Policy Research Working Paper 8957 Are Budget Rigidities a Source of Fiscal Distress and a Constraint for Fiscal Consolidation? Ercio Muñoz Eduardo Olaberria Macroeconomics, Trade and Investment Global Practice August 2019 Policy Research Working Paper 8957 Abstract This paper studies whether budget rigidities affect the prob- that relatively high shares of rigid (observed) components of ability of countries getting into fiscal distress and reduce the public spending contribute to countries getting into fiscal likelihood of governments performing fiscal adjustments. distress and are a constraint for fiscal consolidation. The Budget rigidities are constraints that limit the ability of the paper finds evidence that a relatively high share of nonstruc- government to change the size and structure of the public tural rigid spending contributes to the probability of fiscal budget in the short term. Budget rigidities stem from dif- distress and reduces the probability of fiscal consolidation. ferent institutional arrangements and therefore can take Moreover, the effect of rigid expenditure seems to be more different forms. To build an indicator of rigid spending relevant for economies with high inequality, governments that is comparable across a large set of countries, this paper with lower margins of majority, and countries with lower employs a simple definition based on budget components institutional quality. In addition, when looking at the that are naturally inflexible: the sum of public wages, pen- composition of the measure of rigid expenditure, there is sions, and debt service. It decomposes this measure into also some evidence that higher expenditure on pensions a structural component and a nonstructural component. reduces the probability of fiscal adjustment more robustly Then, the paper applies a linear probability model to a panel than higher expenditure on wages. of 182 advanced and developing countries. A key finding is This paper is a product of the Macroeconomics, Trade and Investment Global Practice. It is part of a larger effort by the World Bank to provide open access to its research and make a contribution to development policy discussions around the world. Policy Research Working Papers are also posted on the Web at http://www.worldbank.org/prwp. The authors may be contacted at eolaberria@worldbank.org and emunozsaavedra@gradcenter.cuny.edu. The Policy Research Working Paper Series disseminates the findings of work in progress to encourage the exchange of ideas about development issues. An objective of the series is to get the findings out quickly, even if the presentations are less than fully polished. The papers carry the names of the authors and should be cited accordingly. The findings, interpretations, and conclusions expressed in this paper are entirely those of the authors. They do not necessarily represent the views of the International Bank for Reconstruction and Development/World Bank and its affiliated organizations, or those of the Executive Directors of the World Bank or the governments they represent. Produced by the Research Support Team Are Budget Rigidities a Source of Fiscal Distress and a Constraint for Fiscal Consolidation? Ercio Muñoz and Eduardo Olaberria1 Keywords: Fiscal consolidation, budget rigidities, fiscal policy JEL codes: H60 E62, E32 1 The authors are very thankful to Carlos Vegh, Guillermo Vuletin, Franziska Ohnsorge, and Santiago Herrera for very helpful comments and suggestions. Contents 1. Introduction ...................................................................................................................................... - 2 - 2. Literature review............................................................................................................................... - 8 - 3. Conceptual framework ................................................................................................................... - 10 - 4. Estimation methodology ................................................................................................................. - 12 - I. Identifying fiscal adjustment need.............................................................................................. - 12 - II. Identifying fiscal adjustment....................................................................................................... - 13 - III. Measuring budget rigidities .................................................................................................... - 14 - IV. Estimation framework ............................................................................................................ - 15 - V. Results ............................................................................................................................................. - 16 - On the determinants of need of fiscal adjustment......................................................................... - 16 - Probability of a successful fiscal adjustment .................................................................................. - 21 - VI. Robustness checks ...................................................................................................................... - 27 - VII. Conclusion ................................................................................................................................... - 29 - References .............................................................................................................................................. - 31 - Appendix 1: Literature Review ................................................................................................................ - 34 - Appendix 2: Episodes of fiscal need and fiscal adjustment .................................................................... - 37 - Appendix 3: Linear probability models: .................................................................................................. - 47 - Appendix 4: Logit models:....................................................................................................................... - 53 - Appendix 5: Conditional logit models: .................................................................................................... - 61 - Appendix 6: Model with sample selection correction ............................................................................ - 69 - Appendix 7: Linear probability model controlling for size of the need (primary gap) ........................... - 73 - Appendix 8: Linear probability model with dependent variable identified as Lavigne (2011) ............... - 77 - Appendix 9: Linear probability model with need under stressed conditions ......................................... - 81 - -1- 1. Introduction The aftermath of the 2008 global financial crisis has shown a clear contrast between OECD and Latin American countries: while, in general, OECD countries have already gone through successful fiscal consolidation processes to adjust their primary deficits, in Latin America these fiscal deficits have continued to increase (Figure 1). Figure 1: General government primary net lending/borrowing (2008-2017) Source: WEO (April 2018) As a result, many countries in the region are facing daunting fiscal challenges following a substantial surge in debt-to-GDP ratios during recent years (Figure 2). Estimates of fiscal gaps suggest that substantial and sustained fiscal tightening will be needed in nearly all countries to bring debt down to prudent levels (Vegh et al, 2017). Furthermore, as world interest rates continue to rise, public debt sustainability will become a major concern in many countries in the region, obliging more governments to generate high primary surpluses to stabilize their debt dynamics. In other words, fiscal consolidation is now the order of the day in the region, and while strong growth would help, the bulk of consolidation will require specific reforms to spending and revenue programs to stabilize and then reduce debt-to-GDP ratios. This raises a very important question from the policy point of view: why has it been harder for governments in Latin America to adjust their fiscal deficits? Although there are many possible answers to this question, a common one among policy makers in the region is that the ability of the governments to -2- follow large fiscal adjustments is constrained by political and institutional factors. For instance, when explaining why it was difficult to further adjust the fiscal deficit in Uruguay, Minister Danilo Astori emphasized there was little room for maneuver because of the "growing participation of endogenous expenditure, which is very difficult to reduce". 2 Figure 2: Most countries in Latin America have seen substantial surge in debt-GDP ratios Source: WEO (2018) What minister Astori calls “endogenous expenditure” is known in the literature as budget rigidities (see Centrángolo et al., 2010). Budget rigidities are institutional, legal, contractual or other constraints that limit the ability of the government to change the size and structure of the public budget, at least in the short term. They are a source of frustration to politicians who find little space to move ahead their government programs. Budget rigidities stem from different institutional arrangements that limit the government’s ability to adjust the composition and size of the budget in the short run. Several budget components are naturally inflexible, like wages, pensions and debt service (these are the components of public expenditure to which Minister Astori was referring). But there are many other inflexibilities that are rooted in the constitution, laws, or decrees that earmark revenues, set minimum spending requirements, or link spending to the evolution of certain macroeconomic variables like inflation, growth, or unemployment (see the section on country case studies to learn more about the different sources of rigidities across Latin American countries). 2 https://www.elobservador.com.uy/nota/astori-a-pesar-de-que-la-economia-acelero-su-crecimiento-a-la- inversion-le-esta-costando-despegar--201822710340. -3- Despite being a well-known problem to policy makers, the issue of how budget rigidities contribute to putting countries in fiscal distress or constrain the ability of government to perform fiscal adjustments remains largely unexplored in the literature. The literature on public choice, for instance, has explored the reasons underpinning the emergence of rigidities, but the pervasive effects of budget rigidity have not received a systematic treatment in the literature despite being regularly mentioned in policy papers dealing with fiscal issues. In this paper we seek to help close this gap in the literature by assessing the effects of budget rigidities on the need and ability of governments to make fiscal adjustments. We consider periods when governments should be making fiscal efforts but fail to do so, as well as periods when no adjustment is required. Therefore, from a policy perspective, this paper addresses two important issues that have received little attention. First, how budget rigidities contribute to creating situations of fiscal distress. While there is plentiful anecdotal evidence of how rigid spending can hinder sound policies, to the best of our knowledge, there has not been much empirical work on the subject. Second, how rigidities influence the likelihood of successful fiscal efforts, defined as those cases when countries that are facing a need to adjust manage to do so. To do this, we would ideally like to use a wide definition of budget rigidities; one that encompasses all institutional, political and legal constraints. However, differences in institutional settings across countries represent a major obstacle to systematically collecting international data for comparison purposes, as comparing budget rigidity across countries requires making judgments about the strength of similar constraints in different institutional settings and political realities. Therefore, for simplicity and to be able to compare measures across a large set of countries, we decided to employ a minimal and generally accepted measure of rigidities (see Vegh et al., 2017): the sum of public wages, social benefits, 3 and debt services as a share of GDP. These expenditure categories, which are naturally rigid, are difficult to cut in the short run because of political economy or credit market access problems. The consensus among policy makers in the region is that, the higher they are, the more difficult it becomes to follow fiscal consolidation via expenditure reduction. Not surprisingly, the countries in the region that require greater fiscal adjustment are generally those countries with the highest shares of rigid expenditures (Figure 3). 3 Given that several countries do not report pensions, we use a proxy of social benefits derived from current expenditure subtracting wages, interests, and goods and services. -4- Figure 3: Primary deficits and rigid spending as a share of GDP in 2017 Source: WEO (April 2018) However, public spending on wages, pensions and debt service as a share of GDP is lower in Latin American countries than in OECD countries (Figure 4 shows red bars tend to be to the left of blue bars). Despite this, OECD countries have been able to consolidate since 2012 (see above), while the fiscal deficit in most Latin American countries has continued growing. Thus, there must be something else. Perhaps it is not the observed level of these components of expenditures. Figure 4: Budget Rigidities as a share of GDP (2017) Source: WEO (April 2018) -5- One hypothesis that we discuss in this paper is that it is not the actual level that governments are spending in these areas that matters, but how much they are overspending in these areas. To look at this, we decompose this measure of rigid spending into a structural and a non-structural component. The structural level is determined by long-run economic fundamentals beyond the policy makers’ control (i.e., the level of development and productivity of the country, which should affect the level of public wages; demographic factors that affect the level of pensions than governments must pay). The non-structural one is the difference between the observed and the structural. When we make this decomposition, we see that, although in Latin America the actual level of the rigid components of government spending is relatively low compared to the OECD, the non-structural components are relatively high. As Figure 5 shows, spending on public wages and on pensions in some countries in Latin America (Argentina, Uruguay, Ecuador, Costa Rica and Brazil) is significantly above what a model based on their level of development and demographic factors would predict. Figure 5: Wages, pensions and debt service deviation from predicted value (2017) Source: Authors’ own calculations based on data from IMF, World Bank and national institutes of statistics. This could be because these components of spending have increased too fast during the commodity super-cycle period, leaving the countries with a higher level of rigid spending than they could tolerate (Table 1). For instance, the public wage bill in Argentina, Chile, Costa Rica, Ecuador, and Panama has increased significantly due to generous policy of public hiring and generous wage arrangements. Also, social benefits (mainly pensions) have increased strongly in Argentina, Brazil, Ecuador and Uruguay -6- because of changes in the eligibility criteria, with more generous replacement ratios and changes in indexation rules. Table 1: Changes in primary deficit and items of public expenditures between 2008 and 2017 (% of GDP) Country Primary deficit Public wages Social benefits Interest Argentina 6.2% 3.3% 5.0% 0.5% Peru 6.1% 0.9% -0.3% -0.5% Chile 5.9% 1.5% -0.5% 0.3% Brazil 5.5% 0.1% 2.1% 0.5% Costa Rica 5.3% 1.7% -0.1% 0.6% Ecuador 4.9% 2.2% 2.4% 1.0% Panama 3.1% 1.9% -0.6% -1.4% Colombia 2.1% -0.2% 0.4% -0.1% Uruguay 1.6% 0.6% 4.0% 0.3% Source: Authors’ own calculations based on data from IMF, World Bank and national institutes of statistics. To estimate how these measures of budget rigidities affect the probability of countries getting into fiscal distress and the likelihood of doing a fiscal adjustment, we use the following strategy. First, we identify periods of adjustment needs based on two different methodologies: one based on consecutive years of primary gaps above certain threshold, and the other based on the level of debt. Second, we identify periods of fiscal adjustment as years where there was at least a 0.1% of GDP improvement in the cyclically adjusted primary balance for two consecutive years (Escolano et al., 2014). Then, we estimate a linear probability model using a panel of 182 advanced and developing countries controlling for economic and political factors that previous literature has identified as potential determinants of governments having fiscal adjustment needs and the ability to do so. We find that the actual levels of rigid components of public spending (wages, pensions and interests) are positively associated with the probability of countries getting into fiscal distress and are negatively associated with the ability to consolidate. This result may appear counterintuitive, as many advanced economies with relatively high shares of rigid spending have had successful fiscal consolidations. However, we find more robust evidence by using the share of non-structural rigid spending (when spending on public wages and pensions is above what the fundamentals of their economy would suggest), which may explain why these apparently rigid economies have been able to pursue fiscal consolidations. Moreover, the effect of rigid expenditure seems to be more relevant for economies with higher inequality, government with lower margin of majority and countries with lower institutional -7- quality. In addition, when looking at the composition of our measure of rigid expenditure, we also find some evidence that higher expenditure in pensions reduces the probability of fiscal adjustment more robustly than higher expenditure in wages. The rest of the paper is organized as follows. Section 2 presents a review of the relevant literature to highlight our main contributions. Section 3 presents the conceptual framework. Then, sections 4 and 5 present the estimation methodology and the main results of the paper. Finally, section 6 concludes. 