Christopher J Gerry
email: c.gerry@ucl.ac.uk

Carmen A Li

Consumption Smoothing and Vulnerability in Russia

Keywords: vulnerability, Russia, safety net, quantile regression, consumption smoothing

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Introduction

The increased availability of longitudinal data at the household level alongside advances in econometric techniques has spurred interest in the dynamics of income and consumption in the context of theoretical models of household behaviour under risk.

Much of this interest has been focused on developing countries and the emerging consensus, that those suffering from low absolute levels of well being also suffer from welfare fluctuations, has produced a concentration of research seeking to understand the concept of economic 'vulnerability' (see [START_REF] Kamanou | Measuring Vulnerability to Poverty[END_REF], [START_REF] Kochar | Explaining household vulnerability to idiosyncratic shocks[END_REF], Ravallion andChaudhuri (1997), Townsend (1994)). In this paper, in applying quantile regression techniques to longitudinal data from a transition economy (Russia), we investigate how shocks to income are transferred into changes in consumption and how the ability and means to smooth consumption differs across households and across the consumption change distribution.

The 1998 Russian financial crisis culminated in the virtual collapse of the commercial banking sector, a 400% devaluation of the exchange rate, a rapid surge in inflation, rising unemployment, declining household incomes and a sharp drop in the value of real wages. In this context, prospects for Russia's beleaguered households looked bleak. Yet, within months, developments deviated from the worst-case scenario to such an extent that 1999 witnessed a 5.4% GDP growth rate and the years subsequent have all produced growth in excess of 4%. Looking beneath this macroeconomic data, suggestive of a deep, though short-lived crisis, we discover a diversity of microeconomic experiences and a range of important policy lessons. Moreover, while [START_REF] Gaidar | Joined at the hip: Economics and Politics in Russia's Transition[END_REF] argues, a dramatic change in world commodity prices alongside a relaxing of economic policy could quite plausibly see the return of major economic instability in Russia.

Individuals and households experience and react to economic shocks in diverse ways. To the individual the shock may take the form of job loss, a decline in real wages, the accumulation of wage arrears, being sent on enforced unpaid leave or experiencing asset depreciation. The particular responses that these shocks evoke will depend partially on the transmission mechanism through which the shock is experienced and partially on the range of institutions, networks and personal resources available to the individual to smooth the potential welfare loss. In Russia these resources include, formal systems of state support (e.g. pensions, social security etc), formal and informal engagement with the labour market, as well as in informal 'coping' mechanisms either rooted in Soviet tradition (e.g. home production) or emerging spontaneously in response to the economic environment (e.g. borrowing capital).

The particular response garnered is determined by the set of resources available to the individual and their household and this in turn varies in concert with the economic cycle. Table 1 provides an overview of the composition of household income marking out the relative importance of different income sources. In so doing it is suggestive of both how Russians are likely to experience shocks (changes in labour market or benefit income) and of how they are going to seek to cope (benefits, relatives and home F o r P e e r R e v i e w 4 production). Interestingly, even following 6 years of continued income growth, 'home production' in Russia still accounts for a relatively large proportion of household income, and seems to be a 'coping' institution with significantly more importance than in other middle income countries.

[TABLE 1 HERE]

These preliminary observations prompt a number of questions defining the core focus of this paper. Specifically, how did fluctuating cash incomes translate into household expenditure? In what ways did individuals experience and respond to the fluctuating economic conditions? What are the characteristics associated with those most at risk and those least able to adapt? Do individuals exploit the market economy, the state welfare system or informal support networks to facilitate coping with shocks and in what ways? In addressing these questions we reveal something of the nature of economic vulnerability in Russia during the late 1990's and early 2000's. Understanding economic vulnerability is important, not least because it speaks to many of Russia's most pressing policy concerns, ranging from social security reform and targeting, to regional reform, to human capital formation and the development of labour market institutions, to rural and agricultural reform and to inequality and well being.

There have been a number of studies reporting the extent and incidence of 'low welfare' in transitional Russia 1 , including some relating to the 1998 financial crisis, but few have studied how the Russian population experiences and responds to periods of 1 See for example, [START_REF] Braithwaite | Poverty Reduction and Economic Management and Human Development Networks[END_REF], [START_REF] Ovcharova | Indicators of Poverty in Transitional Russia[END_REF], [START_REF] Falkingham | Measuring Poverty in Russia: a Critical Review[END_REF] and [START_REF] Klugman | Poverty in Russia: Public Policy and Private Responses[END_REF]. [START_REF] Ligon | Welfare impacts of the 1998 financial crisis in Russia and the response of the public safety net[END_REF], examining the welfare effects of the 1998 financial crisis, find that it was not felt only by those poor prior to 1998 but impacted upon individuals across the income distribution. Analysing the effects of changes in the distribution of social welfare spending they find that social policy was "on balance, poverty reducing". They interpret this as evidence of effective welfare targeting. Offering a counter-view, [START_REF] Lokshin | Household Strategies for coping with Shocks in Post-Crisis Russia[END_REF] conclude that the formal social safety net was of little value to most Russians. Skoufias ( 2003) has a different emphasis, finding that, in the face of shocks, households complement standard insurance strategies such as reduction of non-food expenditure, adjustment of labour supply and increased borrowing, with participation in more informal risk sharing arrangements within their local communities. [START_REF] Clarke | Making Ends Meet in Contemporary Russia: Secondary Employment, Subsidiary Agriculture and Social Networks[END_REF] argues that, rather than forming part of an informal insurance strategy, the use of home production is a culturally embedded practice and has no impact on cash spending for urban residents. Manning and Tikhonova (2004), employing a sociological approach, investigate the notion of social exclusion in Russia around the time of the financial crisis. They identify both key individual household characteristics that 'predetermine' the response of the household and the importance of informal networks in attenuating social exclusion.

We draw on and extend this developing literature in a number of ways. As in Skoufias (2003), we analyse observed changes in consumption (our proxy for welfare) but focus explicitly on a time period characterised by enormous macroeconomic turbulence -namely, the 1998 financial crisis and subsequent period of rapid recovery. The way different individuals experience and react in periods such as this is an important policy question so we provide the first comparison for Russia of the effects of and responses to income fluctuations across the conditional distribution of consumption changes. In this, we apply Quantile Regression Methods (QRM) as proposed by [START_REF] Koenker | Regression Quantiles[END_REF]. Further, as suggested by a growing literature (see [START_REF] Hoddinott | Shocks and their Consequences Across and Within Households in Rural Zimbabwe[END_REF] and references therein), we take as our unit of analysis the individual, rather than the household, enabling us to account for both household and individual characteristics while still controlling for the fact that individuals typically live and share resources within a household structure. We are also more explicit than previous studies in treating observed changes in consumption as a function of the net effect of both the idiosyncratic shocks experienced by individuals as well as the risk management strategies they employ to cope with such shocks. This contrasts with Skoufias (2003) who concentrates on the likelihood of using various coping strategies rather than the explicit contribution they make to consumption smoothing. Unlike previous studies our measure of consumption excludes any imputed cash value attributed to home production thus allowing us to compare our results pertaining to home production with those of [START_REF] Clarke | Making Ends Meet in Contemporary Russia: Secondary Employment, Subsidiary Agriculture and Social Networks[END_REF]. That is, we are concerned with the ability of Russian households to smooth fluctuations in their cash spending.

Applying bootstrapped quantile regression to data from the Russian Longitudinal Monitoring Survey (RLMS) we examine the channels through which individuals experience and seek to cope with changes in income. In so doing we reveal something of the nature of economic vulnerability in contemporary Russia. In terms of characteristics 7 that ease vulnerability, we find that married individuals living in small households, with educated heads, in urban areas are better equipped to smooth consumption. We then investigate the impact and role of idiosyncratic shocks and coping strategies as they pertain to (i) the labour market, (ii) the formal social safety net and (iii) informal support networks. We find that the labour market is an important transmission mechanism allowing households to smooth their consumption but also exposing them to risk through job loss, wage arrears and unpaid leave. Outside of pension payments the formal social safety net does not facilitate consumption smoothing, thus heightening the importance of informal coping institutions. It transpires that both support from relatives/friends and home production act as important insurance mechanisms for the most vulnerable. Most notably, the latter is only true for urban households. In contrast with previous findings, it would seem that regardless of its historical, political and social roots, the garden plots and dachas, often romanticized in Russian literature do provide a means by which urban Russians are able to cope with economic fluctuations. We finish by stressing the important policy lessons for Russia's developing market economy.

The paper proceeds as follows. Section two discusses the concept of vulnerability employed and the theoretical model within which our empirical strategy is anchored.

Section three outlines the econometric specification and data. Section four presents our findings and section five concludes the paper.

