Political uncertainty, public expenditure and growth

European Journal of Political Economy Vol. 20 (2004) 153 – 179 www.elsevier.com/locate/econbase

Political uncertainty, public expenditure and growth Julia Darby a, Chol-Won Li a, V. Anton Muscatelli a,b,* a

Department of Economics, University of Glasgow, Adam Smith Bldg., Glasgow G12 8RT, UK b CES-ifo, Munich, Germany

Received 29 May 2000; received in revised form 11 November 2002; accepted 31 January 2003

Abstract We set out an infinite-horizon political economy model with partisan and office motivation effects in an endogenous growth context to demonstrate that the existence of political uncertainty regarding re-election tends to reduce the amount of public investment by incumbent governments and underlies a switch from government investment to government consumption, thereby reducing growth. The political equilibrium is inefficient and so does not maximise social welfare. Using panel data regressions we show, for OECD countries, that there is empirical support for the hypothesis that political uncertainty tends to reduce public investment, and that there are partisan effects in public investment decisions. D 2003 Elsevier B.V. All rights reserved. JEL classification: O41; H30; H41; E62 Keywords: Political uncertainty; Public investment; Endogenous growth; Policy myopia

1. Introduction The notion that political uncertainty affects growth is well established in economic theory. Major political upheaval, social unrest and revolution are a major disincentive to invest. In these circumstances, the lack of protection for property rights harms prospects for private investment1 and reduces foreign direct investment in a country.2 Similarly, in

* Corresponding author. Department of Political Economy, University of Glasgow, Adam Smith Bldg., Glasgow G12 8RT, UK. Tel.: +44-141-330-6363; fax: +44-141-330-4940. E-mail address: [email protected] (V.A. Muscatelli). 1 For theoretical models in which the lack of enforcement of property rights affects growth, see Tornell and Velasco (1992) and Benhabib and Rustichini (1996). For a survey, see Persson and Tabellini (1998). 2 See Rodrik (1991). 0176-2680/$ - see front matter D 2003 Elsevier B.V. All rights reserved. doi:10.1016/j.ejpoleco.2003.01.001

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countries where rulers are weak and confront the threat of being overthrown, policymakers have an incentive to allow rent-seeking activities, which may again reduce economic growth.3 There is also considerable empirical evidence that major political upheaval (as opposed to routine changes of governments that follow elections) and coups d’e´tat can adversely affect economic growth (see Alesina et al., 1996; Barro, 1996; Easterly and Rebelo, 1993). Political instability can also adversely affect growth through effects on foreign aid (see Chauvet, 2003). In modern democracies, where government changes are generally peaceful and follow constitutional norms, political uncertainty through electoral change may still have an impact on economic growth. The main mechanism at work in the models is through the impact of electoral uncertainty on government myopia. The myopia occurs when forward-looking governments are not interested in carrying out long-term economic policies4 because of uncertain re-election prospects. For instance, Svensson (1998) emphasises how governments may be less inclined to make improvements to the legal system. Calvo and Drazen (1998) show how policy uncertainty can distort the future path of investment decisions. Devereux and Wen (1998) suggest that political uncertainty encourages governments to run down the economy’s assets, with the result that future governments are more likely to raise capital taxation, which depresses private investment. Persson and Tabellini (1998) propose a two-period model in which capital taxation is used to finance public investment, which drives economic growth and enhances the future tax base. In their model, public investment is valued less by an incumbent government if re-election is uncertain, because less of the economy’s future tax revenues will be spent on the incumbent’s preferred public goods. Hence, greater uncertainty of re-election for the incumbent increases policy myopia and reduces public investment. Empirically, there seems to be some evidence indicating a negative link between minor political uncertainty (the frequency of changes in a government’s political complexion) and economic growth (see Alesina et al., 1996; Perotti, 1996). However, this existing empirical evidence makes use of quite limited measures of political uncertainty, and does not always focus on industrial democracies. In this paper, we focus on the link between political uncertainty in electoral outcomes in democracies and economic growth, through the effect on a government’s decisions on how to allocate government expenditure between public consumption and public investment. The novelty of our contribution is the following. First, unlike existing two-period models of the impact of political uncertainty on growth (see Persson and Tabellini, 1998), we propose an infinite horizon model, and examine the dynamic interaction of an endogenous growth model with electoral turnover. This allows us to view political parties as paying attention to the longer-term impact of their policy choices. 3

See Murphy et al. (1991). The notion of policy myopia is quite common in political economy models. For alternative models of fiscal policy in which the incumbent has an incentive not to act in the social interest, see Mueller (1989) and Drazen (2000) for surveys of the earlier public choice literature, and Alesina and Tabellini (1990), Milesi-Ferretti and Spolaore (1994). Peletier et al. (1999) show that binding rules on deficits can reduce public investment to inefficient levels. 4

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Second, in existing models myopia generally arises because incumbent partisan governments realise that they do not have full control over the future benefits from current taxation and spending decisions that will accrue to their own political constituency.5 In our model, we combine partisan preferences with office motivation. Political myopia arises because of office motivation, so that an incumbent government perceives a more limited political benefit from decisions taken now which only impact with a lag on consumer utility. Thus, political uncertainty leads to a shift of government budgets from capital spending to current consumption. Unlike other authors, who have tended to concentrate on public expenditures on different types of public goods (e.g. Alesina and Tabellini, 1990; Tabellini and Alesina, 1990), and have ignored the public investment – growth link, our view is that the relationship between public investment and consumption is important for understanding the consequences of political uncertainty for growth. Third, unlike other attempts to model political uncertainty, we take into account the preferences of consumers and how these affect the political equilibrium. We are therefore able to compare the stochastic steady-state growth equilibrium under political uncertainty with that which would prevail in the presence of a social-welfare maximizing social planner. This allows us to consider the welfare implications of political uncertainty. Fourth, we use a newly constructed data set on measures of political uncertainty to provide empirical support for our theoretical model. Using data on a panel of European countries, we find considerable support for our hypothesis that political uncertainty affects public investment and consumption decisions. The paper is structured as follows. In Section 2, we outline our theoretical model and its main results. In Section 3, we outline our empirical evidence. Section 4 concludes.

2. A theoretical model We develop an endogenous growth model in which government spending is a major determinant of growth. We assume a partisan-type political economy set-up in which two political parties alternate in power and implement taxation policies and allocate government expenditures between government consumption, which increases the current utility of consumers, and government investment, which encourages future growth and benefits consumers in the future. Consumers are assumed to differ in their discount factors, with some consumers benefiting more than others do from future consumption.6,7 Each party’s 5 For instance in Alesina and Tabellini (1990) and Tabellini and Alesina (1990), partisan policymakers not only care about social welfare but also care about the composition of spending between two different types of public goods, and political uncertainty can lead to a ‘deficit bias’. In contrast to this strand of the literature, we do not focus on deficit spending and debt issuance, and on different types of public consumption. 6 In a richer model, one might want to explain the source of these differences in consumers’ time preference. These might arise because of the presence or absence of intergenerational links in a model with overlapping generations as opposed to infinitely lived consumers (as assumed here). However, as long as there is some political uncertainty in the model, our conclusions would still hold in a more general model. 7 See, for example, van Velthoven and van Winden (1990) for some interesting earlier work that examines the impact of heterogeneous discount factors on government budget deficits.

