Japan is shrinking. Current projections indicate a population decrease of around one quarter by mid-century. Depopulation is potentially good news, providing opportunities for reconfiguring living conditions and alleviating human-environmental pressures. Nevertheless, ageing and depopulation have outcomes that require adjustment. One of these is spatial inequalities, which have been accelerating since the 1990s. Japan is the Asia-Pacific’s pioneer ageing and shrinking society. In East Asia both China and South Korea are ageing and expected to begin shrinking soon. Even high immigration Anglophone countries such as New Zealand are experiencing post-growth demographic processes at subnational level. Japan’s significance is in how adaptive responses there inform prospects for others as they experience their own post-growth pathways. This article presents case studies of Sado Island in Japan and New Zealand’s South Island in a comparative qualitative analysis of rural agency under population decline. Overall, I contend there is potential for benefitting from demographic shrinkage - what I term a ‘depopulation dividend’ - and for rural regions in the Asia-Pacific to progress towards a sustainable post-growth economy and society.

We give a complete description of Rees quotients of free inverse semigroups given by positive relators that satisfy nontrivial identities, including identities in signature with involution. They are finitely presented in the class of all inverse semigroups. Those that satisfy a nontrivial semigroup identity have polynomial growth and can be given by an irredundant presentation with at most four relators. Those that satisfy a nontrivial identity in signature with involution, but which do not satisfy a nontrivial semigroup identity, have exponential growth and fall within two infinite families of finite presentations with two generators. The first family involves an unbounded number of relators and the other involves presentations with at most four relators of unbounded length. We give a new sufficient condition for which a finite set X of reduced words over an alphabet $A\cup A^{-1}$ freely generates a free inverse subsemigroup of $FI_A$ and use it in our proofs.

Understanding the determinants of malnutrition is pivotal for public health interventions. This study aimed to identify socio-economic, demographic, dietary and maternal determinants of wasting and overweight among Brazilian children between 6 and 59 months. Data from the Brazilian National Survey on Child Nutrition were analysed (n 11 789). Children’s weight-for-height Z-scores were calculated according to the WHO growth standard and classified as wasting (Z < −2), normal weight (–2 ≤ Z ≤ 1), overweight risk (1 < Z ≤ 2) and overweight (Z > 2). Socio-economic, demographic, dietary and maternal covariables were considered. Adjusted multinomial logistic regression (OR and 95 % CI) was employed. The prevalence of overweight and wasting was 9·5 and 2·6 %, respectively. In the adjusted model, younger age (6–23 months: OR: 1·7; 95 % CI: 1·3, 2·2), consumption of ≥ 5 ultra-processed food groups (OR: 1·8; 95 % CI: 1·1, 3·1), maternal underweight (OR: 0·4; 95 % CI: 0·2, 0·9), overweight (OR: 1·5; 95 % CI: 1·2, 1·9) and mild food insecurity (OR: 0·8; 95 % CI: 0·6, 1·0) were associated with child overweight. The Brazilian Northeast (OR: 4·9; 95 % CI: 2·1, 11·3), Southeast (OR: 7·1; 95 % CI: 3·0, 16·6), South (OR: 4·7; 95 % CI: 1·8, 12·1), Midwest regions (OR: 2·7; 95 % CI: 1·2, 6·2) and maternal underweight (OR: 5·4; 95 % CI: 2·7, 10·7) were associated with wasting. Overweight in Brazil is prevalent among children between 6 and 59 months, while wasting is not a major public health problem. The main determinants of these Brazilian children’s nutritional status were age, ultra-processed food consumption and maternal nutritional status.

