中国农村家户的收入动态

PS 2 706 POLICY RESEARCH WORKING PAPER 2706 Household Income Is effective social protection an investment with long-term Dynamics in Rural China benefits? Does inequality impede growth? Household panel data on incomes in Jyotsna Jalan rural China offer some Martin Ravallion answers. The World Bank Development Research Group Poverty Team November 2001  POLic)' RESEARCH WORKING PAPER 2706 Summary findings Theoretical work has shown that nonlinear dynamics in nonlinearity in the income and expenditure dynvmaics, household incomes can yield poverty traps and there is no sign of a dynamic poverty trap. distribution-dependent growth. If this is true, the The authors argue that existing private and sacial potential implications for policy are dramatic: effective arrangements in this setting protect vulnerable social protection from transient poverty would be an households from the risk of destitution. Howvem e r, their investment with lasting benefits, and pro-poor findings imply that the speed of recovery from an income redistribution would promote aggregate economic shock is appreciably slower for the poor than for others. growth. They also find that current inequality reduces fLiture Jalan and Ravallion test for nonlinearity in the growth in mean incomes, though the "growth (ost" of dynamics of household incomes and expenditures using inequality appears to be small. The maximum panel data for 6,000 households over six years in rural contribution of inequality is estimated to be 4-7 percent southwest China. While they find evidence of of mean income and 2 percent of mean consumption. This paper-a product of the Poverty Team, Development Research Group-is part of a larger effort in the grou p to better understand the dynamic processes influencing household welfare in risk-prone environments. Copies of the paper are available free from the World Bank, 1818 H StreetNW, Washington, DC 20433. Please contact Catalina Cunaran, room MC3-542, telephone 202-473-2301, fax 202-522-1151, email address ccunananteworldbank.org. Policy Research Working Papers are also posted on the Web at http://econ.worldbank.org. The authors may be contacted at jialan(aworldbank.org or mravallion@worldbank.org. November 2001. (28 pages) The Policy Research Working Paper Series disseminates the findings of work in progress to encourage the exchange of ideas a )ut development issues. An objective of the series is to get the findings out quickly, even if the presentations are less than fully polished. khe papers carry the names of the authors and should he cited accordingly. The findings, interpretations, and conclusions expressed in ihis paper are entirely those of the authors. They do not necessarily represent the view of the World Bank, its Executitve Directors, oi the countries they represent. Produced by the Policy Research Dissemination Center  Household Income Dynamics in Rural China Jyotsna Jalan and Martin Ravallion' Indian Statistical Institute and the World Bank I The research reported here would not have been possible without the help of the Rural Household Survey Team of China's National Bureau of Statistics and our colleague Shaohua Chen at the World Bank. Our thanks also go to the World Institute for Development Economics Research (WIDER) and the World Bank for their support of this research and to Stefan Dercon, Marcel Fafchamps and participants at a WIDER conference for their comments.   1. Introduction It is widely believed that a publicly provided safety net - based on transfer payments to those deemed to be currently poor - can provide an important short-term palliative in the presence of uninsured risk. However, a body of recent theoretical work has suggested that safety net policies may well serve a deeper role in alleviating poverty in the longer term. This new perspective stems from the realization that widespread credit and risk-market failures can entail efficiency enhancing functions for a well-designed safety net. With limited access to credit, or other forms of (formal or informal) insurance, a household will suffer from a transient shock - an unexpected but short-lived drop in income. However, it is also possible in theory that such a shock can cause a previously non-poor family to become poor indefinitely; or cause a moderately poor family to fall into persistent destitution. If this theoretical possibility is borne out by the evidence then there are important implications for knowledge about poverty and anti-poverty policies. Lack of a well-functioning safety net might well be a structural cause of persistent poverty. And there will be large long-term benefits from institutions and policies that protect people from transient shocks. The long-run effect of a transient shock depends on properties of household income dynamics. And they are properties which we currently know very little about. Granted, if household incomes follow the simplest type of linear auto-regression then a household that experiences a transient shock will see its income bounce back in due course. The