interest rate _rd,t_ and the domestic inflation rate; and (iii) � where the nominal currency depreciation rate _Êt_ against the US dollar is decomposed into the relative change in tt tt tt dd,tt the real exchange rate _ȇt_ , the domestic inflation rate, and the foreign inflation rate. �1 + EE<sup>�</sup> �= (1 + eê )(1 + pp̂ )/�1 + pp̂ We specify an econometric time-series model—a Vector Auto-regressive (VAR) model—to formalize the dynamic interactions and feedbacks between the real GDP growth rate _ŷt_ , the real currency depreciation rate _ȇt_ , the domestic real interest rate _rd,t_ , and the public investment-to-GDP ratio _KEt_ . The first three variables are treated as endogenous in the VAR specification, and proxy, respectively, Mauritania’s growth, competitiveness, and borrowing costs for the government. Public investment, instead, is deemed an exogenous, policy-driven variable. The VAR model intends to captures the pattern of co-movements between these four variables, e.g., _KEt_ affects _ŷt_ (through the accumulation of physical capital) as well as _ȇt_ (through the productivity improvements, the foreign-exchange inflows associated to external financing of public capital projects, etc.).

For the purposes of this study, the VAR model is seen as a useful device to represent the stylized behavior of key macroeconomic variables driving the public debt dynamics and to simulate shocks and scenarios. Admittedly, the performance of the VAR model for Mauritania is severely affected by data availability constraints and structural breaks in the development experience of recent years. Hence, a strict scrutiny of the statistical properties of the VAR model is likely to reveal weaknesses and drawbacks, e.g., failures to pass basic specification and forecast tests. Nevertheless, lacking a better macroeconomic modelling device and acknowledging that the Mauritanian economic phenomena being modelled are themselves quite complex, the formulation and use of VAR model is justified in our view.

The VAR is estimated blending the historical data in 2003-13 and the projections in 2014-18 embedded in the baseline macro-fiscal framework. As times series are not long, we consider only one lag of the endogenous variables, i.e., a VAR(1) model. A casual observation to the historical series of the three endogenous variables suggests macroeconomic volatility was excessive in the past and would probably be largely attenuated in the next few years (Figure AI.1 and AI.2). In addition, the real exchange rate appreciated extremely fast in 2003-08 and arguably the prospective pace of real currency appreciation will be much slower. Against this backdrop, in order to smooth the volatility of the VAR forecasts and stochastic simulations, we proceed by estimating the VAR model using data points in 2014-18—drawn from the baseline macro-fiscal framework—and adjusting a few estimated covariances and intercepts. The estimated VAR coefficients are reported in Table AI.1 and the (adjusted) estimates are used in Section C to generate the scenario with growth-dividend consistent with the higher-investment policy. The estimated matrix of covariances of residuals is reported in Table AI.2 and the (adjusted) estimates are used in Section B to generate shocks to the macroeconomic trends characterizing the baseline outlook.

In Section B, the analysis of fiscal risks relies on stochastic simulations of macroeconomic scenarios. Starting with the baseline outlook’s trends reported in Table B1, randomly-generated shocks are added to the real GDP growth rate _ŷt_ , the real currency depreciation rate _ȇt_ , and the domestic real interest rate _rd,t_ . Following standard practices, in any given year, the shocks are generated with a multivariate Gaussian distribution centered in zero and with the VAR residuals’ covariance matrix. Shocks are correlated in any given year, but independent through time. The various (shock-driven) paths of the three macroeconomic variables feed into the DSA model and thus underpin the fan charts of public debt and gross financing needs reported in Figure B3 and B4.

For illustrative purposes, the fan charts in Figure AI.3 and AI.4 correspond to the real GDP growth rate and the nominal exchange rate—derived from the real currency depreciation rate and the domestic and foreign inflation rates. The dotted lines represent the baseline (expected) paths: the real GDP growth stabilizes at 7 percent in the next few years; while the nominal exchange rate smoothly moves within the range of 275-300 MRO per unit of US dollar. The colored bands, in turn, depict the probability distribution (density) of the growth and exchange rate outcomes resulting from macroeconomic shocks and stochastic simulations. The bands indicate that there is a 90 percent probability that Mauritania’s real 30