Information about Asia and the Pacific Asia y el Pacífico
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CHAPTER 1 Explaining Higher Inflation in Indonesia: A Regional Comparison

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Thomas Rumbaugh
Published Date:
January 2012
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GEREMIA PALOMBA

Over the 20 years beginning in 1990, inflation in Indonesia has been consistently higher than elsewhere in the Asia region. 1 Indeed, inflation has often exceeded the 7–11 percent threshold above which it is estimated to adversely affect growth (Khan and Senhadji, 2000). At these rates, inflation may also make the poor significantly worse off by reducing real minimum wages and the income share of the lowest quintile (Easterly and Fischer, 2001). The higher inflation rate and its potential adverse effects raise the question: what is driving the Indonesian inflation differential vis-à-vis its neighbors?

This chapter reviews a number of stylized facts comparing inflation in Indonesia with that in other Asian countries. It uses econometric techniques to assess various hypotheses attempting to explain the Indonesian inflation differential with respect to neighboring countries. Finally, it discusses the policy implications for reducing inflation in Indonesia to a level closer to the region’s prevailing rates.

INDONESIAN INFLATION IN THE ASIAN CONTEXT

Inflation in Indonesia has been substantially higher than in the other countries of the region, both before and after the 1997–98 Asian financial crisis. Over the past two decades, the annual inflation rate in Indonesia has averaged about 11.3 percent, or about 8 percentage points higher than in neighboring countries, and has shown significantly higher variance (Figure 1.1 and Table 1.1). Although the magnitude of the inflation differential reflects, in part, the high inflation rates registered in Indonesia during the Asian financial crisis, the differential widened in the period after the crisis because inflation in neighboring countries declined while remaining broadly unchanged in Indonesia (Figure 1.2).

TABLE 1.1Headline Inflation in Selected Asian Economies (1991–2010)
PeriodIndonesiaRepublic of KoreaMalaysiaPhilipppinesSingaporeThailandDifferential
(Annual average)
1991-200512.54.53.07.51.43.89.0
1991-201011.34.22.96.91.73.67.8
Precrisisa8.25.83.89.42.35.13.5
Postcrisisa8.13.12.15.11.62.55.5
19919.49.34.418.73.45.72.5
19927.56.24.88.92.34.22.7
19939.74.83.67.62.33.35.7
19948.56.34.19.13.15.13.4
19959.44.53.56.91.75.85.4
19967.04.93.59.01.45.92.8
19976.24.42.65.92.05.62.4
199858.07.55.19.7-0.38.1
199920.70.82.86.70.00.320.1
20003.82.31.64.31.31.61.8
200111.54.11.46.11.01.79.2
200211.82.81.83.0-0.40.6
20036.83.51.13.50.51.85.1
20046.13.61.46.01.72.83.4
200510.52.83.07.60.54.57.8
200613.12.53.66.21.04.710.1
20076.32.52.02.82.12.24.0
20089.94.75.49.36.65.43.8
20094.82.80.63.20.6-0.9
20105.13.01.73.82.83.32.3
(End-period, 12-month percentage change)
1991-200513.34.22.97.11.33.79.9
1991-201011.64.02.96.51.73.58.3
Crisis, 199877.54.05.210.3-1.44.372.0
Precrisisa8.45.93.78.52.15.33.8
Postcrisisa8.02.82.25.01.72.45.4
19919.99.34.313.12.94.64.1
19925.04.54.88.21.83.11.1
199310.25.83.48.42.64.45.7
19949.65.64.07.22.94.85.0
19959.04.83.18.60.87.45.2
19965.14.93.47.12.04.81.0
199710.36.62.77.32.07.65.7
199877.54.05.210.3-1.44.3
19992.01.42.54.30.70.70.5
20009.30.01.36.72.11.4
200112.53.21.24.1-0.60.8
20029.93.71.72.50.41.68.3
20035.23.41.23.90.71.83.3
20046.43.02.18.61.32.93.5
200517.12.63.26.61.35.813.8
20066.62.33.14.30.83.54.2
20075.83.62.43.93.73.12.5
200811.14.14.48.05.50.47.9
20092.82.81.14.3-0.53.5
20107.03.52.23.04.63.03.8
(Annual standard deviation)
1991-20054.70.60.41.20.50.94.0
1991-20103.90.60.61.10.61.03.2
Crisis,23.80.90.91.80.81.922.5
1998–99
Precrisisa1.20.60.41.30.40.90.6
Postcrisisa2.10.50.61.00.80.91.3
19910.50.50.62.20.60.6-0.2
19922.11.10.40.70.30.81.6
19930.70.50.60.60.20.60.3
19940.90.50.41.10.40.40.4
19950.70.60.31.30.60.90.0
19961.70.30.22.00.31.21.2
19971.90.80.50.90.31.51.2
199823.31.40.81.31.12.222.0
199924.20.41.02.30.51.623.3
20003.90.70.21.20.50.53.4
20011.60.80.21.00.90.61.0
20021.90.50.40.50.50.51.5
20031.00.40.30.40.40.30.6
20040.80.50.51.70.50.70.1
20054.50.40.40.70.51.43.9
20064.50.20.61.10.41.33.9
20070.30.60.60.61.80.6-0.4
20080.10.20.30.40.10.8-0.2
20092.70.92.62.61.72.30.8
20101.30.50.30.61.30.40.7
Source: IMF, International Financial Statistics database.Note: The differential is defined as inflation in Indonesia minus the geometric average of inflation in the other countries. “…” means that the differential is not calculated because of negative inflation in some of the comparator countries

