MIX
Kazusa Yoshimura
2024-04-17
Ratio of rural portfolio/Gross Loan Portfolio (2015)
Urban/Rural with/without equity information
Urban/Rural with/out donation
Deposits to loans (2015, by region)
Return on Assets (2015, by region)
Return on equity (2015, by region)
PAR30 (2015, by region)
Cost per loan (2015, by region)
Percent of female borrowers (2015, by region)
Clients.below.poverty.line (2015, by region)
Gross Portfolio (Individual)/ (Gross Portfolio (Individual) + Gross Portfolio (Group) + Gross Portfolio (Village.Banking))(2015, by region)
Gross Portfolio (Enterprise)/ (Gross Portfolio (Enterprise) + Gross Portfolio (Household))
Gross Portfolio (Enterprise)/ (Gross Portfolio (Enterprise) + Gross Portfolio (Household))
Loan loss rate
Financial Performance of MFIs
Return on equity
Return on equity
## Weighted Difference-in-Differences with Propensity Score
## Matches created with 3 lags
##
## Standard errors computed with 1000 Weighted bootstrap samples
##
## Estimate of Average Treatment Effect on the Treated (ATT) by Period:## $summary
## estimate std.error 2.5% 97.5%
## t+0 -46.276928 56.11079 -173.12073 25.35694
## t+1 17.840665 16.79625 -3.20729 60.34526
## t+2 -14.394808 27.88005 -73.23724 38.13983
## t+3 2.836164 21.76704 -37.76329 47.74995
##
## $lag
## [1] 3
##
## $iterations
## [1] 1000
##
## $qoi
## [1] "att"
Return on equity
## Weighted Difference-in-Differences with Propensity Score
## Matches created with 3 lags
##
## Standard errors computed with 1000 Weighted bootstrap samples
##
## Estimate of Average Treatment Effect on the Treated (ATT) by Period:## $summary
## estimate std.error 2.5% 97.5%
## t+0 1.240169 6.788305 -8.488672 17.74975
## t+1 6.503312 8.767531 -6.121183 28.47467
## t+2 4.455293 11.173306 -12.941395 31.19931
## t+3 -97.013534 115.141505 -387.513127 23.24113
##
## $lag
## [1] 3
##
## $iterations
## [1] 1000
##
## $qoi
## [1] "att"
PAR30
## Weighted Difference-in-Differences with Propensity Score
## Matches created with 3 lags
##
## Standard errors computed with 1000 Weighted bootstrap samples
##
## Estimate of Average Treatment Effect on the Treated (ATT) by Period:## $summary
## estimate std.error 2.5% 97.5%
## t+0 -0.2009073 1.032218 -2.227979 1.775073
## t+1 1.8705628 2.364586 -2.212133 6.786633
## t+2 8.7822865 6.602727 -1.502124 23.278948
## t+3 8.9742292 6.357613 -1.192432 23.329765
##
## $lag
## [1] 3
##
## $iterations
## [1] 1000
##
## $qoi
## [1] "att"
Return on equity
Return on equity
## Weighted Difference-in-Differences with Propensity Score
## Matches created with 3 lags
##
## Standard errors computed with 1000 Weighted bootstrap samples
##
## Estimate of Average Treatment Effect on the Treated (ATT) by Period:## $summary
## estimate std.error 2.5% 97.5%
## t+0 -4.381521 10.37044 -19.61199 21.35503
## t+1 -27.120694 29.73958 -89.08632 20.81892
## t+2 -33.779354 34.86533 -106.60134 16.14771
## t+3 -78.371258 97.28228 -367.97994 21.87792
##
## $lag
## [1] 3
##
## $iterations
## [1] 1000
##
## $qoi
## [1] "att"
PAR30
