Laudatio on the occasion of the Investure of Professor John Denis Sargan with the Degree of Doctor Honoris Causa of the Universidad Carlos III, 2 de Febrero 1993

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A note on the acceptability of regression solutions: another look at computational accuracy.

This note examines the experiment performed by Beaton, Rubin, and Barone (1976) to study the effect of rounding errors in published figures, when these data are used in regression analysis. The experiment could be vitiated by the fact that the error introduced in the trend variable is by no means trivial when one measures the data in deviation from the mean. For this reason, the results presented in Beaton, Rubin, and Barone (1976) do not contain enough evidence to suggest "that it is extremely unlikely that the unperturbed solution" (p. 161) of the Longley model is the correct one.Regression analysis; Rounding adjustments;

The outlook of the Spanish economy in the first quarter of 1993.

The Spanish economy has experienced a quick integration into the European framework since the entrance into the EC in 1986. Thus, the percentage of total Spanish exports bound to Europe increased from 49.7% in 1980-1985 to 71.2% in 1992, and the percentage of total Spanish imports coming from Europe increased from 33% to 60.7%. This mean s that an analysis of the Spanish economy should be done by connecting it with the evolution experienced by the other European partners.Coyuntura económica; Crisis económica; España; S. XX; Comunidad Europea;

Comments on time-series analysis, forecasting and econometric modelling: The structural econometric modelling, time-series analysis (SEMTSA) approach, by A. Zellner.

Professor Zellner has greatly contributed to econometrics in many aspects. This paper compiles a line of research developed by him and associates tha t goes back to the early 1970s, in which time-series techniques and Bayesian analysis are used in the construction of econometric models.Modelo econométrico; Modelo matemático; Análisis de series temporales;

Parsimony and omitted factors: the airline model and the Census X-11 assumptions

El tipo de modelo Arima para el que el metodo de ajuste estacional X-11 es adecuado se ha identificado como (1-L)(1-L12)Xt=G(L)at, (CX), en donde G(L) es de orden 26. En este documento se aproxima el modelo CX mediante un modelo Arima (1,1,2)(0,1,1), con raices complejas en el factor MA regular y se demuestra que tal modelo tiene un factor de estabilidad -mayor potencia espectral en frecuencias bajas- que no esta presente en el "modelo de lineas aereas" propuesto por Box y Jenkins

Forecasting inflation in the euro area using monthly time series models and quarterly econometric models

Economic agents and financial authorities require frequent updates to a path of accurate inflation forecasts and need forecasts to include an explanation of the factors by which they are determined. This paper studies how to approach this need, developing a method for analysing inflation in the euro area, measured according to HICP. Time series models using the most recent information on prices and an important functional and geographically disaggregation can provide monthly forecasts which are reasonably accurate, but they do not provide an explanation of the factors by which the forecast is determined. In this respect, it is important to enlarge the data set used considering explanatory variables and build congruent econometric models including variables which, following previous works by D. Hendry, capture disequilibria on different markets, goods and services, labour, monetary and international. The final result of this work shows that combining the forecasts from a monthly time series vector model, constructed on price subindexes from a disaggregation of the HICP by countries and sectors, with the forecasts derived from a quarterly econometric vector model on aggregate inflation and other economic variables, very accurate forecasts are obtained. Both vector models are specified including empirical cointegration restrictions, which in the first case capture the constrains necessary present between the trends of the price subindexes and in the second approximate the long-run restrictions postulated by economic theory

Econometric modelling for short-term inflation forecasting in the EMU.

Inflation forecasts are in great demand by agents in financial markets and monetary authorities that also require frequent updates. In the case of the EMU, these can be done monthly using Harmonised Indices of Consumer Prices (HICP). Analysing the HICP it was detected in a previous paper that breaking down the HICP in a vector of n sectors so that each price index component corresponds to a group of relatively homogeneous markets, or in a vector of n countries, there are in both cases fewer than (n-1) cointegration relationships. It can then be said that the components of the index are not fully cointegrated in the sense that there is more than one common trend in the HICP vector. In such a case, one way to increase sample information about the HICP trend is to consider the n price components and approach disaggregated econometric modelling. The paper shows that the breakdown that joins both criteria by considering a price index for each large group of markets in each country improves EMU inflation forecasts and establishes a framework in which general and specific explanatory variables and non-linear structures can be introduced for further improvements. The paper shows that VEqCM of ten price indices " two sectors by five geographical areas " including three cointegration relationships, with a sector-block diagonal restriction, generates forecasts of the year-on-year inflation rate in the HICP such that their error variances are one third or one fifth of the forecast errors from an aggregate ARIMA model, depending whether the horizon is three or twelve months. This vector model also provides better forecasts than single-equation models or alternative vector models for the components. A successful formulation of the vector model requires the inclusion of dummy variables to take account of special events such as seasonality changes due to sales, the introduction of the euro, Greece becoming a member of the EMU, the introduction of ecological taxes, bad weather periods and others events altering the evolution of unprocessed food prices, etc. and the inclusion of international Brent prices in euros. With the breakdown used in the paper it is shown that a usual measure of core inflation is not a good predictor of total inflation, but the interest in core inflation could lie in the fact that its corresponding price index is constructed with price indices in which innovations are more persistent than those in the other consumer price indexes excluded from the core. The disaggregated forecasts presented in this paper are useful for policy-making because they tell us which sectors have the highest expected inflation rates and how persistent are the shocks affecting different sectors

A nonlinear model for the investment function in Spain

This paper developpes a nonlinear single equation econometric model for the investment function in Spain, taking as starting point the equation estimated by Andrés et al. (1990). This original model, linear in its structure, incorporates oscillant dynamic relationships between the dependent and the explanatory variables. In the nonlinear model estimated in this paper, the response of the investment to production depends at any moment on the relative prices of energy, as an indicator of uncertainty into the future. This allows the investment to response with big oscillations to movements in production only in moments of great uncertainty. This alternative model introduces a nonlinear error-correction scheme, in which the adjustments to the long-run equilibrium path are affected by an exogenous variable. The model also improves the original adjustment, by reducing the residual variance in more than 30%

Considerations on economic forecasting: method developed in the bulletin of EU and US inflation and macroeconomic analysis

This article presents economic forecasting as an activity acquiring full significance when it is involved in a decision-making process. The activity requires a sequence of functions consisting of gathering and organising data, the construction of econometric models and ongoing forecast evaluations to maintain a continuous process involving correction, perfecting and enlarging the data set and the econometric models used, systematically improving forecasting accuracy. With this approach, economic forecasting is an activity based on econometric models and statistical methods, applied economic research with all its general problems. One of these is related to economic data. The widespread belief that if economic information is published, it is valid fo