pathways less explored – locus of control and technology adoption

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Pathways Less Explored – Locus of Control and Technology Adoption in Ethiopian Agriculture

Alemayehu Seyoum Taffesse (IFPRI),Fanaye Tadesse (IFPRI)

ESSP-EDRI Seminar March 24, 2017

EDRI

Motivation State of Ethiopian Agriculture (no statistics); Pathways less explored – psychological and social

influence that can complement, accelerate; Concepts and Measures

Locus of control Technology adoption A broad schema

Applications to Ethiopia LOC and adoption of modern farm inputs;

Observations – so what?

Outline

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Motivation – State of Agriculture

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Summary – Outcome state low but growing productivity,

Summary – Conditioning states Rising but limited capital stock (physical, human,

infrastructural, natural), Improving but weak institutions (imperfect markets, agencies

of public service delivery, social protection, …, beliefs and norms);

Frequent exposure to shocks (natural, market, policy); Policy Instruments

public investment (research and extension services, education, health, infrastructure);

‘reforms’ – effective policy making process, land reform, public sector reform, incentives (taxes and subsidies, interest rates, regulation);

Question: Are there complementary pathways not yet used? How about beliefs and norms

Motivation – why do poor people do not adopt?

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Underinvestment (non-adoption) by the poor – a source of persistence in low productivity, poverty, and inequality

Focus 1 - ‘external circumstances’ and ‘opportunities’. Low returns to investments; Unexploited opportunities due to lack of information or knowledge; Social constraints;Feder, Just, and Zilberman (1982); and Besley and Coate (1993); WDR (2008); Suri (2011); Sheahan and Barrett (2014)

Opportunities – existent (exploit), new (create) Focus 2 - constraints associated with the manifested

attributes of decision makers Identity issues: sense of self; Psychological issues: impatience, commitment, and psychological

barriers; WDR (2008), WDR (2015); Aspirations failure, ‘external’ locus of control (Tanguy et al.)

Conceptual Issues – Locus of control

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Specific focus: Locus of control

Locus of Control (Rotter, Levenson, Bandura, Hill): a person’s belief regarding the primary causation of events

in his or her life in general (or in a specific area?); ‘internal’ vs. ‘external’ – continuum; deemed a powerful influence on personality and behaviour; used to predict behaviour in a lot of spheres (health,

education, employment …)See: Borghans, Duckworth, Heckman, ter Weel (2008). “The Economics and Psychology of Personality Traits,” Journal of Human Resources, Volume 43, Number 4, pp.972-1059.

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Conceptual Issues – A Schema

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Premise – Poorer households use less modern inputs

Low productivity and poverty persist;

.3.4

.5.6

.7

1 2 3 4 55 quantiles of wealth_index

95% CI predicted fert_use

.1.1

5.2

.25

.3.3

5


95% CI predicted improved_seed

36pp - Fertilizers17pp - Improved

SeedsNote: Chemical fertilizers and improved seeds = 20% of crop output growth during 2005-2013 in Ethiopia (Bachewe et al. (2015))

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Premise – LOC a possible pathwayMeasuring LOC: Binary

Survey LOC-

Destiny (%)

Number of Observation

sEthiopia - PSNP 2008 25.8 4,360Ethiopia - ERHS 2009 30.9 2,068Ethiopia - PSNP 2010 32.3 4,619

Ethiopia - Aspirations Survey 2010-11 37.7 2,068

Ethiopia – AGP Baseline Survey 2011 35.3 7,896Ethiopia – AGP Midline Survey 2013 33.1 7,495IFPRI Pakistan Household Survey

2011 58.1 1,546Malawi Rural Household Survey-2011 27.0 671Ethiopia - FTF Baseline Survey 2013 30.3 6,903

Ethiopia – Transport Survey 2014 31.4 775Ethiopia - FTF Midline Survey 2015 26.5 6,685

“Each person is primarily responsible for his/her success or failure in life.” “A person’s success or failure in life is a matter of his/her destiny.”

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Premise – LOC a possible pathway

Locus of control – pared down version of Levenson (1981)C To a great extent my life is controlled by accidental/chance happenings.O I feel like what happens in my life is mostly determined by powerful people.I When I make plans, I am almost certain/guaranteed/sure to make them work.C Often there is no chance of protecting my personal interests from bad luck

happenings.C When I get what I want, it’s usually/mostly because I’m lucky.C My experience in my life has been that what is going to happen will happen.O My life is chiefly controlled by other powerful people. O People like myself have very little chance of protecting our personal interests

when they conflict with those of more powerful people.C It’s not always wise for me to plan too far ahead because many things turn out to

be a matter of good or bad fortune.O Getting what I want requires making those people above me (people with higher

status) happy with me.I I can mostly determine what will happen in my life.I I am usually able to protect my personal interests (I can usually look after what is

important to me)I When I get what I want, it’s usually because I worked hard for it.O In order to have my plans work, I make sure that they fit in with the desires of

people who have power over me.I My life is determined by my own actions.

