A Unifying framework for analysing common cyclical features in cointegrated time series

This paper provides a unifying framework in which the coexistence of different form of common cyclical features can be tested and imposed to a cointegrated VAR model. This goal is reached by introducing a new notion of common cyclical features, namely the weak form of polynomial serial correlation common features, which encompasses most of the previous ones. Statistical inference is obtained by means of reduced-rank regression, and alternative forms of common cyclical features are detected by means of tests for over-identifying restrictions on the parameters of the new model. Some iterative estimation procedures are then proposed for simultaneously modelling different forms of common features. Concepts and methods are illustrated by an empirical investigation of the US business cycle indicators

Codependence and Cointegration

We introduce the idea of common serial correlation features among non-stationary, cointegrated variables. That is, the time series do not only trend together in the long run, but adjustment restores equilibrium immediately in the period following a deviation. Allowing for delayed re-equilibration, we extend the framework to codependence. The restrictions derived for VECMs exhibiting the common feature are checked by LR and GMM-type tests. Alongside, we provide corrected maximum codependence orders and discuss identification. The concept is applied to US and European interest rate data, examining the capability of the Fed and ECB to control overnight money market rates

Codependence and Cointegration

We introduce the idea of common serial correlation features among non-stationary, cointegrated variables. That is, the time series do not only trend together in the long run, but adjustment restores equilibrium immediately in the period following a deviation. Allowing for delayed re-equilibration, we extend the framework to codependence. The restrictions derived for VECMs exhibiting the common feature are checked by LR and GMM-type tests. Alongside, we provide corrected maximum codependence orders and discuss identification. The concept is applied to US and European interest rate data, examining the capability of the Fed and ECB to control overnight money market rates.VAR; serial correlation common features; codependence; cointegration

Forecasting aggregate and disaggregates with common features.

The paper is focused on providing joint consistent forecasts for an aggregate and all its components and in showing that this indirect forecast of the aggregate is at least as accurate as the direct one. The procedure developed in the paper is a disaggregated approach based on single-equation models for the components, which take into account common stable features which some components share between them. The procedure is applied to forecasting euro area, UK and US inflation and it is shown that its forecasts are significantly more accurate than the ones obtained by the direct forecast of the aggregate or by dynamic factor models. A by-product of the procedure is the classification of a large number of components by restrictions shared between them, which could be also useful in other respects, as the application of dynamic factors, the definition of intermediate aggregates or the formulation of models with unobserved componentsCommon trends; Common serial correlation; Inflation; Euro Area; UK; US; Cointegration; Single-equation econometric models;

Modelling comovements of economic time series: a selective survey

Modelling comovements amongst multiple economic variables takes up a relevant part of the literature in time series econometrics. Comovement can be defined as “move together”, that is as movement that several series have in common. The pattern of the series could be of different nature, such as trend, cycles, seasonality, being the results of different driving forces. As a results, series that comove share some common features. Common trends, common cycles, common seasonality are terms that are often found in the literature, different in scope but all aimed at modeling common behavior of the series. However, modeling comovements is not only a statistical matter, since in many cases common features are predicted by economic theory, resulting from the optimizing behavior of economic agents

How Strong is the Case for Dollarization in Costa Rica? A Note on the Business Cycle Comovements with the United States

We evaluate the proposal for official dollarization in Costa Rica by applying a new approach to measure the business cycle comovements with the United States. While the literature often focuses on the correlation of shocks, we point out that the response of each country to the shocks is also an important aspect of stabilization policy. We analyze whether Costa Rica and the United States share a common synchronized response to shocks, i.e. a common business cycle, using the Engle and Kozicki (1993) and Cubadda (1999, 2007) serial correlation common features tests, in a quarterly GDP data set from 1991 to 2008. Although we find some tendency towards common AR(p) structures and common long run trends, we reject the hypothesis that the two countries share a common business cycle. Based on this evidence, we conclude that official dollarization in Costa Rica would impede the efforts of its stabilization policy, despite the relatively high contemporaneous correlation of shocks.Dollarization, Business Cycle Comovement, Serial Correlation Common Feature, Central America, Costa Rica

