Country Characteristics and Effects of Government Consumption Shocks on Current Account and Real Exchange Rate

Transcription

1 Country Characteristics and Effects of Government Consumption Shocks on Current Account and Real Exchange Rate Soyoung Kim ** Department of Economics Seoul National University First Draft: March 2009 This Version: February 2012 Abstract The effects of government consumption shocks on current account and real exchange rate are examined using VAR model for 19 OECD countries. Empirical results show that although real exchange rate depreciation and current account worsening are the representative results, the effects of government consumption shocks on current account and real exchange rate are diversified across countries in terms of both the sign and the size of the effects. To explain these cross-country differences, the influence of various country characteristics on the effects is examined. Robust empirical findings are as follows. Positive government consumption shocks worsen the current account more severely in a country with smaller size and more persistent government consumption shocks and depreciate the real exchange rate more in a country with more flexible exchange rate regime. These findings provide a new dimension of empirical regularities to evaluate the relative success and failures of open economy macro models. The traditional Mundell-Flemming-Dornbusch model fails to explain real exchange rate responses. Empirical findings are broadly consistent with the basic New Open Economy model; however, some findings, such as the negative influence of shock persistence on current account responses to government consumption shocks and the positive effect of government consumption shock on private consumption, call for further developments of theory. Keywords: Real Exchange Rate, Current Account, Government consumption Shocks, Country Characteristics, VAR JEL Classification: F32, F31, E62, F41, C32 ** Department of Economics, Seoul National University, San 56-1, Sillim-Dong, Gwanak-Gu, Seoul , Korea. Tel.: , soyoungkim@snu.ac.kr.

2 1. Introduction Recent studies on the effects of fiscal policy in open economies have challenged conventional theory and generated lively debates. Kim and Roubini (2008) empirically investigated the issue for the U.S. data using the VAR (Vector Auto-Regression) model. Kim and Roubini (2008) documented that expansionary fiscal policy shocks lead to a short-run current account improvement and real exchange rate depreciation, which contradicts with the prediction of many theoretical models, such as traditional Mundell-Flemming-Dornbush (MFD) model and modern dynamic general equilibrium models. With this paradoxical result, subsequent studies (e.g., Erceg, Guerrieri, and Gust, 2005, Corsetti and Müller, 2006, Müller, 2008, Ravn, Schmitt-Grohé, and Uribe, 2008, Beetsma, Giuliodori, and Klaassen, 2008, Kollman, 2010, and Enders, Müller and Scholl, 2009) have investigated the effects of fiscal policy on current account (or trade balance) and/or real exchange rate. Some studies have expanded a set of countries and/or used different empirical models to document the empirical effects of fiscal policy. Other studies have developed theoretical models to match the empirical evidence. Despite various efforts in these recent studies, the empirical effects of fiscal policy in open economies are still controversial. Predictions of theoretical models match some important empirical evidence; however, theoretical models have not been fully tested for various empirical regularities, especially on the role of country characteristics in accounting for cross-country differences in the effects of fiscal policy. To shed some light on the issue, this paper documents empirical evidence using VAR models for the dataset of 19 industrial countries. This dataset is one of the largest sets of countries used in the literature. 1 Two main questions are investigated: First, what is the general conclusion on the empirical effects of fiscal policy on current account (or trade balance) and real exchange rate in industrial countries? Second, more importantly, what kinds of country characteristics can explain cross-country differences in terms of effects of government consumption shocks on current account (or trade balance) and real exchange rate. Following recent studies, the VAR model is used to examine the effects of government consumption shocks. In the literature, government net tax (or transfer shocks) and government budget balance (or deficit) shocks, as well as government consumption shocks are considered. However, this paper focuses only on government consumption shocks for the following reasons: First, the method of identifying government consumption shocks is less controversial than the 1 For example, Kim and Roubini (2008), Müller (2008), Enders, Müller, and Scholl (2009) used U.S. data. Corsetti and Müller (2006) investigated four individual countries. Ravn, Schmitt-Grohé, and Uribe (2008) investigated five countries using panel VAR models. Beetsma, Giuliodori, and Klaassen (2008) examined 16 countries in the European Union using panel VAR models. 2

3 method of identifying transfer/tax shocks or government budget balance/deficit shocks. Second, high-frequency data on government consumption is available for most OECD countries; however, high-frequency data on government budget balance/deficit or net transfers/taxes are hard to obtain for certain OECD countries. Third, there are more theoretical developments on the effects of government consumption shocks than on the effects of net transfer/tax shocks. The results from individual country estimation of 19 countries based on VAR models show that empirical effects on current account and real exchange rate are very diversified across countries. This may explain the controversies on empirical effects of fiscal policy on real exchange rate and current account in past studies. To explain the differences in effects across countries, the influence of country characteristics on the effects of government consumption shocks is examined by regressing current account and real exchange rate responses to government consumption shocks on various measures of country characteristics. Five types of country characteristics on effects of fiscal policy in open economies are considered: country size, trade openness, exchange rate regime, international capital mobility, and persistence of shocks. These characteristics have been discussed in past theoretical works. Many past theoretical studies have suggested that the effects of fiscal policy in open economies critically depend on country characteristics. Despite these theoretical predictions, very few studies have empirically investigated the theoretical predictions on the influence of country characteristics. 2 This paper contributes to the literature by empirically investigating the issue in a systematic manner. Past studies have mostly used general evidence that does not depend on country characteristics in order to evaluate the relative success and failure of theoretical models. This paper discusses the relative success and failure of theoretical models by exploiting new dimensions of data, that is, influence of country characteristics on the effects of government consumption shocks. As such, this paper contributes to the empirical literature, which has been searching for the theoretical model with empirical relevance. There are two recent studies that examine the influence of economic environments and country characteristics on the effects of fiscal policy, especially on government spending multipliers. 3 Ilzetzki, Mendoza, and Végh (2009) constructed Panel VAR model for two distinguished groups based on each characteristics using quarterly data of 44 countries. Corsetti, Meier, and Müller (2010) employed two-stage process (non-var s) to consider various 2 An exception is Corsetti and Müller (2006), who emphasized the influence of two country characteristics (country size and persistence of shocks) on the effects of fiscal policy on current account using the four sample countries. The current study systematically investigates the issue with more country characteristics (5 characteristics) and larger samples (19 countries). 3 I found these papers while I was revising the current paper. 3