Precrisis includes 1991–97. Postcrisis includes 2000–10, except for end-year inflation which also includes 1999.

Postcrisis includes 2000–10, except for end-year inflation which also includes 1999.

Source: IMF, International Financial Statistics database.Note: The differential is defined as inflation in Indonesia minus the geometric average of inflation in the other countries. “…” means that the differential is not calculated because of negative inflation in some of the comparator countries

Precrisis includes 1991–97. Postcrisis includes 2000–10, except for end-year inflation which also includes 1999.

Postcrisis includes 2000–10, except for end-year inflation which also includes 1999.

Figure 1.1Average Annual Inflation Rates in Selected Asian Countries, 1991–2010

Source: CEIC Data Co. Ltd.

Figure 1.2Average Annual Inflation Rates in Selected Asian Countries

Sources: CEIC Data Co., Ltd.; and IMF staff calculations.

a Differential between Indonesia and average inflation in neighboring countries (in percentage points).

Inflation in Indonesia has been higher across a wide range of products. The country has registered a positive inflation differential vis-à-vis the other countries in the sample across all the main components of the consumer price index (CPI). After the Asian financial crisis, the differential widened for most of the CPI components, although for food items the increase is mainly due to an outlier spike in 2008. Indeed, without this outlier, the inflation differential for food items decreased after the crisis, while widening for all the other categories, particularly housing, education, and transportation and communications (Figure 1.3), therefore challenging the commonly held belief that Indonesia’s high inflation is the result of distortions in the agricultural sector and weak rural infrastructure.

Figure 1.3Indonesia Inflation Differential Across CPI Components

Source: IMF staff calculations.

Note: Other Asian countries include: Republic of Korea, Malaysia, the Philippines, Singapore, and Thailand.

a Only transportation for Republic of Korea and Singapore.

WHAT CAN EXPLAIN INFLATION IN INDONESIA AND IN NEIGHBORING COUNTRIES?

The results clearly show that no single CPI component can explain the Indonesian inflation differential with respect to other Asian countries; hence, other factors need to be explored.

Theories Explaining Inflation Across Countries

The literature includes analyses of several factors to explain the sources of inflation and inflation differentials across countries. It is generally accepted that inflation is

  • A phenomenon with some degree of inertia resulting from, for example, the way expectations are formed. Inflation expectations are in part adaptive or backward looking, particularly in countries that, like Indonesia, have experienced long periods of high inflation (Mankiw, Reis, and Wolfers, 2003).

