do government purchases a ect unemployment? · do government purchases a ect unemployment? steinar...
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Do government purchases affect unemployment?
Steinar Holden and Victoria Sparrman∗
University of Oslo, Department of Economics
November 29, 2012
Abstract
We investigate empirically the effect of government purchases on unemployment in20 OECD countries, for the period 1980-2007. Compared to most earlier studies weuse a more extensive data set, which allows for controlling for a host of factors thatinfluence the effect of government purchases. We find that increased government pur-chases lead to lower unemployment; an increase equal to one percent of GDP reducesunemployment by about 0.3 percentage point in the same year. The effect is greaterin downturns than in booms, and also greater under a fixed exchange rate regime thanunder a floating regime. The effect on unemployment reflects a corresponding positiveeffect of increased government purchases on the employment to population rate.
Keywords: Fiscal policy, unemploymentJEL codes: E62, H3
1 Introduction
During the financial crisis, most OECD countries used fiscal measures extensively to stim-ulate the economy. More recently, increasing public debt and rising default premia onsovereign debt have led to substantial fiscal tightening in many countries. At the sametime, unemployment has soared in many OECD countries. The large changes in fiscal pol-icy and unemployment rates raise the question of how fiscal policy affects unemployment,irrespective of what the motivation for the policy is. This paper explores an importantpart of the fiscal policy, the effect of a change in government purchases of goods andservices on aggregate unemployment.
The effect of fiscal policy on the economy has been subject to considerable interestin the recent years, cf. surveys in Auerbach et al. (2010), Perotti (2007), Beetsma andGiuliodori (2010), Hall (2009) and Ramey (2011). The bulk of this literature has dealtwith the effect of fiscal policy on GDP, while the literature exploring the effect on unem-ployment is much more limited. The distinction between GDP and unemployment is notunimportant: While more output in general requires higher employment and thus lowerunemployment, there are other effects that make the link between GDP and unemploymentless clear. Fiscal actions that lead to increased labour supply may increase unemploymenteven if output grows. Alternatively, if increased public spending crowds out private sectoroutput, and productivity is higher in the private sector, unemployment may fall even if
∗We are grateful to Roel Beetsma, Francesco Furlanetto, Hasem Pesaran, Ragnar Nymoen and FredrikWulfsberg as well as participants at presentations at the BI Norwegian Business School, the GRASP-ESOP workshop and Statistics Norway for comments and discussions. The numerical results in this paperwere obtained by use of OxMetrics 6/PcGive 13 and Stata 12. The paper was started within the projectDemand, unemployment and inflation financed by the Research Council of Norway. The paper is partof the research activities at the centre of Equality, Social Organization, and Performance (ESOP) at theDepartment of Economics at the University of Oslo. ESOP is supported by the Research Council ofNorway.
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aggregate output goes down. This ambiguity is reflected in recent research: While Mona-celli et al. (2010), IMF (2010)) and Ramey (2012) conclude that an increase in governmentpurchases lead to lower unemployment, Bruckner and Pappa (2012) find that increasedgovernment purchases lead to higher unemployment due to increased labour force partici-pation. In the current setting, when unemployment is high on the policy agenda, it seemspertinent with more research on the effect of fiscal policy.
Our study differs from most of the previous studies along several dimensions. First, weuse an extensive panel data set for 20 OECD countries for the period 1980-2007 (some ofthe analysis also includes 1960-1979), which makes it possible to explore whether the effectof fiscal policy depends on a host of other factors, like the cyclical situation of the economy,the type of fiscal impulse, etc. A number of recent papers argue that the effect of fiscalpolicy depends crucially on the possible monetary response (e.g. Eggertson and Woodford(2003), Coenen et al. (2010) and Hall (2009)); we explore this idea by considering how theeffect differs across monetary regimes. Second, we draw upon a large literature, associatedwith among others Layard et al. (1991) and Nickell et al. (2005), which has documented theimportance of labour market institutions for the evolution of the rate of unemployment.Our analysis builds on this literature, investigating the effect of fiscal policy in a regressionframework, controlling for other explanatory variables, including institutions in the labourmarket. This also allows us to explore whether the effect of fiscal policy depends on labourmarket institutions (which we find that it does).
We find that an increase in government purchases equal to one percent of GDP leadsto a reduction in unemployment of about 0.3, irrespective of whether we use fixed effectsor IV estimation. The effect increases somewhat in year 2, for then to decrease graduallyand vanish after 10 years. The size of the effect is highly dependent on other factors in theeconomy. We find that the change in unemployment due to a rise in government purchasesis countercyclical, being greater when the economy is in a downturn; this is consistent withthe recent findings of Auerbach and Gorodnichenko (2012) and Nakamura and Steinsson(2012). Furthermore, we find a strong effect of fiscal policy on unemployment in countrieswith a fixed exchange rate, but less or no effect for countries with a floating exchange rate.This is consistent with recent research mentioned above, arguing that fiscal policy mayhave a strong impact on the economy in situations when the monetary policy is constrained(see e.g. Coenen et al. (2010), Christiano and Rebelo (2011) and Woodford (2011)).We also find a positive effect of increased government purchases on the employment topopulation rate, which corresponds to the negative effect on unemployment. The effecton employment is stronger when the economy is in a recession than a boom.
The rest of the paper is organized as follows. In section 2 we provide a brief review ofthe theoretical and empirical literature on the effect of fiscal policy on GDP and unem-ployment. Section 3 presents our empirical specification, while the empirical results arelaid out in section 4. Section 5 concludes. The data is described in the data appendix.
2 The effect of fiscal policy on unemployment - a compari-son with the literature
Most of the literature on the effect of fiscal policy focuses on the effect on GDP, seesurveys referred to above. While there is large variation in the findings, most studies findthat increased government spending has a positive impact on GDP, even if the size ofthe effect may vary considerably depending on the specific circumstances. The effect onunemployment is clearly linked to the effect on GDP, as one would expect an increasein output to be associated with higher employment. However, as fiscal policy is alsolikely to affect labour supply, a rise in employment may not lead to lower unemployment.Furthermore, if increased public spending crowds out production in the private sector, and
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productivity is higher in the private sector, employment may increase (and unemploymentfall), even if the impact on GDP is small. In this brief review we will focus on the effect onunemployment and employment to save space. However, in the discussion of the empiricalresults below, we will also compare with related studies focussing on the effect on GDP.
An early study is Holmlund and Linden (1993), who explore the effects of public em-ployment in a calibrated search model. They find ambiguous effects on unemployment,as increased wage pressure may counteract the direct unemployment-reducing effect ofincreased public employment. More recently, Michaillat (2012) analyzes a general equi-librium search model where increased public employment leads to lower unemployment.Monacelli et al. (2010) explore the effect of government consumption in a neoclassicalmodel augmented with search and matching frictions. They show that while higher gov-ernment consumption increases the hiring rate due to the negative wealth effect inducinghigher labour supply, this effect is dampened by the rise in the real interest rate. Overall,the effect of an increase in government spending equal to one percent of GDP leads to areduction in the rate of unemployment of 0.2 percentage points. Their empirical study,which is a structural VAR analysis on US data, shows a larger effect of 0.6 percentagepoints. Ramey (2012) also finds that higher public purchases leads to lower unemploy-ment, using structural and expectational VAR analyses on US data. In contrast, Brucknerand Pappa (2012), in an analysis of 10 OECD countries using structural VARs, find thathigher government expenditures increases the unemployment rate. Bruckner and Pappa(2012) explain the difference in results compared to Monacelli et al. (2010) as due todifferent sample period, arguing that the increased government spending raises unemploy-ment after 1975. Note however that Bruckner and Pappa (2012) also find that increasedgovernment spending leads to higher GDP and higher employment, so that the increasein unemployment is caused by higher participation rates due to increased labour supply.Pappa (2009) and Linnemann (2009) also find that increased public employment leads toincreased total employment.
An important methodological problem in an analysis of the effects of fiscal policy isthat the policy potentially is endogenous, by depending on the state of the economy.In the literature, this is typically handled either by focussing on the effect of specificevents that can be thought to be exogenous, such as changes in military spending ina response to political changes (e.g. Ramey and Shapiro (1999) and Eichenbaum andFisher (2005)), or by use of a structural vector autoregression (SVAR) model, where themodel explains several macroeconomic variables by their lags and exogenous shocks to thevariables in the model, see e.g. Blanchard and Perotti (2002), Fatas and Mihov (2001),Beetsma and Giuliodori (2010) and Monacelli et al. (2010). Both these methods have clearadvantages when it comes to dealing with endogenity. However, the methods also havetheir weaknesses, see Monacelli et al. (2010) and Auerbach et al. (2010). For the specificevents approach, it may be asked whether these events also affect the economy directly,implying that one does not detect the true effect of the policy. For the SVAR approach,there are concerns whether the fiscal shocks identified in the analysis might be anticipatedby the private sector in advance, which would cause problems in the interpretation. Morerecently, a number of studies analyze the effect of fiscal policy within structural modelsused for macro policymaking, typically of the Dynamic Stochastic General Equilibrium(DSGE) type, see e.g. Coenen et al. (2010); however, the findings in these studies hingeon whether the model is appropriate, which is a matter that is still open for discussion,cf. e.g. Chari et al. (2009) and Caballero (2010). This is a clear argument for also tryingother approaches.
We consider the effect of a change in government purchases on unemployment and em-ployment, building on a panel data estimation framework derived by Nymoen and Spar-rman (2012). More specifically, we add the real change in government purchases (scaledby the share of trend-GDP), to an empirical equation for aggregate unemployment as a
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function of a number of labour market institutions. This approach has several advantages.First, an extensive literature has shown that aggregate unemployment to a large extent isdetermined by labour market institutions, see e.g. Layard et al. (1991) and Nickell et al.(2005). Thus, it seems appropriate to control for the effect of labour market variableswhen analysing the effect of fiscal policy and investigate if the effect of the fiscal policydepends on the prevailing labour market institutions. Second, with a data set covering 20countries and 27 years, there is large variation in a number of other key variables, makingit possible to explore how the effect of fiscal policy may vary depending on for instancethe monetary regime, the cyclical state of the economy, or the size of the public debt.
Our focus on the effect of government purchases (that is, government consumption andinvestment, which includes expenditure on public employment but not transfers) mitigatesthe endogeneity problem considerably. We do not consider tax revenues and expenditureson transfers, which clearly are endogenous, following changes in the economy accordingto rules and legislation. We also exclude all “passive” unemployment expenditure like un-employment benefits, and the large majority of active unemployment related expenditure,which are classified as transfers, not government purchases. In contrast, government pur-chases are not directly linked to the state of the economy. Clearly, the state of the economyalso affects purchase decisions, but also other factors come into play, like electoral cycles,party politics, lobbyism and pressure groups, media attention, etc. Furthermore, a largepart of government purchases may be subject to a lengthy bureaucratic process involvingboth the decision making and the implementation, implying that there is no clear cut orsimple relationship between the state of the economy and government purchases.
Even if we believe that the endogeneity problem is less important than for other typesof fiscal policy, we nevertheless undertake two different analyses to handle it. First, we useinstrumental variable estimation, where we treat the measure of fiscal policy as endoge-nous, and instrument with past values of the change in government purchases and pastvalues of government debt. Second, we use an omitted variables approach. The idea hereis that fiscal policy might be correlated with the error term because it is affected by otherexplanatory variables that also affect unemployment. By including the omitted variables,the potential bias will be reduced or removed, cf. discussion below.
From a theoretical perspective, one would expect the effect of an increase in governmentspending to depend on whether it is tax-financed or debt-financed. However, to distinguishbetween these two alternatives one must be able to differentiate between tax changesinduced by changes in the economy and tax changes linked to the financing of publicexpenditure. Given the identification problems that are involved, we have chosen not todo this at this stage. Thus, our results must be interpreted as an average effect, wherethe weights depend on the average method of financing over the sample period. In mostcountries both taxes and government debt have increased somewhat relative to GDP overthe sample period, suggesting that the increase in government spending is partly tax-financed and partly debt-financed.
