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This PDF is a selection from a published volume from the National Bureau of Economic Research Volume Title: NBER Macroeconomics Annual 2007, Volume 22 Volume Author/Editor: Daron Acemoglu, Kenneth Rogoff and Michael Woodford, editors Volume Publisher: University of Chicago Press Volume ISBN: 978-0-226-00202-6 Volume URL: http://www.nber.org/books/acem07-1 Conference Date: March 30-31, 2007 Publication Date: June 2008 Chapter Title: Cyclical Budgetary Policy and Economic Growth: What Do We Learn from OECD Panel Data? Chapter Author: Philippe Aghion, Ioana Marinescu Chapter URL: http://www.nber.org/chapters/c4081 Chapter pages in book: (p. 251 - 278) 4_ Cyclical Budgetary Policy and Economic Growth: What Do We Learn from OECD Panel Data? Philippe Aghion, Ioana Marinescu, 1 University of Chicago, Harvard University of Chicago University and NBER Introduction is that there is a decoupling among macroeconomists macroeconomic taxation, money (e.g., budget deficit, policy which should primarily affect price and income stability1 and A common between supply), view if anything, should depend growth, which, only long-run economic structural characteristics the of upon economy (property right enforce and so forth). That macroeco ment, market structure, market mobility, should not be a key determinant is further of growth policy at by recent contributions et al. (2003) and such as Acemoglu Easterly (2005), who argue that the correlation between macroeconomic et al.) or those between and growth volatility (Acemoglu growth and nomic hinted macroeconomic variables (Easterly), become insignificant once one con trols for institutions. The question of whether macroeconomic policy does or does not af fect (productivity) In particular, not is it un growth purely academic. derlies the recent debate on the European Stability and Growth Pact as well as criticisms against the European Central Bank for allegedly pur suing price stability at the expense of employment In this paper we question that view by arguing the budget deficit is significant in explaining GDP and growth. that the cyclicality with of amore growth, the countercyclical budgetary policy being more growth enhancing lower the country's level of financial development. We also identify eco nomic factors that tend to be associated with more countercyclical poli cies. These results hold in a sample of OECD countries with comparable institutional The environments. idea that cyclical macroeconomic affect productiv policy might is suggested ity growth by Aghion, Angeletos, Banerjee, and Manova 252 Aghion and Marinescu in AABM is that credit The argument AABM). (2006; henceforth is constrained firms have a borrowing that condi capacity typically earn tioned by current earnings between (the factor of proportionality with a higher multiplier ing and debt capacity is called credit multiplier, a in the economy). In of financial reflecting development higher degree a recession, current earnings are reduced, and so are firms' ability to bor row in order to maintain investments growth-enhancing (e.g., in skills, or extent structural To the that macroeconomic R&D). capital, higher translates into deeper recessions, it should affect firms' incen volatility tives to engage in such investments. This prediction finds empirical sup in first who show, on AABM, cross-country port, panel regressions by that structural investments of cross-country panel regressions, the lower the level of financial develop country's procyclical and second, in firm-level evidence by Berman et al. (2007). Using the basis are more ment; French firm-level Berman straints, total investment on R&D investments and on credit con panel data over et al. show that: (a) the share of R&D investment credit constraints; (b) the firms are credit constrained; (c) this in the effect is only observed during down-cycle is, pres phases?that ence of credit constraints, R&D investment share plummets during re share turns more cessions is countercyclical procyclical when but doesn't These without increase proportionally during up-cycle periods.2 in turn, suggest macroeconomic that countercyclical findings, or lower nominal interest investment policies, with higher government rates during recessions, may foster productivity growth by reducing the failures (in particular, market of loss induced the output by magnitude in turn should al in a recession, which imperfections) by credit market invest their growth-enhancing firms to preserve low credit-constrained decide the ments over the business For may government example, cycle. for private firms' products by increasing spend to stimulate the demand and thus make ing. This could further increase firms' liquidity holdings without shocks it easier for them to face idiosyncratic having to liquidity invest sacrifice R&D or other types of longer-term growth-enhancing face unemploy the other hand, in a recession, more workers could help so their earnings are reduced. Government ment, spending credit constraints either directly (social programs, them overcome etc.) or this re and therefore labor demand employment; indirectly, by fostering to make workers would allow in laxation of credit constraints, turn, investments in human capital, relocation, and so on. growth-enhancing the more faced by firms and workers, The tighter the credit constraints be.3 should such policies countercyclical growth enhancing ments. On Cyclical Budgetary Policy and Economic Growth 253 in this paper is three fold. First, we compute and an contribution coun of the budget deficit on a panel of OECD the cyclicality alyze in out to the fluctuations deficit how the tries?that is, responds budget some we over time. determinants Second, potential put gap investigate of the budget deficit. Third, we use these yearly of the countercyclicality Our to assess the relationship between growth and the counter at of financial develop various levels of policies budgetary cyclicality as follows: (a) the ment. Our main findings can be summarized budget in most countries OECD deficit has become increasingly countercyclical panel data over the past less twenty years, but this trend has been significantly a more in within the EMU; (b) countries, countercyclical pronounced a with is associated level of finan higher policy positively budgetary a lower level of openness, of an and the adoption cial development, a more countercyclical policy regime; (c) budgetary inflation-targeting is financial development has a greater positive impact on growth when from argue that our results likely reflect the causality at to the least document statistical very they budgetary policy growth, variables that are consistent with between macroeconomic relationships on credit constraints, and the theory and microevidence volatility, lower. While we investments. growth-enhancing While we do not know of any previous the attempt at analyzing de effects of of the budgetary policies, analyses growth countercyclical terminants of the cyclicality of budgetary policies already exist in the lit and Tabellini For example, Alesina (2005) argue that more cor run a more to will fiscal policy. The tend democracies rupt procyclical in voters is demand that the government that, hypothesis good times, cut taxes or provide more public services instead of reducing debt, be erature. cause they cannot observe the debt reduction ernment of appropriating the rents associated In equilibrium, this leads to a more ditions. moral in the sense hazard and can suspect the gov con good economic with procyclical policy as the are more that governments They also show that this problem worsens, to divert in booms. likely public resources in explaining tends to be more powerful mechanism ob than in borrowing constraints alone. While Alesina are a and explore (2005) using large sample of countries in this study we use panel analysis on OECD variations, and Tabellini cross-sectional countries. This makes reasons. First, indices within dices the variation in the data served across the use of