This chapter examines the empirical link between fiscal policy and the current account focusing on microstates, defined as countries with a population of less than 2 million between 1970 and 2009. The extent to which fiscal adjustment can lead to predictable development in the current account remains controversial, with two competing views. The traditional view argues that changes in fiscal policy are associated with changes in the current account through a number of channels that are discussed in the literature review. The traditional view is challenged by the Ricardian equivalence principle, which states that an increase in budget deficit (through reduced taxes) will be offset by increases in private saving, insofar as the private sector fully discounts the future tax liabilities associated with financing the fiscal deficit, hence not affecting the current balance.
This chapter employs panel regression and panel vector autoregression (VAR) to estimate the impact of fiscal policy on the current account. The main challenge in the empirical literature is how to measure fiscal policy that reflects deliberate policy decisions and not simply the impact of business cycle fluctuation. The conventional approach to addressing this problem is to use the cyclically adjusted fiscal data to identify deliberate changes in fiscal policy. The presumption is that cyclically adjusted changes in the fiscal balance reflect decision by policymakers to adjust tax rates and expenditure levels.1 IMF (2010) uses an alternative approach based on identifying changes in fiscal policy directly from historical records. While this approach could be superior to the conventional approach, this chapter follows the conventional approach because of the difficulties in constructing exogenous fiscal policy measures from historical records in microstates.
Panel regression results show that a percentage point improvement in the fiscal balance improves the current account balance by 0.4 percentage points of GDP (similar to the coefficient of 0.34 found for the global sample). The real effective exchange rate has no significant impact on the current account in microstates but the coefficient is significant in the global sample. Panel VAR results show that an increase in government consumption results in real exchange appreciation but the effect on the current account after an initial deterioration dies out quicker in microstates, in contrast to the global sample, where the deterioration remains for extended periods. The results imply that fiscal policy has little effect on the current account in microstates beyond its direct impact on imports. Overall, the results suggest that the weak relative price effect makes fiscal adjustment much more difficult in microstates.
The remainder of the chapter is organized as follows. The next section reviews the theoretical and empirical literature on fiscal policy and the current account. Following that the chapter reviews the literature on microstates with a focus on their characteristics that have implications for the current account. It then evaluates econometrically the relationship between fiscal policy and the current account using both panel regression and panel VAR.
Literature Review
This paper builds on the literature on fiscal policy and the current account and the literature on microstates. The theoretical and empirical relationship between fiscal policy and the current account is studied extensively. Theoretically, there are competing views that give different results depending on the kind of transmission mechanisms considered in the model to explain the link between fiscal policy and the current account.
Theoretical studies differentiate between intratemporal and intertemporal transmission mechanisms (Mundell, 1960; Fleming, 1962; Salter, 1959). The Mundell-Fleming model and the Swan-Salter model focus on an intratemporal (the relative price effect) mechanism. In the Mundell-Fleming model, an expansionary fiscal policy, by raising domestic demand and increasing the interest rate, leads to a real exchange appreciation through higher capital inflows to the domestic economy. In this model, financial openness and exchange rate regime can affect the effectiveness of the transmission mechanism. In the Swan-Salter model, exchange rate is defined as the relative price of tradables to nontradables. If the government spending is skewed to nontradables, the induced real exchange appreciation might worsen the trade balance by driving production away from tradables and switching consumption towards tradables.
The intertemporal approach (Frenkel and Razin, 1996; Baxter, 1995), on the other hand, suggests that declines in public saving resulting from a fiscal expansion would be offset by an equal increase in private saving, leaving the national saving unaffected. In models of the intertemporal mechanism, an increase in debt-financed government spending lead forward-looking private agents to consume less and increase labor supply to offset the future tax increases, resulting in improvements in the current account that counteract the negative effect of government spending on the current account.
New open economy models that incorporate both the intertemporal and intratemporal mechanisms have been developed recently to address empirical findings on developed countries that show positive government spending shocks resulting in an increase in private consumption and real exchange depreciation in spite of the worsening of the trade balance. Monacelli and Perotti (2006) developed an open economy model with non-separable preferences mitigating the negative wealth effect of an increase in government spending and giving rise to a positive consumption response. Furthermore, when the elasticity of substitution between domestic and imported goods is sufficiently small, the model is also successful in delivering real exchange depreciation and trade balance deterioration after government spending shocks. Ravn, Schmitt-Grohe, and Uribe (2007) offer an alternative explanation using a two-country model that incorporates a deep habit mechanism. Under deep habits, an increase in government spending in the domestic economy leads to a decline in domestic markups relative to foreign markups, which induces the real exchange rate to depreciate. At the same time, a decline in domestic markups raises labor demand, giving rise to an increase in domestic real wages. In turn, the rise in wages leads households to increase their leisure consumption strongly enough to offset the negative wealth effect stemming from the increase in government spending, resulting in an equilibrium increase in private consumption.
Empirically, the evidence is less debatable and the balance of evidence seems to support the intratemporal mechanism of a strong relationship between fiscal policy and the current account. Empirical research on the relationship between fiscal policy and the current account can be grouped into two types, according to the fiscal variable of interest and the methodology used. Studies based on the panel regression approach (for example, Chinn and Prasad, 2003) examine the effect of changes in the fiscal balance on the current account. Generally, they find evidence suggesting that fiscal expansion worsens the current account. Estimates of the impact of 1 percentage point of GDP increase in the government deficit on the current account range between 0.2 and 0.7 percentage points of GDP, depending on the sample and techniques used. Studies based on VAR (Ravn, Schmitt-Grohe, and Uribe, 2007; Beetsma, Giuliodori, and Klaassen, 2008) analyze the effect of government spending on the current account. These studies find evidence to show that an increase in government spending has a deteriorating effect on the current account, except for countries like United States, where the results are mixed (Kim and Roubini, 2008).
An important issue in the VAR literature is the identification of the government spending shocks. There are two main approaches to identify government spending shocks, namely, recursive and narrative approaches. The recursive approach assumes that government consumption does not to react to changes in other variables within a given period (Blanchard and Perotti, 2002). The narrative approach examines official documents to capture specific episodes of large exogenous changes in government spending (Ramey and Shapiro 1998; IMF, 2010, 2011). This paper uses the recursive approach, taking into account the difficulty involved in trying to apply the narrative approach in the large sample of countries considered.
Ali Abbas and others (2011) apply both the panel regression and panel VAR approaches to study the effect of fiscal policy on the current account using a large sample of advanced, emerging market, and low-income economies. They find that a strengthening in the fiscal balance by 1 percentage point of GDP is associated with a current account improvement of 0.3 percentage points of GDP. This relationship appears to be stronger in emerging market and low-income economies, when the exchange rate is flexible, in economies that are more open, when output is above potential, and when initial debt levels are above 90 percent of GDP.
Studies on the impact of the relationship between fiscal policy and the current account in microstates are sparse. Imam (2008) attempts to identify policies that help reduce the current account in microstates. The results suggest that microstates are more likely to have large current account adjustments if they are already running large current account deficits; run budget surpluses; and are less open. Interestingly, Imam (2008) finds that changes in the real effective exchange rate do not help drive reductions in the current account deficit in microstates.