4 characteristics simultaneously using annual data of 17 OECD countries. While these papers focus on output effects (or fiscal multipliers), the current paper focuses on open economy effects. 4 Section 2 empirically documents the effects of government consumption shocks on real exchange rates and current accounts in individual 19 OECD countries using the VAR model. Section 3 reviews theories that explain the influence of country characteristics on current account and real exchange rate responses to government consumption shocks. Section 4 explains the empirical methodology and the measure of country characteristics. Section 5 reports the empirical results on the influence of various country characteristics on the effects of government consumption shocks in open economies. Section 6 discusses the empirical results in view of theories. Section 7 concludes with a summary of the findings. 2. Effects of Government consumption Shocks in 19 OECD Countries This section documents the effects of government consumption shocks on current account and real exchange rate in 19 OECD countries using a VAR model for each country. To identify government consumption shocks in each country, government consumption is assumed to be contemporaneously unaffected by other variables. In other words, it takes more than a quarter to change government consumption in response to the state of the economy since quarterly data is used in this paper. This assumption, proposed by Blanchard and Perotti (2002), is persuasive, based on the actual conduct of fiscal policy. It is well-known that fiscal policy involves with long implementation lags. Policy makers are very likely to spend more than a quarter to learn about the state of the economy, to decide how to change government consumption in response to the state of the economy, to pass the changes in policy through the legislature, and actually implement the policy. As a result, such an assumption is widely used in past studies. 5 Recursive VAR model (suggested by Sims, 1980) is constructed with the following variables: [RGCON, RGDP, RIR, RCUR, RER], where RGCON is assumed contemporaneously exogenous to all other variables. 6 RGCON is the log of real government consumption (multiplied by 100). RGDP is the log of the real GDP (multiplied by 100). RIR is the three-month (ex-post) 4 These two papers also discuss some open economy aspects. The results of these studies are discussed in Section 6.1, in comparison with the results of the current study. On the other hand, In terms of methodology, this paper uses VAR based two-sage process to consider various characteristics simultaneously, and also estimates panel VAR for two distinguished groups to further check the robustness of the results. 5 For example, see Fatas and Mihov (2001), Blanchard and Perotti (2002), Müller (2008), Kim and Roubini (2008) for the U.S., and Corsetti and Müller (2006), Ravn, Schmitt-Grohé, and Uribe (2008), Perotti (2004), Beetsma, Giuliodor, and Klassen (2008), and Ilzetzki, Mendoza, and Végh (2009) for various countries. 4

5 real interest rate. 7 RCUR is the balance on goods and services in real term as a percentage of trend real GDP. 8 Note that balance on goods and services (from national income accounts) is used as data for current account/trade balance. 9 RER is the log of real effective exchange rate (multiplied by 100), where an increase is a depreciation. RGCON, RCUR, and RER are the main variables of interests. RGDP represents the general economic activities, and is included to capture the (lagged) endogenous responses of government consumption to economic activities. RIR is included because it is an important variable in the transmission of fiscal policy. The model is estimated for 19 OECD countries in which data series are available for a long time span: Australia (AUS), Austria (AUT), Belgium (BEL), Canada (CAN), Switzerland (CHE), Denmark (DNK), Spain (ESP), Finland (FIN), France (FRA), Germany (GER), the U.K. (GRB), Italy (ITA), Japan (JPN), Netherlands (NLD), Norway (NOR), New Zealand (NZL), Portugal (PRT), Sweden (SWE), and the U.S. (USA) Quarterly data are used. The estimation period is 1981:2 to 2006:4. A constant term and four lags are assumed in the model. 10 Refer to Appendix 1 for details on the data. Figure 1 reports the impulse responses of government consumption, current account, and real exchange rate to government consumption shocks, with 68% probability bands over four years. 11 The responding variables are denoted at the far left of each row. For each column, the first three rows and the next three rows show the results for two different countries. The names of the two countries (the first one for the first three rows and the second one for the next three rows) are denoted at the top of each column. Results show that current account worsening is found in many countries, but a current account improvement is also found in some countries. Real exchange rate depreciation is found in some countries but a real appreciation is also found in other countries. The second and the sixth columns in Table 1 summarize the signs of impulse responses. Here, + (or - ) shows the case in which impulse responses are positive (or negative), with more than 84% probability, for any single horizon and +,- (or -,+ ) shows the case in which they are positive (or negative) initially 6 Since RGCON is assumed contemporaneously exogenous to all other variables, the ordering among other variables does not affect the results when the effects of RGCON shocks are examined. Refer to Christiano, Eichenbaum, and Evans (1999). 7 To construct the real interest rate, the annualized quarterly GDP deflator inflation rate is subtracted from the three-month treasury bill rate. 8 To construct the trend real GDP, a linear trend is assumed for log of real GDP. 9 Quarterly current account data is not available for some countries; therefore, exports of goods and services minus imports of goods and services is used. Some past studies have suggested that short-run dynamics of current account and trade balance are similar (for example, Kim, 2001). 10 All real variables are constructed as domestic real terms. 11 The probability bands are constructed by Monte Carlo integration, as in Doan (2004). 5

