论文信息 - Predicting Credit Demand with ARMS: A Machine Learning Approach - 字舞流文

Predicting Credit Demand with ARMS: A Machine Learning Approach

Kevin Patrick | Jennifer Ifft | Ryan Kuhns

[1] Changes in Debt Patterns and Financial Structure of Farm Businesses: A Double Hurdle Approach , 2009 .

[2] The Debt Finance Landscape for U.S. Farming and Farm Businesses , 2012 .

[3] O. Musshoff,et al. Determinants of loan demand in agriculture: empirical evidence from Germany , 2016 .

[4] A. Katchova,et al. Factors affecting farm credit use , 2005 .

[5] A. Mishra,et al. Modeling debt choice in agriculture: the effect of endogenous asset values , 2017 .

[6] M. Morehart,et al. Multivariate Farm Debt Imputation in the Agricultural Resource Management Survey (ARMS) , 2014 .

[7] T. Hubbs,et al. A disequilibrium evaluation of public intervention in agricultural credit markets , 2017 .

[8] J. Ifft,et al. Debt Use by U.S Farm Businesses, 1992-2011 , 2014 .

[9] Carmen Sandretto,et al. Profits, Costs, and the Changing Structure of Dairy Farming , 2007 .

[10] Max Kuhn,et al. Applied Predictive Modeling , 2013 .

[11] E. Dillon,et al. Modelling the effect of farming attitudes on farm credit use: a case study from Ireland , 2012 .

[12] Stefano M. Iacus. Big Data and Social Science - A Practical Guide to Methods and Tools , 2017 .