Evens Salies

Mergers in the GB Electricity Market: effects on Retail Charges *

Keywords: Energy Competition, Retail Pricing, Vertically Integrated Firms JEL Classification:C31, L22

The opening up of the UK residential electricity sector in 1999 prompted several studies of the impact this had on both the level and structuring of retail charges, and on incumbent players' market power. Drawing on observations of regional tariffs for the month of January 2004, this paper supports previous conclusions based on simulated retail charges, looking at the response of real tariffs to distribution and transmission costs, customer density, and the length of low voltage underground circuit. We also investigate whether vertically integrated suppliers have a particular effect on charges ceteris paribus the effect of cost drivers and supplier-related factors.

Introduction

The GB residential electricity market was opened to competition in May 1999. This had an immediate impact on the level of tariffs and services offered to consumers. The wave of mergers and acquisitions which followed raised concerns about the potential detrimental effect on end-customers. Although much research has been devoted to switching behaviour [START_REF] Giulietti | Consumer Choice and Industrial Policy: A Study of UK Energy Markets[END_REF][START_REF] Waterson | The role of consumers in competition and competition policy[END_REF]Ofgem, 2001Ofgem, , 2002Ofgem, , 2003)), third-degree price discrimination and incumbents' market power [START_REF] Otero | Price discrimination, regulation and entry in the U.K. residential market[END_REF], little information is available about the effect of ownership structures on tariffs.

Oligopoly models show that the proposition that a merger enables firms to exploit economies of scale is not convincing if the merger does not also generate technical synergies. These synergies would lead to lower charges to customers [START_REF] Spector | Horizontal mergers, entry, and efficiency defences[END_REF] see also references herein). A study by Azzam and Rosebaum (2001) which considers the link between efficiency to concentration points out however that it is difficult to discriminate empirically between collusion and cost-efficiency as variables relating to price and profitability. The retail electricity market is a case in point, as high switching costs favour collusive behaviour, thus maintaining high prices.

Using 2002 price data [START_REF] Salies | Charges, costs and market power: the deregulated UK electricity retail market[END_REF] examine similarities between the effects of brand coefficients on retail electricity prices within existing ownership groups but find that evidence of this is weak. Relying on tariffs levels from January 2004, the present paper contributes to the discussion by highlighting the effect of mergers on tariffs in a more efficient way. We test for the specific average effect of several ownership groups on regional electricity retail charges after controlling for cost drivers, economies of scale and customer density. Particular attention is given to the effect of the creation of EDF Energy, the merged London Electricity and SEEBOARD group of companies. In broad terms, we conjecture that if technical synergies exist between distribution networks owned by EDF Energy (situated in contiguous regions:

London, East and South-East England), they should result in lower prices. This paper is structured as follows. Section II briefly reviews the changes in ownership structures that occurred in the GB electricity sector between May 2002 and January 2004. We focus on the probable effect of these changes on the degree of competition and remaining incumbents' market power. We then introduce data, an econometric model and the hypotheses to be tested in section III. Results are given and discussed in section IV, before the conclusion in section V.

Changes in market structure

The ownership structure of each supplier is summarised in Table 1 compared with that of April-May 2002, being the period analysed by [START_REF] Salies | Charges, costs and market power: the deregulated UK electricity retail market[END_REF]. A more detailed picture of the ownership structures of residential distributors and suppliers in GB as at January 2004 is given in the Table 4 (see also Electricity Association, 2003a, b). At the intersection of any given row and column one can see whether a supplier (row) is an incumbent in the distribution region (column). A supplier may not be present in the selected region, as is the case for Basic Power.

Concentration increased from April 2002 as a result of acquisitions, with at the most five ex-Public Electricity Suppliers and three new entrants in most areas, in addition to internet and other suppliers (ex-Public Electricity Suppliers, hereafter "ex-PES", are also known as Regional Electricity Companies). Almost all suppliers operate in the 14 distribution regions that make us England, Scotland and Wales. For reasons unknown to the authors, Basic Power was not operating in Scotland at the time of the study, which remains the case.

In April 2004 Scottish Hydro Electric-Southern Electric (SSE) acquired Atlantic Electric and Gas. Powergen purchased TXU's British generation and retail operations. These mergers raise competition concerns although they may have different detrimental effects given that they involve firms with significantly different market shares. A merger between two firms, each with relatively high market share, may have less impact on competition than one in which a large supplier merges with a smaller rival (RBB, 2002).

The magnitude of the coefficient applied to the ownership group dummies in comparison with the coefficient of other groups will help us to test the data for particular merger effects. 1

Data and econometric model

The retail charges pertain to 14 regions, with up to eight brand names per region. We consider here a single payment method (standard credit) at three levels of consumption.

The distribution charges were taken from distributors' published statements of charges for connection to and use of the distribution system (Ofgem, 2004). Constituting 15-30% of a customer's final bill, these vary across the distribution regions according to the charges levied by the local distribution company, but are levied in the same manner to all suppliers using that distribution network. Generally the tariffs have two components: a charge per consumer and a charge per unit of electricity carried. We note that prepayment distribution charges differ from credit and direct debit charges. 2 Transmission charges form approximately 13% of the invoice and vary from region to region. Charge levels are taken from the National Grid Transco web site (see National Grid Transco, 2003), and are those levied for the period 16:00 hours to 19:00 hours.

Descriptive statistics are shown in Table 2.

For each level of consumption q = 1650, 3300, and 4950 kWh, we estimate the following model:

(1) () () ( ) where indices r and j denote distribution region and supplier, respectively. The payment method is standard credit. "(q)" specifies variables the value of which varies with q. 3 In addition: o gj = 1 if supplier j belongs to ownership group g; 0 otherwise (group dummy)

c rj =
We estimate three regression equations, one for each simulated level of annual demand, relating retail charges to the cost elements which we could identify, to market characteristics and to incumbency and group dummies.

Salies and Waddams Price ( 2004) estimated a model similar to (1) with brand instead of group dummies. Brand dummies capture any effect of suppliers reflected in tariffs (including costs of purchasing electricity). Our model gives us an opportunity to test whether suppliers that are not vertically integrated with other market participants tend to price less compared with integrated suppliers. In this model we replaced brand dummies with fewer group dummies that measure the impact on retail charges of the various ownership groups present in the market at the time of the analysis. There are five mutually exclusive ownership groups: Powergen, Scottish Hydro Electric and Southern Electric, Scottish Power, EDF Energy, and Innogy, plus the three non-ex-PES companies, as listed in Table 1.

Given the findings of Salies and Waddams Price ( 2004), we expect costs variations across regions to be closely mirrored in tariff variations ( 1 α to be close to 1, and 2 α not exceeding one third, reflecting the shorter consumption period to which transmission charges correspond). We allow for both the number of customers and the distribution area using a ratio of the two. It is expected that denser (urbanised) areas allow suppliers to reduce per-customer marketing costs for a given network size, which would be indicated by a negative value for 3 α . The length of low voltage underground circuit is used as a proxy for the size of the network. Underground circuit length has a very close correlation to the number of distribution customers (the correlation coefficient equals 0.88). Its effect on charges shall be measured by 4 α . A negative value for this coefficient would more generally indicate economies of scale.

The additional power of incumbents (the ex-PES), who had retained a market share of between 50% and 85%, would be reflected in higher tariffs and a positive coefficient for the incumbency dummy, 5 α . A positive and significant value for this coefficient may reflect the positive costs of switching from one ex-PES to another.

Using data from April 2002, [START_REF] Salies | Charges, costs and market power: the deregulated UK electricity retail market[END_REF] test for heterogeneity between suppliers by examining the significance of brand dummy coefficients. Here, we test the hypothesis of whether vertical integration has a relatively significant effect on charges using . Unlike the previous study which relied on signs of the estimated coefficients on brand dummies, the present analysis shows some improvement as it statistically tests for the significance of group dummy coefficients; group dummies replace brand dummies. We note that our model may be seen as a constrained version of a model with brand dummies.

α

We have not included a constant; thus, no base group is considered. This allows us to avoid near-colinearity problems and vacuous interpretation of the constant. Following the Salies and Waddams Price ( 2004) we estimated a two-equation seemingly unrelated regression equation (SURE) model for standard and direct debit tariffs. We only report results of the standard credit equation.

As there is a possibility of non-constant residual variance within each equation resulting from the spatial dimension of our data, we tested for conditional heteroskedasticity of unknown form within each equation using [START_REF] White | A heteroskedasticity-consistent covariance matrix estimator and a direct test for heteroskedasticity[END_REF] test. We reject homoskedasticity at the 5% level of significance in the direct debit equation at 1650kWh. We may interpret this result as a stronger attempt from supply businesses to differentiate their tariffs in this market. As will be shown later, this result shows regional incumbents still enjoy market power, particularly in the direct debit market where most switching has occurred. The model's coefficients are reported in Table 3.

Results and discussion

First we consider the responses of retail charges to distribution and transmission charges. As expected, the coefficient on distribution charges is significantly different from zero at the 5% level of significance. If we assume a 95% confidence interval centred about one, distribution costs are almost fully passed on to customers, except in the direct debit and prepayment equations at 1650kWh. With regard to transmission charges, our results are also similar to Salies and Waddams Price ( 2004), with a coefficient about one third due to the short consumption period to which these charges correspond (peak period from 16:00 to 19:00 hours). If in each equation at 3300kWh we multiply by three the estimated coefficient on the transmission variable then we obtain a value that ranges from about 0.7 to 0.8.