The concept of vulnerability and the theoretical framework

The recent proliferation of research pertaining to 'economic vulnerability' is suggestive of the complex, multi-dimensional nature of wellbeing. There is no absolute consensus regarding the measurement of vulnerability but conceptually there is agreement that vulnerability refers to a loss of welfare arising from the realisation of a risk and the subsequent unravelling of associated but uncertain consequences or, more simply, the World Bank (2000) defines it as "the likelihood that a shock will result in a decline in well-being". [START_REF] Hoddinott | Methods for Microeconometric Risk and Vulnerability Assessment[END_REF] identify three empirically realisable categories of vulnerability measurement consistent with this concept: a) Vulnerability to expected poverty (an ex ante measure) i.e. a positive probability that a household will fall below the 'poverty line' in some future period.

Chaudhuri et al 2001), [START_REF] Pritchett | Quantifying Vulnerability to Poverty: A Proposed Measure, Applied to Indonesia[END_REF] and [START_REF] Mansuri | Assessing Vulnerability: An Ex ante Measure and its Application using Data from Rural Pakistan[END_REF] all undertake work in this spirit. b) Vulnerability as low expected utility (an ex post measure) with respect to a given benchmark. [START_REF] Ligon | Welfare impacts of the 1998 financial crisis in Russia and the response of the public safety net[END_REF] measure vulnerability as the difference between the utility associated with some certainty-equivalent consumption and the expected utility defined according to realized consumption. c) Vulnerability as uninsured exposure to risk provides an alternative ex post assessment of welfare loss arising from the onset of an economic shock [START_REF] Glewwe | Are some groups more vulnerable to Macroeconomic shocks than others? Hypothesis tests based on panel data from Peru[END_REF], [START_REF] Maloney | The Distribution of Income Shocks during Crises: An application of Quantile Analysis to Mexico[END_REF] and [START_REF] Ligon | Welfare impacts of the 1998 financial crisis in Russia and the response of the public safety net[END_REF] all offer analysis using this approach). In this paper we utilise the latter empirical category centring on the observed effects of uninsured risk exposure or the inability to effectively manage risk when subjected to shocks. Risks to economic well being come in many different guises. On the one hand aggregate or covariant shocks, such as earthquakes, harvest failures or the closure of the factory in a single company town, typically affect all households within a community or region. In contrast, the effects of individual or idiosyncratic shocks, such as job loss or illness, are likely confined to a particular individual or household. The distinction however is not clear-cut. [START_REF] Dercon | On managing Income Risk of the Poor[END_REF] argues that, in practice, the majority of shocks experienced by individuals include elements of both aggregate and idiosyncratic shocks.

He goes on to argue that being able to identify the type of shock is an important tool in mitigating the consequences. For example, the pooling of risk within a community can, in principal, insure against idiosyncratic shocks but, faced by community wide shocks or non-insured idiosyncratic shocks, some form of external support is required.

In any event, in our framework, without effective risk management tools, shocks in whatever form, impose a welfare loss to the extent that they are associated with a fall in consumption. That is, individuals are exposed to 'risky' events outside of their direct control but which impact upon their welfare. Faced by these risks, they respond in an effort to limit (attenuate) the negative (positive) effects of the event. As the event unfolds, their ex post position reveals the extent of their vulnerability over a given period. The observed outcomes (e.g. changes in welfare), as a function of the magnitude and nature of both the risks themselves and the responses they elicit, therefore suggest something about an individual's economic vulnerability. Since different individuals are To obtain an estimable form of this concept of vulnerability we take observed consumption as our proxy for welfare, and consider how far individuals are able to smooth consumption. Specifically, individuals unable to smooth their consumption, when faced by the occurrence of shocks, are more vulnerable, regardless of whether the shock is aggregate or idiosyncratic. In this context it proves instructive to briefly review the standard problem of consumption optimisation in a model with complete insurance [START_REF] Deaton | The Analysis of Household Surveys: A Microeconometric Approach to Development Policy[END_REF].

Take a community of households (v), all facing the same uncertainty about the state of the world. Combining to provide an optimal mutual insurance scheme, each household (h) is assigned ex ante an insurance value congruent with their relative wealth and utility. The optimisation problem facing the community reduces to identification of the set of individual household consumption levels that maximises the sum of the socially weighted inter-temporal expected utility per household. Assuming an isoelastic utility function (where O is the relative risk aversion coefficient), it can be shown that, once the state of nature is realised, changes in consumption depend only on net changes in the state of nature

The main empirical prediction of this complete insurance model is that, after controlling for the change in aggregate resources, the growth of per capita household consumption should not be positively influenced by changes in household income flows.

Given moral hazard and imperfect information, it is hardly surprising that the empirical evidence, for Russia (see below) and elsewhere, soundly rejects this extreme hypothesis of complete consumption insurance. This being so, shocks to income may still affect consumption even in the presence of informal and formal risk sharing arrangements.

Placing this framework in the context of the large fluctuations in income experienced in Russia, we are prompted not only to investigate the impact on consumption changes but also to examine the effects of formal and informal coping mechanisms directed at offsetting the negative consequences of falling incomes and at identifying the idiosyncratic shocks through which different individuals may actually experience income shocks. as a household-specific error term picking up changes in the unobservable components of household preferences, most empirical specifications of equation ( 1) take one of the following forms [START_REF] Hoddinott | Methods for Microeconometric Risk and Vulnerability Assessment[END_REF]), differing only in their representation of shocks:

F

hv t hv hv t i v t hv t X i S D i i C + + + + = ) ( ) ( ln (2) or hv t hv hv t v t hv t X y D i i C + + + + = ) ( ln (3)
The assumption underlying equation ( 3) is that changes in household income proxy all the idiosyncratic shocks experienced by the household, so that captures the extent to which such shocks impact upon consumption. In contrast equation ( 2 poses problems in terms of measurement error and endogeneity bias, prompting the use of instruments to proxy for income. However, since the idiosyncratic shocks themselves are the only obvious instruments, the advantage of using ( 3) over (2) becomes less clear.

Moreover, the relationship between income and consumption may reflect the adoption of coping strategies rather than community level pooled insurance. Indeed Skoufias (2003), applying OLS to both specifications for Russian data, found that the coefficient in (3) was positive and statistically significant, and that idiosyncratic shocks negatively affected changes in consumption while positively influencing the likelihood of adopting a coping strategy.

Our strategy, using longitudinal Russian household data from a period incorporating the 1998 financial crisis, is to implement a version of equation ( 2) including both idiosyncratic shocks and household coping strategies. We control for the impact of the regionally variable aggregate shock, through the community-time interaction dummy, but our proxy for the idiosyncratic income shock from equation (3) speaks to our conceptual understanding of vulnerability. That is, since observed welfare outcomes depend on the net effect of shocks experienced plus strategies employed to cope with such shocks, we incorporate both the idiosyncratic shocks themselves and the coping responses that the shocks give rise to and apply QRM to our specification. They offer a more complete view of the effects of the explanatory variables on the location, scale and shape of the distribution of our vulnerability measure. In other words, there is a great deal of churning underlying any average such that findings of zero correlation, at the mean, between two variables are perfectly consistent with strong causal relations elsewhere in the distribution. Since our purpose is to understand the entire distribution of 'vulnerability', a good characterisation of the conditional distribution can be obtained by estimating a set of 'representative' quantiles. Clustering by household id, and therefore enabling the individual to be the unit of analysis 2 , we estimate the 10 th , 25 th , 50 th , 75 th and 90 th quantiles 3 .

Our data is drawn from rounds VII (1996), VIII (1998) 15 these important questions, but our data provides a strong indication that during this period there was a large, significant fall in mean incomes as well as the widespread occurrence of idiosyncratic shocks and changes in the utilisation of formal and informal coping strategies (see table 1) and is therefore well suited to investigating consumption smoothing.

Total consumption expenditure is defined as the sum of cash expenditures on all reported food and drink, expenditures on tobacco, clothing, fuel, services, rent and utilities and other non-food purchases, excluding purchases of durables and luxury goods 4 . To account for the variance in nutritional needs within households we equivalise our consumption measure using the Russian Ministry of Labour equivalence factor of 0.9 for children and 0.63 for pensioners 5 .

