hyperinflation in zimbabwe

International Research Journal of Finance and Economics ISSN 1450-2887 Issue 90 (2012) © EuroJournals Publishing, Inc. 2012 http://www.internationalresearchjournaloffinanceandeconomics.com

Monetary Reforms and Inflation Dynamics in Zimbabwe

Carren Pindiriri Economics Department, University of Zimbabwe

P.O. Box 167MP Mt. Pleasent, Harare, Zimbabwe E-mail: [email protected]

Tel: +0263 773 044 364

Abstract

The study examines and assesses the causes of inflation in the post-dollarized Zimbabwe. It employs time series econometric methodology based on monthly data to examine the probable factors influencing inflation in the post-dollarized Zimbabwe. The influence on inflation of factors such imports, consumer expectation about future inflation, exchange rate, interest rates, output growth and money supply, among others is investigated. Although interest rate has been found to be one of the major determinants of inflation in Zimbabwe by studies done during the pre-dollarization period, this study finds statistical evidence of an insignificant relationship between interest rate and inflation in dollarized Zimbabwe. The study however finds evidence that consumer expectations about future inflation, money supply, current exchange rate, and import value are the major factors influencing post-dollarization inflation. Keywords: Cost-push, demand-pull, hyper-inflation, inflation, money supply, seignorage,

structuralism 1. Introduction Economic literature (Blanchard and Fischer, 1989; Walsh, 1998; Sachs and Larrain, 1993; Lewis and Mizen, 2000) argues that unmanageable inflation is one of the major macroeconomic problems although moderate levels of inflation are beneficial in the form of employment creation. Hyper-inflation or run-away inflation erodes consumers’ buying power thereby impoverishing them. On the other hand, negative inflation increases unemployment. There is therefore need to simultaneously tame inflation at levels high enough to create employment and low enough to restore consumers’ buying power.

A number of studies on inflation were done in Zimbabwe before dollarization (Chhibber, 1989; Dzvanga, 1995; Sunde, 1997; Makochekanwa, 2007; Pindiriri and Nhavira, 2011). These studies covered the time series periods before dollarization and found money supply growth (mainly from seinorage), exchange rate variation, output gap, consumer expectations about future prices (lagged inflation) and labour costs as the main determinants of inflation in Zimbabwe. Studies done during the hyper-inflationary decade by Makochekanwa (2007) and Pindiriri and Nhavira (2011) found money supply as the major driver of inflation in Zimbabwe. In addition, Makochekanwa finds the black market for foreign currency as equally a major determinant of the hyper-inflation.

However, Zimbabwe experienced an incredible shift in its macroeconomic environment as a result of dollarization since 2009. The Reserve Bank of Zimbabwe (RBZ) has been incapacitated to

International Research Journal of Finance and Economics - Issue 90 (2012) 208

control money supply and the black market for foreign currency has been partially eliminated. Despite the elimination of money printing and the black market for foreign currency, some pockets of inflationary pressures are still experienced in the economy. The main question is; “What are the main factors influencing these inflationary pressures in the post-dollarization era?” The study therefore attempts to investigate and assess the causes of inflationary pressures since the introduction of dollarization in 2009.

The rest of this study is organized as follows: Section two presents the macroeconomic background of Zimbabwe, section three reviews literature on inflation. The theoretical framework and the empirical model are presented in section four, followed by the analysis of survey findings in section five. Finally, section six presents the policy implications and conclusions. 2. Zimbabwe’s Macroeconomic Background 2.1. A Brief Review of the Pre-Dollarization Decade

In the last quarter of 1997, money supply (M3) growth increased from 13.3% in September to 28.2% in November and further to 34.9% in December (RBZ monthly reports; May 1998). The growth was mainly attributed to increases in both M1 (notes and coins) and quasi money. M1 growth more than doubled from 21.4% in September to 47.7% in December, the same time when War veterans were paid their gratuities (Ndlela, 2001). The local currency crushed against major currencies like the United States dollar (US$) and the British pound (₤) following a 31.8% depreciation on 14 November 1997. Inflation became rampant with food and accommodation prices soaring by more than 100%. Persistent price increases caused food riots in December 1997, people demonstrated against high and unaffordable food prices by destroying and looting food shops. By the end of 1997 broad money supply had grown by 34.9% and CPI inflation by 52.7% (Central Statistical Office (CSO) publication, 1998). Realizing that the government was gradually losing popularity from the majority, price ceilings were again enforced on basic and essential products. By 1999 government opposition had increased as evidenced by the emergence of a strong opposition party, the Movement for Democratic Change (MDC). The increased opposition from the public towards the 2000 general elections forced the government to intensify price ceilings on basic and essential commodities. In 2000 the government implemented the Fast Track Land Reform (FTLR) which displaced most of the white commercial farmers. Agricultural output fell down to its lowest level between 2000 and 2005 as a result of droughts and new farmers’ adjustments to new resettlement areas (Ministry of Agriculture, Mechanization and Irrigation Development publications, 2002-2005).

