Francisco Javier De Miguel

Antonio Manresa

Francisco Javier

Removal of farm subsidies in a regional economy: a computable general equilibrium analysis

Keywords:

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Removal of farm subsidies in a regional economy: a computable general equilibrium analysis

Introduction

One of the features characterizing the economy of Extremadura -an Objective 1 Region of the European Union (EU) located in SW Spain-is the major weight that farming activities have in its production structure. Their relative share in terms of total value added (12.6%) or employment (24%) is far greater than is the case for the Spanish economy as a whole (4.9% and 10.9%, respectively) 2 .

Clearly related to this fact is the enormous significance of the farm subsidies received by the agriculture sector in Extremadura. For example, the proportions of the value added of this sector and of the regional GDP represented by these subsidies are close to 18% and 2.5%, respectively. Apart from being large income injections for this sector, farm subsidies play an important role in fixing the population in rural areas and avoiding population movements towards urban zones 3 .

The principal objective of the present work is to study the dependence of the Extremadura economy on these farm subsidies. A straightforward way of quantifying this dependence is to simulate the removal of these grants and to determine the effects of this scenario. Furthermore, since farm subsidies are financed by the EU, a simulation of this nature would allow one to approximate the current real scenario which is characterized by the enlargement of the EU to 25 member states, which could well involve a reduction in the subsidies received by the Extremadura agriculture.

As a second exercise, we consider the maintenance of these farm subsidies, but its payment is taken over by the Regional Government -not EU, financing it by a 2 These percentages and the subsequent for subsidies are computed considering data for 1990. As it is noted below, statistical limitations are the reason for taking this year as reference for the analysis. More recent data again show a marked importance of the agriculture sector and farm subsidies in this region. 3 These effects are, however, excluded from the subsequent analysis. For the incorporation of effects deriving from population shifts, see, for example, Kehoe and Noyola (1991). 3 linear increase in the income tax rates. The aim of this second simulation is to illustrate an alternative possible economic policy that could mitigate the distortions caused by the removal of subsidies.

These two simulations produce changes that affect all economic sectors and agents in a significant way. It therefore seems necessary to use an analytical framework that includes all the inter-relationships and dependencies involved in the economy. In particular, we use a computable general equilibrium (CGE) model, with a level of disaggregation sufficient to allow the effects on individual agents and sectors to be captured, thereby going beyond the scope of aggregatetype macroeconomic models 4 .

The results of the first simulation clearly show the major negative effects that a hypothetical suppression of farm subsidies would have. For instance, a deterioration of economic activity is apparent in reduced sectoral activity levels, in increases in most of the prices considered, and in generalized welfare loses that are particularly marked for the higher income household groups.

The results of the second exercise, which include fiscal compensation via income tax, are different, especially in regard to the behaviour of prices. While there are greater welfare losses for the higher income households, the distortions in economic activity in this case are less than in the initial simulation.

The work is structured as follows. Section 2 describes in detail the model constructed for Extremadura. Section 3 gives a brief presentation of the social accounting matrix from which the model parameters are obtained. Section 4 analyzes the results of the two simulations. Finally, Section 5 presents the principal conclusions. 4 Different regional CGE models have been applied to agricultural economic issues; see Partridge and Rickman (1998). On the other hand, various topics related to the Common Agricultural Policy have been analysed by means of CGE modelling; see, for example, Philippidis and Hubbard (2001), van Meijl and van Tongeren (2002), and Lips and Rieder (2005).

The model

The computable general equilibrium model constructed for the Extremadura economy -henceforth, CGEM-EXT-consists of a set of equations that reflect the equilibrium conditions and behaviour of the different agents, which in general terms are considered to be producers, households, the public sector, and the foreign sector.

With respect to the level of disaggregation, the model distinguishes 10 production sectors, 9 commodities, and 11 household groups (Figure 1). With respect to the government, it incorporates a broad disaggregation of taxation and transfers.

Finally, three foreign sectors are considered, corresponding to the rest of Spain (RS), European Community (EC), and rest of the world (RW).

[FIGURE 1]

Producers

The model assumes that each of the ten production sectors obtains a homogeneous product as output, employing a technology represented by a nested production function. At the first nesting level, the total production of each sector (Q j ) is obtained as a Cobb-Douglas aggregate of the domestic output (Qd j ) and the three external supplies, i.e., the imports from the three foreign sectors (Qrs j , Qec j and Qrw j ) 5 . In the second nesting level, the domestic production is obtained with a fixed coefficients technology between intermediate inputs (X ij ) and value added (VA j ). Lastly, in the third level, the value added is obtained using a Cobb-Douglas technology to combine the primary factors capital (K j ) and labour (L j ). The Qd j = min { X 1j /a 1j , X 2j /a 2j , ... , X 10j /a 10j , VA j /v j } (2)

VA j = j K j j L j 1 -j j = 1,2,...,10 (3)
In these equations Aj and j are scale parameters; d j , rs j , ec j and rw j are parameters that reflect the shares of domestic and imported production in the total production, normalized to sum to unity; the parameters a zj indicate the minimum amount of z needed to obtain a unit of j; v j is a parameter reflecting the value added technical coefficient; and j and (1j ) are parameters representing the shares of the primary factors capital and labour with respect to the value added.

Finally, firms obtain their demands for inputs and supplies of outputs by maximising profits under these technological constraints.

Households

The utility function used for the different household groups is again a nested function, with two nesting levels in this case. In the first level, the utility is given as a CES function between an aggregate of consumption (Cag f ) and savings (S f ).

In the second level, the consumption aggregate is a new CES function defined over the 9 categories of commodities. The expressions used are:

U f = [ c f Cag f f + (1-c f ) S f f ] 1/ f (4) Cag f = [ 1f C 1f f + 2f C 2f f + ... + 9f C 9f f ] 1/ f f = 1,2,...,11 (5)
In these equations, c f and hf represent the respective distribution parameters of the first and second CES functions; f and f are the substitution parameters; and

C hf represents the consumption of commodity h by household group f. The budget constraint on each household group can be expressed as:

f h f i hf h h h YD S p C vat ts p = + + + 1 ) 1 )( 1 ( f = 1,2,...,11 (6)
The sum on the left-hand side reflects the expenditure in final consumption. In the CGEM-EXT, taxes on consumption were incorporated as duty on alcoholic beverages and tobacco -at a tax rate ts h for commodity h-and value added tax -at an effective rate of vat h . The expression also includes private saving, which is valued in the model at the same price than savings/investment, p i .

The right-hand side of inequality (6) represents disposable income, YD f . For most households, this income comes basically from selling their capital (K f ) and labour (L f ) endowments at the prices r and w, respectively 6 . In addition, the households receive transfers from the public sector (TPS f ), including unemployment benefits and pension payments 7 . They also receive net transfers from the foreign sectors (TFS f ). Finally, the disposable income is given by deducting the employers´ social contributions and income tax, whose rates are esc f and f , respectively.

The resulting equation for the disposable income of household group f is:

YD f = (1-f )[r K f + w L f (1-u) + TPS f + TFS f -esc f w L f (1-u)] (7)
As usual, each consumer derives the consumption demands by maximising his utility function subject to his budget constraint.

Government

On the one hand, the government produces public services, using the technology of the production sector j 10 . On the other, it demands public services (public 6 As will be described in detail below, the model includes the possibility that not all the labour factor is employed. In this sense, u is an endogenous variable of the model that reflects the unemployment rate.

U G = min {C G j10 , G • C G i } (8)
where G is an economic policy parameter representing a fixed proportion between the two.

The budget constraint on the government can be expressed in the following form:

= + + 11 1 10 10 f f G i i G G i i G j j TPS w p R C p C p (9)
The left-hand side of this expression represents this agent's expenditure in public consumption and investment. The right-hand side includes the total tax revenue (R G ), from which are deducted the transfers paid to the 11 household groups. w i G represents public debt or bond issues made by the government to cover budget deficits, that can be purchased by other agents at the same price as savings/investment, p i .

With respect to the tax revenue R G , the model incorporates the employees' social contributions and the income tax as direct taxation. As indirect taxation, it includes taxes on alcoholic beverages and tobacco, value added tax, employers' social contributions, import duty, and net taxes on production -taxation minus subsidies. For the latter, the model takes farm subsidies to be financed, not by the Regional Government, but by the European Community foreign sector via income transfer. The simulations proposed in next section 4 are precisely focu sed on these farm subsidies.

unemployment rate. Pension payments are indexed to the consumption price index (cpi).

Foreign sector

As was noted above, the model distinguishes three foreign sectors: rest of Spain (RS), European Community (EC), and rest of the world (RW). The treatment of these sectors is straightforward. Each one produces a different commerce good, using as inputs the exports from the Extremadura economy based on a fixed coefficients technology. As a consequence of this activity, and also considering transfers to the domestic agents, our economy can undergo into deficit with respect to the foreign sectors. These deficits must be materialized in savings of these foreign sectors in order to achieve macroeconomic equilibrium between savings and investment 8 .

Labour market

The model allows for the rigidities in the labour market, so that in equilibrium the unemployment rate may be positive 9 . In particular, we consider that workers offer the labour factor at a real wage rate that depends on the unemployment rate, but the adjustment is not enough to clear the labour market. This relationship between real wage and unemployment rate is expressed by the following equation:

d u u cpi w 1 0 1 1 = (10)
where (w/cpi) represents the real wage rate in the economy; u is the unemployment rate; u 0 is a parameter representing the unemployment rate at the initial equilibrium; and d is a parameter that represents the sensitivity of the real wage rate with respect to the unemployment rate. 8 The model constructed for the Extremadura economy is static. In this sense, the treatment of investment and savings is relatively straightforward, since the model basically has to ensure that in equilibrium the aggregate savings are equal to the total investment of the economy. 9 The capital factor, however, is always fully employed.

Equilibrium

The concept of equilibrium used in the model is that of Walrasian competitive equilibrium, incorporating the government and the foreign sector together with producers and consumers -households. In particular, equilibrium in the economy is determined by a prices vector, an activity levels vector, and a set of aggregate variables that allow all the markets to be emptied except for the labour market, as was noted above. Also, all the agents in the model attain their corresponding optimal choices under the respective budget constraint, i.e., they verify their optimization problem.

With respect to the model closure, we apply a mixed closure rule. Firstly, we opt to keep the public sector activity level fixed. The aim with this is to show the adjustment of this sector and of the economy as a whole when there was no 10 This aggregate specification for the labour market, similar to that used by Oswald (1982), may be interpreted as a tattonoment process. For further details, see Manresa and Sancho (2005). This specification has also been used in many of the CGE models developed for the Spanish economy. See, for example, Kehoe et al. (1989) and Polo and Sancho (1993). 11 For the specification represented by Equation ( 10), this latter value of the parameter is sufficiently high, and yields results that do not differ greatly from those obtained for a value d = . modification of this activity level. This is found to be a suitable scenario for the fiscal simulations performed. For the foreign sector, we opt to keep the trade deficits fixed at the levels of the initial equilibrium, allowing the activity levels of these foreign sectors to vary.

