GcRsqYX: Nonlinear Granger causality between two time series workhorse...

In generalCorr: Generalized Correlations, Causal Paths and Portfolio Selection

Nonlinear Granger causality between two time series workhorse function.

Description

Function input is y=LHS=First time series and x=RHS=Second time series. Kernel regression np package options regtype="ll" for local linear, and bwmethod="cv.aic" for AIC-based bandwidth selection are fixed. Denote Rsq=Rsquare=R^2 in nonlinear kernel regression. GcRsqYX(.) computes the following two R^2 values. out[1]=Rsqyyx = R^2 when we regress y on own lags of y and x. out[2]=Rsqyy = R^2 when we regress y on lags of y alone.

Usage

GcRsqYX(y, x, px = 4, py = 4, pwanted = 4, ctrl = 0)

Arguments

y	The data vector y for the Left side or dependent or first variable
x	The data vector x for the right side or explanatory or second variable
px	number of lags of x in the data
py	number of lags of y in the data. px=4 for quarterly data
pwanted	number of lags of both x and y wanted for Granger causal analysis
ctrl	data matrix for designated control variable(s) outside causal paths default=0 means no control variables are present

Value

This function returns a set of 2 numbers measuring nonlinear Granger-causality for time series. out[1]=Rsqyyx, out[2]=Rsqyy.

Note

If data are annual or if no quarterly-type structure is present, use this function with pwanted=px=py. For example, the egg or chicken data from lmtest package.

Author(s)

Prof. H. D. Vinod, Economics Dept., Fordham University, NY.

References

Vinod, H. D. 'Generalized Correlation and Kernel Causality with Applications in Development Economics' in Communications in Statistics -Simulation and Computation, 2015, \Sexpr[results=rd]{tools:::Rd_expr_doi("10.1080/03610918.2015.1122048")}

Vinod, H. D. 'New exogeneity tests and causal paths,' Chapter 2 in 'Handbook of Statistics: Conceptual Econometrics Using R', Vol.32, co-editors: H. D. Vinod and C.R. Rao. New York: North Holland, Elsevier Science Publishers, 2019, pp. 33-64.

Vinod, H. D. Causal Paths and Exogeneity Tests in Generalcorr Package for Air Pollution and Monetary Policy (June 6, 2017). Available at SSRN: https://www.ssrn.com/abstract=2982128

Zheng, S., Shi, N.-Z., Zhang, Z., 2012. Generalized measures of correlation for asymmetry, nonlinearity, and beyond. Journal of the American Statistical Association 107, 1239-1252.

See Also

GcRsqX12, kern2, kern2ctrl.

Examples

## Not run: 
library(Ecdat);options(np.messages=FALSE);attach(data.frame(MoneyUS))
GcRsqYX(y,m)  

## End(Not run)

generalCorr documentation built on Oct. 10, 2023, 1:06 a.m.