REDEFINING BUSINESS VISION -ISSUES AND CHALLENGES, VOL-1

REDEFINING BUSINESS VISION-ISSUES AND CHALLENGES

VOL-1:ACCOUNTING AND FINANCE

Edited by –Sanjib Kumar Basu,Soumya Saha,Sumanta Dutta

Regal Publications,F-159,Rajouri Gardens,NewDelhi-110027

Price-Rs1440/-,pp-xiii+382

The book is the outcome of the presented papers in the one day seminar organized by Department of Commerce of St.Xavier’s College,Kolkata in collaboration with University of Calcutta sponsored by UGC

Held on 19March,2016.It includes a comprehensive  coverage of all the issues relating to accounting, and finance and volume-2 covered marketing and human resources.

The contains of the book is as follows.

1] Forensic Accounting:Its role on Fraud Detection(with reference to White Collar Crimes in India)-Hanzala Awais and Priyodarshini Rasquinha

2] Voluntary Disclosure of Corporate Environmental Practices,Corporate Governance and Market Responsiveness:A Longitudinal Study in Indian Context-Abhijit Roy and Sumanta Kumar Ghosh

3]Impact of Companies Act,2013 on Depreciation and its Reporting:A Study of Selected Indian Companies-Abhik Kumar Mukherjee and Subhra jyoti Mondol

4]Impact of IFRS on Voluntary Adopted IT companies in India:A case study of Infosys Ltd,and Wipro Ltd—Malay Ranjan Mahapatra

5]E-Governance Initiatives of Government of West Bengal:A study on its utilization—Uttiya Kar

6]Profitibility position of the commercial banking sector in India:An empirical study on public and private banks—Manidipa Das Gupta and Som Sankar Sen

7]Business Trust in India:A look into its Tax Implication—Prof.Shubhayan Basu

8]Business ethics and corporate social responsibility:Two emerging issues of corporate sectors in India—Suvankar Chakraborty

9]FDI inflows and economic growth in India:A Fusillade of questions-Souvik Mukherjee,Tanusree Das,and S.Kavitha

10]Interpretation of customer perception about life insurance:A study of south Delhi area—Monirul Islam

11]Economic growth,foreign direct investment and financial crises—Debesh Bhowmik

12]India’s economic performance during the pre and post crisis period:A comparative Analysis—Rajib Bhattacherjya

13]Investment in money instrument and precious metals in different  economic phases in Indian context—Sharmistha Ghosh and Tumpa Chakraborty

14] Comparative study  of TATA steel Ltd and SAIL in terms of liquidity and its relation  with profitability—Palash Bandopadhyay and Priyanka  Agarwal

15] Tail Risk Behaviour of the Indian banking  sector  in the context of financial crisis of 2007-08—Piyali Dutta Chowdhury and Basabi Bhattacharjya

16]Financial inclusion:A qualitative critique of recent  finiancial reform—Joyita Banerjee and Hanzala Awais

17]Exchange rate exposure and its determinants on stock returns at firm level around crisis periods:A study of India from 2000-2013---Soumya Saha

18]A study on Asset  liability management as risk management technique in commercial banks in India—Khushboo Thakkar

19]A study on increasing trend of NPA on self help group bank linkage programme—Mithun Das

20]A study on primary market pricing in conflict with  behavioural finance approach-Investors biasness---Sunita Ghatak

21]Financial inclusion through mobile banking :How much merit does it carry?—Debabrata Jana and Abhijit Sinha

22]Inclusion through microinsurance:A case study of Nadia District,West Bengal---Sreemoyee Guha Roy.

My paper—Article no-11,pp167-195

Economic Growth, Foreign Direct Investment and Financial Crises

Dr.Debesh Bhowmik

 (Retired Principal and associated in International Institute for Development Studies, Kolkata)

Email-debeshbhowmik@rediffmail.com

Key words- Foreign Direct Investment, economic growth, financial crises,currency crisis,banking crisis,sovereign crisis

JEL-C23,C33, F21,F01,O55

I.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% and FDI as of GDP is 19.39% in 2014.The highest share was occupied by Mauritius,36%, followed by Singapore,12%,UK ,10%,Japan,8%,and USA,6% respectively. Service sector is leading the sectoral distribution of FDI ie 18%, followed by construction development,11%,telecommunication and computer ,6% each, and drug and pharmaceuticals, 5% respectively in 2013-14 .

