Thanks to Kit Baum, a new package called stackreg is available on SSC.

In empirical work, researchers frequently test hypotheses of parallel form in several regressions, which raises concerns about multiple testing. One way to address the multiple testing issue is to jointly test the hypotheses (e.g. Pei et al. 2019; Lee and Lemieux 2010). While the existing commands suest (Weesie 1999) and mvreg enable Stata users to follow this approach, both are limited in several dimensions. For instance, mvreg assumes homoscedasticity and uncorrelatedness across sampling units and both commands are not designed to be used with panel data. stackreg overcomes the aforementioned limitations and allows for some settings and features that go beyond the capabilities of the existing commands. To achieve this, stackreg runs an ordinary least-squares regression in which the regression equations are stacked as for instance described in Wooldridge (2010, p.166–173), and applies cluster-robust variance-covariance estimation.

References

Lee, D. S. and Lemieux, T. (2010). Regression discontinuity designs in economics, Journal of Economic Literature 48(2): 281–355.

Pei, Z., Pischke, J.-S. and Schwandt, H. (2019). Poorly measured confounders are more useful on the left than on the right, Journal of Business & Economic Statistics 37(2): 205–216.

Weesie, J. (1999). Seemingly unrelated estimation and the cluster-adjusted sandwich estimator, Stata Technical Bulletin 52: 34–47.

Wooldridge, J. M. (2010). Econometric Analysis of Cross Section and Panel Data, 2 edn, MIT Press, Cambridge Massachusetts.

Best wishes,

Michael Oberfichtner

In empirical work, researchers frequently test hypotheses of parallel form in several regressions, which raises concerns about multiple testing. One way to address the multiple testing issue is to jointly test the hypotheses (e.g. Pei et al. 2019; Lee and Lemieux 2010). While the existing commands suest (Weesie 1999) and mvreg enable Stata users to follow this approach, both are limited in several dimensions. For instance, mvreg assumes homoscedasticity and uncorrelatedness across sampling units and both commands are not designed to be used with panel data. stackreg overcomes the aforementioned limitations and allows for some settings and features that go beyond the capabilities of the existing commands. To achieve this, stackreg runs an ordinary least-squares regression in which the regression equations are stacked as for instance described in Wooldridge (2010, p.166–173), and applies cluster-robust variance-covariance estimation.

References

Lee, D. S. and Lemieux, T. (2010). Regression discontinuity designs in economics, Journal of Economic Literature 48(2): 281–355.

Pei, Z., Pischke, J.-S. and Schwandt, H. (2019). Poorly measured confounders are more useful on the left than on the right, Journal of Business & Economic Statistics 37(2): 205–216.

Weesie, J. (1999). Seemingly unrelated estimation and the cluster-adjusted sandwich estimator, Stata Technical Bulletin 52: 34–47.

Wooldridge, J. M. (2010). Econometric Analysis of Cross Section and Panel Data, 2 edn, MIT Press, Cambridge Massachusetts.

Best wishes,

Michael Oberfichtner

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