Keywords: Fiscal consolidation, Government consumption, Government investment. JEL Codes E62, H50

In response to increasing debt paths, governments often implement fiscal consolidation programs. This paper studies the impact of these programs on the composition of government spending. System-GMM estimations performed on a sample of 53 developed and emerging countries over 1980-2011 reveal that fiscal consolidations significantly reduce the government investment-to-consumption ratio, i.e. a composition effect. Robust to a wide set of tests, this significantly stronger contraction of government investment with respect to government consumption is at work particularly when debt is high, for spending-based fiscal consolidations, in the low phase of the economic cycle, and following debt and stock market crises. Therefore, in such contexts, fiscal consolidations aimed at short-run stabilization may hurt the economy in the long-run through their detrimental effect on public investment, calling for a reflection upon how they could be re-designed to allow avoiding such undesirable consequences.

Introduction

To fight the detrimental effects of the recent financial crisis, many governments adopted large demand-based fiscal stimuli. Designed to boost economy activity, these policies resulted into large fiscal deficits and debt-to-GDP ratios. Given the danger on public finance sustainability, governments decided to implement fiscal consolidation programs.

There exists a large and increasing literature on fiscal consolidations. While surveying it is beyond the scope of this paper, important questions related to fiscal consolidations include: (i) the size of the fiscal consolidation episode, see e.g. [START_REF] Giavazzi | Non-Keynesian Effects of Fiscal Policy Changes: International Evidence and the Swedish Experience[END_REF] or [START_REF] Ardagna | Fiscal stabilizations: When do they work and why[END_REF]; (ii) its persistence, see e.g. [START_REF] Drazen | Can Severe Fiscal Contractions Be Expansionary? Tales of Two Small European Countries]: Comment[END_REF], [START_REF] Heylen | Success and failure of fiscal consolidation in the OECD: A multivariate analysis[END_REF], or [START_REF] Barrios | EU fiscal consolidation after the financial crisis -Lessons from past experiences[END_REF]; (iii) its measure, usually based on observed variables such as the cyclically-adjusted primary balance, or on the narrative approach, see e.g. [START_REF] Alesina | Tales of fiscal adjustment[END_REF]; [START_REF] Alesina | Large changes in fiscal policy: Taxes versus Spending[END_REF]; [START_REF] Cotis | Estimates of potential output: benefits and pitfalls from a policy perspective[END_REF]; [START_REF] Guajardo | Expansionary austerity? International evidence[END_REF] for comparisons of alternative methods; and (iv) the variable that adjusts, namely spending or taxes. On this last point, [START_REF] Afonso | Measuring the success of fiscal consolidations[END_REF]; [START_REF] Alesina | Tales of fiscal adjustment[END_REF]; [START_REF] Alesina | Fiscal expansions and adjustments in OECD countries[END_REF]; [START_REF] Mcdermott | An empirical analysis of fiscal adjustments[END_REF], among others, found that successful fiscal consolidations mainly rely on expenditure cuts rather than tax increases, and e.g. [START_REF] Alesina | The design of fiscal adjustments[END_REF]; [START_REF] Alesina | The output effect of fiscal consolidation plans[END_REF][START_REF] Alesina | Is it the "how" or the "when" that matters in fiscal adjustments?[END_REF]; [START_REF] Heylen | Government efficiency, institutions, and the effects of fiscal consolidation on public debt[END_REF]; [START_REF] Schaltegger | Are fiscal adjustments less successful in decentralized governments?[END_REF] conclude that fiscal consolidations led by spending cuts are more likely to generate growth and reduce deficits/debt than those led by tax hikes.

Consequently, focusing on public spending, several contributions investigated the component of public expenditure that should be cut in the process of fiscal consolidation. On the one hand, governments could reduce public investment, which is less effective for debt reduction [START_REF] Alesina | Fiscal expansions and adjustments in OECD countries[END_REF] but politically more acceptable. However, the decline in public investment may hurt overall productivity [START_REF] Aschauer | Is public expenditure productive?[END_REF], economic growth [START_REF] Abiad | The macroeconomic effects of public investment: Evidence from advanced economies[END_REF], and welfare [START_REF] Heijdra | Public investment and intergenerational distribution[END_REF], to the point where, given the current global mild economic conditions, the IMF (2014,2015) advocates for large public investment in infrastructure to sustain the global recovery after the crisis (echoing the 2014 "Juncker Plan" of the European Commission). On the other hand, governments could reduce current spending, which are more efficient for deficit reduction but may affect governments' probability of reelection [START_REF] Roubini | Political and economic determinants of budget deficits in the industrial democracies[END_REF], and raise inequality and poverty [START_REF] Agnello | How does fiscal consolidation impact on income inequality?[END_REF].

Taking stock of these studies, the goal of this paper is to analyze the effect of fiscal consolidations on the composition of public spending. Despite being of particular importance, given the benefits and costs associated with reducing each type of public spending, this issue remains fairly unexplored with the notable exception of [START_REF] Castro | The impact of fiscal consolidations on the functional components of government expenditures[END_REF]. Compared with [START_REF] Castro | The impact of fiscal consolidations on the functional components of government expenditures[END_REF], we draw upon [START_REF] Alesina | The design of fiscal adjustments[END_REF]'s novel measure of fiscal consolidations that accounts for the size and the persistence of the adjustment (instead of a dummy variable as a measure of fiscal consolidations, see also De [START_REF] De Haan | Government capital formation: Explaining the decline[END_REF] 1 ). In addition, while [START_REF] Castro | The impact of fiscal consolidations on the functional components of government expenditures[END_REF] looks at different components of government expenditure in 15 EU countries, we specifically focus on the government investment-toconsumption ratio to assess the relative change between them. Using the system-GMM estimator of [START_REF] Blundell | Initial conditions and moment restrictions in dynamic panel data models[END_REF] that properly tackles endogeneity, our findings based on a large sample of 53 developed and emerging countries over the 1980-2011 period are as follows.

First, while we confirm that fiscal consolidations reduce both the government investment-to-GDP ratio [START_REF] Balassone | Public investment in the Stability Pact framework[END_REF][START_REF] De Haan | Government capital formation: Explaining the decline[END_REF]; [START_REF] Jonakin | The impact of adjustment and stabilization policies on infrastructure spending in Central America[END_REF]; [START_REF] Turrini | Public investment and the EU fiscal framework[END_REF]; [START_REF] Välilä | Evolution and determinants of public investment in Europe[END_REF])2 and the government consumption-to-GDP ratio (Castro ( 2017))-a level effect, we reveal that the government investment-to-consumption ratio equally significantly declines-a composition effect. Consequently, government investment is found to decrease more than government consumption during fiscal consolidations.

Second, we investigate the robustness of this finding with respect to an important source of debate, namely the definition of fiscal consolidations. Moving away from [START_REF] Alesina | The design of fiscal adjustments[END_REF]'s definition (used in our baseline analysis), we consider different lengths of the period used to define a fiscal consolidation episode, as well as endogenous definitions of fiscal consolidations following [START_REF] Yang | Macroeconomic effects of fiscal adjustment: A tale of two approaches[END_REF]. Estimations with these alternative measures confirm the existence of a composition effect, and this decline of the government investment-to-consumption ratio remains robust when further controlling for periods unrelated to fiscal consolidations, or for a wide set of additional control variables.

Third, we explore the sensitivity of the composition effect with respect to fiscal conditions, the overall state of the economy, and the presence of crises. Estimations show that fiscal consolidations significantly reduce the government investment-to-consumption ratio only in a context of high debt, when they are spending-based, and in the low phase of the economic cycle. Next, we find that the contraction of the government investment-to-consumption ratio can be up to four times higher in non-OECD compared with OECD countries following fiscal consolidations. Moreover, further estimations reveal that a composition effect is at work when fiscal consolidations occur after stock market crises and particularly after debt crises, while the ratio government investmentto-consumption is not significantly affected by fiscal consolidations taking place after banking, inflation, or currency crises.

Finally, we assess the effect of fiscal consolidations on the components of public spending. While the contraction of government investment is significantly stronger than that of public wages, education, and health government spending, fiscal consolidations are associated with a higher ratio of government investment to transfers & subsidies, suggesting a relatively stronger decline of the latter with respect to the former.

The paper is organized as follows. Section 2 discusses the measurement of fiscal consolidation episodes, Section 3 presents the data and the methodology, Section 4 reports the baseline results, Section 5 analyzes their robustness, Section 6 explores the sensitivity of our findings to various economic characteristics, Section 7 looks at the sub-components of government consumption, and Section 8 concludes.

