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Forecasting inflation with excess liquidity and excess depreciation: the case of Angola

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Abstract

This paper presents a country case study investigating whether home goods prices in Angola are better forecasted with innovations in the money market or with innovations in the real exchange rate. Using monthly data from 2007m03 to 2019m03, we propose a reduced form error correction representation to model the long-run and short-run relationships between money, the exchange rate, terms of trade, and the price level. In the long run, a stable money demand function and a relationship between the real exchange rate and terms of trade are identified. In the short run, results indicate that “excess depreciation” (defined as deviations of the exchange rate from its long-run relationship) outperforms the “excess liquidity” (defined as deviations of money from the level implied by the determinants of money demand) in forecasting changes in home goods prices.

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Notes

  1. From September 2004 until September 2014 the cumulative devaluation of the official exchange rate vis-à-vis the US dollar had been 13 percent, only. Throughout this period the difference between the parallel and the official exchange rate averaged 6 percent, reflecting a significant enforcement of the official exchange rate with market interventions (data sources are described in the "Appendix"). Although Angola never formally adopted a fixed exchange rate regime, in practice the BNA’s intermediate goal of stabilizing the exchange rate through sales of foreign exchange had been instrumental in containing inflation, delivering—according to the International Monetary Fund (2005)—many of the characteristics of exchange rate stabilization.

  2. Determinants of the real exchange rate other than terms of trade include productivity differentials, preferences, government spending, international transfers, and capital flows (Rogoff 1996; Hinkle and Montiel 1999). In commodity-exporting countries, however, terms of trade have been identified as the main source of persistent changes in the real exchange rate (Amano and van Norden 1995, Cashin et al. 2004, Joyce and Kamas 2010).

  3. The reasoning relies on the assumption that some factors are industry-specific or, as an alternative, that factor mobility across industries is less than perfect, as it looks sensible in the development context. For the case with perfect factor mobility, see Obstfeld and Rogoff (1996).

  4. In Angola, the nominal interest rate has been set at artificially low levels in order to ease the government debt service in the scope of “coordinated management of monetary and fiscal policies” (Government of República Popular de Angola 2017).

  5. Our experiments revealed that including an exchange rate depreciation term in the equation for money does not improve the quality of the fit.

  6. Our experiments with an alternative formulation, whereby nominal money is replaced by money divided by the Consumer Price Index, delivers the same conclusions. The specification above is preferable, though, for two reasons: first, it allows price homogeneity to be statistically tested; second, it allows the price level to face two attractors, nominal money and the nominal exchange rate, enriching the short-run dynamics of the model.

  7. This proxy may be questioned on the grounds that oil production accounts for only about one third of the country’s gross value added. However, according to the quarterly national accounts published by the National Institute of Statistics (available since 2015), the correlation between oil production and GDP stands at around 83%. This high correlation is of no surprise in an economy where oil exports account for more than 95% of the country’s export revenues, and where access to foreign credit is limited. As shown in the model in "Appendix 1", in such a context, the level of domestic absorption (and hence the demand for money) becomes conditional on commodity exports.

  8. Arguably, a single terms of trade proxy could be constructed, averaging TOT and TOTUS. Our experiments reveal, however, that this is not an issue: the variance in the terms of trade is largely dominated by changes in oil prices, in the numerator, with the denominator playing only a minor role.

  9. The results of the interpolation are consistent with the observation by the International Monetary Fund (2010) that the black-market premium reached a maximum of 25 percent in September 2010.

  10. We also experimented with tests including only a constant for variables in which the trend is less clear without altering the conclusions in the main text.

  11. A natural explanation for the observed variation in the money multiplier is that reserve requirements were changed considerably throughout the sample period. For instance, between 2011m12 and 2018m07 the minimum reserves requirement for bank deposits denominated in domestic currency changed nine times, varying between 12.5 and 30%.

