Malawi: Selected Issues and Statistical Appendix

International Monetary Fund

doi:10.5089/9781451828016.002.A001

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Malawi: Selected Issues and Statistical Appendix

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International Monetary Fund

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Publication Date:: 16 Aug 2002

eISBN:: 9781451828016

Language:: English

Keywords:: ISCR; CR; Malawi; export; ERER in Malawi; appreciated exchange rate; open economy; dickey-fuller statistics; flotation of the exchange rate; Real effective exchange rates; Exchange rates; Terms of trade; Government consumption; Africa

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This Selected Issues paper estimates the path of the equilibrium real exchange for Malawi. Based on a dynamic model of a small open economy, the paper identifies and discusses the dynamics between certain fundamental variables and the real exchange rate. It also investigates the presence of a long-term relationship between the real exchange rate and the explanatory variables, and estimates both the equilibrium real exchange rate and the speed at which it converges toward its equilibrium level. The paper also discusses episodes of discrepancies between the real effective exchange rate and its equilibrium level.

Abstract

I. Estimation of the Equilibrium Real Exchange Rate for Malawi¹

1. This section estimates the path of the equilibrium real exchange for Malawi. Based on a dynamic model of a small open economy, the section identifies and discusses the dynamics between certain fundamental variables and the real exchange rate. It also investigates the presence of a long-run relationship between the real exchange rate and the explanatory variables and estimates both the equilibrium real exchange rate and the speed at which it converges towards its equilibrium level. The section concludes with a short discussion on episodes of discrepancies between the real effective exchange rate and its equilibrium level.

2. The Malawi equilibrium exchange rate is treated as time varying defined by a set of long-run fundamental determinants. This approach is chosen for two reasons. First, the real effective exchange rate (REER) series² contains a unit root (i.e., it is I(1)), so a traditional purchasing power parity (PPP) approach is not applicable. Second, certain characteristics of the Malawian economy, such as the importance of one export commodity (tobacco), capital account restrictions, and the lack of a forward foreign exchange market, affect the plausibility of interest rate parities and render industrial country models less useful. As a result, this section uses an error-correction model and a technique developed by Gonzalo and Granger (1995) to analyze the fundamental factors affecting the equilibrium real exchange rate and to construct this rate.

A. Definition and Determinants of the Real Exchange Rate

3. This section defines the equilibrium real exchange rate (ERER) as the relative price of nontradables to tradables, which, for given sustainable values of certain fundamental variables, results in internal and external equilibrium. Internal equilibrium occurs when the market for nontradables clears in the present and is expected to clear in the future, while external equilibrium holds when present and future tradable goods markets clear.

4. Edwards’s (1988 and 1989) dynamic model of a small, open economy in which both tradables and nontradables are exchanged, provides a coherent framework to identify the fundamental variables that are associated with an ERER.³ In its empirical version, the model allows for both real and nominal factors, but only real factors—the “fundamentals”—can influence the equilibrium exchange rate. Edwards’s original model was used to describe nominal misalignment in fixed exchange rate regimes, in particular in small, low-income, open economies.

5. Edwards’s model is particularly suited to identify the fundamental variables that determine the Malawian equilibirum real exchange rate. First, Malawi is a low-income country, where public expenditure accounts for almost one-third of GDP, driven partly by large flows of development assistance. It is also relatively open, with imports and exports exceeding 50 percent of GDP, and dependent on international tobacco exports. Malawi has an underdeveloped industrial base and is very dependent on imported goods, both for consumption and investment. Finally, although the kwacha was floated in the mid-1990s, it has since undergone periods of remarkable stability vis-à-vis the U.S. dollar. The key long-term explanatory variables derived from Edwards’s model and used in this analysis are briefly discussed below, as are the expected signs of their coefficents:

