the poverty impacts of animal diseases in developing countries: new roles, new demands for economics...

The poverty impacts of animal diseases in developing countries: new roles, new demands

for economics and epidemiologyKarl M. Rich, American University in Cairo and International Livestock Research Institute

Brian D. Perry, University of Oxford, University of Pretoria, & University of Edinburgh

Plenary presentation for the XII International Symposium on Veterinary Epidemiology & EconomicsDurban, South Africa, 14 August 2009

Outline

• Motivation– Where are we in our knowledge base?– What’s missing?

• Overview of impacts of animal diseases– Economic impacts– Poverty and livelihood impacts– Frameworks for economic and poverty impact assessment :

operationalizing the value chain for public policy

• The bottom line: Incentives, incentives, incentives … but how?

• The future: where do we need to go to better inform policy?

Motivation

• Animal diseases are taking increased prominence and awareness on the global stage– Rise in globalization: more trade, more potential for the

introduction of pathogens (particularly from LDCs)

– Rise in high-value commodity agriculture, including meat (“livestock revolution”): With increased incomes comes greater demand for meat and food safety; with increased demand arises new opportunities for alternative suppliers, including the poor

– Rise in perceptions and fear: emergence of new diseases or virulent strains of old diseases with potentially dangerous impacts on human health (think avian flu)

– Rise in constraints to trade, particularly those related to non-tariff and SPS barriers

Motivation

• On the supply side, the sophistication of economic impact analysis has greatly improved, particularly those sensitive to pro-poor effects– Reviews: Rushton et al (1999); Rich et al. (2005);

Rushton et al. (2009)– Evaluation of impacts: McLeod and Leslie (2001);

Otte et al. (2004)– Poverty impacts: Perry et al. (1999; 2002; 2003);

Randolph et al. (2002); Perry and Rich (2007); ongoing IFPRI-ILRI-FAO work on HPAI

• Greater appreciation and integration of economics in epidemiological research as well.

Motivation

• So is everything on track, then? Not necessarily …

• Despite improved knowledge and all our fancy tools, we have yet to translate such research into action, particularly in the development of appropriate pro-poor policies.

• Why?

Motivation

• One issue concerns the way disease control programs are designed.

• Most veterinary programs in the developing world are modeled on those from the developed world, including strategies for control (“control at any costs”).

• But the effectiveness of such programs in the developed world is largely based on the effectiveness of veterinary services, surveillance, and (“in general”) credibility government has in providing compensation, for example.– Big differences: developing vs. developed regions– Homogeneity in control, heterogeneity in context: does one-size-

fits-all make sense?

Motivation

• But there is a more subtle issue too.

• Our focus in the economic (and epidemiological) impacts of animal diseases has traditionally been a top-down, normative approach– What should decision-makers do (and data,

resources, etc. to support)?

Motivation

• However, this might not be appropriate in the developing world, where actors are diverse, governments and institutions have limited capacity, and sufficient regulations and compliance are lacking (not to mention little to no data too!).

• In short, context matters – we need better information on why actors behave how they do, what their incentives are, and how they interact.

Motivation

• This implies a new paradigm shift: from the top-down to the bottom-up, including frameworks and tools to accommodate this.

Impacts of animal diseases

• What are the potential economic impacts of an animal disease?

• While many of these are disease-specific, there are some commonalities

• Example: FMD (based on Perry and Randolph, 2003)

FMDOvert disease Disease risk

Livestock production- production losses (mortality, weight, milk loss, lameness)

- Treatment, containment costs- other profit losses (idled capacity, timing of sales, price effects)

Other income activities- crop production (manure, draught)- fuel, transport

Natural resources- land use- settlement & migration- ecosystem sustainability

Risk management- preventive control (surveillance,

fencing, zonation, movement controls)

- maintain DVS capacity

Nationaland

Sectoral

Farm householdreal income levels

Household welfare

Farm-level

Household realincome levels

-wage earnings-meat expenditures

Risk management- own control measures

(vaccination)- compulsory control measures

(movement controls)- traceability

Macro-economy- Other sectors (inputs,

trannsport), multiplier effects- foreign exchange- growth- consumer meat prices

Livestock trade- production losses- profit losses (idled capacity, timing of sales)

Market AccessTo export markets

To local markets

Livelihoods-loss of insurance, financial,social networking functions

-increased vulnerability

Containment -slaughter & compensation- movement controls

Animal welfare

Tourism

Environmental concerns


• Given the diversity of market and non-market impacts from animal diseases, it is helpful to tease out the various dimensions and contexts associated with them:– Disease characteristics– Production characteristics – Market characteristics – Livelihoods characteristics – Control characteristics

Impacts of animal diseases• Disease characteristics: refers to biological

or epidemiological aspects of the disease itself that modulate its general impacts– E.g., mode of spread, frequency, severity,

zoonotic impacts

• Production characteristics: are there aspects about livestock production that influence disease impacts?– Types of systems, cycles, seasonality, multi-

functionality/uses of livestock


• Market characteristics: the contribution of market dynamics to animal health impacts– Commercialization, market interaction, scope/complexity of

value chains, economic linkages

• Livelihoods characteristics: where do livestock fit in different stakeholders’ livelihoods?– Market/non-market/cultural roles

• Control characteristics: how do the logistics and characteristics of control shape impact?– Effectiveness, resources, maintenance, regulation costs,

externalities


• Putting it all together, an important and repeated characteristic that influences the impact of animal diseases is the role of interactions– Between and within different systems– Between and within different actors– Between and within different institutions

• In developing settings, these interactions will be particularly important in understanding poverty impacts and in designing policies sensitive to those impacts.