6 for any single horizon but negative later (or positive) for any single horizon, with more than 84% probability. 12 No sign (or blank) indicates that there are no horizons in which impulse responses are different from zero with more than 84% probability band. For real exchange rate, eight countries have + signs, seven countries have - signs and one country has a +,- sign. For current account, six countries have + signs, eight countries have - signs, and three countries have -,+ signs. Not only the signs of responses but also the sizes of responses are quite different across countries. To summarize the size of responses in each country, the ratios of current account and real exchange rate response to government consumption response under government consumption shocks are calculated. That is, K K RES _ RCUR RCUR k / RGCON k (1) k 1 k 1 K K RES _ RER RER k / RGCON k (2) k 1 k 1 where RCUR k, RGCON k, and RER k are the impulse responses of RCUR, RGCON, and RER at k- period after government consumption shocks, respectively. RCUR and RER responses are divided by RGCON response to take care of the difference in the size of government consumption shocks across countries. In addition, cumulative (or average) responses are used to calculate the ratio because cumulative (or average) effects may better summarize the effects over a certain horizon. The ratios are calculated for various horizons, such as two quarters, one year, and two years (that is, K = 2, 4, 8). The third, fourth, and fifth columns in Table 1 show the measures for real exchange rate for the two-quarter, one-year, and two-year horizons, respectively. The seventh, eighth, and ninth columns in Table 1 show the measures for current account. The median response and 68% probability bands (in parenthesis) are reported. Here, * indicates that the number is different from zero, with more than 84% probability The bands are 68% probability bands. Therefore, when all lines are above zero, the probability that responses are positive is greater than 84%. 13 The ratios are calculated for each draw. Then, the probability is calculated based on those ratios. Also note that these numbers are constructed based on both (cumulative) responses of government consumption and real exchange rate (or current account), but the signs in the second and the sixth columns show are solely based on non-cumulative) responses of government consumption. Since the uncertainty in these 6

7 As discussed, the signs of the effects on current account and real exchange rate are very much diversified across countries. In addition, the sizes of the effects are also quite diversified across countries. For example, the median values range from 1.3 (ESP, ITA) to 1.9 (USA) for real exchange rate with two-year horizon. Current account responses for two-year horizon range from 1.0 (FIN) to 0.5 (NOR). To further infer what is the representative effect of government consumption shock, panel VAR model for all 19 countries is estimated. The individual fixed effect is introduced in the model, to control for country-specific factors that are not included in the model. The identifying assumption is the same as that in the individual VAR model. The impulse responses are reported in Figure 2 under Full Sample. The results show that a current account worsening and a real exchange rate depreciation under a positive government consumption shock are the representative consequence in these OECD countries. Based on these results, two points are worth mentioning. First, as reviewed by past studies (for example, Kim and Roubini, 2008), current account worsening and real exchange rate appreciation are predicted as the consequences of expansionary government consumption shocks in many theoretical models. However, current account improvements and real exchange rate depreciation are found in some countries, which is puzzling. Real exchange responses are more interesting since real exchange rate depreciation is found in more countries and also in the panel estimation that comprises all countries. Second, the sizes and the signs of the effects on current account and real exchange rate are very diversified across countries. This diversified result across countries calls for investigation on the influence of country characteristics on the effects of government consumption shocks. 3. Theoretical Review In this section, theories are reviewed for the influence of country characteristics on the effects of government consumption shocks on current account/trade balance and real exchange rate Country Size measures reflect the uncertainty on both responses and multiple horizons, the measures are less likely to be different from zero than the impulse responses of government consumption themselves as can be seen in Table Refer to Kim and Roubini (2007) for the summary of general effects of fiscal policy on current account and real exchange rate. 7