Government consumption excluding salaries and wages as a share of GDP.⁴ The expected sign is ambiguous, depending on the share of tradables and nontradables in government consumption. If government spending is mainly directed toward nontraded (traded) goods, the effect is expected to be positive (negative). Empirical studies, based on a similar framework to this section, including Cerra and Saxena (2000) on India and Mongardini (1998) on Egypt, found that the impact of government spending on the real exchange rate was positive.
Government salaries and wages as a share of GDP. The expected sign is negative, as civil servants constitute the middle-income class, and any real increment in wages and salaries is expected to increase consumption of (imported) tradables more than nontradables.
Investment. The expected sign is ambiguous, as supply-side effects depend on the relative ordering of factor intensities across sectors. However, for Malawi, which has a low industrial base and low cost of labor, the sign is most likely negative as investment largely finances tradable (and imported) goods.
Terms of trade of goods. The expected sign is positive. The income effect stipulates that, in the case of a positive terms of trade shock, there will be an increase in the real wage in the export sector, and this sector subsequently expands, leading to a trade surplus, to be restored by a REER appreciation.
Technological progress. The expected sign is positive. The Balassa-Samuelson effect stipulates that higher differential productivity growth in the tradables sector improves wages in this sector, which subsequently expands, causing a trade surplus. To restore the internal and external balance, the REER must appreciate. Although the Malawi industrial production index measures production volume, it is used here as a proxy for technological progress, as it measures an expansion or contraction in the tradables sector.
Capital flows. The expected sign is positive. Although an incomplete measure, changes in net foreign assets are used as a proxy for capital flows. Moreover, larger net foreign assets would allow running a larger trade deficit and a more appreciated exchange rate in the future.

B. Data and Key Observations

6. The data reveal a shock to several of the variables in the mid-1990s (Figure I.1). This period was marked by the turmoil associated with the transition to a multiparty democracy and the initiation of an economic reform program, including the flotation of the exchange rate.⁵

Figure I.1.

Malawi: Real Effective Exchange Rate and its Determinants

Citation: IMF Staff Country Reports 2002, 182; 10.5089/9781451828016.002.A001

C. The Empirical Model

7. Edwards’s theoretical model identifies the following “fundamental variables” as the most important ones in determining the ERER: the level and composition of government consumption, external terms of trade, investment, and capital flows.⁶ In addition, a variable has been introduced to capture the Balassa-Samuelson effect (MacDonald and Ricci, 2001 and 2002). Hence, the empirical model for the ERER is

Log (e_{t}) = β_{0} + β_{1} \log (gnwsgdp) + β_{2} \log (gcwsgdp) + β_{3} \log (invdp) + β_{4} \log (totg) + β_{5} \log (techpro) + β_{6} \log (NFA) + ϵ_{t}, & (1)

where the evolution of the logarithm of the real exchange rate (e₁^*) is a function of the logarithms of government spending on wages and salaries as share of GDP (gnwsgdp), government consumption (excluding wages and salaries) as share of GDP (gcwsgdp), investment as share of GDP (invgdp), terms of trade of goods (totg), technological progress (techpro), and capital flows (Δnfa), as well as an error term ε.

8. This analysis focuses on permanent changes in the explanatory variables that bring about changes in the long-run ERER. The observed real exchange rate is composed of two components—the ERER and deviations from the ERER. The ERER is associated with the fundamental variables in their steady state level. Deviations of these variables from their respective steady state level result in deviations from the ERER. Thus, estimating the long-run cointegrating relationship between the real exchange rate and the fundamentals, using the observed values, would yield a biased estimate of the ERER. The econometric approach used in the analysis is described in Appendix II.

D. Econometric Characteristics

9. In order to estimate the empirical model as shown in equation (1), we first test for stationarity of the fundamental variables, then for cointegration, using the Johansen cointegration test (Johansen, 1988), and finally we proceed with the estimation procedure as outlined in Appendix II.

10. Using augmented Dickey-Fuller statistics and selecting the number of lags based on the Schwarz criterion, the results show that all explanatory variables are stationary in the first differences, as is the REER. The difference stationarity of the REER is consistent with other studies of the real exchange rate, and renders the PPP, in its traditional form at least, less useful. In all model specifications tested by using the Johansen cointegration test, the null hypothesis of zero cointegrating equations can be rejected; in some cases there appear to be two cointegrating equations.⁷ The lag length for the error-correction model (ECM) was determined by backward selection, beginning with a lag of four to economize on degrees of freedom. (Table I.1 shows the elasticities of two of the ECMs tested with model 1, including all the variables derived from the theoretical model, and model 2 omitting the two variables that were found to be not significant.