Characteristics of Microstates
This chapter defines microstates as countries with an average population of less than 2 million between 1970 and 2009 (see Table 10.1). Using this definition, about 42 microstates were identified, of which about 70 percent are islands and usually located in the Caribbean, the African region, or the Pacific. Microstates possess a wide range of characteristics such as location, climate, and size, which create a variety of comparative advantages as well as disadvantages. This section highlights some of the unique characteristics of microstates with a focus on those characteristics that have implications for the current account.
Real GDP Per Capita and Population of Selected Microstates, 2009
Real GDP Per Capita and Population of Selected Microstates, 2009
Country | Real GDP per Capita in US$ |
Real GDP per Capita in Purchasing Power Parity |
Population |
---|---|---|---|
Antigua and Barbuda | 12,920 | 18,778 | 87,600 |
The Bahamas | 16,300 | 22,868 | 341,713 |
Bahrain, Kingdom of | 26,021 | 39,200 | 791,473 |
Barbados | 9,244 | 17,504 | 255,872 |
Belize | 4,062 | 6,628 | 333,200 |
Bhutan | 1,831 | 5,113 | 697,335 |
Botswana | 6,064 | 13,384 | 1,949,780 |
Cabo Verde | 3,064 | 3,644 | 505,606 |
Comoros | 812 | 1,183 | 659,098 |
Cyprus | 31,280 | 30,848 | 871,036 |
Djibouti | 1,214 | 2,319 | 864,202 |
Dominica | 5,132 | 8,883 | 73,596 |
Equatorial Guinea | 15,397 | 31,779 | 676,273 |
Fiji | 3,326 | 4,526 | 849,218 |
Gabon | 7,502 | 14,419 | 1,474,586 |
The Gambia | 430 | 1,415 | 1,705,212 |
Grenada | 6,029 | 8,362 | 103,930 |
Guinea-Bissau | 519 | 1,071 | 1,610,746 |
Guyana | 2,656 | 3,240 | 762,498 |
Iceland | 38,029 | 36,795 | 319,062 |
Kiribati | 1,306 | 2,432 | 98,045 |
Lesotho | 764 | 1,468 | 2,066,919 |
Luxembourg | 105,044 | 83,820 | 497,854 |
Maldives | 4,760 | 5,476 | 309,430 |
Malta | 19,248 | 24,814 | 414,971 |
Mauritius | 6,735 | 12,838 | 1,275,323 |
Namibia | 4,267 | 6,410 | 2,171,137 |
Oman | 11,192 | 24,226 | 2,845,415 |
Qatar | 69,754 | 91,379 | 1,409,423 |
Samoa | 2,776 | 4,405 | 178,846 |
São Tomé and Príncipe | 1,171 | 1,820 | 162,755 |
Seychelles | 8,688 | 19,587 | 87,972 |
Solomon Islands | 1,256 | 2,547 | 523,170 |
St. Kitts and Nevis | 10,988 | 14,527 | 49,593 |
St. Lucia | 5,496 | 9,605 | 172,092 |
St. Vincent and the Grenadines | 5,335 | 9,154 | 109,209 |
Suriname | 2,668 | 6,930 | 519,740 |
Swaziland | 2,533 | 4,998 | 1,184,936 |
Trinidad and Tobago | 15,841 | 25,572 | 1,338,585 |
Vanuatu | 2,702 | 4,438 | 239,788 |
Real GDP Per Capita and Population of Selected Microstates, 2009
Country | Real GDP per Capita in US$ |
Real GDP per Capita in Purchasing Power Parity |
Population |
---|---|---|---|
Antigua and Barbuda | 12,920 | 18,778 | 87,600 |
The Bahamas | 16,300 | 22,868 | 341,713 |
Bahrain, Kingdom of | 26,021 | 39,200 | 791,473 |
Barbados | 9,244 | 17,504 | 255,872 |
Belize | 4,062 | 6,628 | 333,200 |
Bhutan | 1,831 | 5,113 | 697,335 |
Botswana | 6,064 | 13,384 | 1,949,780 |
Cabo Verde | 3,064 | 3,644 | 505,606 |
Comoros | 812 | 1,183 | 659,098 |
Cyprus | 31,280 | 30,848 | 871,036 |
Djibouti | 1,214 | 2,319 | 864,202 |
Dominica | 5,132 | 8,883 | 73,596 |
Equatorial Guinea | 15,397 | 31,779 | 676,273 |
Fiji | 3,326 | 4,526 | 849,218 |
Gabon | 7,502 | 14,419 | 1,474,586 |
The Gambia | 430 | 1,415 | 1,705,212 |
Grenada | 6,029 | 8,362 | 103,930 |
Guinea-Bissau | 519 | 1,071 | 1,610,746 |
Guyana | 2,656 | 3,240 | 762,498 |
Iceland | 38,029 | 36,795 | 319,062 |
Kiribati | 1,306 | 2,432 | 98,045 |
Lesotho | 764 | 1,468 | 2,066,919 |
Luxembourg | 105,044 | 83,820 | 497,854 |
Maldives | 4,760 | 5,476 | 309,430 |
Malta | 19,248 | 24,814 | 414,971 |
Mauritius | 6,735 | 12,838 | 1,275,323 |
Namibia | 4,267 | 6,410 | 2,171,137 |
Oman | 11,192 | 24,226 | 2,845,415 |
Qatar | 69,754 | 91,379 | 1,409,423 |
Samoa | 2,776 | 4,405 | 178,846 |
São Tomé and Príncipe | 1,171 | 1,820 | 162,755 |
Seychelles | 8,688 | 19,587 | 87,972 |
Solomon Islands | 1,256 | 2,547 | 523,170 |
St. Kitts and Nevis | 10,988 | 14,527 | 49,593 |
St. Lucia | 5,496 | 9,605 | 172,092 |
St. Vincent and the Grenadines | 5,335 | 9,154 | 109,209 |
Suriname | 2,668 | 6,930 | 519,740 |
Swaziland | 2,533 | 4,998 | 1,184,936 |
Trinidad and Tobago | 15,841 | 25,572 | 1,338,585 |
Vanuatu | 2,702 | 4,438 | 239,788 |
Small Size of Domestic Market
Microstates are characterized by the small size of their domestic market, making the level of domestic demand lie below the minimum efficient scale of output (Armstrong and others, 1993). Due to the small size, microstates are usually disadvantageous as a location for extensive industrial activities, especially those that could substantially raise growth. The small domestic market is less conducive for the development of indigenous technologies, limiting the growth of research and development, technical progress and technology acquisition. In addition, a small domestic market does not allow competitive firms to emerge within microstates because of the limited number of participants involved in any economic activity. As a result, prices of goods are generally higher in microstates than larger economies (Armstrong and others, 1993).
Small Domestic Resource Base
Microstates have a small and/or poor domestic resource base due to their small size. In countries where agriculture dominates economic activity, the sector tends to absorb a significant share of land endowment, thereby depriving other alternative production activities from this resource (Commonwealth Consultative Group, 1997). The relatively small population tends to make labor very scarce in microstates, and as a result output in microstates is usually enhanced through the accumulation of human or physical capital rather than through employment (Bhaduri, Mukherji, and Sengupta, 1982). The small size of the domestic market and scarce labor tend to narrow the structure of domestic output in microstates, making them dependent on a small number of activities and hampering the potential to implement import substitution industrialization strategies, thereby exposing them to exogenous shocks.