Measuring LOC: Four-level (Likert-type) semantic scale (Strongly disagree, Disagree, Agree, Strongly agree)

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Results – LOC and Wealth

77.

58

8.5

9


95% CI predicted LOC_others

11.5

1212

.513

13.5

14


95% CI predicted LOC_internal

8.2

8.4

8.6

8.8

99.

2


95% CI predicted LOC_chance

Poorer individuals have lower (higher) internal (external) locus of control (7-17%) – FTF (2013) survey;

Holds for the AGP, PSNP4, and Transport Surveys;

77.

58

8.5

9


95% CI predicted LOC_others

11.5

1212

.513

13.5

14


95% CI predicted LOC_internal

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Results – LOC and WealthThe LOC-Wealth relations hold after controlling for age, gender, and schooling of the respondent (OLS regression)

LOC-Internal LOC-Chance LOC-Others

FTF 2013

PSNP4 2016

FTF 2013

PSNP4 2016

FTF 2013

PSNP4 2016

Gender (Male=1)

0.272** 0.367***

-0.301**

-0.211**

*

-0.370**

*-

0.31***(0.125) (0.093) (0.124) (0.071) (0.131) (0.077)

Age (Years) -0.005-

0.016***

0.005 0.008*** -0.002 0.007**

*(0.004) (0.002) (0.004) (0.002) (0.004) (0.002)

Schooling (Years)

0.039 0.024*** -0.004 0.005 -0.021 0.001

(0.026) (0.005) (0.024) (0.006) (0.023) (0.006)

Wealth Index0.466**

*0.199**

* -

0.167***

-0.137**

*

-0.265**

*

-0.159**

* (0.081) (0.03) (0.061) (0.027) (0.064) (0.026)

Constant 12.69*** 12.9*** 8.896*** 9.25*** 8.465*** 9.32*** (0.257) (0.176) (0.239) (0.165) (0.223) (0.145)

Number of Observations 5907 6800 5907 6800 5907 6800

Notes: EA –clustered standard errors in parentheses.

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Hypothesis – LOC and Poverty

Poorer individuals have lower internal (higher external) locus of control;

A feedback loop linking LOC and poverty? Poverty lowers internal LOC, but is not a complete

determinant; Weak internal (or strong external) LOC discourages

‘investment’ (including modern technology adoption) by the poor;

Poverty persists … Explore the hypothesis in relation to adoption of modern inputs

by farmers in rural Ethiopia

Six surveys – AGP (2011, 2013), FTF (2013, 2015), Transport (2014), PSNP4 (2016)

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Specification – Propensity to adopt Modern Inputs

Specification – Ordered Probit (semi-nonparametric) regression of adoption of modern inputs (also generalized orderd probit)

Dependent variable: ‘No Fertilizer or Improved Seeds used’ = 0; ‘Either Fertilizer or Improved Seeds used’ = 1; ‘Both Fertilizer and Improved Seeds used’ = 2

Why order? specific way of testing the proposition that LOC attributes are

likely to affect the overall propensity to adopt modern inputs; a simple way of examining why most farmers appear to fail

to benefit from joint fertilizer-improved seed use; exploit well-known ordered choice models/techniques;Adoption

Status FTF1 FTF2 AGP1 AGP2 PSNP4 Transport

0 43.59 32.30 39.90 44.06 51.13 14.711 39.92 37.96 37.86 39.25 35.50 50.972 16.49 29.74 22.24 16.68 13.37 34.32

Total 5969 6117 7316 7505 7287 775

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Specification – Modern Input UseControls: Gender (Male=1), Fraction of Landholding

Deemed Flat,

Age (Years), Fraction of Landholding Cultivated with Cereals,

Schooling (Years), Rainfall (mm in logs)Number of Working-age Male Members in the Household,

Access to Extension Services (Yes=1),

Total Household Landholding (Hectares in logs), Access to Credit (Yes=1),

Fraction of Plots with Land Certificate,

Distance to a Permanent Market (km),

Average Distance of Parcels from the Homestead (minutes), Wealth Quintile,

Fraction of Landholding Deemed Fertile,

Off-farm and/or Non-farm Income (Yes=1)

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Results – LOC and Modern Input Use - AGP (2011)

dy/dx per one SD change (%)0 1 2

Sex of the Household Head (Male=1) -6.8*** 2.7*** 4.1***Age of the Household Head (Years) -13.6*** 4.5*** 9.1***Schooling of the Household Head (Years) -2.6*** 1.1*** 1.6***Proportion of Male Adults in the Household -1.1 0.4 0.7Area Cultivated (Hectares in logs) -2.9*** 1.2*** 1.8***Proportion of land deemed fertile (%) 2.2** -0.8* -1.4**Access to Extension Services (Yes=1) -20.0*** 6.3*** 13.7***Wealth index -1.7*** 0.8** 1.1***LOC – Chance 1.7* -0.7* -1.0*LOC – Others 0.4 0.0 0.0LOC – Internal -2.9*** 1.1*** 1.8***