8 The size of country is at the center of the effects of structural shocks in open economies. Typically, theoretical models are divided into two types depending on size: small and large open economy models. The main difference between these two types of models is whether an economic shock in a country affects the world equilibrium condition and the rest of the world. Since the current account and the real exchange rate tend to reflect the difference in economic condition between a country and the rest of the world, a shock has a smaller effect on current account and real exchange rate in a large open economy because it affects the world equilibrium condition in a large open economy. In the traditional MFD model, an increase in government spending causes upward pressure on domestic interest rate, appreciates nominal and real exchange rates, and worsens current account. In the case of large open economy, exchange rate appreciation and current account worsening are weaker as the world interest rate rises. In the case of small open economy where the world interest rate is given, the exchange rate appreciation and current account worsening are more severe. In simple small open economy intertemporal model with one good (such as those discussed in Obstfeld and Rogoff, 1995a, and Frankel and Razin, 1996), a temporary increase in government consumption decreases the resources available for consumers; therefore, current account worsening is found as consumers smooth consumption by borrowing from the rest of the world. However, in a large open economy, current account worsening is smaller since consumers borrow less from the rest of the world as the world real interest rate increases. In the New Open Economy Model (NOEM) such as that of Obstfeld and Rogoff (1995b), a similar result is obtained because a positive temporary government consumption shock worsens the current account through the same mechanism Trade Openness An important mechanism through which government consumption shocks affect real exchange rate is that the relative price of home vs. foreign goods increases as government consumption mostly falls on domestic goods. This feature is empirically supported, and recent Dynamic Stochastic General Equilibrium (DSGE) models on fiscal policy incorporate this feature. When this feature is combined with a home bias in consumption, the relative consumer price levels of home vs. foreign countries increases. In other words, the (consumption-based) real exchange rate appreciates. However, if there is no home bias in consumption, the relative consumer price level of home vs. foreign countries does not change because domestic and foreign consumer price levels change proportionately. Therefore, in a country with lower trade openness 8

9 (i.e., more home bias in consumption), a government consumption shock would enable the (consumption-based) real exchange rate to appreciate more significantly. Such a mechanism is also found in Ravn, Schmitt-Grohe, and Uribe (2008), who developed a theoretical model with deep habit mechanism to explain the real exchange rate depreciation following government consumption shocks. In the baseline model of Ravn, Schmitt- Grohe, and Uribe (2008) without any home bias in consumption, an increase in government consumption of domestic economy leads to a decline in domestic markups relative to foreign markups because an increase in aggregate demand provides an incentive for firms to lower markups. This implies that domestic prices become lower than foreign prices, or that real exchange rate depreciates. However, in the model with home bias in consumption, the abovementioned mechanism that appreciate real exchange rate is also effective, and real exchange rate depreciation is smaller. That is, a government consumption shock leads to more real exchange rate appreciation (i.e., less real exchange rate depreciation) in a country with lower trade openness (i.e., more home bias in consumption). Corsetti and Müller (2006) and Müller (2008) discuss how trade openness influences the effects of fiscal policy on trade balance. The government consumption shocks improve the terms of trade because government consumption mostly fall on domestically produced goods. The improvement of terms of trade increases the real return to investment more strongly in a relatively more open economy because consumption and investment goods include more import components. As a result, current account worsens more in an economy with larger trade openness 3.3. Exchange Rate Regime The role of exchange rate regime has long been discussed in the context of the models with price stickiness. In the sticky price model, the nominal exchange rate changes translate into real exchange rate changes under floating exchange rate regime. However, such a mechanism would not work under fixed exchange rate regime since nominal exchange rate changes are not allowed. For example, in the traditional MFD model, government spending shocks appreciate real exchange rate via nominal exchange rate appreciation under floating exchange rate regime. However, under fixed exchange rate regime, real exchange rate does not change significantly in the short run because nominal exchange rate remains constant and prices are sticky. Therefore, a stronger short-run real exchange rate appreciation could be found in a more flexible exchange rate regime. However, the conclusion on the direction of the effect is the opposite in the NOEM models, such as in Obstfeld and Rogoff (1995b), because government consumption shocks depreciate the nominal exchange rate in the floating exchange rate regime. Although real 9

10 exchange rate in Obstfeld and Rogoff (1995b) is constant, it can lead to real exchange rate depreciation in an extended model (e.g., Betts and Devereux, 2000, Kim and Lee, 2008). Thus, larger real exchange rate depreciation can be found in a more flexible exchange rate regime. Although the type of exchange rate regime has an influence on current account effects of government consumption shocks, the exact results depend on the types and the specifications of theoretical models. In the traditional MFD model, the relative size of current account worsening under floating and fixed exchange rate regimes depend on the size of the elasticity of import demand with respect to income and the elasticity of trade balance with respect to real exchange rate. When the elasticity of import demand with respect to income is small and the elasticity of trade balance with respect to real exchange rate is large, current account worsening is larger in the floating exchange rate regime than in the fixed exchange rate regime because expenditure switching effect (that works strongly in the floating exchange rate regime) is strong but income absorption effect (that works strongly in the fixed exchange rate regime) is weak. However, the former elasticity is large and the latter elasticity is small, the opposite result is obtained International Capital Mobility Under a low degree of international capital mobility, the effects of government consumption shocks on real exchange rate are likely to be weaker. Under a low degree of international capital mobility, a higher interest rate differential across countries is likely to be allowed. In the Mundell-Flemming model under the floating exchange rate regime, the government consumption shocks tend to appreciate real exchange rate less in the case of a lower degree of capital mobility because, in such a case, less upward pressure on the interest rate would be transmitted to the appreciation of nominal and real exchange rates. With a similar reasoning, exchange rate depreciation is likely to be weaker under a low degree of capital mobility in a model such as that of Obstfeld and Rogoff (1995b). Under a low degree of international capital mobility, the effects on current account are also likely to be weaker. First, as the effects on real exchange rate are weaker, the expenditure switching effect and negative effects on current account are likely to be weaker in the MFD model. In addition, current account movements are driven by international capital movements in the intertemporal model. Under a low degree of international capital mobility, the negative effects on current account are likely to be weaker because capital is less mobile across countries and it is harder for a country to borrow or lend Persistence 10

