Applied Econometrics and International … into three periods: 1950-1965 (the Soekarno-era), 1966-1997 (the Soeharto-era) and 1998-2002 (the post-currency crisis). A visual inspection

Applied Econometrics and International Development. AEID.Vol. 5-4 (2005)

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THE SOURCES AND DYNAMICS OF INFLATION IN INDONESIA:AN ECM MODEL

ESTIMATION FOR 1952-2002 HOSSAIN, Akhtar*

Abstract This paper uses annual data for the period 1952-2002 to investigate the inflationary process in Indonesia within the cointegration-and error-correction modeling framework. The empirical results suggest that the consumer price index (CPI), the stock of narrow (M1) or broad money (M2) and real permanent income form a (weakly) cointegral relationship for the complete sample period. This relationship remains broadly stable for several sub-samples, especially when the model is estimated with a narrow definition of money. The dynamic relationship between money, output, prices, and the exchange rate is investigated within a general-to-specific error-correction modeling framework. The presence of a significant error-correction term implies that given economic growth, there existed a long-run causal relationship between money supply growth and inflation. JEL classification: C22, E31, F31 Key words: Inflation, Money Growth, Error-Correction Model, Indonesia 1. Introduction In the low-inflationary Asia-Pacific region, Indonesia is considered an inflation-prone country. This is largely because of Indonesia’s inflation history in the 1950s and early 1960s when it was on the verge of ‘hyperinflation’ and economic collapse (Arndt, 1971; Hill, 1996; Thomas and Drysdale, 1964; Sundrum, 1973). Most economists, writing on Indonesia’s economy, have subscribed to the view that its high inflation during the 1950s and early 1960s had

* Akhtar Hossain is a Senior Lecturer in Economics at the University of Newcastle, Australia, email: [email protected].


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fiscal-monetary roots1 (Aghevli and Khan, 1977; Arndt, 1971; Corden and Mackie, 1962; Hicks, 1966; Mackie, 1967). As happened in most cases of hyperinflation (Sachs and Larrain, 1993), the political change in 1966 and subsequent stabilization and economic reforms brought Indonesia’s inflation rate down to a single digit level within a remarkably short period of time.

Since the late-1960s to the late-1990s Indonesia experienced moderately high inflation on average within the range of about 10-12 percent per annum, except during three supply/external shocks. The first was the OPEC oil shock during 1973-1974 when Indonesia’s inflation rose to about 35 percent per annum. The second was the OPEC oil shock during 1979-1980 when Indonesia’s inflation was about 20 percent per annum. The third was the Asian currency crisis during 1997-1999 that hit the Indonesian economy, and later its society and polity, the most. During the peak of the crisis in 1998, Indonesia’s inflation rose to about 60 percent. This was a transitory phenomenon, and it did not lead to hyperinflation as many feared because a set of IMF-supported stabilization policies were already in place.2

Such varied inflationary experiences of Indonesia since the early 1950s may be considered a rich source of information on monetary relations for developing countries, especially the linkage between money supply growth and inflation.3 However, although monetary targeting of one form or the other was the preferred strategy of monetary policy in Indonesia since the late 1960s to 2003, to what extent inflation in this country originated from an excess money supply under different exchange rate regimes remains unknown. This paper makes an attempt to fill this gap in the literature. The rest of the paper is organized as follows. Section 2 reports the summary data for inflation, money supply growth and output growth for Indonesia during 1950-2002. Section 3 develops a monetary model of inflation and uses it as a theoretical basis for this study. Section 4 estimates the cointegration-and error-correction models of inflation. Section 5 summarizes findings and draws conclusion. The paper has an appendix, which reports the data sources and a summary of the time series properties of variables used in the regression analysis.4

Hossain, A. The sources and dynamics of inflation in Indonesia

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2. Money, Output and Prices in Indonesia: 1950-2002 Table 1 reports summary data for money growth, inflation and output growth in Indonesia for the period 1950-2002. The data are grouped into three periods: 1950-1965 (the Soekarno-era), 1966-1997 (the Soeharto-era) and 1998-2002 (the post-currency crisis). A visual inspection of the data reveals that during the Soekarno regime, there was a high degree of correlation between money supply growth and inflation. This was the period when the Indonesian economy, which was subsistence in nature, grew slowly and was operating under a repressed financial system. Table 1. Money, Output and Prices in Indonesia: 1950-2002 (Period/annual average, percent) Money Growth Period/Year CPI-

Inflation Narrow Broad Economic

Growth The Soekarno-Era 1950-1954 1955-1958 1959-1965 The Soeharto-Era 1966-1972 1973-1977 1978-1984 1985-1990 1991-1997

The Post-Currency Crisis 1998 1999 2000 2001 2002

20.8 26.6

162.9

41.1 24.4 12.3 7.0 8.5

57.7 20.5 4.4 12.0 11.4

28.0 29.1 104.8

168.5 33.8 23.9 19.0 18.3

25.3 28.8 37.7 8.8 7.4

119.7a

172.4 36.9 28.7 29.8 26.2

62.8 12.2 16.6 12.8 4.5

5.8b

2.3 2.0

6.5 7.9 6.5 5.6 6.9

-13.1 0.8 4.9 3.5 3.7

Sources: Author’s compilation based on Arndt (1971), Thomson and Drysdale (1964), and IMF, IFS Yearbook. Notes: a = 1960-65; b = 1952-53.