2. Literature review This paper is related to several strands of research in the literature (see Table 9 in the appendix). First, it is related to the large literature on the determinants of fiscal distress and adjustment (see Perotti, 1998; Persson and Tabellini, 1999; and Pinho, 2004 for general surveys). Although this literature is extensive, very few studies have focused on the size of budget rigidities and the difficulty of achieving large fiscal adjustments. This literature has identified major determinants of the likelihood of starting fiscal consolidation and its success. Most of the literature concentrates on the composition of consolidation, whether it should be based on expenditure cuts or revenue increases. There seems to be a consensus that adjustments based on expenditure cut tend to be more successful that adjustments based on raising revenues. Adjustments based on expenditure cuts are found to be more effective (Alesina and Ardagna, 1998; Ardagna, 2009; von Hagen et al., 2002; Guichard et al., 2007; Barrios et al., 2010), and the main explanation is that they are often coupled with reforms that enhance the effectiveness of budgetary procedures (European Commission, 2007). Evidence shows that fiscal consolidation is more likely during periods of weak public finance conditions (Barrios et al., 2010; Guichard et al., 2007; European Commission, 2007; Von Hagen and Strauch, 2001). Stronger economic growth can contribute to successful consolidations (von Hagen and Strauch, 2001), as positive output gaps increase the probability of launching a retrenchment. In particular, governments are more likely to undertake consolidation efforts when the domestic economy is doing well relative to other economies (Von Hagen and Strauch, 2001). Perhaps closer to the spirit of our paper, some studies have shown that reducing budget items that are politically sensitive makes a significant contribution to successful consolidations (Perotti et al., 1998). While some studies find that cutting social spending and transfers is key to reach a successful consolidation (Guichard et al., 2007), others find that fiscal consolidation should incorporate cuts in welfare spending and government wages to be successful (Alesina and Perotti, 1997). Von Hagen and -8- Strauch (2001) find that, in OECD countries, cuts in subsidies and transfers reduce on average 50% of current spending during successful consolidations. Cutting public wage expenditures contribute an average of 36% to the reduction in public spending during successful consolidations. On the contrary, they find that a characteristic of unsuccessful fiscal consolidation episodes is that public wages do not fall significantly in relation to GDP. In sum, these results suggest that tackling politically sensitive budgetary items is a characteristic of successful consolidations. A main difference between our paper and most of previous studies in this literature is that we include both advanced and emerging economies, whereas most previous studies (see Table 9 in the appendix) focus only on advanced economies (usually a subset of OECD countries). A second important difference is that most of this literature starts by identifying a fiscal adjustment based on changes in the cyclically adjusted primary balance and examines how successful those adjustments were, where success is usually defined in terms of the lasting effect the adjustment program has on reducing the government debt-to-GDP ratio (see Table 9). In this paper, we first identify which countries are in need of fiscal adjustment (we do this by applying two different methodologies described below) and estimate if budget rigidities contribute to fiscal distress. Then, among the countries that need to adjust, we estimate whether budget rigidities represent a constraint to fiscal consolidation. Second, this paper is related to the literature analyzing the economic implications of budget rigidities. The literature on budget rigidities is surprisingly limited given how well-known and pressing the problem is to policy makers in Latin America. Several authors argue that budget rigidities introduce inefficiencies (Echeverry and others, 2005, 2006 and 2009; Mattina, 2007). These studies suggest there is a negative association between rigidity and efficiency of the public sector, where countries with more rigid spending (measured as a percentage of primary spending or as a percentage of GDP) have lower efficiency scores. According to the previous literature, budget rigidities negatively affect budget management by limiting the reallocation of public spending in response to changing needs, promoting poor quality fiscal adjustments and generating a bias towards higher spending and taxation, introducing distortions in tax policy choices, limiting the scope for countercyclical fiscal policy, and weakening incentives to improve the efficiency of public spending (Alier, 2006). The paper that comes closest to our work is Lavigne (2011), which uses a similar methodology: first identify a fiscal adjustment need and then the determinants of successful adjustment. However, our study differs with respect to Lavigne (2011) in two dimensions. First, it differs because of the criteria used to identify fiscal adjustment needs and the fiscal consolidation process, and the inclusion of budget -9- rigidities as determinants of adjustment needs as well as constraints to successful fiscal adjustments. Second, we take into consideration the panel nature of the data and estimate a model that controls for unobserved time-invariant heterogeneity across countries. This issue in the literature of fiscal adjustment has been previously pointed out by Mierau et al. (2007). 3. Conceptual framework The goals of this paper are first to analyze if budget rigidities contribute to countries getting into fiscal distress and second if budget rigidities represent a constraint to initiate fiscal consolidations. To answer these questions, we develop a framework where a country starts off either in a situation of fiscal need or not. If the country does face a need for fiscal adjustment, then the government must decide whether to attempt it or not. In this process, budget rigidities enter twice. First, they can play a role getting countries in fiscal distress, making a fiscal adjustment a requirement to stabilize or reduce the public debt. Second, in those countries where a fiscal adjustment is necessary, governments must decide whether to do the adjustment or not. Here budget rigidities, in combination with economic and political factors can play a key role. The concept of fiscal need is critical to our purpose. We assume that when any country is facing an objective need for fiscal adjustment, the government will attempt to do so; if it does not do so, it is because of institutional, economic and/or political factors that constrain the government’s ability. For this hypothesis to be reasonable, the fiscal need must be clear and pressing. We identify episodes of fiscal adjustment need using two different approaches. First, we follow Escolano et al. (2014) to define fiscal adjustment need as years in which a country is facing a positive primary gap for two consecutive years greater or equal than an arbitrary threshold (see below for more details). Second, we consider the case of countries with the ratio of public debt over average revenue above a country-specific rolling Gaussian weighted average for two consecutive years. Conceptually it is clear how budget rigidities can increase the probability of countries getting into fiscal distress and constrain the ability of governments to consolidate. The political economy theory emphasizes that government spending often increases because relevant expenditure items are rigid as a result of entitlements or indexation to economic variables that are outside the control of the government (Perotti et al., 1998). This way, expenditures cannot be modified during the annual decision-making - 10 - process over the public budget. These can be very important sources of the loss of control of fiscal policy that can get countries into fiscal distress. Similarly, indication that Latin American countries face tough political battles when trying to implement the fiscal adjustments that involve cutting public wages or social benefits is widespread. For example, Argentina’s lower house on December 2017 had to suspend a vote on President Mauricio Macri’s pension reform plan (which hoped to limit the growth rate of pensions bill), after the debate became a shouting match and protesters and police clashed violently outside Congress. The bill, which was crucial for the government’s efforts to cut the fiscal deficit, drew strong criticism from opposition politicians and labor unions, who said it would hurt retirees and welfare recipients. The pension reform hoped to change the formula used to calculate benefits. Payments would adjust every quarter based on inflation, rather than the previous system of twice-yearly adjustments indexed to wage rises and tax revenue. Also, there are several economic and political variables that can affect the sustainability of public finances. A consensus within the political economy literature is that governments pursue expansionary fiscal policies before elections to get re-elected (see de Haan and Klomp, 2013 for a survey). This means that governments are unlikely to introduce fiscal adjustments when elections are near, as that will be politically very costly. Furthermore, governments are likely to follow expansionary fiscal policies during election years to increase their probabilities of being (re)elected. In sum, the fact that a country is in an election year should increase the probability that the country gets into fiscal distress, and if it is already in need of fiscal adjustment, reduce the probability that a fiscal consolidation process is initiated. However, voters may be fiscal conservatives and therefore not reward expansionary policies during elections (Pelzman, 1992). The margin of majority is another political variable that can affect the fiscal status of countries. Lack of political stability or a minority in Congress can reduce effective government control over the budgetary process, increasing the chances of a successful fiscal effort. Previous empirical evidence shows that an index of political fragmentation correlates well with the size of deficits in advanced countries (Roubini and Sachs, 1989). This is due to short tenures and the difficulty of reaching an agreement among different political parties, explaining why coalition governments are more prone to fiscal indiscipline. Other authors have shown that a highly polarized government with alternating majority in Congress increases the risk of electoral loss and leads policy makers to run deficits that will constrain the actions of their successors (Tabellini and Alesina, 1990). - 11 - Societal divisions that lead to social conflict can also affect the sustainability of public finance. In particular, the level of income inequality can affect the composition and size of government spending. In the words of Sachs (1989), “Economic policymaking in Latin America remains a battleground of conflicting interest of class, sectors, regions, and ethnic groups.” Part of the reason is that income inequality in Latin America remains relatively high. If we take a model with heterogeneous households, these households are going to have different opinions regarding the convenience of following a fiscal adjustment based on cutting public spending. Indeed, the medium voter theory, when income inequality is very high, would predict that voters would rather vote to increase tax rates rather than cut spending. In more unequal societies, the median voter will be relatively poorer than the average household (her income will be lower in relation to mean income). Therefore, if net governmental transfers (transfers minus direct taxes) are progressive, the more unequal is the income distribution, the more the median voter has to lose through fiscal consolidations that are based on cutting current public spending. 4. Estimation methodology The core of the investigation consists of identifying episodes in which countries need fiscal adjustment and whether they adjust or not during those episodes. Having these episodes identified, we will analyze potential economic and political determinants of them with a focus on the impact of a measure of budget rigidities. I. Identifying fiscal adjustment need We identify episodes of fiscal adjustment need using two different approaches. First, we follow Escolano et al. (2014) to define fiscal adjustment need as years in which a country is facing a positive primary gap for two consecutive years greater or equal than an arbitrary threshold. The primary gap is defined as: ∗ = − ∗ where is the primary gap (in percent of GDP), is the debt-stabilizing primary balance (in percent of GDP), and is the actual primary balance (in percent of GDP). We construct the debt- stabilizing primary balance under current market conditions (as defined in Kose et al., 2017) by using: ∗ ( − ) = (1 + ) - 12 - where is the nominal interest rate at the current level, the country nominal GDP growth rate, and is a constant stock of debt (in percent of GDP) based on the historical country-group (advanced economies, and emerging markets and developing economies) median debt stocks as the target debt ratio. The threshold is set to the median primary gap among the countries with positive gap and it is computed by country-group. For advanced countries it corresponds to a primary gap of 3.7% of GDP and for EMEs is 5.7% of GDP. Second, we consider the case of countries with the ratio of public debt over average revenue (defined in Kose et al., 2017 as a measure of fiscal space) above a country-specific rolling Gaussian weighted average for two consecutive years. Table 10 shows the episodes of adjustment need identified for advanced economies. We identify 38 episodes for 26 countries (out of 34 for which we have data). Table 11 shows 68 episodes identified for emerging economies, they span across 49 countries (of 70). Similarly, Table 14 and Table 15 show the episodes identified using debt-to-revenue ratios. We identify 78 episodes for 35 advanced economies (of 36) and 301 episodes spanning across all the 146 developing countries with available data. II. Identifying fiscal adjustment To identify episodes of fiscal adjustment, we follow Escolano et al. (2014) and define adjustment status as periods in which there are two consecutive years with an annual change of at least 0.1% of GDP in the cyclically adjusted primary balance during years of fiscal need. We consider that a period of adjustment continues when the cyclically adjusted balance shows a positive or null change and when a fall of less than 0.3% of GDP is followed by an improvement of at least 0.5% of GDP. These episodes need to coincide with a period of fiscal need, hence for each measure of fiscal need we can compute a different set of episodes of fiscal adjustment. Table 12 shows the 16 episodes of adjustment identified for advanced economies which span across 14 countries (of 26 economies with episodes of need). Table 13 shows the case of emerging economies, we find 18 episodes for 16 countries (of 49 economies with episodes of need). Similarly, Table 16 and Table 17 use need with debt/revenue. We find 59 episodes of fiscal adjustment in advanced economies including 32 countries (of 35 with episodes of need), and 120 episodes in developing economies which span across 89 countries (of 146). - 13 - III. Measuring budget rigidities Measuring budget rigidities in a cross-country setting is a difficult task, as differences in institutional settings represent a major obstacle to systematically collect international data that can be compared across a large set of countries. Comparing budget rigidity across countries requires making judgements about the strength of similar constraints in different institutional settings and political realities. For simplicity, in this paper we have employed a minimal and generally used measure of rigidities (Vegh et al, 2017): the sum of public wages, social benefits, 4 and debt interest payments as a share of GDP; the components of spending that are naturally rigid. This measure of rigidities assumes that these expenditures categories are, in the short run, beyond the policy makers’ control. However, looking only at the actual level of these rigid components of public expenditures could be misleading, in particular for the cases of public wages and social security benefits. For instance, it should be clear that the ratio of public wages to GDP of Honduras will be significantly below the level of France, as they have different levels of productivity. Economic theory teaches us that the wage level increases with the level of wealth of the country (the Balassa and Samuelson effect). Balassa-Samuelson show that different productivity levels across countries lead to higher wages in wealthier countries (higher productivity countries). Similarly, the share of social security (pensions) in GDP will also be affected by demographic factors as well as the level of productivity in the country (as higher wages are related to higher pensions). Thus, theory predicts that the sum of public wages and social benefits as a percentage of GDP (or total public expenditures) will be higher in more advanced countries than in less advanced ones. But having higher shares of public wages and pensions, as theory would predict, will not necessarily get countries into fiscal distress or limit the ability of governments to adjust the fiscal deficit. At the end, their economic structure suggests that these components of government spending should be relatively high in the long-run. Therefore, we also estimate a second measure of rigidity of government spending considering that the wages and pensions can be decomposed into a structural and a non-structural component. While the structural component is determined by long-run economic fundamentals beyond the policy makers’ control, the non-structural one is determined by policy decisions. The structural components are interpreted as the level of spending the countries should have based on their level of development, productivity and age-profile of the population. Then, we compare the structural component of general 4 Current expenditure minus purchase of goods and services, expenditure in wages and paid interests. - 14 - government wage bill and pension payments with the observed rigid spending to arrive to the non- structural. When countries are above their structural level, this means that they could be overspending in areas that are relatively rigid (difficult to reduce in the short run). This could lead them to fiscal distress and reduce their ability to adjust the fiscal deficit through budget cuts. To estimate the structural level of compensation to employees (see section on measurement), we estimate a fixed effects model (for 166 countries over the period between 1990 and 2017) that includes as dependent variable the log of the compensation of employees per capita in constant international dollars regressed against the log of GDP per capita, a linear time trend, and the log of the population. In the case of pensions, we run a fixed effects regression (for 63 countries over the period between 1990 and 2017) using pension payments per capita in constant international dollars as dependent variable, and the old age dependency ratio, GDP per capita in constant international dollars (as a proxy for wage levels, see section on measurement in this report for more details), and the revenues of the general government social security system in constant international dollars, as explanatory variables. In both cases, we correct downward the predicted values using 1.5 times the interquartile range of the residuals. IV. Estimation framework The econometric specification is a linear probability model and corresponds to the following: = + + + where is a binary dependent variable that indicates the fiscal status (need or adjustment conditional on having need) in country i at year t; is a measure of the degree of budget rigidities; is a matrix that include a set of economic and political economy control variables; and δ are the coefficient of interest and a vector of coefficients associated with the control variables; is a country fixed effect to control for potential unobserved time-invariant factors in the regression; and a mean- zero random disturbance. The variable of interest corresponds to a measure of budget rigidity: a) Traditional: The sum of compensation to employees, social security and interest payments as share of GDP; b) Structural: We compute the deviation between the traditional measure and a structural component that reflects the minimum expenditure a country could have given its level of development and other structural factors. - 15 - As control variables we use a group of economic and political variables previously analyzed in the literature of successful fiscal consolidations. In the economic variables we include lagged real GDP growth, lagged inflation rate, and international interest rate (long-term U.S. government bond yield: 10 years). These variables are taken from the IMF World Economic Outlook (October 2018). The information from political variables (majority government and election year) come from the Database of Political Institutions 2017, which is hosted at the Inter-American Development Bank and has coverage of 180 countries from 1975-2017. Rule of law comes from the PRS Group in their International Country Risk Guide. The scores are based on evaluations from experts surveyed and the data are available since 1984 for a group of 140 countries. The Gini coefficient comes from the data set “All the Ginis” created by Branko Milanovic. Table 2 shows some summary statistics of the control variables for the sample with available data to identify need of fiscal adjustment. Table 2: Descriptive statistics of the control variables a) Sample with primary gap b) Sample with debt/revenue ratio N mean SD min max N mean SD min max GDP growth 0.03 0.04 -0.16 0.30 0.04 0.05 -0.46 0.92 Inflation 0.06 0.10 -0.09 2.02 0.06 0.10 -1.30 2.02 Interest rate 3.91 1.55 1.80 8.55 4.11 1.64 1.80 8.55 Gini 39.09 9.84 17.50 74.30 40.31 9.78 17.50 77.40 Rule of law 4.10 1.40 1.00 6.00 3.89 1.37 0.00 6.00 Margin of Majority 0.59 0.17 0.05 1.00 0.64 0.20 0.03 1.00 Election's year 0.29 0.45 0.00 1.00 0.25 0.43 0.00 1.00 Observations 2002 4046 V. Results In general, the results provide evidence that budget rigidities do affect the probability that countries get into financial distress; in addition, we find evidence on rigidities being a constraint for successful fiscal consolidations. Indeed, the factors found to increase the probability of achieving a successful adjustment effort are not necessarily the same as those favoring the maintenance of sound fiscal policies. On the determinants of need of fiscal adjustment In general, the results presented in Table 3 and - 16 - Table 4 are in harmony with our expectations. The first insight is that higher shares of budget rigidities are positively and significantly associated with the need of fiscal adjustment. 