This paper will endeavour to verify nexus between FDI and growth in Indian economy using econometric analysis and studied analytically the changes of FDI during crises.

II. Literature review

The nexus between Growth and FDI inflows varies from country  to country, from one period to another and from one sector to other in which there are many economic literatures that represent economic relevance. Ragimana(2012) studied that FDI growth nexus is positive in Solomon Island during 1970-2010 which was verified through Granger Causality test and Co-integration test. Adelake(2014) found that FDI has positive overall effect on economic growth in Sub-Saharan Africa, although the magnitude of this effect depends on some country specific features during 1996-2010 of 31 SSA countries of panel data where role of governance should positive on encouraging FDI inflows. Tintin(2012) showed that FDI spurs economic growth and development in developed ,developing and the least developed countries which was found from the study of a sample of 125 countries (38 developed,58 developing and 29 least developed countries) over the 1980-2010 period by using least square method of the panel data. Stehrer and Woerz(2009) verified the relation in OECD and non OECD countries during 1981-2000 and found that a 10% increase in FDI can increase 1.2% in growth rate per year. Li and Liu(2005) studied 84 countries using data of 1970-1999 period and concluded that a 10% increase in FDI can stipulate 4.1% growth rate per year. Johnson(2006) took 90 developed and developing countries using data of 1980-2002 period and concluded positive relation through OLS method. Ewing and Yang(2009) studied 48 states in USA during 1977-2001 in manufacturing sector and found direct relation between growth and FDI. Hansen and Rand(2006) used co-integration and causality tests in 31 developing countries during 1970-2000 and showed positive relation.Herzer et.al(2008) verified the nexus in 28 developing countries during 1970-2003 and found positive nexus. Nair (2010) showed that FDI has a positive and highly significant effect on overall growth in India during 1970-2000 in regression results which leads to an increase in market size.The result proves that it cannot be rejected that the FDI does not Granger cause GDP growth at the 5% level, but it can be reflected that GDP growth does not Granger cause FDI.Tiwari and Mikhai(2011) verified that exports and FDI show a significant and positive impact on economic growth in a panel of 23 Asian countries during 1986-2008.Chakraborty and Basu(2002) suggest that GDP in India is not Granger caused by FDI ,the causality seems to run more from GDP to FDI.Oluwatosin,Oluoegun,Fetus and Abimbola(2012) showed that FDI has positive linkage over economic growth in five ECOWAS countries during 1970-2005 which was verified through Granger causality tests in VEC model. Yesuf and Tsehaye(2012) investigated the causal link between FDI and economic growth in Ethiopia during 1974-2010 and did not find any causality running from FDI to growth or vice versa but there was an evidence of co-integration between FDI and growth. The flow of FDI is too small to translate into growth. Using the VAR Granger causality/Block Exogeneity Wald Test in Cote d’Ivoire during 1980-2007,N’guessan and Yue(2010) concluded that there is a long run relationship between FDI, trade openness and growth which stated that about 10% increase in trade openness would lead to about 97% growth of output and 10% increase in FDI would result in about 1% in growth of output.

The UNCTAD study which covers 140 countries over the period 1998-2000 with 8 explanatory variables  show that FDI can be explained in terms of GDP per capita, exports as a percentage of GDP and telephone lines per 1000 of the populations. In general terms the results tell us that countries that are more successful in attracting FDI are developed countries with a high degree of

openness. Factors failing the EBA robustness test as determinants of FDI inflows included: GDP growth rate, commercial energy use, R&D expenditure, tertiary enrolments and country risk.

Anyanwu (2012) estimated from cross-country regressions for the period 1996-2008 which indicate that: (i) there is a positive relationship between market size and FDI inflows; (ii) openness to trade has a positive impact on FDI inflows; (iii) higher financial development has negative effect on FDI inflows; (iv) the prevalence of the rule of law increases FDI inflows; (v) higher FDI goes where foreign aid also goes; (vi) agglomeration has a strong positive impact on FDI inflows; (vi) natural resource endowment and exploitation (such as oil) attracts huge FDI; (vii) East and Southern African sub-regions appear positively disposed to obtain higher levels of inward FDI.