3 Empirical Specification
We want to find the effect of a change in government purchases on the rate of unemploy-ment. However, the size of the public sector varies considerably relative to GDP, bothacross countries and over time within a single country, thus we multiply the real changein the government purchases with government purchases as a share of trend of GDP, seeappendix A for details and calculations. Clearly, if government purchases increase by 5percent, it matters whether public purchases constitute 16 percent of GDP, as in Spain in1980, or 33 percent of GDP, as in Sweden in 1982. An alternative would be to consider thechange in government purchases as a share of GDP, as is done in some studies (e.g. Alesina
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and Ardagna (2009), Duell et al. (2009)). Yet this specification implies that a reductionin GDP caused by a negative external shock, increases the ratio of government purchasesto GDP, even if government purchases is kept constant. Thus, one might erroneouslyconclude that government purchases have a negative effect on GDP. For this reason wealso use a backward-looking measure of trend GDP, where the trend real growth is mea-sured as the moving average of the growth rate over the past ten years. With a two-sidedmeasure of trend-growth, there would be a risk that the future evolution of GDP affectsthe estimated trend-GDP, implying a possibility that the future evolution of GDP affectsthe measure of contemporaneous fiscal policy.
To improve the precision of our estimates, we want to control for other variablesthat may affect unemployment. First, we include an indicator for the export market,captured by the cyclical state of the economy of the trading partners. More specifically,the indicator is calculated as a weighted average of the GDP-gap of the trading partners,where the GDP-gap is the deviation of GDP from Hodrick Prescott-trend, divided by thetrend, and the weights reflect the share of the exports from country i that goes to each ofthe trading partners j. This variable will to a large extent capture the effect of commonshocks related to the world business cycle. Second, as argued above, we include labourmarket institutions. More specifically, we include the change in government purchasesand the export market in the unemployment equation derived in Nymoen and Sparrman(2012), which in accordance with Layard et al. (1991) and Nickell et al. (2005), is a functionof labour market institutions and shocks. Thus, in our main estimations, we estimate anequation of the following form
uit =β0i + β1uit−1 + β2uit−2 + β3uit−3 + β4∆Iit−1 + β5Iit−2
+ β6dGit + β7∆XMit + β8XMit−1 + β8∆XMit−1 + εit (1)
where uit is the unemployment rate in country i in period t, dGit is the real percentagechange in government purchases, multiplied by the ratio of government purchases to trendGDP, XMit is the export market indicator, and Iit−1 is a vector of institutional labourmarket variables which includes unemployment benefits, employment protection legisla-tion, measures of coordination and centralization of wage setting. The dynamic structurefollows from the theoretical labour market framework of Nymoen and Sparrman (2012),where the institutional variables affect the wage and price setting, which subsequentlyshape the evolution of unemployment. The specification in equation (1), with the levelof unemployment and the change in government purchases, reflects how we would ex-pect these two variables to behave in growing economies: Government purchases increaseover time, while unemployment and the change in government purchases are essentiallystationary variables. This presumption is consistent with results from stationarity tests.In table 1, column 1, we report results from Dickey-Fuller tests for a unit root in thelevel of government purchases, considering both homogeneous and heterogeneous autore-gressive parameters across countries, and with several different specifications concerninglags and subtraction of cross-sectional means prior to undertaking the tests, see Matyasand Sevestre (2008). Non-stationarity is not rejected in any of the tests. Correspondingtests reject non-stationarity of the level of unemployment and the change in governmentpurchases (except for the homogeneous alternative with three lags), indicating that thesevariables are stationary, cf table 1, columns 2 and 3.1
In most of the analysis, we use a Fixed Effects (FE) estimator, allowing for permanentcountry-specific differences in unemployment that are not accounted for by the other
1For the growth in government purchases, the test of unit root with lag 3 is not significant. However,as the third lag of the growth in government purchases is not significant, this test is less important.
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Table 1: Unit root test for government purchases, growth in government purchases andunemployment
(Git −Gt)a (dGit − dGt)
b (Uit − U t)c
Homogeneous Heterogenous Homogeneous Heterogenous Homogeneous HeterogenousH1a H1b H1a H1b H1a H1b
lag 1d 8.86 (1.00) 9.54 (1.00) -6.54 (0.00) -7.69 (0.00) -4.19 (0.00) -3.29 (0.00)lag 2d 9.69 (1.00) 8.85 (1.00) -2.22 (0.01) -4.62 (0.00) -2.43 (0.00) -2.20 (0.01)lag 3d 5.71 (1.00) 3.66 (1.00) -0.25 (0.40) -3.09 (0.00) -3.37 (0.00) -2.12 (0.01)
Obs 560 560 560 560 560 560
In these tests, the variables for Germany are prolonged with data for West-Germany before the unionization in 1991 to achieve a balanced panel.
a) Change govt. purchases (Gt) subtracted cross-sectional means (Gt). Trend and country specific constant terms
are included in all the tests.
b) Change growth in govt. purchases (dGt) subtracted cross-sectional means (dGt).
c) Change unemployment (Ut) subtracted cross-sectional means (U t).
d) Numbers in parentheses are p-values for the relevant null.
explanatory variables. A random effect model would require that there is no correlationbetween the country fixed effects and the explanatory variables in the model. However,this assumption is rejected in a Hausman test with a p-value of 1 percent. In principle,the FE estimator is biased when the regression includes a lagged endogenous variable, seeNickell (1981). However, with a long time dimension of 27 years, this bias is small, cf.Judson and Owen (1999). In addition, other estimations methods which avoid the samplebias also have their difficulties, cf. Roodman (2009).
The model is estimated on annual frequency, using data from OECD Economic Out-look, see data appendix. Annual data has the advantage of a allowing a much longertime span (we also undertake some estimations including the 1960s and 70s, and very fewcountries have quarterly data for the fiscal policy for this period). Furthermore, annualdata may capture the actual fiscal decisions better, as the fiscal impulses are likely tofollow annual budgets, as well as mitigating possible anticipation effects, see discussion inBeetsma and Giuliodori (2010).
The growth in government purchases has generally been positive in real terms in thesample period, and the unweighted decade averages in our sample vary in the interval0.52 − 0.74. There is however considerable variation within and across countries, seeappendix table A1.
4 Empirical results
We find that the change in government purchases has a highly significant negative impacton unemployment, the point estimate implying that an increase in government purchasesequal to one percent of GDP reduces unemployment by 0.27 percentage points, or 0.28 withtime dummies, cf table 2. (To focus on the novel variables, the coefficients for the labourmarket institutions are omitted; the complete results are found in the appendix, table B1).The export market variables also have a significant negative effect on unemployment. Notethat even if the level effect of the export market variable is positive, this variable is basedon GDP-gaps and thus by construction only positive in a limited number of years in arow. Simulation exercises show that the overall effect of the export market is dominated bythe strongly negative impact effect throughout the estimation period (results are availableon request). The effect of the export market variables is smaller with year dummies,and the level effect insignificant, suggesting that the export market variables without timedummies also capture the effect of common shocks that affect most or all OECD countries.Figure 1 shows the estimated residuals of the fixed effects model without time dummiesin table 2, and there is little indication of autocorrelation, even if there is some variation
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Table 2: Estimation of equation (1) - Fixed Effects
FE FE with time dummiesCoef. Std p-value Coef. Std p-value
Unemployment previous period 1.34 0.08 0.00 1.37 0.07 0.00Unemployment two years ago -0.57 0.10 0.00 -0.61 0.10 0.00Unemployment three years ago 0.04 0.05 0.43 0.07 0.05 0.15Demand components:Export market, 1st diff. (∆XMt) -0.48 0.10 0.00 -0.39 0.14 0.01Export market, prev. period (XMt−1) 0.17 0.08 0.04 0.05 0.13 0.69Export market, 1st diff. prev. period (∆XMt−1) -0.18 0.08 0.03 -0.07 0.12 0.56Change govt. purchases (dGt) -0.27 0.08 0.00 -0.28 0.08 0.00
Obs = Country*Average groups 483 20 24.1 483 20 24.1Standard deviation of residuals 0.63 0.59χ2 of policy and exports.a 107.61 (0.00) 68.73 (0.00)1st order autocorrelationa 1.50 (0.13) 1.34 (0.18)2nd order autocorrelationa -1.74 (0.08) -1.74 (0.08)
Dependent variable: The unemployment rate.
Estimation method: Fixed effect coeffcients estimate with huber-robust standard error (Stata command xtreg
with cluster(code) is used in all the regressions. It is also controlled for labour market institutions.
a) Numbers in parentheses are p-values for the relevant null.
across countries. The tests reported in the lower part of table 2 do not indicate any firstand second autocorrelation.
Figure 2 shows the dynamic effect on unemployment from a permanent increase ingovernment purchases equal to one percent of trend GDP. The maximum impact of −0.34percentage points is reached in the second year, then the effect weakens gradually to bealmost negligible after 10 years. This effect is somewhat larger than the findings in IMF(2010), based on a study of fiscal consolidations in 15 OECD countries over the last 30years. They find that spending-based deficit cuts equal to one percent of GDP raise theunemployment rate of about 0.2 percentage points. Monacelli et al. (2010) find a largereffect on US data; an increase in government spending equal to one percent of GDP leadsto a fall in the rate of unemployment of 0.6 percentage points after ten quarters. Incontrast, Bruckner and Pappa (2012) find in an analysis of 10 OECD countries usingstructural VARs, that a typical estimate from the impulse responses implies that a 10percent increase in government expenditures increases the unemployment rate at peak(which varies from 3− 16 quarters) of around 0.2− 0.5 percent.
4.1 Endogeneity
As noted above, the estimated coefficient of government purchases will be biased if gov-ernment purchases also react to changes in the state of the economy that are correlatedwith the rate of unemployment. One way to deal with this problem is to find instrumentsthat are uncorrelated with the error term and correlated with the change in governmentpurchases. We use the lagged first difference of the change in government purchases, aswell as the lagged ratio of public debt to GDP.
As shown in Table 3, there is a fairly strong and significant correlation between thechange in government purchases and the instrumental variables. The F-test statistic foradditional instruments is equal to 24, with a p-value of 0. Note that while our results inTable 2 imply that the lagged change in government purchases is correlated with laggedunemployment, the fact that lagged unemployment is also included in the equation impliesthat lagged government purchases may well be a valid instrument. We have also triedelection year, based on the idea that governments may pursue an expansionary fiscalpolicy in connection with elections to increase the probability of reelection; see evidence
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-2-1
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1980 1990 2000 2007
AUS: Australia
Residuals FE-model robust std. errors Residuals FE-model robust std. errors and time dummies
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AUT: Austria
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BEL: Belgium
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CAN: Canada
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DNK: Denmark
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FRA: France
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DEU: Germany
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IRL: Ireland
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ITA: Italy
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JPN: Japan
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NLD: Netherlands
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NOR: Norway
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NZL: New Zealand
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PRT: Portugal
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ESP: Spain
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CHE: Switzerland
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GBR: United Kingdom
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USA: United States
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Time
Figure 1: Estimated residuals of fixed effect model in table 2
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-.4
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0
2007 2009 2011 2013 2015 2017 2019 2021 2023 2025 2027 2029year
Dynamic simulation of U, fixed effects
Simulated unemployment rate with a one percent perm. increase in govt. purchase
Figure 2: The effect of a permanent increase in government purchases, equal to one percentof GDP, from 2008, based on simulation of equation (1) with estimated coefficients fromthe FE model in table 2
in Shi and Svensson (2006). However, including election year did not affect the result, andas election year is potentially endogenous in countries where the government can choosethe time of the election, we decided to leave it out in the presented specification.