Our explanatory variables are defined along two dimensions. They can be 'taste shifter', shock or response variables and they can be individual or household level variables. As individual 'taste shifters' we include controls for age at the start of the period, gender and marital status; at the household level we control for the highest educational achievement of the household head, for the demographic composition of the household, and for the settlement type in which the household resides. To capture the 4 A potential weakness of the RLMS consumption data is that it is based on recall over the previous week or month rather than on records kept. However, not only are the consumption levels consistent over time relative to reported income, but the information is collected at a similar time of year in each round and so, though we add a note of caution in interpreting our results, we see no reason to believe that any data deficiency is non-random 5 We have also tried with other equivalence scales and without equivalising and find little qualitative change in our key results. Our idiosyncratic shocks consist of two qualitative labour market dummy variables for wage arrears or unpaid leave, and for unemployment. These variables assume a value of one where the individual experiences the phenomena in round t, when they didn't in round t-1, and 0 otherwise 6 . Finally, our household level response or 'coping' variables include changes in the value of home production, capital and assets, interhousehold transfers, transfers from charitable organizations and the formal social safety net 7 . In order to better test Clarke's conjecture that increases in home production do not impact upon cash expenditure we create separate variables for home production increases in urban and non-urban areas 8 . Following a similar logic to that motivating inclusion of 'enter into unemployment' as one of the idiosyncratic shocks, we also include an individual level dummy variable -'enter work' -as an idiosyncratic 'coping mechanism' 9 . Table 2 contains definitions and descriptive statistics of the variables used in this study. 6 We make no attempt to measure the level of accumulated wage arrears since the data doesn't identify exactly when the arrears accrued and therefore it is not possible to identify its value in real terms. Instead we combine it with 'unpaid leave' to try and capture informal labour market mechanisms resulting in 'shocks' to income. 7 We additionally ran the estimates with 'initial levels' of the coping variables and find that all results hold. 8 Even in urban and metropolitan areas agricultural production for personal consumption (or sale) has always formed a significant part of the resources of Russian households. See [START_REF] Clarke | Making Ends Meet in Contemporary Russia: Secondary Employment, Subsidiary Agriculture and Social Networks[END_REF], [START_REF] Seeth | Russian Poverty: Muddling through Economic Transition with Garden Plots[END_REF] and [START_REF] Pallot | Geographical Differentiation in Household Plot Production in Rural Russia[END_REF] for a more detailed discussion. 9 In view of the well-documented phenomenon of multiple job holding we experimented with an 'additional job' variable as a coping mechanism but found it not to be significant. We also broke down the 'work' variable into individual occupations and though other results remained robust to this alternative we felt that the story was really one of working or not rather than one of particular occupational affiliation. In addition, our procedure removes the problems associated with individuals changing occupation in response to the economic climate

Results

Prior to presenting our results it is worth briefly reflecting again on the complexity of empirically capturing vulnerability. [START_REF] Hoddinott | Methods for Microeconometric Risk and Vulnerability Assessment[END_REF] discuss potential problems stemming from endeavours to empirically assess vulnerability.

Besides having an operational definition of vulnerability, a related problem is how to classify shocks and their impact across individuals and households. A further problem concerns the endogeneity associated with attempts to identify the drivers of consumption change.

In part, we address the first problem through our use of quantile regression techniques that enable us to examine the full conditional distribution of consumption changes and to identify differences in the vulnerability 'experience' at different parts of the distribution. In order to assess and limit the possibility of endogeneity bias we take a number of precautionary steps 10 . We initially estimate our OLS and quantile regressions based only on the taste shifter variables before adding other explanatory variables in a step-wise manner to explore the impact their inclusion has on the estimated coefficients and standard errors. On no occasion do the qualitative results change in our stepwise addition of coping strategy and idiosyncratic shock variables 11 .

10 Practical estimation and inference methods for instrumental quantile regressions are complex and subject matters of recent research. See for example Chernozhukov and Hansen (2006). 11 For ease of exposition, the results of the regressions are not reported in the paper but available upon request. consumption changes , we find that, as in Skoufias ( 2003), R is positive and significant suggesting rejection of the complete insurance model. We then supplant income change with the combination of idiosyncratic shocks and household coping mechanisms and turn to our estimate of equation ( 2) which we report in table 3.

[TABLE 3 HERE]

The pooled OLS indicates that males, individuals in households with 3 or more children, those entering unemployment or experiencing another labour market shock are more vulnerable to negative consumption changes. On the other hand, being married, having a higher level of education, being in non-rural areas, finding a job and experiencing increases in household pension payments, capital, help from relatives or home production reduces consumption vulnerability. These results are intuitively expected and consistent with those found for other countries (see [START_REF] Glewwe | Are some groups more vulnerable to Macroeconomic shocks than others? Hypothesis tests based on panel data from Peru[END_REF], [START_REF] Mansuri | Assessing Vulnerability: An Ex ante Measure and its Application using Data from Rural Pakistan[END_REF] and [START_REF] Maloney | The Distribution of Income Shocks during Crises: An application of Quantile Analysis to Mexico[END_REF] -human capital, residence in urban areas, access to formal and informal safety nets and the labour market all attenuate vulnerability.

We now turn to the results from applying quantile regression techniques. As expected, the effects of the regressors vary substantively across the consumption change distribution indicating that the traditional OLS method is less informative than the QRM approach used here. In interpreting the tables note that the 10 th (90 th ) quantile refers to the largest decreases (increases) in consumption and that a positive estimated coefficient Looking first at the individual 'taste shifters', there are three findings of note.

First, the changes in sign across the distribution and the marginally significant negative coefficient on age at the 10 th and 50 th quantiles provide some limited evidence that older individuals are more vulnerable toward the lower end of the distribution i.e. among those experiencing negative consumption shocks. The (OLS) observation that males are more vulnerable seems to be driven by an association with consumption increasesindeed, at the 25 th quantile, being male attenuates vulnerability. More concretely, toward the bottom of the distribution being married eases vulnerability, indicating that struggling individuals are able to manage resources more effectively as a family unit in order to stave off the worse effects of economic shocks. This effect is strong at the 10 th and 25 th quantiles, becoming less strong and ultimately of negative sign as we progress through the distribution.

Our household type indicators lend some support to the 'family unit' thesis in revealing interesting differential affects across the consumption change distribution. The presence of children in households has a positive impact on vulnerability among those most affected by consumption falls but the effect is by no means linear. For households with 3 or more children, the impact is negative across the distribution and significantly so at the 50 th quantile. We interpret these results as evidence that larger and younger In terms of human capital, the OLS estimates indicate that households with university-educated heads are less vulnerable in aggregate. The QRM results show that this effect is driven by those individuals able to smooth or marginally increase consumption. A similar finding pertains to 'complete high school' education. That is, there is little evidence that education in contemporary Russia is important for those suffering the biggest falls in consumption. On the contrary, human capital of this sort only proves useful for those experiencing positive shocks. This finding is suggestive of an interesting reinterpretation of the 'Schultz hypothesis' [START_REF] Schultz | Human Capital and Disequilibrium[END_REF]) that more educated households are more adaptable in the face of economic problems. In Russia, it would seem that being endowed with human capital does indeed reduce vulnerability but the effect is not even along the consumption change distribution.

With regard to settlement type indicators, among those experiencing the largest decreases in consumption, being in a non-rural area offers a clear advantage. This indicates that the opportunities on offer for welfare smoothing and thus coping with the severest economic shocks in urban areas are substantially greater than in rural areas. The effect is strongest at the 10 th quantile, reducing progressively across the consumption change distribution. There is strong evidence that individuals entering unemployment pose a significant threat to household wellbeing among the most vulnerable households. That is, even controlling for all the modes of survival available to the household, when an individual enters unemployment s/he is unable to cope with severe shocks to consumption.

Although the 2003 RLMS survey shows that over 10% of workers are still in receipt of arrears, the effect of newly acquired wage arrears and unpaid leave was a significant drawback only at the 75 th quantile although with the anticipated sign at all quantiles.

Notwithstanding this, given how widespread wage arrears were in the 1990's, it is interesting to observe that the occurrence of arrears was bad not only for the individual but also for the household.

We have seen, at least partially, how aggregate shocks are experienced by individuals through their interaction with the labour market, but where do individuals and households turn to in their efforts to maintain their levels of wellbeing? An obvious source of respite in developed economies arrives in the form of state benefits such as unemployment insurance, child benefit and pensions. In Russia, these institutions were and remain somewhat underdeveloped and underfinanced so we may expect that other 'coping mechanisms' -particularly those inherited from the Soviet legacy -transpire to be as or more important.

We find that individuals in receipt of pension increases are less vulnerable across the consumption change distribution except at the 10 th quantile, where the sign remains The story regarding other forms of social security is somewhat different. We find no evidence that other forms of social welfare benefits cushion individuals against declining consumption, though the sign is as we would expect. So, despite being the second largest contributor to household income, changes in social welfare benefits, outside of pension payments, do not appear to be sensitive to changes in consumption. A central target of any welfare system is to act as a buffer against shocks to wellbeing so it is of particular concern that the Russian benefit system seems ill equipped to perform the role of safety net. This provides important food for thought in the context of ongoing social welfare system reforms currently stalling under Vladimir Putin.