Model parameters and social accounting matrix for Extremadura

Model parameters have been obtained by means of the usual calibration procedure, for which we required a social accounting matrix (SAM) for the Extremadura economy. In general terms, these matrices may be conceived of as an extension of the traditional input-output tables, since, together with transactions linked with the productive sphere, they also incorporate disaggregated information on expenditures and income of households, the government, and the foreign sector.

The calibration basically consists in assuming that the SAM represents an initial equilibrium of the economy, i.e., it involves determining the values of the parameters that satisfy this property. Furthermore, in this benchmark equilibrium, the units of measurement are taken to be such that all the prices and activity levels are unitary 12 .

In our case, it is possible to obtain practically the entirety of the model parameters by calibration 13 . It is only necessary to get external estimates of the elasticities of substitution in the CES consumption functions. To this end we use information relative to the Spanish economy as a whole (López-Salido, 1993).

The Extremadura matrix, used as the basis for the calibration, is for 1990, so that 12 For further details, see Mansur and Whalley (1984). 13 The values of the tax rates used in the model are also obtained by calibration, using the tax revenues data included in the social accounting matrix for Extremadura. These are therefore effective tax rates, and not nominal rates. this is the year taken as reference for the analysis 14 . Also, since the matrix is constructed specifically to calibrate the present model, there exists perfect concordance between the SAM and the model. Thus, together with the production sectors, commodities and household groups that were shown in Figure 1, the SAM-Extremadura-1990 also includes the aforementioned three foreign sectors, an aggregate capital account or savings/investment account, two accounts for the labour and capital factors, and the broad disaggregation of taxes considered in the model.

Simulations and analysis of results

Having constructed the model and determined the benchmark equilibrium, we perform various simulations focused on farm subsidies. In particular, we perform the two simulation exercises that will be described in the following.

Firstly, we establish an extreme scenario consisting of a hypothetical total removal of these subsidies, without modifying any other tax or transfer. The goal is to give a clear picture of the Extremadura economy's dependence on these subsidies, by quantifying the negative effects that their absence would have on the principal economic variables.

Although in practice such a wide-reaching modification does not seem likely, with this simulation we also want to highlight the uncertainty that exists with regard to the future of the subsidies received by the Extremadura agriculture. There contribute to this uncertainty, for example, the recent enlargement of the 14 Indeed, this is the only social accounting matrix that has been constructed for the Extremadura economy. For further details, see De Miguel et al. (1998) and De Miguel (2003). An application of this SAM focused on inequality and income distribution can be found in De Miguel and Pérez (2006).

On the other hand, although it would be appropriate to update the matrix, there are especially severe statistical limitations in the present case which prevented us from constructing a reliable matrix referred to a more recent period. For instance, only a single 1990-year input-output table has been constructed for the Extremadura economy, and the currently existing statistics only show a very limited productive disaggregation. Secondly, we perform a simulation including fiscal compensation via the income tax. In particular, in this second exercise the Regional Government is assumed to replace the foreign European Community sector as the agent financing farm subsidies, although, in order to maintain tax revenues constant, income tax rates are increased linearly. There are basically two reasons for using this tax to provide the fiscal compensation: its importance for the overall fiscal system in Spain, and because Spain's regional governments have a certain capacity to modify it.

The goal of this second simulation is to illustrate an alternative measure of economic policy that would buffer the negative effects observed in the first simulation. This exercise also shows the m ajor consequences that the hypothetical regional government's maintenance of these subsidies would have for this economy, in a scenario characterized by a greater direct fiscal pressure on households 15 .

Before going on to the results, we must note that the great quantity of information yielded by the model needs to be presented synthetically. The results of the two simulations will therefore be discussed in terms of three major blocks of variables -prices, activity levels, and household welfare.

Removal of farm subsidies

With respect to the first simulation, Table 1 lists the percentage variations in the different prices for the two labour market scenariosd = 0 and d = 1.5.

Beginning with production prices, one observes that, in general terms, the removal 15 Other simulations might include different fiscal compensation schemes. For example, together with the total removal of farm subsidies, one could consider a simultaneous increase in the taxation applied to the farming sector itself. A good candidate would be employer´s social contributions, since these constitute an especially important fiscal load for the Spanish economy as a whole. 13 of subsidies would cause these prices to rise. The agriculture sector (j 1 ) clearly stands out, with increases of greater than 10% in both scenarios. Because of its link with this sector, there is also a major rise shown by the food, beverages, and tobacco industries sector (j 4 ). There are also important increases experienced by chemicals and mining (j 3 ) and other industries (j 5 ), due on their dependence on the rest of Spain via imports and the major rises observed in the average price of imported products p RS.

There are various sectors -basically services-that present small declines in production prices, due to the modification in factor prices caused by the elimination of subsidies. In this sense, in both scenarios there is a fall in the capital factor price (r), which is sharper for the greater wage rate rigidity 16 . It is important to note that, in all the simulations, the wage rate (w) remains constant due to it is used as numeraire of the model 17 .

Consumption prices also undergo a generalized rise. Again this is especially so for the commodities most closely linked to agriculture (food and non-alcoholic beverages, h 1 ; alcoholic beverages and tobacco, h 2 ). The consumption price index cpi presents percentage increments between 1% and 2.5%, approximately.

[TABLE 1]

Table 2 lists the percentage changes in the different activity levels. For the production sectors, there is a generalized reduction, again especially in the agriculture (j 1 ) and food, beverages, and tobacco industry (j 4 ) sectors. This general 16 This reduction in return on capital factor is determined by a decrease in capital demand respect to its supply -that remains fixed.

17 Therefore, all the price variations commented on in the paper actually represent relative variations, expressed in relation to this numeraire. 14 reduction is closely linked to the decrease that takes place in consumption demand, which is particularly severe for the first two commodities, with reductions between 5% and 6.3% approximately 18 .

Returning to the production sectors, one observes two clear exceptions to the above behaviour -chemicals and mining (j 3 ) and, above all, construction (j 6 ).

These are sectors whose production is to a great degree investment-oriented, and are given an impulse by the rise in investment activity that takes place in this case 19 . Nevertheless, the general decline in sectoral activity levels causes a reduction in factor demand, leading to an increase of more than 1 percentage point in the unemployment rate with respect to the initial equilibrium 20 .

Finally, for most production sectors -except agriculture-the simulation also causes a fall in imports from the three foreign sectors. Given the closure rule employed, this leads to a reduction in their corresponding activity levels 21 .

[

TABLE 2]

Table 3 gives the results for the changes caused by the removal of farm subsidies in the household groups' welfare. In order to obtain a monetary valuation of these changes, the equivalent variations (EV) are calculated.

One observes that the equivalent variations are negative in sign in practically all 18 The activity level of public services (j 10 ) remains constant due to the model closure rule. 19 Given the characteristics of the present model, the investment of the economy is determined by savings. In this simulation, there is a notable rise in aggregate savings. This is basically due to the increase in the European Community foreign sector savings from halting subsidies to farming activities. 20 Given the labour market specification, changes in the unemployment rate only refer to the scenario which involves wage rate rigidityd = 1.5. As was noted above, in the case of absolute wage rate flexibilityd = 0-the unemployment rate remains constant. 21 Particularly striking is the major reduction in the activity level for the rest of the world foreign sector. The reason is that the level of the Extremadura economy's exports to this foreign sector is very low in the initial equilibrium. So, to maintain the trade balance constant, a small alteration in The greatest equivalent variations (in absolute value) correspond to the household groups f 7 , f 6 , f 5 and f 2 , i.e., the high income groups experience the greatest welfare losses. These household groups present a notable share of capital factor incomes in their respective income structures, so they are the more affected by the reduction in return on this factor.

[TABLE 3]

Farm subsidies and compensation with a linear increase in income tax

The second simulation assumes that the Regional Government takes up the payment of farm subsidies that were initially financed by the European Community foreign sector. In order to cover them and maintain total tax revenue constant, the government simultaneously imposes a linear increase in income tax rates.

The results in this case present major differences from those of the initial simulation. This is clearest in the behaviour of relative prices (Table 4). There is a fall in all the production and consumption prices, in the price of savings/investment, and in the three average prices of imported products.

imports from this foreign sector is translated into relatively large variations in its activity level. 22 There is a single household group whose welfare improves, albeit very slightly. This is the group f 3 in the scenario corresponding to d = 1.5. In this scenario, this group has a small reduction in factor income, but its unemployment benefits are clearly greater than those of the initial equilibrium. Furthermore, for each labour market scenario, there is little difference in the changes in production prices and consumption prices between the different sectors. The explanation is that the change imposed does not initially affect production structures, but instead is basically a change in demand.

[TABLE 4]

Table 5 presents the results for the changes in activity levels. There is a decline in the production sector levels, although generally far less pronounced than in the first simulation. Again, chemicals and mining (j 3 ) and construction (j 6 ) are exceptions to the general pattern. There is also a fall in the activity levels Y h , reflecting a reduction in consumption demand -these falls are fairly similar for the different commodities, and are in general also less than in the first simulation.

Finally, there are slight declines in the activity levels of the three foreign sectors, reflecting a minor reduction in imported products. The welfare effects for the different household groups are presented in Table 6.

One observes that in all cases there again occur welfare losses. The equivalent variations clearly show the group f 7 to be the worst affected, that is to say, the non-farming group with the highest incomes, and that supports the highest income tax rate. This result is similar to that obtained in the previous simulation, although it is now far more accentuated.

[TABLE 6]

To conclude the analysis, we present a brief comparison between the two previous simulations. This comparison shows whether, in the case that the European Community foreign sector stops subsidizing farming activities, the maintenance of these subsidies by the Regional Government financing them by a surcharge on income tax would be an appropriate measure of economic policy 24 . In general terms, the results seem to indicate that, if the Extremadura households are willing to support this greater direct fiscal load, the maintenance of these farm subsidies would indeed generate smaller distortions on this economy than their removal.

By way of example, it was already noted above that the reductions in activity levels in this second simulation are clearly less than those in the first exercise.

Indeed, in contrast to the rise in unemployment rate in the first simulation, in the second exercise this rate falls by 0.4 percentage points. No such clear conclusion could be drawn, however, with respect to the welfare of the different household groups. Although, compared to the initial simulation, there are smaller welfare losses in the second simulation for most groups, there are various exceptions to this general pattern (see the household groups f 7 to f 11 ). 24 The variable representing this linear increase in income tax rates is close to 30% in both labour

Conclusions

The enormous importance of farm subsidies for the Extremadura economy leads us to study the dependence and the economic impact of different scenarios involving the elimination of these subsidies.