serial dependence will mean that the family stays poor for a longer period than the duration of the shock. Incomes will not adjust instantaneously. Nonetheless, the household will recover from any draw from a distribution of serially independent income shocks. However, there is no theoretical reason why incomes would behave this way. Linear dynamics is an ad hoc 2  assumption. Indeed, economic theory has pointed to the possibilities for poverty traps arising from multiple equilibria in the dynamics such that destitution can arise from short-lived shocks. This is not a new idea. Nonlinear dynamic models with multiple equilibria have been widely used in explaining why seemingly similar aggregate shocks can have dissimilar outcomes.2 A central feature of these models is the existence of a nonconvexity in the dynamics of househo ld incomes, giving rise to a low-level unstable equilibrium. The nonconvexity can stem from effrcts of past consumption on current productivity, as in the Efficiency Wage Hypothesis (Mirrlees, 1975; Stiglitz, 1976). In such models, a vulnerable household may never recover from a sufficiently large but short-lived shock. Whether such nonconvexities in the dynamics are important in practice, and constitute a new case for safety net interventions, is a moot point. If multiple equilibria existed then there will be high social returns to arrangements that protect vulnerable households - arrangements that might well be implementable by private means, such as through repeated interaction in risky environments (Coate and Ravallion, 1993). It can be conjectured that institutions will develor that assure - possibly imperfectly and at non-negligible cost - that most incomes exceed the low-level unstable equilibrium, thus avoiding the dynamic poverty trap. Even without poverty traps, it is known that credit market failures can generate nonlinear dynamics whereby the rate of growth in an economy depends critically on the initial distribution of income or wealth (Benabou, 1996; Aghion and Bolton, 1997; Aghion et al., 1999). By implication, as long as redistributive policies do not unduly jeopardize other determinants of growth, they can enhance long-term prospects of escaping poverty. The arguments that initial 2 In macroeconomics, examples can be found in models of the business cycle (Chang and Smyta, 1971; Varian, 1979) and certain growth models (Day, 1992; Azariades, 1996). Similar ideas have been employed in modeling micro poverty traps (Dasgupta and Ray, 1986; Banerjee and Newman, 1994; Dasgupta, 1997) and in understanding famines (Carraro, 1996; Ravallion, 1997). 3  distribution matters to future growth also rest on a type of nonlinearity in the dynamics, such that individual income is a concave function of its own lagged value, i.e., a concave recursion diagram. While there is some supportive evidence from cross-country regressions, this is arguably a rather weak basis for testing, given the known problems encountered, such as the potential for spurious correlations between growth and inequality arising from inconsistent aggregation across the underlying microeconomic relationships (Ravallion, 1998) This paper tests for nonlinearity in income and expenditure dynamics in rural China. The setting for our empirical work is rural southwest China in the period 1985-90. With Deng's reforms starting in the late 1 970s, the collective mode of agricultural production had been disbanded in favor of a household-based responsibility system. These reforms brought rapid growth in rural incomes - initially in agriculture, but in due course helping foster non-farm rural development. But it is likely that greater self-reliance that came with the break up of the collectives, and more heavy reliance on markets, also left many households facing greater risk. We analyze a household-level panel data set spanning six years, 1985-90, in four contiguous provinces, Guangdong, Guangxi, Guizhou and Yunnan. From past research (reviewed later) we know that poor farm-households in this setting are exposed to uninsured incomes and health risks. However, identifying the long-term effects of measured risks is clearly difficult. Six years is not long enough to confidently distinguish a slow process of adjustment after a shock - such that a unique long-run equilibrium is restored - from a more complex dynamic process with multiple equilibria arising from a non-convexity at low incomes. We adopt a different approach that is feasible with the data. Instead of attempting to trace the long-run impacts of measured shocks, we directly study the process of income dynamics to see if it is consistent with the type of nonlinearity postulated in the aforementioned 4  theoretical work. With repeated shocks we are presumably observing most households out (if their steady-state equilibrium. The time series for each household can then reveal the dynamics of adjustment out of equilibrium. At any given long-run equilbrium, some households will simply be returning to that equilbrium. However, if there is also a low-level