This paper examines the health-related expenditures of economic agents in Democratic Republic Congo (households, government and its external technical financial partners). Given health care high costs DRC, access to appropriate is hindered due low income. As a result, partners indispensably step ensure that vulnerable households are protected from ruinous expenses. 
 At same time, provides...

A Bayesian model averaging procedure is presented that makes use of a …nite mixture of many model structures within the class of vector autoregressive (VAR) processes. It is applied to two empirical issues. First, stability of the “Great Ratios” in U.S. macro-economic time series is investigated, together with the e¤ect of permanent shocks on business cycles. Second, the linear VAR model is ext...

The vector autoregressive (VAR) model is a powerful tool in learning complex time series and has been exploited in many fields. The VAR model poses some unique challenges to researchers: On one hand, the dimensionality, introduced by incorporating multiple numbers of time series and adding the order of the vector autoregression, is usually much higher than the time series length; On the other h...

This paper examines jump dynamic patterns in three Chinese medical stocks. It also compares the Value-at-Risk (VaR) forecasting performance of a newly proposed realized volatility model allowing for jumps with that of two commonly used realized volatility models, which do not account for jumps. Using the Heterogeneous Autoregressive Realized Volatility model that allows for jumps (HAR-CJN), we ...

We develop a new asymptotic theory for autocorrelation robust tests using a vector autoregressive (VAR) covariance matrix estimator. In contrast to the conventional asymptotics where the VAR order goes to in…nity but at a slower rate than the sample size, we have the VAR order grow at the same rate, as a …xed fraction of the sample size. Under this …xed-smoothing asymptotic speci…cation, the as...

This paper employs a bivaraite vector autoregressive-generalized autoregressive conditional heteroscedasticity (VAR-GARCH) model recently developed by Ling and McAleer (2003) to examine the impact of oil price fluctuations on stock market returns in the Kingdom of Saudi Arabia over the period from January 1, 2007 to December 31, 2011. The proposed model is estimated using maximum likelihood met...

Direct measures of expectations are derived from survey data series in ̄ve European economies over the period 1968-1998. No evidence is found with which to reject rationality in tests applied to these derived series. A Vector Autoregressive (VAR) model of actual and expected output is then used to derive alternative measures of trend output and these measures are compared with the trend obtaine...

We study the problem of learning the dependency graph between random processes in a Vector Autoregressive (VAR) model from samples when a subset of the variables are latent. We show that the dependencies among the observed processes can be identified successfully under some conditions on the VAR model. Moreover, we can recover the length of all directed paths between any two observed processes ...