Information about Asia and the Pacific Asia y el Pacífico
Resilience and Growth in the Small States of the Pacific
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Chapter 6. Global and Regional Spillovers to Pacific Island Countries

Author(s):
Hoe Khor, Roger Kronenberg, and Patrizia Tumbarello
Published Date:
August 2016
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Information about Asia and the Pacific Asia y el Pacífico
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Author(s)
Fazurin Jamaludin, Nlamh Sheridan, Patrizia Tumbarello, Ylqun Wu and Tlek Zeinullayev 

The Pacific island countries (PICs) have been integrating economically with Australia, New Zealand, and Asia’s emerging market economies over the last two decades, creating big economic opportunities for them.1 This integration has greatly benefited PICs, but it has also posed challenges because shocks are transmitted more rapidly in a more interconnected world. Indeed, PICs have become more exposed to regional business cycles. Yet strong linkages with resilient economies—notably Australia and Asia’s emerging markets—helped cushion the downturn in the aftermath of the global financial crisis.

The PICs’ strong linkages with Australia and New Zealand are well established. Australia is by far the largest provider of aid and foreign direct investment (FDI) to these countries, and Australia and New Zealand account on average for one-third of trade with PICs. Remittances from Australia and New Zealand account for about 60 percent of total remittances to Fiji and Samoa, while 60–70 percent of total tourist arrivals in Fiji, Samoa, and Vanuatu come from these two countries. Australian banks, meanwhile, dominate the banking sector in PICs. PICs have also been establishing more substantial links with Asia’s emerging market economies, including China, especially over the last 10 years.

Today, spillovers from regional economies are more important for PICs than advanced economies outside the region. Australia is the main source of direct and indirect spillovers, both over the short and long term, except for the compact agreement countries (Marshall Islands, Micronesia, Palau), for which the United States is the most important partner, consistent with the large volume of U.S. aid. Over the last decade, shocks from Asia’s emerging market economies have had a greater impact on the business cycles of PICs, while the role of more traditional partners, such as Japan, has declined. In the short term, the elasticity of PICs’ output with respect to the GDP of regional partners has at times been higher than one, pointing to the critical role for policies to stabilize business cycles.

While strong linkages with Asia and the Pacific would help in the event of a global downturn, PICs remain particularly vulnerable to global commodity price shocks. The 50 percent decline in crude oil prices between mid-2014 and October 2015 broadly supported their macroeconomic prospects, with the exception of fuel commodity exporters such as Papua New Guinea and Timor-Leste, despite lingering global economic uncertainties. But a jump in oil prices of, say, 50 percent above the baseline would have a substantial negative impact on growth given PICs’ relatively heavy reliance on oil imports—and in some cases the impact would be larger than from a negative global demand shock.2

The increasing regional links of these countries could help mitigate the downside risks generated by business cycles in nonregional advanced economies. Even so, sound policies can enhance resilience, and the Pacific island countries should continue to rebuild policy buffers, undermined during the global financial crisis, and implement growth-oriented structural reforms to ensure sustained and inclusive growth.

The Setting: Pics Before and After the Global Financial Crisis

Growth in PICs has been weak over the last decade. The global financial crisis compounded the problem by reducing growth further, especially among the commodity importers. While many PIC economies have recovered, headwinds remain amid the global economic uncertainty. In the event of a negative global demand shock, adverse spillovers would occur mainly through regional partners. But the linkages with Australia, New Zealand, and Asia’s emerging market economies would help offset the downturn, owing to the strong fundamentals of these countries.

Most PICs seem to be stuck on a low-growth path. Figures 6.1 and 6.2 show that in the 10 years preceding the global financial crisis, PIC growth averaged just 2 percent a year—much lower than comparator countries, namely Asia’s low-income countries (6 percent), the Eastern Caribbean Currency Union countries (4 percent), and other small states (4½ percent). Relative growth performance has been uneven, favoring commodity exporters, which have benefited from global price trends for the better part of the last decade.

Figure 6.1Real GDP Growth

(Percent)

Sources: Country authorities; and IMF staff calculations and projections.

Note: ECCU = Eastern Caribbean Currency Union, and includes Antigua and Barbuda, Dominica, Grenada, St. Kitts and Nevis, St. Lucia, and St. Vincent and the Grenadines. PICs = Pacific island countries.

Figure 6.2Real GDP Growth

(Percent)

Sources: IMF, World Economic Outlook database; and IMF staff calculations.

Note: ECCU = Eastern Caribbean Currency Union; LICs = low-income countries; PICs = Pacific island countries.

PICs recovered from the global financial crisis at different paces (Figure 6.3). This suggests differing levels of resilience—and vulnerability—to shocks in the future. Excluding the net commodity exporters (Papua New Guinea, the Solomon Islands, Timor-Leste), average real GDP fell to −2.0 percent in 2009. Despite a rebound—growth averaged 1.6 percent and 3.3 percent in 2010 and 2011, respectively—average growth in non-resource-rich countries remained about 2 percent in the five years after the crisis. By contrast, real GDP growth averaged above 6 percent during 2010–14 in Papua New Guinea and the Solomon Islands on the back of the development of the liquefied natural gas sector in the former and strong mining and logging in the latter. Nonetheless, being a commodity exporter does not guarantee sustained growth. The depletion of finite natural resources and lower production—due to lower commodity prices and high costs—can weigh on growth and prove challenging for countries like the Solomon Islands, a wood and gold exporter.

Figure 6.3Real GDP Growth Following the Global Financial Crisis

(Percent)

Sources: Country authorities; and IMF staff calculations.

The vulnerability of PICs to natural disasters can also affect growth (see Chapter 5). The 2009 flood in Fiji and, in the same year, the earthquake and tsunami in Samoa, as well as cyclones and floods in Fiji, Samoa, the Solomon Islands, and Vanuatu in 2013–15 are just some of the major natural disasters in the last five years that have had a harmful economic impact.