corruption indices impractical for two no cross-sectional variation in corruption there is almost Second, there is even time for individual countries. the OECD. less variation of these in 254 Aghion and Marinescu In a similar vein, Calderon, Duncan, and Schmidt-Hebbel (2004) show more are more that emerging-market economies with stable institutions a fiscal policy.4 Their empirical analysis countercyclical on the International the varia Country Risk Guide. Although tion in this indicator is limited across OECD countries and time, it pres able to conduct is based ents somewhat more than corruption variation indices.5 as such Perotti Gali Lane (2003) focus, as and and (2003) papers, we do, on OECD countries. Gali and Perotti investigate whether fiscal more in the EMU has become after the Maastricht policy procyclical Other for such a development. treaty. They find no evidence They do find, a more coun a in that while there trend OECD is the toward however, over the is fiscal EMU that trend. behind time, tercyclical policy lagging in the third (2003) paper comes closer to the analysis developed of our paper. Lane examines the cyclical behavior of fiscal policy the OECD. He then uses trade openness, within output volatility, output per capita, the size of the public sector, and an index for political power Lane's section to examine cross-country in cyclicality. The rea differences dispersion a son is taken from Lane and Tor role why power dispersion may play nell (1998): when multiple for political groups compete public spending, more wants to let any substan become No group may they procyclical. subsist because they are afraid that this will not lead to to rather that surplus. but other groups appropriating repayment, trade that GDP growth volatility, evidence Lane finds, in particular, a more to lead divisions and openness, procyclical spending political tial fiscal surplus debt even is not present for all though the effect of political divisions to this literature We contribute of spending. by using yearly categories of budgetary the cyclicality policy and its deter panel data to analyze pattern, countries, and we show that the degree of finan to explain within-country element is an important cial development in such policies, while future or present EMU membership variations minants within OECD we show that inflation tar variations. Moreover, cross-country a more deficit. budgetary countercyclical geting is associated with coun Most closely related to our second-stage analysis of the effect of are Aghion, Angeletos, on Banerjee, policy tercyclical budgetary growth Manova and Aghion, Bacchetta, Ranciere, Rogoff (2006; (2005; AABM), amodel volatil to explain why macroeconomic ABRR). AABM develop explains correlated ity is more negatively and the financial development, the lower growth, productivity test this using cross prediction they from a closed real to an open monetary with panel data. ABRR move and show that a fixed nominal economy country exchange rate regime or lower Cyclical Budgetary Policy and Economic Growth 255 are more rate volatility associated with pro positively and the lower the ductivity growth, the lower the financial development ratio of real shocks to financial shocks. real exchange as follows. Section 2 dis The remaining part of the paper is organized the estimation of the budget deficit for of the countercyclicality each OECD country and each year covered by our panel data set. Section some main determinants 3 uncovers of the countercyclicality of the bud on 4 deficit. Section GDP de financial per capita growth regresses get in the section coefficients 2, the velopment, countercyclicality computed cusses interaction the two, and a set of controls. between Finally, section 5 con cludes. 2 The Countercyclicality of the Budget in the Cross-Country Panel Deficit In this section we measures compute time-varying in our cross-country of of the cyclicality the extent to panel and compare over countercyclical budgetary policy which budgetary time in some policy became more countries than in others. A main is that finding policy in the budgetary United States and the United Kingdom have become significantly more countercyclical EMU area. 2.1 over the past twenty years, whereas it has not in the Data ment data on GDP, the GDP gap (ygap), the GDP deflator, gross debt (ggfl) are taken from the OECD Economic nual series.6 Our measure Panel and govern an Outlook of budgetary is the first difference of policy debt divided by the GDP, which is the same as the budget deficit over GDP. Note that debt and other government data refer to general gov ernment. Financial is measured development by the ratio of private credit to GDP, and annual cross-country data for this measure of finan can be drawn from the Levine database.7 cial development In this latter private credit is all credit to private agents, and therefore in credit to households. The "average years of education in the pop over 25 ulation from the Barro-Lee years old" series is directly borrowed is only available every five years and has been lin dataset; this measure to obtain a yearly series. The openness variable is de early interpolated fined as exports and imports over GDP, and data on it come from the Penn World Tables 6.1. The population share of government growth, measure, cludes 256 Aghion Table 4.1 Statistics Summary Obs. Mean GDP756 gap Gross Budget and Marinescu debt/GDP government deficit/GDP Countercyclicality of budget deficit Countercyclicality of budget deficit rolling window) weighted of budget Countercyclicality of GDP Private credit/GDP population Population capita of schooling over 25 years years Average per 0.000 0.019 0.548 0.295 756 0.048 0.046 0.511 0.563 2.686 -0.342 756 0.578 0.752 3.337 -1.112 532 0.608 1.065 8.972 -3.011 689 0.025 0.026 585 0.801 0.392 0.128 1.989 2.510 share of GDP Investment/GDP Inflation-targeting -0.070 0.046 -0.065 -0.092 old 1.686 0.321 0.116 2.240 585 8.236 605 Openness 53.633 35.641 756 Inflation 0.061 0.066 -0.025 689 0.006 0.005 -0.018 605 12.440 5.709 3.008 27.848 605 24.106 4.983 12.867 41.635 756 0.112 0.316 01 (in %) %)(in dummy 8.705 to observations the Countercyclicality where of budget Sample is not missing. computed using Gaussian weighted rolling windows and Perm World Sources: OECD Economic Outlook, Levine dataset, Barro Lee dataset, 6.1. Note: 0.071 for the growth Government Max. deficit rolling window) (10-years Growth Min. 756 641 (AR[1]) (Gaussian Std. Dev. restricted 12.250 266.883 0.762 0.047 deficit Tables share of GDP also come from the Perm World GDP, and investment is defined using the dates Tables 6.1. The inflation targeting dummy in Vega and inflation targeting, as summarized when countries adopted Winkelried (2005). All nominal variables are deflated using the GDP de statistics can be found in table 4.1. The sample is an un flator. Summary countries: Australia, balanced the following Austria, panel including Spain, Finland, France, United Kingdom, Belgium, Canada, Denmark, New Zealand, Iceland, Italy, Japan, Netherlands, Norway, Germany,8 Portugal, 2.2 Sweden, Public Deficit and the United and Growth: States. The Empirical Challenge are interested in evaluating the impact of the cyclicality of the bud on and of GDP how this effect deficit the per capita, may de get growth on is that a Our expectation the degree of financial development. pend We Cyclical Budgetary Policy and Economic Growth 257 Low financial t -1 in period development L Increased| /f \ countercyclicality | of budgetdeficit | V I in 'Dase Period t"1 szz*~. Lr financial High | Increased j ^ ] countercyclicality | of budgetdeficitJ^*^/^1^*. period t j s?