This paper compares the in‐sample fitting and the out‐of‐sample forecasting performances of four distinct Nelson–Siegel class models: Nelson–Siegel, Bliss, Svensson, and a five‐factor model we propose in order to enhance the fitting flexibility. The introduction of the fifth factor resulted in superior adjustment to the data. For the forecasting exercise the paper contrasts the performances of the term structure models in association with the following econometric methods: quantile autoregression evaluated at the median, VAR, AR, and a random walk. As a pattern, the quantile procedure delivered the best results for longer forecasting horizons. Copyright © 2011 John Wiley & Sons, Ltd.

Quantile Autoregression (QAR) is used to explore asymmetries in the adjustment process of pairwise Real Exchange Rate (RER) between the Italian lire, French franc, Deutsch mark and the British pound. Based on the best specification for each quantile we construct predicted conditional density functions, which guided us to identify two sources of asymmetry: (1) dispersion depends on the conditioned value of the RER, i.e. 'conditional' heteroskedasticity; (2) the probability of increases and falls also changes according to the conditioned value, i.e. there is higher probability for the RER to appreciate (depreciate) given the currency is depreciated (appreciated). We only verified strong heterokedasticity in relations among the lire, franc and mark, which was resolved by estimating quadratic autoregressive model for some quantiles. Relations involving the pound presented stable but higher dispersion indicating larger probability of wider oscillation.

Palavras-chavepolítica monetária, economia bancária, canal de tomada de risco, instituições financeiras JEL Codes

No abstract

Shocks in commodity prices are viewed as a major driver of emerging economies' business cycle. We show this is not the case for Brazil, Chile, Colombia, and Peru when a structural vector autoregressive model accounts for macrofinance linkages at world and domestic levels. The presence of a global financial variable modifies established results as it endogenously influences commodity prices. Global demand shocks have been the main external driver of the business cycle in Brazil, Chile, and Peru, while global economic uncertainty shocks have been the main international driver of the Colombian GDP.*A longer working paper version is available at https://econpapers.repec.org/paper/cdptexdis/td623 .htm under the title "Global shocks and emerging economies: disentangling the commodity roller coaster". We are grateful to Tao Zha and Daniel Waggoner (see Zha, 2000) for sharing their codes, and for the editor and the anonymous referee for their valuable suggestions. All errors are ours.