Suchergebnisse

In developing countries with an unstable economic system, permanent fluctuation in historical data is always a concern. Recognizing dependency and independency of variables are vague and proceeding a reliable forecast model is more complex than other countries. Although linearization of nonlinear multivariate economic time-series to predict, may give a result, the nature of data which shows irregularities in the economic system, should be ignored. New approaches of artificial neural network (ANN) help to make a prediction model with keeping data attributes. In this paper, we used the Tehran Stock Exchange (TSE) intraday data in 10 years to forecast the next 2 months. Long Short-Term Memory (LSTM) from ANN chooses and outputs compared with the autoregressive integrated moving average (ARIMA) model. The results show, although, in long term prediction, the forecast accuracy of both models reduce, LSTM outperforms ARIMA, in terms of error of accuracy, significantly.

This study estimates and compares healthcare expenditure patterns of different income deciles of urban households by ordinary least square (OLS) method. Data is obtained from houshold survey data and includes healthcare expenditure, family income, the education level of parents, number of children and the average age of parents during 2009-2014. The purpose is to identify the effectiveness of each variable on healthcare expenditure between different income deciles. Moreover, it will be examined that if there is any significant difference between effects of variables on healthcare expenditure in different income deciles. The results indicate that the pattern of healthcare expenditure varies between different income deciles. The first and second deciles show a similar pattern and the level of education of parents doesn't have any significant effect on the healthcare expenditure. In these deciles, a percent increase in family income, increases the healthcare expenditure less than 1 percent. In addition, other variables except than the education level have a positive effect on the healthcare expenditure. On the other hand, almost the same pattern is observed in other income deciles as well. Thus, family income, the average age of parents and number of children demonstrated a positive effect on healthcare expenditure and the education level of parents showed a negative effect. This finding seems to be related to the preventive effects of education. What's more is that in the ninth and tenth deciles, a percent increase in family income, leads to more than 1 percent increase in healthcare expenditure. Therefore, the most prominent suggestion to healthcare authorities is to improve the level of awareness of family. And also, this instruction can be categorize base on the average age of parents. This could be done through government agencies or insurance authorities. DOI:10.5901/mjss.2017.v8n2p301