Identification of fiscal consolidation episodes

Fiscal impulse measurement

We define a discretionary fiscal consolidation episode following the cyclically-adjusted primary balance (CAPB) approach developed by [START_REF] Blanchard | Suggestions for a new set of fiscal indicators[END_REF], and adopted by [START_REF] Alesina | Fiscal expansions and adjustments in OECD countries[END_REF]1997) and [START_REF] Alesina | Tales of fiscal adjustment[END_REF]2013), which consists of extracting the discretionary part of fiscal variables, excluding interest payments. Following [START_REF] Alesina | Fiscal expansions and adjustments in OECD countries[END_REF], we build the CAPB in two steps. First, we regress for each country revenues R t and spending G t (in ratio of GDP) on a linear time trend (TREND) and the unemployment rate U t , to obtain the cyclically-adjusted revenues and spending (in ratio of GDP)

R t = α 0 + β 0 T REN D + γ 0 U t + t ,
(1)

G t = α 1 + β 1 T REN D + γ 1 U t + u t .
(2)

Using the estimated parameters we compute what would have been revenues and spending in time t if the unemployment rate has remained constant between t and t -1

R * t (U t-1 ) = α0 + β0 T REN D + γ0 U t-1 , ( 3
)
G * t (U t-1 ) = α1 + β1 T REN D + γ1 U t-1 . (4)
Second, we construct the discretionary change in the fiscal balance as the difference between the cyclically-adjusted fiscal variables in year t, and their respective values in year t -1

CAP B t = [R * t -R t-1 ] -[G * t -G t-1 ].
(5)

Definition of fiscal consolidation episodes

There are several ways to define a fiscal consolidation episode, usually based on a threshold value related to the size or the persistence of the change in the fiscal policy (see [START_REF] Yang | Macroeconomic effects of fiscal adjustment: A tale of two approaches[END_REF], for a summary of different definitions). We define our fiscal consolidation episode following [START_REF] Alesina | The design of fiscal adjustments[END_REF].

Definition 1. A fiscal consolidation is either:

(1) the value of the fiscal retrenchment over a 2-year period if the ratio CAPB/GDP improves each year, and the cumulative improvement is of at least 2 percentage points, or

(2) the value of the fiscal retrenchment over a 3-year or more period if the ratio CAPB/GDP improves each year, and the cumulative improvement is of at least 3 percentage points. This definition has several merits. First, it uses the novel approach that includes both the size and the persistence in the assessment of fiscal consolidations, whereas the size refers to the amplitude (intensity) of the CAPB/GDP change, and the persistence captures the length of the adjustment. Considering both features can overcome the famous "stop-and-go" problem in the fiscal consolidations literature. Second, it ensures the comparability of our analysis with the recent literature on fiscal consolidations that widely draws upon this definition (see e.g. [START_REF] Alesina | Large changes in fiscal policy: Taxes versus Spending[END_REF]2013); [START_REF] Leigh | Will it hurt? Macroeconomic effects of fiscal consolidation[END_REF][START_REF] Guajardo | Expansionary austerity? International evidence[END_REF][START_REF] Yang | Macroeconomic effects of fiscal adjustment: A tale of two approaches[END_REF].

We identified 123 fiscal consolidation episodes during our considered period of 32 years. Figure 1 depicts the distribution of these episodes in percentage of the total number of fiscal consolidations in our sample, based on their size and persistence. Among them, 65 fiscal consolidations (52.85%) last 2 years, 19 (15.45%) last 3 years, and so on (see the Appendix for the list of fiscal consolidations); and 50 fiscal consolidations (40.65%) improve the fiscal balance between 2-4 percentage points of GDP, 38 (30.89%) between 4-6 percentage points of GDP, and so forth. 3 Data, and methodology

Data

Our study is performed in an unbalanced panel covering the period 1980-2011. Using [START_REF] Mauro | A modern history of fiscal prudence and profligacy[END_REF] database, which provides the widest coverage of fiscal aggregates to our knowledge, we obtained data for 56 developed and emerging countries. However, the need of unemployment data to build the CAPB forced us to exclude three countries, leading to a sample of 53 countries. We refrained from considering developing countries in our sample, given the high quality data on unemployment required by the computation of the CAPB. Our dependent variables are government investment (GI), and government final consumption (GC). Government investment includes government expenditure devoted to fixed and durable goods, such as roads, energy, and telecommunications infrastructures (source: (IMF, 2017) database). According to the National Accounting System, government final consumption encompasses all current expenditure used for purchasing goods and services, excluding the military materials that are included in the government investment, but including compensation of employees and interest payments (source: WDI, 2016).

Control variables are those that can impact government spending, and may even affect fiscal consolidations, classified in two groups. First, the macroeconomic variables are (i) debt (DEBT ), (ii) real growth (GROW T H), (iii) private investment (IP RIV ), (iv) foreign direct investment (F DI), (v) aid (AID), (vi) remittances (REM IT ), (vii) trade openness (T RADE), (viii) natural resources rents (N AT R), (ix) terms of trade (T OT ), and (x) a dummy variable capturing the impact of being under an IMF program (IM F P ); except real growth and the IMF program dummy, all variables are in ratio of GDP, and aid is in ratio of GNI. Second, we consider variables related to population, namely: (i) population growth (P OP r), (ii) the share of population above 65 years old (P OP 65), (iii) the urban rate (U RB), and (iv) the log of population size (LP OP ); and to institutions, namely: (v) a left-wing governments dummy (EXECL), (vi) the political color of the legislature (P COL), (vii) the presence of an electoral period (EXELEC), and (viii) government stability (GOV ). The Appendix reports the sources, definitions, and descriptive statistics of variables.

The econometric model

We estimate the following dynamic model with country-fixed effects

GI it = α 0 + ρ 0 GI it-1 + β 0 CON S it + β k 0 X k it + v i + it , ( 6
)
GC it = α 1 + ρ 1 GC it-1 + β 1 CON S it + β k 1 X k it + µ i + u it . ( 7
)
The dependent variable GI it (GC it ) stands for government investment (consumption) in ratio of GDP, ρ accounts for inertia in the dynamics of GI or GC, β k is the marginal effect of each of the k control variable, v i (µ i ) are country-fixed effects, and it (u it ) is the error term. The coefficient of interest is β 0 (β 1 ), which captures the effect of our fiscal consolidation variable (CON S) on GI it (GC it ).

We use the Blundell and Bond (1998) system-GMM estimator in our baseline model, for the following reasons. First, OLS lead to bias estimates, since they do not account for country-unobserved heterogeneity. However, the country-fixed effects estimator is also inconsistent when the time panel dimension is short, due to the correlation between the lagged dependent variable and the error terms [START_REF] Nickell | Biases in dynamic models with fixed effects[END_REF]. Besides, [START_REF] Hauk | A Monte Carlo study of growth regressions[END_REF] emphasize that the fixed-effects estimator worsens the bias related to measurement errors, and undervalues the impact of covariates in a dynamic panel setting with time-persistent regressors, as in our case. Second, while the difference-GMM estimator copes with the heterogeneity bias in the first-difference step and mitigates endogeneity issues, it suffers from a weak-instrument problem due to the weak correlation between lagged variables in level and variables in first-difference in the presence of time-persistence [START_REF] Alonso | Symmetrically normalized instrumental-variable estimation using panel data[END_REF]. Third, the system-GMM provides more consistent and efficient estimators than the difference-GMM in dynamic panels in the presence of highly-persistent variables over time ( [START_REF] Blundell | Initial conditions and moment restrictions in dynamic panel data models[END_REF] and [START_REF] Blundell | Estimation in dynamic panel data models: Improving on the performance of the standard GMM estimator[END_REF]). Finally, the system-GMM provides a smaller bias (in terms of size) than the difference-GMM or the fixed-effects estimators, even when the required stationary condition is doubtful [START_REF] Hauk | A Monte Carlo study of growth regressions[END_REF].

Baseline results

Our baseline results are presented in Tables 1,2, and 3. When implementing the system-GMM estimator, we overcome the proliferation of instruments by collapsing the matrix of instruments to have less instruments than countries [START_REF] Roodman | A note on the theme of too many instruments[END_REF]. 3 In addition to the strong effect of the lagged depending variable, the use of the system-GMM estimator is equally supported by usual diagnostic tests, namely valid instruments (see the p-value of the Hansen test), and the presence (absence) of first-order (second-order) autocorrelation in the dependent variable as shown by the AR(1) (AR(2)) test.

Level effects

According to Table 1, fiscal consolidations significantly decrease GI on average, even in the presence of different control variables. Analogously, fiscal consolidations equally significantly decrease GC on average, as shown by Table 2. 4It is then interesting to compare the effect of fiscal consolidations on GI and GC. As shown by Tables 12, fiscal consolidations are found to decrease both variables. In terms of magnitude, based on columns (8) of Tables 12, a one percentage point increase of the ratio CAPB/GDP (under a fiscal consolidation) reduces the GI (GC) ratio by 0.085 (0.100) percentage points. However, concluding that these coefficients are statistically different (or not) is a fairly complicated task, given that they are of comparable size (all the more if we take into account standard errors), and are extracted from different regressions. In addition, when estimating the effect of fiscal consolidations on GI (GC), we use GC (GI) ratio as a covariate, i.e. the impact of fiscal consolidations on government investment (consumption) is computed for a given level of government consumption (investment); as such, we capture a pure level effect, and cannot assess their relative change. To deal with this issue in a more appropriate manner, we look in the following at the composition effect of fiscal consolidations.

