The asymptotic efficiency of indirect estimation methods, such as the efficient method of moments and indirect inference, depends on the choice of the auxiliary model. To date, this choice has been somewhat ad hoc and based on an educated guess. In this article we introduce a class of...

We study how estimators used to impute consumption in survey data are inconsistent due to measurement error in consumption. Previous research suggests instrumenting consumption to overcome this problem. We show that, if additional regressors are present, then instrumenting consumption may still...

Brief summaries and user instruction are presented for the programs TRAMO ("Time Series regression with ARIMA Noise, Missing Observations and Outlers") and SEATS ("Signal Extraction in ARIMA Time Series").

The paper deals with the problem of identifying stochastic unobserved two-component models, as in seasonal adjustment or trend-cycle decompositions. Solutions based on the properties of the unobserved component estimation error are considered, and analytical expressions for the variances and...

In this monograph, first, we analyze in detail some of the major limitations of the standard procedure to estimate business cycles with the Hodrick-Prescott (HP) filter. By incorporating time series analysis techniques, it is seen how some intuitive and relatively simple modifications to the...

Hodrick-Prescott (HP) Filter of (most often, seasonally adjusted) quaterly series is analysed. Some of the criticism to the filter are adressed. It is seen that, while filtering strongly affects autocorrelations, it has little effect on crosscorrelations. It is argued that the criticism that HP...

The paper deals with estimation of missing observations in possibly nonstationary ARIMA models. First, the model is assumed known, and the structure of the interpolation filter is analysed. Using the inverse or dual autocorrelation function it is seen how estimation of a missing observation is...

Dynamic Stochastic General Equilibrium models are often tested against empirical VARs or estimated by minimizing the distance between the model's and the VAR impulse response functions. These methodologies require that the data-generating process consistent with the DSGE theoretical model has a...

This paper tests the opportunity-cost theory using a panel of Spanish firms during the period 1991-2010. Under this theory, productivity-enhancing activities, such as R&D investment, should increase during downturns because of the fall in their relative cost – in terms of forgone output –....

This paper considers panel growth regressions in the presence of model uncertainty and reverse causality concerns. For this purpose, my econometric framework combines Bayesian Model Averaging with a suitable likelihood function for dynamic panel models with weakly exogenous regressors and fixed...