Role of value chains as a framework

• If we are to better understand how these interactions modulate impact, particularly with an eye towards the development of pro-poor policies, we first need a framework to guide us.

• The oft-heard concept of the value chain is one way to address this… but what exactly is a value chain? And how can it help us?

Is THIS a value chain?

Producers Traders Retailers Consumers

Or is THIS a value chain?

Or THIS?

Inbound logistics

Operations Outbound logistics

Marketing & sales

Service

Margin

Margin

Firm infrastructure

Human resource management

Technology development

Procurement

Or THIS?

Or maybe even THIS?

What is a value chain?• A value chain is “the full range of activities which are required

to bring a product or service from conception, through the intermediary phases of production, delivery to final consumers, and final disposal after use.” (Kaplinsky 2000:121)

• It was adapted by Gereffi (and others) in the 1990s in the context of power (governance) relationships in globalized markets.

• These ideas were formalized and tested at the Institute for Development Studies (IDS) at the University of Sussex in the late-1990s

• The point was to go beyond traditional supply chain analyses rooted in logistics, although modern techniques are closely linked to value chains.

Why value chains for animal disease analysis?

• Animal disease outbreaks take place in a systems context, with the risk and spread of disease contingent on measures taken throughout the chain.

• “Weak links” in the chain may accentuate disease risk, but analysis is needed to understand who these stakeholders are, how they interact with others, and why they behave as they do.

• Utilization in livestock systems and animal health applications increasing (see Kobayashi 2006 and unpublished FAO work in context of HPAI), though a lot of analysis is quite ad hoc

Components of value chain analysis

Step 1: Mapping the value chain (can be done at different levels/systems)

• Idea: – Assess the characteristics of actors and their linkages– Understand role of chain activities in terms of broader

livelihoods context (profit/income)– Identify service providers and roles of public sector– Characterize business environment of the chain– Compute flows of goods throughout the chain,

including prices and seasonal variation.


Mapping the chain (cont’d)

• Main outputs: – Graphical maps of actor linkages and product flows (between

actors and across space)– Quantification of role of livestock in livelihoods– Identification of production practices and costs– Typologies of chain actors based on income– Identification of different chains based on relationships, etc.– Transactions costs and chain constraints

• Note that mapping has an important purpose of showing possible pathways of transmission as well (linkage with risk analysis)

Garissa livestock marketing value chain

Local Somali producersSomalia

Garissa Market

TradersTraders, brokers,

trekkers (60% of cattle)

Butcheries GSA

Traders

NRB. & MSA (66% cattle;63% shoats

Meat W/sellers

Meat Retailers

Consumers

Brokers

S/house, Transporters

KMC

Ranches

Traders, brokers, sellers of fodder etc.

Butcheries

Supermarkets

Abroad

Shipping agencies

CARE LIME Project

Consumers GSA

Hotels

Transporters, trekers

From Wanyoike and Rich (2007)

From Kobayashi (2006)


• Step 2: Governance in the value chain

• Idea: identify the nature of relationships and coordination mechanisms that exist between actors in the value-chain. Also provide details on aspects of the business environment of the chain

• Main outputs: – Who decides what is produced– How the rules of trade are determined– The nature of relationships between the participants– Roles of associations– Coordination mechanisms (contracts, market sales, etc)– The extent of chain “power,” based on the relative size of a

particular actor, share of chain profits, or control over a key technology: could influence practices in other parts of the chain


• Types of coordination– Arms length (spot markets)– Full vertical coordination (total integration of

supply chain)– Intermediate forms (contracts, etc. – in

between arms length and full coordination)

From Kobayashi (2006)


• Step 3: Identify opportunities for upgrading in the value chain

• The usual way we think about upgrading in value chain analysis are ways to add value for specific actors in the chain

• However, a more general way of approaching upgrading is understanding how the chain reacts to changes

• Main outputs:– How has the chain changed over time, in terms of linkages,

products sold, relationships, etc. – How has the chain responded to different events, especially

animal disease outbreaks (e.g., HPAI)?– What are the drivers for change? What are the incentives?


• Step 4: Distributional issues

• Value chain analysis can be used to identify who gains and who loses in value chains. A component of this is calculating how value-added is distributed among chain participants

Contributions of value chain analysis

• In the context of an animal disease, value chains can improve our understanding of the impact of disease on diverse chain actors, including the poor.

• A further contribution of value chain analysis is its ability to understand the various constraints faced by different actors and the context (socio-economic and institutional) behind those constraints.