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There is consensus that the hyperinflationary situation in Indonesia in 1965 was long in making and originated from monetization of sustained budget deficits. Although Indonesia operated under a fixed exchange rate system, the rapid monetary expansion, in the presence of trade and capital controls, led to high inflation. Indonesia’s economic growth rate during the Soeharto regime was rapid and steady until it experienced the currency crisis during 1997-1998. This was the period when Indonesia maintained open capital accounts, had minimum trade restrictions and operated under a pegged or managed floating exchange rate system. Therefore, it is plausible that the linkage between money supply growth and inflation during this period was not precise. Not only that the money supply process became somewhat endogenous, the phenomenal economic growth and any structural change in the money demand function due to financial reforms possibly affected the money growth-inflation relationship. Nevertheless, McLeod (2004:p.1) maintains that “there is a close medium-to-long-term relationship between money growth and inflation in Indonesia, and that this has not been greatly disturbed by the [currency] crisis”. Although the data in Table 1 appears consistent with McLeod’s proposition, this remains a testable hypothesis. 3. A Model of Inflation This section develops a monetary model of inflation and shows the linkage between money supply growth and inflation and between inflation and devaluation. The model is developed within the tradable-nontradable modeling framework. The Domestic Price Level Assume that goods transacted in a small, open economy can be divided into tradables and nontradables. Let the domestic price of transacted goods (Pt) be defined as the geometric average of the prices of tradables (PTt) and nontradables (PNTt). The price level can then be specified in the following natural logarithmic form: ln Pt = φ ln PTt + (1 - φ) ln PNTt, (1)


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where φ is the share of tradables in total expenditure. For simplicity, φ is assumed constant.5

The Price of Tradables

For a small economy the price of tradables in foreign currency is determined in the international market. Following the purchasing power parity proposition, the price of tradables in domestic currency can then be expressed as ln PTt = ln ERt + ln PTf

t, (2) where ER is the exchange rate (defined as units of domestic currency for each unit of foreign currency) and PTf is the price of tradables in foreign currency. Equation (2) suggests that the price of tradables in domestic currency may change in response to a change either in the exchange rate or in the price of tradables in foreign currency or both. When the exchange rate remains fixed, the price of tradables in domestic currency changes with the change in the price of tradables in foreign currency. However, under a flexible exchange rate system, the price of tradables in domestic currency may change when the exchange rate changes with or without a change in the price of tradables in foreign currency. For simplicity, PTf is normalized to unity. Equation (2) can then be written as ln PTt = ln ERt. (2') This shows a one-to-one relationship between the price of tradables and the exchange rate. If the exchange rate is considered an exogenous policy instrument, ceteris paribus, devaluation may lead to a rise in the domestic price level (Prachowny, 1975). However, the exchange rate is not a purely exogenous policy instrument. It can be largely endogenous in the sense of being either determined by market forces under a flexible exchange rate system, or changed by the monetary authorities


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through a reaction function in response to pressure built up on the exchange rate under a fixed or an adjustable pegged exchange rate system. In general, it is suggested that a feedback relationship exists between the price level and the exchange rate. Such a relationship usually becomes pronounced during periods of high inflation or hyperinflation (Dornbusch, 1988). The Price of Nontradables: Assume that the price of nontradables changes in response to disequilibrium in the money market. Within a flow disequilibrium in the money market, the price of nontradables may then change in response to a discrepancy between the log difference of actual real balances at the beginning of the period (∆ln mt-1) and the log difference of real balances that individuals desire to hold at the end of the period (∆ln md

t), such that ln PNTt – ln PNTt-1 = γ (∆ln mt-1 - ∆ln md

t) (3) where m = M/P (M being the nominal money stock and P the price level); γ is the coefficient of adjustment, whose value is expected to lie between zero and unity; and u is a random error term with zero mean and a constant variance. Equation (3) shows that only a proportion (γ) of disequilibrium in the money market is eliminated between periods t – 1 and t. Inflation: Take the first-order logarithmic differences of equations (1) and (2’), such that ln (Pt/Pt-1) = φ ln (PTt/PTt-1) + (1 - φ) ln (PNTt/PNTt-1) (4)

ln (PTt/PTt-1) = ln (ERt/ERt-1). (5)

Substitution of equations (3) and (5) into equation (4), following rearrangement of terms, yields ln (Pt/Pt-1) = φ ln (ERt/ERt-1) + (1 - φ)γ (∆ln mt-1 - ∆ln md

t) (6)


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Because the term representing flow disequilibrium in the money market cannot be measured directly, one way of simplifying this equation is to specify an equation for changes in desired real balances,6 such that ∆ln md

t = β0 + β1 ∆ln ypt, (7)

where yp is real permanent income and the βs are structural parameters. The intercept term β0 captures the trend element in the level of money demand. Substitution of equation (7) into equation (6), after manipulations, yields ln (Pt/Pt-1) = - (1 - φ) γβ0 + φ ln (ERt/ERt-1) + (1 - φ)γ ∆ln Mt-1 – (1 - φ)γ