Although growth in PICs regained precrisis rates, their growth performance is still low relative to other low-income countries. This reflects the relatively small export bases of PICs, which preclude a large increase in external demand associated with global recovery. Helped in part by Australia’s economic resilience during the crisis, PICs recovered more strongly than some comparator regions, such as in the Eastern Caribbean Currency Union, which is tied more closely to the U.S. business cycle. Strong Australian and New Zealand dollars supported the PIC tourist sector for most of 2010–14 (Figure 6.4), although the depreciation of both currencies is expected to affect tourism flows in the medium term.3

Figure 6.4Tourist Arrivals

(2005 = 100)

Source: IMF staff calculations.

A closer look suggests that PIC net commodity importers generally recovered more slowly than in previous recessions. Over the past four decades, PIC importers experienced economic contractions in 1975, 1980, 1987, 1997, and 2009. Only 1975 and 2009 coincided with global recessions. The 2009 contraction was comparable to previous PIC downturns, yet the recovery was weaker (Figure 6.5). For net commodity exporters, however, the contraction was milder than in previous episodes and the recovery much faster (Figure 6.6).

Figure 6.5Commodity Importers among Pacific Island Countries: Real GDP Growth around Downturns

(Percent)

Source: IMF staff calculations.

Note: Historical is average of four downturns.

Figure 6.6Commodity Exporters among Pacific Island Countries: Real GDP Growth around Downturns

(Percent)

Source: IMF staff calculations.

Note: Historical is average of four downturns.

What explains the slow recovery of PIC commodity importers relative to past episodes? Using a vector autoregression analysis following Berg and others (2010), we find that terms-of-trade shocks, to which PICs are most exposed, result in a far greater output loss than shocks to external demand and imply a faster recovery too. Because the 2009 recession was driven by external-demand shocks, this may explain the milder drop in growth rate relative to the precrisis level during 2009 and slower recovery relative to previous episodes. In contrast, external-demand shocks have a larger impact on output in Asia’s low-income countries, which may help explain the greater impact of the global recession on those economies.

Terms-of-trade shocks have a larger impact than external-demand shocks on PICs for several reasons. Given their narrow export and production bases and geographical remoteness, most PICs have structural trade deficits (IMF 2015a). With the exception of Papua New Guinea, the Solomon Islands, and Timor-Leste, PICs are commodity importers and therefore vulnerable to swings in commodity prices. However, heavy reliance on the imports of commodities, particularly fuel, is characteristic of commodity exporters and importers alike in many of these countries, especially when compared to peers. Given greater commodity price volatility in recent years, terms-of-trade shocks have translated into larger output shocks. Changes in import prices have also affected the cost of production and real household income.

Channels of Spillover

If the global economy were to slow or contract again, the channels of contagion would also vary across PICs. The main channels are:

  • Tourism, remittances, and FDI—Fiji, Palau, Samoa, and Vanuatu would be hurt by a fall in tourism, which accounts for between 20 percent and 50 percent of their GDP (Figure 6.7), with spillovers affecting the broader economy through reduced tourism-related FDI. Remittances would be one of the main channels of contagion in Samoa, Tonga, and Tuvalu, and to a lesser extent in Fiji, Kiribati, Marshall Islands, and Micronesia. Tourist arrivals and remittances declined during the global financial crisis (Figure 6.8).
  • Terms of trade—Movements in relative prices that result in a drop in fuel commodity prices would hurt the trade position in Papua New Guinea and Timor-Leste. Among the commodity importers, the decline in food and fuel prices could provide some relief to household budgets because (1) rising real income will increase consumption, (2) production costs will fall due to lower costs of energy, (3) the external position will improve substantially, and (4) inflation will ease.
  • Financial channels—A fall in stock prices in advanced economies would also affect PICs with large trust funds—Kiribati, Marshall Islands, Micronesia, Palau, and Tuvalu—whose assets are invested offshore. A large decline in the value of these trust funds, as happened during the global financial crisis, could worsen fiscal sustainability over the medium and long term.
  • Foreign aid—High dependence on foreign aid flows, averaging over 20 percent of GDP in PICs in 2014, is a source of fiscal vulnerability (Figure 6.9). In the past decade, approximately 40 percent of these countries’ total fiscal receipts consisted of foreign grants. Even under the baseline scenario, the scheduled expiration in 2023/24 of U.S. aid under the compact grant scheme is set to present a fiscal cliff, as these grants make up a significant share of budgets in Marshall Islands, Micronesia, and Palau. In the Solomon Islands, donor assistance will gradually decline (in terms of GDP) over the medium term with the phased withdrawal, starting in 2013, of the Regional Assistance Mission to the Solomon Islands.4
  • Exchange rates—Only six of the 12 PICs discussed in this chapter have their own national currencies (Fiji, Papua New Guinea, Samoa, the Solomon Islands, Tonga, Vanuatu). Marshall Islands, Micronesia, Palau, and Timor-Leste use the U.S. dollar; Kiribati and Tuvalu use the Australian dollar. Apart from Papua New Guinea, all the countries with their own currency and exchange rate implement some form of currency peg. As a result, PIC economies are vulnerable to U.S. dollar and regional currency movements. The depreciation of the Australian and New Zealand dollars against the U.S. dollar and PIC currencies that started in 2014, for instance, could be expected to reduce the size of remittances, aid flows, tourist arrivals, and return on investments.

Figure 6.7Tourism and Remittances

(Percent of GDP, 2014)

Sources: Country authorities; and IMF staff estimates.

Note: Data are the latest available.

Figure 6.8Pacific Island Countries, Channels of Spillover: Stylized Facts

Sources: Country authorities; and IMF staff calculations.

Note: FSM = Federated States of Micronesia; KIR = Kiribati; MHL = Marshall Islands; PLW = Palau; RERF = Revenue Equalization Reserve Fund; U.S. = United States.

1 Fiscal year.

Figure 6.9Grants to Pacific Island Countries

(Percent of GDP, 2014)

Sources: Country authorities; and IMF staff estimates.

Assessing Growth Spillovers

To understand how external shocks from the global economy can affect PICs, one must understand growth spillovers from the region. Stylized facts suggest that direct exposure to Europe is limited. The impact of a global slowdown on PICs would occur through spillovers from regional economies and, to a lesser extent, from the United States.