5 This result is robust to the inclusion of political and economic control variables, as well as to the different methodologies to identify the need for fiscal consolidation (using primary gap or debt over revenue). The results are consistent with the findings of previous studies, i.e., Perotti et al. (1998), who show that higher levels of public wages and social transfers are associated with unsustainable paths of fiscal policy. In addition, the impact of the budget rigidities differs between advanced and emerging economies, being lower in the case of the later (see column 5 in Table 3 and Table 4). Economic factors: our results show that economic factors, such as economic growth, inflation and interest rate, are significant determinants of the need for fiscal adjustment but only growth appears to be robust across different specifications. As expected, higher economic growth in previous years reduces the need for fiscal adjustment. This is consistent with economic theory, as stronger economic growth increases tax revenues, reducing the fiscal deficit. In the case of inflation, the positive and significant coefficient (although not across all specifications) fits with the idea that higher increases in prices are generally associated with bad macroeconomic management, which should lead to periods of fiscal distress. The level of interest rate is negatively associated to fiscal need although only statistically significant when we use the structural measure of rigidities (Table 18 in the Appendix). This is puzzling considering that we would expect higher financing costs leading to more fiscal distress. 5 The results are qualitatively similar if we use the structural measure, these are reported Table 18 and Table 19 in the Appendix to save space. - 17 - Political variables: the previous literature has identified several political factors that can affect the need for fiscal adjustments, focusing mainly on the possible role of elections and budget institutions (Beetsma and others, 2009, 2012 and 2015). In general, these variables are not statistically significant, suggesting that political economy factors do not play a significant role in the dynamics of fiscal adjustment. The only exception is election year, which is positive and significant in specifications that identify need using the primary gap (Table 3 and Table 18 in the Appendix), in line with the prediction of political economy theory that during election years governments are more likely to increase spending (to increase the likelihood of winning the election) and get countries into fiscal distress. Interactions: In addition to adding economic and political controls, we estimate models that allow for non-linearities in the impact of budget rigidities. We do so by interacting our variable of interest with a binary variable indicating developing economies and our political controls. We find some evidence that the impact of the budget rigidities differs between advanced and emerging economies, being lower in the case of the latter (see column 5 in Table 3, Table 4, and Table 18 and Table 19 in the Appendix). We do not find any significant role in the case of the political factors except for some limited evidence that higher rule of law increases the impact of budget rigidities on the probability of fiscal need (see column 7 in Table 4 and Table 19 of the Appendix). This result could potentially be explained by a stronger enforcement of legal rigidities in the budget, but more research is needed to make this statement categorically. Composition: To study the composition of our measure of rigid expenditure, we run a similar set of regressions separating the wage bill from social security expenditure. The results, which are reported in Table 20 and Table 21 of the appendix, are qualitatively similar and suggest that both components are associated with an increase in the probability of fiscal adjustment need. - 18 - Table 3 - 19 - Dependent variable: Need of fiscal adjustment based on Escolano et al. (2014) Variables (1) (2) (3) (4) (5) (6) (7) (8) Rigid expenditure 0.037*** 0.033*** 0.038*** 0.032*** 0.041*** 0.033*** 0.021 0.028*** (% of GDP) (0.006) (0.005) (0.006) (0.005) (0.007) (0.010) (0.013) (0.009) Economic factors GDP growth (t-1) -1.928*** -1.829*** -1.749*** -1.824*** -1.820*** -1.841*** (0.413) (0.420) (0.409) (0.424) (0.416) (0.424) Inflation (t-1) -0.090 -0.053 -0.049 -0.053 -0.051 -0.056 (0.074) (0.066) (0.062) (0.066) (0.067) (0.067) U.S. Interest rate -0.012 -0.015 -0.017 -0.015 -0.017 -0.015 (0.010) (0.011) (0.011) (0.011) (0.011) (0.011) Political factors Gini 0.007 0.005 0.005 0.006 0.005 0.005 (0.005) (0.005) (0.005) (0.007) (0.005) (0.005) Rule of law 0.002 0.012 0.004 0.012 -0.053 0.013 (0.029) (0.030) (0.029) (0.030) (0.050) (0.030) Margin of Majority 0.092 0.059 0.066 0.059 0.063 -0.094 (0.123) (0.124) (0.124) (0.124) (0.125) (0.231) Election's year 0.021 0.028* 0.029** 0.028* 0.028* 0.028* (0.015) (0.015) (0.015) (0.015) (0.015) (0.015) Interactions EMEs * Rigidity -0.017* (0.010) Gini * Rigidity -0.000 (0.000) Rule of law * Rigidity 0.002 (0.002) Majority * Rigidity 0.007 (0.012) Constant -0.840*** -0.607*** -1.212*** -0.884*** -0.874*** -0.913** -0.618* -0.796*** (0.163) (0.136) (0.308) (0.277) (0.275) (0.346) (0.327) (0.297) Observations 1,521 1,500 1,360 1,342 1,342 1,342 1,342 1,342 R-squared 0.126 0.182 0.139 0.186 0.193 0.186 0.188 0.187 Number of ifscode 84 84 75 75 75 75 75 75 Country FE Yes Yes Yes Yes Yes Yes Yes Yes Robust standard errors clustered by country in parentheses *** p<0.01, ** p<0.05, * p<0.1 Table 4 - 20 - Dependent variable: Need of fiscal adjustment based on debt/revenue Variables (1) (2) (3) (4) (5) (6) (7) (8) Rigid expenditure 0.023*** 0.024*** 0.026*** 0.023*** 0.051*** 0.019 0.001 0.031*** (% of GDP) (0.004) (0.005) (0.007) (0.007) (0.011) (0.019) (0.014) (0.012) Economic factors GDP growth (t-1) -1.357*** -1.688*** -1.449*** -1.694*** -1.631*** -1.666*** (0.320) (0.334) (0.340) (0.335) (0.343) (0.332) Inflation (t-1) 0.020 0.214 0.232* 0.215 0.200 0.217* (0.135) (0.132) (0.130) (0.132) (0.133) (0.131) U.S. Interest rate 0.005 0.001 -0.004 0.001 -0.003 0.001 (0.011) (0.012) (0.012) (0.012) (0.012) (0.012) Political factors Gini 0.008 0.007 0.006 0.005 0.007 0.007 (0.005) (0.005) (0.005) (0.009) (0.005) (0.005) Rule of law 0.025 0.033 0.023 0.034 -0.100 0.032 (0.038) (0.046) (0.046) (0.046) (0.087) (0.046) Margin of Majority -0.091 -0.073 -0.080 -0.072 -0.073 0.146 (0.152) (0.156) (0.151) (0.156) (0.158) (0.285) Election's year -0.009 -0.012 -0.009 -0.012 -0.011 -0.013 (0.015) (0.015) (0.016) (0.015) (0.016) (0.016) Interactions EMEs * Rigidity -0.043*** (0.014) Gini * Rigidity 0.000 (0.000) Rule of law * Rigidity 0.006* (0.003) Majority * Rigidity -0.013 (0.013) Constant -0.125 -0.106 -0.558* -0.455 -0.508* -0.383 0.015 -0.589* (0.096) (0.122) (0.321) (0.299) (0.290) (0.420) (0.393) (0.337) Observations 3,046 2,911 2,066 2,007 2,007 2,007 2,007 2,007 R-squared 0.026 0.042 0.031 0.049 0.064 0.049 0.054 0.050 Number of ifscode 147 145 103 102 102 102 102 102 Country FE Yes Yes Yes Yes Yes Yes Yes Yes Robust standard errors clustered by country in parentheses *** p<0.01, ** p<0.05, * p<0.1 Probability of a successful fiscal adjustment Our results for the probability of fiscal adjustment are reported in Table 5 and Table 6 using the traditional measure of fiscal rigidities, and Table 7 and Table 8 using the structural measure. In general, we find evidence suggesting that budget rigidities affect the probability of fiscal adjustment. This negative - 21 - effect is robust to the inclusion of different controls as well as the different methods used to define episodes of fiscal adjustment need. Moreover, in contrast to the case of fiscal need, we do not find evidence of a different impact on the probability of adjustment in the case of emerging economies. Economic variables: In contrast to the case of fiscal adjustment need, we do not find a statistically significant impact of previous GDP growth in any of our specifications. However, we find some evidence of a positive correlation with previous year level of inflation and a negative correlation with the international interest rate. The impact of the interest rate is coherent with previous studies that have documented that consolidation efforts are more likely to be pursued and to succeed if monetary policy stance is eased (Ahrend et al., 2006). The positive association between inflation and the probability of fiscal adjustment is more puzzling. Political variables: Unlike several previous studies, but in line with Mierau et al. (2007) and Wise et al. (2018), our results do not suggest that political-economy variables are robustly related to successful fiscal adjustments. Like us, both take into consideration the panel nature of the data, which may explain the difference with previous papers. We find a negative correlation in the case of the rule of law although not robust to the inclusion of economic factors. Lavigne (2011) argues that lower rule of law could increase the likelihood of adjustment in developing countries by allowing government to take drastic actions sometimes required to adjust their fiscal policy, our results are in line with this hypothesis. The margin of majority appears to increase the probability of fiscal adjustment (see column 4 in Table 6 and Table 8), but the result is statistically significant only when we use debt/revenue to identify episodes of need. Interactions: as we do in the case of fiscal need, we estimate models that allow for non-linearities in the impact of budget rigidities on the probability of fiscal adjustment. We find some, although weak, evidence of nonlinearities. The effect of budget rigidities appears to be weakened with higher rule of law (see column 7 in Table 5 and Table 7) and higher margin of majority (see column 8 in Table 5). On the other hand, income inequality seems to strengthen the effect of rigidities (see column 6 in Table 5 and Table 7). Composition: when we estimate models that consider the wage bill and social security expenditure separately (see Table 22 and Table 23 in the appendix), we find that social security expenditure appears to be more robustly associated with a decrease in the probability of fiscal adjustment. The coefficient associated with the wage component is not statistically significant in any of - 22 - our regressions. This result is robust across all our specifications and holds using the traditional measure of rigid expenditure as well as the structural one. Table 5 Dependent variable: Fiscal adjustment when needed based on Escolano et al. (2014) Variables (1) (2) (3) (4) (5) (6) (7) (8) Rigid expenditure -0.014 -0.023*** -0.014 -0.027*** -0.016* 0.073** -0.080*** -0.062*** (% of GDP) (0.014) (0.008) (0.013) (0.008) (0.008) (0.028) (0.028) (0.019) Economic factors GDP growth (t-1) -0.043 0.479 0.520 0.443 0.400 0.436 (1.337) (1.418) (1.392) (1.393) (1.419) (1.416) Inflation (t-1) 2.500*** 2.721** 3.068*** 2.991*** 3.219*** 2.570** (0.844) (1.098) (1.114) (1.084) (1.000) (1.173) U.S. Interest rate -0.122** -0.157** -0.175** -0.204*** -0.192** -0.172*** (0.051) (0.063) (0.072) (0.059) (0.072) (0.051) Political factors Gini 0.010 0.012 0.014 0.079*** 0.014 0.005 (0.010) (0.012) (0.012) (0.023) (0.012) (0.011) Rule of law -0.214*** 0.091 0.140 0.160 -0.124 0.090 (0.068) (0.131) (0.146) (0.133) (0.127) (0.132) Margin of Majority 0.516 0.250 0.236 0.451 0.243 -1.486* (0.406) (0.385) (0.379) (0.360) (0.375) (0.800) Election's year -0.111 -0.093 -0.085 -0.074 -0.084 -0.079 (0.081) (0.078) (0.075) (0.074) (0.078) (0.081) Interactions EMEs * Rigidity -0.032 (0.029) Gini * Rigidity -0.003*** (0.001) Rule of law * Rigidity 0.012** (0.005) Majority * Rigidity 0.072* (0.041) Constant 0.611 1.167*** 0.758 0.456 0.349 -2.486** 1.414 1.601* (0.393) (0.288) (0.675) (0.923) (0.860) (1.225) (0.910) (0.931) Observations 185 183 165 163 163 163 163 163 R-squared 0.007 0.114 0.073 0.159 0.167 0.191 0.177 0.187 Number of ifscode 60 60 53 53 53 53 53 53 Country FE Yes Yes Yes Yes Yes Yes Yes Yes Robust standard errors clustered by country in parentheses *** p<0.01, ** p<0.05, * p<0.1 - 23 - Table 6 Dependent variable: Fiscal adjustment when needed based on debt/revenue Variables (1) (2) (3) (4) (5) (6) (7) (8) Rigid expenditure -0.004 -0.007 -0.009* -0.012** -0.013 -0.009 -0.020* -0.026** (% of GDP) (0.003) (0.004) (0.005) (0.005) (0.010) (0.015) (0.012) (0.010) Economic factors GDP growth (t-1) -0.329 -0.230 -0.238 -0.227 -0.209 -0.225 (0.274) (0.482) (0.487) (0.483) (0.485) (0.483) Inflation (t-1) 0.038 0.098 0.096 0.100 0.101 0.084 (0.084) (0.164) (0.163) (0.164) (0.167) (0.164) U.S. Interest rate -0.023** -0.028** -0.027* -0.028** -0.030** -0.028** (0.011) (0.013) (0.014) (0.014) (0.014) (0.014) Political factors Gini 0.004 0.004 0.004 0.005 0.004 0.004 (0.004) (0.004) (0.004) (0.007) (0.004) (0.004) Rule of law -0.040 -0.020 -0.020 -0.020 -0.065 -0.020 (0.035) (0.041) (0.040) (0.041) (0.057) (0.041) Margin of Majority 0.221* 0.220* 0.220* 0.218* 0.223* -0.166 (0.132) (0.129) (0.129) (0.130) (0.129) (0.206) Election's year -0.042 -0.048 -0.048 -0.048 -0.048 -0.047 (0.030) (0.031) (0.031) (0.031) (0.031) (0.030) Interactions EMEs * Rigidity 0.002 (0.012) Gini * Rigidity -0.000 (0.000) Rule of law * Rigidit 0.002 (0.003) Majority * Rigidity 0.023 (0.014) Constant 0.303*** 0.479*** 0.352 0.445 0.449 0.396 0.617* 0.678** (0.079) (0.117) (0.301) (0.298) (0.301) (0.350) (0.322) (0.309) Observations 1,121 1,081 771 755 755 755 755 755 R-squared 0.001 0.009 0.012 0.022 0.022 0.022 0.022 0.026 Number of ifscode 147 145 103 102 102 102 102 102 Country FE Yes Yes Yes Yes Yes Yes Yes Yes Robust standard errors clustered by country in parentheses *** p<0.01, ** p<0.05, * p<0.1 - 24 - Table 7 Dependent variable: Fiscal adjustment when needed based on Escolano et al. (2014) Variables (1) (2) (3) (4) (5) (6) (7) (8) Rigid expenditure minus -0.032*** -0.030*** -0.033*** -0.034*** -0.023*** 0.082** -0.096*** -0.066 structural as % GDP (0.011) (0.008) (0.010) (0.010) (0.006) (0.034) (0.033) (0.050) Economic factors GDP growth (t-1) 0.057 0.165 0.217 0.143 0.185 0.160 (1.317) (1.502) (1.481) (1.470) (1.491) (1.515) Inflation (t-1) 2.770*** 3.252*** 3.540*** 3.537*** 3.575*** 3.209** (0.812) (1.182) (1.170) (1.137) (1.137) (1.218) U.S. Interest rate -0.136*** -0.147** -0.158** -0.163*** -0.169** -0.154** (0.051) (0.065) (0.066) (0.060) (0.069) (0.059) Political factors Gini 0.006 0.005 0.004 0.028** 0.005 0.004 (0.009) (0.013) (0.013) (0.014) (0.013) (0.012) Rule of law -0.208*** 0.106 0.141 0.150 0.049 0.114 (0.068) (0.137) (0.137) (0.134) (0.127) (0.137) Margin of Majority 0.385 0.155 0.106 0.228 0.114 -0.342 (0.386) (0.376) (0.375) (0.359) (0.371) (0.621) Election's year -0.110 -0.083 -0.071 -0.052 -0.079 -0.080 (0.079) (0.077) (0.072) (0.073) (0.075) (0.080) Interactions EMEs * Deviation -0.040 (0.025) Gini * Deviation -0.003*** (0.001) Rule of law * Deviation 0.013** (0.006) Majority * Deviation 0.058 (0.096) Constant 0.583*** 0.893*** 0.968 0.270 0.308 -0.810 0.689 0.589 (0.130) (0.190) (0.667) (0.937) (0.919) (0.979) (0.930) (0.845) Observations 182 180 164 162 162 162 162 162 R-squared 0.035 0.157 0.100 0.180 0.190 0.211 0.194 0.184 Number of ifscode 60 60 53 53 53 53 53 53 Country FE Yes Yes Yes Yes Yes Yes Yes Yes Robust standard errors clustered by country in parentheses *** p<0.01, ** p<0.05, * p<0.1 - 25 - Table 8 Dependent variable: Fiscal adjustment when needed based on debt/revenue Variables (1) (2) (3) (4) (5) (6) (7) (8) Rigid expenditure minus -0.009* -0.012** -0.017*** -0.020*** -0.021** -0.017 -0.017 -0.046** structural as % GDP (0.005) (0.006) (0.006) (0.006) (0.010) (0.023) (0.019) (0.020) Economic factors GDP growth (t-1) -0.277 -0.219 -0.229 -0.218 -0.225 -0.236 (0.327) (0.527) (0.533) (0.528) (0.535) (0.528) Inflation (t-1) 0.041 0.083 0.081 0.084 0.082 0.053 (0.085) (0.167) (0.166) (0.167) (0.166) (0.167) U.S. Interest rate -0.026** -0.031** -0.030** -0.031** -0.030** -0.031** (0.010) (0.013) (0.014) (0.013) (0.015) (0.014) Political factors Gini 0.004 0.004 0.004 0.005 0.004 0.005 (0.005) (0.004) (0.004) (0.005) (0.004) (0.004) Rule of law -0.054 -0.028 -0.029 -0.028 -0.023 -0.032 (0.039) (0.045) (0.045) (0.045) (0.053) (0.045) Margin of Majority 0.314** 0.312** 0.311** 0.311** 0.311** 0.033 (0.142) (0.138) (0.138) (0.139) (0.138) (0.186) Election's year -0.045 -0.051 -0.050 -0.051 -0.051 -0.050 (0.032) (0.032) (0.032) (0.032) (0.032) (0.032) Interactions EMEs * Deviation 0.003 (0.013) Gini * Deviation -0.000 (0.001) Rule of law * Deviation -0.001 (0.005) Majority * Deviation 0.044 (0.030) Constant 0.310*** 0.438*** 0.264 0.315 0.314 0.299 0.295 0.487* (0.041) (0.065) (0.288) (0.283) (0.282) (0.291) (0.302) (0.293) Observations 1,015 1,003 713 709 709 709 709 709 R-squared 0.003 0.013 0.022 0.033 0.034 0.034 0.034 0.037 Number of ifscode 137 137 98 98 98 98 98 98 Country FE Yes Yes Yes Yes Yes Yes Yes Yes Robust standard errors clustered by country in parentheses *** p<0.01, ** p<0.05, * p<0.1 - 26 - VI. Robustness checks We evaluate the robustness of our findings by estimating six sets of regressions that either slightly modify the way in which we construct the dependent variable in our baseline specifications or keep the dependent variable but change the estimator. First, we estimate the same econometric specifications using a pooled logistic regression instead of a linear probability model. 6 We find qualitatively similar results in the case of fiscal adjustment need (Table 24, Table 25, Table 26, Table 27 in the Appendix), being again positively correlated with rigid expenditure. The main difference in this exercise is that now the political factors play a greater role. Economic inequality, margin of majority, and election year are all statistically significant with positive sign, while the rule of law is negatively correlated with fiscal adjustment need. We also find that developing economies seems to have higher probability of need, and that margin of majority attenuates the effect of budget rigidities while the rule of law strengthens them. In the case of the probability of fiscal adjustment (Table 28, Table 29, Table 30, and Table 31 in the Appendix), we find that rigid expenditure increases the probability of adjustment, which is at odds with our conceptual framework. This result could be in part driven by the unobserved heterogeneity, which it is not controlled by our pooled estimator. The role of economic factors remains as in our baseline estimation while the political factors again appear to be more relevant compare to the baseline estimation. We find some evidence of nonlinearities with regards to income inequality and rule of law. Second, we consider the same econometric specifications but instead of using the previous pooled logit estimator, we apply a conditional logit estimator, which attempts to control for the unobserved heterogeneity while staying in the maximum likelihood framework. 7 In the case of fiscal need (Table 32, Table 33, Table 34, Table 35 in the Appendix), the results are again qualitatively similar with a positive and statistically significant association between adjustment need and rigid expenditure. The economic factors remain as the baseline exercise in terms of sign and statistical significance. The political factors are still significant but less robust across specifications, and we again find some evidence of nonlinearities in the effect of the rigid expenditure. In the case of fiscal adjustment (Table 36, Table 37, Table 38, and Table 39 in the Appendix), our results are consistent with our baseline linear probability model, and we find the same, although weaker, evidence of a negative relationship between rigid 6 Lavigne (2011) among others have estimated their models with this approach (see the summary of the literature in Table 9: Literature review of the Appendix). 