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political platform is given by the discount factor at which future benefits are capitalised. Consumers vote for the party that most closely represents their views, and political uncertainty is introduced by assuming random voter turnout.8 Before outlining our model in detail, we summarise the key results that emerge. First, the presence of political uncertainty creates policy myopia. The two political parties always adopt policies that give rise to lower growth and a higher fraction of revenues spent on public consumption compared with that desired by consumers who share their discount factor. Second, a higher degree of political uncertainty discourages growth and increases the share of government consumption. Third, we identify a ‘‘policy myopia multiplier effect’’, through which electoral uncertainty that only affects one political party spills over to the rival party, thereby magnifying the net impact of the uncertainty. Fourth, the equilibrium that emerges from the existence of political uncertainty is one in which the economy grows too slowly, and is inefficient so that social welfare is not maximised. 2.1. The production and government sectors We assume a discrete-time model, in which the final output sector is perfectly competitive and there is no private capital.9 The aggregate production function is Yt ¼ ðAt LÞa ð Gt DÞ1a

ð1Þ

where Yt is final output (a numeraire), L is the working population and D is ‘‘land’’ supplied at a fixed quantity. To facilitate exposition, we assume L = D = 1. Productivity is augmented through the flow of public investment, denoted by Gt,10 and the variable At, which captures a learning-by-doing effect. We assume that At increases according to Atþ1 ¼ b1 Yt þ At

ð2Þ

where b>0 measures the degree of the learning-by-doing effect. From Eq. (2), increases in current output raise future productivity, so the flow public expenditure G in Eq. (1) can be interpreted as a form of investment. Using Eqs. (1) and (2), we have Atþ1 x1a ¼ t þ1 At b

ð3Þ

where xt = Gt/At. 8 This is a common assumption in political economy models, see Alesina and Rosenthal (1995) and Drazen (2000). 9 This assumption is not particularly restrictive and can be found in many endogenous growth models (e.g. Aghion and Howitt, 1998). It is assumed here because it makes the model analytically tractable, given that consumers have different discount factors. 10 This assumption follows Barro (1990), and is widely used in the endogenous growth literature and is again made from the point of view of analytical tractability. An alternative assumption that the stock of public investment affects productivity is examined by Futagami et al. (1993).

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The government taxes final output at a rate 0 < s < 1, hence the first-order condition of the profit maximisation of a competitive firm is wt ¼ að1  st ÞAt x1a ; t

qt ¼ ð1  aÞð1  st ÞAt x1a t

ð4Þ

where wt is a wage rate and qt is a rental rate of a factor D. The government allocates a fraction 0 < h < 1 of tax revenue to public investment Gt, and the remainder is used for public consumption, Zt. Hence, government investment is Gt ¼ ht st Yt Z ht st ¼ xat

ð5Þ

using Eq. (1), and public consumption is given by Zt ¼ ð1  ht Þst Yt ¼ ð1  ht Þst At ðst ht Þ

1a a

ð6Þ

where the second equality uses Eqs. (1) and (5). Zt is increasing in s because a higher tax revenue results in more expenditure,11 and the term st(1  a)/a represents the dynamic effects of public investment. Zt is, however, non-monotonically related to ht due to the term ht(1  a)/a, which captures the positive impact on output of government investment. As we shall see below, the policy parameters st and ht will be determined endogenously by the political parties. Now let us define gt + 1 + 1 = At + 1/At where gt + 1 is the rate of productivity growth. Then, using Eqs. (3) and (5), we can derive the economic equilibrium condition:12 bgtþ1 ¼ ðht st Þ

1a a

:

ð7Þ

2.2. Consumer preferences The number of consumers is L = 1. We assume that consumers differ only in their discount factor, and use bi < 1 to denote the discount factor of a consumer i. The discount factor is continuously distributed such that bia[b,b¯ ]. This parameter summarises voters’ ¯ bi give a greater weight to future political preferences: consumers with a higher consumption and therefore tend to support a growth-oriented party. 11

We rule out Laffer curve effects. The growth rate is monotonically increasing in the tax rate, because gross output contributes to learningby-doing (see Eq. (2)). If we had assumed that net output drives learning-by-doing, i.e. At + 1 = b 1(1  st)Yt + At, then Eq. (7) would be replaced with bgt + 1=(1  st)(stht)(1  a)/a, exhibiting a trade-off between the growth stimulating effect of public investment and the growth-decelerating effect of tax revenues needed to finance government investment. We do not model this trade-off for three reasons. First, this trade-off has already been analysed by Barro (1990) where physical capital accumulation plays the same role of learning-by-doing in our model. Second, gross output seems a more relevant measure to capture learning-by-doing. Third, the introduction of the trade-off would not dramatically change our key results. 12

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The intertemporal utility function of a consumer i is l X Ui ¼ E bti clit Zit1l ; 0
ð8Þ

t¼0

where cit is the consumption of final output, Zit is the consumption of government services, and E is an expectation operator. We assume that ‘‘land’’ is equally owned by all consumers. This implies that each consumer earns income wt + qt in each period. For simplicity, we assume the absence of lending and borrowing, so consumers will spend their wages in each instant on private consumption, i.e. cit ¼ wt þ qt ¼ At ð1  st Þðht st Þ

1a a

ð9Þ

13

where Eqs. (4) and (5) are used. The term (1  st) represents a distortionary effect of taxation, and s(1t  a)/a captures the positive impact of public investment. For convenience, Eq. (8) is rewritten as l X Ui ¼ E bti At uðgtþ1 ; st Þ; t¼0

h i1l a uðgtþ1 ; st Þ ¼ bgtþ1 ð1  st Þl st  ðbgtþ1 Þ 1a

ð10Þ

using Eqs. (6), (7) and (9). 2.3. Voters’ behaviour There are two political parties, whose political platforms are summarised by their discount factors: bH for party H and bL for party L such that bH>bL. We follow the standard political economy literature on partisan models by assuming a majoritarian system, where the incumbent party has total control on fiscal policy.14 The framework can be interpreted either as one with a pure two-party system, or one in which two coalition groups with alternative policy platforms are competing in an election. In this class of models, the median voter determines the winning party in the election. Elections are held at the beginning of each period, and political uncertainty is introduced by assuming random voter turnout (see Alesina and Rosenthal, 1995; Drazen, 2000). The distribution of consumers who actually vote stochastically alternates between two states. At this stage, it is sufficient to assume that the incumbent political party loses the election whenever the distribution of voters changes from the previous period (more detail will be given below). Let 1>p>0 denote the probability of this event. Note that p is independent of the type of political parties, and a higher p means more frequent changes of governments. Thus, p is a natural measure of political uncertainty. When party j, j = H,L, is in office, it chooses its policy on sj and hj. Party H is relatively more ‘growth-oriented’ than party L in that it gives greater weight to future outcomes 13 This assumption is for tractability, given differences in consumers’ discount factors. The same assumption is used in many studies of endogenous growth (e.g. Aghion and Howitt, 1998; Young, 1991). 14 One potential extension of our model, which we do not explore here, is that the minority party may also have some control on fiscal policy through a bargaining process.

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(bH>bL). Given the parties’ preferred policy mix (sj,hj), consumers will decide whether to vote for party H or L. They vote for a political party whose policy mix gives a higher utility. To describe voting behaviour, we first characterise the consumers’ ideal policy mix. Note that there are two states: one where party H is in office, and the other where party L is in office and determines fiscal policy. This requires us to examine voters’ ideal policy mix in each state.15 For this, note that Eq. (10) expresses the utility function in terms of st and gt + 1, the latter of which is linked to ht via Eq. (7). Thus, identifying voters’ ideal policy mix (st,ht) is equivalent to finding (st, gt + 1), which maximises their utility. Now let Uij denote the maximised intertemporal utility function of a consumer i when party j is in office. This is defined by the following recursive equation: n  h io  ð11Þ Uij ðAt Þ ¼ max At u gijtþ1 ; sijt þ bi ð1  pÞUij ðAtþ1 Þ þ pUi˜j ðAtþ1 Þ gijtþ1 ;sijt

where j=H,L, ˜j=H,L, j p ˜j, At+1=At (1+gijt+1) and ( gijt + 1,sijt) is the ideal policy mix of a consumer i when party j is in office. A consumer i gains utility Atu ( gjit + 1,sijt) in the current period. In the next period, the technological level of the economy will have improved to At + 1, which enters the value function in period t + 1. In that period, party j will still be in office with a probability of 1  p, and the consumer achieves Ui (At + 1). Or party ˜j will take office with a complementary probability p, and the consumer attains the value Uij˜ (At + 1). Given this, we can establish the following. Lemma 1 . In steady state, (i) the ideal policy mix of a consumer i is given by si u siH = siL and hi u hiH = hiL, therefore her ideal productivity growth is gi u giH = giL, and (ii) a unique interior solution si>0 and gi>0 are defined by a

si ¼ 1  l þ lðbgi Þ 1a ; " # a a ðbgi Þ 1a ðbgi Þ 1a  1 ¼ bi ð1 þ agi Þ 1 : 1a 1a

ð12Þ ð13Þ

for b/(1 + b)>bi. Proof. See Appendix A.

