Tsukuba Economics Working Papers
No. 2009-009

Cyclone, Gender, and Ritualby
Yoshito Takasaki
June 2009

UNIVERSITY OF TSUKUBA
Department of Economics
1-1-1 Tennodai
Tsukuba, Ibaraki 305-8571
JAPAN

1

Cyclone, Gender, and Ritual*
Yoshito Takasaki
University of Tsukuba

Running Title:
Cyclone, Gender, and RitualContact Information:
Yoshito Takasaki
Graduate School of Humanities and Social Sciences
University of Tsukuba
1-1-1 Tennodai, Tsukuba
Ibaraki 305-8571 Japan
Tel./fax: +81 29 853 6280
E-mail address: takasaki@sk.tsukuba.ac.jp

June 5, 2009*

I wish to thank my field team – Jonati Torocake, Viliame Manavure, Viliame Lomaloma, Maria Torocake,and Anaseini Savuiwasa – for their advice, enthusiasm, and exceptional efforts on behalf of this project.
Special thanks are owed to the Fijians of the region who so willingly participated in the survey. Xiaowen
Mo undertook the laborious task of data entry and cleaning. This paper has benefited significantly by thecomments and suggestions of Michael Bennett, Keijiro Otsuka, and conference and seminar participants on
earlier versions of this work presented to the World Congress of Environmental and Resource Economists,
the FASID Workshop of Development Strategy for Poverty Reduction Program, Beijing University, Kobe
University, and University of Tsukuba. This research has been made possible through support provided by
the Sumitomo Foundation, the Japan Society for the Promotion of Science, and the Ministry of Education,
Culture, Sports, Science and Technology in Japan. Any errors of interpretation are solely the author’s
responsibility.

2

Cyclone, Gender, and Ritual
Abstract
This paper demonstrates that the Fijian kava ritual emerges as insurance against cyclone
risk, as women’s production of ritual handicraft gifts is linked with risk sharing. The
cyclone tightens female-heads’ constraints on intra-household male labor allocation in thegendered Fijian society. This is because male labor sharing against dwelling damage
emerges as a new gendered division of labor, and cyclone relief (food aid) crowds out
risk sharing against crop damage, but not against dwelling damage. As a result, eventhough handicraft gift production is normally neutral to the household head’s gender,
only female-headed households intensify production against dwelling damage to receive
more male labor help and reduce production against crop damage to facilitate
intensification against dwelling damage. These gendered responses are caused bygendered constraints other than labor endowment, such as discrimination. The kava ritual
protects women with limited coping capabilities, though it is not sufficient to fill thegender gap in dwelling rehabilitation.

3
1. Introduction
Many gifts are ritualistic in developing societies. Following the seminal work on
gifts, reciprocity, and ritual in Melanesia by Malinowski (1922), anthropologists (e.g.,
Mauss 1967) have highlighted the cultural and social roles of ritual gifts based on theirethnographic field studies, especially in the Pacific Islands (Hann 2006). In contrast,
economists rarely consider ritual to be in their domain, and almost no systematic
economic works using micro survey data from the Pacific Islands exist. Economists haveextensively studied risk sharing, however, as a major motive of private transfers invarious contexts (e.g., Kolm and Ythier 2006; Cox and Fafchamps 2008). Using original
household survey data gathered in Fiji, this paper explores the potential role of ritual gifts
in coping with cyclone risk.1
A dominant symbol in Fijian culture is kava (a beverage infused from the root ofa pepper plant, Piper methysticum, locally known as yaqona, Turner 1986).2 The kava
ritual frequently involves an exchange of ceremonial goods, including indigenous
handicrafts made solely by women. I focus on the production of ritual handicraft gifts,
but not their exchange. Handicrafts can be gifted either by a kin group or a household. If
handicraft gifts substitute for other forms of private transfers, such as cash, other in-kindgifts, and labor, then handicraft making, as a shared ritual duty among kin-groupmembers and for private gift exchange with others, can involve risk-sharing

1

Better understanding how the rural poor cope with natural disasters is of central importance topolicymakers (Skoufias 2003). This is especially so in small island states that heavily rely on foreign aid(Bertram 1986). Some researchers have criticized the deterioration of islanders’ indigenous mechanisms in
coping with cyclones because of their increasing dependency on emergency aid (e.g., Campbell 1984).
2
Yaqona “is used in kinship and chiefship rituals, in the treatment of certain kinds of illness, in theatonement for misdeeds and the repair of social relations, before any major undertaking and after thecompletion of any joint work, in recognition of arrivals and departures, in all public assemblies, and as amatter of hospitality at social gatherings of all kinds. I can recall only one day in which yaqona was not
being drunk in some section of the village where I resided.” (Turner 1986, p206).

4
arrangements.3 Gift production is an ex post labor activity whose return is realized
through risk sharing (along with any social benefits, such as securing social status); thatis, self-insurance and mutual insurance are directly linked. Rosenzweig (2001)
emphasizes this link, in a general sense, as a future research agenda on risk.
In Fiji, female-headed households face greater constraints on intra-household
male labor allocation than those that are male-headed, not only because of their smaller
male labor endowment, but also because of other gender factors, such as discrimination.4
In response to dwelling damage caused by the cyclone, males help each other repair andrebuild dwellings. This new gendered division of labor tightens female-heads’ labor
constraints. As a result, even if handicraft gift production is normally neutral to thehousehold head’s gender, gender difference can emerge in response to dwelling damage.
Furthermore, even if the response to crop damage, another major damage caused by thecyclone, were neutral to gender without dwelling damage, gendered responses to crop
damage could also emerge, if dwelling damage mainly shapes the response to crop
damage. Such an interaction effect becomes significant if gift production more strongly
responds to dwelling damage than crop damage, because risk sharing against dwelling
damage better works than that against crop damage. This is very likely in Fiji, because
cyclone relief crowded out risk sharing against crop damage, but not against dwelling
3This depends on the transformability of handicraft gifts into other forms of transfers. Economists tend to
implicitly assume low transformability, treating risk sharing and ritual separately. Fafchamps and Lund
(2003, p280), for example, attribute Philippine households’ weak responses of gifts to shocks to ritual: “. . .
one possible interpretation is that many recorded gifts are ritual in nature (e.g., gifts at funerals) and arethus insensitive to shocks.”
4
Turner (1992, p291) describes the Fijian hierarchy well: “ . . . hierarchy is defined here as the ranking of
the elements of a whole (society) in relation to the whole. In this sense, the elements that are ranked aresocial categories or positions defined in terms of age, seniority of descent, and gender, and the whole inrelation to which they are ranked is a social system grounded in ritual. Elder is superior to junior, chief tocommoner, and male to female. But while age, rank, and gender differences entail relations ofsuperiority/inferiority among persons, they also create interdependence. . . . These relations of inequality
and interdependence (which do not preclude conflict) are expressed and reproduced in the practice ofeveryday life.” Young (1988) discusses gender issues in Fiji.

5
damage – almost all households in the study area received generous emergency food aid;
public support for dwelling damage was almost nonexistent (Takasaki forthcoming).5
That is, cyclone relief further tightens female-heads’ labor constraints.
While gender has received considerable attention in the literature on risk (e.g.,
Dercon and Krishnan 2000; Attanasio, Low, and Sanchez-Marcos 2005), researchers
have not yet explored how gendered coping responses linked with gendered risk sharing
emerge. Such an inquiry is important for two main reasons. First, it may reveal new
responses that could not be identified otherwise. Second, it leads to a better
understanding of distributional consequences of shocks. Not only do adverse shocks
augment inequalities in coping capabilities among households, but also public safety-net
policies may worsen distributional outcomes.
I explore two other related questions. First, when do people adjust handicraft gift
production to shocks, during the emergency period or after? Since people need quick help
under a state of emergency, for gift production – which takes time – to serve as part ofrisk sharing, reciprocity needs to take place over time. Second, do people adjust their
participation or intensity to shocks? Gendered responses emerge in only intensity if
participation is mainly determined by certain qualifications, such as craftswomen’s skills
and social status. Previous works on ex post labor supply rarely compare participationand intensity: Rose (2001) focuses on participation, and Kochar (1999) employs Tobit
with a constraint that estimated coefficients are the same for both decisions.
5

Attanasio and Rios-Rull (2000) theoretically demonstrate that public transfer crowds out private transfer
in risk sharing, because in the risk-sharing arrangement with limited enforceability, public transfer that
increases the value of autarky relative to the value of staying in the contract reduces the degree of risk
sharing. (They obtain supporting evidence in Mexico’s Progresa program, and Dercon and Krishnan 2005
find similar results for food aid in rural Ethiopia.) Also, risk sharing against crop damage, which depends
on farmers’ pre-cyclone cropping decisions, is often constrained by information problems; risk sharing
against dwelling damage is facilitated by its lack of information problems and randomness, as well as its
seriousness.

