Eastern Visayas after Yolanda: Evidence from a Household Survey

Majah-Leah V. Ravago, Dennis S. Mapa and Associates

University of the Philippines

Yolanda hurled a massive destruction across the central part of the Philippines.

Source:(NEDA-RAY(2(

Yolanda (Haiyan) was one of the strongest storms ever recorded with wind speeds of more than 300 km/h.

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Conditions before Yolanda

Region 8 Popn ('000) Per

Capita Income

Per Capita

Exp

Poverty Incidence

(%) Leyte 1,789 49,251 38,535 31.9 Southern Leyte 399 45,362 36,440 36.4 Eastern Samar 429 30,147 25,240 59.4 Samar (Western Samar) 733 27,393 22,895 36.0 Northern Samar 589 32,367 23,732 43.7 Biliran 162 42,872 40,578 20.7 Region VIII 4,101 40,713 32,440 37.2 Philippines 92,338 58,583 47,752 22.3

Sources:(Popula7on(is(from(2010(Census(and(Housing(Popula7on,(Ave(Annual(Income(and(Ave(Annual(Expenditure((Per(Capita,(2012)(is(based(from(PSA-(FIES(2012,(and(poverty(incidence(is(from(PSA-NSCB(-(2012(First(Semester(Official(Provincial(Poverty(Sta7s7cs.(4(

Social Protection Survey

•  Conducted in May-June 2014 •  Purpose: to investigate the full

spectrum of shocks experienced by the Philippine households and to examine how these households cope with shocks.

•  Used a multi-stage cluster sampling design with a nationally representative sample from 57 provinces.

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Social Protection Survey

3,100 households samples, 695 are from Region 8.

Region 8 Sample Size Urban Rural

Leyte 445 120 325 Southern Leyte 90 15 75 Eastern Samar 100 25 75 Western Samar 30 0 30 Northern Samar 25 0 25 Biliran 5 0 5 Region VIII 695 160 535 Philippines 3,100 1,300 1,800

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Yolanda •  Shock is defined as an unforeseen adverse event

that can lead to a decrease in welfare.

•  Yolanda: Naturally occurring events experienced in Nov 2013

Households Affected by Yolanda Shock Frequency Percent

Strong Winds and Rain 541 87.97% Flood due to continuous rain, storm 51 8.29% Landslide/Mudslide 2 0.33% Tsunami and Storm Surge 21 3.41% Total 615 100%

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Economic Profile of the HH respondents

Average Per capita Income and Expenditure by Quintile

Quintile Income Expenditure

Count Average Count Average

1 - Poorest 117 7,673 125 12,883 2 132 14,577 128 21,621 3 96 21,499 129 31,329 4 107 30,143 120 44,311

5 - Richest 103 55,793 113 81,687 Total 555 24,969 615 37,345 Note:(Income(and(expenditure(quin7le(is(computed(based(on(trimmed(means(where(5%(of(the(highest(and(lowest(order(sta7s7cs(are(eliminated(to(provide(protec7on(against(outliers.(

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About 40% still have not recovered after 6 months

Recovery

Recovery of poorest 20%

Region VIII Household

Not at all

Partial/Full Total

Not at all

Partial/Full Total

Leyte (including Tacloban) 147 227 374 25 54 79 (39) (61) (100) (32) (68) (100) Outside Leyte 71 110 181 15 23 38 (39) (61) (100) (39) (61) (100) Total 218 337 555 40 77 117 (39) (61) (100) (34) (66) (100)

Households’ perceptions on recovery

Note: Poorest 20% belongs to the Quintile 1 of income profile. Total Sample: Chi-Square Statistic = 0.0003 p-value = 0.986; Poorest 20%: Chi-Square Statistic = 0.6988 p-value = 0.403

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Financial coping activities of the household to deal with the cost of Yolanda

INFORMATION ON FINANCES Outside Leyte Leyte (+ Tacloban) TOTAL

Yes TOTAL Yes TOTAL Yes TOTAL Loan 27 196 74 419 101 615 (14) (100) (18) (100) (16) (100) Spent cash savings 54 196 127 419 181 615 (28) (100) (30) (100) (29) (100) Sold household assets and goods 0 196 1 419 1 615 (0) (100) (0) (100) (0) (100) Harvest manufactured products or crops in advance 2 196 1 419 3 615 (1) (100) (0) (100) (0) (100) Delayed/forego investments 0 196 0 419 0 615 (0) (100) (0) (100) (0) (100) Mortgaged or pawned assets 0 196 1 419 1 615 (0) (100) (0) (100) (0) (100) None 114 196 222 419 336 615 (58) (100) (53) (100) (55) (100)

