A Study on Indo-China Bilateral Trade Relations in the Post-Liberalisation Era

I. INTRODUCTION

A bilateral trade is the trade of goods between two Countries promoting trade and outlay. The two nations will cut or get rid of tariffs, import quotas, export restraints, and other trade obstacles to encourage trade and investment. In the United States, the administrative centre of Bilateral Trade dealings curtails trade deficits through negotiating free trade agreements with recent nations, supporting and improving active trade harmony, promoting economic growth out of the Country, and other actions. Among the largely encouraging current developments in India China market and India-China ties is the quick increase in bilateral trade. The drivers of bilateral trade i.e. Comparative Advantage & Rapid Economic Growth of India and China provide grounds for strong economic exchange as the sheer size and growth rates of these economies have boosted bilateral trade, as bigger economies have more to buy and sell.

The title of the present study is ―A study on Indo-China trade relations in the post-Liberalisation era‖. The emergence of both the Asian Giants ―India‖ and ―China‖ after Liberalisation has been considered as the World‘s fastest developing economies, therefore, focusing on Analysing the trade relations.

A vital and essential aspect of a research project is the survey of related literature which means to read and evaluate the past as well as the current literature of research that is related with the planned investigation. According to G. V.VIJAYASRI, 2013, In the recent globe, there is mutual interdependence of the different national economies. Nowadays, it is tough to find the example of a closed market. All economies of the globe have turned into open. But the level of openness varies from one nation to another. Thus, in the contemporary globe, no nation is entirely self-reliance. Self-reliance, in the sense used here, means the percentage of the goods and services addicted to their total productivity with in a nation. But the scale of self-reliance varies from one nation to another. economic reforms in China and India. A closed economy, china started its developments in 1978, with effectively no debt. But it's only in 1993-94 when India penetrated its augmentation and structural amendment phase, much latter than China. The Chinese market grew by 13% in 1992, and growth rate for 1993 is imagined to be higher than 13 per cent in actual terms. This fetch the average development rate in the 16 years (1978-1993) to over 9 percent per year far higher than the 6.1 per cent figure for the preceding 26 years (1953-78) which is outstanding given China's huge population and local diversity. The Indian economy grew at 4.3 percent in real terms in 1992-93 and around an assessed 4.0 percent in 1993-94, tracked by a dip to 1.2 percent in 1991-92 once transformations were initiated in 1990-91. The present research tries to fill the gap by considering the post-liberalisation era for Indo-China relationship. The study also studies the future relationship between the Countries with the help of Time Series Analysis Swapan K. Bhattacharya and Biswa N. Bhattacharya (2007) in their paper disclosed that India and the People‘s Republic of China have significant bilateral trade possibility, which was not explored until now. These countries are currently negotiating for free trade arrangements between them based on their complementarities. This paper did calculations to know approximately the likely benefits in terms of gains or losses in imports of both India and China due to diverse privileged trading arrangements and free trade arrangements using the gravity model. Prof. T P Bhat, Team Leader, Mr Atulan Guha & Dr Mahua Paul (2006), in their Report on ―INDIA AND CHINA IN WTO‖-Building Complementarities and Competitiveness in the External Trade Sector sponsored by Planning Commission explained the bilateral trade relationship with the economic indicators like imports, exports, balance of trade, commodity group but this research has not considered some other economic indicators like GDP, GDP per capita etc. which are also helpful in understanding the bilateral trade relationship. Also, the study focused on finding the trade trends for the future of both the Countries.

2. To understand and analyze the Indo- China trade trends in the last two decades (1991-92 to 2017-18). the bilateral ties between India and China with the help of various economic parameters like import, export, GDP (Real Annual Growth %), GDP Per Capita, Commodity Composition & Balance of trade etc. The study not only identifies the past trend between both the Countries but also identify the future trends as well. 1. Methodology of the study: The method of research would be suitable which includes following characteristics: 2. Hypotheses of the study: Before describing the hypothesis, it is pertinent to mention the trade & economic indicators/macro-economic variables/factors considered for studying the present research.

Hypothesis testing determines the validity of the Hypothesis. In the present study, the Hypothesis was tested at 5% level of significance.

To study and analyses the Indo-China bilateral trade relationship with the help of different macroeconomic indicators like.

It was proposed that the lifeblood of the global market is trade. Exports and Imports affect the bilateral trade relationship as Exporting and importing helps grow national economies and expands the global market. Every country is endowed with certain advantages in resources and skills. To study and analyses the objective, the present study has undertaken Import and Export as major trade indicator. To find out the trade relationship between India and China on the basis of major trade/macro-economic indicator imports and exports, the following hypothesis was formulated:

To understand and analyze the Indo- China trade (export & import) trends in the last two decades (1991-92 to 2017-18). Based on the objective, the following Research Question was formulated. The present study has undertaken to analyses the trade trends between India and China on the basis of the major trade indicator i.e. export & import as Analysing the past trend of export and import between Countries helps in Analysing the future trade relationship between the Countries.

