Nonlinear Error Correction: The Case of Money Demand in the UK (1878-2000).

This paper explores single-equation nonlinear error correction (NEC) models with linear and nonlinear cointegrated variables. Within the class of semiparametric NEC models, we use smoothing splines. Within the class of parametric models, we discuss the interesting properties of cubic polynomial NEC models and we show how they can be used to identify unknown threshold points in asymmetric models and to check the stability properties of the long-run equilibrium. A new class of rational polynomial NEC models is also introduced. We found multiple long-run money demand equilibria. The stability observed in the money-demand parameter estimates during more than a century, 1878 to 2000, is remarkable.Money Demand; Nonlinear Error Correction; Cubic Polynomials; Rational Polynomials; Smoothing Splines; Nonlinear Cointegration;

Fluid flow queue models for fixed-mobile network evaluation

A methodology for fast and accurate end-to-end KPI, like throughput and delay, estimation is proposed based on the service-centric traffic flow analysis and the fluid flow queuing model named CURSA-SQ. Mobile network features, like shared medium and mobility, are considered defining the models to be taken into account such as the propagation models and the fluid flow scheduling model. The developed methodology provides accurate computation of these KPIs, while performing orders of magnitude faster than discrete event simulators like ns-3. Finally, this methodology combined to its capacity for performance estimation in MPLS networks enables its application for near real-time converged fixed-mobile networks operation as it is proven in three use case scenarios

Automated financial multi-path GETS modelling

General-to-Specific (GETS) modelling has witnessed major advances over the last decade thanks to the automation of multi-path GETS specification search. However, several scholars have argued that the estimation complexity associated with financial models constitutes an obstacle to multi-path GETS modelling in finance. We provide a result with associated methods that overcome many of the problems, and develop a simple but general and flexible algorithm that automates financial multi-path GETS modelling. Starting from a general model where the mean specification can contain autoregressive (AR) terms and explanatory variables, and where the exponential variance specification can include log-ARCH terms, log-GARCH terms, asymmetry terms, Bernoulli jumps and other explanatory variables, the algorithm we propose returns parsimonious mean and variance specifications, and a fat-tailed distribution of the standardised error if normality is rejected. The finite sample properties of the methods and of the algorithm are studied by means of extensive Monte Carlo simulations, and two empirical applications suggest the methods and algorithm are very useful in practice

Non-linear error correction, asymmetric adjustment and cointegration

This article links the intertemporal choice model with the non-linear error correction (NEC) model. It has three main components. First, it outlines a model of non-linear error correction, in which the linear error correction term ?Xt (the vector time series Xt is cointegrated, is the cointegrating vector) is replaced by the non-linear term g(?Xt), where g(.) is a non-linear function. Second, several types of asymmetries and the existence of multiple equilibria are discussed. The implications for the NEC model of trending targets are also explained. Third, it is shown that non-linear error correction is present in a trivariate series of UK employment, wage and capital stock.Publicad

Nonlinear error correction, asymmetric adjusment and cointegration

This paper has three main components. First, it outlines a model of nonlinear error correction (NEC) in which the linear error correction term a'Xt (the vector time series Xt is cointegrated, a is the cointegrating vector) is replaced by the nonlinear term g(a'X),ˇ where g(.) is a nonlinear function. Second, several types of asymmetries are discussed. The NEC model is shown to have an underlying structural model in the form of an adjustment cost model, with asymmetric adjustment costs. The implications for the NEC model of trending targets are explained. Third, it is shown that nonlinear error correction is present in a trivariate series of UK employment, wage, and capital stock

Testing Nonlinearity: Decision Rules for Selecting between Logistic and Exponential STAR Models

A new LM specification procedure to choose between Logistic and Exponential Smooth Transition Autoregressive (STAR) models is introduced. The new decision rule has better properties than those previously available in the literature when the model is ESTAR and similar properties when the model is LSTAR. A simple natural extension of the usual LM-test for linearity is introduced and evaluated in terms of power. Monte-Carlo simulations and empirical evidence are provided in support of our claims.Publicad

Cointegration and common factors

Alternative common factors representations for cointegrated vectors are studied. It is shown that dynamic factor models produce as particular cases the alternative common trend representations for cointegrated variables available in the literature, including the one of Stock and Watson(1988). Furthermore, it is proved that common factor representations with I(1) components imply cointegration. A more efficient procedure for fmding the numbers of cointegrated vectors based on this dynamic factors model is suggested

Nonlinear cointegration and nonlinear error correction

The relationships between stochastic trending variables given by the concepts of cointegration and error correction (EC) are well characterized in a linear context, but the extension to a nonlinear context is still a challenge. Few extensions of the linear framework were developed in the context of linear cointegration but nonlinear error correction (NEC) models, and even in this context, there are still many open questions. The theoretical framework is not well developed at this moment and only particular cases have been discussed empirically. In this paper we propose a statistical framework that allow us to address those issues. First, we generalize the notion of integration to the nonlinear case. As a result a generalization of cointegration is feasible, and also a formal definition of NEC models. Within this framework we analyze the nonlinear least squares (NLS) estimation of nonlinear cointegration relations and the extension of the two-step estimation procedures of Engle and Granger (1987) for NEC models. Finally, we discuss a generalization of Granger Representation Theorem to the nonlinear case and discuss the properties of the onestep (NLS) procedure to estimate NEC models

Nonlinear Error Correction Models

The relationship between cointegration and error correction (EC) models is well characterized in a linear context, but the extension to the nonlinear context is still a challenge. Few extensions of the linear framework have been done in the context of nonlinear error correction (NEC) or asymmetric and time varying error correction models. In this paper, we propose a theoretical framework based on the concept of near epoch dependence (NED) that allows us to formally address these issues. In particular, we partially extend the Granger Representation Theorem to the nonlinear case.Publicad

Catching up in total factor productivity through the business cycle : evidence from Spanish manufacturing surveys

Spain has recently experienced more than a decade of price stability and economic growth however now is showing one of the most significant slowdowns in economic activity of the EU economies. There is a general consensus that this slowdown in economic activity is particularly important in Spain due to the low level and low rates of growth experienced by total factor productivity (TFP) during more than a decade. Among the key policy elements that could enhance TFP of manufacturing firms in Spain we find those related to human capital, foreign direct investment, and process innovations. We evaluate the effect of recessions on the productivity growth of firms with different level of productivity. We present evidence on the dynamic of firm’s TFP through the business cycle allowing for a differentiated behavior for technological leaders and followers. We observe lower persistence and faster convergence in TFP during recessions and, higher persistence and non convergence in TFP during expansions. These empirical findings are consistent with the predictions obtained from the technological diffusion literature and from the fact that firm’s innovation is pro-cyclical. These conclusions are obtained from a microeconometric analysis of surveys of Spanish manufacturing firms (ESEE) from 1991 to year 2005