Linkages with Australia and New Zealand, as noted, are strong and well established, stemming from the strong exposure of PICs to these economies through trade, tourism, remittances, FDI, aid, and financial channels. Trade with Australia and New Zealand accounts, on average, for one-third of PICs’ trade, while remittances from Australia and New Zealand account for about 60 percent of total remittances in Fiji and Samoa (Figure 6.10). Tourist arrivals from Australia and New Zealand represent 60–70 percent of total arrivals in Fiji, Samoa, and Vanuatu (Figure 6.11). Australian banks dominate the PICs’ financial sectors, which is discussed later, and Australia is by far the largest provider of aid. Among Organisation for Economic Co-operation and Development countries, Australia is also the largest foreign investor (Figures 6.12 and 6.13) in PICs.

Figure 6.10Remittances by Country of Origin

(Percent of total remittances)

Sources: Country authorities; and IMF staff calculations.

Figure 6.11Tourists by Country of Residence

(Percent of total arrivals, 2014)

Sources: Country authorities; and IMF staff calculations.

Figure 6.12Foreign Direct Investment by OECD Countries

(Percent of total foreign direct investment, 2005–12 average)

Source: Statistics from the Organisation for Economic Co-operation and Development (OECD).

Note: Excludes Belgium, Denmark, Greece, Italy, Netherlands, and Norway.

Figure 6.13Official Development Aid by Donors

(Percent of aid, 2012)

Source: World Bank, World Development Indicators.

The United States has a large impact on some PICs, especially the compact agreement countries. U.S. aid represents over 65 percent of total aid to Palau and 90 percent to Marshall Islands and Micronesia. Remittances from the United States account for 50 percent of total remittances in Tonga (IMF 2012a).

Linkages between PICs and Asia’s emerging market economies have grown over the last decade. Direction of trade data point to a large increase in China’s share of PICs’ trade, with trade with China increasing sevenfold on average since the early 2000s (Figure 6.14). China is now the Solomon Islands’ top trading partner, and external financing from China is substantial for Tonga (Figure 6.15). FDI patterns have become more diverse, with the share of inward FDI from China and other east Asian trading partners, notably Korea, growing at the expense of traditional investors such as Japan (Figure 6.16).

Figure 6.14Solomon Islands: Exports by Destination

(Percent of total)

Sources: Country authorities; and IMF staff calculations.

Note: PICs = Pacific island countries.

1 Excludes China.

Figure 6.15Tonga: Loan Disbursements from China

(Percent of GDP)

Source: Country authorities.

Figure 6.16Foreign Direct Investment (FDI) by Country of Origin

(Percent of total FDI)

Sources: Data from the Organisation for Economic Co-operation and Development; and United Nations Centre for Trade and Development.

Note: Includes Australia, China, Korea, Japan, France, Germany, Italy, Luxembourg, Netherlands, New Zealand, Sweden, United Kingdom, and United States.

Quantitative Analysis

Can growth from fast-growing neighboring economies spill over to PICs as tailwinds to an economic recovery process or buffers during a downward scenario? A simple correlation analysis between the real GDP growth rates of Australia, New Zealand, and Asia’s emerging markets suggests an increasing comovement between the business cycles of PICs and their neighboring economies over the last two decades, with the correlation increasing over the last 10 years (Figure 6.17).

Figure 6.17Pacific Island Countries: Correlation of Real GDP Growth with Australia, New Zealand, and Emerging Asia

(1990–99 and 2000–14)

Sources: Country authorities; and IMF staff calculations.

Econometric Analysis: Baseline Scenario

The econometric analysis further investigates the relevance of potential growth spillovers from the global and regional economies. We use a vector error correction model for each PIC to gauge the impact of global and regional growth spillovers on individual PICs. We use annual data from the late 1970s through 2011.5 The analysis examines both short- and long-term dynamics using historical data. We use a cointegration technique to identify the long-term relationship between GDP in PICs and the GDP of their main trading partners, using variables expressed in levels.6 We use that long-term relationship to build a structural model that captures both long- and short-term dynamics, which is then employed for scenario analysis. Focusing on individual PICs—rather than treating them as a homogeneous group—sheds light on spillovers specific to each country.

Our main findings are summarized as follows (with technical details in Annex 6.1):

  • Using a subsample analysis, PICs appear to be more integrated with Australia’s, New Zealand’s, and Asia’s emerging market economies than they were 20 years ago, suggesting an increase in growth spillovers from the region.
  • Australia is by far the main source of direct and indirect spillovers, both in the short and long term, with the exception of the compact agreement countries. Australia sometimes has an indirect impact on PICs through New Zealand. Direct spillovers from New Zealand are also highly relevant for several PICs.
  • Over the last decade, shocks from Asia’s emerging market economies had a greater impact than in the past on PICs’ business cycles (that is, the short term). This suggests that the role of Asia’s emerging markets in explaining output in PICs has increased, while that of more traditional partners, such as Japan, has declined.
  • In the short term, the elasticity of output with respect to regional partners is at times higher than one, suggesting greater scope for policies to stabilize the business cycle.
  • In the short term, the main channel of spillovers is commodity prices, consistent with the analysis presented earlier. The adverse-oil-shock scenario discussed in the following section shows a larger and more negative impact on growth than the global-demand-shock scenario, confirming that PICs are very vulnerable to commodity price shocks. Conversely, this also suggests that the potentially protracted decline in commodity prices—including oil prices—starting in mid-2014 will provide some support for their economic prospects, despite lingering global economic uncertainties (Box 6.1).

Econometric Analysis: Downside Scenarios

We simulate the impact on PICs’ growth of two external downside scenarios consistent with two global scenarios developed using the IMF’s Global Economy Model.7 Using the econometric models already discussed, we estimate the spillovers to individual PICs from global and regional economies.

The first downside global scenario assumes a negative global demand shock due to financial turmoil in the euro area. This scenario implies that global growth falls short of baseline projections by about 1½ percentage points in the years t + 1 and t + 2, with the euro area growth rate declining by 2.5 percentage points in t + 1 and a further decline of 1.1 percentage points in t + 2. The direct spillovers from stress in the euro area to PICs are estimated to be limited. The slowdown in global growth would spill over to PICs within the same year through their regional partners and the United States.8 For the commodity importers, the decline in GDP growth is estimated, on average, at a little over ½ percentage point each year, compared with the baseline. For the PIC commodity exporters, the impact on growth would be much larger, declining by almost 1 percentage point in each year of the shock. The milder impact on commodity importers depends on the fact that oil prices would decline under this scenario because of lower global growth (Figures 6.18 to 6.21).