Narrow Range of Exports and Export Markets
Microstates have a narrow range of exports and export markets, due in part to the narrowness of their domestic production structures. The need for specialization tends to limit export-oriented domestic output to just a few products. Tourism and financial services are usually the main service sectors in microstates, normally complemented by an uncompetitive agricultural sector. Offshore financial services have become an important sector in microstates due to their strategic location and enabling local laws. Highly liberalized financial systems based on lax regulatory standards or strong supervisory frameworks have been a major attraction in the emergence of microstates as offshore financial centers. The export specialization of microstates renders them vulnerable to external shocks, and the vulnerability is exacerbated by reliance on export markets in just a few countries (Armstrong and others, 1998).
High Degree of Openness
Microstates are usually characterized by a high level of openness to trade. The small domestic markets and the tendency towards a high degree of specialization in output and export limit the potential for import substitution because of the adverse impacts on the price level and competitiveness. The importance of tradable goods to these economies necessitates the pursuit of a highly open trading regime. Consequently, import barriers are less important than for larger states (Selwyn, 1975). There is a substantial asymmetry between the domestic production patterns and consumption of microstates. Therefore, the proportion of imports in domestic consumption is high.
High Transport Cost and Lumpiness of Investment
Armstrong and others (1993) discussed extensively the specific problems of landlocked and island microstates, including high transport cost and a high degree of dependence of adjacent states for surface communications and port facilities and, therefore, access to export markets and import sourcing. High transport cost has the effect of reducing prices received for exports and raising prices of imports, leading the current account to deteriorate. Djankov, Freund, and Pham (2006) estimate that microstates were on the average 50 percent more distant from trading partners than larger countries. Microstates can suffer from lumpiness of investment due to small size. A single large investment project has an immediate effect on the current account, making it more volatile than it would be in larger economies.
Large Size of the Public Sector
The per capita cost of supplying public goods may be higher in microstates than in larger states due to the lack of economies of scale in supplying public goods (Figure 10.1). The public sector as a share of GDP tends to be bigger. Since government spending is biased toward nontradables, and since historically microstates have had large current account deficits, the current account tends to be structurally more vulnerable in these countries (Imam, 2008).
Government Consumption in Selected Microstates and Large Emerging Market Economies, 2010
(Percent of GDP)
Source: Authors’ calculations.While there is near consensus that the salient features of microstates make them disadvantageous, microstates also possess some advantages that could help external stability: greater social homogeneity and cohesion, a consequent greater flexibility and decision making efficiency, greater openness to change and the gains from greater openness (Streeten 1993). For instance, greater social homogeneity should enable adjustment to shocks to be more promptly handled because the shifting of adjustment onto other social groups is not possible (Alesina and Drazen, 1991).
Panel Regression
Data
This chapter uses data from 155 countries, of which 42 are microstates. The main data source is the IMF’s World Economic Outlook (WEO), where we obtained most of the fiscal variables. The real GDP per capita in purchasing power parity is taken from the World Bank’s World Development Indicators (WDI). We used the updated and extended version of the Lane and Milesi-Ferretti (2007) database to get data on net foreign assets. The real effective exchange rate is obtained from the IMF’s Information Notice System database. The data range from 1970–2009 whenever they are available. All details can be found in Appendices 10.1 and 10.2.
The Model
The benchmark specification assumes a fixed-effects model of the form:
where fi is the country fixed effects, Y is the current-account-to-GDP ratio, and X is a vector of explanatory variables including the ratio of the cyclically adjusted primary balance to potential GDP, the lagged log real GDP per capita, trade openness (ratio of imports plus exports to GDP), the ratio of lagged net foreign assets to GDP, the volatility of terms of trade, and the lagged log of real effective exchange rate.
The explanatory variables might influence the current account in the following ways.
Cyclically Adjusted Fiscal Balance
An increase in government balance could improve the current account through an increase in national saving in the absence of Ricardian equivalence. Reduction in government spending or a tax increase would lead to an increase in public saving. Unless the private sector is fully Ricardian, the total national saving would increase, thereby improving the current account. This chapter uses the cyclically adjusted primary balance (CAPB) to potential GDP ratio to capture fiscal balance. This choice is motivated by the fact that there could be some endogeneity problems between fiscal balance and the current account balance because of common reaction to the business cycle. IMF (2011) criticized what they call the conventional approach of using cyclically adjusted fiscal data on the grounds that CAPB may still include non-policy factors, or it may reflect deliberate policy responses to other developments affecting economic activity or to the current account itself. This chapter attempts to address these problems by applying a panel VAR methodology using another fiscal variable less vulnerable to the criticisms, namely government consumption, in the next section.
The CAPB is calculated by applying Hodrick-Prescott (HP) filtering to the real GDP to obtain the output gap measure and then using 1 and 0 as the elasticity of revenue and expenditure, respectively, with respect to the output gap. In this way, the CAPB becomes:
where R is revenue and grants, G is government spending less interest payment, Yp is the potential output, and Y is the actual output.
Trade Openness
Due to the high increase in international trade in the past decades, it would be interesting to study the relationship between trade openness and the current account balance. Microstates are characterized by their narrow range of exports, large proportion of imports, and high degree of openness. We would expect more trade openness in microstates to lead to more imports, implying a negative relationship between trade openness and the current account balance.
Net Foreign Assets
The relationship between net foreign assets (NFA) and the current account is ambiguous, as NFA may have two different effects. On the one hand, a negative relationship can exist between NFA and the current account, because high NFA might lead people to think that economies can afford to prolong trade deficits. On the other hand, high NFA could bring higher net income flows, resulting in a positive relationship with the current account balance.
Terms of Trade Volatility
Increased uncertainty associated with high volatility in terms of trade might lead agents in the economy to save more for precautionary reasons. Moreover, for the same reason, economies may also experience low investment. Therefore, we expect a positive relationship between high terms of trade volatility and the current account balance. The volatility of the terms of trade is constructed by taking the three-year moving standard deviation of the terms of trade of goods and services index.
Real Effective Exchange Rate
Depreciation of the real effective exchange rate makes imports more expensive and exports cheaper. As a result, the real effective exchange rate is expected to be negatively related with the current account balance.
Panel Regression Results
This section presents the panel regression results for the global sample and microstates. Tables 10.2 and 10.3 give the results obtained for the benchmark model and its variations under different specifications. To take into account crosscountry differences in time-invariant characteristics of our microstates, we use a panel fixed-effects estimation as our baseline model. We also control for income levels in all specifications of our model.
Panel Regressions: Global Sample
(Dependent variable: Current-account-to-GDP ratio)
p < 0.1,
p < 0.05,
p < 0.01.