Column 1 in Table 4 shows the results of the instrumental variable estimation. Thepoint estimate indicates that an increase in government purchases equal to one percent ofGDP reduces unemployment by 0.31 percentage points, i.e. close to the effect from the FEestimates. The effect is also highly statistically significant. Thus, there is no indicationthat government purchases is endogenous. The Hausman test statistics is equal to 5.88which does not reject that the residuals are uncorrelated with the error term. The HansenJ overidentification test has a p-value of 0.31, giving no indication of invalid instruments.Note however that these tests have limited power, and the Hansen J-test assumes thatat least one instrument is valid. Thus, we choose to present both FE and IV estimationsbelow.
For robustness, we also try another method, where we control for omitted variables.The idea behind this method is that fiscal policy might be correlated with the error termbecause it is affected by other explanatory variables that are excluded from the regressionand that also are correlated with unemployment. This would be the case if fiscal policy iseither pro- or counter-cyclical. Fiscal policy might be pro-cyclical if higher tax revenues ina boom cause politicians to spend more money; this effect is termed the voracity effect byTornell and Lane (1999). At the same time, the increase in tax revenues during the boommight be correlated with a fall in unemployment. In this case, including tax revenues asa regressor in the unemployment equation would lend government purchases uncorrelatedwith the error term, removing the bias in the coefficient. As the government purchasesare typically decided in the budget process in the fall the year prior to the budget year, itwould be the expectations that prevail when the budget is decided that might affect thebudget. We use predicted tax revenues as a proxy for expected tax revenues, where theprediction is based on a regression with two lags of tax revenues, two lags of the change inreal GDP as well as the output gap, as explanatory variables. Thus, in table 4 we include
9
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Table 3: First stage estimation
First Stage regressionCoef. Std p-value
Unemployment previous period -0.11 0.04 0.01Unemployment two years ago 0.10 0.07 0.12Unemployment three years ago 0.02 0.04 0.51Demand components:Export market, 1st diff. (∆XMt) -0.04 0.10 0.67Export market, prev. period (XMt−1) 0.18 0.07 0.01Export market, 1st diff. prev. period (∆XMt−1) -0.08 0.10 0.42Instruments:Change govt. spending, 1st diff. prev. period (∆dGt−1) 0.13 0.06 0.04Debt previous period -0.01 0.00 0.00
Observations 440F-test of additional instruments, p-value in parenthesis 24 (0.00)
Dependent variable: The change in goverment spending. It is also controlled for labour market institutions.
First stage IV-regression of change in govt. spending (Stata command xtivreg2, see Baum et al. (2002))
the predicted change in tax revenues as a share of trend GDP to capture that higherrevenues might lead to increased government purchases. Alternatively, fiscal policy mightbe countercyclical if the government attempts to use fiscal policy to stabilize the economy.In this case one would expect an increase in government purchases in downturns, whenGDP growth is low, or the output gap is negative. To control for this, we also includeGDP growth and the change in the output gap, both lagged, in table 4.
We observe that the estimated effect of government purchases is somewhat smallerwhen we include the additional explanatory variables in model 2 in table 4, but it is stillstatistically significant. This lends considerable support to the robustness of this effect, asboth the lagged GDP growth and the output gap are variables that are strongly correlatedwith unemployment. Note however that some of the export market variables are no longersignificant. This emphasizes that including lagged GDP growth and lagged output gapentails a strong test of the explanatory power of the variables.
In model 3 in table 4, we control for the possible endogeneity of government purchasesin a somewhat different way, by also including consensus forecast for GDP growth, un-employment and the output gap. (In this regression, the sample is reduced because theforecasts are only available from 1997.) Again, one might conjecture that governmentpurchases would respond to such forecasts, and that the correlation we find between gov-ernment purchases and unemployment is due to both variables being correlated with theforecasts. However, we see that the change in government purchases has a significantnegative impact on unemployment, even when controlling for forecasts.
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Tab
le4:
Equ
atio
n(1
):IV
and
FE
wit
hco
ntr
olfo
rom
itte
dva
riab
les
IVa
Model
2b
Model
3b
Coef
.S
tdp-v
alue
Coef
.Std
p-v
alue
Coef
.Std
p-v
alu
e
Changegovt.
purchases,
(dG
t)-0
.32
0.1
50.
04-0
.20
0.08
0.01
-0.2
00.
100.
05U
nem
plo
ym
ent
pre
vio
us
per
iod
1.37
0.07
0.0
01.
160.
090.
001.
060.
100.0
0U
nem
plo
ym
ent
two
year
sag
o-0
.62
0.09
0.00
-0.3
80.
110.0
0-0
.36
0.1
20.0
0U
nem
plo
ym
ent
thre
eye
ars
ago
0.06
0.04
0.1
50.
030.
050.
470.
090.
060.1
5Export
mark
et:
Exp
ort
mar
ket,
1st
diff
.(∆XM
t)-0
.45
0.08
0.0
0-0
.50
0.10
0.0
0-0
.40
0.1
40.
00E
xp
ort
mar
ket,
pre
v.
per
iod
(XM
t−1)
0.22
0.09
0.01
0.10
0.08
0.25
-0.0
20.
180.9
0E
xp
ort
mar
ket,
1st
diff
.pre
v.
per
iod
(∆XM
t−1)
-0.2
00.
100.
04-0
.05
0.12
0.6
50.
050.
140.
72Controls:
Log
GD
P1s
td
iff.
pre
v.
per
iod
-25.
756.7
40.
00
-22.
9113.8
00.1
0O
utp
utg
ap1s
td
iff.
pre
v.
per
iod
0.13
0.09
0.17
0.03
0.1
30.
81P
redic
ted
Dir
ect
and
indir
ect
taxes
div
ided
by
tren
dG
DP
,1s
tdiff
.0.0
10.
030.7
90.
050.1
60.7
6P
redic
ted
Dir
ect
and
indir
ect
taxes
div
ided
by
tren
dG
DP
,1s
tdiff
.p
rev.
per
iod
-0.0
20.0
70.
810.1
10.1
70.5
3Y
ear t−1
fore
cast
ofG
DP
grow
thyea
rt
0.01
0.08
0.8
8Y
ear t−1
fore
cast
ofou
tput
gap
yeart
-0.0
40.1
00.6
7Y
ear t−1
fore
cast
ofu
nem
plo
ym
ent
yea
rt
-0.1
40.0
70.0
4Y
ear t−1
fore
cast
ofG
DP
grow
thyea
rt
+1
0.00
0.10
0.9
8Y
ear t−1
fore
cast
ofou
tput
gap
yeart
+1
0.10
0.1
20.
40Y
ear t−1
fore
cast
ofu
nem
plo
ym
ent
yea
rt
+1
0.14
0.0
70.0
4
Obs
=C
ountr
y*A
vera
ge
grou
ps
440
2022.
046
420
23.2
207
20
10.
4Sta
ndar
ddev
iati
onof
resi
du
als
0.58
0.60
0.39
F-t
est
ofad
dit
ional
inst
rum
ents
.24
(0.0
0)χ2
ofp
olic
yan
dex
port
s.c
69.
45(0
.00)
25.
74(0
.00)
1st
order
auto
corr
elat
ionc
2.13
(0.0
3)
-2.9
3(0
.00)
2nd
order
auto
corr
elat
ionc
-1.4
7(0
.14)
1.31
(0.1
9)
Han
sen
JO
veri
den
tifi
cati
onte
stc
1.02
(0.3
1)
Dep
enden
tva
riable
:T
he
unem
plo
ym
ent
rate
.In
all
equati
ons
itis
als
oco
ntr
olled
for
lab
our
mark
etin
stit
uti
ons.
a)
Sta
taco
mm
and
xti
vre
g2,
see
Baum
etal.
(2002).
Change
gov
t.purc
hase
s(dG
t)
istr
eate
das
endogen
ous.
Inst
rum
ents
are
:∆dG
t−1
anddebt t
−1.
b)
Fix
edeff
ect
coeffi
cien
tses
tim
ate
.H
ub
er-r
obust
standard
erro
r(Sta
taco
mm
and
xtr
egw
ith
clust
er(c
ode)
.
c)N
um
ber
sin
pare
nth
esis
are
p-v
alu
esfo
rth
ere
leva
nt
null.
11
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4.2 Cyclical effects and variation over time
An important question from a policy perspective is whether the effect of governmentpurchases varies over the business cycle. We measure the cyclical situation of the economyby use of the output gap as measured by the OECD.
In the first column in table 5, we extend equation (1) by including the interactionbetween the output gap and the change in government purchases, the latter measured asdeviation from the country-specific mean, to ensure that the variable has a mean of zero.The interaction term is strongly significant, with positive sign, implying that an increase ingovernment purchases leads to a larger reduction in unemployment in bad times when theoutput gap is negative than in good times. The estimated coefficient is equal to 0.05, whichimplies that if the output gap is negative and equal to −3 percentage point, an increasein government purchases equal to one percent of GDP will decrease unemployment by−0.17 + (−3)∗0.05 = −0.32 percentage points at impact. Note that we control for outputgap in the equation, which may reduce the estimated effect somewhat. The result isconsistent with several recent studies: Auerbach and Gorodnichenko (2012) find a largerfiscal multiplier in recessions than in expansions, using a regime-switching model on U.S.aggregate data; Nakamura and Steinsson (2012) find the same result exploiting differencesacross U.S. regions, while the IMF Fiscal Monitor 2012 reports consistent evidence forsome G7- countries. For theoretical motivation, see the discussion of Michaillat (2012) insection 4.3 below.
The systematic link between the output gap and the effect of government purchaseshas potentially vast policy interest, in particular for countries where fiscal tightening isrequired. The results in table 5 show that it matters when the fiscal tightening takes place,as the same fiscal tightening has a stronger effect on unemployment in a downturn of theeconomy. Ceteris paribus, this suggests that fiscal tightening should be postponed until theeconomy is in better shape. Taken at face value, the result suggests that countercyclicalfiscal policy may reduce the average unemployment rate over time: if the governmentpursued a countercyclical policy that were neutral over the cycle, where the increase ingovernment purchases in downturns were matched by the decrease in booms, the net effectwould, according to table 5, be a decrease in unemployment.
We then consider whether the effect of government purchases on unemployment variesover time, by allowing for a different effect for each decade, cf. model 2 in table 5: In the1960s and 70s, we find essentially no effect of government purchases on unemployment, insharp contrast to the later period. As the relationship clearly has changed significantlyafter 1980, it would be misleading to put so different decades together by imposing thesame relationship. This is the motivation for restricting attention to the time after 1980in the other regressions.
One might speculate that the absence of any effect in the 1960s reflects that unemploy-ment in almost all countries was very stable and low, not giving much room for an effectof government purchases. In contrast, in the 1970s, unemployment rose quite sharply inmost countries, and some countries tried to counteract this rise by use of expansionaryfiscal policy. Thus, there could be a downward bias in the estimate reflecting that therise in unemployment induced increased government spending, suggesting the use of IV.However, the IV results in the third model in table 5 are rather consistent with the FEresults; no effect of government purchases in the 1960s and 70s, and a negative effect forthe last three decades, although statistically significant only in the 2000s.
12
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Tab
le5:
Th
eeff
ect
ofth
ecy
clic
alsi
tuat
ion
and
chan
geov
erti
me
Model
1a
Model
2aIV
b
Coef
.Std
p-v
alu
eC
oef
.S
tdp-v
alue
Coef
.Std
p-v
alu
e
Unem
plo
ym
ent
pre
vio
us
per
iod
1.16
0.09
0.00
1.2
40.
14
0.00
1.2
80.
060.0
0U
nem
plo
ym
ent
two
year
sag
o-0
.45
0.10
0.0
0-0
.38
0.23
0.1
0-0
.46
0.09
0.0
0U
nem
plo
ym
ent
thre
eye
ars
ago
0.06
0.05
0.2
0-0
.02
0.10
0.86
-0.0
10.0
50.
82Demand
components:
Exp
ort
mar
ket,
1st
diff
.(∆XM
t)-0
.28
0.07
0.0
0-0
.48
0.08
0.00
-0.4
60.0
80.
