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Journal of Economic Behavior & Organization 95 (2013) 252– 269

Contents lists available at ScienceDirect

Journal of Economic Behavior & Organization

j ourna l ho me pag e: www.elsev ier .com/ locate / jebo

xperiments in Islamic microfinance�

ohamed El-Komi ∗, Rachel Crosonniversity of Texas at Dallas, 800 W. Campbell Road, Richardson, TX 75080-3021, United States

a r t i c l e i n f o

rticle history:eceived 12 August 2010eceived in revised form 13 June 2012ccepted 14 August 2012vailable online 7 September 2012

EL classification:91038210

eywords:slamic financexperimental economicsicrofinance

nformation asymmetrynterestrofit sharingoint venture

a b s t r a c t

Microfinance has been identified as an important tool in increasing the productivity ofthe poor and in aiding economic development. However, a large proportion of the poorare practicing Muslims, and are thus unable to take advantage of traditional microfinancecontracts which involve the payment of interest. This paper describes and experimentallytests Islamic-compliant microfinance products in the context of information asymmetryand costly state verification. We find significantly higher compliance rates for the Islamic-compliant contracts (profit-sharing and joint venture) than for the traditional contract(interest-based). We believe that there is great promise for these types of loans in themicrofinance context, for both Muslims and non-Muslims.

© 2012 Published by Elsevier B.V.

. Introduction

This paper describes and experimentally tests Islamic-compliant microfinance products. While both microfinance andslamic (macro)finance are well-developed fields of study, very little previous research has examined their intersection. Thisndeavor is important for understanding the financial attitudes and behaviors of low-income consumers, both within the.S. and abroad.

Microfinance has been identified by many as a useful tool in aiding economic development (Comim, 2007; Dowla andarua, 2006; Wright, 2000; Islam, 2007), even though the actual impact on poverty is still a matter of debate. However,he reach of microfinance (and especially microcredit) may be more limited than was previously realized. It is estimatedhat over 1/3 of the world’s poor are Muslims (CIA World Factbook, 2010 and Economist, 2008), and thus are unable to

� We thank Ali Abdul-Rahman, Ahmed Al-Zahrani, Daniel Arce, Catherine Eckel, Mahmoud El-Gamal, Uri Gneezy, and Dean Karlan for their help inhe conceptualization and design of this paper. Special thanks to the CBEES lab staff; Sheheryar Banuri, Tara Larson, Wendy Lee, Elizabeth Pickett anddam Pierce for outstanding support. We particularly thank three anonymous reviewers for their invaluable comments and suggestions. We also thank

he participants at the Southern Economic Association Conference in San Antonio, the Economic Science Association Conference in Chicago, the Europeanconomic Association Conference in Glasgow, the African Econometrics Association Conference in Cairo, the International Conference on Islamic Economicsnd Finance in Qatar and the Symposium on Analytical and Empirical Research in Islamic Finance at Aston Business School for helpful comments.∗ Corresponding author. Present address: Department of Economics, the American University in Cairo, AUC Avenue,P.O. Box 74, New Cairo 11835, Egypt.

el.: +44 0191 334 5433; fax: +44 0191 334 5201.E-mail addresses: [email protected] (M. El-Komi), [email protected] (R. Croson).

167-2681/$ – see front matter © 2012 Published by Elsevier B.V.ttp://dx.doi.org/10.1016/j.jebo.2012.08.009

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M. El-Komi, R. Croson / Journal of Economic Behavior & Organization 95 (2013) 252– 269 253

take advantage of the existing, interest based, microcredit products (CGAP, 2008). The Consultative Group to Assist thePoor (CGAP) conducted a global survey in 19 Muslim countries in 2007, in which 20–40 percent of the respondents citedreligious reasons for not using conventional microloans. Constructing and making available Islamic-compliant microfinanceproducts would extend the reach of microfinance and aid in the economic progress of the Muslim poor in all countries, andthe economic development of nations with large Muslim populations.

Karlan and Morduch (2009) stress the importance of the way microfinance choices are offered, and argue that they maymatter more than the pure economics of the choices with regards to take-up rates. The products tested in this paper rely onprofit and loss sharing (PLS) contracts, and show how these options can contribute to the variety of microfinance choices,which should result in higher take-up rates of microfinance products. Our results indicate that these products can be moreefficient (and more profitable for lenders) than traditional interest based contracts which are primarily offered, even amongnon-Muslim populations.

The use of PLS contracts has traditionally been minimized in Islamic banking due to risks resulting from informationasymmetry (such as enterprise failure, adverse selection, moral hazard and costly state verification) (El-Gamal, 1997). Whilethe problems of enterprise failure and adverse selection are common for both PLS and interest based finance, moral hazardand costly state verification are more acute risks of PLS finance (e.g. Gale and Hellwig, 1985). Our paper focuses on comparingthese PLS and interest based contracts when the lender needs to verify the project’s state when the loan has not been repaid.1

PLS contracts are surprisingly sparse in the field. El-Gamal (1997) notes that Islamic banks over-rely on non-PLS contracts(such as: leasing, cost-plus and deferred payment sales), while using an accounting interest rate for their bookkeeping. Chongand Liu (2009) show that less than 1 percent of Islamic banking operations in Malaysia use PLS-based products and thus,most of the operations are interest based or -pegged. Dar and Presley (2000) cite agency problem as one of the main reasonsbehind the lack of PLS in Islamic banking. However, they confirm that there is no theoretical reason to make us believe thatPLS is inherently less efficient than interest based contracts.

That said, sometimes interest contracts incorporate PLS features. For example, Udry (1990) cites an example from North-ern Nigeria (where Muslims are predominant) in which risk is shared by varying the interest rates that based on the realizationof random production shocks.

Our goal in this paper is to investigate the feasibility of PLS contracts in the presence of information asymmetry. We arguethat PLS contracts pool risk between the lender and the borrower, much as a sharecropper agreement or a profit sharingfranchise agreement. This risk pooling generates in a different power structure between the borrower and the lender thanthe interest contract. As a result, PLS contracts are seen as more equitable than interest contracts, and borrowers will feel astronger obligation to comply with their terms and, in particular, to repay the loan when their project succeeds.2

In this paper, we develop and test Islamic-compliant microfinance contracts that are based on PLS. We use laboratoryexperiments as a “testbed” or “wind-tunnel” for these contracts (Plott, 1987). The laboratory can test, at very low cost, thebehavioral response to different types of contracts. These contracts can then be adjusted or amended before being used inthe field. The laboratory thus serves as an intermediate step between theoretical development and field-testing.

We develop two microfinance contracts which are Islamic-compliant (profit sharing and joint venture) and comparethem with an interest based loan. Borrowers invest these loans in risky projects, whose outcome is known to them butnot to the lender. We examine compliance rates, the rate at which individuals comply with the terms of the loan, in thethree contracts under three conditions. A no-enforcement condition involves a simple repayment or reporting decision bythe borrower. An enforcement condition allows the lender to follow up on the decision, and to force collection or audit theproject’s outcome if appropriate. An enforcement with penalty condition also allows the lender to charge a penalty to theborrower if he has defaulted on the loan or misreported the success of his project.

