## Section 5 — Gender gaps along alternative labor margins (hours worked, labor force participation, unemployment)

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---

### II. Data and definition
- Sample and data frequency:
  - Employment rate and unemployment rate by gender and age available for 38 countries at quarterly frequency from the OECD (30 advanced economies and 8 emerging market economies).
  - Sectoral employment by gender: quarterly Eurostat data for 19 European countries with populations over 2 million.
  - Average hours worked available for European countries only.
  - Analysis ends in 2020:Q3 due to data availability.
- She-cession definitions:
  - Absolute gender gap change (Equation (1)):
    - Δet,2019avg Diff,W−M = (etW − e2019avgW) − (etM − e2019avgM)
  - Relative gender gap change (Equation (2)):
    - Δet,2019avg DiffRatio,W−M = (etW / e2019avgW) − (etM / e2019avgM)
  - A she-cession is called if the gender gap change (Δet,2019avg ⋅,W−M) is negative (women’s drop in employment is greater than men’s).

### III. Extent and persistence of COVID-19 she-cessions across countries
- Central observations for 2020:Q2 (the trough):
  - Median country’s employment rate falls (deviation from 2019 average): women’s employment rate falls by around 1.7 percentage points and men’s by around 1.6 percentage points.
  - Percent change relative to 2019: declines are about 2.5 percent for women and about 2 percent for men.
- Incidence and heterogeneity (absolute gender gap change, Equation (1)):
  - 53 percent of countries in the sample experienced a she-cession in 2020:Q2 (Table 1: All = 0.53).
  - By 2020:Q3, 32 percent of the sample countries remained in a she-cession (Table 1: All = 0.32).
  - Emerging market economies: 50 percent in she-cession in 2020:Q2 and 38 percent by 2020:Q3 (Table 1: EMs 0.50 and 0.38).
  - Severity: Canada and Iceland had absolute gender gap changes of more than 1 percentage point; several countries (Poland, Sweden, Finland, New Zealand, Lithuania) follow with large absolute changes.
  - About 40 percent of the economies experiencing she-cessions had she-cession gender gap changes of a half percentage point or more (or about a fifth of all economies in the sample).
- Incidence and heterogeneity (relative gender gap change, Equation (2)):
  - About two-thirds of economies were experiencing she-cessions in 2020:Q2 (Table 2: All = 0.68).
  - By 2020:Q3 this declines to about 45 percent (Table 2: All = 0.45).
  - Advanced economies: 0.63 in 2020:Q2 and 0.37 in 2020:Q3 (Table 2).
  - Emerging market economies: 0.88 in 2020:Q2 and 0.75 in 2020:Q3 (Table 2).
- Comparison with the global financial crisis:
  - Using the absolute gender gap change comparing 2009:Q2 with the 2007 average: only 8 percent of countries experienced a she-cession in 2009:Q2, and 5 percent by 2009:Q3.