6
The analysis strongly confirms my conjectures. Only female-headed households
intensify ritual handicraft gift production against dwelling damage to receive more malelabor help and reduce production against crop damage to facilitate intensification against
dwelling damage, both during and after the emergency period; at the same time,
participation is independent of shocks and gender. That is, the Fijian kava ritual emerges
as insurance against cyclone risk for some women with limited coping capabilities.
The rest of the paper is organized as follows. Section 2 describes the study area
and offers descriptive evidence of gendered responses in ritual handicraft gift production.
Section 3 provides the theoretical framework that shows how gendered responses tocyclone shocks emerge. Section 4 discusses the econometric specification, which isfollowed by the estimation results in Section 5 and the robustness check in Section 6. The
last section concludes.
2. Study area, cyclone, gender, and handicrafts
On January 13, 2003, Cyclone Ami swept over the northern and eastern parts of
the Fiji Islands (Ami was the only cyclone in that year). Nine native Fijian villages on the
coast were intentionally chosen for the survey, and households were randomly sampled ineach village (n = 374).6 Interviews were conducted between late August and earlyNovember 2003. Enumerators visited each household once within this time frame andinquired about production, income, assets, demographics, cyclone damage, and relief(neither consumption nor labor transfer data were collected). As such, like other post6

Six and three villages, respectively, are located on the Vanua Levu and Taveuni Islands, the second- andthird-largest islands in the country, which significantly lag behind the largest island, Viti Levu, where thestate capital, two international airports, and most tourism businesses are situated. In each village,
households are stratified by the smallest kin-group unit (defined below), as well as the combination ofleadership status and major asset holdings (like shops). Households were randomly sampled in each stratum.
Fiji is divided almost evenly between native Fijians and Indo-Fijians. This study focuses on native Fijians
who practice the kava ritual (Indo-Fijians also drink kava for recreation).

7
disaster surveys (e.g., Morris et al. 2002), the survey collected pre- and post-cyclone
information retrospectively. Respondents were asked about handicraft production in eachmonth over the past one year. This generates a four-period panel of pre-cyclone period 1(October-December 2002) and post-cyclone periods 2-4 (January-March, April-June, andJuly-September 2003, respectively). The analysis is based on 342 households withcomplete data (those with no female adults, potential handicraft producers, are dropped).
Cropping is the most important livelihood activity, accounting for over half of thetotal income before the cyclone (see Table 1). While there is no gendered division oflabor in cropping, female-headed households (12% of the sample) have weaker cropping
capacities than those that are male-headed: Female-headed households are older (bothhead and female adults), less educated (both head and female adults), and smaller in thesize of male adults (female adult size does not significantly differ), and hold less land per
capita (see Table 2).7 As a result, compared to male-headed households, female-headedhouseholds earned less crop income and total income in a per capita term, while there
was no gender difference in other income-earning activities (Table 1).8 Table 3 reports
the proportion of households that produced ceremonial handicraft gifts and the mean

7

Virtually all land is communally owned and by law cannot be sold. The disposition of fishing capital(privately owned) and the transfer of the usufruct of land after the cyclone were nonexistent. Indeed, asset
holdings changed very little over the previous year. Table 2 reports pre-cyclone land and fishing capital
holdings (a year before the interview).
8
Almost all households employ traditional cropping practices (using no mechanized equipment or animal
traction and limited purchased inputs) to produce taro, cassava, coconut, and kava plant. Most households
also engage in subsistence fishing using lines and hooks, simple spear guns, or rudimentary nets, and morecommercially oriented fishermen use boats and engines, along with more valuable nets (fishing was thesecond-most-important activity with a 31% income share before the cyclone). Although female-headedhouseholds own smaller fishing capital per capita than male-headed ones, there was no difference in fishingincome between them (while in other locales males dominate fishing, female fishers are active in Fiji,
Chapman 1987). Enumerators asked questions about the production of major crops and the catch of finfish
and other marine products in the past one month, and then monthly production a year before, in comparison
with the latest figures. While casual wage labor was very uncommon, some households earned significant
income from permanent wage labor in a stable manner. Other income in Table 1 consists of shop profit,
livestock selling, and other self-employment activities like being a middleman.

8values of produced gifts per capita per month in each period.9 Even though only womenmake handicrafts, there was no gender difference in both participation and values inperiod 1.
Ami damaged almost two thirds of residents’ dwellings (consisting of a mainhouse and other small independent units like a kitchen, a shower, and a toilet, if any), andthe mean value of total dwelling damage (hv) was 70 Fiji dollars per capita (F$1 =US$.60) (based on respondents’ subjective assessment probed by enumerators in the
respondents’ homes) (Table 2). Crop damage was experienced by 84% of households,
and the mean value of crop damage (cd) was F$32 per capita, which is about two thirdsof the mean monthly pre-cyclone crop income (crop damage was calculated based on thequantity damaged of each major crop, as reported by respondents). Provisions of relief –by the Red Cross, other nongovernmental organizations (NGOs), and governments –were quite distinct. On one hand, almost all households received generous food aid; inperiods 2 and 3, people received about 10 days worth of food per month on average, that
is, an average household could rely on aid to cover about one third of its foodconsumption. On the other hand, primitive tarpaulins – to be used as emergency shelters

The three most important handicrafts are famous Fijian mats voivoi (made of screw pine, Pandanus
thurstonii), finer mats kuta (made of soft sedge, Eleocharis dulcis), and bark cloths tapa (made of paper
mulberry, Broussnetia papyrifera). These plants (locally known also as voivoi, kuta, and tapa, respectively)
are gathered on communal land and are openly accessible to all villagers, and their extraction is unregulated.
While voivoi is produced in all nine villages, kuta and tapa are produced in some villages, depending on
local environmental conditions. Only kuta is seasonal. Some craftswomen sell their products in local
markets and small resort hotels for tourists, and values of handicraft gifts were imputed from sales data. In
Table 1, handicraft gifts and sales are combined. Gift production was much more common and larger thansales – approximately two times and five times, respectively, over time. People also collected other forest
products, such as wild fruits, earning negligible incomes over time (Table 1).

99
and for temporary dwelling repair – were provisioned to only 11% of households (thegovernment provisioned construction materials more than one year after the cyclone).10
Even though there was no gender difference in crop damage, dwelling damage,and corresponding relief received (Table 2),11 distinct gendered rehabilitation patterns
emerged. While mean crop income decreased by over 40% regardless of gender (Table 1),compared to male-headed households, female-headed households were less likely to havecompletely repaired damaged dwellings at the time of interviews (Table 2). This contrast
is explained by distinct ways of rehabilitation. On one hand, households rehabilitatedcropping individually, without using shared or hired labor (they planted fast-growing
crops like sweet potato after the provision of seeds as part of the relief, and the harvest of
rehabilitated crops started before the interviews). On the other hand, males helped eachother rehabilitate dwellings.12 Hence, the self-rehabilitation of cropping and labor sharing
for dwelling rehabilitation were both incomplete, and only the latter, which involved a
new gendered division of labor, was unequal in the gender sphere.

10

The total cyclone damage across the country (mostly in Vanua Levu and Taveuni Islands) is estimated at
F$104 million, of which residential damage is F$22 million and crop damage is F$40 million (National
Disaster Management Office 2003). Fourteen people were killed (in the sample villages, no casualties andvery limited injuries and illnesses were reported). The total cost of food rations in the country was 20 times
that of tarpaulins (National Disaster Management Office 2003). Because respondents found it difficult tospecify the monetary value of food aid they received, enumerators instead asked the quantity measured in
the number of days it would have taken to consume the food in normal periods (not actual duration). Basedon the government estimate of the cost of food ration, F$1.73 per person per day (National Disaster
Management Office 2003), the value of 60 days food ration for six months (in periods 2 and 3), F$104 percapita, is more than 3 times average crop damage (see Takasaki, forthcoming for details of relief delivery).
11
Crop damage was less common among female-headed households, but this is mainly because their nonparticipation in cropping was relatively more common.
12
Even though a lack of data on across-household labor transfers precludes me from proving that they
serve as a form of risk sharing, supporting evidence is obtained as follows. First, all refugees (almost 40%
of households with damaged main housing) stayed in others’ residences in the same village, and many ofthem lived with households in the same kin group (defined below). This clearly indicates that both village
and kin group served as risk-sharing groups. At the time of interviews, refugees were almost nonexistent.
Second, Takasaki (forthcoming) finds that communal labor for rehabilitating damaged village facilities
involves risk-sharing arrangements against idiosyncratic shocks: Contributions of communal labor are
smaller among households with damaged main housing and with greater crop damage.

