The distributed lag effect of a unit change in one of the explanatory variables on the dependent variable is one of the major shortcomings of the standard linear regression model. Such a model, that specifies a causal relationship between a variable and its determinants, states that a unit change in one of the explanatory variables can result in a change in the dependent variable only during the period specified by the model. In practice, however, changes in, for example, the firm's advertisement may affect its sales over various periods. This paper aimes to develop an approach to estimate the distributed lag effects of a temporary (once -and - for - all) and a permanent (continuous) change in the explanatory variables by using information given by a COINTEGRATION model.

In this paper using nutrients elasticity tools, consumer behavior of urban and rural area was surveyed in long run and short run during 1981-2005. To calculate nutrients elasticity (as a main purpose of this paper), we use Huang and Lin demand model (2001) and Lan-Caster s consumption technology equation. Finally N=S *D matrix was employed to calculate nutrients elasticity, where N contained nutrients elasticity values (related to income variations), S also indicated the percentage of a specific nutrients in each food and D defined the demand elasticity matrix. According to subgroup of food income elasticity, we suggest to subsidize “bread, grains and their products” and also “milk and its products and egg” to enhance the quality level of consumption pattern of urban and rural areas. Also price elasticity of meat subgroups price is highest in urban societies and according to the lack of consumption effects of it, governmental implementation of supporting programs will be necessary. The result of income elasticity of nutrients shows that the more costs taken in each subgroup of foodstuff, the more is consumption of nutrients consumption.

Studies in applied econometrics and related disciplines are widely using time series techniques. Sound application of these techniques requires the satisfaction of their underlying assumptions. One of these techniques is ARDL Model. There are a number of examples in the published works in Iranian economic studies which suffers from misconceptions leading to biased and inconsistent estimates of parameters. For example, without assuring the exogeniety of the other RHS variables of the model, estimates are biased and inconsistent. Although fitting an ARDL model to exogenous and/or predetermined RHS I (0) and/or I (1) variables may seem appropriate,however, to continue the path leading to the extraction COINTEGRATION vectors, would be a misleading strategy. The aim of this paper is to highlight these misconceptions in the application of ARDL technique. To this end, after a theoretical survey of the concept, a dynamic simultaneous equation model (DSEM) of macroeconomic equations is introduced and simulated. The simulated series are used to estimate various versions of the model including VAR, ARDL, DSEM, VECM. Then the correct and incorrect application of ARDL model is specified by using two scenarios.