Impact of Reserves Accumulation on Inflation, Exports, Imports, and Employment: The Philippine Case*

Nikkin L. Beronilla National Anti-Poverty Commission

ABSTRACT

This paper starts by tracing the theoretical connection of accumulation of reserves to ex-change rate intervention down to inflation, exports, imports and employment. The theoretical results are used to build a system of equations for the Philippine case. The equations are estimated using Seemingly Unrelated Regression estimator in conjunction with rolling window technique to generate time series estimates and to ascertain the persistence of theoretical connections that are initially uncovered. The data used is quarterly spanning 1997 to 2013 consisting of 68 data points, and the rolling window chosen is 12 years or 48 data points.

The key findings from the rolling estimates are: 1) money supply as a function of reserves is supported theoretically and empirically; 2) inflation is a random walk process and not affected by changes in reserves; 3) the theoretical relationships that increase in exports encourages employment but increase in imports discourages employment are supported empirically in all forecast periods; and 4) the empirical result that accumulation of reserves leads to increase in both exports and imports is opposite to the theoretical result as they should have moved in opposite directions as reserve accumulation depreciates the exchange rate making exports cheaper and imports dearer. This counterintuitive result could be due to high import content of electronics, the main export of the Philippines.

This paper ends by using the rolling estimates to simulate the impact of $5 billion additional reserves in a quarter, which produces two key results. First, the impact of reserve accumulation on exports is always greater than on imports, meaning its net impact on Gross Domestic Product (GDP) is positive. Second, the impact of reserves on employment is negligible as it is just a tenth of a percentage point and either positive or negative depending on the forecast period. This is understandable as impact of reserves on employment works first through exports and imports which have opposing effect on employment. With the two key results, the main contribution of this paper is in helping untangle the puzzle of the jobless growth in the Philippines. As accumulation of reserves increases GDP growth but neutral on job growth, the policy that could solve the jobless growth is the policy that would decouple the growth of exports and imports.

JEL classification: C32, F31, F47

Keywords: Seemingly Unrelated Regression, accumulation of reserves, employment

* The author is grateful to Undersecretary Jude Esguerra and Raymundo Addun of the National Anti-Poverty Com-mission for their helpful comments and suggestions. The views expressed herein are from the author and do not represent the official views of the National Anti-Poverty Commission. For reproducibility, the R script and the data set are available upon request.

Contact information: email: nlberonilla@gmail.com, cellphone number: 0917-312-0790

1. IntroductionAsian economies have been accumulating international reserves since the aftermath of the 1997

Asian Crisis. For example, the Philippines has begun increasing gross international reserves (GIR) in second quarter of 1998 after a dip in a previous quarter, but the noticeable rise could be clearly observed in 2005 (see figure 1, below). The increase is concentrated on foreign investments which consist mostly of foreign currency bonds (orange band). Although there is a noticeable rise in gold, its share is miniscule compared to foreign investment (green band).

Initially, the move to accumulate reserves was seen as an insurance of future crisis, but was later viewed as a way prevent currency appreciation and maintain competitiveness in the tradeable sector. In recent years, the accumulation of reserves was even criticized by the IMF as excessive. Some authors like Levy Yeyati [2006] and Rodrik [2006]) have even shown that this path is costly. The cost, however, steams from the assumption that accumulation of international reserves is implemented through issuance of foreign debt. Others authors like Fukuda and Kon [2009] have extended the assumption in tracing the impact of increase of foreign reserves on economic growth.

The analysis is valid, of course, for countries that are accumulating foreign reserves through foreign debt issuance. However, if the motivation in accumulation of reserves in recent years is to prevent appreciation, foreign debt issuance is not the best starting point of analysis for two reasons. First, the best route to prevent appreciation is to intervene in the exchange market and not to issue

foreign debt. According to Basu [2009], in floating exchange rate regime where the banks and other foreign exchange dealers are free to announce the exchange rate, the central bank cannot influence by diktat. It must enter in the foreign exchange market to buy dollars at higher exchange rate to prevent appreciation (Basu [2009]) or enter into the non-deliverable forward contracts (Magtulis [2013]). Basu [2009] conceded that the actual process of intervention is a state secret, but this usually involves a public sector bank buying in the foreign exchange market in behalf of the central bank.

Exchange rate intervention could be the route taken by the Philippines as it was able to accumulate reserves without substantially increasing its foreign debt. During the period that the country accumulated reserves (see figure 2, left hand side of graph, in purple text), it was not the foreign debt that substantially gone up, but the domestic debt. Way back in 2000, the amount of government debt was roughly split into foreign and domestic equally. On the other hand, if viewed as a share of gross domestic product (GDP), foreign debt was decreasing starting 2004 (see figure 2, see right hand side of the graph), one year before the steep rise in reserves (recall figure 1).

Figure 1. Ph Gross International Reserves (GIR)

0

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IR in

Mn

$

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Foreign Investments

SDRs

Gold

Reserve in Fund

Source: Bangko Sentral ng Pilipinas

Figure 1. Ph Gross International Reserves (GIR)

Figure 2. Composition of Goverment Debt

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t in

% G

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Domestic Debt

%Foreign/GDP

%Domestic/GDP

Source: Bangko Sentral ng Pilipinas and Bureau of Treasury

Figure 2. Composition of Government Debt

Another evidence why foreign exchange intervention is the route taken by Philippines is that accumulation of reserves coincides with the appreciation of the domestic currency. It would be noted that the period of accumulation of reserves between 2008 and 2012, the domestic currency is appreciating (see black arrow in figure 3). It would be safe to argue that the rise in gross internal reserves during this period is due to an effort to slowdown the appreciation of the local currency. In earlier period between 2004 and 2007, the central bank did not heavily intervene in the foreign exchange market as the appreciation of the domestic currency is not associated with rise in gross international reserves.