With this mixed testimony on the formal state safety net in mind we turn now to less formal coping mechanisms. During this period, the savings and asset-based resources of many Russians were wiped out but those individuals managing to increase their capital and assets are shown to be less vulnerable in general but not significantly so except at the 25 th and 90 th quantiles. In terms of the widely reported informal networks of support the data is mixed. There is no evidence that help from charitable and other non-governmental organizations helps to cushion the blows to welfare imparted by economic shocks although the sign is as expected 13 . It seems likely -as indicated by the small contribution to mean income in this data -that most non-governmental organizations are targeting their support at the homeless and other disadvantaged categories falling outside of the mainstream represented by the RLMS sample. In contrast, the quantile regression results provide evidence that those in receipt of increased support from relatives were less vulnerable at the lower end of the distribution There is powerful evidence stemming from our results concerning the role of home production. [START_REF] Clarke | Making Ends Meet in Contemporary Russia: Secondary Employment, Subsidiary Agriculture and Social Networks[END_REF] argues that, rather than being a specific coping response to economic hardship, the use of home production is predominantly a legacy of the Soviet system. Specifically, Clarke argues that home production had no impact on the money spending on food of urban households. While we do not dispute the relevance of the historical legacy we advance the argument that the practice of home production occurs in a way consistent with the principal of 'coping'. Notably, increasing home production, among urban households facilitates smoothing of cash expenditure across the lower quantiles (10 th , 25 th and 50 th . Comparing this with the interactive term for those in rural areas the same cannot be said since across the lower quantiles the sign is negative, though only significantly so at the 10 th quantile. Aggregating the coefficients, we therefore find that, for the most vulnerable, home production is actually associated with significantly steeper falls in consumption. In other words, home production in Russia offers the more vulnerable urban households a means of coping with shocks and smoothing their consumption expenditure and thus welfare. In contrast, increasing home production in rural areas does not facilitate consumption smoothing and instead would appear to be an outcome foisted on those households experiencing the harshest consumption declines. Finally, it is noteworthy that, just as the labour market acts as the funnel directing aggregate shocks towards the individual, it also provides an outlet through which the individual can contribute to household welfare. Entering work (since the previous round) lowers vulnerability but it is only significant from the 50% quantile onwards.

Concluding Remarks

Using longitudinal data from the RLMS, we apply bootstrapped quantile regression techniques to investigate how shocks to income are transferred into changes in consumption and how the ability and means to smooth consumption differs across households and across the consumption change distribution. In so doing we reveal something of the nature of economic vulnerability in contemporary Russia.

We find that, among the most vulnerable, individuals who are married and live in households with one or two children are better equipped to smooth consumption than small households or those with 3 or more children. In contrast, more traditional measures of human capital show that education is a useful characteristic but not among those at the lower end of the distribution. The latter finding is not inconsistent with [START_REF] Glewwe | Are some groups more vulnerable to Macroeconomic shocks than others? Hypothesis tests based on panel data from Peru[END_REF] for Peru or per se with the 'Schultz hypothesis', that with education comes resourcefulness, but it does flag up the value of the quantile regression approach. Our most interesting and important results derive from our analysis of idiosyncratic shocks and coping strategies along three dimensions: the labour market; the formal social safety net; and informal support networks. Unsurprisingly we find that individuals entering unemployment faced heightened levels of vulnerability among those experiencing the severest consumption shocks even after allowing for household pooling of resources. Interestingly, the occurrence of wage arrears and unpaid leave did not result in the most vulnerable suffering but instead had significant negative impact on consumption growth among the less vulnerable. Equally unsurprisingly, households containing individuals entering the labour market are well equipped to smooth consumption. The value of a well-functioning labour market is paramount.

With social security reform currently stalling in Russia, this is an opportune time to contemplate the role played by the social safety net. On pensions, we find that individuals in receipt of pension increases are less vulnerable across the consumption change distribution except at the 10 th quantile, where the sign remains positive. This is reassuring and perhaps a reminder of the ongoing political power that the pensions lobby maintains in contemporary Russian society. The story regarding other forms of social security is less comforting since we find no suggestion that these forms of social welfare benefit (including childcare allowances, unemployment benefits and disability benefits) cushion individuals against declining consumption. Those in receipt of increased support from relatives were better able to smooth consumption at the lower end of the distribution. Taken together, this provides support for the findings of Manning and Tikhonova (2004) regarding social exclusion.

Specifically, the social resources available to many Russians serve an important role but in the absence of an effective social welfare safety net what becomes of those unable to access social networks.

Of equal importance for many Russians -urban and rural -is their capacity for home production. Most notably, and distinct from earlier findings [START_REF] Clarke | Making Ends Meet in Contemporary Russia: Secondary Employment, Subsidiary Agriculture and Social Networks[END_REF] increasing home production, among urban households, allows the most vulnerable to smooth their cash spending. Regardless of its historical, political and social roots urban Russians do use home production as a resource for coping with economic fluctuations and are likely to continue to do so. In contrast, increasing home production in rural areas does not facilitate consumption smoothing and instead would appear to be the only option available. Perhaps this suggests an important difference between a 'coping' strategy and a 'survival' strategy. Urban Russians use their garden plots as part of the former, while for rural Russians they lie at the heart of the latter. This merits further investigation.

In sum, the welfare of Russian households is affected by the occurrence of economic fluctuations in response to which they are able to protect themselves with varying There are strong arguments for careful targeting and indexing of the social safety net provided by the state so that, as a priority, it provides a basis for offsetting welfare declines rather than propagating welfare increases. Leaving households to rely on home production and the help of relatives as short-term buffers does not represent efficient resource use nor lay the foundations for long-term prosperity. Yet no doubt some of these less formal institutions are reflective of long term path dependencies. Even so, it would appear that the current coping mechanisms provide short-run protection but are a constraint on long-run prospects. Recognising institutional path dependencies and endeavouring to shape incentives is important. As important, if Russia is to halt its population decline, are policies designed to support families -most particularly those with multiple children.

More optimistic lessons derive from the labour market analysis. The labour market is the transmission mechanism through which individuals feel economic shocks but it is also a potential safety net from shocks and a route to increased well being. Efforts to promote job creation and flexible, efficient labour markets should be supported. There is also much talk in Russia about the declining quality of the education system yet it is quite clear that households governed by heads with high levels of human capital are better equipped to prosper. Russia's educational heritage should be fought for. The ability to smooth consumption is important, not only for its immediate buffering effect, but also because it enables individuals and households to pursue longer term strategies that may otherwise be deemed too risky. Currently, Russian's exploit a combination of formal, informal, market and non-market coping strategies but access to these is not strategically targeted or distributed. This paper speaks to the importance of risk influencing policies designed to lower economic vulnerability. Such policies relate to the labour market, the design of social security provision, the banking sector and the private insurance market. .0757* (.0420)

.1158** (.0567) Notes: Each quantile estimate, clustered by family id, includes additional controls for the Primary Sampling Unit (Community), changes in non-pension, social welfare benefits (never significant) and a constant; **/* indicate significance at 5%/1% respectively or significant in bias corrected bootstrap estimates where bias is below 25%; standard errors in parentheses; sample size = 9,125 (full). Omitted categories are: 'Basic education only' and 'Households with working age adults but no children'.

  1998 have seen the implementation of some important economic reforms alongside rapid economic growth, as

  thus little is known of vulnerability in Russia.

  to and manage risk with varying degrees of success, any measure of vulnerability should incorporate the risk itself (idiosyncratic or aggregate), the management of that risk (how individuals respond) as well as the final outcome (change in welfare).

  estimated by minimising the weighted sum of the absolute errors and so are robust to the presence of outliers and non-normal error distributions.

  include a community (primary sampling unit) -time interaction dummy reflecting the downturn between the 1996 and 1998 observations.

  estimate equation (3) to test the covariance of income and (cash)

  offsetting negative consumption changes hence implying that individuals endowed with that characteristic are less vulnerable.

  more adaptable in the face of shocks up to some point, at which children become 'costly'.

  the impact of idiosyncratic shocks and coping responses.

  for the most vulnerable, personal networks are an important form of insurance.

  that for those most in need of support access their welfare insurance through informal institutions. First, personal networks are shown to be important for the most vulnerable.

  . While some prosper, others fail and Russia appears to be faltering in terms of social and economic cohesion. In this context, various policy messages emerge.

  . (2003) 'Consumption Smoothing in Russia: Evidence from the RLMS', The Economics of Transition, Vol.11 (1) pp.67-91 Townsend, R. (1994) Risk and insurance in village India, Econometrica 62(3), pp. 539-91 World Bank (2000) 'World Development Report 2000/2001: Attacking Poverty'. New York: Oxford University Press.

  Needless to say, the timings of data collection for the RLMS do not fit seamlessly with the incidence of the 1998 crisis. In particular, our pre-crisis observation is in late 1996 and our postcrisis observation is in late 1998, arguably before the full effects of the crisis had filtered through the economy. Nevertheless, not only is this the only data with which to address

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and IX (2000)

of the Russian Longitudinal Monitoring Survey (RLMS), a series of nationally representative surveys of the Russian Federation providing comprehensive information on a range of socio-economic and demographic variables. We use an unbalanced panel containing 2,558 households, with observations on 9,125 adults over 18 years of age.

2 See

[START_REF] Bradbury | Conceptual and Measurement Issues[END_REF]

for a discussion regarding the use of the individual or the household as unit of analysis.

3

The standard errors for the quantile regressions are bootstrapped, bias corrected and based on 100 repetitions for data clustered by household.

