Cointegration analysis has led to equilibrium-correction econometric systems being ubiquitous. But in a non-stationary world subject to structural breaks, where model and mechanism differ, equilibrium-correction models are a risky device from which to forecast. Equilibrium shifts entail systematic forecast failure, as forecasts will tend to move in the opposite direction to data. We explain the...

Random Utility models have become standard econometric tools, allowing parameter inference for individual-level categorical choice data. Such models typically presume that changes in observed choices over time can be attributed to changes in either covariates or unobservables. We study how choice dynamics can be captured more faithfully by additionally modeling temporal changes in parameters di...

The bootstrap, like the jackknife, is a technique for estimating standard errors. The idea is to usc Monte Carlo simulation, based on a non-parametric estimate of the underlying error distribution. The bootstrap will be applied to an econometric model describing the demand for capital, labor, energy, and materials. The model is fitted by three-stage least squares. In sharp contrast with previou...

The explanation of aggregate and sectoral investment behavior has been one of the less successful endeavors in empirical economics. Existing econometric models have had little success in explaining or predicting investment spending. This may be because most such models fail to account for the irreversibility of most investment spending. With irreversibility, changes in the riskiness of future c...

Disputes about econometric methodology partly reflect a lack of evidence on alternative approaches. We reconsider econometric model selection from a computer-automation perspective, focusing on general-to-specific reductions, embodied in PcGets. Starting from a general congruent model, standard testing procedures eliminate statistically-insignificant variables, with diagnostic tests checking th...

The aims of this paper are estimate and forecast the Non-Accelerating Inflation Rate of Unemployment, or nairu, for Brazilian unemployment time series data. In doing so, we introduce a methodology for estimating mixed additive seasonal autoregressive (masar) models, by the Generalized Method of Moments (gmm). Furthermore, in order to cover a lack in econometric literature, an asymptotic theory ...

Our modelling strategy assesses model uncertainty explicitly and aims to identify the main drivers of differences in digital variables at household individual levels 99 European NUTS-2 regions. Several economic demographic covariates are found be robust predictors these variables. benchmark projection results indicate that historical convergence trends related access technologies (broadband int...

The spatio-temporal modelling and forecasting of incidences of crimes have now become a routine part of crime prevention operations. However, obtaining reliable forecasts for cases of changing spatial boundaries using models which take the influences of exogenous factors on the spatial and temporal dynamics of crime into account remains a challenge. The proposed Dynamic Spatial Distribution App...

Providing generic and cost effective modelling approaches to reconstruct and forecast freshwater temperature using predictors as air temperature and water discharge is a prerequisite to understanding ecological processes underlying the impact of water temperature and of global warming on continental aquatic ecosystems. Using air temperature as a simple linear predictor of water temperature can ...