11 Persistence of government consumption shock is also an important consideration in theory, especially in relation to the effects on current account. In a simple small open economy intertemporal model with one good, a temporary increase in government consumption temporarily decreases the resources available for consumers. Therefore, current account worsening is found as consumers smooth consumption by borrowing from the rest of the world. However, a permanent increase in government consumption would not change the current account. That is, consumers do not borrow from abroad because the resources available for consumers decrease permanently. Therefore, current account worsening is more likely in the case of temporary government consumption shock. This conclusion also holds in flexible price open economy DSGE models (i.e., see Corsetti and Müller, 2006) and also in some NOEM models (see Obstfeld and Rogoff, 1995b, Betts and Devereux, 2000). On the other hand, a permanent government consumption shock can appreciate real and nominal exchange rates in the long run because government consumption mostly falls on domestic goods. Following permanent government consumption shocks, economic agents expect nominal and real exchange rates to appreciate in the future. Appreciation expectation would appreciate the exchange rate immediately (e.g., interest parity condition implies such a relation). In this way, a permanent shock can lead to stronger real exchange rate appreciation than would a temporary shock, even in the short run. If expenditure switching effect is effective, current account may worsen more severely in the case of a permanent shock. This implication on current account responses contrasts with the implication of intertemporal model discussed in the previous paragraph. This mechanism is shown in the MFD model (see Krugman and Obstfeld, 2008) Summary Table 2 summarizes the theoretical predictions of three types of models and the empirical result (reported in Sections 5). MFD, Equilibrium, and NOEM indicate the predictions of MFD model, flexible price equilibrium model including intertemporal model and Real Business Cycle (RBC) model, and basic NOEM models, including those of Obstfeld and Rogoff (1995b), Betts and Devereux (2000), and their simple extensions, respectively. Result indicates the empirical result. The row titled General Prediction shows the basic prediction of each model and empirical result on real exchange rate and current account responses under positive government spending shocks. For example, (-) under Real Exchange Rate Response and MFD indicates that real exchange rate appreciates (i.e., real exchange rate decreases) in response to a positive government consumption shock. Other rows, titled with various country characteristics, show the prediction of each model and the empirical result when the value of each 11

12 country characteristic increases. For example, (+) in the row titled Country Size under Real Exchange Rate Response and MFD indicates that the effect of a government consumption shock on real exchange rate becomes more positive as the country size increases Measures of Country Characteristics and Empirical Methodology 4.1. Empirical Methodology The following method is used to infer the influence of various country characteristics on the effects of government consumption shocks. First, the ratios of real exchange rate and current account cumulative response to government consumption cumulative response (RES_RER and RES_RCUR) are obtained from the estimated VAR models for each country. Then, these ratios are regressed on various measures of country characteristics. To account for uncertainty, the VAR model is simulated to obtain 2500 values of the estimated ratios, the regression is performed 2500 times, and 5 th, 16 th, 84 th, and 95 th percentiles of empirical distribution of regression coefficients are obtained. A similar method is used by Miniane and Rogers (2007) Measures of Country Characteristics To measure the size of country, the ratio of the nominal GDP of each country (in USD) to the aggregate nominal GDP of 19 countries (in USD) is used ( SIZE ). Two measures of trade openness are used. First, the ratio of imports to GDP is used as in Corsetti and Müller (2006) ( OPEN1 ). This ratio plays an important role in the mechanism described in Corsetti and Müller (2006). Second, another measure of openness, the ratio of the sum of imports and exports to GDP, is also used to check the robustness of results ( OPEN2 ). For exchange rate regime (or exchange rate flexibility), two measures are used. First, the exchange rate regime classification suggested by Reinhart and Rogoff (2004) is used ( EXC1 ). Second, the classification of exchange rate regime in the IMF Annual Report on Exchange Rate Arrangements and Exchange Restrictions is used ( EXC2 ). In both classifications, values from 1 to 4 are assigned based on the flexibility of exchange rate. A higher number indicates a higher degree of exchange rate flexibility. As a measure of international capital mobility, the measure of financial openness developed by Chinn and Ito (2008) is used ( CAP ). The index of Chinn and Ito (2008) is used 15 In Obstfeld and Rogoff (1995b), permanent government spending shocks improve current account because output is demand-determined in the short run, and the short-run output level is larger than the longrun output level. In General Prediction of NOEM model (Table 2), the temporary shock case is used as benchmark case because results from VAR of individual country show that government consumption shocks are temporary in all countries. 12