Aside from intervening the foreign exchange market, the second reason why foreign debt issuance is not the best starting point of analysis is that if the goal is to prevent appreciation, foreign debt issuance has little impact since it is done outside the foreign exchange market. Actually, it is an appropriate option if the goal is not to disturb the exchange rate market. This is relevant especially if the currency is under the risk of rapid devaluation partly due to miniscule international reserves. This was the situation in the Philippines before the 1997 Asian Crisis, when in the 1990s, the gross international reserves was less than $10 billion, and even a single transaction of $500,000 dollars between private banks at an exchange rate of around ₱22 per dollar triggered market volatility and increased the risk of devaluation (Castillo B [1990]). Therefore, the most appropriate option to accumulate reserves before the 1997 Asian Crisis was through foreign debt issuance for the period.

From the two reasons discussed, the era of accumulating reserves through foreign debt issuance had already passed, and so with the increasing cost of interest payment. After 1997 Asian Crisis, the most appropriate starting point of analysis is foreign exchange market intervention down to its link to money supply, inflation, exports, imports and employment. For example, reserve accumulation and money supply are closely linked (Krugman and Obstfeld [2000]), unless the central bank is sterilizing. For the Philippines it is safe to argue that the central bank is not sterilizing, since the gross international reserves (GIR) and

money supply as represented by M2 are highly correlated at close to 100% (see figure 4).

The link between GIR and M2 could be sketched following Mishkin’s [2004] argument using double entry accounting. The central bank buys dollars at the foreign exchange market which are then used to buy foreign bonds; hence, observers outside the central bank see a steep rise in foreign investment, a component of the GIR (recall figure 1, see orange band). In buying the dollars, the central bank issues a check in pesos to the seller, who will either deposit it in the bank or in-cash it in domestic currency. In both options, there is an increase in monetary base which is a component of money supply. It is worth noting that the rise in money supply in figure 4 (as represented by M2) is roughly twice as high than GIR in most of the time (see scale of M2 in left hand side and GIR on right hand side). The doubling in increase is due to the money multiplier which is always greater than 1 and is a function of currency ratio, excess reserve ratio and required reserve ratio (Mishkin [2004]).

Figure 3. Gross International Reserves vs Peso Exchange Rate

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GIR

in M

n $

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/Dol

lar

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Source: Bangko Sentral ng Pilipinas

Figure 3. Gross International Reserves vs Peso Exchange Rate

Figure 4. M2 and GIR Compared Quarterly

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Php)Correlation = 97%

Source: Bangko Sentral ng Pilipinas

GIR (RS)

M2 (LS)

Figure 4. M2 and GIR Compared

Although the high correlation is an evidence to support the close link between GIR and M2, it also poses problem in statistical analysis especially in estimating the effect on variables associated to exchange rate intervention like inflation, exports, imports and employment. There is a higher chance that the GIR and M2 are multicollinear, making it difficult to disentangle the effects of the individual explanatory variable. There are many solutions to deal with this problem like principal component and ridge regression, but the interpretable solution is to drop one of the variables (Maddala [2000]). In other words, to estimate the effect on inflation, only one of either GIR or M2 should appear as explanatory variable.

To estimate the links among GIR, money supply, inflation, exports, imports and employment, there would be separate independent equations to describe their relationships. Usually, these independent equations can be estimated using Ordinary Least Squares (OLS). However, if the errors are correlated, there is an efficiency gain if the equations are estimated jointly using Seemingly Unrelated Regression (SUR) as was shown by Zellner [1962]. If the errors are uncorrelated across equations, then there is no relation between the equations and the SUR estimator will simply degenerate into an OLS estimator applied for each equation separately.

In most regression exercises, impacts of coefficients are usually estimated in one shot to support the theory. However, coefficient should not be assumed fixed (Lim and Montes [1997]) for it varies over time; and, for some variables, it varies substantially. To see if coefficients vary substantially, say from significantly different from zero to non-significantly different zero, the coefficients can be estimated over time using a simple methodology called the rolling regression. For example, suppose the dataset is fifteen-year series with annual data point, a regression is done within a subset, say a five year window. The window is then rolled to the next period, and the regression is repeated over time until fifteen-year period is exhausted. Rolling regression is a well known technique in the stock market because the relationship of finance variables is constantly changing.

With the issues on reserve accumulation and methodology discussed, this paper aims to contribute three things. First, this paper attempts to analyze the impact of reserves accumulation using market intervention as opposed to the common starting point by other authors that a country accumulates large amount of reserves through foreign debt. Second, this paper uses an innovative methodology called rolling SUR to test if the links of different variables are persistent over time. Third, this paper aims to clarify some issues by testing the theory of linkages of variables empirically using the Philippine data and over a period of time.

