The Impact of Stock Market Development on Economic Growth; a Panel Study in the Economies of Pakistan, India and China

Research Article

Austin J Bus Adm Manage. 2018; 2(1): 1021.

The Impact of Stock Market Development on Economic Growth; a Panel Study in the Economies of Pakistan, India and China

Ali Raza Sattar¹*, Muhammad Aamir Ali², Mohsin Rehman², Sehrish Naeem²

¹ACCA, UAECA, MS Banking & Finance, City University College of Ajman

²School of Accounting and Finance, University of Central Punjab, Lahore, Pakistan

*Corresponding author: Ali Raza Sattar, ACCA, UAECA, MS Banking & Finance, City University College of Ajman

Received: January 22, 2018; Accepted: February 09, 2018; Published: February 16, 2018


The stock market development is essential for the economic development and growth. This study is an important attempt at analyzing the importance of the relationship between stock market development and economic growth in Pakistan, India and China. The data for GDP and stock market capitalization has been taken from world bank from 1993-2016. This data frame has considered the smart portion of China, Pakistan Economic Corridor. The panel regression is applied by using Stata 12. The Hausman specific test specifies that random effects model is better for the sample used in this study. The results revealed that stock market capitalization has a positive significant impact on GDP. The policy makers must realize the stock market capitalization, numbers in the development of the economies. This study will help the policy makers to understand the impact and importance of stock market capitalization in these economies for the economic development indicators.

Keywords: Stock Market Capitalization; Panel Regression; Hausman Specific Test and Random Effects Model


Economic growth has been very important in any economy since the industrialization has involved in the history of humans [1]. The policy makers want the indicators of economic growth and development in positive numbers. These indicators are the source of information for the stakeholders of the economy [2]. The stakeholders of the economy, give a push or pull to the economy because of their interests. The economists are very crucial for any country to understand the interests of the stakeholders and to value the economic growth and stability in the economy [3]. Industrialization has rung the bell of development and country growth around the economies of the world [4]. Industrialization is the only source to introduce quick development in any country [5]. Research and development is the key to industrialization, which is the main source of economic growth and development [6]. Research and development are reflected in the development of industrialization in any economy.

To know which economy is paying attention towards research and development, the stock market index numbers are extremely important for the researchers and the policy makers [7]. Because the research and development will lead to industrialization and industrialization will lead to stock market development and stock market growth will lead to economic development and growth [8]. Stock market capitalization is the indicator that shows the interest and confidence of the stakeholders in the industrialization process in the economy [9]. It is said that the better numbers of market capitalization ratio shows that the stakeholders are more motivated and satisfied [10]. The interests of stakeholders are the primary concern for industrialists and the better financial development and economic growth [11].

Stakeholders are always attracted to those countries which have high potential to immediate and better growth [12]. There are many different types of economies all over the world [13]. The stock markets of developed industrialized countries are maturing and stable [14]. Those stakeholders who want stability and better constant earning are more interested in these types of stock markets [15]. On the other hands economies like Pakistan, India and China have great potential to score better numbers in the near future, stakeholders and investors can earn better growth and immediate profits by investing in these types of stock markets. There are very few studies on particularly considering these three countries. Our study has been considering the smart portion of the effect of China, Pakistan economic corridor which has not been considered by many studies in these economies, the study related to this topic has been studied on large scale but the significance of our study is to cover these economies after the effect of China Pakistan economic corridor on these economies. Since 2016 Pakistan, China and India are under the immense pressure of world political influences. There are a lot of unfavorable variables like; instability of Pakistan government, the political clashes of North Korea and USA, the war against terrorism. So the future of this topic in these economies might be the victim of lots of ups and downs. The policy makers must realize the importance of China, Pakistan economic corridor and the negative influences of instabilities and uncertainties.

Literature Review

The world has just come back from a huge financial crisis [16]. The stable economies have not faced the strong after effects as compare to more volatile economies. But no doubt these stable stock markets could not bear the episodes of these types of financial crisis. The financial crisis has rung the alarming bell for the more volatile stock markets [17]. The stock markets with huge potential and with least stability have to understand the worth of stock market growth. The gross domestic products numbers have faced multiple jerks during the history since 1990. The financial crisis has dropped the numbers of GDP around the world. The period of five years starting from 2010 has not faced a better number. But overall the GDP numbers are very much improved since 1990 [18].The problem is that there are lots of researchers who have contributed their contribution in this particular economic field, but there is still a huge gap due to inconsistencies in the world of literature and relevant scholarships. These inconsistencies have introduced a research gap for the upcoming researchers in this field. The panel regression has revealed a positive impact on stock market development on the economic growth and economic development in Pakistan, India and China. The policy makers must understand the importance stock market stability for the better numbers of economic growth in these countries.

The random effects model is better and it is confirmed by Hausman specific test. The random effect model predicts the positive impact of market capitalization on gross domestic products in this Asia specific region. The results are statistically significant and can be understood and considered by the policy makers. The stock market capitalization has positive impact on GDP in Pakistan, India and China. No doubt currently the China is more aggressive than Pakistan and India in development. China is now planning a CHINA PAKISTAN ECONOMIC CORRIDOR in Pakistan and in the near future the stock markets of Pakistan and China are potentially more feasible as compare to other stock markets.