Applying vector error correction model, Dinda (2009) empirically investigated the determinants of foreign direct investment inflows to Nigeria during 1970-2006. This study suggests that the endowment of natural resources, openness, macroeconomic risk factors like inflation and exchange rates are significant determinants of FDI inflows to Nigeria.

 III.Economic growth-foreign direct investment nexus: A Case Study of India

[i] Methodology and data

 I have assumed the co-integrating model of foreign direct investment in the following manner,

Y = f( x₁,x₂ x₃,x₄ ,x₅)

Where Y= foreign direct investment inflows in million US dollars

X₁= GDP growth rate per cent per year

X₂= Degree of openness ( measured by (export+import)/2/GDP )

X₃= Total external debt in million USdollars

X₄= interest rate (lending rate as per availability in time series)

X₅= exchange rate ( nominal rate with respect to US dollar)

We have collected data from the World Bank,Reserve Bank of India, UNCTAD for the year from 1990 to 2013.For co-integration analysis we use Engle and Granger(1987) , Johansen (1991,1996) and Johansen and Juselius (1990) methodologies.

******* VII.Concluding remarks

Taking GDP growth rate, degree of opennesss, total external debt, interest rate and exchange rate as the important determinants of FDI in India during 1990-2013, the paper verified that the Engle-Granger methodology showed that there is co-integrating relationship where degree of openness and interest rate are significant where as Johansen test proved that there are 5cointegrating vectors  in the level series, 5 cointegrating vectors in the first difference series and 5 cointegrating vectors in the log series respectively. The VECM verified  that there are serial correlation and ARCH error with non-normal distribution where all roots lie inside the unit circle including 5 unit roots but impulse response functions do not approach to zero and error correction terms and residual systems are explosive.

In concluding remarks we like to mention that a country which has a stable macroeconomic condition with high and sustained growth rates will receive higher FDI inflows than a more volatile economy. Therefore, it is expected that GDP growth rate, industrial production, and interest rates would influence FDI flows positively and the inflation rate would influence positively or negatively. Market size plays an important role in attracting foreign direct investment from abroad. Market size is measured by GDP. Market size tend to influence the inflows, as an increased customer base signifies more opportunities of being successful and also the fact that with the rampant development the purchasing power of the people has also been greatly influenced moving to many levels higher in comparison to what it was before the economic growth.

The paper also concludes that FDI does not cause Granger financial crises but financial crises do cause Granger FDI. In every financial crisis since 1890,FDI changes downward but in Euro crises and US subprime crises, FDI did not decline in most of the East Asian countries. The declining growth and FDI in all financial crises were the general phenomenon. Also in India, financial crises had negative impact on FDI and growth.

Growth-inflation nexus: threshold model of inflation in India

Author: 

Dr. Debesh Bhowmik

Subject Area: 

Social Sciences and Humanities

Abstract: 

In this paper, author tries to relate inflation rate (measured both by CPI and WPI) with growth rate in India during 1960-2015 and calculated target rate of WPI and CPI. Author used Bai-Perron test (2003) for structural breaks and also used Granger Causality test (1969), Johansen cointegration and vector error correction models (1991,1996) for relationship and used residual test for autocorrelation and found impulse response functions for convergence and stability for both CPI and WPI with growth. By taking Khan and Senhadi model (2001), author found out the target rate of CPI and WPI for India. Author observed that one per cent increase in whole sale price index per year leads to 0.59 per cent increase in GDP growth rate per year in India during 1960-2015. The WPI granger cause growth rate but not vice versa i.e. causality is uni-directional. Growth and WPI is cointegrated in the order of one. VEC Model is stable but change in WPI has slow error correction whereas change in growth rate is not a good fit but its error correction process is faster than change in WPI. Its residuals are not normal having autocorrelation problem and impulse response functions are diverging. During 1960-2015, WPI has four structural breaks at 1974, 1988, 1995 and 2008 respectively. Above the threshold level of WPI=4.12 with 2010=100, the inflation-growth nexus tends to negative. The paper also found that one per cent increase in consumer price index per year leads to 0.55 per cent increase in GDP growth rate per year in India during 1960-2015. The CPI granger cause growth rate but not vice versa i.e. causality is uni-directional. Growth and CPI is cointegrated in the order of one. VEC Model is stable and is highly good fit but only error correction process of change in growth rate is significant for speedy correction. Its residuals are not normal having autocorrelation problem and impulse response functions are diverging. During 1960-2015, CPI has four structural breaks at 1974, 1987, 1996, and 2008 respectively. Above the threshold level of CPI=3.258 with 2010=100, the inflation-growth nexus tends to negative.