unstable equilibrium and sufficiently large uninsured shocks, then we should find both rising and falling incomes amongst the currently poor, with a tendency for incomes to fall amongst the poorest. To make this test feasible with only six years of data, the adjustment process is assumed to be common across households (though allowing for household-specific long-run equilibria). The specification allows the possibility of a low-level unstable equilibrium. In the process, we also see if the recursion diagram is concave, such that current distribution matters to future growth. Our estimation method allows for measurement error in observed incomes and other sources of correlation between lagged incomes and the error term.3 The following section describes the setting for our study. Section 3 puts the present paper in the context of our other recent work on the same data set. Section 4 reviews the arguments as to why we might expect to find nonlinear dynamics. We then turn to our econometric model (section 5), and results (section 6). Conclusions can be found in section 7. 2. The setting and data The household panel used in this study was constructed from China's Rural Household Surveys (RHS) conducted by the National Bureau of Statistics (NBS) since 1984.4 The data set 3 In a linear ARI model, under (over) estimating the lagged income would lead to over (under) estimation of the subsequent change in income - a source of bias in OLS estimates of dynamic models commonly known as "Galton's fallacy". The problem is more complicated in a nonlinear dynamic model, but the general concern with measurement error in lagged incomes remains. 4 Further details on this survey, and the way it has been processed for this study, can be found in Chen and Ravallion (1996). 5  covers four contiguous southern provinces over the period, 1985-90. Three of the four provinces (Guangxi, Yunnan and Guizhou) constitute one of China's poorest regions, while the fourth is the prosperous coastal province of Guangdong (Chen and Ravallion, 1996). The original panel consists of over 6,000 households observed over the period 1985-90 (after which the sample was rotated). The RHS is a good quality budget and income survey, notable in the care that goes into reducing both sampling and non-sampling errors (Chen and Ravallion, 1996). Sampled households maintain a daily record on all transactions, as well as log books on production. Local interviewing assistants (resident in the sampled village, or another village nearby) visit each sampled household at roughly two weekly intervals. Inconsistencies found at the local NBS office are checked with the respondents. The sample frame of the RHS is all registered agricultural households except those who have moved to cities. Our measure of consumption expenditure based on the RHS includes spending (either in cash or the imputed values of in-kind spending) on food, clothing, housing, fuel, culture and recreation, books, newspapers and magazines, medicines and non-commodity expenditures like transportation and communication, repairs etc. The income variable includes both cash and imputed values for in-kind income from various sources (farm-household production, forestry, animal husbandry, handicrafts, gifts) as well as labor earnings and income received as a gift. Our income variable does not include borrowings from (or loans to) informal and/or formal sources. There was very little sample rotation in the RHS between 1985 and 1990. The panel was formed from the sequence of cross-sectional surveys. From discussions with RHS staff we decided that the identifiers in the data could not be trusted for forming the panel. Fortunately, 6  virtually ideal matching variables were available in the financial records, which gave both beginning and end of year balances. Relatively stringent criteria were used in defining a panel household, with extensive cross-checks to assure that the same household was being tracked over time. The relatively few ties by these criteria could easily be broken using demographic data. About one third of the original sample could not be matched by our criteria. Some of this is attrition, but probably the main reason was that the household changed sufficiently for it not to be classified as a panel household by our criteria. In studying nonlinear income dynamics using panel data, there is a concern that attrition may well be endogenous to shocks (Lokshin and Ravallion, 2001); for example, with a sufficient negative shock, a household may become destitute and drop out of the panel. We cannot distinguish such households from those that changed too much to keep in the panel or those who were replaced by the surveyors for some other reason and so were dropped from the panel. However, endogenous attrition may not be a concern in this setting. Sampled households in the RHS are paid to participate, and no doubt this encourages continuing participation by the poor. Furthermore, results from Lokshin and Ravallion (2001) indicate that estimates of the nonlinearity in income dynamics for Russia and Hungary are robust to allowing for endogenous attrition (through a non-zero correlation between the error terms in the attrition model and the dynamic income regression). 