Figure 6.18Pacific Island Countries: Change in Growth under Different Scenarios

(Percent)

Source: IMF staff calculations.

Figure 6.19Pacific Island Countries: Real GDP Growth under Different Scenarios

(Percent)

Source: IMF staff estimates.

Figure 6.20Pacific Island Countries: Real GDP Growth for Commodity Importers

(Percent)

Source: IMF staff estimates.

Figure 6.21Pacific Island Countries: Real GDP Growth for Commodity Exporters

(Percent)

Source: IMF staff estimates.

The impact on PICs’ growth from an adverse-oil-shock scenario—the second scenario—would be substantial. This assumes a negative oil-price shock triggered by geopolitical uncertainty in the Middle East that would raise the real oil price by 50 percent, relative to the baseline, for at least two years. Global output growth would thus be lower than the baseline by about ½ percentage point in t + 1 and a little more than 1 percentage point in t + 2. Simulations using the vector error correction model suggest that negative spillovers spurred by higher oil prices will reduce all PIC growth rates in both years, except for the commodity exporters Papua New Guinea and Timor-Leste, whose terms of trade would improve.9 The decline would average about 1½ percentage points of GDP for fuel commodity importers—where the baseline trend growth is already low, at about 2 percent. On average, this impact on PIC growth would be larger than in the previous scenario (where the financial turmoil in the euro area intensifies). In part, the greater sensitivity of PICs to global oil and commodity prices reflects the large weight of fuel and food in the consumer price index basket, the comparatively high dependence on fuel imports, and the relatively larger share of imported items in consumption and investment, owing to their smaller domestic manufacturing base. It also reflects the fact that PICs would have to cope with higher oil prices amid slower growth among their trading partners.

Box 6.1.Impact of Lower Oil Prices on Pacific Island Country Oil Importers

Commodity prices fell by almost one-fifth in the first nine months of 2015, mainly driven by sharply lower fuel prices. Between June 2014 and September 2015, crude oil prices fell by 57 percent on account of strong supply and concerns about future demand (Figure 6.1.1). In the October 2015 World Economic Outlook (IMF 2015c), average oil prices were projected to fall by 46 percent in 2015, and to decline further in 2016.

Figure 6.1.1IMF Commodity Price Indices

(2005 = 100)

Sources: IMF World Economic Outlook database.

Based on our findings, a 40 percent drop in commodity and oil prices implies a boost to economic growth in Pacific island countries (PICs) by an average of 2 percentage points, all other things being equal.1 This positive effect on growth appears to be broadly confirmed by growth forecast revisions for PICs following the downward revision in oil price forecasts in October 2015. While PIC average growth outlook in 2015 was weighed down by a number of negative shocks—including the devastation wrought by Cyclone Pam—the overall growth trajectory appears to receive a boost from lower oil prices (Figure 6.1.2).

Figure 6.1.2PIC Oil Importers: Growth Projections under Different Oil Price Assumptions

(Percent)

Sources: IMF, World Economic Outlook (WEO) database, October 2014 and January 2015; and IMF staff calculations.

Note: Oil price forecasts in the October 2014 WEO were US$98/barrel for 2015 and $93 a barrel for 2016; forecasts in the January 2015 WEO Update were $51 a barrel for 2015 and $59 a barrel for 2016. PIC = Pacific island country.

More broadly, estimates for PICs from IMF country teams, amid expectations of lower oil prices, also point to lower input costs supporting growth, lowering inflation, strengthening current account balance, and marginally improving the fiscal position of oil importers in 2015 and 2016 (Figure 6.1.3).

Figure 6.1.3Impact of Lower Commodity Prices on PIC Oil Importers: Average Differential from Baseline Projections

(Percentage points)

Source: IMF staff calculations.

Note: PICs = Pacific island countries. Based on simple averages. In both scenarios, countries with an independent monetary policy are assumed to be taking monetary policy action. The differential is calculated as the difference from the latest baseline projections as of December 2014.

1 Based on results for Fiji, Kiribati, Marshall Islands, Micronesia, Palau, and the Solomon Islands, for which a statistically significant relationship between oil and commodity prices is found.

Assessing Spillovers to the Financial Sector

The financial sector in PICs is also closely integrated with regional economies. It consists mainly of foreign-owned banks—primarily Australian—and large provident or trust funds. Banks from other countries include a Papua New Guinea domestic bank (Bank South Pacific), which has operations in Fiji, Samoa, the Solomon Islands, and Tonga, and France’s BRED Bank, which is present in Fiji and Vanuatu (see Annex Table 6.2.1 for a list of commercial banks in the PICs). Over the last few years, a number of domestically incorporated banks have entered the financial sector in PICs and in at least a number of cases, these have also been funded through the injection of foreign capital. Foreign banks in PICs have been profitable and proved resilient to the global financial crisis. Reflecting their asset allocation mix and large exposure to global financial markets, the provident and trust funds did not cope as well with the global financial crisis.

The size of the banking sector varies across PICs. Not surprisingly, total bank assets (in U.S. dollar terms) are greatest in the largest economies, although not as a percent of GDP. Relative to GDP, the size of the banking system is broadly in line with Asia’s low-income countries. Reflecting the small size of PIC economies, the banking sector consists generally of a small number of commercial banks or even just one bank, as in Kiribati and Tuvalu (Figures 6.22 and 6.23).

Figure 6.22Banking Sector Total Assets

(Billions of U.S. dollars, 2014)

Sources: Country authorities; and IMF staff estimates.

Note: The National Bank of Tuvalu performs some monetary functions, including the holding of government accounts and foreign assets.

Figure 6.23Banking Sector Total Assets

(Percent of GDP, 2014)

Sources: Country authorities; and IMF staff estimates.

Note: The National Bank of Tuvalu performs some monetary functions, including the holding of government accounts and foreign assets.

