Marco Gallegati

Wavelet analysis of stock returns and aggregate economic activity

The relationship between stock market returns and economic activity is investigated using signal decomposition techniques based on wavelet analysis. After the application of the maximum overlap discrete wavelet transform (MODWT) to the DJIA stock price index and the industrial production index for the US over the period 1961:1-2006:10 wavelet variance and cross-correlations analyses are used to investigate the scaling properties of the series and the lead/lag relationship between them at different time scales. The results show that stock market returns tend to lead the level of economic activity, but only at the highest scales (lowest frequencies) corresponding to periods of 16 months and longer, and that the leading period increases as the wavelet time scale increases.

A wavelet-based approach to test for financial market contagion

A wavelet-based approach to test whether contagion occurred during the US subprime crisis of 2007 is proposed. After separately identifying contagion and interdependence through wavelet decomposition of the original returns series, the presence of contagion is assessed using a simple graphical test based on non-overlapping confidence intervals of estimated wavelet coefficients in crisis and non-crisis periods. The results indicate that all stock markets have been affected by the US subprime crisis and that Brazil and Japan are the only countries in which contagion is observed at all scales.

The US Wage Phillips Curve across Frequencies and over Time

Although widely used in many areas of applied sciences, wavelet analysis has not fully entered the economic discipline yet. In this article we apply wavelet analysis to one of the most investigated relationships is in empirical macroeconomics: the relationship between wage inflation and unemployment. Using US postwar data we find a frequency-dependent relationship of a sort that is consistent with Phillips’ original insights. It also turns out that this relationship is remarkably stable over the 1948–93 period, but not in the aftermath, as a consequence of a process of adaption of the wage formation process to a low inflation environment.

Wavelet Variance Analysis of Output in G-7 Countries

The large decline in output volatility experienced by most industrialized countries in the last decades has been thoroughly analyzed using standard time and frequency domain methods. In this paper we investigate the issue of moderation of volatility in G-7 economies and its sources, applying a multi-scaling approach to the industrial production indices of G-7 countries between 1961:1-2006:10. Using the MODWT estimates of wavelet variance we provide a scale-based analysis of variance that allows us to characterize the decline in volatility and to detect the importance of the various explanations of the moderation. The main scale-by-scale results stemming from multi scale analysis of variance are: i) a reduction in volatility which, although displayed by all the G-7 countries, is not uniform across time scales (as the decline is larger at short-term scales than at business cycle scales for France and Italy, and quite uniform across scale for the UK and the US) nor countries (as the decline is significant for a subset of countries only, i.e. France, Italy, the UK and the US); and ii) the moderation has to be attributable to the decline in the variance of both common (in the 1970s) and country-specific (in the 1960s) exogenous disturbances hitting the economy.

Semiparametric analysis of the specialization-income relationship

In this paper we investigate the empirical relationship between overall specialization and per capita income. The metric we use to measure overall specialization is the median of the sectoral distribution of the Balassa index of Revealed Comparative Advantages applied to 4-digit (SITC rev.2) sectoral export manufactured data for 39 countries over the period 1985-2001. The result of the semiparametric analysis is that a negative relationship between this metric and per capita income emerges.

Financial constraints and the balance sheet channel: a re-interpretation

Aggregate demand models extending IS/LM fixed price framework yield an enhancement mechanism of the traditional monetary transmission mechanism, the credit channel, which, according to the credit view, works through the ‘balance sheet channel’ and the ‘bank lending channel’. In this paper the augmented IS/LM model is modified assuming that investments may be financed by both internal and external sources of funds. The inclusion of internal funds in the augmented IS/LM fixed price model suggests a different interpretation of the ‘balance sheet channel’ as an enhancement mechanism amplifying monetary policy effects through the quantity rather than the cost of borrowing. Thus, changes in borrowers’ net worth over the cycle can amplify and propagate output fluctuations directly rather than indirectly as in the traditional interpretation of the balance sheet channel. The empirical analysis of the monetary transmission mechanism for Italy in the last decade accords with the interpretation of the balance sheet channel proposed in this paper.

Chapter 4 The Decomposition of the Inflation–Unemployment Relationship by Time Scale Using Wavelets

Abstract In this paper we apply the wavelets methodology to the analysis of the Phillips curve for the US between 1957 and 2004. We decompose core CPI inflation and unemployment rate into different time scale components using the non-decimated discrete wavelet transform and then analyse the relationships among these variables at different time scales. According to our results the long-run Phillips curve is not vertical, as the nonparametric additive model provides evidence, at the lowest time scale, of a nonlinear (generally positive) relationship between inflation and unemployment, with unemployment lagging inflation by more than 4 years. As regards the trade-off at all other scales, we find that the relationship is linear and, even when it is statistically significant, is of borderline significance. Finally, the scatterplots provide evidence, at a detail level, of the so-called “Phillips loops”, loops that are particularly evident at business cycle scales.

Time Scale Analysis of Interest Rate Spreads and Output Using Wavelets

This paper adds to the literature on the information content of different spreads for real activity by explicitly taking into account the time scale relationship between a variety of monetary and financial indicators (real interest rate, term and credit spreads) and output growth. By means of wavelet-based exploratory data analysis we obtain richer results relative to the aggregate analysis by identifying the dominant scales of variation in the data and the scales and location at which structural breaks have occurred. Moreover, using the “double residuals” regression analysis on a scale-by-scale basis, we find that changes in the spread in several markets have different information content for output at different time frames. This is consistent with the idea that allowing for different time scales of variation in the data can provide a fruitful understanding of the complex dynamics of economic relationships between variables with non-stationary or transient components, certainly richer than those obtained using standard time domain methods.

Social networks and labour productivity in Europe: an empirical investigation

This paper uses firm-level data recorded in the Amadeus database to investigate the distribution of labour productivity in different European countries. We find that the upper tail of the empirical productivity distributions follows a decaying power-law, whose exponent α is obtained by a semi-parametric estimation technique recently developed by Clementi et al. [Physica A 370(1):49–53, 2006]. The emergence of “fat tails” in productivity distribution has already been detected in Di Matteo et al. [Eur Phys J B 47(3):459–466, 2005] and explained by means of a model of social network. Here we show that this model is tested on a broader sample of countries having different patterns of social network structure. These different social attitudes, measured using a social capital indicator, reflect in the power-law exponent estimates, verifying in this way the existence of linkages among firms’ productivity performance and social network.

Does Productivity Affect Unemployment? A Time-Frequency Analysis for the US

The effect of increased productivity on unemployment has long been disputed both theoretically and empirically. Although economists mostly agree on the long run positive effects of labor productivity, there is still much disagreement over the issue as to whether productivity growth is good or bad for employment in the short run. Does productivity growth increase or reduce unemployment? This paper try to answer this question by using the property of wavelet analysis to decompose economic time series into their time scale components, each associated to a specific frequency range. We decompose the relevant US time series data in different time scale components and consider co-movements of productivity and unemployment over different time horizons. In a nutshell, we conclude that, according to US post-war data, productivity creates unemployment in the short and medium terms, but employment in the long run.