The composition effect: government investment versus government consumption

To evaluate the relative response of the two types of public spending, we modify equations ( 6)-( 7) and look at the effect of fiscal consolidations on the ratio GI/GC

GI it GC it = α 2 + ρ 2 GI it-1 GC it-1 + β 2 CON S it + β k 2 X k it + λ i + ξ it , (8)
with GI it GC it the ratio between government investment and consumption. Table 3 presents the results. As shown by regression (1), fiscal consolidations significantly decrease the ratio GI/GC. Corroborated with the individual decline previously emphasized for GI and GC, it comes that the relative change in the government investment ratio is stronger than the relative change in the government consumption ratio. With respect to an early literature, which insisted on the fact that fiscal consolidations tend to reduce government investment (see e.g. [START_REF] Oxley | Controlling Government Spending and Deficits: Trends in the 1980s and Prospects for the 1990s[END_REF]Martin (1991), or De Haan et al. (1996)), our findings suggest that government consumption is equally reduced following fiscal consolidations, consistent with the view that challenges its importance for the likelihood of government's reelection [START_REF] Peltzman | Voters as fiscal conservatives[END_REF], Alesina et al. (1998)). However, the composition effect that we reveal suggests that fiscal consolidations lead to a more important cut in government investment than in government consumption.

Robustness

In this section we explore the robustness of our baseline results in several ways.

Alternative definitions of fiscal consolidations

In [START_REF] Alesina | The design of fiscal adjustments[END_REF]'s definition used to compute fiscal consolidations in the baseline specification, the threshold is somehow arbitrary. To check whether our findings are sensitive to a particular threshold, we consider the following alternative definitions of fiscal consolidations.

First, compared with the baseline definition of 2 years & 2 percentage points (hereafter pp), or 3 years & 3 pp, we increase the threshold to stress the fact that the change in fiscal policy is discretionary. With "threshold 1", a fiscal consolidation episode is signalled by either 2 years of consecutive CAPB improvement of at least 2.5 pp of GDP, or 3 years & 3.5 pp improvement; while for "threshold 2" ("threshold 3"), the corresponding numbers are 2 years & 3 pp (4 pp), or 3 years and 4 pp (5 pp). As shown by columns ( 2)-( 4) in Table 4, using these different thresholds to define fiscal consolidations has little impact on the significance or the magnitude of their effect on the GI/GC ratio compared with our baseline results reported in column (1). Second, since countries do not present the same deficit level or the same structural capacity to reduce it, we allow the threshold to vary with respect to the country-specific average (me) and standard deviation (sd) in CAPB changes. Following [START_REF] Yang | Macroeconomic effects of fiscal adjustment: A tale of two approaches[END_REF], "def 1" designs a fiscal consolidation episode defined as: (i) a one-year fiscal consolidation, if the CAPB improvement is at least me+sd for this year, except if the CAPB falls by me+sd in the previous or next year; or (ii) a two-year (three-year or more) fiscal consolidation, if the CAPB improves in the first year by at least me+1/4sd and the cumulative improvement is of at least me+sd (me+3/2sd); and (iii) a fiscal consolidation stops if the CAPB does not improve in one year or improves by less than me+1/4sd, and the cumulative improvement over the following year is of at least me+1/4sd; however, the fiscal consolidation continues if the variation of the CAPB ranges between me+1/4sd and me-1/4sd in this year. Similarly, "def2" and "def3" use the multiples (3/4,1/4,1,3/2) and (2,3/4,2,3) of the standard deviation to construct alternative fiscal consolidations measures. As shown by columns

(1)-(3) of Table 5, despite some magnitude loss, fiscal consolidations are still significantly related with a decrease in the GI/GC ratio.

Third, we further account for country-specific heterogeneities, and particularly for international trade shocks on fiscal policy, by including the terms of trade, in addition to the unemployment rate, when computing the CAPB. As such, a fiscal consolidation episode is signaled by: (i) a 2-year period in which the CAPB improves each year and the cumulative improvement is of at least 2*(mesd) pp; or (ii) a 3-year or more period in which the CAPB improves each year and the cumulative improvement is of at least 3*(me-sd) pp. Despite a lower magnitude compared with the baseline, column (4) of Table 5 confirms yet again the negative effect of fiscal consolidations on the GI/GC ratio.

A "Placebo-test" of fiscal consolidations

Our baseline specification includes only changes in the CAPB during fiscal consolidation episodes. Indeed, we assume that the effect of fiscal consolidations is specific, and not related to discretionary changes in fiscal policy during "normal" times. To take a closer look at this assumption, we introduce in equations ( 6)-( 8) the change in CAPB during the periods of no fiscal consolidations (N CON S it ), following [START_REF] Alesina | The design of fiscal adjustments[END_REF]. Results in Table 6 support our assumption, since the effect of N CON S is rarely and weakly significant. More importantly, we confirm the bias against public investment, since the effect of fiscal consolidations on the GI/GC ratio remains significant and negative.

Additional control variables

We introduce several additional control variables, related to (i) the financing of development (foreign direct investment, aid, remittances, and natural resources rents), to account for a crowding-in/out effect, (ii) the structure of the economy (urban population, and population growth), to capture the burden of the population on government's fiscal stance, and (iii) institutions (the political tendency of the government party, the political color of the legislature, and the electoral period), to control for potential partisan cycles. As shown by Table 17 in the Appendix, the negative effect of fiscal consolidations on the ratio GI/GC is still at work when controlling for these additional variables.

Heterogeneity

This section analyzes the sensitivity of the effect of fiscal consolidations on the GI/GC ratio with respect to fiscal conditions (the debt level, and the adjustment fiscal variable), the overall state of the economy (in the short-run: the position in the business cycle, and in the long-run: the development stage), and financial conditions (financial crises).

Fiscal conditions: the debt level, and the adjustment fiscal variable

First, fiscal consolidations are usually designed to reduce public debt. Consequently, it is appealing to see if their effect depends on the debt level. We use the median of the distribution of the average debt for each consolidation period (equal to 53%, in ratio of GDP) to differentiate between fiscal consolidations arising in high-debt (CON S HD it ) and low-debt (CON S LD it ) contexts. According to Table 7, fiscal consolidations significantly reduce the GI/GC ratio only in a context of high debt, consistent with previous findings of strong public investment contraction in damaged fiscal stance (see e.g. [START_REF] Bacchiocchi | Public investment under fiscal constraints[END_REF].

Second, fiscal consolidations can be performed through spending-cuts or tax-hikes (or a combination of the two). To see if the composition of the adjustment matters, we split fiscal consolidation episodes into "tax-based" adjustments (CT AX it ) for which most of the variation in the CAPB is due to tax hikes, and "spending-based" adjustments (CSP EN D it ) for which most of the variation in the CAPB is due to a reduction in spending [START_REF] Mcdermott | An empirical analysis of fiscal adjustments[END_REF], [START_REF] Guajardo | Expansionary austerity? International evidence[END_REF], or [START_REF] Yang | Macroeconomic effects of fiscal adjustment: A tale of two approaches[END_REF] equally use such a distinction). Table 8 shows that, once we account for control variables (see from column 3 onwards), only fiscal consolidations based on spending-cuts robustly reduce the GI/GC ratio, suggesting that revenue-increasing strategies based on taxes may be a virtuous way to protect government investment.

The state of the economy

First, we consider the state of the economy in the short-run, captured by the phase of the business cycle. Drawing upon the popular [START_REF] Hodrick | Postwar US business cycles: an empirical investigation[END_REF] filter to compute the cyclical component of GDP, we distinguish between "bad" times (CON S LC it ) and "good" times (CON S HC it ). As shown by Table 9, fiscal consolidations significantly reduce the GI/GC ratio only during bad times, corroborating to some extent our finding of a significant effect exclusively in high-debt contexts.

Second, we look at the state of the economy in the long-run, captured by the development stage. Despite most of the literature being devoted to developed countries, fiscal consolidations may impact differently the composition of public spending in OECD compared with non-OECD emerging countries, given the differences in their respective structural characteristics. Estimations reported in Table 10 show that this is indeed the case: although fiscal consolidations significantly reduce the GI/GC ratio in both OECD and non-OECD countries, the magnitude of the estimated coefficient can be up to four times higher in the latter group of countries (for example, if we compare columns 3 and 6). This may be related to a stronger political instability in non-OECD countries, making governments not to take electoral risks associated with cutting consumption spending.

Crises

In addition to the fiscal and economic conditions, the decision of governments to implement fiscal consolidations may be determined by the occurrence of crises. We consider five types of crises, namely debt, banking, inflation, currency, and stock market crises, and we are interested in fiscal consolidation episodes that occur between one and four years after the beginning of a crisis. Results reported in column (1) of Table 11 show that fiscal consolidations arising after a crisis significantly reduce the GI/GC ratio. This overall significant effect is driven by a significant effect of consolidations following stock market crises (column 6), and particularly debt crises (column 2). Indeed, debt and stock market crises put a high pressure on the fiscal balance and increase the risk of a systemic crisis; our results show that the required fiscal space is achieved by a stronger cut in public investment compared with public consumption. Finally, fiscal consolidations occurring after the beginning of banking, inflation, or currency crises were not found to significantly affect the GI/GC ratio, which may illustrate the fact that the policies required during these crises rest relatively less on government funds.