∆ln Pt-1 - (1-φ)γβ1 ∆ln yt (8) This is an estimable model of inflation for a developing country that operates under an adjustable pegged, or managed floating, exchange rate system (Hossain and Chowdhury, 1996). It shows that inflation depends on the rate of devaluation, the rate of permanent income growth, and the rate of growth of the money stock with a one-period lag.7 The variables of interest are the rate of devaluation and the money growth rate. The effect of devaluation on the inflation rate is given by φ , which represents the average share of tradables in total expenditure.8 Exchange Rate Reponses to Inflation: The inflation equation (8) is in quasi-reduced form because devaluation, although it appears in the right-hand side of the equation, cannot be considered an exogenous policy instrument. Under an adjustable pegged exchange rate system, devaluation is essentially a response of the monetary authorities to high inflation in the home country relative to inflation in its trading partners. In the event that the monetary authorities follow a real target approach to exchange rate policy (Corden, 1991,1993), they are likely to adjust the nominal exchange rate to inflation differentials between the home country and its trading partners with a view to preventing the real


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exchange rate from appreciating.9 Accordingly, a policy reaction function that is compatible with the relative purchasing power parity proposition can be specified as follows: ln (ERt/ERt-1) = δ (∆ln Pt-1 - πe

f), (9) where πe

f is foreign inflation (assumed constant) and δ is the reaction coefficient, whose value lies between zero and one. It suggests that devaluation in the current period is in response to an inflation differential between the home country and its trading partners in the last period. Substitution of equation (9) into equation (8) yields ln (Pt/Pt-1) = - [(1 - φ)γβ0 + δπe

f ] + (1 - φ)γ ∆ln Mt-1 + [φδ - (1 - φ)γ] ∆ln Pt-1 - (1 - φ)γβ1 ∆ln yp

t +(1 - φ) ut. (10) This is a restricted model of inflation that has eliminated devaluation from the specification. However, it is consistent with the classical-monetarist tradition, which considers devaluation more an effect than a primary source of inflation. Whether this restricted model is a valid representation of the inflationary process in Indonesia can be considered a testable hypothesis. This hypothesis could be accepted if devaluation is found superfluous in a monetary model of inflation.

The rest of the paper proceeds with estimating this monetary model of inflation within the cointegration and error-correction modeling framework. In a related paper (Hossain, 2005a), a Granger causality test (Granger, 1969; Agenor and Taylor, 1993; Miller and Russek, 1990; Roca, 2000) is conducted to determine the direction of causality between money growth and inflation and also whether devaluation has an independent explanatory power in a generalized model of inflation.


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4. Cointegral Relationship Between Money, Prices and Output There are two basic conditions that need to be fulfilled to establish a causal relationship between money supply growth and inflation. First, there exists a stable money demand function (Friedman, 1956; Judd and Scadding, 1982); and, second, the monetary authorities have control over the money supply, that is, the money stock is an exogenous policy variable. In the literature, the question of stability of the money demand function is considered an empirical issue. There is also consensus that the monetary authorities can maintain an effective control over the monetary base under a floating exchange rate system.

Hossain (2005b) suggests that the narrow money demand function in Indonesia has remained stable since the early 1980s. This satisfies the first requirement for a causal relationship between the narrow money supply growth and inflation in Indonesia. However, the second requirement for the money growth-inflation relationship is not apparently satisfied because Indonesia operated under a fixed/pegged or ‘managed-floating’ exchange rate system since the early 1950s to August 1997 and this made the money stock endogenous for most of the sample period. Nevertheless, the monetary authorities tried to maintain short-to-medium term control over the money stock through policy measures, such as credit controls, trade restrictions, and sterilization of capital flows. Also, importantly, Indonesia has a large non-tradable goods sector, comprising about 40 percent of CPI (Ramakrishnan and Vamvakidis, 2002) where the prices of non-tradable goods remain responsive to domestic monetary conditions. Therefore, whether there existed a stable relationship between money, output and prices in Indonesia can be considered an empirical issue.

Given that there exists a stable demand-for-money function in Indonesia and that the monetary authorities have maintained some control over the money stock through policy measures and/or trade restrictions, it is hypothesized that there existed a cointegral relationship between the stock of the nominal money (narrow M1 or broad M2), the consumer price index (CPI) and real permanent


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income/output (yp). Although the unit root test results are somewhat conflicting and inconclusive, they broadly suggest that the above variables have a unit root and are eligible to form a cointegral relationship.10

The presence of a cointegral relationship can be examined within the cointegration-error correction modeling framework by estimating a regression equation of CPI as a dependent variable on real permanent income/output and the nominal money stock, and any mis-specification bias that may emerge in the cointegration regression as a result of omitted dynamics being forced into the error term can be removed by adding the first-difference terms of the explanatory variables, with or without lags.

For the present purposes, the Engle -Granger two-step test is conducted. The establishment of a cointegral relationship among money, output and prices is the first step that allows testing for a Granger-causality between money supply growth and inflation within the error-correction modeling framework. The test for cointegration among variables in the cointegrating set (ln CPI, ln M1 or ln M2, ln yp) is essentially a test for a unit root in the residuals of the cointegrating regression. When the non-stationary variables form a cointegral relationship, the residuals should be stationary. This is commonly tested by the Augmented Dickey-Fuller (ADF) test. One additional test for cointegration is the Cointegrating Regression Durbin-Watson (CRDW) statistic, proposed by Sargan and Bhargava (1983).

