in: International Research and Reviews in Economics and Administrative Sciences, Gülsün İŞSEVEROĞLU,Mustafa METE,Cumhur ŞAHİN, Editor, Serüven Yayınevi, Ankara, pp.121-138, 2023
This study examines the impact of short and long-term
agricultural credits on agricultural GDP in Turkey. The value of agricultural
gross domestic product serves as an indicator of economic growth in the
agricultural sector in the study. The indicator of agricultural credit is added
to the model as the short and long-term agricultural credit values provided by
banks. Quarterly data from the period 2005:Q4 to 2023:Q3, which has been
seasonally adjusted, is utilized for estimating the econometric model. All
series are estimated by applying a logarithmic transformation. Agricultural
credits are analyzed for the first time by categorizing them into short and
long-term credits unlike other studies. In this context, the study first
investigates whether the variables contain unit roots, and the Augmented
Dickey-Fuller (ADF) unit root test is applied to each variable. The
Autoregressive Distributed Lag (ARDL) boundary test method and the Vector Error
Correction Model (VECM) are used in the coefficient estimation of variables
found to be stationary at different levels. According to the ARDL long-term
boundary test results, it is determined that there is a cointegration
relationship between the variables. Moreover, a 1% increase in long-term
agricultural credits increases agricultural GDP by 0.08%. Before moving on to
the short-term error correction prediction results in the model, diagnostic
test results are provided. According to the diagnostic test results, there are
no problems of changing variance and autocorrelation in the model, the error
terms are normally distributed, and there is no specification problem at the
model determination stage. Finally, the short-term error correction model is
estimated, and the short-term error correction coefficient is founded -0.402. This result implies that the error
correction mechanism is in operation. In other words, it is determined that
short-term imbalances are corrected in (1/0.402) = 2.49 periods. Then, the
model is tested for structural breaks with CUSUM and CUSUMS tests, and it is
concluded that the model prediction results are consistent and stable. It is considered that agricultural
credit interest rates provided to farmers should be kept low; insurance and
risk management tools should be offered against natural disasters, diseases,
and price fluctuations to ensure the security of credit repayments; to promote
the widespread use of technology in agriculture, credit support should be
increased, and transitions to sustainable agricultural practices should be
encouraged; and monitoring and evaluation mechanisms should be established to
assess the effectiveness of credit utilization.