Our results indicate that the Islamic-compliant loans induce at least as much compliance as the interest based loans inall three conditions (no-enforcement, enforcement and enforcement with penalty), although the differences between the threecontracts decrease as the possibility of penalty is introduced. We believe that there is great promise for these types of loansin the microfinance context, and discuss strategies for field implementation in the conclusion of the paper.

The paper is organized as follows. Section 2 discusses the practice of Islamic finance, microfinance, and their combination.Section 3 describes our theoretical model and Section 4 our experimental design. Section 5 presents our experimental resultsand Section 6 concludes.

2. Islamic finance, microfinance, and their combination

2.1. Islamic finance

Islamic finance is in a phase of growth and change. On one hand, Islamic finance is being celebrated as a promising financialindustry. Its assets exceed $1.3 billion (compared to $160 billion in 1997) and the market is estimated to be growing at 10–15

1 This is by no means the only interesting or important problem in microfinance or microcredit. Adverse selection of borrowers, and moral hazard of thechoice of project funded with the borrowed money are also relevant issues, but are beyond the scope of this single paper.

2 We thank an anonymous reviewer for pointing out asymmetric power as a causal mechanism for the increased sense of obligation felt in PLS contracts.

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54 M. El-Komi, R. Croson / Journal of Economic Behavior & Organization 95 (2013) 252– 269

ercent per year (The Economist Online April 4, 2012). On the other hand, despite its boom, the Islamic banking industryuffers from two crucial shortcomings.

The first is its failure to meet the developmental needs of the Muslim poor. Islamic finance is not designed for microfinance,ut focuses on large dollar investments and loans. The second shortcoming is the reliance of the Islamic banking industryn mark-up (murabaha) products that resemble interest based loans in structure (Appendix A provides a description ofhe principles of Islamic finance and different types of products that have been developed, for the interested reader). Thiseliance has reinforced the inability of Islamic finance to reach individuals who are seeking contracts without interest.

.2. Microfinance

Microfinance has attracted significant attention during the last two decades from academics and policy makers alike. Inhis paper we will be focusing on a particular type of microfinance; microcredit, in which small loans ($100 or so) are madeo the very poor. Microcredit has the potential to include the poor in the formal financial system, which is widely believedo contribute to economic development and growth, because formal financial sectors reduce transaction and informationosts, leading to a more efficient economy. Levine (2005) reviews both theoretical and empirical studies demonstrating thatetter functioning financial sectors allow countries to grow faster.

However, microcredit has its challenges. First, it suffers low take-up rates; relatively few people participate in microcreditrograms. Second, in apparent contrast with its mission, microcredit is not cheap. Interest rates between 20 percent and 50ercent annually are quite common in the microfinance industry, even in places where annual inflation rates do not exceed0 percent (Dehejia et al., 2009); these high interest rates reflect the additional risk of this type of borrower. Overall, givenhese challenges, the impact of microcredit on poverty alleviation has not yet been conclusively demonstrated (see, e.g.anerjee et al., 2009).

A few previous studies have examined one or another of these issues. For example, Karlan and Zinman (2009) examinedhe takeup problem, and estimated the impact of enhancing access to consumer loans in a field experiment in South Africa.hey found significant positive effects of expanded access to credit on the overall borrower outcome, in terms of employment,ncome and food consumption. The marginal loans given through the credit expansion were also profitable for the lender.

Abbink et al. (2006) used laboratory experiments to investigate the impact of interest rates on default in group settings.n the one hand, they find that higher interest rates increase default rates. On the other hand, higher interest rates increase

he group’s punishment of defaulters. Thus, higher interest rate had a mixed effect on default rates. Similarly, Dehejia et al.2009) find that different categories of the poor respond differently to increases in interest rates. They increase interestates in the slums of Dhaka, Bangladesh from 2 percent to 3 percent per month. They find that poorer borrowers were moreensitive to the increase in interest rate (with elasticity of −.86) than relatively wealthier borrowers (with elasticity of −.26).

Another important choice in microcredit is between individual and group-lending arrangements (Armendariz andorduch, 2007). Group-lending arrangements are the most popular and well-developed. However, Giné and Karlan (2010)

nd no affect of group liability on repayment rates; individual loans are repaid at the same rate as group loans in their fieldxperiment in the Philippines.

In contrast with this previous research, we will focus on the type of microcredit contract being used; interest basedr PLS based. We will assume that all individuals have access to these contracts, and will hold constant the cost of funds.urthermore, we will focus on individual lending, as we believe that this is the setting where individuals are most likely toxhibit noncompliance.

.3. The combination

The aim of this paper is to combine microfinance and Islamic finance in order to develop financial products for theoor that are consistent with Islamic principles and involve PLS contracts. Almost half of the 1.6 billion World Muslims areoor. Surveys by CGAP (2008, 2009) indicated the 40 percent of the Muslim poor reject interest based microcredit loans foreligious reasons.

We believe that identifying effective PLS contracts will enhance access to finance amongst the Muslim poor, who areften excluded from banking services. 80 percent of Muslims in India are excluded from banking services, as compared with0 percent of non-Muslims. Beyond the Muslim population, identifying potentially new microcredit products will add tohe variety of the available products, which could enhance take-up rates of microcredit, as stressed by Karlan and Morduch2009) above.

. Models

The main question of this research is whether using microcredit products that are compatible with Islamic law (partic-larly PLS contracts) will increase the rate of default compared with interest based contracts. PLS contracts, which adopt
rofit sharing and joint venture mechanisms, are especially prone to the problem of costly state verification; the borroweran observe the project’s return at no cost, but it is costly for the lender to observe (Gale and Hellwig, 1985).
To compare these different contracts theoretically, we constructed game-theoretic models with differing degrees of riskharing as stipulated by different microcredit contracts. The games are one-shot, played between a lender and a borrower.


Fig. 1. Interest loan.

The lender has the opportunity to make a loan of size L to the borrower, who invests the loan in a productive project. Theproject has two states of nature: one is successful with probability p, in which it returns ˛L (where the project’s multiplier

> 1); and the other one is failure, where it pays nothing back. The borrower observes the states of nature at no cost, then shedecides whether to repay the loan according to its terms (comply) or not.3 In the last stage (in some treatment conditions),the lender can follow up (Wydick, 2008). In the interest based treatment, he can do so by forcing collection, which is costly(equivalent to declaring bankruptcy in Gale and Hellwig, 1985). In the PLS treatments, the lender can verify the state of natureby auditing the project’s returns ex post. Both acts of costly verification (forcing collection and auditing) are probabilisticwith m probability of success and v cost (v = ıL, where 0 < ı < 1). It is worth noting that we assume that verification cost vdepends only on the size of the loan L, whilst Cason et al. (2008), for instance, assume that the cost of monitoring dependson the probability of a successful monitoring.4 We also assume that the probability (1 − m) includes bankruptcy (inabilityof the borrower to repay) in addition to the lender’s failure to force the collection of the loan (in case of interest loans) orverify the real outcome of the project (in case of PLS).