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Table 1 :

 1 The Russian context

	Variable	1994 1995 1996 1997 1998 1999 2000 2001 2002 2003
	GDP Growth (%)	-12.6	-4.1	-3.6	1.4	-5.3	6.4	10.0	5.1	4.7	7.3
	Unemployment (%)	8.1	9.5	9.7	11.8 13.3 12.6 10.4	8.7	7.9	8.4
	Inflation (%)	308	197	47.7 14.7 27.7 85.7 20.8 21.5 15.8 12.3
	Exchange Rate (%)	3550 4640 5555 5863 21* 24.6 28.2 30.1 31.8 29.4
	Consumption (R)	10.7k 8835 7987	n/a	6063	n/a	6737 7861 8255 8561
	Income (R)	9439 7091 6831	n/a	5401	n/a	6273 7517 8561 9398
	% wage	40.8	42.1 39.1	n/a	36.2	n/a	41.6	46.5	47.6	45.5
	% benefits	28.5	28.9 23.7	n/a	26.7	n/a	27.6	28.9	28.7	28.3
	% relatives help	5.8	5.5	7.8	n/a	7.0	n/a	6.5	6.0	5.9	6.3
	% capital income	2.1	1.6	1.8	n/a	1.7	n/a	1.5	1.1	1.1	1.2
	% home prod.	17.1	15.3 18.0	n/a	21.0	n/a	15.7	9.8	10.3	9.6
	Real wage/hour (R)	29.7	24.5 24.3	n/a	15.7	n/a	18.1	24.7	27.1	26.7
	Wage Arrears (%)	29.6	28.9 44.6	n/a	54.5	n/a	21.3	17.6	15.5	13.6
	Unpaid leave (%)	10.0	5.2	6.4	n/a	6.6	n/a	2.5	2.4	2.4	2.2
	Notes: R = figures from the RLMS data (there was no RLMS data collected in 1997 or1999). All
	non % figures given in real 1992 roubles.

Table 2 :

 2 Definition of variables and descriptive statistics

	Variable	Definition	Mean and standard deviation
	Change in consumption Change in log consumption	-.030 (.932)
		between 1996 and 1998	-.342 (.913)
		between 1998 and 2000	.266 (.850)
		percentage positive	48.9
	Gender	Gender (1 = male; 0 = female)	.408 (.491)
	Married	Married (1 = married; 0 = unmarried)	.629 (.483)
	HH characteristics
	Education of head
	University	University educated head	.080 (.272)
	Tech & Med	Technical/medical education	.094 (.292)
	Complete high	Complete high school	.178 (.383)
	Incomplete high	Incomplete high school with vocational	.057 (.231)
	Base	Incomplete high school maximum	.051 (.221)
	Household type
	House type 1(base) No children, working age household	.294 (.455)
	House type 2	No children, pensioner only household	.191 (.393)
	House type 3	One child household	.300 (.458)
	House type 4	Two child household	.172 (.377)
	House type 5	Three child household	.044 (.204)
	Dwelling
	Urban	Urban settlement dwelling	.647 (.478)
	Rural (base)	Rural settlement dwelling	.306 (.452)
	PGT	Rural non-agricultural dwelling	.068 (.251)
	Aggregate shocks
	Shock	Dummy for change between 96 and 98	.487 (.500)
	Idiosyncratic shocks
	Enter unemployment Unemployment in t but not in t-1	.059 (.236)
	Arrears/Leave	Wage arrears or unpaid leave in t but not in t-1	.073 (.260)
	Coping mechanisms
	; Pension	Change in household log pension since t-1	.683 (2.68)

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			Change in household child plus other social	.100 (2.56)
	; Social		benefits since t-1
	; Capital		Change in household log sum of assets,	-.012 (1.15)
			investments, rents and bonds since t-1
	; Home		Change in household sum of home production	.041 (1.98)
			(livestock and wildfowl sales, plus cash and
			non-cash values of home produced goods)
			consumed and sold (where consumed is valued
			at local prices) since t-1
	; Relatives F o ; Organisation	Change in household cash and in kind support from friends and relatives since t-1 Change in household support from other	-.044 (2.73) -.012 (1.15)
		r organisations since t-1e.g. NGO's, charities etc
	Enterwork	P Individual enters into formal work since t-1	.065 (.247)
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Table 3 :

 3 Aggregate and idiosyncratic shocks, coping responses and the labour market

		OLS	Q10	Q25	Q50	Q75	Q90
	Age	-.0009	-.0018*	-.0010	-.0017*	.0001	.0005
		(.0006)	(.0011)	(.0008)	(.0008)	(.0008)	(.0010)
	Gender	-.0428***	-.0026	.0444*	-.0293*	-.0569**	-.0867**
		(.0162)	(.0282)	(.0202)	(.0184)	(.0208)	(.0326)
	Married	.0401**	.0742*	.0624**	.0137	-.0082	-.0432
		(.0179)	(.0373)	(.0239)	(.0205)	(.0214)	(.0384)
	University	.0636**	.0195	.0136	.0569*	.0568*	.0852
		(.0271)	(.0488)	(.0334)	(.0290)	(.0324)	(.0490)
	Tech & Med	.0385	-.0158	-.0409*	.0333	.0466	.1188
		(.0268)	(.0512)	(.0307)	(.0316)	(.0405)	(.0699)
	Complete high	.0494**	-.0038	-.0420*	.0421*	.0605**	.0857*
		(.0217)	(.0352)	(.0282)	(.0229)	(.0250)	(.0371)
	Incomplete high	.0565	-.0744	-.0566	.0430	.0567	.1019*
		(.0367)	(.0724)	(.0451)	(.0388)	(.0426)	(.0654)
	House type 1	-.0262	-.0583	-.0121	.0132	-.0343	.0010
		(.0324)	(.0768)	(.0466)	(.0404)	(.0441)	(.0696)
	House type 3	.0271	.1265*	.0664	.0227	-.0199	-.0521
		(.0306)	(.0663)	(.0416)	(.0349)	(.0381)	(.0618)
	House type 4	.0096	.1519**	.0987*	.0298	-.0061	-.0972
		(.0354)	(.0730)	(.0500)	(.0432)	(.0496)	(.0695)
	House type 5	-.1577*	-.1883	-.2249	-.2020**	-.1149	-.0916
		(.0829)	(.1329)	(.1486)	(.0936)	(.0859)	(.2026)
	Urban	.1392***	.4957**	.3087**	.1466**	-.0888	-.2105**
		(.0492)	(.1292)	(.0736)	(.0611)	(.0648)	(.1024)
	PGT	.2505***	.2964**	.2596**	.2429**	.2051*	.1080
		(.0662)	(.1166)	(.0884)	(.0778)	(.1067)	(.1468)
	Shock	-.6155***	-.6693**	-.6569**	-.5991**	-.5647**	-.5680**
		(.0335)	(.0572)	(.0401)	(.0370)	(.0377)	(.0550)
	Enter unemployment	-.1054***	-.1275**	-.1446**	-.0652	-.0414	-.0706
		(.0398)	(.0620)	(.0522)	(.0649)	(.0438)	(.0627)
	Arrears/Leave	-.0717**	-.0511	-.0255	-.0635	-.0850**	-.0827
		(.0346)	(.0537)	(.0423)	(.0340)	(.0374)	(.0526)
	; pension	.0228***	.0095	.0123*	.0222**	.0224**	.0257**
		(.0061)	(.0098)	(.0078)	(.0070)	(.0077)	(.0096)
	; social	.0024	-.0095	.0041	.0060	.0029	.0031
		(.0055)	(.0103)	(.0062)	(.0054)	(.0062)	(.0087)
	; capital	.0356***	.0328	.0323*	.0292	.0204	.0578**
		(.0134)	(.0287)	(.0151)	(.0155)	(.0138)	(.0164)
	; home	.0179***	.0188*	.0209**	.0201**	.0109	.0106
		(.0069)	(.0119)	(.0094)	(.0093)	(.0068)	(.0097)
	; rural_home	-.0105	-.0716**	-.0210	-.0018	.0031	.0063
		(.0176)	(.0258)	(.0216)	(.0169)	(.0176)	(.0268)
	; relatives	.0103*	.0149*	.0118*	.0032	.0012	.0096
		(.0055)	(.0086)	(.0065)	(.0059)	(.0071)	(.0080)
	; organisations	.0157	.0056	.0116	.0189	.0152	.0112
		(.0133)	(.0203)	(.0131)	(.0138)	(.0165)	(.0171)
	Enter work	.0893**	.0373	.0466	.0755**
		(.0377)	(.0533)	(.0561)	(.0360)

Editorial Office, Dept of Economics, Warwick University, Coventry CV4 7AL, UK Submitted Manuscript

