Green (1989) provides a modified P test to deliver a consistent estimator of the different measures of the endogenous variables. It runs an auxiliary regression using the estimated residuals of the two competing models, instead of fitted values of the one same endogenous variable as in the P test ( Davidson and MacKinnon, 1981). Table 4.12 shows the modified P test results for the three groups of performance variables respectively.
Green (1989) points out the modified P estimator will tend to accept H0 more frequently than should be the case, however, on the other hand, it can be used to reject H0 since the t test of the estimator understate the true significance of the estimator. The modified P tests show that PMO can be rejected in favour of PMG. However, for the other models, both of the hypotheses are significant. Therefore none of them can be rejected.
3 Conclusion
This chapter introduces the data used in this chapter and the chapters thereafter, and investigates variables to model the impact of ownership concentration on firm performance. Three groups of measurements for performance are discussed: accounting rates of return (ROA, ROC and ROE), profit margin measurements (PMG and PMO) and combinations of accounting and market return (TQ and MTB). The measurements for ownership concentration are the same as discussed in Chapter Three: continuous ownership concentration variables (H, C1, C3, C5, C10 and C20), dichotomous ownership concentration variables (OC1, OC2, OC3, OC4, OC5, OC6 OC90, OC95 and OC99) and power of multiple large shareholders variables (H_DIFF, H_CON and SV). Size, leverage, intangible assets and risk are also included in the model as control variables. A summary of definitions for all the variables is available in Appendix 1.
Table 4.12 Modified P tests for competing models with different firm performance measurements Hypotheses: M1: Y1 = Xb + e0 ; M2: Y2= Xg + e1 X H C1 OC95 H_DIFF SV Y1 Y2 H0: M1; H1: M2 H0: M2; H1: M1 H0: M1; H1: M2 H0: M2; H1: M1 H0: M1; H1: M2 H0: M2; H1: M1 H0: M1; H1: M2 H0: M2; H1: M1 H0: M1; H1: M2 H0: M2; H1: M1 ROA ROC -17.61*** 59.03*** 7.84*** 6.81*** -17.62*** -59.06*** -17.61*** -59.02*** -17.61*** -59.05*** ROA ROE -13.86*** 166.12*** -13.86*** -188.63*** -13.86*** -166.01*** -13.85*** -166.02*** -13.86*** -166.14*** ROC ROE -13.10*** 90.46*** -13.10*** -90.45*** -13.11*** -90.39*** -13.09*** -90.43*** -13.10*** -90.45*** PMG PMO 40.06*** 0.68 41.06*** -0.70 40.96*** -0.67 41.07*** -0.67 41.06*** -0.68 TQ MTB 16.45*** 42.95*** 47.91*** 7.76*** 472.54*** 7.81*** 473.58*** 7.80*** 476.07*** 7.78***
Note: H, the Herfindahl index; C1, the largest shareholding; OC95, dummy for the probability that the largest shareholding can secure majority support in a contested vote exceeding 90%; H_DIFF, sum of squares of the differences between the largest and second largest shareholdings, and between the second and third largest shareholdings; SV, the Shapley value; ROA, return on assets ratio; ROC, return on invested capital ratio; ROE, return on equity ratio; PMG, gross profit margin; PMO, operating profit margin; TQ, Tobin’s Q; MTB, market to book ratio of equity. *, **, and *** indicate the significance levels of 10%, 5% and 1%.
performance are tested. Models using C1, C3, C5, C10 or C20 (the ownership of the largest one, three, five, ten and twenty shareholders) as the independent ownership variables are nested models in the sense that these variables are included in each other. It is the same case with models using OC1, OC2, OC3, OC4, OC5 or OC6 (dummies for the ownership of the largest shareholder exceeding 5%, 10%, 20%, 30%, 50% and equalling 100% respectively), and models using OC90, OC95 or OC99 (dummies for the probability that the largest shareholding can secure majority support in a contested vote exceeding 90%, 95% and 99% respectively). T-tests for nested models are applied to investigate the significance of difference terms between these variables. C1, OC2 and OC95 are found to contain the most valid information regarding the ownership-performance relationship among their peer. To compare the rest ownership concentration measurements: continuous measurements H and C1; dichotomous measurements OC2 and OC95, and power of multiple large shareholders measurements H_DIFF, H_CON and SV, non-nested J tests and Cox-Pesaran tests are applied. The test results reject OC2 in favour of OC95, and reject H_CON in favour of H_DIFF and SV. In conclusion, the tests in this chapter are in favour of H, C1, OC95, H_DIFF and SV than other ownership concentration variables.
The modified P tests are used to test competing models using different measures of performance as the dependent variables. The operating profit margin (PMO) is rejected in favour of gross profit margin (PMG). However, none of other measures can be rejected by this test.
Chapter Five Testing the Impact of Ownership Concentration on
Firm Performance: Linear regression results
Previous empirical studies regarding the impact of ownership concentration on firm performance reach inconclusive results. These studies are different in the measurements of performance, measurements of ownership concentration and regression methods. Chapter Four investigates modelling the impact of ownership concentration on performance, and compares various measurements of firm performance and ownership concentration. The measurements for performance within three groups are tested: accounting rates of return, profit margin ratios and combination of accounting and market return ratios. The measurements for ownership concentration within three groups are also compared: continuous variables, dichotomous variables and power of multiple large shareholders variables.
Based on the variables discussed in Chapter Four, this chapter will test the linear impact of ownership concentration on performance. To control the problems arising from the restrictions of OLS assumptions, this chapter investigates various regression methods and applies them to the tests. In addition to the aggregated regressions, regressions controlling for country and industry effects are also carried out to identify any difference of the impact caused by nation or industry, and provide further evidence on the linear impact of ownership on performance.
The first section introduces the model and summarizes the hypotheses regarding the linear impact of ownership concentration on firm performance. The second section tests the validity of basic OLS regressions and discusses solutions for violations of OLS assumptions. Regression results for the adjusted model are presented. The third section tests the country and industry effects on the ownership-performance relationship. Dummies for country and industry, and their interaction variables with ownership concentration are added to the original model. The final section concludes.