In the decade 1999 to 2008, Zimbabwe experienced one of the worst macroeconomic performances in the world. During this period the country recorded a continuous negative real GDP growth, an extreme currency depreciation, persistent droughts, a record hyper-inflation which reached over 2 million %, unemployment rate of over 60%, money supply growth which reached over 100 000% by 2008. The CPI inflation rate was 12.5 million and the growth rate was 6 723% in 2007 according to CSO publications, 2008. Broad money supply grew by over 64 000% in 2007 and 2008. Prices were changing on an hourly basis in 2008; the price of a good could change twice while still waiting in the queue to purchase it. The country’s macroeconomic performance over this decade is presented in figure 1 (appendix A). The variables are expressed in natural logs in order to improve the drawing scales distorted by extreme figures of inflation, money supply and GDP experienced over the period 2000 to 2008. It is shown in figure 1 that both money supply (M3) and inflation (CPI) sharply rose over this period while real GDP growth was always negative.

In 2009, Zimbabwe’s main political parties formed an inclusive government which eliminated price ceilings on basic goods, essential goods and foreign exchange, among others. The economy was dollarized, that is, the local currency seized to be the medium of exchange. It was replaced by the US$ and the Rand as the official currencies in the country. Since then the country experienced a credible shift in its macroeconomic performance.

209 International Research Journal of Finance and Economics - Issue 90 (2012)

2.2. Post-Dollarization

From February 2009, just after dollarization, the Zimbabwean economy started to show some symptoms of recovery. Hyper-inflation was eliminated and goods began to fill in the “thirst strained” empty shelves in retail outlets. The broad money supply (M3) and inflation monthly growth rates which were above 100 000% and 1 000 000% in 2008, significantly dropped to growth rates below 30% and 2% respectively, immediately after dollarization (see figure 2 in appendix A). The exchange rate (US$ versus the ZAR) largely determined by the performance of the South African economy has been stable, ranging between seven to nine ZAR per US$. The country’s Gross Domestic Product (GDP) began to grow from -10% in 2008 to 5.7% in 2009, 8.1% in 2010 and to about 9.3% in 2011.

Figure 2 shows that the macroeconomic data on inflation, exchange rates and money supply recorded during the post dollarization period depict some signs of stationarity. Broad money supply (M3) graph depicts no time trends and no clear relationship with inflation, that is, variations in money supply growth are not clearly linked to variations in inflation growth in terms of their trends. This result is also portrayed in the scatter plot of figure 3 in appendix A. Unlike money supply, figures 2 and 4 (appendix A) portray a negative relationship between inflation and exchange rate (Rands/US$1). While the exchange rate has been gradually falling over the study period, inflation seems to have been increasing gradually. The scatter plot on inflation against interest rates proxied by commercial banks’ maximum lending rates gives a picture of no relationship between inflation and the interest rates over the study period. Figure 6 in appendix A illustrates the nature of the relationship between inflation and interest rates after dollarization.

Since dollarization, import volume has been on the rising trend in the country. The increase in imports might be a result of increasing real income. Despite the failure of the scatter graph of inflation against imports to clearly show whether the two are positively or negatively related, the graph indicates that a relationship between inflation and imports exists (see figure 5 in appendix A). Although scatter plots give us a picture of the nature of the relationship between variables, they fail to portray the magnitude and the significance of relationship among variables. There is therefore need to supplement scatter analysis with other statistical techniques such as regression analysis. 3. Literature Review 3.1. Theoretical Literature

Inflation has attracted much attention from researchers in both developed and developing countries. There are three main theoretical approaches to explaining the inflation phenomenon, namely the demand-pull, cost-push and structuralism. All of these three approaches attempt to explain the causes of inflation.

The demand-pull approach has two main schools of thought, the monetarist and the Keynesian schools. Monetarists assert that inflation is purely a monetary phenomenon, that is, they argue that inflation emanates from the expansion in money supply. The excess supply of money relative to money demand will result in high cash balances held by the public and thereby raising the public’s demand for goods and services. In the absence of a corresponding increase in output production, the excess demand will induce upward pressures on prices (Friedman, 1968, Siegel, 1982). Although the Keynesians accept that inflation is a monetary phenomenon, they argue that it is a fiscal-induced phenomenon (Killick, 1981). According to the Keynesian school, inflation arises from the existence of excess demand, that is, aggregate demand being greater than aggregate supply at full employment level of output. The government budget deficit is a major determinant of inflation in this school of thought.

Cost-push arguments are mostly associated with non-monetary forces and imperfectly competitive aggregate supply models. Cost-push theorists argue that economic power is concentrated in the hands of a few sellers, enabling monopolistic firms to raise prices whenever they please. Inflation would emanate from factors such as high nominal wage settlements in excess of levels


warranted by increased labour productivity, imported inflation and excessive devaluations. The high nominal wage settlements not only raise consumers’ spending power and, therefore, demand but will also exert upward pressure on unit production costs and, ultimately, the general level of prices.