Editorial Office, Dept of Economics, Warwick University, Coventry CV4 7AL, UK Submitted Manuscript Editorial Office, Dept of Economics, Warwick University, Coventry CV4 7AL, UK Submitted Manuscript Editorial Office, Dept of Economics, Warwick University, Coventry CV4 7AL, UK Submitted Manuscript Editorial Office, Dept of Economics, Warwick University, Coventry CV4 7AL, UK Submitted Manuscript Editorial Office, Dept of Economics, Warwick University, Coventry CV4 7AL, UK Submitted Manuscript Editorial Office, Dept of Economics, Warwick University, Coventry CV4 7AL, UK Submitted Manuscript Editorial Office, Dept of Economics, Warwick University, Coventry CV4 7AL, UK Submitted Manuscript Editorial Office, Dept of Economics, Warwick University, Coventry CV4 7AL, UK Submitted Manuscript Editorial Office, Dept of Economics, Warwick University, Coventry CV4 7AL, UK Submitted Manuscript Editorial Office, Dept of Economics, Warwick University, Coventry CV4 7AL, UK Submitted Manuscript Editorial Office, Dept of Economics, Warwick University, Coventry CV4 7AL, UK Submitted Manuscript Editorial Office, Dept of Economics, Warwick University, Coventry CV4 7AL, UK Submitted Manuscript Editorial Office, Dept of Economics, Warwick University, Coventry CV4 7AL, UK Submitted Manuscript Editorial Office, Dept of Economics, Warwick University, Coventry CV4 7AL, UK Submitted Manuscript Editorial Office, Dept of Economics, Warwick University, Coventry CV4 7AL, UK Submitted Manuscript Editorial Office, Dept of Economics, Warwick University, Coventry CV4 7AL, UK Submitted Manuscript

Editorial Office, Dept of Economics, Warwick University, Coventry CV4 7AL, UK Submitted Manuscript


MSc Christin Bexelius
email: christin.bexelius@ki.se

MD Hanna Merk

MSc Sven Sandin

MD Olof Nyrén

PhD Sharon Kühlmann-Berenzon

MD Annika Linde

MSc Jan-Eric Litton

Interactive Voice Response and web-based questionnaires for population-based infectious disease reporting

Keywords: Influenza, Sentinel surveillance, Internet

à la diffusion de documents scientifiques de niveau recherche, publiés ou non, émanant des établissements d'enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.

Global surveillance of influenza utilizes national systems (1;2) that are typically based on reports from sentinel physicians and/or on data from routine testing at virology laboratories (3;4). Although invaluable components in complete influenza surveillance schemes, particularly in the early identification of outbreaks of new strains, these data collection mechanisms often lack anchorage in the underlying population. Uncertain denominator data and possible selection forces behind health-care consultations limit the interpretability of resulting rates and complicate epidemic forecasting. Moreover, overtaxing of health care during pandemics may severely bias such surveillance data.

Therefore, there is a need to supplement these mechanisms with robust, population-based data collection with short time-delay [START_REF] Morse | Global infectious disease surveillance and health intelligence[END_REF].

The Internet is already an important component in many of the existing surveillance systems as electronic reporting decreases time-delay (3;6).. Along with the Netherlands, the Nordic countries have the world's highest general Internet penetration [START_REF]ITU/UNCTAD 2007 World Information society report: Beyond WSIS. International Telecomunication Union (ITU)[END_REF] and web-based data collection directly from the public is technically feasible in a growing number of countries including Sweden (8;9). But since the Internet is not available to the entire population, supplementary technologies could potentially be used to improve population coverage and response rates. Interactive Voice Response (IVR), available through both landline and mobile telephones, can be used for short questionnaires [START_REF] Corkrey | Interactive voice response: review of studies 1989-2000[END_REF][START_REF] Tourangeau | Self-administrated questions by telephone[END_REF][START_REF] Rodriguez | Evaluating patients' experiences with individual physicians: a randomized trial of mail, internet, and interactive voice response telephone administration of surveys[END_REF]. Availability of telephone-based interviews as a supplement to the web has been shown to boost response rates [START_REF] Greene | Telephone and web: mixed-mode challenge[END_REF].

In this cohort study, randomly selected subjects were asked to immediately report all occurrences of respiratory tract infection during a 36-week period from September 2007 to May 2008. At entry, they were given the option to respond to the invitation via a study-specific web site or via IVR. During the follow-up period with participant-initiated reporting they were allowed to alternate between these two contact modes. This study aims to investigate the degree to which the reporting method per se might influence incoming self-reports by comparing participants who initially chose the web with those who chose to use IVR; of interest were possible socio-demographic selection forces, patterns of switch-over between the contact modes, and proportions reporting infections.

METHOD Subjects and recruitment

A random sample of 14,000 Stockholm county residents, aged 0 to 95 years, was drawn from the continuously updated Swedish population register at Statistics Sweden (www.scb.se). Mailed invitation letters were sent to all selected individuals. For children under the age of 16 years, the parents were contacted as proxy reporters in lieu of the child. Elderly people with impediments that hindered self-reporting could ask a deputy to act as a substitute. Before start of the infectious disease reporting, participants were required to first register by entering their National Registration Numbers (NRNs) at the study web site or via IVR. Either action was considered informed consent. The participants' choices of technology for this initial registration were used to categorize them as belonging to either the web group or the IVR group.

Follow-up

Registered participants were asked to report all new occurrences of respiratory tract infection (influenza-like illness [ILI] or "common cold") during the 36-week followup period. In the event of such an infection they were to contact the study via the website or IVR. Answering a short questionnaire about specified symptoms and time since onset was an integrated part of the reporting. Both the website and the IVR platform presented the same branched set of questions and they were connected to the same database.

Participants were allowed to freely alternate between the two technologies. Infections that started more than seven days prior the report were not taken into account.

We further plotted the age group-specific proportions of participants who submitted at least one report of respiratory tract infection or ILI during the entire influenza season.

Here, the individual was the unit of observation, and the purpose was to demonstrate the impact of one of the participant-specific characteristics (age) that could potentially result in confounding. To assess the putative effects of choice of reporting technology and other measured background factors on the risk of reporting at least one infection, log-binomial regression models were fitted, both for any respiratory tract infection and for ILI. First, crude relative risk (RR) of ever reporting an infection (yes/no) during the follow-up period was calculated for the web group, relative to the IVR group in a univariable analysis. The model was then multivariably adjusted for age group, gender, level of education, household size and family income. As marital status was highly correlated with size of household, marital status variable was not included in the regression models.

For children under the age of 18 socio-economic data on their parents were obtained and used in Table 2 and in the regression models (Tables 3 and4).

The goodness of fit of the models was evaluated by using the model deviance.

Likelihood ratio tests were used to assess the relative importance of the model covariates.

All statistical tests were done on the two-sided 5% level of significance. All analyses were performed with the SAS 9.1.3 statistical software program. The study was reviewed and approved by the Regional Ethics Review Board in Stockholm in 2007.

RESULTS

Response rate

After two reminders, 436 (3%) of the originally invited 14,000 individuals had actively declined participation and 3,341 (24% of total sample) were registered as participants, of whom 1,297 (9% of total sample) registered via IVR and 2,044 (15% of total sample) registered via the web. The remaining 10,223 (73%) did not repond at all.

Socio-demographic distribution

Participants vs. total sample

Distributions of socio-demographic characteristics for the participants and for the total sample are described in Table 1. Women were over-represented among participants (56%), compared to the total sample (51%). There was a shift toward older ages among participants compared with the total sample, and there was a noteworthy underrepresentation of participants in the age group 18-39 (20% versus 30%). Moreover, participants had, on average, a higher level of education, higher household income, somewhat higher representation of two-person household and a lower representation of individuals who had never been married.

Web vs. IVR participants

The distributions of socio-demographic characteristics among web and IVR participants are shown in Table 2. When comparing socio-demographic characteristics between the participants registered via the web and those who registered through IVR, statistically significant differences emerged in regard to age, gender, education, size of household, marital status and family income. Women, older individuals, and individuals with a lower level of education were over-represented in the IVR group, while participants younger than 65 years and those with a higher level of education were overrepresented in the web group. The web also attracted individuals from larger households, individuals with higher family income, and individuals who had never been married. When looking at the transfer between the two technologies, 103 (8% out of 1,297) IVR registered participants reported at least once through the web and 129 (6% out of 2,044) of those who registered through the web reported at least once through IVR, indicating that most participants used the same technology for reports as for initial registration.

Distribution of reports

Figure 1 illustrates, for each of the 36 studied weeks, the rate of positive reports of any respiratory tract infection with an onset within seven days per 100 person-weeks, by contact mode defined in terms of the technology chosen for the initial registration. The corresponding data pertaining to influenza-like illness (ILI) are shown in Figure 2.

Although slightly higher rates of self-reported infections (both respiratory tract infections and ILI) were observed in the web group compared with the IVR category, the rates in the two groups were on the whole remarkably consistent. Both figures demonstrate an obviously artificial peak immediately following the receipt of the postcard reminder that was sent out before Christmas. This peak was particularly conspicuous in the web group.