10
While about 20% of households produced very small amounts of handicraft gifts
in period 2, as in period 1, both participation and intensity significantly increased later(this matches increased demands for ritual gifts in ceremonial meetings) (Table 3). In
period 4, almost 40% of households participated, and the amount was about 3.5 times thatin period 1. While total income decreased by almost 30%, handicraft income (gifts andsales combined) reached 13% of total income (Table 1). Since crop incomes in periods 2
and 3 – before the harvest of rehabilitated crops – were much smaller than in period 4,
handicrafts’ contributions to the total income in periods 2 and 3 must have been
considerable. While there was no gender difference in participation over periods 2-4,
female-headed households more strongly intensified production than male-headedhouseholds after the cyclone (Table 3), earning even higher income from handicrafts thanfrom cropping and fishing (Table 1). These results give initial evidence of gendered
responses to cyclone shocks in handicraft gift production.
3. Theoretical framework
This section provides a simple theoretical framework that shows how gendered
responses to cyclone shocks emerge in ritual handicraft gift production. Let us consider aunified household model, in which a household head allocates male and female labor to
maximize household utility, determined by household consumption and residential
quality (an intra-household bargaining model does not alter the main results on gendered
responses). Cropping is a unique income-earning activity, with no gendered division oflabor. I assume that a village is the same as a kin group and a household transfer network(this assumption is relaxed later). Only females with certain qualifications (like skills)
can make handicraft gifts, either for others as private transfers or as shared ritual duties.

11
Suppose the household produces some handicraft gifts (I focus on intensity
decisions). The household experiences crop damage, an adverse income shock; it may
also experience dwelling damage, an adverse preference shock, which directly reduces its
residential quality. There are two risk-sharing arrangements to smooth utility: one fornon-labor items and another for male labor for repairing damaged dwellings. By
contributing more handicraft gifts as part of non-labor sharing, the household canaugment not only other forms of net non-labor transfers received, but also net male labortransfers received. How well handicraft gifts compensate for labor sharing depends on thetransformability of handicraft gifts into other private transfers and the amount of own gift
production relative to others’ (considering a gift game does not alter the main results ongendered responses). To receive quick help to repair its damaged dwelling, the household
can produce handicraft gifts later. Specifically, net private transfers received are afunction of total handicraft gifts made over time (that is, credible commitments to future
gifting are sufficient to obtain current help). The household balances the marginal returnto female labor for gift production with its opportunity cost, the forgone contribution tocrop rehabilitation. The household with a damaged dwelling allocates male labor to own
dwelling repair and crop rehabilitation, while receiving labor support from others; thehousehold without a damaged dwelling is a donor of male labor transfer.
There are three types of households: M-household headed by a male with adamaged dwelling; F-household headed by a female with a damaged dwelling; and Nhousehold headed by either a male or a female without a damaged dwelling. With greaterdwelling damage experienced, the male head of M-household allocates more male laborto own dwelling repair to smooth utility by recovering residential quality and less female

12labor to gift production (to shift male labor from crop rehabilitation to dwelling repair).
These labor supply responses (self-insurance) are weakened by risk sharing, because withgreater own dwelling damage, the household can receive more male labor help fromothers (if labor sharing were complete, own labor supply would be unresponsive toidiosyncratic dwelling damage). The response to crop damage is the opposite: With
greater own crop damage, M-household increases gift production to augment net nonlabor transfers to smooth utility by maintaining consumption and reduces male labor for
repair (these responses are weakened by non-labor sharing).
Suppose the female head of an F-household allocates all male labor to own
dwelling repair (i.e., corner solution),13 or has limited control over male labor for anysocial reason, and she can thus adjust female labor only. F-household’s labor response isdistinct from M-household’s: The female head intensifies gift production to augment not
only net non-labor transfers against crop damage, but also male labor help against
dwelling damage (these responses are weakened by corresponding risk sharing). For Nhouseholds, male labor for own dwelling repair is nonexistent (i.e., another corner
solution), and the head intensifies gift production against crop damage only. To sum up,
while crop damage always leads to intensified gift production, M- and F-households
experience opposite impacts of dwelling damage.14

13This is because female-headed households’ male labor endowment is smaller than male-headedhouseholds’, as seen in the sample.
14
Dwelling damage and crop damage also indirectly affect non-labor sharing and labor sharing,
respectively. These effects work in the opposite manner to those of direct shocks. For example, as greaterdwelling damage increases the net non-labor transfer received, M-household lowers handicraft production
and augments dwelling repair, and F-household also reduces handicraft production without being able toadjust male labor. To incorporate communal male labor for village rehabilitation as risk sharing (see note
12) is a straightforward extension. With greater dwelling damage or crop damage, male labor contributions
to communal labor decrease, thereby helping augment handicraft production and own dwelling repair.

13
Now, suppose housing damage and crop damage are not independent but interact
with each other, and household gift production more strongly responds to dwelling
damage than crop damage (because cyclone relief crowds out non-labor sharing, as
discussed above). Then, it is possible that housing damage largely shapes the labor
response to crop damage. In particular, F-household may rather decrease gift production
against crop damage in order to receive more male labor help. That is, dwelling damage
also makes labor responses to crop damage distinct among M-, F-, and N-households.
The hypotheses regarding handicraft gift production can be summarized asfollows: 1) Participation is irresponsive to dwelling damage and crop damage, regardlessof gender; 2) M- and F-households have opposite intensity responses to dwelling damage;3) Dwelling damage mainly determines intensity responses to crop damage, making themdistinct among M-, F-, and N-households; and 4) These gendered responses occur overtime. To formally test hypotheses 1-4 is a task of the remaining sections.
4. Econometric specification
The theoretical framework discussed in the last section suggests the following ex
post labor supply equation for ritual handicraft gift production linked with risk sharing:
L = L(z ,W , x , M ) ,where L is labor supply; z and W, respectively, are household- and village-level adverse
shocks; and x and M, respectively, are household- and village-level factors that affectreturns to labor, such as productive assets and market prices. As it is assumed that avillage is the same as a kin group and a household transfer network, W is a covariate
shock among risk-sharing members, which determines the resources to be shared.
The estimating equation is:

14
Lit = β 0 + β1 zit + δxit + Vvt + ui + eit .

(1)

where i, v, and t stand for household, village, and time, respectively; Vvt is village
dummies and village-time dummies; ui is unobservable household heterogeneity; and eit
is a time-variant error term that is individually and independently distributed. Villagetime dummies fully control for village-level covariate shocks, Wvt, including village
facility damage and cyclone relief received by the village, as well as any other villagelevel time-variant factors, Mvt. A time dummy is added to capture common events ortrends, including seasonality. If handicraft gifts are part of risk sharing, unobservablewelfare weights used in risk sharing directly affect household labor-supply decisions.
Then, as in the full risk-sharing model (Cochrane 1991; Mace 1991; Townsend 1994), it
is crucial to control for household heterogeneity ui, using fixed-effects estimators. In the
Fijian quarterly data, household-level factors, xit, are fixed effects that vanish in fixedeffects estimates; village dummies, which capture fixed village characteristics, such asenvironmental conditions, also vanish. Equation (1) does not tell how individual
households respond to others’ decisions, but to do so is not a goal of this paper. Equation(1) is the same as the ex post labor supply equation commonly used in previous works(e.g., Rose 2001); however, the standard income effect – with greater adverse
idiosyncratic shocks, the household increases labor supply to smooth income, i.e., β1 > 0– does not apply, because the return of this labor activity is realized through risk sharing.
I consider three specifications for household-level shocks, zit: model A with a
combined measure of dwelling damage and crop damage (hvcd = hv + cd); model B witha dummy for dwelling damage (d_hv), cd, and their interaction term (d_hv*cd); andmodel C with hv, cd, and their interaction term (hv*cd) for the sub-sample of M/F-

15households (hv > 0). Model A, which assumes the same marginal effects of hv and cd, isa restrictive model. Model B differentiates between M/F- and N-households (simply
using hv and cd does not do so); it does not capture the impacts of hv. Potential selection
bias in model C is not a major concern, because the incidence of dwelling damage isconsidered exogenous (households with and without damaged dwellings do not differ
significantly from each other in their pre-cyclone income, asset holdings, and household
characteristics, Takasaki forthcoming).15
Equation (1), which ignores gendered heterogeneity, is restrictive. To test
gendered responses (hypotheses 2 and 3), I extend equation (1):
Lit = α + β1 zit + β 2 zit d i + δxit + Vvt + ui + eit .

