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Simulations of Policy Responses and Interventions to Promote Inclusive Adaptation to and Recovery from the COVID-19 Crisis in Ecuador

Research article
Cite this article as: C. Canelas, J. David Robalino; 2022; Simulations of Policy Responses and Interventions to Promote Inclusive Adaptation to and Recovery from the COVID-19 Crisis in Ecuador; International Journal of Microsimulation; 15(3); 89-103. doi: 10.34196/ijm.00271
3 figures and 9 tables

Figures

Individual labour income in 2019/2020 by gender and income decile. Source: ENEMDU December 2019 and authors’ simulations
Income distribution pre-COVID and post-COVID (September 2020) with and without transfers. Source: ENEMDU December 2019 and authors’ simulations. From left to right, the dashed lines represent: the extreme poverty line ($47.80), the moderate poverty line ($84.81), and the minimum wage line ($400). Income in USD
Lorenz curves pre- and post-COVID. Source: ENEMDU December 2019 and authors’ simulations.

Tables

Table 1
Macroeconomic Statistics
Indicator20152016201720182019
GDP (real 2007 $)70,17469,31470,95571,87071,909
GDP growth (% annual)0.1%-1.23%2.37%1.29%0.05%
Per capita GDP (real 2007 $)4,3104,1934,2294,2214,164
Per capita GDP growth (% annual)-1.45%-2.72%0.85%-0.18%-1.36%
Public debt (% GDP)33%38.2%44.6%45.2%44.9%
Primary fiscal deficit (% GDP)-1.68%-5.34%-5.39%-2.46%-2.48%
Total population16,278,84416,528,73016,776,97717,023,40817,267,986
Working age population11,399,27611,696,13111,937,92812,239,02312,402,565
Active population7,498,5287,874,0218,086,0488,027,1308,099,030
Activity rate (% labour force)65.78%67.32%67.73%65.59%65.3%
Unemployment rate (% labour force)4.77%5.21%4.62%3.69%3.84%
Informal work (% employed)*58.4%62.2%63%64.7%66.08%
Self-employed (% employed)*34.1%35.9%35.6%36.9%38.5%
Real mean monthly labour income355.6337.1341.2333.5325.8
  1. Source: Central Bank of Ecuador.

  2. *

    SEDLAC estimates.

  3. $ USD.

Table 2
Empirical change in labour income and employment in 2019/2020 by gender and economic sector
Economic sectorMean income among employed%Δ employmentExpected %Δ mean income
12/201906/202009/202012/19 - 6/2012/19 - 9/2012/19 - 6/2012/19 - 9/20
Female
Agriculture + fishing + mining77.8649.6577.35-26.46%-8.49%-53.11%-9.10%
Industry + electricity, gas & water324.77221.35278.52-25.38%-18.28%-49.14%-29.92%
Construction422.16432.41426.62-16.96%-5.66%-14.94%-4.66%
Trade277.39165.63236.39-27.92%1.39%-56.96%-13.59%
Restaurants & hotels305.5676.37215.01-20.97%-9.98%-80.25%-36.66%
Transportation & communication579.35423.97408.56-20.00%12.19%-41.46%-20.88%
Real estate408.75297.41398.92-48.04%-1.04%-62.20%-3.42%
Public administration and defence1008.34828.78970.1712.01%37.44%-7.94%32.24%
Education766.74702.07717.59-13.69%-0.07%-20.97%-6.48%
Health736.98677.06864.37-17.13%-4.89%-23.87%11.56%
Personal services300.79151.94278.81-44.36%-33.24%-71.89%-38.12%
Other services882.85851.41890.3928.84%30.29%-16.15%31.41%
All female309.97227.62295.71-26.42%-7.36%-45.97%-11.62%
Male
Agriculture + fishing + mining241.79146.09211.96-12.89%-7.57%-47.37%-18.97%
Industry + electricity, gas & water521.88315.27438.02-30.51%-3.19%-58.02%-18.75%
Construction425.92100.86356.34-42.16%-11.64%-86.30%-26.07%
Trade451.57228.04525.78-17.90%-2.71%-58.54%13.28%
Restaurants & hotels414.94145.06274.95-17.63%5.02%-71.20%-30.41%
Transportation & communication494.78211.28408.98-21.47%-19.50%-66.47%-33.46%
Real estate619.63338.42520.18-24.85%-10.52%-58.96%-24.88%
Public administration and defence1016.79925.271067.36-11.51%-9.65%-19.48%-5.16%
Education819.99695.47926.78-12.55%11.28%-25.83%25.77%
Health956.67885.62919.35-8.14%1.57%-14.96%-2.40%
Personal services459.19198.90388.30-23.87%-16.23%-67.02%-29.16%
Other services975.77717.171017.6318.44%10.97%-12.95%15.73%
All male437.45251.64410.99-19.96%-7.02%-53.96%-12.64%
All384.41242.08363.17-22.65%-7.16%-51.29%-12.29%
  1. Source: ENEMDU December 2019, May/June 2020, and September 2020.