In stratified analyses, the lower report frequency in the IVR group compared to the web group was confirmed in both men and women. The proportions reporting respiratory tract infections and ILI by 5-year age groups are plotted in Figures 3 and4.

These proportions were generally higher in the younger age groups than in the older, and the lowest proportions were seen in the oldest age group for both technologies.

Crude and adjusted RRs for reporting at least one respiratory tract infection by technology, estimated in log-binomial regression models, are shown in This socio-demographic distribution among the web group is comparable to other webbased studies (16;17). Interestingly, most participants remained faithful to their initial choice of technology and the proportion that switched over was small (less than 10%) and similar regardless of the initial choice. Although the week-to-week variation in disease reporting was remarkably similar in the web and IVR groups, the overall proportion that reported at least one disease episode was 14% (any respiratory tract infection) and 27%

(ILI) higher in the web group than in the IVR group. This excess, however, was inflated by confounding from socio-demographic factors, notably age. After adjustments for these factors, statistically non-significant excesses of no more than 1-8% remained.

The major limitation of this study is the uncertain generalizability. Out of 14,000 invitations to the representative population sample, 3,341 (24%) registered to participate in the study. On average, the participants were older, had a higher degree of education and were more represented by women than the total sample. This distribution of sociodemographic characteristics among responders vs. non-responders has been demonstrated in other epidemiological studies [START_REF] Tolonen | Effect on trend estimates of the difference between survey respondents and non-respondents: results from 27 populations in the WHO MONICA Project[END_REF][START_REF] Tolonen | 25-year trends and socio-demographic differences in response rates: Finnish adult health behaviour survey[END_REF][START_REF] Eaker | Response rate to mailed epidemiologic questionnaires: a population-based randomized trial of variations in design and mailing routines[END_REF] and seems to be a growing methodological problem (19;21;22). However, in view of the rather heavy commitment expected from the participants in the present study, participation rate in the lower range of what is presently seen in epidemiological studies with active participation of healthy people was foreseen.

While validity of the self-reports are not the focus of the present analysis and therefore subject for a separate study, lack of validity would make the present report superfluous. We therefore compared epidemic curves for ILI derived from populationbased influenza surveillance data with those obtained with the prevailing surveillance method, namely reports from sentinel physicians. Both sets of data are exhibited on the website for the Swedish Institute for Infectious Disease Control (www.smittskyddsinstitutet.se). Figure 5 shows the curves for the first 20 weeks of 2008 and 2009. Although the Swedish sentinel reporting system constitutes a dubious gold standard, providing data only on the relative frequency of patients who are deemed to have ILI among all patients presenting at the sentinel units, the shape of the curves, the timing of the peaks, and the relative difference between the two seasons are strikingly similar. This provides support for the validity of the population-based data. Some counter-intuitive findings deserve to be highlighted, though. In view of the overrepresentation of people with high socio-economic status in the web group, it might be expected that the members of this group would, on average, be healthier (12;18), but they were, in fact, slightly more likely to report new infections. Though there seem to be no association between socio-economic status and common cold among adults [START_REF] Cohen | Objective and subjective socioeconomic status and susceptibility to the common cold[END_REF], there are some evidence of increased susceptibility to upper respiratory tract infections if living under low socio-economic conditions during childhood [START_REF] Cohen | Childhood socioeconomic status and host resistance to infectious illness in adulthood[END_REF]. A lower degree of compliance with the reporting commitment among people with low socio-economic status might be the most plausible explanation for the lower rate of infection in the IVRS group, but the web group contained more participants with large families, and children are notorious vectors of infections [START_REF] Olson | Monitoring the impact of influenza by age: emergency department fever and respiratory complaint surveillance in New York City[END_REF]. This notwithstanding, the adjusted estimate for household size in our mutivarate modelling was not suggestive of any strong independent effect of household size. It might also seem counter-intuitive that the lowest average report frequency was observed among the oldest participants. A higher threshold for reporting trivial symptoms might be one explanation, but the oldest were more likely to live in small households and are probably less often interacting with children. Recent population-centered disease surveillance in connection with the A(H1N1) pandemic has revealed that the older age-groups were surprisingly little affected (26;27). In spite of a general tendency for the immune system to become somewhat less efficient in elderly people, the spectrum of immunity acquired over a long life might confer some protection.

Moreover, during the influenza season under study, the oldest age group was the only one that was subject to systematic vaccination (28;29). A questionnaire to our participants after completion of the registration indicated that 57% of the responders in the oldest age group were vaccinated compared to less than 10% in the other age groups.

The dramatic effect of the first reminder suggests that some participants may have misunderstood the instructions and were waiting for a contact from the study secretariat.

When the first reminder arrived, some telescoping (30) (but also some false positive reports) may have occurred, thus inflating the rates. Interestingly, the phenomenon was expressed in an almost identical way in the web and IVR groups.

The studied technologies require access to the Internet or a telephone. This is probably a minor problem, as according to Statistics Sweden in 2008, 84% of the Swedish population had used the Internet regularly, and most individuals have access to a landline or a mobile phone [START_REF] Jonsson | The Swedish population's use of the Internet and Telephones -an individ survey[END_REF]. Hence, as the system is dependent on a mixed-mode of two techniques, the low response rate is probably not due to lack of accessibility to the technique.

In conclusion, information and communication technologies, such as the web and IVR, have the potential to logistically implement a population-based influenza surveillance system where reports can be registered with short time-delay. Although some socio-demographic factors that determine the preference for registration technology were also linked to the propensity for reporting infections (and presumably to the incidence of such infections) thus confounding the comparison of disease rates in the web and IVR groups, it appears that the technology per se does not have any important effect on the quality of the resulting data. With proper attention to possible confounding, it should be possible to use web and IVR interchangeably for simple reporting of infectious disease symptoms. respectively, based on data from the conventional sentinel physician surveillance system in Sweden (left panel) and the new population-based influenza surveillance scheme (Sjukrapport, right panel). Although the sentinel system cannot generate incidence rates but only percentages of all patients at the sentinel units who present with ILI, the shape, timing of peaks, and relative difference between the two seasons are strikingly similar to the curves generated by the population-based influenza surveillance. All curves are based on data that are exhibited at the web-site of the Swedish Institute for Infectious Disease Control (www.smittskyddsinstitutet.se).

Figure 1 .

 1 Figure 1. Rates (per 100 person-weeks) of self-reports of any respiratory tract infection, week by week during the influenza season 2007/2008, by reporting technology.

Figure 2 .

 2 Figure 2. Rates (per 100 person-weeks) of self-reports of influenza-like illness (ILI), week by week during the influenza season 2007/2008, by reporting technology.

Figure 3 .

 3 Figure 3. Proportions (%) that self-reported at least one respiratory tract infection during the influenza season 2007/2008, by 5-year age group and reporting technology.

Figure 4 .

 4 Figure 4. Proportions (%) that self-reported at least one episode of influenza-like illness (ILI) during the influenza season 2007/2008, by 5-year age group and reporting technology.

Figure 5 .

 5 Figure 5. Epidemic curves for influenza-like illness (ILI) in the first 20 weeks of 2008 and 2009,

  was 46 days (25 in the 25 th percentile and 86 in 75 percentile) in the IVR group and 43 (18 in then 25 th percentile and 82 in 75 percentile) in the web group.

During the 36-week study season, 617 (48% of 1,297) participants in the IVR group submitted 1,035 reports of respiratory tract infections. Of these reports, 283 were identified as ILI, coming from 229 (18% of 1,297) IVR participants. During the same period, 2,032 reports of respiratory tract infections were received from 1,107 (54% of 2,044) web participants. Of these, 695 were ILI episodes, reported by 460 (23% of 2,044) web participants. More than one report of respiratory tract infections was submitted by 440 (66%) in the IVR group and 621 (56%) in the web group; two reports were submitted by 148 (22%) in the IVR group and 284 (26%) in the web group, three reports by 51 (8%) in the IVR group and 108 (10%) in the web group, and 4 or more reports by 30 (4%) in the IVR group and 94 (8%) in the web group. The median time between the first and second reports

Table 3 .

 3 The unadjusted RR in the web group, relative to the IVR group, was 1.14 (95% CI: 1.06, 1.22). When adjusting for gender, the RR increased slightly. After including gender, age group, education, family size and income, the RR shifted to 1.01 (95% CI: 0.94, 1.09), indicating that the difference in reporting frequency between the two techniques was mostly due to other factors, and especially age group (Table3). Crude and adjusted RRs for reported ILI by reporting technology are shown in Table4. The crude RR was

	the RR shifted to 1.08 (95% CI: 0.94, 1.25) (Table 4). No statistical interaction was
	found.
	DISCUSSION
	In this study of population-based influenza surveillance, participants were given
	the opportunity -after having received invitation letters by regular mail -to choose
	between the web and IVR through telephones for participant-initiated self-reporting of
	new upper respiratory tract infections during a 36-week follow-up period. More than 60%

estimated to 1.27 (95% CI: 1.11, 1.47). After adjustment for available background factors of participating individuals chose the web. Differences between socio-demographic strata with regard to preference for communication technology were found, in line with the results of other studies which have compared web-and telephone-based interviews

(12;15)

. More women, elderly, and less educated participants preferred IVR, while individuals younger than 65 years, with a higher level of education, living in larger households, and having a high family income were over-represented in the web group.