Table I.1.

Malawi: Results from the Cointegrating Equation

Table I.1.

Malawi: Results from the Cointegrating Equation

	Model 1	Model 2
LGCNSWGDP(-1)	−0.42	−0.66
Standard error	0.12	0.16
t-statistics	−3.76	−4.07

LGSWGDP(-1)	0.89	1.17
Standard error	0.13	0.16
t-statistics	7.00	7.27

LTOTG(-1)	−0.21	−0.50
t-statistics	0.10	0.17
t-statistics	−2.04	−2.84

LTECHPRO(-1)	0.09
Standard error	0.26
t-statistics	0.34

LINVGDP(-1)	0.19	0.32
Standard error	0.09	0.15
t-statistics	2.06	2.11

LANFA	0.01
Standard error	0.03
t-statistics	0.34

C	−1.75	−0.21
Standard error	0.59	0.99
t-statistics	−3.00	−0.21

Table I.1.

Malawi: Results from the Cointegrating Equation

	Model 1	Model 2
LGCNSWGDP(-1)	−0.42	−0.66
Standard error	0.12	0.16
t-statistics	−3.76	−4.07

LGSWGDP(-1)	0.89	1.17
Standard error	0.13	0.16
t-statistics	7.00	7.27

LTOTG(-1)	−0.21	−0.50
t-statistics	0.10	0.17
t-statistics	−2.04	−2.84

LTECHPRO(-1)	0.09
Standard error	0.26
t-statistics	0.34

LINVGDP(-1)	0.19	0.32
Standard error	0.09	0.15
t-statistics	2.06	2.11

LANFA	0.01
Standard error	0.03
t-statistics	0.34

C	−1.75	−0.21
Standard error	0.59	0.99
t-statistics	−3.00	−0.21

E. Results

11. The results of the estimation are largely consistent with the theoretical model (Tables I.1 and I.2). Public consumption, excluding wages and salaries, has a positive (appreciating) impact on the real exchange rate, indicating that most government spending in Malawi is directed toward nontradables. In contrast, the long-run impact of wages and salaries on the real exchange rate is negative, confirming that a larger wage bill in terms of GDP tends to put pressure on the external current account. The terms of trade of goods is positively correlated with the real exchange rate, confirming the impact of the income effect. Finally, investment is negatively correlated with the real exchange rate.

Table I.2.

Malawi: Results from Error correction Models with d(LREER) as Dependent Variable

Table I.2.

Malawi: Results from Error correction Models with d(LREER) as Dependent Variable

Variable		Model 1	Model 2
CointEql		−0.39	−0.27
Standard error		0.08	0.06
T-statistics		−5.20	−4.67
DLREER(-1)		0.03	−0.02
Standard error		0.11	0.10
T-statistics		0.30	−0.20
DLREER(-2)		0.10	0.03
Standard error		0.12	0.10
T-statistics		0.91	0.32
DLGCNWSGDP(-1)		−0.22	−0.22
Standard error		0.06	0.06
T-statistics		−3.71	−3.67
DLGCWSGDP(-2)		−0.22	−0.22
Standard error		0.05	0.05
T-statistics		−4.13	−4.28
DLGWSGDPC(-1)		0.18	0.14
Standard error		0.07	0.07
T-statistics		2.60	2.02
DLGWSGDP(-2)		0.12	0.09
Standard error		0.06	0.06
T-statistics		1.89	1.54
DLTOTG(-1)		0.03	0.01
Standard error		0.14	0.13
T-statistics		0.19	0.06
DLTOTG(-2)		−0.22	−0.19
Standard error		0.14	0.13
T-statistics		−1.46	−1.43
DLTECHPRO(-1)		0.02
Standard error		0.09
T-statistics		0.17
DLTECHPRO(-2)		0.01
Standard error		0.09
T-statistics		0.09
DLINVGDP(-1)		0.11	0.12
Standard error		0.08	0.07
T-statistics		1.37	1.71
DLINVGDP(-2)		0.11	0.11
Standard error		0.08	0.07
T-statistics		1.44	1.57
DALNFA(-1)		−0.01
Standard error		0.02
T-statistics		−0.47
DALNFA(-2)		0.02
Standard error		0.02
T-statistics		0.96

Memorandum items:
	R-squared	0.41	0.33
	Adj. R-squared	0.29	0.23
	Sum sq. resids	0.49	0.56
	S.E. equation	0.094	0.09
	F-statistic	3.34	3.57
	Log likelihood	93.66	92.83
	Akaike AIC	−1.92	−1.93
	Schwarz SC	−1.48	−1.61
	Mean dependent	−0.00	−0.00
	S.D. dependent	0.10	0.10

Table I.2.

