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Peruvian Fishmeal Industry Resilience and
Adaptions to El Niño Southern Oscillation (ENSO) Events

1.     
Introduction

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Amidst a change in food demand patterns in emerging
economies such as China and India leading to an increase in the consumption of fish
(Gandhi and Zhou 2014) hand in hand with growing
concerns on feeding World population and climate change, not only supply and
distribution of food becomes more important, but also the availability of the
inputs involved in aquaculture. Under this idea, one of the main inputs in the
diets involved in the production of farmed fish is fishmeal. Its relevance
rotates on the fact that fishmeal increases feed intake because of its
attributes of high palatability and high amounts of amino acids helping in the
rapid adjustment of fish production (Jackson 2006). In 2013, world fishmeal
production reached the 4,940,000 metric tons (MT) being Peru the major producer
and exporter with 1,115,000 MT produced and 849,000 MT exported only followed
by China with 560,000 MT produced and by Chile with 236,000 MT exported (SEAFISH 2016). Only behind gold, copper,
and oil, Peruvian fishmeal represents their fourth largest export generating more
than 13,000 jobs in the processing stage and foreign currency income (Nolte 2017; Christensen et al.
2014).
Since November 2014 to April 2016, the Peruvian fishmeal industry was affected
by an El Niño Southern Oscillation (ENSO) event dropping its production by 24%
and its exports by 17% (SEAFISH 2016). From 2009, the Peruvian
government has established measures like Individual Vessel Quotas (IVQs) and
fishing seasons depending on the availability of biomass in order to reduce the
impacts of ENSO on its fisheries and a subsequent overfishing (Tveteras,
Paredes, and Peña-Torres 2011). Despite the government
efforts, some companies have to leave the market when an ENSO event is present,
and as a consequence, people lose their jobs.

With concentration indicators such as the Four-Firm
Concentration Ratio (CR4) and the Herfindhal-Hirschman Index (HHI) demonstrating
that the Peruvian fishmeal exports are becoming more concentrated over time,
producers and other stakeholders are forced to analyze the shocks that make
some firms leave the industry in order to preserve its disintegration. Furthermore,
patterns show that during the adversities brought by El Niño Southern
Oscillation (ENSO) events, the industry becomes more concentrated, occurring the
opposite when ENSO is not present. Due to a reduction in the anchovy landings
caused by ENSO, some firms are not able to survive hence making the market more
concentrated, and leaving some market share available for those who were
resilient enough to survive the shock. Moreover, ENSO has affected Peruvian
fisheries for 9 different times since 1980 thus changing the market
concentration significantly during those periods. This important weather event
leads us to investigate the resilience of some firms to the shocks that ENSO
brings, and the factors that make them more resilient.

Resilience is a term that is being applied in different
industries to refer to the ability of firms and the industry as a whole to
recover from events that cause some disturbances to the system as well as the
risk management strategies applied in order to avoid or reduce losses (Rose 2007; Rose and Liao 2005). In fact, it is well known
that industries and firms in them suffer from inevitable shocks that alter
their performance, and those who have adapted through different measures are
considered to be resilient establishments surviving to the shock or taken less
time to recover (Jüttner
and Maklan 2011; Lindbloom, Shanoyan, and Griffin 2017). The shocks that ENSO causes
are not new to the fishmeal industry and to this day they continue to change to
counteract them. These adaptations include opening more processing facilities,
increasing fishing fleet size, and obtaining biological assets. Existing
studies have focused on the effects of ENSO on fishmeal prices and other
commodities as well as the changes in price ratios between fishmeal and
substitutes such as soybean meal (Ubilava 2014, 2017) without. Although the
resilience framework has been widely used in different scopes such as
automotive industry, urban infrastructure, and farm resilience (Barroso
et al. 2015; Carvalho et al. 2011; Güller et al. 2015; Pant, Barker, and Zobel
2014; Sheffi 2005; Tierney and Bruneau 2007; Zobel 2010; Lindbloom, Shanoyan,
and Griffin 2017),
literature on the resilience framework in fisheries is still underdeveloped. The
purpose of this paper is to fill the gap in the literature by identifying risk
management strategies of Peruvian fishmeal exporters that makes them more
resilient to ENSO.

2.     
Methods and Data

Being used in different industries, the conceptual
framework is the resilience triangle where shocks are plotted in a coordinate
plane (Sheffi 2005;
Tierney and Bruneau 2007; Barroso et al. 2015; Lindbloom, Shanoyan, and Griffin
2017).
The vertical axis represents the performance measure to be used and the horizontal
axis is the time during the shocks. Under this premise, Lindbloom et. al.
(2017) indicated it consists of three point: (A) The level of performance
before being affected by a shock, (B) the level of performance after being
affect by a shock, and (C) level of performance after recovering from the
shock.

In order to calculate resilience of fishmeal exporting
industry, two ENSO events were chosen: i) July 09 – April 2010, and ii)
November 2014 – April 2016. Two datasets were used to make the analysis. The
first data set was obtained from ADUANET which is the Peruvian Customs Agency, Superintendencia
Nacional de Aduanas y de Administración Tributaria (SUNAT), official database
that reports up to date monthly exports of fishmeal from 165 firms. In
addition, data from the National Economic Survey was gathered from the Peruvian
Statistics Institute, Instituto Nacional de Estadística e Informática (INEI),
on fleet size, financial declarations, days worked during the year, and
locations from 194 firms. A resilience index was calculated on the industry and
from firms i, during period t, in a similar way as Barroso 2015 and
Lindbloom 2017:

Where  is the resilience index value for Exporter
,  is the volume exports at time  of Exporter ,  is the time period before the shock,
and  is the time when recovered from shock.

After obtaining each individual’s
resilience, an econometric model is defined to examine the effect that
different factors have on fishmeal exporter’s resilience.

3.     
Expected Results and Implications

The resilience triangle together with the compilation of
data will make not only a great contribution to risk management strategies in fisheries,
but also help in the developing of more sustainable policies for marine assets.
Preliminary descriptive statistics show a significant reduction in fishmeal
exports per firm during both shocks. In addition, only the firms with more locations
around the country were able to stay in business during the two periods.
Finally, this paper will contribute on giving the resilience triangle a new
approach and make smaller fisheries learn from other resilient measures taken
by larger firms in order to survive to the effects of ENSO and maintain
competitiveness. In light of recent changes in food demand patterns and the
growing concerns for climate change, this paper has the potential to generate
interesting discussion among the WAEA audience.
References

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