The next sections are arranged as follows: Section 2 discusses the mathematical relationships of the variables associated with exchange rate intervention; Section 3 summarizes the mathematical models into a framework, discusses the data available to be used in testing the mathematical relationships empirically, and explains the econometric specification based on the framework, the constraint of available variables and preliminary statistical tests; Section 4 presents the empirical results and simulation on the effect of increase of reserves on other variables; and the last section summarizes the issues and concludes.

2. Tracing the Impact of Exchange Rate InterventionThis section attempts to trace the impact of gross reserves, on money supply, inflation, exports,

imports, GDP growth, and employment. There is no attempt to build a new theoretical model, but instead, this paper attempts to build on top of the works of others mainly from Basu [2009], Krugman and Obstfeld [2000] and Mishkin [2004]. The mathematical models are expounded in four subsections below. The generalization will be the guide in specifying the econometric equations and in interpreting the regression results.

2.1 Exchange Rate Intervention and Money Supply

The starting point of tracing the impact of foreign reserves for the Philippines is the exchange rate market under the following simplifying assumptions. Suppose there is only one foreign currency, the dollar and one domestic currency, the peso. Let the foreign exchange rate be E₱/$ =

amount of peso to be exchange per dollar. Suppose further that there are only two types of buyers of dollars, the banks and small buyers. There are n≥2 banks that are buyers of large foreign exchange and therefore, can affect the market price. The small buyers are price takers and could not affect the market and will not be included in the analysis following Basu [2009]. The individual bank has a dollar demand in peso terms that can be summed to D₱($) the total demand of all banks. On the other end, let S$($) be the supply of dollars in foreign exchange market in dollar terms. In equilibrium, it is the exchange rate, E₱/$, that will adjust so that the total demand for dollars will be equal to the total supply of dollars,

D₱($) = E₱/$ × S$($). (1)

Suppose the central bank will enter the foreign exchange market and buy some dollars, then let its demand for dollars in peso terms be denoted by d(cb)

₱($). Since the central bank is a big buyer, the new total demand of dollars of all banks plus the central bank is now D₱($) + d(cb)

₱($). Given that the supply of dollars is fixed in a particular period, equation 1 will be modified with the new equilibrium,

D₱($) + d(cb)₱($) = E*

₱/$ × S$($); (2)

where E*₱/$ is the new equilibrium exchange rate which is greater than the previous exchange rate,

E*₱/$ > E₱/$. The increase in the new exchange rate, E*

₱/$, denotes depreciation which reflects the entry of the central bank into the market, leading to more peso chasing limited number of dollars.

If the central bank's demand for dollars is executed, the central bank accumulates dollars or foreign exchange1, FE, which can be converted into other forms of foreign assets, FA, like foreign bonds. Foreign exchange and foreign assets are all considered component of gross international reserves, GIR, which is expressed in dollars. For simplicity, there is no transaction cost in converting into different types of GIR, say from FE to FA, so that any form of foreign reserves will be added into additional gross international reserves, ΔGIR, so the following equality holds,

d(cb)₱($) = FE = FA = ΔGIR. (3)

After the dollar purchase, the new gross international reserves, say at time t+1, is a cumulative of the previous GIR, say at time t+0, and the additional reserves, ΔGIR, due to market intervention and can be written as,

GIRt+1 = GIRt+0 + ΔGIR t+1. (4)

At the same time the central bank accumulates dollars, it pays domestic currency in return to the seller who can either keep it in the bank as deposit or in use it to be come part of the currency in circulation. In both scenarios and assuming there is no sterilization, the central bank increases the existing monetary base, MB, by an amount denoted ΔMB, so the new monetary base of a given period, say t+1 is,

MBt+1 = MBt+0 + ΔMB t+1. (5)

Using equation 2, the additional monetary base, ΔMB, is equal to the additional GIR, ΔGIR, if expressed in peso terms, so using the series of notations above, the following equality holds,

ΔMB = E*₱/$ × ΔGIR. (6)

With all the equalities defined under the assumption that there is no sterilization, the next step is to trace the impact of exchange rate intervention on money supply, Ms. The link of money supply and reserve accumulation can be traced in the model mentioned by Mishkin [2004] where money supply is a function of monetary base and formally written as,

Ms = m × MB; (7)

where m is the money multiplier and MB is the monetary base. Using equation 5 and 7 the resulting money supply in time period t+1 is,

1 Dollars and foreign exchange are used interchangeably herein after.

Mst+1 = m × MBt+1. (8)

The multiplier assumed to be equal or greater than one so that the increase in money supply is always equal or bigger than the increase in the monetary base.

Another relationship that can gleaned from the series of equations 5 and 6 above is that since both gross international reserve, GIR, and monetary base, MB, are cumulative, then at the start of the creation of central bank or time, t = 0, the GIR is equal to change in GIR, or GIRt=0 = ΔGIR; same with monetary base, MB, at the beginning MBt=0 = ΔMB t=0. Assuming that the central bank is not sterilizing its dollar purchase equation 6 becomes,

MB = E*₱/$ × GIR. (9)

If the assumption of equation 9 holds, then money supply in equation 7 could be rearranged into

Ms = m × E*₱/$ × GIR. (10)

This relationship is helpful since money supply and GIR are highly correlated and appears to be multicollinear.2 The equation above also tells that both variables should not appear as explanatory variables at the same time, theoretically. Empirically the two variables should not appear as they are multicollinear.