The sub-components of government consumption

So far, we focused on aggregate government consumption (GC) spending. We now investigate the effects of fiscal consolidations on disaggregated GC components, expressed in ratio of GDP. First, public wages (W AGE) measure the remuneration of public sector employees, and their consolidation may affect the welfare of the population. Second, transfers & subsidies (SU B) act as a distributional tool of national income, and their consolidation may affect population's living standards, and particularly the poor population. Third, health spending (HEALT H) are related to the healthcare system and social protection. Finally, education spending (EDU C) support the development of human capital, and may influence potential economic growth. Using these variables we look both at the level and the composition effect. Regarding the level effect, Table 12 shows that the decrease of the GC ratio emphasized in our baseline analysis is mainly driven by the contraction of health and education government spending. On the contrary, fiscal consolidations lead to an increase in public wages, while transfers & subsidies are not significantly affected. Regarding the composition effect, Table 13 shows that the decline in GI is stronger than the contraction of public wages, education, and health government spending, corroborating our previous results based on aggregate measures of GC. However, fiscal consolidations are found to increase the ratio between GI and transfers & subsidies, suggesting a strong decline of the latter, relatively more important than the decline of the former.

Conclusion

Existing studies emphasize a negative effect of fiscal consolidations on government investment and consumption as ratios of GDP [START_REF] Balassone | Public investment in the Stability Pact framework[END_REF]; [START_REF] Castro | The impact of fiscal consolidations on the functional components of government expenditures[END_REF][START_REF] De Haan | Government capital formation: Explaining the decline[END_REF]; [START_REF] Jonakin | The impact of adjustment and stabilization policies on infrastructure spending in Central America[END_REF]; [START_REF] Turrini | Public investment and the EU fiscal framework[END_REF]; [START_REF] Välilä | Evolution and determinants of public investment in Europe[END_REF]). This paper looked at the effect of fiscal consolidations on the ratio between government investment and consumption. System-GMM estimations performed on a sample of 53 developed and emerging countries during the period 1980-2011 revealed that the contraction of government investment is more important than that of government consumption, i.e. a composition effect is at work, robust to a wide range of alternative specifications.

Given the large impact of both government consumption and investment on the economy documented by the existing literature, we investigated more in detail this composition effect. In particular, we found that public investment may be particularly affected by fiscal consolidations (i.e. its contraction may be stronger than that of public consumption) when debt is high, for spendingbased fiscal consolidations, in the low phase of the economic cycle, and following debt and stock market crises. Consequently, our findings suggest that caution should be at work in such contexts, during which fiscal consolidations aimed at short-run stabilization may hurt the economy in the long-run through their detrimental effect on public investment. Future work could be devoted to exploring possible mechanisms in the design of fiscal consolidations that may allow avoiding such undesirable consequences.

Figure 1 -

 1 Figure 1 -Distribution of the fiscal consolidation episodes by persistence and size

Table 1 -

 1 The effect of fiscal consolidations on the government investment-to-GDP ratio Standard errors are in brackets. Regressions are based on the Blundell-Bond estimator. Lagged GI is predetermined, lagged debt is exogenous, and the remaining covariates are endogenous variables.

		(1)	(2)	(3)	(4)	(5)	(6)	(7)	(8)
	GI it-1	0.903 * * *	0.798 * * *	0.894 * * *	0.620 * * *	0.734 * * *	0.636 * * *	0.636 * * *	0.928 * * *
		(0.191)	(0.241)	(0.256)	(0.196)	(0.198)	(0.094)	(0.089)	(0.068)
	CON S it	-0.103 * * * -0.096 * * * -0.122 * * * -0.099 * * * -0.100 * * * -0.085 * * * -0.085 * * *	-0.085 * * *
		(0.025)	(0.028)	(0.034)	(0.028)	(0.025)	(0.020)	(0.019)	(0.024)
	GC it		-0.023	-0.010	0.004	0.002	0.001	-0.005	0.007
			(0.054)	(0.062)	(0.057)	(0.052)	(0.057)	(0.054)	(0.042)
	DEBT it-1			-0.004	-0.002	-0.002	-0.002	-0.002	-0.005
				(0.003)	(0.002)	(0.002)	(0.003)	(0.002)	(0.005)
	GROW T H it				-0.016	-0.005	-0.005	-0.003	0.018
					(0.014)	(0.014)	(0.011)	(0.010)	(0.013)
	T RADE it					-0.008 *	-0.007 * *	-0.007 *	-0.014 * * *
						(0.004)	(0.004)	(0.004)	(0.005)
	IP RIV it						-0.028	-0.031	-0.071 * *
							(0.027)	(0.028)	(0.033)
	IM F P it							-0.183	-0.121
								(0.231)	(0.196)
	GOV it								-0.002
									(0.013)
	N	1393	1280	1220	1220	1219	1219	1219	1152
	groups	53	48	48	48	48	48	48	48
	N_instr	8	9	11	13	16	19	20	20
	AR(1)	0.004	0.026	0.012	0.020	0.012	0.000	0.000	0.000
	AR(2)	0.212	0.355	0.566	0.481	0.404	0.286	0.311	0.245
	Hansen	0.191	0.079	0.044	0.282	0.653	0.701	0.677	0.112

5 * p < 0.1, * * p < 0.05, * * * p < 0.01

Table 2 -

 2 The effect of fiscal consolidations on the government consumption-to-GDP ratio Standard errors are in brackets. Regressions are based on the Blundell-Bond estimator. Lagged GC is predetermined, GDP growth and fiscal consolidation are endogenous, and the remaining covariates are exogenous.

		(1)	(2)	(3)	(4)	(5)	(6)	(7)	(8)
	GC it-1	0.760 * * * 0.733 * * * 0.916 * * *	0.867 * * *	0.896 * * *	0.895 * * *	0.893 * * *	0.925 * * *
		(0.072)	(0.089)	(0.063)	(0.071)	(0.065)	(0.065)	(0.073)	(0.061)
	CON S it	-0.145 * * -0.135 * * -0.125 * * * -0.102 * *	-0.101 * *	-0.102 * *	-0.094 * *	-0.100 * *
		(0.062)	(0.060)	(0.047)	(0.049)	(0.045)	(0.044)	(0.044)	(0.046)
	GI it		0.403 * *	0.474 * * *	0.450 * * *	0.409 * * *	0.385 * * *	0.356 * * *	0.181 * *
			(0.157)	(0.093)	(0.112)	(0.107)	(0.108)	(0.101)	(0.092)
	DEBT it-1			-0.010	-0.013 * *	-0.012 * *	-0.012 * *	-0.013 * *	-0.013 * *
				(0.007)	(0.006)	(0.006)	(0.006)	(0.006)	(0.006)
	GROW T H it				-0.080 * * * -0.073 * * * -0.067 * * * -0.065 * * *	-0.082 * * *
					(0.023)	(0.021)	(0.024)	(0.024)	(0.023)
	T RADE it					-0.018 * *	-0.017 * *	-0.015 * *	-0.017 * *
						(0.008)	(0.007)	(0.007)	(0.007)
	IP RIV it						-0.034	-0.042	-0.027
							(0.040)	(0.041)	(0.026)
	IM F P it							-0.226	-0.103
								(0.259)	(0.200)
	GOV it								-0.000
									(0.034)
	N	1278	1278	1218	1218	1218	1218	1218	1151
	groups	48	48	48	48	48	48	48	48
	N_instr	20	12	13	13	12	13	16	16
	AR(1)	0.001	0.002	0.002	0.003	0.002	0.002	0.002	0.003
	AR(2)	0.454	0.592	0.601	0.641	0.518	0.529	0.603	0.852
	Hansen	0.163	0.054	0.775	0.708	0.865	0.869	0.787	0.278

* p < 0.1, * * p < 0.05, * * * p < 0.01

Table 3 -

 3 The effect of fiscal consolidations on the GI/GC ratio Standard errors are in brackets. Regressions are based on the Blundell-Bond estimator. Lagged GI/GC is predetermined, lagged debt, government stability and IMF program are exogenous, and the remaining covariates are endogenous.

		(1)	(2)	(3)	(4)	(5)	(6)	(7)
	GIit-1 GCit-1	0.817 * * * 0.701 * * *	0.712 * * *	0.731 * * * 0.674 * * * 0.678 * * *	0.811 * * *
		(0.201)	(0.141)	(0.156)	(0.170)	(0.106)	(0.109)	(0.179)
	CON S it	-0.392 * * -0.546 * * * -0.512 * * * -0.495 * * * -0.400 * * -0.394 * *	-0.419 * *
		(0.193)	(0.188)	(0.168)	(0.171)	(0.157)	(0.159)	(0.196)
	DEBT it-1		-0.021	-0.019	-0.026	-0.032	-0.032	-0.026
			(0.020)	(0.021)	(0.021)	(0.020)	(0.020)	(0.030)
	GROW T H it			0.112	0.137	0.158	0.156	0.285 * * *
				(0.120)	(0.142)	(0.111)	(0.123)	(0.098)
	T RADE it				-0.0225	-0.0241	-0.0235	-0.0290
					(-0.67)	(-0.84)	(-0.81)	(-0.84)
	IP RIV it					-0.255	-0.256	-0.444 *
						(0.241)	(0.252)	(0.228)
	IM F P it						0.577	-0.023
							(0.806)	(0.820)
	GOV it							-0.029
								(0.072)
	N	1278	1218	1218	1218	1218	1218	1151
	groups	48	48	48	48	48	48	48
	N_instr	7	8	11	14	17	18	19
	AR(1)	0.006	0.001	0.002	0.003	0.001	0.001	0.003
	AR(2)	0.309	0.452	0.467	0.484	0.587	0.611	0.806
	Hansen	0.165	0.543	0.763	0.800	0.805	0.789	0.685

* p < 0.1, * * p < 0.05, * * * p < 0.01

Table 4 -

 4 Fiscal consolidations and the GI/GC ratio: alternative definitions of thresholds

	Alternatives	Baseline	threshold 1	threshold 2	threshold 3
		(1)	(2)	(3)	(4)
	GI it-1 GC it-1	0.811***(0.179)	0.809***(0.182)	0.803***(0.165)	0.828*** (0.165)
	CON S it	-0.419**(0.196)	-0.431** (0.207)	-0.484** (0.205)	-0.489** (0.219)
	N	1151	1151	1151	1151
	Groups	48	48	48	48
	N_instr	19	19	19	22
	AR(1)	0.003	0.003	0.002	0.002
	AR(2)	0.806	0.812	0.822	0.871
	Hansen	0.685	0.682	0.645	0.823
	Controls	Yes	Yes	Yes	Yes

Standard errors are in brackets. Regressions are based on the Blundell-Bond estimator. Lagged GI/GC is predetermined, lagged debt, government stability and IMF program are exogenous, and the remaining covariates are endogenous. We introduce lagged debt, GDP growth, trade, private investment, IMF program and government stability as explanatory variables.