PDF file: 

21230.pdf

Capital inflows and Silver Standard in India

                Capital inflows and Silver Standard in India

THE FOLLOWING ARTICLE IS PUBLISHED IN THE CHANDIGARH CONFERENCE ON 09-11 MARCH,2017,CONDUCTED BY IMRF

VOLUME-3 ,ISSUE-1,73-80

Capital inflows and Silver Standard in India

Dr.Debesh Bhowmik (Retired Principal and Ex.Associate Editor-Arthabeekshan-Journal of Bengal Economic Association)

Abstract

In this paper author tries to relate gold and silver inflows with GDP,GDP per capita,export, import and gold silver price ratio in India during silver standard regime from 1851 to 1893. Author used semi-log,double-log regression models, Johansen cointegration and VAR models (1991,1996) and Bai-Perron model(2003) for structural change taking data from Maddison(2006) and Ambedkar(1923). The paper concludes that gold inflows during 1851-1893 had decreased at the rate of 0.34% per year insignificantly but it was nonstationary, convergent and had no structural breaks. Silver inflows during 1851-1893 had increased at the rate of 1.51% per year insignificantly and found nonstationary and convergent  and had one upward structural break in 1857.No cointegration among gold or silver inflows with GDP,GDP per capita, export, import and gold silver price ratio was found during 1851-1893 where VAR model was unstable and nonstationary and impulse response functions were diverging. Semi-log linear regression model among silver inflows and gold inflows with those variables were also insignificant although GDP, export, import,and gold silver price ratio had been increasing at the rates of 0.52%,9.14% ,5.16% and 0.77% per year significantly. But double-log linear regression model suggested that gold inflows had significant impact from GDP,GDP per capita, export, and gold-silver price ratio but had no significant impact of silver inflows from those variables during 1851-1893 respectively. Yet,there is bidirectional causality among gold inflows, GDP, GDP per capita, export, import and gold silver price ratio significantly during the given period. Even, there were sharp depreciation of rupee sterling rate,falling silver price ,silver production and rising gold price and gold production during the silver standard regime. Thus, gold and silver inflows could not synthesize the silver standard more effective in macro-dynamic adjustment during 1851-1893 although the series of managerial experiments of the commissions and government are equally responsible for instability of the silver standard in India which was equally identical with gold standard in England

Key words-Net gold inflows, net silver inflows, silver standard, GDP, export, import, cointegration, VAR

JEL-E42,F33,N10,N20

I.Introduction

Silver standard in India was introduced in 1835 but the act of XVII and the act of XXI in 1835 declared both silver coin and copper coins as legal tender ,on the other hand , gold coin was not legal tender yet it was circulated. Later on, in 1861 by Act of XIX , gold coin was treated as legal tender. In 1861,the paper currency notes were circulated. The gold:silver was 1:15.5 and rupee sterling rate was fixed at 1s10.5d where exchange was governed by relative values of gold and silver.