The modelling framework chosen for the simulations includes a full incorporation of the interdependences between the different economic agents. In particular, we use a static computable general equilibrium model, which captures the changes in the allocation of resources and the importance of the effects that are produced. It is important to emphasize the utility of this analytical framework for economic policy simulations, since it allows one to observe the micro and macroeconomic effects that result from different policy decisions.

The first exercise that is carried out brings out this relationship of dependence very clearly. This simulation corresponds to an extreme scenario consisting of the total removal of the subsidies. The resulting negative effects on the Extremadura economy are primarily evident in a notable reduction in the welfare levels of practically all the household groups, especially in the groups whose income depends to a major degree on the capital factor. There is also a generalized reduction in the different activity levels, and rises in most of prices -relative to wages-considered, with the sharpest changes for the sectors and commodities more linked to agriculture.

On the basis of this first exercise, the second simulation corresponds to a possible alternative fiscal policy aimed at mitigating the above negative effects. In particular, this second simulation considers that the farm subsidies are maintained by the Regional Government, which finances them by an increased fiscal pressure through income tax rates. Although in this simulation the welfare losses for the market scenarios. Source: The authors' own elaboration.

F

  may take values between zero and infinity. If d = 0, the real wage rate is adjusted sufficiently for the unemployment rate to remain constantand equal to the unemployment rate of the benchmark equilibrium. If d = , the contrary is the case, i.e., the real wage rate remains constant, and it is the unemployment rate that is completely flexible. For intermediate values of d , as this parameter increases, so does wage rate rigidity, i.e., there is a decline in the sensitivity of the real wage rate with respect to the unemployment rate 10 .The simulations to be presented below use two different values of this parameter d = 0 and d = 1.5 11 -representing therefore two labour market scenarios.

  as well as the reforms of the Common Agricultural Policy.

  can therefore state that the elimination of these subsidies would cause a generalized welfare loss 22 . The decline in the factor income received by households leads to a general reduction in disposable income. Given also that consumption prices and savings/investment price rise, the result is a clear fall in private savings and consumption, and hence a marked welfare reduction.

  the different behaviour of the production and consumption prices most closely linked to agriculture. Taking the agriculture sector itself as reference, in contrast with the first simulation, which gave increases of approximately 10%, in this case there are declines of between 0.35% and 0.85% 23 .

[

Production sectors, commodities and household groups included in the CGEM-EXT model PRODUCTION SECTORS:

	Figure 1. j1 -Agriculture	j6 -Construction
	j2 -Energy	j7 -Trade
	j3 -Chemicals and mining	j8 -Transports and communications
	j4 -Food, beverages and tobacco	j9 -Other private services
	j5 -Other industries	j10 -Public services
	COMMODITIES:
	h1 -Food and non-alcoholic beverages	h6 -Medical services
	h2 -Alcoholic beverages and tobacco	h7 -Transports and communications
	h3 -Clothing and footwear	h8 -Leisure, education and culture
	o r F o r F o r h4 -Housing, heating and lighting h5 -Furnishing and fittings F HOUSEHOLD GROUPS: o f1 -Younger than 65, farming sector, low income f2 -Younger than 65, farming sector, high income r f3 -Younger than 65, other sectors, 1st income quintile	h9 -Other commodities f7 -Younger than 65, other sectors, 5th income quintile f8 -65 or older, rural setting, low income f9 -65 or older, rural setting, high income
	P e P e P e f4 -Younger than 65, other sectors, 2nd income quintile f5 -Younger than 65, other sectors, 3rd income quintile P e f6 -Younger than 65, other sectors, 4th income quintile	f10 -65 or older, urban setting, low income f11 -65 or older, urban setting, high income
	e r e r e r e r
	R e v R e v R e v R e v
		i e i e i e i e
		w w w w
		1

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Table 1 . First simulation: Removal of farm subsidies. Percentage variation in PRICES

 1

	Production j1 Agriculture	d = 0 12.59	d =1.5 10.83
	j2	Energy	0.91	-0.8
	j3	Chemicals and mining	4.77	3.18
	j4	Food, beverages, and tobacco	6.16	4.57
	j5	Other industries	4.93	3.41
	j6	Construction	0.91	-0.22
	j7	Trade	0.73	-0.58
	j8	Transports and communications	0.64	-0.5
	j9	Other private services	-0.88	-2.39
	j1o	Public services	0.43	0.06
	Consumption (commodities)
	h1	Food and non-alcoholic beverages	5.59	4.05
	h2	Alcoholic beverages and tobacco	4.36	2.86
	h3	Clothing and footwear	2.6	1.2
	h4	Housing, heating, and lighting	0.14	-1.32
	h5	Furnishings and fittings	1.96	0.72
	h6	Medical services	2.67	1.25
	h7	Transports and communications	1.9	0.49
	h8	Leisure, education, and culture	1.28	-0.14
	h9	Other commodities	1.23	-0.22
	cpi	Consumption price index	2.47	1.02
	Investment
	i	Investment	1.62	0.45
	Weighted average price of imported products
	RS	Rest of Spain	6.12	4.45
	EC	European Community	7.05	5.46
	RW	Rest of the world	7.48	5.88
	Primary factors
	r	Capital	-2.11	-4.14
	w	Labour	Numeraire	Numeraire
	Source: The authors' own elaboration.

Table 2 . First simulation: Removal of farm subsidies. Percentage variation in ACTIVITY LEVELS

 2

	Production j1 Agriculture	d = 0 -3.51	d =1.5 -4.13
	j2 Energy	-2.46	-3.08
	j3 Chemicals and mining	2.73	1.08
	j4 Food, beverages, and tobacco	-4.41	-4.63
	j5 Other industries	-0.38	-1.1
	j6 Construction	6.56	6.04
	j7 Trade	-2.54	-2.6
	j8 Transports and communications	-0.04	-0.84
	j9 Other private services	-0.72	-0.97
	j1o Public services	-	-
	Commodities
	h1 Food and non-alcoholic beverages	-6.3	-5.91
	h2 Alcoholic beverages and tobacco	-5.33	-4.96
	h3 Clothing and footwear	-3.74	-3.44
	h4 Housing, heating, and lighting	-1.22	-0.83
	h5 Furnishings and fittings	-3.15	-3.05
	h6 Medical services	-3.86	-3.56
	h7 Transport and communications	-3.23	-2.95
	h8 Leisure, education, and culture	-2.63	-2.33
	h9 Other commodities	-2.59	-2.27
	Foreign sectors
	RS Rest of Spain	-3.57	-4.41
	EC European Community	-1.97	-2.68
	RW Rest of the world	-19.77	-21.52

Source: The authors' own elaboration.

Table 3 . First simulation: Suppression of farm subsidies. EQUIVALENT VARIATIONS (thousands of millions pesetas) d = 0 d =1.5 f1 -Younger than 65, farming sector, low income

 3

	-1.19	-0.9

-Younger than 65, farming sector, high income

	-2.58	-2.76
	f3

-Younger than 65, other sectors, 1st quintile

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	f4 -Younger than 65, other sectors, 2nd quintile	-0.75 -1.6 w	0.09 -1.32
	f5 -Younger than 65, other sectors, 3rd quintile	-3.12	-3.06
	f6 -Younger than 65, other sectors, 4th quintile	-4.28	-4.29
	f7 -Younger than 65, other sectors, 5th quintile	-9.29	-10.36
	f8 -65 years or more, rural, low income	-0.22	-0.22
	f9 -65 years or more, rural, high income	-1.88	-2.02
	f1o -65 years or more, urban, low income	-0.01	-0.02
	f11 -65 years or more, urban, high income	-0.71	-0.83
	Source: The authors' own elaboration.
			4

Table 4 . Second simulation: Farm subsidies and linear change in income tax. Percentage variation in PRICES

 4

		Submitted Manuscript
	Production j1 Agriculture	d = 0 -0.84	d =1.5 -0.34
	j2 Energy	-0.91	-0.36
	j3 Chemicals and mining	-0.82	-0.33
	j4 Food, beverages, and tobacco	-0.8	-0.32
	j5 Other industries	-0.78	-0.31
	j6 Construction	-0.6	-0.24
	j7 Trade	-0.7	-0.28
	j8 Transports and communications	-0.61	-0.24
	j9 Other private services	-0.82	-0.33
	j1o Public services	-0.19	-0.08
	Consumption (commodities)
	h1 Food and non-alcoholic beverages	-0.78	-0.31
	h2 Alcoholic beverages and tobacco	-0.77	-0.31
	h3 Clothing and footwear	-0.74	-0.29
	h4 Housing, heating, and lighting	-0.79	-0.31
	h5 Furnishings and fittings	-0.65	-0.26
	h6 Medical services	-0.74	-0.3
	h7 Transports and communications	-0.74	-0.3
	h8 Leisure, education, and culture	-0.76	-0.3
	h9 Other commodities	-0.77	-0.31
	cpi Consumption price index	-0.76	-0.3
	Investment
	i	Investment	-0.61	-0.24
	Weighted average price of imported products
	RS Rest of Spain	-0.85	-0.34
	EC European Community	-0.8	-0.32
	RW Rest of the world	-0.8	-0.32
	Primary factors
	r	Capital	-1.12	-0.45
	w Labour	Numeraire	Numeraire
	Source: The authors' own elaboration.

Page 25 of 26 Editorial Office, Dept of Economics, Warwick University, Coventry CV4 7AL, UK

Table 5 . Second simulation: Farm subsidies and linear change in income tax. Percentage variation in ACTIVITY LEVELS

 5

	Production j1 Agriculture	d = 0 -0.61	d =1.5 -0.4
	j2 Energy	-0.59	-0.38
	j3 Chemicals and mining	1.84	2.24
	j4 Food, beverages, and tobacco	-1.25	-1.12
	j5 Other industries	-0.15	0.07
	j6 Construction	6.16	6.9
	j7 Trade	-1.6	-1.51
	j8 Transports and communications	0.08	0.32
	j9 Other private services	-1.16	-1.03
	j1o Public services	-	-
	Commodities
	h1 Food and non-alcoholic beverages	-2.25	-2.25
	h2 Alcoholic beverages and tobacco	-2.23	-2.23
	h3 Clothing and footwear	-2.4	-2.37
	h4 Housing, heating, and lighting	-2.42	-2.42
	h5 Furnishings and fittings	-2.71	-2.61
	h6 Medical services	-2.29	-2.26
	h7 Transports and communications	-2.38	-2.34
	h8 Leisure, education, and culture	-2.57	-2.54
	h9 Other commodities	-2.55	-2.51
	Foreign sectors
	RS Rest of Spain	-0.29	-0.03
	EC European Community	-0.01	-0.2
	RW Rest of the world	-3.29	-2.59

Source: The authors' own elaboration.

