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.

References

[1]Ambedkar,B.R.(1923).The problem of rupee:Its origin and solution,P.S.King & sons Ltd,London.

[2]Bhowmik,Debesh.(2016). B.R.Ambedkar and Silver standard in India,paper will be presented in International seminar in Magadh University.

[3]Bhowmik,Debesh.(1992-93).A profile of Dr.B.R.Ambedkar’s view on the concept of Convertibility of Rupee,published in Indian Economic Association 76^th Conference volume-1993-94,Bombay,14-16,republished in in Debendra Kumar Das (ed)-Great Indian Economists: Their creative vision for socio-economic development,314-320,(Deep and Deep Publications, New Delhi)

[4] Bhowmik,Debesh(ed).(2016).International Monetary System:Past,Present and Future,Regal Publications, NewDelhi.

[5]Bhowmik,Debesh.(2003).Essays on International Money,Deep and Deep Publications, New Delhi.

[6]Ching,Jao Yu.(1965).The Silver Standard and China,1911-1935,University of Hongkong, Thesis for Master of Arts.

[7]Coyajee,J.C.(1983).Development of Currency System in India,Deep and Deep Publications, NewDelhi

[8]Das,Debendra Kumar.(2004).Relevance of Dr.Ambedkar’s Economic Ideas on the Problems of Indian Currency:Some Observations,published published in Indian Economic Association 76^th Conference volume-1993-94,Bombay,7-10,republished in Debendra Kumar Das (ed)-Great Indian Economists:Their creative vision for socio-economic development,299-306,Deep and Deep Publications,NewDelhi).

[9]Fernholz,Ricardo.Mitchener,Kris James &Weidenenmier,Merc.(2013).Pulling up the Transished Anchor:The End of silver as a Global Unit of Account,www.cepr.org

[10]Granger, C.W.J.(1969). Investigating Causal Relations by Econometric Models and Cross-spectral Methods, Econometrica, Vol-37,No-3, 424-438.

[11]Jadhav,Narendra.(2005,April).Exchange Rate Regime and Capital Flows:The Indian experience, Chief Economists’ Workshop,Bank of England.

[12]Johansen,S.(1988).Statistical Analysis of Co-integrating Vectors. Journal of Economic Dynamics and Control, Vol. 12, 231-254.

[13]………….(1991,Nov). Estimation of Hypothesis Testing of Co-integration Vectors in Gaussian Vector Autoregressive Models,  Econometrica  59,1551-80

[14]………….(1994).The role of the constant and linear terms in co-integration analysis of nonstationary variables. Econometric Reviews,13,205-229

[15]Johansen, S.( 1995). Likelihood-Based Inference in Co-integrated Vector Autoregressive

Models. Oxford  University Press.

[16]……….(1996). Likelihood-Based Inference in Co-integrated Vector Autoregressive Models, 2^ndEdition,Oxford University Press.

[17]……….. & Juselius,K.(1990).Maximum likelihood estimation and co-integration with application to the demand of money. Oxford Bulletin of Economics and Statistics,Vol-52,No-2,169-210.

[18]Keynes, J.M.(1913).Indian currency and finance. Macmillan and co.

[19]Leavens,Dickson.H.(1939).Silver Money,Principia Press Inc,Bloomington,Indiana

[20]Ma,Debin.(2012).Money and Monetary System in China in the 19-20^th century:An Overview, Working Paper No-159/12,London School of Economics.

[21]Maddison, A.( 2006).The World Economy: Vol-1 and 2. OECD: Paris

[22]…………..(2007).Contours of the world economy,1-2030:Essays in Macro Economic History,OUP.

[23]Roy,Alokananda.(2004).Ambedkar versus Keynes-On Indian Currency:In the Light of Contemporary Relevance,published in published in Indian Economic Association 76^th Conference volume-1993-94,Bombay,11-13 republished in  Debendra Kumar Das (ed)-Great Indian Economists:Their creative vision for socio-economic development,307-313,Deep and Deep Publications, New Delhi.

[24]Velde,Francois R.& Weber,Warren E.(1998).A Model of Bimetallism,Federal Reserve Bank of Minneapolis,Research Department,Working Paper-588.

[25]Zaraga,Ludovico.(2014).Effects of Exchange Rate Regimes on Trade: the Case of Silver Standard India,Northwestern University,Nov, 24.