^ | 1 k Time v-v-*-v-' t-l t -1 in period development in base t t-l t t-l ^f y^'^^J^^^ v->-*-v-' t-l t Time t Legend Trend GDP growth Realized GDP growth . Figure 4.1 The Impact more of an Increase Budget in the Countercyclicality countercyclical budget financial development when this effect from time variation ure 4.1 illustrates the situation between ment is low ment is high deficit this idea where, of the Budget Deficit on Growth is more likely to enhance growth to identify is lower. Empirically, we wish of budgetary within countries. policy Fig case: we for a hypothetical distinguish in the base period t-l, financial develop deficit financial develop (upper panels), and the situation where a We start in the left with baseline (lower panels). depicted hand side panels of figure 4.1: the budget deficit is thus initially assumed to be procyclical. The right-hand side panels of figure 4.1 illustrate the in period 2 after an increase in the countercyclicality of growth response in period the budget such that deficit the deficit becomes 1, budget If financial development is low, then trend strongly countercyclical. in period 2 increases substantially in figure growth (upper left panel is high, then trend If, on the other hand, financial development a increases amount smaller left (lower growth by panel of figure 4.1).9 at one can think of to most the obvious method Looking figure 4.1, 4.1). compute cyclicality is to regress the public deficit on the GDP growth us 258 Aghion and Marinescu in period t. In prac least squares (OLS) on the observations ing ordinary seems on the GDP more to it reasonable the deficit tice, regress public as where GDP* is the trend GDP) [GDP GDP*]/GDP*, gap (defined like a rather than the GDP growth. Indeed, the GDP gap is very much of the GDP growth, and a forward-looking detrended measure govern budgetary policy should respond to shortfalls from trend rather than to GDP growth per se (for a theory of why fiscal policy should de on the GDP gap, see Barro [1979]). pend to measure the cyclicality of This type of regression-based approach in the literature and can be found, for ex is now common fiscal policies the and Tabellini (2005). However, ample, in Lane (2003) and Alesina ment's used in these papers give rise to only one (or a few) observa tion of cyclicality per country. Since we want to investigate the impact of in cyclicality, we need to compute, for each country, time time variation measures the of for countercyclicality budget deficit. Specifi varying methods to use a yearly panel of countries, we need ameasure cally, as we wish t -1 and that varies yearly. This means that period of countercyclicality are one is reduced to single year each! A regression period t in figure 4.1 so we must use observations from not defined for a single observation, The next a few years in order to compute countercyclicality. can be used to compute discusses what methods 2.3 Methods Econometric one would Generally, to Compute like estimate subsection countercyclicality. Countercyclicality the following equation for each i: country ~ * !'"1 = ifit ?i?W + <hu+ e,v where ~ ei( N(0, <r*), (1) of budgetary the countercyclicality alitmeasures policy. is in in when the front of there is aminus economy sign ygapit: the opposite of the GDP gap and the GDP gap is negative, that the budget deficit increases and so a positive alitmeans where is in a economy Both alit and the to denote the ajit The variables bit:Gross that is positive, the when that is, the budget deficit is countercyclical. recession; iswhy we write which constant a2it10are time-varying, coefficient on the variable ; in country i at year t. 1 are defined as follows: in equation government yit: The GDP Note a recession in country debt in country i and year i at year t, in value t Cyclical Budgetary Policy and Economic Growth 259 as (yit- y%) / it:The GDP gap in country i and year t. It is computed y filter. A of yit using the Hodrick-Prescott y%,where y% is the prediction that of 25 was chosen, following OECD lambda parameter (1995). Note the GDP proach a function ap gap computed production by the OECD using a Hodrick-Prescott so that in is also smoothed by technique, measure the difference between of the GDP gap and the OECD practice the measure used here is very limited: the correlation between the two of the GDP gap is, as expected, positively is 77%. Our measure correlated with the GDP per capita growth: the correlation is, however, variables not so strong, at 36%. that bit - bit_x is exactly equal to the opposite of the budget bal so our to the that is left-hand side variable ance, equal budget deficit as a share of GDP, which we will as budget deficit. We now simply refer to Note examine how One way the coefficients to implement can be estimated econometrically. ajit this is to compute finite (for example, ten least squares (OLS) estimates. The ten ordinary to estimating OLS method the simply amounts t at deficit of the in year (bit bit_Jy{^ budget country countercyclicality iby running the following for each country i, and all possible regression years) year rolling-window rolling window t: years ~ " ''"' = if it -?,?W + ?2?+ ?Wfor t (t - 5, t+ 4). (2) That is, one uses a ten-year centered rolling window to estimate the coun t. at of deficit date This method suffers, how any tercyclicality budget ever, from serious shortcomings. First, by definition, we lose the first five years and the last four years of data for each country. Second, because the a coefficient method involves estimating at each time pe by discarding riod one old observation and taking into account a new one, the coeffi cient can vary substantially when the new observation is very different from the one it replaces. This implies that the series may be jagged and a sudden by noise and transitory changes; moreover, jump in the not be coming from changes series would in the immediate neighbor hood of date t, but from changes five years before and four years after. To deal with the shortcomings of the ten-years rolling window one can use are used for such that all observations method, smoothing each year, but those observations closest to the reference year are given affected greater method The local Gaussian-weighted weight. is one way of achieving this. It consists least squares ordinary co in computing the ajit 260 Aghion and Marinescu available for each country i and by using all the observations one regression then performing for each date t,where the observations are a Gaussian at t.u centered date weighted by efficients ~ it /o\ , , + i,t~l -= -?i?yOT,-T if it where eh ~ N[0, v2/wt(i)\ a2u + (3) e,-T, and wt(j) = i r (T-o2_i ^ exp-^~r~ is less noisy than the OLS method the local Gaussian-weighted a window it similar shortcoming suffers from method, ten-years rolling it comes to testing the idea illustrated in figure 4.1. Indeed, these when While use observations two methods from both the past and the future (previ ous years and future years) to calculate yearly countercyclicality. Ulti we in counter want to look at the impact of year t 1 changes mately, on year t growth, but if countercyclicality is using computed cyclicality some future observations, then in practice we are examining the impact on of both past and (some) future countercyclicality growth. Thus, it is causes hard to be certain that year t -1 countercyclicality year t growth, a and reverse causality becomes problem. One way to address this issue is to use longer lags of countercyclicality (t 2 or t 3 or t 4, etc.), but on that the effects of countercyclicality this requires us to assume a are for delayed specific number of years. growth at year t this problem by making is upon past observations, depend essentially countercyclicality the follow an AR(1) process. Namely, to assume that coefficients using notation from equation 1, for each country i and for each coefficient;: An alternative method, which gets around current + ^^^-i e^eg^N^aJ.). The main is to estimate a2 in implementing this method challenge as same at the variance of the the time the of coefficients) 1. of equation that is, the variance a2 in the formulation (the variance observation, Once these variances best estimates (4) for are estimated, applying the Kalman filter gives the a-it. are extremely hard to com for these variances The optimal estimates turns out to be vir solutions pute. While finding analytical closed-form Carlo Markov Chain Monte (MCMC) methods pro tually impossible, vide