During long 400 years from 1493 to 1893 , gold and silver production were more or less uniform but during 1600-1700,index of gold rose from 130 to 176,which rose to 270 during 1700-1800.In 1870,the index of gold production stipulated to 2124 as compared to 450 for silver. Even the rupee sterling rate depreciated and price of gold silver ratio appreciated to a lager extend. India was one of chief producer of the silver and gold but she was the net importer of both gold and silver which were volatile. Although silver standard during 1873-1893 in India was as like as gold standard in England during 1873-1893,yet British government introduced several policies of mints, currency  circulation as well as bimetallism as an experimental basis which made the silver standard unstable .During this period, most of the countries in the world started to introduce gold standard including British colonies. In India, gold supplies and its prices were stipulating compared to silver, but British Government denied to introduce gold standard in spite of numerous positive signals of implementing gold standard by many commissions. In 1893, England declared gold exchange standard in India where gold was not convertible to rupee but rupee was convertible to sterling which was fixed parity with gold. Therefore , success story of silver standard is little yet there is no vital disturbance in working the system of silver standard in India. 

II.Objective of the paper

In this paper author endeavours to analysis the working of capital inflows in the silver standard in India and its impact on the GDP ,GDP per capita and on international trade and even on the gold silver price ratio during 1851-1893.The net gold import and net silver import were considered as capital flows for the specified period.

III.Methodology and data

Net gold import and net silver import were treated as capital flows in India during 1851-1893.The trend lines of gold inflows, silver inflows, export, import, GDP,GDP per capital, ratio of gold and silver price were calculated by semi-log linear model. Stationary was observed through ARIMA model, structural change was shown by Bai-Perron model(2003).Double-log multiple regression model was used for showing relationship among those variables with gold and silver inflows for the specified period. Since there is no cointegration with gold inflows and other variables and silver inflows with other variables ,author used Johansen VAR model(1991,1996) for showing relationship analysing residual tests and impulse response functions. Even,Granger (1969) model was tested for causality.Data for GDP and per capita GDP were collected from Maddison(2006) and data for all other variables were taken from B.R.Ambedkar(1923). Assume,x₁=GDP,x₂=GDP per capita,X₃=export,x₄=import,x₅=gold silver price ratio,y₁=net gold import,y₂=net silver import

IV.Some observations of the model

During the silver standard regime in India from 1851 to 1893,net gold inflows had been decreasing at the 0.34 per cent per year which was insignificant.

Log(y₁)=14.770-0.003433t

                   (58.54)* (-0.34)

R²=0.0028,F=0.118 ,DW=0.46 , y₁= net gold inflows(imports) ,*=significant at 5% level.

Net gold inflow from 1851 to 1893 is convergent but nonstationary because its AR(1) is convergent and stationary but its MA(1) is convergent and nonstationary.

Log(y_1t)=14.63648+0.7232log(y_1t-1)+ε_t+0.083569ε_t-1+0.26009σ²

                   (40.19)*  (3.46)*                  (0.24)            (6.76)*

R²=0.58  ,F=18.57  ,DW=1.97  ,inverted AR root=0.72 , inverted MA root=-0.08 ,*=significant at 5% level.

This series has no structural breaks during the period.

On the other hand, net inflow of silver in India during silver standard from 1851 to 1893 had been stipulating at the rate of 1.51% per year which was insignificant.

Log(y₂)=15.034+0.015138t

                   (43.84)*  (1.115)

R²=0.029 ,F=1.24 , DW=1.36 , y₂=net inflow of silver ,*=significant at 5%.

The net inflow of silver in India during 1851-1893 is nonstationary but convergent which is shown by ARIMA(1,1,1) model.It is not a good fit yet it is stable.

Log(y_2t)=15.363+0.48873log(y_2t-1)+ε_t-0.183616ε_t-1+1.0639σ²

                   (35.71)*   (0.96)               (-0.34)             (7.32)*

R²=0.11 , F=1.64,DW=1.96,inverted AR root=0.49,inverted MA root=0.18 ,*=significant at 5% level.

Net inflow of silver has one upward structural breaks in 1857 only.This is verified by Bai-Perron test(2003)in which HAC standard errors and covariance was assumed and trimming 0.15 with maximum 5 beaks is assumed.

Table-1: Structural breaks of net inflow of silver

Variables	Coefficient	Standard error	T statistic	Prob
	1851-1856=6 obs
c	14.2328	0.3368	42.25	0.00
	1857-1893=37 obs
c	15.537	0.218	71.30	0.00

R²=0.17  ,F=8.64*  ,DW=1.62;Source-Computed by author

Double log multivariate regression model showed that One per cent increase in GDP,GDP per capita, export, import, gold silver price ratio and net silver inflow led to 12.68% decrease ,19.27% increase,1.89% increase ,1.47% increase,9.93% decrease and 0.13% increase in net inflows of gold per year respectively where relation between gold inflows and GDP,GDP per capita,export, gold silver price ratio are significant at 5% level.