* p < 0.1, * * p < 0.05, * * * p < 0.01

Table 6 -

 6 The effect of fiscal consolidations on the GI/GC ratio: no consolidation episodes

		(1)	(2)	(3)	(4)	(5)	(6)	(7)
	GI it-1 GC it-1	0.781 * * * 0.737 * * * 0.742 * * * 0.797 * * * 0.758 * * * 0.789 * * *	0.856 * * *
		(0.179)	(0.110)	(0.098)	(0.102)	(0.085)	(0.071)	(0.164)
	CON S it	-0.289 * * -0.531 * * * -0.477 * * * -0.472 * * * -0.358 * * -0.342 * *	-0.395 * *
		(0.143)	(0.176)	(0.153)	(0.163)	(0.169)	(0.169)	(0.179)
	N CON S it	-0.131	-0.082	-0.118	-0.130	-0.118 *	-0.121 *	-0.121
		(0.108)	(0.071)	(0.083)	(0.088)	(0.060)	(0.066)	(0.095)
	N	1278	1218	1218	1218	1218	1218	1151
	groups	48	48	48	48	48	48	48
	N_instr	10	11	14	17	19	25	26
	AR(1)	0.006	0.000	0.000	0.000	0.000	0.000	0.003
	AR(2)	0.324	0.464	0.507	0.515	0.585	0.551	0.736
	Hansen	0.231	0.708	0.874	0.811	0.694	0.813	0.839
	Standard errors are in brackets. Regressions are based on the Blundell-Bond estimator. Starting
	from the most parsimonious specification (column 1), we progressively introduce lagged debt, GDP
	growth, trade, private investment, IMF program, and government stability in columns (2)-(7).

* p < 0.1, * * p < 0.05, * * * p < 0.01

Table 7 -

 7 The effect of fiscal consolidations on the GI/GC ratio: debt level sensitivity * * 0.821 * * * 0.806 * * * 0.864 * * * 0.832 * * * 0.805 * * * 0.820 * * * 0.872 * * *

		(1)	(2)	(3)	(4)	(5)	(6)	(7)	(8)
	GI it-1 GC it-1	0.871 (0.209)	(0.189)	(0.179)	(0.194)	(0.200)	(0.146)	(0.131)	(0.063)
	CON S HD -0.914 * * *		-0.880 * * * -0.929 * * * -0.792 * * * -0.743 * * * -0.747 * * * -0.839 * * *
		(0.289)		(0.289)	(0.266)	(0.292)	(0.250)	(0.255)	(0.290)
	CON S LD		-0.055	-0.057	-0.076	-0.009	0.006	-0.004	0.060
			(0.221)	(0.225)	(0.229)	(0.186)	(0.175)	(0.174)	(0.175)
	N	1278	1278	1278	1278	1278	1278	1278	1180
	groups	48	48	48	48	48	48	48	48
	N_instr	7	7	10	13	16	19	20	21
	AR(1)	0.005	0.004	0.004	0.003	0.005	0.002	0.001	0.000
	AR(2)	0.291	0.291	0.303	0.298	0.449	0.634	0.642	0.964
	Hansen	0.293	0.235	0.419	0.536	0.544	0.617	0.562	0.739

*

Standard errors are in brackets. Regressions are based on the Blundell-Bond estimator. Starting from the most parsimonious specification (columns 1-3), we progressively introduce GDP growth, trade, private investment, IMF program, and government stability in columns (

4

)-(

8

).

* p < 0.1, * * p < 0.05, * * * p < 0.01

Table 8 -

 8 The effect of fiscal consolidations on the GI/GC ratio: the adjustment variable

		(1)	(2)	(3)	(4)	(5)	(6)	(7)
	GI it-1 GC it-1	0.898 * * * 0.760 * * * 0.682 * * * 0.703 * * * 0.665 * * * 0.665 * * *	0.752 * * *
		(0.137)	(0.101)	(0.124)	(0.140)	(0.089)	(0.090)	(0.059)
	CT AX it	-0.480 * * -0.368 * *	-0.337	-0.369	-0.248	-0.261	-0.140
		(0.211)	(0.164)	(0.287)	(0.291)	(0.241)	(0.248)	(0.146)
	CEXP D it -0.579 * * * -0.471 * * -0.435 * * -0.387 * * -0.307 * * -0.302 * *	-0.452 * *
		(0.209)	(0.195)	(0.201)	(0.188)	(0.145)	(0.142)	(0.204)
	N	1278	1218	1218	1218	1218	1218	1151
	groups	48	48	48	48	48	48	48
	N_instr	12	15	14	17	20	21	23
	AR(1)	0.001	0.000	0.001	0.002	0.000	0.000	0.000
	AR(2)	0.313	0.377	0.465	0.493	0.582	0.606	0.792
	Hansen	0.340	0.572	0.655	0.718	0.748	0.748	0.669
	Standard errors are in brackets. Regressions are based on the Blundell-Bond estimator. Starting
	from the most parsimonious specification (column 1), we progressively introduce lagged debt, GDP
	growth, trade, private investment, IMF program, and government stability in columns (2)-(7).

* p < 0.1, * * p < 0.05, * * * p < 0.01

Table 9 -

 9 The effect of fiscal consolidations on GI/GC: the phase of the business cycle * * 0.826 * * * 0.733 * * * 0.719 * * * 0.729 * * * 0.698 * * * 0.704 * * * 0.828 * * * Standard errors are in brackets. Regressions are based on the Blundell-Bond estimator. Starting from the most parsimonious specification (columns 1-3), we progressively introduce GDP growth, trade, private investment, IMF program, and government stability in columns (4)-(8).

		(1)	(2)	(3)	(4)	(5)	(6)	(7)	(8)
	GI it-1 GC it-1	0.812 (0.207)	(0.232)	(0.180)	(0.191)	(0.173)	(0.121)	(0.133)	(0.056)
	CON S LC	-0.384		-0.727 * * * -0.676 * * * -0.682 * * * -0.649 * * * -0.641 * * -0.648 * * *
		(0.245)		(0.253)	(0.244)	(0.226)	(0.245)	(0.256)	(0.215)
	CON S HC		4.324	-0.219	-0.156	-0.238	-0.059	-0.048	-0.118
			(7.090)	(0.226)	(0.265)	(0.282)	(0.211)	(0.226)	(0.137)
	N	1278	1278	1218	1218	1218	1218	1218	1151
	groups	48	48	48	48	48	48	48	48
	N_instr	7	8	11	14	15	20	21	22
	AR(1)	0.008	0.049	0.005	0.006	0.005	0.001	0.001	0.000
	AR(2)	0.303	0.864	0.375	0.375	0.430	0.500	0.519	0.735
	Hansen	0.129	0.195	0.321	0.391	0.489	0.501	0.479	0.374

* * p < 0.1, * * p < 0.05, * * * p < 0.01

Table 10 -

 10 The effect of fiscal consolidations on the GI/GC ratio: OECD vs non-OECD countries

		(1)	(2)	(3)	(4)	(5)	(6)
	GI it-1 GC it-1	0.931 * * * 0.903 * * * 0.895 * * *	0.769 * * *	0.639 * * *	0.776 * * *
		(0.064)	(0.041)	(0.043)	(0.230)	(0.159)	(0.062)
	CON S it	-0.306 * * -0.232 * -0.155 * * *	-0.535 * *	-0.722 * * *	-0.628 * *
		(0.148)	(0.134)	(0.055)	(0.257)	(0.246)	(0.257)
	N	646	625	578	632	593	573
	groups	21	21	21	27	27	27
	N_instr	15	12	20	7	8	19
	AR(1)	0.003	0.003	0.002	0.017	0.008	0.001
	AR(2)	0.194	0.273	0.330	0.300	0.498	0.747
	Hansen	0.243	0.166	0.250	0.207	0.552	0.745
	Dvp. stage OECD	OECD	OECD	Non-OECD Non-OECD	Non-OECD
	Standard errors are in brackets. Regressions are based on the Blundell-Bond estimator. Starting
	from the most parsimonious specification (columns 1 and 4), we progressively introduce lagged
	debt in columns (2) and (5), and GDP growth, trade, private investment, IMF program, and
	government stability in columns (3) and (6).