00E
xp
ort
mar
ket,
pre
v.
per
iod
(XM
t−1)
0.28
0.07
0.00
0.16
0.0
80.0
40.
170.0
90.
04E
xp
ort
mar
ket,
1st
diff
.pre
v.
per
iod
(∆XM
t−1)
-0.2
00.
070.0
1-0
.28
0.1
20.0
2-0
.17
0.09
0.0
6C
han
gego
vt.
pu
rch
ases
(dG
t)-0
.17
0.0
70.
02
Inte
ract
ion
chan
ge
govt.
purc
has
es(dG
t−dG
t)an
dou
tput
gapYt
0.05
0.02
0.0
1O
utp
utg
apfr
omO
EC
D(Y
t)-0
.14
0.03
0.00
Chan
gego
vt.
purc
has
es(dG
t),
1960
s0.0
40.
07
0.51
0.1
20.
100.2
4C
han
gego
vt.
purc
has
es(dG
t),
1970
s0.
040.
05
0.4
00.
280.3
00.3
6C
han
gego
vt.
purc
has
es(dG
t),
1980
s-0
.33
0.15
0.03
-0.4
20.3
20.
20C
han
gego
vt.
pu
rch
ases
(dG
t),
1990
s-0
.45
0.18
0.01
-0.3
80.2
60.1
5C
han
gego
vt.
pu
rch
ases
(dG
t),
2000
s-0
.28
0.09
0.00
-0.8
10.3
50.0
2D
um
my
for
1970
s0.
250.
15
0.1
00.
230.3
00.
45D
um
my
for
1980
s0.
770.
15
0.0
01.
130.2
40.
00D
um
my
for
1990
s0.
890.
21
0.0
01.
220.2
30.
00D
um
my
for
2000
s0.
650.
20
0.0
01.
250.2
80.
00
Obs
=C
ountr
y*A
vera
ge
grou
ps
483
20
24.
180
120
40.
0626
20
31.
3Sta
ndar
ddev
iati
onof
resi
du
als
0.58
0.65
0.63
F-t
est
ofad
dit
ional
inst
rum
ents
,19
60s.cd
4(0
.00)
F-t
est
ofad
dit
ional
inst
rum
ents
,19
70s.cd
2(0
.09)
F-t
est
ofad
dit
ional
inst
rum
ents
,19
80s.cd
2(0
.07)
F-t
est
ofad
dit
ional
inst
rum
ents
,19
90s.cd
6(0
.00)
F-t
est
ofad
dit
ional
inst
rum
ents
,20
00s.cd
3(0
.00)
χ2
ofp
olic
yan
dex
por
ts.d
101
.79
(0.0
0)16
2.75
(0.0
0)
97.5
0(0
.00)
1st
order
auto
corr
elat
iond
2.81
(0.0
1)1.
15(0
.25)
2nd
order
auto
corr
elati
ond
1.57
(0.1
2)0.
44(0
.66)
Han
sen
JO
veri
den
tifi
cati
onte
std
15.
98(0
.10)
Dep
enden
tva
riable
:T
he
unem
plo
ym
ent
rate
.In
all
equati
ons
itis
als
oco
ntr
olled
for
lab
our
mark
etin
stit
uti
ons.
a)
Fix
edeff
ect
coeffi
cien
tses
tim
ate
.H
ub
er-r
obust
standard
erro
r(Sta
taco
mm
and
xtr
egw
ith
clust
er(c
ode)
.
b)
Sta
taco
mm
and
xti
vre
g2,
see
Baum
etal.
(2002).
IV:
Change
gov
t.purc
hase
s(dG
t)
istr
eate
das
endogen
ous.
Inst
rum
ents
are
:(∆
dG
t−1),
(dG
t−2),
(∆debt t
−1)
and
(debt t
−1).
c)F
irst
regre
ssio
nre
sult
sof
stata
com
mand
xti
vre
g2,
see
Baum
etal.
(2002).
d)
Num
ber
sin
pare
nth
eses
are
p-v
alu
esfo
rth
ere
leva
nt
null.
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4.3 Distinguishing between types of government purchases: investment,wage consumption and non-wage consumption
Both from a theoretical and policy perspective it is of considerable interest to explorewhether the effect of a change in government purchases differs depending of the type ofpurchase. In statistical sources, one typically distinguishes between three categories, whichwe also use in our analysis: government wage consumption, which is essentially expen-ditures on public employment, ie. employees in the public sector (dCGW ), governmentnon-wage consumption (dCGNW ) and government real investments (dIG). In our sam-ple, government wage consumption constitutes 54 percent of total government purchases,government non-wage consumption 29 percent, and government investments 17 percent(unweighted average across countries, from 1960-2007). We consider the same form of theleft hand side variable as before, i.e. the change in each of this categories (indicated by thed in the variable name), in real terms, and measured as share of trend-GDP, see appendixA for a detailed explanation.
The results are presented in table 6. Model 1 shows that increased government wageconsumption (increased public employment) has a significant negative impact on the un-employment rate, while the estimated effect of government investment is negative but notstatistically significant, and the effect of government non-wage consumption is negativebut small. Ramey (2012) also find a stronger effect on unemployment from governmentwage consumption - hiring workers - than from other parts of government purchases, whileIlzetzki et al. (2010) find about the same point estimates for the effect on GDP of con-sumption and investment for advanced countries, with multiplier estimates (the effect ofgovernment purchases on GDP) of 0.4 at impact and 0.8 in the long run. Ilzetzki et al.(2010) do not distinguish between wage and non-wage consumption.
In model 2 in table 6, we explore whether the effect of the different types of governmentpurchase depends on the cyclical state of the economy. We find a strong positive andstatistically significant interaction term for government wage consumption, implying thatincreased public employment has a stronger dampening effect on unemployment when theoutput gap is negative, consistent with our prior results. The effect is large: with an outputgap of minus 3, the coefficient is −0.55+(−3)∗0.13 = −0.94, implying that an increase ingovernment wage consumption equal to one percent of GDP reduces unemployment withalmost one percentage point at impact. The finding that an increase in government wageconsumption has a much stronger effect on unemployment in a recession is consistent withthe predictions from the dynamic stochastic general equilibrium search model of Michaillat(2012). In the search model of Michaillat (2012), increased public employment has a muchstronger effect on total employment in recessions, because there is much less crowding outof private employment. When unemployment is high, there is no shortage of unemployedworkers, implying that higher public employment has little impact on the hiring of privatefirms.
The third model in table 6 presents the result of model 1 using IV; we find that theeffect of government investment is much stronger, with a point estimate of −0.78, and ap-value of 0.06. The point estimate of wage consumption is about as in the FE estimation,−0.61, but not statistically significant.
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Tab
le6:
Th
eeff
ect
ofd
iffer
ent
typ
esof
gove
rnm
ent
pu
rch
ases
Model
1a
Model
2a
IV3b
Coef
.Std
p-v
alue
Coef
.Std
p-v
alue
Coef
.Std
p-v
alue
Unem
plo
ym
ent
pre
vio
us
per
iod
1.27
0.07
0.0
01.
040.
080.
00
1.27
0.07
0.00
Unem
plo
ym
ent
two
year
sag
o-0
.51
0.10
0.0
0-0
.36
0.08
0.0
0-0
.53
0.1
00.0
0U
nem
plo
ym
ent
thre
eye
ars
ago
0.01
0.05
0.7
80.
050.
040.1
90.
020.
050.
66Demand
components:
Exp
ort
mar
ket,
1st
diff
.(∆XM
t)-0
.43
0.11
0.0
0-0
.24
0.0
70.
00-0
.42
0.0
90.0
0E
xp
ort
mar
ket,
pre
v.
per
iod
(XM
t−1)
0.17
0.12
0.15
0.2
80.
120.0
20.
250.1
00.0
1E
xp
ort
mar
ket,
1st
diff
.pre
v.
per
iod
(∆XM
t−1)
-0.2
30.
100.0
2-0
.28
0.08
0.0
0-0
.24
0.1
10.
03C
han
gego
vt.
inve
stm
ents
,(dIG
t)-0
.13
0.08
0.1
2-0
.07
0.08
0.43
-0.7
80.
420.0
6C
han
gego
vt.
non
-wag
eco
nsu
mpti
on,
(dCGNW
t)-0
.05
0.02
0.01
-0.0
30.
020.0
9-0
.10
0.1
90.6
2C
han
gego
vt.
wag
eco
nsu
mpti
on,
(dCGW
t)-0
.68
0.20
0.0
0-0
.55
0.15
0.0
0-0
.61
0.4
80.
20In
tera
ctio
ndGI t
andYt
-0.0
10.0
40.9
0In
tera
ctio
ndCGNW
tan
dYt
0.0
10.
010.3
5In
tera
ctio
ndCGW
tan
dYt
0.13
0.05
0.0
1O
utp
utg
apfr
omO
EC
D(Y
t)-0
.17
0.03
0.0
0
Obs
=C
ountr
y*A
vera
ge
grou
ps
375
1623
.4375
16
23.
4357
16
22.
3Sta
ndar
ddev
iati
onof
resi
du
als
0.5
90.
530.
60F
-tes
tof
addit
ional
inst
rum
ents
,go
vt.
inve
stm
ents
.cd
5.03
(0.0
0)F
-tes
tof
addit
ional
inst
rum
ents
,go
vt.
non
-wag
eco
nsu
mp
tion
.cd
1.87
(0.0
6)F
-tes
tof
addit
ional
inst
rum
ents
,go
vt.
wage
consu
mp
tion
.cd
3.13
(0.0
0)χ2
ofp
olic
yan
dex
por
ts.b
229
.65
(0.0
0)24
1.64
(0.0
0)1st
order
auto
corr
elat
ionb
1.73
(0.0
8)2.
82(0
.01)
2nd
order
auto
corr
elat
ionb
-1.7
0(0
.09)
0.82
(0.4
1)H
anse
nJ
Ove
riden
tifi
cati
onte
st9.
08(0
.11)
Dep
enden
tva
riable
:T
he
unem
plo
ym
ent
rate
.In
all
equati
ons
itis
als
oco
ntr
olled
for
lab
our
mark
etin
stit
uti
ons.
a)
Fix
edeff
ect
coeff
cien
tses
tim
ate
,ro
bust
standard
erro
rs(x
treg
wit
h,r
obust
)
b)
Sta
taco
mm
and
xti
vre
g2
wit
hopti
on
robust
,se
eB
aum
etal.
(2002).
Change
gov
t.purc
hase
s(dG
t)
istr
eate
das
endogen
ous.
Inst
rum
ents
are
:(∆
dG
t−1),
(dG
t−2)
and
(∆debt t
−1).
c)F
irst
regre
ssio
nre
sult
sof
stata
com
mand
xti
vre
g2,
see
Baum
etal.
(2002).
d)
Num
ber
sin
pare
nth
eses
are
p-v
alu
esfo
rth
ere
leva
nt
null.
15
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4.4 Monetary regime, labour market institutions, debt and openness
In this subsection we first explore whether the effect of government purchases depends onthe monetary regime, as implied by standard text book macro models like the MundellFleming model, and also emphasized in much of the recent literature, e.g. Coenen et al.(2010). Under an inflation target, an expansionary effect of increased government pur-chases will be counteracted by a rise in the interest rate, partly offsetting the effect onunemployment. Also with other types of floating exchange rates, one would expect anexpansionary effect from fiscal policy to be counteracted by changes in the exchange rateand the interest rate. In contrast, if the nominal interest rate is unaffected, as it will bewith a fixed exchange rate and for a small country in a monetary union, and inflationincreases so that the real interest falls, the government multiplier might be considerablyabove unity. Note however that this effect depends on private sector expectations. Aspointed out by Nakamura and Steinsson (2012), if one imposes purchasing power parityin the long run, a short run increase in inflation will be compensated by lower inflation inlater periods, offsetting the effect on the long run real interest rate. Yet to what extentprivate agents in fact take such effects into account remains an empirical question.
