The ‘Neighbourhood Effect’: A multidisciplinary assessment of the case for farmer co-ordination in agri-environmental programmes

In this paper we present a multi-disciplinary analysis of the potential impacts of undertaking similar environmental actions on multiple farms in a small geographic area, using organic farming as a proxy for a co-ordinated approach. Recent papers have called for more co-ordinated efforts between farmers in terms of their environmental actions, but there has been limited applied research demonstrating the environmental benefits or the economic and social implications to farmers of this approach. Comparative analysis of biodiversity, soil and water, and farm profitability were undertaken in England on 32 matched farms in areas of low and high organic farming concentration; qualitative interviews were also conducted with 48 farmers living in two of the eight areas. Findings demonstrate higher overall levels of biodiversity on organic farms (particularly in “hotspot” areas) but this was not universal across the species groups investigated. Higher water infiltration rates were found in organic grasslands, which could prove to be a useful measure to combat flooding. In terms of the technical efficiency of producing these environmental gains, conventional and organic farms in hotspot areas demonstrated equivalent efficiency from a financial perspective. Socio-cultural research identified the different amounts of trust farmers have in their neighbours, based in part on their performance as ‘good farmers’. We discuss the neighbourhood effect with a multi-disciplinary approach and conclude that encouraging local farmer co-ordination can have clear environmental benefits without high economic cost, but must be undertaken with caution - specifically regarding the trade-offs between benefits, local geophysical and social characteristics, and assumptions made about inter-farmer trust.     

Analysis of sectoral credit default cycle dependency with wavelet networks: Evidence from Turkey

In this paper, we investigate the relationship between industrial production and sectoral credit defaults (non-performing loans ratio) cycle by wavelet network analysis in Turkey over the period January 2001–November 2007. We use feedforward neural network based wavelet decomposition to analyze the contemporaneous connection between industrial production cycles and sectoral credit default cycles at different time scales between 2 and 64 months. The main findings for Turkey indicates that industrial production cycles effect the sectoral credit default cycles at different time scales and thus indicate that the creditors should consider the multiscale sectoral cycles in order to minimize credit default rates.     

Health and Financial Strain: Evidence from the Survey of Consumer Finances

Using data from the Survey of Consumer Finances, this study examines the relationship between health status and financial strain controlling for the dual endogeneity between the two factors. Simultaneous two-stage probit models are estimated for self-reported health status and three measures of financial strain. The results from all three models indicate that poor health significantly increases the probability of financial strain. There is little evidence that financial strain contributes to poor health. The findings suggest that severe health conditions may result in larger financial burdens while large financial burdens are unlikely to accelerate a decline in health status. In the end, health may be contributing to widening financial disparities, especially among the poor who are in poor health.     

A Multistage Model of Loans and the Role of Relationships

We develop a multistage model of the loan granting process to understand the contradictory findings of the existing literature on bank‐borrower relationships, credit availability, and loan rates. Upon estimating our model with the 1993, 1998, and 2003 versions of the Survey of Small Business Finances data set, we find that relationships matter in a borrower's decision whether to apply for a loan and in the loan approval/rejection decision by the financial institution. However, the effect of relationships on loan rates depends on the prevailing economic climate. While firms with preexisting relationships obtain credit at lower rates during periods of economic expansion, loan rates are not negatively correlated with preexisting relationships during periods of economic recession.     

Professional financial advice,self‐control and saving behavior

This study investigates whether professional financial advice (“PFA”) can assist households in making better‐informed financial decisions and whether PFA may help households achieve better self‐control in implementing financial plans. In particular, we examine the effects of PFA and self‐control ability on saving behavior, as well as the interaction of PFA and self‐control on saving behavior. We extend the dual‐self model of impulse control and derive three hypotheses: (a) people with higher levels of self‐control save more than those with lower levels of self‐control; (b) PFA has a positive effect on saving behavior; and (c) people with lower levels of self‐control benefit more from obtaining PFA than those with higher levels of self‐control. We use a German household panel dataset SAVE, which was collected annually from 2005 to 2009. Respondents are asked whether they have discussed financial matters with financial advisors in banks, insurance companies or financial service providers. Using a number of behavioral proxies of self‐control, we create an aggregate measure of self‐control through factor analysis. We estimate a fixed‐effects model to identify the effects of PFA and self‐control on financial assets. Empirical results show that both PFA and self‐control have a significant positive relationship with financial assets. The interaction term of PFA and self‐control is a significant predictor of financial assets. We discuss conclusions for the financial advising industry and public policy aimed at consumer financial literacy.