Table 2 reports the cointegration test results, where R2 is the adjusted coefficient of determination and the sample period is adjusted for lagged terms. The unit root test results for the residuals of the cointegration regression suggest that there exists a cointegral relationship between money, output and prices. Note that in the Engle-Granger cointegration regression, even though the OLS parameter estimates are super-consistent, the same is not true for the estimated standard errors of the regression. Thus it is not possible to test for significance of individual coefficients in the cointegrating equation. The variables that entered in the above defined cointegral


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relationship have been made on both theoretical and statistical grounds. In the estimated equations, the first-difference terms are unimportant and are included only to lower the finite sample bias in estimates of coefficients of variables in the level form. Table 2. Cointegral Relationship Between Money, Output and Prices With Narrow Money Sample: 1952/53-2002 ln CPIt = 16.25 + 0.86 ln M1t - 1.23 ln yp

t Sample: 1952-53 Estimator: OLS R2 = 0.99 CRDW = 0.64 ADF(1) = -2.82. ln CPIt = 12.43 + 0.83 ln M1t - 0.89 ln yp

t + 0.75 ∆ln M1t - 1.27 ∆ln yt Sample: 1953-02 Estimator: OLS R2 = 0.99 CRDW= 1.56 ADF(1) = -4.87. The Soekarno Regime Sample: 1952/53-1965 ln CPIt = 36.74 + 1.36 ln M1t - 3.28 ln yp

t Sample: 1952-65 Estimator: OLS R2 = 0.99 CRDW= 1.48 ADF(1) = -2.92. ln CPIt = 7.66 + 0.94 ln M1t - 0.52 ln yp

t + 1.62 ∆ln M1t + 2.36 ∆ln yt Sample: 1953-02 Estimator: OLS R2 = 0.99 CRDW= 1.73 ADF(1) = -2.91. The Soeharto Regime and Thereafter Sample: 1966-2002 ln CPIt = 9.44 + 0.67 ln M1t - 0.42 ln yp


t + 0.13 ∆ln M1t - 0.82 ∆ln yt Sample: 1966-02 Estimator: OLS R2 = 0.99 CRDW = 1.16 ADF(1) = -4.13. Sample: 1970-2002 ln CPIt = 11.82 + 0.79 ln M1t - 0.77 ln yp

t Sample: 1970-2002 Estimator: OLS R2 = 0.99 CRDW = 0.98 ADF(1) = -4.19.


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ln CPIt = 10.92 + 0.74 ln M1t - 0.63 ln ypt - 0.06 ∆ln M1t - 1.10 ∆ln yt

Sample: 1970-02 Estimator: OLS R2 = 0.99 CRDW = 1.19 ADF(1) = -4.24. Sample: 1983-2002 ln CPIt = 11.59 + 0.82 ln M1t - 0.81 ln yp

t Sample 1983-03 Estimator: OLS R2 = 0.99 CRDW = 1.45 ADF(1) = -3.90. ln CPIt = 10.71 + 0.78 ln M1t - 0.67 ln yp

t - 0.28 ∆ln M1t - 1.06 ∆ln yt Sample: 1983-02 Estimator: OLS R2 = 0.99 CRDW = 1.89 ADF(1) = -4.42. With Broad Money Sample: 1960/61-2002 ln CPIt = 21.12 + 0.79 ln M2t - 1.60 ln yp

t Sample: 1960-02 Estimator: OLS R2 = 0.99 CRDW=0.95 ADF(1) = -4.17. ln CPIt = 18.27 + 0.76 ln M2t - 1.32 ln yp

t + 0.36 ∆ln M2t - 0.61 ∆ln yp

t Sample 1961-02 Estimator: OLS R2 =0.99 CRDW=1.67 ADF(1) = 4.87 The Soeharto Regime and Thereafter Sample: 1966-2002 ln CPIt = 16.80 + 0.70 ln M2t - 1.12 ln yp


t - 0.06 ∆ln M2t - 0.29 ∆ln ypt

Sample: 1966-02 Estimator: OLS R2 =0.99 CRDW = 0.69 ADF(1) = -2.61. Sample: 1970-2002 ln CPIt = 16.91 + 0.71 ln M2t - 1.15 ln yp


t - 0.81 ∆ln M2t - 1.01 ∆ln ypt

Estimator: OLS R2 =0.99 CRDW = 0.67 ADF(1) = -3.58.


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Sample: 1983-2002 ln CPIt = 20.75 + 0.77 ln M2t - 1.53 ln yp


t - 0.76 ∆ln M2t - 1.00 ∆ln ypt

Sample: 1983-2002 Estimator: OLS R2 = 0.99 CRDW=0.88 DF = -2.00, ADF(1) = -3.51. An Error-Correction Model of Inflation: Having established the cointegral relationship, it is possible to specify and estimate an error-correction model of inflation. For the present purpose, an error-correction model of inflation of the following general form is specified for estimation:

∆ln CPIt = α0 + α1 ECt-1 + ∑αi Zt-j (i = 2,3,…;j = 0,1,2…) + ut

where ECt-1 is the one-period lagged residual of the cointegrating regression of ln CPI on ln yp, ln M1 or ln M2 and the difference terms of these variables, Z is a vector of stationary variables that are thought to explain the behavior of inflation, such as ∑∆lnCPIt-j-1, ∑∆lnM1t-j or ∑∆ln M2t-j and ∑∆ln yp

t-j and ut is a randomly distributed error term. In the present case, even though the nominal exchange rate does not enter into the long-term price-level relationship, the rate of devaluation can be included in the error correction model with the contention that it may have a short-term effect on inflation. Given that the error-correction model contains only stationary variables, the usual stationary regression theory applies. In this specification, the error-correction term plays the crucial role. The coefficient of one-period lagged error-correction term measures the speed of adjustment to the cointegration relationship if the actual relationship deviates from the long-term relationship due to disturbances or shocks (Engle and Granger, 1987). Unlike the estimation of a cointegral regression, the estimation of an error-correction model is, however, untidy. Beginning with a generalized form, a preferred equation is chosen through experimentation


