Dynamics of Inflation in Uganda

Alain Kabundi

No

152 - August 2012

Correct citation: Kabundi, Alain (2012), Dynamics of Inflation in Uganda, Working Paper Series N° 152 African

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Dynamics of Inflation in Uganda

Alain Kabundi1

1 Alain Kabundi University of Johannesburg

AFRICAN DEVELOPMENT BANK GROUP

Working Paper No. 152 August 2012

Office of the Chief Economist

Abstract

This study identifies main factors

underlying inflation in Uganda, both in

the long - and short-rung, using monthly

data from January 1999 to October

2011. It uses a single-equation Error

Correction Model (ECM) based on the

quantity theory of money including both

external and domestic variables. The

main finding is that both external and

domestic factors explain dynamics in

inflation in Uganda. Over the long-run,

monetary aggregate, world food prices,

and domestic supply and demand effects

in agricultural sector are main

determinants of inflation in Uganda.

While money growth, world food prices,

and energy prices, combined with

domestic food prices have short-term

impact on inflation. Finally, the study

finds evidence of inflation inertia which

can be attributed to expectations of

agents and/or inflation persistence.

Keywords: Uganda, Inflation, Error Correction Model, World food prices, Quantity theory of

money, Money demand, Food supply.

JEL classification: E31, F41, O55

5

Introduction

East Africa witnessed in October of 2011 a considerable surge in inflation reaching on average 20%. This rise in price has been an issue of concern for policymakers and the general public. In Ethiopia inflation rate reached 34%, and inflation attained its highest value of 18.9% in Kenya the very same month. Tanzania was not an exception to the rule. It witnessed a sharp rise in inflation with a maximum of 17.9 in October 2011. Uganda recorded the second highest level of inflation in the region hitting 30.5% during the same period. As stressed by the IMF report of 2011, such an increase in inflation has negative implications for the countries at large and particularly for the poor. Given that the majority of the population lives in rural part of these countries, the consequences can be enormous. It erodes the standard of living of the population and hence it can lead to political unrest of the same magnitude to those that occurred in the Maghreb and the Middle East. Recent studies2 have identified several factors underpinning sudden rise in inflation in developing countries, namely, external factors, internal factors, and accommodative policy in the form of exaggerate rise in money supply. External factors refer to rise in world food prices and world energy prices. The fact that most of developing countries import a considerable amount of food, a rise in world food prices is translated directly to an increase in domestic food prices. As food account for large proportion of basket of an average household in these countries, an increase in domestic food prices leads in turn to a general increase in prices. Similarly, world energy price shock, such as oil price, affect domestic prices almost instantaneously. Internal factors generally refer to supply-side constraint, represented by agricultural shocks. Periods of drought, put upward pressure on food prices and hence on domestic price level. These shocks can also be captured by seasonal pattern in agricultural production. Dry seasons are followed rise in inflation, while inflation is subdued during raining seasons. When analysing determinants of inflation in Chad and Mali, Diouf (2007) find that average rainfall explains significantly inflation. Finally, accommodative policies, especially those followed by massive injection of money in the economy, generally put upward pressure on prices. Empirically, the Phillips curve and the quantity theory of money are main frameworks used by economists to analyse inflation dynamics. The former is popular in analysing inflation in advanced economies, due mainly to the fact that inflation in these countries is essentially due to high aggregate demand which boosts employment. The rise in employment in turn puts pressure on wages and hence on overall price. Durevall et al. (2012) state clearly that this analysis is less likely in countries that predominantly dependent on agricultural sector with huge informal sector, and a low degree of unionisation of the labour market. In this set up, it is difficult to link the increase in aggregate demand to low unemployment and hence rise in wages. In addition, developing countries depict a strong negative relationship between business cycle and inflation. In general, an expansionary period is a result of positive shock from agricultural sector, which drives prices down. Hence, the quantity theory of money is more appropriate in anlysing dynamics of inflation in developing countries, in general, and in Uganda in particular. Like most of East African countries, Uganda has experienced recently a rise in inflation, reaching a maximum of 30.5% in October of 2011 from nearly 0% inflation a year earlier. The question arises as to what are the main drivers of inflation in Uganda. This paper attempts to answer to this poignant question using a single-equation Error Correction Model (ECM), proposed by Durevall et al. (2012), which includes, besides money aggregate, domestic and foreign variables. Nachega (2001) demonstrates that both domestic and