### IV. The role of sectoral workforce composition in asymmetric employment impacts by gender
- Candidate drivers of uneven impacts on women:
  1. Women’s higher preexisting employment shares in sectors particularly hit by COVID-19.
  2. Within-sector worse labor market outcomes for women.
- Aggregate sectoral patterns (restricted sample of 20 European countries with sectoral data):
  - Sectors with larger shares of women’s employment: employment-to-population ratio fell by about 0.11 percentage points on average from 2019 to 2020:Q2.
  - Sectors with higher shares of men’s employment: fell by an average of 0.07 percentage points as of 2020:Q2.
  - Examples:
    - Accommodation and food: accounts for 6.5 percent of women’s employment and saw its employment-to-population ratio decline by 0.62 percentage points on average during the pandemic.
    - Wholesale and retail: accounts for 13.7 percent of women’s employment and saw its ratio drop by 0.42 percentage points by 2020:Q2.
    - Construction: 11.1 percent of employed men have jobs in construction; construction’s employment-to-population ratio fell by 0.17 percentage points on average.
- Sectoral gender-differentiated outcomes:
  - Health sector example: men’s employment increased by 0.14 percentage points while women’s employment fell by 0.14 percentage points.
  - Overall, in 9 sectors women’s employment fell by more than men’s, while the opposite is true in 10 sectors.
- Decomposition of the absolute gender gap change:
  - The change in the gender gap in employment rates between 2019 (average) and 2020:Q2 is decomposed into:
    - Change in sectoral employment (holding fixed women’s employment shares by sector).
    - Change in gender shares of employment within sectors.
  - Country-level decomposition findings (Figure 7, restricted sample Table A.1):
    - About half of the countries (9 out of 20 in the sample) appear to be in she-cession over 2019 to 2020:Q2.
    - In 8 out of these 9 countries, changes in gender shares of sectoral employment are the driving factor of the she-cession.
    - For 2019 average to 2020:Q3 (data-limited sample of 18 countries): 7 out of 18 countries appear to be in she-cession, and in 5 out of these 7 countries changes in gender shares of sectoral employment are the driving factor.
    - For a restricted set using the relative gap change: 12 countries in she-cession, and in 10 out of these 12 the change in gender shares of sectoral employment is the driving factor.

### V. Margins of labor market changes: hours worked, unemployment, and labor force participation
- Importance of margins:
  - Employment rate (extensive margin) does not capture reductions in hours worked (intensive margin) for those still employed.
  - Employment rate change equals changes in labor force participation minus changes in unemployment (with weights).
  - Literature notes women have a higher average likelihood of exiting the labor force than men.
- Average hours worked (intensive margin):
  - Men experienced a larger reduction in average hours worked than women in most countries.
  - Median gender gap change for average hours worked relative to 2019 rose (Figure 8, panel A).
  - The pattern implies she-cessions are largely phenomena related to the extensive margin (employment), not the intensive margin.
- Unemployment vs. labor force participation contributions:
  - Absolute gender gap change decomposition shows declines in women’s labor force participation contribute more frequently and with larger magnitude to negative gender gap changes in employment than relative rises in women’s unemployment (Figures 8 panels b and c; Figure 9).
  - Relative gender gap change indicators show similar patterns: relative labor force participation fell on average in 2020:Q2, while relative unemployment for women rose somewhat; both reverse by 2020:Q3 (Figure 10).
- Sample notes:
  - Analysis of hours worked uses the same sample of 20 countries as the sectoral decomposition due to data availability.

### VI. Conclusion and policy implications
- Summary conclusions:
  - There is high heterogeneity across countries in the incidence and severity of COVID-19 she-cessions.
  - More than half to two-thirds of countries experienced a she-cession in 2020:Q2, but she-cessions tend to be short-lived with between three-fifths to two-thirds of countries out of she-cession by 2020:Q3.
  - For countries with sectoral gender data, she-cessions were predominantly driven by declining women’s shares in employment within sectors, especially in sectors that account for more of women’s employment.
  - COVID-19 she-cessions are primarily phenomena of the extensive margin (employment); average hours worked for employed women fell less than for men.
  - Much of the relative employment decline reflects women’s greater propensity to exit the labor force than men, rather than shifts into unemployment.
  - The relative drop in women’s labor force participation may partly reflect greater impacts on mothers, particularly lower-income and lower-skilled mothers, as childcare burdens increased.
- Policy recommendations:
  - Ensure that affordable and reliable childcare options are available (whether privately or publicly provided).
  - Ensure family leave is available for equitable use by men and women (recognizing evolving gender roles).
  - Provide flexibility in work hours as job requirements allow.

