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Posted 06-04-2016 09:40 PM
(3303 views)

Dear All,

I am running a time-series predictive regression, where left hand side is monthly returns and right hand side are some economic variables. According to Hodrick, R. (1992), I should not use the traditional standard error, but instead use the estimator of the standard errors that imposes the null hypothesis of no serial correlation in returns but does not impose an assumption of conditional homoskedasticity. i.e. Hodrick 1992 (IB)

How can I use SAS 9.4 to compute Hodrick 1992 (IB) standard error and two-sides p value?

Thanks very much.

Josephine

See below.

Hodrick, R. (1992), "Dividend Yields and Expected Stock Returns: Alternative Procedures for Inference and Measurement", Review of Financial Studies, vol 5, 357-386.

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Hello,

reading the paper I believe we don't have a direct implementation of this method in SAS. You can, however, use the AUTOREG or REG procedures to run OLS, get the residuals with the OUTPUT statement and calculate standard errors (equation 😎 in IML. Since the assymptotic distribution of the parameter estimates follows the normal distribution, large sample p-values for the two sided test are also easy to obtain in IML. The paper also suggests that the small sample empirical distribution is different from the assymptotic distribution and therefore if the sample is small the p-values might need to be obtain from a monte carlo simulation.

Thank you for posting,

Jan

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Dear Jan,

Thanks very much for your reply. I still do not understand how to calculate standard errors (equation 😎 in IML. Could you show me with the codes?

For example, now I get 3 columns: time t, independent variable vector x, residual e, can you show me the codes to compute alternative estimator of S0(equation 8).

After obtaining the estimator, what are the codes for performing monte carlo simulation with IML?

Thanks so much! I am new in IML, and I appreciate so much in your patience and effort!!

Best,

Josephine

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