13 among various measures developed in past studies because other measures do not cover all countries and full sample periods are considered in this paper. A higher number indicates a higher degree of international capital mobility. For these measures, the average value for the period , using annual (EXC1, EXC2, CAP) or quarterly (SIZE, OPEN1, OPEN2) data, is calculated for each country. Finally, the estimated impulse responses of government consumption to government consumption shocks are approximated by AR-1 process. Then, the approximated AR-1 coefficient is used as the measure of persistence in government consumption shocks. The following formula is used to approximate AR-1 coefficient: [RGCON 2 /RGCON 1 + (RGCON 3 /RGCON 1 ) 1/2 + (RGCON 3 /RGCON 1 ) 1/3 + +(RGCON m+1 /RGCON 1 ) 1/m ]/m. For the value of m, 8 and 4 are considered PER1 and PER2, respectively. 16 Table 3 shows the value of each measure for 19 countries, while Table 4 reports correlations among those measures. Correlations of OPEN1 and OPEN2, and of PER1 and PER2, are very high (0.99 and 0.98, respectively). Correlation of EXC1 and EXC2 are also quite high (0.74). Given these high correlations between two alternative measures of each country characteristic, PER1, OPEN1, and EXC1 are used in most regressions, and PER2, OPEN2, and EXC2 are used once to examine the robustness of the results. 5. Empirical Results 5.1. Results of the Baseline Models Table 5 report results from regression for real exchange rate and current account responses at two-quarter, one-year, and two-year horizons. The median value is reported, and 68% probability bands are reported in parenthesis. * and ** represent the case that the estimate is different from zero with more than 84% and 95% probability, respectively. The positive effects of OPEN1 and EXC1 on real exchange rate responses are clear in all horizons; the estimated positive coefficients are different from zero, with more than 95% probability in two-quarter horizon, and with more than 84% probability in all three horizons. CAP has a positive effect, which is different from zero with more than 84% probability in two-quarter horizon. SIZE has a negative effect, which is different from zero with more than 95% probability in two-quarter horizon. The effect of PER is not clear; 68% probability bands include 0 in all three horizons. 16 For simplicity, (-) values of a k are treated as 0. The approximated measure for AR-1 coefficient is calculated for each draw, and then the corresponding measure is used for each regression using each draw. 13

14 The positive effects of SIZE and OPEN1 on current account responses are clear; the estimated positive coefficients are different from zero with more than 95% in all three horizons. The negative effects of CAP and PER on current account are also clear; the estimated negative coefficients are different from zero with more than 84% in all horizons and with more than 95% in two horizons. EXC1 has a positive effect, which is different from zero with more than 84% in two-quarter horizon Extended Experiments Various extended experiments are performed to examine the robustness of the results. Tables A.2 A.8 show full results. Table 6 provides the summary of the results. First, alternative measures for country characteristics are used. As discussed in Section 4, alternative measures for trade openness (OPEN2), exchange rate flexibility (EXC2), and persistence of shocks (PER2) are considered. Table 6 under Alternative Measure 1 and Table A.2 report the results. Second, the following alternative measures for effects of government spending shocks on current account and real exchange rate are considered. K 2K RES _ RCUR1 RCUR k / RGCON k (3) k 1 k 1 K 2K RES _ RER1 RER k / RGCON k (4) k 1 k 1 These measures are used because the nature of government consumption shock may be better captured by considering a longer horizon of government consumption responses. 2, 4, and 8 quarters are considered as K. Table 6 under Alternative Measure 2 and Table A.3 reports the results. Third, the following alternative measures for effects of government spending shocks on current account and real exchange rate are considered: K K RES _ RCUR2 RES _ RCUR / GY RCURk / RGCON k GY (5) k 1 k 1 14

15 K K RES _ RER2 RES _ RER / GY RERk / RGCONk GY (6) k 1 k 1 where GY is the average ratio of real government consumption to real GDP over the sample period. The original measures RES_RCUR and RES_RER are divided by GY in order to account for the differences in the units of impulse responses of government consumption and those of real exchange rate and current account. In the case of current account measure, the original current account responses (RCUR k ) are measured as percent deviation from the initial ratio of current account to the trend GDP. Meanwhile, the original government consumption responses (RGCON t ) are measured (approximated) as percent deviation from the original level of government consumption. 17 Since the size of the level of current account changes and the size of the level of government consumption changes may be directly comparable, the measures of current account and government consumption responses are approximately matched by multiplying the average ratio of government consumption to GDP over the sample period. In the case of real exchange rate measure, both original real exchange rate responses (RER t ) and original government consumption responses (RGCON t ) are (approximately) measured as percent deviation from their own original levels. However, percent changes in real exchange rate may depend on the size of the level of government consumption changes as a ratio to the size of the economy (or GDP). 18 Therefore, the original government consumption responses are multiplied by the average ratio of government consumption to GDP over the sample period. Table 6 under Alternative Measure 3 and Table A.4 report the results. Fourth, in addition to the five-variable VAR model for each country, an eight-variable recursive VAR model is also constructed to control for world aggregates. The model is [RGDP*, RGCON*, RIR*, RGCON, RGDP, RIR, RCUR, RER], where RGDP*, RGCON*, and RIR* are 17 Note that the current account data are constructed as the ratio to the level of current account to the trend GDP while natural logarithm is taken for the level of government consumption. 18 Changes in the level of real exchange rate do not have much meaning because the real exchange rate data is an index. Therefore, % changes in the level of real exchange rate are more meaningful measures. Thus, % changes in the level of real exchange rate may depend on changes in the level of government consumption relative to GDP, rather than changes in the level of government consumption or the % changes in the government consumption. The real exchange rate may depend on the overall condition of the economy. The % changes in government consumption may be problematic because they can imply significantly different changes in the level of government consumption. For example, if the initial level of government consumption is very small in number, then, even a large % changes in government consumption from the initial level would not affect the economy significantly. The level of changes in 15