We use three dummies to capture the different monetary regimes within the sampleperiod; fixed exchange rate regimes, floating exchange rate regimes (in recent years in-cluding inflation targeting), and membership in the European Monetary Union (EMU).Countries that took part in the European Exchange Rate Mechanism ERM are defined ashaving a fixed exchange rate regime, except for Germany, which we define as floating inlight of Germany’s dominating position and the independent status of the Bundesbank.We also tried to distinguish between credible and non-credible fixed exchange rate regimesdepending on the interest rate differential relative to the anchor country (in most casesGermany), defining the regime as non-credible if the interest rate differential exceeds 1percentage point in annual terms. The idea here is that if the fixed exchange rate lackscredibility, a fiscal expansion could have a further negative effect on credibility, thus rais-ing devaluation expectations and push up interest rates. However, the point estimateswere essentially the same for credible and non-credible fixed exchange rate regimes, so wedecided to drop this distinction in the results we report.
Model 1 in table 7 shows that the effect of government purchases differs sharply acrossmonetary regimes. The point estimate is −0.32 in the EMU and −0.43 with a fixedexchange rate regime, both statistically significant. In contrast, the point estimate issmaller and imprecisely determined with a floating exchange rate. The difference acrossregimes is in line with our theoretical expectations, where fiscal policy is effective undera fixed exchange rate regime, but not under float. The difference across exchange rateregimes is consistent with those of Ilzetzki et al. (2010); they find a significant positiveeffect of increased government consumption on GDP for fixed exchange rate regimes, whilethe effect is significant and negative at impact for floating regimes. Model 2 displays theIV results: here the coefficient in the EMU is statistically significant and negative, whilethe other coefficients are imprecisely determined and thus not statistically significant.
In model 3, we explore whether the interaction with the cyclical situation of the econ-omy depends on the monetary regime. We do this by including an interaction term betweenthe output gap, a dummy for monetary regime and the change in government purchases,measured as a deviation from the country-specific mean. The interaction terms are allpositive, consistent with our results above the fiscal policy has a stronger effect on unem-ployment during a downturn, but the coefficient is only significant for the fixed exchangerate.
16
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Tab
le7:
Th
eeff
ect
ofm
onet
ary
regi
me
and
lab
our
mar
ket
inst
itu
tion
s
Model
1a
IVb
Model
3a
Model
4a
Model
5a
Coef
.Std
p-v
alu
eC
oef
.Std
p-v
alue
Coef
.Std
p-v
alu
eC
oef
.Std
p-v
alu
eC
oef
.Std
p-v
alu
e
Unem
plo
ym
ent
pre
vio
us
per
iod
1.32
0.07
0.00
1.37
0.0
60.0
01.
13
0.08
0.0
01.
32
0.08
0.0
01.
30
0.0
70.0
0U
nem
plo
ym
ent
two
year
sag
o-0
.56
0.10
0.00
-0.6
30.
090.0
0-0
.43
0.0
90.0
0-0
.53
0.1
00.
00
-0.5
30.1
00.0
0U
nem
plo
ym
ent
thre
eye
ars
ago
0.04
0.04
0.36
0.0
60.
040.1
90.0
60.
04
0.1
90.0
20.0
50.6
50.
02
0.05
0.6
8Export
mark
et:
Exp
ort
mar
ket,
1st
diff
.(∆XM
t)-0
.47
0.09
0.00
-0.4
30.0
80.0
0-0
.27
0.0
70.0
0-0
.48
0.10
0.00
-0.4
70.
10
0.0
0E
xp
ort
mar
ket,
pre
v.
per
iod
(XM
t−1)
0.15
0.08
0.06
0.19
0.09
0.0
30.
28
0.07
0.0
00.2
10.
08
0.0
10.1
80.
09
0.0
4E
xp
ort
mar
ket,
1st
diff
.pre
v.
per
iod
(∆XM
t−1)
-0.1
90.
090.
03-0
.19
0.10
0.0
6-0
.21
0.0
70.
00
-0.2
20.
09
0.0
2-0
.22
0.1
00.
02
Govt.
purchasesand
moneta
ryre
gim
e:
Chan
gego
vt.
purc
has
es(dG
t)M
onet
ary
unio
n(E
MU
)-0
.32
0.16
0.05
-0.4
00.
210.0
6-0
.55
0.2
40.
02
-0.4
50.
13
0.0
0C
han
gego
vt.
purc
has
es(dG
t),
Fix
edex
chan
gera
te-0
.43
0.13
0.00
-0.1
10.
250.6
7-0
.21
0.1
00.0
4-0
.31
0.11
0.01
Chan
gego
vt.
purc
has
es(dG
t),
Flo
atin
gex
chan
gera
te-0
.05
0.09
0.56
-0.2
50.
240.3
00.0
40.0
80.
62
-0.2
30.
08
0.0
1D
um
my
for
EM
U0.
010.
270.
97-0
.14
0.26
0.58
0.0
60.2
50.8
10.0
00.
21
1.00
Dum
my
for
Fix
edex
chan
gera
te0.
470.
270.0
90.
080.
340.
82
0.1
60.2
80.
56
0.3
30.2
10.
11
Inte
ract
ion
chan
gego
vt.
purc
has
es(dG
t)an
dou
tput
gapY
,M
onet
ary
unio
n(E
MU
)0.1
10.0
90.
21
Inte
ract
ion
chan
gego
vt.
purc
has
es(dG
t)an
dou
tput
gapY
,F
ixed
exch
ange
rate
,cr
edib
le0.0
60.0
20.
02
Inte
ract
ion
chan
gego
vt.
purc
has
es(dG
t)an
dou
tput
gapY
,F
loat
ing
exch
ange
rate
0.0
20.0
50.
65
Outp
utg
apfr
omO
EC
D(Y
t)-0
.16
0.03
0.0
0Govt.
purchasesand
labourmark
et:
Chan
gego
vt.
purc
has
es,
(dG
t)-0
.31
0.0
70.0
0In
tera
ctio
nch
ange
govt.
purc
has
esan
dth
epre
dic
ted
effec
tof
lab
our
mar
ket
inst
ituti
ons
-0.2
60.0
70.0
0-0
.27
0.0
60.0
0
Obs
=C
ountr
y*A
vera
gegr
oups
483
2024.
144
020
22.
0483
2024.1
483
20
24.
1483
2024
.1Sta
ndar
ddev
iati
onof
resi
dual
s0.
620.
580.5
70.6
20.6
1F
-tes
tof
addit
ional
inst
rum
ents
,E
MU
.cd
6.6
3(0
.00)
F-t
est
ofad
dit
ional
inst
rum
ents
,F
ixed
exch
ange
rate
.cd
4.84
(0.0
0)F
-tes
tof
addit
ional
inst
rum
ents
,F
loat
ing
exch
ange
rate
.cd
5.98
(0.0
0)χ2
ofp
olic
yan
dex
por
ts.d
135.
87(0
.00)
127
.24
(0.0
0)
103.7
9(0
.00)
138.
21
(0.0
0)
1st
order
auto
corr
elat
iond
1.26
(0.2
1)2.
73
(0.0
1)1.
51
(0.1
3)0.9
9(0
.32)
2nd
order
auto
corr
elat
iond
-1.5
9(0
.11)
1.1
2(0
.26)
-1.4
8(0
.14)
-1.7
1(0
.09)
Han
sen
Jov
erid
enti
fica
tion
test
8.10
(0.2
3)
Dep
enden
tva
riable
:T
he
unem
plo
ym
ent
rate
.In
all
equati
ons
itis
als
oco
ntr
olled
for
lab
our
mark
etin
stit
uti
ons.
a)
Fix
edeff
ect
coeff
cien
tses
tim
ate
,ro
bust
standard
erro
rs(x
treg
wit
hro
bust
).
Hub
er-r
obust
standard
erro
r(Sta
taco
mm
and
xtr
egw
ith
clust
er(c
ode)
.
b)
Sta
taco
mm
and
xti
vre
g2,
see
Baum
etal.
(2002).
Change
gov
t.purc
hase
s(dG
t)
istr
eate
das
endogen
ous.
Inst
rum
ents
,se
para
tely
for
each
regim
e,are
:(∆
dG
t−1),
(dG
t−2)
and
(debt t
−1).
xti
vre
g2
wit
hro
bust
c)F
irst
regre
ssio
nre
sult
sof
stata
com
mand
xti
vre
g2,
see
Baum
etal.
(2002).
d)
Num
ber
sin
pare
nth
esis
are
p-v
alu
esfo
rth
ere
leva
nt
null.
17
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We then turn to the importance of labour market institutions. The theoretical resultsare mixed: Ardagna (2007) finds that an increase in government purchases leads to in-creased unemployment in a monopoly union model, while Furlanetto (2011) shows thatreal wage rigidity may play an important role to preserve the traditional effect of fiscalpolicy in New Keynesian models, i.e. that increased purchases leads to higher employment.
First, as noted above we include institutions in all the regressions. This turns out tobe of limited importance, as the effect of fiscal policy is only slightly larger in a regressionwithout the labour market institutions (results available on request). Second, we wantto explore whether the effect of fiscal policy varies across countries with different labourmarket institutions. To this end, we first construct a summary index on the basis ofour regression results. Specifically, we detect the estimated effect of the labour marketinstitutions in the appendix, model 3 in table B1, by calculating the index as the productof the estimated coefficients and the actual values of the labour market institutions. Wecompute the deviation of the index from its sample mean to obtain an index with zeromean. We then interact the change in government purchases with the index of labourmarket institutions. The results in Table 7, column 4, shows that an increase in governmentpurchases has a stronger negative impact on unemployment in country-years with labourmarket institutions that induce higher unemployment. The effect is highly significantstatistically, and numerically rather strong: In Australia, labour market institutions are”employment-friendly” with mean index value −0.77, and the effect on unemployment ofan increase in government purchases equal to one percent of GDP is equal to −0.31 +(−0.77) ∗ (−0.26) = −0.11, In contrast, in Sweden, institutions are more conducive tounemployment with mean index of 0.38, implying that the overall coefficient for an increasein government purchases is−0.31+0.38∗(−0.26) = −0.41. Thus, fiscal policy seems to havea stronger impact on unemployment in countries with adverse labour market institutions.One possible interpretation of this is that there is less crowding out of private employmentin countries with rigid labor markets.
One possible concern with these results is that may be caused by spurious correlation,as labour market institutions are generally more rigid in Continental Europe, where wealso find most of the EMU countries. Thus, in column 5, we also include the interactionof fiscal policy and monetary regime, and we find that the results still hold - fiscal policyhas a larger effect with adverse labour market institutions. In fact, the coefficient forgovernment purchases is now negative and statistically significant for all three monetaryregimes, suggesting that an increase in government purchases has a negative impact alsounder a floating regime, as long as the labour market institutions are at the average.
We have also tried other possible interaction effects. Giavazzi and Pagano (1990) arguethat a severe fiscal contraction might be expansionary in situations with concern for therisks of high public debt. This suggests that the effect of government purchases maydepend on the level of public debt. In a recent study using structural VARs on quarterlydata for 44 countries, both advanced and developing countries, Ilzetzki et al. (2010) findthat the fiscal multiplier depends on the level of government debt, and that the fiscalmultiplier is zero in high debt countries. To explore the possible importance of publicdebt, we interact the change in government purchases with lagged public debt as a ratioto GDP (measured as deviation from sample mean, which is equal to 0.65). We interactwith debt above and below the mean separately, to allow for non-linear effects, and wealso include debt as a separate explanatory variable, as the levels of debt might well becorrelated with the level of unemployment, cf. Bertola (2010). However, the interactionterms have no explanatory power, with coefficients of about 0.001 and fairly small standarderrors (0.006 and 0.004), implying that these effects are fairly precisely estimated to zero(results available on request).