Below, we describe the models for each of our three types of finance. The extensive form representation of the sequentialgames for the interest loan model is shown in Fig. 1; the profit sharing (mudaraba) model is in Fig. 2; and the joint venturefinance (musharaka) model is in Fig. 3. The lender starts with L loan that he can choose to lend to the borrower in time t for
some agreed upon interest at rate i (in the interest loan model) or share s of the project’s returns (in the PLS models). Thecalculations of i and s depend on the lender’s required rate of return R (his reservation price or opportunity cost of capital),as will be shown below.
3 For simplicity, we control for adverse selection (the borrower type) and moral hazard (the riskiness of the project chosen) to focus on the costlyverification problem.

4 As Cason et al. (2008) mentions, monitoring can work in different ways in practice. However, since we are concerned with forcing collection/auditing,not monitoring per se, we assume that the higher the stakes are, the higher the cost the bank is willing to pay in order to retrieve its loan.


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Fig. 2. Profit sharing (P-S).

The borrower can invest L loan in a risky project that yields ˛L in time t + 1 with probability p or zero otherwise. Thus,here are two states of nature that can only be observed at no cost by the borrower. The borrower then chooses to pay backhe loan plus interest i (in case of interest based) or share s (in case of PLS) at nodes (3) and (4) of the extensive form. Wealibrate all of our models using a myopic lender (Stiglitz, 1990; Wydick, 2008) and assuming (naively) that borrowers willepay their loans when their projects are a success, and not otherwise. The lender only knows if he is paid or not at nodes (5)nd (6), but does not know the true state of nature. The game proceeds similarly through the following three models withome variations.

.1. Interest contract

This debt contract requires that the borrower repays (1 + i)L regardless of the state of nature. The left branch of the game’sxtensive form in Fig. 1 shows the good state of nature, when the project returns ˛L with probability p, whilst the rightranch shows the bad state of nature when the project returns zero. The lender calculates his interest rate i as follows:

(1 + R)L = p(1 + i)L

i = 1 − p + R

p

Fig. 1 shows the extensive form of the complete game of a model with costly verification. On the left branch (good statef nature), the borrower decides in node (3) at t + 1, after learning the real outcome of the project, whether she repays or
efaults on the loan. In the no-enforcement condition, the game ends here. In the enforcement or enforcement with penaltyonditions, the lender can attempt to force collection if the loan is not repaid. The lender succeeds in forcing collection withrobability m at cost v, but at no charge for the borrower.5 In this case, the borrower’s payoff is ( − 1 − i)L if collection is
5 The lender has no incentive to force collection if the loan is repaid, of course.


Fig. 3. Joint venture (JV).

successful and ˛L if collection is unsuccessful. The lender gets (1 + i)L − v for successful collections/repayment of the loan,while he gets (−L − v) for unsuccessful collection with no loan repayment.

On the right branch of the tree (bad state of nature), the borrower decides, at node (4), whether to pay or default. In theno-enforcement condition, the game ends here. In the other conditions, the lender chooses to force collection or not (at costv and probability m for successful collection). The borrower’s payoff is −(1 + i)L, if she decides to pay back or if collectionwas successful when defaulting. She earns zero if defaulting when collection is not successful. The lender earns (1 + i)L − vfor repayment and collection, or (1 + i)L for repayment with no collection. He earns (−L − v) for unsuccessful collection withno loan repayment. In the enforcement condition, the lender bears the cost of verification v, while it is born by the borrowerin the enforcement with penalty condition.

The Bayesian Nash equilibrium is for the borrower to default in both the good and bad states of nature whenever m < 1, asassumed. Knowing this, the lender will force the collection of an unpaid loan whenever the expected returns when forcingcollection are higher than those without forcing collection:

EL(Default Default, Collect) > EL(Default Default, Don’t Collect),This is satisfied if:

m >pı

1 + p + R

This is a necessary condition for forcing repayment, but not sufficient for the lender to lend. The lender’s expected payoffsat node (5) should be greater than his expected payoffs when not lending (keeping his capital L). Therefore, he should lendand force collection whenever:

EL(Default Default, Collect) > L

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Then, the equilibrium is: (Default, Default, Collect), if m ≥ (p(2 + ı))/1 + p + R and m < 1 (when p < (1 + R)/1 + ı).Otherwise, the equilibrium is: (Default, Default, Don’t Lend), when: m < (p(2 + ı))/1 + p + R. This means that the probability

f successful (costly) collection should be high enough for the lending to be feasible.We will choose parameters to induce an equilibrium of (Default Default, Collect) in this model, and parallel parameters

n the other two models.

.2. Profit sharing contract

According to the profit sharing contract, the borrower must repay the loan only if her project succeeds. However, similaro the interest based contract, only the borrower knows the outcome of her project. The borrower self-reports the project’sutcome (thus determining her repayment requirements).

If the borrower reports that her project has failed and thus does not repay, the lender can choose to audit (or verify) theutcome of the project. The lender succeeds in its audit with probability (m) and pays auditing (verification) fee (v). If theudit is successful and the borrower has incorrectly reported the outcome of the project, she must repay the loan (possiblyith a penalty v in the enforcement with penalty condition).

The lender calculates his share in the project’s outcome (s) as follows:

(1 + R)L = psf (L)

Assuming that the investment project is divisible and the loan’s production function f(L) is linear (for simplicity), we cane-write it as follows:

f (L) = ˛L

⇒ (1 + R)L = ps˛L

⇒ s = 1 + R

p˛, s < 1

⇒ 1 + R

p˛< 1

So, for a profit sharing loan to be feasible, the probability of the project’s success should be large enough (p > (1 + R)/˛).Both the lender and the borrower face the game in Fig. 2.The extensive form of the game for the profit sharing contract has only a few differences from the one for the interest

ontract. In the good state of nature and when the borrower repays, the lender receives his share in the project’s outcome˛L and leaves the rest (1 − s)˛L to the borrower.

In the bad state of nature, the situation is different, as the lender will always get (−L − v) if the borrower does notay, whether auditing is successful or not, which is the distinguishing feature of the profit sharing contract. In this case, theorrower (if she chooses not to repay) will earn zero (as opposed to the loss of −(1 + i)L in the interest contract). The Bayesianash equilibrium for this game (here, assuming m < 1/p; since p < 1 by definition, this reduces to m < 1), is for the borrower

o default whether her project succeeds or fails. Knowing that the borrower will Default, the lender will Audit (at node “6”)f:

EL(Default Default, Audit) > EL(Default Default, Don’t Lend),

m ≥ 2 + ı

1 + p + R

Thus the lender will audit as long as: m > (2 + ı)/1 + p + R and m ≤ 1.As mentioned earlier, we will choose parameters to induce this equilibrium of (Default Default, Audit) in this model.

