GcRsqYXc function

Nonlinear Granger causality between two time series workhorse function.(local constant version)

Function input is y=LHS=First time series and x=RHS=Second time series. Kernel regression np package options regtype="lc" for local constant, and bwmethod="cv.ls" for least squares-based bandwidth selection are fixed. Denote Rsq=Rsquare=R^2 in nonlinear kernel regression. GcRsqYXc(.) 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 own lags of y alone.

GcRsqYXc(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

Returns

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, Thurman W.N. and Fisher M.E. (1988)

Examples

## Not run:

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

References

Vinod, H. D. `Generalized Correlation and Kernel Causality with Applications in Development Economics' in Communications in Statistics -Simulation and Computation, 2015, 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

GcRsqX12c

kern_ctrl

Author(s)

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