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Colombian Supply Chain Organizati ons

How Publ ic Pol icy Shapes Agr icu l ture

Rafael Isidro Parra-Peña S. and Mark LundyCIAT

Policy Analyst and Senior Researcher

Presentation @ IFPRINovember 2013

Rural ColombiaWhile in urban areas, 30% of the population is considered poor, 7% extremely poor, in rural areas poverty is at 65% and 33% are extremely poor.

• In the last decade rural GDP increased 2.8%

• Land concentration and inequality has increased in rural areas. The Gini index of rural areas of land owners increased from 0.74 to 0.88

• 60% of rural employment is in the informal sector

• 55% of poor peasants have never received any kind of technical assistance or training

• 11% do not have a home, and 16% live in homes in disrepair

• The average income of a peasants in 2009 was 220,000 pesos, while their urban counterparts earned an average of 668,000 pesos

• Illiteracy rate is 18.5% and 60% do not have access to potable water

Since the early 1990's, Colombia has pursued an innovative policy agenda to promote the competitiveness of agricultural supply chains, with a particular focus on programs and initiatives that support rural smallholder farmers

Has the time come to ask“has this policy been effective?”In terms of:

Competitiveness Alleviating rural poverty

OBJECTIVE: to analyze the results of public supply chain policies in Colombia

Timeline

A typical Supply Chain Organization

National Council

Regional Committee

Regional Committee

Regional Committee

Committee or thematic table

National technical secretariat

Competitiveness Agreement

Diagnostic Strategy

Strategic Plan

SWOT Analysis

Operative Plan

Future Vision

Vegetable Committee of Boyacá

Assuming that increased contact between national and local actors will facilitate the adoption of technologies, access to training , technical assistance, access to state programs at the local level, the policy ultimately aims to improve market competitiveness and, in turn, generate higher incomes for the region's vegetable producers.

37 Supply Chain Organizations– Aquaculture– Avocado– Cotton-textiles– Basic goods– Rice– Banana– Cacao– Coffee– Farmed shrimp– Sugar cane– Beef– Pork– Natural rubber

– Citrus– Coconut– Beekeeping– Equine– Fibers– Flowers and foliage– Forestry– Bamboo– Guava– Herbs– Dairy– Mango– Sheep and goat

– Palm– Panela– Potato– Aromatic plants– Plantains – Aloe– Tobacco– Yucca– Passionfruit– Deciduous – Blackberries

I- Macro Analysis- Geographic focus

- Institutional Strength Index (ISI)

- ISI and competitiveness

- Selection of case studies

What frameworks did you use to frame your study?

II-Mezzo Analysis- Supply chain performance in terms of competitiveness, institutional strength, equity and social inclusion

- Key factors such as success, limitations, lessons learned, and challenges that help generate recommendations for improved design

III- Microeconomic Analysis

- The impact of supply chain policy on the livelihood of an average farmer

- The tomato supply chain organization as a case study

A mix of qualitative and quantitative analysis

Statistical analysis of available hard data

• Correlations between policy focalization and performance of social indicators

Qualitative analysis

• Semi-structured interviews - SWOT Analysi.

Household surveys and econometrics

• Determinants of Production (MCO)Associated probability (Probit)Assessing the impact on poverty, income and productivity (PSM)Changes in poverty levels (Probit)

How do you identify and engage different actors in the policy process research?

• Donors / government / Researcher interest must match

• Offer support in the identification of themes that have the biggest potential to impact on policies

Average ISI and Variability by Supply Chain Organization

Empirical Findings/Reflections on Policy Process Research

COMPETITIVE RESULTS

Case Studies

• Cacao in Santander– ISI: 21– 48% of national production

• Plantains in Quindío– ISI: 8.3– 11% of national production

• Vegetables in Boyacá– ISI: does not exist– 24% of national production

Concepts

SANTANDER REGIONAL CACAO COMMITTEE: SWOT

Changes in the poverty level (PPI score)

A unit increase in the index of training given by a producer association to the tomato producers represents an increase of 1.38% in the probability that the household PPI score experiment a positive change, on average ceteris paribus

If the farmer diversifies, an additional crop apart from tomato, increased the probability by 9.24% of having higher PPI score

When the proportion of male in the household increases, it is more likely to escape poverty

Dependent Variable: Positive changes in PPI (Yes=1; No=0)Policy Variable: Membership with a producer associationMethodology: Probit

What worked well about your methods?

• Research is focused on identifying, designing and communicating products as inputs for decision making.

“3PBs” + “WORKSHOP” + “Meetings” + “Blogs”

• Defining a Scope: the work is geographic- and theme-specific

• The best approach is a combinations of methods. Quantitative data may hide farmers realities

• Dialogue with the actors and design of an ad hoc survey.

What still needs improvement?

• Incidence on policy requires research by Demand. Donor interest may be not enough…

Example:

• Improving the ISI index must have public support

Unanswered questions/new research topics?

We don’t have the right to impose our conclusions. Indeed, the Ministry of Agriculture is quite adverse to impact assessments of its policies. We need more data. For example, at the macro level Colombia has serious data gaps. A way to measure competiveness is with indicators/data but there is no…lack of agricultural census..

More case studies. One case study can not speak for the whole

How can we move from research to action on policy processes?

1. We need a theory of change of the research;

2. Identification of key people to influence and how;

3. Systematic interchanges with these groups to identify research demands and potential clients for current and new research outputs.

Example Rural Development Group in Colombia supported by Rimisp

• Caveats : Research is a public good. Not all research is indented to impact policy.

Thank You!

Impact on Poverty, Income and Productivity

Methodology: Propensity Score Matching

Propensity score: the estimated probability to associated given observble characteristics

Impact Method Sample Treatment Control Difference T-stat

Progress out of Poverty Index(PPI)

Kernel

Unpaired 48.82 44.51 4.32 1.66

PTT 48.25 46.42 1.83 0.53

Revenue per cycle

(millions of COP)

Unpaired 46.28 42.46 3.83 0.45

PTT 46.79 48.35 -1.57 -0.14

Productivity (canastillas/

m2)

Unpaired 0.61 0.76 -0.15 -0.78

PTT 0.63 0.73 -0.1 -0.5

Institutional Strength Index (ISI)

• ISI evaluates the implementation of supply chain policy at the regional level

• Defined positively on a scale from 0 to 3, with higher scores indicating better performance of supply chain policy

RELATIONSHIPS BETWEEN PRODUCTION, PERFORMANCE AND SOCIOECONOMIC INDICATORS