We find economies of density at 1650 kWh and less significantly at 3300 kW. Closely related, the negative impact on retail charges of the length of the underground circuit in all markets would reflect economies of scale: a customer's bill is lower in distribution regions that have more kilometres of circuit underground. The low significance of the coefficient applied to density might result from the excessive correlation between this variable and circuit's length variables. The existence of those economies leads us to reject the hypothesis that urban and rural customers benefit equally from competition. In any event, NAO (2001, p.8) reported that rural customers are less likely to change their electricity supplier than those who live in urban areas because many customers change their supplier in response to a visit from a sales agent, and direct marketing of electricity has so far been less intensive in rural areas.

This negative relationship between retail charges and both the size of the network and the number of customers per km 2 reflects first technical economies at the distribution stage: heavy investments create an incentive for distributors to spread their costs among a large number of connected households. This situation could support the increasing concentration through horizontal integration in the retail sector; given the existence of decreasing per customer distribution charges paid by suppliers, they have an interest in servicing a large number of customers. The two-component structure of distribution tariffs in all but the Sweb regions implies technical economies of scale, in that the "per unit" distribution charge necessarily decreases when the amount of energy supplied to consumers increases.

As expected, Atlantic Electric and Gas and Basic Power have the lowest impact on charges with potential average annual savings (see [START_REF] Waterson | The role of consumers in competition and competition policy[END_REF] of up to £50, as between the cheapest and the most expensive supplier. Note that these savings do not account for consumer perception of switching costs. This difference was highest in the direct debit market at 4950kWh (we do not report this result). Conversely, the effect of Innogy and Powergen groups on charges is greater or equal to the average effect. This seems consistent with integrated suppliers charging higher prices raising competition concerns. It is well known that the existence of consumer switching costs creates a further incentive for firms to grab more customers, which necessarily gives an advantage to older suppliers in the market [START_REF] Farrell | Coordination and lock-in: competition with switching costs and Network effects, U //elsa[END_REF].

Ofgem (2003, p.38) reports that more households are switching to non-prepayment markets and low-income customers switch less often.

Interestingly, EDF Energy group has, on average, a lower impact on charges than SSE and Innogy. We suspect a more efficient vertically integrated structure and pricing strategy. Note that EDF Energy includes the Seeboard and Eastern distribution businesses that are in neighbouring regions. It is worth noting, as [START_REF] Spector | Horizontal mergers, entry, and efficiency defences[END_REF] emphasises, that the proposition that a merger allows firms to exploit economies of scale is not convincing if the merger does not also generate technical synergies, through learning for example.

Technical synergies may exist between distribution networks owned by EDF Energy because they are in contiguous regions (London, the East and South East). In addition, EDF Energy holds generation assets, giving it the ability to bypass the volatile and often illiquid electricity exchanges in order to hedge its customer base.

SSE also seems efficient at low consumption levels compared with Powergen, Scottish Power, Innogy and British Gas, but overall less efficient than the EDF Energy group.

Unlike this latter entity, SSE owns very distant networks, one in Scotland and the other in the South of England, which, in accordance with our previous discussion, would not favour technical synergies.

Conclusion

Using regional observations on tariffs offered in December 2003, the present paper set out to investigate the particular effect of various integrated structures on the relationship between annual retail charges and cost drivers. We find evidence of different pricing strategies by the various ownership groups, which suggests that the effect on retail charges of integrated suppliers varies depending on the spatial dispersion of the merged networks.

Overall these results support Salies andWaddams Price (2003, 2004) who also pointed out the negative (respectively positive) effect on unit rates and bills of a change in the number of customers (respectively the distribution area). Our density variable, however, provides a more flexible interpretation as the particular influence on charges in rural (less dense) areas proves to be significant. Alongside this variable, the size of the underground network leads to a similar result as the number of customers: coefficient estimates range from -0.7 to -0.3. For example, if the underground circuit increases by 3,000 km, then retail charges would decrease by £1 in the standard credit market at 1,650kWh.

We could bring more information to the discussion by extending the range of consumption levels considered or using longitudinal data. This would have the further advantage of increasing the number of observations for brands such as Manweb, SWEB, Swalec, and Seeboard.

  retail charge in region r from supplier j d r = distribution charge in region r t r = transmission charge in region r n r = total number of distribution customers per km 2 in region r (density) u r = length of underground circuit in region r i rj = 1 if supplier j is the incumbent in region r; 0 otherwise (incumbency dummy)

Table 2 . Descriptive statistics -January 2004 P (a)

 2

	P

Table 3 . Standard Credit; Dependent variable: annual bill

 3

					Annual consumption
			1650kWh		3300kWh		4950 kWh
	Distribution Charge		.86	*** 1.03	*** .89	***
			(.12)		(.07)		(.07)
	Transmission Charge		.54	*** .26	*** .16	***
			(.08)		(.03)		(.03)
	Density (customers / kmP 2	P P P)	-.23	**	-.16	*	-.20
			(.09)		(.08)		(.13)
	Underground Lines (×1000)	-.32	*** -.38	*** -.69	***
			(.09)		(.09)		(.13)
	Incumbent		7.51	*** 18.69	*** 29.74	***
			(2.64)		(1.82)		(2.63)
	Suppliers (£)
	Sempra Energy, etc. (Atlantic	101.46	*** 167.07	*** 256.51	***
	Electric and Gas)
			(7.65)		(6.41)		(8.16)
	Utility Link (Basic Power)	116.68	*** 176.89	*** 260.51	***
			(7.64)		(6.34)		(8.06)
	Powergen		111.06	*** 191.49	*** 296.07	***
			(7.44)		(6.40)		(8.14)
	SSE		104.51	*** 182.75	*** 284.68	***
			(7.46)		(6.43)		(8.19)
	Scottish Power		119.88	*** 186.18	*** 276.83	***
			(7.44)		(6.40)		(8.15)
	EDF Energy		103.30	*** 175.69	*** 272.72	***
			(7.48)		(6.44)		(8.20)
	Innogy		111.94	*** 182.27	*** 286.07	***
			(7.58)		(6.40)		(8.14)
	Centrica (British Gas)		113.74	*** 179.28	*** 270.44	***
			(7.45)		(6.41)		(8.16)
	Adj. 2 R		.731		.909		.919
	Notes: standard errors in parentheses. '*' = significant at the 10% level. '**' = significant at

the 5% level. '***' = significant at the 1% level.

Table 4 . Ownership structure in the UK residential electricity market at December 2003

 4 Incumbent, E = Entrant, N = Neither. (a) SSE counts for one supplier Manweb region = Merseyside, Cheshire, North Wales. Scottish Hydro region = North Scotland. Scottish Power region = South and Central Scotland

	Aquila Inc.	Owned

Endnotes

This group acquired SWALEC in 2000 thus we do not ignore the influence of the SWALEC acquisition. For Scottish Power and Scottish Hydro regions, we employed data from the 2002-03 period as this was the only data available to us in the appropriate format (p/kWh) when completing the present study. Prepayment distribution standing charges were replaced with their nonprepayment equivalent when the data was missing, which occurs in four regions. At 1,650kWh, this substitution is fairly accurate, as the extra charge for prepayment customers does not exceed £10, i.e. 15% of distribution charges (or less than 3% of retail charges).

Given the non-linear structure of most tariffs offered by network utilities (see Wilson, 1997), these models have some advantage over models considering a single mean level of consumption. V.-Cervera and J-Málaga ( 2001) and Ofgem's works also consider more than one level of annual demand. This methodology is appropriate as most tariffs intersect at some level of consumption reflecting various pricing strategies and tactics to attract targeted consumers; some suppliers prefer to target low energy demand customers while others offer attractive tariffs to customers whose annual demand exceeds an average level known to suppliers.


Jean-Paul Fitoussi
email: jeanpaul.fitoussi@sciences-po.fr

Francesco Saraceno
email: francesco.saraceno@sciences-po.fr

The Intergenerational Content of Social Spending: Health Care and Sustainable Growth in China †

Keywords: Social Spending, Health Care, Sustainable Growth, Chinese Economy, Savings Glut

The paper endorses the thesis that current macro imbalances are partly due to an excess of household savings in China, whose origin is to be found among other things in household uncertainty about the provision of public services like health care, pensions and education. Focusing on health services, because of their priority in the concerns of the Chinese people, we describe the recent trends in the provision of health care. We then argue that social spending by the government may have important intergenerational content, in that it allows higher private spending, lower inequality, higher levels of human capital and the like. All these factors are related to the potential growth rate of the economy. We conclude that a more important role of the government in the sector of public services, and in particular of health care, may help reduce the possibility of future bottlenecks, and hence help keeping the Chinese economy on a sustainable growth path. We conclude the paper by an assessment of the current debate on how to reform the system, and we advocate universal publicly funded basic health coverage.

Introduction

The Chinese economy is becoming increasingly unequal. The outstanding long term growth performance of the country has been obtained partly thanks to the very low priority given to all the other policy objectives, including spatial and sector equality. But the rise of inequalities has been so large in size that in the past few years the phenomenon triggered a reaction by the Chinese authorities, in fear of social unrest that could undermine the economic performance of the country and its political stability. This paper argues that growing inequality should be combated also because it may have long lasting effects on human capital, macroeconomic imbalances, and the overall efficiency of the economy. We suggest that current public spending, in particular social spending (health, education etc.), has a strong intergenerational content as it affects the distribution of resources among generations, and hence the future level of "well being", whatever the definition of the term.

