SUMMARY Decision makers often observe point forecasts of the same variable computed, for instance, by commercial banks, IMF and the World Bank, but the econometric models used by such institutions are frequently unknown. This paper shows how to use the information available on point forecasts to...

Using data from Pakistan, we study the effect of family wealth on the utilization of child labor. We find evidence of a positive relationship between land wealth and child labor only for children in the upper quantiles of the distribution. We hypothesize that the so-called “wealth paradox”...

In this paper we investigate fiscal sustainability by using a quantile autoregression (QAR) model. We propose a novel methodology to separate periods of nonstationarity from stationary ones, allowing us to identify various trajectories of public debt that are compatible with fiscal...

This paper contributes to the debate on whether the Brazilian public debt is sustainable or not in the long run by considering threshold effects on the Brazilian Budget Deficit. Using data from 1947 to 1999 and a threshold autoregressive model, we find evidence of delays in fiscal stabilization....

In this paper, we propose a novel approach to econometric forecasting of stationary and ergodic time series within a panel-data framework. Our key element is to employ the (feasible) bias-corrected average forecast. Using panel-data sequential asymptotics we show that it is potentially superior...

This paper is concerned with evaluating Value-at-Risk estimates. It is well known that using only binary variables, such as whether or not there was an exception, sacrifices too much information. However, most of the specification tests (also called backtests) available in the literature, such...

There has been a large amount of research on long memory in economic and financial time series. However, there is still no consensus on its presence in these series. We argue in this article that spurious short memory may be found because of the use of bandwidth parameters that diverge too...