16 the log of world aggregate real GDP, the log of world aggregate real government consumption, and the world aggregate real interest rate, respectively. 19 In this model, the world aggregates are assumed to be contemporaneously exogenous to other variables, including domestic government consumption; however, domestic government consumption is assumed to be contemporaneously exogenous to other variables. This model controls for world aggregates in order to identify country specific domestic government consumption shocks. For example, in global recession, some countries may take a fiscal expansion simultaneously. In such a case, the effects of domestic fiscal shocks may be mixed with the effects of foreign fiscal shocks or global shocks in the model that does not control for world aggregates. Table 6 under World Aggregate and Table A.5 report the results. Fifth, many countries in the sample are included in the European Monetary Union (EMU) from Some past studies such as Blanchard and Giavazzi (2002) suggest that the behavior of the current account change drastically with EMU. In this regard, the model is estimated for the period before EMU ( ). Table 6 under Before EMU and Table A.6 reports the results. Sixth, currencies of Australia, Canada, and New Zealand are known as commodity currencies. Some past studies like Chen and Rogoff (2003) suggest that commodity currencies differ in their behavior from other currencies. In this regard, a constant dummy for these three countries is added in the second stage estimation. Table 6 under Commodity Currency and Table A.7 report the results. Seventh, government budget balance may have an important implication on the effects of fiscal policy. By constructing a model that includes government budget balance additionally, the robustness of the results is checked. The quarterly data on budget balance is only available for limited number of countries and limited sample periods. So it is hard to perform the second stage estimation after estimating individual VAR s. Therefore, individual country results are checked for those countries where quarterly data series on government budget balance is available for the full sample. Those countries are USA, CAN, JPN, and GRB. As in the baseline model, government consumption is assumed contemporaneously exogenous to all other variables including budget balance. In addition, the model indlucing structural government budget balance (instead of government budget balance) is also estimated. 20 government consumption may also be problematic. For example, if the size of GDP is huge, a large size of the level of changes in government consumption may not have much effect on the economy. 19 For the model of each country, world aggregate, excluding own country is used. The aggregate measures are constructed by the method suggested by Beyer, Doornik, and Hendry (2001), using a time-varying weight of nominal GDP in USD terms. 20 Structural government budget balance is constructed by using the residual from the regression of government budget balance on output gap. Potential output is calculated using H-P filtered real GDP. 16

17 The estimated coefficients are not exactly the same in some cases but quite stable. For example, as in the baseline result (in Table 1), the positive response of RER is significant in USA and GRB but the negative response of RER is significant in CAN. In addition, the relative ranking of countries on the size of effects does not change much. Table A.8 reports the results. Table 6 summarizes the results of the experiments in Sections 5.1. and 5.2. (+)* (or (- )* ) indicates that the effect is positive (or negative) with more than 84% probability at least for one horizon. (+)** (or (-)** ) indicates that the effect is positive (or negative) with more than 95% probability at least for one horizon. The baseline results are often consistent with the results from the extended experiments. A positive effect of SIZE on current account responses and a negative effect of PER on current account are quite robust in all experiments except for one case in which insignificant effect is found. A negative effect of CAP on current account is found in all experiments but one case in which a positive effect is found. A positive effect of OPEN on current account, a negative effect of SIZE on real exchange rate, and positive effects of OPEN, EXC, and CAP on real exchange rate are less robust but found in at least four out of seven cases. PER does not seem to have a strong effect on real exchange rate response. The signs of the effect of EXC on current account responses are mixed Panel VAR with Non-Interpolated Data Some studies such as Perotti (2004) and Ilzetzki, Mendoza, and Végh (2009) suggest that data on government consumption is often interpolated and it is important to use non-interpolated data. In this regard, Ilzetzki, Mendoza, and Végh (2009) document the sources of noninterpolated dataset for various countries. However, the sample period is too short to estimate the individual country model for many countries considered in this paper. Therefore, panel VAR models are estimated for groups of countries with different characteristics to check the robustness of the results. Sample countries are divided into two distinct groups based on each characteristic, that is, large vs. small size, large vs. small trade openness, high vs. low flexibility, high vs. low capital mobility, and high vs. low persistence of shocks. Then, the effects of government consumption shocks in two groups are compared for each characteristic. In addition, the fixed vs. floating exchange rate regimes are also compared by using countries and sub-samples of the fixed and floating exchange rate regimes. This analysis cannot consider various country characteristics 17

18 simultaneously, but it may still provide complementary evidence based on non-interpolated data. 21 The individual fixed effect is introduced in the Panel VAR model to take care of countryspecific effects that are not captured in the model. The variables and the identification are the same as before. Table A.9 reports the detailed effects in each model. Table 7 (1) shows the probability that the effect is larger in the group of countries with high value of each characteristic than in the group of countries with low value of each characteristic. For example, 40.0 under SIZE at two-quarter horizon of real exchange rate implies that the probability (that the effect on real exchange rate is larger in the large size of countries than in the small size of countries) is 40%. 22 Then, Table 7 (2) shows transformed signs that can be compared to other results based on the second stage regression using the individual VAR results. (+) (or (-) ) indicates that the probability is larger (or smaller) than 50%. (+)* (or (-)* ) indicates that the probability is larger than 84% (or smaller than 16%). (+)** (or (-)** ) indicates that the probability is larger than 95% (or smaller than 5%). The positive effect of EXC on real exchange rate responses and the positive effects of SIZE and the negative effect of PER on current account responses are consistent with the previous results based on the second stage estimation. However, some results like the effect of OPEN on RER responses and the effect of CAP on current account responses are not consistent with the previous results. Finally, panel VAR models are constructed using all non-interpolated data. Figure 2 under Non-Interpolated shows the impulse responses of government consumption, real exchange rate, and current account to government consumption shocks. As in the case of previous full sample results (reported in Figure 2 under Full Sample ), real exchange rate depreciates and the current account worsens. Therefore, the conclusion that real exchange rate depreciation and current account worsening are the representative consequences of positive government consumption shocks is robust with the usage of non-interpolated data. 6. Performance of Theory 6.1. Summary of Empirical Results 21 See Appendix 1 for more details on data and grouping of countries and samples. In addition, the result for the group of countries and samples with the highest value of capital mobility is also reported. The result is clearly different from the results for all countries and samples using non-interpolated data. 22 The effects are compared for 2500 times, based on Monte Carlo Integration of each model with 2500 draws. 18

