ABSTRACT
The relation between equity and efficiency remains at the heart of regional policy. This study captures the effect of the COVID-19 pandemic government responses on the above-mentioned relation. To do so, we employ cross-sectional data from US states for 2020 and a spatial econometric model specification in the context of Corona policy effects. We find an inverted-‘U’ relationship between inequality and efficiency. Additionally, the effect of the intensity of government responses to COVID-19 on the equity–efficiency relation depends on the state’s per capita gross domestic product (GDP) levels.
ACKNOWLEDGEMENTS
We thank three anonymous referees and an associate editor for their constructive comments and suggestions, which substantially enhanced the merit of the paper. All remaining errors are ours.
DISCLOSURE STATEMENT
No potential conflict of interest was reported by the authors.
Notes
1. Following the no ‘island’ rule, Alaska and Hawaii were excluded from our sample.
2. The values of the Gini index range from 0 to 1, where 0 indicates that the income distribution is equal (everyone earns the same income) and 1 denotes perfect inequality (one person/household earns all the income).
3. The indices reported by the Oxford COVID-19 Government Response Tracker at the state level for the United States do not include federal policies that apply to the country as a whole. However, these indices may reflect a mixture of federal and state government responses since the federal government gave recommendations which may have been followed.
4. The corresponding data were retrieved from the following sources: unionstats.com – a description of the dataset is provided by Hirsch and Macpherson (Citation2003) (labour union membership), US Census Bureau (human capital), US Census Bureau (environmental organizations), and America’s Health Rankings (Citation2021) (adolescent fertility).
5. At this point, it is important to note that the fact that the Gini index is a fraction may produce predictions outside the [0, 1] boundary. Therefore, as a robustness check, we re-estimate our model using a spatial Tobit estimator (the estimation was performed using the -spregcs- Stata command; Shehata, Citation2016). The results (which are available from the authors upon request) are qualitatively similar to those presented in .
6. From a total of 384 MSAs, 18 were removed due to missing values and 40 due to the spatial specification (islands).
7. D5/D1 had also a strong positive correlation with another widely used measure of inequality – that of D9/D1 (the ratio between the upper 10th and the lower 10th percentile of wages) in our data.
8. The level of economic support provided during the pandemic may increase moral hazard in a similar way as do the level of unemployment insurance benefits.