.3. Joint venture contract

This model is the same as profit sharing, except that the borrower contributes capital (k) to the investment alongside theender’s capital (l). The lender’s share in the project’s outcome (s) is calculated as follows:

(1 + R)l = ps˛(l + k), where : l + k = L

⇒ s = l(1 + R)p˛L

for s < 1 :p˛ l
⇒
1 + R<

L, where : l = �L, k = (1 − �)L, 0 < � < 1

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The extensive form of the game for the joint venture model (Fig. 3) looks exactly the same as the one for the profit sharingmodel, except for replacing the lender’s capital L in profit sharing with both the lender’s and borrower’s (entrepreneur)capitals (l + k). The game proceeds in the same way as in profit sharing in the good state of nature, with the lender gettinghis share of the project’s outcome s (l + k) when the borrower repays, while losing his capital (−l) if the borrower defaults.In the bad state of nature, the lender loses his capital (l) and the borrower loses hers (k).

Under similar assumptions as before, the equilibrium of this model is exactly the same as that of the profit sharingcontract (Default Default, Audit); the borrower will always Default whenever m < 1/p (which means m < 1, because p < 1) andthe lender will only Audit (at node “6”) if: m ≥ (2 + ı)/1 + p + R.

In summary, our three models are parameterized to induce the lender to loan, the borrower to default and the lender toenforce compliance (either via forced collection or an audit) under all three contracts.

3.4. Predictions

Our experimental parameters are chosen so as to generate the aforementioned equilibria in these three games. Theseequilibrium predictions thus suggest that behavior in the three models will be identical; the borrower will default in thegood state, default in the bad state and the lender will enforce costly verification.

Behaviorally, however, we may see very different outcomes between our contracts and our enforcement settings. Forexample, previous work has shown that the inclusion of the threat of verification can induce honesty (Townsend, 1979).This would suggest that compliance will be the highest in the enforcement with penalty conditions, somewhat less in theenforcement conditions, and the lowest in the no-enforcement conditions.

Perhaps more interestingly, we might imagine differences in compliance rates between the three contracts. Some wouldargue that compliance rates will be higher in the interest contract than in the PLS contracts. After all, any incentive todeclare a state of nature different than the true one will be stronger under contracts that are state-contingent (such as PLScontracts) rather than under interest contracts. Familiarity with debt contracts (in day to day life) might further enhance theparticipants’ compliance with interest loan contracts. Similarly, PLS contracts involve more equal power divisions betweenthe borrower and the lender, while interest contracts involve more power to the lender than the borrower. The typical storyis that if the lender is more powerful (as in interest based contracts), compliance will be increased. These factors predicthigher compliance rates in interest contracts than in PLS contracts.

In contrast, we might imagine psychological forces which would lead to higher levels of compliance with PLS contracts. Asmentioned above, PLS contracts equalize the power between the lender and the borrower, and borrowers could respond tothis equalized power with increase compliance. This hypothesis is analogous to models of gift exchange in labor economics(which Akerlof, 1982 used to explain efficiency wages), and which are here being applied to credit markets.

Beyond the power equalization, PLS contracts might be seen as more equitable than interest based contracts, becausein the negative state of nature the borrower does not have to repay the loan and the lender shares in the downside riskwith the borrower. Borrowers might feel more obligated to comply with the terms of this more “fair” contract, than theywould feel to comply with the terms of a more “unfair” contract. We note that this notion is not drawing on the literatureof other-regarding preferences (e.g. altruism, or inequality/inequity aversion) where individuals are concerned about therelative earnings of the parties involved. In any microcredit situation (ours included), the income/wealth of the borrower andlender are likely to be extremely dissimilar, and paying back a microloan will increase inequality, not decrease it. Instead, thisidea draws on the concept of living up to one’s obligations, or moral/ethical actions which apply regardless of the identityof one’s partners. These two possibilities (equalized power and obligation) predict that compliance in PLS contracts will behigher than that in interest based contracts.

4. Experimental design and parameters

Our objective is to compare compliance rates in the nine treatments which change the degree of risk sharing (threecontracts) and costly state verification (three enforcement conditions). The experiment’s design thus abstracts away fromadverse selection or moral hazard problems; all participants are assumed to be equally qualified for a loan and invest theproceeds in the same risky project.

The primary dependent variable of interest is compliance, whether the participant complied with the terms of the contract(paying back principal and interest in the interest based contract, paying back a share of profits if profits are earned in theprofit sharing and joint venture contracts).

4.1. Experimental design

We examine each of the three contracts under three conditions. In the no-enforcement condition, participants chooseto whether comply with the terms of the contract or not, but there are no penalties for noncompliance. These conditionstruncate the game-trees in Figs. 1–3 after nodes (3) and (4). In the enforcement condition, the lender enforces the contract.For the interest-loan contract when borrowers do not comply, lenders attempt to force collection, which succeeds only


Table 1Experimental treatments.

Degree of costly state verification (conditions)

No-enforcement Enforcement Enforcement with penalty

Financial contractInterest loan T11 T12 T13

Profit sharing T21 T22 T23

Joint venture T31 T32 T33

Table 2Possible orders (contracts).

Number of Individuals

1 Interest Profit-sharing Joint venture 72 Interest Joint venture Profit-sharing 73 Profit-sharing Interest Joint venture 74 Joint venture Interest Profit-sharing 11

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5 Profit-sharing Joint venture Interest 56 Joint venture Profit-sharing Interest 7

robabilistically.6 For the profit sharing and joint venture contracts when borrowers report that their project has failedand thus no repayment is necessary), lenders audit the report, which yields an accurate picture of the success or failuref the project probabilistically. If the borrower is discovered misrepresenting the success of the project they are forced toomply with the contract. As in Figs. 1–3, however, these enforcements are costly and the cost is borne by the lender. In thenforcement with penalty condition, borrowers who are discovered misrepresenting the success of the project are forced tooth comply with the contract and to pay the costs of enforcement; those costs are loaded into the terms of the repayment.he experimental design thus involves nine treatments; three contract types (interest, profit sharing, joint venture) andhree conditions (no-enforcement, enforcement, enforcement with penalty). We use a 3 × 3 experimental design, as shown inable 1.

We took a number of steps to maximize the number of independent observations we would get. The first design decisionas to automate the lenders. Participants in our experiment all played the role of borrowers, received loans, invested the

oan in projects (and learned about their outcomes), and decided whether to repay their loans or not. The decisions of theenders, while potentially interesting, were not the focus of our study.

As a result, when borrowers paid back loans, they were paying back to the experimenter, rather than to another participantn the room. We believe that this design decision might have had the impact of lowering compliance rates in all of ourreatments. However, there is no reason to think that it affects one contract or condition differently than another, thusreserving the differences among treatments.