Serious and chronic inflation of Latin American countries resulted in the emergence of another school of thought, the structuralist school. Kirkpatrick and Nixon (1976) argue that an attempt to use orthodox theories of inflation in Less Developed Countries (LDCs) would be inevitably introduce the problem of misplaced aggregation because the economic and institutional setting of LDCs are fragmented and heterogeneous. Sectoral imbalances and market imperfections would make the notions of aggregate demand and aggregate supply inapplicable. Instead a wide range of structural factors have been cited as the causes of inflation in LDCs. These include the relative inelasticity of food supplies and foreign exchange constraints (Ghatak, 1981). According to Ghatak, higher prices of agricultural products and the demand for wage increases by urban industrial workers may result in wage-price spiral making prices for industrial products go up as industrialists seek to maintain their profit margins.

In Obstfeld and Rogoff (1996), Cagan studied seven hyperinflations in 1956 where hyperinflation was defined as periods during which the price level of goods in terms of money rises at a rate averaging at least 50% per month. Cagan developed a model regarded as a special case of the LM curve or a simplified Keynes (1936)-Hicks (1937) LM. The model states that the real money demand in the current period depends positively on the current price level and negatively on the expected change in price, that is: }{ 1 tttt

dt ppEpm −−=− +η , where d

tm is real money demand in the current period, tp is current price level, tE is expectation, 1+tp is post lagged price level and η is a constant. Generally the model says inflation is a function of money supply and the expected inflation. Obstfeld and Rogoff solved the Cagan model and concluded that the price level depends on a weighted average of future expected money supplies, with weights that decline geometrically as the future unfolds.

Unlike the Cagan model, Dornbusch (1976) developed a model on inflation based on the exchange rate (foreign component). According to Dornbusch, a change in the domestic price level depends on the output gap and exchange rate variations. The model is simply expressed as:

ttdttt eeyypp −+−=− ++ 11 )(θ , where tt pp −+1 is a change in the price level, )( yy d

t − is the output gap, tt ee −+1 is exchange rate growth and θ is a constant. Obstfeld and Rogoff added expected inflation to the Dornbusch model as one of the determinants of inflation.

It can be deduced from the theories explained in this section that no single approach is sufficient and complete in explaining the determination of the rate of inflation. However, the models are necessary as they help us derive the possible determinants of inflation in a given economy. The models clearly show that inflation emanates from excess money supply, excessive government spending, output gap, and exchange rates variations, among others. 3.2. Empirical Literature

There is wide coverage of empirical work on inflation in both developed and developing countries. We will however consider a few studies carried out in Zimbabwe and other countries. Moser (1995) uses an error correction methodology to develop an inflation model of Nigeria. The study finds nominal money stock, the exchange rate, rainfall and real income to be cointegrated. Monetary expansion, devaluation and agro-climate conditions were found to be the major factors influencing inflation in Nigeria. Like Moser, Olubusoye and Oyaromade (2008) apply the error correction mechanism to model Nigeria’s inflation process and find out that lagged inflation, expected inflation, petroleum prices and real exchange rate significantly propagate the dynamics of inflation in Nigeria. The level of output is found to be insignificant and money supply is found to negatively influence inflation (disapproving the theories of inflation). Although the different researchers use the same methodology for the same country, the results are not the same indicating the importance of keeping on updating these models.


In Zimbabwe, a number of studies on inflation were done in the 80s and 90s. Chhibber et. al (1989) examine the inflation dynamics in Zimbabwe through the use of Two Stage Least Squares (2SLS) methodology from 1969 to 1986. They identify labour costs, interest rates, exchange rates, foreign prices, monetary growth and real income growth as factors explaining inflation in Zimbabwe. Dzvanga (1995) applies the same methodology of 2SLS to investigate the determinants of inflation in Zimbabwe over the period 1983 to 1994. Money supply growth, exchange rate depreciation, and real output are found to be the main factors influencing inflation in Zimbabwe. However, the results of these studies are questionable because of the sample sizes used; the samples are small for 2SLS methodology. Sunde (1997) develops a dynamic inflation model for Zimbabwe over the period 1989 first quarter to1996 second quarter. The results indicate that money supply growth, real output growth, exchange rate depreciation, budget deficit and nominal deposit rates were the major determinants of inflation in Zimbabwe. Makochekanwa (2007) examines the causes of hyperinflation in Zimbabwe and identifies money supply, the black market for foreign exchange and lagged values of hyper inflation as the major determinants of hyper inflation in Zimbabwe. However, the political index variable was found to have an unusual negative influence on hyper inflation.

Very little effort has been applied to update the inflation models developed in the 80s and 90s. Given that Zimbabwe experienced one of the world’s worst inflation records over the period 2000 to 2008 and that the previous studies were done before this period, Pindiriri and Nhavira (2011) model Zimbabwe’s inflation process in the hyper-inflationary period. Unlike Makochekanwa’s study, Pindiriri and Nhavira include the worst years of hyper-inflation, 2007 and 2008, in their study. The study applies a time series methodology covering the period 1975 to 2008 and reveals that the major drivers of inflation in Zimbabwe are low production levels, increased money supply, expectations about future prices, interest rates and historical exchange rates and budget deficits. The current levels of real exchange rates and budget deficits were found to be insignificant in explaining inflation variation in Zimbabwe. The historical real output levels were also found to be insignificant in explaining inflation variation. From their ARDL model they concluded that expectations about future prices, money supply, real output, interest rates and historical exchange rates and budget deficits are of particular importance when developing the inflation model for Zimbabwe. Real output is found to have the largest influence on inflation variation in the country.