  • Closely related to country-specific shocks. These include demand and supply shocks associated with, among other factors, the pace of economic activity (Coe and McDermott, 1997), the stance on monetary policy, and exchange rate fluctuations (Rajaguru and Siregar, 2002). High demand pressures, expansionary monetary policy (e.g., rapid growth in monetary aggregates), and significant currency depreciations have been found to be positively correlated to inflation across countries (Campillo and Miron, 1996; Anglingkusumo, 2005).

  • Dependent on the structural features of the economy. For example, the degree of central bank independence, economic openness (Romer, 1993), the public debt burden (Campillo and Miron, 1996), and the type of exchange rate regime (Loungani and Swagel, 2001) are found to have an impact on the rate of inflation across countries. Central bank independence is generally found to reduce inflation, especially in less developed countries, because it helps to insulate monetary policy from political influences. Inflation is often found to be negatively associated with economic openness because openness increases the costs of unanticipated monetary expansion and allows for additional productivity gains and price competition (IMF, 2006). Fiscal imbalances may also lead to higher inflation either by triggering higher money growth or forcing currency depreciation.

  • Related to the degree of political stability and institutional development. For example, frequent cabinet changes and weak institutions shorten the time horizon of governments and make difficult the pursuit of consistent and sound policies for maintaining low inflation. A number of political and institutional variables have been found to affect inflation, particularly in developing countries (Cukierman, Edwards, and Tabellini, 1991; Aisen and Veiga, 2005).

Some Simple Facts That Explain Inflation in Indonesia and Neighboring Countries

Some factors explaining inflation seem to play a more important role in Indonesia than in neighboring countries.

  • Inflation inertia appears to be stronger in Indonesia than in the other countries in the sample. Countries that have had relatively high inflation rates in the past (e.g., in the precrisis period) have registered lower inflation rates in more recent years. In this respect, Indonesia seems to face stronger inflation inertia than the other countries as evidenced by the fact that inflation has been as high after the crisis as before the crisis (Figure 1.4).

  • The positive relationship between inflation and the distance the economy is from full employment (the output gap) is stronger in Indonesia. As expected, smaller output gaps are associated with higher inflation rates across all the countries in the sample (Figure 1.5). Once again, Indonesia appears to be an outlier, with much higher inflation for a given output gap (Table 1.2).2

  • Political and institutional factors affect inflation differently across countries. Political risks and government instability (measured by the International Country Risk Guide’s [ICRG’s] indexes) are positively correlated with inflation across selected Asian countries. However, Indonesia is once again an outlier in the region, with high political risks associated with relatively higher inflation (Figures 1.6 and 1.7). 3

Figure 1.4Pre- and Postcrisis Annual Average Inflation in Selected Asian Countries

Sources: CEIC Data Co., Ltd.; and IMF staff calculations.

Figure 1.5Average Inflation Versus Average Output Gap in Selected Asian Countries, 1991–2005

Sources: CEIC Data Co., Ltd.; and IMF staff calculations.

TABLE 1.2Inflation Correlations in Selected Asian Countries and Indonesia, 1991–2005
VariableAsian CountriesIndonesia
Output gap-0.16-0.47
Political risks0.430.39
Government stability0.20-0.12
M2 growth0.620.79
NEER, percentage change-0.58-0.69
Source: IMF staff calculations.Note: Asian countries include Indonesia, Republic of Korea, Malaysia, the Philippines, Singapore, and Thailand. M2 = money supply; NEER = nominal effective exchange rate.
Source: IMF staff calculations.Note: Asian countries include Indonesia, Republic of Korea, Malaysia, the Philippines, Singapore, and Thailand. M2 = money supply; NEER = nominal effective exchange rate.

Figure 1.6Average Inflation Versus Average Government Instability in Selected Asian Countries, 1991–2005

Source: Government stability derived from ICRG, as rebased.

Note: Higher government instability index denotes greater government instability.

Figure 1.7Average Inflation Versus Average Political Risk in Selected Asian Countries, 1991–2005

Source: Political risk derived from ICRG, as rebased.

Note: Higher political risk index indicates greater political risk.