2 See for example, Durevall et al. (2012), IMF (2011), Leoning (2011), and Diouf (2007).

6

foreign factors are important determinant of inflation in Uganda. He establishes a stable money demand function and linkage between domestic and foreign interest rates. Expansionary macroeconomic policies which result in rise in monetary aggregate tend to be inflationary. However, he does not examine the impact of agricultural sector on inflation. Most recently, studies2 on inflation in Africa find evidence that inflation in most of African countries is caused by increase in world food prices and energy prices. The rationale is, most African countries are small open economies with a large agricultural sector. Food prices represent a considerable proportion in basket of an average household. Rise in world food prices and energy prices have direct and positive effects on domestic prices. In addition to commodity prices, these studies find that weather-related factors such as rainfall or drought, shortage in agricultural production to be important determinants of inflation. The drought witnessed recently in the horn of Africa coincides with a period of high inflation in the region. Finally, the expectations of economic agents and the stickiness nature of prices can also explain dynamics of inflation in Uganda. Most studies, such as Diouf (2007), Kinda (2011), and Davoodi et al. (2012) use the Structural VAR approach to examine inflation dynamics in Africa. The limitations of this approach are can be attributed to first of all difficulty of getting relevant data for most of African countries, since these models are very sensitive to degree of freedom. Furthermore, the SVAR used seldom examine both long - and short-run determinants of inflation, unless one combines long – and short-term restrictions in a Structural Vector Error Correction Model (SVECM). The single-equation ECM approach used in this study enables the identification of equilibrium relationship and short-term dynamics in inflation. It does not have a degree-of-freedom issue encountered in other studies. The framework accommodates domestic and foreign variables, and examines equilibrium relationship of inflation while taking into account short-term dynamics. This paper contains three findings. First, over the long-run domestic and foreign variables are important determinants of inflation in Uganda. As suggested by Nachega (2001), monetary aggregate portrays an equilibrium relationship with Inflation. It means that expansionary policy that drives up money supply is inflationary over the long-run. There is evidence of considerable rise in real money growth, attaining a maximum of 36% in November of 2010, prior to recent rise in inflation. Subsequently, the Bank of Uganda adopted a contractionary policy before seeing the inflation coming down. Besides, the results support previous studies findings pointing to agricultural supply shocks as crucial for inflation in Uganda. Constraints on agricultural production together with high demand both domestically and from neighbouring countries push domestic food price and hence creates a rise in overall price level, given high percentage share of food price in Consumer Price Index (CPI). However, the study is silent regarding the effects of seasonal pattern of agricultural production on price. Lastly, the paper identifies external factors, mainly world food price and energy prices, key factors in explaining equilibrium inflation in Uganda. Like most of countries in the region, Uganda is not an exception, in that movements in world food and energy prices are directly transmitted to country via import prices or prices of internationally traded goods. Second, like in the long-run, internal and external factors drive inflation in the short-run. We identify Ugandan food prices and monetary growth as key domestic drivers, while the world food prices affect inflation also in short-term. Finally, the paper finds evidence of inflation inertia due possibly to persistence in expectations of agent, since they are backward looking, and stickiness nature of price in the country.

2 Durevall and Ndung’u (2001) on Kenya, Diouf (2007) on Mali, Kinda (2011) on Chad, and Durevall et al. (2012) on Ethiopia