7 Miearau et al. (2007) apply the same type of estimator to study fiscal adjustment in OECD countries. - 27 - expenditure and the probability of fiscal adjustment. It is worth noting that the sign of the effect of budget rigidities switches from positive to negative when we control for unobserved heterogeneity, in other words, when we move from a pooled logit model to a conditional logit or linear probability model with fixed effects. The role of economics factors, political factors, and nonlinearities is also consistent with our baseline specification, which supports our claim that unobserved heterogeneity could be driven the results in the pooled logit estimator. Moreover, it is also worth noting that the negative effect of rigid expenditures is only statistically significant when we use the structural measure. Third, given that we identify episodes of fiscal adjustment conditional on having fiscal need and use only those years, as a robustness check, we also attempt to control for sample selection in our estimation of the determinants of fiscal adjustment. We do so by using the Heckman two-step correction for sample selection bias in which we assume that election year affects the probability of fiscal adjustment need but does not affect the probability of fiscal adjustment. The results of this exercise are like the pooled logit estimator that does not correct for sample selection and show either a positive or an insignificant relationship between rigid expenditure and fiscal adjustment (see Table 40, Table 41, Table 42, and Table 43 in the Appendix). In this model, as in the pooled logit regression, we do not account for unobserved heterogeneity because the second step uses a pooled probit model that does not allow fixed effects, so our result again is likely driven by this factor. Fourth, we estimate our baseline specifications for fiscal adjustment controlling for a measure of the size of the need of fiscal adjustment using a one year lagged value of the primary gap. Our results are consistent with our baseline models, we find a negative relationship that is statistically significant and robust when we identify fiscal adjustment need using primary gap or debt over revenue (see Table 44, Table 45, Table 46, and Table 47 in the Appendix). Fifth, we estimate our baseline specifications with ordinary least squares but using episodes of fiscal need and fiscal adjustment identified as in Lavigne (2011), detailed in the literature review provided in the Appendix, which results in a lower number of events. The results are qualitatively similar. In the case of fiscal need (Table 48 and Table 49 in the Appendix), we confirm the positive association with rigid expenditure, the lack of significance for most of the political factors and that the results for the economic variables continue to hold but the effect of economic growth is weaker. In the case of fiscal adjustment, we find the expected negative sign for rigid expenditure (Table 50 and Table 51 in the Appendix), which again is statistically significant and in contrast to our baseline models, we find that election year decreases - 28 - the probability of adjustment significantly. Lastly, unlike our baseline specification, we do not find evidence of nonlinearities in the effect of rigid expenditure. Sixth, we estimate the model using a linear probability model identifying the episodes of need with a measure of primary gap under stressed conditions (see Kose et al., 2017), which results in a larger number of episodes. The results are qualitatively similar for the need of fiscal adjustment (Table 52 and Table 53 in the Appendix), with rigid expenditure being positively associated to need. Among the economic factors, economic growth remains as in our baseline models, but previous inflation rate and interest rate are negatively correlated. Among the political factors, only rule of law is significantly correlated with need in some of the specifications. In the case of fiscal adjustment (Table 52Table 54 and Table 55 in the Appendix), we confirm our baseline results and find evidence that rigid expenditure reduces the probability of adjustment, however only when we use the structural measure of rigidity. Moreover, growth and the interest rate are negatively associated to the probability fiscal adjustment, as we expected. In contrast with our baseline estimation, we find statistical evidence that income inequality and the rule of law increase the likelihood of adjustment. In addition, we find some evidence of nonlinearities as the impact of rigid expenditure is attenuated by margin of majority. VII. Conclusion This paper was motivated by the fact that many Latin American countries are facing significant challenges to adjust their fiscal deficits. Consecutive years of large fiscal deficits contributed to sharp increases in the public debt. To bring their debt back to a sustainable path, some countries in the region need to reduce government expenditures or find new sources of revenues. However, many policy makers claim that is hard to reduce spending, as a large portion of it is explained by salaries of public employees, pensions and interest payments, all components that are rigid in the short run. This paper contributes to the existing literature by looking at how budget rigidities affect the probability that governments get into fiscal distress and the probability that they initiate successful fiscal adjustment while they are in need. It considers the effect of budget rigidities not only during periods of fiscal adjustment, but also during periods when governments should be making fiscal efforts and fail to do so, as well as periods when no adjustment is required. Unlike several previous studies, but in line with Wise et al. (2018), our results do not suggest that political-economy variables are robustly related to successful fiscal adjustments. However, we do find evidence that budget rigidities can constrain fiscal - 29 - consolidation, especially when the rigid components (wages and pensions) are above what the structure of their economies would demand. The key findings are that relatively high shares of rigid (observed) components of public spending (wages, pensions and interests) contribute to getting countries into fiscal distress and are a constraint for fiscal consolidation. This could come as a surprise, as many advanced economies with relatively high shares of rigid spending have had successful fiscal consolidations. Nonetheless, we find evidence that a relatively high share of non-structural rigid spending (when spending on public wages and pensions is above what the fundamentals of their economy would suggest) contributes to the probability of fiscal distress and reduces the probability of fiscal consolidation, which is stronger relative to the use of a traditional measure of rigid expenditure. Moreover, the effect of rigid expenditure seems to be more relevant for economies with high income inequality, governments with lower margin of majority and countries with lower institutional quality. Finally, we also find some evidence that higher expenditure in pensions reduces the probability of fiscal adjustment more robustly than higher expenditure in wages. - 30 - References Abiad, A. and T. Baig. (2005). “Underlying Factors Driving Fiscal Effort in Emerging Market Economies.” IMF Working Paper No. 05/106. Alesina, A., Ardagna, S., (1998). “Tales of fiscal adjustment.” Economic Policy 27, 489-545. Alesina, A. and A. Drazen. (1991). “Why Are Stabilizations Delayed?” American Economic Review 81(5): 1170–88. Alesina, A. and R. Perotti. (1995). “Fiscal Expansions and Fiscal Adjustments in OECD Countries.” NBER Working Paper No. 5214. Alesina, A., R. Perotti, and J. Tavares. (1998). “The Political Economy of Fiscal Adjustments.” Brookings Papers on Economic Activity 0(1): 197–248. Alier, Max, (2006), “Measuring Budget Rigidities in Latin America,” IMF Working Paper, forthcoming (Washington: International Monetary Fund). Ardagna, S. (2009), “Determinants and Consequences of Fiscal Consolidations in OECD Countries” in: European Commission: European Economy 2009, European Commission, Brussels. Barrios, S., S. Langedijk and L. Pench (2010). “EU Fiscal Consolidation after the Financial Crisis-Lessons from Past Experiences.”, paper presented at the 12th Banca d’Italia Public Finance Workshop Fiscal Policy: Lessons from the Crisis held in Perugia on 25-27 March. Beetsma, R., J. Cimadomo, O. Furtuna, and M. Giuliodori. (2015). “The confidence effects of fiscal consolidations,” ECB Working Paper, No. 1770. Cetrángolo, O., J.P. Jiménez and R. Ruiz del Castillo (2010) “Rigidities and fiscal space in Latin America: a comparative case study”, Series Macroconomía del Desarrollo 97, Economic Commission for Latin America and the Caribbean (ECLAC), Santiago, Chile. de Haan, J., Klomp, J., (2013). “Conditional political budget cycles: a review of recent evidence.” Public Choice 157, 387-410. Dollar, D. and J. Svensson. (2000). “What Explains the Success or Failure of Structural Adjustment Programs?” Economic Journal 110(October): 894–917, Royal Economic Society. Echeverry, J.C., J.A. Bonilla and A. Moya (2006) “Rigideces institucionales y flexibilidad presupuestaria: los casos de Argentina, Colombia, México y Perú”, Documento CEDE 2006-33, Universidad de los Andes, Bogotá, Colombia. Echeverry, J.C., L. Fergusson and P. Querubín (2005) “Budget inflexibility”, Documento CEDE 2005-52, Universidad de los Andes, Bogotá, Colombia. Echeverry, J.C. V. Navas, y A. Clavijo, (2009). Rigideces presupuestales en Colombia y Peru, en Centrangolo y Juan P. Jimenez. CEPAL, 2009. Edin, P. and E. Ohlsson. (1991). “Political Determinants of Budget Deficits: Coalition Effects versus Minority Effects.” European Economic Review 35: 1597–1603. Escolano, J., L. Jaramillo, C. Mulas-Granados and G. Terrier (2014). "How Much is A Lot? Historical Evidence on the Size of Fiscal Adjustments," IMF Working Papers 14/179, International Monetary Fund. - 31 - European Commission (2007). European Economy – Public Finance in EMU. European Commission, Brussels. Guichard, S., M. Kennedy, E. Wurzel and C. André (2007), “What Promotes Fiscal Consolidation: OECD Country Experiences”, OECD Economics Department Working Paper, No. 553 Gupta, S., E. Baldacci, B. Clements, and E.R. Tiongson. (2003). “What Sustains Fiscal Consolidations in Emerging Market Countries?” IMF Working Paper No. 03/224. Gupta, S., B. Clements, E. Baldacci, and C. Mulas-Granados. (2004). “The Persistence of Fiscal Adjustments in Developing Countries.” Applied Economic Letters: 1350–4851. Kose, A., Kurlat, S. A., Ohnsorge, F. L., Sugawara, N. (2017). “A cross-country database of fiscal space.” Policy Research working paper; no. WPS 8157. Washington, D.C.: World Bank Group. Lavigne, R., (2011). “The political and institutional determinants of fiscal adjustment: entering and exiting fiscal distress”. European Journal of Political Economy, 27, 17-35. Mattina, T. and V. Gunnarsson. (2007). “Budget Rigidity and Expenditure Efficiency in Slovenia”, IMF Working Paper, WP/07/131. McDermott, C.J. and R.F. Wescott. (1996). “An Empirical Analysis of Fiscal Adjustment.” IMF Staff Papers No. 43, 725–53. Mierau, J.O., Jong-A-Pin, R., de Haan, J., (2007). “Do political variables affect fiscal policy adjustment decisions? New empirical evidence.” Public Choice 133, 297-319. Mulas-Granados, C. (2003). “The Political and Economic Determinants of Budgetary Consolidation in Europe.” European Political Economy Review 1(1): 015–039. Pelzman, S., (1992). “Voters as fiscal conservatives”. Quarterly Journal of Economics. 57, 327-361. Perotti, R. (1998). “The Political Economy of Fiscal Consolidations.” Scandinavian Journal of Economics 100(1): 367–94. Perotti, R., Strauch, R. and Hagen, J. von (1998). Sustainable public finances. London: CEPR. Persson, T. and Tabellini, G., (1999). Political economics and macroeconomic policy, ch. 22, p. 1397-1482 in Taylor, J. B. and Woodford, M. eds., Handbook of Macroeconomics, vol. 1, Part C, Elsevier. Pinho, M. (2004). "Political models of budget deficits: a literature review," FEP Working Papers 138, Universidade do Porto, Faculdade de Economia do Porto. Purfield, C. (2003). “Fiscal Adjustment in Transition Countries: Evidence From the 1990s.” IMF Working Paper No. 03/36. Roubini, N. and J. Sachs. (1989). “Political and Economic Determinants of Budget Deficits in the Industrial Democracies.” European Economic Review 33(5): 903–33. Sachs, J. (1989). “Social Conflict and Populist Policies in Latin America.” NBER Working Paper No. 2897. Tabellini, G., Alesina, A., (1990). “Voting on the budget deficit.” American Economic Review 80, 37-49. - 32 - Tavares, J. (2004). “Does Right or Left Matter? Cabinets, Credibility and Fiscal Adjustments.” Journal of Public Economics 88: 2447–68. Vegh, C. A., Lederman, D., and Bennett, F., (2017). “Leaning against the Wind: Fiscal Policy in Latin America and the Caribbean in a Historical Perspective.” Washington, D.C. : World Bank Group. Von Hagen, J. and R.R. Strauch (2001), “Fiscal Consolidations: Quality, Economic Conditions and Success”, Public Choice, Vol. 109. Von Hagen, J., A.H. Hallett and R.R. Strauch (2002), “Budgetary Consolidation in Europe: Quality, Economic Conditions and Persistence”, Journal of the Japanese and International Economies, Vol. 16. Wiese, R., (2014). “What triggers reforms in OECD countries? Improved reform measurement and evidence from the healthcare sector.” European Journal Political Economics, 34, 332-352. World Bank (2017) “Leaning against the wind: Fiscal policy in Latin America and the Caribbean in a historical perspective”, Semiannual Report, Office of the Chief Economist, Washington D.C. - 33 - Appendix 1: Literature Review Table 9: Literature review Paper Fiscal Adjustment Succesful fiscal adjustment Multivariate analysis? Sample Alesina and Blanchard Fiscal Impulse (BFI) is Three years after the adjustment the gross debt to GDP No. 20 (OECD), Perotti less than 1.5% of GDP ratio is at least 5 percentage points lower 1960-92 (1995) McDermott CAPB improves by at least 1.5% Reduction of at least 3 (or 5) percentage points of debt Logit model, conditional 20 (OECD), and Wescott over two years and does not to GDP ratio in second (or third) year after the on adjustment taking 1970-95 (1996) decrease in either of those years adjustment. place. Alesina and BFI falls by more than 1.5% of If either (i) in the three years after the adjustment the No. 20 (OECD), Perotti GDP of a period of two ratio of the CAPB (as % of GDP) is on average at least 2% 1960-94 (1997) consecutive years in which BFI below the last year of adjustment (ii) three years after falls by at least 1.25% per year in the adjustment the debt to GDP ratio is 5% below the both years. level of the last year of the adjustment Alesina and CAPB (as % of GDP) improves by If either (i) in the three years after the adjustment, theProbit model for 20 (OECD), Ardagna at least 2%, or a period of two ratio of the CAPB (as % of GDP) is on average at least 2 success, conditional on 1960-96 (1998) consecutive years in which the percentage points below its value in the year of adjustment taking CAPB improves by at least 1.5% adjustment, or (ii) three years after adjustment, place, but do not per year, in both years. government debt (as % of GDP) is 5 percentage points include spending and below its level in the adjustmnet year. revenues simultaneously. Alesina et al. The ratio of the primary deficit to If (i) either in the three years following the adjustment Only probit estimates 19 (OECD), (1998) GDP is reduced by at least 1.5% year, the deficit-to-GDP ratio is on average at least 2 for consequences of 1960-95 percentage points below its level in the adjustment fiscal adjustments on year; or (ii) three years after the adjustment, the debt- political economy to-GDP ratio is at least 5 percentage points below its variables. All years level in the adjustment year. included, or all years where the change om the deficit is positive. Haylen and Periods of at least two These authors do not define succesful adjustments but OLS estimates using 19 (OECD), Everaert consecutive years when the CAPB estimate model for the change in the debt/GDP ratio as periods when 1960-98 (2000) (as % of GDP) improved by at dependent variable. adjustment took place. least 2%. Furthermore, in the first year of consolidation period the CAPB improves by at least 0.25%, whereas in all other years its change is positive. von Hagen The cyclically adjusted (total) Two years after the initial adjustment, the government Probit models for 20 (OECD), et al. government budget balance budget balance stands at no less than 75% of the succesful adjustments 1960-98 (2001,2002) increases by at least 1.25% of balance in the first year of the consolidation episode. (but do not include cyclically adjusted GDP in two spending and revenue consecutive years, or the cyclically changes) adjusted budget balance increase by at least 1.5% of cyclically adjusted GDP in one year and was positive but perhaps less than 1.25% in both the preceding and subsequent year. Mulas- CAPB increases by at least 1.25% NA. FE models by 15 (EU), 1970- Granados of GDP in two consecutive years, component and LPM. 01 (2003) or if the change in CAPB exceeded 1.5% of GDP in one year and was less than 1.25% of GDP in the following or the precedent year. Baldacci et Year (or set of years) in which the Primary balance exceeds the sustainability threshold at Probit model to 25 emerging al. (2004) general government primary least for one year during the adjustment episode or determine the market budget balance improves by at during the following two years. A country's fiscal contribution of economies, least 0.5% of GDP per year. position is deemed sustainable when its primary economic and political 1980-01 balance is such that debt stock is not increasing as a factors in succesful share of GDP. fiscal adjustments. - 34 - Table A0: Literature review (continuation) Paper Fiscal Adjustment Succesful fiscal adjustment Multivariate analysis? Sample Tavares The change in the primary deficit If the total change in the primary deficit in the 3 years Probit model . Only 19 (OECD), (2004) is -1.5% of GDP or less. after the adjustment is -1% (or less) of GDP or, 3 years adjustment periods 1960-95 after the initial adjustment year, the debt-to-GDP ratio considered. is 5% below its level before the adjustment. Ardagna The CAPB must increase by at A succesful fiscal stabilization is an episode in which the Probit model, but 17 (OECD), (2004) least 1.5% of potential GDP over CAPB improves, and, 2 years after, the debt-to-GDP sample also includes 1975-02 two years and not decrease. ratio is at least 3% lower than in the year of the fiscal years without tightening. adjustment. Ahrend et al. CAPB increases by at least 1% of Classified as seriously pursued if in the two years Probit and FE estimator 24 (OECD), (2006) GDP in one year or over two following the adjustment an additional adjustment of at using cumulative CAPB 1980-05 consecutive years with at least least 1% of GDP is achieved. Success based on the changes. 0.5% in the first year. cumulative adjustment. Tsibouris et Any year or succession of years of Episodes in which reversals over the first three post- Case studies and 165, 1971-01 al. (2006) uninterrupted improvement in adjustment years were less than 1/5 of the total success rates. the fiscal primary balance. adjustment. Guichard et Starts if the CAPB improves by at NA. Probit. 24 (OECD), al. (2007) least 1% of potential GDP in one 1978-05 year or in two consecutive years with at least 0.5% improvement occuring in the first of the two years. Contines as long as CAPB improves allowing deterioration of no more than 0.3% in one year offset by 0.5% improvement next year and stop when CAPB stops increasing or improves less than 0.2% of GDP in one year and then deteriorates. Miearau et 1) An improvement of the CAPB NA. Conditional FE logit. 20 (OECD), al. (2007) by 1.25% points in two 1970-03 consecutive years or an improvement of 1.5% points of the budget balance preceded by a positive change in the budgetary position. 