How to sell a condom? The Impact of Demand Creation Tools on Male and Female Condom Sales in Resource Limited Settings

Transcription

1 How to sell a condom? The Impact of Demand Creation Tools on Male and Female Condom Sales in Resource Limited Settings Fern Terris-Prestholt 1 & Frank Windmeijer 2 Fern.Terris-Prestholt@LSHTM.AC.UK 1 London School of Hygiene &Tropical Medicine 2 Bristol University HESA retreat Sept 14, 2015

2 HIV, risky sex and condoms End of HIV not in sight, despite recent advances in HIV prevention (VMMC and ARV-based prevention) Condoms highly effective at preventing HIV: 50 million infections averted (Stover 2015), and very cheap Annual condom gap: 8 million condom shortfall (UNAIDS 2014) 8 condoms per sexually active persons in Africa (Desperthes, 2014) Demand and supply constraints; Need for accessible and consistent supplies Demand creation to increase (and sustain) use

3 Social Marketing: Why can t we sell brotherhood like we sell soap? Sweat et al, WHO bulletin 2011

4 AIMS To estimate key drivers of aggregate demand for male and female condoms (static panel model) Identify differences between products Estimate short and long run effects of demand creation tools and obtain unbiased estimates of effect (dynamic panel estimator)

5 Aggregate Condom Demand Model Demand (country level male/ female condom sales) as a function of: Price (own) Price of substitutes (P male condom ; Presence of female condom in marketing mix) Income (GDP per capita) Promotion: Mass media advertising and IEC (interpersonal communications) Programme effort (Local Staffing levels) Product maturity Adult HIV prevalence Population Size All prices in 2011 PPP

6 Data 1: Sales over time Male condom Female condom n=11 n=52 n=3 n=28 n=430 n=155

7 Data 2: Descriptives Variables Mean (min-max) Sales 15,900,000 ( ,000,000) Price (ppp$2011) $0.10 ($0 - $0.95 ) Advertising expend. (ppp$2011) Information & Education Campaign expend. (ppp$2011) $778,457 ($0-$8,263,314 ) $467,164 ($0-$12,400,000 ) Product maturity 8.89 ( ) HIV adult prevalence 5.53% (0.10%-28.70% ) Mean (min-max) 147,802 (26-4,238,960) $0.37 ($0-$4.14 ) $64,170 ($0-$690,505 ) $28,930 ($0-$441,515 ) 4.21 (1-13 ) 8.16% (0.10%-28.70% )

8 Econometric approach 1: static panel- OLS and FE ln( q kit ) FC j j j j ln( X j kit ) FC *ln( X j kit ) v i w t kit k= 1, 2; i =1...N; t =1...T, Where : q= natural log of: Sales quantity X = natural log of: Price, Advertising, IEC, Programme Effort, Product Age, HIV, Income, Population k = product type (male condom, female condom) i = country t = time

9 Results 1: Differences in drivers of condom sales Static model FE, Year as trend, VARIABLES Main effects Constant Ln Advertising 0.192*** * Ln IEC ** 0.176* Ln Price Ln Programme Effort Ln GDP per capita Ln Population Size *** Ln Adult HIV prevalence 0.445* 0.336*** Ln product maturity 0.383** Year Observations 515 R-squared 0.93 Country effects Female condom dummy LR-test (FE versus OLS) 335*** Country effects not shown *** p<0.01, ** p<0.05, * p<0.1

10 Econometric approach 2: Dynamic panel- systems GMM j j ln( qit ) ln( X j it ) ln( qi, t 1) v i w t it Where : q= natural log of Country Sales quantity X = natural log of: Price, promotion, Programme Effort, country vars λ= sales persistence i = country t = time k= 1, 2; i =1...N; t =1...T, Long run effect: β_ (1- λ)

11 Estimation results: dynamic panel data model of the demand for condoms Male Condom Female Condom VARIABLES GMM Long-run GMM Long-run Lag Ln Condom Sales (λ) 0.503*** 0.378*** Ln Promotion 0.165** 0.332** 0.185** 0.297** Ln Price * *** *** Ln Programme effort * Ln GDP per capita Ln product age Ln Population size 0.191** 0.385*** 0.166* LN Adult HIV prev ** 0.331** ar1p ar2p hansenp Observations Number of Countryc Robust standard errors in parentheses, *** p<0.01, ** p<0.05, * p<0.1 Parameters for year, country and dummys for: no promotion, free condoms and no staffing and their lags not shown

12 Limitations Data limitations Income distribution should have been included to account for aggregation bias but was not widely available for full panel Narrow definition of substitute market Potential measurement errors in routine program M&E data. Sample relatively small, though large for subject area

13 Robustness Estimates largely intact when estimated: Excluding: large countries; Eastern Europe & Central Asia; Without country context variables alternative specification of lags (2-4); excluding 0 value observations; using GMM-Differences did affect results considerably, but Sargan test could not reject GMM-SYS in favour of GMM-DIF

14 Conclusions Demand stimulation tools affect demand products differently: No one-size fits all marketting for new products Advertising only effective for male condoms IEC important for both products, but far greater impact on female condoms Price elasticity of demand is > female condoms Demand for condoms slow to adjust Sales of both products are persistent, though male condom more so.

15 Acknowledgments Support for the write up of this work was provided by Leverhulme Trust s International Academic Fellowship I thank University of Toronto for hosting my sabbatical June to August We thank Population Services International, Research & Metrics Department, Washington D.C. for providing the data. These were analysed independently and the authors take full responsibility for the conclusions drawn there from.