Presentation on theme: "Money or Ideas? A Field Experiment on Constraints to Entrepreneurship in Rural Pakistan Xavier Giné, DECFP Ghazala Mansuri, PRMPR Money or Ideas? A Field."— Presentation transcript:
Money or Ideas? A Field Experiment on Constraints to Entrepreneurship in Rural Pakistan Xavier Giné, DECFP Ghazala Mansuri, PRMPR Money or Ideas? A Field Experiment on Constraints to Entrepreneurship in Rural Pakistan Xavier Giné, DECFP Ghazala Mansuri, PRMPR
Entrepreneurship plays a central role in the process of economic growth and development (Knight, 1921; Schumpeter, 1942) –In Solows (1957) seminal paper, only a modest fraction of the increase in output per worker was driven by increases in capital, the rest was attributable to technical change, requiring entrepreneurial talent. Some countries have grown dramatically while others have remained stagnant, but it is hard to believe that poor countries lack entrepreneurial talent. So what are the main barriers to entrepreneurship in a poor country?MotivationMotivation
Access to Finance –Large empirical and theoretical literature (Blanchflower and Oswald, 1984; Holtz-Eakin, Joulfaian and Rosen, 1994a and 1994b and more recently Paulson, Townsend and Karaivanov, 2006; de Mel, McKenzie and Woodruff, 2008 and Banerjee et al. 2010) –Mohamed Yunus sides with this view: Giving the poor access to credit allows them to immediately put into practice the skills they already know (Yunus, Banker to the Poor 1999) Access to business skills or managerial capital –Builds on the occupational choice models of Lucas (1978) with the assumption that managerial capital can be taught (Bloom and Van Reenen, 2010; Bruhn, Karlan and Schoar, 2010 and Schoar, 2010).MotivationMotivation
In partnership with Pakistan Poverty Alleviation Fund (PPAF), we conduct a randomized field experiment with one of its largest MFI partner organizations. We interviewed 4,160 members from 4 different geographical regions organized in groups. 2x2 design offering: –Business Training Groups divided into two equal sized bins: BT and no BT Members of BT groups were offered a 8 day course (36 hours). –Loan Lottery Eligible members were allowed to submit loan requests of up to Rs 100K, (current limit around Rs 15K) for a 7 month period If request is approved, then the borrower enters a lottery: If winner, borrower gets loan approved. If loser, borrower gets regular loan size based on their loan cycle So clients fall in one of four categories. What do we do?
What are the key constraints to entrepreneurship? –Is it lack of skills or lack of capital? To MFI clients: –How beneficial is business training (BT)? Does it lead to the creation and management of more profitable enterprises? Does it lead to lower business failure? –Does it improve client retention? –Does current loan size inhibit enterprise growth and profitability? Ie, are clients constrained? To MF Institutions: –Does it improve repayment? Client retention? Is it cost-effective? Key Questions
GMKVDFS Target AudienceMF clients, not all entrepreneurs MF clients, all entrepreneurs Program DesignLocal firm based on ILO Local firm and FFH FFH and researchers InstructorsMF staff ? Total Number of Hours 461115-18 FrequencyDaily, 9am-4pm Once a week, 30 min Once a week, 3 hours Duration6+2 days22 weeks6 weeks BT Training
TimelineTimeline Nov 06Jan 07 Baseline Survey Orientation for BT Feb-May 07 BT Rollout Loan Lottery June 08 Nov 07 Dec 08 Follow-up Survey
3 sources of data: –MIS (administrative) data from NRSP, including client retention, loan disbursement and repayment. –Baseline Survey (before BT was offered) and Follow-up Survey. FU surveys include a business visit of all businesses operated by clients. In addition, surveys include a variety of questions on the socio-economic characteristics of clients.DataData
The response rate in the follow-up survey for the remaining regions is 85%, including individuals that are no longer clients. –There are no differences in attrition rate between clients offered BT or winning the Loan Lottery Data: Response Rate
Business Training was implemented as planned. –82% of clients offered BT correctly recall the offer at FU. –Attendance rate is 98% (transport, lunch and per diem allowance was provided). Loan Lottery implementation was not perfect. –Only 35% of clients recall the offer at FU. –Most lottery applicants that lost believe to have been rejected by NRSP. –Only 30% of eligible clients ended up applying over the 7-month period. Implementation of Experimental Design
We report Intent-to-Treat (ITT) effects –Disregard possible heterogeneity in exposure to treatment First difference (only FU data) or double-difference (BL and FU when available) Y ij1 = α + β 1 BT j + β 2 LL ij + β 3 BT j and LL ij + γX ij + δ Y ij0 + ε ij, –Fixed effects at the branch level, clustering SEs at the level of the borrower group, the unit of randomization Follow Kling, Liebman, and Katz (2007) and construct standardized measures for families of outcomes. –Convert each variable k to a z-score, the summary measure will be Z ij = Σ k z ijk /k, where z ijk = (Y ijk - μ k ) / σ k Estimation Methods
Are gender differences masking differences in other characteristics? –Inclusion of a range of controls does not affect results Training received by women is of low quality –The same staff trained male and female members If labor markets are missing for women, the quality of the marginal entrepreneur will be lower for females. Women may see business as fall-back option (Lucas, 1978; Emran et al, 2007). Women face mobility and time constraints that prevent them from capitalizing on BT –Training designed for non-literate audience –Time Allocation Analysis What explains gender differences?
Evidence that BT led to improved business and household outcomes, especially among men. The impact of Loan Lottery is weaker, perhaps because clients were not credit constrained. Treatments seem also successful from institutional perspective: –BT increases demand for larger loans without an effect on repayment Caveat: Children schooling is adversely affected –BT raised income but also the opportunity cost of children, so net affect is ambiguous.ConclusionsConclusions