7

The remainder of the paper is as follows. Section 2 gives a background of inflation in Uganda. It describes the recent rise of inflation and depicts a relationship with the key identified factors. The ECM is discussed in Section 3. Section 4 discusses the data used, their sources and their transformation. In addition, it discusses the results obtained from model elaborated in Section 3. The last section concludes the study and provides some policy recommendations. Inflation in Uganda Recently East Africa has experienced a period of increasing inflation attributed to both domestic and external factors. Particularly in Uganda, the IMF (2011) points to three principal causes of rise in inflation, namely, higher food and fuel prices, supported by accommodative monetary policy. Rise in food prices is a result of supply and demand constraints coupled with an increase in world food prices. It is clear from Figure 1 that inflation in Uganda plummets in September of 2009 as a result of the recent financial crisis, following a sharp decrease in food inflation. A year after food price inflation starts rising again after attaining a minimum of -10%. The increase in food price inflation puts an upward pressure on overall inflation, reaching a maximum of 27% in September of 2011. In addition, the region has experienced a period of food shortage due to adverse weather conditions. Hence, the shortage of supply of food causes an increase in domestic price of food. It is evident from Table 1, that food price inflation is a major contributor to the basket of an average household, with a weight of 27. Non-food inflation seems subdued in periods preceding the downturn, but it is on increase most recently and lags dynamics in both food price and overall inflation. As with food prices, the IMF (2011) identifies energy prices, especially fuel price as the second determinant of inflation dynamic in Uganda. According the IMF report recent rise in petrol prices has put pressure in fuel prices in most of African countries, which is subsequently passed on to the consumer, resulting in a general rise in prices. However, Figure 1 does not provide evidence supporting the importance of energy prices. Domestic energy price does not lead inflation in Uganda, on the contrary it lags. Besides food and fuel prices, the IMF report argues that accommodative monetary policy, in the form of massive monetary expansion, has contributed somewhat to recent surge in inflation. The government responded to a combination decrease in inflation and output gap in September of 2009 with massive quantitative easing and money growth reached a maximum of 36% in November of 2011. As a result the currency depreciated and hence pushing the domestic price up even further. The central bank reacted with a contractionary monetary policy by increasing short-term interest rates by 700 basis points. Eventually, money growth declines steadily into negative, the currency appreciates, and eventually inflation comes down.

8

Figure 1: Domestic Inflation

Figure 2: Domestic Food and Foreign Prices

-20

-10

0

10

20

30

40

501999M01

1999M07

2000M01

2000M07

2001M01

2001M07

2002M01

2002M07

2003M01

2003M07

2004M01

2004M07

2005M01

2005M07

2006M01

2006M07

2007M01

2007M07

2008M01

2008M07

2009M01

2009M07

2010M01

2010M07

2011M01

2011M07

Non-Food

Food

Energy

Inflation

Table 1: Consumer Price Index, (Base: 2005/2006 =100)

Component

Food

Beverages and tobacco

Clothing and footwear

Rent, Fuel and utilities

H.hold and personal goods

Transport and communication

Education

Health ,entert. & Others

All items index

16.83

100.00

Weight

27.16

4.72

4.43

14.84

4.50

12.83

14.69

-20

-10

0

10

20

30

40

1999M

01

1999M

07

2000M

01

2000M

07

2001M

01

2001M

07

2002M

01

2002M

07

2003M

01

2003M

07

2004M

01

2004M

07

2005M

01

2005M

07

2006M

01

2006M

07

2007M

01

2007M

07

2008M

01

2008M

07

2009M

01

2009M

07

2010M

01

2010M

07

2011M

01

2011M

07

Inflation

Real Money growth

REER

9

Nevertheless, domestic factors are not the only causes underpinning surge in inflation in East Africa, in general, and in Uganda in particular. Leoning (2011) and Durevall et al. (2012) find that inflation in agricultural economies are associated with sharp rise in foreign prices, which account for import prices or prices of internationally traded goods. Figure 3 depicts domestic food prices together with world food price and world energy price. It is clear that since 2007 domestic food prices follow closely both world food and energy prices. Both foreign prices display an increase in January of 2007, which seems to be translated into domestic food price increase a year later. World inflation declines steadily in 2008 as a consequence of the financial crisis which subsequently attains the real sector. The effect is transmitted in Uganda in February of 2009, followed by a small recovery and then a sharp fall in September of the same year. Both world food and energy prices depict an upward trend in the second half of 2010, followed immediately by a rise domestic food price. It is even evident from Figure 4 that dynamics in inflation in Uganda is associated with development in domestic food prices, which in turn respond closely to global shocks. Figure 3: Domestic Food and Foreign Prices