(2)

where di is a dummy for female head (fhead). zitdi includes hvcd*fhead in model A,
d_hv*fhead and d_hv*cd*fhead in model B, and hv*fhead, cd*fhead, and hv*cd*fhead inmodel C. Model B captures distinct effects of d_hv between M- and F-households and of
cd among N-, M-, and F-households (d_hv*cd*fhead captures distinct interaction effectsof two shocks between male- and female-headed households).16 Model C fully
differentiates between M- and F-households.

15

Household crop damage is potentially endogenous, because unobservable household and village
characteristics, such as land quality, farming skills, market conditions, and environmental conditions (e.g.,
resource stock), which affect pre-cyclone cropping decisions and thus crop damage, can be correlated withex post labor-supply decisions. Even if the incidence of housing damage is more random, damage loss
depends on unobservable initial dwelling quality, which may be correlated with unobservable determinantsof ex post labor-supply decisions. In the Fijian quarterly data, all of these unobservable factors are timeinvariant factors that are fully controlled for by fixed-effects estimators. Relief received by individual
households is not included as an explanatory variable, because it is endogenously determined as part ofprivate risk sharing (Dercon and Krishnan 2005).
16
In the sample, about 55% and 9% of households, respectively, are M- and F-households, and theremaining 36% are N-households, of which more than 90% are headed by males (Table 2). The limited
number of observations of female-headed N-households precludes me from differentiating them from maleheaded N-households. I used cd*fhead instead of d_hv*cd*fhead, treating male-headed N-households as abase case (F-households and female-headed N-households cannot be differentiated). I found almost thesame results.

16
Even if gendered responses (non-zero β2) are found, equation (2) does not tellwhich gender constraint matters, labor endowment or other. To directly control for thelabor-endowment effect, I extend equation (2):Lit = α + β1 zit + β 2 zit d i + β 3 zit mi + δxit + Vvt + ui + eit .

(3)

where mi is labor endowment (the numbers of female and male adults, fadlt and madlt,
respectively).17 If gendered responses persist in equation (3), it is caused by gendered
constraints other than labor endowments.
To capture potentially distinct responses in participation and intensity (hypothesis1), I estimate the determinants of the probability of participation – the linear probability(LP) model – and the intensity of production conditional on participation separately. Thisis effectively a hurdle model, and its ease of estimating marginal effects is an advantage(all marginal effects reported in the next section are based on this model). An alternative
fixed-effects sample selection model (Kyriazidou 1997) is unfeasible with the Fijian data,
which lack the identifying instruments required to credibly estimate the selection
equation. I also employ the trimmed least-squares (LS) estimator developed by Honoré(1992). Although the constraint that estimated coefficients are the same for participationand intensity decisions is a disadvantage in this fixed-effects censored regression model,
its similar results to those of the conditional model on intensity give me confidence about
the findings’ robustness. With a lack of time allocation information, I use values ofhandicraft gifts produced (Table 3) as a proxy. The fixed-effects models control for any
systematic difference between values and labor inputs caused by unobservable skills andany other fixed factors (market prices are controlled for by village-time dummies).
zitmi includes hvcd*fadlt and hvcd*madlt in model A, d_hv*fadlt, d_hv*madlt, cd*fadlt and cd*madlt inmodel B, and hv*fadlt, hv*madlt, cd*fadlt and cd*madlt in model C. To control for potential roles of childlabor in risk coping, I also considered the number of elder children for mi, finding no significant results.

17

17
I also estimate direct impacts of observable household fixed-effects, such as fhead,fadult, and madult,18 using three corresponding, random-effects models for participation,
intensity conditional on participation, and unconditional intensity (random-effects tobit).
A key question is whether gender (fhead) does not directly affect labor supply, even if italters labor responses to shocks. Random-effects estimates are biased if idiosyncratic
shocks are correlated with unobservable fixed effects. While the trimmed LS estimator isrobust to heteroskedasticity and non-normality, the presence of either of these two also
makes random-effects tobit estimates biased.
To test whether gendered responses occur over time (hypothesis 4), I conduct
two-period analyses separately for periods 1 and 2, periods 1 and 3, and periods 1 and 4.
In the latter two, labor input in period 3 or 4 is connected with the shocks experienced inperiod 2, and periods 2-3 or periods 2-4 are treated as one post-cyclone period. This is astandard practice in analyzing annual survey data that lack information over time within
the year. If private transfers are a function of total handicraft gifts made over postcyclone periods, gifts made during the period of interest are negatively correlated withthose in “unobserved” previous post-cyclone period(s), causing bias. In particular, thepositive and negative impacts of dwelling damage and crop damage, respectively, inperiod 2 causes downward and upward biases in the estimates in periods 3 and 4.
5. Estimation results
Fixed-effects results are reported in Tables 4-7. All results of model A appear in
Table 4 – LP, conditional LS, and trimmed LS in the top, middle, and bottom panels,

18

Other fixed factors included are the number of children, the age of household head, the education ofhousehold head (schooling years), land per capita, fishing capital per capita, the mean age of female adults,
and the highest schooling years of female adults (potential handicraft producers). Village dummies do notvanish in random-effects estimates, of course.

18
respectively. The results of these three estimators of models B and C appear in Tables 5,6, and 7, respectively – model B in the top panel and model C in the bottom one. In allthese four tables, the first, second, and third sets of three columns show results in periods
1 and 2, periods 1 and 3, and periods 1 and 4, respectively; in each set, the first, second,
and third columns report results of equations (1), (2), and (3), respectively. Table 8 shows
the random-effects results of equation (3) (models B and C only).19
Most results regarding the damage variables’ impacts on participation – in allmodels in all periods – are very weak (even though some estimated coefficients in model
C are statistically significant, the marginal effects are almost zero) (Tables 4 and 5).
Hence, participation is always insensitive to idiosyncratic shocks, regardless of gender,
i.e., hypothesis 1 holds. In the random-effects estimates (Table 8), larger male laborendowment (with no interaction term) increases the probability of participation in all
periods. Households with more male labor can better mobilize female labor.20 No otherhousehold characteristics affect participation in a strong manner. In particular,
participation is neutral to gender itself with labor endowments controlled for. Therefore,
whether females produce ritual handicraft gifts depends on household male laborendowment and unobservable factors, such as craft skills and social status.
Results on intensity responses are summarized as follows (Tables 4, 6, and 7).
Most results of the restricted equation (1) are nonsignificant, and almost all statisticallysignificant results in (1) become nonsignificant in the corresponding equations (2) and (3).
19

Robust standard errors are reported in all estimation results. One village with almost no handicraft
production is dropped for periods 1 and 3 in models A and B and for all periods in model C. The null
hypothesis that the random-effects estimates are the same as the pooled estimates (i.e., the absence ofindividual heterogeneity ui) is strongly rejected by the likelihood-ratio test in all models.
20
This effect is weakened by crop damage in periods 2 and 3 (results not shown), indicating that crop
rehabilitation reduces the labor capacity for gift production (the same relationship also holds in the fixedeffects models).