2.2 Money Supply and Inflation

The impact of accumulation of reserves on money supply was shown in equations 8 and 10. The next step is to show the impact money supply to inflation but since this involves changes in prices then the analysis starts aggregate demand for money which is a function of price level and real aggregate demand. Following the notations of Krugman and Obstfeld [2000], let the aggregate demand for money be defined as,

Md= P × AD, (11)

where Md is the aggregate demand for money, P is the price level, AD is the aggregate real demand for money. The equation above can be rearranged to get the aggregate real money demand

Md/P = AD. (12)

In equilibrium in the money market, aggregate demand for money is equal to aggregate supply of money Ms=Md, which can be rewritten using equation 12 as,

Ms/P= AD. (13)

The equations above could be rearranged to show the price level as a function of money supply and aggregate demand,

P = Ms/AD, (14)

which depends on money supply and aggregate demand. In the equation above price level will go up if increase in money supply is not associated with aggregate real demand for money.

In textbook economics it is well known that supply of money is the cause of inflation. With that in mind, the rational expectation's model of inflation is given as,

πe = (Pe – P)/P; (15)

where πe is the expected inflation at time t+1; Pe is the expected price at time t+1 and P is the current price. In rational expectations model, the agents' expectation of inflation is equal to the true inflation since the agent is using the best available information. From equation 14, it is established that price level is proportionally affected by increase in money supply so equation 15 becomes,

πe = ([Ms/AD]e – [Ms/AD])/(Ms/AD). (16)

For the inflation to become positive the expected money supply in the next period is higher than

2 Based on the initial tests of the author using Philippine data.

the current period. Given that the Philippines is classified as country independently floating exchange rate, the best estimate of future money supply is the current money supply plus a random variable. With that line of thinking, inflation due to money supply growth expectation is expected to be zero.

2.3 Exchange Rate Intervention, Exports and Imports

The impact of exchange rate on export and import is easy see to since it has direct effect export price and import price. The entry of central bank in the foreign exchange market will lead to increase in exchange rate or depreciation which will lead to decrease in export price and increase in import price. To see this mathematically and following Maddala [2000], the starting point is a linear demand function as,

q = a – b*p, (17)

where q is the quantity demanded, a is some constant, and -b is the slope and p is the price of an export or an import good. The negative slope reflects the reduction in quantity demanded if there is an increase in price and vice versa.3

With a demand function above, the next step is to show the impact of increase in exchange rate on price of export and import goods. To start, the export good has domestic px

₱ but since it is sold in the foreign market the export price is in dollars and given as,

px$ = px

₱/(E₱/$); (18)

where px$ is the price of export good in dollars while px

₱ is price of export good in domestic price. If the central bank enters into the foreign exchange market then the exchange rate will depreciate E*

₱/$

> E₱/$ causing the new export price in dollars to decrease such that px*$ < px

$, which theoretically increases the demand for exports. This a pass-through effect on the price of export goods which remain to be seen if supported by data. This assumes that the exporter will immediately pass on any increase in changes in exchange rate. The pass through effect will happen if the seller reflects the depreciation in currency into the export prices. In some instances, though, it would take some time for the exporter to change the price and reflect the exchange rate depreciation. Some seller may resist changing the price, thinking that depreciation in exchange is temporary.

For import goods the more important price is the domestic price and mirroring equation 18, the domestic price is given as

pm₱ = pm

$ × E₱/$; (19)

where pm₱ is the price of import good in domestic price while pm

$ is the price of import good in dollar price. If the central bank enters into the foreign exchange market then the exchange rate will depreciate E*

₱/$ > E₱/$ causing the new import price in pesos to increase such that pm*$ > pm

$, which theoretically decreases the demand for imports. With this, changes in exchange rate will immediately be felt by the buyer since the changes happens in the buyers currency or the domestic currency. There is no need for the seller of imports to raise the price to feel the effect. This is pass-through effect of import and will be tested in the data set.

2.4 Exchange Rate Intervention, GDP and Employment

The impact of export and import on GDP is obvious as they are component of GDP in the following model,

Y = C + I + G + (X-M) (20)

where Y is GDP, C is private consumption, I is investment, G is government consumption, X is export and M is import. From equations 17, 18 and 19, export and import could be further specified where X= qm*px

₱ and M= qm*pm₱, respectively.

It is well known that Y is a function of labor, L and capital, K or Y = f(K, L), then it could also be

3 The generalization of the demand function will apply to any downward sloping function.

that employment growth rate is as function economic growth rate, which can be expressed as,

(L1 – L0)/L0 = c + (Y1 – Y0)/Y0 (21)

where L is labor and Y is GDP. Given that in equation 20 GDP is a function of exports and imports, then exports and imports have impact on employment rate. Based on their relation to GDP, exports are increasing to GDP, it is corollary that exports is increasing with employment as most of the production happens domestically. On the other hand, imports are decreasing with GDP hence it is decreasing with employment since production of imports happens abroad.

3. The Framework, Data, Initial Tests and MethodologyFrom the series of equations in the previous section, the linkages of reserves accumulation is

summarized in the diagram below (see figure 5). When the central bank intervenes in the exchange rate market, it accumulates initially by buying dollars which is later converted into other assets which is likely to be foreign assets, reflecting the most dominant component in the gross international reserves. Buying dollars in particular or acquiring international reserves in general,

would pump domestic currency, and without sterilization, there is an equivalent increase in monetary base and ultimately money supply. Increase in money supply has the potential to increase inflation if there is an expectation of increase money supply in the next period.