5

This means that the ideal policy mix, and hence productivity growth, is independent of the states, which depend on the types of political parties. This should not come as a surprise, since the consumer’s maximisation problem is symmetric between different states in all respects.16 Fig. 1 shows the determination of gi. The left- and right-hand sides of Eq. (13) intersect once, giving a unique interior solution. Note that a higher bi shifts the curve RHS upward, 15 In doing so, we take voter turnout as a pure random process, and refrain from analysing voters’ decisions on whether to vote or not (see Drazen, 2000). Our interest, as in standard partisan models, is not in the source of political uncertainty, but in its macroeconomic impact. 16 One could introduce an asymmetry through the probability that party j loses the election given that it was in office in the previous period. This conditional probability is p for both political parties in our model. If this were to differ depending on j = H,L, consumers’ ideal g would be different between two states. However, there are two observations that may justify our focus on the symmetric case. First, there is no priori reason why p should be high or low for a political party with a high (or low) discount factor. Second, an increase in a common p allows us to analyse the impact of increasing political uncertainty that is not biased against any one political party.

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Fig. 1. The determination of gi.

increasing the ideal productivity growth rate. In addition, we can also establish the following lemma concerning the relationship between the consumers’ discount factor and their preferred fiscal policies. Lemma 2. In steady state, si, hi and gi are monotonically increasing in bi. Proof . See Appendix B.

5

This lemma means that a more patient consumer prefers a larger fraction of the tax revenue to be spent on public investment, and would pay higher taxes for higher productivity growth.

Fig. 2. The preferences and policies of the political parties.

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To describe the voting behaviour of consumers, consider the equilibrium condition (Eq. (12)), which is depicted in Fig. 2. All consumers are distributed along the line, and g(b) ¯ represent ideal productivity growth rates of the most impatient and patient voters, and g(b) respectively. Note that there are ‘‘closed’’ indifference curves around a point where consumers are located along the line. Those indifference curves are defined by Ui=u( g,s)/ (1  bi( g + 1)), using Eq. (10). Moreover, as we will shortly verify, the policy choices of the political parties are also located along the line in Fig. 2. For example, points aL and aH represent the policies of parties L and H, respectively. Now consider consumers who are indifferent to the policy choices of both parties. Such consumers with a discount factor b˜ are defined by uðgL ; sL Þ uð gH ; s H Þ ¼ : ˜ 1  bðgL þ 1Þ 1  b˜ðgH þ 1Þ Diagrammatically, those threshold consumers are characterised by both points aL and aH being located on the same indifference curve, as shown in Fig. 2. Note that b˜ is unique given that consumers differ only in their discount factor. Therefore, it is clear that consumers with bi>b˜ vote for party H, and those with bi < b˜ vote for party L. 2.4. Political uncertainty In this class of majoritarian political economy models, the median voter determines the winning party in each election. Political uncertainty is assumed to arise from stochastic changes in the median voter caused by random voter turnout. Let us assume that N < 1 denotes the total number of consumers who actually vote in each period.17 The distribution of the voters randomly alternates between two states. In one state, the distribution function of voters is given by Fh(b), and it changes to Fl(b) in another state. We use bhmed and bmed l to denote the discount factor of the median voters associated with each distribution function, i.e. Fl(blmed) = Fh(bhmed) = N/2. The only condition that we impose on the distribution functions is:18 bmed < b˜ < bmed l h

ð14Þ

Given the discussion in the preceding section, the measures of consumers who will vote ˜ and N  Fk(b), ˜ k = l,h, respectively. Assumption for party L and party H are given by Fk(b) ˜ l(blmed) = N/2 and Fh(b˜ ) < Fh(bhmed) = N/2. Therefore, party L will (14) implies that Fl(b)>F win the election in periods with Fl(b), and party H will win in periods with Fh(b) with the two parties alternating in power. Recall that p was defined as the conditional probability of an incumbent political party losing an election. This means that, given the voters distribution Fl(b) (or Fh(b)) in the previous period, p is the probability of this distribution changing to Fh(b) (or Fl(b)). 17 18

Our main results do not change even if the total number of voters changes between two states. It does not matter if there is a shift in either of the supports of the distribution.

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2.5. Political parties and policies We now turn our attention to the incentives faced by each party in deciding on its policy set. Political parties know the distribution functions of voters and the conditional probability p. When in office, each party maximises the sum of the intertemporal utility functions of the consumers who support it, but using the party’s own discount factor. The further assumption is that each party is office-motivated in that it has a zero pay-off when it is out of office.19 In determining their fiscal policy in each period, each party takes the future policy of its rival party as given. That is, the equilibrium concept used is that of a dynamic Nash – Markov equilibrium. Let Vj(At) denote the value function of party j when it is in office, and Vˆj(At) when it is out of office. We can now write down the Bellman equations for party j = H,L:  

 Vj ðAt Þ ¼ max Nj At u gjtþ1 ; sjt þ bj ð1  pÞVj ðAtþ1 Þ þ pVˆ j ðAtþ1 Þ ð15Þ gjtþ1 ;sjt

where j = H,L, At + 1 = ( gjt + 1 + 1)At, and Nj is the number of voters for party j when it was ˜ and NH = N  Fh(b). ˜ In Eq. (15), party j gains utility Nju( gjt + 1) in elected, i.e. NL = Fl(b) period t when it is in office. In the next period, it achieves Vˆ(At + 1) with a probability p, or Vj(At + 1) with a complementary probability 1  p. Given an infinite horizon, a party that loses office always expect to return to office at some future date and its current policies will therefore affect future pay-offs even after losing an election. This must be taken into account in computing Vˆj(At + 1), which is defined by the following recursive equation

 Vˆ j ðAt Þ ¼ bj pVj ðAtþ1 Þ þ ð1  pÞVˆ j ðAtþ1 Þ : ð16Þ We can now establish the following proposition. Proposition 1. In steady state, unique interior solutions sj and gj exist and they are defined by  a sj ¼ 1  l þ l bgj 1a ; ð17Þ 

" # a  a     bgj 1a bgj 1a  1 ¼ bj Mj g˜j 1 1 þ agj 1a 1a

ð18Þ

for b/(1 + b) >bi where Mj(g ˜j ) = 1  p(1  bj(g ˜j )+ 1)/[1  b j(1  p)(g ˜j + 1)], j = H, L and j p ˜j. 19 There are different ways of introducing office motivation in a political party’s pay-off function (see Rogoff, 1990; Persson and Tabellini, 1990, 1998). In models where elections have a disciplining effect on incumbent governments, one can introduce office motivation as a fixed benefit from being in office, or fixed cost from being out of office. However, our purpose here is to show how policy myopia can arise in a partisan model, and policy myopia effects will emerge as long as the political benefits to a party from being in office are related to the policy actions taken. Thus, for instance, our results would still hold in a model where each party derives some benefit when it is out of office from the policies undertaken, as long as the benefits when in office depend in some measure on the utility of the consumers who elected the government. Of course, assuming a zero pay-off for each party when it is out of office involves a gain in analytical simplicity.