a feasible the method We implement approximation. variances and the that the of coefficients equation numerical Matlab, assuming the same for all countries.12 We are thus left with three variances in are to esti Cyclical Budgetary Policy and Economic Growth 261 = 1,2) and one for the vari in the equation the MCMC method (a;:). Intuitively, aMarkov hence the chain, name) awide spec (using randomly explores trum of possible values and one then retains a set of for the variances, mate: two for the coefficient processes (v2a.,j ance of the error that is representative of probable values, given the data.13 An ad over maximum likelihood vantage of the MCMC method type methods is that it does not get stuck in local solutions and thus properly repre sents uncertainty about the variances.14 Once we obtain the estimates of values the three variances, Kalman filter. these ajit coefficients can be calculated using the over the previous methods is to be preferred for two AR(1) MCMC reasons. First, it reflects a reasonable about is, assumption policy?that on the immediate past. Second, that policy changes slowly and depends and most in that itmakes it is econometrically appealing coefficients mainly depend on the past (because ajit are used as the coefficients thus, when specification);15 ajit variables in panel regressions, it is less likely that there importantly, reflected in the policy of the AR(1) explanatory should be a reverse 2.4 causation problem. Results now use the AR(1) method as previously to characterize described the level and time path of the countercyclicality of budget deficits in the in our sample. We also report some basic results with OECD countries We the ten-year rolling window and Gaussian-weighted OLS methods. Table 4.1 summarizes the descriptive statistics of our main variables of interest. For all three measures, the budget deficit is countercyclical is consistent with Lane's (2003) finding that (positive coefficient), which the primary surplus is procyclical. It isworth noting that the three dif ferent methods used in the first stage to estimate countercyclicality give in terms of the mean: amean of about .5means similar results that, very on average, in our sample a 1 percentage in increase the point opposite of the GDP gap (i.e., a worse leads to about .5 percentage recession) points increase in the budget deficit as a share of the GDP. In terms of the we can see that the standard error is of these measures, largest as for the ten-years rolling window it is smaller for method, expected; the Gaussian method, and even smaller for the AR(1) MCMC method. We now look at the evolution of the countercyclicality of budget the estimated 1. coefficients from deficit, as measured alit by equation 4.2 shows the evolution of the of the Figure countercyclicality budget variance 262 Aghion cm- and Marinescu K LO_ \^ J V^ O] 1I ' ' I I I I I I ' I 1960 1970 I I .j I 1990 1980 2000 2010 Year - 10 years rolling window-Gaussian-weighted rollingwindow -AR(1)MCMC Figure 4.2 The Countercyclicality Note: gap Source: OECD of the Budget Deficit in the United i.e., the coefficients plots the alit coefficients, estimation 1, using various techniques. The graph in equation Economic States on the opposite of the output Outlook. described States, estimated by the three methods can readily see that, as expected, the construction given previously. standard and their empirical of these measures errors, the ten-years results, and the AR(1) method rolling window yields the most volatile deficit for the United We in be OLS method with the Gaussian-weighted is the smoothest, show an increase in countercyclical tween. Overall, all three methods a recent trend toward decreasing countercyclicality, ity over time, with OLS and Gaussian-weighted shown by the ten-years rolling window methods. of the budget deficit esti In figure 4.3, we show the countercyclicality a in our sample. countries method for few the AR(1) through mated tend to increase countercyclicality Kingdom over time, especially since the 1980s. On the other hand, the average in EMU countries of slightly de policy budgetary countercyclicality between EMU creases over time. Also, one can observe some divergence the counter at the beginning of the period, countries: and non-EMU United States and United of the budget deficit in EMU countries was very similar to cyclicality as of the 1990s, the United States States: however, that in the United Cyclical Budgetary Policy and Economic Growth 263 /" / / ^ "*^-,_^ ?j?i?i?i?i?i?i?i?i?i?|?i?i?i?i?i?i?i?i?i?|?i?i?i?i?i?i?i?i?i?|?i?i?i?i?i?i?i?i?i?|?i?i?i?i?i?i?i?i?i?|? 1970 1960 1980 1990 2000 2010 Year - United States-United countries -EMU Kingdom 4.3 Figure The Countercyclicality of Budget Deficits Using theAR(1) MCMC Method on the The graph plots the alit coefficients, i.e. the coefficients of the output opposite the AR(1) MCMC method. For EMU countries 1, using gap in equation (i.e., countries who are or will be part of the EMU), the line represents the average of the estimated coefficients in the sample; for the EMU countries is only computed the average for those years present where all EMU countries have nonmissing observations. Note: Source: OECD and Economic the United Outlook. Kingdom more significantly Union did not. became whereas the European Monetary In figure 4.4, we plot the same countercyclical, this time based on coeffi evolution, the OLS. Trends in using Gaussian-weighted similar to those obtained using the AR(1) method. that are estimated cients estimates These are very results are consistent with Gali and Perotti (2003), who show, their in that in the fiscal deficits decades, splitting sample by general, OECD have become more so in less EMU countercyclical, although countries. Here we confirm these results, using a time-series full-fledged measure of countercyclicality. To summarize deficit has become United Kingdom tion we investigate our found that the budget results, we descriptive more in the United States and the countercyclical than in EMU countries since the 1990s. In the next sec possible explanations for these observed differences 264 Aghion CM and Marinescu / / / / / ^4 - o-_ : / |?i?i?i?i?i?i?i?i?i?|?i?i?i?i?i?i?i?i?i?|?i?i?i?i?i?i?i?r-i?|?i?i?i?i?i?i?i?i?i?|?i?i?i?i?i?i?i?i?i?|? 1960 1970 1990 1980 2000 2010 Year - United States-United countries -EMU Kingdom Figure 4.4 The Countercyclicality of Budget Deficits the Gaussian-Weighted OLS Method using on the opposite of the output i.e., the coefficients plots the alit coefficients, For EMU the Gaussian-weighted OLS method. 1, using gap rolling window are or will be part of the EMU), the aver the line represents countries (i.e., countries who in the sample; the average for the EMU countries coefficients age of the estimated present all EMU countries have nonmissing observations. is only computed for those years where Note: The graph in equation Source: OECD Economic Outlook. in the countercyclicality of budgetary deficit across countries and over time. 3 First Stage: Determinants of Budgetary Policy of the Countercyclicality derived using coefficients In this section, we use the series of cyclicality of budget and regress the countercyclicality the AR(1) MCMC method our sample is re a over Since set of macroeconomic variables. ary policy stricted to OECD little variation countries, or other institutional variables corruption so far.16 Instead, we development, has adopted be expected from the considered by the literature should candidate variables: financial focus on the following and whether the EMU country openness, membership,17 inflation targeting. We also include GDP growth volatility Cyclical Budgetary Policy and Economic Growth 265 as measured error of GDP growth, by the standard lag of log-real GDP as share of GDP control variables. per capita, and the government as Financial development it influences both the is a plausible suspect, to and of the borrow governments ability willingness during recessions in order to finance a budget deficit. Lower financial development should into lower