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Incidence of borrowing to cope with Yolanda

Income Classification Total

Not Loan Loan Leyte

Non-Leyte

Poorest 40% 249 201 48 37 11 (100) (81) (19) (15) (4) Upper 60% 366 313 53 34 15 (100) (86) (14) (9) (4) Total 615 514 101 71 26 (100) (84) (16) (12) (4)

Pearson chi2(1) = 2.4835 Pr = 0.115 Total Pearson chi2(1) = 2.1201 Pr = 0.145 Leyte Pearson chi2(1) = 0.1540 Pr = 0.695 Non- Leyte

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Incidence of spending cash savings to cope with Yolanda.

Income Classification

Total

Not Spent Cash

Savings

Spent Cash

Savings Leyte Non-Leyte

Poorest 40% 249 186 63 46 17 (100) (75) (25) (18) (7) Upper 60% 366 214 92 64 28 (100) (70) (30) (17) (8) Total 615 400 155 110 45 (100) (72) (28) (18) (7)

Pearson chi2(1) = 1.5481 Pr = 0.213 Total Pearson chi2(1) = 0.4159 Pr = 0.519 Leyte Pearson chi2(1) = 1.5743 Pr = 0.210 Non- Leyte

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Incidence of seeking or receiving assistance to bear the cost of Yolanda

Outside Leyte Leyte (+ Tacloban) Total - Yolanda

Yes Total Yes Total Yes Total

Government Assistance

22 196 72 419 94 615

(11.22) (100.00) (28.80) (100.00) (15.28) (100.00)

Private Assistance (Individual, NGO, charity)

32 392 118 838 150 1230

(8.16) (100.00) (14.08) (100.00) (12.20) (100.00)

No, did not receive nor ask for assistance

153 196 250 419 403 615

(78.06) (100.00) (59.67) (100.00) (65.53) (100.00)

Only 15% received of sought assistance from the gov’t.

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Region 8 Income

Classification

Sought/Received Government Assistance

Yes No Total

Poorest 40% 199 50 249 (79.9) (20.1) (100.0)

Upper 60% 322 44 366 (88.0) (12.0) (100.0)

Total 521 94 615 (84.7) (15.3) (100.0)

Chi-Square Statistic = 7.43; p-value = 0.006

Of those few that received gov’t assistance, most of them are poor. Incidence of seeking or receiving government assistance.

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Gov assistance vs Loans vs Savings

Sought/Received Government Assistance

Financial Coping Mechanism No Yes Total

Loan 89 12 101 (88) (12) (100) Not Loan 432 82 514 (84) (16) (100) Total 521 94 615 (85) (15) (100)

Spent Cash Savings 143 38 181 (79) (21) (100) Not Spent Cash Savings 378 56 434 (87) (13) (100) Total 521 94 615 (85) (15) (100)

Pearson chi2(1) = 1.0810 Pr = 0.298 Loan Pearson chi2(1) = 6.4582 Pr = 0.011 Cash savings

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What influences recovery? Dependent Variable: Household has Partially/Completely Recovered Explanatory Variables Coeff. Robust SE P-value

Household Made Loan 0.6609 0.2714 0.0150 Household Spent Own Savings (Cash) 0.4106 0.2175 0.0590 Received Government Assistance -0.9498 0.2949 0.0010 Took Precautionary Measures before Disaster = 1 3.0698 1.0923 0.0050

HH Head is Elementary Graduate 0.4327 0.269 0.1080 HH Head is HS Undergraduate 0.3119 0.3195 0.3290 HH Head is HS Graduate 0.2635 0.2633 0.3170 HH Head is College Undergraduate 0.0340 0.3296 0.9180 HH Head is College Graduate or Post - Graduate 0.9648 0.4841 0.0460

CCT Household -0.4213 0.2525 0.0950 Interaction: HH getting gov't assistance and CCT HH 1.1188 0.6152 0.0690

Age of HH Head -0.0091 0.0070 0.1960 Sex of HH Head (Female=1) -0.1832 0.2974 0.5380 Constant 0.6868 0.5668 0.2260

Number of Obs. = 554; LR Statistic = 30.78 (p-value=0.0037); McFadden R-square = 0.07 16(

What influences recovery?

