This paper assesses empirically the relationship between GDP per capita growth uctuations and the age structure and intensity of human capital across developed and developing countries We estimate a spatial vector autoregressive model of income dynamics where the economic distance between countries is de ned on their similarity in measures of human capital and its distribu tion across age group...

The paper examines the causal nexus between financial development and economic growth in India in a multivariate VAR model. The empirical analysis is based on cointegration and causality test. The cointegration test finds the presence of long run equilibrium relationship between financial development and economic growth. The Granger causality test finds the existence of bidirectional causality ...

Using model selection techniques based on out-of-sample predictive ability criterion in a Vector Autoregression (VAR) framework, this paper empirically examines the causal relations among growth, trade, and wage inequality in Bangladesh between 1971 and 2000. There is some evidence of bi-directional causality between growth and inequality and between trade and growth. That growth causes trade a...

We report evidence that the relation between the financial sector share, private savings and growth in the United States 1948–1996 is characterized by several regime shifts. The finding is based on vector autoregressions on quarterly data that allow for Markov switching regimes. The evidence may be interpreted as support for a hypothesis that the relation between financial development and growt...

Univariate autoregressive (AR) models can be extended to the multivariate case to study dynamic interrelationships among several variables, all viewed as endogenous. The resulting vector autoregression (V AR) models describe the evolution over time of a vector of n variables yt = (y1t y2t...ynt)0 as a function of its past realizations yt−1,yt−2, ... and a vector of stochastic terms ut = (u1t u2...

We explore two popular approaches to empirical analysis of monetary policy: the New Keynesian and the identified vector autoregression approaches. Stylized models of private behavior coupled with simple rules describing policy behavior characterize New Keynesian work. Vector autoregressions consist of minimally identified dynamic descriptions of private behavior coupled with a detailed rule for...

Vector Autoregression Models (VAR) are widely used by researchers to capture the linear interdependencies among multiple time series. We propose a novel method called Clustered VAR (CVAR) to identify components of the data generated by a mixture of K VAR processes. By applying a CVAR model to a consumer-level time series dataset on shopping behavior at a retailer, we segment consumers based on ...

This paper uses Monte Carlo simulations to evaluate alternative identi…cation strategies in VAR estimation of monetary models, and to assess the accuracy of measuring money instability as a cause of output ‡uctuations. I construct theoretical monetary economies using general equilibrium models with cash-in-advance constraints, which also include technology shocks, labor supply shocks, and monet...

Empirical evidence suggests that asset returns correlate more strongly in bear markets than conventional correlation estimates imply. We propose a method for determining complete tail–correlation matrices based on Value–at–Risk (VaR) estimates. We demonstrate how to obtain more efficient tail–correlation estimates by use of overidentification strategies and how to guarantee positive semidefinit...

Vector autoregressive models are often used in Macroeconomics to draw conclusions about the effects of policy innovations. However, those results depend on the researcher’s priors about the particular ordering of the variables. As an alternative, this paper presents a very simple rule based on the maximum entropy principle that can be used to find the “most likely” ordering. The proposal is ill...