  2. Note: The last two columns take into account the change in employment as zero-income.

  3. Note: Income in USD.

Table 3
Empirical change in non-labour income in 2019/2020
IncomeChange
Dec. 2019May 2020Sept. 2020% Δ Dec.-May% Δ Dec.-Sept.
Non-labour income44.3438.3744.30-13.46%-0.09%
Government transfers4.445.944.8033.75%8.06%
  1. Source: ENEMDU December 2019, May and September 2020 and authors’ calculations.

  2. Note: Changes in May 2020 and September 2020 are calculated with respect to December 2019.

  3. Note: Income in USD.

Table 4
Change in household per capita income in 2019/2020
December 2019May/June 2020September 2020
IncomeIncomeChangeIncomeChange
Household per capita income214.49120.21-43.95%193.18-9.93%
Household per capita labour income170.1481.83-51.90%148.83-12.52%
Household per capita non-labour income44.3538.38-13.46%44.30-0.13%
  1. Source: ENEMDU December 2019 and authors’ simulations of post-COVID incomes.

  2. Note: Income in USD.

Table 5
Monthly individual labour income pre- and post-COVID
Group% of workersDecember 2019May/June 2020September 2020
IncomeIncomeChangeIncomeChange
By gender
Female37.33%389.26205.62-47.18%343.53-11.75%
Male62.67%474.01216.82-54.26%412.6-12.96%
By age
<2611.11%309.61137.88-55.47%265.76-14.16%
26-6580.64%476.93231.60-51.44%418.23-12.31%
>658.25%282.97127.95-54.78%242.50-14.30%
By ethnicity
Indigenous13.72%300.51134.19-55.34%256.10-14.78%
Afro American5.03%379.83181.32-52.26%321.26-15.42%
Mestizo/white73.95%470.54227.53-51.65%414.01-12.02%
Other7.31%344.86163.54-52.58%290.20-15.85%
By education level
No high school50.73%320.6946130.5171-59.30%262.7539-18.07%
High school33.29%445.1933201.1437-54.82%383.0887-13.95%
Higher education15.98%835.7534506.4722-39.40%801.7644-4.07%
By employment type
Informal75.19%346.88139.44-59.80%289.17-16.64%
Formal24.81%669.88387.09-42.22%619.47-7.53%
By area
Rural28.92 %343.81164.66-52.11%287.72-16.31%
Urban71.08%483.09232.47-51.88%427.76-11.45%
By firm size
Big private (gt5 employees)23.8%576.07268.50-53.39%497.93-13.56%
Small private68.99%339.61135.30-60.16%282.72-16.75%
Public7.21%843.22646.44-23.34%864.642.54%
By income decile
110%111.8849.19-56.03%92.11-17.67%
210%185.9878.47-57.81%152.43-18.04%
310%248.93106.49-57.22%207.91-16.48%
410%274.42113.7-58.57%227.43-17.12%
510%304.21128.83-57.65%255.47-16.02%
610%344.37143.86-58.23%285.62-17.06%
710%382.19168.71-55.86%323.78-15.28%
810%444.31204.22-54.04%381.42-14.15%
910%529.2268.01-49.36%471.92-10.82%
1010%976.74525.97-46.15%896.08-8.26%
  1. Source: ENEMDU December 2019 and authors’ simulations of post-COVID incomes.

