Publications
Given that poor individuals face worse survival conditions than non-poor individuals, one can expect that a steeper income gradient in mortality leads, through stronger income-based selection, to a lower poverty rate at the old age (i.e. the "missing poor" hypothesis). This paper uses U.S. state-level data on poverty at age 65+ and life expectancy by income levels to provide an empirical test of the missing poor hypothesis. Using average temperature as an instrument for mortality differentials, we show that instrumented changes in mortality differentials have a negative and statistically significant effect on old-age poverty: a 1 % increase in the mortality differential implies a 16 % decrease in the 65+ headcount poverty rate. Using those regression results, we compute hypothetical old-age poverty rates while neutralizing the impact of the income gradient in mortality, and show that correcting for heterogeneity in income-based selection effects modifies the comparison of old-age poverty prevalence across states.
This paper develops an overlapping generations model that links a public health system to a pay-as-you-go (PAYG) pension system. It relies on two assumptions. First, the health system directly finances curative health spending on the elderly. Second, public pensions partially depend on health status by introducing a component indexed to society’s average level of old-age disability. Reducing the average disability rate in the economy then lowers pension benefits as the need to finance long-term care services also drops. We study the effects of introducing such a ‘comprehensive’ Social Security system on individual decisions, capital accumulation, and welfare. We first show that health investments can boost savings and capital accumulation under certain conditions. Second, if individuals are sufficiently concerned with their health when old, it is optimal to introduce a health-dependent pension system, as this will raise social welfare compared to a system where pensions are not tied to the society’s average level of old-age disability. Our analysis thus highlights an important policy recommendation: making PAYG pension schemes partially health-dependent can be beneficial to society.
A common thread in the literature shows that an oil price shock can have a major impact on global economic conditions. We examine the global dimensions of changes to the global oil price and world economic uncertainty using three model types: ordinary least square (OLS); general additive model (GAM); and non-linear vector autoregression (VAR) model with local projections (LP). Our study highlights a positive and statistically significant effect of oil prices on economic uncertainty during non-expansionary periods, yet the impact is negative on economic uncertainty during periods of economic growth. Using a VAR-LP we analyze the global dimensions of a world oil price shock on global economic conditions and investigate whether there is consistency in how an oil price shock influences economic growth, consumer prices and economic uncertainty based on the state of economic conditions. The empirical evidence shows that during an expansionary (a non-expansionary) period, the impact of an oil price shock lowers (elevates) economic uncertainty. The empirical evidence from the three model types taken together indicate a presence of state dependence on the influence of an oil price shock.
Purpose The blue and green firms are notable contributors to sustainable development. Similar to other businesses in circular economies, blue and green firms also face financing constraints. This paper aims to assess whether blue and green lending help in optimizing the interest rate spreads and the likelihood of default. Design/methodology/approach This analysis is based on an unbalanced panel of banks from 20 eurozone countries for eleven years between 2012 and 2022. The key indicators of banking include interest rate spread and a market-based probability of default. The paper assesses how these indicators are influenced by exposure to green and blue firms after controlling for several exogenous factors. Findings The results show a positive relationship between green and blue lending and spread, while there is a negative link with the probability of default. This confirms that the blue and green exposure positively supports the credit portfolio both in terms of profitability and risk management. Originality/value The banking system is among the key contributors to corporate finance and to enable continuous access to sustainable finance, the banking firms must be incentivized. While many studies analyze the impact of green lending, to the best of the authors’ knowledge, this study is among the very few that extend this analysis to blue economy firms.
BackgroundThe extent of left ventricular (LV) trabeculation and its relationship with cardiovascular (CV) risk factors is unclear.PurposeTo apply automated segmentation to UK Biobank cardiac MRI scans to (a) assess the association between individual characteristics and CV risk factors and trabeculated LV mass (LVM) and (b) establish normal reference ranges in a selected group of healthy UK Biobank participants.Materials and MethodsIn this cross-sectional secondary analysis, prospectively collected data from the UK Biobank (2006 to 2010) were retrospectively analyzed. Automated segmentation of trabeculations was performed using a deep learning algorithm. After excluding individuals with known CV diseases, White adults without CV risk factors (reference group) and those with preexisting CV risk factors (hypertension, hyperlipidemia, diabetes mellitus, or smoking) (exposed group) were compared. Multivariable regression models, adjusted for potential confounders (age, sex, and height), were fitted to evaluate the associations between individual characteristics and CV risk factors and trabeculated LVM.ResultsOf 43 038 participants (mean age, 64 years ± 8 [SD]; 22 360 women), 28 672 individuals (mean age, 66 years ± 7; 14 918 men) were included in the exposed group, and 7384 individuals (mean age, 60 years ± 7; 4729 women) were included in the reference group. Higher body mass index (BMI) (β = 0.66 [95% CI: 0.63, 0.68]; P < .001), hypertension (β = 0.42 [95% CI: 0.36, 0.48]; P < .001), and higher physical activity level (β = 0.15 [95% CI: 0.12, 0.17]; P < .001) were associated with higher trabeculated LVM. In the reference group, the median trabeculated LVM was 6.3 g (IQR, 4.7–8.5 g) for men and 4.6 g (IQR, 3.4–6.0 g) for women. Median trabeculated LVM decreased with age for men from 6.5 g (IQR, 4.8–8.7 g) at age 45–50 years to 5.9 g (IQR, 4.3–7.8 g) at age 71–80 years (P = .03).ConclusionHigher trabeculated LVM was observed with hypertension, higher BMI, and higher physical activity level. Age- and sex-specific reference ranges of trabeculated LVM in a healthy middle-aged White population were established.© RSNA, 2024Supplemental material is available for this article.See also the editorial by Kawel-Boehm in this issue.