Malawi: Results from Error correction Models with d(LREER) as Dependent Variable

Variable		Model 1	Model 2
CointEql		−0.39	−0.27
Standard error		0.08	0.06
T-statistics		−5.20	−4.67
DLREER(-1)		0.03	−0.02
Standard error		0.11	0.10
T-statistics		0.30	−0.20
DLREER(-2)		0.10	0.03
Standard error		0.12	0.10
T-statistics		0.91	0.32
DLGCNWSGDP(-1)		−0.22	−0.22
Standard error		0.06	0.06
T-statistics		−3.71	−3.67
DLGCWSGDP(-2)		−0.22	−0.22
Standard error		0.05	0.05
T-statistics		−4.13	−4.28
DLGWSGDPC(-1)		0.18	0.14
Standard error		0.07	0.07
T-statistics		2.60	2.02
DLGWSGDP(-2)		0.12	0.09
Standard error		0.06	0.06
T-statistics		1.89	1.54
DLTOTG(-1)		0.03	0.01
Standard error		0.14	0.13
T-statistics		0.19	0.06
DLTOTG(-2)		−0.22	−0.19
Standard error		0.14	0.13
T-statistics		−1.46	−1.43
DLTECHPRO(-1)		0.02
Standard error		0.09
T-statistics		0.17
DLTECHPRO(-2)		0.01
Standard error		0.09
T-statistics		0.09
DLINVGDP(-1)		0.11	0.12
Standard error		0.08	0.07
T-statistics		1.37	1.71
DLINVGDP(-2)		0.11	0.11
Standard error		0.08	0.07
T-statistics		1.44	1.57
DALNFA(-1)		−0.01
Standard error		0.02
T-statistics		−0.47
DALNFA(-2)		0.02
Standard error		0.02
T-statistics		0.96

Memorandum items:
	R-squared	0.41	0.33
	Adj. R-squared	0.29	0.23
	Sum sq. resids	0.49	0.56
	S.E. equation	0.094	0.09
	F-statistic	3.34	3.57
	Log likelihood	93.66	92.83
	Akaike AIC	−1.92	−1.93
	Schwarz SC	−1.48	−1.61
	Mean dependent	−0.00	−0.00
	S.D. dependent	0.10	0.10

12. The finding that the industrial production index and net foreign assets were not significant might be due to the choice of these variables as proxies for technological progress and capital flows, respectively. Real GDP per capita could have been an alternative proxy for technological progress. However, given that GDP also captures nontradables and agricultural value added that is largely subsistence farming or not exported owing to high transportation costs, the industrial production index appears a more suitable proxy for technological progress. The finding that net foreign assets are not significant in a data set starting in 1980 might be due to tobacco export earnings and balance of payments assistance becoming a substantial part of net foreign assets only during the 1990s.

13. The long-run relationship between the REER and the key explanatory variables can be summarized as follows (Table I.1):

A 1 percent increase in the level of government consumption, excluding wages and salaries, as a share of GDP is associated with an appreciation of the REER of 0.4-0.7 percent.
A 1 percent increase in the level of government wages and salaries as a share of GDP is associated with a depreciation of the REER of 0.9-1.2 percent.
A 1 percent increase in the terms of trade of goods is associated with an appreciation of the REER of 0.2-0.5 percent.
A 1 percent increase in investment as a share of GDP is associated with a depreciation of the REER of 0.2-0.3 percent.

F. Adjustment Speed

14. When there is a gap between the value of the real exchange rate and its equilibrium level, the real exchange rate will tend to converge to its equilibrium level. Depending on the cause of the gap, the adjustment requires that the real exchange rate either move progressively toward a new equilibrium level, or return from its temporary deviation to the original equilibrium value.