  12. Following Kremers et al. (1992), co-integration is assessed by the sign and significance of the auto-regressive term in columns (ii) and (iii). Since the corresponding t-statistic has a non-standard distribution under the null, absence of co-integration is tested referring to the ADF critical values. Testing with the Engle and Granger’ two-step-procedure delivers the same conclusions.

  13. Gelbard and Nagayasu (2004) also tested the stability of a real exchange rate indicator computed with the black-market exchange rate in Angola. Using monthly data from 1992m01to 2002m01 the authors found evidence of cointegration involving the real exchange rate index, the price of oil, and the US real interest rate, allowing for a time trend in the cointegrating equation. In our sample we find that changes in oil prices account for all of the permanent innovations in the real exchange rate, implying that no other regressor is needed in the corresponding long-run relationship.

  14. This choice revealed being consistent with the Pantula principle (Johansen 1992).

  15. Residual non-normality is a limitation in our analysis, due to the presence of outliers, as described below.

  16. Experimenting with more restricted money demand systems—dropping X, INF, or both—we failed to obtain a positive coefficient in the relationship between P and M. This evidence implies that both X and INF play a key role in establishing a sensible money demand relationship with the expected signs in this sample. These results are available from the author upon request.

  17. To check the possibility of spurious cointegration, we investigated whether orthogonal relationships with a single variable only could be identified, experimenting with one variable at a time. In all cases, the overidentifying restrictions were rejected. Although failure to reject would provide convincing evidence that at least one variable in the system was stationary, rejection does not necessarily rule out the presence of near integrated processes in the system (Hjalmarsson and Osterholm 2010). We thank an anonymous referee for suggesting this check.

  18. The large and positive residuals after 2015 could also be explained by the failure to account for a structural break in the long-run relationship. However, to our knowledge, there is no a priori reason to model a sudden change in the agents’ attitude toward money at that time. Our conjecture is that the considerable increase in inflation from 2015–2016 caused a temporary but sizeable departure of existing real money balances from the level implied by the long-run relationship, followed by slow error correction. The low magnitude of the estimates for \(\alpha_{11}\) and \(\alpha_{21}\) in Table 3 is consistent with this interpretation.

  19. As before, no single-variable cointegrating vector passes the LR test on binding restrictions. However, this does not rule out the presence of near integrated processes in the system. That being the case, both reduced rank tests will over-reject the null, the more the greater the number of variables in the system (Hjalmarsson and Osterholm 2010). Consistently with this conjecture, we verify that the significance levels of the trace test in Table 4 are systematically lower than those of the maximum eigenvalue test. Further experiments revealed that no alternative specification delivered sensible long-run relationships.

  20. In the figure, the residuals are not centred at zero before 2015. The reason is that the large departures from the long-run relationships after 2015 are a source of asymmetry, biasing the estimated intercepts of the long-run relationships upwards. The implied “level effect” is however controlled for by the constant term in the equations describing the short-run dynamics. Since the large deviations occur at the end of the sample, the qualitative implications of the exercise are not likely to be at stake.

  21. Imposing the additional restriction \(\alpha_{11} = 0\) in the model with M2 improves the p-value of the corresponding LR tests to 0.452.

  22. Similar findings were obtained by Nell (2003) in the context of the South African economy. Investigating the demand for M3 from 1968–1997, the author found a stable money demand relationship, but rejected the null of weak exogeneity of money. The author also failed to obtain significance of excess liquidity in forecasting the price level.

  23. In Table 1 the Jarque–Bera statistic points to residual non-normality, reflecting the presence of inflation outliers. These are related to administrative price changes in transports, fuels, and electricity at odds with the seasonal pattern, namely in 2010m09, in 2016m01, and in 2018m09. Our experiments revealed that controlling for these outliers with impulse dummies considerably reduces the value of the Jarque–Bera statistic and of the standard error of the regression. Since no other noticeable effect is achieved with these dummies, we prefer not to use them in Table 1, for the results to be as crude as possible.

