BOOK RELEASE

THIS BOOK IS RELEASED DURING THE UGC ,SAP (DRS-1) SUPPORTED INTERNATIONAL SEMINAR IN VIDYASAGAR UNIVERSITY,DEPARTMENT OF ECONOMICS, MIDNAPORE, 28-29 MARCH,2018 

ECONOMETRIC  APPLICATIONS

by

Dr.Debesh Bhowmik

MANGLAM PUBLISHERS AND DISTRIBUTORS

K-129,GROUND FLOOR,GALI NO-3,3-1/2 PUSTA,GAUTAM BIHAR,ND-110053

manglam.publishers@rediffmail.com

www.manglampublications.com

pp380,price-1450/-

The book consists of 15 research articles on econometric applications in the areas of fiscal deficit,infrastructure,female unemployment,growth –unemployment nexus,exports,non-perorming-assets,ecommerce,rupee/dollar nominal exchange rate and real effective exchange rate,silver standard,growth-inflation nexus, agricultural productivity and growth nexus,and small scale industries sectors respectively.Some of the papers have been presented in the seminars and conferences and some are published in journals.I have compiled those articles in a book form because it may help to the students and teachers of econometrics who use frequently econometric models.This book may be useful to the professionals and policy makers who apply econometrics in economic policy frameworks.

Contents

Foreword

Preface

Acknowledgement

List of Figures and Tables

Chapter-1: Macro Economics of India’s fiscal deficit and fiscal convergence of Indian States

Chapter-2: Infrastructure, Economic Growth And The Economy Of Bihar

Chapter-3: Relation Between GDP Growth Rate And Unemployment Growth Rate In India Since The Reform Period

Chapter-4: Non Performing Assets And Its Relation With  Advance,Lending Rate And GDP In Indian Banking Sector

Chapter-5: The Trends And Determinants Of Indian Exports:An Econometric Analysis

Chapter-6: India’s Retail Sales of ECommerce: An Econometric Analysis

Chapter-7: Rupee USDollar Nominal Exchange Rate Of India: Behaviour,Cointegration And Vector Autoregression

Chapter-8: Global Female Unemployment: An Econometric Study

Chapter-9: B.R.Ambedkar and Silver standard in India

Chapter-10: Growth-Inflatio Nexus : Threshold Model Of Inflation In India

Chapter-11: Behaviour and determinants of Real Effective Exchange Rate of India

Chapter-12: Agricultural Productivity and Economic Growth in India

Chapter-13: Capital inflows and Silver Standard in India

Chapter-14: Retail Sales Of E-Commerce In India And USA:A Comparative Study

Chapter-15: Econometric Analysis of the performance of SSI sector in India during 1980-81-2014-15

debeshbhowmik@rediffmail.com

RELEASE OF BOOK ON APPLICATIONS OF ECONOMETRICS IN ECONOMICS

APPLICATIONS OF ECONOMETRICS IN ECONOMICS

     By 

Dr. Debesh Bhowmik

SYNERGY BOOKS INDIA ,NEW DELHI (www.synergybooksindia.com

Price- 1695/-

The Foreword of this book is written by Prof. Dante A. Urbina Padilla,

National University of San Marcos ,Lima,Peru 

Contents

1.Causes of Euro crises

2.Economic growth ,foreign direct investment and financial crises

3.An analysis of convergence and cointegration of sectoral shares and growth in India

4.An econometric model of Inflation in India

5.Bangladesh-India trade financial integration linkages

6.Cointegration between world trade ,gold and SDR

7.The nexus between productivity and employment 

8.The nature of Indian GDP growth rate

9.Cointegration and VAR analysis in Indian growth -unemployment -inflation linkages

10.Indo-Bangladesh trade financial integration linkages

11.Is there any relation between gold price and inflation in India?

12.Convergence and cointegration of credit deposit ratio in India

13.Poverty,inequality and globalisation with special reference to India.

14. Indo-China Trade ,Yuan in SDR basket and world economy

15.Daily exchange rate behaviour of special drawing right per yuan   

Bibliography

Subject Index

Today (23 March ,2018) at Rabindra Bharati University ,the book is released on the seminar" Human Development  in India :A State level Analysis" in the Centre for Human Development Studies,

Kolkata  

Foreign Direct Investments (FDIs) and Opportunities for Developing Economies in the World Market

by

Venkataramanaiah Malepati (University of Gondar, Ethiopia) and C. Mangala Gowri (University of Gondar, Ethiopia)

Release Date: December, 2017|Copyright: © 2018 |Pages: 315

ISBN13: 9781522530268|ISBN10: 1522530266|EISBN13: 9781522530275|DOI: 10.4018/978-1-5225-3026-8

Chapter 1:Foreign Direct Investment, Technological Innovation, and Export Performance: Empirical Evidence From Developing Asia (pages 1-24)—by-Arzu Tay Bayramoglu, Tezcan Abasız