## Weighted Difference-in-Differences with Propensity Score
## Matches created with 3 lags
##
## Standard errors computed with 1000 Weighted bootstrap samples
##
## Estimate of Average Treatment Effect on the Treated (ATT) by Period:## $summary
## estimate std.error 2.5% 97.5%
## t+0 -0.2009073 1.028498 -2.268220 1.783861
## t+1 1.8705628 2.241359 -1.859366 6.733272
## t+2 8.7822865 6.574672 -1.582539 23.665384
## t+3 8.9742292 6.211125 -1.967031 21.226646
##
## $lag
## [1] 3
##
## $iterations
## [1] 1000
##
## $qoi
## [1] "att"
Write-off ratio
## Weighted Difference-in-Differences with Propensity Score
## Matches created with 3 lags
##
## Standard errors computed with 1000 Weighted bootstrap samples
##
## Estimate of Average Treatment Effect on the Treated (ATT) by Period:## $summary
## estimate std.error 2.5% 97.5%
## t+0 -0.26586660 0.7384929 -1.767662 1.253248
## t+1 0.97751598 2.7010799 -3.633648 6.626379
## t+2 -0.03888599 2.5171844 -5.843995 3.576874
## t+3 1.52360566 3.4465106 -4.084763 8.975505
##
## $lag
## [1] 3
##
## $iterations
## [1] 1000
##
## $qoi
## [1] "att"
| Â | Model 1 | Model 2 | Model 3 | Model 4 | Model 5 | Model 6 | Model 7 | Model 8 |
|---|---|---|---|---|---|---|---|---|
| rural_ratio | 0.69 (0.85) | -1.17 (7.75) | -1.30 (0.53)* | -1.36 (0.56)* | -0.11 (0.15) | -1.23 (1.91) | 0.09 (0.35) | -0.25 (0.25) |
| equity_donatedNot_Donated | -0.63 (0.54) | -0.91 (4.93) | -0.01 (0.34) | -0.13 (0.36) | -0.07 (0.09) | -0.47 (1.23) | 0.55 (0.22)* | 0.34 (0.16)* |
| Percent.of.female.borrowers | 0.04 (0.01)** | 0.37 (0.12)** | 0.01 (0.01) | -0.01 (0.01) | -0.01 (0.00)*** | -0.09 (0.03)** | 0.01 (0.01) | -0.00 (0.00) |
| individual_ratio | 1.39 (0.75) | 20.87 (6.88)** | 0.97 (0.47)* | 1.04 (0.50)* | 0.07 (0.13) | -1.31 (1.71) | 1.34 (0.31)*** | 1.05 (0.23)*** |
| enterprise_ratio | 1.97 (1.36) | 21.16 (12.51) | -0.10 (0.87) | -0.24 (0.99) | 0.01 (0.26) | -2.96 (3.13) | 0.87 (0.57) | 1.28 (0.41)** |
| Clients.below.poverty.line | 0.00 (0.01) | -0.01 (0.08) | 0.01 (0.01) | 0.01 (0.01) | -0.00 (0.00) | 0.02 (0.02) | 0.00 (0.00) | 0.00 (0.00) |
| Deposits.to.loan | 0.01 (0.01) | 0.08 (0.06) | -0.01 (0.00) | -0.01 (0.00)* | -0.00 (0.00)** | 0.08 (0.02)*** | 0.01 (0.00)* | 0.01 (0.00)*** |
| Y | Return.on.assets | Return.on.equity | Write.off.ratio | Write.off.ratio - Loan.loss.rate | Loan.loss.rate | PAR30 | Net Operating Income | Operating Expense |
| R2 | 0.03 | 0.04 | 0.03 | 0.04 | 0.13 | 0.09 | 0.09 | 0.11 |
| Adj. R2 | 0.00 | 0.00 | -0.00 | 0.01 | 0.10 | 0.06 | 0.05 | 0.09 |
| Num. obs. | 492 | 494 | 501 | 485 | 485 | 513 | 435 | 515 |
| ***p < 0.001; **p < 0.01; *p < 0.05 | ||||||||
Difference of summary statistics between rural and urban MFIs
| Rural (N=2987) |
Urban (N=2824) |
P-value | |
|---|---|---|---|
| Administrative.expense | |||
| Mean (SD) | 1940000 (5650000) | 32700000 (1470000000) | 0.287 |
| Median [Min, Max] | 485000 [-1640000, 176000000] | 685000 [-912000, 75100000000] | |
| Average_loan_balance | |||
| Mean (SD) | 1450 (9310) | 554000 (29100000) | 0.315 |
| Median [Min, Max] | 407 [0, 279000] | 1070 [2.00, 1540000000] | |
| Average_outstanding_balance_perGNI | |||