Panel Regressions: Global Sample
(Dependent variable: Current-account-to-GDP ratio)
Fixed Effects | Fixed Time Effects | Pooled OLS | Excluding Oil-Exporting Countries |
Dynamic Panel GMM |
|
---|---|---|---|---|---|
Cyclically adjusted primary balance | 0.346*** | 0.322*** | 0.367*** | 0.289*** | 0.297*** |
10.61 | 9.76 | 11.41 | 8.63 | 8.57 | |
Lagged log per capita income | −0.481 | 0.836 | 0.628*** | −0.666 | −1.713* |
(−1.00) | 1.37 | 2.72 | (−1.35) | (−1.93) | |
Trade openness | −0.0128* | −0.00328 | −0.0154*** | −0.00684 | −0.0488*** |
(−1.87) | (−0.46) | (−3.13) | (−0.98) | (−4.92) | |
Lagged net foreign-assets-to-GDP ratio | 0.0221*** | 0.0263*** | 0.0256*** | 0.0203*** | −0.0120*** |
7.81 | 9.32 | 10.87 | 7.07 | (−2.59) | |
Volatility of terms of trade | 0.00152 | 0.00207 | 0.00116 | 0.00108 | −0.00123 |
0.65 | 0.89 | 0.5 | 0.47 | (−0.13) | |
Lagged log of real effective exchange rate | −1.237*** | −1.279*** | −1.032** | −0.968** | −1.569** |
(−2.79) | (−2.71) | (−2.41) | (−2.00) | (−2.23) | |
Lagged current-account-to-GDP ratio | 0.324*** | ||||
14.21 | |||||
Constant | 8.599* | −4.562 | −1.586 | 8.219* | 22.85*** |
1.87 | (−0.87) | (−0.53) | 1.75 | 2.7 | |
N | 2,370 | 2,370 | 2,370 | 2,211 | 2,131 |
p < 0.1,
p < 0.05,
p < 0.01.
Panel Regressions: Global Sample
(Dependent variable: Current-account-to-GDP ratio)
Fixed Effects | Fixed Time Effects | Pooled OLS | Excluding Oil-Exporting Countries |
Dynamic Panel GMM |
|
---|---|---|---|---|---|
Cyclically adjusted primary balance | 0.346*** | 0.322*** | 0.367*** | 0.289*** | 0.297*** |
10.61 | 9.76 | 11.41 | 8.63 | 8.57 | |
Lagged log per capita income | −0.481 | 0.836 | 0.628*** | −0.666 | −1.713* |
(−1.00) | 1.37 | 2.72 | (−1.35) | (−1.93) | |
Trade openness | −0.0128* | −0.00328 | −0.0154*** | −0.00684 | −0.0488*** |
(−1.87) | (−0.46) | (−3.13) | (−0.98) | (−4.92) | |
Lagged net foreign-assets-to-GDP ratio | 0.0221*** | 0.0263*** | 0.0256*** | 0.0203*** | −0.0120*** |
7.81 | 9.32 | 10.87 | 7.07 | (−2.59) | |
Volatility of terms of trade | 0.00152 | 0.00207 | 0.00116 | 0.00108 | −0.00123 |
0.65 | 0.89 | 0.5 | 0.47 | (−0.13) | |
Lagged log of real effective exchange rate | −1.237*** | −1.279*** | −1.032** | −0.968** | −1.569** |
(−2.79) | (−2.71) | (−2.41) | (−2.00) | (−2.23) | |
Lagged current-account-to-GDP ratio | 0.324*** | ||||
14.21 | |||||
Constant | 8.599* | −4.562 | −1.586 | 8.219* | 22.85*** |
1.87 | (−0.87) | (−0.53) | 1.75 | 2.7 | |
N | 2,370 | 2,370 | 2,370 | 2,211 | 2,131 |
p < 0.1,
p < 0.05,
p < 0.01.
Panel Regressions: Microstates
(Dependent variable: Current-account-to-GDP ratio)
p < 0.1,
p < 0.05,
p < 0.01.
Panel Regressions: Microstates
(Dependent variable: Current-account-to-GDP ratio)
Fixed Effects | Fixed Time Effects |
Pooled OLS | Excluding Oil -Exporting Countries |
Dynamic Panel GMM |
|
---|---|---|---|---|---|
Cyclically | 0.394*** | 0.443*** | 0.416*** | 0.313*** | 0.361*** |
adjusted primary balance | 5.25 | 5.71 | 5.63 | 4.02 | 5.49 |
Lagged log per capita income | −1.043 | 2.305 | 1.398* | −1.607 | −4.807*** |
(−0.76) | 1.2 | 1.73 | (−0.92) | (−3.17) | |
Trade openness | −0.0537*** | −0.0519*** | −0.0599*** | −0.0394** | −0.0335* |
(−2.84) | (−2.74) | (−3.70) | (−1.97) | (−1.88) | |
Lagged net foreign-assets-to-GDP ratio | 0.0363*** | 0.0381*** | 0.0421*** | 0.0322*** | 0.00589 |
4.57 | 4.53 | 7.59 | 3.87 | 0.78 | |
Volatility of terms of trade | −0.000823 | −0.0014 | −0.000528 | −0.00081 | −0.00163 |
(−0.27) | (−0.46) | (−0.18) | (−0.27) | (−0.72) | |
Lagged log of real effective exchange rate | 1.599 | −1.896 | 1.733 | 1.828 | 3.105 |
−0.58 | (−0.63) | 0.7 | 0.64 | 1.38 | |
Lagged current-account-to-GDP ratio | 0.428*** | ||||
10.59 | |||||
Constant | 2.84 | −7.807 | −17.52 | 4.434 | 26.75 |
0.14 | (−0.37) | (−1.17) | 0.19 | 1.43 | |
N | 510 | 510 | 510 | 472 | 444 |
p < 0.1,
p < 0.05,
p < 0.01.
Panel Regressions: Microstates
(Dependent variable: Current-account-to-GDP ratio)
Fixed Effects | Fixed Time Effects |
Pooled OLS | Excluding Oil -Exporting Countries |
Dynamic Panel GMM |
|
---|---|---|---|---|---|
Cyclically | 0.394*** | 0.443*** | 0.416*** | 0.313*** | 0.361*** |
adjusted primary balance | 5.25 | 5.71 | 5.63 | 4.02 | 5.49 |
Lagged log per capita income | −1.043 | 2.305 | 1.398* | −1.607 | −4.807*** |
(−0.76) | 1.2 | 1.73 | (−0.92) | (−3.17) | |
Trade openness | −0.0537*** | −0.0519*** | −0.0599*** | −0.0394** | −0.0335* |
(−2.84) | (−2.74) | (−3.70) | (−1.97) | (−1.88) | |
Lagged net foreign-assets-to-GDP ratio | 0.0363*** | 0.0381*** | 0.0421*** | 0.0322*** | 0.00589 |
4.57 | 4.53 | 7.59 | 3.87 | 0.78 | |
Volatility of terms of trade | −0.000823 | −0.0014 | −0.000528 | −0.00081 | −0.00163 |
(−0.27) | (−0.46) | (−0.18) | (−0.27) | (−0.72) | |
Lagged log of real effective exchange rate | 1.599 | −1.896 | 1.733 | 1.828 | 3.105 |
−0.58 | (−0.63) | 0.7 | 0.64 | 1.38 | |
Lagged current-account-to-GDP ratio | 0.428*** | ||||
10.59 | |||||
Constant | 2.84 | −7.807 | −17.52 | 4.434 | 26.75 |
0.14 | (−0.37) | (−1.17) | 0.19 | 1.43 | |
N | 510 | 510 | 510 | 472 | 444 |
p < 0.1,
p < 0.05,
p < 0.01.