The data used in all the studies done during the hyper-inflation period are questionable. Economic activities were not accurately recorded during this period because of lack of resources, both financial and labour. Hence the data could have been measured with huge margins of error thereby rendering the estimated models biased and inconsistent. In addition to this problem, all previous studies on inflation have concentrated on yearly or annual inflation averages ignoring the possibility of high frequencies in inflation variation. It is against this background that this study attempts to model the factors influencing monthly inflation averages in the post dollarization period. The post dollarization period is associated with smaller figures of variable measurement hence reduced margins of error in variable measurement. We therefore expect to develop a better parsimonious model than those developed during the hyper-inflationary period. 4. Methodology 4.1. Theoretical Framework and the Empirical Model

Inflation is caused by cost-push as well as demand-pull factors, that is, it originates from both the supply side and demand side of the economy. It is against this background that this paper develops an empirical model based on the Dornbusch (1980), Olubusoye and Oyarembe (2008) and Pindiriri and Nhavira (2011) models in which the general price level ( P ) is considered to be the weighted average of the price of the tradable ( TP ) and non-tradable ( NP ). The price index P is therefore specified as:

φφ −= 1NT PPEP 10 << φ (1)


where E is the nominal exchange rate and φ is the share of tradable goods in total expenditure. Equation (1) can also be expressed as:

NN

T PPPEP φ

φ

= = NPeφ (2)

where φ

φφ

N

T

PPEe = and e is the real exchange rate.

The price of non-tradable goods ( NP ) is also a weighted average of the price of non-tradable food ( NF ) and non-tradable other goods ( NO ), that is,

ββ −= 1NONFN PPP (3)

where β is the share of non-traded food items in total expenditure of the non-tradable sector. In log-linear, we can express equation (3) as follows:

NONFN PInPInPIn )1( ββ −+= (4) By letting PInp = for any variable P , equation (4) can be expressed as:

NONFN ppp )1( ββ −+= (5) If equation (3) is substituted into equation (2) we obtain;

ββφ −= 1NONF PPeP (6)

Equation (6) can be expressed in log-linear form as follows: NONF ppeInp )1( ββφ −++= (7)

Equation (7) demonstrates that in the goods market, the general price level is a weighted average of the real exchange rate (price of the tradable) and price of the non-tradable which is also a weighted average of the price of non-traded food and non-traded other.

In the money market P

MP

M DS

= , which can also be expressed in log-linear form as: DS mMp −= )log( (8)

where Dmandp are the logs of P and real money demand respectively, SM is the nominal stock of money. Equating equations (7) and (8) and solving for NOp gives:

[ ]NFDS

NO peInmMLogp βφλ −−−= )( (9) where 1)1( −−= βλ . The demand for real money balances ( Dm ) is assumed to be a function of real income ( y ), expected inflation rate ( ep ) and the interest rate ( i ), that is:

),,( ipyfm eD = (10) All variables in equation (10) are in natural logarithmic form. Theoretically, real income is

expected to increase the demand for real money balances while expected inflation rate and the rate of interest are expected to reduce the demand for real money balances. By assuming a linear demand function, we can express the money demand function in equation (10) as:

ipym eD321 πππ −−= (11)

Substituting equation (11) into (9) gives: [ ]NF

eSNO peInipyMLogp βφπππλ −−++−= 321)( (12)

By substituting equation (12) into equation (5), we obtain: [ ])()1( 321 NF

eSNFN peInipyMLogpp βφπππλββ −−++−−+= (13)

Equation (13) can be generalized as: eInipymp eS

N 54321 ϕϕϕϕϕ +++−= (14) From equation (7)


eInp φ= + Np (15) Replacing Np in equation (15) by Np in equation (14) we obtain the function for the general

price level defined as follows: =p eInipym eS

54321 ηηηηη +++− (16) Equation (16) gives the general inflation model which can be generally expressed as:

=tp ),,,,( ttett

St eipymf (17)

Zimbabwe has also been largely depending on imports mostly from South Africa over the study period. On one hand import volumes supplement domestic supplies thereby suppressing prices. Increased importation increases competition within the domestic market, thus reducing monopoly power and prices. On the other hand in economies where the market is dominated by imported goods, prices are mostly determined by foreign inflation levels, that is, by price levels in countries from which the imports originate. This is the case of imported inflation in which we expect import value to be positively related to domestic price levels. In line with this, the study includes imports ( tMports ) as one of the determinants of inflation in Zimbabwe. Duty on imported goods reduces import volumes and increases monopoly power in the domestic market. The import variable also encompasses the implications of an import duty. We can therefore model Zimbabwe’s inflation process by augmenting equation (17) and re-express it as follows:

=tp ttttett

St uMportseipym +++++++ 6543210 ααααααα (18)

Given the dynamics of most economic variables, we re-model equation (18) into a general dynamic model, an autoregressive distributed lag model of order k . Equation (18) is therefore expressed as follows:

t

k

jjtjjt

k

jj

jt

k

jj

ejt

k

jjjt

k

jj

k

j

Sjtj

k

jjtjt

uMportse

ipympp

∑∑

∑∑∑∑∑

=−−

=

−=

−=

−==

−=

−

+++

+++++=

06

05

04

03

02

01

110

αα

ααααγα (19)