Table 6 . Second simulation: Farm subsidies and linear change in income tax. EQUIVALENT VARIATIONS (thousands of millions pesetas) d = 0 d =1.5 f1 -Younger than 65, farming sector, low income

 6

	-0.46	-0.53

-Younger than 65, farming sector, high income

		-1.52	-1.38
	f3 -Younger than 65, other sectors, 1st quintile	-0.36	-0.6
	f4 -Younger than 65, other sectors, 2nd quintile	-0.52	-0.58
	f5 -Younger than 65, other sectors, 3rd quintile	-1.69	-1.62
	f6 -Younger than 65, other sectors, 4th quintile	-2.63	-2.49
	f7 -Younger than 65, other sectors, 5th quintile	-12.37	-11.44
	f8 -65 years or more, rural, low income	-0.49	-0.46
	f9 -65 years or more, rural, high income	-2.13	-1.98
	f1o -65 years or more, urban, low income	-0.17	-0.16
	f11 -65 years or more, urban, high income	-1.61	-1.49

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

It is important to bear in mind that, unlike the first simulation, in this second exercise farming activities do receive the corresponding subsidies.

ACKNOWLEDGEMENTS

This work has been supported by the Ministerio de Ciencia y Tecnología (SEC2003-06080) and by the Generalitat de Catalunya (2004XT00095). The second author also acknowledges a Ministerio de Ciencia y Tecnología grant (SEC2003-06630) and financial support from the Generalitat de Catalunya (2001SGR00029).


Oscar Bajo-Rubio

Carmen Díaz-Roldán

Vicente Esteve
email: vicente.esteve@uv.es.

US deficit sustainability revisited: A multiple structural change approach *

Keywords: E62 -Fiscal Policy|Public Expenditures, Investment, and Finance|Taxation Fiscal policy, Sustainability, US budget deficit. JEL classification: E62, H62 Fiscal policy, Sustainability, US budget deficit. JEL classification: E62, H62

In this paper we re-examine the long-run sustainability of US budget deficits, using Bai and Perron's multiple structural change approach. While the deficit would have been weakly sustainable over the full sample (1947:1-2005:3), strong sustainability would appear only between 1982:1 and 1996:2.

Introduction

US government finances have experienced a remarkable turnaround in recent years. Large budget deficits in the 1980s and early 1990s led to a substantial amount of empirical work aimed to examining their long-run sustainability. However, later on, the record surpluses in the late 1990s and early 2000s turned into record deficits after 2002, with budget projections showing large federal deficits over the next decade. As a result, the US general government deficit is now among the highest in the OECD, and its sustainability has become again a highly relevant issue.

When analyzing the sustainability of budget deficits, the traditional approach has consisted of testing whether the government's intertemporal budget constraint (IBC) holds, that is, whether the current market value of debt equals the discounted sum of expected future surpluses. However, empirical tests on sustainability are largely inconclusive due to differences in the econometric methodology, the particular specification of the transversality condition, and the sample period used.

Several procedures to test for the IBC have been proposed in the literature, focusing either on the univariate properties of the government's deficit and debt (e.g., Hamilton and Flavin, 1986;Wilcox, 1989), or on the presence of a long-run cointegration relationship between government revenues and expenditures (e.g., Trehan andWalsh, 1988, 1991;Haug, 1991). Furthermore, the eventual occurrence of a structural break in the cointegrating relationship has been examined in, e.g., Quintos (1995) and Martin (2000). Overall, the results of these and other studies suggest that the US deficit would have undergone a shift in recent times, with the deficit being either unsustainable or only weakly sustainable in the post-break period.

In this paper we re-examine the sustainability of US budget deficits, using a new approach developed by Bai andPerron (1998, 2003a). This procedure allows to test endogenously for the presence of multiple structural changes in an estimated relationship, and has a number of advantages over previous approaches. In particular, the underlying assumptions are less restrictive, confidence intervals for the break dates can be calculated, the data and errors are allowed to follow different distributions across segments, and the sequential method used in the application can allow for the presence of serial correlation in the errors and heterogeneous variances across segments; see Bai and Perron (2006) for details. As a further contribution, as compared with previous studies where the sample ends at the early 1990s, our period of analysis extends to 2005, including the most recent developments in the evolution of the US budget deficit.

The rest of the paper is organized as follows. A brief description of the underlying theoretical framework is provided in section 2, the methodology and empirical results are presented in section 3, and the main conclusions are summarized in section 4. Assuming that budget deficits are financed using bonds of one-period maturity, in any single period a government faces the following budget constraint:

∆B t = G t -R t (1)
where B t , G t , and R t denote, respectively, the real market value of government debt, real government expenditure inclusive of interest payments, and real tax revenues. The real interest rate is assumed to be stationary around a mean r so that, defining EXP t as G t -rB t-1 , the constraint (1) can be rewritten as:

B t = EXP t -R t + (1 + r)B t-1 (2)
Since (2) holds every period, solving for B t and iterating forward over an infinite horizon yields the IBC:

B t = ∞ X j=0 µ 1 1 + r ¶ j+1 (R t+j+1 -EXP t+j+1 ) + lim j→∞ µ 1 1 + r ¶ j+1 B t+j+1 (3)
If we denote as E t the expectations operator, conditional on information at time t, fiscal sustainability involves:

lim j→∞ µ 1 1 + r ¶ j+1 E t B t+j+1 = 0 (4)
i.e., the government must run future budget surpluses equal, in present-value terms, to the current value of its outstanding debt; in other words, the budget deficit would be sustainable if and only if the stock of debt is expected to grow no faster on average than r (taken as a proxy of the growth rate of the economy).

The cointegration framework for testing the IBC would follow once first differences are taken in (3):

∆B t = ∞ X j=0 µ 1 1 + r ¶ j+1 (∆R t+j+1 -∆EXP t+j+1 ) + lim j→∞ µ 1 1 + r ¶ j+1 ∆B t+j+1
(5) so that sustainability would require:

lim j→∞ µ 1 1 + r ¶ j+1 E t ∆B t+j+1 = 0 (6)
Under a no-Ponzi scheme rule, the right-hand side of equation ( 5) will be stationary as long as government revenues and expenditures, and the stock of public debt, are all stationary in first differences. In order to test for condition (6), the usual procedure consists of testing for the stationarity of

∆B t = G t -R t , F o r P e e r R e v i e w
provided that both G t and R t are I(1), with a cointegration relationship (1, -1), in a regression model of the form:

R t = α + βG t + ε t (7)
and then testing the linear restriction β = 1. In particular, Quintos (1995) shows that: (i) The fiscal deficit would be strongly sustainable if and only if R t and G t are cointegrated and β = 1.

(ii) The fiscal deficit would be only weakly sustainable if R t and G t are cointegrated and 0 < β < 1.

(iii) The fiscal deficit would be unsustainable if β ≤ 0.

Methodology and empirical results

In this section we provide a test of the sustainability of the US budget deficit, over the period 1947:1 to 2005:3. The data on federal government revenues and expenditures, inclusive of interest paid on debt, are taken from the National Income Product Accounts (NIPA, Table 3.1), and real values are calculated using the GDP deflator (NIPA, Table 1.1.4).

As a first step of the analysis, we test for the order of integration of the series using the tests of Ng and Perron (2001). The results are shown in Table 1, and the null hypothesis of non stationarity cannot be rejected, independently of the test, for the two series in levels; at the same time that the presence of two unit roots is clearly rejected at the 1% significance level. Accordingly, both series would be concluded to be I [START_REF] Bai | Estimating and testing linear models with multiple structural changes[END_REF].

Next, we perform a cointegration analysis of equation ( 7) over the whole sample, with no breaks included. The estimation is made using the method of Dynamic Ordinary Least Squares (DOLS) of Stock and Watson (1993). So, we first estimate a long-run dynamic equation including leads and lags of the explanatory variables in equation (7):

R t = α + βG t + q X j=-q γ j ∆G t-j + υ t (8)
where υ t is an error term, and then perform Shin's (1994) test from the calculation of C μ , a LM statistic from the DOLS residuals, which tests for deterministic cointegration (i.e., when no trend is present in the regression).

The results in the first column of Table 2 show that the null of deterministic cointegration between R t and G t is not rejected at the 1% level of significance, and the estimated value for β is 0.93, significantly different from zero at the 1% level. But this estimate would be significantly different from one at the 1% level, according to a Wald test on the null hypothesis β = 1 against the alternative β < 1, distributed as a χ 2 1 and denoted by W DOLS in Table 2. Accordingly, since R t and G t would be cointegrated and 0 < β < 1, the US fiscal deficit would have been only weakly sustainable over the full sample 1947:1-2005:3. This would confirm, over a more extended period, previous results by Quintos (1995) and Martin (2000) for the same sample ending at 1992.3.

But the main objective of this section is estimating equation ( 7) through a multiple endogenous break model. Hence, we now proceed to test for multiple breaks at unknown dates in equation (7), making use of the approach of Bai andPerron (1998, 2003a), who suggest several statistics in order to identify the break points:

• The sup F T (k) test, i.e., a sup F -type test of the null hypothesis of no structural break versus the alternative of a fixed (arbitrary) number of breaks k.

• Two maximum tests of the null hypothesis of no structural break versus the alternative of an unknown number of breaks given some upper bound, i.e., UD max test, an equal weighted version, and W D max test, with weights that depend on the number of regressors and the significance level of the test.

• The sup F T (l + 1|l) test, i.e., a sequential test of the null hypothesis of l breaks versus the alternative of l + 1 breaks.

The results of applying the Bai-Perron tests to the relationship between R t and G t , allowing up to five breaks, are shown in Table 3. Both the UD max and W D max tests are highly significant, which implies that at least one break is present. Next, all the sup F T (k) tests are significant, with k running between 1 and 5, so that at least one break would be present in this relationship. In turn, the sup F T (l+1|l) test is not significant for any l ≥ 3, so the sequential procedure selects three breaks. Hence, the results of the Bai-Perron tests would suggest a model of four regimes, with the dates of the breaks estimated at 1955:3, 1982:1, and 1996:3; their confidence intervals are shown in Table 3.

