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A Measure of Comovement for Economic Variables: Theory and Empirics

TL;DR: In this article, a measure of dynamic comovement between (possibly many) time series and names it cohesion is defined in the frequency domain and is appropriate for processes that are costationary, possibly after suitable transformations.
Abstract: This paper proposes a measure of dynamic comovement between (possibly many) time series and names it cohesion. The measure is defined in the frequency domain and is appropriate for processes that are costationary, possibly after suitable transformations. In the bivariate case, the measure reduces to dynamic correlation and is related, but not equal, to the well known quantities of coherence and coherency. Dynamic correlation on a frequency band equals (static) correlation of bandpass-filtered series. Moreover, long-run correlation and cohesion relate in a simple way to co-integration. Cohesion is useful to study problems of business-cycle synchronization, to investigate short-run and long-run dynamic properties of multiple time series, and to identify dynamic clusters. We use state income data for the United States and GDP data for European nations to provide an empirical illustration that is focused on the geographical aspects of business-cycle fluctuations.

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Citations
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Journal ArticleDOI
TL;DR: In this article, the characteristics and comovement of cycles in house prices, residential investment, credit, interest rates, and real activity in advanced economies during the past 25 years were described using a dynamic generalized factor model and spectral techniques.

78 citations


Cites methods from "A Measure of Comovement for Economi..."

  • ...The degree of comovement between cycles is measured using dynamic correlations (Croux, Forni, and Reichlin, 2001) and coherence and phase-angle statistics....

    [...]

Journal ArticleDOI
TL;DR: In this article, the co-movements between stock market indices and real economic activity over the business cycle in France, Germany, Italy, the United Kingdom and the United States, using two complementary approaches in their analysis.
Abstract: In this paper, we study the co-movements between stock market indices and real economic activity over the business cycle in France, Germany, Italy, the United Kingdom and the United States, using two complementary approaches in our analysis. First, we identify the turning points in real economy indicators and stock market indices and determine the extent to which these series co-move. Second, we calculate the correlations between the cyclical components of real economy indicators and excess returns, on the one hand, and the correlations between the structural components and these indicators, on the other. We then analyse the co-movements between three-month interest rates and the cyclical and structural components of the real economy and stock market indices.

75 citations


Cites methods from "A Measure of Comovement for Economi..."

  • ...Second, we compute the dynamic correlations between the studied variables, following the work by Croux et al. (2001)....

    [...]

Journal ArticleDOI
TL;DR: In this paper, a new approach based on a dynamic coherence function (DCF) was applied to study the interactions bringing together different real estate markets (the securitized market, the commercial market and the residential market).

74 citations

Journal ArticleDOI
TL;DR: In this paper, the authors establish stylized facts on economic linkages between NMS and the euro area using dynamic correlation and cohesion measures, and identify the main structural common euro-area shocks and investigate their transmission to NMS by means of a large scale factor model.

73 citations

Journal ArticleDOI
TL;DR: In this article, the effects of net tax and government spending shocks on GDP, inflation and interest rates were investigated in Germany, the UK and the US, and in cross-border fiscal spillovers from Germany to the seven largest European Union economies.
Abstract: This paper documents time variation in domestic fiscal policy multipliers in Germany, the UK and the US, and in cross-border fiscal spillovers from Germany to the seven largest European Union economies. We propose two VAR models which incorporate three "global factors" representing developments in the world economy, and we combine them with identification of fiscal shocks a la Blanchard and Perotti (2002) and Perotti (2005), to study the effects of net tax and government spending shocks on GDP, inflation and interest rates. By recursively estimating these models on different samples of data, we find that the domestic impact of tax shocks has been positive but vanishing for Germany and the US, stably not significant for the UK. Financial markets deregulations may play an important role in that since they allow households to be less dependent on disposable income and to smooth more easily consumption. Domestic government spending multipliers are found to be positive but feeble in the short-run and close to zero or slightly negative in the medium-run, implying that private consumption and investments might be crowded out. These results suggest that, in the European Monetary Union, discretionary fiscal policy "surprises" (i.e. unexpected tax cuts and government spending expansions) cannot be used by governments as substitutes for lost national monetary instruments, since they have shown to be progressively ineffective over time. Finally, we find that fiscal expansions in Germany have had beneficial (though declining) effects for neighboring countries, especially the smaller ones. This may indicate that the trade channel of transmission of fiscal policy dominates the interest rate one.