-80

-60

-40

-20

0

20

40

60

80

100

1999M

01

1999M

07

2000M

01

2000M

07

2001M

01

2001M

07

2002M

01

2002M

07

2003M

01

2003M

07

2004M

01

2004M

07

2005M

01

2005M

07

2006M

01

2006M

07

2007M

01

2007M

07

2008M

01

2008M

07

2009M

01

2009M

07

2010M

01

2010M

07

2011M

01

2011M

07

Food

World Food

World Energy

10

Figure 4: Domestic Prices and Foreign Prices

Model Recent studies on inflation (Durevall et al., 2012 and Leoning, 2011) show that the Phillips curve approach, which is mainly used to estimate inflation in developed economies, is not appropriate for agricultural economies, like Sub-Saharan African economies. The Phillips curve argues that a rise in aggregate demand results in higher employment, which in turn exerts pressure on wages first and then to general level of price. It is less likely that this framework describes reality faced by most East African countries. Durevall et al. (2012) argue eloquently that these economies are characterized by massive self - and underemployment, large informal sector, and a low degree of unionization of the labour market. Like Durevall et al. (2012) and Leoning (2011), most studies use the quantity theory of money. This framework accounts for role of money as the major determinant of inflation, together with some supply shocks. The current study follows closely the methodology proposed by Durevall et al. (2012). It takes into account both short- and long-run determinants of inflation in Uganda. Hence, the empirical strategy includes international prices, monetary aggregate, and the role of agricultural supply shock. Long-run relationships are estimated as follows:

Rypm 210 (1)

1 wpepnf (2)

2 wfpepf (3)

3 wpeepe (4)

where m is the log money supply M3, p is the log of the domestic price level, y is the log of the real output, R is the deposit rates, pnf, pf, and pe are the log of domestic non-food price, food price, and energy prices, e is the log of real exchange rate, wp, wfp, and wpe are log of world non-food, food, and energy prices, and τ1, τ2, and τ3 are potential trends in relative prices.

-80

-60

-40

-20

0

20

40

60

80

1001999M

01

1999M

06

1999M

11

2000M

04

2000M

09

2001M

02

2001M

07

2001M

12

2002M

05

2002M

10

2003M

03

2003M

08

2004M

01

2004M

06

2004M

11

2005M

04

2005M

09

2006M

02

2006M

07

2006M

12

2007M

05

2007M

10

2008M

03

2008M

08

2009M

01

2009M

06

2009M

11

2010M

04

2010M

09

2011M

02

2011M

07

World FoodWorld EnergyInflation

11

Equation 1 represents equilibrium in monetary sector. Nachega (2001) argues that money demand in Uganda can be explained both output and exchange rate or inflation. The latter variables represent the cost of holding money. Given that the financial sector is not well-developed in Sub-Saharan Africa, both depreciation and inflation are good proxies of such a cost. Besides these four factors, supply side effects are non-negligible determinant of inflation in East Africa. We use production of cereal as a proxy of agricultural production. The long-run measure of agricultural production is obtained using its cycle component, after removing the trend. Following, Durevall et al. (2012), we combined domestic and external factors in a single regression, which deals with both short- and long-run

t

tt

k

oi

iti

k

oi

iti

k

oi

iti

k

oi

iti

k

oi

iti

k

oi

iti

k

i

itit

vpewpeepfwfpepnfwpe

Rypmagwpewp

wfpeRmpp

)()()(

)(

342312

121118

1

7

1

6

1

5

1

4

1

3

1

2

1

1

1

(5)

where all variables are in logs, Δ is the first difference operator, and vt is the error term, which follows an independent and identically distributed normal distribution with zero mean and constant variance. Data and Empirical Results

Data

Domestic prices, the real effective exchange rate, and monetary aggregate (M3) are obtained from the Bank of Uganda. We interpolate annual real GDP to obtain monthly series of output3. We use annual forecast from the IMF to compute 2011 observations. In addition, we use cereal production to obtain as a proxy of agricultural production. The cereal production was obtained from the FAO. Given that these are only observed annually, we interpolate them to calculate the monthly component. In addition, we detrend cereal production, using the Hodrik-Prescott approach, to compute their cyclical component. Similarly, we use the Hodrik-Prescott approach to calculate the detrended components of relative prices. Data cover the period starting from January 1999 to October 2011. We use the DF-GLS proposed by Elliot, Rothenberg, and Stock (1996) and the KPSS developed by Kwiatowski, Phillips, Schmidt, and Shin (1992) to assess unit root in all series. All series are integrated of order 1.

