Purpose: Food security is a critical global challenge that is influenced by research and innovation in the field. Therefore, the objective of this study is to analyze the scientific output of developing countries in food security and examine its relationship with patents and GROSS DOMESTIC Product (GDP).Methodology: This applied research utilized the Scientometric approach. A total of 8,416 papers published between 1992-2023 in the field of food security by developing countries were included in the study using citation databases from Clarivate Analytics. Additionally, patent registrations from the WIPO database and GDP data from the World Bank were analyzed. Information was collected through note-taking, and the data was analyzed using Pearson's correlation coefficient.Findings: The findings reveal an upward trend in the publication and citation of scientific outputs related to food security in developing countries. China has higher numbers of papers, patents, GDP, and food production index compared to Iran, Japan, and South Korea. There is also a positive correlation observed between population and the number of papers, GROSS production and the number of papers, food production and the number of published papers, as well as the number of patents and papers citing scientific outputs of countries.Conclusion: These results highlight the significant relationship between increasing scientific output, GDP, the number of patents, and food security. Greater emphasis on food security contributes to enhanced scientific output, GDP, and innovation. Similarly, increasing scientific output, GDP, and innovation positively impact food security in countries.Value: This study emphasizes the importance of scientific outputs in driving technological advancements, innovations, and ultimately, ensuring food security in developing countries.

This paper provides a brief technical survey of the historical national accounts of Iran. Gaining access to longer-term time series in compliance with concepts, classifications and standards comparable to the present one help fulfill quantitative studies in the area of business cycles. Despite the shortage of reliable, standardized and classified information, the methodology applied in this paper could present data for a 70 year period, including the existing 48 years time series which is available now. The historic endeavors of the pioneer researchers in the field of the system of national accounts, despite certain ambiguity and shortcomings, have been gateway in the context of historical data, compilation.

Higher education is important to the socio-economic development. This paper examine the causality between investment in higher education and GROSS DOMESTIC product (GDP) in Iran.  To this end, standard Granger causality test, Hsiao test, and ARDL method have been applied to test the hypothesis that investment in higher education causes GDP to rise. The period of the study is 1974-2004. The findings of the research show that investment in higher education neither causes GDP, nor is caused by GDP. All three methods confirm this result.

GROSS DOMESTIC product (GDP) is one of the key indicators of macroeconomics. Predicting this index is very important in the economic planning of the country, because this variable reflects the general state of a country's economy. So far, many models have been proposed to predict this variable, but models that use accounting information have not been considered. The purpose of this paper is to examine the relationship between GDP and total corporate profits, as one of the known variables in accounting. For this purpose, the quarterly time series data of macro level companies of Tehran Stock Exchange and macroeconomics in the period 2009 to 2018 are analyzed in two stages. In the first step, the relationship between these two variables is determined by specifying a linear regression model that will be estimated using the least squares method. To evaluate the predictive power of this model, the root mean square error (RMSE) criterion is estimated in two scenarios with total corporate profit and no corporate total profit. Second, the GDP response to the shock to firms' profits is estimated through a vector auto regression (VAR) model, and the contribution of this variable to GDP fluctuation is measured. The results show that the profit of all companies improves GDP forecast in the leading horizons. Also, the shock to the profits of all companies, as much as a standard deviation, explains about 28% of GDP fluctuations.

The recent theories of economic growth indicated human capital and technology knowledge have an important role on economic growth. This study is going to investigate the role of human capital on GDP of Iran. We use James Raymo (1995) model which includes three variables: physical capital, labor force and human capital. Using ) cointegration method of Johanson and Juselius, The results of this paper suggest human capital has a positive impact on GDP in longrun, while it has a little and negative impact on GDP in short-run.

The main objective of this study is to evaluate the impact of changes in energy consumption on real GDP in Iran within the framework of the non-linear smooth transition autoregressive method between 1965 and 2013. In this regard, the linear model is tested against a nonlinear model. It is found that the nonlinear model has better estimation. Then, using Trasvirta test, the nonlinear logistic model is estimated. The variations in the independent variables are divided into three parts including up, low and middle thresholds of changes), based on the nonlinear logistic model. The results show that the effect of gas consumption on the real GDP is U-shaped. This means that the low threshold rises to the middle threshold, and the middle threshold declines to the high threshold. In the case of electricity consumption, the results indicate that a positive and increasing relationship exists in all the thresholds. Positive changes in oil consumption in the low threshold have a positive effect on GDP changes, and this effect is reduced by moving from the low to the up threshold; in the up threshold, the effect will be in the opposite direction of oil consumption changes.