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Proof. See Appendix C.

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5

Equilibrium conditions (Eq. (18)) for j = H,L can be regarded as the reaction functions of political parties in terms of gj. Equilibrium values of gH and gL can be solved from those equations. Once gH and gL are obtained, equilibrium values of sj and hj can be recovered from Eqs. (7) and (17). Note that equilibrium condition (Eq. (17)) is the same as Eq. (12). This means that the policy mix chosen by political parties lies on the line in Fig. 2, verifying our earlier claim. 2.6. Policy myopia due to political uncertainty First, we examine whether the existence of political uncertainty induces a bias in fiscal policy. We compare the growth rates chosen by political parties with the ideal growth rate of consumers who share the same discount factors as the two parties. If they differ, fiscal policy is ‘‘biased’’. We are also interested in the direction of any policy bias. First, we consider supporters of party H. Recall that the ideal growth rate of consumers with bH, which is denoted as gi = g (bH), is defined by Eq. (13), and it is depicted in Fig. 1. Now consider party H. Eq. (18) shows that it differs from Eq. (13) only by the presence of MH( gL). Since this term is positive but strictly less than one, the curve RHS of Eq. (18) must be located entirely below that of Eq. (13), and is shown in Fig. 1 as a dotted line. Note that this is true irrespective of the value of gL as long as p>0. For p = 0, we have MH( gL) = 1, so Eqs. (13) and (18) are the same without policy myopia. As long as there is a small chance of an incumbent political party losing an election, its fiscal policy is distorted in the sense that gH < gi = g(bH). Moreover, as p rises, the policy distortion gets greater. Note that this also applies to party L. Thus, given Eqs. (7) and (17), the following proposition follows naturally. Proposition 2. Political parties always set policies such that (i) the growth rates are lower, (ii) tax rates are lower and (iii) the fraction of tax revenue spent on public consumption is higher than consumers with the identical discount factor. This proposition is due to the presence of a term Mj(), j = H,L, in Eq. (18). This captures the policy myopia created by political uncertainty. In capitalising future benefits, consumers use their discount factor bi. However, the two parties essentially use an uncertainty-adjusted discount factor bj Mj() which is lower than bj, since Mj() < 1. This means that future benefits are less important to political parties than consumers who share the same bj. The knowledge that the party will lose office at some stage in the future creates this shortsightedness in policy. Putting it differently, recall that the political parties are office-motivated or gain nothing when they are out of office. Therefore, the sum of future discounted benefits that parties gain in office is strictly smaller than that of consumers with the same discount factor, who benefit from productivity growth no matter which party is in office. That is, the policy myopia arises since the political parties are less interested in the future than the consumers. Viewed this way, it should be clear that an assumption of political parties gaining a zero pay-off when they are in opposition is not crucial for the policy myopia result. What is important is an assumption that political parties gain less out of office than in office, which is plausible.

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Eq. (18) shows that the policy-myopia effect is increasing in the discount factor (i.e. BMj()/Bbj < 0, j = H,L). That is, a growth-oriented party tends to suffer more from this detrimental effect. Another implication is that a higher growth policy of one party tends to exacerbate policy myopia suffered by another party (i.e. BMj()/Bg˜j < 0, j,j˜ = H,L, j p ˜j ). Note that this is not because a rival party’s policy worsens the prospect of winning a next election, but because it increases the opportunity cost of being out of office when it cannot benefit from an opponent’s growth-oriented policy. This observation is explored further below as a ‘‘policy myopia multiplier effect’’, through which political uncertainty affecting one party magnifies its effect by spilling over to another party. Next, we solve the reaction functions (Eq. (18)) to characterise the equilibrium gH and gL. Note that political parties capitalise future benefits using an effective discount factor bj Mj, j = H,L, as mentioned above. Hence, there are direct and indirect effects of an increase in bj on the choice of gj. The direct effect is due to bj of bj Mj, and the indirect (or myopia) effect operates via Mj. The direct effect increases bjMj, hence gj, while this effective discount factor tends to fall due to the indirect effect which reduces Mj, hence gj. We assume that the direct effect dominates the indirect effect (i.e. B(bjMj)/Bbj>0). This assumption not only allows us to avoid a taxonomic analysis but also seems reasonable, since a higher discount factor (i.e. a lower interest rate) is widely regarded as correlated with higher growth. Given this assumption, we first establish the following. Proposition 3 . Given bL < bH and B (bjMj) / B bj >0, j = H, L, political parties choose fiscal policy such that gL < gH, sL < sH and hL < hH. This is explained using Fig. 3, which depicts the reaction functions (Eq. (18)). First consider the case of bˆ u bL = bH, i.e. both political parties have the same discount factor (but with political uncertainty, i.e. p>0). In this symmetric case, it is easy to see that the growth rates chosen by political parties are the same, i.e. gL = gH. This is depicted by dotted curves in Fig. 3, which intersect on the 45j line at a point A. The ideal growth rate of consumers with the same discount factor bˆ would be located northeast of a point A on the 45j line.

Fig. 3. Political parties’ reaction functions.

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Starting from this symmetric equilibrium, let us raise bH and lower bL. Party H’s reaction function shifts upward, while that of party L shifts leftward. In general, a new equilibrium B is located above the 45j line. Thus, we have gL < gH for bL < bH. Moreover, sL < sH and hL < hH are obvious from Eqs. (7) and (17). We are now in a position to examine the impact of political uncertainty on the choice of fiscal policy by political parties. It is summarised in the following proposition. Proposition 4. As political uncertainty rises (i.e. p increases), the incumbent political party (i) reduces the growth rate, (ii) decreases the tax rate, and (iii) increases the proportion of public consumption. This proposition can be established using Fig. 4 where the reaction functions (Eq. (18)) are depicted. As p rises, the both curves shift towards the origin, so that equilibrium B moves to C. In general, the new equilibrium is located southwest of the original equilibrium, so that gH and gL both fall. Results (ii) and (iii) are obvious from Eqs. (7) and (17). The intuition behind this result lies in policy myopia. As the prospect of winning an election becomes more uncertain, political parties in effect place more weight on the shortrun benefits of being in office by more heavily discounting longer-run benefits. This is reflected in the fact that the policy myopia term increases Mj with p. Note that a higher p means that the incumbent party is more likely to lose, but the opposition party is more likely to win the election. Thus, an increase in p has a detrimental incentive effect on the incumbent party, but a positive effect on the opposition. Proposition 4 shows that current fiscal policy is influenced more by the gloomier prospects of the outcome in the immediate election than the brighter prospect of being re-elected, since the latter is too distant in future to matter significantly now. Decomposing the effect of a greater political uncertainty reveals what one could call a ‘policy myopia multiplier effect’. A movement of an equilibrium B to C in Fig. 4 can be taken as a two-step operation, i.e. via an intermediate point D. A shift from a point B to D

Fig. 4. The ‘policy myopia multiplier effect’.