19
Contrarily, once gendered heterogeneity is controlled for in equation (2), many results
become statistically significant. Most results in another restricted model A are also
nonsignificant. Shock impacts on intensity decisions are mostly opposite to each other bygender and shock, and thus they cancel out each other in these restricted models; ignoring
this heterogeneity makes it impossible to identify true impacts.
Let me first discuss detailed results in period 2. According to equation (2), Fhouseholds greatly intensify gift production (in both incidence and magnitude) in
response to dwelling damage. Results of two fixed-effects models are qualitatively thesame, indicating that trimmed-LS results reflect intensity, not participation. The
estimated marginal effects are huge: F$15 per capita per month (more than six times
mean production) for d_hv at means in model B, and .20 for hv at means in model C (i.e.,a one standard deviation increase in hv augments production by more than three standard
deviations). In equation (3), all labor-endowment effects are nonsignificant (results notshown), and all significant results in (2) still hold. Thus, gender factors other than laborendowments matter. M-households’ responses are the opposite, but much weaker inmagnitude and in a statistical sense. These results confirm hypothesis 2.
Strong interaction between dwelling damage (incidence, in particular) and crop
damage weakens the net impacts of dwelling damage among both male- and femaleheaded households, making the overall impacts of crop damage positive and negative,
respectively (crop damage variables with no interactions are mostly nonsignificant). As
clearly shown in model C, households (F-households in particular) more strongly respondto dwelling damage than crop damage, and as a result, the former mainly shapes theimpacts of the latter. F-households intensify gift production against dwelling damage by20
reducing production against crop damage;21 the converse holds true among M-households
to a much weaker degree. These results confirm hypothesis 3.
These female-headed households’ responses to shocks also hold in periods 3 and
4 (model B, in particular), while the results are statistically much weaker than in period 2.
The estimated coefficients of dwelling damage in periods 3 and 4 are smaller than thosein period 2, but they can be biased downward as discussed above; despite the potential
downward bias in the estimated coefficients of crop damage in periods 3 and 4, they are
similar across periods 2-4. Male-headed households are insensitive to cyclone damage inperiods 3 and 4. These results are consistent with hypothesis 4.
The estimated coefficients of cyclone damage in the random-effects models(Table 8) are distinct from corresponding fixed-effects estimates, suggesting bias in theformer. In particular, female-headed households’ responses to shocks do not hold in astrong manner, especially in the random-effects-tobit estimates. Labor endowments andthe gender of household head as fixed effects are nonsignificant in all models. That is,gendered responses to shocks emerged in the gender-neutral activity.
6. Robustness check
This section discusses the robustness of the estimation results presented in the lastsection. I examine recall bias, consider risk-sharing groups other than village, andprovide evidence for the link between gendered responses and risk sharing.
6.1. Recall bias

21

In models B and C of equation (2), the marginal effects of crop damage with dwelling damage and at themean dwelling damage value, respectively, are -.10 and -.12 (i.e., a one standard deviation increase in crop
damage reduces production by .7 standard deviation). An illustrative finding is that in model C of equations(2) and (3), the estimated coefficients of cd*fhead are nonsignificant, but become strongly significant whenhv*cd and hv*cd*fhead are dropped.

21
Special attention needs to be given to measurement errors in the retrospective data.
First, measurement errors in the values of dwelling damage and crop damage can beconsiderable and systematic. Compared to hv, the main house damage index (hd) 22
should contain smaller measurement errors, because relief officers used similar categories– no damage, partial damage, and complete damage – in their damage assessments, andthus the damage status of each house was common knowledge among villagers.
Measurement errors in the dwelling damage dummy and a dummy for crop damage(d_cd) should be minimal. I repeated the analyses using hd and d_cd, finding
qualitatively similar results. The advantage of using hv and cd is that it is possible todirectly compare the impacts of these two shocks and examine aggregate shock hvcd forcomparison.
Second, because handicraft gifts are culturally and socially important in the kava
ritual and they coincide with memorable events like funerals, respondents could recall
production reasonably well, but such recollections may still contain considerable errors.
While the time dummy fully controls for common memory inaccuracy, the correlation ofrecall errors in gift production, especially in period 1, with idiosyncratic shocks can cause
bias. Specifically, a positive (negative) correlation – households with larger idiosyncratic
shocks tend to report higher (lower) pre-cyclone production than the real – causes upward(downward) bias. This potential bias is not a major concern for qualitatively testing
gendered responses, because with no a priori reason for different recall errors and their
distinct correlations with idiosyncratic shocks among M-, F-, and N-households, their
distinct responses should not be a biased result.
22

Enumerators asked about the severity of main housing damage, using five options: 0 = no damage (47%),
1 = little damage (20%), 2 = some damage (12%), 3 = big damage (13%), 4 = completely destroyed (7%),
where the proportions of households are shown in parentheses.

22
6.2. Risk-sharing groups other than village
Risk-sharing groups other than the village can play a significant role (see, e.g.,
Fafchamps and Lund 2003; De Weerdt and Dercon 2006 for recent works on risk-sharing
networks). First, labor sharing may take place within a village sub-group. In particular, a
kin group that plays central roles in ritual gift exchange also serves as a risk-sharing
group (see note 12). I repeated the analyses treating the kin group as a risk-sharing group,by replacing village-time dummies with kin-group-time dummies, finding very similar
results on idiosyncratic shocks.23 Second, if non-labor sharing takes place in a spacelarger than the village, the estimates using village- or kin-group-time dummies may bebiased. This is not a major concern for the latter estimates because the data indicate thatmost across-villages non-labor transfers were made with households belonging to thesame kin group (like those in a city).24
6.3. Evidence for the link between gendered labor responses and risk sharing
Confirming hypotheses 2 and 3 does not necessarily indicate that gendered
responses are caused by their link with risk sharing. Here, as indirect evidence for thatlink, I report the nonexistence of gendered responses in handicraft selling, which is notpart of risk sharing. The same theoretical framework as above shows that 1) all M/F/Nhouseholds increase sales against crop damage to earn extra income (this income effect isweakened by non-labor sharing), and 2) M/F-households do not adjust sales to dwelling
damage, because to do so does not directly increase labor help. Takasaki (2009) confirms
The hierarchical kin structure in Fiji is well known among anthropologists: The bottom is tokatoka,
followed by mataqali, yavusa, and vanua, and all native Fijians belong to one tokatoka, which belongs to
one mataqlai, and so forth (Ravuvu 1983). While vanua ranges over several villages, yavusa, mataqali, andtokatoka are often formed within the village. The sample contains 15 yavusa, 36 mataqali, and 53 tokatoka(excluding several mataqali and tokatoka consisting of only one household). In this alternative analysis, I
treat yavusa, mataqali, and tokatoka as a risk-sharing group separately.
24
Ex ante risk management is unlikely to be a significant factor. Distinct from other islands in the country,
the study area is less prone to being hit by cyclones.
23

23
these conjectures: Households augment sales against crop damage, but not dwelling
damage, independent of dwelling damage and gender.
7. Conclusion
This paper demonstrates that the Fijian kava ritual emerges as insurance against
cyclone risk, as women’s production of ritual handicraft gifts is linked with risk sharing.
The cyclone tightens female-heads’ constraints on intra-household male labor allocationin the gendered Fijian society. This is because male labor sharing against dwelling
damage emerges as a new gendered division of labor, and cyclone relief (food aid)
crowds out risk sharing against crop damage, but not against dwelling damage. As aresult, even though handicraft gift production is normally neutral to the household head’s
gender, only female-headed households intensify production against dwelling damage to
receive more male labor help and reduce production against crop damage to facilitate
intensification against dwelling damage. These gendered responses are caused bygendered constraints other than labor endowment, such as discrimination. Gendered
responses occur both during and after the emergency period; thus, reciprocity in risk
sharing takes place over time. Restricted models that ignore heterogeneity caused bygender and shock yield nonsignificant results, because true impacts are mostly opposite
to each other. Participation in gift production, however, is independent of shocks andgender. Only females with sufficient household labor endowment and some unobservablequalifications, such as craft skills and social status, can make ritual handicraft gifts. As
such, the kava ritual protects a subset of women with limited coping capabilities, though
it is not sufficient to fill the gender gap in dwelling rehabilitation.

24
These findings suggest the following implications for policy and research. First,
the scope of risk coping is broader than usually thought. Ritual can emerge as a rational
coping action in certain situations. Second, capturing heterogeneous coping responses(especially opposite ones) is critically important. Heterogeneity may newly emerge asshocks augment inequalities in coping capabilities among households. Third, a better
understanding of the effects of public safety-net policies on private mechanisms isstrongly needed. Efficient resource allocation across relief types not only better satisfies
victims’ demands, but also can improve equity when victims’ coping capabilities areunequal. Even if this is practically difficult for small developing countries that rely on
emergency aid from donors, policymakers can design redistributive relief policies (e.g.,
subsidizing dwelling rehabilitation for females). As private mechanisms adjust over time,such policies can be effectively implemented even after the emergency period.
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28

Table 1. Household sectoral incomes by period and gender.