* p < 0.1, * * p < 0.05, * * * p < 0.01

Table 11 -

 11 The effects of fiscal consolidations on the GI/GC ratio: crises Standard errors are in brackets. Regressions are based on the Blundell-Bond estimator. Lagged GI/GC is predetermined, lagged debt, government stability and IMF program are exogenous, and the remaining covariates are endogenous. CON S DC , CON S BC , CON S IC , CON S CC , and CON S SM design fiscal adjustments occurring within 1 to

		(1)	(2)	(3)	(4)	(5)	(6)
	GI it-1 GC it-1	0.811 * * * 0.790 * * * 0.932 * * * 0.816 * * * 0.817 * * *	0.834 * * *
		(0.179)	(0.053)	(0.085)	(0.108)	(0.129)	(0.075)
	CON S it	-0.419 * *
		(0.196)
	CON S DC		-0.952 * *
			(0.464)
	CON S BC			-0.116
				(0.387)
	CON S IC				0.159
					(0.800)
	CON S CC					0.071
						(0.312)
	CON S SM						-0.400 * *
							(0.197)
	N	1151	1151	1151	1151	1151	1151
	groups	48	48	48	48	48	48
	N_instr	19	17	19	19	19	20
	AR(1)	0.003	0.000	0.000	0.001	0.001	0.000
	AR(2)	0.806	0.973	0.646	0.757	0.800	0.628
	Hansen	0.685	0.566	0.327	0.599	0.474	0.397

Table 12 -

 12 The effect of fiscal consolidations on theGC sub-components (in GDP ratio) Standard errors are in brackets. Regressions are based on the Blundell-Bond estimator. Lagged Dep_V ar t-1 is predetermined, lagged debt, government stability and IMF program are exogenous, and the remaining covariates are endogenous. For each sub-component, we also control by the other sub-components of government consumption.

		(1)	(2)	(3)	(4)
		W AGE	SU B	HEALT H EDU C
	Dep_V ar it-1 0.673 * * * 0.582 * * *	0.909 * * *	0.525 * * *
		(0.057)	(0.076)	(0.120)	(0.103)
	CON S it	0.094 * *	0.011	-0.099 * * *	-0.039 * *
		(0.044)	(0.120)	(0.035)	(0.018)
	N	457	461	451	417
	groups	41	41	41	41
	N_instr	30	24	33	25
	AR(1)	0.054	0.024	0.001	0.043
	AR(2)	0.647	0.822	0.358	0.410
	Hansen	0.557	0.587	0.136	0.282

* p < 0.1, * * p < 0.05, * * * p < 0.01

Table 13 -

 13 The effect of fiscal consolidations on the ratio GI/GC-sub-components Standard errors are in brackets. Regressions are based on the Blundell-Bond estimator. Lagged Dep_V ar t-1 is predetermined, lagged debt, government stability and IMF program are exogenous, and the remaining covariates are endogenous.

		(1)	(2)	(3)	(4)
		GI_W AGE GI_SU B GI_HEALT H GI_EDU C
	DepV ar it-1	0.778 * * *	0.490 * * *	0.997 * * *	0.769 * * *
		(0.098)	(0.013)	(0.017)	(0.045)
	CON S it	-0.864 *	13.676 * *	-0.655 * *	-0.808 * *
		(0.479)	(6.804)	(0.273)	(0.400)
	N	167	223	732	711
	groups	17	17	48	48
	N_instr	16	16	26	29
	AR(1)	0.107	0.266	0.036	0.020
	AR(2)	0.320	0.594	0.274	0.599
	Hansen	0.312	0.681	0.318	0.415

Table 16 -

 16 Summary statistics

		count mean	sd	min	max
	GI	1455	4.1	2.5	0.2	21.9
	GC	1333	16.2	4.8	3.0	43.5
	GI/GC	1333	28.7 22.2	1.4	203.7
	CONS	1393	0.5	1.1	0	13.5
	TRADE	1340	63.4 31.7 11.5 190.1
	IPRIV	1455	15.8	5.5	0.4	36.2
	REMIT	1250	1.2	2.3	0.0	21.6
	AID	609	1.7	4.8	-0.7	72.1
	GROWTH 1449	3.2	3.5 -13.4 18.3
	DEBT	1438	54.9 32.6	4.1	231.0
	NATR	1451	2.6	4.3	0	33.8

Table 17 -

 17 The effect of fiscal consolidations on the GI/GC ratio: other controls p < 0.1, * * p < 0.05, * * * p < 0.01

		(1)	(2)	(3)	(4)	(5)	(6)
	GI it-1 GC it-1	0.822 * * *	0.830 * * *	0.717 * * *	0.824 * * *	0.788 * * *	0.728 * * *
		(0.202)	(0.122)	(0.085)	(0.043)	(0.031)	(0.092)
	CON S it	-0.408 * *	-0.815 * * *	-0.515 * * *	-0.800 * * *	-0.436 * *	-0.508 * * *
		(0.200)	(0.305)	(0.150)	(0.242)	(0.221)	(0.153)
	F DI	0.020
		(0.031)
	AID		0.191 * * *
			(0.047)
	DEBT it-1			-0.019	-0.002	-0.009	-0.018
				(0.018)	(0.015)	(0.020)	(0.018)
	T OT			0.394 * * *			0.384 * * *
				(0.055)			(0.069)
	P COL				0.747	1.059 *
					(0.588)	(0.629)
	EXECL				-0.431	-0.366
					(0.425)	(0.425)
	EXELEC				-0.310	0.038
					(0.852)	(0.711)
	CON S_L				0.646 * *
					(0.294)
	GROW T H						0.098
							(0.076)
	N AT R						0.148
							(0.226)
	N	1254	528	1191	982	982	1191
	groups	48.000	22.000	47.000	41.000	41.000	47.000
	N_instr	10.000	8.000	11.000	14.000	20.000	15.000
	AR(1)	0.006	0.002	0.000	0.001	0.001	0.001
	AR(2)	0.307	0.373	0.358	0.037	0.027	0.312
	Hansen	0.360	0.455	0.732	0.609	0.171	0.865
	Standard errors in parentheses

*

Alternatively, Oxley and Martin (1991) draw upon descriptive statistics.

Following the pioneering work of[START_REF] Musgrave | The nature of budgetary balance and the case for the capital budget[END_REF],[START_REF] Blanchard | Improving the SGP through a proper accounting of public investment[END_REF], among others, defended the idea of a "golden rule" of public finance, for protecting public investment by excluding it from the accountancy of the Stability and Growth Pact (SGP)

3% deficit rule. For a theoretical analysis of the golden rule, see e.g.[START_REF] Minea | Borrowing to Finance Public Investment? The 'Golden Rule of Public Finance' Reconsidered in an Endogenous Growth Setting[END_REF].

Études et Documents n° 8, CERDI, 2019

In addition, we report that the variables are stationary (results are available upon request).

Only few control variables are significant. For example, an increase in private investment sometimes raises GI, but does not affect GC, suggesting that substitution effects between private and public investment may be at work. Conversely, higher economic growth and debt reduce only GC, the latter effect arising probably because of the reallocation of resources towards the payment of the increasing debt burden. Finally, higher trade is associated with a decrease in both GI and GC.

This result can be intuitively supported as follows. The mean of the government investment ratio (4.13%) is roughly four times lower than the mean of the government consumption ratio (16.22%). Since the negative effect of fiscal consolidations is roughly the same (see the coefficients of CON S in Tables1-2), the relative decrease of the GI ratio is stronger. However, what Table 3 adds, in particular, is that this decrease is significant. According to the last column of Table3, an improvement of the CAPB of 1.70 percentage points of GDP (the average CAPB improvement during fiscal consolidations) reduces the GI/GC ratio by roughly 3.8 percentage points of GDP in the long-run.

years after the starting of sovereign debt, banking, inflation, currency, and stock market crises, respectively.* p < 0.1, * * p < 0.05, * * * p < 0.01