In particular, this paper focuses on health policy. In November 2007, the Chinese National Bureau of Statistics organized the Seventh Sampling Survey on Public Sense of Security, interviewing more than 100,000 households1 . According to the survey, medical care was the top concern of the household (15.3% of the respondents), followed by a vaguer "social issues" with 14.3%. "Social Security", related to the affordability of health and retirement came third with 13.2%. The growing public concern about health care access has prompted in the past few years a response from the government, which is rolling back on the deregulation implemented before. A new plan, "Healthy China 2020", has been unveiled in December 2007 by the Chinese government2 . This plan spells out an intermediate objective, a basic Medicare system to be set up by 2010, with the goal of universal health care and equal access to public services for its 1.3 billion people by 2020.

While other categories of social spending in China require attention because of the distortions and inequalities linked to their provision (notably education and social security), none of them seems to generate the same level of public anxiety than health expenditures, and rightly so, as a decent level of health is a prerequisite for benefiting from other categories of social spending. If we use this perspective, the household survey mentioned above reveals a lexicographic ordering in household's preferences, which justifies our focus on health care provision as an example of social spending.

The structure of the paper is as follows: in Section 2 we discuss the role of China in today's global macro imbalances: we tend to agree with the thesis that the source of excess savings -a too high level of households' saving rate -can mostly be traced to the uncertainty about future provision of social goods which in turn is due to the gradual disruption of the community based social protection system. Section 3 discusses the evolution of the health care system in the post reform period. In section 4 we develop the reasons why current social spending may have strong intergenerational content. Finally, section 5 gives a snapshot of today's attempts to correct the distortions in the provision of health care, which are based on voluntary adhesion to an insurance scheme. After showing why this attempt would not have the positive effects that the authorities hope for, we conclude by giving some indications about what we believe to be the necessary policy and institutional changes for the future, and by trying to assess whether the "Healthy China by 2020" plan responds to these requirements.

The sources of Excess Savings

In the debate on global imbalances that rages in the academic literature and in the specialized press, the excess expenditure of US consumers and firms is usually contrasted with the "saving glut" [START_REF] Bernanke | The Global Saving Glut and the U.S. Current Account Deficit[END_REF]) of other areas of the world, notably East Asian countries. Because of its size, China is usually pointed out as the main example of this world excess saving that helps sustain the current global imbalances. In fact, as figure 1 shows, both the remarkable levels of investment that China experienced since the early 1980s and the recent boom of the current account surplus happened thanks to an important This aggregate figure hides wide regional and sector diversity, along the well known differences in growth between coastal and western provinces, and between rural and urban areas (for a survey see, [START_REF] Lim | China and the Global Economy: Medium-Term Issues and Options -a Synthesis Report[END_REF]). If we look at the savings rates (figure 2), we can observe two remarkable trends: The first is a generalized increase (that obviously mirrors the decrease in consumption) of savings, which today account for almost 25% of household incomes. The second is, within this general trend, a more than proportional increase in savings for rural households (being on average poorer they should on the contrary save less). The saving rate, that in the early 1990s was lower for poorer rural households, has since the mid 1990s been consistently larger, and has converged only recently [START_REF] Kraay | Household Saving in China[END_REF][START_REF] Kuijs | Investment and Saving in China[END_REF]).

While there is some debate as of the causes of this excessive savings (see e.g. [START_REF] He | Understanding High Saving Rate in China[END_REF], who argue that demand deficiencies are to be attributed to a decrease of disposable income and not to the increase in savings rate), the changing behaviour of rural and urban households seems to be undoubtedly related to increased income uncertainty and to lower social protection. A high saving rate is then a rational reaction against the increase Source: [START_REF] Chamon | Why Are Saving Rates of Urban Households in China Rising?[END_REF] of both of those risks3 . [START_REF] Chamon | Why Are Saving Rates of Urban Households in China Rising?[END_REF] besides the growing uncertainty, point to the insufficient development of financial markets, as one of the main causes of the lack of consumption smoothing by Chinese households.

In the same vein, the literature on savings, risk and insurance (for a survey, see [START_REF] Besley | Savings, Credit and Insurance[END_REF]) documents that developing rural economies experience widespread income risk, and that households adapt their behaviour in order to be protected from this risk, either in the form of self insurance, or of more or less informal risk sharing contracts with other households. Changing patterns in the social contract, notably in the items that play the role of insuring households against risk, quite naturally affect the expected payoffs of households, and hence the intertemporal consumption-saving choices. [START_REF] Pradhan | Insurance Health Impacts on Health and Non-Medical Consumption in a Developing Country[END_REF] recently provided an example of this behaviour, showing that in Vietnam overall consumption was positively affected by the implementation of a public health insurance scheme. This finding is hardly astonishing, as we know from the policy evaluation proposition that a change in policy affects the parameters of the behavioural functions of a model. In a more pedestrian way, a transfer from private to public insurances is equivalent to "forced saving", which implies a reduction in (residual) private hoarding.

As the intertemporal decisions of households affect among other things the distribution of resources between generations, it follows that current spending, notably in social items (education, health, social security), has an important intergenerational content, through its effect on private spending. This content, often neglected, appears to be particularly important in fast growing economies undergoing deep structural change like China.

The Evolution of Social Spending During the Reform Period

The health coverage system put in place in the early 1950s by Maoist China was at the charge of the employment unit of the workers, mainly the State Owned Enterprises (SOE) in cities and the communes in rural areas. Prevention was given a prominent role, and the system was designed to fit within the dual structure of the economy [START_REF] Guan | China's Social Policy: Reform and Development in the Context of Marketization and Globalization[END_REF]).

In urban areas, the two main pillars of health were the Government Insurance Scheme (GIS), which covered current and retired government employees plus selected categories like students, and the Labour Insurance Scheme (LIS), that applied to SOEs. Both schemes were financed by the government, and offered total coverage to the employees (and generous, although not total coverage to their dependents). In rural areas, preventive health action was organized and financed through the Cooperative Medical System (CMS), ran by the collective organizations (communes) and subsidized by the government. The capillary provision of basic health care services, from prevention to cure, was provided through a mass of practitioners with basic training, the so called barefoot doctors. Finally, hospitals were owned and funded by the government. The three-tiered4 organization for the delivery of health care was designed to promote the efficient allocation of health care resources between primary and tertiary care facilities. This system quickly extended health care provision, and provided an efficient framework for patient referral and treatment.

To summarize, through subsidies, direct coverage, and low prices, the system provided near to universal health care. As a consequence of the focus on prevention, and on basic health services, the improvement in general health conditions of the Chinese population was spectacular. The two most cited figures are life expectancy, that almost doubled (rising from 35 to 68 years) between 1950 and 1990, and infant mortality, that fell from 200 to 34 per 1000 live births over the same period (Hesketh and Wei, 1997;Blumenthal and Hsiao, 2005).

The radical transformation of China's society that began in the late 1970s consisted in a de facto privatization of the economy. The main, if not the only focus of the three decades since 1978 has been economic growth. The issue of a fair distribution of resources has been virtually absent, at least until very recently. As soon as the reform period begun, reorganizing the provision of public services' quickly became a priority because they were seen as a source of inefficiency for the economy [START_REF] Guan | China's Social Policy: Reform and Development in the Context of Marketization and Globalization[END_REF]). The dismantlement of the pre-reform welfare system was extremely fast, and in some cases (like health care) there

was no clear substitute. The main innovation introduced in the early 1980s was a strong reduction of central government involvement in the provision of public services, with the idea of freeing resources to be allocated at more productive uses. For what concerns health care, investment by the central government was dramatically reduced, going from around a third of GDP in 1978, to the current level of about 15%. The responsibility for providing and funding health care services was transferred to provincial and local governments, through the receipts of local taxation. To compensate for the reduction of transfers from the central government, the local communities were allowed to raise funds from some services, like sanitary controls and high end medical services. As was easily predictable, local authorities focused on the provision of these services, neglecting prevention and unprofitable basic health care. The main effect of this process of decentralization was a dramatic increase in regional inequality both in income and in public goods provision [START_REF] Kanbur | Fifty Years of Regional Inequality in China: A Journey through Central Planning, Reform, and Openness[END_REF], Qiao, Martinez-Vazquez and Xu (forthcoming), [START_REF] Chou | Explaining China's Regional Health Expenditures Using Lm-Type Unit Root Tests[END_REF]).

The richer regions (mainly the metropolitan areas and the coastal regions) were able to provide a decent level of public services, while the others experienced serious deficiencies in the provision of even the most basic public goods. Zhang and [START_REF] Kanbur | Fifty Years of Regional Inequality in China: A Journey through Central Planning, Reform, and Openness[END_REF] describe at length the huge differences in education and public health levels that stemmed from this inequality. Besides the decentralization of public services' provision and financing, two other specific decisions had an impact on China's health care system. First, the government put in place a system of price regulation with the idea of continuing to provide access to basic health care. The price of routine visits and standard diagnostic tests was strictly regulated, while new drugs and technologies were left unregulated. Furthermore, a system of wage incentives was put in place, linking the remuneration of physicians to the amount of revenues generated for the hospitals. The result was an exponential increase of expensive drugs sales, and high tech services, and once again the neglect of the price regulated basic health care. Second, the dismantlement of the rural communes and the shift from what [START_REF] Guan | China's Social Policy: Reform and Development in the Context of Marketization and Globalization[END_REF] calls public ownership to a multiple-ownership economy, also entailed the disruption of the system of safety nets that had assured basic health services for the mass of inhabitants of rural China. Without the CMS, hundreds of millions of Chinese peasants became uninsured, because of their lack of resources. As recently as 2003, surveys highlighted that 36% and 39% of households in urban and rural households respectively gave up medical treatment because they were unable to afford it. (Markus, 2004;Yu, 2006;[START_REF] Lim | China and the Global Economy: Medium-Term Issues and Options -a Synthesis Report[END_REF]. Unemployed barefoot doctors were forced into the private sector, where in absence of regulation they found it more profitable to sell drugs or to provide high end services (for which they were untrained) than to provide basic health care and prevention.