Taking changes in equation (19), we obtain:

t

k

jjtjjt

k

jjjt

k

jj

ejt

k

jjjt

k

jj

k

j

Sjtj

k

jjtjt

vMportsei

pympp

+Δ+Δ+Δ+

Δ+Δ+Δ+Δ+=Δ

∑∑∑

∑∑∑∑−

=−−

−

=−

−

=

−

−

=−

−

=

−

=−

−

=−

1

06

1

05

1

04

1

03

1

02

1

01

1

110

βββ

βββλα (20)

If the variables in equation (18) are co-integrated, then all the variables in equation (20), that is, the first differences of the variables in equation 18, including the error term tv are stationary. In the long run inflation can have a tendency to move towards its steady state path. Therefore the inflation process can correct the short run variations by dampening the inflation towards its steady state path. An error correction model (ECM) is used to model such a process. In an ECM (1), that is, in the model with a one lag correction factor, equation (20) can be expressed as:

ttttett

Stt

k

jjtjjt

k

jj

jt

k

jj

ejt

k

jjjt

k

jj

k

j

Sjtj

k

jjtjt

Mportseipymp

Mportse

ipympp

εδδδδδδψ

θθ

θθθθλμ

+−−−−−−−

Δ+Δ+

Δ+Δ+Δ+Δ+Δ+=Δ

−−−−−−−

−

=−−

−

=

−

−

=−

−

=−

−

=

−

=−

−

=−

∑∑

∑∑∑∑∑

)( 1615141312111

1

06

1

05

1

04

1

03

1

02

1

01

1

110

(21)

The term in brackets of equation (21) is the error correction term and ψ is the error correction coefficient. It measures the speed of adjustment towards the long run steady state path. If inflation in the previous period, 1−t , rises above its long run equilibrium, then the error correction term in


brackets of equation (21) assumes a positive sign. The error correction coefficient, ψ , measures the speed at which the short run disequilibrium is cleared off. In the case that the variables in equation (18) are not cointegrated the study will apply the general Autoregressive Distributed Lag, ARDL(p,q), models presented in equations (19) and (20). 4.2. Stationarity and Cointegration Tests

Modeling of economic variables requires data cleaning before running the regressions. The most important step in cleaning time series data is to check for stationarity. There is a high risk of running a spurious regression if non-stationary time series data are used in time series modeling. In this study we apply the Augmented Dickey-Fuller (ADF) test for stationarity. If the variables are integrated of the same order, that is, if they become stationary after differenced the same number of times, then we will apply the Engle-Granger and Johansen tests for cointegration. The order of ARDL, (p,q), is determined through the Akaike information criterion (AIC). 4.3. Variable Definition and Data Sources

The study uses monthly secondary data spanning from January 2009 to December 2011. Growth rates are used. A change in the Consumer Price Index (CPI) is used as a proxy for the inflation variable ( tp ) which is the most important variable in the study. Other series used are the real income approximated by the real GDP ( ty ) converted into monthly values, the exchange rate ( te ) which is measured as ZAR per US$1, interest rate approximated by the commercial bank lending rate ( ti ), imports ( tMports ), and money supply ( s

tm ). Imports are measured in value terms, that is, in US$ and money supply is defined as the broad money (M3). We assume that households make their future decisions based on the current level of inflation, that is, they expect the current rate of inflation to persist in the next period. Hence we approximate the current expected level of inflation ( e

tp ) by the previous period inflation level ( 1−tp ). While a number of studies (Moser, 1995; Olubusoye and Oyaromade, 2008) have used rainfall as one of the major factors influencing inflation, in this study we take it as a major factor influencing the real output in Zimbabwe. Rainfall influences output in the country hence it is implicitly included in the real output variable of the model. Real Income ( ty ) We use GDP as a measure of purchasing power in the economy. Since GDP is measured per year, we convert the yearly values into monthly data. An increase in the purchasing power of consumers is expected to raise consumption demand thereby forcing the price levels up. We therefore hypothesize that a positive growth in real income will increase inflation, that is, there exist a positive relationship between inflation and real income. Exchange Rate ( te ) This is defined as the number of South African Rands (ZAR) per one United States dollar (US$). The US$ is the unit of measurement for most economic variables in Zimbabwe. It is the official currency for the payment of wages, salaries and many other activities. Therefore if the Rand depreciates against the US$, we expect inflation to go down in Zimbabwe. Inflation will go down in two ways; first, a unit of a dollar will buy more of the South African goods, that is, imports from SA will be cheaper thereby pushing prices down in Zimbabwe. Second, the depreciation of the Rand will increase the demand for South African goods by Zimbabweans which will in turn increase competition and supply in the domestic market. Prices are suppressed as monopoly power is lessened out in the domestic market. We therefore expect an increase in the exchange rate (depreciation of the Rand) to reduce inflation in Zimbabwe.