We also explore whether the effect of government purchases depends on the opennessof the country. According to traditional Keynesian analysis, the government expenditure
18
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multiplier is smaller in an open economy. In line with this, Beetsma and Giuliodori (2010)find in an analysis of 14 EU countries a clear positive effect of a rise in governmentpurchases on GDP in “closed economies” (defined as countries where the ratio of exportplus import to GDP is below sample average), and no significant effect in the remaining“open economies”. Ilzetzki et al. (2010) also find a stronger expansionary effect in closedeconomies than in open. To analyse the effect of openness, we interact the change ingovernment purchases with an indicator of openness, based on the ratio of export plusimport to GDP. As the degree of openness has increased over time, we consider twodifferent specifications of this indicator, one where the indicator measures the deviationof the export plus import ratio from the overall sample mean, implying that the indicatoralso captures the increase in openness over time, and one where the indicator is measuredas deviation from year mean, thus omitting the change in openness over time. However,in both cases the interaction term is close to zero when we control for monetary regime(results available on request).
4.5 The effect on the employment rate
In this section we explore whether our findings of a clear effect on the unemployment rate isreflected in a corresponding effect on the employment rate. Generally, we find effects whichare very similar as those reported above, with coefficients of the opposite sign. For example,when we estimate equation 1 with the employment rate as the dependent variable, thecoefficient for the change in government purchases is 0.23, with a p-value of 0.00, cf. table8. Models 2 and 3 show that it is essentially government wage consumption which has apositive effect on employment, and for this variable the effect is much stronger in recessions(when the output gap is negative), consistent with our unemployment findings above. Thecorrespondance between the effects on employment and on unemployment indicates thatvariation in government purchases usually has limited effect on labour supply. In table 9we repeat the regressions from table 7, but with employment rather than unemploymentas the dependent variable. We observe that in the regressions in column 1, the change ingovernment purchases is only significant for countries with a fixed exchange rate. The IVresults in column 2 are not significant. In column 3, which includes an interaction withthe output gap, government purchases has a significant effect in EMU countries, while theinteraction term is significant for both EMU and countries with a fixed exchange rate.For EMU countries, both point estimates are quite large, implying a substantial impactof fiscal policy in a downturn.
As above, we find that the effect of government purchases on the labour market isstronger in countries with institutions that are conducive to unemployment. Furthermore,when we control for labour market institutions, we find that an increase in governmentpurchases leads to higher employment also in countries with a floating exchange rate(Model 5 in table 9), even if the point estimate is still considerably lower than under afixed exchange rate.
19
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Tab
le8:
Th
eeff
ect
onth
eem
plo
ym
ent
rate
Model
1M
od
el1
wit
hM
odel
2M
odel
3ti
me
dum
mie
sC
oef
.Std
p-v
alu
eC
oef
.S
tdp-v
alu
eC
oef
.Std
p-v
alu
eC
oef
.Std
p-v
alu
e
Em
plo
ym
ent
pre
vio
us
per
iod
1.54
0.09
0.00
1.53
0.09
0.00
1.56
0.0
90.0
01.
300.1
30.
00E
mplo
ym
ent
two
year
sag
o-0
.76
0.12
0.00
-0.7
40.
110.
00
-0.8
20.1
30.0
0-0
.64
0.12
0.0
0E
mplo
ym
ent
thre
eye
ars
ago
0.14
0.05
0.0
00.
130.
040.
000.
150.0
50.0
00.
19
0.0
40.
00Demand
components:
Exp
ort
mar
ket,
1st
diff
.(∆XM
t)0.
400.
090.
000.
380.
160.
020.
330.1
00.0
00.
160.
070.
03E
xp
ort
mar
ket,
pre
v.
per
iod
(XM
t−1)
-0.1
60.0
70.
01-0
.03
0.16
0.85
-0.1
60.
080.0
3-0
.29
0.0
90.
00E
xp
ort
mar
ket,
1st
diff
.pre
v.
per
iod
(∆XM
t−1)
0.14
0.07
0.06
-0.0
40.
150.7
80.
140.0
80.0
90.
18
0.0
60.0
0C
han
gego
vt.
pu
rch
ases
(dG
t)0.
230.
070.0
00.2
50.
070.0
0C
han
gego
vt.
inve
stm
ents
,(dIG
t)0.
100.
050.0
50.0
80.0
60.2
1C
han
gego
vt.
non
-wag
eco
nsu
mpti
on,
(dCGNW
t)0.
030.
010.
00-0
.00
0.0
20.9
0C
han
gego
vt.
wag
eco
nsu
mpti
on,
(dCGW
t)0.4
50.1
60.
010.3
50.
130.
01In
tera
ctio
ndGI t
andYt
0.00
0.0
40.
92In
tera
ctio
ndCGNW
tandYt
0.00
0.0
00.
91In
tera
ctio
ndCGW
tan
dYt
-0.1
20.0
20.
00O
utp
utg
apfr
omO
EC
D(Y
t)0.1
70.0
40.0
0
Obs
=C
ountr
y*A
vera
ge
grou
ps
483
20
24.1
483
2024
.137
516
23.4
375
1623.4
Sta
ndar
ddev
iati
onof
resi
du
als
0.66
0.63
0.60
0.5
4χ2
ofp
olic
yan
dex
port
s.a
39.6
8(0
.00)
23.8
0(0
.00)
1st
order
auto
corr
elat
iona
1.5
8(0
.11)
2.59
(0.0
1)
1.73
(0.0
8)
2.66
(0.0
1)2nd
order
auto
corr
elat
iona
-0.5
2(0
.60)
-0.8
5(0
.40)
-1.7
0(0
.09)
2.0
4(0
.04)
Dep
enden
tva
riable
:T
he
emplo
ym
ent
top
opula
tion
rate
.
Est
imati
on
met
hod:
Fix
edeff
ect
coeff
cien
tses
tim
ate
wit
hhub
er-r
obust
standard
erro
r(S
tata
com
mand
xtr
eg
wit
hcl
ust
er(c
ode)
and
robust
opti
on
isuse
din
all
the
regre
ssio
ns.
Itis
als
oco
ntr
olled
for
lab
our
mark
etin
stit
uti
ons.
a)
Num
ber
sin
pare
nth
eses
are
p-v
alu
esfo
rth
ere
leva
nt
null.
20
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Tab
le9:
Th
eeff
ect
onth
eem
plo
ym
ent
rate
Model
1a
Model
2IV
bM
odel
3a
Model
4a
Model
5a
Coef
.Std
p-v
alu
eC
oef
.Std
p-v
alue
Coef
.Std
p-v
alu
eC
oef
.Std
p-v
alu
eC
oef
.Std
p-v
alu
e
Em
plo
ym
ent
pre
vio
us
per
iod
1.51
0.09
0.00
1.64
0.07
0.0
01.3
10.1
00.0
01.
54
0.0
90.
00
1.5
00.
09
0.00
Em
plo
ym
ent
two
year
sag
o-0
.75
0.12
0.00
-0.9
20.
120.0
0-0
.62
0.1
10.
00
-0.7
60.1
20.
00
-0.7
40.1
20.0
0E
mplo
ym
ent
thre
eye
ars
ago
0.14
0.04
0.00
0.1
90.0
60.
00
0.1
90.0
50.0
00.
14
0.0
50.
00
0.14
0.0
40.
00
Export
mark
et:
Exp
ort
mar
ket,
1st
diff
.(∆XM
t)0.
400.
090.
000.3
10.0
90.
00
0.2
10.0
70.
00
0.40
0.0
90.
00
0.4
00.
09
0.0
0E
xp
ort
mar
ket,
pre
v.
per
iod
(XM
t−1)
-0.1
10.
060.
06-0
.11
0.10
0.29
-0.2
30.0
60.0
0-0
.18
0.07
0.0
1-0
.12
0.06
0.0
5E
xp
ort
mar
ket,
1st
diff
.pre
v.
per
iod
(∆XM
t−1)
0.14
0.07
0.04
0.13
0.09
0.15
0.1
40.
05
0.01
0.1
50.0
70.
02
0.1
50.
07
0.0
3Govt.
purchasesand
moneta
ryre
gim
e:
Chan
gego
vt.
purc
has
es(dG
t)M
onet
ary
unio
n(E
MU
)0.
250.
190.
210.
010.
170.9
70.5
70.2
30.
01
0.3
10.
17
0.06
Chan
gego
vt.
purc
has
es(dG
t),
Fix
edex
chan
gera
te0.
350.
110.
00-0
.17
0.38
0.67
0.1
00.
13
0.4
50.
28
0.1
10.
01
Chan
gego
vt.
purc
has
es(dG
t),
Flo
atin
gex
chan
gera
te0.
060.
070.
38-0
.37
0.29
0.2
1-0
.04
0.0
60.
51
0.1
50.
08
0.04
Dum
my
for
EM
U0.
250.
250.3
20.
160.
300.
600.
30
0.25
0.23
0.2
60.
23
0.2
5D
um
my
for
Fix
edex
chan
gera
te-0
.37
0.23
0.1
0-0
.28
0.45
0.53
0.0
50.2
90.
85
-0.2
90.1
90.
12
Inte
ract
ion
chan
gego
vt.
purc
has
es(dG
t)an
dou
tput
gapY
,M
onet
ary
unio
n(E
MU
)-0
.17
0.09
0.0
5In
tera
ctio
nch
ange
govt.
purc
has
es(dG
t)an
dou
tput
gapY
,F
ixed
exch
ange
rate
,cr
edib
le-0
.06
0.0
30.
01
Inte
ract
ion
chan
gego
vt.
purc
has
es(dG
t)an
dou
tput
gapY
,F
loat
ing
exch
ange
rate
-0.0
30.
05
0.5
0O
utp
utg
apfr
omO
EC
D(Y
t)0.
17
0.03
0.0
0Govt.
purchasesand
labourmark
et:
Chan
gego
vt.
purc
has
es,
(dG
t)0.
25
0.0
70.
00
Inte
ract
ion
chan
gego
vt.
purc
has
esan
dth
epre
dic
ted
effec
tof
lab
our
mar
ket
inst
ituti
ons
0.15
0.0
70.
02
0.1
40.
05
0.01
Obs
=C
ountr
y*A
vera
gegr
oups
483
2024
.144
020
22.0
483
20
24.1
483
20
24.1
483
20
24.1
Sta
ndar
ddev
iati
onof
resi
dual
s0.
650.
600.5
90.6
50.6
4F
-tes
tof
addit
ional
inst
rum
ents
,E
MU
.cd
5.92
(0.0
0)F
-tes
tof
addit
ional
inst
rum
ents
,F
ixed
exch
ange
rate
.cd
4.17
(0.0
0)F
-tes
tof
addit
ional
inst
rum
ents
,F
loat
ing
exch
ange
rate
.cd
7.16
(0.0
0)χ2
ofp
olic
yan
dex
por
ts.b
57.7
7(0
.00)
170.3
1(0
.00)
56.9
4(0
.00)
66.9
0(0
.00)
1st
order
auto
corr
elat
ionb
1.50
(0.1
3)2.5
8(0
.01)
1.32
(0.1
9)1.2
8(0
.20)
2nd
order
auto
corr
elat
ionb
-0.4
7(0
.64)
2.34
(0.0
2)
0.49
(0.6
2)
-0.4
1(0
.68)
Han
sen
JO
veri
den
tifica
tion
test
2.92
(0.4
0)
Dep
enden
tva
riable
:T
he
emplo
ym
ent
top
opula
tion
rate
.In
all
equati
ons
itis
als
oco
ntr
olled
for
lab
our
mark
etin
stit
uti
ons.
a)
Fix
edeff
ect
coeff
cien
tses
tim
ate
,ro
bust
standard
erro
rs(x
treg
wit
hro
bust
).H
ub
er-r
obust
standard
erro
r(Sta
taco
mm
and
xtr
egw
ith
clust
er(c
ode)
.
b)
Sta
taco
mm
and
xti
vre
g2,
see
Baum
etal.
(2002).
Change
gov
t.purc
hase
s(dG
t)
istr
eate
das
endogen
ous.