As a consequence, the price regulation and the dismantlement of the communes had the unintended effect of skyrocketing prices and out-of-pocket expenditures, together with a substantial deterioration of the quality of the service.

Today less than one third of the population has medical insurance, almost 60% of health care expenditures are out-of-pocket, and national spending on health care of all types (including public health) almost doubled from 3.0% to 5.5% of GDP between 1978 and 2002. Furthermore, half of this expenditure goes to drugs, compared with a worldwide average of 15 percent (World Bank, 2004;Meng et al., 2005). Today the number of health care facilities is substantially larger than in the 1970s, but they are substantially less efficient and less accessible than they used to be. The effect of "reforms" on the cost and the quality of China's health care is quite clear: "To many in the United States, this portrait of pockets of medical affluence in the midst of declining financial access and exploding costs and inefficiency will sound depressingly familiar" (Blumenthal and Hsiao, 2005, p.

1168).

The consequence on public health indicators is also striking. All the spectacular improvements experienced until the late 1970s were stopped and sometimes even reversed by the reform [START_REF] Liu | Equity in Health and Health Care: The Chinese Experience[END_REF]). It does not come as a surprise then if at the turn of the century China's overall health system performance ranked only 144 th in a pool of 191 countries, well behind the other Asian emerging giant, India, that has a rank of 112 th (WHO, 2000, Ma andSood, 2008).

To sum up, the spectacular growth performance triggered by the reform period was not matched by a similar improvement in health care provision. The fading insurance role of the government contributed to the widening of inequality which, in turn, made the absence of social spending and collective insurance more problematic; this vicious circle until now has not affected the overall efficiency and the growth performance of the Chinese economy. In the next section we argue that this may not be the case forever, in the light of a number of theoretical and empirical results which show how increasing inequality may in the long run harm growth.

The intergenerational Content of Current Spending

The belief according to which nothing of substance would be lost if growth and fluctuations were studied separately, the former being linked to supply factors (technology, endowments and other "fundamentals"), while the latter depends on demand factors, has for a long period dominated the analysis of business cycles. True, no economist would have admitted that the two phenomena were completely independent, and many have expressed the idea that the building of new capacity today (investment) have long lasting effect on either potential output or growth (cf. i.e. Hahn and Solow). More generally, economists have investigated how many short term phenomena may have long lasting effect like for example unemployment, "false prices" in Hicks' sense, and so on. But the two frameworks

were not really integrated, until the emergence of Real Business Cycles (RBC) theory (initiated by [START_REF] Kydland | Time to Build and Aggregate Fluctuations[END_REF]). What the RBC theory accomplishes is to present a single model able to account for growth and fluctuations. But this effort of construction of a unifying model was realized at the expense of demand factors that are absent from the RBC, which also attribute short run fluctuations to supply factors. Hence whether the dichotomy between growth and fluctuations holds or not, economic policy, and in particular social spending, has at best only short run effects through changes in aggregate demand. This view being obviously debatable, it has been questioned by theoretical and empirical work alike. For example, in a widely known paper, [START_REF] Ramey | Cross-Country Evidence on the Link between Volatility and Growth[END_REF] robustly show using a large sample of countries, that higher aggregate income volatility is associated with lower long term growth. [START_REF] Fatas | Government Size and Automatic Stabilizers: International and Intranational Evidence[END_REF] further document a strong negative correlation between government size and output volatility both for the OECD countries and, even more markedly, across US states. This empirical regularity is shown to correspond to a simple new Keynesian model in which consumers are not perfectly rational [START_REF] Andrés | The Stabilizing Role of Government Size[END_REF]). But it may have other interpretations as well. For example, if we assume the level of corruption not to be overwhelming, a higher level of public spending means the provision of more public goods, including social goods, and stronger automatic stabilizers.

For both reasons -better collective risk insurances, and "built in" stabilization -the volatility of output will be lower5 .

The most straightforward channel through which public spending reduces income variability is the smoothing of income volatility (for a survey, see Creel and Saraceno (forthcoming)). It has to be emphasized that income volatility in developing countries,

where almost by definition the system of social protection is less developed, may have very disruptive effects on social and productive structures. As Amartya Sen has for long documented, in these countries the stability of growth matters much more than the level of growth, as a recession may have irreversible consequences on the destiny of the more vulnerable fraction of the population.

In particular, social spending strengthens the correlation of current spending and current income, and the reduction of precautionary savings. On the other hand, one should also consider the opposite effect, namely that excessive income security distorts the incentives and results in a reduction of labour supply. This argument has been used

extensively in the European debate on fiscal policy. In addition to not being extremely robust,6 the argument can be raised only for developed countries, and has limited relevance for the purpose of this paper. For developing countries, in effect, it exists a vast empirical literature showing that larger social spending increases the level of private consumption and reduces its variability. To quote only two recent contributions, [START_REF] Dehejia | Child Labor: The Role of Financial Development and Income Variability across Countries[END_REF] show that schooling duration increases with parent's income. Similarly, Mangyo (forthcoming) shows that in poor households the food intake of children is directly affected by income increases. Increased provision of health care may also bring about a general improvement of the conditions for the creation of wealth. Recent estimates show a direct impact of household health on income and productivity (Liu et al. (forthcoming)). These empirical results are an indirect proof of the existence of resources' constraints on the poorest households, that can be lifted by social spending thus leading to a more efficient allocation of resources.

Besides its role as an "insurance" against income and consumption fluctuations, especially for poorer households, social spending has a more direct effect. Increasing the collective supply of public goods would free part of the income that is now saved for precaution, and make it available for investment in both physical and human capital. In other words, social spending could "crowd in" private expenditure and raise the economy's current and future growth rate alike while decreasing its volatility.

In a country like China, where income is growing at unprecedented pace, this kind of constrains play a relatively limited role for an increasing number of households, but a very important one for those who are not benefiting from growth, a huge number indeed. Its effect could become even more important when in the future the average growth rate will fatally decrease.

Other mechanisms may also play a role. Higher civil servants' wages would increase the quality of public services that are complementary to private spending in sustaining present and above all future growth. The same holds for expenditure geared to strengthen the legal system, and to set up an effective means to protect property rights.

Furthermore, social mobility ("giving to my children better opportunities than I had") is one of the engines of growth and prosperity. But social mobility is all the more likely if somehow "counters are reset", at least partially, at each generation. One of the roles of social spending is a transfer of resources that helps reducing inequalities of initial conditions for the new generations.

When thinking about some of today's challenges -environment and the use of natural resources, population aging, etc. -we frequently reason as if the welfare levels of future and present generations were substitutes. But if we consider the infinite chain of generations and extrapolate for future ones the relationship existing between two successive generations, say "parents" and "children" we may be led, concerning health, education, income stability and more generally the social protection system, to a quite different hypothesis, complementarity rather than substitutability, which seems to us much more appealing. The hypothesis amount to saying that if the parents care about their children and the latter about their own children etc., there should be, at least for the kind of expenditures we are discussing here, strong complementarity between the welfare of different generations. Current public spending on all levels of education have obviously an intergenerational content. What is almost universally verified is that the consent to pay by the parents for the education of their children is very high. The health of the parents is almost a precondition for that of their children: willingly or not, current spending on health has thus an intergenerational content. The same can be said of a number of public spending items, including those which are aimed at fighting unemployment. To belabour the obvious, the conditions of education are certainly disturbed by the unemployment of the parents. The improvement of housing conditions through public schemes will likely benefit the chain of generations7 .

Besides, there is a domain where the welfare levels of present and future generations may be considered to exhibit an important degree of complementarity, that of social justice.

If social justice is not a sufficient condition of complementarity it is at least a necessary condition. There are two reasons why it is so; the first is more of the order of a conjecture, the second of a constraint. First, in a society where would prevail a pervading feeling of injustice, it seems unlikely that there would be space for intergenerational altruism. It would be hard to assume that intergenerational equity would preoccupy the members of the society in a context where intragenerational equity is not assured. The second reason is related to the state of inequalities. When the latter are large and growing, an important fraction of society has not the means to project itself towards the future, even if it wished to do so. The difficulties of day to day conditions make it prisoner of the present. It is why a well functioning social protection system by giving people a feeling of fairness and allowing them to contemplate the future with less anxiety would benefit the chain of generations.

This section outlined a number of mechanisms through which social spending may not only sustain current activity, and the standard of living of current generations, but also, and more importantly, affect the potential for future growth and benefit future generations.

In the light of this discussion, the next section will describe the recent changes in health policy in China, and conclude on some characteristics that the reformed system should have in light of our analysis.