3 Like Durevall et al. (2012) the interpolated GDP constructed using the random walk option. We add the IMF (2011) forecast of 2011 to reduce the end-sample issue related to the use of Hodrick-Prescott filter. It is important to note that this approach is not perfect as it misses monthly fluctuations in the data, which happen to be necessary to extract cyclical component in GDP and agricultural production.

12

Empirical Results

Table 2: Monetary Sector

m-p y Δ12e4

1.00 -1.48 -0.007 [-26.24] [-3.69]

Adjustment coefficients

-0.16 [-2.83]

Note: t-statistic are in brackets

Table 2 presents results of the error correction model in as specified in Equation 1. The results indicate the presence of long-term relationship in money demand equation. Furthermore, the Johasen (1991) test indicates a presence of one cointegrating equation. The adjustment coefficient is negative and statistically significant. It means 16% of discrepancy between long-term and short-term real money growth is eliminated within a month. The adjustment process is relatively slow. Unlike Durevall et al. (2012), we find evidence that exchange rate in Uganda acts as cost of holding money. Nachega (2001) uses the short-term interest rate as cost of holding money. However, since the financial market in Uganda is small, we prefer using the exchange rate or inflation. The long-term dynamics in money is then used in Table 3 to assess its impact on inflation. Again, the results obtained in Table 3, in contrast to Durevall et al. (2012), show evidence of long-term relationship between money aggregate and inflation in Uganda. It means that an expansionary monetary policy aimed at supporting the real sector is inflationary. These results confirm the long-term relationship between real money growth and inflation as depicted in Figure 2. A percentage increase in monetary growth induces a 0.03% rise in inflation over the long-run. The results support the hypothesis that expansionary monetary policy in Uganda puts upward pressure on price. Most recently the Bank of Uganda embarks in expansionary monetary policy in reaction to a decline in output gap in order to boost the economy which was somewhat affected by the recent financial crisis. But, the policy was not immune to unexpected negative effects. Inflation soars to its highest value in more than a decade. In addition, world food price affects inflation in Uganda over the long-run. The effect is statistically significant. However, it is difficult to isolate the impact of world energy price on domestic inflation, given its closer link with world food price (see Figures 3 and 4). In general, a rise energy price is transmitted directly to an increase in food price. Again, food constitutes an important component of imports. Therefore, a rise in world food prices translates directly to a subsequent increase in domestic food prices. Similarly, change in price of oil has direct effects in the country. Like most of East African countries, oil imports represent a significant proportion of imports in Uganda. Likewise, agricultural supply shocks have significant and long lasting effects on inflation in Uganda. The negative and statistically significant coefficient indicates that periods of good harvest put downward pressure on inflation, and conversely periods of adverse agriculture weather conditions, such as the one experienced recently, push prices up. From Table 3, agriculture cycle portrays the same effect as world food price in the long-run. It means external shocks have the same effects as agricultural supply shocks. The East African region as a whole is sensitive to agricultural supply

4 Δ12e is the annual growth rate of exchange rate.

13

shocks. However, the study is silent regarding the impact of seasonal pattern of agricultural production in inflation given the frequency used. Durevall et al. (2012) find similar results for Ethiopia, even though the magnitude is different. It is understandable that Ethiopia, with a large part of desert, is more affected by agricultural constraints than other countries, except for Eritrea. Their results portray coefficients of -0.07 for agricultural gap and 0.047 for world food price component. It is essential, especially in East Africa, to establish, in addition to cyclical effect of agricultural output, the influence of dry season on price. Equally important is the asymmetric manner in which dry season and raining season affect price. Unfortunately, due to data limitation, agricultural production is only available annually, and hence we could not investigate such an important aspect of inflation dynamic.