The research is based mainly on secondary data sources. Data and information from secondary sources were collected by consulting various relevant journals, EXIM Bank, Economic review, World Bank, WITS, publication of WTO and Ministry of Commerce, Govt. of India. The information published in the different newspapers and websites in recent times have been consulted in order to present the recent trade and performance of Indian and Chinese economies. The collected data and information were then processed, tabulated and analyzed to present the findings in a logical and objective manner. The study‘s Source of data used was from World Bank, Ministry of Commerce, WTO & WITS

The present study entitled ―A study of Indo-China trade and economic relations in the post-Liberalisation era‖ is Exploratory cum Descriptive type of Research. ► Finally as the researcher has planned the study carefully including the tests to be used, the Exploratory cum Descriptive Research Method was employed for the present ► An Exploratory research is research conducted for a problem that has not been studied more clearly, intended to establish priorities, develop operational definitions and improve the final research design. Given its fundamental nature, this type of research often relies on techniques such as secondary research - such as reviewing available literature and/or data. ► The significance and nature of Descriptive Survey Method has been explained as: Descriptive survey study describes and interprets ‗what is‘. It is concerned with conditions or relationships that exist, opinions that are held, processes that are going on, effects that are evident, or trends that are developing. Therefore, the researcher found it justifiable to use Descriptive Survey method for the present study.

For analysis of desired status of the study, the tester should analyse the past and future pattern for different macro-economic indicators, “Time Series analysis” should be applied to understand the relationship with China with the help of components of Time Series i.e Secular Trends (or General Trends), Seasonal Movements, Cyclical Movements, Irregular Fluctuations. The “Regression equations” can also be formed for observing a significance regression amongst the independent and dependent variables. Further, “Time Series Multiplicative Model” can be used for calculation of values of macro-economic indicators if the Trend and Cyclic components are moving simultaneously. In order to predict the value of one variable for other variable, the “Time-Series Regression Model” can be developed. The mass of data collected through the administration of the tools is required to utilize data meaningfully. The role of statistics in research is to function as a tool in designing research, analyzing its data and drawing conclusion there from. Most research statistics result in a large volume or raw data, which must be used for further analysis. The

Data were analyzed by applying statistical operations through Social Sciences (SPSS) Version 20.0. SPSS Statistics 20.0 is a comprehensive system for analyzing data. SPSS Statistics can take data from almost any type of file and use them to generate tabulated reports, charts and plots of distribution and trends, descriptive statistics and complex statistical analyses. SPSS Statistics makes statistical analysis more accessible for the beginner and more convenient for the experienced user. Simple menus and dialogue box selections make it possible to perform complex analyses without typing a single line of command syntax. The data offers a simple and efficient spreadsheet- like facility for entering data and browsing the working data file.

After collection of data, it is analyzed and interpreted through Time Series Analysis, Linear Regression analysis, Time Series Multiplicative Model Analysis, ANOVA (Analysis of Variance), Time Series Regression and Multiple Regression. The results of different statistical techniques have been presented according to the objectives of the study. It would be interesting and important to analyse to what extent the bilateral trade and economic relations helps in maintaining the overall relationship between India and China.

First, the pattern is analyzed for ―Imports from China (in USD Million)‖. Time series analysis is applied to understand the import relationship from China. A forecasting model is presented with use of trend and cyclic components. In the study, time is taken as independent variable (t) and imports from china is taken as a dependent variable (y) for analysis.

The time series plot presents the movement of imports from China over the period of time in post liberalization era. One could observe that Indian imports have grown phenomenally in post liberalization era especially after 2003. The graph best fits with the linear trend line and a simple linear regression equation can be generated by using linear regression analysis for prediction of imports from china in 2019. Following tables present the result for regression;

One can observe a significance regression amongst time (t) and imports from China (y). Hence, the Regression equation is formed. Next table presents the components for regression.

The regression forecasting equation with above components can be given by; By using the regression equation (1) the forecasting for imports from China for successive years can be given. Forecasted value of imports from China for year 2019 can be given as following. Since trend is not the only component therefore we further use Time Series Multiplicative Model Analysis for Imports from China Following table studies the multiplicative model of time series in which seasonal and irregular trends are not considered as they are not seen in the chart plotted above. The model calculates the Import value as under; Where T is linear trend and C is cyclic trend

average component of cyclic trend thus calculate is C =1.04. The time – series equation including trend and cyclic variation can be given by; By using equation (3) the prediction for 2019 imports from china can be calculated as; Further, the researcher is analysing overall imports of India. Following graph presents the output in graphical form.

One can observe from the above graph that post liberalization imports actually took off after 2002. The cyclic trend in the imports can be observed after 2007. We use multiplicative model described in (1) to predict the imports for coming years. The cyclic trend in the data can be observed 2007 onwards; therefore the component of cyclic trend is incorporated in the model only after 2007.

One could observe that the variation in overall imports data over the period of time is significant to develop a regression equation for forecasting. A linear regression equation can be developed from following regression table.

It can be observed that the intercept and coefficient with respect to time are significant, hence following regression equation can be developed for forecasting overall imports. For 2019, the predicted value of imports can be given by; Same way overall import for successive years can be projected. Now time series analysis is applied to incorporate cyclic component. Following table shows Time series analysis.

average component of cyclic trend thus calculate is C =1.07. The time-series equation including trend and cyclic variation can be given by; Hence the new projected value of overall imports in India can be given by

Following graph present the Indian exports to china.