The Role of Social Spending for Sustainable Growth

The beginning of the years 2000s marked an important change in priorities for the Chinese government. The deepening spatial and sector inequality, both in income and in the provision of public goods, was eventually perceived as a potential cause of excessive imbalances, with possible effects on social stability and overall growth. In October 2002, the first China National Rural Health Conference was held in Beijing, and a set of reforms in the provision of health care was announced. [START_REF] Liu | Providing Health Insurance in Rural China: From Research to Policy[END_REF], [START_REF] Wagstaff | Extending Health Insurance to the Rural Population : An Impact Evaluation of China[END_REF]). The scheme is now in a pilot phase, the coverage of all counties is predicted to be completed by 2008.

The New Cooperative Medical System (NCMS) is based on voluntary adhesion. The unit of the scheme is the county instead than the village, increasing the scale of each unit for better risk pooling and economies of scale in the provision of health care services. To enrol in the program households have to pay a flat 10 reminbi per person and per year contribution, that is matched by public subsidies amounting to up to 40 reminbi for the poorest households (the burden is shared equally by the provincial and the central government). The level of discretion of each county is very high, from coverage to cost sharing, to fees, etc., in observance to the principle of decentralization in health policy introduced with the reform.

A voluntary insurance scheme is confronted to all the typical asymmetric information problems associated with the provision of public goods. These concerns are reinforced by the wide inequalities in income level and in needs in the recipient population, and by the diversity in economic structures among provinces. Even if it is too soon to assess the effectiveness of the new system, an attempt has been made by Wagstaff and Yu (2007), and [START_REF] Wagstaff | Extending Health Insurance to the Rural Population : An Impact Evaluation of China[END_REF]. Their first remark is that the budget of the NCMS is too small to significantly affect households' out-of-pocket spending. The per capita contribution, including the subsidies, is around 20% of total per capita rural health spending; furthermore, the large deductibles, and high coinsurance rates make copayments large. The excessive financial burden that remains on the insured could induce the poor households to avoid enrolling in the scheme, thus letting out of medical coverage the group that is supposed to be the main beneficiary of the program (a finding that is hardly surprising, see also [START_REF] Jalan | Are the Poor Less Well Insured? Evidence on Vulnerability to Income Risk in Rural China[END_REF] and Wang and Rosenman (2007)). By looking at the urban program, [START_REF] Lindelow | Can Insurance Increase Financial Risk ? The Curious Case of Health Insurance in China[END_REF] further argue that, because of the distortions in the pricing mechanism and in the widespread practice of fee-per-service reimbursement, higher end care is more profitable and hence over-provided with respect to basic health services (see also [START_REF] Eggleston | Health Service Delivery in China: A Literature Review[END_REF]). As a consequence, actual spending by households may even end up increasing.

The preliminary assessment of [START_REF] Wagstaff | Extending Health Insurance to the Rural Population : An Impact Evaluation of China[END_REF] at any rate gives mixed results.

On the positive side, the cost remained unchanged in spite of increased utilization of expensive equipment. On the other hand, enrolment by the poor was as expected low, as well as their access to health care. Furthermore, the authors report no evidence of decreases in out-of-pocket expenditure.

As the discussion above suggests, these results are hardly surprising. All the standard asymmetric information problems experienced by insurance schemes for the provisions of public goods are likely to be exacerbated in presence of strong inequalities and high income uncertainty.

This overview of the reform in the health care sector, and of the recent attempts to roll back on some of its more harmful effects, seems to suggest a number of policy conclusions:

1. First, and in general, attention to equality should be paid, in order to obtain income stabilization and provide private households with a less uncertain environment (see also [START_REF] Kuijs | China's Pattern of Growth: Moving to Sustainability and Reducing Inequality[END_REF]). In particular, for the Chinese case, the region/sector inequality seems to be one of the most serious obstacles on the way of continued strong growth.

2. An effective solution to the worsening conditions in health provision seems to be the move towards universal health coverage. Collective insurance seems to be the only way to reduce the huge differences in access to health care. This does not mean that the provision of health services should necessarily be public. In fact, there is no reason to reduce private involvement in this sector, rather the contrary (see [START_REF] Eggleston | Health Service Delivery in China: A Literature Review[END_REF] for pros and cons of the different frameworks). Nevertheless, for a socially sensible public good like health care, appropriate regulation is a priority.

3. The spatial inequality that inevitably accompanied the process of decentralization has been a major cause for increased inequality in income and in social conditions. (Qiao, Martinez-Vazquez and Xu (forthcoming)). This calls for a central management of the health system, and/or for a system of strong interprovincial transfers [START_REF] Chou | Explaining China's Regional Health Expenditures Using Lm-Type Unit Root Tests[END_REF] documents a strong correlation between provincial government deficit and health care provision). In both cases problems of free riding and moral hazard should be appropriately taken into account.

To summarize, it is our belief that a reformed health care sector should be centred around universal coverage to be managed centrally, or at the provincial level. In this latter case, nevertheless, an interprovincial transfer system would be necessary to guarantee financing of the insurance scheme regardless of the income level of the provinces.

Furthermore, very detailed regulation should be designed prior to further involvement of the private sector in the provision of health care services.

The Chinese government has been working for almost two years at a new plan, far more ambitious than the NCMS. As of today (August 2008), the details are not fully known yet, the plan being currently fine-tuned in consultation with the various government agencies involved. But the guidelines were unveiled in December 2007 by the Health Minister Chen Zhu: by 2010 (a date that will probably be pushed forward, given the delays in the finalization of the detailed plan), China will set up a basic medical and health care system to balance the disparity between medical access and quality of services in urban and rural areas, as well as between different regions within the country and for people with different income levels. By 2020, according to the plan, China will have completed the establishment of a public medical and health care services network, a universal coverage medical insurance system, a drug supply system and a medical institution management system. Most of the concerns outlined above would hence be addressed by the plan, which would go in the direction that the present paper envisions.

In particular, two aspects of the plan emerge as new with respect to the current situation.

The first and more important is the commitment to an increased involvement of the central and local government in the health sector; this would take the form of an increase of public spending as a percentage of total health expenditure. Such an effort would initially be addressed to increasing affordability of health care for the poorest households, and in a second moment to improve the quality of service. Increased involvement of the government would also take the form of a more balanced allocation of resources between urban and rural areas, the latter being today strongly underfunded. According to the plan, the government and households should split the cost of basic medical care, but the burden of specialized medical care would still be borne by patients directly or through private insurance.

The second important innovation of the new plan concerns the management of health care facilities, in an effort to change the incentive structure from profits to public health performance. This is the part of the plan that the government has more difficulties in finalizing. The main lines of action are clearer definition of the responsibilities and rewards of public managers, and a disconnection of hospital funding from revenues; the latter should help curb drugs' over-prescription, and excessive prices.

Increased dialogue and engagement with the private sector is announced, but no details are given on whether this will lead to the much needed substantial redesign of the regulatory framework.

Fig

  Fig. 1 -Macro Aggregates as % of GDP

Fig

  Fig. 2 -Household Savings Rates

The communiqué summarizing the results of the survey can be found on the NBS website at http://www.stats.gov.cn/english/newsandcomingevents/t20080109_402457006.htm

http://english.gov.cn/2007-12/26/content_844593.htm

[START_REF] Modigliani | The Chinese Saving Puzzle and the Life-Cycle Hypothesis[END_REF] argue that following the implementation of the one child policy, Chinese households substituted investment in human capital with savings; while somehow exotic, this explanation also points to the essentially precautionary characteristics of today's saving rates.

In urban areas they were the street (sub-district), district and municipal level hospitals, and in rural areas they consisted of village stations, township health centres, and county hospitals.

On this kind of mechanism and other fundamental issues regarding stability, cf . Joseph E. Stiglitz & ali: Stability with Growth, Oxford University Press, The Initiative for Policy Dialogue Series, , 2006

The counterexample of Scandinavian countries shows that the incentive argument has limited validity(Fitoussi and Laurent, 2008).

Many studies have shown that housing conditions play a very important role for the success of children at school, which explains that part of the uneven results of schooling is due to inequalities in between present generations.

A careful assessment of the new plan will have to wait for the details to be made public. From the vague guidelines described above it seems that the burden that the redesigned system will impose to households is still important; nevertheless, the proposed reform plan certainly represents an important step ahead in the direction of providing access to basic health care to all citizens, regardless of their means or of their region of residence.

If the implementation of the plan will proceed as announced, this will contribute to smoothing the current imbalances and to provide sustainable growth in the years to come.

Series, 4150, March Wagstaff, A. and S. Yu (2007)


Guillaume Allègre

Gérard Cornilleau

Jérôme Creel

Ramón Peña

Working poor in the EU: an exploratory comparative analysis 1

Keywords: Poverty, In-work Poverty, Welfare regimes. JEL classification: I3, J38

This article explores the determinants of working poverty in the Europea n Union. At t he individual and household level, the factors contributing to working poverty differ in importance across countries. Nonetheless, being a lone parent, having low education, having a temporary contract, working part-time or less than full-year, appear to be the most important risk factors.

Low pay, under-employment and family structures combine to explain working poverty. At the national level, the correlation between poverty and in-work poverty is strong: countries with low levels of in-work poverty are also the ones which keep overall poverty low. At this level there does not appear to be a dilemma between fighting in-work poverty and overall poverty. The strongest determinant contribution to low in-work poverty is high social spending as a proportion of GDP. The level of spending is more important than the way the spending is done or financed: both the social democratic and the social assurance regimes have good performances in terms of in-work poverty. Women's employment rate, which is generally viewed as being a factor in keeping in-work poverty low, is no more significant when level of social spending is taken into account. This underlines the ambiguous effect of employment on in-work poverty: employment can lift households out of poverty but it can also increase the number of poor workers.

