Recognition of Demand Factors for Domestic Tourists of Mashhad (Using the two stage-model of Heckman)

In many countries، tourism acts as an engine for development through foreign exchange earnings and the creation of direct and indirect employment. Tourism contributes 5% of the world’s GDP. It accounts for 6% of the world’s exports in services being the fourth largest export sector after fuels، chemicals and automotive products. Tourism is responsible for 235 million jobs or one in every 12 jobs worldwide (UN World Tourism Organization، 2012) [1]. As Iranian economy is related to the oil industry which is a nonrenewable natural resource، concerning other economic sectors such as tourism is so important. One kind of tourism which is so popular in Iran is religious tourism. In some cases، the birth or demise places of religious figures are locations for tourists to visit. Countries، in which many of these places are located، are usually involved in attracting tourists and earning more income through offering various services to different tourist segments. It seems that the purposes of religious tourism inherently relate to religious beliefs and tenets. The aim of this paper is to perform an econometric analysis of the domestic tourism of Iranian Households to Mashhad city as a famous religious location in Iran. Mashhad has always been culturally، economically and socially important، Because of Holy Razavi Shrine [2] located there. Iranian people''s beliefs are considered another reason to visit Razavi shrine. The destination for most of the Iranian domestic trips has been the city of Mashhad annually. In 2008 during the period from spring to winter، the number of domestic tourists to Mashhad reached 4. 7، 7. 1، 5. 1 and 2. 6 million persons respectively، totally 19 million persons. The number of tourists to Mashhad included 33. 5 percent of the entire number of national travelers (SCI report، 2008). In this research، we are going to estimate the demand function to Mashhad for domestic tourism using two stages Heckman model. The data were collected by the statistical center of Iran، (SCI) in 2008 which is the main data source in Iran. SCI has collected the data about the tourism behavior of Iranian households in 2008 and the data is the only and the most important database for tourism. For gathering the data، 4416 households in 4 seasons of 2008 were interviewed by SCI. To be able to estimate the demand function، the households who have travelled to Mashhad at least one time a year and have spent at least one night there، were selected. After making these selections، 371 cases were left، which is 8. 4% of the original sample. This was the sample that was used for constructing the model. Some price indexes were added to the data. These price indexes are based on monthly price indexes of hotels and restaurant، public transport and total price index collected by Statistics Center of Central bank of Iran. Also، the consumer price index was added. To model the demand for tourism of Iranian households to Mashhad، Heckman two-staged model will be used. It has been assumed that the households go through two stages of decision-making. In the first stage، the household members decide on whether to undertake the trip or not. In other words، the households initially decide on undertaking the trips and then، make decisions about the destination، number of trips، expenditures on trips، i. e. To estimate the demand equations، a selection had to be made to find all households that went on a trip and consequently had expenditure. This was necessary because it was possible that the large amount of zeros in the sample could have influenced the magnitude and statistical significance of the estimates. The first stage functioned as a selection mechanism assigning at one to all households that had expenditures on domestic tourism makes the selection. The first stage model was a binary choice model. In this model households had the choice between going on a trip and consequently having expenditure on tourism and not going on a trip and not having expenditure. The binary choice model had the form of a Probit-model to make sure that probabilities were between zero and one (Coenen، 2003، P 117). By Heckman''s two-staged model to determine the factors affecting any of the above-mentioned sets، Tobit model was broken down to probit model and the linear regression model. The dependent variable in probit model includes a two-termed variable، in which number one indicates the willingness to undertake an activity (trips). This variable is made based on the dependent variable in Tobit model. To do so، those 14Y''> s with value of zero، remain zero. As a result، the dependent variable of probit model is made for all observations. Discussion and The results show that the variables such as head of households'' age and financial problems have negative effect on the willingness to travel of the households in general. The next part of the research results show that the variables such as price index of tourism commodity and households'' income sector have negative effect on the number of households'' travels، the region of living and seasonal conditions and head of households'' income have positive effect on the number of households'' travels. Also the price of travel commodities and the households'' income has positive effect on the travel expenditure and the households'' less distance region of living has negative effect on the travel expenditure. The results of elasticity accounting of the research show that the demand elasticity of the Mashhad traveling numbers was -0. 55. And the income elasticity of it was 0. 3. The expenditure elasticities have confirmed the above results. The results of the research، shows that traveling to the Mashhad city is as the necessity good for domestic tourists. Domestic tourists’ households in the sample of the research have traveled to the city even if their heads were old or their traveling time was in the cold seasons. Their tourism behavior were some different in this kind of traveling in compare of the traveling behavior in general. It seems that if the policy makers want to have the best decision in tourism industry، they should have enough concern to the different behavior of tourists in different kind of tourism. By this way they can offer the best services to their customers.