Number of observations 7212Note: Robust Standard errors used; *** <0.1%, ** <1%, *<5%

Note: Statistical and ‘economic’ significance;

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Results – LOC and Modern Input Use - FTF (2013)


Sex of the Household Head (Male=1) 2 -1.1 -0.9

Age of the Household Head (Years) 2.9 -1.5 -1.5Schooling of the Household Head (Years) 1.96* -0.9* -0.9*Proportion of Male Adults in the Household -2.4** 1.3** 1.1**

Area Cultivated (Hectares in logs) -9.1*** 5.1*** 4.0***Proportion of land deemed fertile (%) 8.9*** -5.0*** -3.9***Access to Extension Services (Yes=1) -17.9*** 9.6*** 8.2***

Wealth index -2.7*** 1.4*** 1.1***LOC – Chance 1.9* -1.1* -0.8*LOC – Others 3.1*** -1.5*** -1.2***LOC – Internal -2.9*** 1.6*** 1.2***

Number of observations 5641

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Results – LOC and Modern Input Use – PSNP4 (2016)


Sex of the Household Head (Male=1) 1.7 -1.1 -0.6

Age of the Household Head (Years) -17.2*** 10.9*** 6.2***Schooling of the Household Head (Years) -1.9*** 1.3*** 0.6***Proportion of Male Adults in the Household -3.4*** 2.3*** 1.2***

Area Cultivated (Hectares in logs) -6.3*** 4.2*** 2.2***Proportion of land deemed fertile (%) -0.5 0.4 0.2Access to Extension Services (Yes=1) -15.3*** 8.9*** 6.4***

Wealth index -6.6*** 4.5*** 2.3***LOC – Chance 0.0 0.0 0.0LOC – Others 1.6* -1.1* -0.5*LOC – Internal -1.7** 1.1** 0.6**


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Results – LOC and Modern Input Use - Transport (2014)


Sex of the Household Head (Male=1) -19.8** 3.5 16.3***

Age of the Household Head (Years) -7.1 -4.3 11.4Schooling of the Household Head (Years) 1.3 0.6 -1.9Proportion of Male Adults in the Household -0.4 -0.2 0.6

Area Cultivated (Hectares in logs) -17.2** -8.7 25.9**Proportion of land deemed fertile (%) -1.9* -1.0 2.9*Access to Extension Services (Yes=1) -13.1*** -2.4 15.5***

Wealth index -3.3 -1.7 5.1***LOC – Chance 0.3 0 -0.3LOC – Others 0.4 0.4 -0.7LOC – Internal -2.3** -1.3 3.7**


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Summary

PSNP4 (2016)

AGP (2011

)

FTF (2011

)

AGP (2013

)

Transport

(2014)

AGP (2013)

(Lagged)

10.32 14.75 19.25 38.88 8.4 21.43

p-value 0.016 0.002 0.000 0.000 0.038 0.000

All LOC coefficients: 32 out of 54 are significant below the 5% level with the hypothesized sign;

Internal LOC coefficients: 14 out of 18 are significant below the 5% level with the hypothesized sign;

The null hypothesis that the three LOC indicators are jointly insignificant is rejected in all cases.

2(3)χ

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Summary ‘Standard’ associations detected – extension, wealth, farm

size, credit, labour availability, age, gender are correlated with adoption;

LOC and adoption: Sign: Internal’ locus of control – positive; ‘chance’ and

‘powerful others’ locus of control – negative. Size 1: size of the correlation is comparable to that with

schooling. Size 2: association averages across datasets at -12 percent

(LOC-Chance), -15 percent (LOC-Others), and 18 percent (LOC-Internal) of the corresponding association for ‘access to extension’.

Gender Women heads appear less likely to adopt; and Women heads have lower LOC-Internal and higher LOC-

Chance and LOC-Others (not huge but statistically significant differences);

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ObservationsSo what? Any policy implications?

Ascertain the nature and extent of “psychological and social influences” that affect behaviour – “desirable, possible, ‘thinkable’” (WDR (2015));

Relevance to policy design (complementary to incentives and widening opportunities): Focus both on ‘what’ and ‘how” – timing, labelling, simplifying,

reminding; Understand target communities – norms, identity (internal

constraints); Examples from the suggestive evidence above:

Poor vs. non-poor – same delivery modality may not work; Male vs. female – additional reason to enhance women

empowerment in agriculture;Motivational devices, Role modelsA lot to be learnt – more research and experimentation

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Caveats

Association, not causation – correlations uncovered in multiple datasets;

Costs and benefits of adoption; Distance to markets – access, prices; Education, farm size, availability of labour; Access to credit, wealth;

Cross-sectional data – learning, other dynamics (risk);

Risk and time preferences; wealth, education, agro-ecological factors (rain,

soil fertility, temperature), correlated errors;

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Thank you

pathways less explored – locus of control and technology adoption

Government & Nonprofit