Introduction:

Promoting participation in employment is part of the EU strategy to fight the risk of poverty and social exclusion. Promoting a high level of employment is also at the heart of the Lisbon strategy in order "for the European Union to become the most competitive and dynamic knowledge-based economy in the world capable of sustainable economic growth with more and better jobs and greater social cohesion". The European employment strategy states that labour market policies should be combined with an active inclusion strategy in order to fight poverty. The Council of the European Union recommends a balanced approach in its employment report (Council, 2008): member countries should on one hand make work more attractive than benefits and on the other hand create opportunities for the low-skilled. The integration into the labour market is supposed to increase social inclusion and improve the sustainability of social protection systems.

However, whereas it was assumed in the past that employment was a good protection against poverty, the debate around in-work poverty has increased in recent years. Obviously, working is not always sufficient to escape poverty: particular family structures, less than full-time work and low pay can explain the development of in-work poverty. Since 2003, reducing working poverty has become a priority at the European Union level: the employment guidelines specifically recognized the need to tackle in-work poverty and new indicators were defined in the context of the Open Method of Coordination in order to apprehend the number of working poor and their characteristics (Bardone and Guiot, 2005). These indicators were added in 2003 to the original list of "Laeken indicators" on poverty and social exclusion developed by the European Council in 2001 as part of the Lisbon Strategy.

The measure of in-work poverty combines an individual and a household dimension: among the employed population, the working poor are those who live in a household whose equivalised disposable income is below 60% of the national median equivalised disposable income 2 . The employment status is determined on the basis of their "most frequent activity status". Under this definition an individual is considered employed if he was working at least 15 hours a week for at 2 Equivalised income is defined as the household's total income divided by its equivalent size, in order to take account of its size and composition. Eurostat uses the modified OECD equivalence scale that gives a weight of 1 to the first adult, 0.5 to other household members aged 14 years and over, and 0.3 to children below 14. least 7 months of the year3 . This concept is different from the active poor (which include the unemployed population) and the low-wage workers concepts. A worker can be considered as low-wage but not poor or conversely poor but not low-wage (if for example he is the only wage earner in a family with a lot of dependents). According to this definition, in-work poor represented 8% of the employed population in the European Union in 2006. People in employment are less at risk of poverty than the general population: 15% of the EU population was poor in 2006; the risk of poverty stood at 41% for the unemployed and 16% for the retired population. The working poor nonetheless represent around a quarter of the poor population aged 16 and over and therefore should be an important policy concern. This article will explore the determinants of working poverty in the European Union. Existing studies focus on individual and household characteristics to explain working poverty at the household level. Comparative studies that relate working poverty with welfare regimes are rare.

We aim in this article to identify relationships between welfare regimes and working poverty. We try to answer the following questions: what are the determinants of low working poverty at the country level? Which welfare regimes tackle working poverty best? What are the common characteristics of countries with low proportion of working poor?

In a first section, we will examine which individual and household characteristics lead to working poverty in the EU member states. Section 2 deals with characteristics at the country level: which are associated with high and low levels of working poverty? Section 3 explores the relationships between welfare regimes and working poverty.

Data:

This study is based on the latest ( 2006 (over 16 and under 65). For more information concerning the data source, see Eurostat (2007Eurostat ( , 2008)). EU-15 refers to the 15 member states before the 2004 expansion, EU-25 to the 25 member states before the 2007 enlargement; the coverage of this study will be referred as EU25+ (EU-25 + Iceland and Norway).

Incidence of in-work poverty risk and factors contributing to working poverty

The European Union is not a homogeneous economic area: not surprisingly, the risk of in-work poverty differs greatly across member states (Figure 1). It stands at 8% in the European Union but is lowest in the Czech Republic (3%), Belgium, Denmark, the Netherlands and Finland (4%).

These countries, which are successful in keeping in-work poverty low, will be referred in this study, for practical purpose, as the "successful countries". In contrast, Greece (14%), Poland (13%) and Portugal (11%) are the countries where the risk of working poverty is the highest.

[Figure 1 here] Working poverty combines and individual and a household characteristic: it is therefore necessary to take both an individual and a household perspective when analysing the factors that increase the risk of being poor while working. Table 1 presents the risk of in-work poverty risk by main characteristics of the employed population. The characteristics are divided in three categories reflecting the different dimensions of working poverty: personal, job and household characteristics.

[Table 1 here] In the European Union as a whole, low education, having a temporary contract, working parttime or less than full-year, being a lone parent are important risk factors. Conversely, sex and age do not seem to be important risk factors. There are risk factors in the three dimensions of working poverty (personal, job and household): low pay, under-employment and family structures combine to explain working poverty. Lone parents are particularly vulnerable to in-work poverty: 17% of lone parents who work are poor in the EU-25. Household characteristics are therefore a key risk factor of working poverty. Bardone and Guio show that in 2001 sole earners with children in 2 adults or more households were even more vulnerable to working poverty: 20% of sole earners with children in the EU-15 were working poor against 19% of lone parents. The authors conclude that "the most important risk factors of in-work poverty relate to the household situation of workers".

The factors contributing to working poverty differ in importance across the European countries.

Gender is a more important factor in Italy, Greece, Spain, Malta and Poland than in other countries: in these countries, in-work poverty risk for men is higher than for women by at least three points. Greece, Italy and Spain are also the countries where the employment gap between men and women is highest: respectively 29.5%, 27.9% and 23.9%. If employed women are less likely than employed men to be poor, it is probably because women at risk of poverty (low qualification, high number of dependents) are less likely to work. In Nordic countries (Denmark, Sweden, Finland and Norway), younger workers are sensibly more vulnerable than other workers. This is probably due to specific living arrangements of young people in Nordic countries where they are more likely to leave their parental home early. However, if the data underestimates family financial support of children living separately, then poverty of young people will be overestimated in countries where co-residence with parents is low. Similarly, the standard of living of families helping children living separately might be overestimated4 . In Greece and Portugal, it is the eldest workers who are the most at risk. Education is important in every country but more particularly in the least developed European countries: Greece, Portugal and most Eastern European countries. Job characteristics are also important in every country. The differences between countries are not as marked. Having children make singles more vulnerable to "in-work" poverty except in Denmark and Finland. Similarly couples with children are more at risk than the overall population except in Germany, Sweden and Norway.

Table 2 presents the risk of in-work poverty and the share of in-work poor by household type. Inwork poverty does not have the same face across European countries: it results from very different living arrangements. The share of single adults with no children in the working poor population is much more important in the Nordic countries (Denmark, Finland, Norway, Sweden) and Germany than in other countries: they account for more than 30% of the working poor in these five countries (41% in Denmark) against 15% in the EU25. This type of household represents a higher share of working poverty in these five countries because the poverty risk differential relative to other households is higher but also because they represent a higher share of the population: 22% of the population live in single adult households in Denmark, 20% in Norway and Sweden, and 18% in Finland and Germany against 13% in the EU25. If single parents face higher risk of in-work poverty in all countries, their share in the working poor population differ mainly because their weight in the overall population vary from country to country: they represent only a very small part of the population in Greece, Spain (2%), Italy, Portugal, and Slovenia (3%), but a much higher in Ireland, the United Kingdom, Sweden and Iceland (8%). Consequently, their weight in the working poor population is more than twice the EU25 average (11%) in Ireland, Iceland and Sweden as well as in Estonia where their in-work poverty risk is particularly high. More than half (53%) of the working poor in the European Union belong to households with 2 or more adults and dependent children. This proportion is especially high in Malta (81%), Poland (74%), Slovakia (70%) and Spain (67%).

[Table 2 here] Part-time employees are more vulnerable to in-work poverty in all European countries except Belgium where their poverty risk is equally low (4%) than for the overall employed population (Table 3). There are wide differences between European countries in the way part-time employment and in-work poverty inter-relates. In most eastern European countries part-time employment is much lower than the EU25 average (19%): even though their risk of in-work poverty is higher, the share of working poor working part-time is relatively low. It is, to a lesser extent, also the case of southern European countries. Conversely, part-time employment is a more important concern in the United Kingdom: in-work poverty risk is 50% higher than national average for part-time employees who also represent a higher share of employment (26%) than on average in the EU25 (19%). Consequently, part time employees account for 45% of in-work poor in the UK against 27% in the EU25.

[Table 3 here] The working poor concept differs from the low-wage concept: while working poor combines both an individual and a household dimension, low wage is intrinsically individual. According to Eurostat's definition, a low-wage employee is an employee working at least 15 hours a week whose wage is below 60% of the national median monthly wages. If all households were composed only of employed workers earning the same wages then every low pay employees would be poor and every poor would be low pay. Table 4a&b show how the concepts were intertwined in 1996. Table 4a shows the proportion of working poor and low pay employees as % of all employees, the proportion of working poor among low-pay employees and the proportion of low-pay employees among working poor for EU-15 countries less Sweden and Finland. In table 4b, the employees are divided in 4 categories depending on their low-pay and working poor status. In the studied countries, 20% of low-wage employees were poor and 37% of working poor were low-wage. Being low-wage is therefore an important contributing factor to inwork poverty but not a decisive one. We calculated odds ratio (table 4b) as a measure of the interdependence of the two notions: an odds ratio of 1 means independence and the greater the odds ratio the stronger the relationship between the two groups. Among the studied countries, it is in Greece and France that the notions of low wage and working poor are the most related: the relative risk of being working poor among the low-wage compared to the non low-wage is the greatest in these two countries. Conversely, it is in the Netherlands and Spain where the relationship between the two notions is the weakest. Ireland and the UK are also below average whereas Belgium, Austria, Germany and Portugal are above average.