Chapter 2:Determinants of FDI Inflows in Developing Countries: A Dynamic Panel Approach (pages 25-45)—by--Dinesh Kumar Choudhury, Prabhakara Rao

Chapter 3:The Role of Foreign Direct Investment in Less-Developed Countries (pages 46-65)-by-

Chengchun Li, Sailesh K. Tanna

Chapter 4:Socio-Economic Impact of Foreign Direct Investment in Developing Countries (pages 66-81)-by-Christopher Boachie, Eunice Adu-Darko

Chapter 5:FDI as a Factor of Improving the Competitiveness of Developing Countries: FDI and Competitiveness (pages 82-104)-by-Ivana S. Domazet, Darko M. Marjanović

Chapter 6:The Relative Importance of Trade vs. FDI-Led Economic Growth in Thailand (pages 105-122)-by-Sailesh Tanna, Kitja Topaiboul, Chengchun Li

Chapter 7:FDI Inflows and Current Account Evidence From BIMSTEC (pages 123-141)-by-

Nida Rahman, Shehroz Alam Rizvi

Chapter 8:The Comparative Study of the FDI in India and China in Retail Sector (pages 142-168)

-by-Rita Naraindas Khatri

Chapter 9:M&A vs. Greenfield: FDI for Economic Growth in Emerging Economies (pages 169-185)

-by-Sana Moid

Chapter 10:Patterns of Technology Acquisition: Upstream Linkages Between MNEs and Local Suppliers (pages 186-212)-by-António Carrizo Moreira

Chapter 11:The Role of Governance on Foreign Direct Investment Inflows: A New Theoretical Perspective and Cross-Country Analysis (pages 213-247)-by-Adem Gök

Chapter 12:Econometric Analysis of India's Foreign Direct Investment Inflows (pages 248-275)

-by-Debesh Bhowmik

Chapter 12

Econometric Analysis of India’s Foreign Direct Investment Inflows

Debesh Bhowmik(International Institute for Development Studies, Kolkata, India)

ABSTRACT

In this chapter, the author explains the trend lines, random walk, stationary,

structural breaks, and volatility of FDI inflows in India during 1971-2015. Both

log linear and exponential trends are significant. FDI inflows are stationary and

showed four structural breaks in 1985, 1994, 2000, and 2006. The author found the

relation among FDI inflows, growth rate, interest rate, inflation rate, exchange rate,

fiscal deficit, external debt, and trade openness with the help of Granger causality,

Johansen cointegration test, and vector error correction models. Trace statistic

has four cointegrating equations, and Max Eigen statistic has three cointegrating

equations. The speed of the vector error correction process is more or less slow

except for change in interest rate and change in inflation rate, which are significant

where VECM is stable and diverging. Limitations and future scope of research is

added. Policy recommendations are also included.

INTRODUCTION

Foreign direct investment (FDI) is an investment in a business by an investor from

another country for which the foreign investor has control over the company purchased.

The Organization of Economic Cooperation and Development (OECD) defines

control as owning 10% or more of the business. Businesses that make foreign direct

investments are often called multinational corporations (MNCs) or multinational

enterprises (MNEs). FDI provides a win – win situation to the host and the home countries. FDI as a strategic component of investment is needed by India for its

sustained economic growth and development. FDI is necessary for creation of jobs,

expansion of existing manufacturing industries and development of the new one.

Indeed, it is also needed in the healthcare, education, R&D, infrastructure, retailing

and in long term financial projects. Need of FDI depends on saving and investment rate

in any country. Foreign Direct investment acts as a bridge to fulfill the gap between

investment and saving. In the process of economic development foreign capital helps

to cover the domestic saving constraint and provide access to the superior technology

that promotes efficiency and productivity of the existing production capacity and

generate new production opportunity. Foreign investments mean both foreign portfolio

investments and foreign direct investments (FDI). FDI brings better technology and

management, marketing networks and offers competition, the latter helping Indian

companies improve, quite apart from being good for consumers. The effectiveness

of FDI in bringing about the desired growth may be constrained by the level of

infrastructural developments and other macroeconomic variables . Infrastructural

development, openness and domestic market size are major determinants of FDI.

Even, exchange rate and interest rate may influence FDI inflows. Besides, balance of

payments adjustment is a good correlation with FDI flows. Political instability and

financial crises influence FDI flows negatively. Alongside opening up of the FDI

regime, steps were taken to allow foreign portfolio investments into the Indian stock

market through the mechanism of foreign institutional investors. The objective was

not only to facilitate non‐debt creating foreign capital inflows but also to develop the

stock market in India, lower the cost of capital for Indian enterprises and indirectly

improve corporate governance structures. FDI have helped India to attain a financial

stability and economic growth with the help of investments in different sectors. FDI

has boosted the economic life of India.