In other respects, Indonesia is similar to other Asian countries. The influence of changes in monetary aggregates and exchange rates on inflation in Indonesia is broadly similar to that in neighboring countries (Figures 1.8 and 1.9). In Indonesia, monetary growth and currency depreciation (as measured by the nominal effective exchange rate, or NEER) are on average higher, but the degree of correlation with inflation appears to be similar to that in other countries (Table 1.2). Notably, the more expansionary monetary policy and the higher average inflation rate in Indonesia suggest that the country’s inflation differential may be, in part, a monetary phenomenon.

Figure 1.8Average Inflation Versus Nominal Effective Exchange Rate in Selected Asian Countries, 1991–2005

Sources: CEIC Data Co., Ltd.; and IMF, Information Notice System.

Note: a Lower number indicates currency depreciation.

Figure 1.9Average Inflation Versus Growth of Money Supply in Selected Asian Countries, 1991–2005

Sources: CEIC Data Co., Ltd.; and IMF, International Financial Statistics.

Overall, inflation in Indonesia appears to differ from that in neighboring countries in the way it relates to certain structural factors while being similar in other respects. Therefore, an econometric analysis is needed both to clarify the differences and similarities of the inflation process in Indonesia and to explore the reasons underlying Indonesia’s inflation differential vis-à-vis its neighbors.

AN ECONOMETRIC ANALYSIS

In this section, an econometric analysis is used to explain why inflation in Indonesia has been higher than elsewhere in the region. The analysis is carried out in three steps. First, a cross-country empirical model identifying the main inflation determinants across the sample is estimated. 4 Second, a set of Indonesia-related slope dummies is employed to investigate whether the role of the inflation determinants in Indonesia differs from the average of the selected countries. 5 Finally, the causes of Indonesia’s higher inflation are examined by looking at the combined effect of two elements: how inflation determinants have evolved in Indonesia compared with other countries in the sample and how they have affected inflation in Indonesia differently as compared with other countries (using the coefficients of the dummy variables). In this framework, the basic econometric model sets a benchmark against which to test different hypotheses about the reasons for higher inflation in Indonesia.

Step 1. Explaining Cross-Country Inflation in Selected Asian Countries

A simple model explains inflation well in the selected Asian countries. Across the sample, the rate of inflation depends positively on past inflation, the output gap, growth in the money supply (as defined by “M2,” meaning money in circulation and close substitutes), and currency depreciation (Table 1.3). Inflation also depends on institutional factors as measured, for example, by the ICRG’s political risk index. In particular, government instability and the quality of national bureaucracies are the two institutional factors that make the strongest contribution to inflation.6 Structural factors such as the degree of economic openness, the public debt burden, and the level of price regulation (as measured by an index from the Heritage Foundation) play no role in shaping inflation dynamics across the selected countries. (These results are not reported.)

TABLE 1.3Determinants of Cross-Country Inflation in Asian Countries
VariableModel (1)Model (2)
Previous inflation0.64***0.6***
Output gap0.12*0.11**
M2 growth0.03***0.03***
NEER growtha-0.20**-0.20**
Political risk0.10**
Government instability0.14***
Lack of bureaucracy quality0.59*
Chi-square0.660.00
Number of observations348348
Source: IMF staff estimates.Notes: Difference GMM estimations using quarterly data 1990:Q4–2005:Q4. Independent variable: End-period inflation rate.Countries: Indonesia, Republic of Korea, Malaysia, the Philippines, Singapore, and Thailand.

denotes significance at 10 percent.

denotes significance at 5 percent.

denotes significance at 1 percent.

Negative changes indicate depreciation.

Source: IMF staff estimates.Notes: Difference GMM estimations using quarterly data 1990:Q4–2005:Q4. Independent variable: End-period inflation rate.Countries: Indonesia, Republic of Korea, Malaysia, the Philippines, Singapore, and Thailand.

denotes significance at 10 percent.

denotes significance at 5 percent.

denotes significance at 1 percent.

Negative changes indicate depreciation.

Step 2. What Is Special about Inflation in Indonesia?

