakow, Poland, in June 2021.* The total of 260 full papers and 57 short papers presented in this book set were carefully reviewed and selected from 635 submissions. 48 full and 14 short papers were accepted to the main track from 156 submissions; 212 full and 43 short papers were accepted to the workshops/ thematic tracks from 479 submissions. The papers were organized in topical sections named: Part I: ICCS Main Track Part II: Advances in High-Performance Computational Earth Sciences: Applications and Frameworks; Applications of Computational Methods in Artificial Intelligence and Machine Learning; Artificial Intelligence and High-Performance Computing for Advanced Simulations; Biomedical and Bioinformatics Challenges for Computer Science Part III: Classifier Learning from Difficult Data; Computational Analysis of Complex Social Systems; Computational Collective Intelligence; Computational Health Part IV: Computational Methods for Emerging Problems in (dis-)Information Analysis; Computational Methods in Smart Agriculture; Computational Optimization, Modelling and Simulation; Computational Science in IoT and Smart Systems Part V: Computer Graphics, Image Processing and Artificial Intelligence; Data-Driven Computational Sciences; Machine Learning and Data Assimilation for Dynamical Systems; MeshFree Methods and Radial Basis Functions in Computational Sciences; Multiscale Modelling and Simulation Part VI: Quantum Computing Workshop; Simulations of Flow and Transport: Modeling, Algorithms and Computation; Smart Systems: Bringing Together Computer Vision, Sensor Networks and Machine Learning; Software Engineering for Computational Science; Solving Problems with Uncertainty; Teaching Computational Science; Uncertainty Quantification for Computational Models *The conference was held virtually. Chapter “Intelligent Planning of Logistic Networks to Counteract Uncertainty Propagation” is available open access under a Creative Commons Attribution 4.0 International License via link.springer.com. The six-volume set LNCS 12742, 12743, 12744, 12745, 12746, and 12747 constitutes the proceedings of the 21st International Conference on Computational Science, ICCS 2021, held in Krakow, Poland, in June 2021.* The total of 260 full papers and 57 short papers presented in this book set were carefully reviewed and selected from 635 submissions. 48 full and 14 short papers were accepted to the main track from 156 submissions; 212 full and 43 short papers were accepted to the workshops/ thematic tracks from 479 submissions. The papers were organized in topical sections named: Part I: ICCS Main Track Part II: Advances in High-Performance Computational Earth Sciences: Applications and Frameworks; Applications of Computational Methods in Artificial Intelligence and Machine Learning; Artificial Intelligence and High-Performance Computing for Advanced Simulations; Biomedical and Bioinformatics Challenges for Computer Science Part III: Classifier Learning from Difficult Data; Computational Analysis of Complex Social Systems; Computational Collective Intelligence; Computational Health Part IV: Computational Methods for Emerging Problems in (dis-)Information Analysis; Computational Methods in Smart Agriculture; Computational Optimization, Modelling and Simulation; Computational Science in IoT and Smart Systems Part V: Computer Graphics, Image Processing and Artificial Intelligence; Data-Driven Computational Sciences; Machine Learning and Data Assimilation for Dynamical Systems; MeshFree Methods and Radial Basis Functions in Computational Sciences; Multiscale Modelling and Simulation Part VI: Quantum Computing Workshop; Simulations of Flow and Transport: Modeling, Algorithms and Computation; Smart Systems: Bringing Together Computer Vision, Sensor Networks and Machine Learning; Software Engineering for Computational Science; Solving Problems with Uncertainty; Teaching Computational Science; Uncertainty Quantification for Computational Models *The conference was held virtually. Chapter “Intelligent Planning of Logistic Networks to Counteract Uncertainty Propagation” is available open access under a Creative Commons Attribution 4.0 International License via link.springer.com. Chapter: Modelling and Forecasting Based on Recurrent Pseudoinverse Matrices” is available open access under a Creative Commons Attribution 4.0 International License via link.springer.com.

Japan: Selected Issues

Demographic developments have been regarded as one important cause of the long-term movement in global interest rates. This paper provides empirical evidence of the relationship between demographics and interest rates over a wide sample of advanced and emerging market economies. It also finds that capital account openness limits the direct sensitivity of a country’s interest rates to its own demographics. The results suggest that future demographic developments will continue to apply downward pressure on the interest rates in Asia which foresees a rapid aging.

We develop a heterogeneous agent, overlapping generations model with nonhomothetic preferences that nests several explanations for the decline in the natural rate of interest (r∗) suggested in the literature: demographic change, a slowdown in productivity growth, a rise in income inequality, and public policy. The model can account for a 2.2 percentage point (pp) decline in r∗ between 1975 and 2015, which is within the range of empirical estimates. Rising income inequality is an important driver (-0.70 pp), and together with demographic change (-0.71 pp) and the slowdown in productivity growth (-1.0 pp) explains most of the decline. Growing public debt is the major counteracting force (+0.31 pp). Permanent income inequality is of greater importance than inequality due to uninsurable income risk, and matching the degree of nonhomotheticity in consumption and savings behavior to empirical estimates is essential for this result. We predict that r∗ will reach a low of 0.38% by 2030, after which a slow reversal will begin. The natural rate will stabilize at 1% in the long run, a low level when compared with the postwar path of r∗ implied by the model. This remains true even if we take into account soaring public debt levels due to the COVID-19 pandemic. Policy can have considerable impact on the level of r∗ through the tax and transfer system.

The recession that began with a cyclical peak in Dec. 2007 originated in a combination of real shocks because of a fall in housing wealth and a fall in real income from an increase in energy prices. The most common explanation for the intensification of the recession that began in the late summer of 2008 is the propagation of these shocks through dysfunction in credit markets. The alternative explanation offered emphasizes propagation through contractionary monetary policy. The 1st explanation stresses the importance of credit-market interventions (credit policy). The 2nd emphasizes the importance of money creation (money-creation policy). "The System should always be engaged in a ruthless examination of its past record."

The first book of the next crisis. A history of interest rates by a leading financial commentator, updated with a new postscript. *Winner of the 2023 Hayek Book Prize* *Longlisted for the 2022 Financial Times Business Book of the Year Award* All economic and financial activities take place across time. Interest coordinates these activities. The story of capitalism is thus the story of interest: the price that individuals, companies and nations pay to borrow money. In The Price of Time, Edward Chancellor traces the history of interest from its origins in ancient Mesopotamia, through debates about usury in Restoration Britain and John Law ' s ill-fated Mississippi scheme, to the global credit booms of the twenty-first century. We generally assume that high interest rates are harmful, but Chancellor argues that, whenever money is too easy, financial markets become unstable. He takes the story to the present day, when interest rates have sunk lower than at any time in the five millennia since they were first recorded - including the extraordinary appearance of negative rates in Europe and Japan - and highlights how this has contributed to profound economic insecurity and financial fragility. Chancellor reveals how extremely low interest rates not only create asset price inflation but are also largely responsible for weak economic growth, rising inequality, zombie companies, elevated debt levels and the pensions crises that have afflicted the West in recent years - conditions under which economies cannot possibly thrive. At the same time, easy money in China has inflated an epic real estate bubble, accompanied by the greatest credit and investment boom in history. As the global financial system edges closer to yet another crisis, Chancellor shows that only by understanding interest can we hope to face the challenges ahead.