Finally, we proceed to estimate the cointegration equation ( 8) for the four sub-samples, and the results are shown in the last four columns of Table 2. As can be seen, in the first and second regimes (1947:1-1955:2 and 1955:3-1981:4) the null of deterministic cointegration is not rejected at the 1% level, and the restriction on the estimate of β being equal to one is clearly rejected, which implies that the US budget deficit would have been only weakly sustainable as in the whole sample. In turn, in the third regime (1982:1-1996:2) the null of deterministic cointegration is again not rejected at the 1% level, but now the estimate of β would not be significantly different from one according to the Wald test, so that the US budget deficit would have been strongly sustainable during this period. Finally, in the fourth regime (1996:3-2005:3) no long-run relationship between public revenues and expenditures would appear, since the null of deterministic cointegration is now rejected at the 10% level, and with an estimate of β well above one, reflecting the fact that the US budget deficit would have registered a large surplus during an important part of this period. The above results are summarized in Table 4. In this paper we have re-examined the long-run sustainability of US budget deficits, using the multiple structural change approach of Bai andPerron (1998, 2003a). We found evidence of weak sustainability of the deficit over the full sample 1947:1-2005:3, extending previous results obtained for the period ending at the early 1990s. In addition, we have detected up to three breaks (estimated at 1955:3, 1982:1, and 1996:3) along the whole sample period, so that the US budget deficit would have been strongly sustainable only in the third regime 1.

b The autoregressive truncation lag has been selected using the modified Akaike information criterion, as proposed by Perron and Ng (1996). The number of leads and lags selected was q = 3 ' INT ¡ T 1/3 ¢ , as proposed in Stock and Watson (1993). The long-run variance of the cointegrating regression residuals was estimated using the Bartlett window with b The number of breaks (in our case, three) has been determined according to the sequential procedure of Bai and Perron (1998), at the 5% size for the sequential test sup F T (l + 1|l).

l = 5 ' INT ¡ T 1/2
c 95% confidence intervals in brackets. When analyzing the sustainability of budget deficits, the traditional approach has consisted of testing whether the government's intertemporal budget constraint (IBC) holds, that is, whether the current market value of debt equals the discounted sum of expected future surpluses. However, empirical tests on sustainability are largely inconclusive due to differences in the econometric methodology, the particular specification of the transversality condition, and the sample period used.

Several procedures to test for the IBC have been proposed in the literature, focusing either on the univariate properties of the government's deficit and debt (e.g., Hamilton and Flavin, 1986;Wilcox, 1989), or on the presence of a long-run cointegration relationship between government revenues and expenditures (e.g., Trehan andWalsh, 1988, 1991;Haug, 1991). Furthermore, the eventual occurrence of a structural break in the cointegrating relationship has been examined in, e.g., Quintos (1995) and Martin (2000). Overall, the results of these and other studies suggest that the US deficit would have undergone a shift in recent times, with the deficit being either unsustainable or only weakly sustainable in the post-break period.

In this paper we re-examine the sustainability of US budget deficits, using a new approach developed by Bai andPerron (1998, 2003a). This procedure allows to test endogenously for the presence of multiple structural changes in an estimated relationship, and has a number of advantages over previous approaches. In particular, the underlying assumptions are less restrictive, confidence intervals for the break dates can be calculated, the data and errors are allowed to follow different distributions across segments, and the sequential method used in the application can allow for the presence of serial correlation in the errors and heterogeneous variances across segments; see Bai and Perron (2006) for details. As a further contribution, as compared with previous studies where the sample ends at the early 1990s, our period of analysis extends to 2005, including the most recent developments in the evolution of the US budget deficit.

The rest of the paper is organized as follows. A brief description of the underlying theoretical framework is provided in section 2, the methodology and empirical results are presented in section 3, and the main conclusions are summarized in section 4. Assuming that budget deficits are financed using bonds of one-period maturity, in any single period a government faces the following budget constraint:

∆B t = G t -R t ( 1
)
where B t , G t , and R t denote, respectively, the real market value of government debt, real government expenditure inclusive of interest payments, and real tax revenues. The real interest rate is assumed to be stationary around a mean r so that, defining EXP t as G t -rB t-1 , the constraint (1) can be rewritten as:

B t = EXP t -R t + (1 + r)B t-1 (2)
Since ( 2) holds every period, solving for B t and iterating forward over an infinite horizon yields the IBC:

B t = ∞ X j=0 µ 1 1 + r ¶ j+1 (R t+j+1 -EXP t+j+1 ) + lim j→∞ µ 1 1 + r ¶ j+1 B t+j+1 (3)
If we denote as E t the expectations operator, conditional on information at time t, fiscal sustainability involves:

lim j→∞ µ 1 1 + r ¶ j+1 E t B t+j+1 = 0 (4)
i.e., the government must run future budget surpluses equal, in present-value terms, to the current value of its outstanding debt; in other words, the budget deficit would be sustainable if and only if the stock of debt is expected to grow no faster on average than r (taken as a proxy of the growth rate of the economy).

The cointegration framework for testing the IBC would follow once first differences are taken in (3):

∆B t = ∞ X j=0 µ 1 1 + r ¶ j+1 (∆R t+j+1 -∆EXP t+j+1 ) + lim j→∞ µ 1 1 + r ¶ j+1 ∆B t+j+1
(5) so that sustainability would require:

lim j→∞ µ 1 1 + r ¶ j+1 E t ∆B t+j+1 = 0 (6)
Under a no-Ponzi scheme rule, the right-hand side of equation ( 5) will be stationary as long as government revenues and expenditures, and the stock of public debt, are all stationary in first differences. In order to test for condition (6), the usual procedure consists of testing for the stationarity of ∆B t = G t -R t , provided that both G t and R t are I(1), with a cointegration relationship (1, -1), in a regression model of the form:

R t = α + βG t + ε t (7)
and then testing the linear restriction β = 1. In particular, Quintos (1995) shows that: (i) The fiscal deficit would be strongly sustainable if and only if R t and G t are cointegrated and β = 1.

(ii) The fiscal deficit would be only weakly sustainable if R t and G t are cointegrated and 0 < β < 1.

(iii) The fiscal deficit would be unsustainable if β ≤ 0.

Methodology and empirical results

In this section we provide a test of the sustainability of the US budget deficit, over the period 1947:1 to 2005:3 1 . The data on federal government revenues and expenditures, inclusive of interest paid on debt, are taken from the National Income Product Accounts (NIPA, Table 3.1), and real values are calculated using the GDP deflator (NIPA, Table

As a first step of the analysis, we test for the order of integration of the series using the tests of Ng and Perron (2001). The results are shown in Table 1, and the null hypothesis of non stationarity cannot be rejected, independently of the test, for the two series in levels; at the same time that the presence of two unit roots is clearly rejected at the 1% significance level. Accordingly, both series would be concluded to be I(1).

Next, we perform a cointegration analysis of equation ( 7) over the whole sample, with no breaks included. The estimation is made using the method of Dynamic Ordinary Least Squares (DOLS) of Stock and Watson (1993). So, we first estimate a long-run dynamic equation including leads and lags of the explanatory variables in equation ( 7):

R t = α + βG t + q X j=-q γ j ∆G t-j + υ t (8)
where υ t is an error term, and then perform Shin's (1994) test from the calculation of C μ , a LM statistic from the DOLS residuals, which tests for deterministic cointegration (i.e., when no trend is present in the regression).

The results in the first column of Table 2 show that the null of deterministic cointegration between R t and G t is not rejected at the 1% level of significance, 1 An alternative, though indirect, way of analyzing the sustainability of fiscal policy (used, e.g., in the context of testing for the fiscal theory of the price level) involves the estimation of a long-run (cointegration) relationship between budget surplus and (lagged) government debt, so that a positive and significant estimate of the regression coefficient would be a sufficient condition for solvency. Then, when a government is solvent (i.e., satisfies the IBC), its fiscal policy is sustainable; this is the approach followed in, e.g., [START_REF] Bohn | The behavior of U.S. public debt and deficits[END_REF] and the estimated value for β is 0.93, significantly different from zero at the 1% level. But this estimate would be significantly different from one at the 1% level, according to a Wald test on the null hypothesis β = 1 against the alternative β < 1, distributed as a χ 2 1 and denoted by W DOLS in Table 2. Accordingly, since R t and G t would be cointegrated and 0 < β < 1, the US fiscal deficit would have been only weakly sustainable over the full sample 1947:1-2005:3. This would confirm, over a more extended period, previous results by Quintos (1995) and Martin (2000) for the same sample ending at 1992.3.

But the main objective of this section is estimating equation ( 7) through a multiple endogenous break model. Hence, we now proceed to test for multiple breaks at unknown dates in equation (7), making use of the approach of Bai andPerron (1998, 2003a), who suggest several statistics in order to identify the break points:

• The sup F T (k) test, i.e., a sup F -type test of the null hypothesis of no structural break versus the alternative of a fixed (arbitrary) number of breaks k.

• Two maximum tests of the null hypothesis of no structural break versus the alternative of an unknown number of breaks given some upper bound, i.e., UD max test, an equal weighted version, and W D max test, with weights that depend on the number of regressors and the significance level of the test.

• The sup F T (l + 1|l) test, i.e., a sequential test of the null hypothesis of l breaks versus the alternative of l + 1 breaks.

The results of applying the Bai-Perron tests to the relationship between R t and G t , allowing up to five breaks, are shown in Table 3. Both the UD max and W D max tests are highly significant, which implies that at least one break is present. Next, all the sup F T (k) tests are significant, with k running between 1 and 5, so that at least one break would be present in this relationship. In turn, the sup F T (l+1|l) test is not significant for any l ≥ 3, so the sequential procedure selects three breaks. Hence, the results of the Bai-Perron tests would suggest a model of four regimes, with the dates of the breaks estimated at 1955:3, 1982:1, and 1996:3; their confidence intervals are shown in Table 3.

Finally, we proceed to estimate the cointegration equation ( 8) for the four sub-samples, and the results are shown in the last four columns of Table 2. As can be seen, in the first and second regimes (1947:1-1955:2 and 1955:3-1981:4) the null of deterministic cointegration is not rejected at the 1% level, and the restriction on the estimate of β being equal to one is clearly rejected, which implies that the US budget deficit would have been only weakly sustainable as in the whole sample. In turn, in the third regime (1982:1-1996:2) the null of deterministic cointegration is again not rejected at the 1% level, but now the estimate of β would not be significantly different from one according to the Wald test, so that the US budget deficit would have been strongly sustainable during this period. However, in the fourth regime (1996:3-2005:3) relationship between public revenues and expenditures would appear, since the null of deterministic cointegration is now rejected at the 10% level, and the estimate of β would be above one; hence, no clear conclusions can be drawn for this period, characterized by decreasing deficits at the start, which became surpluses from 1998:1 on (and reached record figures in 2000), followed again by large deficits after 2001:3. The above results are summarized in Table 4.

Conclusions

In this paper we have re-examined the long-run sustainability of US budget deficits, using the multiple structural change approach of Bai andPerron (1998, 2003a). We found evidence of weak sustainability of the deficit over the full sample 1947:1-2005:3, extending previous results obtained for the period ending at the early 1990s. In addition, we have detected up to three breaks (estimated at 1955:3, 1982:1, and 1996:3) along the whole sample period, so that the US budget deficit would have been strongly sustainable only in the third regime (1982:1-1996:2), weakly sustainable in the first and second regimes (1947:1-1955:2 and 1955:3-1981:4, respectively), and no clear conclusions emerge for the final regime (1996:3-2005:3), where both record surpluses and large deficits would have coexisted. 1.

b The autoregressive truncation lag has been selected using the modified Akaike information criterion, as proposed by Perron and Ng (1996). 1, for m = 1.

b t-statistics in parentheses.

c The number of leads and lags selected was q = 3 ' INT ¡ T 1/3 ¢ , as proposed in Stock and Watson (1993). The long-run variance of the cointegrating regression residuals was estimated using the Bartlett window with l = 5 ' INT ¡ T 1/2 ¢ , as proposed in Newey and West (1987). b The number of breaks (in our case, three) has been determined according to the sequential procedure of Bai and Perron (1998), at the 5% size for the sequential test sup F T (l + 1|l).

c 95% confidence intervals in brackets.