Lending Rate ( ti ) High rates of interest reduce aggregate demand which will in turn force the general price level down. We therefore expect a negative relationship between inflation and interest rates. We use the commercial bank lending rate as a proxy to the interest rate variable. Imports ( tMports ) On one hand increased importation increases competition within the domestic market, thus reducing monopoly power and prices. On the other hand in economies where the market is dominated by imported goods, prices are mostly determined by foreign inflation levels, that is, by price levels in countries from which the imports originate. This is the case of imported inflation in which we expect import value to be positively related to domestic price levels. The relationship between import value and inflation is expected to be positive whilst that of import volumes and inflation is expected to be negative. This study however makes use of the import value rather than the import volume because import volumes are greatly influenced by exchange rates. The exchange rate variable therefore takes care of import volumes as well. Money Supply ( s

tm ) In this study broad money (M3) is used as a measure of money supply. Increase in money supply increases consumption demand. Theoretically inflation is defined as a monetary phenomenon implying that increased money supply has the effect of increasing the general price level. The expected relationship is therefore positive. Expected Inflation ( e

tp ) This variable is measured by lagged inflation. We assume static inflation expectation, that is, we assume that consumers expect the current inflation level to be the same as the previous period one. The relationship between expected inflation and the actual inflation is expected to be positive. Data Sources Data were obtained from Zimstats, the Reserve bank of Zimbabwe Annual Reports, Ministry of Finance Budget Statements and other relevant Ministries. 5. Results and Analysis of Survey Findings 5.1. Descriptive Statistics and Data Sources

Table 1 in Appendix B provides the summary descriptive statistics of all the variables used in the study. The variables have 36 monthly observations. As indicated in the table, the broad money supply ( s

tm ), interest rates ( ti ) and import value ( tMports ) had the largest variations over the study period. Smaller variations were experienced in inflation ( tp ), exchange rate ( te ) and real income growth ( ty ).

Variations in inflation and the exchange rate have sharply gone down after dollarization. The standard deviations of inflation and exchange rate growth went down from 4.767 and 5.050 to 1.014 and 0.848 respectively. However variations in the growth rates of money supply and interest rate went up (see table 2). Money supply growth has been varying from negative to positive since dollarization. For example, in September 2010, M1 grew by 10.7%, M2 by 10.8% and M3 by 12.2% and the succeeding month of October recorded a decline in money supply, M1 declined by 15.2%, M2 by 9.1% and M3 by 6%. This might be a result of the Reserve Bank of Zimbabwe’s incapacity to control money supply. Money supply has been largely determined by external factors.


Despite recording changes in data variations, the nature of data distributions remained similar to pre-dollarization distributions. The Jarque-Bera statistics illustrated in table 2 (Appendix B) indicate that only the real income variable has a closer to a normal distribution. 5.2. Empirical Analysis and Results

We found out that all the variables have a unit root. They are found to be non-stationary at their levels. However, their growth rates are all stationary except that of real income ( ty ) implying that most of the variables are integrated of order one, I(1) except real income which is integrated of order two, I(2). Since the variables are not integrated of the same order there is no likelihood of cointegration.

One of the necessary conditions for economic variables to be cointegrated is the presence of the same order of integration. In this study the condition is not satisfied hence no need for further cointegration tests. Table 3 in appendix C presents the results of the unit root tests. Since the computed ADF test statistic is less than the ADF critical values at the 5% level for all the variables expressed in growth rates except real income, we have enough statistical evidence to conclude that these growth rates are stationary or are integrated of order zero at the 5% level of significance while real income is integrated of order two. We therefore apply the ARDL model in equation (20). In the model non-stationarity is corrected by using differenced series. The Akaike information criterion indicates that the maximum optimal lag for most of the variables is zero. Table 4a presents the results of the parsimonious ARDL(1, 0) specific model while table 4b in appendix C presents the general model. The Jarque-Bera test statistic with a p-value of 0.64 (figure 7; Appendix C) fails to reject the null hypothesis of normality of the residuals at the 5% level of significance. The residuals are also homoscedastic as indicated by the Breusch-Pagan-Godfrey test for heteroscedasticity presented in table 4(c) of Appendix C. The error term satisfies the assumptions of classical linear regression model.

The adjusted R-squared of the estimated model (see table 4a) shows that about 69% of the variation in inflation ( tp ) is explained by the combined variations in the regressors and the F-test shows that the overall regression is significant at the 1% level. The Durbin-Watson statistic value of almost two indicates the absence of autocorrelation. The results in table 4 show that inflation in Zimbabwe is significantly influenced by money supply, exchange rate, real income growth, expected inflation and imports value. All these variables are significant at 5% level except real income growth which is found to be significant at the 10% level. The interest rate variable is found to have no influence on inflation in Zimbabwe as shown in Table 4b for the results of the general model. This result contradicts Pindiriri and Nhavira’s pre-dollarization study which found interest rate to be significant at the 5% level. Unlike most of the studies done before dollarization which found money supply growth as the major determinant of inflation in Zimbabwe, this study found the exchange rate to be the most powerful factor influencing post-dollarization inflation in Zimbabwe.