### Annex: Robustness on the role of sectoral workforce composition
- Robustness checks performed:
  - Alternative 1: Change from 2019 (average) to 2020:Q3 (instead of 2020:Q2 used in Section IV).
  - Alternative 2: Decomposition of the change using the relative gender gap change (equation (A.1)) from 2019 (average) to 2020:Q2.
- Findings (absolute change, 2019 to 2020:Q3):
  - For 2019 to 2020:Q3: 7 out of 18 countries (instead of 9 out of 20 countries) appear to be in she-cession — that is, the change in the overall gender gap in employment rates is negative.
  - In 5 countries out of these 7 countries, changes in gender shares of sectoral employment are the driving factor of the she-cession.
- Findings (relative change, 2019 to 2020:Q2):
  - Using the relative gender gap change from equation (A.1): 12 out of 20 countries appear to be in she-cession.
  - In 10 countries out of these 12 countries, changes in gender shares of sectoral employment are the driving factor of the she-cession.
- Mathematical decomposition (relative gender gap change, equation (A.1) as presented):
  - (
    푒푡+1푤 −푒푡푤
   )/푒푡푤 − (
    푒푡+1푚 −푒푡푚
   )/푒푡푚
   = [
   (
    ∑ 휔푠,푡 (퐸푠,푡+1푃푡+1푤 − 퐸푠,푡푃푡푤) 푠
   )/푒푡푤 − (
    ∑ (1−휔푠,푡) (퐸푠,푡+1푃푡+1푚 − 퐸푠,푡𝑃𝑡𝑚) 푠
   )/푒푡𝑚
   ] ︳ change in sectoral employment
   +
   [
   (
    ∑ (휔푠,푡+1 − 휔푠,푡) (퐸푠,푡+1𝑃𝑡+1푤) 푠
   )/푒푡푤 − (
    ∑ (휔푠,푡 − 휔푠,푡+1) (퐸푠,푡+1𝑃𝑡+1𝑚) 푠
   )/푒푡𝑚
   ] ︳ change in gender share

*Source: wpiea2021095-print-pdf*

### Section 5 examines gender gaps along alternative labor margins, including hours worked, labor force

### Section 5 — Gender gaps along alternative labor margins (hours worked, labor force participation, unemployment)

### II. Data and definition
- Sample and data frequency:
  - Employment rate and unemployment rate by gender and age available for 38 countries at quarterly frequency from the OECD (30 advanced economies and 8 emerging market economies).
  - Sectoral employment by gender: quarterly Eurostat data for 19 European countries with populations over 2 million.
  - Average hours worked available for European countries only.
  - Analysis ends in 2020:Q3 due to data availability.
- She-cession definitions:
  - Absolute gender gap change (Equation (1)):
    - Δet,2019avg Diff,W−M = (etW − e2019avgW) − (etM − e2019avgM)
  - Relative gender gap change (Equation (2)):
    - Δet,2019avg DiffRatio,W−M = (etW / e2019avgW) − (etM / e2019avgM)
  - A she-cession is called if the gender gap change (Δet,2019avg ⋅,W−M) is negative (women’s drop in employment is greater than men’s).

### III. Extent and persistence of COVID-19 she-cessions across countries
- Central observations for 2020:Q2 (the trough):
  - Median country’s employment rate falls (deviation from 2019 average): women’s employment rate falls by around 1.7 percentage points and men’s by around 1.6 percentage points.
  - Percent change relative to 2019: declines are about 2.5 percent for women and about 2 percent for men.
- Incidence and heterogeneity:
  - Using the absolute gender gap change (Equation (1)):
    - 53 percent of countries in the sample experienced a she-cession in 2020:Q2 (Table 1: All = 0.53).
    - By 2020:Q3, 32 percent of the sample countries remained in a she-cession (Table 1: All = 0.32).
    - Emerging market economies: 50 percent in she-cession in 2020:Q2 and 38 percent by 2020:Q3 (Table 1: EMs 0.50 and 0.38).
    - Severity: Canada and Iceland had absolute gender gap changes of more than 1 percentage point; several countries (Poland, Sweden, Finland, New Zealand, Lithuania) follow with large absolute changes.
    - About 40 percent of the economies experiencing she-cessions had she-cession gender gap changes of a half percentage point or more (or about a fifth of all economies in the sample).
  - Using the relative gender gap change (Equation (2)):
    - About two-thirds of economies were experiencing she-cessions in 2020:Q2 (Table 2: All = 0.68).
    - By 2020:Q3 this declines to about 45 percent (Table 2: All = 0.45).
    - Advanced economies: 0.63 in 2020:Q2 and 0.37 in 2020:Q3 (Table 2).
    - Emerging market economies: 0.88 in 2020:Q2 and 0.75 in 2020:Q3 (Table 2).
- Comparison with the global financial crisis:
  - Using the absolute gender gap change comparing 2009:Q2 with the 2007 average: only 8 percent of countries experienced a she-cession in 2009:Q2, and 5 percent by 2009:Q3.