The results show that in both the global sample and microstates, the fiscal balance appears to be positively associated with the current account. The size of the CAPB coefficients is 0.34 and 0.39 for the global sample and the microstates, respectively. The coefficient for microstates reflects their openness to trade and the likely impact of fiscal expansion on imports. Our results compare well with the CAPB coefficient obtained by Ali Abbas and others (2011) for a large sample of countries; they find a coefficient of 0.35 and also show that the coefficient is larger for countries with a high degree of trade openness.
In line with a priori expectations, the degree of openness appears to be negatively related to the current account balance. The coefficient is statistically significant at 1 percent in microstates, while it is only significant at the 10 percent level in the global sample. One possible interpretation of this is that with the limited exports and already high trade openness in microstates, an increase in the degree of openness is likely to imply more imports. Chinn and Prasad (2003) find a similar negative relationship in the medium term between openness and the current account balance.
The coefficient of the NFA is positive and statistically significant both for the global sample and for microstates, implying that high NFA helps countries to obtain higher net income flow and that negative NFA is associated with a low current account balance due to outward interest payment. Imam (2008), however, finds a negative relationship between NFA and the current account and suggests that high NFA helps to finance and sustain a current account deficit.
The coefficient of terms of trade volatility appears to have an insignificant relationship with the current account in both the global sample and microstates. One plausible explanation is that changes in saving and investment decisions taken by agents—the main channel through which volatility affects the current account balance—could be more of a medium-term behavior that is difficult to capture in our annual data framework. Chinn and Prasad (2003) support this hypothesis by finding a strong positive relationship between terms of trade volatility and the current account in the medium term (using five-year averages) but a negligible relationship in the short term.2
In the global sample, the coefficient of the real effective exchange rate implies that appreciation appears to be associated with deterioration of current account balance. However, in microstates the impact is not statistically significant. As counter-intuitive as it may sound, the result is not surprising. This might be due to the fact that imports, mainly food and fuel, are inelastic in microstates, preventing the expenditure switching effect from taking place as the relative price changes. Moreover, most imports are not produced locally, limiting the ability of substitution. In addition, exports such as tourism and banking are usually conducted in foreign currency, suggesting exports may not be cheaper after devaluation. Imam (2008) documents similar results for microstates.
Robustness Tests
We examined the robustness and sensitivity of our results to different estimation techniques. As in the previous section, we control for GDP per capita, trade openness, NFA, and the volatility of terms of trade. In the first specification, we allow for country fixed effects as well as time effects. The results are very similar to the benchmark model that allows for only country fixed effects. The next specification excludes oil-exporting countries. Here, the coefficients for CAPB weaken to 0.28 and 0.31 for the global sample and microstates, respectively. This is not surprising, given that oil price shocks typically induce large co-movements in public sector balances through oil revenues and in the current account through oil exports in oil-exporting countries. In addition, we estimated the baseline model using a pooled ordinary least squares (OLS) regression and a dynamic panel data model, where the lagged variable of the current account is included as an explanatory variable. The results are similar to those obtained from the benchmark model. We also restricted the sample to a more recent period (1990–2009) and estimated the benchmark model using different estimation methods. Overall, our main results seem to hold (see Appendix Table 10.3).
Panel Vector Autoregression
The Model
The next exercise we conduct in this chapter is to examine the impact of fiscal policy on the current account using panel vector autoregresssion (VAR) methodology. The panel VAR technique combines the traditional VAR approach that treats all variables in the system as endogenous with the panel data approach that allows for unobserved individual heterogeneity. In this chapter, the benchmark specification is a second-order panel VAR model of the form:
where Zt is a four-variable vector of log of real government consumption, log of real GDP, current-account-to-GDP ratio, and log of real effective exchange rate. We have allowed for individual heterogeneity by adding country fixed effects, fi. As the fixed effects are correlated with the lags of the dependent variables, instead of the mean-differencing procedure, a forward mean-differencing procedure is used to remove the fixed effects.3
Identification of government consumption shocks is achieved through a methodology that is commonly known as the recursive approach. This methodology assumes government spending does not react contemporaneously to shocks to other variables in the system. The argument is that movements in government spending, unlike movements in taxes, are largely unrelated to the business cycle. Therefore, it seems plausible to assume that government spending is not affected contemporaneously by shocks originating in the private sector. To this end, a reduced-form model—with variables ordered as government spending, GDP, current-account-to-GDP ratio, and the real effective exchange rate—is used.
Results
The results show that a one-standard-deviation shock in government consumption on impact increases government consumption by 12 percent in the global sample and by 11 percent in the microstates. In both cases the effect on government consumption seems to die slowly. The effect on GDP is small in both samples, indicating a very small multiplier. However, while the effect in microstates dies out quickly, it persists in the global sample.
As the current account is used as percent of GDP, we normalize the one-standard-deviation shocks in government consumption to a 1 percentage point increase in the government-consumption-to-GDP ratio, and we assess the result to the recalculated effect on the current-account-to-GDP ratio. To do this, we follow a number of steps. First, we calculate the average government-consumption-to-GDP ratio over the sample period for the global sample and microstates. This gives 18.5 percent and 22.5 percent, respectively. Second, we transform the increase in government consumption to an increase in the government-consumption-to-GDP ratio. For the global sample, an increase in 12 percent of the average 18.5 percent government-consumption-to-GDP ratio translates to a 2.2 percent increase in the average government-consumption-to-GDP ratio. For microstates, a similar calculation gives 2.5 percent. Third, we normalize these changes and the effects on the current-account-to-GDP ratio to a 1 percentage point increase in the government-consumption-to-GDP ratio (Figure 10.2).
Panel Vector Autoregression: Global Sample—Impulse Response to One-Standard-Deviation Shocks in Government Consumption
Source: Authors’ calculations.A percentage point increase in government-consumption-to-GDP ratio leads to a 0.21 percentage point deterioration in the current-account-to-GDP ratio in the global sample. The equivalent effect for microstates is a worsening of the current account by 0.42 percentage points (Figure 10.3). The result is not surprising, given the fact that the proportion of imports in domestic consumption is high. Although the impact effect of a government consumption shock is larger in microstates, the impact is short-lived and dies out in two years and becomes insignificant. On the other hand, the impact effect of a government consumption shock in the global sample, though smaller, is significant and persistent even after five years.
Panel Vector Autoregression: Microstates—Impulse Response to One-Standard-Deviation Shocks in Government Consumption
Source: Authors’ calculations.The effect of an increase in government consumption on the real effective exchange rate is not significant in the global sample, while in microstates there seems to be a significant appreciation of the real effective exchange rate on impact, although it becomes insignificant in the subsequent periods. The appreciation of the real effective exchange rate in microstates might be the result of their limited ability to influence the price of tradable goods as opposed to nontradable goods. However, the real exchange rate is unable to reinforce the deterioration of the current account. Once again, this highlights the weakness of the relative price effect and limits the impact of fiscal policy on the current account in microstates.