How Strong is the Case for Dollarization in Costa Rica? A Note on the Business Cycle Comovements with the United States

We evaluate the proposal for official dollarization in Costa Rica by applying a new approach to measure the business cycle comovements with the United States. While the literature often focuses on the correlation of shocks, we point out that the response of each country to the shocks is also an important aspect of stabilization policy. We analyze whether Costa Rica and the United States share a common synchronized response to shocks, i.e. a common business cycle, using the Engle and Kozicki (1993) and Cubadda (1999, 2007) serial correlation common features tests, in a quarterly GDP data set from 1991 to 2008. Although we find some tendency towards common AR(p) structures and common long run trends, we reject the hypothesis that the two countries share a common business cycle. Based on this evidence, we conclude that official dollarization in Costa Rica would impede the efforts of its stabilization policy, despite the relatively high contemporaneous correlation of shocks.dollarization, business cycle comovement, serial correlation common feature, Central America, Costa Rica

How Strong is the Case for Dollarization in Central America? An Empirical Analysis of Business Cycles, Credit Market Imperfections and the Exchange Rate

In this paper, we contrast two different views in the debate on official dollarization. The Mundell (1961) framework of optimal currency areas and a model on boom-bust cycles, by Schneider and Tornell (2004), who take account of credit market imperfections prevalent in middle income countries. We highlight that the role of the exchange rate is strikingly different in the two models. While in the Mundell framework the exchange rate is expected to smooth the business cycle, the other model predicts that the exchange rate plays an amplifying role. We empirically evaluate both models for eight highly dollarized Central American economies, and find that the main benefit of official dollarization derives from avoiding a mismatch between foreign currency liabilities and domestic revenues, as well as the boom-bust episodes that are likely to follow from it. Using a new method of Cubadda (1999, 2007), we furthermore test for cyclical comovement and reject the hypothesis that the countries form an optimal currency area with the United States according to the Mundell definition.dollarization, real exchange rate, business cycle comovement, serial correlation, common feature, boom-bust cycles, credit market imperfections, Central America

Forecasting aggregates and disaggregates with common features

This paper focuses on the provision of consistent forecasts for an aggregate economic indicator, such as a consumer price index and its components. The procedure developed is a disaggregated approach based on single-equation models for the components, which take into account the stable features that some components share, such as a common trend and common serial correlation. Our procedure starts by classifying a large number of components based on restrictions from common features. The result of this classification is a disaggregation map, which may also be useful in applying dynamic factors, defining intermediate aggregates or formulating models with unobserved components. We use the procedure to forecast inflation in the Euro area, the UK and the US. Our forecasts are significantly more accurate than either a direct forecast of the aggregate or various other indirect forecasts.Antoni Espasa acknowledges financial support from Ministerio de Educacin y Ciencia, proyect ECO 2009-0810

Discovering pervasive and non-pervasive common cycles

The objective of this paper is to propose a strategy to exploit short-run commonalities in the sectoral components of macroeconomic variables to obtain better models and more accurate forecasts of the aggregate and of the components. Our main contribution concerns cases in which the number of components is large, so that traditional multivariate approaches are not feasible. We show analytically and by Monte Carlo methods that subsets of components in which all the elements share a single common cycle can be discovered by pairwise methods. As the procedure does not rely on any kind of cross-sectional averaging strategy: it does not need to assume pervasiveness, it can deal with highly correlated idiosyncratic components and it does not need to assume that the size of the subsets goes to infinity. Nonetheless, the procedure works both with fixed N and T going to infinity, and with T and N both going to infinity.The second author acknowledge financial support from the Spanish Ministry of Education and Science, research project ECO2012-3240