  24. The series of “Excess liquidity” in Table 6 is constructed based on the results of Table 4, column (ii). Using the results from Table 3, column (ii) delivers the same conclusions.

  25. In general, the signs and the significance of the coefficients in the conditional model are similar to those found under VECM estimation, in Table 4.

  26. The one-step-ahead Chow test (not reported) reveals major disturbances in 2010m09, 2016m01, and 2018m09, corresponding to the above-mentioned episodes of administrative price adjustment at odds with the seasonal pattern.

  27. Following Dreger and Wolters (2014), in the forecasting exercise we use the cointegrating vectors estimated with the full sample.

  28. In this simple model, revenues of the natural resource sector act like a transfer from abroad. Modelling production in the natural resource sector would not change the conclusions regarding the long-run relationship between the real exchange rate and terms of trade. For a recent formulation with endogenous decisions in the commodity exporting sector see Kulish and Rees (2017).

  29. If alternatively the constraint (a8) were not binding, the pattern of consumption would be determined according to the permanent income hypothesis, given the international interest rate. A condition equivalent to (a17) would still hold if we postulated \(\beta \left( {1 + r_{{}}^{*} } \right) = 1\) and all components of (a16) to be invariant over time (Végh 2013 ).

  30. Kinguila Hoje (http://www.kimguilahoje.com).

  31. The adjusted weights are as follows: “Housing and utilities” (35.84%), “Health” (9.75%), “Transport” (22.74%), “Communication” (9.55%), “Recreation and Culture” (6.42%), “Education” (7.02%), and “Restaurants and hotels” (8.69%). The following items are excluded: “Food and non-alcoholic beverages”, “Alcoholic beverages and Tobacco”, “Clothing and footwear”, “Household contents”, “Equipment and maintenance”, and “Miscellaneous”.

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Acknowledgements

We acknowledge Luis Catela Nunes and two anonymous referees for helpful comments and suggestions to an earlier version of this paper. This paper draws on background materials produced by the author in the scope of a research project involving Banco Millenium Atlântico and NovAfrica at Nova School of Business and Economics. We acknowledge Cátia Batista, José Pedro Soeiro, Osvaldo Vitorino, Jânio Ambrósio, Anta Bandola, Miguel Lino Ferreira, Tomás Rosa, and António Marques for helpful discussions and assistance during the implementation of the project.

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Appendices

Appendix 1: Terms of trade and the real exchange rate in a three-goods economy

In this appendix we present a simple three-goods model to motivate the relationship between terms of trade and the real exchange rate that underlies the empirical exercise. We consider a small open economy under flexible prices with restricted access to international finance. In this economy, three non-storable goods are produced: a non-tradable good (\(Q_{t}^{N}\)), an importable good (\(Q_{t}^{I}\)), and an exportable natural resource (\(X_{t}^{{}}\)). The importable and non-tradable goods are produced by private firms using labour hired from households. The national resource sector delivers an exogenous amount of production each period that is appropriated by the government.Footnote 28 The price of the non-tradable good (\(P_{t}^{N}\)) is determined domestically. The domestic currency prices of the importable good (\(P_{t}^{I}\)) and of the natural resource (\(P_{t}^{X}\)) are equal to the product of the nominal exchange rate (\(e_{t}^{{}}\)) by the corresponding prices abroad, that are exogenously determined in units of foreign currency. Households are blessed with perfect foresight and use income from wages and profits to pay a lump sum tax (\(T_{t}\)), to consume importable and non-tradable goods (\(C_{t}^{I} ,C_{t}^{N}\)), and to save, in the form of money (\(M_{t}\)), government bonds denominated in domestic currency (\(B_{t}^{{}}\)), or foreign bonds denominated in foreign currency (\(B_{t}^{*}\)). The private sector faces a binding constraint on foreign borrowing. The government sector consists of the treasury, the central bank, and the natural resource sector. To save on notation we assume that the government consumes only non-tradable goods (\(G_{t}^{N}\)) and does not borrow abroad.