countercyclicality thus translate of budget deficit. While are arguably countries less subject to borrowing constraints, there is still a fair amount of cross-country variation in financial devel OECD is also a plausible candi opment between OECD countries. Openness as one can to in flow date, expect foreign capital during booms and flow out during recessions, the cost that of capital is higher during implying recessions rather than booms. This, in turn, tends to increase the long run cost of financing countercyclical taining the overall debt constant, budget deficit policies while main on average, over the long run. The in candidate, given: (a) our observation EMU dummy is also a plausible 4.2 and 4.3, that the budget figures is less countercyclical in the (b) the deficit Kingdom; and debt restrictions imposed by the Stability and Growth Pact and also the restrictions that individual countries in or imposed on themselves eurozone than in the United deficit States or the United der to qualify for EMU membership. Inflation should also targeting improve a country's or willingness to conduct one countercyclical budgetary policy. In particular, that reces factor to borrow in governments potential might discourage sions is people's expectation that such borrowing might result in higher ability in the future?for example, as away for the government reduce This, in turn, would tially default on its debt obligations. on pact of current government borrowing private (long-term) inflation ment. Inflation increases the effectiveness to par the im invest of government less reasonable. targeting in recession by making such expectations borrowing Table 4.2, where measures are derived the countercyclicality shows results that are consistent with AR(1) MCMC method, using the these con (a)while countries that are more financially developed jectures, namely: tend to have a less countercyclical (column 1), as a budgetary policy more more it exhibits a country gets financially developed, significantly deficit the results from column (column 2); using countercyclical budget increase in private 2, our estimates imply that a 10 percentage points credit over GDP is associated with an increase of about 0.0196 in the of the budget deficit; in other words, it is precisely countercyclicality when the countercyclicality of the budget deficit ismore cor positively related with growth, namely when financial development is low, that 266 Aghion Table and Marinescu 4.2 The Determinants of the Countercyclicality of Budget Deficits _(1)_(2) Year Private credit/GDP f .e. Country -0.453 f .e. 0.196 (0.115)*** EMU year (0.018)*** -0.127 country (0.038)*** error of GDP Standard -3.364 growth (0.818)*** Lag(log [realGDP per capita]) 0.011 0.072 Government share of GDP (in%) (0.017) 0.000 (0.071) 0.004 (0.005) (0.001)*** Inflation targeting 0.292 0.112 (0.081)*** (0.015)*** -0.007 Openness -0.002 (0.001)*** Observations 515 (0.001)*** 515 R-squared 0.21 0.99 on the opposite is the coefficient The explained variable the AR(1) MCMC method. EMU country 1, estimated using 1 for all countries that are part of the EMU as of 2006. errors in parentheses. Robust standard Note: *Significant of the GDP is a dummy gap in equation variable equal to at 10% **Significant ***Significant Sources: OECD at 5% at 1% Economic Outlook, Levine dataset, Barro Lee dataset, and Perm World Tables 6.1. seems hardest to achieve; (b) when countercyclicality more trade openness is effects (column 2) using country- and year-fixed counter and with associated deficit positively significantly budgetary budgetary deficit coefficient on openness); (c) EMU (the table shows a positive and countries with a larger standard error of GDP growth ap deficit countercyclical pear to have a harder time achieving budgetary on the EMU that, average, EMU coun ity (column 1); dummy implies is is lower tries' budgetary countercyclicality by 0.127, which policy cyclicality countries about more a fourth of a standard deviation; is the effect of the EMU dummy already imposed by the precur likely to be explained by rigidities sor EMS regime and then reinforced Treaty, rather by the Maastricht than the 1999 implementation of the EMU itself;18 further investigation Cyclical Budgetary Policy and Economic Growth 267 of this question the scope of this paper; (d) a higher is, however, beyond in the GDP is associated with amore countercycli share of government cal budgetary inflation targeting is associated with policy; (e) pursuing amore budget deficit. Note that the coefficient in column 2 is of the same magnitude dummy countercyclical on the in as the co targeting in column 1, but of opposite efficient on the EMU dummy sign. a lower level of financial development, a higher Hence, degree of to tar the and the EMU absence of inflation openness, group, belonging are a in the all associated with lower degree of countercyclicality geting we move a In next to deficit. the section budget second-stage analysis of flation the effect of budget 4 Second deficit on growth. cyclicality Stage: Cyclical Budget Deficit and Growth In this section we for bud coefficients regress growth on the cyclicality in derived section 2, financial development, the interaction getary policy between the two variables, and microeconomic theory and a set of controls. evidence in the introduction R&D/growth the greater Our discussion of the on volatility, credit constraints, and that the lower financial de suggests the correlation should be between growth and a more coun of budgetary the is idea that policy: can the reduce that effect neg tercyclical budgetary help policy negative ative liquidity shocks impose on credit-constrained firms that invest in velopment, the countercyclicality R&D and innovation. 4.1 Empirical Our empirical ty* = PA?i Specification specification + P2rVi + and Results is: Ps^t-iPu-i + XA + 7, + 8, + eit, (5) of the log of real GDP per capita in coun Ayit is the first difference i and the is of the budget deficit as es year t; alit_x try countercyclicality timated by the AR(1) MCMC method. Since ait_x is an estimated coeffi where each observation cient, we weigh by the inverse of the variance of this coefficient in thus to coefficients Stata), (aweights giving higher weight that are more precisely in the first stage. The ratio of estimated private from Levine and Demirguc-Kunt credit, p/>1Lto GDP is borrowed (2001); con that vary with the specification Xit is a vector of control variables a is and is the sidered, 7. is a country-fixed effect, St effect, eit year-fixed error term. 268 Aghion and Marinescu In table 4.3, we first report results with a limited set of controls, repre of growth: lag of log real senting the most widely accepted determinants over GDP (column GDP per capita, population growth, and investment trade openness, infla 1).We then add more controls, namely schooling, share and inflation Note of tion, government GDP, targeting (column 2). that since we control for inflation, we indirectly control for the impact of monetary policy on growth. is that of a positive The prediction for the effect on (^ coefficient of the of the deficit when growth budget private countercyclicality on credit over GDP is 0, and of a negative (33coefficient countercyclical In the first column of table financial development. ity interacted with coeffi 4.3, using a limited set of controls, we see that the corresponding a are more and cients have the anticipated signs statistically significant: correlated with growth, but countercyclical budget deficit is positively term between and financial develop countercyclicality a in column 2 does not set of controls richer Including are a coeffi If estimates the results. the point anything, larger: change means that cient of 0.11 of the lagged countercyclicality of budget deficit the interaction ment is negative. if private credit over GDP is 0, then increasing the countercyclicality of 0.11 increases the budget deficit by one percentage per point growth by over centage points. For each percentage point increase in private credit diminishes