On the other hand, central bank intervention in the exchange rate market exerts pressure on dollar demand, depreciating the local currency (or increasing the value of foreign exchange rate) which directly reduces export prices and increases import prices. Assuming a downward

sloping demand, this would increase demand for exports abroad and decrease local demand for imports. Since they are components of GDP, movements of exports and imports have impact on GDP. Finally, given that economic output is function of labor and capital, the growth in economy leads to increase in employment.

From the framework above, the ideal scenario is that there is an equivalent variable that represents for every variable in figure 5. However, this is not the case as some variables are non-existent or impractical to obtain like the individual prices of export and import goods. Hence, this paper uses the following variables in the empirical analysis: gross international reserves, M24 money (representing money supply), peso-dollar exchange rate (end of period), exports, imports, inflation, GDP, and employment. These data sets were collected from the Philippine government websites. For example, the GIR, M2 and exchange rate were collected from Bangko Sentral ng Pilipinas website. On the other hand, the GDP, exports and imports were collected from the National Statistics Coordination Board website. The data frequency is quarterly starting from 1997 to 2013 since this is roughly the period in which the mode of acquiring reserves is through market intervention, and not through debt issuance. This selected time period stretches 17 years consisting of 68 data points.

The data are used to construct series of independent equations to capture causalities of different variables. This paper explores two possible causalities into two systems of equations which is

4 Money Supply (M2) is defined as narrow money (M1) and other deposits (quasi-money). M1 consists of currency in circulation and transferable deposits. Quasi-money consists of savings deposits and time deposits.

Figure 5. Framework Summary

labelled System I, and System II. The two systems equations are the same, except on exports and imports which are specified differently in System I than in II (see figure 6 and 7). In System II, exports and imports are affecting each other as represented by the blue arrow. This relationship has been discovered after running system I equations and after testing using Granger Causality test which showed that exports is caused by imports and vice versa.

Except for the slight differences in specifying exports and imports, both systems of equations

start with equation 10 as shown in the top boxes of the two figures. Since the original equation is in multiplicative form, it must be transformed in double-log form as,

log(M2) = constant + log(exchange rate) + log(GIR). (22)

Since M2 and GIR appear in opposite side, they should not appear as explanatory variables at the same time as this would result to misspecification error. This analysis is supported by the empirical data as initial test shows that the two variables are multicollinear. This means that GIR and M2 are significant explanatory variables when regressed to exports and to imports independently. However, when both appear as explanatory variables (based on initial analysis), only one variable become significant and with reverse coefficient sign from the theoretical point of view. In addition, the variables are mutually causing each other based on Granger Causality5 test. Furthermore, the two series are cointegrated based on Augmented Dickey Fuller test6.

Looking at figures 6 and 7, variable GDP is not included as opposed in the theoretical framework summary in Figure 5, and for two reasons. First, GDP is only used as base proportion so that exports and imports are expressed as a share of GDP to avoid heteroscedasticity later in regression estimation. Second, GDP is not a significant explanatory variable in predicting employment based on initial regression run. This is a well known analysis as the media even pointed out that high GDP growth in recent years have not made a dent in employment (Habito [2013]).

With those similarities and differences, the System I series of independent equations are specified below:

log(M2) = constant + log(exchange rate) + log(GIR); (22)

inflation = constant + log(exchange rate) + log(GIR) + inflation t-1; (23)

log(export) = constant + log(exchange rate) + log(GIR);  (24a)

log(import) = constant + log(exchange rate) + log(GIR);  (25a)

employment = constant + %export + %import. (26)

It is worth noting that the right hand side variables of the equation 10, which are equivalent to money supply, are present in four out of five independent econometric equations above.

On the other hand, the System II independent equations are specified below:

log(M2) = constant + log(exchange rate) + log(GIR);  (22)

inflation = constant + log(exchange rate) + log(GIR) + inflationt-1; (23)

5 Granger Causality test was done in open source software R.2.15.3 using lmtest package.6 Augmented Dickey Fuller test was done in the same software using tseries package.

Figure 6. Snapshot of System I Equations Figure 7. Snapshot of System II Equations

log(exports) = constant + log(M2) + log(imports);  (24b)

log(imports) = constant + log(M2) + log(exports) ;  (25b)

employment = constant + %exports + %imports. (26)

As mentioned before, the main differences between System I and II are on how the exports and imports are specified (compare equation 24a vs 24b, and 25a vs 25b). First, both are assumed to be causing each other. Second, the other explanatory variable of both exports and imports is M2, instead of the right hand side of equation 10. This is based on initial runs that if GIR appears together as explanatory variable with either exports or imports, they appear to be multicollinear especially in the later period.