  (1982:1-1996:2), weakly sustainable in the first and second regimes (1947:1-1955:2 and 1955:3-1981:4, respectively), and a surplus would have prevailed over the final regime (1996:3-2005:3).

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Table 1

 1

	Ng-Perron tests of unit roots
	I(2) vs. I(1) Variable	Case: p = 0, c = -7.0 MZ GLS α MZ GLS t ADF GLS
	∆R t ∆G t	-42.30 * -63.41 *	-4.58 * -5.61 *	-6.03 * -7.40 *
	I(1) vs. I(0) Variable	Case: p = 1, c = -13.5 MZ GLS α MZ GLS t ADF GLS
	R t G t	-1.54 0.99	-0.77 0.70	-0.78 0.66
	Notes:

a * denotes significance at the 1% level. The critical values are taken from Ng and Perron (2001), Table

Table 2

 2 Estimation of long-run relationships: Stock-Watson-Shin cointegration tests The critical values for the Shin test are taken from Shin (1994), Table 1, for m = 1.

	Parameter	Full sample	First regime Second regime Third regime Fourth regime
	estimates	1947:1-2005:3 1947:1-1955:2 1955:3-1981:4 1982:1-1996:2 1996:3-2005:3
	α	0.36	0.99	0.31	-0.65	-26.5
		(2.42)	(2.47)	(2.14)	(-0.59)	(-3.48)
	β	0.93	0.83	0.94	1.06	4.35
		(47.4)	(12.76)	(46.24)	(7.59)	(4.51)
	R2	0.99	0.91	0.99	0.97	0.98
	σ2	0.045	0.056	0.035	0.026	0.013
	C μ	0.087	0.079	0.061	0.093	0.310 * * *
	W DOLS	10.15 *	6.62 *	6.22 * *	0.24	12.08

*

Notes: a *, **, and *** denote significance at the 1%, 5%, and 10% levels, respectively. b t-statistics in parentheses.

c

Table 3

 3 Bai-Perron tests of multiple structural changes in the long-run relationship * denotes significance at the 1% level. The critical values are taken from Bai and Perron (1998), tables I and II; and from Bai and Perron (2003b), tables 1 and 2.

	Tests statistics:
	UD max		W D max
	138.67 *	136.45 *
	sup F T (1)	sup F T (2)	sup F T (3)	sup F T (4)	sup F T (5)
	136.45 *	92.41 *	92.66 *	70.48 *	57.63 *
	sup F T (2|1) sup F T (3|2) sup F T (4|3) sup F T (5|4)
	38.27 *		64.22 *	4.76	0.0
	Break dates estimates:
	T 1	1955:3
	[1955:1-1957:3]
	T 2	1982:1
	[1980:4-1982:2]
	T 3	1996:3
	[1996:2-1996:4]
	Notes:

a

Table 4

 4 Sustainability of the US public deficit: Summary results US government finances have experienced a remarkable turnaround in recent years. Large budget deficits in the 1980s and early 1990s led to a substantial amount of empirical work aimed to examining their long-run sustainability. However, later on, the record surpluses in the late 1990s and early 2000s turned into record deficits after 2002, with budget projections showing large federal deficits over the next decade. As a result, the US general government deficit is now among the highest in the OECD, and its sustainability has become again a highly relevant issue.

		Full sample	First regime Second regime Third regime Fourth regime
		1947:1-2005:3 1947:1-1955:2 1955:3-1981:4 1982:1-1996:2 1996:3-2005:3
	Cointegration	Yes	Yes	Yes	Yes	No
	Estimate of β	0.93	0.83	0.94	1.06	4.35
	Null β = 1	No	No	No	Yes	No
	Sustainability	Yes (weak)	Yes (weak)	Yes (weak)	Yes (strong)	-

Table 1

 1 * denotes significance at the 1% level. The critical values are taken from Ng and Perron (2001), Table

	Ng-Perron tests of unit roots
	I(2) vs. I(1) Variable	Case: p = 0, c = -7.0 MZ GLS α MZ GLS t ADF GLS
	∆R t ∆G t	-42.30 * -63.41 *	-4.58 * -5.61 *	-6.03 * -7.40 *
	I(1) vs. I(0) Variable	Case: p = 1, c = -13.5 MZ GLS α MZ GLS t ADF GLS
	R t G t	-1.54 0.99	-0.77 0.70	-0.78 0.66
	Notes:

a

Table 2

 2 Estimation of long-run relationships: Stock-Watson-Shin cointegration tests *, **, and *** denote significance at the 1%, 5%, and 10% levels, respectively. The critical values for the Shin test are taken from Shin (1994), Table

	Parameter	Full sample	First regime Second regime Third regime Fourth regime
	estimates	1947:1-2005:3 1947:1-1955:2 1955:3-1981:4 1982:1-1996:2 1996:3-2005:3
	α	0.36	0.99	0.31	-0.65	-26.5
		(2.42)	(2.47)	(2.14)	(-0.59)	(-3.48)
	β	0.93	0.83	0.94	1.06	4.35
		(47.4)	(12.76)	(46.24)	(7.59)	(4.51)
	R2	0.99	0.91	0.99	0.97	0.98
	σ2	0.045	0.056	0.035	0.026	0.013
	C μ	0.087	0.079	0.061	0.093	0.310 * * *
	W DOLS	10.15 *	6.62 *	6.22 * *	0.24	12.08

*

Notes: a

Table 3

 3 Bai-Perron tests of multiple structural changes in the long-run relationship sup F T (2|1) sup F T (3|2) sup F T (4|3) sup F T (5|4) * denotes significance at the 1% level. The critical values are taken from Bai and Perron (1998), tables I and II; and from Bai and Perron (2003b), tables 1 and 2.

	Tests statistics:
	UD max		W D max
	138.67 *	136.45 *
	sup F T (1)	sup F T (2)	sup F T (3)	sup F T (4)	sup F T (5)
	136.45 * 57.63 38.27 * 92.41 * 92.66 * 70.48 * 64.22 * 4.76 0.0
	Break dates estimates:
	T 1	1955:3
	[1955:1-1957:3]
	T 2	1982:1
	[1980:4-1982:2]
	T 3	1996:3
	[1996:2-1996:4]
	Notes:

* a

Table 4

 4 Sustainability of the US public deficit: Summary results

		Full sample	First regime Second regime Third regime Fourth regime
		1947:1-2005:3 1947:1-1955:2 1955:3-1981:4 1982:1-1996:2 1996:3-2005:3
	Cointegration	Yes	Yes	Yes	Yes	No
	Estimate of β	0.93	0.83	0.94	1.06	4.35
	Null β = 1	No	No	No	Yes	No
	Sustainability	Yes (weak)	Yes (weak)	Yes (weak)	Yes (strong)	-

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

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

The authors acknowledge financial support from the Spanish Ministry of Education and Science, through the projects SEJ2005-08738-C02-01 (O. Bajo-Rubio and C. Díaz-Roldán) and SEJ2005-01163 (V. Esteve). * The authors acknowledge financial support from the regional government of Castilla-La Mancha, through the project PBI-05-008; and from the Spanish Ministry of Education and Science, through the projects SEJ2005-08738-C02-01 (O. Bajo-Rubio and C. Díaz-Roldán) and SEJ2005-01163 (V. Esteve).


Anthony C Burton

Katherine S Carson

Susan M Chilton
email: s.m.chilton@ncl.ac.uk

W George Hutchinson

Why do people non-demand reveal in hypothetical double referenda for public goods?

Keywords: C91 -Laboratory, Individual Behavior < C9 - Non-demand revelation, double referenda, public goods

Running title: Non-demand revelation in hypothetical double referenda for public goods

Hypothetical Contingent Valuation (CV) Surveys used to elicit values for environmental and other public goods often employ variants of the referendum mechanism due to the cognitive simplicity and familiarity of respondents with this voting format. One variant, the double referendum mechanism, requires respondents to state twice how they would vote for a given policy proposal given their cost of the good. Data from these surveys often exhibit anomalies inconsistent with standard economic models of consumer preferences. There are a number of published explanations for these anomalies, mostly focusing on problems with the second vote. This paper investigates which aspects of the hypothetical task affect the degree of non-demand revelation and takes an individual-based approach to identifying people most likely to non-demand reveal. A clear profile emerges from our model of an individual most likely to non-demand reveal as one who faces a negative surplus i.e. a net loss in the second vote and invokes non-self interested, non-financial motivations during the decision process.

Why do people non-demand reveal in hypothetical double referenda for public goods?

Hypothetical Contingent Valuation (CV) Surveys used to elicit values for environmental and other public goods often employ variants of the referendum mechanism due to the cognitive simplicity and familiarity of respondents with this voting format. One variant, the double referendum mechanism, requires respondents to state twice how they would vote for a given policy proposal given their cost of the good. Data from these surveys often exhibit anomalies inconsistent with standard economic models of consumer preferences. There are a number of published explanations for these anomalies, mostly focusing on problems with the second vote.

This paper investigates which aspects of the hypothetical task affect the degree of non-demand revelation and takes an individual-based approach to identifying people most likely to non-demand reveal. A clear profile emerges from our model of an individual most likely to non-demand reveal as one who faces a negative surplus i.e. a net loss in the second vote and invokes non-self interested, non-financial motivations during the decision process.

Introduction

It has long been known that voters have an incentive to cast demand revealing votes in a one shot binding referendum [START_REF] Gibbard | Manipulation of voting schemes: A general result[END_REF]Satterthwaite, 1975).

Economic theory has nothing to say regarding the impact of the non-binding nature of the task on demand revelation in hypothetical versions of the same referendum.

Despite this, the NOAA Panel on Contingent Valuation recommended that the hypothetical referendum mechanism be used in surveys to estimate losses associated with natural resource damages [START_REF] Arrow | Report of the NOAA panel on contingent valuation[END_REF]).

The single referendum has largely been superceded by the double referendum in contingent valuation surveys about environmental goods. This form of referendum requires the respondent to answer two yes-no questions of the type: "Would you pay £X for A?" The first question poses a value of £X previously selected from a range of values. The second question poses a value taken from a sub-range (either higher or lower than £X) that depends on the respondent's answer to the first question. If the respondent says yes (no) to the first question, they receive a higher (lower) offer amount in the second referendum round.

