The impact of adopting shareholder primacy corporate governance on the growth of the financial market in developing countries. By



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A comparison of corporate governance coefficient (b1) mean estimates of 0.0659 with the mean estimates of control variables like economic growth coefficient (b2) 0.4169 and industrial value addition coefficient (b4) 0.3706, shows that economic growth coupled with technology-led industrial growth has twelve times more impact on financial market development than a change in corporate governance model towards more shareholder value.

Another way of presenting the data would be to state that the model predicts that keeping other factors constant increasing the economy and high technology output by 1.25 times double the financial development, while to reach the same level of financial development growth only by improving corporate governance would require a fifteen fold shift in the corporate governance regime towards a shareholder value model. As seen in the previous subchapter, the corporate governance regimes in all the countries have reached peak shareholder value orientation, it is possible therefore to posit that there is no scope for the level of change required in corporate governance models to make any significant contribution to financial market growth. Armour, Deakin et al. also found that ‘increases in shareholder protection have not led to greater stock market development, as might have been expected.’310 However they also posited that given the data was for 1995 to 2005 ‘the strengthening of shareholder rights which took place in the 1990s and 2000s has not been having its principal intended effect.’311 This research confirms that even under a longer time period, data change in the corporate governance model does not have any noticeable impact on financial market growth.

However the estimate of impact of change in corporate governance (b1) 0.0659 has more bearing on financial market development in comparison to the country level variables like GINI coefficient (R2) -0.0082, peace index (R3) -0.0208, HDI (R1) -0.0793, except for rule of law estimated at (R4) 0.161 which has double the impact on financial market development.

The model predicts that GINI coefficient (-0.0082) has almost no impact on financial market development. What is interesting is that HDI affects the financial market development negatively, this can be correlated to the fact that lower HDI would mean lower wages which would lead to more FDI and hence greater financial development. However, this also paradoxically reduces the amount of technology-led exports and R&D expenditure which has a high impact on financial market growth.

The model also predicts that rule of law is twice as important as adopting shareholder primacy models on the growth of financial markets. This is in line with the common understanding that investors move to countries with a stable legal and judicial system.

So we can summarise that for the developing countries, studied under this research there is a weak impact of change in the corporate governance model on financial market growth, especially in comparison to the overall impact of financial, technological and economic growth.


4.4 Individual country-based models

From the analysis of the structural model in the previous subchapter it is evident that a pro-shareholder change in corporate governance regulation has little impact on financial market development in emerging economies. However, it will be interesting to find out the range of impact on a per country basis, i.e. instead of running a structural model incorporating all countries a basic OLS regression for each country will be used. This will help to isolate any country which may have reacted more positively than others which is the natural corollary to the varying intercept structural model in the previous subchapter. If a country which has reacted more positively to change in corporate governance is found, it will set the foundations for future qualitative research to find out, for example, what happened differently in that country in comparison to others, what sui generis factors were present, and so on.



In this subchapter regression utilising both frequentist and Bayesian approaches is applied. The results of the regression coefficients are presented first, in a tabular format. Then a brief report is presented for each country describing the impact of change in corporate governance on the financial market. This will be accompanied by sets of three 3D graphs showing the contrasting impact of corporate governance change and three controls on the financial market using both frequentist and Bayesian outputs. Each graph will show local regression planes, light red is the frequentist regression plane whilst green denotes the Bayesian regression plane.


Bayesian analysis




Corporate Governance coefficient

Intercept

Control 1 coefficient

Control 2 coefficient

Control 3 coefficient




Mean

2.5% quantile

97.5% quantile

Mean

Mean

Mean

Mean

Brazil

0.062853

0.049519

0.0761

-0.11515

0.418122

0.084039

0.43738

China

0.032681

0.018637

0.046816

-0.00826

0.46066

0.24393

0.327721

Chile

0.139975

-1.24498

2.030255

-0.14729

0.399509

0.079426

0.468502

Colombia

0.075378

-0.03726

0.185066

-0.13884

0.425973

0.079505

0.429411

India

0.062502

0.003676

0.120785

-0.01918

0.398711

0.057521

0.472082

Indonesia

0.066574

0.038958

0.094967

-0.14892

0.411826

0.087087

0.465394

Peru

0.060262

0.011902

0.116667

-0.20842

0.394241

0.079355

0.39691

Pakistan

0.062161

0.033106

0.091461

-0.25478

0.43312

0.079625

0.414556

Poland

0.077912

-0.00566

0.158403

-0.3002

0.480641

0.070058

0.393737

Russia

0.064709

0.051765

0.077738

-0.24181

0.413657

0.084067

0.452866

Argentina

0.066942

-0.01842

0.158039

-0.2454

0.413628

0.08443

0.456878

South Africa

0.064471

0.053535

0.07527

-0.11819

0.417834

0.087343

0.435347

Iran

0.019438

-0.27192

0.308407

-0.27136

0.489304

0.088699

0.428396

Kenya

0.097482

-2.01627

2.025642

-0.04713

0.548885

0.107545

0.604804

Nigeria

0.055016

-0.07813

0.182682

-0.19151

0.416011

0.088196

0.436266

Hong Kong

0.074224

-0.06334

0.212401

0.274053

0.410382

0.0851

0.453187

Philippines

0.054709

0.017428

0.089057

-0.25566

0.421624

0.07878

0.351537

El Salvador

0.040808

-0.18211

0.2067

-0.24525

0.31797

0.06451

0.292567

Vietnam

0.060049

0.037825

0.086218

-0.04812

0.450734

0.084713

0.37679

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