3. Risk and poverty in southwest China In past research, we have found considerable vulnerability to both idiosyncratic and (village-level) covariate risks in this setting. In Jalan and Ravallion (1999) we tested for systematic wealth effects on the extent of consumption insurance against income-risk. Motivated by the theory of risk-sharing, our tests entailed estimating the effects of income changes on 7  consumption (with current income treated as endogenous), after controlling for aggregate shocks through interacted village-time dummies. We also tested for insurance against covariate risk at village level. To test for wealth effects, we stratified our sample on the basis of household wealth per capita, and whether or not the household resides in a poor area. The full insurance model was convincingly rejected. The lower a household's wealth, the stronger is the rejection, in that the estimated excess sensitivity parameter on changes in current income (implied by the test equation for consumption changes) is higher for less wealthy households.5 We interpret these results as indicating that, while there are clearly arrangements for consumption insurance in these villages, they work considerably less well for the poor. It is not then surprising that we also find considerable transient poverty in this setting. Year-to-year fluctuations in consumption account for one third of the mean poverty gap (Jalan and Ravallion, 1998). About 40% of the transient poverty is found amongst those who are not poor on average, but almost all of this is for households whose average consumption over time is no more than 50% above the poverty line. A comparison with similar tests for three villages in semi-arid areas of rural India (Chaudhuri and Ravallion, 1994) suggests that there is far more transient poverty in this region of rural China. These findings tell us nothing about the long-term consequences of uninsured risk. We have also studied portfolio and other behavioral responses to idiosyncratic risk using the same China panel (Jalan and Ravallion, 2001). In keeping with past empirical work on precautionary wealth, we extracted a measure of income risk from a first-stage income regression estimated on household panel data and then used this measure of risk as a regressor in attempting to explain 5 This conclusion was found to be robust to changes in the set of instruments, and to changes in the wealth measure. It holds for both total consumption and food consumption, although the latter is better protected. There is little sign, however, that living in a poor area enhances exposure to risk at a given level of individual wealth. 8  liquid wealth holdings.6 Our results suggest that wealth is held in unproductive liquid forms to protect against idiosyncratic income risk. However, we find that the effect is small; even if all income risk were eliminated, the mean share of wealth held in liquid forms would fall only slightly, from 26.5% to 25.8%. We also find that there is an inverted U relationship between ihe precautionary wealth effect and permanent income, such that neither the poorest quintile nor the richest appear to hold liquid wealth because of income risk; it is the middle income groups that do so. We suspect that the rich do not need to hold precautionary liquid wealth, and the poor cannot afford to do so. We have found some evidence that liquid wealth is also held as a precaution against risk to foodgrain yields (independently of income risk). We found no clear signs of a precautionary response to health risk, though our measure (based on medical spending) is far from ideal (Jalan and Ravallion, 2001). Schooling and (hence) future incomes appear to be protected from both income and health risk. However, greater uncertainty about incomes at home does appear to constrain the temporary out migration of family labor. In the following analysis we turn to yet another possible longer-term implication of risk, such that vulnerable households can never escape from the adverse impact of a short-lived (serially independent) but sufficiently large uninsured shock. We next discuss how this might come about in theory. 4. Theoretical models with nonlinear dynamics Probably the simplest model that can generate a dynamic poverty trap assumes that a family cannot borrow or save and derives income solely from labor earnings, but with a nonconvexity at low earnings arising from a dependency of the worker's productivity and 6 We extended past methods by allowing for serial dependence in income shocks and by using quantile regression methods that are more robust to the evident non-normality in the data on liquid wealth holdings (Jalan and Ravallion, 2001). 