PurposeThis study aims to determine the nexus between agricultural production and agricultural loans for the period Q1 2003–Q4 2018 in Turkey.Design/methodology/approachThe authors employ the time-series analyses within the scope of the study. Firstly, they run the Engle–Granger two-step cointegration test and the Toda–Yamamoto causality analysis. They also use the dynamic ordinary least squares (DOLS) model estimator and estimate the vector autoregression model for predicting the dynamic structure of time series.FindingsThe results of time series analyses reveal that the variables are cointegrated and there are causal relationships between agricultural loans and agricultural production. Also, the variance decomposition findings indicate that the effect of agricultural loans provided by development-investment banks and participation banks on agricultural production has increased over the years, and the deposit banks have a high impact on agricultural production. The results of the DOLS model indicate that agricultural loans have a positive effect on agricultural production.Originality/valueThis research is one of the few studies that comprehensively determines the direction of nexus between agricultural production and agricultural loans in Turkey economy. This is the first contribution of the study in the literature. Another contribution of this study is to investigate the nexus between agricultural production and agricultural loans for banking sector groups. Unlike other studies in the literature, this study calculates the variance decomposition by going beyond unit root and cointegration tests. Thus, this study has deep findings.
One of the major tools in agricultural finance is agricultural loans. Therefore, it is important to investigate the relationship between agricultural loans and agricultural production. In this study we aim to determine whether there is a causality relationship between the agricultural loan and agricultural production value. For this purpose we use the time series data for the years of 2005-2018. In the study, we use Phillips-Perron unit root test to determine the stationarity levels of the variables examined. After we examine the stationary levels of time series, we perform Granger causality test to detect the causality relationship between agricultural loans and agricultural production. As a result of the Granger causality test, we determine that there is a unilateral causality relationship from the agricultural loan variable to the agricultural production value variable, that is, it can be said that agricultural loans affect the value of agricultural production. For this reason, we can state that facilitating the use of loans in the agricultural sector, and increasing the lending institutions will contribute to the increase of agricultural production value in meeting the input needs of the producers effectively.
ÖZET: Türkiye'de yaş meyve ve sebze pazarlamasında çeşitli kanallar mevcuttur. Ancak çoğunlukla yaş meyve ve sebze pazarlaması Toptancı Hal'lerinde yapılmaktadır. Çalışmada, üretim bölgesi olarak Mersin Yaş Meyve ve Sebze Toptancı Hali'nde faaliyette bulunan aracılarla anket yapılmıştır. Türkiye'de yaygın yaş meyve ve sebze pazarlama kanallarından, en uygun olanı sağlık, maliyet, süre ve kayıt altına alınma kriterlerine göre belirlenmeye çalışılmıştır. Bu amaçla Analitik Hiyerarşi Prosesinden (AHP) yararlanılmıştır. AHP sonuçlarına göre, Mersin Toptancı Hali'nde en uygun pazarlama kanalı; "Üretici → Üretim Merkezi Komisyoncusu → Tüketim Merkezi Komisyoncusu → Perakendeci → Tüketici" %42,68 oranla ilk sırada yer almış bunu "Üretici → Tüketim Merkezi Komisyoncusu → Perakendeci → Tüketici" %35,90 ile takip etmiştir. AHP sonuçları Tobit model ile analiz edilmiştir. Anahtar Sözcükler: Yaş meyve ve sebze toptancı hali, pazarlama kanalı, AHP, Tobit model
Bacterial activities of milk obtained from Savanna brown doe, were chemically assessed before and after pasteurization. A total of 60 L of milk was collected from a randomly selected doe in 10 different herds within Minna, and was stratified into 3 treatments (T 1 -T 3 ), with 5 replicates (R 1 -R 5 ), in a completely randomized design (CRD). After collection one quarter of it was homogenously pooled and immediately taken to the laboratory for analysis (T 1 ), the other portion was left on the laboratory table to ferment (T 2 ) .The last quarter was pasteurized using the145°F (63°C) for 30 min (LTLT) (T 3 ). The biochemical results revealed an uneven disparity in all the treatments with high protein for fresh milk while fat was highest for pasteurized milk, this could be attributed to low activity of proteolytic and spoilage microorganism in fresh milk and the multiplication of fat splitting microorganism in the unpasteurized milk, the bacterial count (Pseudomonas, Lactobacillus, Bacillus, Staphylococcus and streptococcus) and frequently occurrence in treatments T 1 -T 2 indicate that these treatments was heavily loaded with different types of bacteria (proteolytic, lipolytic, coliform and lactic acid) when compared with T 3 (pasteurized), this could be due to lack of proper hygienic measure at all stages of collection and storage and/or pasteurization and diseased udder at the time of milk collection. Producer of milk and milk products should be pasteurized immediately after collection and should observe absolute aseptic measures when handling milk and milk products.
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