The statistical properties of this mechanism and its advantages are welldocumented [START_REF] Hanemann | Statistical efficiency of doublebounded dichotomous choice contingent valuation[END_REF][START_REF] Alberini | Efficiency vs. bias of willingness-to-pay estimates: Bivariate and interval-data models[END_REF] setting is a problem (McFadden and Leonard, 1993;[START_REF] Cameron | Estimation using contingent valuation data from a 'dichotomous choice with follow-up' questionnaire[END_REF][START_REF] Alberini | Efficiency vs. bias of willingness-to-pay estimates: Bivariate and interval-data models[END_REF]De Shazo, 2002).

This evidence provides the motivation for this paper. If a respondent treats a referendum survey as hypothetical, then there are no economic predictions about the degree of non-demand revelation that might be present. Nevertheless, by taking an individual-based approach to the problems of non-demand revelation, we may be able to observe systematic behavioural patterns in the data that suggest the chance of nondemand revelation is higher in certain situations. Some types of individuals may be more prone to non-demand revelation than others.

This approach contrasts with the contemporary view in the literature that nondemand revelation is driven by a "one size fits all" behaviourally driven motivation, such as anchoring on the first offer [START_REF] Herriges | Starting point bias in dichotomous choice valuation with follow-up questioning[END_REF] or loss aversion (De Shazo, 2002). If it is possible to identify those individuals more likely to cast nondemand revealing votes, we can begin to disentangle how people behave when faced with such a decision mechanism, despite its hypothetical nature. 1 In addition, we can provide the first experimental evidence to address the caution noted by the NOAA Panel who stated that "If a double-bounded dichotomous choice or some other question form is used in order to obtain more information per respondent, experiments should be developed to investigate biases that may be introduced," (Arrow et al., 1993, p. 4612).

Such experimental investigation has, to date, been notably lacking. Although an experiment may be considered different in many ways from a survey, lessons can nevertheless be drawn from it which can assist in survey design and/or model estimation. For example, in the experiment to be reported we find that the likelihood The remainder of the paper is organized as follows. The experimental design is in Section 2. We report the results in Sections 3 and 4 and discuss their implications in Section 5. Concluding thoughts are in Section 6.

Treatments, Voting Patterns and Experimental Design

In a survey, respondents' benefits from the public good are unknown. In addition, we do not know how respondents to field-based survey instruments perceive the incentive structure of the survey. There is the potential for different perceived incentives present within the same survey. These two problems make the laboratory environment preferable to a field setting for investigating questions about potential sources of bias. The induced value setting allows the researcher to know each subject's value of the public good, allowing us to easily distinguish between demand revealing and non-demand revealing responses. In addition, it is possible for the researcher to carefully control the incentive structure, to ensure that the referendum is purely hypothetical i.e. inconsequential.

We define the experimental public good as a group investment. Individuals are allocated a return (R) from the investment (their benefit) and a personal cost (C). This induced value structure is analogous to the benefits and costs to the respondent in a CV survey. We generate an underlying WTP distribution and bid scheme by varying the R and C across subjects. For some subjects the benefit outweighs the cost and they should vote for provision of the good while for others the reverse is true. The main point here is to highlight those subjects who vote yes, even when the cost outweighs the benefit and, as such, appear to exhibit hypothetical bias. It is hypothesised that it is this type of respondent who contributes at least in some part to the anomalies observed in field data.

In this experiment, for each subject type (defined by an individual's value of R and C) there are two sets of voting patterns of interest: demand revealing (DR) and observed (OB). The DR voting pattern is that which is predicted by and truthfully reflects the distribution of induced values. The OB voting pattern is the pattern actually observed for a treatment. This may or may not coincide with the DR pattern.

In a field double referendum only the OB voting pattern is observed. As we cannot make any theoretical prediction of the likely effect of inconsequentiality we test the null hypothesis that the OB and DR voting patterns are the same.

One hundred forty-four students at the U.S. Air Force Academy participated voluntarily in the experiment. Each experimental session consisted of a group of nine subjects, for a total of 16 experimental sessions.

The decision mechanism is an inconsequential double referendum. In each session, subjects participate in two voting rounds on the provision of the group After the first round vote, subjects learn that they will vote again on the group investment. They receive new secret ballots with the same return (R) but a new cost (NewC). Is a subject voted yes in the first vote, his or her cost is higher in the second vote. The reverse is true for a subject who voted no in the first vote. The second vote proceeds just as the first. As with the first vote, subjects' cash earnings are $10 regardless of the outcome of the vote. As with a double referendum CV surveys, subjects do not know that they will vote twice when they make their first voting decision. In order to explore whether individual characteristics of subjects were responsible for the propensity to cast demand revealing or non-demand revealing votes we administered a qualitative debriefing questionnaire after the second vote which asked respondents to explain in their own words their reasons for voting the way they did.

Experimental Results

Table 1 reports the DR and OB vote distributions. For clarity, we will use the notation C1 to refer to subjects' first round costs and C2 to refer to subjects' second round costs throughout this discussion of the results. We analyse the differences between the DR and OB vote distributions across each of the double bounded intervals, a process which is not possible with field data because the DR vote distributions are unknown. This analysis allows us to clearly identify (i) the degree of demand revelation in the sample as a whole, (ii) subject types with a greater propensity for non-demand revelation and (iii) the intervals where non-demand revealing behaviour is most prevalent.

We can clearly see that non-demand revealing behaviour is not confined to the second vote, at odds with the conventional assumption in the econometric analysis of field data [START_REF] Cameron | Estimation using contingent valuation data from a 'dichotomous choice with follow-up' questionnaire[END_REF][START_REF] Alberini | Efficiency vs. bias of willingness-to-pay estimates: Bivariate and interval-data models[END_REF] We turn first to prospect theory as applied to iterative CV question formats by [START_REF] Deshazo | Designing transactions without framing effects in iterative question formats[END_REF]. From our data set we draw out the negatively framed prospect in the ascending branch R=80, C1=50, C2=70. This is the subject group to which prospect theory is most likely to apply. In this group, 23 out of 24 subjects voted yes to both C1=50 and C2=70, as predicted by conventional economic theory. Under prospect theory we would expect some subjects to vote yes-no. We observe none (one subject voted no-no). Furthermore, comparing the negatively framed R=80, C1=50, C2=70, subject type with the comparable unframed prospect (R=80, C1=70), we observe that 23 out of 24 subjects voted yes to C=70 in the former and 22 out of 24 voted yes to C=70 in the latter. Thus prospect theory does explain the deviations from demand revealing behaviour present in our data.

We then turn to seven further strategies (Table II). Five of the response strategies (Strategies1-5) conflict with our observed voting patterns for all subject types. These strategies assume demand revealing voting in the first round while we observe some non-demand revealing responses for each subject type in the first round.

Of the remaining two strategies, Strategy 6 (yea-saying affecting the first and second vote) performs better than Strategy 7 (bargaining affecting the first and second vote) We hypothesise that the reason for the failure of any of the above strategies to predict our observed voting patterns is that some non-demand revealing voters are adopting one strategy and some another. As a result no single strategy predicts population voting patterns. This leads us to the results from the second part of our experiment.

Subjects' responses to the qualitative debriefing questionnaire were content analysed 3 (Krippendorf, 1980) by three independent coders using the coding frame in Table III. 4 To take account of the possibility of different subject strategies we combine subjects' induced values (R-C1 and R-C2) and the behavioural heuristics cited in the questionnaires in a predictive logit model (N = 116). 5 The model allows us to establish whether either or both of the above individual-specific data are good predictors of incorrectly bounding a subject's WTP. If a characteristic indicates a high likelihood that a subject's WTP will be incorrectly bounded, we can define a separating-out mechanism to identify individuals most likely to cast non-demand 3 Content analysis is a method of counting the occurrence of certain concepts within a piece of qualitative data. This is a robust form of analysis that allows qualitative factors to be quantified and counted in a reliable and objective manner. The aim of this technique is not to capture all available information but rather to capture the key points from the data. It is possible to isolate concepts from the data and to assess their importance in generating the observed responses. Applying this analysis to the subjects' written responses provides a set of codes which can be used to test which heuristics demand revealing and non-demand revealing subjects used to explain their voting in the referendum. 4 Our coding scheme can be considered reliable. To generate our reliability statistic (kappa) we use [START_REF] Fleiss | The reliability of dichotomous judgements: Unequal numbers of judges per subject[END_REF] extension of the Cohen kappa method for three or more coders with two possible responses per coder (technical validation is in [START_REF] Fleiss | Statistical methods for rates and proportions (2nd edition)[END_REF]. Statistically highly significant z tests for all codes indicate that we reject the null hypotheses that the ratings are independent (i.e. kappa = 0) and conclude that agreement is better than one would expect by chance. Kappa's for the codes reported herein range from 0.61 to 0.95 with 50% in the "good" category and 50% in the "very good" category using [START_REF] Landis | The measurement of observer agreement for categorical data[END_REF] five point scale ranging from < 0.2 = poor to > 0.81 = very good.

5 28 subject questionnaires were drawn as a stratified random sample from the 144 total to develop the coding frame. These are not included in the final analysis in order to comply with the independence criterion (Krippendorf 1980). This left 116 questionnaires for the subsequent analysis. With the exception of Vote2, the qualitative variables are all statistically significant at the 1% or 5% levels. These heuristics can be grouped into two broad categories: those expressing either self-interested, financially motivated considerations (RvsC, PROFIT, LOSS) and those that do not (GROUP, HYPOTHETICAL, VOTE2). The signs of the coefficients are as might be expected in that subjects who cite heuristics in the second category are more likely to be incorrectly bounded, as indicated by positive signs on these coefficients. Those in the first category are less likely to be incorrectly bounded, as shown by negative signs on these coefficients. Examination of the odds ratio (Exp(B)) shows, for example, that subjects who cite HYPOTHETICAL are 50.94 times more likely than not to be incorrectly bounded. Similarly those mentioning GROUP are 11.76 times more likely than not to be incorrectly bounded while those citing PROFIT are 330 times less likely (i.e. 1/.003) to be incorrectly bounded.

Regarding the two quantitative variables (SURPLUS VOTE 1 and SURPLUS VOTE 2) we find that only SURPLUS VOTE 2 is significant (1% level), indicating that negative surplus in the second round increases the probability that an individual will be incorrectly bounded and a positive surplus that they will be correctly bounded.

The model is 90% correct in predicting incorrect bounding and 98% correct in predicting correct bounding as shown in Table IV. Two things are clear from the above analysis. The first is that the nature of the surplus matters. In our inconsequential double referendum, hypothetical gains appear to have incentive properties similar to real gains. The same does not apply to hypothetical losses, where the incentive properties seem very weak, particularly in the second vote. Here, when faced with a loss, some subjects invoke non-self interested, non-financial considerations and give non-demand revealing responses. The second is that the impact of individual specific characteristics seems to be a more comprehensive, albeit simple, explanation of non-demand revelation in a hypothetical double referendum than more complicated behavioural strategies.

