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Caste and Credit: A Woeful Tale?
The Journal of Development Studies
Abstract
This paper examines caste-based differences in farmers' access to bank loans in rural India. We investigate whether banks practice taste-based discrimination on the basis of caste. In order to identify potential discrimination, we consider loan applications and approval decisions separately. We find significant inter-caste differences in application rates, and evidence of discrimination against Scheduled Tribe borrowers at the approval stage. To rule out the role of statistical discrimination, we simulate unobserved credit histories with various distributions. Evidence for taste-based discrimination persists despite accounting for unobservables. However, we find that this discrimination does not affect small farmers.
... Except for gender, all household-specific factors, such as farm size (in hectares), years of schooling of the decision-maker in the household, diploma/ certificate of professional education, level of awareness, access to a smartphone, farming experience (in years), average hours spent on the farm per day (in hours) and farmers perception are hypothesised to have a positive impact on access to extension services. Owing to gender inequity, sociocultural and religious norms, it is thought that women decision-makers would have less access to extension services (Kumar and Venkatachalam, 2019). They are also often burdened by their tasks, such as caregivers, household chores and other household obligations. ...
... The set of other variables, including training in agriculture, access to credit, access to the mass media, and group membership, are also hypothesised to have a positive impact on the dependent variable. Based on prior art, it is hypothesised that marginalised castes have poor access to extension services (Gupta et al., 2020;Kumar and Venkatachalam, 2019;Krishna et al., 2019, Rao, 2017Singh et al., 2013). ...
... If an HOH is male, he has far more probability of having access to such services than a female HOH. Many studies have reported that households with female heads are less likely to access agricultural extension services than their male counterparts (Kumar and Venkatachalam, 2019;Ragasa et al., 2012). The most plausible explanation could be that female-headed households in developing countries are poor and marginalised due to social and cultural taboos and constraints on access to resources, market information, technical knowledge, and credit. ...
This paper examines the key determinants of farmers access to agricultural extension services, and the sources of agricultural extension services preferred and accessed by farmers. An ordered logistic regression model was used to analyse the data of 360 sample households based on a primary survey conducted in western Uttar Pradesh, India. The study finds that farmers decision to engage in the agricultural extension programme is significantly influenced by factors such as education level, gender, farming experience, social group, group membership, farm size, credit access, awareness of the extension scheme, farmers perception and distance from extension sources. The most intriguing finding of this study is that progressive farmers, who have long been regarded as a major source of knowledge diffusion, are the most distrusted sources of information as they are suspected of withholding vital information from potential beneficiaries. The positive relationship between farm size and ‘Access’ underlines that the extension services should revisit their strategies for targeting more marginal and small farmers by incorporating their priorities into their outreach programs. The study suggests that marginal and small farmers productive potential could still be greatly augmented by the appropriate technology, advisory services, guidance and improved market access.
... Differences in socio-economic characteristics of the household may also lead to credit rationing of loan amounts. For example, household borrowings from a formal credit source are dependent on fulfilment of eligibility criteria for loan approval, which may in turn depend on different socio-economic factors like caste (Kumar & Venkatachalam, 2018). The study by Kumar and Venkatachalam showed that there was not only a slight bias against Scheduled Tribes (ST) in loan approval decisions but also the loan application decision also seemed to follow a stereotypical class hierarchy, even after accounting for the credit histories of the individuals. ...
... Depending on the nature of information available, economic status is assessed by either per capita consumption, per capita income or household wealth, captured by an index of possession of durable goods categorised into quintiles or poverty status of the household. Thus, studies use one or the other variable to study the relationship between loan source and/or loan amount and economic status (Kumar & Venkatachalam, 2018;Swain & Floro, 2012). In this study, poverty rate and per capita income (quintiles) are used to capture economic status. ...
... Biases relating to social caste and capital often play a role in the credit source choices made by households. Kumar and Venkatachalam (2018) provide evidence on how caste influences an institution's decision to approve the loan as well as a household's decision to apply for loan from a loan source category. Our study assesses the formal-informal loan source combination, by cross-tabulating caste and the extended loan source classification (Table 4). ...
Due to various supply and demand factors, households in developing countries may borrow from a single source or combination of sources—formal, informal and microfinance institutions (MFI). Who is accessing what types of loan sources? This study uses Indian Human Development Survey (2011–2012) to analyse, for the first time, households accessing microfinance loans either alone (8%) or in combination with other sources (13%). We find that the more developed southern states have the highest MFI-linked borrowers (39%). Despite the low overall share of MFI borrowing, microfinance supports inclusiveness with higher presence among the economically disadvantaged and socially underprivileged, such as female-headed, casual labour, Other Backward Classes and dalit households. Expectedly, the effects of social networking are more pronounced among MFIlinked borrowers.
... Several authors have studied the differences in characteristics of the household borrowing across different sources (Langer, 2009;Mitra and Venkatachalam, 2018;Chakraborty and Gupta, 2017). However, most of these studies use only primary survey data of a small region of the country while this study uses a large secondary data that is representative of the country"s social and demographic diversities. ...
... Theoretical models usually envisage unidirectional linkages with access to credit helps individuals acquire physical capital that they can turn into economic rewards to pull themselves out of this life of dearth (Ray 2007). Institutional credit for instance, enhances production, productivity, profits and consumption and households with limited access to financial assets or those from socially disadvantaged groups are discriminated in this formal credit market 7 (Mitra and Venkatachalam, 2018). This shows that there are interlinkages across different forms of capital and missing out on or the other leads to a poverty trap. ...
... Accessibility and affordability is essential to acquire credit from a formal source that 8 enables borrowers to improve their income and consumption levels. For instance, considering the agricultural sector, it is essential for buying the raw materials and inputs during the sowing season (Mitra and Venkatachalam, 2018). A small farmer may not be able to generate enough revenue to invest again for next season. ...
To identify the factors that determine the choice of the households
... The structure and pattern of borrowing by fishermen is closely connected with factors such as fishing technology adopted, the scale of fishing, returns to investment and relative resource allocation by fishers on productive as well as non-productive assets [4,5]. The collective behavior of small holders/small-scale fishers also influence the choice of credit options, which depend considerably on relative factor-distributions, patron-client relationships, bargaining strength of various actors, and other complex caste-class equations existing within a community over and above economic demand-supply forces per se [6][7][8][9][10]. ...
... Commissions on harvest proceeds are charged by auctioneers (4-10%) 6 and Matsyafed (3-6%). 7 Quite obviously, the rates of commission charged by auctioneers were higher compared to Matsyafed in most of the cases. 8 Loan term is another important factor that determines the demand for loans across sources. ...