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is caused by an increase in political uncertainty against and specific to party L, as the reaction function of party H does not change. Note that such an increase in political uncertainty, which is biased against party L, reduces the growth rates chosen by party H as well as party L. To put it differently, the effect of political uncertainty affecting one party spills over to the other political party.20 This is despite the fact that this ‘‘biased’’ greater uncertainty is in favour of party H, as it means a higher probability of party H returning to office. This interesting result is obtained due to the fact that the policy myopia term MH of party H is affected by the growth rate chosen by party L( gL). Obviously, a similar policy myopia multiplier effect exists in the opposite direction (i.e. from party H to party L) when p increases affecting both parties. Before we turn to our empirical evidence, we briefly mention the efficiency properties of the political economy equilibrium. It should be clear that some inefficiency is bound to arise, given the assumption that the distribution of the discount factors of consumers and the position of political parties are both exogenously given. Perhaps a more interesting exercise is to identify the inefficiency caused solely by policy myopia. To do this, we can compare the politico-economic outcome with the growth rates that would be chosen by some critical voters, assuming that their rates of time preference happen to coincide with those of the political parties.21 Then, given Proposition 2, it can be easily established that the policy myopia caused by political uncertainty tends to make the average growth rate inefficiently low compared with the social optimum.22

3. Empirical evidence Our theoretical model suggests a link between political uncertainty and public investment, with greater uncertainty leading to higher government consumption and lower public investment. In this section, we focus on this link and present new empirical evidence, particularly in relation to public investment. Of course, our theoretical model also assumes a link between public investment and growth. This is not investigated here. A large literature on the impact of government investment spending on productivity growth presents strong evidence on the positive impact that public investment, particularly spending on public infrastructure, has on productivity growth in industrialised economies.23 Policymakers increasingly perceive that 20 Without such a spillover effect, the biased political uncertainty would move an equilibrium to a point DV rather than D in Fig. 4. 21 For our purposes, it does not matter whether the critical voters are the mean or median voters of the entire population or the voting population. 22 The average growth rate of the political economy equilibrium is given by g=(1  p)( gL + gH). The social optimal average growth rate is similarly defined. 23 This includes both evidence from production and cost function estimates (see inter alia Aschauer, 1989; Munnell, 1990; Morrison and Schwartz, 1996), and from cross-country panel studies (see, for example, Easterly and Rebelo, 1993). Although the size of the total impact of public capital spending on productivity growth is a matter of some debate (see Holtz-Eakin and Schwartz, 1995) and obviously varies between countries and sectors, the evidence is generally that government investment is productive. In contrast, most studies tend to find a negative impact of government consumption on economic growth (see Barro, 1996). For some contrary evidence from developing countries where sometimes capital spending is misallocated, see Devarajan et al. (1996).

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long-term economic success requires a reallocation of government spending towards public investment. This has led some governments, notably in the UK, to commit to a ‘golden rule’ of public spending, whereby deficit spending is only allowed (over the cycle) on public investment. The evidence linking political change in democracies and fiscal policy is more mixed. Numerous studies explain the rise in the proportion of current expenditures in total government spending since the mid-1960s in many of the OECD economies in terms of the political complexion and the weakness of governments (see Roubini and Sachs, 1989; Alesina and Perotti, 1996, 1997; De Haan and Sturm, 1997). Many of the attempts in the European economies to stabilise increasing debt burdens in the late 1980s and 1990s have resulted in increases in taxation and cuts in capital outlays (see Alesina and Perotti, 1996, 1997). Perotti and Kontopoulos (2002) provide evidence linking fragmentation in governments (the numbers of parties in coalition governments and the number of ministers in cabinet) to different dimensions of fiscal policy. Here, we provide further evidence on the links between key fiscal variables identified in our theoretical model and political change in democracies. Our empirical uses an extended set of measures of political uncertainty, which goes beyond the usual measures reported in sources such as Woldendorp et al. (1993), Mackie and Rose (1991) and Mackie and Rose (1997). In particular, we not only use variables that measure the fragmentation of coalition governments, but also investigate measures of political change in democracies relating to composition of cabinets, and electoral volatility. The political data used is documented extensively in Carmignani (1999), and the interested reader is referred to this for further details of sources and data construction.24 In what follows, we examine the impact of political change in democracies on fiscal policy decisions in a panel of 13 European OECD countries.25 These include all of the main Western European nations, excluding Greece, Portugal and Spain because they did not have democratic regimes throughout our sample period. The reason for restricting our analysis to European countries is that the specification of our panel data model requires some homogeneity in the countries being considered. There are also some limitations in the availability of the political data for non-European OECD economies. With the exception of the UK, the European economies have electoral systems that tend to give rise to coalition governments. Although our theoretical model is cast in terms of a two-party system, the results can readily be interpreted for coalition governments. The key result, which is that government myopia leads to underspending on public investment and a shift to public consumption, will carry over in the case where the two parties (L and H) are interpreted as alternating coalitions. In this case, the probability of re-election is partly a function of fluctuating electoral preferences, but also in part dependent on the strength of the coalition. The latter will be affected by shifts in the coalition groupings, parliamentary and cabinet fragmentation between different parties, and the perceived time horizon or probability of survival of the incumbent coalition government. 24 The construction of this data set is in part from Carmignani (1999). We are grateful to him for access to his data set, which is defined for individual legislatures and governments, and which we converted to an annual data set for the purposes of our empirical work. 25 Specifically, Austria, Belgium, Denmark, Finland, France, Germany, Iceland, Ireland, Italy, the Netherlands, Norway, Sweden, the UK.

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We examine how three key fiscal ratios, the share of government investment in total government spending, ln(GI/G), and the ratios of government investment and government consumption to GDP, ln(GI/GDP) and ln(GC/GDP), are affected by a set of measures of political uncertainty and by the type of incumbent government. The variables used in our regressions are set out in Table 1. Our panel data regressions are estimated over the period26 1963 – 1996, and the regressions are estimated using a fixed-effects specification. A fixed-effects specification was seen as most appropriate given our choice of countries in the sample.27 In addition to the political variables described below, we include two lags of real GDP growth, DLY, and current and lagged changes in the unemployment rate, DUR, and an intercept dummy starting in 1990, MAAS. The DLY and DUR terms are intended to capture cyclical variations in the fiscal measures due to automatic stabilisers and not to the political environment, whilst MAAS is included to capture the fiscal consolidation process following the signing of the Maastricht Treaty. This is to ensure that we are not simply capturing a spurious correlation between the political variables and the deceleration in government spending, particularly in public investment, during the 1990s.28 We focus on a small number of indicators of political uncertainty. The first is the type of government (TOG): clearly single-party majority governments will tend to be more secure than multi-party majority governments, and these in turn will be more stable than minimal winning coalitions or minority governments. Our second measure is ENPR, the effective number of parties in government relative to the effective number of parties in parliament. A low value of ENPR is consistent with a larger and more concentrated opposition, which leads to less security of the incumbent. A higher value of ENPR implies that the government has a wider coverage within the parliament and the opposition is smaller and more fragmented. This situation should both increase the security of the incumbent and make it easier to enact plans. Finally, VOL measures the changeover in seats at elections and hence is a measure of electoral uncertainty.29 One reason for using a number of indicators of political uncertainty is that different countries display different kinds of 26

Although our political data covers the period from 1945 to 1998, we choose to use fiscal data from the OECD in order to ensure consistent definitions across the 13 countries, and this determines the sample used in estimation. The panel is unbalanced because the political data is only available up to 1995 for some countries. 27 We experimented with a random-effects specification and obtained very similar results. In the case of the random-effects models, the Hausman specification test found no significant correlation between the random effects and the regressors. 28 Whilst this ‘‘Maastricht’’ variable appears to be successful in capturing a drop in the ratio of government investment as a proportion of GDP and as a proportion of total government spending, and a deceleration in government consumption, it is worth noting that it has no impact on the signs of the coefficients on the political variables or on their statistical significance. 29 One difficulty in measuring the degree of political uncertainty or instability from data on actual electoral outcomes is that these represent measures of uncertainty as perceived ex post. This is not a perfect measure of the ex ante degree of political uncertainty and external competition experienced by the incumbent government during its term of office. Mid-term elections (where these take place) and regular opinion polls may provide a better guide to the changing pattern of electoral preferences. However, mid-term national elections tend to be the exception (cf. the United States), and it is difficult to obtain systematic opinion poll data on a comparable basis, at least for the period before 1980. All studies in this area (e.g. De Haan et al., 1996; Perotti and Kontopoulos, 2002) use ex post measures of volatility.