effect of countercyclicality GDP, this positive by 0.0004. The is thus small: private credit over GDP would of the interaction to be larger than 2.75 for a countercyclical budgetary policy to be come growth reducing. Such a high value of private credit over GDP is effect need not observed in our sample: of this variable States the United our in sample. in 2000, at 2.24, has highest value Then, in columns 3 and 4, we repeat the same specifications umns 1 and 2, but allow the impact of the interaction between the as in col the coun of the budget deficit and private credit over GDP to differ over GDP (the first quartile is then the by quartiles of the private credit the dummy For example, excluded "2ndq (Private Credit/ category). to 1 if ratio lies in the second the Private is Credit/GDP GDP)" equal tercyclicality zero otherwise. As the results in these columns quartile, and is equal to is and financial development show, the interaction between cyclicality ra credit the when nonlinear, with a significant private jump occurring tio moves from the second to the third quartile. In other terms, it is only bud that countercyclical development less growth enhancing. getary policy becomes noticeably of a positive effect of a Table 4.3 is thus consistent with the prediction at fairly high levels of financial Table 4.3 The Effect of the Countercyclicality of Budget Deficits on Growth, (2) _(1) lag(Countercyclicality of budget deficit) 0.058 0.081 (0.016)*** (0.018)*** -0.005 lag(Countercyclicality deficit*3rdq[Private lag(Countercyclicality deficit*4thq[Private of budget -0.009 (0.003)*** -0.024 (0.008)*** (0.007)*** -0.030 (0.008)*** -0.140 (0.010)*** -0.132 -0.142 (0.022)*** (0.022)*** (0.022)*** 0.002 0.002 0.002 0.002 (0.000)*** (0.000)*** -1.702 (0.268)*** for the (0.284)*** (0.000)*** -1.484 (0.272)*** 0.002 population over 25 years old Government share of GDP (in%) (0.000)*** (0.000)** -0.053 (0.022)** (0.021)** -0.004 Openness Observations 477 0.60 R-squared (0.290)*** (0.003) -0.001 -0.049 targeting (0.000)*** -1.635 0.003 (0.003) -0.001 Inflation Inflation -0.131 (0.022)*** -1.490 Population growth (0.007) (0.014)*** -0.023 credit/GDP]) of schooling (0.007)** -0.008 -0.040 (0.003)** credit/GDP]) of budget Investment/GDP (in%) years -0.014 -0.022 lag(log [realGDP per capita]) Average (0.008) -0.006 deficit*2ndq[Private credit/GDP]) (4) 0.110 (0.012)*** of budget (3) (0.024)*** (0.008) lag(Countercyclicality Method 0.075 -0.030 of budget lag(Countercyclicality deficit*Private credit/GDP) MCMC (0.021)*** -0.010 lag(Private credit/GDP) AR(1) -0.001 (0.005) 0.001 (0.005) 0.001 (0.000)** (0.000)*** 467 0.64 477 0.62 467 0.65 Note: The explained variable is the first difference of the log of real GDP per capita. All include country and year fixed effects. Columns 3 and 4 allow for the effects specifications of countercyclicality of the budget to differ with deficit of private credit/GDP. quartiles errors in Robust standard parentheses. *Significant at 10% **Significantat5% ***Significant Sources: OECD 6.1. at 1% Economic Outlook, Levine dataset, Barro Lee dataset, and Perm World Tables 270 Aghion countercyclical budget interaction significant and Marinescu on and growth, whereas we see a negative credit and counter between the private deficit effect a country is, the cyclicality variable. Thus, the less financially developed more it is for the government to be countercyclical in growth-enhancing we its budgetary In that EMU observe countries have policy. particular, budgetary the United that are, on average, far less countercyclical than in policies States (0.37 vs 0.61), even though the United States ismore fi than the EMU: thus, the ratio of private credit to developed nancially GDP in 2000 in the EMU Then, to the extent policy to growth, is equal to 1.02, against 2.24 in the United States. that it reflects the causality from cyclical budgetary in table 4.3 suggests the regression that increasing the of the budgetary countercyclicality policy would the EMU the States. for than for United hancing 4.2 Robustness This section mates. We ification ternative be more growth en Tests discusses various potential issues with our table 4.3 esti take as the reference for this discussion the spec specification in table 4.3, column 2. Therefore, when we report on al on this reference specification. specifications, they are all based shown A potential first source of concern for our estimation strategy is auto is typical in panel growth correlation of residuals, which regressions. This implies that the standard errors may be biased. To correct for this errors to adjust the standard we used Newey plea of the potential bias, errors in the reference specification. of er for autocorrelation Allowing rors up to lag 1 increased the standard errors very slightly and left the at the 1% level. Allowing for autocorrelation up significant of the budget deficit at to 5 lags leaves the effect of the countercyclicality but makes the interaction be the same level of statistical significance, coefficients of the budget deficit and private credit be the countercyclicality it does not at the 2% instead of the 1% level. Globally, only significant seem that autocorrelation affects the standard of residuals substantially tween errors of Second, get deficit our estimates. the reader may wonder increase growth when about what components of the bud For ex they are more countercyclical. that ul of total government spending ample, is it the countercyclicality and social matters about transfers What for security growth? timately as for the run the same analysis for these variables spending? We have budget deficit,19 and found cant in explaining economic was not signifi that their countercyclicality growth. This indicates that the cyclical be Cyclical Budgetary Policy and Economic Growth 271 to fully account for our results: is unlikely stabilizers case it not is the that just increasing transfers and social security namely, in increases economic recessions for spending growth. What matters se is not the countercyclicality of spending (be it discre per growth havior of automatic is financed this spending tionary or not) but rather the degree towhich to which the debt?that the is, government injects extra liq by degree into the economy. uidity in knowing what happens if of countercyclicality the by OLS. In the case of rolling window the reader may be interested the AR(1) MCMC estimate replace Third, we or the ten-years Gaussian-weighted on the the Gaussian, the coefficients of the budget countercyclicality deficit and on its interaction with private credit have the same sign as in at the 1% level. The only the reference specification and are significant on the countercyclicality difference is that the value of the coefficient of the budget dow method, statistically are much deficit is lower. the coefficients significant, In the case of the ten-years rolling win of interest are of the same sign, but are not which is not surprising, since these estimates noisier. of Fourth, one may still be skeptical about the causal interpretation our estimates. As mentioned in section 2, our AR(1) MCMC estimate of with the uncorrelated should, in principle, be mostly countercyclicality in First, to check whether, is independent of growth, we include deed, measure both the lag and the lead of the countercyclicality in the refer ence specification. so not does the coefficient Doing significantly change on the an but and lagged countercyclicality yields insignificant positive coefficient on the lead of procyclicality. These results are consistent with causing growth, not the reverse. Second, we noticed countercyclicality that inflation targeting is associated with a less countercyclical budget deficit but is in explaining (table 4.2) (table 4.3). insignificant growth This raises the possibility of using inflation targeting as an instrument a in GMM framework. for countercyclicality In the GMM estimation, we future, the endogeneity reducing future countercyclicality problem. instrument both the countercyclicality variable