... The small units sourced major share of the capital from third-party sources followed by private money lenders, Matsyafed, auctioneers and commercial banks 6 This includes a service charge for auction that ranges from 1 to 2% and the rest accounted as interest towards loans. 7 Through designated auctioneers engaged by the Matsyafed. This generally includes services charges on auction (1% each for the primary society concerned and Matsyafed) as well as savings (1.5%) which is generally returned to the units in the form of bonus during festivals. ...
... But despite its multiple benefits, scores of studies have drawn attention to inequities in financial access. In the context of developing economies where societies have long been characterized by interlocking social and economic gradients, there remain major barriers to accessing financial services for households and individuals from socially marginalized backgrounds (Kumar and Venkatachalam 2019;Kumar 2013;Ghosh and Vinod 2017;Asiedu et al. 2012;Demirgüç-Kunt et al. 2013;De Andrés et al. 2021;Aristei and Gallo 2016). ...
... The caste dummy shows that as we move from lower to upper caste women, we get lower predicted probabilities of having bankaccess. This result seems to be unexpected given that considerable evidence has pointed to a caste gap in financial inclusion (Kumar 2013;Kumar and Venkatachalam 2019;Kaur and Kapuria 2020;Ghosh and Vinod 2017;Chavan 2020). Our result, however, may be explained by the complex "intersectionality" 5 of caste and gender in India that can get overlooked by studies that take households as their units of analysis. ...
... We evaluate access to institutional loans by sectors, particularly focusing on agricultural sector, and how bank expansion affects agricultural technology, labor hours and earnings by caste groups, aiming to discern whether historically marginalized groups encounter disproportionate impacts of bank presence, in light of their constrained access to credit in the agricultural sector Kumar, 2013;Kumar and Venkatachalam, 2019). Following this, we examine whether additional bank branches affect non-farm business revenues, household's overall labor force participation rates and labor market earnings for marginalized and non-marginalized caste groups. ...
... In an underbanked area, the credit market is predominated by informal lenders, such as professional moneylenders, landlords, merchants etc. These informal lenders discriminate extensively against the marginalized castes (Dreze et al., 1997;Kumar, 2013;Kumar and Venkatachalam, 2019). In most cases, the mode of discrimination is the excessive and unrealistic rate of interest demanded from the SCs, which almost always leads to them falling into a debt trap (Kumar, 2013). ...
... But despite its multiple benefits, scores of studies have drawn attention to inequities in financial access. In the context of developing economies where societies have long been characterized by interlocking social and economic gradients, there remain major barriers to accessing financial services for households and individuals from socially marginalized backgrounds (Kumar and Venkatachalam 2019;Kumar 2013;Ghosh and Vinod 2017;Asiedu et al. 2012;Demirgüç-Kunt et al. 2013;De Andrés et al. 2021;Aristei and Gallo 2016). ...
... The caste dummy shows that as we move from lower to upper caste women, we get lower predicted probabilities of having bankaccess. This result seems to be unexpected given that considerable evidence has pointed to a caste gap in financial inclusion (Kumar 2013;Kumar and Venkatachalam 2019;Kaur and Kapuria 2020;Ghosh and Vinod 2017;Chavan 2020). Our result, however, may be explained by the complex "intersectionality" 5 of caste and gender in India that can get overlooked by studies that take households as their units of analysis. ...
A number of studies have analyzed the determinants of financial inclusion in India, but few if any have focused specifically on the factors that shape women's access to finance. This paper draws on the trove of women‐specific data collected in the fourth round of the National Family Health Survey (NFHS‐4), conducted in 2015–16 in India, to examine the factors that influence women's access to finance. The results indicate that while the forces that shape women's access to finance function at multiple levels, micro‐level factors appear to be powerful drivers of inclusion. The analysis reveals that household‐level economic indicators like wealth, gender of household head and their rural‐urban location are crucial, but so are individual‐level characteristics which explain approximately 83% of the variation in the multilevel regressions. Informal gender norms that govern women's mobility and economic activity crucially influence the ability of women to access loans and open bank accounts.
... However, the conversation around effectively incorporating other forms of social identity, such as caste and ethnicity, for better targeted agriculture policy remains inadequate. In countries where social identity is tied to patterns of landholding, occupation segregation and access to public services (Balasubramanya et al. 2022;Krishna et al. 2019;Kumar and Venkatachalam 2019;Raghunathan et al. 2023), large economic shocks such as the pandemic induced lockdowns, intensified the vulnerability of marginalised groups (Acharya and Christopher 2022;Regmi et al. 2022), potentially trapping them in a cycle of low productivity and subsequent investment (Abraham et al. 2022;Deshpande and Ramachandran 2023). In this paper, we use panel survey data to examine heterogeneity in the outcomes of this economic shock on different caste groups, migrant households, and women farmers in Nepal. ...
Capacity to weather economic shocks is often mediated by social identity, which in turn determines access to social, economic and physical capital. We study the repercussions of a large economic shock on access to agriculture inputs, agricultural extension, output markets, and the consequent effects on income and livelihoods in rural Nepal. We focus on heterogeneity by caste, gender, and household migration status, using panel survey data from 2300 maize farmers. We observe prolonged effects of the 2020 pandemic induced lockdowns on the incomes of farmers, driven in part by reduced remittances. The shock intensified inequalities in agriculture, especially for female farmers and farmers from disadvantaged caste groups. As the economic impacts of multiple crises continue, policy measures to support the agriculture sector should target disadvantaged farmers, while simultaneously implementing long term strategies to shield the agriculture sector from future shocks.
... Studies have linked caste to borrowing, loan application and approval in India. SCs access bank loans, apply for bank loans and get their applications approved by banks as frequently as upper caste borrowers (Kumar, 2013;Kumar and Venkatachalam, 2019). Banks collateralize their loans, implying SCs are more likely to offer collateral. ...
Formal lenders widely accepted land collateral against loans. Those who were too poor to offer collateral, used collateral substitutes. Yet, both collateral and collateral substitutes are pointers to information asymmetry, where the lender did not know the borrower well enough. But in rural communities, lenders, aware of borrower types, might segregate borrowers into two categories, namely, honest and opportunistic. Quite expectedly, honest borrowers are exempt from offering collateral. Instead, they find personal guarantors substituting collateral. This study, based on face-to-face interviews of 839 rural borrowers from four districts of Andhra Pradesh and Telangana states in Southern India, follows a systematic sampling, and investigates the drivers for collateral, and those for finding personal guarantors who substitute collateral. The study builds a lender, borrower payoff matrix, linking borrower type, and collateralization to the payoffs to both the parties therein.
... Literature focused on credit discrimination based on gender, caste or marital status 1,[27][28][29][30] . The literature further examined borrower strategies like transfer of formal credit for informal lending, borrowing from one source to repay another and credit diversion 5,10,13,29,30 . ...