Although contributing factors have different intensity depending on the studied country, in-work poverty always has the same sources: particular family structures, low-wage, part-time and unstable jobs. This is not surprising considering the definition of in-work poverty (a working individual in a poor household): everything else being equal, what makes the household poorer (less work and pay, more dependents) will increase the risk of in-work poverty.

[Table 4a andb here] 2. Working poor in the European Union: a comparative analysis perspective.

Which characteristics are related to working poverty at the national level? Before an analysis in terms of welfare regimes (section 3), we look at the institutional variables that are linked with inwork poverty.

Figure 2 shows the correlation between poverty (at a 60% level) and working poverty. The correlation is positive and rather strong (R 2 =0.53): working poverty is highest in countries with high poverty. At this level, there does not seem to be a dilemma -or tension -between fighting poverty in general and fighting in-work poverty. On the contrary, countries which do well in fighting poverty (the Czech Republic, the Netherlands) do also well in keeping in-work poverty low. Countries below the regression line do comparatively better against in-work poverty than poverty in general: this is the case of Belgium and Romania and, to a lesser extent, Ireland, Finland, Denmark and the Czech Republic. Figure 3 shows the relationship between the poverty rate before social transfers (pensions excluded) and in-work poverty risk: the two variables are not correlated (R 2 =0.003). This means that the correlation between poverty and working poverty is the consequence of social transfers: social transfers that are effective in fighting poverty are also effective in fighting in-work poverty; the hypothesis that there is no dilemma between the two public policy goals is confirmed by this data in the European Union context. Of course, when designing specific public policies to fight poverty, policy makers might have to choose between instruments that are more effective in fighting either working poverty or poverty in general. However, the countries that reduce poverty by social transfers the most are also the ones with the lowest risk of in-work poverty. Figure 4 shows the relationship between in-work poverty risk and the percentage reduction of poverty by social transfers: the correlation is strong (R 2 = 0.45).

[Figure 2, 3 and 4 here] How does social spending reduce in-work poverty? Figure 5 graphs the relationship between social spending (excluding pensions) and in-work poverty. There is a relatively strong correlation (R 2 = 0.25): the countries which spend most on social budgets (sickness, invalidity, unemployment, family, housing, social exclusion) are also the ones with the lowest risk of inwork poverty. Among the successful countries, the Czech Republic stands out: in-work poverty is the lowest in the EU25+ whereas its social spending is below average. Amongst the country with high in-work poverty, Greece and Poland have poor results relative to their level of spending. The Baltic countries have low social spending and high in-work poverty.

[Figure 5 here] There is a relatively strong correlation (R 2 =0.23) between the employment rate for women and in-work poverty (Figure 6). This relationship was emphasized by [START_REF] Cazenave | Onze millions de travailleurs pauvres en Europe[END_REF]. In theory, high employment has an ambiguous effect on working poverty risk. On the one hand, the highest the work intensity at the household level, the lowest the risk of in-work poverty5 , but on the other hand, reducing the employment of people with high poverty risk might lower the risk of in-work poverty. This might explain why the correlation between working poverty and men's employment is weaker than the one between working poverty and women's employment (Figure 7). Since men are more likely to work than women, non-employment of men in couples is much less likely to result in in-work poverty of their spouse (because they are less likely to work) than non-employment of women. Belgium and the Czech Republic on the one hand and Poland and Greece on the other hand stand out; the first two because of lower working poverty than predicted by the regression while the later have higher working poverty rates. The figure also reveals two clusters of countries each with a geographical intruder: on the successful hand, the Nordic countries (Sweden, Norway, Denmark and Finland) and the Netherlands; and on the other hand the Mediterranean countries (Spain, Italy and Greece) and Poland. Western and Eastern continental countries and the Anglo-Saxon islands stand in the middle.

[Figure 6 & 7 here] In theory, high unemployment is ambiguous regarding working poverty: if compensation is low, it increases the risk of poverty of the household but if unemployment is long, the concerned worker is not considered employed and is therefore not included in the working poor population.

As expected, unemployment rates do not seem to be a good explainer of working poverty (Figure 8): when the outliers are excluded (Greece, Poland), the correlation disappears. Some successful countries have low unemployment (The Netherlands, Denmark) while other have average unemployment (Finland, Belgium). Germany which has the second highest unemployment rate among the studied countries is relatively successful in keeping in-work poverty low.

[Figure 8 here] A high minimum wage should lower risk of in-work poverty in two ways: not only does it reduce wage disparity of low income workers but it also could exclude workers with the lowest productivity from the labour market. On the other hand, by excluding some workers from the labour market, it can also increase the risk of poverty and in-work poverty of other members of their household. Figure 9 shows a negative correlation between in-work poverty and the level of minimum wage relative to average wage. However, the correlation is relatively weak (R 2 =0.10).

Greece, the Czech Republic and Belgium are the outliers.

[Figure 9 here] What other labour market institutions are related to in-work poverty? Figure 10 draws the correlation between average weekly hours and in-work poverty. Employees from countries with high rates of in-work poverty tend to work on average longer weekly hours. However, Figure 10 also shows very dissimilar average weekly hours worked among countries that are successful in keeping in-work poverty low: on one hand, in the Netherlands employees average very low weekly hours (due to the prevalence of part-time work among women); on the other hand, working hours are high in the Czech Republic and Finland whereas Belgium and Denmark stand in-between. This shows that there are different successful strategies in order to keep in-work poverty low. It appears here that there is also a Dutch specificity (employment rates for women already showed that there was a Belgian and a Czech specificity). Figure 11 looks at another dimension of labour market institutions: employment protection. We use the employment protection legislation index elaborated by the OECD. This index is calculated along 18 basic items which summarizes for each country the strictness of regulation for regular contracts, temporary contracts and collective dismissals. Strict employment protection is supposed to lead to segmentation in the labour market between insiders with protected jobs and outsiders with fixed-term, part-time or temporary contracts: this can have an effect on the risk of workingpoverty. On Figure 11, we see that there is a weak correlation between strictness of employment protection and in-work poverty: the correlation is due to the southern European countries which cumulate high employment protection and high in-work poverty. Without Spain, Greece and Portugal, the correlation would actually be reversed.

[Figure 10 &11 here]

In Figure 12, we look at the relationship between the average size of households and in-work poverty. We saw in section 1 that that the presence of dependents increased the risk of working poverty. The size of households is an imperfect measure of the number of dependents: it also takes into account the proportion of adults living alone. This should have an opposite effect on inwork poverty since adults living alone have a greater probability of being working poor, especially if there are children. Figure 11 shows a positive correlation between size of households and in-work poverty (R 2 =0.19). Nordic countries and Germany have both small households and low-in work poverty.

[Figure 12 here] Obviously, many of the variables that are related to in-work poverty are also inter-related. Table 4 presents least squares estimation of in-work poverty risk for the EU25+ countries, weighted by population size. High social spending (excluding pensions) as a percentage of GDP appears to be a robust predictor of low working poverty. This variable is highly correlated to working poverty even when we include poverty rate in the equation (eq. 2): it not only explains low working poverty but also the better performances regarding low-working poverty relative to the ones regarding poverty. Women's rate of employment is no longer significant when high social spending (excluding pensions) is added to the equation (eq. 4): countries with higher women's rate of employment are also the ones with higher social spending and the latter variable seems to better explain low working poverty. This is coherent with the theoretically ambiguous effect of employment on in-work poverty risk. Average size of households is the only variable that remains significant when social spending is taken into account (eq. 5 & 6). The household situation of workers seems crucial to understanding working poverty. However, interpretation in terms of causality is not simple because living arrangements are also a consequence of poverty risk: if the risk of poverty increases with the number of dependents, it is also true that the risk of poverty might increase the number of dependents.

[Table 4 here]

Working poverty and welfare state regimes

From the analysis in section 1 and 2, we see that working poverty is a result of interactions between three sets of institutions: labour market, household structures and social protection.

Labour market institutions determine employment and wages; household structures, the number of dependents active adult support; and social protection, the level of social transfers received by households. These institutions interact: living arrangements are not just the result of a social norm; they are also altered by social protection and labour market institutions. Young people will leave their parental home earlier if they can benefit from housing allowances, if student allowances and loans are generous, and if youth unemployment is low. Older people will be cared by their family when retirement benefits are low. Women's employment and divorce might also be related: women's employment lowers the economic cost of divorce and give women resources to leave unsatisfactory marriages. These resources can also be allocated by social protection.

Labour market and social protection interactions result in varying financial incentives to work: generous social protection might lower incentives to work, especially for the less productive workers or the ones for which working is the costlier (for example women because they have to care for children or parents). Social protection instruments can be specifically targeted to working poor and/or low pay workers in order to increase their standard of living and/or increase financial incentives to work. Theoretically, these instruments have an ambiguous effect on in-work poverty: by increasing the standard of living of low pay workers, they reduce their risk of poverty but by increasing financial incentives to work of low qualified workers, these transfers can increase work in poor household and hence in-work poverty (but not overall poverty).

In this section, we look at the relationships between welfare state regimes and working poverty.

The literature on welfare state regimes is vast and expanding since Esping-Andersen's seminal book, The three worlds of welfare capitalism (1990). Most of the literature consists of classifications of welfare states. State welfare is complex and a classification is necessary to reduce complexity for comparative purposes. Welfare States provisions are numerous and intertwined: it is therefore nearly impossible to uncover a causal relationship between a specific welfare state provisions and policy relevant outcomes.