and the lagged GDP per we use For the the classic instruments' second and third lag latter, capita. of GDP per capita. Excluded instruments in our GMM regression are thus second and third lag of GDP per capita and the inflation targeting our GMM estimates allow for errors of lag 1. Moreover, dummy. Newey We have thus re-estimated the reference specification using GMM. First are estimates but the explanatory stage power of inflation significant, targeting for countercyclicality is limited. Overidentifying restrictions 272 Aghion and Marinescu are not we do not reject the counter rejected by the J test. However, with and its interaction which private credit are exogenous, cyclicality on means that GMM is not more appropriate than OLS. The coefficients and its interaction with private credit are of similar countercyclicality as in the reference specification, but they are not significant magnitudes that our counter exercise thus around This confirms 30%). (P-values measure to is be unlikely endogenous. cyclicality of our effects: when in a given year, how the effect on growth persist? One way to answer this the reference specification by replacing the lag of the Finally, one may be interested in the time horizon of the budget deficit changes the countercyclicality far in the future does question is tomodify of the budget deficit, private credit over GDP, and the countercyclicality interaction of the two by further lags. When using the second lag of these the coefficients of interest (P: and 03) are still significant and of variables, same the slightly. When using the third lag of sign, but the R2 diminishes of the deficit is still the coefficient on the countercyclicality these variables, no with credit is but interaction the private longer significant. significant, in even further lags makes of interest become the coefficients Using an of bud increase in the countercyclicality significant. Thus, it seems that getary policy 5 affects GDP growth up to two or three years later. Conclusion and determinants the dynamics of the In this paper we have analyzed on a yearly panel of OECD countries, and policy cyclicality of budgetary and financial development, this cyclicality, between the relationship as follows: can be summarized Our economic first, findings growth. increased over time. of budget deficits has generally countercyclicality less the budget deficit became in EMU countries, However, slightly of budgetary Second, countercyclicality policy appears a lower de a financial of level development, higher by a to inflation to trade, and monetary policy committed gree of openness are more we found that countercyclical budget deficits targeting. Third, of finan level the lower the with associated country's growth positively cial development. interest in this paper bears potentially The line of research pursued our second-stage In regres particular, implications. ing growth policy sions suggest that growth in EMU countries could be fostered if the bud more countercyclical. Our first-stage get deficit in the eurozone became that this, in turn, could be partly achieved by hav suggests regression countercyclical. to be facilitated Cyclical Budgetary Policy and Economic Growth 273 area move toward inflation targeting; for example, follow ing the EMU in UK the lead this and also the coordination respect, ing by improving in the eurozone on fiscal policy over the cycle between finance ministers so as tomake it become more countercyclical.20 in this paper should be seen as one step in a broader re The analysis search program. the same kind of anal First, one could try to perform countries ysis for other groups of countries; for example, middle-income or in Central and Eastern Europe. Second, one could in Latin America to volatility, take a similar AABM-type of approach financial develop to further explore the relationship and growth between ment, growth to and the conduct of monetary For what allow extent, policy. example, can for short-term of nominal interest rates, ing higher procyclicality in recessions and/or R&D investments improve govern to ability implement growth-enhancing countercyclical budget one could the interactions ary policies? Finally, investigate possible in growth between and regressions countercyclical budgetary policy structural reforms in the product and labor markets. firms maintain ments' Appendix 1 The AR(1) MCMC Method for Calculating Cyclicality in the First Stage is to give a brief description of how we used the Kalman filter together with Markov Chain Monte Carlo methods the coefficients from equation (MCMC) in order to estimate 1, under ajit the assumption that they follow an AR(1) process as described by equa was carried out in Matlab. tion 4. The implementation the Estimating means and variances of the coefficients of interest?that is in equa ajit tion 4?involves two procedures: com Kalman and MCMC. To filtering the with coefficients the Kalman we filter each for to need pute country, The aim of this section know the values of three variances: in equation 4, for j = 1,2; that is, the process of the Kalman filter minology a2 variances in the ter a2 of the error term e, in equation 1; that is, the measure error variance in the of the Kalman filter. terminology the variance ment Moreover, observation to use the Kalman filter, we need a prior for the first period of for each country?that of our expectation is, a specification 274 Aghion over and Marinescu at the first time step. As we do not have any mean ajit at the first observed about cyclicality information period, the values ingful prior we use a very high variance around the prior mean, so that this prior has a the set of initial values effect on the estimates. Specifically, negligible of the coeffi for the coefficients were chosen to be the OLS estimates cients using the first ten years of data for each country, and the value is set to be 100,000 times the estimated variance the initial variance these coefficients. error ment are <j2z unknown ful prior over them. We therefore need ues for these three unknown variances. can think of MCMC are useful. One case of we simulation, know the we and do not amethod This have any meaning to find reasonable iswhere as the opposite parameters of a2 and the measure variances the process However, variance of of MCMC of simulating: our val methods in the process?for ex it and every time we run a simulation program, ample, the variances, a set of us data. observed More the specifically, probabil gives possible set data is the defined of of observed any by the ity getting probability model sume is the opposite: we as and the parameters. MCMC a set of pos a given dataset, and we are producing a in that of ac This is done fashion the probability such that we have that we have sible parameters. a parameter to the probability that this is identical value cepting our im in the data. value has actually produced Specifically, parameter we use the classic (MH) sampler to Metropolis-Hastings plementation, see an to MCMC and introduction do MCMC (for Metropolis-Hastings, and Greenberg [1995]). InMH, one starts with arbi a random change values. Every iteration one proposes trary parameters a our case is This iswhat the of small Gaussian (in parameters. change) for example called cepted * Accept Chib this change the proposal distribution. Subsequently, or rejected. The probability is: of acceptance = min T is either ac I p(data new_parameters) 1/ -T7?1-:-:?7 (*) I L p(data previous_parameters) | from the cor is actually sampling It is easy to prove that this procedure over the parameter values. MCMC rect posterior distribution algo In the first rithms go through two different stage, the sampler stages. of the data in terms of the pa to a probable converges interpretation in stage is called burn-in, and took about 500 iterations our case. Within increased dramati these 500 iterations, probabilities a stable high level. Afterward, the MCMC to and then converged cally three runs, Over of relevant the space parameters. explores algorithm we took 10,000 samples per run