In institutional design, public policy and for society as a whole, securing freedom of choice for individuals is important. But how much choice should we aim for? Various theorists argue that above some level more choice improves neither wellbeing nor autonomy. Worse still, psychology research seems to suggest that too much choice even makes us worse off. Such reasons suggest the Sufficiency View: increasing choice is only important up to some sufficiency level, a level that is not too far from the level enjoyed by well-off citizens in rich liberal countries today. I argue that we should reject the Sufficiency View and accept Liberal Optimism instead: expanding freedom of choice should remain an important priority even far beyond levels enjoyed in rich liberal countries today. I argue that none of the arguments given for the Sufficiency View work. Neither psychological evidence nor any broader social trends support it. If anything, they support Liberal Optimism instead. I also show why further increases are possible and desirable, and sketch some implications for debates around immigration, economic growth, markets and the value of community.

A common assessment research design is the single-group pre-test/post-test design in which examinees are administered an assessment before instruction and then another assessment after instruction. In this type of study, the primary objective is to measure growth in examinees, individually and collectively. In an item response theory (IRT) framework, longitudinal IRT models can be used to assess growth in examinee ability over time. In a diagnostic classification model (DCM) framework, assessing growth translates to measuring changes in attribute mastery status over time, thereby providing a categorical, criterion-referenced interpretation of growth. This study introduces the Transition Diagnostic Classification Model (TDCM), which combines latent transition analysis with the log-linear cognitive diagnosis model to provide methodology for analyzing growth in a general DCM framework. Simulation study results indicate that the proposed model is flexible, provides accurate and reliable classifications, and is quite robust to violations to measurement invariance over time. The TDCM is used to analyze pre-test/post-test data from a diagnostic mathematics assessment.

Nitrogen (N) is the most significant nutrient affecting crop growth and development for all types of crops, except legumes. The goal of this study was to optimize the N level for cotton grown in a semi-arid environment to enhance growth and development, determine N status, and increase seed cotton yield and biomass. Two independent field experiments each three years in duration were conducted, from 2007 to 2009 (Exp.-I) and 2018 to 2020 (Exp.-II). Experiments were laid out in a randomized complete block design with three replicates. The N treatments in Exp.-I were comprised of 0, 40, 80, 120, 160, 200 and 240 kg N/ha, while treatments in Exp.-II were comprised of 0, 70, 140, 210 and 280 kg N/ha. A wide range of data sets for cotton traits were recorded, including canopy height, leaf area index, the N status of the leaf and stem, seed cotton yield and time-series biomass data. The higher N rates 240 and 280 kg N/ha performed better for all these traits. However, the highest leaf N contents were recorded for 210 kg N/ha. Based on these results, it is suggested that under semi-arid conditions, slightly higher rates than optimum or recommended N rates could be applied as a strategy by cotton growers for a higher seed cotton yield. The findings of this study may also increase profitability in other cotton-growing areas that have similar weather conditions.

Data show that an increase in the Gini coefficient is associated with a falling bottom $p_{B}$% income share and an increasing top $p_{T}$ % income share where, for example $p_{B}$ = 40 and $p_{T}$ = 1. This relationship, which we call the $X$ inequality relationship, is pervasive in the sense that it is observed in many countries, including the US, the UK, France and others. The purpose of this paper is (i) to construct a Schumpeterian growth model to explain the relationship, and (ii) to identify/quantify factors behind it via calibration of the US economy. Our model gives rise to a double-Pareto distribution of income as a result of entrant and incumbent innovations. Its advantage is that it allows us to develop iso-Gini loci and iso-income share schedules in a tractable way. Using a double-Pareto distribution as an approximation of an underlying income distribution, calibration analysis reveals that a declining business dynamism and fiscal policy changes in the past decades played a significant role in generating the $X$ inequality relationship in the US.

In this paper, we construct an elaborate general equilibrium model with a continuum of production fragments for an intermediate good, then incorporate it in a growth model to address the effects of global production fragmentation, vertical specialization, and trade on growth and inequality for a small developing country. Among other things, we show that a small developing economy grows faster than the rest of the world as a result of global fragmentation and trade in intermediates if it is skilled-labor scarce. We further address the effects of such a trade opening on wage inequality.