Playing against the experimenter may decrease the participants’ willingness to comply in all treatments if compliances motivated by reciprocation or avoiding social disapproval. Fehr and Falk (2002) cite these two factors as strong socialncentives in contracts (see also Ferraro et al., 2003). However, we note that we have not eliminated the human factorompletely from their decision-making, because participants know that they are taking the laboratory’s money, whichelong to human beings.

A second design decision was to use a within-subject design. Each participant faced all nine treatments. This again max-mized the number of observations we got from each session, and allowed us to control for individual-specific effects withppropriate statistical tests (e.g. paired t-tests). However, we were concerned about order effects. We counterbalanced therder in which each participant saw the three contractual types. Thus individuals were randomly assigned to see one of sixotential orders listed in Table 2.

Although each participant faced the types of contracts in a different order, the order of treatments within the contractas always from least complex to most complex: no-enforcement, enforcement, enforcement with penalty. Thus, for example,

participant in order 1, the first row of Table 2 saw the contracts in the following order

nterest no-enforcementnterest enforcementnterest enforcement with penaltyrofit sharing no-enforcementrofit sharing enforcementrofit sharing enforcement with penalty
oint venture no-enforcementoint venture enforcementoint venture enforcement with penalty
6 As mentioned above, the reader might think of m as including the likelihood that the borrowers are able to repay.


4.2. Experimental parameters

Since we are interested in the frequency with which individuals will engage in misrepresenting the project’s outcome,we chose parameters to maximize the number of times we would be able to observe this behavior. This entailed settingthe probability of a successful project high (90 percent) in order to ensure that participants had sufficient opportunities tocomply with their contracts (repay the loan). The outcome for each project was independently drawn for each participantand for each project. We set the following parameters to be consistent across the nine treatments, and to be consistent withexisting investment opportunities.

opportunity cost of capital (R) = .05 (the cost of capital, or discount rate)

investment’s multiplier (˛) = 2 (thus successful projects doubled the investment)

cost of forcing collection/auditing (ı) = .05 of the loan size

We sought three further conditions for setting parameters. First, we set parameters to equalize the earnings of theborrower across all nine treatments when the project is successful (90 percent of the time) and she complies with the termsof the contract. Thus,Interest payoffs = Profit sharing payoffs = Joint venture payoffs(˛ − 1 − i)L = (1 − s)˛L ≈ (1 − s) ˛(l + k)

This condition determined the loan size for the interest and profit sharing contracts of (L) = 1000, but a different loansize for the joint venture treatments. In joint venture contracts, the lender provides (l) = 330, while participants contribute(k) = 340 out of their own endowments. For clearer understanding of the decisions facing the participants, we show theexperimental parameters we used in the extensive forms of the three models in Figs. 1–3.

Second, we wanted to ensure that when the borrower reported a failure or defaulted on her contract, the lender wasindifferent between enforcing the contract and not. This ensured that the borrower’s behavior in the different treatmentswould not be influenced by differences in the expectation of the lender’s actions. This generated an 80 percent success rateof enforcing collection for the interest contracts, and a 90 percent success rate of auditing the project’s outcome for theprofit sharing and joint venture contracts. Finally, we chose parameters to satisfy the zero-profit condition for the lendermentioned in the theoretical section above. Alternatively, we could have equalized success rates in both standard debtcontracts and the PLS contracts. However, this would have varied the borrower’s payoffs when successful and complyingbetween both types of contract. The motivation for complying then, can be confounded by the different payoffs, not by thecontract itself, which is what we target.

4.3. Experimental implementation

The experiment was run in late October and early November 2009 in the CBEES (Center for Behavioral and ExperimentalEconomic Science) lab at UT Dallas. 44 participants completed the experiment, making one decision in each of the ninetreatments. Each subject was endowed with 10,000 points at the beginning of the session, and earned (or lost) points basedon the outcomes of the risky project, their decisions about compliance, and the probabilistic enforcement actions of theirlender. At the end of the experimental session, the participants’ point balance was converted into dollars at the rate of 1500points = $1. Each participant received a $5 participation fee, plus her/his earnings in the experiment. Experimental sessionslasted an average of 45 min, and average earnings were $18 (including the show-up fee).

Table 3 shows the demographic breakdown of our subjects. Demographics will be included as controls in the analysesbelow, although our within-subject design also allows participants to serve as their own controls (by comparing behaviorfrom the same person across treatments).

Participants arrived in the lab, and signed in at the check-in desk. When we were ready to begin, they were randomlyassigned to a station number, and led into the lab. They took their seats at their station, and were asked to turn off cellphones and other electronic devices.

The experiment was programmed in zTree (Fischbacher, 2007). All instructions were given on-screen and are availablefrom the authors upon request. Participants worked through the instructions at their own pace.

All parameters in the experiment were common knowledge. Participants could take as much time (or as little) as theywished to complete each task. After they had made all nine decisions, they were reminded of their total earnings, and weretaken to a post-experimental questionnaire. The questionnaire included demographic questions, as well as questions onreligiosity and other attitudes.

After they had completed the questionnaire, participants were asked to please wait quietly. When the group had finished,each participant was individually called (by station number) to the check-in desk to be paid privately and dismissed.

5. Experimental results

Our primary variable of interest is compliance rates; the rate at which individuals comply with the terms of their con-tract. Recall that our experimental parameters are chosen so that individuals have no financial incentive to comply. Thuscompliance represents a voluntary costly action.


Table 3Demographic details of participants.

SexMale 57%Female 43%

Ethnicity

White 39%Hispanic 5%Asian 52%Other 2%Don’t reveal 2%

Class

Freshman 0%Sophomore 14%Junior 11%Senior 36%Graduate 36%Not student 2%

Religion

Agnostic/atheist/no religion 24%Hindu 33%Catholic 3%Protestant 18%

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Don’t reveal 12%Other 9%

We begin by comparing compliance rates across the treatments using paired t-tests.Result 1: Compliance rates vary significantly by contract (interest, profit sharing, joint venture), at least in some enforce-

ent conditions.Fig. 4 depicts the proportion of compliance decisions in the nine treatments. A paired t-test between proportions demon-

trates that compliance rates are significantly higher in joint venture contracts than in interest contracts in the no-enforcementnd enforcement conditions. Compliance rates are marginally higher in profit sharing contracts than in interest contracts inhe no-enforcement condition and significantly higher in the enforcement condition. These results are consistent with theogic of increased obligation for compliance in PLS conditions overall.

Compliance rates across contracts are directionally similar but not statistically different in the enforcement with penaltyondition. Interestingly, this is not due to a decrease in compliance rates in PLS contracts, but an increase in complianceates in interest contracts. Compared with the baseline (interest contract, no enforcement), our conclusion is that a lender
an increase compliance rates in two ways. He can increase them by adding an enforcement with a penalty to his interestased contract. Or he can increase them (as we will see later, much more cheaply) by using a profit sharing or joint ventureontract instead.
Fig. 4. Compliance rates. +p < .1 and *p < .05 (difference when compared with interest-loan contract).


