An Econometric Analysis of World GDP Share of India during 1960-2015

SocioEconomic Challenges, Volume 2, Issue 1, 2018
(SUMY STATE UNIVERSITY,UKRAINE)

An Econometric Analysis of World GDP Share of India during 1960-2015

Debesh Bhowmik
PhD, Retired Principal and Associated with The Indian Econometric Society, India

Abstract

In this paper author attempted to analyse India’s international GDP share during 1960-2015 with the help of econometric models taking the data from the World Bank. Semilog linear trend model and exponential trend model were used to find the trend of growth. Variance ratio test was used to show random walk. AR(1) model was used to show stationary, convergence and oscillations. ARIMA (1,1,1) model was tested for the stationary of the series. Forecast for 2035 of the AR(1) and ARIMA(1,1,1) models verified stationary long term patterns. Bai-Perron (2003) model explained to show structural breaks and the study of Bartoletto, Chiarini, Marzano & Piselli (2015) was followed to compute peaks, troughs, durations of cycles, amplitudes and slopes of both the short and medium cycles during 1960-2015. Hodrick-Prescott Filter (1997) model minimized the cycles for smoothness of trend of GDP share.The paper concludes that international GDP share of India has decreased at the rate of 0.459% per year during 1960-2015 and declined exponentially at the rate 0.259% per year significantly. The growth rate of the GDP share is downward sloping significantly till 2030.
It follows random walk without drift. Its AR(1) is stable, convergence and stationary. Forecast for 2035 of AR(1) is also converging. ARIMA(1,1,1) is stable and non-stationary and suffers from AC and PAC problems. Its forecast model for 2035 is tending towards stationary insignificantly. GARCH (1,1) showed excessive volatility. It has two downward structural breaks in 1968 and 1988 and one upward break in 2006 which are significant. The paper verified short and medium cycles to calculate peaks and troughs, duration of downturn and upturn, amplitude and slope of the cycles respectively. HP filter model makes the cycle more smooth with only one trough assuming lamda comprises 1600 but symmetric and asymmetric filter showed two peaks and two troughs. The frequency response function clarified its peaks and amplitude of cycle clearly.Keywords: international GDP share, exponential growth, structural break, non-stationary, HP filter, peaks,trough.

JEL Classification: N13, N15, O21, O24, O57, O10.
© The Author, 2018. This article is published with open access at Sumy State University.

1. Introduction

The world’s GDP share of India is an important indicator which can explain the nature of Indian economic development in comparison to other international economies. During ancient past of economic development of India, it was evident that India’s world GDP share was highest till 1500 AD and India was the dominant country. During 1500-1650, China was dominant followed by India, and then during 1650-1750, India was dominant followed by China. Since 1870, the world scenario changed rapidly due to rise in western civilization and industrial revolution where Europe was the dominant country and India and Chinese GDP started to decline rapidly. After the First and the Second World Wars, USA’s dominance in trade, finance and commerce outweigh UK dominance and USA became the largest GDP share holder in the world up till now. And India’s share has been falling till 1993, and then upswing started in but it is too little in comparison to other nations. During 1AD, India’s share was 33%,followed by 30% in 1000AD,24% in 1500-1700AD, 17% in 1820AD,7% in 1913, and now it is 2.79% in 2015 respectively. But, within 2025, China will recover his previous historical dominance in terms of GDP in the world. In Figure 1, India, China and other nations’ world GDP shares are plotted during 1AD-2008AD for comparative study.

http://armgpublishing.sumdu.edu.ua/journals/sec/volume-2-issue-1/article-4/

Financial Crises and Nexus Between Economic Growth and Foreign Direct Investment

Financial Markets, Institutions and Risks, Volume 2, Issue 1, 2018

(Sumy State University,Ukraine)

Financial Crises and Nexus Between Economic Growth and

Foreign Direct Investment

Debesh Bhowmik

Dr., Retired Principal and Associated with International Institute for Development Studies, Kolkata, Life member, Indian Economic Association, The Indian Econometric Society, Bengal Economic

Association, Ex.Associate Editor-Arthabeekshan-The Journal of Bengal Economic Association,Residence, India.

