The COVID-19 pandemic have brought unexpected and unprecedented disruption to everyday life: its repercussions on mental health appear to be the most ignored by policy-makers to date.

In this paper, we contribute to the literature on mental health and the pandemic by analysing the drivers of self-assessed mental health within the population group of working-age (20-65) women. Specifically, exploiting a unique survey run in July 2020 on a representative sample of about 4,000 women in Italy, we investigate the relative roles of two groups of drivers: Present issues and Expectations. Present issues are defined by factors that play a role at the moment of filling the survey (e.g., present working status), while expectations includes the respondent’s speculations about future events (e.g., fear of loosing the job).

Italy is an interesting case study because during the first wave was a European unique case for both the intensity of the pandemic and the measure adopted to contain its spread. From the beginning of March 2020 and for 10 weeks, extremely strict restrictions to mobility and economic activities were enforced even in areas where the level of contagion was quite low (e.g. Southern part of the country).2 During the second wave of the pandemic, started at the end of October 2020, mobility was heavily limited, a night curfew was established, and regions were assigned to a system based on 3 colours from yellow, the lowest severity with fewer daily life restrictions, to red, the highest severity and restrictions. It was established that every other week, the colour assigned to each region would be updated on the basis of the most recent data on their intensive care units occupancy rate. From November 3rd to February 15, some regions, never experienced a red week, while others spent more than a month in red status.

Our aim is to evaluate the role of present issues and of expectations in explaining variations in self-assessed mental well-being. The outcome is measured by means of a proxy: level of mental distress (e.g., feelings of depression). We add two additional outcomes: one groups potential causes of mental distress and it is proxied by the level of personal concerns (e.g., being concerned for own health), the other proxied potential consequences, as the use of drugs to fight anxiety or sleeping problems. Net of socio-demographics covariates and contextual factors (i.e., provincial-level controls and regional fixed-effects), our findings show that present issues play a minor role compared to expectations. The relevance of expectations is remarkable also on the components of each outcome index (see Table 2): among the present issues, especially the level of agreement with the stay-at-home orders do play a significant role (e.g., on the fear that something bad is about to happen, the consumption of drugs, the concerns over the personal and relatives’ health).

Our results are robust to a rich set of tests, which include the use of additional controls (Table A7), a different sample selection (Table A8), alternative controls for the incidence of the pandemic (Table A9), and dummyTXdummy-(alternative definitions of the outcomes (Table A10). Moreover, we show that controlling for unobservable individual characteristics with a follow-up run in February 2021, still preserves the role of negative expectations on mental distress (Table A13).

We further dig into the role of expectations on mental health by analysing 4 potential drivers of expectations: age, the level of education, the sector of employment, and the individual gender stereotypes. The latter is included following the intuition behind the work of [1], according to which the larger gender gap in ordinary mental conditions (e.g., depression, anxiety) is a function of women feeling disempowered and lacking control over the major socioeconomic determinants such as income, employment, and social position. Comparing the reported happiness of men and women since the 1970s [2] show that women’s self-reported well-being has greatly decreased, both in absolute terms and relative to that of men. They suggest that this finding could be related to changes in women’s aspirations: although these are no longer fulfilled only within the household, women are still expected to play greater roles as caregivers.

Focusing on Present issues and Expectations links our contribution to the broader literature on how instability, especially in the labor market, affects mental health and its potential drivers (see, for instance, [3], [4]). However, we improve in that respect since we are not testing the relevance of an objective uncertainty (sudden closure of a firm or working under a particular working agreement), but we focus on a general fear of the future triggered by the pandemic. More recently, this stream has been enriched by researches that specifically focus on the role played by instability during COVID-19 and their effects on mental health using both data from the US, [5] and [6], and from Europe [7]. [5] observe that concerns on the economic consequences of the pandemic are more relevant than the immediate impact of the pandemic to predict a deterioration in mental health, while [6] find that job insecurity due to COVID-19 have a direct effect on the frequency of depressive symptoms. [7] find evidence of a strong association between experiencing economic hardships during the COVID-19 lockdown and a deterioration in mental health (i.e., incidence rates of feelings of depression and anxiety), with occupational position mediating the magnitude of the correlation (i.e., individuals in higher prestige-ranked jobs are less exposed to a deterioration in mental health). [8] mainly focus on the role of present issues, showing a deterioration in mental health after day life restrictions, while [9] provides evidence that women were more affected than men during this period (see also [10] and [11]). However, [9] excludes the relationship between potential channels for these more adverse outcomes and present issues such as financial distress, increased childcare responsibility, and local intensity of COVID-19 outbreaks.

This paper is organized as follows. Section 2 provides a description of our dataset (Section 2.1), the outcomes of interest (Section 2.2) and the econometric specifications (Section 2.3). Section 3 presents the main results, while robustness checks are described in Sections 3.3 and 3.4. Section 3.5 analyses the drivers, and section 4 concludes the paper.