Doing research in the field of macroeconomics has been always a matter of differing opinion. The different economic situation in every country is different and therefore the findings can be significantly different in every economy. The researchers are always aware of different findings. The impact of stock market growth and economic development has been studied in the field of research a lot, but still, the researchers do not find a conclusive verdict on it. There are many valuable researchers who have come to different conclusions.

Marques (2013) [19], has studied the Portugal Economy, It has been claimed that the stock market growth does granger cause the economic growth. For this research he used time series study from 1993-2011and granger causality test. He also claimed that Portugal is a smaller economy as compare to other European countries but still this economy matters for the stakeholders. Babajide (2016) [20], argues a very confident findings that stock market strongly and significantly changes to the economic growth, at the same time he advises the policy makers to consider this impact with deep interest for future policy making process. He also adds his conclusions by testing the relationship of many macroeconomic factors, along with interest rates and the stock market growth.

Muhammad Aamir Ali (2014) [21], argues that GDP per capita is strongly influenced by stock market development. His study is based on the Asian big economies from 1991-2011. He also considers many other macroeconomic variables in his study. Ayadi (2015) [22], argues by considering the data from 1985-2009 that the GDP has significant negative impact on the stock market liquidity and size. This is a panel study and in this study, he advises the policy makers to consider the impact of stock market growth in the economy. The evidence of his conclusion is very strong as he has conducted his research with a very wide range of panel data. His result has created a big consistency with Marques (2013) and Babajide (2016) because their findings were not defining the direction of the relationship between these variables and Carpenter (2017) [23], conducts research in China economy and comes up with a very strong analysis of the fastest growing economy in the world. He argues that the stock market is playing a vital role in the field of economics and stock market growth is extremely important in economic growth in China. His findings are in line with Marques (2013) and Babajide (2016).

Every year the new research opens a new door for the policy makers, the conclusive and consistent findings do not come on to the stage. The different time series and cross sectional studies are the pillars of rich literature. Now the era of 2017 has come up, but this topic is still fighting for consistent findings. And this is the beauty of economics and social science which most of the times gives inconsistent findings lead to more researches in the future.

Faisal (2017) [24], argues with time series research totally based in China. He applied auto regressive model and the data is collected from 19990-2015. He studied the impact of stock market growth on economic development and FDI in China. He studied the positive impact of FDI on stock market growth and negative impact of financial development. He also applied granger causality run, which also predicts the uni directional relationship similarly Barro (2017) [25], argues by studying 30 countries and he also explains the worth of stock market by saying that when the stock market gets crushed the economy feels depression. The depression is significantly related to the performance of stock market performance. The inconsistent findings over the different economies are the main concern for the future researchers and this is the only reason for research gap. The impact of stock market growth on economic growth and the economic development is the important topic of research in these days.


The framework for this study is based on and supported by rich literature. Most of the researchers have used stock market capitalization (stmarkcap) as independent variable and gross domestic product (GDP) as the dependent variable. The following econometric model is supported by Marques (2013), Babajide (2016), Muhammad Aamir Ali (2014) and Carpenter (2017). The panel regression is applied in this study, the panel study is a very strong econometric tool for forecasting [26]. There are three models which have been used in this study, firstly the pooled regression model in which the panel of the data is not considered, it is basically the simple regression model which is more relaxed. Secondly the fixed effects model is applied. The fixed model is very effective when the panels are considered to be invariant over the countries. It is assumed in the fixed effects models that there are no significant changes in the culture of the countries [27]. Finally the Hausman test is applied to check which one is better than fixed effects model and random effects model [28].

In our study there are three countries have been used, Pakistan, India and China. No doubt these countries have huge cultural differences, but as far as the Asian significance is concerned, these countries are in the same region [29]. After the fixed effect model the random model is applied, which is again a relaxed model as compared to fixed effect model. The data are consisted over 25 years for each country, the data span is from 1993-2016 and data are collected from the world bank data bank. The Stata 12 is used as statistical software in this study. The reason for selecting this span is very critical, during this span the economies of Pakistan, India and China have faced a lot of ups and downs. Particularly Pakistan has been facing the war against terrorism since 2001 [30] which has put a lot of effects on the stock market numbers.

In the model the GDP is considered dependent variable and stmarkcap as independent variable. The GDP is gross domestic product values in US dollars and stock market capitalization is also measured in US dollars.

[gdp]_it= β_0 + β_1 [stmarkcap]_it+ ε_it

In the above equation the dgp is dependent variable and stmarkcap as independent variable. The β_0 & β_1 are used as constant and coefficient respectively. The “i” means numbers of panel (countries) whereas “t” is used as a time. On the other side “ε_it” is used as the error term in the equation. Finally the robust function test [31] on random effects model is applied in Stata 12, the robust function controlls for the serial correlation and accounts for the heteroscedasticity problem [32].

Results and Discussion

Table 1 shows the summary statistics, which shows 72 observations in this study, the table 2 shows the results of pooled regression. The value of the coefficient of determination is 88.43%, which shows that the pooled regression model is explaining 88.43% explanation in the model, the 11% explanation cannot be covered by the model [33]. The R-square numbers are very important for the overall fit of the model [34]. The stock market capitalization is explaining almost 90% variation in the dependent variable which is Gross Domestic Products (GDP). The probability of F-statistics are 0.0000 which shows that model is the best fit [35].