| Mean (SD) | 65.0 (1050) | 108 (664) | 0.0665 |
| Median [Min, Max] | 21.1 [0, 55800] | 32.0 [0.0300, 28500] | |
| Cost.per.borrower | |||
| Mean (SD) | 169 (738) | 37600 (1840000) | 0.314 |
| Median [Min, Max] | 83.0 [-493, 34400] | 225 [0, 91000000] | |
| Debt.to.equity.ratio | |||
| Mean (SD) | 5.16 (35.3) | 4.99 (33.6) | 0.855 |
| Median [Min, Max] | 3.05 [-168, 1310] | 2.99 [-336, 1440] | |
| Deposits.to.loan | |||
| Mean (SD) | 30.3 (99.0) | 43.1 (130) | <0.001 |
| Median [Min, Max] | 3.35 [0, 4320] | 2.25 [0, 5700] | |
| Gross.Loan.Portfolio | |||
| Mean (SD) | 64900000 (394000000) | 1280000000 (63700000000) | 0.31 |
| Median [Min, Max] | 8110000 [132, 14000000000] | 9680000 [562, 3380000000000] | |
| Gross.loan.portfolio.to.total.assets | |||
| Mean (SD) | 85.9 (78.1) | 78.5 (33.1) | <0.001 |
| Median [Min, Max] | 82.5 [0.420, 2240] | 80.5 [1.29, 983] | |
| Net.operating.income | |||
| Mean (SD) | 1950000 (13100000) | 7570000 (287000000) | 0.313 |
| Median [Min, Max] | 195000 [-217000000, 251000000] | 255000 [-3370000000, 14300000000] | |
| Number_active_borrowers | |||
| Mean (SD) | 137000 (548000) | 66500 (280000) | <0.001 |
| Median [Min, Max] | 16200 [3.00, 8170000] | 10300 [3.00, 5890000] | |
| Number_loan_officer | |||
| Mean (SD) | 381 (1610) | 210 (696) | <0.001 |
| Median [Min, Max] | 65.0 [0, 55000] | 42.0 [0, 14100] | |
| Number_loans_outstanding | |||
| Mean (SD) | 170000 (1070000) | 73300 (311000) | <0.001 |
| Median [Min, Max] | 16800 [3.00, 48100000] | 10700 [3.00, 5890000] | |
| Operating.expense | |||
| Mean (SD) | 5620000 (13900000) | 78500000 (3520000000) | 0.287 |
| Median [Min, Max] | 1470000 [-2590000, 244000000] | 1930000 [-881000, 181000000000] | |
| Percent.of.female.borrowers | |||
| Mean (SD) | 69.4 (27.9) | 58.7 (24.3) | <0.001 |
| Median [Min, Max] | 73.7 [0, 100] | 55.3 [0, 100] | |
| Portfolio.at.risk..30.days | |||
| Mean (SD) | 6.72 (14.6) | 7.71 (18.4) | 0.0253 |
| Median [Min, Max] | 2.86 [0, 373] | 4.13 [0, 711] | |
| individual_ratio | |||
| Mean (SD) | 0.579 (0.435) | 0.762 (0.366) | <0.001 |
| Median [Min, Max] | 0.775 [0, 1.00] | 1.00 [0, 1.00] | |
| enterprise_ratio | |||
| Mean (SD) | 0.828 (0.264) | 0.794 (0.268) | <0.001 |
| Median [Min, Max] | 0.952 [0, 1.00] | 0.912 [0, 1.00] | |
| Loan.loss.rate | |||
| Mean (SD) | 1.26 (5.47) | 2.28 (21.2) | 0.0196 |
| Median [Min, Max] | 0.180 [-65.1, 131] | 0.620 [-28.8, 989] | |
| Write.off.ratio | |||
| Mean (SD) | 1.70 (5.21) | 2.44 (8.13) | <0.001 |
| Median [Min, Max] | 0.390 [0, 131] | 1.00 [-10.8, 311] | |
| diff_loss | |||
| Mean (SD) | 0.333 (1.82) | 0.0636 (20.2) | 0.512 |
| Median [Min, Max] | 0 [-5.87, 65.1] | 0.0100 [-989, 30.9] | |
| Return.on.assets | |||
| Mean (SD) | 1.92 (8.70) | 1.36 (9.70) | 0.0302 |
| Median [Min, Max] | 2.31 [-113, 142] | 1.78 [-155, 45.3] | |
| Return.on.equity | |||
| Mean (SD) | 16.1 (618) | -35.6 (2120) | 0.242 |
| Median [Min, Max] | 9.61 [-13400, 27700] | 7.85 [-106000, 4950] |
PCA Analysis1 (2015)
PCA Analysis2 (2015)
PCA Analysis3 (all data)
PCA Analysis4 (all data)