9  (hence) wage rate on consumption. (We discuss alternative interpretations of this nonconvexity below.) Nonlinear dynamics can be introduced by simply assuming that the wage rate in any period is contracted at the beginning of the period. Finally we assume that this dynamic process of income determination has at least one stable equilibrium. Combining these assumptions, the process generating the current income of household i (y, 2 0 ) with exogenous characteristics xi, can be written as the nonlinear difference equation: Yi, = f (Yi,- ], xid (1 ) where f is continuous and vanishing for all y<yo (>0) and the function is increasing and concave in Yit-I for all y>yo. (The control variables xit are of a sufficient dimension that the functionf is the same across all i.) An equilibrium of this model is a steady-state solution that varies with xit such that y = f(y, xi,) . It is evident that if there is more than one such solution then there will be an unstable equilibrium. The recursion diagram in Figure I illustrates a case of multiple equilibria. There are two attractors, at 0 and yT (>yo), and y* is an unstable equilibrium. Consider a household at y . With any shock exceeding y - y ** , the household will be driven beyond the unstable equilibrium, and will then see its income decline steadily towards zero. Destitution will be the inevitable result. One can propose more complicated models. For example, one can allow for some positive lower bound to incomes. Assuming that this lower bound is below y in Figure I there will be a stable equilibrium at the lower bound. Again, with a large negative shock, a household at its high (stable) income will see its income decline until it reaches the lower bound. There are several possible interpretations of the nonconvexity. One is the Efficiency Wage Hypothesis (Mirrlees, 1975; Stiglitz, 1976; Dasgupta and Ray, 1986; Dasgupta, 1993). 10  This assumes that labor productivity and earnings are zero at a low but positive level of consumption; only if consumption rises above some critical level, yo>0, will the worker be productive. In the efficiency wage literature, yo is usually interpreted as the nutritional requirements for a basal metabolism, which account for about two-thirds of normal nutritional requirements (Dasgupta, 1993). There are other interpretations. One can assume that a minimum expenditure level is necessary to participate in society, including getting a job. The expenditure is required for housing and adequate clothing. Thus one can say that consuming below this point creates "social exclusion." Higher consumption permits social inclusion, but there are presumably diminishing income returns to this effect. For example, earnings rise but at a declining rate until after some point the productivity effect of consumption vanishes. Alternatively, we can think of a liquidity-constrained household that faces the choice of investing in (physical or human) capital accumulation or consuming all income in a given period. Suppose that the household is only willing to forgo current consumption in order to invest if its income exceeds a critical level yo. The investment yields an income at time t off (yt-) where this function has the same properties as above. Nonlinearity in the dynamics also has implications for the growth rate of mean household income. Mean current income is: n y' = If (yi,- ],xi,)/n (2) i=1 If the functionf is nonlinear in yi, l then initial distribution will matter to future income at given current income. Iff is strictly concave in yit-l then the mean current income will be a strictly quasi-concave function of the levels of income in the previous period. By the properties of concave functions, higher initial inequality will entail lower future mean income for any given 11  initial mean, holding x,t constant for all i. Recent theoretical papers have shown how concavity of the recursion diagram for income or wealth can arise from credit market failures, given decreasing returns to own capital (Benabou, 1996; Aghion and Bolton, 1997; Aghion et al., 1999; Banerjeee and Duflo, 2000). This type of model has a powerful policy implication. A transfer payment not less than y will eliminate the low-income unstable equilibrium. The family will be fully protected from the possibility of a transient shock having an adverse long-term effect. Not only will the transfer help protect current living standards, but it will also generate a stream of future income gains. An effective safety net will then be a long-term investment, and with a potentially high return. 5. Econometric model We now look for evidence in our data of the type of nonlinear dynamics discussed above. We introduce the nonlinearity in the form of a cubic function of the lagged dependent variable in a panel data model. (Lokshin and Ravallion, 2001, further discuss this specification choice.) Another point to note is that we allow for only first-order autoregression in our model. This is done primarily to estimate a parsimonious model given that we have a very short time-series for each household. We also allow for an independent time trend. Thus our general econometric specification for i at date t is of the form: Yit = a + St +