The banks are well capitalized, with high total capital and Tier 1 capital adequacy ratios. This provides a buffer against financial shocks (Figures 6.24 and 6.25). Reflecting the vulnerability of PICs to shocks, the authorities have in many cases opted for a capital requirement ratio in excess of the Basel II minimum requirements. Furthermore, several banks exceed the required minimum ratio, which varies widely across the islands.

Figure 6.24Banking Sector Total Capital Ratio

(Percent, 2013)

Sources: Country authorities; and IMF staff estimates.

Figure 6.25Banking Sector Tier 1 Capital Ratio

(Percent, 2013)

Sources: Country authorities; and IMF staff estimates.

Because banks rely largely on domestic deposits for funding, the funding structure provides an additional buffer against turmoil in international financial markets. The lower loan-to-deposit ratios in Papua New Guinea and the Solomon Islands reflect the large excess liquidity these countries have faced since the global financial crisis. Given the large bank capitalization, high loan-to-deposit ratios do not necessarily imply reliance on wholesale funding. These ratios have been generally stable in recent years, with the exception of Tonga and the Solomon Islands, where banks have improved their funding profiles since 2008 by increasing their reliance on deposits (Figures 6.26 and 6.27).

Figure 6.26Banking Sector Loan-to-Deposit Ratios

(Percent)

Sources: Country authorities; and IMF staff estimates.

Figure 6.27Banking Sector Loan-to-Deposit Ratios

(Percent, 2014)

Sources: Country authorities; and IMF staff estimates.

The quality of loans in PICs appears to be relatively good, with some variation reflecting country-specific circumstances, including collateral laws.10 The ratio of loan-loss provisioning to total loans—a proxy for loan quality—suggests an improvement across almost all PICs after the global financial crisis (Figure 6.28).

Figure 6.28Banking Sector Ratios of Provision Expense to Gross Loans

(Percent)

Sources: Country authorities; and IMF staff estimates.

Provident and Trust Funds

A more direct effect of a global economic slowdown will occur through the impact on PICs’ provident and trust funds. These are large, relative both to GDP (Table 6.1) and to the size of the domestic banking systems. In some cases, the objective of the funds is to provide retirement benefits, while in others it is to finance budget deficits. The experience during the global financial crisis highlights the vulnerability of these funds, as demonstrated by the negative returns on investment exceeding 20 percent for the compact trust funds of Micronesia and Marshall Islands (Table 6.2).

Table 6.1Pacific Island Countries: Selected Sovereign Funds
DateEstimated Value (Percent of GDP)
NameCountryCreated2007201020122013
Trust Fund for the People of the Federated States of Micronesia (FSM Compact Trust Fund)Micronesia200448.060.478.9102.7
Trust Fund for the People of the Republic of the Marshall Islands (RMI Compact Trust Fund)Marshall Islands200457.168.889.8107.6
Revenue Equalization Reserve Fund (RERF)Kiribati1956407.9335.7338.3353.4
Tuvalu Trust Fund (TTF)Tuvalu1987335.3311.2339.1354.3
Petroleum Fund of Timor-Leste (Petroleum Fund)Timor-Leste200570.4163.8210.5285.9
Fiji National Provident Fund (FNPF)Fiji196663.458.156.656.5
Nambawan Super (Nambawan)Papua New Guinea196112.011.711.712.3
Marshall Islands Social Security Trust Fund (MISSA)Marshall Islands199145.342.040.039.0
Palau Compact Trust FundPalau199483.476.573.177.1
Sources: Annual Reports; and authors’ estimates.
Sources: Annual Reports; and authors’ estimates.
Table 6.2Pacific Island Countries: Rates of Return on Sovereign Fund Assets(Percent)
FY06FY07FY08FY09FY10FY11FY12FY13
FSM Compact Fund−10.018.4−22.9−1.817.4−1.135.240.8
Fiji National Provident Fund7.45.95.56.96.26.86.67.2
Kiribati RERF7.43.7−7.75.14.03.312.89.5
RMI Social Security Administration9.111.6−9.95.18.2−2.310.9
RMI Compact Fund14.620.4−23.02.09.3−2.620.414.8
Palau Compact Trust Fund6.816.2−13.21.99.00.921.514.0
PNG Nambawan10.927.07.49.912.50.811.810.3
Timor Leste Petroleum Fund4.35.410.70.74.13.24.33.2
Tuvalu Trust Fund (TTF)4.65.1−12.72.011.47.210.612.0
Source: Annual Reports.Note: FSM = Federated States of Micronesia; RMI = Republic of the Marshall Islands.
Source: Annual Reports.Note: FSM = Federated States of Micronesia; RMI = Republic of the Marshall Islands.

The domestic versus foreign investment split of asset portfolios differs considerably across PICs. The difference naturally means that the implications for the vulnerability of the funds to external shocks vary.

Spillovers from a Downside Scenario

Although banks in PICs seem somewhat sheltered from shocks through their ownership and funding structures, the financial systems of PICs remain vulnerable to any worsening in the global economy.

Financial stress could occur through a fall in stock prices, which could affect PICs with large provident and trust funds whose assets are invested offshore (Kiribati, Marshall Islands, Micronesia, Palau, Tuvalu). Lower GDP growth attributable to a fall in remittances and tourism receipts would weaken the quality of loans and reduce banks’ profitability, which in turn would affect banks’ liquidity. Noninterest income, arising largely out of foreign exchange activities, plays a key role in determining bank profitability in the region and is higher than in other regional comparators (Table 6.3).11 Thus, a slowdown in tourism and remittances will put downward pressure on profits. Banks may attempt to make up for this lost revenue through higher interest rates, which could further stifle credit growth.

Table 6.3Interest and Noninterest Income in Pacific Island Countries and Selected Regional Comparators
Net Interest Income

(Percent of Total Assets, 2013)1
Noninterest Operations

(Percent of Average Assets, 2013)1
Fiji3.02.7
Papua New Guinea3.82.0
Samoa4.93.6
Solomon Islands3.94.1
Tonga4.04.3
Vanuatu3.83.0
Australia1.71.3
New Zealand0.50.2
Indonesia4.92.4
Malaysia1.91.4
Philippines2.72.2
Sources: Country authorities; IMF, Financial Soundness Indicators database; and IMF staff estimates.

Papua New Guinea data are for 2012.