### IV. The role of sectoral workforce composition in asymmetric employment impacts by gender
- Two candidate drivers of uneven impacts on women:
  1. Women’s higher preexisting employment shares in sectors particularly hit by COVID-19.
  2. Within-sector worse labor market outcomes for women.
- Aggregate sectoral patterns (restricted sample of 20 European countries with sectoral data):
  - Sectors with larger shares of women’s employment: employment-to-population ratio fell by about 0.11 percentage points on average from 2019 to 2020:Q2.
  - Sectors with higher shares of men’s employment: fell by an average of 0.07 percentage points as of 2020:Q2.
  - Examples:
    - Accommodation and food: accounts for 6.5 percent of women’s employment and saw its employment-to-population ratio decline by 0.62 percentage points on average during the pandemic.
    - Wholesale and retail: accounts for 13.7 percent of women’s employment and saw its ratio drop by 0.42 percentage points by 2020:Q2.
    - Construction: 11.1 percent of employed men have jobs in construction; construction’s employment-to-population ratio fell by 0.17 percentage points on average.
- Sectoral gender-differentiated outcomes:
  - Health sector example: men’s employment increased by 0.14 percentage points while women’s employment fell by 0.14 percentage points.
  - Overall, in 9 sectors women’s employment fell by more than men’s, while the opposite is true in 10 sectors.
- Decomposition of the absolute gender gap change (Equation (2) decomposition):
  - The change in the gender gap in employment rates between 2019 (average) and 2020:Q2 is decomposed into:
    - Change in sectoral employment (holding fixed women’s employment shares by sector).
    - Change in gender shares of employment within sectors.
  - Findings from country-level decomposition (Figure 7, restricted sample Table A.1):
    - About half of the countries (9 out of 20 in the sample) appear to be in she-cession over 2019 to 2020:Q2.
    - In 8 out of these 9 countries, changes in gender shares of sectoral employment are the driving factor of the she-cession.
    - For 2019 average to 2020:Q3 (data-limited sample of 18 countries): 7 out of 18 countries appear to be in she-cession, and in 5 out of these 7 countries changes in gender shares of sectoral employment are the driving factor.
    - For a restricted set using the relative gap change: 12 countries in she-cession, and in 10 out of these 12 the change in gender shares of sectoral employment is the driving factor.

### V. Margins of labor market changes: hours worked, unemployment, and labor force participation
- Importance of margins:
  - Employment rate (extensive margin) does not capture reductions in hours worked (intensive margin) for those still employed.
  - Employment rate change equals changes in labor force participation minus changes in unemployment (with weights).
  - Literature notes women have a higher average likelihood of exiting the labor force than men.
- Average hours worked (intensive margin):
  - Contrary to prior expectation, men experienced a larger reduction in average hours worked than women in most countries.
  - Median gender gap change for average hours worked relative to 2019 rose (Figure 8, panel A).
  - The pattern implies she-cessions are largely phenomena related to the extensive margin (employment), not the intensive margin.
- Unemployment vs. labor force participation contributions:
  - Absolute gender gap change decomposition shows declines in women’s labor force participation contribute more frequently and with larger magnitude to negative gender gap changes in employment than relative rises in women’s unemployment (Figures 8 panels b and c; Figure 9).
  - Relative gender gap change indicators show similar patterns: relative labor force participation fell on average in 2020:Q2, while relative unemployment for women rose somewhat; both reverse by 2020:Q3 (Figure 10).
- Sample notes:
  - Analysis of hours worked uses the same sample of 20 countries as the sectoral decomposition due to data availability.

