Loading...

Export Performance of Marine Products from India

by Swaminathan Balasubramaniam (Author) V. D. Tarpara (Author) M. G. Dhandhalya (Author)

Academic Paper 2017 31 Pages

Economics - Foreign Trade Theory, Trade Policy

Excerpt

Inhalt

Introduction

Review of Literature

Methodology and data sources

Analytical tools
Compound growth rate
Instability Analysis
Markov Chain Approach
Goodness of fit test

Prediction of exports from India

Results and Discussion

Possible factors for growth erosion
Market-wise instability
Commodity-wise growth
Commodity-wise instability

Trade composition
Destination of trade
Direction of trade

Export market projections

Conclusion

Recommendation for policy makers

References

Introduction

Marine products industry alone has a share of at least 6 per cent in world exports in which India is the fourth largest exporting country after China, Peru and Japan (Das et al., 2016). In fact, out of 7.85 million tonnes (mt) of overall fish production of India, roughly 43 per cent (3.32 mt) is contributed by the marine sector though it turns out to be less than half to that of India’s major competitors in fish trade (MPEDA, 2017). Marine products exports play a pivotal role in Indian economy in terms of employment and income generation besides valuable foreign exchange earnings. They have created a huge demand in international trade and are acclaimed to be one of the fastest moving commodities in the world food market (Manjunath et al., 2017). China, Thailand, Vietnam, Chile, Taiwan, Indonesia, India, Peru and South Korea are the main sea-food exporters comprising more than 60 per cent of trade value of marine products. In general, 38 per cent (live weight equivalent) of total fisheries product is traded internationally. But with only 20 per cent of its total fish production entering world trade, Indian seafood exports are far below than the global average (Parvathy and Rajasenan, 2012). Fortunately, India’s vast coastline of 8,129 km stretching almost two-thirds of the country and encompassing an exclusive economic zone (EEZ) of more than 2.2 million sq. km. offers sufficient surplus of fish and fishery products, which is currently under-exploited (Ancy and Raju, 2016). As of 2015-16, marine products with export earnings crossing Rs. 30,420 crores constituted 21 per cent of the total agricultural exports from India which in turn was 1.2 per cent of its gross domestic product (GDP) and 4.72 per cent of its Agri-GDP (Anon., 2017).

Undoubtedly marine sector is identified as a sunrise sector under the Special Focus Initiative of the Foreign Trade Policy of the Government of India. The global trade environment has undergone a drastic change after the implementation of World Trade Organization- General Agreement on Trade in Services (WTO-GATS). Nullified quantitative restrictions under post-WTO regime offer a kind of level playing field for all the trading nations. Moreover, the marine products are considered to be of industrial origin under WTO and are being addressed within the non-agricultural market access (NAMA) negotiations. Thereby, compliance to Sanitary and Phyto-sanitary (SPS) standards of developed countries can even result in huge trade dividends. This indicates potential for Indian marine products exports through up-scaling technologies and multilateral negotiations. In this context, this study has attempted to analyze growth, instability, destination pattern and trade direction of Indian marine products exports before and after WTO regime with the following specific objectives: (i) To ascertain growth pattern in the exports of fresh and dried marine products from India; (ii) To measure variability in marine products exports and to compute the index of instability; (iii) To analyze the direction of trade and structural changes in marine products exports; and (iv) To predict the future marine products exports from India with its major trading countries.

Review of Literature

The approach to address the above mentioned specific questions was formulated after reviewing various past studies available in the field. Rajeev (2009) noted that the fishing policy declared on account of liberalization policy of 1991 is a game-changer for Indian marine sector as it legalized deep sea fishing and joint ventures for large scale industrial houses and multilateral companies. Subsequently, modernization and technological advancement of seafood industry have paved the way for higher exports in India (Sathiadas et al., 2012). A visible shift of exports from low value dried items in 1970s to canned items in 1990s and later towards high value frozen items in 2000s has spiked growth in export earnings (Bhattacharya, 2004). At the same time, decline in price competitiveness of shrimp, India’s major exportable marine item, was also noticed due to shortage of raw material for processing and rising trend of domestic production cost (Kamat and Kamat, 2007). The Indian export scenario of marine products have been dominated by several challenges such as declining shrimp catches (Krishnan and Ayyapan, 2005); overcapitalization of production and marketing activities (Mathew, 2003; Saradan et al., 2006); price instability (Raguram and Asopa, 2008) and decreasing profitability (Nicholas et al., 2015). Post-WTO, the per unit price realization of Indian marine products exports have either become insufficient or stagnant due to the emergence of new suppliers on account of increasing international competition (Jeyanthi and Gopal, 2012). On the other hand, maximum sustainable yield (MSY) levels have been almost achieved in the inshore waters and there is still inadequate exploitation of deep sea fishing resources (Parvathy and Rajasenan, 2012). At the same time, India’s compliance with the WTO guidelines on sanitary and phyto-sanitary measures and food quality specifications (such as HACCP of European Union) in marine products is also very limited (Kumar, 2004 and Henson et al., 2004). Moreover, India’s position in the WTO negotiations on fisheries trade and other related issues were mostly at the receiving end and often found to be unconvincing (Ancy and Raju, 2016).