Production of I and N is undertaken by firms that are owned by households and hire labour from households. The production functions are assumed as follows:

$$Q_{t}^{N} = L_{t}^{N} ,$$
(a1)
$$Q_{t}^{I} = F\left( {L_{t}^{N} } \right),\;{\text{with}}\;F_{L} > 0,F_{LL} < 0$$
(a2)

where \(L_{t}^{N}\) and \(L_{t}^{I}\) refer to employment levels in the N and the I sectors, respectively. We assume that the total labour supply in each period, \(\overline{L}_{t}^{{}}\), is inelastic. The resource constraint of the economy is as follows:

$$\overline{L}_{t}^{{}} = L_{t}^{N} + L_{t}^{I}$$
(a3)

Profit maximization in the non-tradable goods sector implies the equality between the nominal wage and the price of non-tradable goods, \(W_{t}^{{}} = P_{t}^{N}\). Profit maximization in the importable goods sector, delivers an optimal supply function of the form:

$$Q_{t}^{I} = Q_{{}}^{I} \left( {\overline{\theta }_{t} ,.} \right)$$
(a4)

where \(\theta_{t} = {{P_{t}^{N} } \mathord{\left/ {\vphantom {{P_{t}^{N} } {P_{t}^{I} }}} \right. \kern-\nulldelimiterspace} {P_{t}^{I} }}\) is the real exchange rate (an increase corresponds to an appreciation). Combining the optimal demand for labour implied by (a4) with (a1) and (a2), one obtains a function that relates the full employment supply of non-tradable goods to the real exchange rate:

$$Q_{t}^{N} = Q_{{}}^{N} \left( {\mathop {\theta_{t}^{{}} }\limits^{ + } ,.} \right)$$
(a5)

The representative household is blessed with infinite life and maximizes a discounted utility function of the form:

$$U = \sum\limits_{t = 1}^{\infty } {\beta^{t - 1} } \left[ {\alpha \ln C_{t}^{I} + \left( {1 - \alpha } \right)\ln C_{t}^{N} + \chi \ln \left( {{{M_{t} } \mathord{\left/ {\vphantom {{M_{t} } P}} \right. \kern-\nulldelimiterspace} P}_{t}^{I} } \right)} \right]$$
(a6)

where \(\beta\) is a subjective discount factor. The household flow budget constraint is as follows:

$$b_{t}^{{}} + b_{t}^{*} + \frac{{M_{t} - M_{t - 1} }}{{P_{t}^{I} }} = b_{t - 1}^{{}} \left( {1 + r_{t - 1} } \right) + b_{t - 1}^{*} \left( {1 + r_{{}}^{*} } \right) + \left( {Q_{t}^{I} - T_{t} - C_{t}^{I} } \right) + \theta_{t}^{{}} \left( {Q_{t}^{N} - C_{t}^{N} } \right)$$
(a7)

where \(r_{t}\) and \(r_{{}}^{*}\) denote for the domestic and foreign real interest rates, \(b_{t}^{{}} = {{B_{t} } \mathord{\left/ {\vphantom {{B_{t} } {P_{t}^{I} }}} \right. \kern-\nulldelimiterspace} {P_{t}^{I} }}\), \(b_{t}^{*} = {{B_{t}^{*} } \mathord{\left/ {\vphantom {{B_{t}^{*} } {\left( {{{P_{t}^{I} } \mathord{\left/ {\vphantom {{P_{t}^{I} } {e_{t} }}} \right. \kern-\nulldelimiterspace} {e_{t} }}} \right)}}} \right. \kern-\nulldelimiterspace} {\left( {{{P_{t}^{I} } \mathord{\left/ {\vphantom {{P_{t}^{I} } {e_{t} }}} \right. \kern-\nulldelimiterspace} {e_{t} }}} \right)}}\). In addition to (a7), the household faces a constraint on foreign borrowing:

$$b_{t}^{*} \ge \overline{b}_{{}}^{*}$$
(a8)

