Weather risk, wages in kind, and the off-farm labor supply of agricultural households in a developing country.

This article investigates the effects of weather risk on the off-farm labor supply of agricultural households in a developing country. In low-income developing countries like India, markets for agricultural inputs and outputs are well developed, while the development of credit and insurance markets has been lagging behind (Townsend 1994; Kochar 1997a, 1997b). This means that people in general, and particularly poor farmers, have few means to hedge against the vagaries of production and price shocks that may put their livelihood at risk (Fafchamps 2003; Dercon 2005). It has long been argued that poor farmers in developing countries attempt to reduce their exposure to risk by growing their own necessities (Finkelshtain and Chalfant 1991; Fafchamps 1992; Kurosaki and Fafchamps 2002), diversifying their activities (Walker and Ryan 1990; Kurosaki 1995), adopting risk-reducing production inputs/factors (Just and Pope 1979), and through other income smoothing measures. If risk avoidance inhibits gains from specialization and prevents farmers from achieving the output potential they would be capable of, the provision of efficient insurance mechanisms becomes highly important in poverty reduction policies.

As an example of such inefficiency due to risk avoidance, we focus on the labor supply of farmers in developing countries. In the development literature, the relationship between risk and labor market participation has been analyzed by several authors. For example, Kochar (1999) and Cameron and Worswick (2003) examined the role of labor market participation as an ex post risk-coping mechanism for households hit by idiosyncratic shocks, such as injury or plot-level crop failure. The two studies showed that additional wage income was critically important for shock-hit households in India (Kochar 1999) and in Indonesia (Cameron and Worswick 2003) to maintain consumption levels. Rose (2001) focused on the role of labor market participation both as an ex ante and an ex post response to covariate shocks. She showed that households facing a greater risk in terms of the reliability of rainfall were more likely to participate in the labor market (ex ante response). Moreover, unexpectedly bad weather and low rainfall also increased labor market participation (ex post response). Finally, Townsend (1994) showed that Indian villagers found it more difficult to insure against covariate risk than against idiosyncratic risk.

Taking these findings as our point of departure, we argue that, in low-income developing countries, it is important to distinguish different types of off-farm labor markets: agriculture and nonagriculture on the one hand, and wages paid in cash and wages paid in kind on the other. This article shows that the distinction matters in determining the off-farm labor supply of farmers in a developing country. The evidence shown in this article contributes to the existing literature on risk-poverty linkages in three ways.

First, the quantitative evidence on locally covariate shocks on household behavior is still very scarce for developing countries in general. The classic paper on households' risk coping in India (Townsend 1994) suggested the difficulty to cope with locally covariate shocks, but its main analysis was focused on the extent to which idiosyncratic shocks affect the welfare of the poor. The impact of locally covariate shocks on household welfare has been discussed often in the Sub-Sahara African context (e.g., Fafchamps 2003), where the land-man endowment ratio is more favorable and rural markets are more segregated due to large transportation costs than in South Asia. Considering the concentration of the poor in South Asia, the quantitative evidence in this article is important in understanding risk-poverty linkages in developing countries. Rose's (2001) analysis for India simply considered a single labor market outside the farm, without considering the possible heterogeneity of off-farm labor returns. This article explicitly focuses on the difference between the covariance between farming returns and agricultural wages on the one hand, and the covariance between farming returns and nonagricultural wages on the other. When an area is hit by bad weather, not only may this lead to a decline in a farmer's own farm income, but also may reduce the demand for agricultural labor outside the farm, resulting in a high covariance between own-farm returns and wages available from agricultural work. In contrast, wages outside agriculture are likely to be less correlated with own-farm returns because they are less likely to be affected by the same kind of shocks. This line of reasoning suggests that agricultural households would find it more attractive to engage in nonagricultural work as a means of ex ante risk diversification.

The second point that distinguishes this article from the existing studies is our focus on in-kind wages (1) and our attempt to understand them based on explicit modeling of farmers' optimization under food price risk. In the literature on farmers' production choice, Finkelshtain and Chalfant (1991) and Fafchamps (1992) showed the theoretical possibility that farmers' crop choices are affected by the covariance between farm revenue and food prices, because growing crops whose returns are risky but positively correlated with food prices is advantageous to food-insecure farmers. Kurosaki and Fafchamps (2002) show that this effect is empirically significant in explaining poor farmers' cropping choice in Pakistan. Adjustments in production choices are not the only way to improve food security, however. Another possibility to achieve food security is through off-farm labor markets. For farmers for whom food security is an issue, agricultural work may be more attractive than nonagricultural work if agricultural wages are paid in kind, because the monetary value of wages paid in paddy (the staple crop) is positively correlated with the paddy price. This line of reasoning suggests that food-insecure farm households would find it more attractive to engage in agricultural work paid in kind as a means of improving food security. Despite the importance of in-kind wages in developing countries, especially during the early stage of development, this aspect has been neglected in the literature. This article explicitly models this aspect, thereby providing a new insight to understand the functioning of rural labor markets.

Third, the empirical evidence of this article focuses on the impact of weather risk, which is closely related with an emerging literature on weather index insurance in developing countries. (2) In the existing literature on weather index insurance, the level of potential insurance demand has been analyzed extensively, but mostly based on a reduced-form approach. This article shows one mechanism of the risk-poverty linkages underlying such insurance demand. The econometric results show that distinguishing off-farm sectors into agricultural wage work paid in cash, agricultural wage work paid in kind, and nonagricultural wage work is important, suggesting that demand for weather index insurance may also vary depending on the characteristics of off-farm labor markets.

The remainder of the article is organized as follows. In the next section, we present a theoretical model to explain how farmers decide to allocate their labor, incorporating considerations of food security. We test the predictions of the model using household data from two Indian states, Bihar and Uttar Pradesh. The data set is described in the third section, while the regression results of a multivariate two-limit tobit model of labor allocation are presented in the fourth section. The results robustly show that the share of the off-farm labor supply increases with weather risk, the increase is much larger in the case of nonagricultural work than in the case of agricultural wage work, and the increase is much larger in the case of agricultural wages paid in kind than in the cash wage case. The fifth section shows simulation results based on the regression estimates in order to examine whether the sectoral difference is economically significant. The last section concludes the article.

A Theoretical Model of Labor Allocation

In this section, we present a theoretical model to guide our empirical analysis of labor supply shares to different activities. Throughout the section, we assume a unitary decision-making process at the household level with respect to labor allocation (Singh, Squire, and Strauss 1986). (3) To stylize the conditions of low-income developing countries, we assume that there are only three consumption goods: "leisure," which is defined as the residual after subtracting labor supply from the time endowment; "food," which is the main output in production and an important item in consumption; and "nonfood," whose price is normalized at one. The food price is p (=[[theta].sub.p][bar.p]), where [[theta].sub.p] is the multiplicative price risk with a mean of one.

Time is divided into discrete intervals during which decisions are made and exogenous price and output shocks are realized. The timing of shocks and decisions is as follows. In period 1, the household decides on labor supply, enjoying leisure. After period 1, the household observes the realized prices and labor returns. Depending on the realization, the value of consumption expenditure y is determined. In period 2, the household allocates y into "food" and "nonfood," enjoying consumption of the two goods.

Letting L denote the total labor supply, u(L) denote the disutility from work in period 1 (u'(L) < O, u"(L) < 0, which implies that the marginal disutility of labor increases with more labor), and v(y, p) denote the indirect utility function derived from the second-period optimization. We assume that the welfare of the household at the time of labor decision making (4) is measured by u(L) + E[v(y, p)], where E[x] is an expectation operator. We assume the following properties for v(y, p):

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