Table 4Logit regressions of compliance (clustered standard errors).

Including order effects Including demographics Including religiosity

Profit-sharing 0.716** 0.734** 0.869** 0.888**

(0.255) (0.261) (0.303) (0.310)Joint venture 0.840** 0.861** 1.019** 1.042**

(0.282) (0.292) (0.338) (0.346)Enforcement 0.135 0.138 0.164 0.168

(0.210) (0.216) (0.255) (0.261)Enforcement with penalty 0.298 0.306 0.362 0.370

(0.226) (0.232) (0.276) (0.281)PLS contract first 0.751 0.924*** 0.889**

(0.424) (0.280) (0.293)Female 1.189*** 1.026**

(0.361) (0.351)Hispanic 0.686 0.412

(1.010) (0.885)Asian 0.946** 0.623

(0.363) (0.385)Other ethnicity −0.689 −0.572

(0.388) (0.392)Agnostic/atheist −0.439 0.335

(0.666) (0.679)Hindu −0.324 −0.0698

(0.324) (0.338)Catholic 0.756 0.966*

(0.443) (0.382)Religion not revealed 1.601*** 2.173***

(0.480) (0.530)Other religion 1.214** 0.818

(0.429) (0.615)Attend religious service 0.348*

(0.150)Constant −1.167*** −1.713*** −3.218*** −3.762***

(0.292) (0.468) (0.560) (0.555)Observations 396 396 387a 387a

Pseudo R-squared 0.025 0.045 0.139 0.157

Standard errors in parentheses.a We dropped observations from nine individuals who did not reveal their ethnicity.*
p < 0.05.
** p < 0.01.*** p < 0.001.

Result 2: Compliance rates do not vary significantly by enforcement condition (no-enforcement, enforcement, enforce-ment with penalty).

Comparing compliance rates within contract across enforcement conditions using paired t-tests yields directional butnot statistically significant results. Compliance in the joint venture contract remains constant (45 percent) regardless ofcondition. While we see some increase in compliance in the profit sharing contract (36 percent in no-enforcement to 45percent in the other two enforcement conditions), these changes are not statistically significant. We similarly see increasesin compliance rate in interest contracts as enforcement conditions change (23 percent in no-enforcement and enforcement,34 percent in enforcement with penalty), but these changes are themselves not statistically significant.

5.1. Regression analysis

Similar but more statistically significant results are obtained using panel data regression techniques. We begin withlogit regressions, where the dependent variable is 1 if the individual complies with their contract, and 0 otherwise. We useclustered standard errors at the individual level to account for the fact that we have multiple observations from the sameindividual. In addition to treatment, we include controls for order effects, demographics, and religiosity. The results areshown in Table 4.

This analysis supports Results 1 and 2 described above. Coefficients on profit sharing and joint venture contracts areconsistently and significantly positive, demonstrating that even in the presence of controls, compliance rates are higher inthese contracts than in the interest contract. However, there are no significant differences between the profit sharing and
the joint venture coefficients, consistent with the results above.
We find directional but not statistically significant effects of condition. Compliance rates are higher in enforcement andenforcement with penalty conditions than in no-enforcement, but those differences are not statistically significant (neitherare the differences between enforcement and enforcement with penalty).

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These results are robust to controlling for the order in which participants saw the three types of contracts, which reassuress that order effects are not causing our results.

Interestingly, the order effect is itself significant. In particular, compliance rates are highest when starting with a PLS con-ract (profit sharing or joint venture) rather than an interest contract. We believe that these spillover effects are themselvesupportive of the obligation hypothesis, and of the idea of implementing these types of loans in practice. Our results thusuggest that compliance in PLS contracts will not only be higher than compliance in interest contracts, but that participationn a PLS contract may increase compliance in a subsequent interest contract. We want to be careful in interpreting this resultas this was not what our experiment was designed to show), but believe that it deserves further study.

Results 1 and 2 are also robust when controlling for individual characteristics although, again, some of these characteristicsre themselves significant. For example, women are significantly more likely to comply with the terms of their contracthan men, consistent with previous literature (and current practice) in microfinance of focusing on women as recipients of

icroloans (Armendariz and Morduch, 2007). While the results on religion are somewhat noisy (due to the low numbers ofndividuals self-reporting various religions), the coefficient on religiosity is positive and statistically significant. Participants

ho attend religious services are significantly more likely to comply than those who do not, as are those individuals whoo not reveal their religion.

A second set of regressions provides a robustness check for our result. We use logit regressions with fixed effects forndividual, order or treatment. The results are presented in Appendix B and are the same as those from previous analyses;ignificant increases in compliance rates for profit sharing and joint venture contracts over interest contracts, directional butnsignificant differences between profit sharing and joint venture contracts, no significant differences between enforcementreatments, higher compliance rates for women and those who attend religious services.

.2. Within-subject tests

Our analysis up until this point has not leveraged the additional power available due to our within-subject experimentalesign. In this section we categorize individuals based on their compliance decisions in the different treatments.

Some participants always comply (7 percent) and others never comply (also 7 percent). The complying 7 percent can beescribed as those who have a certain image of themselves as fair or law-abiding, as per Akerlof and Kranton (2005, 2010).he never-complying 7 percent may also have formed a certain identity. However, the vast majority of our participants (86ercent) complied in some settings, but not in others. We analyze the compliance behavior of these individuals, to identifyystematic changes. We compare the distributions of compliance in the various treatments against the no-enforcementypothesis of random actions using a t-test of proportions. Results are reported in Fig. 5, panels a, b and c.7

Fig. 5a shows the percentage of individuals who change their compliance behavior between the interest and profit sharingontracts. In the no-enforcement treatment, 21 percent of individuals comply with the profit sharing contract but not thenterest contract, while 7 percent of individuals comply with the interest contract but not the profit sharing contract. Thisattern is marginally different than what would be expected if individuals were making their decision randomly (p = .0744).e see a similar but statistically significant difference in the enforcement treatment (p = .0049), but no significant effect in

he enforcement with penalty treatment (p = .1928).We see the same pattern of results when comparing interest and joint venture contracts in Fig. 5b. In the no-enforcement

reatment, 30 percent of individuals comply in joint venture but not in interest contracts, while only 7 percent of individualsomply in interest contracts but not in joint venture contracts. These are again significantly different than what woulde expected with random compliance patterns (p = .0055). Similarly, significant differences are seen in the enforcementreatment (p = .0098), with directional but insignificant differences in the enforcement with penalty treatment (p = .2092).

Finally, in Fig. 5c we see individuals are no more likely to comply in profit sharing contracts and not in joint ventureontracts than vice versa (p = .2770 in no-enforcement, p = 1.000 in enforcement, p = 1.000 in enforcement with penalty).