Log(y₁)=-19.359-12.683log(x₁)+19.275log(x₂)+1.89log(x₃)+1.47log(x₄)-9.938log(x₅)+0.1319log(y₂)

                  (-0.56)   (-1.99)*          (2.86)*          (2.54)*          (1.53)       (-3.35)*           (1.35)

R²= 0.48, F=5.67*   ,DW=1.24 , where x₁=GDP,x₂=GDP per capita,x₃=export,x₄=import,x₅= gold silver price ratio,y₂= net inflows of silver

Similarly, one per cent increase in GDP,GDP per capita, export, import, gold silver price ratio and net gold inflow per year led to11.11% fall,12.13% rise,1.86% increase,0.045% rise,1.47% increase and 0.37% increase in net silver inflows in India per year during 1851-1893 in silver standard regime which are all insignificant.

Log(y₂)=2.739-11.1162log(x₁)+12.139log(x₂)+1.86log(x₃)-0.045log(x₄)+1.47log(x₅)+0.37log(y₁)

                (0.047) (-1.10)               (0.98)            (1.416)         (-0.027)          (0.25)            (1.35)

R²=0.24 ,F=1.89 , DW=1.59 ,  

To show linear combination of silver inflows with other variables, Johansen Cointegration test suggests that there is no cointegrating vector shown by Trace and Max Eigen Statistic (Table-2).

Table-2:Cointegration test

Hypothesised no of CEs	Eigen value	Trace statistic	0.05 CV	Prob*
None	0.524	113.692	125.615	0.211
At most 1	0.445	83.189	95.753	0.266
At most2	0.412	58.993	69.818	0.267
At most3	0.299	37.219	47.856	0.337
At most4	0.245	22.630	29.797	0.264
At most5	0.236	11.095	15.494	0.205
At most6	0.0006	0.026	3.841	0.87
Hypothesised no of CEs	Eigen value	Max Eigen statistic	0.05 CV	Prob*
None	0.524	30.502	46.231	0.75
At most 1	0.445	24.196	40.077	0.825
At most2	0.412	21.774	33.876	0.625
At most3	0.299	14.588	27.584	0.779
At most4	0.245	11.534	21.131	0.593
At most5	0.236	11.068	14.264	0.150
At most6	0.0006	0.0266	3.841	0.870

*=Mackinnon Haug Michelis(1999) p values

Since there is no cointegration ,The estimated VAR model is given below.

Δx_1t=8451.51+0.212Δx_1t-1-2.161Δx_2t-1+3.10E-06Δx_3t-1+1.53E-05Δx_4t-1+174.27Δx_5t-1-9.07E-06Δy_1t-1+7.32E-06Δy_2t-1

         (3.6)*       (1.02)        (-0.54)           (0.32)             (1.27)                   (1.45)               (-0.22)                  (0.51)

R²=0.92  ,F=56.29  , AIC=14.47  SC=14.80

Δx_2t=313.711-0.025Δx_1t-1+0.796Δx_2t-1+1.20E-07Δx_3t-1+3.32E-07Δx_4t-1+7.67Δx_5t-1-8.67E-07Δy_1t-1+2.37E-07Δy_2t-2

           (3.97)*   (-3.53)*           (5.83)*      (0.365)             (0.807)             (1.86)             (-0.86)            (0.48)

R²=0.765  , F=15.81  , AIC=7.72  , SC=8.05

Δx_3t=-46481278+4953.34Δx_1t-1-137563.9Δx_2t-1+0.466Δx_3t-1+0.068Δx_4t-1+4792340Δx_5t-1+1.919Δy_1t-1-0.355Δy_2t-1

            (-1.08)           (1.27)                (-1.84)         (2.59)*           (0.305)         (2.14)*             (2.57)*         (-1.33)