Robustness Tests
The robustness of our results is tested by the following measures (see Appendix Tables 10.3 and 10.4, and Appendix Figures 10.1 to 10.4). First, we estimated the benchmark model with different specifications, including changing the lag length from 2 to 3 and changing the order of the variables in the model. Second, we reestimated the panel VAR model excluding oil-exporting countries. Third, we restricted the time period to recent years starting from 1990. All in all, the results seem to support our benchmark results for microstates: a short-lived, larger-impact period response of the current account after an increase in government consumption.
Summary and Conclusion
This chapter has examined the empirical link between fiscal policy and the current account in microstates. The results suggest that there is indeed a relationship between fiscal policy and the current account in microstates. Panel regression results suggest that a strengthening of the fiscal balance improves the current account in microstates. However, the real effective exchange rate has no significant impact on the current account in microstates. Panel VAR results show that an increase in government consumption leads to an immediate deterioration of the current account in microstates. The deterioration effect dies out together with the government consumption, notwithstanding the appreciated exchange rate, which according to theoretical mechanisms should have sustained the deterioration longer. The result implies that fiscal policy has little effect on the current account in microstates beyond its direct impact on imports. Overall, the results suggest that the weak relative price effects make fiscal adjustment much more difficult in microstates.
Appendix 10.1
Selected Recent Empirical Works
Selected Recent Empirical Works
Selected Works | Sample and Methodology | Results |
---|---|---|
This chapter | 155 countries of which 42 are microstates; annual data, 1970–2009; panel regression and panel VAR |
|
Ali Abbas and others (2011) | 124 countries; annual and quarterly data, 1985–2007; panel regression and panel VAR |
|
Abiad, Leigh, and Mody (2009) | 135 countries; five-year averages, 1975–2004; panel regression | 1% of GDP increase in the budget balance improves the current account by 0.3% of GDP. |
Beetsma, Giuliodori, and Klaassen (2008) | 14 European Union countries; annual data, 1970–2004; panel VAR | 1% GDP increase in government spending worsens the trade balance by 0.5% of GDP on impact and a peak fall of 0.8% of GDP after two years. |
Chinn and Prasad (2003) | 89 countries; annual data, 1971–95; panel regression | 1% of GDP increase in the budget balance improves the current account by 0.25–0.4% of GDP |
Corsetti and Müller (2006) | Australia, Canada, the United Kingdom and the United States; quarterly data, 1975–2001; VAR | 1% GDP increase in government spending worsens the trade balance by 0.5% of GDP in the United Kingdom, by 0.17% of GDP in Canada and to a non-significant effect of trade balance in the United States and Australia on impact. |
Monacelli and Perotti (2006) | Australia, Canada, the United Kingdom and the United States; quarterly data, 1975–2006; VAR | 1% GDP increase in government spending worsens the trade balance by 0.4 to 0.9 percentage point of GDP. |
Ravn, Schmitt-Grohe, and Uribe (2007) | Australia, Canada, the United Kingdom and the United States; quarterly data, 1975–2005; panel VAR | 1% increase in government spending worsens trade balance (to GDP ratio) by around 0.03% at impact and to a peak of 0.05% after one year. |
Selected Recent Empirical Works
Selected Works | Sample and Methodology | Results |
---|---|---|
This chapter | 155 countries of which 42 are microstates; annual data, 1970–2009; panel regression and panel VAR |
|
Ali Abbas and others (2011) | 124 countries; annual and quarterly data, 1985–2007; panel regression and panel VAR |
|
Abiad, Leigh, and Mody (2009) | 135 countries; five-year averages, 1975–2004; panel regression | 1% of GDP increase in the budget balance improves the current account by 0.3% of GDP. |
Beetsma, Giuliodori, and Klaassen (2008) | 14 European Union countries; annual data, 1970–2004; panel VAR | 1% GDP increase in government spending worsens the trade balance by 0.5% of GDP on impact and a peak fall of 0.8% of GDP after two years. |
Chinn and Prasad (2003) | 89 countries; annual data, 1971–95; panel regression | 1% of GDP increase in the budget balance improves the current account by 0.25–0.4% of GDP |
Corsetti and Müller (2006) | Australia, Canada, the United Kingdom and the United States; quarterly data, 1975–2001; VAR | 1% GDP increase in government spending worsens the trade balance by 0.5% of GDP in the United Kingdom, by 0.17% of GDP in Canada and to a non-significant effect of trade balance in the United States and Australia on impact. |
Monacelli and Perotti (2006) | Australia, Canada, the United Kingdom and the United States; quarterly data, 1975–2006; VAR | 1% GDP increase in government spending worsens the trade balance by 0.4 to 0.9 percentage point of GDP. |
Ravn, Schmitt-Grohe, and Uribe (2007) | Australia, Canada, the United Kingdom and the United States; quarterly data, 1975–2005; panel VAR | 1% increase in government spending worsens trade balance (to GDP ratio) by around 0.03% at impact and to a peak of 0.05% after one year. |
Variables and Sources of Data
Variables and Sources of Data
Descriptor | Database |
---|---|
Current account balance | WEO |
Imports of goods and services | WEO |
Exports of goods and services | WEO |
Central government balance | WEO |
Central government, total expenditure, and net lending | WEO |
General government, total revenue, and grants | WEO |
General government expenditure, interest | WEO |
Public consumption expenditure, current prices | WEO |
Gross domestic product, current prices | WEO |
Gross domestic product deflator | WEO |
Gross domestic product, current prices, U.S. dollars | WEO |
Consumer price index | WEO |
Terms of trade, goods, and services | WEO |
GDP per capita purchasing power parity (constant 2005 international dollars) | WDI |
Real effective exchange rate | INSDATA |
Net foreign-asset-to-GDP ratio (%) | LM |
Variables and Sources of Data
Descriptor | Database |
---|---|
Current account balance | WEO |
Imports of goods and services | WEO |
Exports of goods and services | WEO |
Central government balance | WEO |
Central government, total expenditure, and net lending | WEO |
General government, total revenue, and grants | WEO |
General government expenditure, interest | WEO |
Public consumption expenditure, current prices | WEO |
Gross domestic product, current prices | WEO |
Gross domestic product deflator | WEO |
Gross domestic product, current prices, U.S. dollars | WEO |
Consumer price index | WEO |
Terms of trade, goods, and services | WEO |