Inst
rum
ents
,se
para
tely
for
each
regim
e,are
:(∆
dG
t−1)
and
(debt t
−1).
c)F
irst
regre
ssio
nre
sult
sof
stata
com
mand
xti
vre
g2,
see
Baum
etal.
(2002).
d)
Num
ber
sin
pare
nth
esis
are
p-v
alu
esfo
rth
ere
leva
nt
null.
21
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5 Concluding remarks
The vast policy interest of fiscal policy issues has led to a fast increasing body of researchtrying to detect the effect of a change in fiscal policy. However, few of these studies explorethe effect on unemployment, and the results in the existing studies are mixed. We inves-tigate the effect of changes in government purchases on unemployment and employmentby use of panel data estimation, building on an empirical equation where long run unem-ployment is a function of a number of labour market variables, along the lines of Layardet al. (2005) and Nickell et al. (2005). Our study exploits a fairly large data set, covering20 countries and 27 years, making it possible to explore how the effect differ according tothe circumstances, like monetary regime, cyclical situation of the economy, and whetherthe labour market institutions are ”employment-friendly”. It turns out that the effectdiffers strongly with these circumstances, underscoring the importance of exploring thedifferences.
We find that a permanent increase in government purchases equal to one percent ofGDP on average leads to a reduction in unemployment of 0.3 percentage point, using bothfixed effects and IV estimation. There is considerable variation in the effect of governmentpurchases depending on the specific circumstances. Consistent with recent studies likeAuerbach and Gorodnichenko (2012) and Nakamura and Steinsson (2012), we find thatthe effect is considerably larger when the economy is in a weak cyclical situation.
The systematic link between the output gap and the effect of government purchaseshas potentially vast policy interest. In many countries, the increasing public debt impliesthat fiscal policy has to be tightened before long, so there is little scope for using fiscalpolicy to reduce unemployment. However, taken at face value the results in table 5 suggestthat even a fiscally neutral countercyclical policy may reduce the average unemploymentrate over time. According to these results, if the increase in government purchases indownturns were matched by a decrease of the same magnitude in booms, the net effectwould be a decrease in unemployment. Such an effect would be inconsistent with standardtheories of equilibrium unemployment, but it is in line with the countercyclical effect offiscal policy in the general equilibrium search model of Michaillat (2012). The persistenthigh unemployment rates in many OECD countries, indicating long-lasting deviationsfrom long run equilibrium levels, makes the result highly relevant for policy.
The monetary regime is important for the effect. In line with the Mundell Flemingmodel, we find a strong effect of government purchases on unemployment for countrieswithin a monetary union or with a fixed exchange rate regime, and much weaker effectsof government purchases for countries with a floating exchange rate. This finding is con-sistent with the argument of among others Coenen et al. (2010), that fiscal policy hasa strong impact on the economy when the monetary policy does not respond. Consid-ering different types of government purchases, we only find a strong significant effect ofgovernment wage consumption (i.e. public employment), while the IV estimates suggestthat government investment has a strong dampening effect on unemployment. The effectof government wage consumption is strongly countercyclical, consistent with the searchmodel of Michaillat (2012). We also find that the fiscal policy has a stronger effect incountries with labour market institutions that are conducive to high unemployment.
Finally, we explore the effect of a change in government purchases on the employmentrate. For the most part, the results correspond well to the unemployment results. In-creased government purchases equal to one percent of GDP is estimated to increase theemployment rate by 0.23 percentage points. The effect essentially comes for governmentwage consumption (i.e. public employment), it is stronger in a downturn, and also strongerin countries with a fixed exchange rate.
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A Appendix: Data definitions and sources
The data are from OECD (2008b) unless otherwise noted. The sample period is from 1980to 2007, except for Table 5, which also includes 1960-1979, with the following countries:Australia, Austria, Belgium, Canada, Denmark, Finland, France, Germany, Ireland, Italy,Japan, Netherlands, Norway, New Zealand, Portugal, Spain, Sweden, Switzerland, UnitedKingdom and United States (for Germany, the data starts in 1991). The labour marketdata is also based on the OECD (2008b), but the more detailed description is given inSparrman (2010).
A.1 Government purchases
The change in government purchases (dG) is measured as the growth rate in real termsof government purchases, multiplied with government purchases as a share of trend GDP.The formula of dG is:
dGit =(CGVit + IGVit)− (CGVit−1 − IGVit−1)
(CGVit−1 + IGVit−1)∗ CGit + IGit − CFKGit
Y CTit∗ 100 (A1)
where CG is government consumption, IG government investments, CFKG is consump-tion of fixed capital, and Y CT is trend-GDP. The variables are in nominal prices, exceptthose where the last letter V indicates real terms. Note that government purchases donot include transfers like social security expenditures etc. Note also that we subtractconsumption of fixed capital (CFKG) from government consumption to obtain the ac-tual expenditure, as the consumption of fiscal capital is an imputed measure. CFKG isnot subtracted in the real growth rate for reasons of data availability, but this is unim-portant as there presumably is little variation over time in the imputed consumption offixed capital. Investment data is missing for some countries (Spain, Italy, Switzerland)and for these countries we use government consumption only. Trend-GDP is equal to thebackward looking 10 year moving average of real GDP (Y Q) multiplied with the two yearmoving average of the price deflator (PGDP ) to a variable in nominal terms. Some ofthe volume variable series are calculated on the basis of the relevant identities with valuesand deflators, as they are not published by the OECD.
A.2 Monetary regime
We have constructed 3 dummies to account for changes in the monetary regime over thesample period; a floating exchange rate, a fixed exchange rate, and membership in theEuropean Monetary Union (EMU). The dummy Dfloat indicates a floating exchange rate:Australia, Canada, Germany, Japan, New Zealand, Switzerland, United States and UnitedKingdom (except 1990 and 1991 2). Germany is defined to have a floating regime in lightof Germany’s dominating position European Exchange Rate Mechanism ERM, and theindependent status of the Bundesbank. Later also Sweden (since 1992) and Norway (since1999, which is usually assumed to be the year with the de facto change of regime) adopteda floating exchange rate, with inflation targeting. The dummy Dfixed indicates a fixedexchange rate, and this includes the countries that took part in the ERM, except Germany.DEMU indicates EMU membership, covering Austria, Belgium, Finland, France, Germany,Ireland, Italy, Portugal and Spain since 1999.
A.3 Export market indicator
The export market (XM) indicator is calculated as a weighted average of the GDP-gap ofthe trading partners, where the GDP-gap is the deviation of GDP from Hodrick Prescott-
2The UK was a member of the European exchange rate mechanism (ERM) from October 1990 toSeptember 1992
23
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trend (with smoothing parameter 100), and the weights reflect the share of the exportsfrom country i that goes to each of the trading partners j. The formulae is
XMit = Σjwijt ∗GAPjt (A2)
where wijt = xijt/Σjxijt. xijt is export from country i to county j in year t. The tradingpartners to one country in the sample are all the other countries in the sample and the restof ’the world’. The exports data is from SITC Revision 2 OECD (2010), and are used tocalculate the export shares for each country in the sample. The time series are prolongedbackwards with the exports to the world when observations are missing. The GDP-gapfor each of the twenty OECD countries is calculated using data from OECD (2008b).The world GDP-gap is constructed using data for the real GDP in The Conference Board(2010). We have used the GDPGK-series with GDP expressed in 1990 U.S. dollars, whichcovers 123 countries in the database.
A.4 Other variables
The unemployment rate - we use the standardized unemployment rate (UNR) fromEconomic Outlook OECD (2008a) .
Output gap - is defined as the actual GDP less potential GDP, as a share of potentialGDP. It is measured in percentage points and collected from OECD (2008b).
Election year - is collected from Armingeon et al. (2010), and the original data sourceis European Journal of Political Research (Political Data Yearbook, various issues); Mackieand Rose (1991); Keesing’s Archive; Parline database. The variable describes date ofelection of national parliament (lower house). The variable covers the years in the period1960 to 2008.
Gross Public Debt - is collected from Armingeon et al. (2010), and the original datasource is several versions of Oecd Economic outlook. See details regarding versions andthe mission observations in Codebook by Armingeon et al. (2010).
Openness - is total trade (export and imports ) in percentage of GDP. The variableis collected from Armingeon et al. (2010). See details regarding versions and the missionobservations in Codebook by Armingeon et al. (2010).
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Table A1: Real growth in government purchases, multiplied by the ratio of governmentpurchases to trend GDP - country specific mean and standard deviation
Country stats 1960-69 1970-79 1980-89 1990-99 2000-07 1960-07
Australia mean 1.38 0.87 0.87 0.64 0.80 0.90sd 0.75 0.60 0.57 0.26 0.21 0.55Austria mean 0.93 0.89 0.23 0.48 0.13 0.53sd 0.48 0.35 0.24 0.29 0.30 0.46Belgium mean 1.55 1.36 0.17 0.35 0.43 0.75sd 0.52 0.40 0.53 0.37 0.29 0.70Canada mean 1.56 1.16 0.72 0.25 0.82 0.88sd 0.59 0.70 0.36 0.52 0.20 0.66Denmark mean . 0.89 0.16 0.54 0.52 0.51sd . 0.69 0.52 0.45 0.31 0.55Finland mean 1.31 1.19 0.79 0.20 0.37 0.77sd 1.07 0.72 0.32 0.85 0.35 0.81France mean 1.13 0.89 0.80 0.44 0.49 0.72sd 0.21 0.35 0.24 0.41 0.20 0.38Germany mean 1.47 1.22 0.19 0.45 0.13 0.68sd 0.94 0.58 0.51 0.48 0.21 0.78Ireland mean 1.06 1.59 -0.04 1.11 1.45 1.02sd 0.57 0.81 1.41 0.50 1.37 1.13Italy mean 0.88 0.70 0.59 0.04 0.40 0.51sd 0.15 0.19 0.24 0.37 0.17 0.37Japan mean 2.17 1.79 0.53 0.73 -0.08 1.03sd 0.85 1.44 0.47 0.62 0.21 1.14Netherlands mean 1.12 0.78 0.67 0.65 0.93 0.81sd 0.37 0.76 0.32 0.24 0.76 0.54New Zealand mean 0.73 0.97 0.28 0.54 0.93 0.68sd 1.07 1.49 0.94 1.01 1.14 1.13Norway mean 1.64 1.56 0.87 1.18 0.90 1.22sd 0.58 0.45 0.53 0.61 0.53 0.61Portugal mean . 1.80 0.93 0.94 0.21 0.80sd . 0.83 0.66 0.61 0.61 0.74Spain mean 0.49 0.99 0.96 0.79 1.18 0.91sd 0.18 0.27 0.50 0.46 0.18 0.40Sweden mean 1.86 1.10 0.50 0.41 0.24 0.80sd 0.49 0.70 0.31 0.56 0.45 0.76Switzerland mean 0.37 0.22 0.36 0.10 0.07 0.21sd 0.13 0.32 0.27 0.24 0.15 0.27United Kingdom mean 0.70 0.53 0.20 0.30 0.74 0.46sd 0.75 0.62 0.32 0.39 0.82 0.60United States mean 1.20 0.12 0.67 0.26 0.44 0.51sd 0.82 0.43 0.42 0.28 0.23 0.58Total mean 1.25 1.00 0.52 0.52 0.56 0.74sd 0.77 0.80 0.61 0.58 0.65 0.73
25
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Table A2: Public debt for the countries in the panel over the sample period.