... It is worth noting, that in the Indian context, caste and social identity also play an important role in determining access to formal credit (Karthick and Madheswaran, 2018;Chavan, 2012), and disparity in credit seeking behavior is widely documented. Much of this arises from structural inequalities, such as inadequate access to land as collateral and awareness of credit schemes, but there is also evidence of discrimination in loan approvals (Kumar and Venkatachalam, 2019) for historically marginalized groups. This points to the need for dismantling structural inequalities that limit access to formal finance and credit facilities for smallholder farmers, along with promotion of financial literacy to generate demand for such services. ...
... 3 SHGs are groups that are formed by people who pool in money and then use it for lending to either members of the group or others in the same locality. Banks or microfinance institutions also use SHGs to channelize their lending programs. ...
Amidst the large and persistent economic impact of the COVID19 pandemic in India, household borrowing and its accumulation
can serve as a tool to mitigate the impact by enabling people to
spread their spending over time, thereby promoting economic
activity. Thus, it is essential for the credit market to actively engage
in such a scenario, especially at the sub-national level. To this end,
this study utilizes the nationally representative CMIE-CPHS data
to analyze the borrowing tendency and credit market access of
households in Kerala during the pandemic and recovery stage in
comparison to other states. The study found that Kerala had a high
borrowing reliance pre-pandemic, which more or less continued
during the crisis, driven mainly by debt repayment. The lower
middle-income households, particularly in rural area, had a high
incidence of borrowing and low financial resilience, while
Backward communities and informal sector workers, such as small
traders and wage earners, who were most affected by the
pandemic, relied heavily on borrowing. The study also revealed an
unprecedented and worrisome lack of support from the organized
banking sector in offering loans to individuals during crises,
especially when there is a drop in income due to job loss. During
the pandemic, the CD ratio of the state declined steadily, despite
banks thriving, and Kerala's bank dependence decreased by 25%,
while bank reliance at the national level and in other states dropped
by 5-6%. Despite the banks' retreat in the face of the crisis, Kerala's
SHGs and cooperatives stepped forward and provided massive
lending, mainly through interest-free loans, which benefitted
lower-middle-income households, scheduled communities, small
traders, and wage earners. Since household borrowing has not yet
fully returned to pre-pandemic levels, it is essential to ensure sufficient access to credit markets for households during crises as
reduced household spending can have adverse effects on the state's
economic recovery.
... Raj and Sasidharan (2018) show that the firms owned by socially-disadvantaged groups have a lower probability of obtaining credit from a formal institution. Caste-based disparities also appear in farmer's access to bank credit in rural India (Kumar, 2013;Karthick and Madheswaran, 2018;Kumar and Venkatachalam, 2019;Fisman et al., 2017;Rao, 2018;Tiwari et al., 2022), as well as in the informal markets (Khanna and Majumdar, 2020). Additionally, smaller size of firms owned by under-privileged groups may serve as a further detriment since small firms have significantly less access to formal credit (Beck and Demirguc-Kunt, 2006;Ayyagari et al., 2008;Bloom et al., 2010). ...
IEG working paper
https://iegindia.org/upload/publication/Workpap/WP460.pdf
... When the borrowers are indifferent between the contracts of the bank and of the moneylender, we assume that the borrowers choose the contract offered by the bank. This assumption is motivated from previous studies (Andersen and Malchow-Møller, 2006;Jain, 1999;Kochar, 1997;Kumar and Venkatachalam, 2019). We make further assumptions in Section 5 when we consider capacity constraint of the moneylender. ...
Purpose
The purpose of this study is to propose a model of competition between a formal lender (bank) and an informal lender (moneylender) with informational asymmetry between these two lenders. Further, the authors introduce capacity constraint on the lending capacity of the moneylender and assume that borrowers differ in risk and wealth.
Design/methodology/approach
The solution concept of Nash equilibrium has been used to derive the optimal strategies of the lenders.
Findings
The equilibrium strategies in most of the results depend on the difference between the expected returns from risky and safe projects where the risky project has higher expected returns. The credit market is segmented in terms of risk and wealth levels. Rationing of poor safe borrowers from the credit market is inevitable when the moneylender's capacity is sufficiently small, suggesting a low-income trap for them. Further, when moneylender has capacity constraint of some form, a zero-profit outcome is never a Nash equilibrium outcome.
Research limitations/implications
There is a possibility of collusion between the lenders. However, the authors do not derive all possible outcomes under capacity constraint
Practical implications
When the informal lender has limited capacity, competition between formal and informal lenders may not alleviate credit rationing, instead aggravate the problem. Thus, the government should devise policies to ensure credit availability to resource poor households
Originality/value
While the literature models strategic interaction between lenders under the assumption of zero-profit (Bertrand Paradox) condition, this study shows that zero profit is not the only outcome under such a set-up. Also, in presence of capacity constraint of the moneylender, a zero-profit outcome is never a Nash equilibrium outcome for the lenders. There is an optimal contract at which the lenders differentiate in terms of repayment and collateral and earn positive profits under certain conditions.
... While Okeahalam (2009) does not find any impact of race on branches of five retail banks in South Africa, Hegerty (2016) finds that the cities of Milwaukee and Buffalo, characterized by a large black population, have significantly higher unbanked areas. In the Indian context, studies by Kumar (2013), Karthick and Madheswaran (2018), Kumar and Venkatachalam (2019) and Rao (2018) found evidence of caste-based discrimination in farmer's access to bank credit in rural India. Tiwari et al. (2022) record this evidence at the household level in the state of Uttar Pradesh. ...
Purpose
Financial access is key to achieving several economic goals in developing countries. This paper aims to construct a longitudinal village-level measure of financial access in India and understand the role of RBI's policies and village characteristics in influencing the access.
Design/methodology/approach
The authors adopt a spatial approach in developing a metric of financial access. In particular, they measure the distance of each unbanked village in India to the nearest banked-centre from 1951 to 2019. The authors use this measure to conduct two exercises. First, a descriptive study is undertaken to assess how RBI's policies on bank branch expansion from 1951 to 2019 influenced the proximity to bank branches. Second, the authors conduct regression analyses to investigate how socio-economic and demographic characteristics of villages influence their proximity to bank branches.
Findings
The average distance of an unbanked village to the nearest banked-centre has declined from 43.5 km in 1951 to 4.2 km in 2019. The gain in bank access has varied geographically and over time. In 2001, bank branches were relatively distant from villages with under-privileged caste groups and proximate to areas with better infrastructure. This relationship worsened after 2005 when RBI introduced liberalized branch expansion policies. By 2019, proximity responds much more adversely to the presence of underprivileged groups. At the same time, banks have moved closer to economically better-off villages and villages with workforce in non-farm enterprises rather than agriculture.
Originality/value
First, studies in the Indian context focus on state-level determinants of bank branching, this is the first study to develop a longitudinal measure of financial access at the village level. This helps to understand spatial heterogeneity in bank branch access within states, which other studies are unable to do. Second, the paper analyses the role of village-level socio-economic and demographic characteristics in proximity to bank branches. This analysis helps in discovering micro-foundations of growth of bank branch network. The granularity of the approach adopted here overcomes the confoundedness problems that the studies at a more aggregate level face.
