درخت حوزه‌های تخصصی

The negative and destructive impact of climate change on the efficiency and productivity of agricultural inputs has been demonstrated in many regions of the world, particularly in arid and semi-arid areas. In this context, the adoption of innovative strategies to increase farmers' flexibility and adaptability to climate change has increased. Hence, understanding the impact of climate adaptation strategies on agricultural efficiency and yields is crucial. This study examined the effects of climate change adaptation strategies, input utilization, and external factors beyond farmers' control on technical efficiency using the Endogenous Modified Stochastic Frontier (EMSF) model. Data were collected from 265 questionnaires distributed among wheat farmers during the 2022-2023 cultivation period, using a stratified random sampling approach. The climate adaptation strategy index was formulated using the Principal Component Analysis (PCA) technique. The PCA revealed that changes in farm size (0.812), adaptation of conservation tillage (0.797), and adjustments in planting dates (0.619) were the most influential factors. Conversely, rainwater harvesting (0.219) and biofertilizer application (0.327) emerged as the adaptation strategies with the lowest factor loadings among farmers. In this study, the average technical efficiency of wheat farmers was calculated to be 82%. The model estimation results showed that labor input, chemical pesticides, chemical fertilizers, water, and machinery significantly and positively contribute to wheat production efficiency. Additionally, the implementation of climate adaptation strategies by farmers reduces technical inefficiency. Variables such as education level, farming experience, access to climate information, and access to credit also effectively reduce technical inefficiency.

In an expansive test of nations over distinctive geographic districts and over a long period of time, we discover restricted nation and variable-specific impacts of central bank straightforwardness on figure exactness and their scattering among an expansive set of proficient figures of monetary and macroeconomic factors. More communication indeed increments estimate mistakes and scattering. So the aim at this study is a systematic review of central bank transparency and capital market reaction. This study was conducted using a systematic review. At first all papers (n=165) related to keywords (capital market reaction and central bank transparency) searched for Persian and English databases; Google, Google scholar, PubMed covering the period from 2012 through 2022 was performed. Then all qualitative and quantitative papers related to central bank transparency selected and analyzed (n=28). As a result to inclusion and exclusion criteria, papers related to central bank transparency were found and analyzed (n=28). Predefined inclusion and exclusion criteria were: papers related to central bank transparency, papers were Persian and English, types of papers were original and all the papers were free full text. In the initial search, 165 papers were found that after reviewing the titles and abstract articles and removing repetitive and non-related, 54 possible related articles were investigated. Of these, 31 papers were omitted from the abstract because of lack of access to the original article and lack of sufficient information. Finally, 28 papers were included in the study. There are very few studies that have examined the effect of central bank transparency on capital market turmoil. The effect of central bank transpar-ency on the domestic capital market has not been studied. There is no agreement in the literature on theoretical discussions on whether increasing central bank transparency affects capital market turmoil. In foreign research, we can also refer to the study of Dinser and Eichngreen (2007) who have studied this effect empirically using the main transparency index. The pre-sent systematic review shows that almost whole of papers on central bank transparency and capital market reaction highlighted similar findings con-cerning monetary policy decisions.

An investment portfolio is a collection of financial assets consisting of investment tools such as stocks, bonds, and bank deposits, among others, which are held by a person or a group of persons. In this research, we use the Markowitz model to optimize the stock portfolio and identify the minimum spanning tree (MST) structure in the portfolio consisting of 50 stocks traded in the TSE. The observable which is used to detect the minimum spanning tree (MST) of the stocks of a given portfolio is the synchronous correlation coefficient of the daily difference of logarithm of closure price of stocks. The correlation coefficient is calculated between all the possible pairs of stocks present in the portfolio in a given time course. The goal of the present study is to obtain the taxonomy of a portfolio of stocks traded in the TSE by using the information of time series of stock prices only. In this research, report results obtained by investigating the portfolio of the stocks used to compute 50 stocks of the Iran Stock Exchange in the time period from January 2012 to October 2022.