Econometric Analysis of the performance of SSI Sector in India during 1980-81-2014-15

ABSTRACT

In this paper, author attempts to establish relationship among output, employment, average productivity of labour and export of SSI sector in India and GDP in India during 1980-81-2014-15 through simple regression analysis, causality test, cointegration and vector error correction models. The paper concludes that output of SSI sector has been increasing at the rate of 10.12% per year and exponentially at the rate of 0.554% per year during 1980-81-2014-15.The series is stationary, stable and divergent as indicated by ARIMA and AR models. Average productivity, employment and export of SSI sector have been rising at the rates of 1.68%, 8.43%, and 13.34% per year respectively during the same period. One per cent increase in export led to 0.48% increase in GDP per year during the specified period. Production, employment, average productivity and export of SSI showed two cointegrating vectors whose vector error correction model is stable, divergent and insignificant error correction process. India’s GDP,SSI sector’s output, employment, average productivity and export have two cointegrating vectors but its vector error correction model is stable, divergent and insignificant error correction having problem of autocorrelations. New policy recommendations of RBI and new government policy on MSME are likely to accelerate the performance of SSI and its contribution to the national economy.   

I.Introduction

The promotion of the small-scale sector in India has been an important thrust of industrial policy since independence though the focus of concern changed with the priorities of each five year plan. A Small Scale Industries Board was set up in 1954. Small Scale Industries and Agricultural & Rural Industries and the Small Industries Development Organisation (SIDO) which was under the Development Commissioner, Small Scale Industries were set up in 1956. At the State level, the Commissioner/ Directorate of Industries were the main institutional authority for SSIs. This structure has remained, though several other institutions have come into being in the 1970s and 1980s, particularly at the State level.

The Karve Committee Report (1955) was one of the earliest of these exercises which recommended a protective environment for the growth of small industries in India. Since then, policies targeted for the SSI sector have aimed at fostering its growth through positive policy interventions in the areas of finance, technology, infrastructure and extension services, among several other requirements of the sector. Supportive policies through the 1960s, 70s and 80s took the form of reservation of products exclusively for the SSI sector (836 products are reserved exclusively for SSIs at present) grant of fiscal concessions and government procurement of supplies from the sector. Due to liberalization, globalization and privatisation, SSI sector has so far been insulated to a large extent from pressures of competition both domestically and internationally. There are at least 3lakh units declared as sick and out of production, accounting for 10 percent of the recorded units.

The sector now employs 17 million persons and is the second largest employer of India's workforce after agriculture. It now accounts for 95% of all industrial units in the country and 40% of total output. About 7,500 products are manufactured in the small-scale sector. The export share is 35%.The composition of exports shows the largest shares of SSIs are in the industry groups : hosiery and garments (29.0%) , food products (21.4%) and, leather products (18%). The industry groups which have recorded high growth rates and a large share in total production of SSIs are: textile products, wood, furniture, etc., paper and printing, and metal products.
The total number of SSI working units in the country is estimated to be around 3 million. In terms of ownership, the vast majority of SSI units are proprietary concerns (80.5%) with only 16.8% functioning as partnerships and private limited. A UNIDO study defines clusters as 100 registered small-scale units. There are estimated 350 SME clusters in India which contribute directly and indirectly to 60% of India's exports. The location-wise distribution of clusters shows 65% concentrated in cities and metros and only 13% in small towns and rural areas. There is scope for encouraging the development of clusters in rural areas and rural-based artisan centres. The micro, small and medium enterprises (MSMEs) currently employ 12 crore individuals and contribute 15 percent to GDP. 

II. Objective

In this paper, the author tried to find out the growth of output, employment, average productivity and export of small scale industries in India during 1980-81-2014-15 and relate among them with GDP in India by causality, cointegration and VEC models.

How much Indian GDP is affected by those factors was also calculated by the author during the specified period. The new policy of the Government of India on MSME is an added area of this paper.

III. Methodology and data

Semi-log linear and exponential model were used to calculate growths of output, employment, average productivity, and export of SSI sector during 1980-81-2014-15. Double log multi-variable models were used to show relationship between GDP, output, employment, average productivity and export of SSI sector of India in the same period. Granger Causality, Johansen cointegration and Vector Error Correction Models were used to relate among them. The data of production, employment, average productivity of labour, exports of SSI sector in India and GDP at factor cost of India during 1980-81-2014-15 were collected from the Reserve Bank of India.

