| dc.description.abstract | The first paper examines the impact of the microfinance sector on small/ micro enterprises in Ghana. The study uses 2007 BEEPS data and employs the financing constraints approach to study if the presence of microfinance institutions has been successful in alleviating financing constraints associated with small enterprises. This is done by comparing investment sensitivity to internally generated funds (cash flow) in enterprises with and without access to microfinance institutions. The study also uses a Propensity Score Matching method to reinforce/ support the results obtained from the financing constraints approach. The results obtained from the analyses indicate that small/ micro enterprises in areas with adequate MFIs have investment less sensitive to the availability of internal funds due to the fact that they have better access to external funds, and thus imply that the microfinance sector is alleviating financing constraints in the country.
The second paper uses the Ricardian (Hedonic model) approach to determine the impact of climate change on agricultural farmland values for the southeastern United States. The analyses employ a 5-year pooled cross-sectional data from the ARMS database, climate data from the GHCND and soil data from the SSURGO database. Marginal effects and climate impact projections for 2100 from the three Atmospheric Oceanic General Circulation Models (Hadley CM3, ECHO-G and NCAR PCM) are used in calculating the impacts on the regional farmland values. The Ricardian regression results show that farmland values increase with higher winter and summer temperatures but fall with higher spring and fall temperatures. Winter and summer temperatures have a positive but declining impact on farmland values, whereas spring and fall temperatures have negative and increasing impacts. The results also show that an increase in spring precipitation increases farmland values whilst increases in winter, summer and fall precipitations tend to decrease farmland values. Spring precipitation has a positive but declining impact on farmland values, whereas precipitation in the winter, summer and fall have negative and increasing impacts. The marginal effects indicate that higher annual temperature is beneficial for farmland values throughout the region with the exception of Florida and Mississippi. Increases in annual precipitation are detrimental to most of the states except Alabama, Mississippi and Tennessee. The marginal effects for the seasonal temperature and precipitation also varied significantly across the states. Lastly, the projections show that the aggregate farmland value for the entire Southeast US is likely to decrease under the three model scenarios considered in the analyses.
The third paper examines the factors and behaviors that affect Southeast US farmers’ ability to meet their loan payment obligations within a stipulated loan term. The study also estimates a credit risk model using farm-level financial information to determine the credit worthiness of various different farmers in different states and their possible repayment capabilities. The study uses a 10-year (2003-2012) pooled cross-sectional data from the USDA ARMS survey data (Phase III). A probit approach is used to regress delinquency against various borrower-specific, loan-specific, lender-specific, macroeconomic and climatic variables for the first part, whilst a logistic approach is used to regress farmers’ coverage ratio (repayment capacity) on financial variables (liquidity, solvency, profitability, and financial efficiency) in addition with tenure, to determine how creditworthy the various kinds of farmers are, and in what particular states. The results show that older farmers, farmers with larger farms, farmers with insurance, farmers with higher net income, farmers with smaller debt to asset ratio, farmers with single loans and those that take majority of their loans from sources apart from commercial banks are those that are less likely to be delinquent. Temperature and precipitation increases also lowers farmer delinquency, unless in excessive quantities where certain thresholds are exceeded. The results for the credit model also show which particular farmers and in what states are more likely to be creditworthy based on their financial variable information. | en_US |