... cooperative banks discriminate against marginalized caste borrowers, whereas commercial banks instead bias lending in their favour in accordance with affirmative action policies. Discrimination in general is observed in mainly three different ways (Kumar and Venkatachalam 2019). First is taste-based discrimination (Becker 1957) which occurs if the differences in some outcomes (such as loan approvals or wages) based on race, caste, or a factor, are not 'objective'. ...
Using a large publicly available dataset, we examine the extent of difficulty faced by marginalized caste entrepreneurs from the unorganized sector in India when trying to access formal credit for their small businesses. Contrary to the expectation that a perceived social vulnerability would translate to more difficult credit access, we find that entrepreneurs from marginalized castes are in fact more likely to obtain credit from the formal financial system. This result on the extensive margin of credit could be interpreted as the formal financial system’s positive bias towards the marginalized castes. However, when we focus on the actual loan amounts received, we find that all else being equal, entrepreneurs from marginalized castes receive significantly lower loan amounts. This result on intensive margin of credit could potentially be interpreted as evidence of negative discrimination by the formal financial system. Therefore, determining whether financial inclusion policies for marginalized caste entrepreneurs have been successful yields answers both ways, depending on whether we look at extensive or intensive margin of credit. This finding has serious implications for a good design, monitoring and evaluation of financial inclusion policies (such as mandatory lending within affirmative action programmes or priority sector lending) for borrowers from marginalized communities.
... It is worth noting, that in the Indian context, caste and social identity also play an important role in determining access to formal credit (Karthick and Madheswaran, 2018;Chavan, 2012), and disparity in credit seeking behavior is widely documented. Much of this arises from structural inequalities, such as inadequate access to land as collateral and awareness of credit schemes, but there is also evidence of discrimination in loan approvals (Kumar and Venkatachalam, 2019) for historically marginalized groups. This points to the need for dismantling structural inequalities that limit access to formal finance and credit facilities for smallholder farmers, along with promotion of financial literacy to generate demand for such services. ...
... One can argue that the societal structure based on the caste system has led to significant discrimination in business ownership, wealth creation, and choice of occupation (Desai and Dubey, 2012). In a study, Kumar and Venkatachalam (2019) found that farmers belonging to STs and SCs castes are 16-20 % less likely to apply for credit than farmers of higher castes. ...
This study examines the role of caste-based affiliations in the smallholders’ social network interactions for adoption choices. In particular, whether lower-caste, namely Scheduled Castes/Scheduled Tribes, farmers rely more on social networks for information than their counterparts. We further explore whether social network effects are more pronounced when farmers interact within their caste than otherwise. Finally, the study tests whether the effects (intra-caste and inter-caste) vary by caste—SC/ST versus non-SC/ST farmers. The study uses a survey of 478 mustard farmers in Rajasthan, India. Econometric concerns related to unobserved heterogeneity are addressed by employing specifications with village fixed effects and a series of robustness tests. Simultaneity concerns are addressed by analyzing the social network effects in a dynamic adoption framework. Results show that the adoption choices regarding hybrid mustard seeds are more pronounced for the lower-caste farmers than for their counterparts. Findings reveal that social network effects are significant in intra-caste but not in the case of inter-caste. Finally, the result shows that the likelihood of accepting advice in technology adoption is higher when SC/ST farmers interact with non-SC/ST network members than when non-SC/ST farmers interact with SC/ST network members.
... The identity of both the borrowers and lenders also shapes the former's experiences of living with debt. Oftentimes, the borrowers' caste determines the terms on which lenders extend credit (Kumar and Venkatachalam 2018). Further, the uncertainties inherent to agriculture, state policies like loan waivers, and the emergence of new sources of credit such as banks and microfinance institutions alongside the persistence of traditional ones like informal moneylenders all contribute to make debts exploitative (Taylor 2013;Carswell et al. 2020;Green 2020). ...
Climate change and indebtedness have been repeatedly highlighted as major causes of distress for rural households in India. However, despite the close connection between climate conditions and rural livelihoods, there has been little attempt to systematically examine the association between the two. To address this gap, we combine national-level longitudinal data from IHDS, MERRA-2, and the Indian Ministry of Agriculture to study the impact of climate anomalies on household indebtedness across rural India. Using a multilevel longitudinal approach that accounts for potential confounders at household, village, and district levels, we find pervasive effects of season-specific, 5-year climate anomalies on multiple dimensions of household debt, particularly in arid and semi-arid areas. Most notably, temperature anomalies in the winter cropping season in arid and semi-arid areas are associated with increasing household indebtedness. We further find that climate change interacts with existing socioeconomic differences—caste and landholding in particular—to deepen both the size and the depth of indebtedness for rural households.
... Scholars (Kumar and Venkatachalam 2018;Rana and Vishwanathan 2019;Tripathi 2017) and bankers (Pradhan 2013) have used large secondary datasets to map trends, reasons, and sources of household borrowing. Others have used qualitative methods and small-sample surveys to study local experiences of rural indebtedness (Guérin and Venkatasubramanian 2020;Ramprasad 2018;Sethi 2018). ...
Rural indebtedness is a major development challenge confronting India. In 2018, scores of farmers protested rising household debt, and the popular coverage of the time asserted that farmers were under crushing debt. Combining data from the All‐India Debt and Investment Survey with other sources and using a class analysis, I interrogate this “crushing debt” narrative. Rural households, depending on the socioeconomic and contextual vulnerabilities that they experience, are indebted in different ways. The rural elite borrow more loans and have higher loan amounts, while asset‐poor households are more dependent on informal credit sources and also pay higher rates of interest. Households from the wage worker class are more likely to be over‐indebted relative to others. I further find that petty commodity producers bear less debt burden and are less likely to be over‐indebted relative to other classes. These findings underscore the fact that rural indebtedness is a nuanced problem that manifests in a multitude of ways across India.
... Scheduled Castes and Scheduled Tribes (SCSTs) are marginalized groups that have been historically subjected to practices of untouchability and large-scale exclusion from mainstream society. While there have been some improvements in terms of educational attainment and incomes since affirmative action was introduced in 1950 (Hnatkovska, Lahiri and Paul, 2012), lower castes continue to fare systematically worse than upper castes in terms of wages, occupations, education, credit access, etc. 11 Discrimination in labor and credit markets play an important role in determining the adverse outcomes ofSCSTs (e.g.,Deshpande, 2011;Kumar and Venkatchalam, 2019). Further, caste is immutable as it is determined at birth, and intergenerational mobility in India remains generally low. ...