Methodology and data sources

The study was based on time series secondary data on exports of marine products from India obtained from various government published sources and website portal of Marine Products Export Development Authority, Kochi during the last 30 years starting from 1986 to 2015 (MPEDA, 2017). Further to account the impact of WTO in the Indian marine trade prospects, the study period was classified in to pre-WTO period (1986-1994), transition-WTO period (1995-2004) and post-WTO period (2005-2015).

Pre-WTO phase: This was considered from1986-87 to 1994-95 and it included the period before the implementation of WTO. This was the period of the start of deep sea exploitation (Mathew, 2003), motorization of fishery production activities and ban on monsoon trawling (Raguram and Asopa, 2008). Though WTO was not formally promulgated, this period witnessed the dawn of New Economic Policy (1991) in India, on account of which, there were noticeable changes in marine export products composition and market destination.

Transition-WTO phase: It was considered from 1995-96 to 2004-05 and it was assumed critical for the study as impact of WTO, if any, would certainly require a lag of some period (say 10 years) before it can actually be captured. As this period is marked with the implementation of WTO, quality revolution in the marine products exports was kicked-off and the Indian exporters were bound to comply with HACCP (Hazard Analysis and Critical Control Points) checks of the European Union and other stringent international quality assurance standards. This period also witnessed export ban of Indian marine products in almost all high-end importing countries such as European Union, USA and Japan on the grounds of lack of quality and food safety. Since the quantitative restrictions of importing countries were not permitted under WTO principles, the developed nations started to restrict Indian imports using qualitative restrictions which often were found to be biased and unreasonable.

Post-WTO phase: This was considered from 2005-06 to 2015-16 and it witnessed the issue antidumping duty by USA and European Union on Indian shrimp exports. This was also marked with global recession which casted a serious impact on seafood export processing industry (Ancy and Raju, 2016). The temporal changes in marine products exports were analyzed both in terms of commodity composition and market destination. The major Indian export markets selected included Japan, USA, South-East Asia, European Union, China and Middle East as they constituted more than 70 per cent share its exports in all the three periods of the study.

Analytical tools

Compound growth rate

Different functional forms including linear growth model (Y = a+bt), exponential function (Y = abt) and quadratic function (Y = a+bt+ct2) were attempted in the study to analyze the growth rate of marine products. However, exponential function of the specification Yt = abt was found suitable since the adjusted R-squared value were found to be higher and significance levels of the estimates were also robust. Accordingly, market-wise and commodity-wise growth of Indian marine products exports in terms of quantity, value and unit value were estimated using compound growth rate (CGR) by fitting exponential trend distribution as given in equation (1).

Abbildung in dieser Leseprobe nicht enthalten

Where,

Abbildung in dieser Leseprobe nicht enthalten

Subsequently, logarithmic transformation was provided for the estimation of equation (1),

Abbildung in dieser Leseprobe nicht enthalten

The above equation (2) was analyzed using ordinary least square technique (OLS). Compound growth rate (g) was then estimated following the specification given in equation (3)

Abbildung in dieser Leseprobe nicht enthalten

Instability Analysis

The coefficient of variation (CV) is generally used to measure variability in any variable on account of its ease of use and interpretation, and it can be obtained by,

Abbildung in dieser Leseprobe nicht enthalten

However, CV is most suitable when data has no trend as it does not account for the time trend. In the case of time series data (e.g. marine products exports used in the study), there is always some trend; therefore, one has to be very careful to use CV as measure of instability. Thereby, in this study instability is estimated by the Cuddy-Della Valle (CDV) index (Jeyanthi and Gopal, 2012). In this way, for estimating CDV the Coefficient of Variation was multiplied by the square root of the difference between the unity and coefficient of determination (r2). If the estimates turn to be insignificant then CV itself is to used to measure instability instead of CDV.

Abbildung in dieser Leseprobe nicht enthalten

Where,

r2 = Coefficient of determination adjusted for number of degree of freedom obtained from trend regression in equation (2).

It is to be noted that while calculating growth rate and instability index for value of items against quantity exported, the money value was deflated to the year 2012 using consumer price index (CPI), so as to neutralize the effect of inflation (Das et al., 2016).