Trend of the proportion of rural portfolio by countries since 2010
Factors that might affect the proportion of rural portfolio
Data Source: MIX, WDI (WB); Data: Since 2010, Around 4,200 observations of MFIs; Dependent variable: Proportion of rural portfolio
## Oneway (individual) effect Within Model
##
## Call:
## plm(formula = rural_ratio ~ Agriculture..forestry..and.fishing +
## GDP + GDP.growth + Mobile.cellular.subscriptions + Urban.population.growth +
## Access.to.electricity..rural + Agricultural.land + Average.precipitation.in.depth +
## Crop.production.index + Employment.in.agriculture + Fertilizer.consumption +
## Forest.area + Life.expectancy.at.birth..total + Political.Stability.and.Absence.of.Violence.Terrorism..Estimate +
## Population.density + Rural.population + Number_loan_officer +
## Percent.of.female.borrowers, data = new_mix6, model = "within",
## index = c("Time.x", "Country.Code.x"))
##
## Unbalanced Panel: n = 10, T = 49-784, N = 5284
##
## Residuals:
## Min. 1st Qu. Median 3rd Qu. Max.
## -2.49215 -0.71344 0.01200 0.64512 2.33117
##
## Coefficients:
## Estimate
## Agriculture..forestry..and.fishing 0.03576366
## GDP -0.05891002
## GDP.growth 0.00070055
## Mobile.cellular.subscriptions 0.07942318
## Urban.population.growth 0.02112574
## Access.to.electricity..rural 0.19464463
## Agricultural.land 0.07425899
## Average.precipitation.in.depth 0.02738661
## Crop.production.index -0.01416074
## Employment.in.agriculture -0.00546732
## Fertilizer.consumption 0.04053409
## Forest.area 0.06548738
## Life.expectancy.at.birth..total -0.00958831
## Political.Stability.and.Absence.of.Violence.Terrorism..Estimate 0.04294165
## Population.density 0.12713711
## Rural.population 0.41657972
## Number_loan_officer 0.00951772
## Percent.of.female.borrowers 0.03775701
## Std. Error
## Agriculture..forestry..and.fishing 0.02553586
## GDP 0.01555467
## GDP.growth 0.01426046
## Mobile.cellular.subscriptions 0.01981362
## Urban.population.growth 0.01899816
## Access.to.electricity..rural 0.02621790
## Agricultural.land 0.01992915
## Average.precipitation.in.depth 0.02608527
## Crop.production.index 0.01573718
## Employment.in.agriculture 0.02528999
## Fertilizer.consumption 0.01991238
## Forest.area 0.02605674
## Life.expectancy.at.birth..total 0.02936669
## Political.Stability.and.Absence.of.Violence.Terrorism..Estimate 0.01862114
## Population.density 0.02078527
## Rural.population 0.02542608
## Number_loan_officer 0.01229787
## Percent.of.female.borrowers 0.01457004
## t-value
## Agriculture..forestry..and.fishing 1.4005
## GDP -3.7873
## GDP.growth 0.0491
## Mobile.cellular.subscriptions 4.0085
## Urban.population.growth 1.1120
## Access.to.electricity..rural 7.4241
## Agricultural.land 3.7261
## Average.precipitation.in.depth 1.0499
## Crop.production.index -0.8998
## Employment.in.agriculture -0.2162
## Fertilizer.consumption 2.0356
## Forest.area 2.5133
## Life.expectancy.at.birth..total -0.3265
## Political.Stability.and.Absence.of.Violence.Terrorism..Estimate 2.3061
## Population.density 6.1167
## Rural.population 16.3840