•  Number of Obs. = 555; LR Statistic = 38.12 (p-value=0.000); McFadden R-square = 0.05

Dependent Variable: Household has Partially/Completely Recovered

Explanatory Variables Coeff. Robust SE P-value Marginal Effect

Household Made Loan 0.6612 0.2711 0.0150 0.1398 Household Spent Own Savings (Cash) 0.4203 0.2159 0.0520 0.0910

Received Government Assistance -0.9508 0.2867 0.0010 -0.2154

Took Precautionary Measures before Disaster = 1 3.0845 1.0787 0.0040 0.3773

HH Head is College Graduate or Post - Graduate 0.8173 0.4505 0.0700 0.1647

CCT Household -0.3754 0.2488 0.1310 -0.0843 Interaction: HH getting gov't assistance and CCT HH 1.1692 0.6038 0.0530 0.2168

Constant 0.2721 0.1400 0.0520 Number of Obs. = 555; LR Statistic = 38.12 (p-value=0.000) McFadden R-square = 0.05

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Highlights 1 •  For the households that took precautionary

measures before Yolanda, the probability of partial to full recovery after the disaster increases by about 38 percentage points (marginal effect), controlling for other factors.

•  For households with cash savings and utilized such savings, the probability of partial to full recovery increases by about 9 percentage points relative to households without savings, controlling for other factors.

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Highlights 2 •  For households who availed of loans, the probability

of partial to full recovery increases by about 14 percentage points, controlling for other factors.

–  It is important to note that 56 percent of the households availed of the loan from informal moneylenders, with about 42 percent from relatives and friends.

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What influences recovery? Dependent Variable: Household has Partially/Completely Recovered

Explanatory Variables Coeff. Robust SE P-value Marginal Effect

Household Made Loan 0.6612 0.2711 0.0150 0.1398 Household Spent Own Savings (Cash) 0.4203 0.2159 0.0520 0.0910

Received Government Assistance -0.9508 0.2867 0.0010 -0.2154

Took Precautionary Measures before Disaster = 1 3.0845 1.0787 0.0040 0.3773

HH Head is College Graduate or Post - Graduate 0.8173 0.4505 0.0700 0.1647

CCT Household -0.3754 0.2488 0.1310 -0.0843 Interaction: HH getting gov't assistance and CCT HH 1.1692 0.6038 0.0530 0.2168

Constant 0.2721 0.1400 0.0520

Number of Obs. = 555; LR Statistic = 38.12 (p-value=0.000) McFadden R-square = 0.05

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•  The probability of partial to full recovery for households who received government assistance (unconditional assistance), differs between CCT and non-CCT beneficiaries by a scanty 0.14 (-0.2154 + 0.2168) percentage points, with CCT beneficiaries having a slightly higher incremental effects of having received government assistance on average.

•  0.14 is the incremental effect on the probability of recovery for receiving government assistance as the status of household changes from non-CCT to CCT.

•  This implies that non-CCT households who received government assistance feel worse-off.

•  For non-poor households, the financial impact of typhoon Yolanda is tremendous such that government assistance is not enough to improve their immediate recovery.

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Concluding remarks 1.  Most prominent coping activity is taking

precationary measures and asset disposal, e.g. spending cash savings and selling goods.

2.  Hard for poor to prepare for disaster. Disposable assets are low, and investments in the future, e.g. Need good years to prepare for bad years.

3.  Billie Holiday: “Them that’s got shall cope; them that don’t shall lose. So the bible says, and it still is news.”

4.  “Living at subsistence” is a non-sequitor.

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Salamat po! MAJAH-LEAH V. RAVAGO, PhD Assistant Professor and Director for Research UP School of Economics E-mail: mvravago@econ.upd.edu.ph

DENNIS S. MAPA, PhD Dean UP School of Statistics E-mail: cdsmapa@yahoo.com

We#acknowledge#the#excellent#research#assistance#of#Manuel#Albis,#Pia#Medrano,#and#Helen#Santos!#