This study uses household-level panel data from a nationally representative survey to estimate the effect of agricultural productivity shocks—as proxied by exogenous annual rainfall deviations—on education expenditures and children’s work status in rural India. We find that a transitory increase in rainfall significantly reduces education expenditures and increases the likelihood of child labor across multiple work activities. Additionally, households owning land and those with better credit access increase the use of child labor as rainfall increases because labor (and land) markets are incomplete. The effects of productivity shocks are reinforced for marginalized castes and for less educated households, thereby exacerbating inequalities in education.
... Increasingly, researchers in Development Studies use mathematical models to simulate complex social and economic systems. For example, Kumar and Venkatachalam (2018) used survey data from bank loan applicants of various castes in rural India to create a model that enabled them to run simulations of different hypothetical scenarios; they found that lower loans were given to farmers from lower castes but, surprisingly, this discrimination did not affect owners of small farms. This research approach, in which modelling and simulation (M&S) is utilized, typically involves the following steps. ...
Researchers in the social sciences are increasingly applying modelling and simulation (M&S) as research approach. They create virtual worlds to discover relations across variables, and test theories and potential policies. We introduced the research approach to students in the department of Development Studies at our university. The goal was to investigate the way in which such students can gain meta-knowledge about M&S-based research, that is, general knowledge about its nature and rationale. We organized a seminar to introduce the research approach, and illustrated it with an accessible simulation of citizens in a virtual city and their tolerance towards out-group neighbors, based on Schelling's segregation model. We analyzed students' interaction through a socio-cultural lens. Students were able to gain meta-knowledge about M&S-based research, and judged these as useful in their future as professionals when working in development projects.
... obtaining a loan using the double-hurdle model. This is important as formal credit institutions can also discriminate by providing smaller loans to borrowers from certain caste groups (Kumar and Venkatachalam 2018). Table 1 points to this possibility as we observe significant caste-wise differences in loan amounts. ...
This study examines whether caste affiliation matters in obtaining credit from institutional sources. We employ Fourth All India Census of Micro, Small and Medium Enterprises 2006—2007 data to empirically verify this relationship. We conduct an econometric analysis of loan outcomes by caste affiliation of the firm owner and observe that firms owned by socially disadvantaged categories have lower probability of obtaining formal credit even after controlling for differences in creditworthiness and other factors. Our results also show that discrimination by formal credit institutions extends to amount of loan sanctioned as well. These results thus suggest that affirmative action programs in India have not had much impact on the credit market access for the socially marginalized entrepreneurs, and policymakers should address this concern by introducing special programs and regulatory incentives to encourage banks and others to increase their lending toward these disadvantaged groups.
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The paper examines the status of indebtedness across social categories and investigates why Dalits on average pay higher interest rate on their loans compared to non-Dalits, even when borrowing under the same scheme. About one-third of households were in indebtedness by the end of June 2018, 90% of which became indebted during 2013–2018. The extent of indebtedness during this period was higher among SCs and OBCs. SCs and STs on average paid higher interest rates than OBCs and ‘Others’ regardless of lending institutions. They also faced higher interest rates even on loans taken under the schemes specifically designed to provide easy credit to marginalized community at supposedly lower interest rates. Using the Oaxaca–Blinder & Fairlie decomposition techniques, the paper reveals that around 40% of the gap in accessing credit from formal sources between SCs and forward castes or ‘Others’ is unexplained and can be attributed to discrimination. Similarly, 40–70% of the difference in interest rates between the groups are unexplained, further suggesting discrimination. Due to such biases, Dalits are 11% less likely to obtain credit, and cost of credit for them is on average 2.4% higher compared to the “Others” category.
This study investigates the relationship between financial literacy and financial well-being among marginalized women, focusing on the moderating role of caste-based discrimination. Despite affirmative action programs in India, caste-based inequalities persist, impacting access to resources and economic opportunities. Data from 404 Scheduled Caste women in Karnataka’s Koppal district, an underbanked region, were analyzed using structural equation modelling (Smart PLS). The findings reveal a significant positive relationship between financial literacy and financial well-being, indicating that financial literacy enhances financial stability, security, and informed decision-making among scheduled caste women. However, caste-based discrimination negatively affects financial well-being and moderates the FL-FW relationship, reducing the benefits of financial literacy in promoting well-being. This highlights systemic barriers that limit marginalized women’s ability to achieve financial empowerment. This research contributes to the discourse on social equity and economic empowerment, emphasizing the intersection of financial literacy, well-being, caste, and gender. It underscores the necessity of addressing systemic barriers to ensure financial literacy initiatives benefit marginalized communities effectively
Even though management research on caste is growing, it is not yet on a clear trajectory to realize its vast potential due to varying terminology and framing of caste, the limited incorporation of directly relevant work from proximate disciplines, and the narrow and selective usage of the attributes of caste. To remove these obstacles, we review 259 scholarly works on caste (216 articles and 43 books and research reports) and develop an integrative framework to (a) clarify the contemporary manifestations of caste as being a graded hierarchy, an inherited membership, and a set of socially enforced practices; and (b) summarize the outcomes of caste at individual, occupational, organizational, and societal levels, while also consolidating the mechanisms through which caste influences these outcomes. Additionally, to position management scholarship on this topic for greater impact, we develop a research agenda that reflects contemporary interests in management research and the world at large about inclusion in organizations and societies. The caste system has practical significance for a large portion of the global population.
This essay provides a thematic discussion of discrimination in credit. Through a selective review of the literature I illustrate that caste, gender and race are all persistent axes of discrimination in credit, and that discrimination has been shown to exist across diverse contexts. I examine the main conceptual tools used in this literature to shed light on the causal mechanisms that lead to discrimination, and in particular attempt to delineate the role of individuals, institutions and formal regulation. By briefly exploring the links between discrimination in credit and group-based inequality in other arenas of economy and society, I argue why the implications of the former extend far beyond credit alone, and are a powerful force in shaping inequality more generally including across generations.
Social networks influence technology diffusion but targeting formal leaders (institutional central nodes) may lead to distributional consequences. This paper analyzes the role of informal social networks in technology diffusion in a socially hierarchical caste-based society. Often, information flow and technology diffusion are constrained by social and economic boundaries where informal nodes such as caste play a very decisive role in everyday life. Proper targeting and dissemination of technology to the marginalized sections of society are very important for their development. We observed that only one-fourth of farmers cultivate newer varieties which include hybrids and recently released high yielding varieties. The results showed that individuals belonging to marginal groups are influential and act as informal leaders when they are the dominant caste in the village. Progressive farmers are found to fail in disseminating new varieties, and targeting influential informal leaders who belong to the dominant caste of the village appears to be a better strategy. Among non-dominant caste members, influential leaders belonging to Other Backward Classes (OBCs) or Scheduled Tribes (STs) are more desirable targets than other caste groups. The more concentrated a network is in terms of its caste composition, the faster will be the spread of any technology.