## Number_loan_officer 0.7739
## Percent.of.female.borrowers 2.5914
## Pr(>|t|)
## Agriculture..forestry..and.fishing 0.1614147
## GDP 0.0001540 ***
## GDP.growth 0.9608212
## Mobile.cellular.subscriptions 6.195e-05 ***
## Urban.population.growth 0.2661938
## Access.to.electricity..rural 1.317e-13 ***
## Agricultural.land 0.0001965 ***
## Average.precipitation.in.depth 0.2938178
## Crop.production.index 0.3682537
## Employment.in.agriculture 0.8288518
## Fertilizer.consumption 0.0418383 *
## Forest.area 0.0119917 *
## Life.expectancy.at.birth..total 0.7440568
## Political.Stability.and.Absence.of.Violence.Terrorism..Estimate 0.0211455 *
## Population.density 1.024e-09 ***
## Rural.population < 2.2e-16 ***
## Number_loan_officer 0.4390057
## Percent.of.female.borrowers 0.0095846 **
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Total Sum of Squares: 5181.2
## Residual Sum of Squares: 4198.9
## R-Squared: 0.18959
## Adj. R-Squared: 0.18543
## F-statistic: 68.3122 on 18 and 5256 DF, p-value: < 2.22e-16| Â | Model 1 |
|---|---|
| Agriculture..forestry..and.fishing | 0.04 (0.03) |
| GDP | -0.06 (0.02)*** |
| GDP.growth | 0.00 (0.01) |
| Mobile.cellular.subscriptions | 0.08 (0.02)*** |
| Urban.population.growth | 0.02 (0.02) |
| Access.to.electricity..rural | 0.19 (0.03)*** |
| Agricultural.land | 0.07 (0.02)*** |
| Average.precipitation.in.depth | 0.03 (0.03) |
| Crop.production.index | -0.01 (0.02) |
| Employment.in.agriculture | -0.01 (0.03) |
| Fertilizer.consumption | 0.04 (0.02)* |
| Forest.area | 0.07 (0.03)* |
| Life.expectancy.at.birth..total | -0.01 (0.03) |
| Political.Stability.and.Absence.of.Violence.Terrorism..Estimate | 0.04 (0.02)* |
| Population.density | 0.13 (0.02)*** |
| Rural.population | 0.42 (0.03)*** |
| Number_loan_officer | 0.01 (0.01) |
| Percent.of.female.borrowers | 0.04 (0.01)** |
| R2 | 0.19 |
| Adj. R2 | 0.19 |
| Num. obs. | 5284 |
| ***p < 0.001; **p < 0.01; *p < 0.05 | |
| Â | Model 1 | Model 2 |
|---|---|---|
| mobile_money | -0.12 (0.03)*** | -0.07 (0.03)* |
| Rural.population | 0.47 (0.04)*** | 0.37 (0.04)*** |
| Mobile.cellular.subscriptions | 0.15 (0.04)*** | 0.17 (0.04)*** |
| Cost.per.borrower | Â | -0.44 (0.06)*** |
| Number_loan_officer | Â | 0.03 (0.02) |
| Percent.of.female.borrowers | Â | 0.08 (0.04)* |
| R2 | 0.18 | 0.27 |
| Adj. R2 | 0.17 | 0.26 |
| Num. obs. | 867 | 730 |
| ***p < 0.001; **p < 0.01; *p < 0.05 | ||
## Oneway (individual) effect Within Model
##
## Call:
## plm(formula = poverty_6.85 ~ rural_ratio + mean_GDP + mean_Access.to.electricity..rural,
## data = a, model = "within", index = c("Time.x", "Level"))
##
## Unbalanced Panel: n = 10, T = 1-45, N = 338
##
## Residuals:
## Min. 1st Qu. Median 3rd Qu. Max.
## -44.48574 -13.23336 -0.49023 9.97149 44.59376
##
## Coefficients:
## Estimate Std. Error t-value Pr(>|t|)
## rural_ratio 33.937265 4.750283 7.1443 5.979e-12 ***
## mean_GDP 1.252029 0.597780 2.0945 0.03699 *
## mean_Access.to.electricity..rural -0.717276 0.039509 -18.1550 < 2.2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Total Sum of Squares: 259450