Table 1 .

 1 Distributions of socio-demographic characteristics among participants and the total sample in a study of population-based infectious disease surveillance via the Web or Interactive Voice Response (IVR) telephone service during a 36-week period from September 2007 to May 2008 in Stockholm, Sweden a

		Participants	Total
		n=3,341	n=14,000
		n	(%)	n	(%)
	Age Group
	0-17		727 (22%)	3,089 (22%)
	18-39		665 (20%)	4,220 (30%)
	40-64	1,247 (37%)	4,639 (33%)
	≥65		702 (21%)	2,052 (15%)
	Gender
	Men	1,473 (44%)	6,882 (49%)
	Women	1,868 (56%)	7,118 (51%)
	Education
	≤ 9 years		232 (7%)	1,985 (14%)
	10-12 years		875 (26%)	4,078 (29%)
	13-15 years		433 (13%)	1,461 (10%)
	>15 years		805 (24%)	2,487 (18%)
	Missing b		996 (30%)	3,989 (28%)
	Household size
	1		916 (27%)	4,205 (30%)
	2		835 (25%)	2,827 (20%)
	3		536 (16%)	2,337 (17%)
	4		713 (21%)	2,958 (21%)
	5		279 (8%)	1,192 (9%)
	≥6		62 (2%)	378 (3%)
	Missing		0 (0%)	103 (1%)
	Marital Status
	Never married	1,552 (45%)	7,361 (53%)
	Married	1,297 (39%)	4,841 (35%)
	Divorced		340 (10%)	1,466 (10%)
	Widow/widower		139 (4%)	574 (4%)
	Missing		13 (0%)	0 (0%)
	Household income c
	Low		239 (7%)	1,924 (14%)
	Low/middle		296 (9%)	1,676 (12%)
	Middle		556 (17%)	2,372 (17%)
	High/middle		561 (17%)	2,166 (15%)
	High	1,645 (49%)	5,627 (40%)
	Missing		44 (1%)	235 (2%)
	a All data compared on aggregated level
	b Including children in the age group 0-17 years
	c Household income categorized as low (<14,915€/year), middle/low (14,916-24,129€/year),
	middle (24,130-36,220€/years) middle/high (36,221-50,415€/year), high ( 50,416€/year), and unknown

Table 3 .

 3 Relative Risk (RR) and 95% Confidence Intervals (CI) for reports of any respiratory tract infection, obtained using log-binomial regression modelling. Results of univariable and multivariable models (the latter including all variables in the table). Children under the age of 17 represented by the parent who reported in lieu of the child. b Household income categorized as low (<14,915€/year), middle/low (14,916-24,129€/year), middle (24,130-36,220€/years) middle/high (36,221-50,415€/year), high ( 50,416€/year), and unknown

		Univariable			Multivariabl
					e
		RR	95% CI	p-value	RR	95% CI	p-value
	Technique
	IVR	ref			ref
	Web	1.14	1.06, 1.22	0.003	1.01	0.94, 1.09	0.74
	Age group
	0-17				1.36	1.18, 1.57	<0.0001
	18-39				1.23	1.08, 1.41	0.002
	40-64				1.06	0.94, 1.20	0.36
	≥65				ref
	Gender
	Women				1.24	1.61, 1.33	<0.0001
	Men				ref
	Education a
	≤ 9 years				0.91	0.80, 1.04
							0.16
	10-12				0.94	0.87, 1.02
	years						0.14
	13-15				1.12	1.03, 1.21
	years						0.006
	>15 years				ref
	Household
	size
	1				ref
	2				1.04	0.93, 1.16	0.53
	3				1	0.89, 1.12	0.97
	4				0.97	0.86, 1.09	0.57
	5				1	0.87, 1.14	0.94
	≥6				1.03	0.81, 1.32	0.8
	Household
	income b
	Low				0.93	0.81, 1.08	0.35
					0.89	0.77, 1.02
	Middle/Low						0.1
	Middle				0.91	0.82, 1.02	0.1
					0.98	0.89, 1.08
	Middle/high						0.7
	High				ref
	a

Table 4 .

 4 Relative Risk (RR) and 95% Confidence Intervals (CI) for reports of Influenza-like Illness (ILI), obtained using log-binomial regression modelling. Results of univariable and multivariable models (the latter including all variables in the table). Children under the age of 17 represented by the parent who reported in lieu of the child. b Household income categorized as low (<14,915€/year), middle/low (14,916-24,129€/year), middle (24,130-36,220€/years) middle/high (36,221-50,415€/year), high ( 50,416€/year), and unknown

			Univariable		Multivariable
		RR	95% CI	pvalue	RR	95% CI	p-value
	Technique
	IVR	ref			ref
	Web	1.27	1.11, 1.47	0.0008	1.08	0.94, 1.25	0.28
	Age group
	0-17				1.87	1.38, 2.52	<0.0001
	18-39				1.57	1.18, 2.09	0.0018
	40-64				1.24	0.95, 1.61	0.11
	≥65				ref
	Gender
	Women				1.47	1.28, 1.70	<0.0001
	Men				ref
	Education a
	≤	9			1.12	0.88, 1.41
	years						0.36
	10-12				0.98	0.84, 1.16
	years						0.85
	13-15				1.14	0.95, 1.37
	years						0.16
	>15				ref
	years
	Household
	size
	1				ref
	2				1.16	0.92, 1.46	0.71
	3				1.17	0.92, 1.49	0.20
	4				1.02	0.81, 1.30	0.19
	5				0.89	0.55, 1.42	0.85
	≥6				1.12	0.84, 1.50	0.45
	Household
	income b
	Low				0.67	0.48, 0.94	0.02
					1	0.76, 1.31
	Middle/Low
							0.99
	Middle				0.81	0.55, 1.02	0.75
					1.04	0.86, 1.26
	Middle/high
							0.71
	High				ref
	a

FUNDING

This work was supported in part by the Swedish Ministry of Health and Social Affairs, and in part by the European Community FP7 Integrated Project 231807 EPIWORK .

Conflicts of interest: None declared


Ralf Winkler

Susanne Fuchs

Pascal Perrier

Mark Tiede

published or not. The documents may come   L'archive ouverte pluridisciplinaire

Can the location of the vocal tract bending constrain individual vowel articulation? Evidence from biomechanical modelling.

Ralf Winkler 1 , Susanne Fuchs 1 , Pascal Perrier 2 , Mark Tiede 3,4 1 ZAS Berlin, 2 GIPSA-lab Grenoble, 3 Haskins Labs New Haven, 4 MIT Boston Although native speakers of a given language all use the same phonemic inventory, speakers vary from one to another with respect to their acoustics and articulation. The variability among speakers may be driven by a variety of factors. This paper focuses on anatomical factors, in particular on the position of the bending of the vocal tract relative to its total length. For most acoustic tube models the relative position of the vocal tract bending does not matter for the simulation of vowels, since these models treat the vocal tract as a straight series of tubes. In contrary, the relative position of the vocal tract bending is supposed to be fundamental for tongue biomechanics, since the soft tongue body has to fit its surrounding vocal tract borders and muscles may not generate forces in exactly the same direction. If the relative bending position of the vocal tract is rather anterior (model A), the length of the horizontal dimension (palatal region) is short in comparison to the vertical dimension (pharynx). A more posterior location of the vocal tract bending (model B) corresponds to the reverse, if a similar vocal tract length is considered in both models. We expect a larger articulatory variability in the vertical dimension for model A and a larger variability in the horizontal dimension for B. In order to test these hypothesis two biomechanical models were built. Both models were based on MRI data of one speaker. For model A we lengthened the original tissue contours of the pharynx by 1.5 cm in the vertical direction and for model B the oral cavity in the horizontal direction. For each model 8000 simulations were run by varying motor commands of the six major tongue muscles randomly around their values at tongue rest position. The biomechanical models were coupled with a harmonic acoustical model based on a distance to area function conversion to calculate the corresponding formants. Since we assume that auditory targets are the primary goal of speech production, the vowel targets for /a/, /u/ and /e/ were defined as identical formant ellipses for both models. Results of our simulations provide evidence that articulatory variability of the tongue in the horizontal dimension is larger for model B than A, reaching the same acoustic vowel target ellipsis for /e/. For /u/ this effect is similar, but smaller. Furthermore, model A showed more articulatory variability in the vertical dimension than model B for vowel /a/ which is in agreement with the relatively large pharynx length. In our experiment articulatory variability is constrained by the relative position of the vocal tract bending. This position can shape the allowed degrees of freedom and constrains speaker specific articulatory precision for a given vowel target.