### VI. Conclusion and policy implications
- Summary conclusions:
  - There is high heterogeneity across countries in the incidence and severity of COVID-19 she-cessions.
  - More than half to two-thirds of countries experienced a she-cession in 2020:Q2, but she-cessions tend to be short-lived with between three-fifths to two-thirds of countries out of she-cession by 2020:Q3.
  - For countries with sectoral gender data, she-cessions were predominantly driven by declining women’s shares in employment within sectors, especially in sectors that account for more of women’s employment.
  - COVID-19 she-cessions are primarily phenomena of the extensive margin (employment); average hours worked for employed women fell less than for men.
  - Much of the relative employment decline reflects women’s greater propensity to exit the labor force than men, rather than shifts into unemployment.
  - The relative drop in women’s labor force participation may partly reflect greater impacts on mothers, particularly lower-income and lower-skilled mothers, as childcare burdens increased.
- Policy recommendations (preserving source emphasis and language):
  - Ensure that affordable and reliable childcare options are available (whether privately or publicly provided).
  - Ensure family leave is available for equitable use by men and women (recognizing evolving gender roles).
  - Provide flexibility in work hours as job requirements allow.

*Source: IMF staff analysis in the provided content unit.*

### References

### References

### Key citations
- Adams-Prassl, A., Boneva, T., Golin, M., and C. Rauh. 2020. “Inequality in the impact of the coronavirus shock: Evidence from real time surveys.” Journal of Public Economics 189: 104245.
- Aisenbrey, S., Evertsson, and D. Grunow. 2009. “Is There a Career Penalty for Mothers’ Time Out? A Comparison of Germany, Sweden, and the United States.” Social Forces, 88 (2): 573–605.
- Albanesi, S., and J. Kim. 2021. “The Gendered Impact of the COVID-19 Recession on the US Labor Market.” NBER Working Papers 28505. National Bureau of Economic Research, Cambridge, MA.
- Albrecht, J., P. Edin, M. Sundström, and S. Vroman. 1999. “Career Interruptions and Subsequent Earnings: A Reexamination Using Swedish Data.” Journal of Human Resources, 34 (2): 294–311.
- Alon, T., M. Doepke, J. Olmstead-Rumsey, and M. Tertilt. 2020. “This Time It’s Different: The Role of Women’s Employment in a Pandemic Recession.” NBER Working Paper 27660. National Bureau of Economic Research, Cambridge, MA.
- Bahn, K. and C. Sanchez Cumming. 2020. “How the coronavirus recession is impacting part-time U.S. workers.” Equitable Growth (blog).
- Blau, F. D. and L. M. Kahn. 2013. “Female Labor Supply: Why Is the United States Falling Behind?” American Economic Review 103 (3): 251–56.
- Caselli, F., F. Grigoli, D. Sandri, and A. Spilimbergo. 2020. “Mobility under the COVID-19 Pandemic Asymmetric Effects across Gender and Age.” IMF Working Paper 20/282. International Monetary Fund, Washington, DC.
- Chetty, R., J. Friedman, N. Hendren, M. Stepner, and The Opportunity Insights Team. 2020. “The Economic Impacts of COVID-19: Evidence from a New Public Database Built Using Private Sector Data.” NBER Working Paper 27431. National Bureau of Economic Research, Cambridge, MA.