Dalit Capital explores the relationship between caste and economics in contemporary India. It reveals the ways in which caste and social discrimination reinvent themselves under the guise of modern capitalism. Drawing on business histories of Dalit entrepreneurs, the book demonstrates how 'inclusion' — perpetrated by the state, markets and the civil society — in fact holds Dalits at a disadvantage.
Dalit Capital is an original study of how social inequalities find expression in the economic sphere. It describes how the economy is embedded in economic as well as non-economic institutions and connects this
to the contemporary reality of castes. Through new empirical data, the volume shows how Dalit participation in the economy is on unfavourable terms. Canvassing a wealth of information on Dalit entrepreneurs, and supported by rigorous conceptual apparatus, the book provides a distinctive voice to the socially ‘excluded’.
The study offers an insightful examination of the linkages between social identity and economics and serves as a stark reminder of the persistence of social exclusion. It will greatly interest researchers and scholars of Dalit and social exclusion studies, sociology, political science, economics, development studies, social entrepreneurship, and public policy
This paper analyzes whether caste impedes access to formal agricultural credit in India. Credit is provided mainly through cooperative and commercial banks. Using national data, we find that cooperative banks discriminate against lower caste borrowers, and find weak evidence that commercial banks instead bias lending in their favor in accordance with affirmative action policies. We compare the organizational structures of the two types of bank, and explain discrimination by cooperative banks in terms of interest group capture at the district level by showing that discrimination takes place in those districts where higher castes dominate.
This paper employs data from the 1998 and 2003 Survey of Small Business Finances to analyze whether, after controlling for observable factors that influence loan decisions, there is a significant difference in the loan approval rate and the interest rate charged on approved loans for businesses owned by minority or white females and firms owned by white males.
This paper presents a case study of credit transactions in Palanpur, a north Indian village. Drawing on detailed informtion from all borrowers and lenders in the village, we examine a number of issues related to the functioning of rural credit markets. These include the segmentation of the credit market, the achievements and failure of public lending institutions, the role of interest-free lending, the lending strategies of village moneylenders, social inequalities in access to credit, and the politics of rural credit, among others. An attempt is also made to relate these findings to those of other studies of credit in rural India.
The demand and supply of credit in the rural credit markets is investigated in this article using household data from India. The aim is to study the effects of household, farm productive characteristics and the policy variables on the demand and supply of credit. A type 3 Tobit model is estimated which corrects for sample selection and endogeniety bias. In addition, a generalized Double Hurdle model is estimated where the information on the household's access to credit is included to estimate the demand and supply of credit. The results suggest that the size of the operational holdings, net-wealth, dependency ratio, educational level of the household and the wages and output prices are important determinants of the demand and supply of credit for farm households. The Double Hurdle model confirms that the 'size of land owned' plays a crucial role in whether the household has access to a loan or not.
An analysis of the ICRISAT data from three Indian villages raises concern about the extent of rationing mechanism inhibiting the spread of formal credit in rural India where a significant proportion of households do not have any outstanding loan or borrow from the informal sector only. A limited-dependent econometric analysis of the factors jointly determining household sectoral choice and effective demand for informal loan conditional on whether a formal loan is available suggests that compared to formal loan easy and adequate access and prompt recovery are significant determinants of the popularity and viability of informal rural credit among sample households; also some households substitute labour income to ease the extent of credit. Thus, rationing of the formal credit is not the only factor inhibiting the spread of formal credit in the study villages. Copyright 2002 by Taylor and Francis Group
This paper takes the results of an employment and training program thatwas run as a field experiment, in which the participants were randomlyassigned into a treatment or a control group, and compares these results to the estimates that might have been produced by an econometrician who evaluated the program using the same econometric procedures that have been used in the program evaluation literature. This comparison shows that many of these econometric procedures fail toreplicate the experimentally determined results, and suggests that researchers should be aware of the potential for specification errorsin other nonexperimental evaluations. Copyright 1986 by American Economic Association.
This paper provides a survey on studies that analyze the macroeconomic effects of intellectual property rights (IPR). The first part of this paper introduces different patent policy instruments and reviews their effects on R&D and economic growth. This part also discusses the distortionary effects and distributional consequences of IPR protection as well as empirical evidence on the effects of patent rights. Then, the second part considers the international aspects of IPR protection. In summary, this paper draws the following conclusions from the literature. Firstly, different patent policy instruments have different effects on R&D and growth. Secondly, there is empirical evidence supporting a positive relationship between IPR protection and innovation, but the evidence is stronger for developed countries than for developing countries. Thirdly, the optimal level of IPR protection should tradeoff the social benefits of enhanced innovation against the social costs of multiple distortions and income inequality. Finally, in an open economy, achieving the globally optimal level of protection requires an international coordination (rather than the harmonization) of IPR protection.
This paper models the inner workings of relationship lending, the implications for bank organisational structure, and the effects of shocks to the economic environment on the availability of relationship credit to small businesses. Relationship lending depends on the accumulation over time by the loan officer of "soft" information. Because the loan officer is the repository of this soft information, agency problems are created throughout the organisation that may best be resolved by structuring the bank as a small, closely-held organisation with few managerial layers. The shocks analysed include technological innovations, regulatory regime shifts, banking industry consolidation, and monetary policy shocks.
This paper proposes a simple technique for assessing the range of plausible causal conclusions from observational studies with a binary outcome and an observed categorical covariate. The technique assesses the sensitivity of conclusions to assumptions about an unobserved binary covariate relevant to both treatment assignment and response. A medical study of coronary artery disease is used to illustrate the technique.
INTRODUCTION Tribal groups or Adivasis in India are considered to be the earliest inhabitants of a country that experienced diverse waves of invaders and other settlers over thousands of years, making it difficult to identify the precise origin of today’s tribal peoples from a purist’s perspective. The term Adivasi is commonly translated as “indigenous people” or “original inhabitants” and literally means “Adi (earliest time)” and “vasi (resident of).” The state and discourse in India, however, reject the term “indigenous peoples” as it is considered “divisive, undermining the unity of the Indian nation.” Furthermore, it is the government’s official position that all citizens of India are indigenous. The government instead recognizes most Adivasis under the Constitutional term “Scheduled Tribes” (see Annex 1). The Constitution Order 1950 declared 212 tribes located in 14 states of India as Scheduled Tribes (STs). The government of India today identifies 533 tribes, with 62 of them located in the state of Orissa. To many, therefore, any aggregate analysis of STs is meaningless because it is impossible to aggregate these diverse groups of peoples. That being understood, this analysis is an attempt to use the available data to understand what happened to this artificially and statistically “homogenized” group over time. Social stratification in India is primarily determined by the fourfold varna system commonly known as the caste system. STs do not strictly fall within this Hindu caste hierarchy because they have traditionally lived in forest areas, away from mainstream village life, and have distinct (often considered non-Hindu) cultural and religious practices and social mores. Although “Scheduled Castes (SCs) and Scheduled Tribes” is sometimes said in the same breath, they are distinct social categories. Whereas STs do not face ritual exclusion in the form of untouchability, as do the SCs or Dalits , when exclusion is defined more broadly in terms of being “prevent(ed)… from entering or participating” or “being considered or accepted,” STs fit squarely within the conception of excluded people. The major difference in the development status of the SCs and STs is that whereas the former lived among but were segregated socially and ritually from the mainstream and from upper-caste groups, the latter were isolated physically, and hence socially (Béteille, 1991), although the degree of “isolation” remains in question.