Inflation in Indonesia is more persistent and more sensitive to country-specific shocks and political risks than it is in other Asian countries. The estimates of the slope dummies suggest that inflation in Indonesia is more sensitive to past inflation, the output gap, exchange rate fluctuations, and political risks than it is in the other countries of the sample. The estimated magnitude of these effects appears significant. For example, using a modified version of our basic model (Table 1.4, Model 3), an additional 1 percentage point in past inflation is associated with an increase in the inflation rate of about 0.65 percent in Indonesia, 0.2 percentage points higher than the sample average. This suggests that the historically high inflation rates in Indonesia have generated strong inflation inertia. At the same time, an additional 1 percentage point change in either the output gap or in the depreciation of the currency in Indonesia is associated with an increase in the inflation rate of about 0.36 percent, 0.3 percentage points higher than in other countries (Table 1.4, Models 4 and 6). Finally, a 1 percentage point increase in the overall political risk index increases inflation in Indonesia by 0.2 percentage points compared with an increase of 0.1 percentage points for the average of the sample (Table 1.4, Model 7). The results are robust to structural changes caused by the crisis as the model estimated for the whole sample is broadly similar to the model estimated for the postcrisis period.

Monetary policy has similar effects on inflation in Indonesia and other Asian countries. The coefficient of the Indonesia-related slope dummy for money growth is not significant (Table 1.4, Model 5). This suggests that an additional 1 percentage point increase in the growth of M2 is associated with an increase in inflation of a magnitude similar to that in neighboring countries.

TABLE 1.4Determinants of Cross-Country Inflation
VariableModel (3)Model (4)Model (5)Model (6)Model (7)
Previous inflation0.45***0.67***0.60***0.53***0.63***
Output gap0.13*0.08*0.12**0.09**0.12**
M2 growth0.03***0.03***0.02***0.01***0.03***
NEER growtha-0.20***-0.19**-0.18**-0.06***-0.19**
Political risk0.12***0.10*0.11***0.90***0.07**
Indonesia dummy
Previous inflation0.20**
Output gap (Indonesia dummy)0.28***
M2 growth (Indonesia dummy)0.07
NEER growth (Indonesia dummy)-0.30***
Political risk (Indonesia dummy)0.10***
Chi-square0.000.000.000.000.00
Number of observations348348348348348
Source: IMF staff estimates.Notes: Difference GMM estimations using quarterly data 1990:Q4–2005:Q4. Independent variable: End-period inflation rate.Countries: Indonesia, Republic of Korea, Malaysia, the Philippines, Singapore, and Thailand.

denotes significance at 10 percent.

denotes significance at 5 percent.

denotes significance at 1 percent.

Negative changes indicate depreciation.

Source: IMF staff estimates.Notes: Difference GMM estimations using quarterly data 1990:Q4–2005:Q4. Independent variable: End-period inflation rate.Countries: Indonesia, Republic of Korea, Malaysia, the Philippines, Singapore, and Thailand.

denotes significance at 10 percent.

denotes significance at 5 percent.

denotes significance at 1 percent.

Negative changes indicate depreciation.

Step 3. Explaining the Indonesian Inflation Differential

The inflation differential between Indonesia and neighboring countries is largely explained by inflation inertia and political risks along with rapid monetary expansion and currency depreciation. In general terms, the inflation differential can be explained by a combination of two elements: how the different factors influencing inflation have evolved over time in each country and how differently these factors have affected inflation in Indonesia relative to other countries (in this model, the coefficients of the Indonesia slope dummies). Looking at the combined effects of these two elements, inflation inertia and political risks explain, on average, about 75 percent of the Indonesian inflation differential with respect to selected Asian countries (Table 1.5). 7 Monetary policy and exchange rate depreciation are also seen to contribute to the inflation differential, although to a smaller extent (about 25 percent), with the additional money-generated inflation coming from the expansionary monetary policy in Indonesia compared with other countries. In contrast, the output gap has played little role in determining the Indonesian inflation differential because its stronger effect on inflation (significant and large slope dummy coefficient) has been largely offset by the lower average output gap in Indonesia compared with the other countries in the sample.