73 citations

References
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Journal ArticleDOI
TL;DR: The relationship between co-integration and error correction models, first suggested in Granger (1981), is here extended and used to develop estimation procedures, tests, and empirical examples.
Abstract: The relationship between co-integration and error correction models, first suggested in Granger (1981), is here extended and used to develop estimation procedures, tests, and empirical examples. If each element of a vector of time series x first achieves stationarity after differencing, but a linear combination a'x is already stationary, the time series x are said to be co-integrated with co-integrating vector a. There may be several such co-integrating vectors so that a becomes a matrix. Interpreting a'x,= 0 as a long run equilibrium, co-integration implies that deviations from equilibrium are stationary, with finite variance, even though the series themselves are nonstationary and have infinite variance. The paper presents a representation theorem based on Granger (1983), which connects the moving average, autoregressive, and error correction representations for co-integrated systems. A vector autoregression in differenced variables is incompatible with these representations. Estimation of these models is discussed and a simple but asymptotically efficient two-step estimator is proposed. Testing for co-integration combines the problems of unit root tests and tests with parameters unidentified under the null. Seven statistics are formulated and analyzed. The critical values of these statistics are calculated based on a Monte Carlo simulation. Using these critical values, the power properties of the tests are examined and one test procedure is recommended for application. In a series of examples it is found that consumption and income are co-integrated, wages and prices are not, short and long interest rates are, and nominal GNP is co-integrated with M2, but not M1, M3, or aggregate liquid assets.

27,170 citations

01 Jan 1987

3,983 citations


"A Measure of Comovement for Economi..." refers background in this paper

  • ...In this category belong the following three concepts: (i) the idea of co-integration (Engle & Granger, 1987): two processes are co-integrated if the spectral density at frequency zero has rank one; (ii) codependence (Gourieroux & Peaucelle, 1992), which refers to linear combinations of correlated…...

    [...]

Journal ArticleDOI
TL;DR: In this article, the authors present evidence that most of the unemployment fluctuations of the seventies (unlike those in the sixties) were induced by unusual structural shifts within the U.S. economy.
Abstract: A substantial fraction of cyclical unemployment is better characterized as fluctuations of the "frictional" or "natural" rate than as deviations from some relatively stable natural rate. Shifts of employment demand between sectors of the economy necessitate continuous labor reallocation. Since it takes time for workers to find new jobs, some unemployment is unavoidable. This paper presents evidence that most of the unemployment fluctuations of the seventies (unlike those in the sixties) were induced by unusual structural shifts within the U.S. economy. Simple time-series models of layoffs and unemployment are constructed that include a measure of structural shifts within the labor market. These models are estimated and a derived natural rate series is constructed.

1,128 citations

ReportDOI
TL;DR: In this paper, the authors introduce a class of statistical tests for the hypothesis that some feature that is present in each of several variables is common to them, which are data properties such as serial correlation, trends, seasonality, heteroscedasticity, auto-regression, and excess kurtosis.
Abstract: This article introduces a class of statistical tests for the hypothesis that some feature that is present in each of several variables is common to them. Features are data properties such as serial correlation, trends, seasonality, heteroscedasticity, autoregressive conditional hetero-scedasticity, and excess kurtosis. A feature is detected by a hypothesis test taking no feature as the null, and a common feature is detected by a test that finds linear combinations of variables with no feature. Often, an exact asymptotic critical value can be obtained that is simply a test of overidentifying restrictions in an instrumental variable regression. This article tests for a common international business cycle.

550 citations

Posted Content
TL;DR: The existence of a serial correlation common feature among the first differences of a set of I(1) variables implies the existence of common cycle in the Beveridge-Nelson-Stock-Watson decomposition of those variables as mentioned in this paper.
Abstract: The existence of a serial correlation common feature among the first differences of a set of I(1) variables implies the existence of a common cycle in the Beveridge-Nelson-Stock-Watson decomposition of those variables. A test for the existence of common cycles among cointegrated variables is developed. The test is used to examine the validity of the common trend-common cycle structure implied by Flavin's excess sensitivity hypothesis and Campbell and Mankiw's mixture of rational expectations and rule-of-thumb hypothesis for consumption and income. Linear independence between the cointegration and the cofeature vectors is exploited to decompose consumption and income into their trend and cycle components. Copyright 1993 by John Wiley & Sons, Ltd.

511 citations