• Finally, value chain analysis can also help to inform critical control points in the chain that accentuate risk: – Interface with risk analysis to understand the socio-economic

context behind risk pathways and disease transmission

Value chain actor Potential constraints faced in animal disease control

Supply-side incentive mechanisms

Demand-side incentive mechanisms

Producers Limited incomes and asset basesLimited market accessLimited access to government servicesLimited importance of livestock to livelihoods

Investment in government servicesInvestments in infrastructure and technology

Improved regulatory environments (domestic and international)Opening of marketsFines for non-compliance

Government officials Limited resources (human and budgetary)Limited knowledge of policy options

Improved coordination of government functionsImproved capacity in policy analysis

Improved commercialization of livestock sector

Small-scale traders Limited operating capitalLimited alternative activities

Investments in infrastructure and technology

Improved financial marketsImproved regulatory environmentsFines for non-compliance

Slaughterhouses and processors

Limited operating capitalLow technology

Investments in infrastructure and technology

Improved regulatory environments (domestic and international)Opening of marketsFines for non-compliance

From Taylor et al. (2008)

Value chain analysis: limitations

• Despite the strengths of value chain analysis, several weaknesses remain:– Lack of quantitative rigor (mostly descriptive, often

“storytelling”)– Chains are complex: which products, regions,

stakeholders? How can we appropriately focus the analysis?

– Strong on the “what” (context), but limited insights on the “how,” particularly in terms of aligning incentives where interactions exist

• Where do we go from here?

Incentives, incentives, incentives• The information economics literature provides one

venue for understanding how incentives can be better aligned.

• A workhorse of this literature is the principal-agent model.– General idea: Models the process of aligning incentives

between a principal (think a manager or the government) and an agent (think a farmer) when asymmetric information exists between the two parties

Incentives, incentives, incentives

• Limited direct applications of the principal-agent model in animal health economics– Exception: Gramig et al. (2009) highlights need for

multiple mechanisms to handle different information asymmetries between producers and government

• Most related literature looks instead at producer- or government-level behavior subject to various constraints related to production, disease evolution, etc.– Examples: Bicknell et al. (1999), Stott et al. (2003;

2005), Horan and Wolf (2005), Hennessey (2007), Horan and Fenchel (2007).

Limitations of the information economics literature

• Information economics nonetheless falls somewhat short if we take the full value chain into account:– Limited scope for handling complex

interactions– Strong assumptions concerning behavior to

“make the math work” (see Rich 2007)• Prices• Rationality/behavior• Interface of actors with evolution of disease

Next steps

• Where do we go from here?

• Rich (2007) highlighted the need for stronger direct integration between the epidemiology of disease and its economic impact.

• This integration is important because feedbacks matter: as a disease evolves, it changes producer incentives in terms of control, production and marketing decisions, etc.

• Likewise, these may influence how the disease itself will evolve and on the choice of mitigation strategy to control it, particularly those that are sensitive to pro-poor considerations.

Next steps

• What this necessitates is improved (possibly different) models, ones that take into account bottom-up approaches and address the interactions, constraints, and behavior of multiple actors

• Possible role for simulation/agent models here to characterize the interaction of multiple agents and the evolution of disease.

Breeding

Hatching

Eggs

Growing

Chicks

Maturing

GrowersSlaughtering

Birds for sale

Disease

incidence Disease

incidence

Chick losses

Grower losses

Mature losses

Obtaining breeding stock

Breeding stock losses

Breeding stock

Culling breeding stock

Disease

incidence

Disease

incidence

Eggs laid

Inventory

Packing

Sales

Desired inventory

Customer ordersInventory coverage

Desired inventory

coverage

Expected PriceChange in

expected price

Expected price

change delayExpected Price

Duration of

demand shiftEffect on price

Effect on price

Indicated demandBreeding intercept

Stock productive life

Conversion rate

Coverage elasticity

Price

Price elasticity

of demand

Breeding price

elasticity

Desired stock

Stock delay

Demand intercept

Desired stock

Gestation time

Proportion laying

hens

Growing timeMaturing time

Disease

incidence

Infected

deaths

Time prior to slaughter

Conversion rate

Total market

population

Other demand

shifters

Hatching rate

Eggs for

breeding

Infected

Next steps

• With new models comes the need for improved data.

• Perry et al. (2001) stressed the need for improved information resources and data quality to support animal health decision making.

• To this, we add the need for data that supports value chain and systems approaches to livestock policy and development.

Next steps

• Examples of data resources:– Participatory epidemiology techniques (Jost et al.

2007)• Obtain data in a local context to better understand behavior

and improve disease spread information• Contextualize community drivers behind disease, its control,

and response

– LSMS-ISA surveys of the World Bank• Focus on living standards at HH level, interface of

government policies on behavior, plus ex ante/ex post impact assessments.

• But more needs to be done …

Next steps

• A crucial step will be a change in mindset towards analysis from the bottom-up.

• Models still matter, but the level of analysis and the context in which that analysis takes places matters much more (and our models need to recognize this!).

• This will require “out-of-the-box” thinking from economists and epidemiologists alike to drive new methodological innovations.– Re-orientation of focus of epi-econ training?– Re-orientation of epi-econ research?