GDP per capita purchasing power parity (constant 2005 international dollars) | WDI |
Real effective exchange rate | INSDATA |
Net foreign-asset-to-GDP ratio (%) | LM |
Panel Regressions: Global Sample
(Dependent variable: current-account-balance-to-GDP ratio) (Sample period resticted to 1990–2009)
Panel Regressions: Global Sample
(Dependent variable: current-account-balance-to-GDP ratio) (Sample period resticted to 1990–2009)
Fixed Effects | Fixed Time Effects | Pooled OLS | Excluding Oil- Exporting Countries |
Dynamic Panel GMM |
|
---|---|---|---|---|---|
Cyclically adjusted primary balance to potential GDP ratio | 0.326*** | 0.319*** | 0.358*** | 0.238*** | 0.233*** |
(8.72) | (8.56) | (9.76) | (6.18) | (5.25) | |
Lagged log per capita income | −1.920*** | −0.494 | 0.612** | −2.327*** | −3.290** |
(−2.94) | (−0.59) | (2.36) | (−3.39) | (−2.30) | |
Trade openness | −0.0125 | −0.0046 | −0.0157*** | −0.00838 | −0.0437*** |
(−1.52) | (−0.53) | (−2.83) | (−1.01) | (−3.39) | |
Lagged net foreign-assets-to-GDP ratio | 0.0179*** | 0.0233*** | 0.0238*** | 0.0155*** | −0.0309*** |
(5.15) | (6.70) | (8.69) | (4.42) | (−5.26) | |
Volatility of terms of trade | 0.00448 | 0.0131 | 0.00346 | −0.00731 | 0.00292 |
(0.47) | (1.37) | (0.37) | (−0.75) | (0.22) | |
Lagged log of real effective exchange rate | −1.121* | −0.972 | −0.998 | −0.841 | 1.625 |
(−1.77) | (−1.54) | (−1.64) | (−1.26) | (1.52) | |
Lagged current-account-to-GDP | 0.266*** | ||||
(8.54) | |||||
Constant | 20.07*** | 6.213 | −1.693 | 21.55*** | 19.99 |
(3.33) | (0.85) | (−0.45) | (3.45) | (1.55) | |
Number of observations | 1,915 | 1,915 | 1,915 | 1,787 | 1,641 |
Panel Regressions: Global Sample
(Dependent variable: current-account-balance-to-GDP ratio) (Sample period resticted to 1990–2009)
Fixed Effects | Fixed Time Effects | Pooled OLS | Excluding Oil- Exporting Countries |
Dynamic Panel GMM |
|
---|---|---|---|---|---|
Cyclically adjusted primary balance to potential GDP ratio | 0.326*** | 0.319*** | 0.358*** | 0.238*** | 0.233*** |
(8.72) | (8.56) | (9.76) | (6.18) | (5.25) | |
Lagged log per capita income | −1.920*** | −0.494 | 0.612** | −2.327*** | −3.290** |
(−2.94) | (−0.59) | (2.36) | (−3.39) | (−2.30) | |
Trade openness | −0.0125 | −0.0046 | −0.0157*** | −0.00838 | −0.0437*** |
(−1.52) | (−0.53) | (−2.83) | (−1.01) | (−3.39) | |
Lagged net foreign-assets-to-GDP ratio | 0.0179*** | 0.0233*** | 0.0238*** | 0.0155*** | −0.0309*** |
(5.15) | (6.70) | (8.69) | (4.42) | (−5.26) | |
Volatility of terms of trade | 0.00448 | 0.0131 | 0.00346 | −0.00731 | 0.00292 |
(0.47) | (1.37) | (0.37) | (−0.75) | (0.22) | |
Lagged log of real effective exchange rate | −1.121* | −0.972 | −0.998 | −0.841 | 1.625 |
(−1.77) | (−1.54) | (−1.64) | (−1.26) | (1.52) | |
Lagged current-account-to-GDP | 0.266*** | ||||
(8.54) | |||||
Constant | 20.07*** | 6.213 | −1.693 | 21.55*** | 19.99 |
(3.33) | (0.85) | (−0.45) | (3.45) | (1.55) | |
Number of observations | 1,915 | 1,915 | 1,915 | 1,787 | 1,641 |
Panel Regressions: Microstates
(Dependent variable: current-account-balance-to-GDP ratio)
Panel Regressions: Microstates
(Dependent variable: current-account-balance-to-GDP ratio)
Fixed Effects | Fixed Time Effects | Pooled OLS | Excluding Oil- Exporting Countries |
Dynamic Panel GMM |
|
---|---|---|---|---|---|
Cyclically adjusted primary- balance-to- potential-GDP ratio | 0.356*** | 0.417*** | 0.377*** | 0.220** | 0.431*** |
(4.21) | (4.83) | (4.51) | (2.49) | (4.95) | |
Lagged log per capita income | −0.123 | 3.002 | 1.776* | −3.83 | −7.76 |
(−0.07) | (1.34) | (1.95) | (−1.50) | (−1.61) | |
Trade openness | −0.0659*** | −0.0600*** | −0.0659*** | −0.0545** | −0.133*** |
(−2.95) | (−2.67) | (−3.57) | (−2.33) | (−4.18) | |
Lagged net foreign-assets-to-GDP ratio | 0.0108 | 0.0171 | 0.0322*** | −0.000521 | −0.0171 |
(1.04) | (1.56) | (4.86) | (−0.05) | (−1.20) | |
Volatility of terms of trade | 0.00542 | 0.0286 | 0.00877 | −0.0201 | 0.0105 |
(0.19) | (0.97) | (0.34) | (−0.63) | (0.29) | |
Lagged log of real effective exchange rate | 2.414 | 0.387 | −0.629 | 4.236 | −0.223 |
(0.69) | (0.11) | (−0.20) | (1.18) | (−0.05) | |
Lagged current-account-to- GDP ratio | 0.355*** | ||||
(7.03) | |||||
Constant | −8.589 | −24.61 | −9.742 | 12.42 | 76.76 |
(−0.35) | (−0.94) | (−0.54) | (0.43) | (1.58) | |
Number of observations | 415 | 415 | 415 | 382 | 343 |
Panel Regressions: Microstates
(Dependent variable: current-account-balance-to-GDP ratio)
Fixed Effects | Fixed Time Effects | Pooled OLS | Excluding Oil- Exporting Countries |
Dynamic Panel GMM |
|
---|---|---|---|---|---|
Cyclically adjusted primary- balance-to- potential-GDP ratio | 0.356*** | 0.417*** | 0.377*** | 0.220** | 0.431*** |
(4.21) | (4.83) | (4.51) | (2.49) | (4.95) | |
Lagged log per capita income | −0.123 | 3.002 | 1.776* | −3.83 | −7.76 |
(−0.07) | (1.34) | (1.95) | (−1.50) | (−1.61) | |
Trade openness | −0.0659*** | −0.0600*** | −0.0659*** | −0.0545** | −0.133*** |
(−2.95) | (−2.67) | (−3.57) | (−2.33) | (−4.18) | |
Lagged net foreign-assets-to-GDP ratio | 0.0108 | 0.0171 | 0.0322*** | −0.000521 | −0.0171 |
(1.04) | (1.56) | (4.86) | (−0.05) | (−1.20) | |
Volatility of terms of trade | 0.00542 | 0.0286 | 0.00877 | −0.0201 | 0.0105 |
(0.19) | (0.97) | (0.34) | (−0.63) | (0.29) | |
Lagged log of real effective exchange rate | 2.414 | 0.387 | −0.629 | 4.236 | −0.223 |
(0.69) | (0.11) | (−0.20) | (1.18) | (−0.05) | |
Lagged current-account-to- GDP ratio | 0.355*** | ||||
(7.03) | |||||
Constant | −8.589 | −24.61 | −9.742 | 12.42 | 76.76 |
(−0.35) | (−0.94) | (−0.54) | (0.43) | (1.58) | |
Number of observations | 415 | 415 | 415 | 382 | 343 |
Panel Vector Autoregression: Impulse Response to One-Standard-Deviation Shocks in Government Consumption—Length of Lag Set to Three
Source: Authors’ calculations.Note: Confidence bands are the 5th and 95th percentiles from Monte Carlo simulations based on 500 replications.Panel Vector Autoregression: Impulse Response to One-Standard-Deviation Shocks in Government Consumption—Excluding Oil Exporters
Source: Authors’ calculations.Note: Confidence bands are the 5th and 95th percentiles from Monte Carlo simulations based on 500 replications.Panel Vector Autoregression: Impulse Response to One-Standard-Deviation Shocks in Government Consumption—Government Consumption Ordered Second
Source: Authors’ calculations.Note: Confidence bands are the 5th and 95th percentiles from Monte Carlo simulations based on 500 replications.Panel Vector Autoregression: Impulse Response to One-Standard-Deviation Shocks in Government Consumption, 1990–2009
Source: Authors’ calculations.Note: Confidence bands are the 5th and 95th percentiles from Monte Carlo simulations based on 500 replications.References
Abiad, Abdul, Daniel Leigh, and Ashoka Mody, 2009, “Financial Integration, Capital Mobility, and Income Convergence,” Economic Policy, Vol. 24, pp. 241–305.
