<i>Information Asymmetry and Trust: A Framework for Studying Microfinance in India</i>
Bibliographic record
Abstract
In recent times, microfinance has emerged as a major innovation in the rural financial marketplace. Microfinance largely addresses the issue of access to financial services. In trying to understand the innovation of microfinance and how it has proved to be effective, the author looks at certain design features of microfinance. He first starts by identifying the need for financial service institutions which is basically to bridge the gap between the need for financial services across time, geographies, and risk profiles. In providing services that bridge this gap, formal institutions have limited access to authentic information both in terms of transaction history and expected behaviour and, therefore, resort to seeking excessive information thereby adding to the transaction costs. The innovation in microfinance has been largely to bridge this gap through a series of trustbased surrogates that take the transaction-related risks to the people who have the information — the community through measures of social collateral. In this paper, the author attempts to examine the trajectory of institutional intermediation in the rural areas, particularly with the poor and how it has evolved over a period of time. It identifies a systematic breach of trust as one of the major problems with the institutional interventions in the area of providing financial services to the poor and argues that microfinance uses trust as an effective mechanism to address one of the issues of imperfect information in financial transactions. The paper also distinguishes between the different models of microfinance and identifies which of these models use trust in a positivist frame and as a coercive mechanism. The specific objectives of the paper are to: Superimpose the role of trust in various types of exchanges and see how it impacts the effectiveness of repeated transactions. While greater access to information fosters trust and thus helps social networks to reduce transaction costs, there could be limits to which exchanges could solely depend on networks and trust. Look at the frontiers where mutual trust cannot work as a surrogate for lower appraisal costs. Use an example in the Canadian context and see how an entity that started on the basis of social networks and trust had to morph into using the techniques used by other formal nonneighbourhood institutions as it grew in size and went beyond a threshold. Using the Canadian example, the author argues that as the transactions get sophisticated, it is possible to achieve what informal networks have achieved through the creative use of information technology. While we find that the role of trust both in the positivist and the coercive frame does provide some interesting insights into how exchanges with the poor could be managed, there still could be breaches in the assumptions. This paper identifies the conditions under which the breaches could possibly happen and also speculates on the effect of such breaches.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.003 | 0.011 |
| Scholarly communication | 0.008 | 0.007 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".