This article examines the prevalence of discrimination in the job application process of private sector enterprises in India. The study is based on a field experiment where authors replied to job advertisements in major English dailies sending three applications to each call – as an upper caste Hindu applicant, as a dalit and as a Muslim. Using statistical analysis they assess the data and find that discriminatory processes operate even at the first stage of the application process.
The policy intervention in agriculture has been credit driven. This is even more pronounced in the recent interventions made by the State in the package announced for distressed farmers, in doubling agricultural credit, providing subvention and putting an upper cap on interest rates for agricultural loans. We use existing literature and data to argue that the causality of agricultural output with increased doses of credit cannot be clearly established.
We argue that Indian agriculture is undergoing a fundamental change wherein the technology and inputs are moving out of the hands of the farmers to external suppliers. This, over a period of time may have resulted in the de–skilling of farmers and without adequate public investments in support services and without appropriate risk mitigation products, has created a near–crisis in agriculture. Thus, we argue that policy interventions have to be necessarily patient and holistic.
Looking specifically at the rural financial markets using some primary data, we argue that it is necessary to understand the rural financial markets from the demand side. We conclude the article by identifying some directions in which the policy intervention could move, keeping the overall rural economy in view rather than being focussed only on agriculture.
Poor returns to cultivation and absence of non-farm opportunities are indicative of the larger socio-economic malaise in rural India. This is accentuated by the multiple risks that the farmer faces – yield, price, input, technology and credit among others. The increasing incidence of farmers’ suicides is symptomatic of a larger crisis, which is much more widespread. Risk mitigation strategies should go beyond credit. Long term strategies requires more stable income from agriculture, and more importantly, from non-farm sources. Private credit and input markets need to be regulated. A challenge for the technological and financial gurus is to provide innovative products that reduce costs while increasing returns. The institutional vacuum of organising farmers needs to be addressed through a federation of self-help groups (SHGs) or alternative structures.
This chapter summarizes recent research in economics that investigates differentials by race and gender in the labor market. We start with a statistical overview of the trends in labor market outcomes by race, gender and Hispanic origin, including some simple regressions on the determinants of wages and employment. This is followed in Section 3 by an extended review of current theories about discrimination in the labor market, including recent extensions of taste-based theories, theories of occupational exclusion, and theories of statistical discrimination. Section 4 discusses empirical research that provides direct evidence of discrimination in the labor market, beyond “unexplained gaps” in wage or employment regressions. The remainder of the chapter reviews the evidence on race and gender gaps, particularly wage gaps. Section 5 reviews research on the impact of pre-market human capital differences in education and family background that differ by race and gender. Section 6 reviews the impact of differences in both the levels and the returns to experience and seniority, with discussion of the role of training and labor market search and turnover on race and gender differentials. Section 7 reviews the role of job characteristics (particularly occupational characteristics) in the gender wage gap. Section 8 reviews the smaller literature on differences in fringe benefits by gender. Section 9 is an extensive discussion of the empirical work that accounts for changes in the trends in race and gender differentials over time. Of particular interest is the new research literature that investigates the impact of widening wage inequality on race and gender wage gaps. Section 10 reviews research that relates policy changes to race and gender differentials, including anti-discrimination policy. The chapter concludes with comments about a future research agenda.
This review examines portions of the vast literature on rural financial markets and household behavior in the face of risk and uncertainty and limited commitment. In addition to examining household strategies and bilateral contracting we place particular emphasis on studying the important role of financial intermediaries, competition and regulation in shaping the changing structure and organization of rural markets. Our goal is to provide a framework within which the evolution of financial intermediation in rural economies can be understood.
This paper is an empirical attempt to quantify caste-based discrimination in the labor market using household data taken from rural North India. In the regression analysis, transaction costs associated with entry into the labor market and reservation wages are estimated simultaneously along with market wages. The estimation results provide evidence of the existence of transaction costs in the labor market and discrimination against backward classes with regard to access to regular employment. In line with previous studies, the results suggest that the achievements of India's reservation policy so far have at best been limited. In addition, a comparison between the estimates from the model employed in this paper and conventional (reduced-form) approaches shows that discrimination in labor market entry is likely to be underestimated in the conventional reduced-form approaches.
This paper is a practical guide (a toolkit) for researchers, students and practitioners wishing to introduce randomization as part of a research design in the field. It first covers the rationale for the use of randomization, as a solution to selection bias and a partial solution to publication biases. Second, it discusses various ways in which randomization can be practically introduced in a field settings. Third, it discusses designs issues such as sample size requirements, stratification, level of randomization and data collection methods. Fourth, it discusses how to analyze data from randomized evaluations when there are departures from the basic framework. It reviews in particular how to handle imperfect compliance and externalities. Finally, it discusses some of the issues involved in drawing general conclusions from randomized evaluations, including the necessary use of theory as a guide when designing evaluations and interpreting results.
We study the role of caste and religion in India s new economy sectors software and call-
centers by sending 3160 ctitious resumes in response to 371 job openings in and around
Delhi (India) that were advertised in major city papers and online job sites. We randomly
allocate caste-linked surnames across resumes in order to isolate the e¤ect of caste on appli-
cants job-search outcomes. We nd no evidence of discrimination against non-upper-caste
(i.e. Scheduled Caste, Scheduled Tribe, and Other Backward Caste) applicants for software
jobs. We do nd larger and signi cant di¤erences between callback rates for upper-castes and
Other Backward Castes (and to a lesser extent Scheduled Castes) in the case of call-center
jobs. There is no evidence of discrimination against Muslims for either of the two kinds of
jobs we apply for. Overall, the evidence suggests that applicants caste identities do not signi cantly a¤ect the callback decisions of rms in these rapidly-growing sectors of the Indian
economy
Despite policies targeting scheduled castes (SC) and scheduled tribes (ST), there remain large disparities of living standards between SC/ST and non-SC/ST households in India. The SC/ST households may be poorer because they possess lower human and physical capital, but they may also earn lower returns to these assets. This study finds that 30%-50% of the welfare disparities are attributable to different returns. Such structural differences between the SC and the non-SC/ST are partly because the SC earn lower returns to schooling. A large part of the structural disparities between the ST and the non-SC/ST comes from the fact that the areas where the ST live are different from those where the non-SC/ST live. In addition, the ST tend to earn lower returns even with controls for geographical conditions.