after the end of burn-in. To avoid the au rameters. This Cyclical Budgetary Policy and Economic Growth 275 aMarkov chain, we only retain to the final estimates. compute samples From these three runs, we thus get a total of 300 essentially uncorrected we wish to estimate. Conver samples for each of the three parameters that typically characterizes in order every 100 iterations tocorrelation chain was gence of the Markov the across-chain correlation with the within-chain comparing From these 300 samples, correlation. and variances estimate means of the three parame we can then directly ters of interest. In order growth in our second-stage the value of the cyclicality assessed on of cyclicality to not determine regressions, only (alit), but also the uncertainty we have about to correctly infer the effect we need in other words, the standard devia to consider the relevant is necessary it. To estimate this uncertainty?or tion of the cyclicality estimates?it sources Two sources are relevant in our case. One is the of uncertainty. that is filter that stems from the uncertainty represented by the Kalman finite number uncertainty of noisy observations. The other source of uncertainty is about the three parameters that are modeled the MCMC by To process. combine 4- varianceMCMC them, varianceKalman, we where use the = approximation varianceKalman denotes variancetotal the average over the 300 Kalman filter runs using the 300 samples that we retained from the MCMC estimates of the three variances. This approx correct if the variance, as estimated by the Kalman imation becomes fil variance ter, is similar over different runs of the Markov chain, which our a data. Finally, for full general statistical approximation used here can be found in Kording-Marinescu of the methods was a good description (2006). Acknowledgments is indebted to Robert Barro, who contributed abundant ad comments and editorial of vice, and to the very helpful suggestions Daron Acemoglu, Olivier Blanchard, Ken Rogoff, and Michael Wood ford. We also thank Ricardo Caballero and Anil Kashyap for their useful This work discussions. At earlier from fruitful conver stages this project benefited Tim Laurence Bacchetta, Bloch, Elie Cohen, Philippe Besley, Romain and our col Moutot, Ranciere, Jean Pisani-Ferry, sations with Philippe in the Institutions, leagues Organizations Canadian Institute for Advanced Research. group at the are very grateful to Ann and re Anne-Laure for Helfman, Kolev, Julian Piganeau outstanding we search assistance. thank Konrad for his collabora Finally, Kording tion on the first-stage analysis section, and more for helping specifically, us implement the MCMC methodology. and Growth We 276 Aghion and Marinescu Endnotes in an Lucas (1987) analyzes costs of income volatility the welfare rate as given. for individual insurance, complete markets taking the growth in an and Phelan the welfare from countercyclical (1994) analyze policy gains with insurance markets but no growth. Both find very small effects incomplete 1. For example, with ity (or of countercyclical 2. As at aimed policies out by several authors, come that may pointed problem endogeneity sales and investment. economy Atkeson economy of volatil it) on welfare. reducing results may be biased because of an simultaneous determination of some of these from the potential and Cette Berman, (BEAAC) check the Eymard, Aghion, Askenazy, rate ex in sales by an exchange of their results by instrumenting the variation on rate variations and firms' export status. This variable, which posure depends exchange sales variation without is strongly correlated with variable by investment being affected decisions. Their results are robust to this instrumentation. robustness in an economy increase aggregate sub intervention government might efficiency to been out Holmstrom and shocks has credit constraints already by ject aggregate pointed to explore po in this section may be seen as a first attempt and Tirole (1998). Our analysis and public idea for between tential empirical of this the relationship implications growth over the cycle. spending 3. That 4. There is most is also likely ning a budget fore minimizes by by Talvi the paper to generate and Vegh procyclical pressures surplus generates political that surplus and becomes a volatile and output, (2000), who government output volatility is that run hypothesis the government there The spending. to spend more: procyclical. a volatile tax base. therefore that high argue This movement is then accentuated no in our analysis. However, sig they typically have are less widely as our in Moreover, they sample. growth the available restricts of interest, their use considerably than our main variables available not to use these indi We to have therefore decided estimates. less leading precise sample, cators in the results reported here. 5. We have nificant also used effect these in parentheses 6. Codes indicators on GDP over Data is available scribers 7. Data the names indicate at www.oecd.org. to that service. from Ross downloadable time of variables in the dataset. can be downloaded Levine's home page, from http/ Full documentation for sub sourceoecd.org /: www.econ.brow.edu/fac/ Ross_Levine/Publications.htm. involves are The adjustment for the German reunification. level variables adjusted 1991 in the ten years before of interest on time and a constant each variable regressing use the estimated to predict the coefficients (data based on West Germany only). We then in values ratio between actual and predicted values for 1991 to 2000. We take the average 1991. the years 1991 to 2000. We use this ratio to proportionally adjust values before 8. All in the countercyclicality effect of a decrease at high enough levels of financial development, more and spending. efficient private borrowing 9. The of public deficit could become negative out crowds if the government's deficit as a measure of structural constant a2it can be interpreted to the part of budget deficit it corresponds by construction the business cycle. 10. The deed, upon In practice, we ing this smoothing 11. chose value a value slightly of 5 for a. While does this choice not qualitatively affect budgetary that does is somewhat the results. deficit: in not depend arbitrary, chang Cyclical Budgetary Policy and Economic Growth 277 12. This is reasonable, since the OECD in our sample countries share similar assumption and degrees of economic this assumption is similar Moreover, development. no across a to assuming heteroskedasticity panels when estimating panel regression, is the standard which variances would assuming assumption. Finally, country-specific institutions make estimates observations more much would have due to the fact that our relatively imprecise, to be used to identify many more parameters. 1 for more 13. See appendix on the implementation details small number of of this method. to use maximum 14. It is indeed also possible to estimate methods the likelihood-type but these are precisely liable to get stuck in local solutions. In a previous version variances, so that it does not of this paper, we used such amethod, amended get stuck systematically in a local solution. are that method In practice, the estimates of the coefficients correlated with the ones obtained here highly we had obtained ajit using MCMC. using on the future, inasmuch as their variance us coefficients also depend is calculated of available observations. the GDP because Moreover, gap is con ing the full sample an HP filter, future GDP structed trend GDP as computed re is also partially using by on the GDP gap. in the coefficients flected in the GDP gap and hence 15. The 16. As mentioned earlier, using ICRG indicators variable takes a value dummy and 0 for all the other countries. turns out not to be of interest 17. This of 1 for all countries EMU, This years, so that the countries many fore the EMU is fully effective. that would but 20. The funds, Sapir supervised 1,we replaced the EMU eventually have in equation 19. 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