By allowing MNC in Indian economy, the government of India with the help of

World Bank and IMF introduced the macro-economic stabilization and structural

adjustment program. As a result of these reforms India open its door to FDI inflows

and adopted a more liberal foreign policy in order to restore the confidence of foreign

investors. Further, under the new foreign investment policy Government of India

constituted FIPB (Foreign Investment Promotion Board) whose main function was

to invite and facilitate foreign investment.

OBJECTIVE OF THE STUDY

In this paper, the author endeavors to explain the patterns of behavior of India’s foreign

direct investment inflows during 1971-2015. Besides, the author tries to relate FDI

inflows with macro variables like growth rate, interest rate, inflation rate, exchange

………………….read from

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DAILY EXCHANGE RATE BEHAVIOUR OF SPECIAL DRAWING RIGHTS PER YUAN

-Dr.Debesh Bhowmik 

Key words- SDR Yuan exchange rate, Autoregressive model,ARIMA model,GARCH model,volatility of exchange rate

JEL-C22,C52,F3,F31

Summery

After the inclusion of Yuan in SDR, the paper scrutinizes the daily exchange rate behavior of SDR per Yuan from 1/12/2015 to 16/2/2016 because monetarists predicted that RMB will be more volatile. The paper conducted to find out semilog trend values of exchange rate including residuals test for serial correlation, heteroscedasticity, autocorrelation and coefficient test for confidence ellipse. The paper verified the autoregressive models at lag one and three for which visibility of autocorrelations were also tested. Even, Box and Pierce(1970) ARMA model is estimated for stationary and stability of the series. Finally, to test volatility the ARCH test has been done including GARCH, and its conditional variance following Bollerslev(1986).The structural break was tested by Bai-Perron model(2003).

The paper showed that the estimated semilog linear  model of the daily exchange rate of SDR per Yuan during 1/12/2015 to 16/2/2016 showed that the exchange rate has been decreasing at the rate of 0.0697% per day which is statistically significant.

The paper showed that the exchange rate is declining, showing stationary and stability but marginal volatility is observed in the ARCH and GARCH models that can be minimized if China slowly and steadily introduce the capital account convertibility and financial sector reform including Yuan internationalization and if China can integrate policy of shore price and onshore pricing.

The sequential F statistic of break test are significant at 5% level which are shown in Table where repartitions were observed at 8,18,26 observations respectively.

After the declaration of the inclusion of RMB in SDR basket in November,2015, the SDR per Yuan is marginally depreciated with US Dollar which follows naturally with spot market rate with SDR and the more volatility was observed since then as predicted by the monetarists. But, the above models showed that those errors can be minimized through good management technique of stabilising exchange rate policy which can be helpful through new liberalized interest rate policy of PBC which can increase offshore and onshore liquidity and minimize their price differences, can follow convergence of forex market, can do more swapping, speed up 20-20 development strategy, introduce macro prudential management, to increase more RMB payments centers, increase linkages between offshore and onshore markets, and increase scope of FTA and so on. To face the absolute gap between RMB fixing and the previous trading day close , the investors can use HKEx’S USD/CNH futures based upon their trading preferences and investment objectives, either as a cost efficient risk management tool to hedge against RMB price risk, to capitalize on short term trading opportunities, or to exploit price discrepancy across the offshore and onshore markets.

The paper concludes that the SDR per Yuan daily exchange rate is not much volatile as has been found from several models studied here and the fear about volatility due RMB inclusion in SDR might be media effect and is not justified because China had already liberalized interest rate and depreciated RMB recently by about 6% that could not boost the volatility of the exchange rate abnormally rather the process of capital account convertibility and measures on Yuan internalization have been continuing speedily. Yet, China has to face competition in the freely floating exchange rate and interest rate with US Dollar and Euro in commodity, money, capital and stock markets respectively where it will have to increase its market capitalization and turn over. 

