This research aims to study the relationship between tax planning & performance and the stock prices & dividend payments of companies listed on the Stock Exchange of Thailand SET100 group. It was conducted by collecting information from financial statements annual reports and the information registration forms (Form 56-1) of 69 companies from 2015 to 2019. Descriptive statistics and inferential statistics were used for data analysis including correlation analysis and multiple regression analysis. The study results show that the return on equity ratio (ROE) book value per share (BV) and earnings per share (EPS) ratio positively correlated with the stock prices. The corporate income tax rate to total assets (TAX/ASSETS) the return on total assets (ROA) the return on equity (ROE) and the book value per share (BV) ratio were positively correlated with the dividend yield (DY) ratio. The earnings per share (EPS) ratio had a negative correlation with the dividend yield (DY) ratio and the effective corporate income tax (ETR) ratio had a positive correlation with the dividend payout ratio (DP) with a statistical significance at 0.01 and 0.05 levels.

The objectives of this research were to create a model for time sereries data prices and yields of natural rubber to be more accurate prediction and to compare the proposed model with the classical time series models such as the Holt-Winters Additive Exponential smoothing model (Holt-Winters ES) and the seasonal autoregressive integrated moving average model (SARIMA). The proposed model was a linear mixed model (LMM) consisting with trend autoregression outliers and sesonal terms. Dummy varialbles and Fourier seasonal effects were studied. Bayesian estimation was used and the estimated prices and yields were used for prediction. The results show that the proposed model with a Fouries seasonal effect is the most appropriated comparing with the dummy seasonal effect the Holt-Winters ES and the SARIMA having the least mean absolute values (MAE) both fiting and validating parts. The proposed model with sesaonal dummy variables should be the first consideration for forecasting spatial time series with a seasonal component.

The purposes of this research were 1) to study organic rice production of Praknamdaeng Community Amphawa Samutsongkhram 2) to investigate explicit knowledge of organic rice plantation in Praknamdaeng Community and 3) to discover guidelines on promotion to grow organic rice for food security of Praknamdaeng Community. The population groups were agricultural government officials and Praknamdaeng’s farmers. The research tool was interview analyzed by content analysis. The results revealed as follows: 1) According to organic rice production of Praknamdaeng Community there were 288 hectares (1800 rais in Thai) rice-growing areas and 90 farmers’ families in villages 2 3 4 and 6. The land was full of clay not flooded and in the downstream irrigation area. The weather was humid because it was near the sea. There were many different types of rice varieties grown in Praknamdaeng Community namely; Khao Leuang Patew Chumphon Pathumthani fragrant rice RD 31 Suphan Buri 1 RD 59 RD 47 Sangyod Maung Phatthalung rice Aromatic Black (Hom–nin) rice and Riceberry rice. Rice farming process was mostly taught by villages’ ancestors or experts through learning by doing and working together. The problem of traditional rice growing was soil degradation. The organic rice cultivation in Praknamdaeng Community began in 2005. Khao Leuang Patew Chumphon the loca rice was highly grown. Nowadays 70 percentage of the land was full of GAP organic rice production. The biggest problem for the farmers in the community was drought. 2) As for the appropriate knowledge of organic rice production in Praknamdaeng Community the rice farming processes between traditional and organic rice growing were not different. In the case of organic rice production bio-chemicals were used as herbicides and pesticides but the amount of chemical substances was reduced and only used in a short period for safe. 3) Due to guidelines on promotion to grow organic rice for food security of Praknamdaeng Community there were some guidelines for the 2 groups: farmers and community. The guidelines for the farmers were 1) the pursuit of knowledge or transfer of knowledge to the farmers 2) establishing the learning center of organic rice production in the community by chemical-free cultivation 3) providing organic rice paddy demonstration plot for learning 4) preparing the local people to understand and be volunteers for organic rice cultivation 5) developing farmer organization and 6) promoting comprehensive marketing. The guidelines for the community were 1) in the aspect of the quality of life organic rice consumption has to be promoted for the local people and for food security in the future 2) in the aspect of promotion of farmer career organic rice products can be more value-added make pride and more money for the community 3) systematic community enterprise management 4) support for the networks of producers food processing and distribution of organic rice among other communities and provinces. In the aspect of food security the farmers firstly focus on farmer career stability because they consider it as one of the important careers to produce food to the society. Moreover standard qualified products and suitable demand and supply are included.

The objective of this study was to construct the black pepper prices forecasting model by 4 statistical methods: Box-Jenkins method Holt’s exponential smoothing method Brown’s exponential smoothing method and damped trend exponential smoothing method. Time series of monthly black pepper prices which were gathered from the website of the Office of Agricultural Economics during January 2005 to December 2018 of 168 observations were divided into 2 datasets. The first dataset had 156 observations from January 2005 to December 2017 for constructing the forecasting models. The second dataset had 12 observations from January to December 2018 for comparing the accuracy of the forecasts via the criteria of the lowest mean absolute percentage error (MAPE) and root mean squared error (RMSE). Research findings indicated that for all forecasting methods that had been studied the most accurate method was damped trend exponential smoothing method (MAPE = 6.5773 RMSE = 10.3775)

The purpose of this research was to construct the appropriate forecasting model for the prices of field corn in Thailand using four time series analysis methods including Box-Jenkins method Holt’s exponential smoothing method damped trend exponential smoothing method and combined forecasting method. Time series data from the website of the Office of Agricultural Economics with total 227 months during January 1997 to November 2015 are used and divided into two series. The first 216 months from January 1997 until December 2014 used to build the forecasting models and the last 11 months from January until November 2015 used to compare the forecasting methods accuracies via the criteria of the lowest mean absolute percentage error and root mean squared error. Research finding indicated that combined forecasting model was the most accurate.