Abstract

In this paper, author tried to find relation of foreign direct investment inflows with its determinants like growth rate, interest rate, exchange rate, inflation rate, fiscal deficit, openness in India during 1971-2015 through causality, co-integration and vector error correction models. In this paper, it was attempted to explain clearly that how foreign direct investment inflows and outflows have changed during several financial crises in different regions of the world since 1970s in support with a historical analysis over global financial crises. The paper concludes that FDI inflows in India has been catapulting at the rate of 21.56% per year during 1971-2015 and exponentially at the rate of 0.6044% per year significantly. It has four upward structural breaks in 1985, 1994, 2000 and 2006 respectively during the specified period. FDI inflows in India has causal relation uni-directionally with fiscal deficit, and bi-directionally with inflation, exchange rate, interest rate and growth rate during 1971-2015.Johansen co-integration test confirmed that Trace Statistic contains four co-integrating equations and Max Eigen Statistic has three co-integrating equations. VECM is stable, non-stationary and not

good fit for four estimated equations and error corrections for the equations of change of interest rate and inflation rate showed significant with speeds of 23% and 103% per year. The paper also concludes that FDI does not cause Granger financial crises, but financial crises do cause Granger FDI.

Keywords: Foreign Direct Investment, economic growth, financial crises, co-integration, vector error correction.

JEL Classification: C23, C33, F21, F01, O55.

Introduction

Foreign Direct Investment has several dimensions. It affects host countries’ balance of payments and development process. It has long run effects on economic growth and sustainable development which depend on the character of FDI. However, the nexus between growth and FDI is indeterminate since it varies from region to region, country to country and from period to period although the globalization, liberalization and privatization drives accelerated the speed of the nexus towards positive direction irrespective of the distribution of income. Historically, FDI changes from merchants’ capital to multinational investments, from imperialistic attitude to trade domination through economic integration (via financial integration) in international trade and finance.

FDI does not cause crises directly, but it has indirect causes of bubbles and busts. Debt finance through FDI may stimulate debt burden under recession. Financial and banking crises may emerge if FDI in banking sector find losses and shut downs. Yet we cannot avoid the fact that FDI does not Granger cause of financial crises

but financial crises do Granger cause FDI changes which were observed in all the financial crises in the world.

Since the Baring crisis in 1870, India’s FDI was dominated by British imperialism through East India Company whose chief competitors were Dutch East India Company, Danish East India Company, Portuguese East India Company, French East India Company and Swedish East India Company respectively. In 1913, India’s foreign investment stood 35% of GDP and per capita foreign investment was 6 dollar at 1900 US dollar and foreign

direct investment as percent of domestic capital stock was 9%.Presently,India’s FDI inflows is very low in comparison to other countries ,e.g. in 2017 , India’s FDI was accounted as 1.9% of GDP and government of India expects it to rise to 2.5% of GDP with in next five years. In 2017, Mauritius was the top donor country to India comprising 11.47 billion US Dollar followed by Singapore 5.29 billion US Dollar, Netherlands 1.95 billion US Dollar, USA 1.33 billion US Dollar and Germany 934 million US Dollar respectively. As on 2017, Service sector is leading the sectoral distribution of FDI i.e. 8.68 billion US Dollar followed by

telecommunication 5.56 billion US Dollar, Computer hardware and software 3.65 billion US Dollar, Trading..............

APPLICATIONS OF ECONOMETRICS IN ECONOMICS---BOOK REVIEW

BOOK REVIEW-- In Financial Markets, Institutions and Risks, Volume 2, Issue 1, 2018,Ukraine Sumy State University. 

BY

PROF.DANTE A.URBINA

LIMA,PERU

Application of Econometrics in Economics

Dante A. Urbina

University of Lima.

© The Author, 2018. This article is published with open access at Sumy State University.

Bhowmik, D. (2017). Applications of Econometrics in Economics. New Delhi: Synergy Books, 332 pages,

1695 rupees, ISBN 978-93-82059-49-3.