IV. Literature review

Rao and Kiran(2014) studied that the sector has characterized by low investment, operational flexibility, location wise mobility and import substitution. The Sector has been undergone a metamorphic change in the era of globalization. Many changes have taken place both national and international markets. The sector is playing a prominent role in ensuring the inclusive growth and regional balance. The sector is consistently registered a higher growth rate than the rest of industrial sector. There are over 6000 products ranging from traditional to high-tech items manufactured by this sector. Besides, the sector is facing challenge in the form of competition and opened opportunities due to improved technology, collaborations government intervention. Malapati(2011) showed that small-scale industries have been playing a momentous role in overall economic development of a country like India where millions of people are unemployed or underemployed. This sector solves these two problems through providing immediate large-scale employment, with lower investments. According to Dr. Manmohan Singh, “the key to our success in employment lies in the success of manufacturing in the small scale sector.” In a country like India, where capital is scarce and unemployment is wide spread, growth of small-scale industries is vital in order to achieve balanced economic growth. The strength of small-scale enterprises lies in their wide spread dispersal in rural, semi-urban and urban areas, fostering entrepreneurial base, shorter gestation period, and equitable distribution of income and wealth. Susmita Mohan(2014) described that in Kerala the amount of investment and the value of production has increased but, with respect to the amount of employment and the number of enterprises, a marginal decline has been observed. The total number of small enterprises does not show a real progress. If the potential of SSI is properly harnessed, it can help in accelerating the pace of socio-economic development and balanced regional growth apart from creation of employment opportunities. It is very essential to develop the industrial sector of Kerala mainly through the development of SSI sector. Hussain(2004) showed that the growth, production, export potentiality of SSI sector of India are high. Bayiuei(2004) explained that paper highlights the role and performance of small-scale industries in the economy with the parameters of number of units, production, employment and exports. The Report of Loksava Secretariat (2014) showed the export, credit and sick industries and government policies of SSI sector of India. Garg(1996) analysed the growth of SSI sector especially after 1980 and examined structure of fiscal incentives which improved the growth of SSI sector. Vanipriya and Venkatrumaraju (2011) studied that Small scale industry is widely recognized as a powerful instrument for socio economic growth and balanced sectoral development. One of the distinctive characteristics of small scale sector is that the development of these industries would create broader employment opportunities assisting entrepreneurship and skills development and ensure better use of scarce financial resources and appropriate technology. The small enterprises have by now established their competence to manufacture a wide variety of sophisticated goods in different product lines requiring a high degree of skill and precision. Chowdhury and Saini (2015) indicate that small manufacturers are affected in the globalization era and facing lot of problems to run their businesses. It has been observed that units from all surveyed industries irrespective of age and turnover believed that liberalization has resulted into more competition, increased quality consciousness, difficulty in marketing, dumping of cheaper goods by other countries, reduction in profit margin and high level of customer satisfaction. Small units are not using latest machinery to manufacturer quality product with latest design as per international standards.

There is absence of clear policies relating to marketing and human resource management. Most of the units do not have separate marketing and human resource departments. Small manufacturers are unable to attract the professionals because of their financial limitations. Another problem of the small units is that there is lack of cluster association for the small industry. The operational cluster associations are ineffective and not helping much to the industry. The domestic and foreign markets have become highly competitive due to the process of liberalization. Sonia and Kansal(2009)showed the growth of output, employment and export of SSI sector of the Indian economy after reform. Jena(2009) emphasized in the Vishesh Krishi and Gramin Udyog Yojana (VKGUY) including other incentives and concessions, the export obligation period for cottage and tiny industrial sector in  SEZ Schemes the export oriented Small Scale Industries and the clusters approach for development of small and medium scale industries and potentiality of export. Shivani Mishra(2012) threw light on the role of MSME to uplift the social disadvantage group and highlighted the MSME status in the era of globalization and also mentioned review for the same. Lastly she suggested that apart from governmental role it is also responsibility of MSME sector to be empowered about awareness, access and usage of government policy and programme. This proactive approach helps MSME sector to sustain in liberalization era.

V. Econometric observations on small scale industries in India.

Production of SSI in India during 1980-81-2014-15 has been increasing at the rate of 10.12% per year significantly.

Log(x₁)=6.066699+0.10126t 

             (35.307)*  (12.16)*

R²=0.817  ,F=147.94* ,DW=0.2298 ,where x₁=output of SSI sector , *=significant at 5% level.

Even the SSI production has been increasing exponentially at the rate of 0.554% per annum during 1980-81-2014-15 which is significant at 5% level. 

The estimated AR(2) process in the model of ARMA Maximum Likelihood  method of the SSI production during 1980-81-2014-15 is highly good fit and stable but its AR(1) is significant and AR(2) process in insignificant and thus the model is divergent.