15. This study estimates that between 26 percent and 39 percent of the gap is eliminated every quarter, implying that, in the absence of further shocks, half of the gap would be eliminated within five to eight months. This adjustment speed is relatively fast, compared to the half-life of a shock to the real exchange rate in South Africa, estimated to be about 2½–3 years (Ricci, 2002).

G. The Gap Between the Real Exchange Rate and the Equilibrium Level

16. During the last decade, there were several episodes when the ERER and REER were misaligned (Figure I.2).⁸ Two major droughts, in 1992 and 1994, caused food prices to rise substantially, reversing the gains made in reducing inflation. In 1995, the flotation of the exchange rate and the sharp depreciation of the nominal exchange rate, led to an undervaluation of the REER. This was reversed in 1996, when the REER peaked as the Reserve Bank of Malawi (RBM) maintained the nominal exchange rate at MKT 5.3 per U.S. dollar and the expansionary monetary and fiscal policies resulted in high inflation. A subsequent adjustment program had some initial success in bringing down inflation, which was, however, lost in 1999, when the RBM maintained a nominal exchange rate to the U.S. dollar. The REER appears to have been in equilibrium in late 2001 and early 2002.

Figure I.2.

Malawi Actual and Real Effective and Equilibrium Real Exchange Rates

(March 1981 - March 2002, in logs)

Citation: IMF Staff Country Reports 2002, 182; 10.5089/9781451828016.002.A001

H. Conclusion

17. The section shows that the ERER in Malawi is affected by various factors. Government consumption, excluding wages and salaries has a positive impact on the real exchange rate, indicating that most government spending is directed toward nontradables. In contrast, the long-run impact of wages and salaries on the real exchange rate is negative, indicating that a larger wage bill in terms of GDP tends to put pressure on the external current account. The terms of trade of goods is positively correlated with the real exchange rate, confirming the impact of the income effect. Investment appears to be negatively correlated with the real exchange rate.

18. The results also indicate a rapid adjustment speed from any deviation to the real exchange rate from its equilibrium value. The section shows that, in the absence of further shocks, about half the gap between the actual value of the REER and its equilibrium values could be eliminated within five to eight months.

References

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APPENDIX I Variables: Definitions and Sources

19. The quarterly data set from March 1980 to March 2002 consists of the following variables:

LGNS WGDP: Natural logs of government consumption excluding wages and salaries as share of GDP. Sources: IMF, International Financial Statistics (IFS); and staff estimates.
LGSWGDP: Natural logs of government wages and salaries as share of GDP. Sources: IFS; and staff estimates.
LINVGDP: Natural logs of investment as share of GDP. Source: National Statistical Office, Malawi.
LTOTG: Natural logs of terms of trade of goods. Sources: IFS; and staff estimates.
LTECHPRO: Natural logs of the index of industrial production. Source: National Statistical Office, Malawi.
LΔNFA: Natural logs of changes in net foreign assets. Sources: IFS; and Reserve Bank of Malawi.

APPENDIX II: Cointegration and Orthogonal Decomposition

20. This section relies on an econometric technique developed by Gonzalo and Granger to decompose the observed real exchange rate (RER) into a transitory and a permanent component. The estimated ERER is taken to be the permanent component, while the transitory component reflects deviations from equilibrium.

21. In order to understand the link between equilibrium and cointegration, it is useful to depart from the theory of purchasing power parity (PPP), which implies a constant value of ERER. In econometric terms, PPP implies a stationary process for the RER (i.e., that the RER is integrated of order zero (1(0)). However, if the RER contains a unit root (i.e., it is an I(1) variable), no constant equilibrium can be defined for RER, and the PPP hypothesis is rejected.