* p < 0.1, * * p < 0.05, * * * p < 0.01

 1984-1985;[START_REF] Oxley | Controlling Government Spending and Deficits: Trends in the 1980s and Prospects for the 1990s[END_REF]-1993;[START_REF] Heijdra | Public investment and intergenerational distribution[END_REF]-20043 Australia 1983-1988;;1993-19972 Austria 1996-1997;;[START_REF] Heylen | Success and failure of fiscal consolidation in the OECD: A multivariate analysis[END_REF][START_REF] Blundell | Estimation in dynamic panel data models: Improving on the performance of the standard GMM estimator[END_REF]2 Belgium 1984-1987;;1993-1995 [START_REF] Nickell | Biases in dynamic models with fixed effects[END_REF]-1982;1990-19972 Chile 1987[START_REF] Aschauer | Is public expenditure productive?[END_REF]1994-1995;2003-2006;2010[START_REF] Bacchiocchi | Public investment under fiscal constraints[END_REF]4 China 2004-20071 Colombia 1985-1987;[START_REF] Heylen | Success and failure of fiscal consolidation in the OECD: A multivariate analysis[END_REF][START_REF] Blundell | Estimation in dynamic panel data models: Improving on the performance of the standard GMM estimator[END_REF]2003-20043 Costa Rica 1981-1982;[START_REF] Oxley | Controlling Government Spending and Deficits: Trends in the 1980s and Prospects for the 1990s[END_REF][START_REF] Peltzman | Voters as fiscal conservatives[END_REF]1995-19973 Denmark 1983-1986;;2003[START_REF] Välilä | Evolution and determinants of public investment in Europe[END_REF]2 Dominican Republic 2004-20071 Finland 1984-1985;1988[START_REF] Aschauer | Is public expenditure productive?[END_REF]1993-1994;1996-19984 France 1994-1999 ; ;2010[START_REF] Bacchiocchi | Public investment under fiscal constraints[END_REF]2 Germany 1982-1985;;1996[START_REF] Heylen | Success and failure of fiscal consolidation in the OECD: A multivariate analysis[END_REF]2004-20073 Greece 1986-1987;;1990[START_REF] Oxley | Controlling Government Spending and Deficits: Trends in the 1980s and Prospects for the 1990s[END_REF][START_REF] Välilä | Evolution and determinants of public investment in Europe[END_REF]-20063 Honduras 1985[START_REF] Aschauer | Is public expenditure productive?[END_REF], 1995-1996;;2003-20043 Hong kong 2006-2007;;[START_REF] Roodman | A note on the theme of too many instruments[END_REF]-20102 Hungary 1999[START_REF] Heylen | Success and failure of fiscal consolidation in the OECD: A multivariate analysis[END_REF]2003-2004;2007-20083 Iceland 1990[START_REF] Peltzman | Voters as fiscal conservatives[END_REF]2004 1993-1995;1997[START_REF] Heylen | Success and failure of fiscal consolidation in the OECD: A multivariate analysis[END_REF]2004-20073 Italy 1982-1983;;1988[START_REF] Peltzman | Voters as fiscal conservatives[END_REF]1995-1997;2006 1985-1988;[START_REF] Peltzman | Voters as fiscal conservatives[END_REF]-1995;[START_REF] Heylen | Success and failure of fiscal consolidation in the OECD: A multivariate analysis[END_REF][START_REF] Välilä | Evolution and determinants of public investment in Europe[END_REF]3 Nicaragua 1991[START_REF] Peltzman | Voters as fiscal conservatives[END_REF]1997-1998;2010[START_REF] Bacchiocchi | Public investment under fiscal constraints[END_REF]3 Norway 1981-1985;;1988-1990;1993-1996;1999[START_REF] Heylen | Success and failure of fiscal consolidation in the OECD: A multivariate analysis[END_REF]2004-20065 Pakistan 1988-1990 ; ;1993-1994;1998-1999;2006-20074 Panama 1985-1986;;[START_REF] Aschauer | Is public expenditure productive?[END_REF]-1990;[START_REF] Välilä | Evolution and determinants of public investment in Europe[END_REF]-20073 Paraguay 1985-1986;;[START_REF] Aschauer | Is public expenditure productive?[END_REF]-1990;1993-1994;2003-20044 Peru 1984-1985;;1988[START_REF] Aschauer | Is public expenditure productive?[END_REF]2004-2007;2010[START_REF] Bacchiocchi | Public investment under fiscal constraints[END_REF]4 Portugal 1981-1984;;[START_REF] Heijdra | Public investment and intergenerational distribution[END_REF]-2003;2006-2007;2010- 1994-1995;1998-1999;2004-20073 South Korea 1995[START_REF] Heylen | Success and failure of fiscal consolidation in the OECD: A multivariate analysis[END_REF]1 Spain 1983-1988;2010[START_REF] Bacchiocchi | Public investment under fiscal constraints[END_REF]2 Sweden 1981-1987;;1993-1998;2004[START_REF] Välilä | Evolution and determinants of public investment in Europe[END_REF]3 Switzerland 1992-1996;;[START_REF] Välilä | Evolution and determinants of public investment in Europe[END_REF]-20062 Turkey 1981-1983;;1994-1995;1998-1999;[START_REF] Heijdra | Public investment and intergenerational distribution[END_REF][START_REF] Välilä | Evolution and determinants of public investment in Europe[END_REF]4 United Kingdom 1981-1986 ;1995[START_REF] Heylen | Success and failure of fiscal consolidation in the OECD: A multivariate analysis[END_REF]2010-


Yu-Jun Cui
email: cui@cermes.enpc.fr.

Anh-Minh Tang

Altin Theodore Mantho

Emmanuel De Laure

Monitoring field soil suction using a miniature tensiometer

Keywords: Field monitoring, suction, miniature tensiometer, TDR, volumetric water content, water retention curve

An experimental device was developed to monitor the field soil suction using miniature tensiometer. This device consists of a double tube system that ensures a good contact between the tensiometer and the soil surface at the bottom of the testing borehole. This system also ensures the tensiometer periodical retrieving without disturbing the surrounding soil. This device was used to monitor the soil suction at the site of Boissy-le-Châtel, France. The measurement was performed at two depths (25 and 45 cm) during two months (May and June 2004). The recorded suction data are analyzed by comparing with the volumetric water content data recorded using TDR (Time Domain Reflectometer) probes as well as the meteorological data. A good agreement between these results was observed, showing a satisfactory performance of the developed device.

Introduction

Unsaturated soil mechanics is often applied to geotechnical problems such as embankments, dams, pavements, foundations, landfills, slopes, nuclear waste disposals, etc. Analyzing such problems requires information about soil suction variations. This explains why significant effort has been made from all over the world on suction measurement techniques under field conditions. [START_REF] Rahardjo | Suction measurements[END_REF] presented several devices and techniques that are used for in situ soil suction measurement. Jet fill tensiometer and small-tip tensiometer are often used to instrument soil slopes [START_REF] Rahardjo | Response of a residual soil slope to rainfall[END_REF]. [START_REF] Konrad | Desiccation of a sensitive clay: field experimental observations[END_REF] used small-tip tensiometer to observe the desiccation of sensitive clay in field. In general, the soil suction range of these tensiometers is below 100 kPa. [START_REF] Ng | Performance of an unsaturated expansive soil slope subjected to artificial rainfall infiltration[END_REF] used thermal conductivity sensor to measure higher suctions in an unsaturated swelling soil slope. The highest suction recorded reached 900 kPa. Although the suction range was enlarged using thermal conductivity sensor, hysteresis phenomenon and long time for stabilization are still the drawbacks of this technique [START_REF] Nichol | Long-term measurement of matric suction using thermal conductivity sensors[END_REF]. Wray et al. (2005) reported field data from three test sites where soil suction was measured using thermocouple psychrometer. The suction range for the involved soils varied from 100 kPa to 10 MPa. According to [START_REF] Andraski | Thermocouple psychrometry[END_REF], the monitoring of soil suction with psychrometer technique in the near surface zone (less than 0.4 m depth) could be affected by the temperature variations. However, as [START_REF] Cui | Field simulation of in-situ water content and temperature changes due to ground-atmospheric conditions[END_REF] reported, in practice only the suction in the near surface zone varies significantly under soil-atmosphere interaction.

Miniature tensiometer has been widely employed in laboratory tests to measure the soil matric suction (Tarantino andTombolato 2005, Singh and[START_REF] Singh | Estimation of unsaturated hydraulic conductivity using soil suction measurements obtained by an insertion tensiometer[END_REF]. It has been observed that the initial good saturation of tensiometer is essential to obtain a maximum measured suction; otherwise, the cavitation phenomenon can occur before the real soil suction is captured. Two techniques are often used to ensure a satisfactory saturation [START_REF] Take | Tensiometer saturation and the reliable measurement of soil suction[END_REF]: i) initial water percolation under vacuum, ii) cyclic pre-pressurization (high pressure application and cavitation under high suction).

In the present work, a miniature tensiometer was used to monitor the field suction in the near surface zone (at 25 and 45 cm depth). An experimental procedure was developed to install the miniature tensiometer in field. The variation of soil suction during 2 months was interpreted using the recorded meteorological data and the water volumetric content changes measured using TDR probes.

Field conditions and experimental devices

The field monitoring test was performed at a location near the village of Boissy-le-Châtel, France, which is located at about 50 km east of Paris, in the South of the Orgeval basin, at an altitude of 133 m above sea level. Since 1996, meteorological data and soil volumetric water content changes have been recorded by CEMAGREF, the French public organization devoted to agricultural and environmental engineering research. More details on this instrumented field site can be found in [START_REF] Cui | Field simulation of in-situ water content and temperature changes due to ground-atmospheric conditions[END_REF]. The soil can be classified as a silty soil and its Atterberg limits are: plastic limit PL = 20 %, liquid limit LL = 29 %.

The meteorological data and soil volumetric water content recorded during May and June 2004 are presented in Figure 1. Four main rainfall periods can be observed: (1) from May 4 to May 8; (2) from May 30 to June 1; (3) on June 11; (4) from June 19 to June 22. The daily mean wind speed varies between 2 and 18 km/h (data from May 18 th to June 10 th were not recorded).

The global solar radiation (R) decreases during the rainfall periods (down to 90 W/m 2 on May 9) and increases after each rainfall period (up to 1300 W/m 2 ) on June 6. On the other hand, the air relative humidity (RH) increases during the rainfall periods (up to 100 %) and varies between 60 and 80 % in other days. As May and June correspond to the beginning of the summer, it can be observed that the air temperature (T) trends to rise and soil water content trends to decrease.