The first-order conditions of the household maximization problem with respect to \(C_{t}^{N}\), \(C_{t}^{I}\), and \(b_{t}^{{}}\) deliver the following equations:

$$\theta_{t}^{{}} = \frac{{\left( {1 - \alpha } \right)C_{t}^{I} }}{{\alpha C_{t}^{N} }}$$
(a9)
$$\frac{{C_{t + 1}^{I} }}{{C_{t}^{I} }} = \beta \left( {1 + r_{t} } \right)$$
(a10)

Condition (a9) states that the real exchange rate in each period shall correspond to the marginal rate of substitution between importable and non-tradable goods. (a10) is the Euler equation for importable goods. The corresponding equation for non-tradable goods can be obtained from (a9) and (a10).

The first-order condition with respect to \(M_{t}\) together with (a9) and (a10), delivers the optimal money demand. Using the Fisher Equationss \(1 + i_{r} = \left( {1 + r_{t} } \right)\left( {{{P_{t + 1}^{I} } \mathord{\left/ {\vphantom {{P_{t + 1}^{I} } {P_{t}^{I} }}} \right. \kern-\nulldelimiterspace} {P_{t}^{I} }}} \right)\) and the definition of private expenditure measured in units of the importable good,

$$A_{t}^{P} = C_{t}^{I} + \theta C_{t}^{N}$$
(a11)

the money demand function becomes:

$$\frac{{M_{t} }}{{P_{t}^{I} }} = \chi A_{t}^{P} \left( {1 + \frac{1}{{i_{t} }}} \right)$$
(a12)

When (a8) is not binding the first-order condition with respect to \(b_{t}^{*}\) implies the equality between the domestic and international interest rates, \(r_{t} = r^{*}\). In what follows, we assume that the constraint (a8) is binding. In this case, the domestic interest rate is endogenous and exceeds the cost of borrowing abroad:

$$r_{t} > r^{*} ,\;When\;b_{t}^{*} = \overline{b}^{*}$$
(a13)

In the market for non-tradable goods, production must equal national expenditure:

$$Q_{{}}^{N} = C_{t}^{N} + G_{t}^{N}$$
(a14)

The flow budget constraint of the government is as follows:

$$b_{t}^{{}} + \frac{{M_{t} - M_{t - 1} }}{{P_{t}^{I} }} = b_{t - 1}^{{}} \left( {1 + r_{t - 1} } \right) + \theta_{t}^{{}} G_{t}^{N} - T_{t} - \tau_{t} X_{t}$$
(a15)

In (a15), the term \(\tau_{t} = {{P_{t}^{X} } \mathord{\left/ {\vphantom {{P_{t}^{X} } {P_{t}^{I} }}} \right. \kern-\nulldelimiterspace} {P_{t}^{I} }}\) denotes for terms of trade. Using (a7), (a14), and (a15) we obtain the economy flow budget constraint:

$$b_{t}^{*} - b_{t - 1}^{*} = r_{{}}^{*} b_{t - 1}^{*} + \tau_{t} X_{t} + Q_{{}}^{I} - C_{t}^{I}$$
(a16)

Since we are assuming that the borrowing constraint is binding in each period, there is an “admissible” level of \(C_{t}^{I}\), for each level of the remaining variablesFootnote 29:

$$C_{t}^{I} = r_{{}}^{*} b_{t - 1}^{*} + \tau_{t} X_{t} + Q_{{}}^{I}$$
(a17)

Using (a17), (a11), and (a4) the admissible level of expenditure will be:

$$A_{t}^{P} = \frac{1}{\alpha }\left[ {r_{{}}^{*} b_{t - 1}^{*} + \tau_{t} X_{t} + Q_{{}}^{I} \left( {\mathop {\theta_{t}^{{}} }\limits^{ - } } \right)} \right]$$
(a18)