Sources: Country authorities; IMF, Financial Soundness Indicators database; and IMF staff estimates.

Papua New Guinea data are for 2012.

A prolonged slowdown in credit growth would hinder private sector development and lower prospects for inclusive growth. Both demand and supply factors are likely to lead to lower credit growth. Tighter credit standards, as occurred after the global financial crisis, will likely follow heightened global uncertainty and turmoil in global financial markets; and lower economic growth coupled with potentially higher interest rates will reduce demand for credit. During 2008–09, credit growth fell across all PICs, with the largest declines—albeit from a high base—in commodity exporters. Since then, credit growth has remained anemic, with some mild signs of pickup in commodity exporters, but it has not yet recovered in commodity importers (Figures 6.29 and 6.30).12

Figure 6.29Pacific Island Countries: Credit to Private Sector

(Percent of GDP)

Source: IMF staff estimates.

Figure 6.30Pacific Island Countries: Change in Credit to Private Sector

(Percent, year-over-year)

Source: IMF staff estimates.

A scenario where financial turmoil in the euro area leads to the deleveraging of European banks, for instance, could trigger a funding shock to Australian banks given their relatively high reliance on wholesale funding. But this risk is limited. Australian banks were highly resilient to the global financial crisis, mainly because of sound regulation and supervision. The government’s Guarantee Scheme for Large Deposits and Wholesale Funding for banks, begun in late 2008, also helped maintain access to funding, as did the swap arrangement between the Reserve Bank of Australia and the U.S. Federal Reserve. Indeed, an IMF study (Jauregui and Schule 2011) suggests that Australia is better placed to cope with shocks from the deterioration of the global outlook than any other country, because of its large policy space and flexible exchange rate (IMF 2014).

Our analysis suggests that the ratio of provisions to loans would increase by nearly 1 percent in the event of a downside scenario (Figure 6.31). To estimate the impact of negative spillovers on PIC banks from a global slowdown, we use the growth results generated by the previous vector error correction model analysis for PICs and previous IMF analysis (Jauregui and Schule 2011) to gauge the impact of the deterioration of the global outlook on Australia.13 We then estimate the impact of the slowdown on banks’ provisioning. Simple econometric analysis suggests that the ratio of provisions to loans in PICs is linked to both the Australian and domestic business cycles, with all coefficients significant and with the expected sign.

Figure 6.31Pacific Island Countries: Impact of a Downward Scenario on the Financial Sector: Ratio of Provisions to Loans

(Percent)

Source: IMF staff estimates.

What Role for Policies? Rebuilding Policy Buffers and Implementing Structural Reforms

The policy response to a downward economic scenario would vary across PICs depending on their policy space. Fiscal space is limited in countries with high public debt, narrowing the scope for countercyclical policies (Figure 6.32). In some countries with large trust funds, fiscal rules that prevent additional drawdowns to finance budget deficits in the face of a crisis could also lead to procyclical policies. Addressing fiscal rigidities by reducing recurrent spending could help make fiscal policy less procyclical (see Chapter 10 for further discussion). While fiscal space in some PICs (Kiribati, Marshall Islands, the Solomon Islands) has increased in recent years relative to the precrisis level, in others, fiscal space has diminished on account of lower underlying fiscal balances (Figure 6.33). All islands have accumulated comfortable levels of foreign exchange reserves, which could provide a temporary cushion. Greater exchange rate flexibility would be warranted in economies with relatively weak monetary transmission mechanisms. This is also the case in Papua New Guinea, where the exchange rate channel of monetary policy remains effective, but excess liquidity is currently weakening interest rates and credit channels. The onset of lower inflation pressure because of falling oil prices has also reduced the monetary policy trade-off, increasing policy space.

Figure 6.32Public Debt, 2014

(Percent of GDP)

Sources: Country authorities; and IMF staff calculations.

Figure 6.33Rebuilding Policy Buffers

Sources: IMF, World Economic Outlook database; and IMF staff estimates.

To strengthen their resilience to shocks, PICs need to step up the rebuilding of policy buffers. Most PICs have made progress on this front since the global financial crisis, especially on reserves. However, more than half of PICs emerged from the crisis with somewhat less comfortable fiscal buffers (higher debt and larger fiscal deficits). Implementing growth-oriented structural reforms would help boost investor confidence and ensure sustainable and inclusive growth. Savings from the windfall of lower oil prices should be used to rebuild buffers and cushion the effects of revenue volatility, as well as put PICs in better stead to deal with the threat of natural disasters. This is particularly critical given that aid flows are expected to slowly decline in the medium and long term. In addition, focusing on the quality of spending and improving the spending mix toward education, health, and infrastructure will be key in lifting long-term growth potential.

Annex 6.1. Technical Summary of Econometric Methodology and Results

Econometric Methodology

Econometric analysis has given us an understanding of the short- and long-term relationships between GDP in each of the Pacific island countries (PICs) and GDP in other countries or regions. The analysis has also enabled us to assess the relevance of commodity price shocks in PICs, using measures of real oil prices, real food prices, or real nonoil commodity prices. We also investigated country-specific factors, such as shocks to sugar output in Fiji, the role of aid and remittances, and the impact of changes in global equity prices.

We employed three methodologies to this end. First, we used a cointegration analysis to test and estimate long-term relationships using a vector error correction model. Second, within the model, we used the impulse response analysis to gauge the impact on each PIC’s real GDP of a shock to the other variables in the model. And third, a structural version of the error correction model gave us estimates of the immediate impact of shocks and formed the basis of the scenario analysis.

Summary of Econometric Results for Each Country

Using the Johansen procedure, we found a cointegrating relationship for 10 of the 11 countries examined. For each country, we present the cointegrating relationship: the coefficient on the partner GDP variable is the long-term elasticity of growth in the PIC with respect to external partner GDP.

Details are provided of any restrictions on the long-term elasticities that were imposed and not rejected; for example, in some cases the coefficient estimate was close to one, suggesting that when a trading partner’s GDP increases over the long term, GDP in the PIC under examination increases by an equal percentage. From this long-term equation, a variable is constructed that measures the deviation from long-term equilibrium.