2) Any period starting with an improvement of the budget balance by at least 0.25% in the first year, with a minimum duration of 2 years and a total improvement of 2%. Schaltegger A period of fiscal adjustment is A period of fiscal adjustment is succesful if, in the three Probit model, but Swiss and Feld defined as a year in which the years after adjustment, the (cantonal and local) primary sample also includes cantons, 1981- (2009) (cantonal and local) primary balance improved on average by at least 0.5%. years without 01 balance per GDP improves by at adjustment. least 1%, or a period of two consecutive years in which the primary balance improves by at least 0.8%, in both years. Alesina and A period of fiscal adjustment If the cumulative reduction of the debt-to-GDP ratio 3 OLS, growth regressions OECD, 1970- Ardagna (stimulus) is a year in which the years after the beginning of a fiscal adjustment is using only periods 07 (2010) CAPB improves (deteriorates) by greater than 4.5% (the value of the 25th percentile of where an adjustment at least 1.5% of GDP. the change of the debt-to-GDP ratio empirical density in took place. all episodes of fiscal adjustments). Biggs et al. CAPB improves by at least 1.5% of Debt to potential GDP ratio has declined three years No. 21 [15] (2010) GDP and data of Devries et al. following the first year of the consolidation by at least (OECD), 1970- (2011). 4.5%. 07 [1980-07] - 35 - Table A0: Literature review (continuation) Paper Fiscal Adjustment Succesful fiscal adjustment Multivariate analysis? Sample Barrios et al. Improvement of at least 1.5% If it brings down the public debt level by at least 5% of Two-stage probit. 27 (EU) plus 8 (2010) taking place in one single year or GDP in the three years following the attempt. (OECD), 1970- taking place over three years if 08 each and every year the CAPB does not deteriorate by more than 0.5% of GDP. Arin et al. Attempts are episods where the If at least one of the two criteria holds: 1) in the three Probit model and IV 28 (OECD), (2011) Blanchard fiscal impulse (BFI) is years after the attempt, the ratio of cyclically adjusted regression with an 1978-07 above 1.5%. BFI measures the primary deficit to GDP is on average at least 2% of GDP instrument that varies difference between a year CAPB below the attempt year and 2) three years after the only across countries. and the unadjusted primary attempt, the ratio of debt to GDP is at least 5% of GDP balance of the year before. below the level of the attempt year, as suggested by Alesina and Perotti 1997. Lavigne Need when cumulative total of NA. Logit model. 60 advanced (2011) central government deficits over and the past five years is greater than developing, or equal to 20% of GDP. An 1985-02 adjustment is defined as a continuous positive change in the primary balance amounting to at least 1.5% of GDP over a period of 5 years. Molnar 5 def. using underlying CAPB 1) Three definitions are used: debt stabilises 1) the year Probit, duration, 28 (OECD), (2012) continuous improvement in after 2) two years after 3) three years after the episode truncated regression 1960-09 budget balance, 2) 1% fall in ends. and bivariate Heckman budget balance/GDP in a single selection models. year or in two years with at minumum 0.5 in the first year, 3) 1.5 fall in one or two year with at minimum 1.25 in each, 4) 1.5 fall in a single year or three with less than 0.5 deterioration in any year, 5) 2% fall in a single year or in two with a minimum of 1.5 in each. Baldacci et Authors do not provide definition The length of succesful debt consolidation spell is the Survival analysis of the 120, 1980-10 al. (2012) of fiscal adjustments as their time interval between periods in which the ratio of debt length of the succesful analysis focuses on public debt to GDP declined from a high level to reach the prudent period. reduction, defined as periods of at threshold. This threshold is 60% of GDP for advanced least two consecutive years of economies and 40% of GDP for emerging economies. continuos reduction in the ratio of public debt to GDP. Hernandez A fiscal consolidation episode in a NA. OLS and IV regressions 20 (OECD), de Cos and given year if the CAPB improves concerning 1994-06 Moral- by at least 1.5% of GDP. expansionary Benito Alternatively, we also consider the adjustments. (2012) narrative approach. Alfonso and Four different definitions, Improvement in the CAPB for two consecutive years is Logit model. 18 (OECD), Jalles (2012) including those of Devries et al. at least 1 standard deviation of the CAPB in the full 1970-10 (2011) panel. Alesina and Either (1): a 2-year period in If the debt to GDP ratio is 2 years after the end of a A growth regression on 21 (OECD), Ardagna which the CAPB improves in each fiscal adjustment is lower than the debt to GDP ratio in whether fiscal shocks 1970-10 (2013) year and the cumulative the last year of the adjustment. impact growth (not improvement is at least two fiscal adj.). All years are points of the balance/GDP ratio or included, not only (2): a 3-year or more period in adjustment years. wich the CAPB improves in each year and the cumulative improvement is at least 3%. Holden and A period of fiscal adjustment If the cumulative change in the debt/GDP ratio from the No. 24 (OECD), Larsson (stimulus) is a year in which the year of adjustment and two years forward is smaller 1970-07 Midthjell CAPB improves (deteriorates) by than the 25th percentile of the same variable's density (2013) at least 1.5% of GDP. in all episodes of fiscal adjustments. Variables are measured as ratio to GDP for the two years prior to the adjustment, and as ratio to trend GDP for the adjustment year and the two years after the adjustment. - 36 - Table A0: Literature review (continuation) Paper Fiscal Adjustment Succesful fiscal adjustment Multivariate analysis? Sample Kaplanoglou Attempts are defined as an At least one of the two following criteria holds: 1) in the Logit model. 29 (OECD), et al. (2015) improvement in the CAPB of at three years after the attempt, the ratio of the cyclically 1971-09 least 1.5% of GDP taking place in adjusted primary deficit to GDP is on average at least one year or taking place over 2% of GDP below the attempt year, 2) three years after three years, if in each and every the attempt, the ratio of the debt-to-GDP is at least 5% year the CAPB does not of GDP below the levelk of the attempt year. (following deteriorate by more than 0.5% of Alesina Perotti 1997)_ GDP. Gupta et al. Updates data of Devries et al. Analyses difference between the size of planned fiscal Analyses difference 17 (OECD), (2017) (2011). adjustment and the size of the realized fiscal between planned and 1978-15 adjustment as measured by changes in the primary actual fiscal budget balance (all expressed in percent of GDP) consolidations. Wiese et al. BP test on cyclically adjusted fiscal BP test to the growth rate of the debt-to-GDP ratio. If Probit model with 20 (OECD), (2018) balance to identify the beginning fiscal adjustments are identified prior to, or random effects 1967-13 of an adjustment and then it simultaneously with the beginning of regimes with pretesting using Mudlak continues as long as the change is negative growth rates, and the periods are not more approach. positive. than 4 years apart, we code it as succesful. Appendix 2: Episodes of fiscal need and fiscal adjustment Table 10: Adjustment need in advanced countries under current conditions Country Begin End Country Begin End Australia 1992 1994 Japan 1994 1996 Australia 2010 2010 Japan 1999 2014 Austria 1994 1996 Latvia 2010 2010 Canada 1991 1994 Lithuania 2010 2010 Cyprus 2010 2013 Netherlands 2010 2012 Czech Republic 2001 2003 New Zealand 2010 2011 Czech Republic 2010 2010 Norway 1993 1994 Estonia 2009 2009 Portugal 1994 1994 Finland 1992 1996 Portugal 2005 2005 France 1992 1997 Portugal 2010 2014 France 2010 2010 Slovak Republic 2001 2002 Germany 1996 1997 Slovak Republic 2010 2010 Germany 2003 2003 Slovenia 2010 2013 Greece 1993 1993 Spain 1993 1995 Greece 2009 2015 Spain 2009 2014 Iceland 1993 1993 Sweden 1993 1995 Iceland 2009 2010 United Kingdom 1992 1995 Ireland 2009 2013 United Kingdom 2009 2013 Israel 2003 2003 United States 2009 2012 Table 11: Adjustment need in developing countries under current conditions Country Begin End Country Begin End Angola 2015 2015 India 2012 2012 Argentina 1996 1996 Iraq 2014 2016 Argentina 1999 2004 Jordan 2012 2014 - 37 - Armenia 2016 2016 Kazakhstan 2016 2016 Azerbaijan 2016 2016 Lebanon 1999 2001 Belarus 2016 2016 Mongolia 2014 2016 Belize 2013 2013 Morocco 2012 2012 Belize 2016 2017 Mozambique 2001 2001 Bolivia 1999 2003 Mozambique 2010 2010 Bolivia 2016 2017 Mozambique 2015 2016 Botswana 2004 2004 Namibia 2015 2016 Botswana 2008 2013 Nigeria 1999 1999 Botswana 2016 2017 Nigeria 2016 2016 Bulgaria 2010 2010 Pakistan 2013 2013 Bulgaria 2015 2015 Paraguay 1998 2002 Cameroon 2015 2017 Philippines 2001 2001 Colombia 1999 1999 Poland 2010 2010 Côte d'Ivoire 2000 2008 Romania 2010 2010 Croatia 2010 2015 Russian Federation 2016 2016 Ecuador 1996 1996 Saudi Arabia 2002 2002 Ecuador 1999 2000 Senegal 2000 2001 Ecuador 2014 2017 Senegal 2010 2015 Egypt, Arab Rep. 2003 2004 Serbia 2010 2010 Egypt, Arab Rep. 2012 2017 Serbia 2015 2015 El Salvador 2010 2010 South Africa 2013 2016 Ethiopia 1998 2002 Trinidad & Tobago 2015 2017 Gabon 2016 2016 Tunisia 2016 2017 Georgia 2010 2010 Ukraine 2014 2014 Georgia 2014 2016 Uruguay 2002 2002 Guatemala 2000 2000 Vanuatu 2001 2002 Honduras 2003 2003 Vanuatu 2015 2017 Honduras 2010 2010 Venezuela, RB 2012 2015 Honduras 2013 2013 Vietnam 2013 2016 India 1997 2002 Zambia 2015 2015 Table 12: Adjustment status in advanced countries using current conditions Country Begin End Country Begin End Cyprus 2012 2013 Netherlands 2010 2012 France 1994 1997 Norway 1993 1994 Germany 1996 1997 Portugal 2011 2013 Greece 2010 2013 Spain 2010 2014 Iceland 2009 2010 Sweden 1994 1995 Ireland 2011 2013 United Kingdom 1994 1995 Japan 2004 2007 United Kingdom 2010 2011 Japan 2011 2014 United States 2010 2012 Table 13: Adjustment status in developing countries using current conditions Country Begin End Country Begin End Argentina 2002 2004 Egypt, Arab Rep. 2016 2017 - 38 - Belize 2016 2017 Georgia 2015 2016 Bolivia 1999 2000 India 1999 2000 Botswana 2010 2013 Mozambique 2015 2016 Botswana 2016 2017 Paraguay 1998 1999 Côte d'Ivoire 2000 2001 Senegal 2014 2015 Côte d'Ivoire 2007 2008 South Africa 2013 2015 Croatia 2012 2014 Vanuatu 2001 2002 Ecuador 1999 2000 Vietnam 2014 2015 Table 14: Adjustment need in developed countries using debt/revenue ratio Country Begin End Country Begin End Australia 1993 1999 Korea, Rep. 2005 2007 Australia 2012 2017 Korea, Rep. 2010 2010 Austria 1995 1996 Korea, Rep. 2014 2017 Austria 2010 2016 Latvia 2010 2017 Belgium 1992 1999 Lithuania 2000 2001 Belgium 2012 2016 Lithuania 2010 2016 Canada 1994 1999 Luxembourg 1996 1998 Canada 2010 2017 Luxembourg 2009 2017 Cyprus 2003 2005 Malta 1999 1999 Cyprus 2013 2017 Malta 2004 2005 Czech Republic 2002 2004 Malta 2010 2014 Czech Republic 2010 2015 Netherlands 1991 1998 Denmark 1994 1999 Netherlands 2010 2016 Denmark 2011 2014 New Zealand 1991 1995 Estonia 1996 1997 New Zealand 2011 2016 Estonia 2003 2003 Norway 1992 1994 Estonia 2013 2017 Norway 2004 2010 Finland 1994 1998 Norway 2017 2017 Finland 2011 2017 Portugal 1991 1991 France 1996 1999 Portugal 1995 1996 France 2010 2017 Portugal 2011 2017 Germany 1996 1999 Singapore 1992 1992 Germany 2005 2005 Singapore 1999 1999 Germany 2010 2014 Singapore 2002 2005 Greece 1994 1997 Singapore 2009 2013 Greece 2001 2001 Singapore 2017 2017 Greece 2011 2017 Slovak Republic 2000 2004 Hong Kong SAR, China 2002 2002 Slovak Republic 2012 2017 Hong Kong SAR, China 2005 2005 Slovenia 2001 2002 Iceland 1994 1997 Slovenia 2013 2017 Iceland 2009 2014 Spain 1994 2000 Ireland 1991 1997 Spain 2012 2017 Ireland 2011 2014 Sweden 1994 1999 Israel 2002 2006 Sweden 2015 2016 Italy 1994 1999 Switzerland 1995 2000 Italy 2011 2017 Switzerland 2003 2005 - 39 - Japan 2000 2005 United Kingdom 1994 1998 Japan 2010 2017 United Kingdom 2010 2017 Korea, Rep. 1991 1991 United States 2010 2017 Table 15: Adjustment need in developing countries using debt/revenue ratio Country Begin End Country Begin End Afghanistan 2003 2005 Lesotho 1993 1994 Albania 1998 2000 Lesotho 1999 2002 Albania 2014 2017 Liberia 2001 2007 Algeria 1995 1996 Macedonia, FYR 2001 2005 Algeria 1999 2000 Macedonia, FYR 2013 2017 Algeria 2017 2017 Madagascar 1992 1993 Angola 2001 2004 Madagascar 1999 2005 Angola 2016 2017 Madagascar 2017 2017 Antigua & Barbuda 1991 1991 Malawi 2003 2005 Antigua & Barbuda 1999 2004 Malawi 2014 2017 Antigua & Barbuda 2014 2015 Malaysia 1991 1993 Argentina 2003 2006 Malaysia 2004 2004 Argentina 2016 2017 Malaysia 2010 2017 Armenia 1997 2003 Maldives 2002 2002 Armenia 2010 2017 Maldives 2010 2017 Azerbaijan 2000 2004 Mali 2001 2001 Azerbaijan 2016 2017 Mali 2004 2005 Bahamas, The 1994 1998 Mali 2016 2017 Bahamas, The 2011 2017 Marshall Islands 2002 2009 Bahrain 1999 2004 Mauritania 2001 2005 Bahrain 2016 2017 Mauritania 2016 2017 Bangladesh 2004 2009 Mauritius 2003 2005 Barbados 1996 1996 Mauritius 2011 2011 Barbados 2010 2017 Mauritius 2014 2017 Belarus 2010 2012 Mexico 1999 1999 Belarus 2016 2017 Mexico 2003 2003 Belize 2004 2007 Mexico 2014 2017 Belize 2017 2017 Micronesia, Fed. States 1996 1999 Benin 2000 2002 Micronesia, Fed. States 2009 2011 Benin 2016 2017 Micronesia, Fed. States 2014 2014 Bhutan 1994 1994 Moldova 1999 2002 Bhutan 2003 2006 Moldova 2015 2017 Bhutan 2014 2017 Morocco 1994 2002 Bolivia 2003 2005 Morocco 2014 2017 Bolivia 2017 2017 Mozambique 2000 2003 Bosnia & Herzegovina 1999 1999 Mozambique 2016 2017 Bosnia & Herzegovina 2011 2016 Myanmar 2001 2005 Botswana 2010 2015 Namibia 1999 1999 Brazil 2002 2005 Namibia 2004 2006 Brazil 2016 2017 Namibia 2016 2017 Brunei Darussalam 2012 2017 Nepal 2001 2006 - 40 - Bulgaria 1999 2003 Nicaragua 2000 2005 Bulgaria 2015 2017 Niger 2000 2005 Burkina Faso 2003 2005 Niger 2016 2017 Burkina Faso 2016 2017 Nigeria 1991 1994 Burundi 2003 2008 Nigeria 2000 2004 Cabo Verde 1998 1998 Nigeria 2016 2017 Cabo Verde 2001 2005 Oman 1993 2003 Cabo Verde 2014 2017 Oman 2016 2017 Cambodia 2003 2006 Pakistan 2000 2003 Cambodia 2012 2013 Pakistan 2013 2017 Cameroon 1999 2005 Panama 1995 1996 Cameroon 2016 2017 Panama 2002 2006 Central African Rep. 2001 2005 Papua New Guinea 1998 2004 Central African Rep. 2015 2017 Papua New Guinea 2015 2017 Chad 2000 2003 Paraguay 1991 1992 Chad 2015 2017 Paraguay 2000 2004 Chile 1992 1994 Paraguay 2016 2017 Chile 2002 2003 Peru 2001 2006 Chile 2013 2017 Philippines 1994 1995 China 2003 2003 Philippines 2002 2006 China 2010 2010 Poland 1996 1997 China 2014 2017 Poland 2004 2006 Colombia 2001 2005 Poland 2010 2013 Colombia 2015 2017 Qatar 1995 2003 Comoros 1991 2000 Qatar 2012 2012 Congo, Dem. Rep. 2001 2007 Qatar 2016 2017 Congo, Rep. 2001 2004 Romania 2001 2003 Congo, Rep. 2016 2017 Romania 2011 2017 Costa Rica 1999 2005 Russian Federation 2000 2002 Costa Rica 2014 2017 Russian Federation 2015 2017 Côte d'Ivoire 1998 2002 Rwanda 1996 1996 Côte d'Ivoire 2006 2008 Rwanda 2000 2005 Croatia 2011 2017 Rwanda 2016 2017 Djibouti 2003 2010 Samoa 1999 2002 Dominica 2002 2006 Samoa 2013 2017 Dominica 2014 2015 São Tomé & Príncipe 2002 2006 Dominican Republic 2004 2004 Saudi Arabia 1996 2004 Dominican Republic 2013 2017 Saudi Arabia 2017 2017 Ecuador 2002 2007 Senegal 2001 2005 Ecuador 2016 2017 Senegal 2014 2017 Egypt, Arab Rep. 2003 2006 Serbia 2001 2001 Egypt, Arab Rep. 2014 2017 Serbia 2013 2017 El Salvador 1992 1993 Seychelles 1999 2004 El Salvador 2003 2004 Seychelles 2008 2008 El Salvador 2010 2017 Sierra Leone 2002 2006 Equatorial Guinea 1991 1995 Sierra Leone 2017 2017 Equatorial Guinea 2016 2017 Solomon Islands 2004 2009 Eritrea 2002 2003 South Africa 2001 2003 Eritrea 2008 2008 South Africa 2013 2017 - 41 - Ethiopia 1994 1996 Sri Lanka 1991 1991 Ethiopia 2002 2005 Sri Lanka 2001 2004 Ethiopia 2016 2017 Sri Lanka 2016 2017 Fiji 1995 1997 St. Kitts & Nevis 2003 2012 Fiji 2007 2012 St. Lucia 2002 2006 Gabon 1991 1993 St. Lucia 2012 2017 Gabon 1999 2004 St. Vincent & the Grenadines 1991 1992 Gabon 2016 2017 St. Vincent & the Grenadines 2000 2001 Gambia, The 2002 2006 St. Vincent & the Grenadines 2005 2006 Gambia, The 2015 2017 St. Vincent & the Grenadines 2012 2017 Georgia 2001 2004 Sudan 1993 1995 Georgia 2010 2010 Sudan 2013 2013 Georgia 2016 2017 Sudan 2016 2017 Ghana 1995 1995 Suriname 1991 1993 Ghana 2000 2003 Suriname 2000 2005 Ghana 2014 2017 Suriname 2016 2017 Grenada 2003 2007 Eswatini 1999 2003 Grenada 2010 2014 Eswatini 2016 2017 Guatemala 2010 2017 Syrian Arab Republic 1991 1994 Guinea 2000 2006 Syrian Arab Republic 1998 2004 Guinea 2011 2011 Tajikistan 1999 2003 Guinea-Bissau 2001 2009 Tajikistan 2017 2017 Guyana 1998 2006 Tanzania 2002 2005 Haiti 2001 2006 Tanzania 2015 2017 Haiti 2016 2017 Thailand 1999 2005 Honduras 1991 1993 Thailand 2013 2017 Honduras 2003 2005 Togo 2006 2009 Honduras 2014 2017 Togo 2016 2017 Hungary 1996 1996 Tonga 2013 2016 Hungary 2009 2014 Trinidad & Tobago 1992 2002 India 1992 1994 Trinidad & Tobago 2016 2017 India 2002 2006 Tunisia 1994 1997 Indonesia 2001 2004 Tunisia 2000 2000 Indonesia 2017 2017 Tunisia 2004 2005 Iran, Islamic Rep. 1997 1998 Tunisia 2015 2017 Iran, Islamic Rep. 2003 2004 Turkey 2002 2005 Iran, Islamic Rep. 2016 2017 Turkmenistan 1998 2001 Iraq 2005 2007 Turkmenistan 2013 2017 Iraq 2017 2017 Tuvalu 2006 2006 Jamaica 2003 2005 Tuvalu 2016 2017 Jamaica 2010 2014 Uganda 2000 2005 Jordan 1991 1993 Uganda 2015 2017 Jordan 2003 2004 Ukraine 1999 2002 Jordan 2014 2017 Ukraine 2015 2017 Kazakhstan 2003 2004 United Arab Emirates 2009 2012 Kazakhstan 2015 2017 United Arab Emirates 2016 2017 Kenya 1999 1999 Uruguay 2003 2006 Kenya 2002 2004 Uzbekistan 2001 2005 Kenya 2015 2017 Vanuatu 1999 2004 - 42 - Kiribati 1994 1997 Vanuatu 2016 2017 Kiribati 2016 2017 Venezuela, RB 2003 2004 Kosovo 2007 2008 Venezuela, RB 2012 2014 Kosovo 2016 2017 Vietnam 2010 2010 Kuwait 1992 1995 Vietnam 2013 2017 Kuwait 2017 2017 Yemen, Rep. 2000 2003 Kyrgyz Republic 2001 2005 Yemen, Rep. 2016 2017 Kyrgyz Republic 2016 2017 Zambia 2001 2004 Lao PDR 2002 2005 Zambia 2016 2017 Lao PDR 2015 2017 Zimbabwe 2009 2010 Lebanon 2004 2008 Zimbabwe 2017 2017 Lebanon 2017 2017 Table 16: Fiscal adjustment in advanced countries using debt/revenue ratio Country Begin End Country Begin End Australia 1994 1997 Japan 2004 2005 Australia 2012 2015 Japan 2011 2016 Austria 2010 2013 Korea, Rep. 2005 2006 Belgium 1993 1998 Korea, Rep. 2016 2017 Belgium 2012 2013 Latvia 2010 2012 Canada 1994 1997 Latvia 2015 2016 Canada 2011 2015 Lithuania 2014 2016 Cyprus 2004 2005 Luxembourg 1996 1997 Cyprus 2013 2014 Luxembourg 2011 2013 Czech Republic 2010 2012 Malta 2004 2005 Denmark 1995 1999 Malta 2010 2011 Denmark 2013 2014 Netherlands 2010 2013 Estonia 2013 2014 New Zealand 1992 1995 Finland 1996 1998 New Zealand 2011 2016 Finland 2015 2016 Norway 1993 1994 France 1996 1999 Norway 2004 2006 France 2011 2013 Portugal 2011 2013 France 2015 2017 Portugal 2015 2016 Germany 1996 1999 Slovak Republic 2012 2014 Germany 2011 2014 Slovak Republic 2016 2017 Greece 1994 1996 Slovenia 2014 2016 Greece 2011 2013 Spain 1996 1999 Iceland 1995 1997 Spain 2012 2014 Iceland 2009 2014 Sweden 1994 1998 Ireland 1991 1994 Sweden 2015 2016 Ireland 1996 1997 United Kingdom 1994 1998 Ireland 2011 2014 United Kingdom 2010 2011 Israel 2003 2006 United Kingdom 2015 2017 Italy 1995 1997 United States 2010 2015 Italy 2011 2013 - 43 - Table 17: Fiscal adjustment in emerging countries using debt/revenue ratio Country Begin End Country Begin End Albania 2015 2016 Iran, Islamic Rep. 2003 2004 Algeria 1995 1996 Jamaica 2012 2013 Algeria 1999 2000 Jordan 2014 2017 Antigua & Barbuda 2002 2004 Kenya 2003 2004 Argentina 2003 2004 Kuwait 1992 1995 Armenia 2010 2012 Kyrgyz Republic 2001 2002 Armenia 2016 2017 Macedonia, FYR 2002 2003 Azerbaijan 2000 2001 Macedonia, FYR 2015 2017 Azerbaijan 2016 2017 Madagascar 2002 2003 Bahamas, The 1994 1995 Malaysia 2010 2013 Bahamas, The 2014 2016 Mauritania 2016 2017 Bahrain 1999 2000 Mexico 2015 2017 Bahrain 2003 2004 Moldova 2015 2017 Bahrain 2016 2017 Morocco 1995 1997 Bangladesh 2006 2007 Morocco 2014 2017 Barbados 2016 2017 Mozambique 2002 2003 Belarus 2010 2012 Mozambique 2016 2017 Belarus 2016 2017 Namibia 2005 2006 Belize 2004 2007 Namibia 2016 2017 Benin 2016 2017 Nepal 2002 2003 Bolivia 2003 2005 Nicaragua 2002 2003 Botswana 2010 2013 Niger 2016 2017 Brazil 2016 2017 Oman 1994 1997 Bulgaria 2015 2016 Oman 1999 2000 Cabo Verde 2001 2004 Pakistan 2000 2002 Cabo Verde 2014 2016 Pakistan 2013 2014 Cambodia 2003 2005 Panama 1995 1996 Cambodia 2012 2013 Panama 2005 2006 Chad 2000 2002 Paraguay 2003 2004 