22. Failure of PPP to hold does not necessarily imply that no equilibrium exist,, but rather that the equilibrium may be time varying. In this case, if log (gnwsgdp), log (gwsgdp), log (invgdp), log (totg), log (techpro), and log (nfa) are cointegrated, the RER will fluctuate around a time-varying equilibrium characterized by the long-run cointegrating relationship [1-β₁-β₂-β₃-β₄-β₅-β₆]. Thus, the presence of cointegration among a set of variables allows for the presence of a time-varying equilibrium and presents a very desirable property: it allows for the decomposition of the relationship among the variables into two components. The permanent component, which would be I(1), describes the long-run properties of the relationship among the variables and can be identified with a time-varying equilibrium path; a transitory component, which would be I(0), corresponding to deviations over time from the permanent component and would represent departures of the fundamentals from their steady state values.

23. Gonzalo and Granger (1995) propose a way of solving the econometric problem so that the permanent (equilibrium) component of the key endogenous variable, the real exchange rate, can be constructed by means of the permanent components, rather than the actual values of the fundamental determinants. Their approach is to derive a decomposition where the transitory component does not “Granger cause” the permanent component in the long run, and where the permanent component is a linear component of contemporaneous observed variables. The first restriction implies that the changes in the transitory component will not have an effect on the long-run values of the variables. The second restriction makes the permanent component observable and assumes that the contemporaneous observations contain all the information necessary to extract the permanent component.

24. The Gonzalo and Granger procedure is as follows:

Let X_t be a (px1) vector of I(1) series with mean 0 and assume that there exists a matrix α_pxr of rank r such that α’X_t is I(0). Then the vector X_t has the following ECM representation:

\begin{matrix} Δ X = \underset{p x r}{γ} \underset{r x p}{α'} X_{t - 1} + Σ_{t = 1}^{\infty} Γ_{t} Δ X_{t - 1} + ϵ_{t}, & (A 1) \end{matrix}

where Δ is the lag operator. The elements of X_t consist of (p-r) I(1) variables, f_t, known as the common factors, plus some I(0) components, as follows:

\begin{matrix} \underset{p x l}{X_{t}} = \underset{p x k}{A_{1}} \underset{k x l}{f_{t}} + \underset{p x l}{\tilde{X}}, & (A 2) \end{matrix}

where k = p-r, Gonzalo and Granger define A₁f_t and $\tilde{X_{t}}$ as the permanent and temporary components of X_p respectively, such that only the innovations from the permanent component can affect the long-run forecast of X_t. Innovations to the temporary components of all the endogenous variables, including the fundamental determinants, do not affect the long-run, i.e., “equilibrium” forecast of X_t.

25. The only linear combination of X_t that precludes $\tilde{X_{t}}$ from having any long-run impact on X (the conditions sufficient to identify the common factor f_t) is given by:

\begin{matrix} f_{t} = \underset{k x p}{γ' ⊥} \underset{p x l}{X_{t}}, & (A 3) \end{matrix}

where γ_⊥ is the orthogonal complement of γ(i.e. γ⊥γ = 0) and k = p-r. Once the common factors f_t have been identified, the matrix (γ⊥, α)’ can be inverted to obtain the P-T decomposition as follows:

\begin{matrix} \underset{p x l}{X_{t}} = \underset{p x k}{A_{t}} \underset{k x p}{γ' ⊥} X_{t} + \underset{p x r}{A_{2}} \underset{r x p}{α'} X_{t}, & (A 4) \end{matrix}

where A₁ = (γ⊥′ α⊥)^-1 and A₂ = (α′γ)^-1. The first term on the right-hand side provides the permanent component at each point in time, t, for the vector of endogenous variables (the RER and the fundamental variables).

Prepared by Johan Mathisen.

Not seasonally adjusted. Based on IMF, Infoimation Notice System (INS) methodology and Malawian authorities’ 1994 trade weights.

The model is discussed in depth in Williamson (1994).

As data on government consumption of nontradables and tradables are unavailable, spending on public wages and salaries is excluded because the impact on the real exchange rate may differ from general government consumption.

The analysis uses quarterly data from the International Finance Statistics (IFS), staff estimates, and Malawian authorities and, in some cases are interpolated from annual data. The variables and the data sources are listed in Appendix I.

In addition to these long-run fundamentals, Edwards identifies macroeconomic policies (monetary and fiscal (as the source of short-term deviations of the exchange rate from the ERER.

The results in (Tables I.1 and I.2 are obtained by estimating the ECM by imposing one cointegrating vector for ease of interpretation.

