Using a survey approach, we ask consumers to reveal their preferences over pricing schemes that may differ in terms of the average price of consumption, the amount of price variation, and the probability of being rationed. We find that consumers dislike pricing schemes that vary prices more but...

A sizeable literature examines exchange rate pass-through to disaggregated import prices but very few micro-studies focus on consumer prices. This paper explores exchange rate pass-through to consumer prices in South Africa during 2002-2007, using a unique data set of highly disaggregated data...

We propose a numerical method, based on indirect inference, for checking the identification of a DSGE model. Monte Carlo samples are generated from the model's true structural parameters and a VAR approximation to the reduced form estimated for each sample. We then search for a different set of...

Time series models are often adopted for forecasting because of their simplicity and good performance. The number of parameters in these models increases quickly with the number of variables modelled, so that usually only univariate or small-scale multivariate models are considered. Yet, data...

This paper provides a new way of analyzing tenure profiles in wages, by modelling simultaneously the evolution of wages and the distribution of tenures. Starting point is the observation that within-job log wages for an individual can be described by random walk. We develop a theoretical model...

This Paper considers the problems facing decision-makers using econometric models in real time. It identifies the key stages involved and highlights the role of automated systems in reducing the effect of data snooping. It sets out many choices that researchers face in construction of automated...

We extend the standard approach to Bayesian forecast combination by forming the weights for the model averaged forecast from the predictive likelihood rather than the standard marginal likelihood. The use of predictive measures of fit offers greater protection against in-sample overfitting and...