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%

Forecasting inflation in the european monetary union: a disaggregated approach by countries and by sectors

Inflation in the European Monetary Union is measured by the Harmonised Indices of Consumer Prices (HICP) and it can be analysed by breaking down the aggregate index in two different ways. One refers to the breakdown into price indexes corresponding to big groups of markets throughout the European countries and another considers the HICP by countries. Both disaggregations are of interest because in each one, the component prices are not fully cointegrated, having more than one common factor in their trends. The paper shows that the breakdown by group of markets improves the European inflation forecasts and constitutes a framework in which general and specific indicators can be introduced for further improvement

Forecasting monthly us consumer price indexes through a disaggregated I(2) analysis

In this paper we carry a disaggregated study of the monthly US Consumer Price Index (CPI). We consider a breakdown of US CPI in four subindexes, corresponding to four groups of markets: energy, food, rest of commodities and rest of services. This is seen as a relevant way to increase information in forecasting US CPI because the supplies and demands in those markets have very different characteristics. Consumer prices in the last three components show I(2) behavior, while the energy subindex shows a lower order of integration, but with segmentation in the growth rate. Even restricting the analysis to the series that show the same order of integration, the trending behavior of prices in these markets can be very different. An I(2) cointegration analysis on the mentioned last three components shows that there are several sources of nonstationarity in the US CPI components. A common trend analysis based on dynamic factor models confirms these results. The different trending behavior in the market prices suggests that theories for price determinations could differ through markets. In this context, disaggregation could help to improve forecasting accuracy. To show that this conjecture is valid for the non-energy US CPI, we have performed a forecasting exercise of each component, computed afterwards the aggregated value of the non energy US CPI and compared it with the forecasts obtained directly from a model for the aggregate. The improvement in one year ahead forecasts with the disaggregated approach is more than 20%, where the root mean squared error is employed as a measure of forecasting performance

Forecasting monetary union inflation: a disaggregated approach by countries and by sectors.

Inflation in the European Monetary Union is measured by the Ra.IlJllonised Consumer Price Index (RCP!) and it can be analysed by breaking down the aggregate index in two different ways. One refers to the breakdown into price indexes corresponding to big groups of markets throughout the European countries and another considers the RCP! by countries. The paper shows that both disaggregations are of interest because in each one, the component prices are not fully cointegrated and then have more than one common factor. For purposes of forecasting the RCP! for the global EMU the disaggregation matters in all the horizons, one to twelve months, considered in the paper. The question is that innovations in an aggregate of non-fully cointegrated componentes will have different long-run effects depending on the common trend which they mainly stem from. Then the resulting ARIMA model for the aggregate can have a quite complex structure which restrictions which could be captured more easily through a disaggregate approachCore inflation; Cointegration; Univariate models; VeqCM;

Macroeconomic forecasts for the euro-zone and some policy implications.

This paper deals with the recent evolution, perspectives and some policy considerations for the Euro-Zone on the basis of the analysis of inflation, GDP and Industrial Production in EMU. The analysis shows that the year on year rates of growth will recover form the third quarter of 2002 for GDP and from October 2002 for Industrial Production. Regarding inflation, the ECB target of 2% will be attained between March and November 2002, but after this month, and during 2003 inflation will be around 2,1%

Consideraciones sobre la función de inversión en España

En este artículo se realiza un estudio detenido del modelo para la inversión estimado por Andrés et al. (1990). Dicha estimación contiene filtros racionales con raíces complejas que producen respuestas oscilantes ante variaciones de tipo impulso sobre las variables explicativas. Se detecta que tal característica de los filtros se debe a que las oscilaciones en la inversión ocurridas en los años de las crisis energéticas, 1974-80, sólo pueden captarse en el modelo mencionado mediante filtros, ya que las variables explicativas no contienen oscilaciones de tal magnitud. En este trabajo se permite que la respuesta de la inversión ante variaciones en la producción sea función de los precios relativos de la energía, con lo que las grandes oscilaciones de éstas se transmiten a la inversión. Con ello desaparece la necesidad de incorporar una estruetura oscilante en la respuesta de la inversión respecto al producto en ausencia de perturbaciones importantes en los precios relativos de la energía. El modelo obtenido en este trabajo supone una reducción de la varianza residual del 32.4 por ciento respecto al modelo de Andrés et al. (1990)