19 Based on all the empirical results, the most robust findings are positive effect of EXC on RER, positive effect of SIZE on RCUR, and negative effect of PER on RCUR. These effects are found to be significant in most experiments. In addition, the median estimates show the same direction of effects mostly even in the cases that the effects are not significant. Then, negative effect of SIZE and positive effects of OPEN and CAP on RER, positive effect of OPEN and EXC and negative effect of CAP on RCUR are often found although these results are less robust. In Table 2 under Results, these results are summarized with signs.? indicates that the results are less robust. For General Prediction, the directions of the effect of government consumption shocks on real exchange rate and current account are reported. The results from the panel VAR s of all countries, using both the full sample and non-interpolated data, show that real exchange rate depreciates ( + ) and current account worsens ( - ) in response to positive government spending shocks. Also, in the individual country VAR s, such results are found in more countries. But? is added since different results are obtained in some countries. Some past studies like Corsetti, Meier and Muller (2010) and Ilzetzki, Mendoza, and Végh (2009) document that more current account worsening is found in a fixed exchange rate regime, which is consistent with the result of the current paper. On the other hand, both studies discuss the influence of exchange rate regime on the effects of government consumption shocks real exchange rate and current account. While Ilzetzki, Mendoza, and Végh (2009) found that more appreciation is found in a fixed exchange rate regime, Corsetti, Meier and Muller (2010) found that more depreciation is found in a currency peg. The result of current paper supports Corsetti, Meier, and Muller (2010). The MFD model fails to explain real exchange rate responses. The empirical results on the signs of real exchange rate responses are clear in one case: the positive influence of exchange rate flexibility. However, the predictions of MFD model do not match the sign. In addition, although they are less robust, the negative influence of country size and the positive effect of capital mobility are contradict with the predictions of MFD model. In terms of General Prediction, the empirical result on real exchange rate does not match the prediction of the MFD model. On the other hand, predictions on the signs of current account responses mostly match the signs of empirical results. However, the most important mechanism to explain the signs of current account responses in the MFD model is the real exchange rate effect (or expenditure switching effect), which clearly fails to match the data. Therefore, the MFD model fails to match the data. Note that this clear failure of the MFD model may not be clearly detected if only the general prediction of the model on the effects of government consumption shocks on real exchange rate and current account is tested. Although real exchange rate depreciation is found in 19

20 some countries, real exchange rate appreciation is also found in other countries. Hence, while the performance of the MFD model is suspected, it is difficult to be sure of the failure of the model. This suggests that this new dimension of empirical regularities (i.e., the influence of country characteristics on the effects) is very useful in judging the relative success and failure of theoretical models. The general prediction of equilibrium model on real exchange rate tends to fail since the equilibrium model predicts the appreciation of real exchange rate but the empirical results suggest the opposite. On the other hand, the equilibrium model predicts that current account worsens after government consumption shocks, which is consistent with the empirical results. However, in terms of the influence of country characteristics, the model fails to explain a few empirical results. The empirical result on the negative influence of shock persistence on current account is clearly at odd with the theory. Although less robust, the empirical result on the positive influence of trade openness does not match the theoretical prediction. This also suggests that this new dimension of empirical regularities is useful. The predictions of the basic NOEM models on the signs of both current account and real exchange rate responses are mostly consistent with the data. However, there is an important puzzling feature that is difficult to explain. The basic NOEM model predicts that current account worsens less severely in response to more persistent government consumption shocks. However, the empirical result shows the opposite. As this positive influence of shock persistence is also at the center of the intertemporal model, the failure in the data is worth paying attention Transmission Mechanism In the previous section, the relative successes and failures of theoretical models are discussed in view of the influence of country characteristics. The results show that the basic NOEM models tend to match most of empirical results. This section further explores transmission mechanism especially in view of the NOEM models. For this purpose, variables are added one by one in the baseline model. The identifying assumption is the same as before: government consumption is assumed contemporaneously exogenous to other variables. First, nominal effective exchange rate is included additionally to infer the role of price stickiness. Figure 2 under Extended Model 1 shows the impulse responses of real exchange rate, nominal exchange rates ( NER ) and the relative price ( RP, which subtracts NER responses from RER responses) from Panel VAR of all countries with full sample. Both real and nominal depreciation is strong and two variables are much correlated. On the other hand, the relative price does not contribute much to the real exchange rate depreciation. The results are similar in the 20