Search results

The purpose of this paper is to evaluate the rural credit demand by providing a theoretical and econometric framework which controls the problem of selection bias.

The study is conducted in Assam, India, and uses a quasi-experiment design to gather primary data. Heckman two-stage procedure and type 3 Tobit model are used to evaluate the rural credit demand.

It is observed that, in general, rural households’ credit demand is influenced by the ability and capacity to work, the value of physical assets of the borrowers as well as some other lenders’ and borrowers’ specific factors. But, the direction of causality of the factors influencing borrowers’ credit demand is remarkably different across credit sources.

The study recommends that it is possible to provide an efficient credit demand estimate through a correct theoretical and econometric framework. The possible limitation of the study can be due to the exclusion of the role of “traditional community based organizations” in rural Assam while evaluating the credit demand, and therefore, this limitation is left to future research.

The study contributes to the literature by assessing the probable differences among formal, semiformal and informal credit sources with respect to rural credit demand.

In this chapter, the authors contribute toward building a better understanding of farmers’ responses to behavioral drivers of land-use decision by establishing an alternative analytical procedure, which can overcome various drawbacks suffered by methods currently used in existing studies. Firstly, our procedure makes use of spatially high-resolution data, so that idiosyncratic effects of physical environment drivers, e.g., soil textures, can be explicitly modeled. Secondly, we address the well-known censored data problem, which often hinders a successful analysis of land-use shares. Thirdly, we incorporate spatial error dependence (SED) and heterogeneity in order to obtain efficiency gain and a more accurate formulation of variances for the parameter estimates. Finally, the authors reduce the computational burden and improve estimation accuracy by introducing an alternative generalized method of moments (GMM)–quasi maximum likelihood (QML) hybrid estimation procedure. The authors apply the newly proposed procedure to spatially high-resolution data in England and found that, by taking these features into consideration, the authors are able to formulate conclusions about causal effects of climatic and physical environment, and environmental policy on land-use shares that differ significantly from those made based on methods that are currently used in the literature. Moreover, the authors show that our method enables derivation of a more effective predictor of the land-use shares, which is utterly useful from the policy-making point of view.

Several popular and academic pieces of late have expressed concerns regarding the sustainability of public defined benefit pension funds. Since the onset of the Great Recession, concern has increased. In this paper recent arguments are analyzed in the context of three related data sets: panel data on public sector pensions spanning 2001-2009, historic asset return data, and business cycle data. Findings generally indicate that while public sector plans have suffered a difficult decade, current anxieties may be somewhat overwrought. Several remedial policies are investigated. Remedial policies, such as improving plan administration, altering portfolio allocations, and increasing both employee and employer contributions, are observed to be more promising than either freezing or closing the funds.

The purpose of this paper is to study an innovative rice value chain financing system (VCFS) established in Benin, to identify the determinants of producers and processors access to formal credit, both at intensive and extensive margins. It focuses on multi-stakeholder platforms (MSP) which connect producers and processors in need of credit to potential financial lenders.

The empirical analysis uses rich cross-sectional survey data collected in Northern Benin in 2018. The sample consists of 215 rice producers and 217 rice processors randomly selected through a multi-stage sampling and interviewed with structured questionnaires. The empirical models analyze the determinants of the likelihood to receive a credit and the amount of credit received. To account for the sample selection and censored nature of the main outcome variable, the study considers a Heckman two-stage model coupled with a Tobit model for robustness checks.

The study finds that the MSP are effective in increasing access to formal credit and the amount borrowed. Producers and processors who are members of the MSP are more likely to receive credit and, conditional on being approved for credit borrower, a larger amount. Other key factors that significantly explain access to credit include the use of soft guarantee for securing a loan, the degree of participation in the platform and demographic characteristics. These findings are consistent across the Heckman and Tobit models.

The study attempts to rigorously analyze the factors explaining producers and processors access to credit using cross-sectional survey data. But it has some limitations. The main limitation is the type of data used. Ideally, one would like to run a randomized control trial (RCT) to randomly assign participation in the MSP to causally estimate its impact of access to credit. The second-best option would be to have a panel data covering the period before and after the establishment of the platform. However, in the absence of an RCT or panel data, the study resorts to cross-sectional data and empirical models that account for sample selection bias and the censored nature of the credit received.

One of the key findings of the study is that participation in the MSP (through different value chain stages associations) increases access to formal credit. This highlights an important and effective mechanism, a well-coordinated value chains that integrated lenders, that policymakers can leverage to facilitate access to credit in the agricultural sector.

Access to credit is important to boost agricultural productivity and income. Hence, the findings of the study have social implications in terms of poverty reduction in rural areas.

The study contributes to earlier theories and empirical studies on the demand for credit. It focuses on an innovative VCFS, increasingly adopted in many developing countries, adds originality and value to the understanding of mechanisms to unlock agricultural actors’ access to credit in low-income countries.

The study analyses the preference for forestry insurance amongst tree growers in the Ashanti Region of Ghana. Specifically, the authors examine the factors influencing the amount of forestry insurance and the choice for forestry insurance types.

A total of one hundred and seventy (170) tree growers were sampled for the study. The tobit model, multi-nomial regression and Kendall's tau were employed to analyse the factors affecting the amount for forestry insurance, the choice for forestry insurance types and the perils to forest quality, respectively.