- Coibion, O., Y. Gorodnichenko, and M. Weber. 2020. “Labor Markets during the Covid-19 Crisis: A Preliminary View.” NBER Working Paper 27017. National Bureau of Economic Research, Cambridge, MA.
- Elborgh-Woytek, K., M. Newiak, K. Kochhar, S. Fabrizio, K. Kpodar, P. Wingender, B. Clements, and G. Schwartz. 2013. “Women, Work and the Economy: Macroeconomic Gains from Gender Equity.” Staff Discussion Note SDN13/10, International Monetary Fund, Washington.
- Fabrizio S., D. Gomes, and M. M. Tavares. 2021. “COVID-19 She-cession: The Employment Penalty of Taking Care of Young Children.” IMF Working Paper 21/55. International Monetary Fund, Washington, DC.
- Fuchs-Schündeln, N., D. Krueger, A. Ludwig, and I. Popova. 2020. “The Long-Term Distributional and Welfare Effects of COVID-19 School Closures.” NBER Working Paper 27773. National Bureau of Economic Research, Cambridge, MA.
- Goldin, C. 2015. “How to Achieve Gender Equality.” Milken Institute Review, 2015 (Q3): 24–33.
- Gonzales, C., S. Jain-Chandra, K. Kochhar, M. Newiak, and T. Zeinullayev. 2015a. “Catalyst for Change: Empowering Women and Tackling Income Inequality.” Staff Discussion Note SDN/15/20, International Monetary Fund, Washington.
- Giupponi, G. and C. Landais. 2020. “Building Effective Short-term Work Schemes for the COVID-19 Crisis.” VoxEU (blog).
- Hoynes, H., D. Miller, and J. Schaller. 2012. “Who Suffers During Recessions?” Journal of Economic Perspectives, 26 (3): 27–48.
- Hupkau, C. and B. Petrongolo. 2020. “Work, Care, and Gender During the COVID-19 Crisis.” Fiscal Studies, 41 (3): 623–51.
- International Monetary Fund (IMF). 2021. “Recessions and Recoveries in Labor Markets: Patterns, Policies, and Responding to the COVID-19 Shock.” In World Economic Outlook April 2021.
- Mongey, S., L. Pilossoph, and A. Weinberg. 2020. “Which Workers Bear the Burden of Social Distancing Policies?” NBER Working Paper 27085. National Bureau of Economic Research, Cambridge, MA.
- Petrongolo, B. 2004. “Gender Segregation in Employment Contracts.” Journal of the European Economic Association, 2: 331–45.
- Romei, V. 2021. “I am close to quitting my career’: Mothers step back at work to cope with pandemic parenting,” available at https://www.ft.com/content/d5d01f06-9f7c-4cdc-9fee-225e15b5750b
- Russell, L., and C. Sun. 2020. “The effect of mandatory childcare center closures on women's labor market outcomes during the COVID-19 pandemic.” Covid Economics 62: 124–54.
- Shibata, I. 2020. “The Distributional Impact of Recessions: The Global Financial Crisis and The Pandemic Recession.” IMF Working Paper 20/96. International Monetary Fund, Washington, DC.
- Vuri, D. 2016. “Do Childcare Policies Increase Maternal Employment?” IZA World of Labor, 2016 (March): 241.
- Wall, H. 2009. “The Man-Cession of 2008-09: It’s Big, But It’s Not Great.” The Regional Economist. 2009 (October): 4–9.
- Zamarro, G., and M. Prados. 2021. “Gender Differences in Couple’s Division of Childcare, Work and Mental Health.” Review of Economics of the Household 19: 11–40.

### Table A1: List of countries by section

- Columns: Country, iso3code, AEs, EMs, Full Sample, Restricted Sample
- Entries (preserve values exactly):