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following, say, a general-to-specific modeling strategy that uses a range of diagnostic tests for model selection. The diagnostic tests normally include the Lagrange multiplier test for the ith order autocorrelation in the residuals and the Ramsey RESET Lagrange multiplier test for any incorrect functional form. When the error correction model fails some diagnostic tests, it may indicate a problem with specification of the model. The error-correction model may then be respecified until the diagnostic tests indicate that the model is theoretically consistent and statistically adequate. Sometimes theoretical considerations may be given precedence over minor statistical inadequacies. Table 3 reports the estimated error-correction models of inflation for several sample periods that fitted the data best. These models are selected after some experimentation with the general form of the specification. As expected, the coefficient of the error-correction term with one-period lag bears a negative sign. This coefficient remains significant irrespective of whichever combination of variables is used in the regression model. The explanatory power of the model is high for the sample period 1971-2002. The model, however, suffers from some statistical problems when it is estimated with data for the 1970s that experienced economic shocks and uncertainties. The model estimated for the shorter sample period 1983-2002, that covers the period of financial reforms, is found superior in statistical sense, except that the explanatory power of the model is somewhat low. Unlike the estimated models with data beginning from the 1950s, 1960s or 1970s, the models estimated with data from the early 1980s do not suffer from any functional form mis-specification, serial correlation and heteroskedasticity.11


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Table 3. The Error-Correction Model of Inflation (∆ln CPI) With Narrow Money Sample: 1953-1965 ∆ln CPIt = -0.18 + 1.57 ∆ ln M1t - 0.56 ECt-1

(t-ratio) (2.09) (9.50) (2.14) Estimator: OLS R2 = 0.88 DW = 1.83 Additional diagnostic tests: A: Serial Correlation: F(1,9) = 0.21; B: Functional Form: F(1,9) = 0.26; C: Normality: χ2

(2) = 0.74; D: Heteroskedasticity: F(1,11) = 0.04. Sample: 1967-2002 ∆ln CPIt = 0.02 + 0.79 ∆ ln M1t -1.36 ∆ln yp

t - 0.53 ECt-1

(t-ratio) (0.71) (11.16) (3.71) (3.77) Estimator: OLS R2 = 0.79 DW = 2.16 Additional diagnostic tests: A: Serial Correlation: F(1,31) = 1.49; B: Functional Form: F(1,31) = 0.10; C: Normality: χ2

(2) = 61.05; D: Heteroskedasticity: F(1,34) = 5.94 Sample: 1971-2002 ∆ln CPIt = -0.07 + 0.65 ∆ln CPIt-1 + 0.40 ∆ ln M1t - 0.61 ECt-1 + 0.26 ∆ ln ERt (t-ratio) (2.82) (5.69) (3.99) (4.63) (7.01) Estimator: OLS R2 = 0.74 Dh = 1.33 Additional diagnostic tests: A: Serial Correlation: F(1,26) = 0.63; B: Functional Form: F(1,26) = 19.31; C: Normality: χ2

(2) = 0.57; D: Heteroskedasticity: F(1,30) = 2.98 Sample: 1984-2002 ∆ln CPIt = 0.05 + 0.51 ∆ln CPIt-1 - 0.64 ∆ ln yp

t - 0.50 ECt-1 + 0.21 ∆ ln ERt (t-ratio) (1.24) (3.11) (1.54) (3.64) (3.15) Estimator: OLS R2 = 0.92 Dh = 1.33 Additional diagnostic tests: A: Serial Correlation: F(1,13) = 1.01; B: Functional Form: F(1,13) = 19.48; C: Normality: χ2

(2) = 1.43; D: Heteroskedasticity: F(1,17) = 0.77 Sample: 1953-2002 ∆ln CPIt = 0.08 - 2.24 ∆ln yp

t + 0.78 ∆ ln M1t - 0.30 ECt-1 (t-ratio) (0.92) (2.02) (3.82) (1.53) Estimator: OLS R2 = 0.34 DW = 2.07 Additional diagnostic tests: A: Serial Correlation:F(1,45) = 0.15; B: Functional Form: F(1,45) = 12.00; C: Normality: χ2

(2) = 153.63; D: Heteroskedasticity: F(1,48) = 61.99 With Broad Money Sample: 1961-2002


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∆ln CPIt = 0.05 - 2.76 ∆ln ypt + 0.88 ∆ ln M2t - 0.67 ECt-1

(t-ratio) (0.53) (2.61) (6.25) (4.28) Estimator: OLS R2 = 0.54 DW = 2.03 Additional diagnostic tests: A: Serial Correlation: F(1,37) = 0.06; B: Functional Form: F(1,37) = 0.99; C: Normality: χ2

(2) = 254.09; D: Heteroskedasticity: F(1,40) = 9.42 Sample: 1971-2002 ∆ln CPIt = -0.04 + 0.48 ∆ln CPIt-1 + 0.30 ∆ ln M2t - 0.22 ECt-1 + 0.25 ∆ ln ERt (t-ratio) (1.19) (3.91) (2.31) (2.34) (5.37) Estimator: OLS R2 = 0.65 Dh = 1.91 Additional diagnostic tests: A: Serial Correlation: F(1,26) = 0.67; B:Functional Form: F(1,26) = 5.71; C:Normality: χ2