From above figure, it can be observed that there is overall growth in Indian Export, though the cyclic trend in exports is observed after 2007. Hence the exports from India to China is projected in two different ways by using simple linear regression equation and trend and by incorporating cyclic trend and using multiplicative model of time-series.

One can observe that the regression is significant and the regression equation that is to be used for forecasting exports is statistically significant and can be driven from following table.

It can be observed that the intercept and coefficient of regression i.e. time both are playing a significant role in the equation. A simple linear regression equation can be given by; Now the time series analysis is used to forecast exports in 2019 and henceforth. Following table presents the results of Time series analysis.

Using cyclic trend average value after 2007 (1.05) the time series equation can be given by; Further looking into overall Indian exports, following chart presents the results.

One can see from figure above that overall exports have grown over the period of time after post liberalization. The faster growth in overall exports is observed after 2002. In order to project the overall exports from India in 2019 and years after first the linear regression analysis has been used as the linear trend is best fitting trend in this case. Following tables present the regression analysis.

One can observe that the regression is significant as the F-calculated is above the F-significant. Following table presents the coefficients of regression equation.

The table above shoes that the intercept and slope both are significant as the p-value is below the level of significance i.e. . Hence a significant regression equation for predicting overall exports is given by; As we can see that the cyclic trend is occurring in data from 2007 onwards and there is no irregularity or seasonal component present in the data hence we use time series analysis and smooth cyclic trend after 2007. The average level of cyclic trend is given by C=1.06 in this case. Following table shows the calculations of trend and cyclic trend.

Further the time series regression equation can be given by; Further we see the contribution of India‘s exports to China with respect to overall exports. Following chart presents the result.

One can see that the exports to china has taken a real swing from 1995 to 1996 the exports to china went down phenomenally it started recovering in 2002 reached a high in 2004 and started dipping from 2010 onwards. A recovery phase can be observed in 2019. Since china in itself is a one of the largest manufacturing hubs of the world hence the scope of supplying finished goods to China is very low. Exports of raw material or edibles have a higher scope comparatively.

One can observe that the imports from china are far higher than that of export to China. One can also see that there is a significant difference as p-value is less than level of significance i.e. . Therefore the null hypothesis is rejected and conclude that the difference between exports and imports is statistically significant.

India has been enjoying the trade surplus with China since 1991 to 1996. Since then, the trend has been negative. India‘s rising trade deficit with China is now close to US $ 62 million in 2018 leading to serious concerns over India‘s ability to sustain it. The deficit is the result of China‘s structural shift from a primary products base to a manufacturing regime. The major change in imports and exports can be observed after 2002, this may be due to the Third Trade Policy Review of India given by the Trade Policy Review Body of the WTO on 19 and 21 June 2002. There were jumps in 2011-2012 and 2014-15, mainly due to an increase in Chinese exports to India, but trade has been somewhat stagnant in recent years.

ensuring that the Sino-Indian relationship continues to prosper. • Imports from china are forecasted to drop by 18% with respect to 2018 in 2019 if calculated with respect to trend purely while it shall be dropped by 15% in comparison to 2018 if the cyclic trend is also considered. This forecasted dip in trend can be due to multiple political and non-political reasons such as make in India initiatives taken by Government. • Overall imports of India to rise by approximately 10% in 2019 while the share of imports from china with respect to overall import shall remain around 18% in 2019. • Overall exports from India shall grow by 10% if cyclic and trend components are considered in 2019 while the exports to china shall rise by 11.33% approximately in 2019.

It can be concluded that the rapid growth of China and, more recently, of India, is having major effects on every facet of the global economy, including the environment, and this influence is projected to continue to expand in the foreseeable future. The growth of these two ‗giants‘ in the developing world has produced a massive surge in manufacturing exports as well as in imports of both intermediates and primary commodities. In manufactures, even as competitive pressures have sharpened in labor-intensive export sectors, new growth opportunities have emerged for complementary expansion. China attaches great importance to strengthening of economic and trade relations with all her neighbors. The Chinese side desires to establish an overall, long-term and stable economic and trade relationship with India while the Indian business community strongly desires to strengthen the trade and economic ties with China. The bout of tactful action sustained into 2018, with not only a focal point on justifying security matters but also taking in hand economic barriers in the rapport. At the freshly completed 11th conference of the India-China Joint Group on Economic Relations, Trade, Science and Technology, the two countries explored ways to develop bilateral trade and investment support, handling upon ways to trim down their trade imbalance and potentially starting dialogues on a Free Trade Agreement (FTA). Indian and Chinese delegates also take part in the fifth iteration of the bilateral Strategic Economic Dialogue to communicate means to develop their lucrative assurance and clear any obstacles in doing so. These developments are testimony to the verity that China economic cooperation more tough. • This includes economic constraints, border disputes and perception problems. Difficulties aside, the two countries‘ common interests provide the bases for a brighter future for India-China relations.

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Mewar University, India