R²=0.96  ,F=130.0*  , AIC=34.14 , SC=74.47

Δx_4t=-1.11E+08+9232.72Δx_1t-1-84374.41Δx_2t-1+0.084Δx_3t-1+0.3377Δx_4t-1+3264343Δx_5t-1+0.2086Δy_1t-1-0.235Δy_2t-1

            (-3.92)*   (3.61)*            (-1.72)               (0.713)           (2.29)*             (2.21)*          (0.425)            (-1.33)

R²=0.98  , F=247.81*  , AIC=33.3  , SC=33.63

Δx_5t=4.0918-8.24E-05Δx_1t-1+0.00176Δx_2t-1+4.27E-09Δx_3t-1-2.07E-08Δx_4t-1+0.716Δx_5t-1-6.34E-08Δy_1t-1+1.22-E08Δy_2t-1

             (1.8)             (-0.401)         (0.439)       (0.45)               (1.75)                (6.06)*               (-1.73)              (0.908)

R²=0.97  , F=212.09*   , AIC=0.629  ,   SC=0.96  

Δy_1t=-8108862+636.61Δx_1t-1+4042.18Δx_2t-1-0.0215Δx_3t-1-0.00204Δx_4t-1-76501.53Δx_5t-1+0.8244Δy_1t-1+0.033Δy_2t-1

            (-0.81)       (0.708)            (0.23)             (-0.51)           (-0.03)                (-0.14)            (4.78)*             (0.54)

R²=0.67 , F=10.28  , AIC=31.21  , SC=31.54

Δy_2t=-63316662+3366.48Δx_1t-1+311.52Δx_2t-1-0.034Δx_3t-1-0.204Δx_4t-1+1705435Δx_5t-1+1.036Δy_1t-1+0.235Δy_2t-1

           (-2.56)*      (0.50)                  (0.007)      (-0.33)           (-1.58)              (1.3)            (2.42)*            (1.53)

R²=0.42  , F=3.63  , AIC=33.03  , SC=33.36 , *=significant at 5% level

The estimated VAR model states that [i] change of GDP per capita is negatively related with change of previous period’s GDP and positively related with previous period’s GDP per capita,[ii] change of export is positively related with change of previous period’s export,ratio of gold and silver price,change of gold inflows,[iii] change of import is positively related with change of previous period’s GDP,import and gold silver price ratio,[iv]change of gold and silver inflows are positively related with their previous period .Other relations are insignificant.         

This VAR model is unstable because one of its 7 roots is greater than one ,two roots are imaginary and 4 roots are less than one (,ie 1.012998,0.853108±0.084339i,0.527198, 0.307550,0.272081),so all roots do not lie inside the unit root circle.

The impulse response functions are diverging so that it is nonstationary and unstable.The exogenous shocks could not tend the model into equilibrium.

VII.Conclusion

The paper concludes that gold inflows during 1851-1893 had decreased at the rate of 0.34% per year insignificantly but it was nonstationary,convergent and had no structural breaks.Silver inflows during 1851-1893 had increased at the rate of 1.51% per year insignificantly and found nonstationary and convergent  and had one upward structural break in 1857.No cointegration among gold or silver inflows with GDP,GDP per capita,export,import and gold silver price ratio was found during 1851-1893 where VAR model was unstable and nonstationary and impulse response functions were diverging.Semi-log linear regression model among silver inflows and gold inflows with those variables were also insignificant although GDP,export,import,and gold silver price ratio had been increasing at the rates of 0.52%,9.14% ,5.16% and 0.77% per year significantly.But double-log linear regression model suggested that gold inflows had significant impact from GDP,GDP per capita,export,and gold-silver price ratio but had no significant impact of silver inflows from those variables during 1851-1893 respectively.Yet,there is bidirectional causality among gold inflows,GDP,GDP per capita,export,import and gold silver price ratio significantly during the given period.Even,there were sharp depreciation of rupee sterling rate,silver price and production and gold price increased with production during the silver standard regime.Thus,gold and silver inflows could not synthesize the silver standard more effective in macro-dynamic adjustment during 1851-1893 although the series of managerial experiments of the commissions and government are equally responsible for instability of the silver standard in India which was equally identical with gold standard in England.

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