The results also indicate sign of inflation inertia depicted by lagged inflation ( 1 tp ). 1 tp accounts

for both other domestic factors that are not explicitly specified and inflation expectations (see Durevall et al., 2012 and Leoning, 2011). The inertia seems strong and significant. Moreover, lagged inflation explains stickiness in prices, periods of high inflation tend to persist and conversely periods of low inflation will also persist. External factors, such as world food and energy prices affect inflation in the short-run. They do not only affect prices in long-run, but their effects are also felt in short-run. The impact of world energy price is transmitted after a monthly, while it takes seven months for world food price to be

Variables Δp

EC-Monetary 0.03

[2.35]

EC-External 0.01

[2.34]

Agricultural gap -0.01

[-2.11]

Lagged Inflation 0.24

[3.40]

Food Imports 0.05

[2.00]

Energy Imports 0.02

[1.92]

Food Domestic 0.13

[2.16]

Energy Domestic -0.17

[-3.70]

Lagged Money 0.03

[2.63]

Constant -0.03

[-2.19]

Note: t -statistics are in brackets.

Table 3: Empirical Results

14

transmitted into inflation in Uganda. Similarly, monetary policy is transmitted to price both in the long-run and over the short-term. Finally, domestic food prices, given their importance in the composition of CPI, exhibit significant effects on inflation in the short-run.

Conclusion and Policy Recommendations Both external factors and domestic factors are main factors underlying inflation in Uganda. The current study, using a single-regression model which includes both long – and short-run determinants find that monetary aggregate and world food prices have long lasting effects on inflation in Uganda. In addition, movement in inflation attributed to domestic supply and demand effects in the agricultural sector. Another important factor explaining dynamics in inflation is the inflation inertia. Over the short-run money growth, world food and energy prices, combined with domestic food prices seem to have non-negligible effects. Given these findings, the current study proposes a close monitoring of dynamics in world food and energy prices in order to curtail their secondary effects. Moreover, policymakers should push for massive investment in agricultural sector, especially in rural areas. This policy will assist to mitigate effects of adverse climatic conditions which most of countries in the region have been subject to. Another benefit of such action is employment creation in rural parts of the country where unemployment is rampant. In addition, the country should adopt policies which advocate for massive production in agriculture to avoid scarcity in periods of adverse weather conditions. Finally, the independence monetary policy authority is crucial. The results clearly point to short – and long-run effects of monetary aggregate on inflation. Hence, sound monetary and fiscal policies should strive for macroeconomic stability. In other words policymakers should be reluctant to pursue programs that are inflationary and/or can result in higher deficit. References Davoodi, H.R., Dixit, S., and Pintor, G. (2012) “Monetary Transmission Mechanism in the East African Community: Implications for Monetary Union,” forthcoming IMF Working Paper Diouf, M.A. 2007. “Modeling Inflation for Mali.” IMF Working Paper WP/07/295. Durevall, D. and Ndung'u, N. (2001) “A Dynamic Model of Inflation of Kenya, 1974-96.” Journal of African Economies 10(1): 92-125. Durevall, D., Loening, J.L., and Birru, Y.A. (2012) “Inflation Dynamics and Food Prices in Ethiopia,” Mimeo Elliott, G., T.J. Rothenberg, and Stock, J. (1996) “Efficient Tests for an Autoregressive Unit Root,” Econometrica 64: 813–836. IMF (2011) “Uganda,” IMF Country Report 11/308 Johansen, S. (1991) “Estimation and Hypothesis Testing of Cointegration Vectors in Gaussian Vector Autoregressive Models,” Econometrica 59: 1551-1580. Kinda, T (2011) “Modeling Inflation in Chad,” IMF Wprking Paper 11/57 Kwiatowski, D., P.C.B. Phillips, P. Schmidt, and Shin, Y. (1992) “Testing the Null Hypothesis of Stationarity Against the Alternative of a Unit Root: How Sure Are We That Economic Time Series Have a Unit Root?” Journal of Econometrics 54:159–178. Loening, J.L (2011) “Middle East and North Africa Countries’ Vulnerability to Commodity Price Increases,” Mimeo Nachega, J-C (2001) “Financial Liberalization, Money Demand, and Inflation in Uganda,” IMF Working Paper 01/118.

15

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