A two factor model to combine US inflation forecasts

The combination of individual forecasts is often a useful tool to improve forecast accuracy. The most commonly used technique for forecast combination is the mean, and it has frequently proven hard to beat. This paper considers factor analysis to combine US inflation forecasts showing that just one factor is not enough to beat the mean and that the second one is necessary. The first factor is usually a weighted mean of the variables and it can be interpreted as a consensus forecast, while the second factor generally provides the differences among the variables and, since our observations are forecasts, it may be related with the dispersion in the forecasting expectations and in a sense with its uncertainty. Within this approach, the paper also revisits Friedman's hypothesis relating the level of inflation with uncertainty in expectations at the beginning of the 21st century

MACROECONOMIC FORECASTS FOR THE EURO-ZONE AND SOME POLICY IMPLICATIONS.

This paper deals with the recent evolution, perspectives and some policy considerations for the Euro-Zone on the basis of the analysis of inflation, GDP and Industrial Production in EMU. The analysis shows that the year on year rates of growth will recover form the third quarter of 2002 for GDP and from October 2002 for Industrial Production. Regarding inflation, the ECB target of 2% will be attained between March and November 2002, but after this month, and during 2003 inflation will be around 2,1%.

22 Years of inflation assessment and forecasting experience at the bulletin of EU & US inflation and macroeconomic analysis

The Bulletin of EU & US Inflation and Macroeconomic Analysis (BIAM) is a monthly publication that has been reporting real time analysis and forecasts for inflation and other macroeconomic aggregates for the Euro Area, the US and Spain since 1994. The BIAM inflation forecasting methodology stands on working with useful disaggregation schemes, using leading indicators when possible and applying outliers' correction. The paper relates this methodology to corresponding topics in the literature and discusses the design of disaggregation schemes. It concludes that those schemes would be useful if they were formulated according to economic, institutional and statistical criteria aiming to end up with a set of components with very different statistical properties for which valid single-equation models could be built. The BIAM assessment, which derives from a new observation, is based on (a) an evaluation of the forecasting errors (innovations) at the components' level. It provides information on which sectors they come from and allows, when required, for the appropriate correction in the specific models. (b) In updating the path forecast with its corresponding fan chart. Finally, we show that BIAM real time Euro Area inflation forecasts compare successfully with the consensus from the ECB Survey of Professional Forecasters, one and two years ahead.Along these 22 years many people have contributed to this Bulletin and this paper has benefited from their work. It would be impossible to name all these contributors but we want to express our deepest gratitude to them. Since 2002, Angel Sánchez has been responsible for the analysis of the US economy and we are very grateful for providing some material for this paper. Our many thanks also to Guillermo Carlomagno for his permission for using some results from his PhD thesis. The authors acknowledge financial support from Spanish Ministry of Economy and Competitiveness project numbers (MINECO/FEDER) ECO2015-70331-C2-2-R, ECO2015-66593-P and ECO2016-76818-C3-3-P

Circulant singular spectrum analysis: A new automated procedure for signal extraction

Sometimes, it is of interest to single out the fluctuations associated to a given frequency. We propose a new variant of SSA, Circulant SSA (CiSSA), that allows to extract the signal associated to any frequency specified beforehand. This is a novelty when compared with other SSA procedures that need to identify ex-post the frequencies associated to the extracted signals. We prove that CiSSA is asymptotically equivalent to these alternative procedures although with the advantage of avoiding the need of the subsequent frequency identification. We check its good performance and compare it to alternative SSA methods through several simulations for linear and nonlinear time series. We also prove its validity in the nonstationary case. We apply CiSSA in two different fields to show how it works with real data and find that it behaves successfully in both applications. Finally, we compare the performance of CiSSA with other state of the art techniques used for nonlinear and nonstationary signals with amplitude and frequency varying in timeFinancial support from the Spanish government, contract grants MINECO/FEDER ECO2015-70331-C2-1-R, ECO2015-66593-P, ECO2016-76818-C3-3-P, PID2019-107161GB-C32 and PID2019-108079GB-C22 is acknowledge