1. Australia AUS 1 0 1  
2. Austria AUT 1 0 1 1  
3. Belgium BEL 1 0 1 1  
4. Canada CAN 1 0 1  
5. Chile CHL 0 1 1  
6. Colombia COL 0 1 1  
7. Czech Republic CZE 1 0 1 1  
8. Denmark DNK 1 0 1 1  
9. Estonia EST 1 0 1  
10. Finland FIN 1 0 1 1  
11. France FRA 1 0 1 1  
12. Germany DEU 1 0 1  
13. Greece GRC 1 0 1 1  
14. Hungary HUN 0 1 1 1  
15. Iceland ISL 1 0 1  
16. Ireland IRL 1 0 1 1  
17. Israel ISR 1 0 1  
18. Italy ITA 1 0 1 1  
19. Japan JPN 1 0 1  
20. Korea KOR 1 0 1  
21. Latvia LVA 1 0 1  
22. Lithuania LTU 0 1 1  
23. Luxembourg LUX 1 0 1  
24. Netherlands NLD 1 0 1 1  
25. New Zealand NZL 1 0 1  
26. Norway NOR 1 0 1 1  
27. Poland POL 0 1 1 1  
28. Portugal PRT 1 0 1 1  
29. Russia RUS 0 1 1  
30. Slovak Republic SVK 1 0 1 1  
31. Slovenia SVN 1 0 1 1  
32. South Africa ZAF 0 1 1  
33. Spain ESP 1 0 1 1  
34. Sweden SWE 1 0 1 1  
35. Switzerland CHE 1 0 1  
36. Turkey TUR 0 1 1 1  
37. United Kingdom GBR 1 0 1 1  
38. United States USA 1 0 1

- Totals line: 38 20

### Annex: Robustness on the role of sectoral workforce composition

### Robustness checks performed
- Decomposition of the total change in the gender gap:
  - Alternative 1: Change from 2019 (average) to 2020:Q3 (instead of 2020:Q2 used in Section IV).
  - Alternative 2: Decomposition of the change using the relative gender gap change (equation (A.1)) from 2019 (average) to 2020:Q2.

### Findings (absolute change, 2019 to 2020:Q3)
- For 2019 to 2020:Q3: 7 out of 18 countries (instead of 9 out of 20 countries) appear to be in she-cession — that is, the change in the overall gender gap in employment rates is negative.
- In 5 countries out of these 7 countries, changes in gender shares of sectoral employment are the driving factor of the she-cession.

Note explaining chart interpretation:
- Grey dot: gender gap change.
- Blue bar: component due to the change in gender share.
- Red bar: component due to the change in sectoral employment.
- A negative value indicates the relevant factor contributed to a more negative impact for women than for men; a positive value means the relevant factor contributed to a more negative impact for men than women.
- Note: Figure A1 is based on restricted sample (Table A.1).

### Findings (relative change, 2019 to 2020:Q2)
- Using the relative gender gap change from equation (A.1): 12 out of 20 countries appear to be in she-cession.
- In 10 countries out of these 12 countries, changes in gender shares of sectoral employment are the driving factor of the she-cession.

Note explaining chart interpretation:
- Figure A2 reports the two components which sum to the average gender gap change by country as defined by Equation (2). Based on restricted sample (Table A.1).
- For Figure A2 only 18 countries are included due to data availability for 2020:Q3.

### Mathematical decomposition (as presented)
- Relative gender gap change expression (A.1) as given in the source:
  - (
    푒푡+1푤 −푒푡푤
   )/푒푡푤 − (
    푒푡+1푚 −푒푡푚
   )/푒푡푚
   = [
   (
    ∑ 휔푠,푡 (퐸푠,푡+1푃푡+1푤 − 퐸푠,푡푃푡푤) 푠
   )/푒푡푤 − (
    ∑ (1−휔푠,푡) (퐸푠,푡+1푃푡+1푚 − 퐸푠,푡푃푡푚) 푠
   )/푒푡푚
   ] ︳ change in sectoral employment
   +
   [
   (
    ∑ (휔푠,푡+1 − 휔푠,푡) (퐸푠,푡+1푃푡+1푤) 푠
   )/푒푡푤 − (
    ∑ (휔푠,푡 − 휔푠,푡+1) (퐸푠,푡+1푃푡+1푚) 푠
   )/푒푡푚
   ] ︳ change in gender share

- Variables are notated similarly to Section IV of the main text.

*Source: wpiea2021095-print-pdf - References*

---


_Source: https://www.imf.org/-/media/files/publications/wp/2021/english/wpiea2021095-print-pdf.pdf_