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For many countries, statistical information on macroeconomic variables is not abundant and hence creating forecasts can be cumbersome. This paper addresses the creation of current year forecasts from a MIDAS regression for annual inflation rates where monthly inflation rates are the explanatory variables, and where the latter are only available for the last one and a half decade. The model can be viewed as a hybrid New-Keynesian Philips curve (NKPC). Specific focus is given to the forecast accuracy concerning the high inflation period in 2016-2017.

The parallel market nominal exchange rate of the United States dollar vis‐à‐vis the Surinamese dollar (USD/SRD) exhibited periods of severe volatility which were often followed by episodes of stability, usually at a cost of sharp depreciations. This study seeks to model this exchange rate using autoregressive conditional duration models. These models are suitable for modelling events occurring with irregular intervals. Exchange rates in developing countries have distinct features compared to exchange rates in countries with well‐established and accessible financial markets. A key feature is that for these developing countries, exchange rates only occasionally experience jumps. Our findings suggest that past exchange rate changes appear to be a significant driver of future exchange rate jumps. Furthermore, our results show that money, international reserves, and commodity prices can explain jumps in the market USD/SRD exchange rate.