Based on the long-run relationship summarized above and some short-run deviations as shown in (Table I.2 the ERER has been estimated for 1980-2002. As the estimated ERER shows a high degree of volatility—partly owing to shocks to the “fundamentals” as shown in Figure I.1—the ERER has been smoothed using a Hodrick-Prescott filter with a smoothing factor of 500. Although Hodrick-Prescott filters tend to perform poorly at both ends of the series, the results for 2001 and 2002 are broadly consistent with the estimated series.

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Malawi: Selected Issues and Statistical Appendix

Author:

International Monetary Fund

Volume/Issue:: Volume 2002: Issue 182

Publisher:: International Monetary Fund

ISBN:: 9781451828016

ISSN:: 1934-7685

Pages:: 95

DOI:: https://doi.org/10.5089/9781451828016.002

Keywords
I. Estimation of the Equilibrium Real Exchange Rate for Malawi1
References
- APPENDIX I Variables: Definitions and Sources
- APPENDIX II: Cointegration and Orthogonal Decomposition

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Figure I.1.

Malawi: Real Effective Exchange Rate and its Determinants

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Figure I.2.

Malawi Actual and Real Effective and Equilibrium Real Exchange Rates

(March 1981 - March 2002, in logs)

Table I.2.

Malawi: Results from Error correction Models with d(LREER) as Dependent Variable

Variable		Model 1	Model 2
CointEql		−0.39	−0.27
Standard error		0.08	0.06
T-statistics		−5.20	−4.67
DLREER(-1)		0.03	−0.02
Standard error		0.11	0.10
T-statistics		0.30	−0.20
DLREER(-2)		0.10	0.03
Standard error		0.12	0.10
T-statistics		0.91	0.32
DLGCNWSGDP(-1)		−0.22	−0.22
Standard error		0.06	0.06
T-statistics		−3.71	−3.67
DLGCWSGDP(-2)		−0.22	−0.22
Standard error		0.05	0.05
T-statistics		−4.13	−4.28
DLGWSGDPC(-1)		0.18	0.14
Standard error		0.07	0.07
T-statistics		2.60	2.02
DLGWSGDP(-2)		0.12	0.09
Standard error		0.06	0.06
T-statistics		1.89	1.54
DLTOTG(-1)		0.03	0.01
Standard error		0.14	0.13
T-statistics		0.19	0.06
DLTOTG(-2)		−0.22	−0.19
Standard error		0.14	0.13
T-statistics		−1.46	−1.43
DLTECHPRO(-1)		0.02
Standard error		0.09
T-statistics		0.17
DLTECHPRO(-2)		0.01
Standard error		0.09
T-statistics		0.09
DLINVGDP(-1)		0.11	0.12
Standard error		0.08	0.07
T-statistics		1.37	1.71
DLINVGDP(-2)		0.11	0.11
Standard error		0.08	0.07
T-statistics		1.44	1.57
DALNFA(-1)		−0.01
Standard error		0.02
T-statistics		−0.47
DALNFA(-2)		0.02
Standard error		0.02
T-statistics		0.96

Memorandum items:
	R-squared	0.41	0.33
	Adj. R-squared	0.29	0.23
	Sum sq. resids	0.49	0.56
	S.E. equation	0.094	0.09
	F-statistic	3.34	3.57
	Log likelihood	93.66	92.83
	Akaike AIC	−1.92	−1.93
	Schwarz SC	−1.48	−1.61
	Mean dependent	−0.00	−0.00
	S.D. dependent	0.10	0.10

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Abstract

I. Estimation of the Equilibrium Real Exchange Rate for Malawi1

A. Definition and Determinants of the Real Exchange Rate

B. Data and Key Observations

C. The Empirical Model

D. Econometric Characteristics

E. Results

F. Adjustment Speed

G. The Gap Between the Real Exchange Rate and the Equilibrium Level

H. Conclusion

References

APPENDIX I Variables: Definitions and Sources

APPENDIX II: Cointegration and Orthogonal Decomposition

Same Series

Other IMF Content

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I. Estimation of the Equilibrium Real Exchange Rate for Malawi¹