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For some variables it is difficult to assign them to one of the three categories. For instance ownership of the building can be seen as a firm internal factor, but also as a site characteristic. Hence we adopt an eclectic approach for the operationalisation of the explanatory stated preference of the firms with regard to migration in this model variables in the packers and movers pune and movers and packers pune empirical model.

Before turning to the empirical results some remarks will be made about the data and the model. The analysis is based on a very rich micro data set derived from regular surveys among the panel of firms managed by the Faculty of Spatial Sciences of the university of Groningen. We use data for 1338 firms that we questioned in 1995/ 1996. A detailed description of the data can be found in Van Steen 1998a. due to the panel character of the data for most firms in the sample we have also information at earlier points in time.

From the survey we know the actual spatial behavior of firm for each year from 1980 and also the propensity to move within the next two years. We have detailed information about the present location characteristics of firms and this information can be used to explain future migration. If firms moved in previous years the present location is the final result. In this paper we will focus on the stated preference of the firms with regard to migration.

Firms were asked to indicate the probability of moving in 1996 or 1997. They could choose from the following categories: 0%, 0-10%, 10-25%, 25- 50%, 50- 75%, 75- 90%, 90- 100% and 100%. For the empirical analysis we interpret this at that the respondent expresses a preference with an ordinal ranking. There is no significance to the unit distance between the set of observed values. With this eight categories the dependent variable y= PMOVE can take values between 0 and 7.

Of all firms 60% answered that they will certainly not move in the next two years. Almost a quarter shows a propensity to move of less than 10% and about 10% indicate that three is a chance of more than 25% that they will move to another location.

For this type of dependent variable the ordered probability model is a suitable tool of analyses see Greene, 1995, p. 469- 481. The two alternative model types the ordered logit and the ordered probit give more or less the same result up to a scale factors.

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