Productivity and stock prices.

This study looks at the degree of correlation between stock prices and productivity at different levels, i.e. analysis of the correlations between certain components of the two variables and how correlations vary according to the different frequencies characterising these variables. It should be acknowledged that the approach used is only designed to isolate the stylised facts related to the cyclical components of the variables under review and not to explain them. In particular, the method chosen cannot be used to make forecasts or to provide a refi ned economic interpretation of these stylised facts. Nonetheless, this analysis, applied to the United States and the euro area over the period 1973(1)-1985(4), highlights the following points: • in the United States, an increase (or reduction) in the cyclical component of the rate of stock returns is positively correlated with current or future increases (or reductions) in that of the productivity growth rate; • in the euro area, this correlation is less strong. It appears, for example, that a sharp fall in stock prices precedes a marked decline in productivity (link between stock prices and future productivity) and, as a result, in profi ts. This fall could then be interpreted as a normal, even desirable, adjustment mechanism for asset prices. Correspondingly, a sharp rise in stock prices should not automatically be interpreted as the emergence of a future bubble given that such rises appear to foreshadow an increase in productivity and therefore in profi ts. Over the most recent period 1986(1)-2002(4), these correlations appear less pronounced, thus indicating a possible break. Our result is robust given that two complementary methods corroborate it and that it is similar to Estrella’s (2003) findings for the United States. This pattern appears to suggest that the cyclical component of stock prices is in phase with that of productivity.

Equity market interdependence: the relationship between European and US stock markets.

In this article, the degree of interdependence between European and US stock markets is measured by the conditional correlation between stock returns: the correlation coefficient is estimated using a model describing the variations over time in a number of variables (returns and volatility, for example), and its estimate takes account of all available information at a given time. We estimate conditional variance in the same way. Moreover, two statistical tools, recently introduced in applied finance, are combined. The first, developed by Engle in 2001 – an original specification of the conditional correlations in multivariate models – enables us to describe time-varying correlations between two or more assets. The second tool, copula functions, allows us to apply distributions that are more consistent with the stylised facts observed on financial markets than those commonly used. The approach used in this study is original in that it combines both the above tools. Using a multivariate model implies rejecting the two assumptions traditionally adopted in empirical studies in finance: correlations between assets are presumed to be constant; asymmetry or the presence of rare events are not taken into account in asset price distributions. Consequently, our empirical findings corroborate the assumption that correlations vary over time and validate the choice of an asymmetric joint distribution integrating the presence of rare events. We also observe the presence of periods of strong and weak correlations and similar periods for volatility. Furthermore, our results highlight a close link between the correlations and volatilities observed on the different equity markets: in phases of high volatility, the correlation tends to rise above its medium-term average; inversely, in phases of low volatility, markets seem to display greater independence. Lastly, the correlation coefficient of close to 1 confirms that French and German stock market indices have been converging in recent years. This may reflect the growing integration of these two markets and of the economies of these two countries within Economic and Monetary Union.

Technology Shocks and Monetary Policy in an Estimated Sticky Price Model of the Euro Area.

In this paper, we seek to characterize the dynamic effects of permanent technology shocks and the way in which European monetary authorities reacted to these shocks over the past two decades. To do so, we develop an augmented sticky price-sticky wage model of the business cycle, which is estimated by minimizing the distance between theoretical, dynamic responses of key variables to a permanent technology shock and their structural VAR counterparts. In a second step, we conduct a counterfactual experiment consisting to compare these responses with the outcome of the optimal monetary policy. A significant discrepancy emerges between these responses, suggesting the European monetary authorities might not have responded optimally to permanent technology shocks.Sticky prices and wages ; Taylor rule ; Optimal monetary policy.

Interest Rate Transmission and Volatility Transmission along the Yield Curve.