Chad 2015 2017 Peru 2001 2002 Comoros 1996 1997 Peru 2004 2006 Congo, Dem. Rep. 2001 2002 Philippines 2003 2006 Congo, Dem. Rep. 2004 2006 Poland 2004 2005 Congo, Rep. 2003 2004 Poland 2011 2013 Congo, Rep. 2016 2017 Romania 2011 2012 Costa Rica 2015 2016 Russian Federation 2016 2017 Côte d'Ivoire 2000 2001 Rwanda 2003 2004 Côte d'Ivoire 2007 2008 Saudi Arabia 1996 1997 Croatia 2012 2017 Saudi Arabia 1999 2000 Dominica 2002 2003 Saudi Arabia 2003 2004 Dominican Republic 2013 2015 Senegal 2014 2016 Egypt, Arab Rep. 2016 2017 Sierra Leone 2004 2006 El Salvador 2013 2017 South Africa 2013 2015 Equatorial Guinea 2016 2017 Sri Lanka 2001 2003 Eritrea 2002 2003 Sri Lanka 2016 2017 Ethiopia 2003 2004 St. Lucia 2013 2016 - 44 - Gabon 1999 2000 St. Vincent & the Grenadines 2014 2016 Gambia, The 2002 2003 Sudan 1993 1994 Georgia 2001 2002 Thailand 2015 2016 Georgia 2016 2017 Togo 2007 2008 Ghana 2002 2003 Trinidad & Tobago 2000 2001 Ghana 2014 2015 Uganda 2003 2004 Guatemala 2011 2016 Uganda 2015 2017 Guinea 2004 2005 United Arab Emirates 2010 2012 Guinea-Bissau 2008 2009 United Arab Emirates 2016 2017 Honduras 1991 1992 Uruguay 2003 2004 Honduras 2004 2005 Uzbekistan 2003 2005 Honduras 2014 2017 Vanuatu 2001 2004 India 2004 2006 Vietnam 2014 2016 Indonesia 2001 2002 Zimbabwe 2009 2010 - 45 - Figure A1: Countries doing fiscal adjustment Number of countries doing fiscal adjustment Advanced economies EMDEs 20 30 15 20 10 10 5 0 0 1990 2000 2010 2020 1990 2000 2010 2020 Year Year Primary gap Debt/revenue Primary gap Debt/revenue - 46 - Appendix 3: Linear probability models: Table 18 Dependent variable: Need of fiscal adjustment based on Escolano et al. (2014) Variables (1) (2) (3) (4) (5) (6) (7) (8) Rigid expenditure minus 0.038*** 0.032*** 0.039*** 0.032*** 0.041*** 0.041*** 0.010 0.026 structural as % GDP (0.007) (0.006) (0.006) (0.006) (0.008) (0.014) (0.020) (0.016) Economic factors GDP growth (t-1) -2.034*** -1.901*** -1.807*** -1.869*** -1.860*** -1.909*** (0.422) (0.419) (0.410) (0.423) (0.411) (0.422) Inflation (t-1) -0.046 -0.001 -0.013 -0.004 -0.008 -0.003 (0.063) (0.052) (0.056) (0.052) (0.056) (0.054) U.S. Interest rate -0.016 -0.022* -0.024* -0.023* -0.025** -0.022* (0.011) (0.012) (0.012) (0.012) (0.012) (0.012) Political factors Gini 0.007 0.006 0.005 0.007 0.006 0.006 (0.006) (0.006) (0.006) (0.007) (0.006) (0.006) Rule of law 0.001 0.021 0.017 0.020 -0.026 0.021 (0.031) (0.032) (0.031) (0.031) (0.035) (0.032) Margin of Majority 0.082 0.052 0.068 0.052 0.061 -0.030 (0.128) (0.129) (0.128) (0.130) (0.129) (0.152) Election's year 0.021 0.029* 0.031** 0.029* 0.030* 0.029* (0.015) (0.015) (0.015) (0.015) (0.015) (0.015) Interactions EMEs * Deviation -0.020* (0.011) Gini * Deviation -0.000 (0.000) Rule of law * Deviation 0.005 (0.004) Majority * Deviation 0.011 (0.026) Constant -0.226*** -0.041 -0.581* -0.379 -0.355 -0.446 -0.183 -0.327 (0.065) (0.070) (0.323) (0.295) (0.281) (0.340) (0.268) (0.290) Observations 1,467 1,451 1,318 1,304 1,304 1,304 1,304 1,304 R-squared 0.104 0.164 0.118 0.171 0.179 0.172 0.176 0.172 Number of ifscode 83 83 74 74 74 74 74 74 Country FE Yes Yes Yes Yes Yes Yes Yes Yes Robust standard errors clustered by country in parentheses *** p<0.01, ** p<0.05, * p<0.1 - 47 - Table 19 Dependent variable: Need of fiscal adjustment based on debt/revenue Variables (1) (2) (3) (4) (5) (6) (7) (8) Rigid expenditure minus 0.012** 0.009* 0.013* 0.009 0.036*** 0.030 -0.026 0.017 structural as % GDP (0.005) (0.005) (0.007) (0.007) (0.010) (0.027) (0.019) (0.019) Economic factors GDP growth (t-1) -1.504*** -1.999*** -1.750*** -1.967*** -1.910*** -1.992*** (0.363) (0.353) (0.367) (0.360) (0.371) (0.354) Inflation (t-1) 0.026 0.285** 0.273** 0.273** 0.262** 0.288** (0.145) (0.128) (0.128) (0.129) (0.129) (0.128) U.S. Interest rate -0.008 -0.016 -0.020 -0.017 -0.020 -0.016 (0.012) (0.013) (0.013) (0.013) (0.013) (0.013) Political factors Gini 0.007 0.007 0.007 0.010 0.007 0.007 (0.006) (0.005) (0.005) (0.007) (0.005) (0.005) Rule of law 0.014 0.039 0.034 0.036 -0.033 0.039 (0.044) (0.050) (0.051) (0.050) (0.061) (0.050) Margin of Majority -0.162 -0.143 -0.129 -0.149 -0.135 -0.067 (0.153) (0.157) (0.154) (0.156) (0.158) (0.248) Election's year -0.010 -0.007 -0.004 -0.006 -0.005 -0.007 (0.015) (0.016) (0.016) (0.016) (0.016) (0.016) Interactions EMEs * Deviation -0.044*** (0.013) Gini * Deviation -0.001 (0.001) Rule of law * Deviation 0.009* (0.004) Majority * Deviation -0.012 (0.027) Constant 0.274*** 0.384*** 0.021 0.068 0.072 -0.039 0.328 0.019 (0.038) (0.064) (0.298) (0.282) (0.276) (0.326) (0.303) (0.307) Observations 2,799 2,738 1,949 1,918 1,918 1,918 1,918 1,918 R-squared 0.005 0.023 0.011 0.039 0.052 0.040 0.044 0.039 Number of ifscode 138 137 98 98 98 98 98 98 Country FE Yes Yes Yes Yes Yes Yes Yes Yes Robust standard errors clustered by country in parentheses *** p<0.01, ** p<0.05, * p<0.1 - 48 - Table 20 Dependent variable: Need of fiscal adjustment based on Escolano et al. (2014) Variables (1) (2) (3) (4) (5) (6) (7) (8) Rigid expenditure, CE 0.058*** 0.052*** 0.061*** 0.053*** 0.051*** 0.053*** 0.051*** 0.053*** (% of GDP) (0.015) (0.013) (0.014) (0.013) (0.014) (0.014) (0.014) (0.013) Rigid expenditure, SS 0.031*** 0.029*** 0.034*** 0.029*** 0.039*** 0.029** 0.015 0.030** (% of GDP) (0.008) (0.007) (0.007) (0.007) (0.008) (0.014) (0.019) (0.012) Economic factors GDP growth (t-1) -2.093*** -1.963***-1.850***-1.962***-1.934***-1.960*** (0.424) (0.427) (0.408) (0.429) (0.415) (0.436) Inflation (t-1) -0.016 0.021 -0.000 0.021 0.016 0.021 (0.054) (0.043) (0.048) (0.043) (0.046) (0.044) U.S. Interest rate 0.002 -0.002 -0.000 -0.002 -0.002 -0.002 (0.010) (0.012) (0.012) (0.012) (0.012) (0.012) Political factors Gini 0.007 0.005 0.004 0.005 0.005 0.005 (0.006) (0.006) (0.006) (0.007) (0.006) (0.006) Rule of law 0.032 0.023 0.014 0.023 -0.029 0.022 (0.027) (0.031) (0.029) (0.031) (0.046) (0.032) Margin of Majority 0.050 0.041 0.057 0.041 0.057 0.060 (0.123) (0.125) (0.124) (0.126) (0.129) (0.165) Election's year 0.020 0.028* 0.030** 0.028* 0.029** 0.028* (0.015) (0.015) (0.014) (0.015) (0.014) (0.015) Interactions EMEs * Rigidity -0.020 (0.013) Gini * Rigidity -0.000 (0.000) Rule of law * Rigidity 0.003 (0.003) Majority * Rigidity -0.002 (0.014) Constant -0.840***-0.685***-1.345***-1.000***-0.980***-1.004*** -0.806** -1.011*** (0.199) (0.175) (0.308) (0.283) (0.280) (0.337) (0.324) (0.292) Observations 1,521 1,500 1,360 1,342 1,342 1,342 1,342 1,342 R-squared 0.115 0.172 0.134 0.179 0.184 0.179 0.181 0.179 Number of ifscode 84 84 75 75 75 75 75 75 Country FE Yes Yes Yes Yes Yes Yes Yes Yes Robust standard errors clustered by country in parentheses *** p<0.01, ** p<0.05, * p<0.1 - 49 - Table 21 Dependent variable: Need of fiscal adjustment based on Escolano et al. (2014) Variables (1) (2) (3) (4) (5) (6) (7) (8) Rigid CE minus structural as % GDP 0.064*** 0.054*** 0.068*** 0.055*** 0.054*** 0.055*** 0.056*** 0.055*** (0.015) (0.012) (0.015) (0.014) (0.014) (0.014) (0.014) (0.014) Rigid SS minus structural as % GDP 0.031*** 0.027*** 0.031*** 0.027*** 0.036*** 0.028** 0.010 0.026*** (0.007) (0.006) (0.007) (0.006) (0.008) (0.012) (0.016) (0.010) Economic factors GDP growth (t-1) -1.976*** -1.848***-1.721***-1.841***-1.835***-1.850*** (0.427) (0.425) (0.407) (0.427) (0.422) (0.434) Inflation (t-1) -0.054 -0.012 -0.036 -0.013 -0.018 -0.012 (0.053) (0.043) (0.049) (0.043) (0.042) (0.043) U.S. Interest rate -0.016 -0.021* -0.025* -0.022 -0.012 -0.021 (0.011) (0.012) (0.013) (0.013) (0.013) (0.013) Political factors Gini 0.006 0.005 0.004 0.005 0.005 0.005 (0.006) (0.006) (0.006) (0.007) (0.006) (0.006) Rule of law 0.001 0.020 0.011 0.020 -0.045 0.020 (0.031) (0.032) (0.030) (0.032) (0.039) (0.033) Margin of Majority 0.085 0.054 0.073 0.055 0.076 0.043 (0.124) (0.126) (0.126) (0.127) (0.127) (0.162) Election's year 0.021 0.028* 0.030** 0.028* 0.029* 0.028* (0.015) (0.015) (0.015) (0.015) (0.015) (0.015) Interactions EMEs * Rigidity -0.020 (0.013) Gini * Rigidity -0.000 (0.000) Rule of law * Rigidity 0.004 (0.003) Majority * Rigidity 0.001 (0.012) Constant -0.255*** -0.071 -0.576* -0.375 -0.248 -0.377 -0.324 -0.374 (0.069) (0.071) (0.327) (0.296) (0.275) (0.303) (0.288) (0.296) Observations 1,467 1,451 1,318 1,304 1,304 1,304 1,304 1,304 R-squared 0.111 0.169 0.127 0.176 0.181 0.176 0.180 0.176 Number of ifscode 83 83 74 74 74 74 74 74 Country FE Yes Yes Yes Yes Yes Yes Yes Yes Robust standard errors clustered by country in parentheses *** p<0.01, ** p<0.05, * p<0.1 - 50 - Table 22 Dependent variable: Fiscal adjustment when needed based on Escolano et al. (2014) Variables (1) (2) (3) (4) (5) (6) (7) (8) Rigid expenditure, CE -0.020 -0.026 -0.028 -0.066 -0.048 -0.041 -0.060 -0.062 (% of GDP) (0.063) (0.055) (0.062) (0.060) (0.064) (0.061) (0.060) (0.055) Rigid expenditure, SS -0.025** -0.038*** -0.026** -0.034***-0.022*** 0.106* -0.121*** -0.079** (% of GDP) (0.012) (0.011) (0.011) (0.011) (0.007) (0.057) (0.033) (0.032) Economic factors GDP growth (t-1) -0.296 0.311 0.465 0.383 0.245 0.341 (1.387) (1.441) (1.444) (1.450) (1.432) (1.436) Inflation (t-1) 2.625*** 2.731*** 3.609*** 3.370*** 3.701*** 2.587** (0.774) (0.996) (1.048) (0.999) (0.997) (1.074) U.S. Interest rate -0.129** -0.167** -0.175***-0.197***-0.201***-0.180*** (0.051) (0.063) (0.065) (0.055) (0.069) (0.050) Political factors Gini 0.008 0.007 0.009 0.054** 0.009 0.001 (0.009) (0.011) (0.011) (0.022) (0.012) (0.010) Rule of law -0.224*** 0.092 0.129 0.122 -0.061 0.096 (0.062) (0.124) (0.125) (0.121) (0.112) (0.126) Margin of Majority 0.437 0.154 0.118 0.272 0.150 -0.944* (0.383) (0.357) (0.361) (0.339) (0.351) (0.550) Election's year -0.111 -0.087 -0.073 -0.068 -0.070 -0.074 (0.079) (0.075) (0.070) (0.071) (0.075) (0.080) Interactions EMEs * Rigidity -0.058* (0.033) Gini * Rigidity -0.004** (0.002) Rule of law * Rigidity 0.018*** (0.006) Majority * Rigidity 0.088 (0.059) Constant 0.807 1.384** 1.247 1.180 0.972 -0.996 1.882** 1.948** (0.600) (0.555) (0.815) (0.981) (0.973) (1.428) (0.877) (0.905) Observations 185 183 165 163 163 163 163 163 R-squared 0.021 0.139 0.090 0.185 0.200 0.224 0.214 0.206 Number of ifscode 60 60 53 53 53 53 53 53 Country FE Yes Yes Yes Yes Yes Yes Yes Yes Robust standard errors clustered by country in parentheses *** p<0.01, ** p<0.05, * p<0.1 - 51 - Table 23 Dependent variable: Fiscal adjustment when needed based on Escolano et al. (2014) Variables (1) (2) (3) (4) (5) (6) (7) (8) Rigid CE minus structural as % GDP -0.039 -0.035 -0.030 -0.055 -0.037 -0.035 -0.044 -0.051 (0.068) (0.052) (0.064) (0.063) (0.066) (0.056) (0.065) (0.060) Rigid SS minus structural as % GDP-0.031***-0.030***-0.033***-0.032***-0.020*** 0.107* -0.110** -0.077** (0.012) (0.009) (0.012) (0.011) (0.006) (0.056) (0.047) (0.029) Economic factors GDP growth (t-1) 0.053 0.143 0.424 0.332 0.195 0.129 (1.340) (1.527) (1.573) (1.544) (1.536) (1.520) Inflation (t-1) 2.747*** 3.224*** 3.758*** 3.453*** 3.731*** 3.265*** (0.808) (1.166) (1.108) (1.120) (1.069) (1.200) U.S. Interest rate -0.136** -0.151** -0.162** -0.240*** -0.144** -0.147** (0.051) (0.066) (0.067) (0.059) (0.068) (0.058) Political factors Gini 0.006 0.004 0.008 0.058** 0.003 -0.003 (0.010) (0.013) (0.013) (0.027) (0.014) (0.013) Rule of law -0.208*** 0.115 0.131 0.120 -0.041 0.132 (0.068) (0.141) (0.136) (0.119) (0.168) (0.147) Margin of Majority 0.386 0.143 0.115 0.313 0.120 -0.982* (0.385) (0.373) (0.376) (0.355) (0.381) (0.515) Election's year -0.111 -0.081 -0.071 -0.069 -0.069 -0.065 (0.079) (0.077) (0.071) (0.072) (0.075) (0.082) Interactions EMEs * Rigidity -0.061 (0.037) Gini * Rigidity -0.004** (0.002) Rule of law * Rigidity 0.016* (0.008) Majority * Rigidity 0.089 (0.057) Constant 0.599** 0.907*** 0.956 0.354 0.437 -0.483 0.486 0.779 (0.231) (0.253) (0.718) (0.940) (0.905) (0.982) (0.937) (0.897) Observations 182 180 164 162 162 162 162 162 R-squared 0.035 0.157 0.100 0.181 0.196 0.225 0.201 0.202 Number of ifscode 60 60 53 53 53 53 53 53 Country FE Yes Yes Yes Yes Yes Yes Yes Yes Robust standard errors clustered by country in parentheses *** p<0.01, ** p<0.05, * p<0.1 - 52 - Appendix 4: Logit models: Table 24 Dependent variable: Need of fiscal adjustment based on Escolano et al. (2014) Variables (1) (2) (3) (4) (5) (6) (7) (8) Rigid expenditure 0.003** -0.000 0.007*** 0.004*** 0.004** -0.002 0.005* 0.008** (% of GDP) (0.001) (0.001) (0.002) (0.001) (0.002) (0.004) (0.003) (0.004) Economic factors GDP growth (t-1) -1.953*** -1.329*** -1.294*** -1.318*** -1.329*** -1.286*** (0.346) (0.288) (0.286) (0.280) (0.288) (0.285) Inflation (t-1) -0.326 -0.384** -0.474*** -0.425*** -0.411** -0.364** (0.248) (0.158) (0.144) (0.160) (0.163) (0.154) U.S. Interest rate -0.021** -0.013* -0.011 -0.012 -0.013* -0.013* (0.010) (0.007) (0.007) (0.007) (0.007) (0.007) Political factors Gini 0.003** 0.003** 0.002** -0.001 0.003** 0.003*** (0.002) (0.001) (0.001) (0.003) (0.001) (0.001) Rule of law -0.026*** -0.019** -0.011 -0.019** -0.010 -0.019** (0.009) (0.008) (0.008) (0.008) (0.016) (0.008) Margin of Majority 0.189** 0.162*** 0.149*** 0.150*** 0.162*** 0.337*** (0.081) (0.055) (0.050) (0.056) (0.056) (0.130) Election's year 0.037*** 0.037*** 0.035*** 0.036*** 0.036*** 0.036*** (0.014) (0.012) (0.012) (0.012) (0.011) (0.012) Interactions EMEs 0.040 (0.075) EMEs * Rigidity 0.001 (0.002) Gini * Rigidity 0.000 (0.000) Rule of law * Rigidity -0.000 (0.001) Majority * Rigidity -0.008 (0.005) Observations 1,521 1,500 1,360 1,342 1,342 1,342 1,342 1,342 Country FE No No No No No No No No r2_p 0.0121 0.121 0.0738 0.182 0.194 0.187 0.183 0.187 Robust standard errors clustered by country in parentheses *** p<0.01, ** p<0.05, * p<0.1 - 53 - Table 25 Dependent variable: Need of fiscal adjustment based on debt/revenue Variables (1) (2) (3) (4) (5) (6) (7) (8) Rigid expenditure 0.003*** 0.002*** 0.003*** 0.001 0.006 0.005 -0.005 0.008 (% of GDP) (0.001) (0.001) (0.001) (0.001) (0.004) (0.006) (0.004) (0.005) Economic factors GDP growth (t-1) -1.568*** -1.939*** -1.862*** -1.923*** -1.890*** -1.918*** (0.352) (0.361) (0.370) (0.363) (0.369) (0.359) Inflation (t-1) -0.065 0.064 0.088 0.066 0.078 0.060 (0.107) (0.110) (0.108) (0.109) (0.106) (0.108) U.S. Interest rate -0.006 -0.005 -0.007 -0.006 -0.007 -0.005 (0.010) (0.011) (0.012) (0.012) (0.012) (0.011) Political factors Gini 0.002 0.002 0.002 0.004 0.002 0.002 (0.002) (0.002) (0.001) (0.003) (0.001) (0.001) Rule of law 0.008 0.016 0.018 0.015 -0.018 0.014 (0.010) (0.011) (0.013) (0.011) (0.024) (0.011) Margin of Majority -0.046 -0.039 -0.034 -0.033 -0.029 0.154 (0.081) (0.084) (0.089) (0.085) (0.087) (0.183) Election's year -0.011 -0.017 -0.014 -0.017 -0.015 -0.018 (0.015) (0.015) (0.015) (0.015) (0.015) (0.015) Interactions EMEs 0.189 (0.129) EMEs * Rigidity -0.007* (0.004) Gini * Rigidity -0.000 (0.000) Rule of law * Rigidity 0.001* (0.001) Majority * Rigidity -0.011 (0.008) Observations 3,046 2,911 2,066 2,007 2,007 2,007 2,007 2,007 Country FE No No No No No No No No r2_p 0.00427 0.0180 0.00586 0.0219 0.0248 0.0221 0.0232 0.0229 Robust standard errors clustered by country in parentheses *** p<0.01, ** p<0.05, * p<0.1 - 54 - Table 26 Dependent variable: Need of fiscal adjustment based on Escolano et al. (2014) Variables (1) (2) (3) (4) (5) (6) (7) (8) Rigid expenditure minus 0.010*** 0.004 0.017*** 0.010*** 0.014*** 0.003 0.010** 0.021*** structural as % GDP (0.003) (0.003) (0.003) (0.002) (0.003) (0.007) (0.005) (0.007) Economic factors GDP growth (t-1) -1.701*** -1.117*** -1.078*** -1.144*** -1.117*** -1.058*** (0.381) (0.272) (0.257) (0.272) (0.272) (0.274) Inflation (t-1) -0.296 -0.433*** -0.465*** -0.456*** -0.433** -0.399** (0.220) (0.165) (0.139) (0.169) (0.173) (0.159) U.S. Interest rate -0.021** -0.011 -0.010 -0.010 -0.011 -0.010 (0.010) (0.007) (0.007) (0.007) (0.007) (0.007) Political factors Gini 0.004** 0.003*** 0.002** 0.001 0.003*** 0.003*** (0.001) (0.001) (0.001) (0.002) (0.001) (0.001) Rule of law -0.024*** -0.020*** -0.008 -0.019*** -0.020 -0.019*** (0.009) (0.007) (0.008) (0.007) (0.013) (0.007) Margin of Majority 0.192** 0.163*** 0.136*** 0.158*** 0.163*** 0.310*** (0.084) (0.055) (0.045) (0.055) (0.055) (0.093) Election's year 0.034** 0.035*** 0.034*** 0.034*** 0.035*** 0.035*** (0.014) (0.012) (0.012) (0.012) (0.012) (0.012) Interactions EMEs 0.112* (0.063) EMEs * Deviation -0.004 (0.004) Gini * Deviation 0.000 (0.000) Rule of law * Deviation -0.000 (0.001) Majority * Deviation -0.017 (0.011) Observations 1,467 1,451 1,318 1,304 1,304 1,304 1,304 1,304 Country FE No No No No No No No No r2_p 0.0374 0.125 0.114 0.211 0.227 0.213 0.211 0.216 Robust standard errors clustered by country in parentheses *** p<0.01, ** p<0.05, * p<0.1 - 55 - Table 27 Dependent variable: Need of fiscal adjustment based on debt/revenue Variables (1) (2) (3) (4) (5) (6) (7) (8) Rigid expenditure minus 0.006*** 0.003 0.006* 0.001 0.014* 0.019 -0.018* 0.010 structural as % GDP (0.002) (0.002) (0.004) (0.004) (0.008) (0.015) (0.010) (0.013) Economic factors GDP growth (t-1) -1.670*** -2.131*** -1.948*** -2.084*** -2.042*** -2.120*** (0.382) (0.376) (0.388) (0.383) (0.390) (0.376) Inflation (t-1) -0.066 0.099 0.127 0.096 0.112 0.100 (0.108) (0.109) (0.107) (0.109) (0.105) (0.108) U.S. Interest rate -0.009 -0.011 -0.015 -0.013 -0.015 -0.011 (0.011) (0.012) (0.012) (0.013) (0.013) (0.012) Political factors Gini 0.002 0.002 0.002 0.005* 0.002 0.002 (0.001) (0.001) (0.001) (0.003) (0.001) (0.001) Rule of law 0.006 0.017 0.018 0.015 -0.022 0.016 (0.010) (0.012) (0.014) (0.012) (0.022) (0.012) Margin of Majority -0.089 -0.075 -0.067 -0.061 -0.064 0.022 (0.080) (0.084) (0.091) (0.084) (0.087) (0.170) Election's year -0.011 -0.010 -0.006 -0.010 -0.007 -0.011 (0.015) (0.015) (0.016) (0.015) (0.016) (0.015) Interactions EMEs 0.200* (0.106) EMEs * Deviation -0.022** (0.009) Gini * Deviation -0.000 (0.000) Rule of law * Deviation 0.005** (0.002) Majority * Deviation -0.015 (0.019) Observations 2,799 2,738 1,949 1,918 1,918 1,918 1,918 1,918 Country FE No No No No No No No No r2_p 0.00308 0.0185 0.00510 0.0252 0.0313 0.0264 0.0281 0.0256 Robust standard errors clustered by country in parentheses *** p<0.01, ** p<0.05, * p<0.1 - 56 - Table 28 Dependent variable: Fiscal adjustment when needed based on Escolano et al. (2014) Variables (1) (2) (3) (4) (5) (6) (7) (8) Rigid expenditure 0.005* 0.005* 0.006 0.003 0.011 0.047*** -0.034* 0.002 (% of GDP) (0.003) (0.003) (0.005) (0.006) (0.009) (0.018) (0.017) (0.024) Economic factors GDP growth (t-1) -0.454 -0.966 -0.575 -1.118 -1.086 -0.968 (1.115) (1.359) (1.278) (1.294) (1.261) (1.356) Inflation (t-1) -0.131 0.751 1.583 0.953 1.678* 0.744 (0.654) (0.890) (0.973) (0.837) (0.938) (0.896) U.S. Interest rate -0.034 -0.051 -0.070** -0.074** -0.088** -0.051 (0.028) (0.036) (0.034) (0.032) (0.040) (0.036) Political factors Gini 0.008** 0.008** 0.009*** 0.040*** 0.008** 0.008* (0.004) (0.004) (0.003) (0.011) (0.004) (0.004) Rule of law 0.063 0.113*** 0.088* 0.115*** -0.147 0.113*** (0.042) (0.041) (0.051) (0.036) (0.136) (0.043) Margin of Majority 0.061 0.075 0.157 0.136 0.075 0.033 (0.246) (0.348) (0.348) (0.335) (0.324) (1.040) Election's year -0.094* -0.102* -0.085 -0.089* -0.081 -0.102* (0.052) (0.055) (0.059) (0.053) (0.059) (0.055) Interactions EMEs 0.408 (0.335) EMEs * Rigidity -0.024 (0.015) Gini * Rigidity -0.001*** (0.000) Rule of law * Rigidity 0.009** (0.004) Majority * Rigidity 0.002 (0.042) Observations 185 183 165 163 163 163 163 163 Country FE No No No No No No No No r2_p 0.0183 0.0338 0.0718 0.110 0.156 0.146 0.149 0.110 Robust standard errors clustered by country in parentheses *** p<0.01, ** p<0.05, * p<0.1 - 57 - Table 29 Dependent variable: Fiscal adjustment when needed based on debt/revenue Variables (1) (2) (3) (4) (5) (6) (7) (8) Rigid expenditure 0.006*** 0.006*** 0.006*** 0.005*** 0.007** 0.010 -0.006 0.008 (% of GDP) (0.001) (0.001) (0.002) (0.002) (0.003) (0.008) (0.006) (0.007) Economic factors GDP growth (t-1) 0.017 -0.210 -0.190 -0.201 -0.215 -0.203 (0.266) (0.480) (0.481) (0.479) (0.480) (0.480) Inflation (t-1) -0.170 -0.405 -0.332 -0.402 -0.357 -0.404 (0.239) (0.273) (0.259) (0.272) (0.257) (0.271) U.S. Interest rate -0.017* -0.028** -0.030** -0.030** -0.034** -0.028** (0.010) (0.013) (0.013) (0.013) (0.013) (0.012) Political factors Gini 0.002 0.002 0.002 0.005 0.002 0.002 (0.002) (0.002) (0.002) (0.005) (0.002) (0.002) Rule of law 0.023 0.027 0.020 0.026 -0.033 0.027 (0.019) (0.020) (0.022) (0.021) (0.037) (0.020) Margin of Majority -0.191 -0.189 -0.183 -0.184 -0.177 -0.119 (0.130) (0.126) (0.125) (0.123) (0.122) (0.245) Election's year -0.037 -0.042 -0.040 -0.042 -0.039 -0.042 (0.029) (0.029) (0.030) (0.029) (0.030) (0.030) Interactions EMEs 0.067 (0.142) EMEs * Rigidity -0.005 (0.005) Gini * Rigidity -0.000 (0.000) Rule of law * Rigidity 0.002* (0.001) Majority * Rigidity -0.004 (0.010) Observations 1,121 1,081 771 755 755 755 755 755 Country FE No No No No No No No No r2_p 0.0296 0.0353 0.0533 0.0676 0.0705 0.0681 0.0726 0.0678 Robust standard errors clustered by country in parentheses *** p<0.01, ** p<0.05, * p<0.1 - 58 - Table 30 Dependent variable: Fiscal adjustment when needed based on Escolano et al. (2014) Variables (1) (2) (3) (4) (5) (6) (7) (8) Rigid expenditure minus 0.006 0.006 -0.004 -0.009 -0.002 0.069** -0.063* -0.001 structural as % GDP (0.006) (0.006) (0.010) (0.010) (0.014) (0.030) (0.034) (0.055) Economic factors GDP growth (t-1) -0.630 -1.331 -0.747 -1.437 -1.456 -1.335 (1.036) (1.348) (1.248) (1.256) (1.334) (1.345) Inflation (t-1) 0.155 1.345 1.755 1.320 1.661 1.380 (0.752) (1.057) (1.103) (1.151) (1.156) (1.054) U.S. Interest rate -0.035 -0.051 -0.062* -0.068** -0.070* -0.051 (0.030) (0.038) (0.036) (0.033) (0.039) (0.037) Political factors Gini 0.005 0.006 0.007** 0.027*** 0.005 0.006 (0.004) (0.004) (0.003) (0.007) (0.004) (0.004) Rule of law 0.096** 0.145*** 0.094* 0.149*** 0.022 0.147*** (0.048) (0.039) (0.055) (0.037) (0.106) (0.040) Margin of Majority -0.067 -0.023 0.116 0.045 -0.054 0.122 (0.225) (0.327) (0.359) (0.321) (0.318) (0.847) Election's year -0.099* -0.112** -0.095 -0.094* -0.101* -0.112** (0.054) (0.054) (0.059) (0.052) (0.055) (0.054) Interactions EMEs 0.090 (0.275) EMEs * Deviation -0.036 (0.023) Gini * Deviation -0.002*** (0.001) Rule of law * Deviation 0.012 (0.008) Majority * Deviation -0.015 (0.096) Observations 182 180 164 162 162 162 162 162 Country FE No No No No No No No No r2_p 0.00706 0.0236 0.0630 0.115 0.169 0.155 0.138 0.116 Robust standard errors clustered by country in parentheses *** p<0.01, ** p<0.05, * p<0.1 - 59 - Table 31 Dependent variable: Fiscal adjustment when needed based on debt/revenue Variables (1) (2) (3) (4) (5) (6) (7) (8) Rigid expenditure minus 0.011*** 0.010*** 0.007 0.004 0.004 0.005 -0.014 0.010 structural as % GDP (0.003) (0.003) (0.004) (0.005) (0.008) (0.020) (0.014) (0.018) Economic factors GDP growth (t-1) -0.070 -0.370 -0.324 -0.371 -0.387 -0.360 (0.287) (0.509) (0.512) (0.509) (0.511) (0.509) Inflation (t-1) -0.188 -0.376 -0.318 -0.377 -0.358 -0.372 (0.238) (0.257) (0.245) (0.258) (0.250) (0.258) U.S. Interest rate -0.019* -0.033** -0.034** -0.033** -0.037*** -0.033*** (0.011) (0.013) (0.014) (0.013) (0.013) (0.013) Political factors Gini 0.001 0.001 0.002 0.002 0.002 0.001 (0.002) (0.002) (0.002) (0.005) (0.002) (0.002) Rule of law 0.041** 0.045** 0.031 0.045** 0.013 0.045** (0.019) (0.021) (0.024) (0.021) (0.035) (0.021) Margin of Majority -0.259* -0.260** -0.254* -0.260** -0.257** -0.190 (0.134) (0.129) (0.132) (0.128) (0.127) (0.243) Election's year -0.040 -0.047 -0.047 -0.047 -0.046 -0.048 (0.030) (0.030) (0.031) (0.030) (0.031) (0.031) Interactions EMEs -0.024 (0.145) EMEs * Deviation -0.006 (0.011) Gini * Deviation -0.000 (0.001) Rule of law * Deviation 0.004 (0.003) Majority * Deviation -0.010 (0.028) Observations 1,015 1,003 713 709 709 709 709 709 Country FE No No No No No No No No r2_p 0.0166 0.0246 0.0394 0.0581 0.0614 0.0581 0.0606 0.0583 Robust standard errors clustered by country in parentheses *** p<0.01, ** p<0.05, * p<0.1 - 60 - Appendix 5: Conditional logit models: Table 32 Dependent variable: Need of fiscal adjustment based on Escolano et al. (2014) Variables (1) (2) (3) (4) (5) (6) (7) (8) Rigid expenditure 0.361*** 0.400*** 0.386*** 0.398*** 0.589*** 0.672*** 0.125 0.336*** (% of GDP) (0.036) (0.044) (0.040) (0.046) (0.093) (0.139) (0.091) (0.076) Economic factors GDP growth (t-1) -26.752*** -26.493***-24.799***-26.180***-25.308***-26.841*** (3.563) (3.836) (3.859) (3.923) (3.824) (3.850) Inflation (t-1) -12.167*** -11.215*** -9.861***-11.526*** -9.756***-10.992*** (3.716) (3.829) (3.658) (3.843) (3.513) (3.810) U.S. Interest rate -0.064 -0.076 -0.159 -0.153 -0.155 -0.090 (0.087) (0.101) (0.110) (0.109) (0.108) (0.101) Political factors Gini 0.098*** 0.077** 0.068* 0.238*** 0.072* 0.073* (0.035) (0.038) (0.037) (0.085) (0.038) (0.038) Rule of law 0.326 0.169 0.095 0.168 -1.825*** 0.195 (0.269) (0.339) (0.341) (0.343) (0.697) (0.340) Margin of Majority 1.539 1.919* 1.914* 2.125* 1.895* -0.810 (1.076) (1.155) (1.148) (1.174) (1.135) (2.936) Election's year 0.239 0.441* 0.452* 0.427* 0.462* 0.441* (0.214) (0.237) (0.237) (0.236) (0.237) (0.236) Interactions EMEs * Rigidity -0.304*** (0.112) Gini * Rigidity -0.007** (0.003) Rule of law * Rigidity 0.073*** (0.022) Majority * Rigidity 0.109 (0.108) Observations 1,080 1,065 960 948 948 948 948 948 Number of ifscode 60 60 53 53 53 53 53 53 Country FE Yes Yes Yes Yes Yes Yes Yes Yes r2_p 0.203 0.344 0.233 0.352 0.366 0.360 0.370 0.354 Standard errors in parentheses *** p<0.01, ** p<0.05, * p<0.1 - 61 - Table 33 Dependent variable: Need of fiscal adjustment based on debt/revenue Variables (1) (2) (3) (4) (5) (6) (7) (8) Rigid expenditure 0.104*** 0.107*** 0.117*** 0.107*** 0.269*** 0.086* 0.012 0.139*** (% of GDP) (0.012) (0.014) (0.016) (0.017) (0.036) (0.044) (0.034) (0.029) Economic factors GDP growth (t-1) -6.476*** -7.620*** -6.558*** -7.644*** -7.398*** -7.518*** (1.116) (1.485) (1.475) (1.487) (1.483) (1.483) Inflation (t-1) 0.060 1.077* 1.061* 1.091* 0.968 1.098* (0.397) (0.630) (0.615) (0.631) (0.619) (0.628) U.S. Interest rate 0.027 0.005 -0.013 0.006 -0.010 0.003 (0.029) (0.038) (0.039) (0.038) (0.038) (0.038) Political factors Gini 0.031** 0.028** 0.026** 0.019 0.030** 0.028** (0.012) (0.012) (0.012) (0.021) (0.012) (0.012) Rule of law 0.115 0.152 0.093 0.157 -0.432** 0.148 (0.104) (0.118) (0.119) (0.119) (0.217) (0.119) Margin of Majority -0.441 -0.360 -0.355 -0.354 -0.335 0.543 (0.392) (0.404) (0.400) (0.404) (0.403) (0.775) Election's year -0.043 -0.058 -0.050 -0.058 -0.055 -0.062 (0.103) (0.106) (0.107) (0.106) (0.106) (0.106) Interactions EMEs * Rigidity -0.228*** (0.041) Gini * Rigidity 0.001 (0.001) Rule of law * Rigidity 0.024*** (0.008) Majority * Rigidity -0.053 (0.039) Observations 3,046 2,911 2,066 2,007 2,007 2,007 2,007 2,007 Number of ifscode 147 145 103 102 102 102 102 102 Country FE Yes Yes Yes Yes Yes Yes Yes Yes r2_p 0.0235 0.0373 0.0276 0.0432 0.0581 0.0433 0.0478 0.0440 Standard errors in parentheses *** p<0.01, ** p<0.05, * p<0.1 - 62 - Table 34 Dependent variable: Need of fiscal adjustment based on Escolano et al. (2014) Variables (1) (2) (3) (4) (5) (6) (7) (8) Rigid expenditure minus 0.341*** 0.367*** 0.369*** 0.375*** 0.606*** 0.787*** -0.042 0.403*** structural as % GDP (0.037) (0.045) (0.041) (0.047) (0.094) (0.186) (0.124) (0.140) Economic factors GDP growth (t-1) -26.612*** -25.740***-24.202***-25.364***-24.277***-25.700*** (3.497) (3.720) (3.774) (3.834) (3.759) (3.727) Inflation (t-1) -12.074*** -10.558*** -9.418** -10.984*** -9.698** -10.616*** (3.597) (3.754) (3.732) (3.769) (3.837) (3.770) U.S. Interest rate -0.146* -0.199** -0.305*** -0.271** -0.298*** -0.197** (0.084) (0.100) (0.108) (0.105) (0.106) (0.100) Political factors Gini 0.108*** 0.094*** 0.077** 0.173*** 0.083** 0.095*** (0.033) (0.036) (0.036) (0.050) (0.036) (0.037) Rule of law 0.144 0.196 0.128 0.198 -0.875* 0.192 (0.259) (0.332) (0.336) (0.334) (0.453) (0.332) Margin of Majority 1.266 1.561 1.705 1.702 1.720 2.033 (1.043) (1.118) (1.118) (1.135) (1.112) (2.476) Election's year 0.229 0.406* 0.446* 0.431* 0.435* 0.408* (0.211) (0.231) (0.233) (0.232) (0.233) (0.231) Interactions EMEs * Deviation -0.383*** (0.114) Gini * Deviation -0.010** (0.004) Rule of law * Deviation 0.107*** (0.031) Majority * Deviation -0.047 (0.220) Observations 1,065 1,053 957 947 947 947 947 947 Number of ifscode 60 60 53 53 53 53 53 53 Country FE Yes Yes Yes Yes Yes Yes Yes Yes r2_p 0.161 0.307 0.193 0.320 0.341 0.329 0.342 0.320 Standard errors in parentheses *** p<0.01, ** p<0.05, * p<0.1 - 63 - Table 35 Dependent variable: Need of fiscal adjustment based on debt/revenue Variables (1) (2) (3) (4) (5) (6) (7) (8) Rigid expenditure minus 0.051*** 0.037** 0.058*** 0.042** 0.173*** 0.132* -0.121** 0.070 structural as % GDP (0.014) (0.015) (0.018) (0.019) (0.034) (0.069) (0.054) (0.050) Economic factors GDP growth (t-1) -7.299*** -9.008*** -8.035*** -8.914*** -8.732*** -8.978*** (1.166) (1.526) (1.523) (1.529) (1.527) (1.526) Inflation (t-1) 0.044 1.358** 1.234* 1.289** 1.191* 1.370** (0.400) (0.644) (0.631) (0.644) (0.633) (0.644) U.S. Interest rate -0.032 -0.067* -0.088** -0.073* -0.086** -0.067* (0.030) (0.039) (0.039) (0.039) (0.039) (0.039) Political factors Gini 0.029** 0.029** 0.027** 0.042*** 0.030** 0.029** (0.012) (0.013) (0.013) (0.016) (0.013) (0.013) Rule of law 0.062 0.178 0.153 0.163 -0.161 0.180 (0.108) (0.121) (0.122) (0.122) (0.160) (0.121) Margin of Majority -0.714* -0.633 -0.572 -0.660 -0.597 -0.337 (0.406) (0.419) (0.418) (0.419) (0.419) (0.639) Election's year -0.043 -0.036 -0.026 -0.032 -0.029 -0.038 (0.105) (0.107) (0.108) (0.107) (0.107) (0.107) Interactions EMEs * Deviation -0.210*** (0.043) Gini * Deviation -0.002 (0.002) Rule of law * Deviation 0.040*** (0.012) Majority * Deviation -0.048 (0.078) Observations 2,798 2,738 1,949 1,918 1,918 1,918 1,918 1,918 Number of ifscode 137 137 98 98 98 98 98 98 Country FE Yes Yes Yes Yes Yes Yes Yes Yes r2_p 0.00444 0.0209 0.00939 0.0338 0.0460 0.0347 0.0389 0.0340 Standard errors in parentheses *** p<0.01, ** p<0.05, * p<0.1 - 64 - Table 36 Dependent variable: Fiscal adjustment when needed based on Escolano et al. (2014) Variables (1) (2) (3) (4) (5) (6) (7) (8) Rigid expenditure -0.085 -0.117 -0.082 -0.161 -0.127 0.710 -0.551 -0.481** (% of GDP) (0.097) (0.133) (0.112) (0.162) (0.255) (0.493) (0.389) (0.237) Economic factors GDP growth (t-1) -1.308 1.757 2.106 3.416 2.141 1.373 (7.427) (8.017) (8.324) (8.739) (8.525) (8.293) Inflation (t-1) 20.772* 25.758** 25.280** 27.675** 20.914 28.117** (10.786) (12.509) (12.744) (13.258) (12.981) (13.476) U.S. Interest rate -0.768** -1.130*** -1.134*** -1.322*** -1.292*** -1.374*** (0.307) (0.421) (0.422) (0.451) (0.458) (0.483) Political factors Gini 0.070 0.089 0.094 0.626* 0.089 -0.026 (0.127) (0.278) (0.278) (0.341) (0.270) (0.184) Rule of law -1.195 1.231 1.223 1.426 -1.258 1.753 (0.735) (1.120) (1.115) (1.154) (2.405) (1.259) Margin of Majority 4.471 3.348 3.417 5.389 4.741 -13.440 (3.234) (3.620) (3.655) (4.026) (3.992) (9.192) Election's year -0.697 -0.480 -0.459 -0.316 -0.325 -0.428 (0.512) (0.550) (0.563) (0.576) (0.570) (0.581) Interactions EMEs * Rigidity -0.058 (0.346) Gini * Rigidity -0.021* (0.013) Rule of law * Rigidity 0.090 (0.077) Majority * Rigidity 0.592* (0.317) Observations 111 110 98 97 97 97 97 97 Number of ifscode 21 21 18 18 18 18 18 18 Country FE Yes Yes Yes Yes Yes Yes Yes Yes r2_p 0.0103 0.160 0.102 0.238 0.239 0.272 0.255 0.278 Standard errors in parentheses *** p<0.01, ** p<0.05, * p<0.1 - 65 - Table 37 Dependent variable: Fiscal adjustment when needed based on debt/revenue Variables (1) (2) (3) (4) (5) (6) (7) (8) Rigid expenditure -0.026 -0.042 -0.053 -0.066 -0.059 -0.030 -0.200** -0.125* (% of GDP) (0.030) (0.033) (0.038) (0.041) (0.059) (0.091) (0.095) (0.067) Economic factors GDP growth (t-1) -3.374 -1.430 -1.380 -1.383 -1.189 -1.478 (2.492) (3.026) (3.041) (3.027) (3.032) (3.033) Inflation (t-1) -0.095 0.277 0.267 0.278 0.144 0.220 (0.849) (1.592) (1.596) (1.594) (1.613) (1.601) U.S. Interest rate -0.130** -0.159** -0.162** -0.166** -0.197** -0.158** (0.060) (0.074) (0.075) (0.075) (0.078) (0.074) Political factors Gini 0.024 0.024 0.024 0.042 0.027 0.027 (0.027) (0.027) (0.027) (0.049) (0.027) (0.027) Rule of law -0.273 -0.092 -0.095 -0.101 -0.911 -0.087 (0.246) (0.270) (0.271) (0.272) (0.591) (0.271) Margin of Majority 1.786* 1.995* 1.999* 1.977* 2.157** -0.049 (1.036) (1.073) (1.074) (1.076) (1.090) (2.107) Election's year -0.234 -0.270 -0.270 -0.271 -0.264 -0.268 (0.209) (0.211) (0.211) (0.211) (0.211) (0.212) Interactions EMEs * Rigidity -0.015 (0.081) Gini * Rigidity -0.001 (0.002) Rule of law * Rigidity 0.029 (0.019) Majority * Rigidity 0.099 (0.089) Observations 798 790 583 579 579 579 579 579 Number of ifscode 102 102 75 75 75 75 75 75 Country FE Yes Yes Yes Yes Yes Yes Yes Yes r2_p 0.00118 0.0127 0.0178 0.0297 0.0297 0.0301 0.0348 0.0322 Standard errors in parentheses *** p<0.01, ** p<0.05, * p<0.1 - 66 - Table 38 Dependent variable: Fiscal adjustment when needed based on Escolano et al. (2014) Variables (1) (2) (3) (4) (5) (6) (7) (8) Rigid expenditure minus -0.279** -0.264* -0.300* -0.324* -0.172 1.029 -1.088* -0.707 structural as % GDP (0.139) (0.154) (0.161) (0.177) (0.282) (0.692) (0.568) (0.497) Economic factors GDP growth (t-1) -0.957 -0.168 1.374 3.592 1.757 0.078 (8.219) (8.383) (9.042) (9.841) (9.446) (8.447) Inflation (t-1) 19.399* 25.158** 24.763* 29.131** 20.231 25.211** (11.390) (12.745) (12.844) (14.276) (13.535) (12.840) U.S. Interest rate -0.940*** -1.090*** -1.125*** -1.220*** -1.327*** -1.183*** (0.351) (0.423) (0.433) (0.450) (0.478) (0.449) Political factors Gini 0.021 0.010 0.028 0.412 0.010 -0.007 (0.125) (0.250) (0.294) (0.338) (0.325) (0.219) Rule of law -1.132 1.229 1.216 1.359 -0.528 1.509 (0.741) (1.109) (1.115) (1.171) (1.660) (1.184) Margin of Majority 3.731 3.076 3.489 6.204 5.454 -3.350 (3.460) (3.909) (4.070) (4.703) (4.608) (8.392) Election's year -0.675 -0.414 -0.336 -0.282 -0.253 -0.391 (0.526) (0.562) (0.572) (0.591) (0.578) (0.569) Interactions EMEs * Deviation -0.240 (0.376) Gini * Deviation -0.032* (0.018) Rule of law * Deviation 0.176 (0.112) Majority * Deviation 0.606 (0.723) Observations 106 105 98 97 97 97 97 97 Number of ifscode 20 20 18 18 18 18 18 18 Country FE Yes Yes Yes Yes Yes Yes Yes Yes r2_p 0.0598 0.224 0.149 0.272 0.277 0.315 0.300 0.280 Standard errors in parentheses *** p<0.01, ** p<0.05, * p<0.1 - 67 - Table 39 Dependent variable: Fiscal adjustment when needed based on debt/revenue Variables (1) (2) (3) (4) (5) (6) (7) (8) Rigid expenditure minus -0.055 -0.077** -0.098** -0.122** -0.108* -0.028 -0.238 -0.210* structural as % GDP (0.033) (0.038) (0.044) (0.050) (0.063) (0.161) (0.166) (0.128) Economic factors GDP growth (t-1) -3.049 -1.913 -1.893 -1.943 -1.975 -1.971 (2.533) (3.101) (3.105) (3.103) (3.101) (3.102) Inflation (t-1) -0.123 -0.164 -0.245 -0.220 -0.374 -0.203 (0.857) (1.647) (1.670) (1.653) (1.685) (1.652) U.S. Interest rate -0.152** -0.189** -0.194** -0.200** -0.207** -0.188** (0.063) (0.079) (0.080) (0.081) (0.083) (0.079) Political factors Gini 0.027 0.026 0.025 0.042 0.027 0.028 (0.027) (0.028) (0.028) (0.038) (0.028) (0.028) Rule of law -0.349 -0.154 -0.152 -0.164 -0.386 -0.172 (0.261) (0.282) (0.283) (0.284) (0.427) (0.284) Margin of Majority 2.404** 2.732** 2.749** 2.720** 2.785** 1.576 (1.101) (1.156) (1.159) (1.161) (1.166) (1.913) Election's year -0.238 -0.273 -0.274 -0.278 -0.270 -0.271 (0.214) (0.217) (0.217) (0.217) (0.217) (0.217) Interactions EMEs * Deviation -0.034 (0.096) Gini * Deviation -0.003 (0.004) Rule of law * Deviation 0.025 (0.035) Majority * Deviation 0.149 (0.199) Observations 758 750 554 550 550 550 550 550 Number of ifscode 100 100 74 74 74 74 74 74 Country FE Yes Yes Yes Yes Yes Yes Yes Yes r2_p 0.00456 0.0181 0.0303 0.0478 0.0481 0.0486 0.0490 0.0491 Standard errors in parentheses *** p<0.01, ** p<0.05, * p<0.1 - 68 - Appendix 6: Model with sample selection correction Table 40 Dependent variable: Fiscal adjustment when needed based on Escolano et al. (2014) Variables (1) (2) (3) (4) (5) Rigid expenditure 0.020** 0.027** 0.035* -0.010 0.038 (% of GDP) (0.009) (0.013) (0.018) (0.017) (0.023) Economic factors GDP growth (t-1) -7.068** -5.267* -6.461** -5.847* -6.908** (3.007) (3.067) (3.015) (3.022) (2.977) Inflation (t-1) -1.174 -0.506 -0.937 -0.046 -1.107 (0.988) (1.223) (1.054) (1.123) (0.973) U.S. Interest rate -0.107*** -0.107*** -0.116*** -0.121*** -0.104*** (0.036) (0.034) (0.034) (0.036) (0.036) Political factors Gini 0.020*** 0.016** 0.031** 0.017** 0.021*** (0.007) (0.006) (0.012) (0.007) (0.008) Rule of law 0.001 0.030 0.013 -0.171* 0.002 (0.057) (0.051) (0.056) (0.094) (0.057) Margin of Majority 0.852** 0.622 0.795** 0.689* 1.514* (0.387) (0.382) (0.368) (0.389) (0.890) Interactions EMEs 0.619 (0.441) EMEs * Rigidity -0.018 (0.012) Gini * Rigidity -0.000 (0.001) Rule of law * Rigidity 0.007** (0.003) Majority * Rigidity -0.029 (0.027) lambda 0.668** 0.477 0.591* 0.521* 0.659** (0.307) (0.309) (0.308) (0.310) (0.308) Constant -2.163** -2.081** -2.427*** -1.053 -2.635** (0.839) (1.001) (0.693) (0.999) (1.173) Observations 163 163 163 163 163 R-squared 0.120 0.153 0.149 0.152 0.120 Country FE No No No No No Standard errors in parentheses *** p<0.01, ** p<0.05, * p<0.1 - 69 - Table 41 Dependent variable: Fiscal adjustment when needed based on debt/revenue Variables (1) (2) (3) (4) (5) Rigid expenditure 0.003 -0.008 0.001 0.005 -0.008 (% of GDP) (0.003) (0.011) (0.010) (0.010) (0.014) Economic factors GDP growth (t-1) 3.803 4.782 3.811 4.094 3.957 (2.999) (3.212) (2.997) (3.187) (2.911) Inflation (t-1) -0.332** -0.385* -0.335** -0.349* -0.333** (0.168) (0.200) (0.170) (0.188) (0.165) U.S. Interest rate -0.018 -0.011 -0.018 -0.018 -0.018 (0.012) (0.016) (0.013) (0.016) (0.012) Political factors Gini -0.003 -0.005 -0.004 -0.004 -0.004 (0.004) (0.005) (0.008) (0.005) (0.004) Rule of law -0.008 -0.032 -0.008 0.005 -0.006 (0.030) (0.036) (0.029) (0.044) (0.026) Margin of Majority -0.059 -0.045 -0.067 -0.062 -0.357 (0.110) (0.108) (0.105) (0.104) (0.312) Interactions emes -0.461 (0.379) EMEs * Rigidity 0.014 (0.014) Gini * Rigidity 0.000 (0.000) Rule of law * Rigidity -0.001 (0.003) Majority * Rigidity 0.016 (0.019) lambda -1.202 -1.540 -1.207 -1.312 -1.257 (0.892) (0.992) (0.899) (0.973) (0.874) Constant 1.559 2.378 1.601 1.658* 1.834 (1.042) (1.452) (1.172) (0.938) (1.235) Observations 755 755 755 755 755 R-squared 0.074 0.081 0.075 0.082 0.075 Country FE No No No No No Standard errors in parentheses *** p<0.01, ** p<0.05, * p<0.1 - 70 - Table 42 Dependent variable: Fiscal adjustment when needed based on Escolano et al. (2014) Variables (1) (2) (3) (4) (5) Rigid expenditure minus 0.026 0.014 0.073** -0.021 0.047 structural as % GDP (0.022) (0.024) (0.030) (0.034) (0.046) Economic factors GDP growth (t-1) -4.827** -2.283 -4.534* -3.709 -4.139* (2.415) (2.214) (2.499) (2.454) (2.249) Inflation (t-1) -0.216 0.866 -0.002 0.757 0.056 (1.044) (1.150) (1.087) (1.164) (0.991) U.S. Interest rate -0.083*** -0.075** -0.095*** -0.088*** -0.076** (0.032) (0.029) (0.031) (0.032) (0.031) Political factors Gini 0.015** 0.009 0.028*** 0.012 0.014** (0.007) (0.006) (0.008) (0.007) (0.007) Rule of law 0.055 0.063 0.060 -0.021 0.067 (0.051) (0.044) (0.051) (0.069) (0.049) Margin of Majority 0.577 0.302 0.563 0.408 0.864 (0.362) (0.320) (0.358) (0.369) (0.699) Interactions EMEs 0.126 (0.305) EMEs * Deviation -0.027 (0.019) Gini * Deviation -0.001 (0.001) Rule of law * Deviation 0.009* (0.005) Majority * Deviation -0.043 (0.054) lambda 0.453* 0.170 0.402 0.303 0.377 (0.271) (0.240) (0.279) (0.279) (0.254) Constant -1.556* -0.677 -1.900*** -0.725 -1.612 (0.802) (0.836) (0.717) (0.910) (0.975) Observations 162 162 162 162 162 R-squared 0.113 0.150 0.149 0.128 0.110 Country FE No No No No No Standard errors in parentheses *** p<0.01, ** p<0.05, * p<0.1 - 71 - Table 43 Dependent variable: Fiscal adjustment when needed based on debt/revenue Variables (1) (2) (3) (4) (5) Rigid expenditure minus 0.001 -0.045 -0.046 0.039 -0.013 structural as % GDP (0.005) (0.029) (0.043) (0.039) (0.025) Economic factors GDP growth (t-1) 4.911 6.502* 4.915 5.473 5.097 (3.956) (3.774) (3.983) (4.096) (3.905) Inflation (t-1) -0.416* -0.567** -0.414* -0.472* -0.428* (0.222) (0.270) (0.222) (0.256) (0.225) U.S. Interest rate -0.004 0.021 0.001 0.007 -0.003 (0.023) (0.032) (0.027) (0.032) (0.023) Political factors Gini -0.004 -0.006 -0.013 -0.006 -0.004 (0.004) (0.005) (0.012) (0.005) (0.004) Rule of law -0.002 -0.042 0.003 0.071 -0.002 (0.036) (0.042) (0.033) (0.052) (0.035) Margin of Majority -0.013 0.043 -0.042 -0.009 -0.161 (0.173) (0.165) (0.156) (0.166) (0.178) Interactions EMEs -0.794* (0.440) EMEs * Deviation 0.073 (0.045) Gini * Deviation 0.001 (0.001) Rule of law * Deviation -0.010 (0.010) Majority * Deviation 0.022 (0.036) lambda -1.435 -2.013* -1.467 -1.647 -1.489 (1.077) (1.115) (1.108) (1.162) (1.068) Constant 1.758 3.036** 2.134 1.734* 1.923 (1.116) (1.492) (1.422) (0.942) (1.240) Observations 709 709 709 709 709 