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Table 1 Description of economic and political variables Dependent variables ln(GI/GDP) Log(Government Investment/GDP) ln(GI/G) Log(Government Investment/Total Government Spending) ln(GC/GDP) Log(Government Consumption/GDP) Type of government TOG1 = 1 if Single-Party Majority; TOG2 = 1 if Minimal Winning Coalition; TOG3 = 1 if Multi-Party Majority Coalition; TOG4 = 1 if Single-Party Minority; TOG5 = 1 if Multi-Party Minority; TOG6 = 1 if Caretaker Government; Index of ideology ID

= 0 otherwise. = 0 otherwise. = 0 otherwise. = 0 otherwise. = 0 otherwise. = 0 otherwise.

Each party is located on a left to right scale of 1 – 10, L(i), the ID variable then weights individual parties within the government, so ID = SS(i)L(i). The median location is 5.5, so a value >5.5 indicates a right of centre government. Unlike the five-point complexion scale reported in Woldendorp et al. (1993), our data uses updated scales constructed by political scientists, capturing the increasing centralisation of parties over time. See Laver and Schofield (1990) and Carmignani (1999).

Ratio of effective number of parties in government to effective number of parties in parliament ENPR ENP measures follow Laakso and Taagepera (1979) calculated as 1/S(S(i))2, where S(i) is the share of seats held by party i. ENPR takes the ratio of ENP for the governing coalition to ENP for the parliament as a whole. A higher ratio implies wider coverage within government, making it easier to enact plans and increasing the security of the incumbent. Electoral volatility VOL The share of seats added or lost by each party at the previous election. A higher figure indicates higher volatility, reflecting volatile voter preferences, and hence greater political uncertainty. See Powell (1982) and Carmignani (1999). Conditioning variables DLY GDP Growth: DLYt = log(GDP)t  log(GDP)t  1 DLY(  i) lagged GDP Growth: DLY(  1) = DLYt  1 DUR change in the unemployment rate DUR(  i) lagged change in the unemployment rate DUR(  1) = DURt  1 MAAS Dummy variable to capture fiscal restraint following implementation of the Maastricht Treaty ( = 1 from 1990 to the end of the sample and = 0 otherwise). Interaction variables TiVOL (TOGi)*VOL TiENPR (TOGi)*ENPR

political change. For example, in Italy there was little electoral volatility in terms of parliamentary representation prior to 1994 (because of the prior pure proportional representation system), but much more volatility in the effective number of parties in

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Table 2 Panel regression results ln(GI/G) Coefficient DLY DLY(  1) DLY(  2) DUR DUR(  1) MAASC ID TOG2 TOG3 TOG4 TOG5 ENPR VOL

1.3430 1.8246 1.2856 0.0425 0.0436  0.0601  0.0313  0.2019  0.1508  0.1744  0.2804 0.0014  0.0029

ln(GI/GDP) t-stat (3.89) (5.20) (4.02) (2.95) (3.02) (  3.62) (  5.42) (  10.50) (  5.40) (  6.37) (  6.73) (3.75) (  2.36)

ln(GC/GDP)

Coefficient

t-stat

Coefficient

t-stat

0.7461 1.5264 1.0412 0.0499 0.0513  0.0989  0.0380  0.2597  0.2022  0.2261  0.3443 0.0018  0.0007

(1.92) (3.97) (2.76) (2.84) (2.87) (  4.47) (  4.82) (  8.18) (  5.27) (  5.92) (  6.11) (3.19) (  0.44)

 0.5953  0.4312  0.3769 0.0078 0.0000  0.0280 0.0015  0.0038 0.0018 0.0252 0.0412 0.0004 0.0019

(  4.74) (  3.43) (  3.55) (2.04) (0.00) (  5.35) (0.93) (  0.42) (0.17) (1.93) (2.79) (2.37) (8.20)

Weighted statistics Adjusted R2 S.E. Mean of D. Vbl.

0.9858 0.1999 3.3050

0.8831 0.2363 1.4648

0.9980 0.0714 3.9087

Unweighted statistics Adjusted R2 S.E. Mean of D. Vbl.

0.6464 0.2049 2.5591

0.5052 0.2405 1.1684

0.7738 0.0750 3.0656

Unbalanced Panel 432 observations 1963 – 1996. Estimation of each equation is by GLS using cross section weights with White’s consistent standard errors and covariances. Fixed country effects were included but are not reported to save space. TOG1 is the reference value and is omitted. TOG6 is insignificant.

the governing coalition (which affected the stability of governments). In contrast, in Belgium electoral volatility is a much more important variable. We also control for different partisan policies through an ideology variable, ID. In contrast to previous studies (e.g. Alesina et al., 1998; De Haan et al., 1996), we do not use the five-point complexion scale reported in Woldendorp et al. (1993). A disadvantage of this scale is that the ideology parameter attached to each party that has remained constant over time. Our data uses updated scales composed by political scientists and allow us to capture the increased centralisation of parties over time (see Laver and Schofield, 1990; Huber and Inglehart, 1998; Carmignani, 1999). The results from our panel regressions are set out in Tables 2 and 3. Table 2 shows the results of a common base specification. The results in Table 2 indicate that there is a clear hierarchy in the effects of TOG on investment.30 This is confirmed in both the regression for the log ratio of government investment to total government spending, ln(GI/G), and the logged investment to GDP ratio, ln(GI/GDP). The most detrimental type of government in its impact on investment is 30

The reference category is TOG1, single-party majorities.

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TOG5, multi-party minority. TOG2 and TOG4, minimal winning coalitions and single party minorities have the next largest negative effects and, whilst the impact of TOG2 is estimated to be slightly stronger than that of TOG4, these effects are not significantly different from each other (t-statistics = 0.91 and 0.86, respectively). However, as we show below, it is possible to differentiate between the effects of these types of government once we allow for interaction between the type of government, and the stability variables (VOL and ENPR). Multiparty majorities, TOG3, also invest less than single party majorities but this effect estimated to be significantly smaller than those for the minority and minimal winning governments.31 It is also clear in Table 2 that greater coverage within government and a fragmented opposition, reflected in high values of ENPR, result in more government investment. In line with our expectation that such governments are able to enact their plans more easily. Electoral volatility results in higher government consumption as a percentage of GDP and hence lower investment as a proportion of total government spending, but it does not appear to have an independent effect on investment in the ln(GI/GDP) regression. The ln(GC/GDP) regression also indicates that governments consume more if they are concentrated with fragmented opposition (high ENPR) and if they are single-party or multiparty minorities (TOG4 and TOG5). The positive effect of ENPR on ln(GC/GDP) would seem to counteract the positive impact on ln(GI/GDP), but the key point is that ln(GI/G) increases with ENPR, as predicted by theory. In addition, there seems to be a tendency for a partisan approach to public investment. We find some support for the notion that right-wing governments invest less in both the ln(GI/G) and ln(GI/GDP) regressions. This result contrasts with an earlier study (De Haan et al., 1996), which found that ideology had no significant effect on public investment. However, there are a number of differences between De Haan et al. and the present paper. First, our measure of ideology has the advantage of capturing the increased centralisation of parties over time, an effect that is not present in the Woldendorp data used by De Haan et al. Second, our estimation period, 1963– 1996, is much longer than their 1980 –1992 sample, and finally, our testing regression has a different structure so the two models are essentially non-nested. Overall, the results clearly suggest that less stable forms of government with greater electoral volatility (high VOL) and greater fragmentation of the government relative to the parliament as a whole (low ENPR) induce lower public investment as a share of total government spending, as predicted by our model. Following Perotti and Kontopoulos (2002), we also allow present results that allow for interactions between political variables and types of government, for example TOG and ENPR and TOG and VOL. Table 3 presents results from both the common general specifications and a set of specifications obtained at the end of a general-to-specific search, i.e. following successive elimination of insignificant regressors. These regressions show which types of government exhibit the greatest sensitivity of government investment and

31 No significant effect was detected from caretaker governments, TOG6, which is omitted, but this is not surprising since few of the observations in our sample relate to such governments.