In summary, our analyses in these two sections demonstrate two main findings. Nonparametrics, panel regressions andithin-subject analyses show that individuals are more likely to comply in PLS contracts (joint venture and profit sharing)

han in interest contracts, especially in our no-enforcement and enforcement treatments. In addition, seeing a PLS contractrst increases compliance rates in subsequent non-PLS contracts.

.3. Lender’s earnings

A final analysis addresses a different question; which contracts should a lender choose to offer? Although the experimentalarameters were chosen to induce zero profits for lenders when borrowers repay their loans when their project succeedsnd default when it fails, behaviorally borrowers often deviated from this strategy. Given the actual behavior of borrowers,ow much profit did lenders earn in the various conditions?8

7 Note that the data in Fig. 5 is a subset of the data in Fig. 4. Fig. 4 includes all our experimental participants. Fig. 5 includes only those whose behaviorhanged as the treatment changed.

8 As a reminder, none of our experimental participants acted as lenders in the experiments. This analysis calculates how much a single lender wouldave earned had they been facing all our experimental borrowers as a portfolio of loans.


Fig. 5. Percentage of individuals with compliance patterns (+p < .1 and *p < .05).


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Fig. 6. Lender’s return on investment by treatment.

For this analysis, we calculate the lender’s return on investment (ROI) (percent of borrower’s repayment amount minusuditing or collection costs/loan principal). These returns are shown in Fig. 6.

As might be expected, lender’s earnings are primarily driven by their opportunity to (probabilistically) collect on aefaulted loan. Thus earnings are higher in the enforcement and the enforcement with penalty treatments than in the no-nforcement treatment, although there are no significant differences between the enforcement and enforcement with penaltyreatments. Earnings are not significantly different between the three contracts, either within each treatment or when pooledcross all treatments.

In summary, we find that compliance rates are significantly higher in profit sharing and joint venture contracts (Result 1).e find directional but not significant differences in compliance rates between the no-enforcement, enforcement and enforce-ent with penalty treatments (Result 2), although lender’s earnings are significantly higher when they can probabilistically

orce collection (enforcement and enforcement with penalty) than when they cannot (no-enforcement).

. Conclusions

This paper provides an experimental test of Islamic-compliant microfinance contracts, which involve profit and lossharing (PLS). While there have been scattered endeavors to establish Islamic microfinance projects in the field, no previousesearch has experimentally compared the performance of Islamic-compliant loans with traditional interest based loans.

In our setting, the lender gives money to an individual borrower under different contractual agreements (interest, profitharing and joint venture). The borrower invests it in a risky project, which doubles the investment with a 90 percent chance.he outcome of the investment is known only to the borrower, who decides whether to comply with the terms of the loan,r not. In the no-enforcement condition, this is the end of the game. In the enforcement condition, the lender can expendesources to force collection (of the interest loan) or audit the outcome (of the other loans). Collection/auditing is successfulnly probabilistically, in which case the borrower is forced to comply with the loan terms. In the enforcement with penaltyreatment, the borrower pays the cost of the state verification when she does not comply with the loan terms. Our settinghus controls for adverse selection and instead focuses on costly state verification.

We choose parameters for these models so that borrowers have an incentive to default, regardless of contract or condition.ur measure of interest, then, is the proportion of individuals who voluntarily comply with the terms of the contract.

We find that compliance is significantly higher in the PLS contracts than in the interest based contract. Under the no-nforcement condition, compliance in the joint venture contract is significantly higher than in the interest based contract.nder the enforcement condition, both profit sharing and joint venture contracts have significantly higher compliance

ates than the interest based contract. Under the enforcement with penalty condition there are no significant differencesetween the contracts. We also find that women comply more than men; this agrees with common wisdom and practice inicrofinance. Further, religiosity increases compliance rates in general.We believe that the improved performance of profit sharing and joint venture contracts over interest contracts has to do

ith their perceived fairness and the resulting obligation which borrowers feel in response. In particular, these contracts doot require individuals to repay their loans when their projects fail. As a result, participants feel more obligated to complyith the terms of the contract when their projects succeed. This condition of risk-sharing characterizes many PLS contracts

including those seen in sharecropping or franchising arrangements, or in labor markets with gift-exchange), not simply the
nes we tested here.
Notions of altruism, inequality or inequity aversion or other social preferences do not capture the sense of obligationhat we believe is being generated here. After all, in our experiment the lender is a computer program (although behind thatrogram are the experimenters themselves). In the field, lenders are likely to be significantly more wealthy than borrowers,


making these other-regarding social preferences less likely to influence behavior. We think of this effect as being moreethical than social.

Interestingly, we find that individuals who experience PLS contracts first exhibit significantly more compliance through-out our entire experiment. Although our experiment was not designed to investigate this result, it suggests that spillovereffects from PLS contracts might make interest based contracts even more effective (by increasing compliance rates). Futurework should explicitly explore this possibility.

All research has limitations, and this paper is no exception. Our experimental economics methodology can provide a usefultestbed for contracts like these, but a true test will need to follow in the field. Our participants are students, not farmers ormicroentrepreneurs, and while we believe that individual reactions to different contracts are likely to be universal, this is anempirical question that can be answered only with data. Udry (1990)’s findings, that interest contracts in Northern Nigeriawere edited to incorporate PLS, suggests that in some credit markets risk-sharing may be normative and may indicate thateffects for a Muslim population would be larger than effects found in the U.S. with university students.

While the experiment involved small-stake loans for real money, the project’s outcome was randomly determined (withinfive seconds) with no input from the borrowers. In contrast, in the field, the likelihood of success of a project depends (atleast in part) on the effort individuals expend. Now that these contracts have performed well in the lab, future work in thefield will provide a stronger test of their suitability.

Additionally, our experiment abstracted away from issues of moral hazard (choosing a more risky project) and adverseselection (the type of lender) to focus on the problem of costly state verification. Clearly, however, these problems are alsopresent in the field, and future research should investigate the impact of contract type and enforcement condition in thesesettings.

The results of this research can be useful in many domains. Within Islamic banking, practitioners have minimized theiruse of profit sharing and joint venture contracts due to concerns about the increased costs for verifying the state of nature.This research suggests that costly state verification may not be as serious a problem as was feared; we find that even withno enforcement, 45 percent of borrowers complied with the terms of their joint venture contract. Furthermore, the level ofthe incentive to cheat in profit sharing and joint venture contracts is comparable to (and perhaps somewhat less than) thelevel in interest contracts. This research thus opens the door for Islamic banking to reconsider the use of these contracts.

In microfinance and microcredit, our results suggest that profit sharing and joint venture contracts might be useful toolsfor both the Muslim and the non-Muslim populations. Among Muslims, it can increase the pool of potential borrowers. Amongnon-Muslims, our results suggest that these contracts may yield greater compliance rates than the contracts currently in use.We anticipate a similar effect in the Muslim population as well. More generally, Hoff and Stiglitz (1990) suggest problemscaused by asymmetric information in the U.S. are resolved using indirect mechanisms. Our results suggest that risk-sharingproperties of a financial contract may be one indirect mechanism to consider.