X_1t=8.107859+1.168611x_1t-1-0.187227x_1t-2+0.06178σ²_t

          (5.55)*       (3.66)*       (-0.608)             (7.27)*

R²=0.95  , F=203.61*  , DW=2.01 , Inverted AR root=0.98 and 0.19 respectively.

Similarly the ARIMA(1,1,1) model of SSI production is estimated as stable, stationary and divergent because its AR(1) is significant and convergent but its MA(1) is insignificant and divergent and its root is imaginary .The estimated equation is a good fit and is given below.

X_1t=8.119189+0.9800x_1t-1+ε_t+0.1557ε_t-1+0.0621σ²_t

          (5.50)*      (7.30)*             (0.396)     (7.26)*

R²=0.95,F=202.26* , root of AR=0.98 , root of MA=-0.16

Average productivity of SSI in India during 1980-81-2014-15 has been increasing at the rate of 1.68% per year significantly

Log(x₃)=4.3707+0.016822t

                 (33.40)* (2.65)*

R²=0.1758 ,F=7.04 ,DW=0.289,*=significant

VIII. Conclusions

The paper concludes that output of SSI sector has been increasing at the rate of 10.12% per year and exponentially at the rate of 0.554% per year during 1980-81-2014-15.The series is stationary, stable and divergent as indicated by ARIMA and AR models. Average productivity, employment and export of SSI sector have been rising at the rates of 1.68%, 8.43%,and 13.34% per year respectively during the same period. One per cent increase in export led to 0.48% of GDP per year during the specified period. Production, employment, average productivity and export of SSI showed two cointegrating vectors whose vector error correction is stable,divergent and insignificant error correction process. India’s GDP, SSI sector’s output, employment, average productivity and export have two cointegrating vectors but its error correction model is stable, divergent and insignificant error correction having problem of autocorrelations. New policy recommendations of RBI and new government policy on MSME are likely to accelerate the performance of SSI and its contribution to the national economy.

References

Bala, N. (20007). Economic Reforms and Growth of Small Scale Industries, New Delhi, Deep & Deep Publications.

Bansal, S. K. (1992). Financial Problems of Small Scale Industries, New Delhi ,Anmol Publications.

Basem, M. Lozi.(2008). Small-Scale Industries in the Globalization Era: The case of Jordan, Journal of Business and Public Affairs. www.scientificjournals. org/journals2008 /articles1348.pdf

Bayiuei,Srinivasulu.(2004).The role and performance of small scale industries in Indian Economy, The IUP Journal of Managerial Economics.

Bhavani, T.A. (2002,July). Small-Scale Units in the Era of Globalisation: Problems and Prospects, Economic and Political Weekly, Special Article.

Chowdhury,Mamata.,&Saini,Anjali.(2015,Jan-June). Globalisation and Its Impact on the Performance of Small Scale Industries in India, International Journal of Trade and Commerce,4(1),160-171.

Datt, R., & Sundaram, K. P. M. (1999). Indian Economy, (39th Edn.). New Delhi ,S. Chand & Company.

Desai,Vasanta.(2007). Management of Small Scale Industry, Mumbai,Himalaya Publishing House, 564-565

Garg,C.C.(1996,October).Growth of Small Scale Industries in India-some policy issues, Working Paper-10,NIPFP

Government of India. (2010).Report on Prime Minister Task Force on Micro, Small and Medium Enterprise. Ministry of Micro, Small and Medium Enterprise, New Delhi.

Government of India.(2012-17). Report on Working Group on Micro, Small and Medium Enterprise Growth for 12th Five year Plan.

Grant ,Thornton. (2010,April). Vision 2020: Implication for MSME (Online)

Hussain, Syed Vazith.(2004,Jan).Performance of small scale industries in India and the challenges ahead, Indian Journal of Industrial Relation,39(3),391-401.

Jain,Neelam.(2004,March).Small Scale Industries in the new Millennium, SEDME, 30(1).

Jena,R.K.(2009,May).Small Scale Industries in the Path of growth and promoting exports. DGCIS.

Kumar,Nallabal Kalyan.,& Sardar, Gugloth. (2011,Jan-June). Competitive Performance of Micro, Small and Medium Enterprise in India.  Asia Pacific Journal of Social Science,8 (1).

Loksava Secretariat.(2014).Growth and performance of Medium and Small Scale Industries. New Delhi

Malapati,Venkataramanaiah.(2011,June).The Performance of Small Scale Industries in India:An Overview,ssrn.com

Mishra,Shivani.(2012,July).Small Scale Industries:Striving and Friving in the era of globalization,  International Journal of Enterprise Computing and Business Systems,2(2).