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Table 3 Panel regression results ln(GI/G) 1.3791 1.7981 1.3026 0.0422 0.0397  0.0659  0.0374  0.2728  0.0526  0.1553  0.6844  0.0006 0.0014  0.0003 0.0000 0.0061 0.0054  0.0010  0.0070  0.0057 0.0065

(3.72) (4.84) (3.81) (2.96) (2.69) (  3.59) (  6.48) (  3.41) (  0.56) (  1.47) (  3.58) (  0.37) (3.05) (  0.26) (0.02) (3.05) (0.70) (  0.55) (  3.91) (  3.80) (1.68)

1.4064 1.8035 1.3279 0.0411 0.0405  0.0703  0.0354  0.2360

(4.02) (5.13) (4.16) (2.89) (2.84) (  4.84) (  6.61) (  6.91)

 0.1290  0.5419

(  4.59) (  4.62)

0.0012

(2.69)

0.0057

(3.08)

 0.0084  0.0052

(  7.20) (  4.02)

0.8407 1.5157 1.1080 0.0493 0.0486  0.1084  0.0412  0.2723  0.0391  0.1972  0.6870 0.0004 0.0014  0.0001  0.0001 0.0059 0.0102 0.0004  0.0078  0.0008 0.0082

ln(GC/GDP) (2.03) (3.71) (2.77) (2.70) (2.64) (  4.62) (  5.37) (  2.65) (  0.33) (  1.42) (  3.26) (0.19) (2.01) (  0.08) (  0.05) (2.58) (0.92) (0.19) (  3.50) (  0.33) (1.79)

0.9317 1.5901 1.1565 0.0492 0.0493  0.1124  0.0383  0.1951

(2.44) (4.22) (3.16) (2.72) (2.74) (  5.91) (  5.37) (  7.84)

 0.2346  0.5771

(  7.48) (  4.22)

0.0057

(2.67)

 0.0100

(  5.87)

 0.6046  0.4223  0.3899 0.0063 0.0003  0.0338 0.0028  0.0191 0.0687  0.0272 0.0300 0.0000 0.0001  0.0006  0.0002  0.0000 0.0024 0.0023  0.0001 0.0055 0.0028

(  4.41) (  3.26) (  3.56) (1.50) (0.08) (  6.13) (1.43) (  0.93) (2.15) (  0.71) (0.59) (0.11) (0.39) (  1.41) (  0.19) (  0.15) (0.90) (6.30) (  0.37) (4.39) (1.75)

 0.6979  0.5167  0.3735

(  6.94) (  5.00) (  4.08)

 0.0413 0.0036  0.0246 0.0278  0.0448

(  7.67) (2.10) (  2.95) (3.38) (  2.58)

0.0024

(8.78)

0.0056 0.0037

(5.14) (5.57)

Weighted statistics Adjusted R2 S.E. Mean Dep. Vbl.

0.9852 0.1978 3.2809

0.9869 0.1986 3.3511

0.8780 0.2324 1.4450

0.8959 0.2353 1.4869

0.9978 0.0704 3.8721

0.9984 0.0728 4.0567

Unweighted statistics Adjusted R2 S.E. Mean Dep. Vbl.

0.6477 0.2045 2.5591

0.6489 0.2042 2.5591

0.5064 0.2402 1.1684

0.5060 0.2403 1.1684

0.7786 0.0742 3.0656

0.7750 0.0758 3.0631

See Table 1. Unbalanced Panel 432 observations 1963 – 1996. Estimation of each equation is by GLS using cross section weights with White’s consistent standard errors and covariances. Fixed country effects were included but are not reported to save space. TOG1 is the reference value and is omitted. TOG6 is insignificant.

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DLY DLY(  1) DLY(  2) DUR DUR(  1) MAASC ID TOG2 TOG3 TOG4 TOG5 T1ENPR T2ENPR T3ENPR T4ENPR T5ENPR T1VOL T2VOL T3VOL T4VOL T5VOL

ln(GI/GDP)

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consumption to electoral volatility and the concentration of the government relative to its opposition. Once again, there is a clear hierarchy. Multi-party minorities, TOG5, are most detrimental to investment. Only if the opposition is highly fragmented as well, so that ENPR is high, is there some degree of claw-back as indicated in the positive coefficient on T5ENPR. It is now easier to separate the impact of minimal winning coalitions and single party minority governments on investment. Both have a tendency to lower investment, as indicated in the negative coefficients on TOG2 and TOG4. However, in the case of single party minorities the impact on investment is made worse by high electoral volatility (as indicated in the significant negative coefficient on T4VOL). This effect is not present for minimal winning coalitions. Instead, the negative impact of such governments can be mitigated by a concentration of parties in government and a relatively fragmented opposition (giving a high value of ENPR). Once we allow for interaction effects, the only difference between the impact of majority coalitions and single party majorities (TOG3 and TOG1) occurs through electoral volatility, which serves to reduce the investment spending of majority coalitions. The regressions involving the logged government consumption to GDP ratio, ln(GC/ GDP), add further support to these results. The estimates show that ln(GC/GDP) is higher for more volatile and less stable government forms (T5VOL, T2VOL and T4VOL) than for single-party majorities. There also seems to be a tendency for multi-party majorities (TOG3) to spend more than single-party majorities. In the final ln(GC/GDP) equation, there is also a weakly significant effect from the ideology variable, suggesting that right wing governments consume more. In general, the results from both the government investment and consumption regressions suggest that greater political uncertainty results in lower public investment and greater public consumption.32 From the point of view of finding support for our theoretical model, we would expect two results to emerge from our empirical work. First, in line with the assumption of the partisan model, we should find some link between the ideological position of the government and the fiscal policy actions taken. Second, we would expect to find that government policy is affected by political uncertainty insofar as it impacts on the perceived duration of the incumbent government’s tenure. Both of these results emerge from the panel regressions. Our results also support the notion that political uncertainty, as measured by type of government formation, measures of fragmentation in government relative to their

32 In addition to the results reported here, we also experimented with a regression for the tax/GDP ratio. These results were less clear-cut. Although our theoretical model (Proposition 2) predicts a negative correlation between government investment and taxation, it does not allow for deficit financing. Once deficit financing is introduced, the simple link between the share of public spending dedicated to investment and taxation is broken. It is well known, for instance, that in the EU countries political instability has led to debt financing and a delay in increasing taxes to fund increasing deficits, especially in coalition governments (see Alesina and Perotti, 1996, 1997). Hence, we focus our attention on the results for public investment and consumption spending rather on the financing decision, which is likely to be affected by other strategic considerations.

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opposition and electoral volatility affect public investment negatively relative to public consumption, and tend to boost government consumption.

