Modified Variance Ratio Test for Autocorrelation in the Presence of Heteroskedasticity
Keywords:
Regression, variance break, wild bootstrap.Abstract
Given that autocorrelation tests do not perform well in the presence of heteroskedasticity and in variance-break cases, we present three modified weighted variance ratio tests of autocorrelation. The numerical results show that the proposed tests perform better for small samples. They provide a better approximation of asymptotic distributions and are more powerful when the lag length is mis-specified. The study also applies these tests to data on the daily returns of two companies listed on the Pakistan Stock Exchange.
References
Breusch, T. S. (1978). Testing for autocorrelation in dynamic linear models. Australian Economic Papers, 17(31), 334–355.
Engle, R. F. (1982). Autoregressive conditional heteroscedasticity with estimates of the variance of United Kingdom inflation. Econometrica, 50(4), 987–1007.
Godfrey, L. G. (1978). Testing against general autoregressive and moving average error models when the regressors include lagged dependent variables. Econometrica, 46(6), 1293–1301.
Guo, B., & Phillips, P. C. (2001). Testing for autocorrelation and unit roots in the presence of conditional heteroskedasticity of unknown form
(Economics Working Paper No. 540). Santa Cruz, CA: UC Santa Cruz.
Hyun, J.-Y., Mun, H. H., Kim, T.-H., & Jeong, J. (2010). The effect of a variance shift on the Breusch–Godfrey’s LM test. Applied Economics Letters, 17(4), 399–404.
Jeong, J., & Kang, B. (2012). Wild-bootstrapped variance-ratio test for autocorrelation in the presence of heteroskedasticity. Journal of
Applied Statistics, 39(7), 1531–1542.
Kim, J. H. (2006). Wild bootstrapping variance ratio tests. Economics Letters, 92(1), 38–43.
Lo, A. W., & MacKinlay, A. C. (1988). Stock market prices do not follow random walks: Evidence from a simple specification test. Review of
Financial Studies, 1(1), 41–66.
Mantalos, P., & Shukur, G. (2005). The effect of the GARCH (1, 1) on autocorrelation tests in dynamic systems of equations. Applied Economics, 37(16), 1907–1913.
Mun, H.-H., Shim, E.-Y., & Kim, T.-H. (2014). A robust test for autocorrelation in the presence of a structural break in variance.Journal of Statistical Computation and Simulation, 84(7), 1552–1562.
Pagan, A. (1984). Econometric issues in the analysis of regressions with generated regressors. International Economic Review, 25(1), 221–247.
Pagan, A. (1986). Two stage and related estimators and their applications. Review of Economic Studies, 53(4), 517–538.
Shim, E., Moon, H., & Kim, T. (2006). Autocorrelation tests robust to a structural break in variance. Unpublished manuscript, Yonsei University, Seoul.
Wooldridge, J. M. (1991). On the application of robust, regression-based diagnostics to models of conditional means and conditional variances. Journal of Econometrics, 47(1), 5–46.
Yasmin, B. (2009). Trade liberalization and the lead role of human capital and job attributes in wage determination: The case of Pakistan’s
labor market. Lahore Journal of Economics, 14(1), 1–37.
