ABSTRACT
The COVID-19 pandemic has affected all areas of our lives. Among other outcomes, the academic literature and popular media both discuss the potential effects of the pandemic on fertility. As fertility is an important determinant of population development and population forecasts are important for policy decisions and planning, we need to address to which extent fertility forecasts performed before the pandemic still apply. Using Monte Carlo forecasting based on principal components of fertility rates, we quantify the effects of the pandemic on fertility for 22 countries and discuss whether forecasts made prior to the pandemic need adjustment based on more recent data. Among the studied countries, 14 countries show no signifi cant effect of the pandemic at all, while six countries have signifi cantly lowered numbers of births in comparison to counterfactual trajectories that assume that past trends will hold. These countries are primarily in the Mediterranean and East Asia. For Finland and South Korea, there is statistical evidence for increased fertility in the early phases of the pandemic. In all cases with statistically signifi cant fertility differentials caused by the pandemic, reproductive behavior normalized quickly. Therefore, we fi nd no evidence for long-term effects of the pandemic on fertility, leading to the conclusion that pre-pandemic fertility forecasts still apply. © 2023, Bundesinstitut fur Bevolkerungsforschung. All rights reserved.
ABSTRACT
This paper provides estimates of the impact of the COVID-19 outbreak on Brazilian Ethanol sales. To this end, weekly data on Ethanol sales volumes are analyzed through an ITS SARIMA model and a counterfactual analysis covering the 2019–2020. We find that the real effect of COVID-19 was a reduction above 77.97% in Brazil after the first COVID-19 death, in March 2020, and still a decrease of about 50.15% at the end of 2020. The empirical evidence confirms that the impact of the pandemic crisis, the counterfactual analysis allows estimating the real effect of COVID-19 is on average 3.76% greater than the observed against an index date reference. These results suggest that ethanol sales in Brazil were more affected than only when comparing previous results to the effects of the pandemic. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.
ABSTRACT
This article appears as an essential contribution for decision-makers in the Cape Verdean tourism sector given the impact that the number of overnight stays has on the economy of the country and the Sal Island, which until 2018 had been increasing every year. Since seasonality is a strong feature of the island’s tourism, decision-makers are interested in knowing the seasonal variation in tourism demand. Thus, this study focussed on the application of the Box-Jenkins method to the time series of the monthly number of nights stays in tourist establishments on the Sal Island, Cape Verde, over the period from January 2000 to December 2018, to find a model that better describes the series and with good forecast results for the year 2019. Several SARIMA models were studied using the Box-Jenkins method, with the SARIMA (1, 1, 1 ) (0, 1, 1 ) 12 and the SARIMA (2, 1, 0 ) (0, 1, 1 ) 12 demonstrating the best predictive performance in the test phase. However, in forecasting the series for the year 2019, the SARIMA (2, 1, 0 ) (0, 1, 1 ) 12 achieved the best results with a MAPE = 6.77%. This model can be used to simulate and analyze the number of overnight stays that be expected on the Island, if the tourism sector was not affected by the pandemic caused by COVID-19. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.