The two systems of equations are to be estimated using an innovative technique called rolling SUR (seemingly unrelated regression),7 a combination of rolling regression and SUR. SUR assumes that the series of equations are independent but their errors are assumed to be correlated (Zellner [1962]). If there is no correlation, the estimator would just boil down to OLS. To implement a rolling SUR, the coefficients are estimated over time. This is done in this paper by choosing a twelve-year rolling window within the 17 years data. The window consists of 48 data points out 17 years data set of 68 data points. Once the coefficients are estimated using SUR, the window is move by another quarter (i.e., dropping the oldest data point and adding a new one) and coefficients are estimated again until it reaches the end of the time period. With this, there are coefficient estimates beginning fourth quarter of 2008 until the last quarter 2013, amounting to 21 quarters or roughly five year forecast period. This is enough to see if the coefficients are fairly constant overtime or if there are abrupt changes of coefficients, say from significantly different from zero to non-significantly different. This technique is useful since it is possible that coefficient estimates may support the theory in some periods but not in all periods due to factors not anticipated in the theory. Another way of looking at persistence of estimates is the stability of standard errors over time as reflected by the confidence interval. Stable relationship may show stable standard errors; while, unstable relationship may show an increasing standard errors even if the point estimate is still significantly different from zero.

4. Results and Discussion This section has three subsections: the first two subsections discuss the results of rolling SUR of

System I and II; while, the last subsection shows the simulation results using the series of estimated models from the previous subsections. The simulation investigates the effect of accumulation of reserves on other explained variables like exports, imports and employment.

Since the estimates of systems of equations are rolling, there are results beginning the fourth quarter (4Q) of 2008 up to fourth quarter of 2013, which is referred in this paper as the forecast period. Hence, within this forecast period the goodness-of-fit between System I and II can be compared. For example, from 4Q 2008 to 4Q 2013, the McElroy R2 in System I is around 81% on the average; while, it increased to 87% in System II when the explanatory variables of exports and imports were modified to capture the effect the imports causing imports.

The overall improvement on goodness-of-fit on system of equations is also reflected on individual goodness-of-fit as shown in the Adjusted R2s’ of System I and II as shown below. Since the only differences between the two systems of equations are the explanatory variables of exports and imports, these are the only Adjusted R2s’ that are different in the two figures below, as

7 The software used in estimating SUR is R.2.15.3 using systemfit package.

0.0

0.2

0.4

0.6

0.8

1.0

4Q 2008 4Q 2009 4Q 2010 4Q 2011 4Q 2012 4Q 2013

System IISystem I

Figure 8. Goodness-of-fit: McElroy R-squared

-0.4

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log(ex rate)

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represented by green (for exports) and blue (for imports). In System I, both the Adjusted R 2s of exports and imports hovered around 60% of the time; while they are definitely higher in System 2, causing the improvement of its system goodness-of-fit. It is also worth noting that the adjusted R2 of equation 10 (see dark red line in both figures) is very high at around 94%, indicating the close relationship of GIR and M2.

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employment = constant +%export + %importinf lation = constant + log(exrate) + log(GIR) + lag inf lationlog(export) = constant + log(exrate) + log(GIR)log(import) = constant + log(exrate) + log(GIR)log(M2) = constant + log(exrate) + log(GIR)

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employment = constant +%export + %importinflation = constant + log(exrate) + log(GIR) + lag inflationlog(export) = constant + log(M2) + log(import)log(import) = constant + log(M2) + log(export)log(M2) = constant + log(exrate) + log(GIR)

In the next two subsections, the figures show point estimates in solid line together with a 2 standard errors band in broken lines. The band is equivalent to 95% confidence interval.

4.1.a System I Results: log(M2) = constant + log(exchange rate) + log(GIR)

The first series of results in this subsection are on impacts of both exchange rate and GIR on money supply, and on estimated constant over time. In figure 11 below, the constant is always different from zero from the period considered (4Q 2008 to 4Q 2013), as indicated by the two-standard error band. Since the econometric equation is in double-log form, the constant could not be interpreted simply as the mean of M2, but as a multiplier of impacts of both GIR and exchange rate.

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In figure 12, the exchange rate is positively different from zero at the beginning of the forecast period but it is declining in 2011 and since 2012 its effect on supply is zero. Specifically, in the beginning of the forecast period, a 1% increase in exchange rate leads to 0.5 to 0.8% increase in M2 money supply, but in the end periods (beginning in 3Q 2011), a 1% increase has no impact on money supply. This means that increase in exchange rate in the later periods does not lead to increase on money supply. It is possible there was a policy change in later period, so that the central bank was not actively buying dollars and accumulating reserves when the exchange rate increases. This may explain the high standard error of exchange rate impact in the later forecast periods (see orange broken lines in figure 12).

On the other hand, the impact of GIR on money supply is consistently different from zero with a downward trend in recent years. Particularly, a 1% rise in GIR leads to 0.8% increase in money supply in the early periods but declines to 0.6% in later periods. The impact of GIR is declining but

Figure 9. System I Adjusted R-squared

Figure 10. System II Adjusted R-squared

Figure 11. Estimated constant over time

Figure 9. System I Adjusted R-squared

Figure 12. Estimated impact of exchange rate and GIR on M2

still different from zero. Given that the two-standard error band of GIR impact appears to be stable compared to exchange rate impact, it is expected that accumulation of reserves always leads to increase in money supply in the coming periods, although the impact is declining.

4.1.b System I Results: Inflation = constant + log(exchange rate) + log(GIR) + lag Inflation

The second series of results are on impact on inflation due to exchange rate, gross international reserves and previous inflation. The estimates are lumped in figure 13, below. From the figure, the constant, exchange rate and GIR are not different from zero, and therefore have no effect on inflation. Theoretically based on equation 16 in the previous section, inflation increases if there is a rise in expectation future money supply which is a function of expected future exchange rate and GIR. Given that the impact is zero, the expectation of inflation is well anchored so that the expected future money supply of the people is just as the same as the current money supply. This also means that the independently floating exchange regime is successful in setting the people expectations.