Which welfare regimes tackle working poverty best? The answer to this question might depend on which classification of welfare state regimes we choose. Given the complexity of the procedure, most classifications are only concerned with a limited number of countries, mostly OECD countries. We therefore try to expand the traditional classifications in order to include all the studied countries.

Living arrangements

Separations

Work incentives

Esping-Andersen's classification of welfare state regimes is based on a decommodification index.

The author defines decommodification as 'the degree to which individuals or families can uphold a socially acceptable standard of living independently of market participation" (Esping- [START_REF] Esping-Andersen | The three worlds of welfare capitalism[END_REF]. The level of decommodification depends on the eligibility rules of welfare state instruments (the more universal, the more decommodified), on the level of income replacement and on the range of social risks covered (unemployment, disability, sickness and old age). The decommodification concept takes into account both a quantitative and a qualitative dimension of welfare state provisions. Table 5 shows Esping-Andersen classification of our countries of interest. Out of the five successful countries we defined, three belong to the social democratic cluster (Finland, Denmark, and the Netherlands) and one to the social assurance cluster (Belgium); the Czech Republic welfare regime was not analysed by Esping-Andersen. However, the decommodification index calculated by Esping-Andersen does not seem to be a good explainer of working poverty levels: in-work poverty risk is lower in Ireland, the European country with the lowest decommodification index score, than in Sweden, which enjoys the highest score. The decommodification index scores from 1990 should be updated before drawing definitive conclusions but welfare state reforms are slow and rank order of countries would probably not be much different today than in 1990.

[Table 5 here]

Along the line of the literature following Esping-Andersen's classification, Peña-Casas and Latta (2004) identify four types of welfare regimes in the European Union: liberal (Ireland, UK), social assurance (Austria, Belgium, France, Germany and Luxembourg), social democratic (Denmark, Finland, the Netherlands, Norway and Sweden and Mediterranean (Greece, Italy, Portugal and Spain). The authors find a clear difference between the Mediterranean welfare cluster, which has a proportion of working poor of 12%, with the three other clusters where the proportion is more of less at the same level, twice as low as in the Mediterranean cluster (around 6%). If there is clearly a "bad" model in terms of working poverty, the distinction between the three other clusters is more difficult when we look at the working poor dimension. However, the authors also show that proportion of unemployed poor is much lower in the social democratic cluster: the social democratic welfare state copes better with active poverty (employed and unemployed) than the other clusters.

Giuliano Bonoli (1997) points to a limit of Esping-Andersen's approach: the later projects elements of two dimensions, which Bonoli classifies as "how much" and "how", on one single dimension (decommodification). Boloni argues that Esping-Andersen's classification is therefore based essentially on the quantity of welfare provided by welfare states and does not discriminate between the ways this welfare is provided. The author proposes his own two-dimension classification of European Welfare States. He classifies the welfare states according to the quantity of welfare they provide and to where they stand on the Beveridge versus Bismarck dimension. Bismarkian social policies are based on social insurance: the benefits are earningsrelated; entitlement is conditional upon contributions which are the base for financing. In Beveridgean social policies, entitlement is universal, benefits are typically flat rate and financing is usually based on general taxation. The author uses two indicators to capture these two dimensions: social expenditure as a proportion of GDP and the proportion of contributionfinancing in total social expenditure. He identifies four ideal-types of welfare state (Table 6).

Successful countries in fighting in-work poverty are recruited in high spending/Beveridgean and in high spending/Bismarkian regimes: the level of spending seems more important than the way the spending is done. This is confirmed by Figure 13 which plots the relationship between the proportion of contribution-based financing and working poverty in the EU25+: there appears to be no correlation. In Figure 14 regimes but we just saw that in-work poverty is not correlated to the proportion of contributionbased financing, so the difference is probably not robust to changing thresholds.

[Figure 13 & 14 here]

Conclusion

It appears from this study that if countries with different welfare regimes are successful in keeping the proportion of working poor low, high social spending as a proportion of GDP is the main factor contributing to low in-work-poverty. Table 6 summarizes the individual, job, household and national factors contributing to in-work poverty.

In terms of welfare regimes, the following conclusions can be drawn: the Mediterranean regime, with low social spending, low employment and large households has bad performances in terms of working poverty. The liberal regime, with average social spending has average performance.

The social democratic regime with high social spending and small households has good performances except, relatively, for Sweden. The social assurance regime has both high social spending and good performances. Overall, the level of spending seems more important than the way the spending is done or financed.

The correlation between poverty and working poverty is strong: countries with low levels of inwork poverty are also the ones which keep general poverty low. Women's employment rate, which is generally viewed as being a factor in keeping in-work poverty low, is no more significant when level of social spending is taken into account. Unemployment rate (in %)

In-work poverty (in %)

Excuding gr and pl : R

  ) Eurostat data, unless otherwise mentioned. Eurostat launched EU-SILC (Community Statistics on Income and Living Conditions), an EU wide survey, in 2003 in order to collect harmonized data concerning Income and Living Conditions in the EU and calculate the so-called "Laeken" Indicators of Social Inclusion. The EU member states plus Iceland, Norway, Switzerland and Turkey participate in this program. Bulgaria, Romania, Turkey and Switzerland have launched SILC in 2006 but data for these countries are not available yet. We therefore use data from 27 countries: the 25 EU member states in 2006 plus Iceland and Norway. EU-SILC operates under a framework regulation of the Council and the Parliament and a series of Commission implementing regulations. Data concerning labour market conditions are based on the results of the European Labour Force Survey (EU LFS). In-work poverty measures concern the population in working age

Figure 2 :

 2 Figure 2: Poverty and in-work poverty in the EU-25+

Figure 4 :

 4 Figure 4: Poverty reduction by social transfers and in-work poverty in the EU-25+

Figure 6 :

 6 Figure 6: Rate of employment for women (15-64) and in-work poverty in the EU-25+

Figure 7 :

 7 Figure 7: Rate of employment for men (15-64) and in-work poverty in the EU-25+

Figure 8 :

 8 Figure 8: Unemployment rates and in-work poverty in the EU-25+

Figure 9 :

 9 Figure 9: Minimum wage as a % of average wage and working poverty

Figure

  Figure 11: employment protection and in-work poverty in the EU

Figure 13 :

 13 Figure 13: Percentage of contribution-based financing and in-work poverty risk, EU25+

Risk of poverty for employed individuals by country, 2006

  The Czech Republic which has relatively low social spending is nevertheless a successful country in keeping in-work poverty low. According to Eurostat data, it actually enjoys the lowest risk of in-work poverty in the EU25+. This Czech mystery should be investigated 6 . Among the successful countries, Belgium enjoys the best performance relative to its overall poverty level. It is also, with the Czech Republic, the country with the lowest employment rates for men and for women. A successful strategy in keeping in-work poverty low might consist in excluding the lower productivity workers from the labour market. More analysis is needed to test this hypothesis. There are several alternative strategies in fighting in-work poverty. It therefore seems relevant to carry out in-depth analysis of successful countries. The Czech Republic model which has very low in-work poverty level relative to its level of social spending and the Belgium model which has the best performance relative to its general poverty level need further attention.

	lv: Latvia
	lt: Lithuania
	lu: Luxembourg
	hu: Hungary
	mt: Malta
	nl: The Netherlands
	at: Austria
	pl: Poland
	Figure 1: In %
	16
	14
	12
	10
	8
	6
	4
	2
	0
	EU	EU	be cz dk de ee ie	gr es	fr	it	cy	lv	lt	lu hu mt nl	at	pl	pt	si sk	fi	se uk is no
	25	15
	Source: Eurostat
		b e : B e l g i u m							p t : P o r t u g a l
		cz: The Czech Republic							si: Slovenia
		dk: Denmark							sk: Slovakia
		ee: Estonia							fi: Finland
		ie: Ireland							se: Sweden
		gr: Greece							uk: United Kingdom
		es: Spain							is: Iceland
		f r : F r a n c e							n o : N o r w a y
		it: Italy
		cy: Cyprus

Table 1 : In-work poverty risk by main characteristics of the employed population, 2006

 1

	In %

Table : In-work poverty risk and share of in-work poor by household type

 :

Source: Eurostat, 2006 ; author's calculation

Table 3 : in-work poverty risk and share of working poor of part-time employees

 3

	En %

Table 4a & b: Low wage workers and working poor in the European Union, 1996

 4a

Source:

Eurostat (2000)

Source: Eurostat (

2000

), author's calculations.

Table 5 : Least squares estimation of in-work poverty risk, EU25+, weighted by population

 5

Standard errors in parenthesis *** Significant at the 1% level; ** significant at the 5% level; * significant at the 10% level

See Peña-Casas and Latta (2004), Chapter 1, for a discussion on the difficulties relating to the definition of the working poor

Since poverty is measured at the household level, it is assumed that solidarity is total among member of the same household. Conversely, it is likely that parental financial transfers are underreported in living condition surveys such as EU-SILC. The differences in terms of standard of living and poverty levels that are the consequences of living arrangements of young people are therefore partly statistical constructions.

This holds true everything else being equal but if high employment is attained through a lowering of job quality (number of hours, low pay…), a higher work intensity might not result in lower poverty risk.

The question regarding the reliability of the data provided by Eurostat should also be considered.

=0.0018Source: Eurostat