The exchange rate is significant at the 1% level. A unit depreciation of the Rand against the US$ reduces inflation in Zimbabwe by 0.737 units. Depreciation of the Rand will mean Zimbabweans will buy more goods per dollar in South Africa. Imports will be cheaper for Zimbabweans. Since the country is still largely depending on goods from South Africa, more imports from a depreciating Rand will mean increased supply of cheaper imports in the country. This suppresses prices of goods in the domestic market hence reducing inflation.

Money supply, expected inflation, income growth and imports positively influence inflation in Zimbabwe. These variables are significant at the 5% level except income growth which is significant at 10% level. Their signs are theoretically expected. The imports variable has a positive sign because the study has used import value instead of import volumes. In terms of import volumes we expect a negative relationship with inflation but expensive or high-valued imports attract a higher price in the domestic market. In other words, foreign inflation has a positive impact on the domestic price level. The study findings portray that post-dollarization inflation in Zimbabwe is also largely influenced by foreign inflation. A unit increase in import value raises the domestic price level by 0.013 units while


that of money supply and expected inflation raise inflation by 0.037 and 0.317 units respectively. The income growth variable has the largest coefficient of about 5.666 although it is weakly supported by statistical evidence. Table 4a: Regression results of the specific model

Dependent Variable: tp Variable Coefficient Std. Error t-Statistic Prob. Constant 5.209585 1.563730 3.331511 0.0028

1−tp 0.316943 0.149599 2.118620 0.0447

te -0.737082 0.214847 -3.430733 0.0022 stm 0.037136 0.016599 2.237162 0.0348

ty 5.666255 2.761107 2.052168 0.0512

tMports 0.013332 0.005980 2.229234 0.0354

R-squared 0.743196 Mean dependent var 0.020000 Adjusted R-squared 0.689695 S.D. dependent var 1.014175 S.E. of regression 0.564946 Akaike info criterion 1.872684 Sum squared resid 7.659944 Schwarz criterion 2.152924 Log likelihood -22.09026 F-statistic 13.89131 Durbin-Watson stat 2.428931 Prob(F-statistic) 0.000002

6. Summary; Policy Recommendations and Conclusions The intention of the study was to identify the major drivers of inflation in post-dollarized Zimbabwe through the use of an econometric methodology. Overall, the empirical analysis reveals that the major drivers of inflation in Zimbabwe are exchange rate, money supply, expectations about future prices, imports and real income growth. We therefore recommend that when targeting inflation in Zimbabwe more effort must be directed to increasing productivity in order to reduce imported inflation. There is also need to control government spending in salaries as this has a strong impact on increasing real income which will in turn cause demand-pull inflation. Since the Central Bank has no power to influence money supply in the post dollarization period, we suggest that more effort must be directed to the management of imports, government wage bill and productivity in order to effectively control inflation in the country.

The study also notes that although trade opening reduces inflation through increased competition it might result in employment costs. Domestic firms might be pushed out of production as demand shift to cheaper imports. When the first fiscal policy statement of the inclusive government eliminated import duties on food staffs in 2009, the country recorded a negative trend in food price during the first half of the year. Domestic producers of commodities such as poultry and cooking oil among others failed to compete with the cheap imports which resulted in subdued employment creation in the food industry. However when the government re-introduced import duties on food staffs in 2011, the price level of food staff has maintained a positive trend. Despite the policy’s negative impact on inflation management, it stimulated employment creation in the food industry.

Effort to control inflation might lead to increased unemployment, that is, there exists a trade off between the two. It is against this background that we suggest that there is need to model inflation and employment simultaneously in order to develop optimal policies. For example, when designing an import duty we must look at its likely impact on employment and its likely impact on inflation. The policy will only be optimal if its marginal cost in terms of inflation growth is equal to its marginal benefit in terms of employment creation. In conclusion the study suggests that in the future more


interdependent macroeconomic models must be developed simultaneously in order to solve the problem of trade off between some macroeconomic variables. References [1] Blanchard, O. J and S. Fischer. (1989). Lectures on macroeconomics. MIT Press. Cambridge,

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[3] Central Statistical Office of Zimbabwe, Various Publications. CSO, Zimbabwe [4] Dewan, E., S, Hussein and S. Morling. (1999). “Modeling inflation in Fiji”. Working paper

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selective review. Manchester University Press. United Kingdom. [15] Lewis, M. K and P. D. Mizen. (2000). Monetary economics. Oxford University Press. New

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Zimbabwe”. Working Paper Series 2007-10. University of Pretoria, Pretoria [17] Moser, G. G. (1995). “The main determinants of inflation in Nigeria”. IMF Staff Papers, 42(2):

271-89 [18] Ncube, M. (1995). “Financial sector reform and liberalization: The case of Zimbabwe”. African

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Strategic Studies, Zimbabwe


[24] Reserve Bank of Zimbabwe. Monthly, Quarterly and Annual Various Publications. RBZ, Zimbabwe

[25] Seigel, W. F. (1982). Monetary economics. Manchester University Press, United kingdom. [26] Sachs, J and F. Larraine. (1993). Macroeconomics in the global economy. Prentice Hall.