Markov Chain Approach

The structural change and direction of trade in the export of commodities can be analyzed using Markov Chain analysis (Mahadevaiah et al., 2005; Kusuma and Basavaraja, 2014 and Manjunath et al., 2017). It is usually employed to analyze the structural change in any system, whose progress through time can be measured in terms of single outcome variable (Dent, 1967). In the present study, the dynamic nature of trade patterns, that is the gains and losses in export of Indian marine products to major importing countries was examined using the Markov chain model. The approach involves developing a transitional probability matrix ‘P’, whose elements, Pij indicate the probability of exports switching from country ‘i’ to country ‘j’ over time period. The diagonal element Pij, where, i=j, measures the probability of a country retaining its market share or in other words, the loyalty of an importing country to a particular country’s exports. The probability matrix was estimated for all the three different periods considered.

In the context of current application, structural change was treated as a random process with seven major importing countries of Indian marine products and the assumption was that the average export of marine products from India, amongst the importing countries in any period depends only on the export in the previous period and this dependence is same among all the periods. This can be algebraically expressed as,

Abbildung in dieser Leseprobe nicht enthalten

Where,

Abbildung in dieser Leseprobe nicht enthalten

The transitional probabilities Pij, which can be arranged in a (c x n) matrix, have the following properties.

Abbildung in dieser Leseprobe nicht enthalten and 0 £ Pij £ 1 (7) Thus, the expected export share of each country during period‘t’ is obtained by multiplying the exports to these countries in the previous period (t-1) with the transitional probability matrix. Transitional probability matrix (T) which is the crux of Markov chain analysis was estimated in this study using linear programming (LP) framework adopted in the method called as minimization of Mean Absolute Deviation (MAD).

The MAD method used in the analysis is given as follows:

Abbildung in dieser Leseprobe nicht enthalten

Goodness of fit test

As discussed above, transitional probability matrices can be obtained by using Markov chain approach. Such matrices can be used to predict the exports over a time-period. Now, the predicted exports can be compared with the actual exports (MPEDA, 2017) to test whether the observed shares of exports to different countries and the predicted shares follow similar distributions. For that, the chi square statistics of the following type was used as given below,

Abbildung in dieser Leseprobe nicht enthalten

Where,

Abbildung in dieser Leseprobe nicht enthalten

Prediction of exports from India

Export performances of any country are highly volatile as they are determined by a number of tangible and intangible factors including inter-country relationships and policy conditions. Thereby, past performance is no guarantee for future exports. Ceteris paribus, future exports of Indian marine products was attempted. But, as the future export behaviour is difficult to predict, however efficient the past predictions turn out to be (Equation 9), but for long term forecast it is difficult one. Hence, the forecast of marine exports was carried out for limited period of next four years (i.e. 2016-17 to 2019-20). The formulation used for the prediction of exports is given as follows,

Abbildung in dieser Leseprobe nicht enthalten

Where,

B0 = Quantity exported in Base years;

Bt = Quantity exported in next year (prediction); and

T = Transitional probability matrix.

Results and Discussion

Market-wise growth

During pre-WTO phase the Indian exports were majorly focused on Japan, USA, European Union, South East Asia and the post-WTO period witnessed diversification in the export markets with the inclusion of China and Middle East as the country’s major trading partners (Table 1). The growth rates of exports in terms of volume, value and per unit price were found to be highly positive and significant in the pre-WTO phase (1986-1994) when compared to both transition-WTO (1995-2004) and post-WTO (2005-2015) regimes (Table 1). This may be due to increased competition from the Asian trading giants like China, Malaysia, Philippines, Thailand, Singapore and Indonesia. It can be also noted that except, for double-digit growth in Middle East, USA and South East Asia, the growth in terms of all export parameters in the other markets was either found to be low or negative in the post-WTO regime. In case of USA, both the export volume and value were found to be highly significant in all the three periods. But a slight dent observed during transition-WTO phase in USA imports may be due to its anti-dumping duty on frozen shrimp from India. Negative growth rates of export price observed during transition-WTO and post-WTO (though non-significant) for USA and other countries show India’s decreasing competitiveness, as the country being pushed to be a price taker. This is in line with the findings of Das et al. (2016) who also showed diminishing values of per unit marine products exports of India.

Table 1: Market-wise growth rate analysis of marine products exports from India

Abbildung in dieser Leseprobe nicht enthalten

Note: 1. ***, ** and * indicate significance at 1 %, 5 % and 10 % levels, respectively.

2. Nominal export values (Rs. crores) were deflated using CPI of the base year 2011-12.

[...]

Details

Pages
31
Year
2017
ISBN (eBook)
9783668700413
ISBN (Book)
9783668700420
File size
728 KB
Language
English
Catalog Number
v424798
Grade
Tags
export performance marine products india

Authors

Share

Previous

Title: Export Performance of Marine Products from India