## Residual Sum of Squares: 121180
## R-Squared: 0.53292
## Adj. R-Squared: 0.51567
## F-statistic: 123.603 on 3 and 325 DF, p-value: < 2.22e-16## Oneway (individual) effect Within Model
##
## Call:
## plm(formula = poverty_6.85 ~ rural_ratio + mean_RP, data = a,
## model = "within", index = c("Time.x", "Level"))
##
## Unbalanced Panel: n = 10, T = 1-45, N = 344
##
## Residuals:
## Min. 1st Qu. Median 3rd Qu. Max.
## -54.6599 -13.9108 1.7556 13.5580 39.2322
##
## Coefficients:
## Estimate Std. Error t-value Pr(>|t|)
## rural_ratio -21.351150 4.764391 -4.4814 1.022e-05 ***
## mean_RP 1.302420 0.059572 21.8630 < 2.2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Total Sum of Squares: 272020
## Residual Sum of Squares: 108090
## R-Squared: 0.60265
## Adj. R-Squared: 0.58948
## F-statistic: 251.765 on 2 and 332 DF, p-value: < 2.22e-16| Â | Model 1 | Model 2 |
|---|---|---|
| rural_ratio | 33.94 (4.75)*** | -21.35 (4.76)*** |
| mean_GDP | 1.25 (0.60)* | Â |
| mean_Access.to.electricity..rural | -0.72 (0.04)*** | Â |
| mean_RP | Â | 1.30 (0.06)*** |
| R2 | 0.53 | 0.60 |
| Adj. R2 | 0.52 | 0.59 |
| Num. obs. | 338 | 344 |
| ***p < 0.001; **p < 0.01; *p < 0.05 | ||
## Oneway (individual) effect Within Model
##
## Call:
## plm(formula = poverty_6.85 ~ rural_ratio + mean_RP, data = a,
## model = "within", index = c("Time.x", "Level"))
##
## Unbalanced Panel: n = 10, T = 1-45, N = 344
##
## Residuals:
## Min. 1st Qu. Median 3rd Qu. Max.
## -54.6599 -13.9108 1.7556 13.5580 39.2322
##
## Coefficients:
## Estimate Std. Error t-value Pr(>|t|)
## rural_ratio -21.351150 4.764391 -4.4814 1.022e-05 ***
## mean_RP 1.302420 0.059572 21.8630 < 2.2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Total Sum of Squares: 272020
## Residual Sum of Squares: 108090
## R-Squared: 0.60265
## Adj. R-Squared: 0.58948
## F-statistic: 251.765 on 2 and 332 DF, p-value: < 2.22e-16## Oneway (individual) effect Within Model
## Instrumental variable estimation
##
## Call:
## plm(formula = poverty_6.85 ~ rural_ratio + mean_RP | mean_RP +
## Mobile.cellular.subscriptions, data = a, model = "within",
## index = c("Time.x", "Level"))
##
## Unbalanced Panel: n = 10, T = 1-45, N = 344
##
## Residuals:
## Min. 1st Qu. Median 3rd Qu. Max.
## -77.22826 -14.61049 -0.31711 16.20499 89.76688
##
## Coefficients:
## Estimate Std. Error z-value Pr(>|z|)
## rural_ratio -103.75999 20.81848 -4.984 6.227e-07 ***
## mean_RP 1.73031 0.13141 13.168 < 2.2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Total Sum of Squares: 272020
## Residual Sum of Squares: 205490
## R-Squared: 0.4219
## Adj. R-Squared: 0.40275
## Chisq: 279.133 on 2 DF, p-value: < 2.22e-16| Â | Model 1 | Model 2 | Model 3 |
|---|---|---|---|
| rural_ratio | 33.94 (4.75)*** | -21.35 (4.76)*** | -103.76 (20.82)*** |
| mean_GDP | 1.25 (0.60)* | Â | Â |
| mean_Access.to.electricity..rural | -0.72 (0.04)*** | Â | Â |
| mean_RP | Â | 1.30 (0.06)*** | 1.73 (0.13)*** |
| Model | Panel | Panel | Panel+IV |
| R2 | 0.53 | 0.60 | 0.42 |
| Adj. R2 | 0.52 | 0.59 | 0.40 |
| Num. obs. | 338 | 344 | 344 |
| ***p < 0.001; **p < 0.01; *p < 0.05 | |||
