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Long-term forecasts about commodity market indicators play an important role in informing policy and investment decisions by governments and market participants. Our study examines whether the accuracy of the multi-step forecasts can be improved using deep learning methods.

We first formulate a supervised learning problem and set benchmarks for forecast accuracy using traditional econometric models. We then train a set of deep neural networks and measure their performance against the benchmark.

We find that while the United States Department of Agriculture (USDA) baseline projections perform better for shorter forecast horizons, the performance of the deep neural networks improves for longer horizons. The findings may inform future revisions of the forecasting process.

This study demonstrates an application of deep learning methods to multi-horizon forecasts of agri-cultural commodities, which is a departure from the current methods used in producing these types of forecasts.

Following the recent global financial crisis, US regulatory agencies issued laws to implement the Basel III accords to ensure the resiliency of the US banking sector. Theories predict that enhanced regulations may alter credit issuance of the regulated banks due to increased capital requirements, but the direction of changes might not be straightforward especially with respect to the agricultural loans. A decrease in credit availability from banks might pose a serious problem for farmers who rely on bank credit especially during economic recessions. The paper aims to discuss these issues.

In this study, the impact of Basel III regulatory framework implementation on agricultural lending in the USA is examined. Using panel data of FDIC-insured banks from 2008 to 2017, the agricultural loan volume and growth rates are examined for agricultural banks and all US banks.

The results show that agricultural loan growth rates have slowed down, but the amount of agricultural loan volume issuance still remained positive. More detailed examination finds that regulated agricultural banks have decreased both the agricultural loan volume and their loan exposure to the agricultural sector, showing a possible sign of credit crunch.

This study examines whether the implementation of the Basel III regulation has resulted in changes in agricultural loan issuance by US banks as predicted by the lending channel theory.