This variable is then used in a structural equation for each country, together with other variables that could influence growth in the short term. The structural equation shows the immediate or within-the-same-period spillover to the PIC from external demand and the impact of other shocks (such as food and fuel prices or global equity prices). The parameter estimates from the long-term equation and the structural equation are then used as inputs into the scenario analysis. See Annex Figure 6.1.1 for a summary of our findings for selected countries.

Fiji

Long-term equation:

We found a long-term cointegrating relationship between log real GDP in Fiji and log real GDP in Australia.14

Structural equation:

Annex Figure 6.1.1Pacific Island Countries: Growth Spillovers

Source: IMF staff calculations.

In the short term, supply factors also matter in determining GDP in Fiji. On the domestic side, sugar output has a positive and significant coefficient, consistent with the importance of the sugar sector in the economy. A 1 percent increase in sugar production would boost GDP by 0.13 percent. As expected, higher international oil prices have a negative impact on output in Fiji.

Kiribati

Long-term equation:

A long-term cointegrating relationship was found between log real GDP in Kiribati and log real GDP in Australia.

The restriction that the long-term elasticity was equal to one was not rejected (χ2: 3.63, p-value 0.06).

Structural equation:

In the long term, growth in Australia spills over to Kiribati one for one. In the short term, fluctuations in Australian GDP affect Kiribati with an elasticity of 0.4. Real oil price shocks have a large impact on Kiribati GDP in the short term: a 10 percent increase in oil prices reduces GDP growth by 0.8 percentage point. World equity prices also influence Kiribati GDP in the short term, with a 10 percent rise in world equity prices boosting GDP by 0.5 percent.

Marshall Islands

Long-term equation:

We found a long-term cointegrating relationship between log real GDP in Marshall Islands and the United States.

The restriction that the long-term elasticity was equal to one was not rejected (χ2: 5.68, p-value 0.06).

Structural equation:

D(ln(RGDPMHL)) = 0.65*D(ln(RGDP USA)) -0.91*ECM(-1) -0.03*ln(real oil) + constant

In the long term, fluctuations in U.S. growth spill over to Marshall Islands one for one. In the short term, the impact is smaller but still large, with a short-term elasticity of 0.65. Real oil price shocks have a strong impact on the GDP of Marshall Islands in the short term, with a 10 percent increase in oil prices reducing GDP growth by 0.3 percent.

Micronesia

Long-term equation:

A long-term cointegrating relationship was found between log real GDP in Micronesia and the United States.

The restriction that the long-term elasticity was equal to one was not rejected (χ2: 0.05, p-value 0.82).

Structural equation:

In the long term, fluctuations in U.S. growth spill over one for one to Micronesia, as in Marshall Islands. Most of this impact occurs quickly, with a short-term elasticity of 0.84. Real oil-price shocks have a large impact on Micronesia’s GDP in the short term, with a 10 percent rise in oil prices lowering GDP growth by 0.8 percent.

Palau

Long-term equation:

A long-term cointegrating relationship was found between log real GDP in Palau and the United States.

The restriction that the long-term elasticity was equal to one was not rejected (χ2: 1.48, p-value 0.46).

Structural equation:

In the long term, fluctuations in U.S. growth spill over one for one to Palau, as is the case in both Marshall Islands and Micronesia. In the short term, the impact is estimated to be greater than one, suggesting an overshooting in the near term. Real oil price shocks have a large impact on Palau GDP in the short term, with a 10 percent increase in oil prices reducing GDP growth by 0.5 percent.

Papua New Guinea

Long-term equation:

A long-term cointegrating relationship was found between log real GDP in Papua New Guinea and log real GDP in Australia and aid to Papua New Guinea.

Structural equation:

There is a long-term relationship between Papua New Guinean GDP, Australian GDP, and real aid to Papua New Guinea. Growth spillovers from Australia are large: holding the other variables constant, a 1 percent increase in Australian GDP would raise output in Papua New Guinea by 0.8 percent. Aid also appears to be important in the long term, but not in the short term. The coefficient on the real oil price is positive, consistent with Papua New Guinea being a commodity exporter.

Samoa

Long-term equation:

A long-term cointegrating relationship was found between log real GDP in Samoa and log real GDP in both Australia and New Zealand.

The restriction that the long-term elasticity was equal to one was not rejected (χ2: 0.67, p-value 0.41).

Structural equation:

Australia and New Zealand affect Samoa in both the short and long term, but the direct growth spillovers from New Zealand to Samoa are larger than from Australia. Over the long term, a 1 percent increase in GDP in New Zealand—holding other variables constant—will raise Samoan GDP by 1 percent, while the direct impact of Australia is much smaller. In the short term, the elasticity of Samoa’s GDP with respect to that of New Zealand is 0.5.

The Solomon Islands

Long-term equation:

A long-term cointegrating relationship was found between log real GDP in the Solomon Islands and log real GDP in Australia.

The restriction that the long-term elasticity was equal to one was not rejected (χ2: 3.16, p-value 0.02). Structural equation:

Australia is the main source of growth spillover, with a long-term elasticity of one. In the short term, however, there is no immediate impact on growth from Australia (but the impact begins to be felt after one year through the error correction term). GDP for the Solomon Islands is heavily influenced by international commodity prices, with nonoil commodity prices having a strong positive impact on growth, as might be expected for a commodity exporter. As an oil importer, however, higher oil prices are a drag on growth.

Tonga

Long-term equation:

A long-term cointegrating relationship was found between log real GDP in Tonga and New Zealand.

Structural equation:

New Zealand’s growth spills over to Tonga in both the short and long term. In the short term, a 1 percent increase in New Zealand GDP boosts GDP in Tonga by 0.2 percent, other things being equal. However, over the long term the effect is twice as large. Commodity prices negatively affect the business cycle. Subsample analysis suggested the increasing importance of emerging Asia in generating growth spillovers in Tonga, but the above equation was preferred for the scenario analysis.

Tuvalu

Given the short data sample, long-term analysis was not feasible for Tuvalu, but the short-term dynamics (that is, using growth rates) suggest that the elasticity of Tuvalu with respect to world GDP is 0.5. Moreover, spillovers from regional economies would also occur through Tuvalu’s trust fund, whose assets are invested offshore. The elasticity of Tuvalu GDP with respect to world equity prices is 0.05: a 10 percent increase in the world stock market will affect GDP growth in Tuvalu by ½ percentage point through wealth effects. For the scenario analysis, the elasticity of GDP in Tuvalu with respect to global oil prices is assumed to be 0.02, in line with other countries in the study.

