ATLANTIC ECONOMIC JOURNAL最新文献

This paper offers empirical evidence on minimum wage spillovers into rental housing markets. Minimum wage spillovers may arise from two channels shifting housing demand: migration or minimum wage impacts on low-wage worker real income. Reduced-form estimation and a pooled event study exploit state-by-year variation from 1985—2023 in effective minimum wages to estimate the minimum wage’s impact on below median housing rents and low-wage worker population shares. The empirical strategies rely on rent data from the United States Department of Housing and Urban Development’s Fair Market Rents series and American Community Survey population shares data from the United States Census Bureau. The minimum wage has an inconclusive effect on low-wage worker population shares while reducing rents. A $1 minimum wage increase reduces below-median monthly rents by 0.7 – 2 percentage points. In contrast to the limited existing evidence for the minimum wage raising local housing prices, this paper’s evidence of the minimum wage decreasing below-median local housing rents contributes to the literature by suggesting a heterogeneous housing price response to increasing the minimum wage. It also offers new evidence affirming that higher minimum wages improve housing affordability.

In April 2023, Jake Sullivan, in a speech to the Brookings Institute, formally announced the replacement of what had become known since the1990s as the Washington Consensus with a New Washington Consensus. This paper defines and briefly describes the original Washington Consensus. It goes on to describe and discuss in detail the New Washington Consensus and its implications. Finally, the paper outlines the potential Trump approach to this specific Biden legacy, whether or not acknowledged. The broad geoeconomic and geopolitical implications of the unwinding of what is likely to transpire are explored briefly in the context of the Trump Presidency.

Since the 2008 global financial crisis, the detection of housing bubbles has attracted unprecedented attention. By using price-to-rent data collected from the Organization for Economic Co-operation and Development, this paper adopts the Phillips et al. right-tailed unit root tests to identify housing bubbles across the Group of Seven countries from the first quarter of 1970 to the second quarter of 2021. In addition, a novel estimation approach (the dynamic panel probit model) was employed to take account of the bubble persistence and explore the macroeconomic determinants driving the housing bubbles. The empirical results indicate that each country experienced episodes of housing bubbles and the bubble clusters appeared in two phases, namely, 2003–2008 and post-2016. More importantly, there is evidence that certain macroeconomic variables drove the housing bubbles, especially a low interest rate and rapidly-growing money supply. The policy implication of this study is that central banks implementing ultra-loose monetary policy need to take housing bubble risk into careful consideration.

Changes in population size and density in a jurisdiction affect its economic and social characteristics. Since increases and decreases in subnational population tend to offset each other resulting in a more subdued change at the national level, the challenge of population volatility is therefore largely a subnational problem. This research defines a parametric function called ɛ-volatility to analyze population volatility across the 50 states of the United States and the District of Columbia between 2010 and 2019. Three levels of volatility were considered to cover the full range of population changes: ɛ-normal, mildly ɛ-volatile, and strongly ɛ-volatile. Using data from the U.S. Census Bureau and Bureau of Labor Statistics, a multinomial linear regression model was used to examine the impact of educational attainment, unemployment, housing starts, wage, age and race on subnational volatility. The results suggest that subnational population volatility is most strongly influenced by the older working age group (45–64) that are at least high school graduates. The younger working age-group (18–44) also positively impacted population volatility regardless of educational attainment. The senior population (65 +) with high school or higher education affected population volatility to a lesser extent under certain circumstances. High population volatility can lead to urban squalor, congestion and fewer resources for social and municipal services. The ability to identify strong, mild, and normal population volatility can facilitate the formulation of policy decision-making at all levels.

Driven by the unfolding asymmetry in the United Kingdom output dynamics since 1955, this paper aims to explore the contribution of fiscal policy. To this end, the dynamic connectivity between United Kingdom government spending and economic growth is assessed through the concept of causality. Since the implementation of economic policy can asymmetrically affect output dynamics, both linear and nonlinear causality tests are employed. The empirical findings underscore the feature of nonlinearity. The detected nonlinear causality appears to be subject to different economic regimes. During the Great Moderation, the linear connectivity between government spending and economic growth strengthened, while in the post-2007 era, the absence of substantial linkages supports the idea that the information transmission channel between government spending and economic growth is broken. The study’s novelty lies in the implementation of linear and nonlinear causality tests within a rolling windows analysis framework. This approach enables the exploration of connectivity characteristics between United Kingdom government spending and output growth under changing monetary policy and economic stances. The findings confirm the role of fiscal policy as an economic stabilizer, mainly during periods of loose monetary policy with moderate inflation and predominantly positive economic growth rates. The results also reveal a significant structural break in 2007, coinciding with a change in monetary conditions and a period of limited fiscal control over output growth.

This study uses national natality data from the National Vital Statistics System, provided by the National Center for Health Statistics, covering the years 2011 to 2018 (N = 23,810,031) to investigate racial disparities in cesarean section (C-section) rates between non-Hispanic Black and non-Hispanic White mothers in the United States. This analysis offers a comprehensive perspective on the factors contributing to C-section disparities by considering mothers' demographic characteristics, health conditions, and infant health status. Using multivariable logistic regression, the findings reveal consistently higher C-section rates for non-Hispanic Black mothers compared to non-Hispanic White mothers, with the gap widening over time. Even after adjusting for sociodemographic and health-related factors, non-Hispanic Black mothers remained more likely to undergo C-sections. Using Blinder-Oaxaca decomposition methods, key factors contributing to this C-section rates disparity include maternal age, the source of delivery payment, and fetal presentation. This study highlights the pressing need for further investigation into healthcare system factors and racial inequities driving these disparities, alongside the growing urgency for policy and practical interventions to reduce unnecessary C-sections.