PUBLISHED IN FAME,VOLUME-2,MARCH 2017,THE JOURNAL OF FINANCE,ACCOUNTING,MANAGEMENT AND ECONOMICS,

SHRI SHIKSHAYATAN COLLEGE ,DEPARTMENT OF COMMERCE

KOLKATA 

REAL EFFECTIVE EXCHANGE RATE OF INDIA:PATTERNS AND DETERMINANTS

INTERNATIONAL JOURNAL FOR RECENT TRENDS IN BUSINESS AND TOURISMVOLUME-1,ISSUE-4,2017,OCTOBER--LINCOLN UNIVERSITY COLLEGE , MALAYSIA

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REAL EFFECTIVE EXCHANGE RATE OF INDIA: PATTERNS AND DETERMINANTS

Debesh Bhowmik

Former Principal, International Institute for Development Studies, Kolkata, India

Corresponding Author Email: debeshbhowmik@rediffmail.com

ABSTRACT

In this paper, author endeavors to establish the patterns and trends of Real Effective Exchange Rate of India during 1970-2015 and tries to show the determinants of REER e.g., growth rate, current account deficit as percent of GDP, percent of openness, foreign direct investment inflows, and foreign exchange reserves excluding gold. The author used semi-log, double log linear and exponential model, autoregression, ARIMA, GARCH models for trends and volatility. Bai and Perron (2003) model was applied to show structural breaks and Hodrick and Prescott (1997 ) model was applied for smoothness of cyclical trend. Johansen (1988, 1991, 1996) models were used to fit co-integration test and vector error corrections. Residual tests were done to verify autocorrelations, normality and impulse response functions were found to show stability and convergence.       

The paper concludes that REER has been declining at the rate 0.4085 percent per year which is insignificant at 5% level during 1970-2015 but it is exponentially declining at the rate of 0.2028 percent which is significant. AR(1) of REER is convergent, stationary and significant but AR(2) is convergent, non-stationary and insignificant. Even ARIMA(1,1,1) is non-stationary because AR(1) is stationary but MA(1) is non-stationary. GARCH(1,1) showed insignificant. Thus the series REER is highly volatile. This series contains five significant structural breaks in 1976, 1986, 1992, (downward) 2004 and 2010 (upward). Its pattern is cyclical which was turned to smooth cycle. Trace statistic showed three cointegrating vectors and Max-Eigen Statistic showed two cointegrating vectors that verify cointegration in the order one. Vector Error Correction model is stable because all roots lie in the unit root circle but it is non-stationary because impulse response functions are diverging and error corrections are significant  only in degree of openness and FDI inflows in relating REER during 1970-2015 with one period lag. Residuals test of VECM confirmed non normality and autocorrelations.

Only sound fiscal and monetary policy can control upward movement of REER so that significant relationships can be achieved with those selected determinants that would spur the growth of international trade.

Keywords- Real Effective Exchange Rate, Stationary, Structural Breaks, Causality, Co-integration, Vector Error Correction

INTRODUCTION

Real Effective Exchange Rate is an important tool in managing international trade and finance and macroeconomic stability in an open economy. It influenced export and import prices and trade volumes. Appreciation and depreciation of REER determined terms of trade, openness, foreign exchange reserves of an economy to a great extent. FDI inflows and current account balance are largely depend on the REER because in the liberalized and globalised world the adjustment in balance of payments is largely correlated with the movement of REER. The REER is closely related with the nominal and real rate by definition when it is trade weighted or export weighted with group of countries. Exchange rate policy whether it is nominal or real controls national inflation and influenced international inflation in which interest rate differential is the crucial and key variable. Today, under globalization REER is closely related with the growth rate also since volatility of REER is the barrier of high growth in which volume of trade matters. According to Balassa-Samuelson effect, volatility of REER influences export competitiveness and productivity. In calculating REER based with export or trade weighted 36 countries, RBI did not consider productivity. Even, India has not long run data on REER and NEER. However, India could not predict well the nature of capital account convertibility, the productivity changes and terms of trade changes in relating to REER. Therefore, the task before RBI is crucial because policy of exchange rate is also related with monetary and fiscal policies as well.

(A) Objective of the study

This paper endeavors to study the behavioral patterns of REER and its determinants in India during 1970-2015 where the author assumed that the basic determinants of REER are growth rate, current account deficit as percent of GDP, openness of the economy, foreign direct investment inflows, foreign exchange reserves excluding gold and so on. The relations were calculated through cointegration and vector error correction models. The policies of REER and limitations of the paper are also the aims of this study.

(B) Methodology and Data

Semi-log, and double-log regression models have been used for trends and relations and exponential model was used also for goodness of fit. AR(1), AR(2), ARIMA(1,1,1) and GARCH(1,1) models were applied to show autoregression, stationary and volatility analysis. Bai-Perron (2003) model was applied to find structural breaks. Granger  model(1969) was used to get causality. Hodrick-Prescott Filter model (1997) was used to find smoothness of cycles which allows to manage the exchange rate volatility. Johansen models (1988, 1991, 1996) were applied for cointegration and vector error correction analysis. Moreover, residual tests of VECM were also done for autocorrelation and normality. The data of REER, growth rate, current account deficit, openness, FDI inflows and foreign exchange reserves during 1970-2015 have been collected from RBI, World Bank and International Financial Statistics(IMF).

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