The schematic diagram of the miniature tensiometer is presented in Figure 2a. The high-air entry value (HAEV) ceramic stone (1.5 MPa) is stuck on the tensiometer body in stainless steel, with epoxy glue. The water reservoir volume is minimized with a distance of 0.1 mm between the porous stone and the diaphragm. The strain gauges that are stuck on the other side of the diaphragm allowed the monitoring of water pressure applied on the diaphragm after a preliminary calibration.

Prior to use, the tensiometers were saturated by pre-pressurizing with de-aired water at high pressure (until 4 MPa). They were then calibrated in the positive pressures rang and the calibration curve in the negative pressures was extrapolated. All the calibration tests were performed at temperature controlled laboratory conditions, at 20 °C. Similar procedure was described by [START_REF] Tarantino | Experimental procedures and cavitation mechanisms in tensiometer measurements[END_REF]. In order to estimate the effect of temperature on the response of tensiometer, the tensiometers were calibrated at constant pressure and changing temperature (from 20 °C to 32 °C). It was observed that the pressure given by the tensiometer increases with the temperature rise, at a rate of 1 kPa/°C. This value is close to that obtained by [START_REF] Hoffmann | Thermal effect on response of high suction tensiometer[END_REF]; it was used to make corrections of the recorded suction at Boissy-le-Châtel site.

The schematic diagram of the in-situ suction measurement system is showed in Figure 2b.

This system consists of two PVC (Polyvinyl chloride) tubes (see also Figure 2c). The outer tube (63 mm in exterior diameter) is equipped with a metallic leading edge at the lower end. This facilitates insertion of the tube in soil and the centering of the inner tube. Several O-rings are installed to make the system waterproof.

To install this system in field, a hole is first bored by pushing the outer PVC tube, which is equipped with metallic leading edge, in the soil. When the tube reaches the depth planned for suction monitoring, the soil surface in the bottom of the hole is leveled and cleaned. To provide better contact between the soil and the outer tube, the tube is coated within a thin layer of soil paste. This layer would prevent any "short-circuit" infiltration from the ground surface along the tube during rainfall. Finally, the φ63 mm support is installed to fix the outer tube.

The procedure of tensiometer installation is described as follows:

-fix the tensiometer, which is previously saturated in laboratory, to the inner tube; -coat a thin layer of the soil paste on the surface of the tensiometer to prevent any desaturation of the porous stone during installation; -install the inner tube until it reaches the desired depth where the tensiometer is in contact with the soil surface; -install the φ50 mm support and the shutter support.

The TDR probe contains three waveguide stainless steel rods; each being 20 cm long and 0.3 cm in diameter.

Experimental results

The field suction was monitored at two depths (25 and 45 cm) during May and June 2004 and results are presented in Figure 3a. It can be observed that the suction values increase during this period. This is consistent with air temperature and soil water content changes (Figure 1).

To prevent the cavitation due to air diffusion from soil to water reservoir through the porous stone, the tensiometer was changed every two or three weeks for re-saturation in laboratory. The changing process lasted about half an hour and resulted in a suction reduction. In Figure 3a, the installations of tensiometer correspond to the points where the suction drops down to zero.

During these two months, four rainfall periods were recorded (Figure 3b). Except the last rainfall period from June 19 to June 22, the rainfall periods induced a slight reduction of suction at the two depths. The results are zoomed in Figure 3c,d,e where the variation of suction is presented with respect to time. During the first period (from May 4 to May 8, Figure 3c), a suction reduction of 8 kPa was recorded at the two depths. In addition, this reduction took place at almost the same time. On the contrary, during the other rainfall periods (from May 30 to June 1, Figure 3d, and on June 11, Figure 3e), the suction reduction at 25 cm was less significant than at 45 cm: the rainfall on May 30 caused a suction reduction of 15 kPa at 45 cm depth and 5 kPa at 25 cm depth; the rainfall on June 1 induced a suction reduction of 5 kPa at 45 cm depth but an insignificant change at 25 cm depth; the rainfall on June 11 resulted in a suction decrease of 25 kPa at 45 cm depth and 8 kPa only at 25 cm depth.

Discussion

It can be observed that in low suction range (20 -160 kPa), the tensiometer can be used to monitor the suction changes during more than two weeks without cavitation. After the last changes of tensiometers on June 7 (45 cm) and June 10 (25 cm), the tensiometers were left in the field for three weeks. Despite this longer duration, no cavitation was observed. Nevertheless, the authors expected that with higher field suction, this duration would be shorter because of a probable more significant air diffusion from soil to the water reservoir of tensiometer. Indeed, the periodical changes of tensiometers should be more frequent. [START_REF] Tarantino | Experimental procedures and cavitation mechanisms in tensiometer measurements[END_REF] observed that cavitation occurred after 4 days at 1275 kPa suction when using this type of tensiometer.

A daily fluctuation of the suction values at the two depths can be observed in Figure 3d. The fluctuation at deeper level (45 cm) seems to be smaller than at near surface level (25 cm). That can be attributed to the daily fluctuation of air temperature. Indeed, the soil at shallower level is more influenced by climate than at deeper level. For example, during May 31, the suction at 25 cm depth varied from 70 kPa to 75 kPa when air temperature varied from 7 °C to 20 °C.

Assuming that the soil temperature at 25 cm depth is equal to the air temperature, the corresponding value of ∆logs/∆T is -2.3×10 -3 (1/°C). This value is in the same order of magnitude with the value estimated by [START_REF] Tang | Controlling suction by the vapour equilibrium technique at different temperatures and its application in determining the water retention properties of MX80 clay[END_REF] by considering the interfacial tension changes with temperature, ∆logs/∆T = -1.1×10 -3 (1/°C).

For further discussion, the results measured by tensiometer and by TDR probes are plotted in Figure 4. These are well known water retention curves. It appears that no unique relationship exists for the two depths. In addition, for each depth, the fluctuation in suction is quite significant, which can be related to the changes in climatic conditions, especially in terms of rainfalls. As pointed out by several researchers [START_REF] Pham | A study of hysteresis models for soilwater characteristic curves[END_REF] the water retention curve depends on soil suction history: because of the well known hysteresis phenomenon there are two bounding curves which delimit a zone where any changes in water content with suction changes are possible. The upper bounding curve corresponds to the drying curve from fully saturated state, whereas the lower one corresponds to the wetting curve from a dry state at residual water content. In Figure 4, the two bounding curves are plotted.

The hysteresis phenomenon can be used to explain the suction changes observed during the rainfall periods (Figure 3a,b): it was observed that for the two rainfalls on May 30 and June 11 the deeper tensiometer (45 cm depth) showed a more significant suction decrease than the shallow tensiometer (25 cm depth). From Figure 4, it can be seen that the water retention curve at 45 cm depth situates above the curve at 25 cm depth. Thus, the curve at 45 cm depth is closer to the bounding drying curve and the curve at 25 cm depth is closer to the bounding wetting curve. During rainfall, as both of the two curves tend to rejoin the bounding wetting path, the resulted suction decrease at 45 cm depth must be more significant than that at 25 cm depth.

Conclusions

A miniature tensiometer was used to monitor in situ soil suction at the site of Boissy-le-Châtel at two depths (25 and 45 cm). An experimental device was developed that allowed a periodical changing of the tensiometer for re-saturation without disturbing the soil. A changing frequency of two weeks was generally applied to avoid tensiometer cavitation. It was observed that even with a longer monitoring duration of three weeks, the tensiometers did not cavitate with a suction ranging from 20 to 160 kPa. However, it is believed that in case of higher field suctions, the monitoring duration would be shorter because of a probable more significant air diffusion from soil to the water reservoir of tensiometer.

Data recorded during two months (May and June 2004) are found to be in good agreement with meteorological conditions and in situ water content measurement by TDR probes. The suction tended to increase, in concordance with the air temperature rise and the soil water content decrease. In the near surface zone, the suction seems to be influenced by temperature changes, at a rate: ∆logs/∆T = -2.3×10 -3 (1/°C). Abrupt suction decreases were observed during rainfall periods. In addition, the decrease was different for the two considered depth; the decrease was more significant at 45 cm depth.

Hysteresis seems to be the origin of this difference. Indeed, because during the monitoring period the retention curve at 25 cm depth is closer to the bounding wetting curve than that at 45 cm depth, any rainfall would lead to a more significant suction decrease at 45 cm depth.

11 Wray, W. K., El-Garhy, B., and Youssef, A. A., 2005, "Three-dimensional model for moisture and volume changes prediction in expansive soils," Journal of Geotechnical and Geoenvironmental Engineering,Vol. 131,No. 3,.

Figure 1 .

 1 Figure 1. Meteorological data and soil water content during May and June 2004.

Figure 2 .Figure 3 .

 23 Figure 2. Schematic layout of miniature tensiometer (a), the in-situ suction measurement system (b), and picture of the inner tube and the outer tube (c).

  n d i n g d r y i n g c u r v e B o u n d i n g w e t t i n g c u r v e

Figure 4 .

 4 Figure 4. Volumetric water content versus suction.

Acknowledgement

The authors are grateful to CEMAGREF for providing data about climate condition and soil volumetric water content, as well as for making easier the suction monitoring, at Boissy-le-Châtel site.