(2) = 0.19; D: Heteroskedasticity: F(1,30) = 0.38 Sample: 1984-2002 ∆ln CPIt = 0.13 + 0.17 ∆ln M2t - 0.17 ECt-1 + 0.05 ∆ ln ERt -1.51 ∆ln yp

t (t-ratio) (3.82) (1.36) (1.35) (1.26) (5.55) Estimator: OLS R2 = 0.86 DW = 1.77 Additional diagnostic tests: A: Serial Correlation: F(1,13) = 0.02; B:Functional Form: F(1,13) = 13.53; C:Normality: χ2

(2) = 0.69; D: Heteroskedasticity: F(1,17) = 0.32 5. Summary and Conclusion This paper has investigated the inflationary process in Indonesia with annual data for the period 1952-2002 within the cointegration-and error-correction modeling framework. The empirical analysis has been made for sub-samples 1952-1965 and 1966/1970-2002 that broadly represent two different political and economic regimes. The period 1966-1969 is considered a transition phase from Soekarno’s ‘old order’ regime to Soeharto’s ‘new order’ regime when both stabilization and structural reform measures were undertaken after a period of ‘hyperinflation’ in 1965 that brought the real economy of Indonesia to a halt. Since the early 1970s Indonesia has experienced moderately high and fluctuating inflation, including a major inflationary shock during the peak of the currency crisis in 1998. However, despite a sustained moderately high and fluctuating inflation, the post-Soekarno era represents the phase of Indonesia’s remarkable economic growth and structural transformation.


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The empirical results suggest that the consumer price index (CPI), the stock of narrow (M1) or broad money (M2) and real permanent income form a weakly cointegral relationship for the complete sample period. This relationship remains broadly stable for several sub-samples, especially when the model is estimated with a narrow definition of money. The dynamic relationship between money, output, prices, and the exchange rate is investigated within a general-to-specific error-correction modeling framework. The presence of a significant error-correction term implies that given economic growth, there existed a long-run causal relationship between money supply growth and inflation.

Notes 1. Mackie (1967:p.59) has stated this view succinctly:

“Prices have risen in very close conjunction with the increase in volume of money since 1950, and the latter figure has been influenced predominantly by budget deficits, with credit expansion occasionally playing a small part. That, at its simplest, is the problem of inflation in Indonesia. Put differently, Indonesia’s postwar inflation may be seen as a problem of excess demand “too much money chasing too few goods” since the increase of cash-purchasing power has not stimulated a proportionate increase in the supply of goods and services.”

2. Indonesia abandoned the exchange rate peg in July 1997. The Rupiah depreciated by nearly 85 percent during June 1997 to June 1998. Moreover, Bank Indonesia (central bank of Indonesia) lost control over the money supply when it, acting as a lender-of-last-resort, provided massive liquidity support to banks, which was not sterilized. Bank Indonesia regained monetary control in mid-1998, when it adopted the IMF stabilization program that centered on tight control over the growth of the monetary base. Consequently, the Rupiah recovered by about 40 percent in the last quarter of 1998 and the monthly inflation rate slowed down sharply, resulting in the annual inflation rate falling back to a single digit level by the second half of 1999 (IMF, 2002).

3. In addition to determining the main sources of inflation, Mackie (1967:p.1) raised some theoretical issues on the dynamics of inflation in Indonesia in the 1950s and early 1960s:


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“… the problems of analysing Indonesia’s inflation are fascinating on theoretical grounds. Among the obvious puzzles is the paradox of Indonesia’s apparent “resilience” from inflation. How is it that overall production has remained so little affected by the strains and disruptions of the financial system? Why had there not been a more rapid acceleration in the velocity of circulation of money before 1965? Prices did not spiral exponentially (as in the later stages of China’s inflation, or the classic European inflations in Germany and Hungary), despite the constant depreciation of the currency: evidently people were not rushing to purchase goods so as to get rid of Rupiah. In fact speculation against the Rupiah seems to have been only an intermittent factor pushing up prices, rather than a major dynamic in the inflationary process.”

4. To conserve space, the detailed unit root test results are not reported in the paper but would be available from the author upon request. 5. This is a restrictive assumption. In general, openness and economic growth have different effects on the share of tradables in total expenditure. For example, the share of tradables in total expenditure rises as the economy opens, provided that opening lowers trade restrictions and transactions costs, both implicit and explicit. However, a rise in income per capita, with or without an increase in openness, increases the relative demand for nontradables and thereby causes a structural transformation of the economy in favor of nontradables. Therefore, analytically, φ can be expressed as a function of the real exchange rate, which, in turn, depends on a set of real and nominal factors, including economic growth, capital flows, the terms of trade, and the stance of monetary and fiscal policies (Edwards, 1989; Hossain, 2000). 6. For simplicity, the rate of expected inflation or the nominal interest rate (a proxy for the opportunity cost of holding money) is assumed constant. 7. In the simplified equation (8), the growth of real money is expressed as the differential between the growth of the money stock and the rate of inflation. 8. If the exchange rate remains fixed under a fixed exchange rate system or does not change much under a pegged exchange rate arrangement, the coefficient of ln (ERt/ERt-1) would not be different from zero. Imposing a zero restriction, equation (8) can then be written in the following form: ln (Pt/Pt-1) = - γβ0 + γ ∆ln Mt-1 - γ ∆ln Pt-1 - γβ1 ∆ln yt + ut. (8')


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This is a variant of the conventional monetary model of inflation, such as Harberger’s (1963) model of inflation for Chile. This restricted model can be derived from the flow equilibrium condition of the money market, such that ∆ln (M/P) = ∆ln md(y).