Salience theory relies on the assumption that not only the marginal distribution of lotteries, but also the correlation of payoffs across states impacts choices. Recent experimental studies on salience theory seem to provide evidence in favor of such correlation effects. However, these studies fail to control for event-splitting effects (ESE). In this paper, we seek to disentangle the role of correlation and event-splitting in two settings: (1) the common consequence Allais paradox as studied by Bordalo et al. (Q J Econ 127:1243–1285, 2012), Frydman and Mormann (The role of salience in choice under risk: An experimental investigation. Working Paper, 2018), and Bruhin et al. (J Risk Uncertain 65:139–184, 2022); (2) choices between Mao pairs as studied by Dertwinkel-Kalt and Köster (J Eur Econ Assoc 18:2057–2107, 2020). In both settings, we find evidence suggesting that recent findings supporting correlation effects are largely driven by ESE. Once controlling for ESE, we find no consistent evidence for correlation effects. Our results thus shed doubt on the validity of salience theory in describing risky behavior.
When can exogenous changes in beliefs generate endogenous fluctuations in rational expectation models? We analyze this question in the canonical one-sector and two-sector models of the business cycle with increasing returns to scale. A key feature of our analysis is that we express the uniqueness/multiplicity condition of equilibirum paths in terms of restrictions on five critical and economically interpretable parameters: the Frisch elasticities of the labor supply curve with respect to the real wage and to the marginal utility of wealth, the intertemporal elasticity of substitution in consumption, the elasticity of substitution between capital and labor, and the degree of increasing returns to scale. We obtain two clear-cut conclusions: belief-driven fluctuations cannot exist in the one-sector version of the model for empirically consistent values for these five parameters. By contrast, belief-driven fluctuations are a robust property of the two-sector version of the model—with differentiated consumption and investment goods—, as they now emerge for a wide range of parameter values consistent with available empirical estimates. The key ingredients explaining these different outcomes are factor reallocation between sectors and the implied variations in the relative price of investment, affecting the expected return on capital accumulation.
We study the impact of socioeconomic factors on two key parameters of epidemic dynamics. Specifically, we investigate a parameter capturing the rate of deceleration at the very start of an epidemic, and a parameter that reflects the pre-peak and post-peak dynamics at the turning point of an epidemic like coronavirus disease 2019 (COVID-19). We find two important results. The policies to fight COVID-19 (such as social distancing and containment) have been effective in reducing the overall number of new infections, because they influence not only the epidemic peaks, but also the speed of spread of the disease in its early stages. The second important result of our research concerns the role of healthcare infrastructure. They are just as effective as anti-COVID policies, not only in preventing an epidemic from spreading too quickly at the outset, but also in creating the desired dynamic around peaks: slow spreading, then rapid disappearance.
We propose Fieller-type methods for inference on generalized entropy inequality indices in the context of the two-sample problem which covers testing the statistical significance of the difference in indices, and the construction of a confidence set for this difference. In addition to irregularities arising from thick distributional tails, standard inference procedures are prone to identification problems because of the ratio transformation that defines the considered indices. Simulation results show that our proposed method outperforms existing counterparts including simulation-based permutation methods and results are robust to different assumptions about the shape of the null distributions. Improvements are most notable for indices that put more weight on the right tail of the distribution and for sample sizes that match macroeconomic type inequality analysis. While irregularities arising from the right tail have long been documented, we find that left tail irregularities are equally important in explaining the failure of standard inference methods. We apply our proposed method to analyze income per-capita inequality across U.S. states and non-OECD countries. Empirical results illustrate how Fieller-based confidence sets can: (i) differ consequentially from available ones leading to conflicts in test decisions, and (ii) reveal prohibitive estimation uncertainty in the form of unbounded outcomes which serve as proper warning against flawed interpretations of statistical tests.