All

Male head(fhead=0 )Femalehead(fhead=1 )All

Male head(fhead=0 )Femalehead(fhead=1 )Mean test (p-value)
By period
By gender
FePre- PostMaleAll
male
cycyheadhead clone clone

49.6 (78.3)

53.4 (82.2)

22.7 (29.5)

29.5 (49.2)

31.8 (51.7)

13.1 (18.9)

0.00

0.00

0.08

0.02 0.02

30.5 (56.2)

30.2 (54.7)

32.4 (66.4)

18.8 (30.4)

19.4 (31.7)

14.2 (17.1)

0.00

0.00

0.09

0.82 0.29

2.3 (7.4)

2.2 (7.0)

2.8 (9.6)

8.7 (20.5)

7.5 (16.1)

17.5 (39.1)

0.00

0.00 0.02

0.60 0.00

0.5 (1.7)

0.5 (1.7)

0.3 (0.8)

0.5 (2.7)

0.5 (2.9)

0.3 (1.0)

0.76

0.76

0.95

0.36 0.66

0.4 (2.7)

0.4 (2.6)

0.8 (2.9)

0.8 (4.4)

0.7 (4.5)

1.2 (4.1)

0.17

0.21

0.56

0.34 0.50

8.5 (32.9)

9.2 (34.1)

3.5 (22.6)

8.4 (32.8)

9.1 (33.9)

3.5 (22.6)

0.96

0.96

1.00

0.29 0.30

5.2 (34.3)

5.7 (36.6)

1.4 (4.8)

2.2 (8.2)

2.3 (8.6)

1.5 (5.0)

0.12

0.12

0.93

0.45 0.56

97.0 (118.1) 101.7 (122.0) 63.9 (77.4)

68.8 (71.4)

71.3 (72.0)

51.3 (64.8)

0.00

0.00

0.42

0.05 0.09

342

342

300

Pre-cyclone

Cropping
Fishing
Handicrafts (gifts and sales)aNon-handicraft forest products
Casual wage laboraPermanent wage labor
Other
Total
No. observations
a

a

a

300

Post-cyclone

42

42

T he data in periods 1 and 4 are shown for the pre- and post-cyclone periods, respectively.
Note - Household sample means of incomes per capita per month are shown. Standard deviations are in parentheses. Mean test results are italicized andthose with a 5% significance level are bolded.

29
Table 2. Household characteristics, cyclone damage, relief, and rehabilitation by gender.

All

Male head(fhead =0)

Femalehead(fhead=1 )

0.00

1.00

Mean
/prop.
Test(p-value)

Household characteristics:
Female head dummy (fhead )0.12

Age of household head

49.7 (14.0) 48.4 (13.8) 59.0 (11.6)

0.00

Schooling years of household head

8.7 (3.2)

8.9 (3.1)

6.9 (3.1)

0.00

No. female adults (fadlt )1.7 (1.1)

1.7 (1.1)

1.9 (1.0)

0.46

No. male adults (madlt )n.a.

1.8 (1.2)

1.9 (1.2)

1.2 (1.2)

0.00

No. children

2.4 (1.9)

2.5 (1.9)

1.6 (1.5)

0.01

Average age of female adults

40.0 (12.6) 38.5 (11.8) 50.4 (13.3)

0.00

Highest schooling years of female adults

10.9 (3.0)

9.7 (3.6)

0.00

Land holdings per capita (acres)

0.97 (1.40) 1.04 (1.47) 0.48 (0.47)

0.01

Fishing capital per capita (F$)

83 (262)11.1 (2.8)
90 (276)

31 (111)0.01

Cyclone damage:
Crop damage dummy (d_cd )

0.84

0.86

0.71

0.02

Dwelling damage dummy (d_hv )

0.64

0.63

0.71

0.27

Crop damage per capita (F$) (cd )32 (49)23 (40)0.17

67 (133)

91 (199)0.29

1.2 (1.3)

1.2 (1.4)

0.69

0.07

0.12

0.22

0.04

0.05

0.00

0.15

0.78

0.79

0.69

0.15

Food aid in period 3 dummy

0.78

0.78

0.81

0.66

Food aid per capita per month in period 2 (days)

10.3 (8.8)

10.5 (8.9)

8.8 (8.8)

0.27

Food aid per capita per month in period 3 (days)

9.7 (8.2)

9.7 (8.4)

10.0 (7.1)

0.82

0.64

0.67

0.48

0.05

342

300

42

Dwelling damage per capita (F$) (hv )70 (143)

Main house damage index (0-4) (hd )1.2 (1.3)

Tarpaulins in period 2 dummy

0.07

Tarpaulins in period 3 dummy
Food aid in period 2 dummy

34 (50)Cyclone relief:

Dwelling repair among victims (d_hv=1 ):Dwelling repair dummy
No. observations:

Note - Standard deviations are in parentheses. t-test and chi-squared tests compare the means andproportion for continuous and dummy variables, respectively. Test results are italicized and thosewith a 5% significance level are bolded.

30
Table 3. Household handicraft gift production by period and gender.

Period 1

Period 2

Period 3

Period 4(n=342)

Mean/prop. test by
period: Period 1 vs.
2

3

4

Participation (proportion):
All

0.18

0.22

0.27

0.39

0.25

0.01

0.00

Male head (fhead=0 )

0.18

0.22

0.26

0.39

0.31

0.02

0.00

Female head (fhead=1 )

0.19

0.24

0.29

0.45

0.59

0.31

0.01

Prop. test by gender

0.91

0.75

0.76

0.41

Mean values of production per capita perm onth (F$):
All

1.9 (6.7)

2.3 (7.7)

3.0 (9.1)

6.7 (15.0)

0.47

0.08

0.00

Male head (fhead=0 )

1.8 (6.4)

2.0 (6.5)

2.7 (7.9)

6.2 (14.7)

0.81

0.16

0.00

Female head (fhead=1 )

2.3 (8.7)

4.6 (13.3)

5.0 (15.2) 10.5 (16.2)

0.35

0.31

0.00

Mean test by gender

0.70

0.04

0.12

0.08

Note - Standard deviations are in parentheses. t-test and chi-squared tests compare the means andproportion of continuous and dummy variables, respectively. Test results are italicized and those with
a 5% significance level are bolded.

31

Table 4. Determinants of handicraft gift production - fixed-effects model A.
Periods 1 and 2
Eq. (1)

Eq. (2)

Periods 1 and 3

Eq. (3)Eq. (1)

Eq. (2)

Periods 1 and 4

Eq. (3)Eq. (1)

Eq. (2)

Eq. (3)0.0000(0.0002)0.0000(0.0002)-0.0001(0.0005)

0.0002(0.0003)0.0000(0.0005)

Participation - linear probability
hvcd-0.0001(0.0001)-0.0001(0.0001)

0.0003(0.0003)0.0001(0.0001)-0.0003(0.0002)

No

No

Yes

No

No

Yes

No

No

Yes

0.05

0.06

0.07

0.08

0.09

0.11

0.17

0.18

0.19

0.041

0.049

0.039

0.009

0.015

0.002

0.000

0.000

0.000

684

684

684

600

600

600

684

684

684

hvcd*fheadzm
R squared
F (p-value)
No. obs.

0.0004 *(0.0002)0.0004 *0.0005(0.0002)(0.0006)-0.0003(0.0003)-0.0009 **(0.0004)

Production per capita per month - conditional on participation
hvcd-0.005(0.013)-0.009(0.014)0.014(0.027)0.079(0.059)0.074(0.060)

No

No

Yes

0.14

0.20

0.000
178

hvcd*fheadzm
R squared
F (p-value)
No. obs.

0.021(0.013)0.021(0.013)0.061 *
(0.035)0.026 *
(0.014)0.022(0.014)0.078 **
(0.034)0.025(0.055)0.016(0.053)0.047 *
(0.027)0.026(0.027)

No

No

Yes

No

No

Yes

0.21

0.15

0.15

0.21

0.27

0.29

0.31

0.000

0.001

0.277

0.343

0.035

0.000

0.000

0.000

178

178

220

220

220

308

308

308

0.020
(0.017)0.044(0.044)0.039(0.027)0.013(0.028)

Production per capita per month - trimmed least squares
hvcd-0.010(0.027)-0.013(0.019)0.017(0.026)0.217(0.251)0.205(0.254)

No

No

Yes

4276.83786.40.000
684

hvcd*fheadzmLoss function
Chi sq. (p-value)
No. obs.