R-squared 0.063 0.070 0.063 0.067 0.064 Country FE No No No No No Standard errors in parentheses *** p<0.01, ** p<0.05, * p<0.1 - 72 - Appendix 7: Linear probability model controlling for size of the need (primary gap) Table 44 Dependent variable: Fiscal adjustment when needed based on Escolano et al. (2014) Variables (1) (2) (3) (4) (5) (6) (7) (8) Rigid expenditure -0.015 -0.023*** -0.014 -0.027*** -0.016** 0.073** -0.080*** -0.063*** (% of GDP) (0.013) (0.008) (0.011) (0.008) (0.008) (0.029) (0.028) (0.020) Primary gap (t-1) -0.004 0.003 0.001 -0.003 -0.004 -0.004 -0.003 -0.004 (0.010) (0.006) (0.010) (0.008) (0.008) (0.007) (0.008) (0.008) Economic factors GDP growth (t-1) -0.307 0.736 0.848 0.731 0.611 0.725 (1.360) (1.246) (1.224) (1.252) (1.227) (1.279) Inflation (t-1) 2.579*** 2.706** 3.066*** 2.976*** 3.203*** 2.552** (0.931) (1.042) (1.057) (1.032) (0.965) (1.113) U.S. Interest rate -0.124** -0.159** -0.178** -0.206*** -0.194** -0.174*** (0.051) (0.064) (0.074) (0.060) (0.073) (0.052) Political factors Gini 0.010 0.013 0.016 0.081*** 0.015 0.007 (0.011) (0.012) (0.012) (0.023) (0.012) (0.011) Rule of law -0.218** 0.110 0.167 0.183 -0.106 0.113 (0.086) (0.142) (0.162) (0.144) (0.139) (0.143) Margin of Majority 0.509 0.269 0.259 0.474 0.258 -1.475* (0.443) (0.397) (0.387) (0.366) (0.384) (0.794) Election's year -0.111 -0.097 -0.089 -0.078 -0.087 -0.083 (0.080) (0.078) (0.075) (0.075) (0.079) (0.081) Interactions EMEs * Rigidity -0.034 (0.030) Gini * Rigidity -0.003*** (0.001) Rule of law * Rigidity 0.011** (0.005) Majority * Rigidity 0.073* (0.042) Constant 0.611 1.191*** 0.791 0.314 0.164 -2.660** 1.288 1.447 (0.395) (0.305) (0.971) (1.004) (0.962) (1.293) (1.016) (0.983) Observations 185 183 165 163 163 163 163 163 R-squared 0.009 0.115 0.073 0.160 0.169 0.192 0.178 0.189 Number of ifscode 60 60 53 53 53 53 53 53 Country FE Yes Yes Yes Yes Yes Yes Yes Yes Robust standard errors clustered by country in parentheses *** p<0.01, ** p<0.05, * p<0.1 - 73 - Table 45 Dependent variable: Fiscal adjustment when needed based on debt/revenue Variables (1) (2) (3) (4) (5) (6) (7) (8) Rigid expenditure -0.011 -0.009 -0.010 -0.008 -0.009 -0.012 -0.018 -0.021 (% of GDP) (0.007) (0.008) (0.008) (0.008) (0.012) (0.022) (0.018) (0.014) Primary gap (t-1) 0.001 0.006 0.001 0.004 0.004 0.004 0.004 0.005 (0.003) (0.005) (0.003) (0.005) (0.005) (0.005) (0.005) (0.005) Economic factors GDP growth (t-1) -0.669 -0.271 -0.284 -0.276 -0.233 -0.301 (0.835) (0.872) (0.879) (0.874) (0.892) (0.868) Inflation (t-1) -0.038 0.031 0.026 0.031 0.046 -0.013 (0.206) (0.201) (0.205) (0.201) (0.208) (0.200) U.S. Interest rate -0.028* -0.026 -0.026 -0.025 -0.030 -0.027 (0.017) (0.019) (0.021) (0.020) (0.022) (0.020) Political factors Gini 0.006 0.006 0.006 0.004 0.006 0.006 (0.007) (0.007) (0.007) (0.014) (0.007) (0.007) Rule of law -0.027 0.001 0.001 0.000 -0.062 0.003 (0.061) (0.071) (0.071) (0.070) (0.108) (0.071) Margin of Majority 0.456* 0.442* 0.440* 0.438* 0.442* -0.086 (0.234) (0.231) (0.231) (0.234) (0.232) (0.379) Election's year -0.031 -0.030 -0.030 -0.030 -0.030 -0.027 (0.041) (0.042) (0.042) (0.042) (0.042) (0.041) Interactions EMEs * Rigidity 0.002 (0.016) Gini * Rigidity 0.000 (0.000) Rule of law * Rigidity 0.002 (0.004) Majority * Rigidity 0.023 (0.019) Constant 0.613*** 0.689*** 0.226 0.178 0.183 0.287 0.451 0.476 (0.184) (0.231) (0.511) (0.525) (0.528) (0.715) (0.568) (0.545) Observations 562 559 504 503 503 503 503 503 R-squared 0.005 0.013 0.014 0.021 0.021 0.021 0.021 0.024 Number of ifscode 84 84 75 75 75 75 75 75 Country FE Yes Yes Yes Yes Yes Yes Yes Yes Robust standard errors clustered by country in parentheses *** p<0.01, ** p<0.05, * p<0.1 - 74 - Table 46 Dependent variable: Fiscal adjustment when needed based on Escolano et al. (2014) Variables (1) (2) (3) (4) (5) (6) (7) (8) Rigid expenditure minus -0.034*** -0.030*** -0.033*** -0.035*** -0.023*** 0.083** -0.098*** -0.067 structural as % GDP (0.011) (0.008) (0.009) (0.010) (0.006) (0.035) (0.032) (0.051) Primary gap (t-1) -0.005 0.002 -0.001 -0.003 -0.004 -0.004 -0.003 -0.003 (0.009) (0.006) (0.009) (0.007) (0.007) (0.007) (0.007) (0.008) Economic factors GDP growth (t-1) -0.095 0.369 0.532 0.419 0.424 0.377 (1.325) (1.323) (1.327) (1.336) (1.318) (1.341) Inflation (t-1) 2.832*** 3.213*** 3.493*** 3.486*** 3.531*** 3.166*** (0.873) (1.120) (1.109) (1.091) (1.090) (1.154) U.S. Interest rate -0.136** -0.148** -0.160** -0.164*** -0.170** -0.155** (0.051) (0.065) (0.067) (0.061) (0.069) (0.059) Political factors Gini 0.006 0.006 0.006 0.030** 0.006 0.005 (0.011) (0.013) (0.013) (0.014) (0.014) (0.012) Rule of law -0.203** 0.119 0.162 0.168 0.064 0.128 (0.084) (0.150) (0.151) (0.146) (0.142) (0.151) Margin of Majority 0.393 0.170 0.126 0.248 0.131 -0.331 (0.419) (0.387) (0.383) (0.367) (0.379) (0.619) Election's year -0.111 -0.086 -0.075 -0.055 -0.082 -0.084 (0.079) (0.077) (0.073) (0.074) (0.076) (0.080) Interactions EMEs * Deviation -0.042 (0.025) Gini * Deviation -0.003*** (0.001) Rule of law * Deviation 0.013** (0.006) Majority * Deviation 0.059 (0.097) Constant 0.561*** 0.905*** 0.927 0.161 0.143 -0.968 0.565 0.477 (0.149) (0.200) (0.923) (1.029) (1.000) (1.054) (1.027) (0.912) Observations 182 180 164 162 162 162 162 162 R-squared 0.040 0.157 0.100 0.180 0.192 0.212 0.195 0.185 Number of ifscode 60 60 53 53 53 53 53 53 Country FE Yes Yes Yes Yes Yes Yes Yes Yes Robust standard errors clustered by country in parentheses *** p<0.01, ** p<0.05, * p<0.1 - 75 - Table 47 Dependent variable: Fiscal adjustment when needed based on debt/revenue Variables (1) (2) (3) (4) (5) (6) (7) (8) Rigid expenditure minus -0.024*** -0.022** -0.025*** -0.022** -0.018 -0.011 -0.022 -0.047* structural as % GDP (0.007) (0.009) (0.008) (0.009) (0.012) (0.028) (0.029) (0.025) Primary gap (t-1) -0.000 0.004 -0.001 0.003 0.003 0.003 0.003 0.003 (0.003) (0.005) (0.003) (0.005) (0.005) (0.005) (0.005) (0.005) Economic factors GDP growth (t-1) -0.445 -0.271 -0.216 -0.257 -0.271 -0.317 (0.838) (0.918) (0.939) (0.922) (0.951) (0.921) Inflation (t-1) 0.064 0.131 0.154 0.141 0.131 0.066 (0.209) (0.202) (0.212) (0.208) (0.209) (0.213) U.S. Interest rate -0.035** -0.035* -0.037* -0.037* -0.035 -0.037* (0.017) (0.020) (0.021) (0.021) (0.023) (0.021) Political factors Gini 0.005 0.005 0.005 0.008 0.005 0.006 (0.007) (0.007) (0.007) (0.009) (0.007) (0.007) Rule of law -0.044 -0.008 -0.005 -0.007 -0.008 -0.006 (0.062) (0.075) (0.076) (0.076) (0.089) (0.075) Margin of Majority 0.508** 0.491** 0.502** 0.495** 0.491** 0.135 (0.239) (0.237) (0.238) (0.238) (0.238) (0.323) Election's year -0.029 -0.027 -0.028 -0.028 -0.027 -0.024 (0.043) (0.044) (0.044) (0.044) (0.044) (0.043) Interactions EMEs * Deviation -0.011 (0.016) Gini * Deviation -0.000 (0.001) Rule of law * Deviation 0.000 (0.007) Majority * Deviation 0.045 (0.041) Constant 0.548*** 0.675*** 0.298 0.242 0.234 0.139 0.242 0.433 (0.070) (0.108) (0.474) (0.506) (0.509) (0.574) (0.519) (0.517) Observations 534 531 480 479 479 479 479 479 R-squared 0.015 0.025 0.027 0.037 0.038 0.037 0.037 0.039 Number of ifscode 83 83 74 74 74 74 74 74 Country FE Yes Yes Yes Yes Yes Yes Yes Yes Robust standard errors clustered by country in parentheses *** p<0.01, ** p<0.05, * p<0.1 - 76 - Appendix 8: Linear probability model with dependent variable identified as Lavigne (2011) Table 48 Dependent variable: Need of fiscal adjustment based on Lavigne (2011) Variables (1) (2) (3) (4) (5) (6) (7) (8) Rigid expenditure 0.029*** 0.032*** 0.041*** 0.043*** 0.041*** 0.037*** 0.031*** 0.040*** (% of GDP) (0.006) (0.006) (0.005) (0.006) (0.009) (0.011) (0.011) (0.009) Economic factors GDP growth (t-1) -0.217 -0.136 -0.152 -0.140 -0.111 -0.144 (0.231) (0.266) (0.261) (0.267) (0.262) (0.263) Inflation (t-1) 0.358** 0.601*** 0.606*** 0.604*** 0.581*** 0.604*** (0.146) (0.130) (0.129) (0.129) (0.128) (0.130) U.S. Interest rate 0.009 -0.002 -0.002 -0.002 -0.003 -0.002 (0.011) (0.013) (0.012) (0.012) (0.012) (0.013) Political factors Gini -0.007*** -0.006** -0.006** -0.009* -0.006** -0.006** (0.003) (0.003) (0.003) (0.005) (0.003) (0.003) Rule of law 0.025 0.030 0.031 0.031 -0.040 0.030 (0.040) (0.041) (0.041) (0.041) (0.066) (0.041) Margin of Majority 0.015 0.033 0.034 0.037 0.034 -0.041 (0.106) (0.111) (0.111) (0.111) (0.112) (0.212) Election's year -0.003 -0.001 -0.001 -0.001 -0.001 -0.000 (0.011) (0.011) (0.011) (0.011) (0.011) (0.011) Interactions EMEs * Rigidity 0.003 (0.011) Gini * Rigidity 0.000 (0.000) Rule of law * Rigidity 0.003 (0.003) Majority * Rigidity 0.004 (0.011) Constant -0.384*** -0.495*** -0.542** -0.651*** -0.648*** -0.553** -0.418 -0.609** (0.129) (0.144) (0.225) (0.231) (0.233) (0.278) (0.267) (0.249) Observations 2,474 2,462 1,824 1,819 1,819 1,819 1,819 1,819 R-squared 0.076 0.086 0.129 0.143 0.143 0.143 0.146 0.143 Number of ifscode 127 127 97 97 97 97 97 97 Country FE Yes Yes Yes Yes Yes Yes Yes Yes Robust standard errors clustered by country in parentheses *** p<0.01, ** p<0.05, * p<0.1 - 77 - Table 49 Dependent variable: Fiscal adjustment when needed based on Lavigne (2011) Variables (1) (2) (3) (4) (5) (6) (7) (8) Rigid expenditure -0.002 -0.003 -0.005* -0.007* -0.008 -0.005 0.000 -0.005 (% of GDP) (0.001) (0.002) (0.003) (0.003) (0.005) (0.005) (0.004) (0.003) Economic factors GDP growth (t-1) -0.022 -0.057 -0.081 -0.056 -0.095 -0.055 (0.130) (0.175) (0.166) (0.175) (0.175) (0.175) Inflation (t-1) -0.279 -0.389 -0.387 -0.387 -0.397 -0.389 (0.209) (0.260) (0.262) (0.261) (0.260) (0.260) U.S. Interest rate -0.006 -0.010 -0.010 -0.010 -0.010 -0.010 (0.007) (0.012) (0.012) (0.012) (0.012) (0.012) Political factors Gini 0.000 -0.000 -0.000 0.000 -0.001 -0.000 (0.000) (0.001) (0.001) (0.002) (0.001) (0.001) Rule of law -0.016 0.000 0.001 -0.000 0.050 0.001 (0.018) (0.025) (0.024) (0.026) (0.040) (0.025) Margin of Majority -0.067 -0.071 -0.065 -0.074 -0.054 -0.028 (0.050) (0.055) (0.053) (0.061) (0.052) (0.072) Election's year -0.017* -0.023** -0.023** -0.023** -0.023** -0.023** (0.010) (0.010) (0.010) (0.010) (0.010) (0.009) Interactions EMEs * Rigidity 0.002 (0.006) Gini * Rigidity -0.000 (0.000) Rule of law * Rigidity -0.002 (0.001) Majority * Rigidity -0.002 (0.004) Constant 0.073** 0.135** 0.250* 0.328** 0.326** 0.311** 0.158 0.305** (0.033) (0.061) (0.130) (0.141) (0.142) (0.128) (0.125) (0.126) Observations 687 677 485 482 482 482 482 482 R-squared 0.002 0.016 0.013 0.041 0.041 0.041 0.046 0.041 Number of ifscode 88 87 65 64 64 64 64 64 Country FE Yes Yes Yes Yes Yes Yes Yes Yes Robust standard errors clustered by country in parentheses *** p<0.01, ** p<0.05, * p<0.1 - 78 - Table 50 Dependent variable: Need of fiscal adjustment based on Lavigne (2011) Variables (1) (2) (3) (4) (5) (6) (7) (8) Rigid expenditure minus 0.023*** 0.024*** 0.032*** 0.033*** 0.029*** 0.026 0.021 0.032** structural as % GDP (0.006) (0.006) (0.006) (0.006) (0.011) (0.019) (0.018) (0.013) Economic factors GDP growth (t-1) -0.333 -0.289 -0.328 -0.297 -0.263 -0.289 (0.232) (0.262) (0.267) (0.262) (0.264) (0.261) Inflation (t-1) 0.353** 0.627*** 0.642*** 0.634*** 0.605*** 0.627*** (0.155) (0.139) (0.138) (0.138) (0.138) (0.137) U.S. Interest rate 0.002 -0.014 -0.014 -0.014 -0.016 -0.014 (0.011) (0.013) (0.013) (0.013) (0.013) (0.013) Political factors Gini -0.006* -0.005* -0.005* -0.006 -0.005* -0.005* (0.003) (0.003) (0.003) (0.004) (0.003) (0.003) Rule of law 0.026 0.042 0.043 0.043 0.020 0.042 (0.042) (0.045) (0.045) (0.045) (0.046) (0.045) Margin of Majority 0.038 0.057 0.058 0.060 0.056 0.053 (0.114) (0.118) (0.117) (0.117) (0.120) (0.171) Election's year 0.000 0.001 0.000 0.000 0.001 0.001 (0.012) (0.011) (0.011) (0.011) (0.011) (0.011) Interactions EMEs * Deviation 0.007 (0.013) Gini * Deviation 0.000 (0.000) Rule of law * Deviation 0.003 (0.004) Majority * Deviation 0.001 (0.021) Constant 0.061 0.041 0.083 0.005 0.001 0.040 0.088 0.007 (0.046) (0.072) (0.186) (0.189) (0.188) (0.213) (0.188) (0.197) Observations 2,372 2,367 1,760 1,757 1,757 1,757 1,757 1,757 R-squared 0.040 0.046 0.067 0.085 0.085 0.085 0.086 0.085 Number of ifscode 124 124 95 95 95 95 95 95 Country FE Yes Yes Yes Yes Yes Yes Yes Yes Robust standard errors clustered by country in parentheses *** p<0.01, ** p<0.05, * p<0.1 - 79 - Table 51 Dependent variable: Fiscal adjustment when needed based on Lavigne (2011) Variables (1) (2) (3) (4) (5) (6) (7) (8) Rigid expenditure minus -0.003 -0.004* -0.006* -0.008* -0.007 0.005 -0.004 -0.006 structural as % GDP (0.002) (0.002) (0.004) (0.004) (0.004) (0.010) (0.008) (0.004) Economic factors GDP growth (t-1) -0.042 -0.085 -0.058 -0.083 -0.104 -0.090 (0.136) (0.172) (0.154) (0.172) (0.166) (0.174) Inflation (t-1) -0.307 -0.434 -0.442 -0.431 -0.432 -0.432 (0.216) (0.272) (0.278) (0.273) (0.273) (0.273) U.S. Interest rate -0.003 -0.006 -0.006 -0.007 -0.006 -0.006 (0.007) (0.012) (0.012) (0.012) (0.012) (0.012) Political factors Gini 0.000 -0.000 -0.000 0.002 -0.001 -0.000 (0.001) (0.001) (0.001) (0.002) (0.001) (0.001) Rule of law -0.003 0.010 0.010 0.009 0.016 0.010 (0.015) (0.025) (0.025) (0.024) (0.025) (0.025) Margin of Majority -0.057 -0.054 -0.058 -0.073 -0.050 -0.032 (0.046) (0.053) (0.055) (0.068) (0.053) (0.053) Election's year -0.016 -0.021** -0.021** -0.022** -0.021** -0.021** (0.011) (0.010) (0.010) (0.010) (0.010) (0.010) Interactions EMEs * Deviation -0.003 (0.007) Gini * Deviation -0.000 (0.000) Rule of law * Deviation -0.001 (0.002) Majority * Deviation -0.004 (0.008) Constant 0.053*** 0.092** 0.127 0.178** 0.178** 0.133* 0.151* 0.168** (0.016) (0.041) (0.082) (0.087) (0.088) (0.070) (0.090) (0.081) Observations 648 645 464 463 463 463 463 463 R-squared 0.004 0.018 0.013 0.043 0.044 0.046 0.044 0.043 Number of ifscode 84 83 62 61 61 61 61 61 Country FE Yes Yes Yes Yes Yes Yes Yes Yes Robust standard errors clustered by country in parentheses *** p<0.01, ** p<0.05, * p<0.1 - 80 - Appendix 9: Linear probability model with need under stressed conditions Table 52 Dependent variable: Need of fiscal adjustment based on Escolano et al. (2014) Variables (1) (2) (3) (4) (5) (6) (7) (8) Rigid expenditure 0.028*** 0.022*** 0.030*** 0.022*** 0.031*** 0.013 0.007 0.024*** (% of GDP) (0.005) (0.005) (0.006) (0.005) (0.010) (0.017) (0.008) (0.008) Economic factors GDP growth (t-1) -1.412*** -1.474*** -1.385*** -1.499*** -1.424*** -1.466*** (0.275) (0.276) (0.265) (0.278) (0.276) (0.273) Inflation (t-1) -0.122*** -0.144* -0.145* -0.144* -0.146 -0.144* (0.035) (0.085) (0.086) (0.085) (0.090) (0.086) U.S. Interest rate -0.043*** -0.058*** -0.060*** -0.057*** -0.061*** -0.058*** (0.012) (0.013) (0.014) (0.013) (0.014) (0.013) Political factors Gini -0.001 -0.002 -0.002 -0.007 -0.001 -0.001 (0.006) (0.005) (0.005) (0.011) (0.005) (0.005) Rule of law 0.013 0.068** 0.062** 0.070** -0.020 0.068** (0.025) (0.029) (0.029) (0.029) (0.051) (0.029) Margin of Majority -0.054 -0.102 -0.108 -0.103 -0.107 -0.031 (0.096) (0.088) (0.086) (0.088) (0.088) (0.205) Election's year 0.000 0.002 0.003 0.001 0.002 0.001 (0.015) (0.015) (0.015) (0.015) (0.015) (0.015) Interactions EMEs * Rigidity -0.014 (0.012) Gini * Rigidity 0.000 (0.000) Rule of law * Rigidity 0.004* (0.002) Majority * Rigidity -0.004 (0.010) Constant -0.350*** 0.026 -0.408 -0.064 -0.072 0.132 0.276 -0.107 (0.124) (0.139) (0.316) (0.315) (0.313) (0.504) (0.333) (0.322) Observations 1,825 1,772 1,597 1,555 1,555 1,555 1,555 1,555 R-squared 0.064 0.127 0.074 0.158 0.162 0.159 0.163 0.158 Number of ifscode 84 84 75 75 75 75 75 75 Country FE Yes Yes Yes Yes Yes Yes Yes Yes Robust standard errors clustered by country in parentheses *** p<0.01, ** p<0.05, * p<0.1 - 81 - Table 53 Dependent variable: Fiscal adjustment when needed based on Escolano et al. (2014) Variables (1) (2) (3) (4) (5) (6) (7) (8) Rigid expenditure 0.002 -0.005 0.002 -0.005 0.005 0.016 -0.022** -0.026** (% of GDP) (0.005) (0.006) (0.006) (0.006) (0.010) (0.020) (0.010) (0.010) Economic factors GDP growth (t-1) -1.494*** -1.145** -1.056** -1.106** -1.103** -1.180** (0.482) (0.488) (0.468) (0.495) (0.474) (0.518) Inflation (t-1) -0.186** 0.427 0.419 0.446 0.426 0.350 (0.082) (0.291) (0.286) (0.290) (0.264) (0.286) U.S. Interest rate -0.025 -0.053** -0.054** -0.056*** -0.056*** -0.056** (0.016) (0.021) (0.021) (0.021) (0.021) (0.021) Political factors Gini 0.008 0.008* 0.008* 0.022* 0.008* 0.007* (0.005) (0.004) (0.004) (0.013) (0.004) (0.004) Rule of law 0.028 0.104** 0.093** 0.102** -0.018 0.103** (0.037) (0.044) (0.046) (0.043) (0.098) (0.043) Margin of Majority -0.075 -0.001 0.009 0.019 -0.008 -0.918*** (0.118) (0.126) (0.130) (0.129) (0.134) (0.323) Election's year -0.011 -0.017 -0.016 -0.018 -0.016 -0.012 (0.031) (0.031) (0.031) (0.031) (0.032) (0.031) Interactions EMEs * Rigidity -0.018 (0.011) Gini * Rigidity -0.001 (0.000) Rule of law * Rigidity 0.004 (0.003) Majority * Rigidity 0.038*** (0.014) Constant 0.122 0.470** -0.237 -0.188 -0.170 -0.739 0.281 0.364 (0.142) (0.189) (0.388) (0.312) (0.309) (0.578) (0.416) (0.354) Observations 638 624 558 546 546 546 546 546 R-squared 0.000 0.032 0.006 0.046 0.052 0.049 0.052 0.056 Number of ifscode 68 68 61 61 61 61 61 61 Country FE Yes Yes Yes Yes Yes Yes Yes Yes Robust standard errors clustered by country in parentheses *** p<0.01, ** p<0.05, * p<0.1 - 82 - Table 54 Dependent variable: Need of fiscal adjustment based on Escolano et al. (2014) Variables (1) (2) (3) (4) (5) (6) (7) (8) Rigid expenditure minus 0.031*** 0.026*** 0.034*** 0.026*** 0.029** 0.015 -0.002 0.024** structural as % GDP (0.006) (0.006) (0.006) (0.006) (0.012) (0.024) (0.014) (0.011) Economic factors GDP growth (t-1) -1.425*** -1.533*** -1.503*** -1.560*** -1.458*** -1.535*** (0.260) (0.273) (0.264) (0.276) (0.271) (0.271) Inflation (t-1) -0.102** -0.111 -0.115 -0.107 -0.126 -0.111 (0.048) (0.084) (0.085) (0.081) (0.089) (0.084) U.S. Interest rate -0.047*** -0.064*** -0.064*** -0.063*** -0.067*** -0.064*** (0.013) (0.014) (0.015) (0.014) (0.015) (0.014) Political factors Gini -0.001 -0.001 -0.001 -0.003 -0.001 -0.001 (0.007) (0.006) (0.006) (0.008) (0.006) (0.006) Rule of law 0.008 0.066** 0.065** 0.068** 0.012 0.066** (0.024) (0.029) (0.029) (0.029) (0.040) (0.029) Margin of Majority -0.092 -0.142 -0.140 -0.142 -0.141 -0.173 (0.098) (0.086) (0.086) (0.087) (0.086) (0.138) Election's year 0.002 0.003 0.004 0.003 0.005 0.004 (0.016) (0.015) (0.015) (0.015) (0.015) (0.015) Interactions - EMEs * Deviation -0.005 (0.014) Gini * Deviation 0.000 (0.001) Rule of law * Deviation 0.007* (0.003) Majority * Deviation 0.005 (0.017) Constant 0.079 0.369*** 0.090 0.294 0.298 0.370 0.517 0.313 (0.051) (0.071) (0.313) (0.301) (0.299) (0.359) (0.320) (0.307) Observations 1,753 1,707 1,538 1,502 1,502 1,502 1,502 1,502 R-squared 0.059 0.130 0.071 0.166 0.166 0.166 0.172 0.166 Number of ifscode 83 83 74 74 74 74 74 74 Country FE Yes Yes Yes Yes Yes Yes Yes Yes Robust standard errors clustered by country in parentheses *** p<0.01, ** p<0.05, * p<0.1 - 83 - Table 55 Dependent variable: Fiscal adjustment when needed based on Escolano et al. (2014) Variables (1) (2) (3) (4) (5) (6) (7) (8) Rigid expenditure minus -0.005 -0.013** -0.005 -0.011** -0.001 0.018 -0.027** -0.029** structural as % GDP (0.005) (0.005) (0.006) (0.005) (0.010) (0.026) (0.013) (0.013) Economic factors GDP growth (t-1) -1.530*** -1.204** -1.100** -1.166** -1.167** -1.185** (0.489) (0.490) (0.483) (0.491) (0.485) (0.506) Inflation (t-1) -0.190** 0.455 0.434 0.465 0.460 0.396 (0.083) (0.298) (0.299) (0.294) (0.291) (0.307) U.S. Interest rate -0.031* -0.055** -0.055*** -0.058*** -0.058*** -0.056*** (0.015) (0.021) (0.020) (0.020) (0.020) (0.021) Political factors Gini 0.006 0.007 0.006 0.013* 0.006 0.006 (0.005) (0.004) (0.004) (0.007) (0.004) (0.004) Rule of law 0.021 0.104** 0.095** 0.101** 0.066 0.104** (0.039) (0.046) (0.047) (0.045) (0.064) (0.045) Margin of Majority -0.067 0.009 0.032 0.032 0.025 -0.313 (0.120) (0.126) (0.131) (0.131) (0.130) (0.233) Election's year -0.014 -0.020 -0.019 -0.019 -0.020 -0.018 (0.032) (0.032) (0.031) (0.031) (0.032) (0.032) Interactions emes = o, - EMEs * Deviation -0.017 (0.011) Gini * Deviation -0.001 (0.001) Rule of law * Deviation 0.004 (0.004) Majority * Deviation 0.034* (0.020) Constant 0.238*** 0.485*** -0.053 -0.159 -0.129 -0.377 -0.004 0.046 (0.051) (0.094) (0.323) (0.255) (0.261) (0.330) (0.313) (0.291) Observations 619 607 541 531 531 531 531 531 R-squared 0.002 0.041 0.007 0.054 0.059 0.058 0.057 0.058 Number of ifscode 67 67 60 60 60 60 60 60 Country FE Yes Yes Yes Yes Yes Yes Yes Yes Robust standard errors clustered by country in parentheses *** p<0.01, ** p<0.05, * p<0.1 - 84 -