TABLE 1.5Sources of the Average Indonesian Inflation Differential
Mean variablesAverage additional inflation effecta
VariableCoefficients of dummiesSamplebIndonesiaPercentage differenceTotal (percentage points)Proportion (percentage of total)
Previous inflation0.205.512.7132.05.242.6
Output gap0.28-0.2-0.1-19.40.00.0
M2 growthc0.0712.920.457.51.19.0
NEER growth-0.3-2.5-6.9176.52.016.0
Political risk0.1031.845.844.04.032.4
Total12.3100.0
Source: IMF staff estimates.

Effects calculated using different models and average values.

Countries: Indonesia, Republic of Korea, Malaysia, the Philippines, Singapore, and Thailand.

Coefficient not significant.

Source: IMF staff estimates.

Effects calculated using different models and average values.

Countries: Indonesia, Republic of Korea, Malaysia, the Philippines, Singapore, and Thailand.

Coefficient not significant.

CONCLUSIONS AND POLICY ISSUES

Over the past two decades, Indonesia has recorded persistently higher inflation than its neighbors have. This analysis suggests that the causes of the Indonesian inflation differential with respect to other countries in the region include various factors such as strong inflation inertia and political instability, combined with expansionary monetary policy and currency depreciation. Conversely, structural factors such as the degree of economic openness, the public debt burden, and the level of price regulation play no role in explaining differences in inflation across Asian countries.

In light of the entrenched nature of inflation in Indonesia, reducing it requires maintaining a consistent monetary framework and establishing the credibility of that framework. The strong persistence of inflation implies that the convergence process toward the lower regional inflation rates might be slow and costly to economic growth. To reduce this cost, and to accelerate the convergence process, Bank Indonesia has to build its credibility and thus affect the formation of inflation expectations. In this respect, Bank Indonesia’s development and establishment of a strong and credible inflation-targeting framework could play an important role in reducing inflation to regional standards.

REFERENCES

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    AnglingkusumoR.2005Money-Inflation Nexus in Indonesia: Evidence from a P-Star Analysis,Tinbergen Institute Discussion Paper No. 05-054/4 (Rotterdamthe Netherlands: Tinbergen Institute).

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    CampilloM. and J.A.Miron1996Why Does Inflation Differ Across Countries?NBER Working Paper No. 5540 (CambridgeMassachusetts: National Bureau of Economic Research).

    CoeD.T. and C.J.McDermott1997Does the Gap Model Work in Asia?Staff Papers International Monetary Fund Vol. 44 (March) pp. 5980.

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IMF Country Report Nos. 09/230 and 10/284.

The analysis in this chapter is based on a panel of quarterly data covering the period 1990:Q4–2010:Q4, and includes, in addition to Indonesia, five neighboring countries: the Republic of Korea, Malaysia, the Philippines, Singapore, and Thailand. The econometric analysis relies on quarterly data through 2005:Q4 to exclude the introduction of the inflation-targeting framework in Indonesia. A database from CEIC Data Company Ltd. as of 2006 is used for inflation data for the period 1990:Q4–2005:Q4 and CEIC updates as of 2011 for the period 2006:Q1–2010:Q4.

Results remain broadly unchanged if the average inflation rate calculation excludes the crisis period.

Indonesia would be less of an outlier if the average annual inflation rate calculation excluded the crisis period. Despite the similarity in the average level of political risk between Indonesia and Korea (and the lower average government instability in Indonesia), Indonesia has recently been falling behind Korea on both accounts. However, before the crisis, Indonesia had lower political risk and instability, thus showing a better average rating than Korea for the period as a whole.

The basic model is a dynamic panel in which the explanatory variables include the lagged dependent variable. To address possible endogeneity problems, difference generalized method of moments (GMM) estimators are used (Arellano and Bond, 1991).

The coefficients of the slope dummies measure the extent to which the impact of a given variable on inflation is different in Indonesia compared with the sample of selected countries.

The ICRG political risk variable aggregates 12 subcomponents, including government stability and bureaucracy quality. The indexes have been rebased so that the greater the political risks (instability, lack of quality of the bureaucracy, and so on), the higher are the indexes.

These values are only indicative because they are obtained by using coefficients from different models.

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