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Working Papers, University of Zimbabwe, Harare. [28] Walsh, C. (1998). Money and monetary policy. MIT Press, Cambridge, Massachusetts, USA. Appendix A Figure 1: Zimbabwe’s growth rates of the natural

logarithms of GDP, CPI and M3 Source: Pindiriri, C and J. Nhavira (2011)

Figure 2: Zimbabwe’s growth rates of inflation, exchange rate and M3(Post-dollarization) Source: Study data from RBZ monthly reports

Figure 3: Scatter graph (Inflation, M3) Source: RBZ monthly reports data

Figure 4: Scatter graph (Inflation, exchangerate) Source: RBZ monthly reports data


Figure 5: Scatter graph (Inflation, Imports) Source: RBZ monthly reports data

Figure 6: Scatter graph (Inflation, interest rate) Source: RBZ monthly reports data

Appendix B Table 1: Descriptive statistics

tp tMports te ti stm ty

Mean 0.020000 3.728667 7.569333 6.521000 8.196667 0.630000 Median 0.200000 2.840000 7.470000 0.000000 5.600000 0.680000 Maximum 1.200000 44.42000 10.00000 140.0000 30.50000 0.780000 Minimum -3.200000 -69.46000 6.670000 -53.33000 -6.000000 0.480000 Std. Dev. 1.014175 19.81271 0.848207 33.57064 8.488023 0.122474 Skewness -2.019406 -1.230355 1.627572 2.415240 1.202102 -0.229091 Kurtosis 7.092540 7.958312 5.308558 10.26688 3.998773 1.456599 Jarque-Bera 41.32611 38.29994 19.90675 95.17641 8.472175 3.240021 Probability 0.000000 0.000000 0.000048 0.000000 0.014464 0.197897 Observations 36 36 36 36 36 36

Source: Study data Post versus Pre-Dollarization Variations

Table 2: Variation and normality measurements before and after dollarization

Standard deviation Jarque-Bera Pre-dollar Post-dollar Pre-dollar Post-dollar

Variable

tp 4.767 1.014 35.781 41.326

te 5.050 0.848 54.495 19.907

ty 0.236 0.122 2.090 3.240 stm 7.561 8.488 279.505 8.472

ti 1.933 33.571 47.631 95.176

tMports - 19.813 - 38.300 Source: Study data and Pindiriri and Nhavira (2011)


Appendix C Table 3: Stationarity tests (Unit root tests) Inflation Growth

ADF Test Statistic -3.620498 1% Critical Value* -2.6453 5% Critical Value -1.9530 10% Critical Value -1.6218

*MacKinnon critical values for rejection of hypothesis of a unit root. M3 Growth


*MacKinnon critical values for rejection of hypothesis of a unit root. Exchange Rate Growth


*MacKinnon critical values for rejection of hypothesis of a unit root. Interest Rate Growth


*MacKinnon critical values for rejection of hypothesis of a unit root. Imports Growth


*MacKinnon critical values for rejection of hypothesis of a unit root. Real Income Growth (in levels)

ADF Test Statistic -0.823215 1% Critical Value* -3.6752 5% Critical Value -2.9665

10% Critical Value -2.6220 *MacKinnon critical values for rejection of hypothesis of a unit root. GDP Growth (First Fifferences)


*MacKinnon critical values for rejection of hypothesis of a unit root.


Table 4b: Regression results of the general model

Dependent Variable: tp Method: Least Squares Date: 02/06/12 Time: 15:58 Sample(adjusted): 2009:02 2011:07 Included observations: 35 after adjusting endpoints Variable Coefficient Std. Error t-Statistic Prob. C 5.056098 1.595915 3.168149 0.0043

1−tp 0.330084 0.152389 2.166059 0.0409

te -0.720172 0.218525 -3.295610 0.0032 stm 0.039724 0.017184 2.311648 0.0301

ty 0.014894 0.006446 2.310521 0.0302

tMports 7.700679 4.034999 1.908471 0.0689

ti -0.003223 0.004616 -0.698166 0.4921 R-squared 0.748526 Mean dependent var 0.020000 Adjusted R-squared 0.682924 S.D. dependent var 1.014175 S.E. of regression 0.571077 Akaike info criterion 1.918380 Sum squared resid 7.500977 Schwarz criterion 2.245326 Log likelihood -21.77569 F-statistic 11.41010 Durbin-Watson stat 2.435724 Prob(F-statistic) 0.000006

Table 4c: Heteroscedasticity test for residuals

Heteroskedasticity Test: Breusch-Pagan-Godfrey F-statistic 1.145710 Prob. F(6,23) 0.3683 Obs*R-squared 6.903192 Prob. Chi-Square(6) 0.3299 Scaled explained SS 2.979984 Prob. Chi-Square(6) 0.8114

Figure 7: Normality test for residuals

0

1

2

3

4

5

6

7

8

-1.00 -0.75 -0.50 -0.25 0.00 0.25 0.50 0.75 1.00 1.25

Series: ResidualsSample2009M0220 11M07Observations 30

Mean 4.76e-16Median 0.011406 Maximum 1.111514 Minimum -0.866853 Std. Dev. 0.508701 Skewness 0.332498 Kurtosis 2.468861

Jarque-Bera 0.905409 Probability 0.635906

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