0.041 **
(0.020)0.042 **
(0.024)0.061 **
(0.030)0.025(0.016)0.136(0.403)0.100(0.378)

No

No

Yes

No

No

Yes

3719.39354.99221.83332.721663.3

21503.821294.6

0.000

0.000

0.044

0.111

0.000

0.000

0.000

0.000

684

684

600

600

600

684

684

684

*10% significance, **5% significance, ***1% significance.
Note - Robust standard errors are in parentheses. zm includes hvcd*fadlt and hvcd*madlt . Other control variables which are notshown here are time dummy and village-time dummies (and constant for linear models).

32
Table 5. Determinants of participation in handicraft gift production - fixed-effects linear probability.
Periods 1 and 2

Periods 1 and 3

Eq. (1)

Eq. (2)

Eq. (3)Eq. (1)

0.0676(0.0456)

0.0556(0.0483)

0.0831(0.0681)0.1212(0.0774)0.0001(0.0003)0.0001(0.0003)

0.0023 **(0.0010)-0.0007(0.0009)-0.0005(0.0010)-0.0002(0.0006)

0.0883(0.0795)-0.0010(0.0013)

Eq. (2)

Periods 1 and 4
Eq. (3)Eq. (1)

Eq. (2)

Eq. (3)0.1072(0.0796)

0.1092(0.0982)-0.0302(0.0740)-0.0394(0.0773)-0.0511(0.1139)0.0004(0.0007)0.0004(0.0007)0.0009(0.0013)-0.0011(0.0010)-0.0011(0.0010)0.0006(0.0016)-0.0008(0.0012)-0.0006(0.0014)0.0005(0.0011)0.0006(0.0012)0.0006(0.0013)0.0008(0.0014)0.0973(0.0776)

0.1066(0.1037)

0.0518(0.1005)

0.0727(0.1104)

0.0223(0.1147)-0.0021 **(0.0010)-0.0010(0.0015)-0.0020(0.0013)0.0004(0.0018)0.0000(0.0020)

No

Yes

No

Yes

Model Bd_hv

cdd_hv*cd

d_hv* fhead

d_hv*cd*fheadzm
R squared
F (p-value)
No. obs.

No

No

Yes

No

No

0.06

0.07

0.11

0.08

0.08

0.14

0.18

0.18

0.19

0.044

0.068

0.004

0.006

0.011

0.000

0.000

0.000

0.000

684

684

684

600

600

600

684

684

684

-0.0003 ** -0.0005 ** -0.0005(0.0002)(0.0002)(0.0004)

0.0005(0.0003)0.0006 *(0.0003)0.0008(0.0007)-0.0002(0.0003)-0.0003(0.0004)-0.0009(0.0010)-0.0011(0.0010)-0.0012(0.0011)0.0021(0.0014)-0.0001(0.0012)-0.0001(0.0013)0.0009(0.0018)-0.0015(0.0011)-0.0014(0.0012)0.0025(0.0023)0.00001(0.0000)

0.00001 *(0.0000)

0.00001 **(0.0000)

0.00000(0.0000)-0.00001(0.0000)-0.00001 *(0.0000)

0.00001 ** 0.00001(0.0000)(0.0000)

0.00001(0.0000)

0.0006 *(0.0003)0.0011 **(0.0005)-0.0005(0.0004)-0.0006(0.0007)-0.0001(0.0004)-0.0004(0.0008)

0.0004(0.0011)-0.0010(0.0008)

0.0007(0.0013)-0.0012(0.0013)-0.0025(0.0024)-0.0034(0.0021)-0.00002 *(0.0000)-0.00002 **(0.0000)

0.00000(0.0000)

0.00000(0.0000)

0.00006 *** 0.00006 ***(0.0000)(0.0000)

Model C
hv

cd

hv*cd

hv* fhead

cd*fhead

hv*cd*fheadzm
R squared
F (p-value)
No. obs.

No

No

Yes

No

No

Yes

No

No

Yes

0.08

0.09

0.15

0.10

0.11

0.19

0.19

0.21

0.24

0.169

0.297

0.000

0.042

0.070

0.000

0.000

0.000

0.000

396
396
396
396
396
396
396
396
396
*10% significance, **5% significance, ***1% significance.
Note - Robust standard errors are in parentheses. zm includes d_hv*fadlt , d_hv*madlt (model B), hv*fadlt , hv*madlt (model C), cd*fadlt ,and cd*madlt . Other control variables which are not shown here are time dummy, village-time dummies, and constant.

33
Table 6. Determinants of handicraft gift production per capita per month - fixed-effects conditional on participation.
Periods 1 and 2
Eq. (1)

Eq. (2)

Periods 1 and 3

Eq. (3)Eq. (1)

Eq. (2)

Periods 1 and 4

Eq. (3)Eq. (1)

Eq. (2)

Eq. (3)Model Bd_hv

cdd_hv*cd-0.002(2.182)-2.799(2.053)-1.268(4.754)4.945(4.173)

3.430(4.215)4.450(8.724)0.330(4.065)-1.037(4.215)

6.007(7.731)-0.015(0.013)-0.021(0.015)0.018(0.040)-0.033(0.047)-0.035(0.048)0.027(0.109)-0.052(0.034)-0.054(0.035)0.036(0.090)0.017(0.030)0.049(0.036)0.081(0.049)0.060(0.079)0.088(0.094)0.162(0.126)0.092(0.079)0.111(0.086)0.132(0.088)20.518 **(10.121)20.953 **(9.030)8.537(7.313)8.723(6.646)

11.449 *(6.139)10.124 *(5.401)-0.129 *(0.071)-0.163 **(0.072)-0.141(0.097)-0.228 *(0.131)-0.150(0.091)-0.209 **(0.098)d_hv* fhead

d_hv*cd*fheadzm
R squared
F (p-value)
No. obs.

No

No

Yes

No

No

Yes

No

No

Yes

0.14

0.31

0.38

0.17

0.20

0.30

0.27

0.28

0.34

0.001

0.003

0.020

0.096

0.145

0.060

0.000

0.000

0.000

178

178

178

220

220

220

308

308

308

-0.039 *(0.023)-0.053 **(0.025)-0.009(0.043)0.012(0.010)0.012(0.010)0.053 **
(0.020)0.041(0.032)0.025(0.032)0.042(0.054)-0.029(0.023)-0.004(0.030)0.053(0.122)0.009(0.056)0.039(0.079)0.338 *
(0.181)

0.046(0.090)0.053(0.094)0.238 *
(0.134)0.0005(0.0004)

0.0006(0.0004)

0.0005(0.0007)0.0003(0.0006)

0.0002(0.0007)-0.0004(0.0006)-0.0001(0.0005)

0.0001(0.0006)

0.0003(0.0006)

0.317 **
(0.127)0.326 **
(0.125)0.202(0.184)0.227(0.162)0.143 **
(0.066)0.125 **
(0.056)0.029(0.145)0.021(0.158)0.047(0.348)-0.079(0.303)-0.081(0.078)-0.154 *(0.089)-0.003(0.005)-0.004(0.005)-0.005(0.011)-0.006(0.009)-0.001(0.001)-0.001(0.001)

No

No

Yes

No

No

Yes

No

No

Yes

0.16

0.41

0.45

0.21

0.26

0.46

0.38

0.42

0.49

0.261

0.150

0.042

0.285

0.339

0.003

0.000

0.000

0.000

Model C
hv

cd

hv*cd

hv* fhead

cd*fhead

hv*cd*fheadzm
R squared
F (p-value)
No. obs.

114
114
114
144
144
144
198
198
198
*10% significance, **5% significance, ***1% significance.
Note - Robust standard errors are in parentheses. zm includes d_hv*fadlt , d_hv*madlt (model B), hv*fadlt , hv*madlt (model C),
cd*fadlt , and cd*madlt . Other control variables which are not shown here are time dummy, village-time dummies, and constant.