Discussion

Each of these findings has differing implications in respect of the potential to deal with them in a CV survey. Regarding the weak incentive property of hypothetical losses, as the decision task is hypothetical, we cannot call on economic theory to explain why the prospect of a loss has poorer incentive properties than a hypothetical gain and leads some people to invoke such heuristics. Nevertheless, it may be possible in field surveys to develop a series of questions that could provide some indication as to the likelihood that a respondent who voted yes would face a net loss if the referendum passed. The effect on WTP of taking these subjects' responses out of the WTP estimation could be explored.

In a similar and possibly more fruitful vein, it may be more feasible to address the second issue of how individual characteristics affect demand revelation. The experiment shows that subjects were easily able to provide coherent reasons for their vote and the responses showed that the subjects were not confused by the task or mechanism per se. Any additional difficulty in answering a referendum question in a survey would therefore arise out of the complexity of the good and subjects' uncertainty about their value for the good. Given the difficulties inherent determining whether a subject derives a positive or negative surplus if the referendum passes, we recommend that any separating mechanism in a field CV survey rely, at least at this stage, on subject-stated heuristics. A practical mechanism that is compatible with field data can be derived from this experiment. In this experiment, incorrectly bounded subjects are identified as those who cite one or more non-self-interested, non-financially motivated heuristics and who do not cite a self-interested, financially motivated heuristic relating to the positive surplus they could gain from their vote. In our experiment, the nonself-interested, non-financially motivated heuristics were HYPOTHETICAL, GROUP and VOTE2 and the self-interested, financially motivated heuristics were RvsC, PROFIT and LOSS. In a CV survey of an environmental good other expressions may be used to describe these concepts of PROFIT and LOSS. In addition, to an extent, heuristics are an artifact of the task. Thus, in the field, one might expect respondents to express the importance or value for money of preserving the environment. A response that expressed more concern for the benefits to others than the respondent's own benefits from the good would indicate that the respondent is motivated by GROUP concerns.

Applying our practical separating mechanism based only on heuristics to our sample of 116 responses identifies 18 out of the 20 incorrectly bounded subjects. It identifies a data set of 86 correctly bounded responses, of which only 2 are observed as incorrectly bounded. This mechanism is not as precise as the logit model and identifies 12 correctly bounded responses as incorrectly bounded. This paper set out to explore whether any systematic patterns exist in terms of non-demand revelation in a hypothetical experiment designed to explore voting decisions in a double referendum, the mechanism of choice of many CV practitioners.

Conclusion

It demonstrates the usefulness of using subjects' underlying values for the public good in discovering the origin of hypothetical bias. It also set out to determine whether some individuals are more prone to non-demand revelation than others. In both case, we report affirmative results, in that if subjects face a net loss they are more likely to vote against their interests in the sense of voting yes when they should have voted no, and further admitted to using heuristics that differed from their demand revealing counterparts.

Findings from this experiment can be carried over into CV survey design in the sense that the experiment demonstrates the potential to develop customized debriefing surveys that can subsequently be used to separate out groups of respondents in the data set to explore their impact on WTP estimation. Clearly, the more non-demand revealers in a sample, the more inaccurate will be the resulting estimate so a mechanism by which to identify such respondents in a hypothetical field survey could be potentially very important.

0 =0 =0 =0 =0 =0 >0 =0 50-70 YN 5 0 =0 =0 =0 =0 =0 >0 =0 30-50 NY 35 48 <48 <48 <48 <48 =48 <48 <48 0-30 NN 2 0 >0 >0 >0 >0 =0 =0 >0 R = 40, C1 = 70 90- YY 5 0 =0 =0 =0 =0 =0 >0 =0 70-90 YN 1 0 =0 =0 =0 =0 =0 0 =0 50-70 NY 1 0 =0 =0 =0 =0 >0 0 =0 0-50 NN 41 48 =48 =48 =48 =48 <48 <48 =48 R = 80, C1 = 50 70- YY 23 24 <24 <24 =24 =24 =24 =24 <24 50-70 YN 0 0 >0 >0 =0 =0 =0 =0 =0 30-50 NY 0 0 =0 =0 =0 =0 =0 =0 =0 0-30 NN 1 0 =0 =0 =0 =0 =0 =0 >0 R = 80, C1 = 70 90- YY 1 0 =0 =0 >0 >0 >0 >0 =0 70-90 YN 21 24 =24 =24 <24 <24 <24 <24 <24 50-70 NY 0 0 =0 =0 =0 =0 0 0 =0 0-50 NN 2 0 =0 =0 =0 =0 =0 =0 >0

HYPOTHETICAL

Allusion to the inconsequential nature of the task (e.g. that dollar earning are not affect by voting decisions; that token earnings do not affect dollar earnings).

VOTE2

Allusion to the fact that this was a second vote (e.g. mentions of previous/changing costs, previous vote, possible future votes).

*The following quotes illustrate statements that result in a code being marked as present for a given questionnaire. Additional examples available from the authors. R vs. C: "The return was greater than the value invested."

PROFIT: "In order to end up with more tokens than I originally started with I had to vote yes. I knew there was no change, but still making more tokens seem like the logical thing to do.

LOSS: If we voted Yes then I would lose 10 tokens.

GROUP: I just figured if I was at a loss everyone else was probably gaining so I though I would help them out.

HYPOTHETICAL: First of all, I thought about how the tokens don't matter with the money…" VOTE2: "However, if there is the possibility of long term capital gains, it might not be awful to lose 10 tokens at first."

F

  subject in the experiment is endowed at the start with 100 tokens (the experimental currency). In the first voting round subjects know their return (R) and cost (C) of the investment. Subjects cast secret ballots on whether or not the group should make the investment. If the vote passes, each subjects' token balance changes from 100 tokens to 100 -R + C tokens. If the vote fails, subjects keep their original 100 tokens. The vote requires at least six yeses to pass. Because the incentive structure of the experimental design requires an inconsequential referendum in order to correspond with the incentives of a truly hypothetical field referendum survey, there no link between subjects' token balance and their experimental earnings in dollars. Subjects earn $10 for a 40-minute experimental session regardless of their final account balance in tokens. 2

Figure 1

 1 Figure 1 presents a schematic of the double referendum design. Two key

  a priori. All experimental packets were assembled so as to make the proper materials available to the subject no matter which way he or she voted in the first round.The distribution of R is such that 2/3 of the subjects have the low R value of 40, and 1/3 have the high R value of 80. This distribution of values allows us to obtain more observations from subjects who we expect to exhibit hypothetical bias (R=40 subjects), the issue of interest in this study. This distribution has no effect on any one individual's likelihood of non-demand revelation as it is unknown. If individuals behave as if the referendum is consequential, then their optimal response it to cast a demand revealing vote. The demand revealing voting paths for each subject type are in bold. Although the overall distribution of first round costs and returns is as in Figure1, we randomly assign costs and returns from this distribution to individual subjects in each experimental session. In this way, the distribution of subject types differs across sessions.

  Explanations of Double Referendum Voting PatternsBefore considering the impact of individual heuristics and motivations of voting behaviour, we first turn to the literature for behavioural explanations consistent with our data. If deviations in our OB data match the predictions from the literature, a customised exploration becomes unnecessary. If such explanations exist, we might assume that non-demand revelation in a hypothetical referendum, whether in an experiment or a CV survey, may well be generated by this behaviour and mitigating procedures could be developed and introduced into a CV survey where possible.

  to predict five observed votes in the NN interval for three subject types (R=40, C1=50; R=80, C1=50; R=80, C1=70).

  Thus, the probability of incorrect bounding in the double referendum is modeled as a function of the qualitative heuristics cited by the individual and their surpluses (net gains or losses) in the first and second votes. Table IV contains the results. We consider the implications of these results for CV surveys below.

  . and Leonard, G.K. (1993) Issues in the contingent valuation of environmental goods: Methodologies for data collection and analysis, in Contingent valuation: A critical assessment (Ed.) J. Hausman, Amsterdam: North-Holland. Satterthwaite, M.A. (1975) Strategy-proofness and Arrow's conditions: Existence and correspondence theorems for voting procedures and social welfare functions, Journal of Economic Theory 10, 187-217.

FIGURE 1 .

 1 FIGURE 1. Schematic of the Design of the Inconsequential Double Referendum Experiment

  other members of the group (e.g. the effect of an individual vote on the group outcomje or the payoffs of other members of the group; consideration of what might happen to others if the vote passed or failed).

		TABLE III
		Content Analysis Coding Frame
	CODE	DESCRIPTION
	R vs. C	A self-interested, explicit comparison of subject's cost of the
		investment compared to the return
	PROFIT	Explicit mention of the fact that subject may profit, return,
		gain, or earn (including calculations thereof).
	LOSS	Explicit mention of the fact that subject may make a loss or
		lose money (including calculations thereof).
	GROUP	Acknowledgement of the

TABLE IV Logit

 IV Model Relating the Likelihood of Non-Demand Revealing Bounding to the Use of Heuristics and Respondent Surpluses

			B	S.E.	Wald	df	Sig.	Exp(B)
		R vs. C	-3.60	1.42	6.38	1	0.012	0.027
		PROFIT	-5.16	1.76	8.63	1	0.003	0.006
		LOSS	-2.92	1.41	4.26	1	0.039	0.054
		GROUP	2.46	1.12	4.82	1	0.028	11.60
	HYPOTHETICAL	3.93	1.26	9.78	1	0.002	50.94
		VOTE2	1.88	1.28	2.16	1	0.142	6.55
	SURPLUS VOTE 1	0.04	0.03	1.68	1	0.195	1.04
	SURPLUS VOTE 2	-0.10	0.03	10.95	1	0.001	0.905
	CONSTANT	-1.08	1.34	0.65	1	0.420	0.339
			-2*LOG LIKELIHOOD			37.4421
		COX & SNELL R-SQUARED			0.449
		NEGELKERKE R-SQUARED			0.7473
					N			116
					Predicted bounding	%
					Correct		incorrect
	Observed	Correct			94		2	98
	bounding	Incorrect		2		18	90
	Overall %							97

Page 21 of 22 Editorial Office, Dept of Economics, Warwick University, Coventry CV4 7AL, UK

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There is a trend to assert that respondents may treat contingent valuation surveys as advisory, rather than inconsequential (after[START_REF] Carson | Incentive and informational properties of preference questions[END_REF]. Unless this is proven, we take the view that at least some respondents will treat the exercise as truly hypothetical (which may vary from a large majority to a small minority, depending on the survey). As such, this paper relates to these respondents and not all respondents to a CV survey.

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

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