In order to analyse the interest rate transmission mechanism, we study daily Euro-rates term structure for the US, Germany, and the UK between 1983 and 1997. We estimate multivariate VECM-GARCH models, which take into account moste of the usual features of financial data (non-stationarity, cointegration, heteroskedasticity, asymmetric effects) The estimates of these models, allows us to study interest rate transmission as well as volatility transmission along the yield curve. Due to the huge number of the parameters it is quite difficult to interpret the empirical result. To avoid this problem we use the impulse responses framework to examine the transmission mechanism along both the yield and volatility curves.Term structure ; Volatility spillovers ; Financial Market ; Interest Rate

On the Welfare Costs of Misspecified Monetary Policy Objectives

This paper quantifies the effects on welfare of misspecified monetary policy objectives in a stylized DSGE model. We show that using inappropriate objectives generates relatively large welfare costs. When expressed in terms of ‘consumption equivalent’ units, these costs correspond to permanent decreases in steady-state consumption of up to two percent. The latter are generated by both the inappropriate choice of weights and the omission of variables. In particular, it is costly to assume an interest-rate smoothing incentive for central bankers when it is not socially optimal to do so. Finally, a parameter uncertainty decomposition indicates that uncertainty about the properties of markup shocks gives rise to the largest welfare costs.Welfare ; Monetary policy objectives ; DSGE model ; Bayesian econometrics.

Interactions between Business Cycles, stock Market Cycles and Interest Rates: the Stylised Facts.

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.Stock returns ; Comovements ; Turning points ; Spectral analysis.

FACTORS AFFECTING THE NUMBER AND TYPE OF SMALL-FARM DIRECT MARKETING OUTLETS IN MISSISSIPPI

The objective of this study was to delineate and measure the effects of selected economic demographic characteristics of Mississippi counties on the number and type of direct marketing of fruits and vegetables. A combination of primary data collected through a survey of county agents and secondary data from government sources were assembled to achieve the objective. Regression equations representing pick-your own marketing, farmerÂ’s' markets and farm stands were estimated with the iterative three stage least squares technique. Results indicated that economic factors such as income, employment, acreage, and demographic factors (e.g., total population of county, and the size of cities and towns within county boundaries) have varied impacts on the different types of direct marketing.Agribusiness,

Bayesian single-epoch photometric classification of supernovae

Ongoing supernova (SN) surveys find hundreds of candidates that require confirmation for their various uses. Traditional classification based on follow- up spectroscopy of all candidates is virtually impossible for these large samples. The use of Type Ia SNe as standard candles is at an evolved stage that requires pure, uncontaminated samples. However, other SN survey applications, such as measuring cosmic SN rates, could benefit froma classification of SNe on a statistical basis, rather than case by case. With this objective in mind, we have developed the SN-ABC, an automatic Bayesian classifying algorithm for supernovae. We rely solely on single- epoch multiband photometry and host-galaxy (photometric) redshift information to sort SN candidates into the two major types, Ia and core-collapse supernovae. We test the SN-ABC performance on published samples of SNe from the Supernova Legacy Survey (SNLS) and GOODS projects that have both broadband photometry and spectroscopic classification (so the true type is known). The SN- ABC correctly classifies up to 97% (85%) of the Type Ia (II-P) SNe in SNLS, and similar fractions of the GOODS SNe, depending on photometric redshift quality. Using simulations with large artificial samples, we find similarly high success fractions for Types Ia and II-P, and reasonable (~75%) success rates in classifying Type Ibc SNe as core-collapse. Type IIn SNe, however, are often misclassified as Type Ia. In deep surveys, SNe Ia are best classified at redshifts z ≳ 0.6 or when near maximum. Core-collapse SNe (other than Type IIn) are best recognized several weeks after maximum, or at z ≾ 0.6. Assuming the SNe are young, as would be the case for rolling surveys, the success fractions improve by a degree dependent on the type and redshift. The fractional contamination of a single-epoch photometrically selected sample of SNe la by core-collapse SNe varies between less than 10% and as much as 30%, depending on the intrinsic fraction and redshift distribution of the core-collapse SNe in a given survey. The SN-ABC also allows the rejection of SN "impostors" such as active galactic nuclei (AGNs), with half of the AGNs we simulate rejected by the algorithm. Our algorithm also supplies a good measure of the quality of the classification, which is valuable for error estimation