Alesina, Alberto, and Allan Drazen, 1991, “Why Are Stabilizations Delayed?” American Economic Review, Vol. 81, pp. 1170–80.
Ali Abbas, S. M., Jacques Bouhga-Hagbe, Antonio Fatás, Paolo Mauro, and Ricardo C. Velloso, 2011, “Fiscal Policy and the Current Account,” IMF Economic Review, Vol. 50, pp. 603–29.
Arellano, Manuel, and Olympia Bover, 1995, “Another Look at the Instrumental Variable Estimation of Error Component Models,” Journal of Econometrics, Vol. 68, pp. 29–51.
Armstrong, H., R. J. De Kervenoael, X. Li, and R. Read, 1998, “A Comparison of the Economic Performance of Different Micro-States, and between Micro-States and Larger Countries,” World Development, Vol. 26, pp. 639–56.
Armstrong, H. W., G. Johnes, J. Johnes, and A. I. Macbean, 1993, “The Role of Transport Costs as a Determinant of Price Level Differentials between the Isle of Man and the United Kingdom, 1989,” World Development, Vol. 21, pp. 311–18.
Baxter, Marianne, 1995, “International Trade and Business Cycles,” in Handbook of International Economics: 1985, ed. by G. M. Grossmann and K. Rogoff (Amsterdam: North-Holland, Elsevier).
Beetsma, R., Massimo Giuliodori, and Franc Klaassen, 2008, “The Effects of Public Spending Shocks on Trade Balances and Budget Deficits in the European Union,” Journal of the European Economic Association, Vol. 6, pp. 414–23.
Bhaduri, Amit, Anjan Mukherji, and Ramprasad Sengupta, 1982, “Problems of Long-Term Growth in Small Economies: A Theoretical Analysis,” in Problems and Policies in Small Economies: 1982, ed. by B. Jalan (London and Canberra: Croom Helm).
Blanchard, Olivier, and Roberto Perotti, 2002, “An Empirical Characterization of the Dynamic Effects of Changes in Government Spending and Taxes on Output,” Quarterly Journal of Economics, Vol. 117, pp. 1329–68.
Chinn, Menzie D., and Eswar S. Prasad, 2003, “Medium-Term Determinants of Current Accounts in Industrial and Developing Countries: An Empirical Exploration,” Journal of International Economics, Vol. 59, pp. 47–76.
Commonwealth Consultative Group, 1997, A Future for Small States: Overcoming Vulnerability (London: Commonwealth Secretariat).
Corsetti, Giancarlo, and Gernot J. Muller, 2006, “Budget Deficits and Current Accounts: Openness and Fiscal Persistence,” Economic Policy, Vol. 21, pp. 597–638.
Djankov, Simeon, Caroline Freund, and Cong Pham, 2006, “Trading on Time,” Working Paper No. 3909 (Washington: World Bank).
Fleming, J.M., 1962, “Domestic Financial Policies Under Fixed and Under Floating Exchange Rates,” IMF Staff Papers, Vol. 9, pp. 369–79.
Frenkel, Jacob A., and Assaf Razin, 1996, Fiscal Policies and Growth in the World Economy (Cambridge, Massachusetts: MIT Press).
Imam, Patrick, 2008, “Rapid Current Account Adjustments: Are Microstates Different?” IMF Working Paper 08/233 (Washington).
International Monetary Fund, 2010, World Economic Outlook (Washington, October).
International Monetary Fund, 2011, World Economic Outlook (Washington, September).
Kim, Soyoung, and Nouriel Roubini, 2008, “Twin Deficit and Twin Divergence? Fiscal Policy, Current Account, and Real Exchange Rate in the U.S.,” Journal of Economic Literature, Vol. 74, pp. 362–83.
Lane, Philip R., and Gian Maria Milesi-Ferretti, 2007, “Updated and Extended Version of the External Wealth of Nations Mark II Database Developed by Lane and Milesi-Ferretti, The External Wealth of Nations Mark II,” Journal of International Economics, Vol. 73, pp. 223–50.
Monacelli, Tommaso, and Roberto Perotti, 2006, “Fiscal Policy, the Trade Balance, and the Real Exchange Rate: Implications for International Risk Sharing,” unpublished (Bocconi: Università Bocconi).
Mundell, Robert A., 1960, “The Monetary Dynamics of International Adjustment under Fixed and Flexible Exchange Rates,” Quarterly Journal of Economics Vol. 74, pp. 227–57.
Ramey, Valerie A., and Matthew D. Shapiro, 1998, “Costly Capital Reallocation and the Effects of Government Spending,” in Carnegie-Rochester Conference Series on Public Policy, Vol. 48, No. 1, pp. 145–94.
Ravn, Morten O., Stephanie Schmitt-Grohe, and Martin Uribe, 2007, “Explaining the Effects of Government Spending Shocks on Consumption and the Real Exchange Rate,” unpublished (Durham, North Carolina: Duke University).
Salter, Wilfred A., 1959, “Internal and External Balance: The Role of Price and Expenditure Effects,” Economic Record, Vol. 35, pp. 226–38.
Selwyn, Percy, 1975, Development Policy in Small Countries (London: Croom Helm).
Streeten, Paul, 1993, “The Special Problems of Small Countries,” World Development, Vol. 21, pp. 197–202.
IMF (2011) outlines a number of shortcomings of using the cyclically adjusted fiscal balance as a measure of deliberate fiscal policy changes.
We used a five-year moving standard deviation and changes in terms of trade, but the result remains the same.
This procedure, also known as the Helmert transformation, is based on Arellano and Bover (1995). The procedure preserves the orthogonality between the transformed variables and the lagged regressors that thus can be used as instruments to estimate the coefficients by system generalized method of moments (GMM).