We hope that this research will encourage microfinance scholars and practitioners to consider new and innovativecontractual designs, which will help de-constraining access to credit before the limited-income consumer. Microfinance hasthe potential to significantly alleviate poverty, but to accomplish this goal the field needs to cater for different tastes anddifferent levels of poverty. Therefore, varying the choices offered and compatibility with different social norms will lead tohigher take-up rates in microfinance. Exploring and testing alternative contractual types, in the lab and in the field, can helpin this move.

Appendix A. Principles and instruments of Islamic finance

To understand Islamic microfinance, we need some understanding of the principles on which it is based. Four principlesare derived from Shari’a (Islamic jurisprudence) and are seen by most scholars to form the core of modern Islamic finance.

The first principle, which is the most famous and perhaps the most controversial from a financial point of view, is theprohibition of interest. The accuracy of the term “interest” is questionable in this context, since the Arabic term “riba” (ribbitin Hebrew) is usually translated as usury, not interest. However, riba does not refer to usury as in modern economics, chargingexcessive interest rates. The prohibition of riba allows for administrative expenses accrued by financial intermediaries andalso for compensation for inflation. It does not allow for profits from the sole activity of lending money (a piece of moneycannot beget another piece, according to Aristotle) (Iqbal and Mirakhor, 2007). Because the prohibition of riba does allowfor some interest payments (inflation and administrative expenses), prohibition of riba is a more accurate description thanprohibition of interest.

The prohibition of riba is related to other principles of Islamic finance. The second principle is risk-sharing, which meansthat lenders share in the profits and losses of the businesses they finance. This requires determining the profits ex post, whichis not necessary in an interest-based loan. Prohibiting riba and promoting risk-sharing make the suppliers of funds investorsinstead of creditors. Sharing of profits is justified because each party shares in the responsibility of the economic activity.The lender is entitled to the profits only because they bear the risk in case of loss (Iqbal and Mirakhor, 2007).

The third principle involves calculations of the time-value of money and sheds light on the wisdom behind banning
riba. Money, according to Sharia’a rules, is only a medium of exchange, as long as it is not invested in productive activities.Thus, money has no time-value unless it is used in a productive activity. This principle draws a clear distinction betweenusing money for investment and using it for mere lending/consumption (Iqbal and Mirakhor, 2007). When money is usedfor investment it acquires time-value because its usage yields a financial reward. In this situation, the person who provides

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oney for investments has the right to share this reward, whether it is positive (profits) or negative (losses), consistent withhe principle of risk-sharing. On the other hand, when money is used to finance consumption or other activities that yield nonancial reward, it has no time-value and should be considered as an act of charity. Thus, Shari’a recognizes the time-valuef money only when it acts as real capital, but not when it is potential capital (Iqbal, 1997).

With regards to investments, the prohibition of riba follows the principle of the timevalue of money. The ban of riba isased on the fact that interest is fixed and earned whether the productive purpose to which it is put is successful or not.his makes it a certain profit while the financial outcome (profit or loss) from investing the money is uncertain. Earning aertain reward as a compensation for the uncertain is unjustifiable both morally and economically.

The forth principle is the prohibition of Gharar. Gharar is, as riba, an Arabic term that has no exact English translation.t simply means taking excessive risks and speculative behavior such as gambling. Literally, gharar means uncertainty ormbiguity created by the lack of information or control in an economic transaction. A classic example of gharar is sellingsh that are not yet caught or an unborn calf in its mother’s womb. Gharar includes any uncertainty related to the quantity,uality, recoverability or existence of the content of the exchange contract (El-Gamal, 2006).

Prohibition of gharar leads to avoiding transactions involving pure speculation. Consequently, trading in gharar-relatedontracts is prohibited. However, many scholars find that writing certain types of insurance is not characterized by excessivencertainty (or gharar) because the process itself transforms uncertainty to controlled risk.

A number of financial instruments have been devised to adapt the principles of Islamic finance to modern banking. Theollowing three instruments are perhaps the most relevant to thetopic of microfinance. These instruments can be classifiednto equity finance (PLS) and debt finance.

Equity finance includes profit-sharing agreements, “mudarabah”, which is similar to sharecropping. According to thisrrangement, the financier provides funds to the entrepreneur to be invested in an economic activity (usually short toedium term projects) for an agreed-upon share of the profit. If the project returns a profit, the profit is shared as agreed.

f the project incurs losses, the financier’s loses her capital and the entrepreneur loses his effort and time (El-Gamal, 2000).ne of the contracts we will develop and test will be a profit sharing (mudarabah) contract. A second popular PLS contract

nvolves equity participation (musharaka). Musharaka is a classic joint venture. This contract is a hybrid of partnership andudarabah. The entrepreneur and the investor contribute to the capital and managerial expertise in agreed upon amounts

nd they also agree on the share of the profits and losses. A second contract we will develop and test will be a joint venturemusharaka) contract.

Debt finance includes several contracts, such as murabaha (mark-up sale), ijara (leasing), salam (forward sale), istisna’commission to manufacture). The most widely used contract in the Islamic banking industry is the controversial murabahanance. The problem with this contract is its economic resemblance to an interest loan, which made it criticized by many

slamic scholars and also made it unpopular among the Muslim poor (El-Gamal, 2006; Obaidullah and Khan, 2008). This ishy this paper will only focus on the PLS contracts (mudaraba and musharaka), as they present an original variation to the

ypes of microfinance arrangements that are currently used.

ppendix B. Fixed effects Logit regressions of compliance

Individual Order Treatment

ComplyProfit-sharing 0.949** 0.834**

(0.310) (0.287)Joint venture 1.106*** 0.981***

(0.309) (0.287)Enforcement 0.177 0.158

(0.298) (0.281)Enforcement with penalty 0.389 0.350

(0.295) (0.280)Female 1.051*** 1.036***

(0.263) (0.261)Agnostic/atheist 1.015* 1.001*

(0.415) (0.412)Hindu 0.229 0.226

(0.314) (0.311)Catholic 0.895 0.885

(0.780) (0.773)Religion not revealed 2.208*** 2.181***

(0.491) (0.487)Other religion 0.702 0.688

(0.514) (0.511)Sorority 0.148 0.147

(0.273) (0.271)Attend religious service 0.423*** 0.418***

(0.110) (0.109)0.732*

(0.290)


Appendix B (Continued)

Individual Order Treatment

Observations 342 396 396Log lik. −137.9 −208.8 −203.0Chi-squared 17.20 59.36 68.31

Standard errors in parentheses.* p < 0.05.

** p < 0.01.*** p < 0.001.

Appendix C. Supplementary data

Supplementary data associated with this article can be found, in the online version, at http://dx.doi.org/10.1016/j.jebo.2012.08.009.

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