Socio-economic factors affecting preferences for Clean Energy Technologies (CET) across households in rural and peri-urban Ethiopia

Transcription

1 Socio-economic factors affecting preferences for Clean Energy Technologies (CET) across households in rural and peri-urban Ethiopia Empirical results and practical implications for Microfinance Institutions (MFI) Giulia Corso February, 28 th, /21

2 CEPM Project Ethiopia (1) 3/21

3 CEPM Project Ethiopia (2) Technology Selection Process Credit Scheme Implementation 1 Demand Analysis Energy needs assessment Preferred energy systems Market segments 2 Supply side Analysis Market Maturity Supplier suitability CET & Supplier selection 3 Business Development Contracts with suppliers Supply chain design CET credit line integration 4 - Pilot CET loans given out Monitoring & Evaluation Scale-up plans 4/21

4 CEPM Project Ethiopia (3) 4 - Pilot CET loans given out Monitoring & Evaluation Scale-up plans The Best Climate Practice Award atch?v=p0ijv6bnpoi&feature =youtu.be Solar Home Systems are currently offered 5/21

5 Demand Analysis 1 Demand Analysis Energy needs assessment Preferred energy systems Market segments 2 Supply side Analysis Market Maturity CET selection Supplier selection 3 Business Development Contracts with suppliers Supply chain design CET credit line integration 4 -Pilot CET loans given out Monitoring & Evaluation Scale-up plans 6/21

6 Survey conducted across MFI clients 347 observations 7/21

7 Sample Description - Energy Expenses Expenditures for Energy Services Service Monthly Expenses %Av. Income Average (ETB) Average (EUR) Electricity (phone) % Cooking % Lighting % Tot % 8/21

8 Sample Description - Energy Sources Energy Sources for Cooking 9/21

9 Sample Description - Energy Sources Energy Sources for Lighting 60% 50% 40% 49% 30% 20% 10% 0% 13% 3% 13% 22% Access to Electricity 10/21

10 Demand for CET Preferences towards 5 CET SHS ICS PV Lamp SWP Biodigester 11/21

11 Demand for CET and Occupation Main Occupation Interest in purchasing a CET 12/21

12 Research Objectives 1. Identification of drivers of MFI clients interest in purchasing a CET in rural and peri-urban Ethiopia; 2. Identification of market segments or target groups. Methodology Inferential multivariate analysis through models y~ f(x, β) Usage of collected data to estimate model s parameters to find correlations between variables Discrete-choice analysis and random utility models 13/21

13 Discrete-choice analysis In a choice situation P(i C n ) = Pr [U in U jn, all j C n ] U in = V in (x in, β) + ε in = β z ik + β x in + ε in y ~ f (x, β) Model Type Binary logit Choice set 2 Alternatives: CETWILL + NOCET Multinomial (MNL) logit >2 Alternatives: 5 CET (+ NOCET) 14/21

14 Drivers of CET choice CETWILL = β 0 + β 1 *PURCHDEV + β 2 *AGE + β 3 *INCOME + β 4 *HHSIZE + β 5 *SAVEDEV + β 6 *INTRATE + β 7 *TRADFINANCE + ε 16/21

15 Main Findings (1) Factors influencing the interest in a specific CET: Coefficients Std. Error z value Pr(> z ) (Intercept) 4.51** AGE -3.97** SAVEDEV 8.32** PURCHDEV 1.79*** HHSIZE INCOME -5.49*** INTRATE -7.63* TRADFINANCE 8.84* Significance codes: 0 *** 0.01 ** 0.05 * /21

16 Main Findings (2) Factors influencing the interest in a specific CET: Hours Cooking (+) Female Decision- Making (-) Lighting Expenses (-) Energy needs/ purchase power Residues for fire (-) trade-off perception On-grid (-) No backup technology Land rent (-) 18/21

17 Marketing Strategy for the MFIs Identification of Target groups : First Movers Young clients Men clients Lower income clients Clients owning land Second Movers Elder clients Women clients Better-off clients Clients renting land Information that can be used for effective Communication and Sale strategy to increase CET loan demand and sales, e.g.: Hours Cooking Overcome trade-off perception 19/21

18 20/21

19 Comments and limitations Stated preferences provide subjective data Data quality could be improved Models are not exhaustive - by including new variables the parameters might vary Method not always viable because of long procedure and need of skills qualitative research methods are also meaningful although less accepted 21/21

20 Thank you for your attention! 22/21