The results of the study indicate that the incidence of bush fire and theft were the key perils that affect forest quality. In total, 52.94% of respondents preferred forest plantation fire insurance as named-peril insurance whereas 70.59% preferred a combination of forest plantation fire, windstorm and consequential loss insurance as multi-peril insurance. The majority (89.4%) of the respondents were willing to pay an amount between Ghc 10.00–49.00 (US$ 2–8) per stand. On the one hand, results of the tobit model reveal age, income, experience in forest management, land ownership and the previous occurrence of fire as the factors affecting the amount for forestry insurance. On the other hand, the multi-nomial results indicate the previous occurrence of fire, gender, forest size, income and risk aversion significantly influenced the choice for forestry insurance types, namely named peril and multi-peril.

Several studies exist for forestry insurance in the developed countries. However, in West Africa specifically, Ghana, studies on forestry insurance appear to be non-existent. Above and beyond, this study, therefore, adds to the paucity of research on forestry insurance in Ghana and serves as a framework for agricultural insurance institutions such as the Ghana Agricultural Insurance Pool (GAIP) and World cover and other agricultural insurance institutions globally.

The purpose of this study is to enhance understanding labour supply dynamics of the UK workers by examining whether and to what extent there is state dependence in the labour supply at both the extensive and intensive margins.

A dynamic two-tiered Tobit model is applied to the first seven waves of Understanding Society: the UK Household Longitudinal Study. The model used accounts for observed and unobserved individual heterogeneity and serially correlated transitory shocks to labour supply to draw inferences on state dependence.

The results show that both observed and unobserved individual heterogeneity contributes to observed inter-temporal persistence of the labour supply of the UK workers, and the persistence remains after these factors are controlled for, suggesting true state dependence at both the extensive and intensive margins of the labour supply. The study also finds that at both the margins, the state dependence of labour supply is larger for females than for males and that for both genders the state dependence is larger for people with low education, mature aged workers and people with long-standing illness or impairment. The results also show that estimates from a conventional Tobit model may produce misleading inferences regarding labour supply at the extensive and intensive margins.

This study adds to the international literature on labour supply dynamics by providing empirical evidence for both the extensive and intensive margins of labour supply, while previous studies tend to focus on the extensive margin of labour force participation only. Also, unlike earlier studies that often focus on females, this study compares labour supply dynamics between males and females. The study also compares the estimates from the more flexible two-tiered Tobit model with that from the conventional Tobit model.

This paper aims to investigate the determinants of women representation on Australian corporate boards under the ASX’s “if not, why not” corporate governance framework. It further aims to improve the study of Geiger and Marlin (2012) by using a theoretically sound two-limit Tobit model to examine the determinants.

This study uses the two-limit Tobit model to examine the determinants of women representation on ASX 500 boards. This approach is used due to the censored nature of the dependent variable.

This study finds that the two-limit Tobit model is an appropriate methodology to accommodate the censored dependent variable. It further finds that firm size, women as chair of boards, corporate governance index, Global Reporting Initiative signatory, debt ratio, average board age, BIG4 auditors, chief executive officer tenure and shareholder concentration are major determinants of women on boards.

The use of only ASX 500 companies and the sample years (2011-2014) may limit the generalisation of the findings.

This is the first extensive longitudinal Australian study to examine the drivers of women representation on corporate boards. It is also the first of its kind to use the two-limit Tobit model to consider these determinants.

This paper addresses the following questions: Why do some firms employ multiple debt types? What explains debt heterogeneity? Is the choice of the source of debt a function of corporate governance?

The author's paper is empirical and uses multiple regression analysis.

Firms under weak corporate governance have a higher propensity to use multiple debt types and have a dispersed debt structure. Contrastingly, firms that are well-managed tend to concentrate debt and borrow predominantly from a few creditors. The author also found that while bank debt is negatively associated with debt concentration, market debt is positively associated with debt concentration.

Firms under weak corporate governance have a higher propensity to use multiple debt types and have a dispersed debt structure. Well-managed firms tend to concentrate debt and borrow predominantly from a few creditors. Bank debt is negatively associated with debt concentration and market debt is positively associated with debt concentration.

Policymakers and practitioners need to account not only for changes in the firm’s total debt level but also for changes within the firm’s debt composition. Understanding a manager’s choice of debt structure can incentivize creditors to effectively monitor and use debt concentration as a form of commitment device that transfers some control rights from the manager to creditors.

While a vast body of corporate finance literature examines the conflict between shareholders and management, there is little empirical work on the conflict between creditors and management. In this paper, the author examines how managerial entrenchment affects debt structure. The results provide a comprehensive picture of how corporate governance influences debt choice(s).

The aim of this paper is to analyze the determinants of the main phases of the innovation process in Portuguese manufacturing firms. The analysis will adopt as its main frame of reference an interactive model of the innovation process, on which empirical tests will be carried out, making use of tobit and probit models and simultaneous equation systems. It is broadly concluded that the relationships shown between the main variables that are typical of the innovation process in the context of Portuguese manufacturing firms are tenuous and unsystematic.

This paper analyses the link between educational qualification structure and information technology (IT) in the service production process. The analysis is based on 1996 cross‐sectional data for approximately 1,000 West German firms. The empirical evidence indicates that IT capital and high‐skilled labor are complements in the production process: firms with higher IT investment output ratios employ a larger fraction of high‐skilled workers at the expense of unskilled workers. To a lesser extent, the positive IT effect carries through for workers with vocational degrees including masters and technicians. Furthermore, we find that firms’ expectations of the future size of their high‐skilled workforce are positively related to their initial IT investment output ratio. To account for censoring in the employment variables, the empirical analysis uses Powell’s Censored Least Absolute Deviations estimators as well as standard Tobit estimators.