Vanuatu

Long-term equation:

A long-term cointegrating relationship was found between log real GDP in Vanuatu and log real GDP in New Zealand and real tourism receipts.

Structural equation:

Australia is the main source of spillovers over both the short and long term. Subsample analysis suggests that Australia’s importance has increased over time. Real tourism receipts are also relevant, both in the short and long term, consistent with the importance of tourism in the Vanuatu economy. Tourism receipts capture growth spillovers from economies other than Australia. The long-term elasticity of Australia and tourism with respect to Vanuatu GDP is 0.3.

Annex 6.2. Commercial Banks
Annex Table 6.2.1Commercial Banks in Small States of the Pacific and Papua New Guinea
CountryAustralian BanksU.S. Banks1OtherDomestic Banks
FijiANZ

Westpac
Bank of Baroda (India)

Bank South Pacific (Papua New Guinea)

Bred Bank (Banque Populaire, France)
Home Finance Company
KiribatiANZ
Marshall IslandsBank of GuamBank of Marshall Islands
MicronesiaBank of GuamBank of the FSM1
PalauBank of Guam

Bank of Hawaii

Bank Pacific
Asia Pacific Commercial Bank

Palau Construction Bank
Papua New GuineaANZ

Westpac
Bank South Pacific

Kina Bank
SamoaANZBank South Pacific

(Papua New Guinea)
National Bank of Samoa

Samoa Commercial Bank
Solomon IslandsANZBank South Pacific

(Papua New Guinea)
Pan Oceanic Bank
Timor-LesteANZCaixa (Portugal)

Bank Mandiri (Indonesia)
National Commercial Bank of Timor-Leste
TongaANZBank South Pacific

(Papua New Guinea)

MBF Bank (Malaysia)
Tonga Development Bank

Pacific International

Commercial Bank
TuvaluNational Bank of Tuvalu

Development Bank of Tuvalu
VanuatuANZBred Bank

(Banque Populaire, France)

Bank South Pacific

(Papua New Guinea)
National Bank of Vanuatu
Sources: Country authorities; and IMF staff compilation.

Insured under the Federal Deposit Insurance Corporation scheme.

Sources: Country authorities; and IMF staff compilation.

Insured under the Federal Deposit Insurance Corporation scheme.

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This chapter is based on IMF Working Paper 12/154 (Sheridan, Tumbarello, and Wu 2012). We thank Peter Montiel, Richard Wood, and the other participants in the 2012 Pacific Islands conference in Samoa for their valuable comments. We also thank Ben Hunt and Keiko Honjo from the IMF Research Department for providing the data underlying the global shock scenarios, and Sri Joedianna Pg Hj Mohammed for collecting the information on the financial sector used in the section Assessing Spillovers to the Financial Sector. We greatly benefited from comments by Roberto Cardarelli, Matt Davies, Huidan Lin, Shanaka Peiris, Haiming Tan, John Vaught, and Aki Yoshida. We are very thankful to Professor Vance Martin for all his suggestions on the econometric analysis. We are in debt to Branan Karae and Ambassador Mack Kaminaga for liaising with the authorities in the Pacific island countries and providing the data underlying this analysis. Safieh Hekmat provided excellent editorial assistance.
1The PICs covered in this chapter are the IMF Pacific island members Fiji, Kiribati, Marshall Islands, Micronesia, Palau, Papua New Guinea, Samoa, the Solomon Islands, Timor-Leste, Tonga, Tuvalu, and Vanuatu.
2Global scenarios involving a negative global demand shock and a sharp increase in oil prices are described, for instance, in the IMF’s April 2012 World Economic Outlook. The January 2015 World Economic Outlook Update highlights global economic uncertainties as well as a significant drop in oil prices.
3Both the Australian and the New Zealand dollars depreciated by about 25 percent against the U.S. dollar between September 2014 and September 2015.
4Technical assistance from the Regional Assistance Mission to the Solomon Islands started in 2003, after the civil war, as a partnership between the government of the Solomon Islands and 15 Pacific countries. The assistance focuses on security, justice, law, and economic growth.
5A shorter sample period may apply, depending on country data availability.
6Cointegration models are preferable to single equation models, with variables expressed in percentage changes, because the former can capture both long- and short-term relationships among variables, not just the short-term ones.
7See IMF (2012b) for a description of these scenarios.
8The U.S. growth rate is assumed to fall by 0.75 percentage point at t + 1 and by 0.6 percentage point at t + 2. In Asia’s emerging market economies, growth is assumed to decline by 0.8 percentage point at t + 1 and by 0.4 percentage point at t + 2. For other countries (a grouping of countries in the Global Economy Model that includes Australia and New Zealand, among others) growth is estimated to decline by 1½ percentage points at t + 1 and by ½ percentage point at t + 2, relative to the baseline.
9The sensitivity of PICs’ growth rates to global commodity price shocks is similar to that described in Chapter 13.
10In most PICs, land is owned by the government and by families (communal land) rather than individuals. This often makes property rights unclear and constrains the use of land as collateral.
11See Davies and Vaught (2011) for a more detailed discussion of bank profits in PICs.
12In the commodity exporters (Papua New Guinea, the Solomon Islands), favorable terms of trade continue to support growth. Investment in the commodity sector lately has been financed mainly offshore, through FDI.
13According to Jauregui and Schule (2011), Australia’s growth rate drops by 1½ percentage points in the first year after the global negative shock and by 1 percentage point in the second year.
14The cointegration analysis suggests two long-term relationships at work (that is, two cointegrating vectors): one between Australia and New Zealand and one between Fiji and Australia. The relationship between Australia and New Zealand is 1 to 1 in the long term, consistent with previous IMF analyses; see Sun (2011) for the importance of growth spillovers from Australia to New Zealand. Direct growth spillovers from Australia to Fiji were found to be stronger than from New Zealand. In the long term, a 1 percent increase in GDP in Australia will raise GDP in Fiji by 0.8 percent.

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