9. Although the Indonesian authorities did not explicitly follow the real exchange rate targeting approach to exchange rate policy, such an approach was somewhat revealed by or could be discerned from the movement of the real exchange rate, especially since the early 1980s. However, this proposition is essentially a working hypothesis as part of establishing the point that external balance, rather than price stability, might have the main objective of the government’s monetary and exchange rate policy. 10. This finding is based on the ADF, DF-GLS and the Phillips-Perron tests. Under these tests, the null-hypothesis is that the series under consideration is non-stationary. However, the KPSS tests, where the null hypothesis is that the series is stationary, suggest that the series under consideration are trend stationary. Such conflicting results could partly be due to the small sample size. 11. It appears that the heteroskedasticity problem in the estimated equations with data for the 1950s to 1970s is due to exclusion of inflation volatility (Engle, 1983). Given the limited scope of this paper, this issue is not addressed here. Appendix. The Data Sources, Definitions of Variables and the Time Series Properties Data Sources and Compilation

Variables Units Compilation/Estimation Based on: Narrow Money (M1) Broad Money (M2) Consumer Price Index (CPI) GDP at Constant Prices (RGDP) Exchange Rate of Rupiah against the US dollar (NER)

Millions of Rupiah Millions of Rupiah 1995=100 Millions of Rupiah Rp/$

Arndt (1971); IMF, IFS Yearbook IMF, IFS Yearbook Arndt (1971); IMF, IFS Yearbook Thomas and Drysdale (1964); IMF, IFS Yearbook; Bank Indonesia Annual Report IMF, IFS Yearbook.


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Definitions of Variables ln M1 = natural log of stock of narrow money M1, Millions of Rupiah. For estimation purposes, the monetary aggregate is defined as the unweighted average of current and last year’s end of period figures. ln M2 = natural log of stock of narrow money plus quasi-money M2, Millions of Rupiah. For estimation purposes, the monetary aggregate is defined as the unweighted average of current and last year’s end of period figures. ln yp

=natural log of real permanent output/income (RGDPp), Millions of Rupiah at 1995 prices, estimated as yp=0.9•RGDP+ 0.1•RGDP(-1) where RGDP is GDP at constant prices. The rationale behind generating this series is given below. ln CPI = natural log of the consumer price index CPI, 1995 = 100. ln NER =natural log of the nominal exchange rate of Indonesian Rupiah against the US dollar. Estimation of Real Permanent Income The following approach has been used to construct a series for real permanent income. According to Friedman (1959:p.337), permanent income (or what is sometimes defined as expected income) can be defined as a weighted average of past incomes, where the weights decline exponentially. Friedman followed the adaptive expectations model to analyze the process by which economic agents form their expectations about expected income. He suggests that the value of expected income is revised over time at a rate that is proportional to the difference between expected and actual income. Assume that yp is permanent income and y is actual income, then following the adaptive expectations hypothesis: yp

t – ypt-1 = θ (yt- yp

t-1) (1) where θ is the coefficient of adjustment, whose value is expected to lie between zero and unity. Equation (1) can be written as: yp

t = θ yt + (1-θ) ypt-1 (2)


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Equation (2) can be converted into a distributed lag model by successive substitutions, such that yp

t = θ yt + θ (1-θ) yt-1 + θ(1-θ)2 yt-2 + (3) In equation (3), θ is unknown. However, when θ is known, yp can be estimated. Since the value of θ lies between zero and unity, seven permanent income series have been constructed by setting θ = 1.00, 0.9, 0.8, 0.6, 0.5 and 0.4. The ln yp series that gave the highest correlation coefficient with the log of real money stock (ln M/P) has been chosen for estimation purposes. With some experimentation with both narrow and broad money balances, θ = 0.9 has been found to give a yp series that performs well on a consistent basis. So the yp series has been estimated by: yp

t = 0.9 yt + 0.1 yt-1 (4) where y is the actual GDP at constant prices. The Time Series Properties of Variables: The variables included for unit root testing are the narrow and broad money stocks, real permanent income, the consumer price index and the nominal exchange rate of Rupiah against the US dollar. Four tests for the unit roots the Augmented Dickey-Fuller (ADF), the GLS-detrended Dickey-Fuller (DF-GLS), the Phillips-Perron (PP), and the Kwiatkowski, Phillips, Schmidt and Shin (KPSS), were conducted. Note that the first three tests treat the series under consideration non-stationary as a null hypothesis, while the last test treats the series stationary as a null hypothesis. The test results were somewhat conflicting. While the ADF, the DF-GLS and PP tests suggest that the series under tests have a unit root, the KPSS tests suggest that they are trend-stationary. Such conflicting results could partly be due to the small sample size. References Agenor, Pierre-Richard and Mark P. Taylor (1993). ‘The Causality Between Official and Parallel Exchange Rates in Developing Countries’. Applied Financial Economics 3, 255-266.