34
Table 7. Determinants of handicraft gift production per capita per month - trimmed least squares.
Periods 1 and 2
Eq. (1)

Eq. (2)

Periods 1 and 3

Eq. (3)Eq. (1)

Eq. (2)

Periods 1 and 4

Eq. (3)Eq. (1)

Eq. (2)

Eq. (3)Model Bd_hv

cdd_hv*cd-0.516(4.314)-5.724 *(3.400)-6.054(5.733)9.103(9.842)4.311(11.810)15.790(18.270)

5.906(7.985)3.050(7.271)20.850(17.530)-0.021(0.016)-0.043(0.045)0.015(0.071)-0.077(0.078)-0.074(0.083)-0.025(0.156)-0.039(0.128)-0.043(0.128)0.063(0.159)0.033(0.054)0.116 *
(0.064)0.121 *
(0.072)0.106(0.133)0.267(0.222)0.240 *
(0.123)0.048(0.171)

0.077(0.174)0.106(0.144)d_hv* fhead

d_hv*cd*fheadzmLoss function
Chi sq. (p-value)
No. obs.

51.100 *** 48.380 ***(15.570)(16.620)43.860 *** 34.810 **(15.170)(15.830)

24.270 **4.976(11.860)(16.300)-0.302 *** -0.302 ***(0.106)(0.116)-0.442 *(0.240)-0.286 **(0.137)-0.396 ***(0.152)-0.224(0.155)

No

No

Yes

No

No

Yes

No

No

Yes

4271.92530.02416.59165.77976.57434.121736.920814.9

20051.4

0.000

0.000

0.000

0.374

0.028

0.014

0.000

0.000

0.000

684

684

684

600

600

600

684

684

684

-0.048 **(0.019)-0.078(0.128)-0.121(0.205)0.026(0.308)0.019(0.340)0.017(0.163)0.060 **
(0.024)0.032(0.122)-0.002(0.139)-0.053(0.075)0.022(0.178)0.185(0.273)0.203(9.115)0.316(8.166)0.504(1.522)0.009(0.090)-0.002(0.108)0.200(0.223)0.0006(0.0007)0.0007(0.0015)0.0006(0.0012)-0.0001(0.0891)-0.0005(0.0808)-0.0005(0.0019)-0.0001(0.0004)

0.0001(0.0012)0.0002(0.0007)

Model C
hv

cd

hv*cd

hv* fhead

0.798 *** 0.878 ***(0.110)(0.129)0.462 ***
0.531
(0.161)(0.371)

0.283(0.401)-0.021(0.317)-0.197(0.178)-0.096(0.985)0.009(11.000)-0.699(2.808)-0.540(0.417)-0.339(0.719)-0.001(0.007)-0.006(0.030)-0.012(0.335)0.009(0.112)0.013(0.020)0.006(0.025)

No

No

Yes

No

No

Yes

No

No

Yes

3791.3

1669.31436.18063.76131.73332.79532.29102.78251.1

0.199

0.000

0.000

0.329

0.000

0.000

0.000

0.000

0.000

396

396

396

396

396

396

396

396

396

cd*fhead

hv*cd*fheadzmLoss function
Chi sq. (p-value)
No. obs.

*10% significance, **5% significance, ***1% significance.
Note - Robust standard errors are in parentheses. zm includes d_hv*fadlt , d_hv*madlt (model B), hv*fadlt , hv*madlt (model C),
cd*fadlt , and cd*madlt . Other control variables which are not shown here are time dummy and village-time dummies.

35
Table 8. Determinants of handicraft gift production - random-effects.
Participation - linear probability

Production per capita per month conditional on participation

Production per capita per month tobit

Periods

1&2

1 &3

1& 4

1 &2

1&3
Model B

1& 4

1&2

1& 3

1& 4

d_hv

0.072
(0.071)

0.111(0.099)-0.139(0.099)-4.719(5.135)-1.866(6.456)0.962(6.629)0.222(3.763)

5.318(5.788)-6.459(6.756)cd

0.003 **
(0.001)

0.002(0.001)0.001(0.001)

0.068(0.058)0.157 **
(0.078)0.176 **
(0.089)0.085 *
(0.049)0.143 **
(0.071)0.186 **
(0.094)d_hv*cd-0.001(0.001)-0.001(0.001)0.001(0.001)

0.053(0.057)0.090(0.100)0.043(0.096)9.713 **
(4.205)

1.697(6.540)1.027(7.939)d_hv* fhead

0.064(0.077)-0.004(0.107)-0.014(0.111)18.068 **(7.360)

7.148(6.005)6.750(5.168)-0.006(0.039)-0.010(0.057)0.041(0.071)d_hv*cd*fhead-0.001(0.002)0.000(0.002)0.003 **
(0.001)-0.139 **(0.056)-0.190 *(0.113)-0.142 *(0.085)-0.064(0.053)-0.045(0.087)0.071(0.113)

fhead

0.042
(0.068)0.033(0.077)0.007(0.071)

0.859(4.664)-1.593(2.653)-4.389(3.194)-1.326(3.146)-0.713(4.391)-3.298(5.253)fadlt-0.013(0.023)-0.033(0.028)0.002(0.025)0.612(1.118)0.534(0.832)0.533(0.984)-0.753(1.162)-1.777(1.573)0.061(1.868)madlt

0.072 ***
0.080 *** 0.069 ***(0.023)(0.025)(0.022)-0.723(1.053)0.212(0.685)-0.238(0.968)2.326 *** 3.306 ***3.270 **
(0.877)(1.199)(1.449)F/Chi sq. (p-value)

0.000

0.000

0.000

0.000

0.000

0.000

0.001

0.002

0.000

654

574

654

176

214
Model C

298

654

574

654

hv

-0.0003(0.0004)

0.0012(0.0007)-0.0005(0.0009)

0.000(0.042)0.052 *** 0.052(0.016)(0.045)-0.071(0.058)0.071 **
(0.032)0.003(0.038)cd

0.0012(0.0015)0.0001(0.0024)0.0020(0.0017)

0.022(0.092)

0.334 *
(0.176)0.232 **
(0.109)0.005(0.076)0.168 **
(0.082)0.256 **
(0.103)hv*cd

0.00001 ** -0.00001(0.0000)(0.0000)

0.00000(0.0000)

0.001(0.000)0.000(0.000)0.000(0.000)0.101 *
(0.052)-0.050(0.040)-0.099 **(0.049)hv* fhead

0.0008 *(0.0004)-0.0010(0.0007)-0.0010(0.0008)0.251 **
(0.104)0.171(0.130)0.144 ***
(0.039)0.144(0.100)-0.030(0.115)-0.141(0.121)

cd*fhead

0.0011(0.0017)0.0015(0.0018)0.0004(0.0017)0.057(0.125)-0.007(0.230)-0.065(0.075)0.001 **
(0.001)0.000(0.000)0.000(0.000)hv*cd*fhead-0.00003 *** -0.00001(0.0000)(0.0000)

0.00005 ***(0.0000)-0.003(0.004)-0.007(0.007)-0.002 **(0.001)-0.003(0.002)-0.001(0.002)0.004 ***
(0.001)

No. obs.

fhead

0.075
(0.085)0.137(0.090)0.032(0.088)-1.146(3.065)-1.325(2.507)-7.081 **(3.543)2.123(3.747)6.918(5.010)-1.752(5.341)

fadlt-0.027(0.035)-0.023(0.037)-0.007(0.035)1.734(1.083)

1.845 *
(1.048)0.069(0.898)-0.939(1.591)0.445(2.053)-0.846(2.285)madlt

0.085 ***
0.070 **
(0.032)(0.030)0.081 ***
(0.030)-1.160(0.857)0.797(0.598)-0.803(0.741)2.249 **
(1.145)2.857 *
(1.544)

3.639 **
(1.680)F/Chi sq. (p-value)

0.000

0.000

0.000

0.000

0.000

0.398

0.022

0.000

No. obs.

0.000

378
378
378
112
140
190
414
378
414
*10% significance, **5% significance, ***1% significance.
Note - Robust standard errors are in parentheses. Other control variables which are not shown here are d_hv*fadlt , d_hv*madlt (modelB), hv*fadlt , hv*madlt (model C), cd*fadlt , cd*madlt , no. children, age of household head, education of household head, land per
capita, fishing capital per capita, mean age of female adults, highest education of female adults, time dummy, village dummies, villagetime dummies, and constant.