This condition establishes a negative relationship between the “admissible” private expenditure and the real exchange rate. All else equal, when the real exchange rate appreciates, the production of importable goods decreases, causing the trade balance to deteriorate. For the borrowing constraint to be met, domestic absorption must fall to induce a lower demand for importable goods. This equation is represented in Fig. 8 by the downward sloping schedule XX. A terms of trade deterioration implies that fewer resources will be available to spend on importable goods, causing the XX curve to shift to the left.

Fig. 8
figure 8

A terms of trade deterioration in the three-goods economy

Using (a11) and (a5) in (a15), we obtain a condition describing the equilibrium in the labour market and in the market for non-tradable goods as a function of the real exchange rate and national expenditure:

$$Q_{{}}^{N} \left( {\mathop {\theta_{t}^{{}} }\limits^{ + } } \right) = \frac{1 - \alpha }{\theta }A_{t}^{P} + G_{t}^{N}$$
(a19)

Equation (a19) describes the combinations of real exchange rate and of private expenditure that balance the market for non-tradable goods. When national expenditure increases, the demand for non-tradable goods rises, calling for a real exchange rate appreciation to induce a reallocation of production toward non-tradable goods. The equilibrium in the market for non-tradable goods is described in Fig. 8 by the upward sloping curve NN.

We finally examine the impact of a terms of trade change. In the figure we describe by point 0 an initial equilibrium with internal balance and in which the borrowing constraint is met. Departing from this equilibrium, suppose that a terms of trade deterioration causes the XX curve to shift to the left. With a lower admissible expenditure, the demand for non-tradable goods falls. If the real exchange rate were to remain unchanged (say, under currency peg and short-term price stickiness) meeting the borrowing constraint would force the economy to point 1’, with unemployment. Under flexible prices, nominal wages and the price of non-tradable goods fall to restore internal balance. As the real exchange depreciates, there is an expenditure switching toward the non-tradable goods and a reallocation of supply toward the importable goods (point 1). This will be the long-run adjustment to a terms of trade shock.

In light of this model, one could explore the possibility of the borrowing constraint to depend positively on the terms of trade. As pointed out by Kaminski et al. (2004), changes in terms of trade affect the country’s creditworthiness and the value of collateralizable resource revenues, lessening the borrowing constraints during boom times and tightening the external constraint during bad times. Similarly, one could assume that government expenditures depended positively on the terms of trade: as argued by Tornell and Lane (1999), when oil revenues are mediated through the government budget—as is the case in Angola—political pressures may cause government spending to act pro-cyclically, even if “saving for rainy days” looked more sensible. These two effects act reinforcing the positive relationship between terms of trade and the real exchange rate captured by the model above.

Appendix 2: Data sources and descriptive statistics

The data sources are as follows: The data on the parallel-market exchange rate (E) are from the IMF until March 2016 and updated thereafter using an internet source.Footnote 30 The official exchange rate (EO), Money (M2), and monetary base (MB) are obtained from the International Financial Statistics and updated with BNA data. The series on oil exports (X) is from the Angolan Ministry of Finance. The inflation rate (INF) is computed as the monthly variation of the Consumer Price Index for the region of Luanda, published by the Angolan National Institute of Statistics. The price of non-tradable goods (P) is constructed from the components of the Consumer Price Index.Footnote 31 Data on Brent oil prices are from the US Energy Information Association. The euro-dollar exchange rate and the foreign price indexes are from Eurostat (Tables 8, 9).

Table 8 Descriptive statistics of the main variables
Table 9 Correlation matrix

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Lebre de Freitas, M. Forecasting inflation with excess liquidity and excess depreciation: the case of Angola. Econ Change Restruct 56, 473–514 (2023). https://doi.org/10.1007/s10644-022-09427-y

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