Country stats 1960-69 1970-79 1980-89 1990-99 2000-07 1960-07
Australia mean . . 0.24 0.33 0.19 0.26sd . . 0.01 0.07 0.03 0.09Austria mean . 0.23 0.48 0.65 0.70 0.50sd . 0.07 0.09 0.06 0.04 0.19Belgium mean . 0.60 1.08 1.31 1.01 1.00sd . 0.04 0.17 0.07 0.09 0.28Canada mean 0.61 0.48 0.62 0.93 0.75 0.68sd 0.06 0.04 0.10 0.08 0.06 0.17Denmark mean . . 0.66 0.73 0.48 0.63sd . . 0.10 0.07 0.09 0.14Finland mean . 0.11 0.17 0.52 0.49 0.34sd . 0.03 0.02 0.18 0.04 0.20France mean . 0.33 0.35 0.57 0.70 0.48sd . 0.04 0.04 0.12 0.04 0.17Germany mean . 0.22 0.38 0.51 0.65 0.43sd . 0.05 0.04 0.10 0.04 0.17Ireland mean . 0.61 0.94 0.80 0.34 0.70sd . 0.05 0.15 0.16 0.04 0.26Italy mean 0.37 0.75 0.91 1.18 1.18 0.91sd 0.03 0.13 0.06 0.13 0.03 0.29Japan mean . 0.24 0.65 0.87 1.59 0.80sd . 0.12 0.10 0.22 0.14 0.50Netherlands mean 0.72 0.56 0.79 0.86 0.59 0.71sd 0.03 0.05 0.11 0.07 0.04 0.13New Zealand mean . . . 0.49 0.31 0.39sd . . . 0.09 0.04 0.11Norway mean . 0.43 0.34 0.34 0.47 0.39sd . 0.05 0.04 0.05 0.10 0.08Portugal mean . . . 0.66 0.69 0.68sd . . . 0.03 0.04 0.04Spain mean . . 0.47 0.64 0.55 0.58sd . . 0.02 0.11 0.08 0.11Sweden mean . 0.30 0.62 0.74 0.59 0.56sd . 0.03 0.09 0.13 0.06 0.19Switzerland mean . . . 0.45 0.54 0.49sd . . . 0.08 0.04 0.08United Kingdom mean 0.95 0.58 0.47 0.45 0.44 0.53sd 0.05 0.08 0.05 0.08 0.03 0.16United States mean 0.56 0.44 0.52 0.68 0.59 0.56sd 0.05 0.02 0.08 0.04 0.03 0.09Total mean 0.62 0.43 0.59 0.69 0.64 0.60sd 0.16 0.19 0.26 0.27 0.31 0.28
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B Appendix: Additional information of Table 2
Table B1 presents the complete results of the models in table 2, including the estimatesfor the labour market variables. Thus, model 1 is reestimation of the unrestricted unem-ployment equation of Nymoen and Sparrman (2012), including dummies for large outliers.Model 2 includes government purchases and the indicator for the export market, and inmodel 3, the dummies for large outliers are omitted, as including them is likely to involve adownward bias in the effect of the fiscal policy. For comparison, table B1 also includes twomodels more, 2i and 3i. Comparing models 2 and 2i shows the effect of omitting the largeoutliers, which is a fairly large increase in the coefficient values of government purchasesand the export market. Model 3i extends model 3 by including year dummies. We observethat the coefficients for the export market become much smaller, reflecting considerableco-movement of the export markets for all countries. In contrast, the coefficient for thechange in government purchases is not affected, presumably because any comovement ingovernment purchases across countries is not linked to comovement in unemployment. Theestimated autoregressive coefficients have the expected sign from a wage-bargain model,cf. Nymoen and Sparrman (2012). The dynamic specification is based on that the insti-tutional variables jointly affect the wage and price-setting in the next period, cf. Nymoenand Sparrman (2012).
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Tab
leB
1:E
stim
atio
nof
equ
atio
n(1
)w
ith
the
chan
gego
vern
men
tp
urc
has
esan
dex
por
tm
ark
ets(
tab
le11).
Model
1M
odel
2M
odel
2i
Model
3M
odel
3ia
Coef
.Std
p-v
alue
Coef
.Std
p-v
alue
Coef
.Std
p-v
alu
eC
oef
.Std
p-v
alu
eC
oef
.Std
p-v
alu
e
Unem
plo
ym
ent
pre
vio
us
per
iod
1.44
0.07
0.00
1.35
0.06
0.00
1.35
0.0
70.0
01.3
40.0
80.
001.3
70.0
70.0
0U
nem
plo
ym
ent
two
year
sag
o-0
.66
0.08
0.00
-0.5
50.
080.
00-0
.58
0.0
90.0
0-0
.57
0.10
0.0
0-0
.61
0.1
00.
00U
nem
plo
ym
ent
thre
eye
ars
ago
0.08
0.04
0.03
0.05
0.03
0.1
20.0
40.0
40.
290.0
40.0
50.4
30.0
70.0
50.
15In
stitutions:
Em
plo
ym
ent
pro
tect
ion
(EP
L),
1st
diff
.pre
vio
us
per
iod
0.45
0.39
0.25
0.38
0.36
0.2
90.
330.4
30.4
40.3
10.4
20.4
60.0
80.3
70.8
4E
PL
,tw
oye
ars
ago
0.2
70.
120.
020.
230.
130.0
80.1
60.
160.3
10.1
60.1
60.
310.0
90.1
70.6
1B
enefi
tre
pla
cem
ent
rati
o(B
RR
),1s
tdiff
.pre
vio
us
per
iod
0.7
90.
740.
281.
090.
780.1
62.2
50.9
50.0
22.2
70.
970.0
21.
790.7
00.0
1B
RR
,tw
op
erio
ds
ago
1.48
0.68
0.03
0.94
0.58
0.1
11.6
90.6
00.0
01.7
10.6
10.0
01.5
10.6
50.0
2B
enefi
tdura
tion
(BD
),1s
tdiff
.pre
vio
us
per
iod
-0.9
50.
690.
17-0
.54
0.66
0.4
2-0
.38
0.85
0.6
6-0
.38
0.8
30.6
5-0
.18
0.5
70.
75B
D,
two
per
iods
ago
-0.7
90.
480.
10-0
.54
0.40
0.18
-1.0
20.4
00.0
1-1
.02
0.4
10.0
1-1
.03
0.4
20.0
1In
tera
ctio
n-
BR
Ran
dB
D1s
tdiff
.pre
vio
us
per
iod
-1.3
22.
730.
630.
382.
440.
883.
143.0
90.3
12.8
12.9
80.
352.6
42.6
40.3
2In
tera
ctio
n-
BR
Ran
dB
Dtw
op
erio
ds
ago
3.4
71.
940.
072.
421.
490.
103.
271.8
20.
073.2
91.8
60.0
83.6
71.
770.0
4In
tera
ctio
n-
CO
and
UD
NE
T1s
tdiff
.pre
vio
us
per
iod
-4.5
72.
430.
06-6
.42
2.88
0.03
-5.5
83.3
00.0
9-5
.29
2.7
90.0
6-4
.28
3.0
80.1
6In
tera
ctio
n-
CO
and
UD
NE
Ttw
op
erio
ds
ago
-0.7
60.
770.
33-1
.01
0.46
0.0
3-1
.14
0.83
0.1
7-1
.09
0.8
60.
21-0
.88
0.8
00.
27In
tera
ctio
n-
CO
and
TA
X1st
diff
.pre
vio
us
per
iod
-6.9
55.
230.
18-7
.10
4.01
0.0
8-8
.12
4.7
70.
09-7
.79
4.6
90.1
0-6
.66
4.8
70.1
7In
tera
ctio
n-
CO
and
TA
Xtw
op
erio
ds
ago
-1.6
31.
340.
22-0
.76
1.28
0.55
-1.9
61.6
20.2
3-1
.99
1.6
10.2
2-1
.56
1.6
40.3
4U
nio
nden
sity
(UD
NE
T),
1st
diff
.pre
vio
us
per
iod
-0.5
53.
880.
89-1
.58
3.73
0.6
70.
013.3
91.0
00.1
53.4
90.9
71.9
23.9
30.6
3U
DN
ET
,tw
op
erio
ds
ago
0.91
0.96
0.35
0.88
1.02
0.39
1.75
1.2
20.1
51.7
31.2
20.
160.9
61.2
70.4
5C
oor
din
atio
n(C
O),
1st
diff
.pre
vio
us
per
iod
0.2
10.
290.
460.
190.
230.
42-0
.44
0.3
10.1
6-0
.47
0.32
0.1
4-0
.34
0.37
0.3
6C
O,
two
per
iods
ago
-0.0
50.
100.
63-0
.07
0.11
0.5
3-0
.15
0.1
50.
33-0
.15
0.1
50.3
3-0
.10
0.1
50.4
8T
axle
vel
(TA
X),
1st
diff
.pre
vio
us
per
iod
-5.6
33.
050.
06-3
.57
2.74
0.1
9-4
.48
2.4
10.
06-4
.12
2.3
40.0
8-0
.21
2.2
40.9
2T
AX
,tw
op
erio
ds
ago
2.01
1.43
0.16
1.40
1.45
0.3
31.
961.7
20.2
52.0
01.7
10.2
42.7
01.6
50.1
0L
arg
eou
tlie
rb0.
84
0.04
0.00
0.78
0.03
0.0
0Demand
components:
Exp
ort
mar
ket,
1st
diff
.(∆XM
t)-0
.42
0.07
0.0
0-0
.49
0.1
00.0
0-0
.48
0.1
00.0
0-0
.39
0.1
40.0
1E
xp
ort
mar
ket,
pre
v.
per
iod
(XM
t−1)
0.14
0.07
0.05
0.16
0.0
80.0
40.1
70.0
80.0
40.0
50.1
30.
69
Exp
ort
mar
ket,
1st
diff
.pre
v.
per
iod
(∆XM
t−1)
-0.2
10.
060.0
0-0
.18
0.0
80.
04-0
.18
0.0
80.0
3-0
.07
0.1
20.5
6C
han
gegov
t.purc
hase
s,1s
tdiff
.(∆dG
t)-0
.20
0.07
0.01
-0.2
70.0
80.0
0C
han
gego
vt.
purc
has
es,
pre
v.
per
iod
(dG
t−1)
-0.3
00.
100.0
0-0
.31
0.11
0.0
1C
han
gegov
t.purc
hase
s,1s
tdiff
.pre
v.
per
iod
(∆dG
t−1)
0.09
0.07
0.1
70.0
70.0
80.4
3C
han
gegov
t.purc
hase
s,(dG
t)-0
.27
0.0
80.0
0-0
.28
0.0
80.0
0
Obs
=C
ountr
y*A
vera
gegro
ups
483
2024
.148
320
24.1
483
20
24.1
483
20
24.
1483
20
24.1
Sta
ndar
ddev
iati
onof
resi
duals
0.5
70.
520.6
30.6
30.5
9χ2
of
all
the
exog
enou
sva
riab
les.c
1162
82.9
3(0
.00)
1397
.08
(0.0
0)25
40.
83(0
.00)
5777.6
0(0
.00)
51711.8
0(0
.00)
χ2
ofdum
my,
fisc
alp
olicy
and
exp
orts
.c14
69.3
1(0
.00)
χ2
ofp
olic
yan
dex
por
ts.c
144.
78(0
.00)
121.
25(0
.00)
107.6
1(0
.00)
68.
73(0
.00)
1st
order
auto
corr
elat
ionc
1.01
(0.3
2)0.
99(0
.32)
1.5
4(0
.12)
1.5
0(0
.13)
1.3
4(0
.18)
2nd
order
auto
corr
elat
ionc
-2.8
8(0
.00)
-2.5
5(0
.01)
-1.8
3(0
.07)
-1.7
4(0
.08)
-1.7
4(0
.08)
Dep
enden
tva
riable
:U
nem
plo
ym
ent.
Est
imati
on
met
hod:
Fix
edeff
ect
coeff
cien
tses
tim
ate
,ro
bust
standard
erro
rs(x
treg
wit
h,r
obust
)is
use
din
all
the
regre
ssio
ns.
a)
Wit
hti
me
dum
mie
s.
b)
Bre
ak
by
larg
eoutl
ier
appro
ach
.
c)N
um
ber
sin
pare
nth
eses
are
p-v
alu
esfo
rth
ere
leva
nt
null.
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