We use data from the 1993 and 1998 National Surveys of Small Business Finances to examine the existence of racial discrimination in the small-business credit market. We conduct an econometric analysis of loan outcomes by race and find that black-owned small businesses are about twice as likely to be denied credit even after controlling for differences in creditworthiness and other factors. A series of specification checks indicates that this gap is unlikely to be explained by omitted variable bias. These results indicate that the racial disparity in credit availability is likely caused by discrimination. Copyright (c) 2003 President and Fellows of Harvard College and the Massachusetts Institute of Technology.
I. Introduction, 599.—II. Sharecropping, 601.—III. Work conditions: the rat race, 603.—IV. Statistical discrimination, 606.—V.
Caste and group organizations, 608.—VI. Conclusions, 617.
State-led credit and savings programs have been implemented in numerous low income countries, but their success in reaching the poor remains widely debated. We report on research that exploits the policy features of the Indian social banking program to provide evidence on this issue. State-led branch expansion into rural unbanked locations reduced poverty across Indian states. In addition, the enforcement of directed bank lending requirements was associated with increased bank borrowing among the poor, in particular low caste and tribal groups. Copyright (c) 2005 The European Economic Association.
Firms spend billions of dollars developing advertising content, yet there is little field evidence on how much or how it affects
demand. We analyze a direct mail field experiment in South Africa implemented by a consumer lender that randomized advertising
content, loan price, and loan offer deadlines simultaneously. We find that advertising content significantly affects demand.
Although it was difficult to predict ex ante which specific advertising features would matter most in this context, the features that do matter have large effects. Showing
fewer example loans, not suggesting a particular use for the loan, or including a photo of an attractive woman increases loan
demand by about as much as a 25% reduction in the interest rate. The evidence also suggests that advertising content persuades
by appealing “peripherally” to intuition rather than reason. Although the advertising content effects point to an important
role for persuasion and related psychology, our deadline results do not support the psychological prediction that shorter
deadlines may help overcome time-management problems; instead, demand strongly increases with longer deadlines.
This paper draws on a conceptual analysis of discrimination to improve the methodology for estimating discrimination in small-business credit markets and to provide some evidence about the possible causes of discrimination in these markets. Using a variety of statistical enhancements to existing studies, we find statistically significant evidence of substantial discrimination in loan approval against black-owned and Hispanic-owned businesses in 1998. We also find some hints that this discrimination takes the form of statistical discrimination, driven by lenders' stereotypes about the ability of black- and Hispanic-owned businesses to succeed under some circumstances. Although we find no discrimination, on average, in interest rates on approved loans, we also find that black-owned businesses do face discrimination in interest rates when they borrow from finance companies and businesses, such as mutual fund companies and leasing companies, with a primary mission other than lending. These findings suggest that federal financial regulatory agencies should re-double their efforts to uncover and prosecute lenders who discriminate against black- and Hispanic-owned businesses and that new tools may be needed to find discrimination by firms not well covered by the existing fair-lending enforcement system.
The diffusion of temporary work agency (TWA) jobs has led to a harsh policy debate and ambiguous empirical evidence. Results for the USA, based on quasi-experimental evidence, suggest that a TWA assignment decreases the probability of finding a stable job, while results for Europe, based on the conditional independence assumption (CIA), typically reach opposite conclusions. Using data for two Italian regions, we rely on a matching estimator to show that TWA assignments can be an effective springboard to permanent employment. We also propose a simulation-based sensitivity analysis, which highlights that only for one of these two regions are our results robust to specific failures of the CIA. We conclude that European studies based on the CIA should not be automatically discarded, but should be put under the scrutiny of a sensitivity analysis like the one we propose. Copyright © 2008 John Wiley & Sons, Ltd.
Despite anti-discrimination policies, women are paid 20% less then men in the UK. A large proportion of this wage gap is usually left unexplained. In this paper, I investigate whether the unexplained component is due to mis-specification. Using a sample of recent UK graduates, I examine the role of choice variables (subject of study and occupation) as well as career expectations and aspirations. The evidence indicates that women are more altruistic and less career-oriented than men. Career break expectations, for example, explain 10% of the gender wage gap in the favoured model. By omitting attitudinal variables, most studies are likely to overestimate the unexplained component of the gender wage gap. Women with a more traditional view concerning childrearing are also found to have less intensive search behaviour. Since aspirations may reflect perceived discrimination or social pressure, current legislations are unlikely to reduce the gender wage gap. Copyright 2007 Blackwell Publishing Ltd.
Racial discrimination pervades every aspect of a society in which it is found. It is found above all in attitudes of both races, but also in social relations, in intermarriage, in residential location, and, frequently, in legal barriers. It is also found in levels of economic accomplishment; that is, income, wages, prices paid, and credit extended. It is natural to suppose that economic analysis can cast light on the economic effects of racial discrimination. But the pervasiveness of the phenomenon must give us pause. Can a phenomenon manifest everywhere in the social world really be understood, even in only one aspect, by the tools of a single discipline? I want to explore here the scope and limits of ordinary economic analysis for understanding racial discrimination even in markets.
We study race in the labor market by sending fictitious resumes to help-wanted ads in Boston and Chicago newspapers. To manipulate perceived race, resumes are randomly assigned African-American- or White-sounding names. White names receive 50 percent more callbacks for interviews. Callbacks are also more responsive to resume quality for White names than for African-American ones. The racial gap is uniform across occupation, industry, and employer size. We also find little evidence that employers are inferring social class from the names. Differential treatment by race still appears to still be prominent in the U. S. labor market.
Report of the Working Group to Examine the Procedures and Processes of Agricultural Loans
- Reserve Bank
- India
Reserve Bank of India (2007). Report of the Working Group to Examine the Procedures
and Processes of Agricultural Loans. Technical report, Reserve Bank of India, Mumbai.
- Burgess R.
Discrimination in labor markets
- K J Arrow
Arrow, K. J. (1973). The theory of discrimination. In Orley Ashenfelter and Albert
Rees (Eds.), Discrimination in labor markets., pp. 3-33. Princeton, N.J.: Princeton
University Press.
Master circular: Priority sector lending facilities to Scheduled Castes (SCs) & Scheduled Tribes (STs)
- Reserve Bank
- India
Reserve Bank of India (2004). Master circular: Priority sector lending facilities to Scheduled Castes (SCs) & Scheduled Tribes (STs). Mumbai: Reserve Bank of India.
Master Circular -Priority Sector Lending -Credit Facilities to SCs and STs
- Reserve Bank
- India
Reserve Bank of India (2011). Master Circular -Priority Sector Lending -Credit Facilities
to SCs and STs. Mumbai: Reserve Bank of India.
Report of the expert group on agricultural indebtedness. New Delhi: Ministry of Finance
- India Government Of