According to Karl Popper, one of 20th century’s greatest philosophers of science, “theories are nets cast to

catch what we call ´the world´: to rationalize, to explain, and to master it”. And that is right. Scientists and

researchers seek to catch reality by mean of theories. In the case of economics, we seek to catch “economic

reality”. We have economic theories. In fact, there are several approaches within economic theory (neoclassical

economics, behavioral economics, institutionalism, post-Keynesianism, etc.). But we need specific tools and

methods in order to evaluate in a rigorous way the connection between our theories and economic reality. In

that context, econometrics become a very important aspect of research in economics.

So, in the book Applications of Econometrics in Economics, which is a compilation of Debesh Bhowmik’s

papers, we can find several demonstrations of this in practice since Dr. Bhowmik shows how econometrics

can be used in several ways to perform interesting and relevant research with respect to different aspects of

economic reality (namely, growth, inflation, employment, productivity, crisis, international trade,

globalization, financial integration, poverty, inequality, etc.). In that vein, he writes: “Nowadays, quantitative

economics plays an important role in theory and in practice where econometric models and their applications

in the economic analysis have acquired both the educational values and policy prescriptions” (p. xvii).

Basically, the econometric applications in the book are focused on time series analysis. For example, in the

paper “Causes behind the euro crisis”, Bhowmik uses ARIMA and GARCH models and he find that “nominal

euro/dollar exchange rate is stationary, convergent and volatile during 1999Q1-2015Q2” (p. 1). In addition,

there are several papers which use cointegration analysis like “An analysis of convergence and cointegration

of sectoral shares and growth in India”, “Cointegration between world trade, gold and SDR” and “Convergence

and cointegration of credit deposit ratio and Indian economic growth”. Relevant tests as the Granger causality

test are also applied and interesting results are obtained. For instance, in the paper “Economic growth, foreign

direct investment and financial crisis” it is found that “FDI does not cause Granger financial crises but financial

crises do cause Granger FDI” (p. 57). The book also includes applications of VAR models, which have the

important advantage that they allow to avoid endogeneity problems given that in this kind of models all the

variables are considered as endogenous. Thus, in the paper “Cointegration and VAR analysis in Indian growthunemployment-inflation linkages” it is concluded that “the policy makers should choose either inflation or

unemployment as the target variable to achieve specified growth rate and formulate other macroeconomic

policies” (p. 191). We can also find applications of the specific variant known as vector error correction model

(VECM). For example, in the paper “Is there any relation between gold price and inflation in India” one of the

main results is that “the estimated VECM states that the first difference gold price is significantly related with

the change of inflation rate (percentage change in CPI) and the change of WPI [wholesale price index] of the

previous periods and even related with the change of gold price of the previous period significantly” (p. 231).

However, it must also be said that the book has limitations. As was mentioned previously, it has several

applications of time series analysis. But there are no detailed applications of data panel analysis (in general

this is only mentioned in the section “Literature review” of some papers). So, I am very much of the opinion

that it would be valuable to include that in a next edition of the book because data panel methods (random

effects models, fixed effects models, Arellano-Bond estimators, panel cointegration analysis, etc.) are very

important in applied research.

By other hand, Bhowmik’s discussions also include valuable comments about the conditions for a rigorous

application of econometric tools. For example, in the paper “Poverty, inequality and globalization with special

reference to India”, he says: “India’s database is very poor in comparison to other developed nations. The

collection, compilation and interpretation data through NSS should be more scientific and modernized. More

emphasis must be given in collecting time series data in poverty, inequality and globalization so that policy

prescription through measuring modern tools can be applied in the framework of planning” (p. 278).

Thus, it is clear that Dr. Bhowmik’s book is of considerable importance for applied econometricians because

it addresses very diverse topics using different econometric tools with great mastery. Of course, like any

econometric analysis and result, what is presented in this book is debatable because it depends on numerous

methodological and procedural choices. But this is something that affects every work of applied econometrics.

The point is that, if we have the data (which would be our quantitative connection with reality), we can validly

discuss different methodological approximations in order to “catch” economic reality in quantitative models

with relevant qualitative meaning. In that context, the book explains in detail how data is processed and this

allows the discussion. And from discussion comes out the light. So, this book will help to illuminate our path

to a better and deeper understanding of economic reality.