  2. Note: Income in USD.

Table 6
Average household per capita income pre-COVID and post-COVID with and without public transfers
Dec. 2019Sept. 2020 simulated income
IncomeWithout transfersWith transfers
All214.49193.19197.99
Poor54.2447.5353.36
  1. Source: ENEMDU December 2019 and authors’ simulations.

  2. Note: Income in USD.

Table 7
Poverty rates pre-COVID and post-COVID with and without transfers
December 2019May/June 2020 simulated incomeSeptember 2020 simulated income
IncomeW/out transfersWith transfersW/out transfersWith transfers
All23.86%58.11%56.51%30.82%30.27%
By gender
Female24.05%58.24%56.60%31.28%30.69%
Male23.66%57.97%56.40%30.34%29.84%
By age group
[0, 14]34.13%71.48%69.93%42.69%42.10%
[15, 24]24.73%63.74%61.74%32.68%32.01%
[25, 40]20.62%56.16%54.31%27.66%27.12%
[41, 64]17.61%49.77%48.20%23.27%22.72%
[65+]13.30%31.34%30.77%16.54%16.35%
By ethnicity
Indigenous49.27%80.06%79.84%57.45%57.41%
Afro American38.05%67.69%66.42%42.50%42.16%
Mestizo/white18.57%52.78%51.03%25.39%24.74%
Other24.83%62.14%60.56%32.26%31.96%
By education level
No high school29.20%66.40%65.06%37.55%37.07%
High school12.90%46.44%44.03%17.84%17.05%
Higher education4.01%13.15%12.35%5.18%4.96%
By employment type
Informal25.56%62.23%61.54%32.67%32.55%
Formal3.38%26.18%21.87%5.64%4.48%
By area
Rural35.65%69.28%68.46%43.73%43.64%
Urban18.36%52.90%50.93%24.80%24.04%
By geographic region
Sierra21.07%53.83%52.16%27.16%26.66%
Costa24.61%61.04%59.42%32.17%31.57%
Amazonia40.82%68.42%67.53%49.71%49.31%
  1. Source: ENEMDU December 2019 and authors’ simulations.

  2. Note: The official poverty line is $84.81.

Table 8
Inequality measures pre- and post-COVID
Percentile ratiosGini
p90/p10p90/p50p50/p10p75/p25
December 20197.652.812.722.880.46
May/June 2020 without transfers10.433.632.873.280.52
May/June 2020 with transfers8.773.612.433.140.50
September 2020 without transfers8.423.052.762.970.48
September 2020 with transfers7.593.052.493.010.47
  1. Source: ENEMDU December 2019 and authors’ simulations.

Table A1
Share of poor individuals by gender pre- and post-COVID
FemalesMales
Dec. 2019May 2020Sept. 2020Dec. 2019May 2020Sept. 2020
All0.240.580.310.240.580.30
By area
Rural0.360.700.440.350.680.43
Urban0.190.530.250.180.530.24
By employment type
Informal0.260.610.330.250.630.32
Formal0.020.180.030.040.320.07
By age group
[0, 14]0.330.720.420.350.710.43
[15, 24]0.260.650.340.230.630.31
[25, 40]0.230.590.300.180.540.25
[41, 64]0.170.480.230.180.510.24
[65+]0.120.300.160.140.330.18
By ethnicity
Indigenous0.500.800.570.490.800.57
Afro American0.370.680.420.390.670.43
Mestizo/white0.190.530.260.180.530.25
Other0.260.630.340.240.610.31
By education level
No high school0.300.670.380.290.660.37
High school0.140.480.200.120.450.16
Higher education0.030.120.050.050.140.06
By geographic region
Sierra0.210.540.270.210.540.27
Costa0.250.610.330.240.610.31
Amazonia0.410.690.500.410.680.49

Data and code availability

Data available at https://www.ecuadorencifras.gob.ec/estadisticas/

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