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From figure 13a, the only significant predictor of current inflation is the previous (or lag) inflation as shown in purple lines. The point estimate says that a 1% increase in the previous inflation leads to 0.8% increase in current inflation. From this result, econometric equation 24 could be rewritten as:

inflation = 0.8 * inflation t-1 + error term. (27)

From figure 13a, the upper bound of the coefficient is close 1 at 95% confidence interval; however, if t-value used is at 99% level, this will give a much wider interval (see figure 13b). Therefore, the null hypothesis that the coefficient of lag inflation is not different from 1 cannot be rejected (see upper bound in figure 13b above 1). This means that at 99% confidence level, the true model is random walk, that is,

inflation = 1 * inflation t-1 + error term. (28)

Since inflation is generated under a random walk process, this means that both GIR and exchange have no impact on inflation. Other authors (e.g., Lim and Montes [1997]) have also observe that increase in M3 has no impact on inflation. It is possible that the effect of explanatory variables examined here may affect inflation through the error term, although, this will not be pursued in this paper.

4.1.c System I Results: log(Exports) = constant + log(exchange rate) +log(GIR)

The third series of figures show the estimates of constant, and impacts of both exchange rate, and GIR on exports. In figure 14, the constant is significantly different from zero, and given that the equation is in double-log form, it multiplies the impact of exchange rate and exports. From figure 15, the impact of exchange rate on exports is zero in most of the forecast period, except in the late 2009 up to early 2011. This means that in most cases a 1% increase in exchange rate will not lead to increase exports except for a brief period in the late 2009 up to early 2011. It is possible that the

Figure 13a. Estimated coefficients of explanatory variables affecting current inflation

Figure 13b. Estimated coefficients of previous inflation at 99% confidence interval

exporters did not automatically reflect the change in exchange rate on the export prices, hence, there is no increase of exports in most of the forecast period. In the periods in which the impact of exchange rate is positive, a 1% increase in exchange rate leads to 0.4% increase in exports on the average. On the other hand, the effect of GIR on exports is always different from zero in all the forecast periods although the effect is declining. For example, in early period a 1% rise in GIR leads to 0.4% rise in exports but drops to 0.2% rise in later period.

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4.1.d System I Results: log(Imports) =constant + log(exchange rate) + log(GIR)

The fourth series of figures show the constant and the impacts of both the exchange rate and GIR on imports. In figure 16, the constant is different from zero so it acts as a multiplier of the impacts of other variables. In figure 17, the result shows that a 1% rise in exchange rate may lead to 03.% to 0.7% of imports until 1Q 2012, and beyond that the impact is not different from zero. The same figure shows that a 1% rise in GIR leads to 0.27% rise in imports, on the average, in all the forecast period.

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The results in figure 17 are contrary from the theoretical implication of equation 10 that the imports should decrease as exchange rate increases. In fact, the impacts of exchange rate and GIR on imports appear to be similar to exports. This leads to the hypothesis that since the top Philippine exports are in electronic products8 which have high import components, then imports would behave like exports. This result is the main reason for modifying the exports and imports equations as discussed later in System II results in Section 4.2.

4.1.e System I Results: Employment = constant + %exports + %imports

The last subsection shows the constant and the impacts of exports and imports on employment in figures 18 below. The constant in the figure means that assuming exports and imports are both

8 Electronic products comprise 41% of the total exports in the first three months of 2014 according to the Philippine Statistical Authority website www.census.gov.ph. Accessed June 8, 2014.

Figure 14. Estimated constant overtimeFigure 15. Estimated coefficients of

explanatory variables affecting exports

Figure 16. Estimated constant over time Figure 17. Estimated coefficients of explanatory variables affecting imports

zero, the average employment ranges from 91 to 99% over the forecast period. The same figure shows that increase in exports share to GDP promotes employment; while, increase in imports share reduces employment in all forecast period. For example a 1% increase in exports share leads to 0.2% increase in employment. On the other hand, a 1% increase in share of imports leads to a decline in employment by 0.3%.

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The findings that exports increase employment while imports reduce employment supports the theoretical implication based on equation 21. In addition, this empirical result is similar to the findings of Lim and Montes [1997] that employment in the Philippines is growing in export oriented sectors. The mechanism why exports promote employment while imports discourage employment is easy if value chain is included in the analysis. For example, the value chains in producing export goods are located locally; hence, employment is generated locally. On the other hand, the value chains of producing import goods are located abroad; hence, employment is generated outside the Philippines. The jobs generated in imports are only in the services sector like the handling of goods and in retailing sector. Take for example a poultry product produced here viz a vis produced abroad, there are more employment produced if poultry is produced here than if produced abroad.

Lastly in this subsection, it is worth noting that among the different independent equations the employment equation has the most stable standard errors for all explanatory variables. Therefore, the technique of expressing exports and imports as share of GDP is successful in reducing heteroscedasticity.

4.2 System II Results

This subsection focuses on the discussion on the independent models that are specified differently from System I, specifically the exports and the imports models, referred as equations 25b and 26b respectively. Other independent equations that are specified similarly have the same results and not repeated in this subsection.