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Aghevli, Bijan B. and Mohsin S. Khan (1977). “Inflationary Finance and the Dynamics of Inflation: Indonesia 1951-72”. American Economic Review 67(3), 390-403 Arndt, Heinz W. (1971). “Banking in Hyperinflation and Stabilization”. In Glassburner, Bruce (ed.) The Economy of Indonesia: Selected Readings. Ithaca: Cornell University Press. Bank Indonesia (various years). Annual Report. Jakarta: Bank Indonesia. Corden, W. Max (1991). “Exchange Rate Policy in Developing Countries,” in Trade Theory and Economic Reform: North, South and East, ed. by de Melo, Jaime and Andre Sapir, Oxford: Basil Blackwell. Corden, W. Max (1993). “Exchange Rate Policies for Developing Countries,” Economic Journal 103 (January), 198–207. Corden, W. Max and J.A.C. Mackie (1962). ‘The Development of the Indonesian Exchange rate System’. Malayan Economic Review 7(April), 37-60. Dornbusch, Rudiger (1988) Exchange Rates and Inflation. Cambridge, Massachusetts: MIT Press. Edwards, Sebastian (1989) Real Exchange Rates, Devaluation, and Adjustment: Exchange Rate Policy in Developing Countries. Cambridge, Massachusetts: MIT Press. Engle, Robert F. (1983). ‘Estimates of the Variance of U.S. Inflation Based Upon the ARCH Model’. Journal of Money, Credit and Banking 15(3), 286-301. Engle, Robert and Clive Granger (1987). ‘Cointegration and Error Correction: Representation, Estimation and Testing’, Econometrica, 55, 251-276. Friedman, Milton (1956). ‘The Quantity Theory of Money: A Restatement’, in Studies in the Quantity Theory of Money. Chicago: University of Chicago Press. Friedman, M. (1959). The Demand for Money: Some Theoretical and Empirical results. Journal of Political Economy 67, 327-351. Granger, Clive (1969) “Investigating Causal Relations by Econometric Models and Cross-Spectral Methods,” Econometrica, 37 (January), 424–438. Harberger, Arnold (1963). “The Dynamics of Inflation in Chile,” in Measurement in Economics: Studies in Mathematical Economics in


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Memory of Yehuda Grunfeld, ed. by Christ, Carl Stanford, California: Stanford University Press. Hicks, George L. (1966). “The Indonesian Inflation”. Philippine Economic Journal 6(2), 210-224. Hill, Hal (1996). The Indonesian Economy Since 1966. Cambridge: Cambridge University Press. Hossain, Akhtar (2000). Exchange Rates, Capital Flows and International Trade. Dhaka: The University Press Limited. Hossain, Akhtar (2005b). ‘The Granger-Causality Between Inflation, Money Growth, Currency Devaluation and Economic Growth in Indonesia: 1954-2002’. International Journal of Applied Econometrics and Quantitative Studies, Vol.2-3. Hossain, Akhtar (2005a). The Money Demand Behavior in Indonesia: 1952-2002. School of Policy. University of Newcastle, Australia. (Processed). Hossain, Akhtar and A. Chowdhury (1996), Monetary and Financial Policies in Developing Countries: Growth and Stabilisation, London: Routledge. International Monetary Fund (IMF) (various years). International Financial Statistics Yearbook . Washington, DC.: IMF. International Monetary Fund (2002). ‘Indonesia: Selected Issues.’ IMF Country Report No.02/152, Section II: 14-25, July. http://www.imf.org/country information. Judd, J.P. and J.L. Scadding (1982). ‘The Search of a Stable Money Demand Function: A Survey of the Post-1973 Literature’, Journal of Economic Literature, 20, 993-1023. Mackie, J.A.C. (1967). Problems of the Indonesian Inflation. Monograph Series. Department of Asian studies, Cornell University, Ithaca, New York. McLeod, Ross H. (2004). ‘Toward Improved Monetary Policy in Indonesia’. Indonesia Project, Economics Division, Australian National University. (Processed.) Miller, S. M. and Russek, F.S. (1990). ‘Co-integration and Error-Correction Models: The Temporal Causality between Government Taxes and Spending’. Southern Economic Journal 57, 221-29. Prachowny, Martin (1975), Small Open Economies, Lexington, Massachusetts: Lexington Books.


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Ramakrishnan, Uma and Athanasios Vamvakidis (2002). ‘Forecasting Inflation in Indonesia’ IMF Working Paper 02/111. Washington, DC: IMF. Roca, Eduardo (2000). Price Independence Among Equity Markets in the Asia-Pacific Region: Focus on Australia and ASEAN, Aldershot, England: Ashgate. Sachs, Jeffrey, and Felipe Larrain (1993). Macroeconomics in the Global Economy, New York: Harvester Wheatsheaf. Sargan, J.D. and A. Bhargava (1983). ‘Testing Residuals from Least Squares Regression for Being Generated by the Gaussian Random Walk’. Econometrica 51, 153-74. Sundrum, R.M. (1973). “Money Supply and Prices: A Reinterpretation”. Bulletin of Indonesian Economic Studies 9(3). Nov. Thomas, K.D. and P. Drysdale (1964). “Indonesian Inflation 1951-60”. Economic Record December, 535-553. ____________________________ Journal published by the Euro-American Association of Economic Development. http://www.usc.es/economet/eaa.htm

Documents

Applied Econometrics and International … into three periods: 1950-1965 (the Soekarno-era), 1966-1997 (the Soeharto-era) and 1998-2002 (the post-currency crisis). A visual inspection