4. Conclusion This paper has developed a theoretical model to analyse the links between political uncertainty in democracies, public investment, and productivity growth in the OECD economies. Our model shows that, with greater political uncertainty, policy myopia effects set in and rational incumbent politicians tend to reduce spending on investment, and to increase the share of government consumption in total government spending. These effects remain, even if there is a prospect of exit from office and a subsequent return to power by the incumbent politicians. Policy myopia also tends to make political parties adopt growth-discouraging policy platforms with lower taxes and lower government investment spending than their own constituency would prefer. The result is an inefficient outcome, with therefore less than maximal social welfare. The predictions of our theoretical model for the links between spending decisions and political uncertainty are supported by our empirical results. Using data on a panel of 13 European countries over the period 1963 –1996, we show that there is a strong correlation between increased political uncertainty in democracies and reductions in government investment as a proportion of total fiscal spending. We also detect significant partisan effects on government decisions on public investment. Our theoretical model complements existing political economy models of fiscal policy and political change, and provides extensions to an infinite-horizon framework and an analysis of endogenous growth. In contrast to previous contributions, our focus is on the role of the ratio of government consumption to government investment. A number of extensions of our framework are possible. One possible extension is the inclusion of an explanation for different rates of time preference amongst voters– consumers. The existence of demographic trends in an overlapping-generations model could explain why, over time, the distribution of consumer preferences might change, thus affecting fiscal policy and the long-term growth prospects of the economy. One might then be able to explain changes in political polarisation and political platforms as functions of more fundamental forces such as gradual demographic change in the industrialised economies. Acknowledgements Muscatelli gratefully acknowledges research funding from the ESRC Award R000237816. We are particularly grateful to two anonymous referees and to the editor of this journal for extremely helpful comments that improved the paper considerably. We are also grateful to participants at seminars at the Universities of Aberdeen, Bari, Bristol, Glasgow, the Royal Institute for Economic Affairs and at the Royal Economic Society Conference in Nottingham, April 1999, and the Money Macro Finance Conference in

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London, September 2000 for comments on earlier versions of the paper. The usual disclaimer applies.

Appendix A . Proof of Lemma 1 Use RHS to denote the right-hand side of Eq. (11). The first-order conditions33 are   Bu gijtþ1 ; sijt BRHS ¼ At ¼0 Bsijt Bsijt

ð19Þ

    BUi˜j ðAtþ1 Þ Bu gijtþ1 ; sijt BUij ðAtþ1 Þ BRHS ¼ At þ bi ð 1  p Þ þp ¼0 Bgijtþ1 Bgijtþ1 Bgijtþ1 Bgijtþ1

ð20Þ

where h  ai     l sijt  bgijtþ1 1a þ ð1  lÞ 1  sijt Bu gijtþ1 ; sijt il ¼ bgijtþ1 a  1l h   1a Bsijt s  bg 1s ijt

ijt

ð21Þ

ijtþ1

!l   h n a o Bu gijtþ1 ; sijt 1  sijt a i ¼b sijt  1 þ ð1  lÞ bgijtþ1 1a : a   1a 1a Bgijtþ1 sijt  bgijtþ1 ð22Þ In steady state where Uij(At + 1) = Uij0At +1, gijt +1 = gij and sijt = sij, the first-order conditions (Eqs. (19) and (20)) give  a sij ¼ 1  l þ l bgij 1a ;

ð23Þ

h i   ug gij ; sij ¼ bi ð1  pÞUij0 þ pUi0˜j

ð24Þ

where we can also write ug( gij,sij) = bll(1  l)1  l[1  (bgij)(a/1  a)/(1  a)] u ug( gij), using Eq. (23). Now in steady state, Eq. (11) becomes i  h   Uij0 ¼ u gij ; sij þ bi gij þ 1 ð1  pÞUij0 þ pUi0˜j       ¼ u gij ; sij  gij þ 1 ug gij ; sij

33 The second-order conditions for all the derivations in the appendices are available from the authors on request.

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" 1l

l

¼ bl ð1  lÞ



#  a  bgij 1a    1 uU gij 1 þ agij 1a

ð25Þ

where the second line is due to Eq. (24) and the third line is obtained after re-arrangement with the use of Eq. (23). Substituting the last line of Eq. (25) into Eq. (24) yields h  i     ð26Þ ug gij ¼ bi ð1  pÞU gij þ pU gi˜j : Given UV( gij)>0, Eq. (26) defines giH = f (giL) and giL = f (giH). Substituting one of these equations into another give giH = f ( f (giH)) and giL = f ( f (giL)), which implies gi u giL = giH. Given this result and Eq. (23), it is obvious that si u siL = siH. It is also clear from Eq. (7) that hi u hiL = hiH. Therefore, Eq. (23) is reduced to Eq. (12), and Eq. (26) can be rewritten as Eq. (13). A.1 . Unique interior solution Use EL( gi) and ER( gi) to denote the left- and right-hand sides of Eq. (13). First define giL such that E L(g iL) = 0, and g iR such that ER(g iR) = 0 (see Fig. 1). Note that g iL=(1  a)(1a)/a¯/b, ¯ ¯ by (1+ag iR)(1¯ a)/ag iR=(1  a)(1  a)/a/b. Therefore, ¯ and g iR is implicitly defined ¯ ¯ ¯ g Li > gRi ð27Þ Next, in steady state the intertemporal utility function converges to a finite value for gi < gimax where gimax = 1/bi  1 (see Eq. (10)). Given Eq. (27), therefore, at least one interior solution gi>0 exists for EL( gimax)>ER( gimax) or b/(1 + b)>bi. Moreover, such a solution gi>0 gi>0 is unique since a

a

BEL ðgi Þ aðbgi Þ 1a aðbgi Þ 1a BE R ðgi Þ ¼ > b i ð gi þ 1Þ ¼ ; 2 2 Bgi Bgi ð 1  aÞ gi ð 1  aÞ gi

ð28Þ

given gi < gimax.

Appendix B . Proof of Lemma 2 Bgi/Bbi>0 is obvious in Fig. 1. Moreover, Eq. (12) confirms that Bsi Bsi Bgi ¼ > 0: Bbi Bg Bb |{z}i |{z}i ð þÞ

ð29Þ

ð þÞ

In addition, Eq. (12) can be re-expressed as si = 1  l + lhisi using Eq. (7). This implies Bhi Bhi Bsi lsi Bsi ¼ ¼ > 0: Bbi Bsi Bbi 1  lhi Bbi |fflfflfflffl{zfflfflfflffl} |{z} ð þÞ

ð þÞ

ð30Þ

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Appendix C . Proof of Proposition 1 Use RHS to denote the right-hand side of Eq. (15). The first-order conditions are   Bu gjtþ1 ; sjt BRHS ¼ At Nj ¼0 ð31Þ Bsjt Bsjt     Bu gjtþ1 ; sjt BVj ðAtþ1 Þ BVˆ j ðAtþ1 Þ BRHS ¼ At Nj þ bj ð 1  p Þ þp ¼0 Bgjtþ1 Bgjtþ1 Bgjtþ1 Bgjtþ1

ð32Þ

where (Bu( gjt + 1,sjt)/Bsjt) and (Bu( gjt + 1,sjt)/Bgjt + 1) are the same as Eqs. (21) and (22) if the subscript i is dropped. In steady state where Vj(At + 1) = V j0At + 1, Eqs. (31) and (32) give condition Eq. (17) and h i   Nj ug gj ; sj ¼ bj ð1  pÞV 0j þ pVˆ 0j ð33Þ h i    a   where ug gij ; sij ¼ bll ð1  lÞ1l 1  bgij 1a =ð1  aÞ uug gij after rearrangement using Eq. (17). Now in steady state, Eqs. (15) and (16) become i    h V 0j ¼ Nj u gj ; sj þ bj gj þ 1 ð1  pÞV 0j þ pVˆ 0j ; ð34Þ  h i Vˆ 0j ¼ bj g˜j þ 1 ð1  pÞVˆ 0j þ pV 0j :

ð35Þ

Substituting Eq. (33) into Eq. (34) gives

      V 0j ¼ Nj u gj ; sj  gj þ 1 ug gj ; sj " ¼ Nj bll ð1  lÞ

1l



#  a  bgj 1a 1 1 þ agj 1a

ð36Þ

where the second equality uses Eq. (17). Next, plugging Eq. (36) into Eq. (35) yields " #  a     bgj 1a 1l l 1 bl ð1  lÞ Nj bj p g˜j þ 1 1 þ agj 1a 0   Vˆ j ¼ : ð37Þ 1  bj ð1  pÞ g˜j þ 1 Using Eqs. (36) and (37), Eq. (33) is rewritten as Eq. (18). C.1 . Unique interior solution The proof is essentially the same as in that of a corresponding part of Lemma 1, and hence is omitted.

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