4.2.a System II: log(Exports) = constant + log(M2) + log(Imports)

The two figures below show the constant and the impacts of M2 and imports on exports. In figure 20, the constant is not different from zero so the impacts of other explanatory variables are not magnified. In figure 21, the impact of money supply9 on exports is always positive as a 1% rise in M2 leads to 0.16 to 0.3% increase in exports. On the other hand, the impact of imports on exports in the same figure is always positive as 1% rise in imports leads to 0.6 to 0.8% rise in exports. Between the two explanatory variables, imports have greater impact than M2 on exports. For completeness, there is no lag effect of the previous imports on current exports (result not shown).

9 Recall that money supply is a function of exchange rate and GIR.

Figure 18. Estimated coefficients of explanatory variables affecting employment

Figure 20. Estimated constant over timeFigure 21. Estimated coefficient of explanatory

variables affecting exports

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4.2.b System II Results: log(Imports) = constant + log(M2) + log(Exports)

The series of figures below show the constant and the impacts of M2 and exports on imports. In figure 22, the constant is not zero which means the impacts of other explanatory variables are multiplied further. In figure 23, the impact of M2 on imports is zero in the early periods and began to be slightly significant beginning in 4Q 2011. Beginning this period a 1% rise in M2 leads to 0.1% increase in exports. On the other hand, the a 1% rise in imports, in the same figure, leads to 0.6% increase in early periods and has decelerated to 0.4% in the later forecast period.

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It is worth noting that in general, standard errors of System II equations on exports and imports are more stable than in System I. In addition, it appears that it is exchange rate that is causing higher variance of coefficient estimates.

4.2 Simulation Impact of $5 bn additional reserve at different forecast periods

The series of figures below show the simulated impact of additional reserves on exports, imports and employment. Simulation on inflation is not included since there is no impact to start with as inflation is generated in random walk process.

Figure 24 below shows the impact of $5 bn additional reserves on exports and imports. System I tends to estimate a higher on both exports and imports than system II. The simulation results in the two systems capture the relationship that exports and imports move in the same direction due to high import content of exports. In both systems, the increase in value of exports due to additional reserves is always higher than imports. Another trend that can be observed in figure 24 is that in both systems the simulated impact of additional reserves for exports and imports tend to converge in the end period around ₱10bn in System I (see solid lines) and ₱4bn in System II (see broken lines).

On the other hand, the impact of additional reserves on employment is shown in figure 25 which very minimal at less than 1 percentage point. Specifically, the impact of additional $5bn reserves on employment ranges from 0.15% to -0.05% for System I and 0.15% to 0% for System II. In general,

Figure 23. Estimated coefficient of explanatory variables affecting imports

Figure 22. Estimated constant overtime

the impact of additional reserves on employment is declining especially at the later period. For System I the impact on employment becomes negative beginning 4Q 2010; while, for System II, the impact on employment goes near to zero beginning 4Q 2011.

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5 Summary and ConclusionThis paper traces the linkages of reserve accumulation to other variables through a series of

mathematical equations. The starting point of the series of equations is the exchange rate intervention instead of the foreign debt issuance. The mathematical equations are tested empirically by building two systems of econometric equations under limited variables. The systems of equations are estimated using rolling SUR to track the changes of the coefficients. The results show that the goodness-of-fit at system level is around 80% for System I and rises to 87% in System II, while the goodness-of-fit at the level of individual equation ranges from 40% to 94%.

Although the ranges of goodness-of-fit for individual equations are fairly good, explanatory variables are sometimes not significant in explaining dependent variable. For example, the Philippine inflation series is not affected by reserve accumulation, and exchange rate increase since the series is a random walk process. In fact, the best explanatory variable for inflation is the previous value of inflation. Aside from inflation, though, the explanatory variables are significant in explaining other dependent variables but only vary in their persistence over time. For example, the exchange rate as explanatory variable is not persistent as it is significant only in the early forecast period in explaining dependent variables M2 and imports. However, it becomes non-significant in later periods. In explaining exports, exchange rate is only significant in a brief period in the middle of the forecast period. On the other hand, GIR is always significant in explaining the dependent variables M2, exports and imports. The impact of M2 as explanatory variable on exports and imports in System II is generally weak as it is close to zero in absolute and only in some period it is significantly different from zero. In general, the relationship of explanatory and dependent variables is getting weaker in recent years as the estimated coefficients are in a downward trend. This trend happens near the end of the forecast period, when the accumulation of reserves has stagnated while the exchange rate has increased.

The exports and imports as explanatory variables are persistent in predicting employment. It is clear that imports discourage employment while exports encourage employment. If there exists a policy encourage exports and discourage imports, this could enhance economic growth and bring down unemployment. However, both imports and exports move in the same direction as exports have high import component. In the end, a reserve accumulation leads to increase in both exports and imports so that the net gain in economic growth is minimal, while the net gain in employment is positively small number in early forecast period to zero or even negative net employment in later period.

The government policy, therefore, is to encourage exports that have high local content and this

Figure 24. Impact of Additional $5 bn Reserves on exports and imports

Figure 25. Impact of Additional $5 bn Reserves on employment

could come from agricultural products processing. This strategy would decouple the impact of reserves on import and export. When decoupling happens accumulation of reserves may increase exports and decrease imports. This would encourage economic growth through exports which is different from the findings that increase in foreign reserve, may enhance economic growth through investment (Fukuda and Kon [2009]).

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