The number of observations was sufficient when the models were based on individual transactions. In case of regional models based on the survey results we had only 15 observations (hypotheses 1 and 2)<sup>22</sup> , thus we tried to supplement our survey-based estimates with analysis of publicly available data for all regions of Russian Federation. While our survey-based conclusions stood up to these tests, it is important to point out those variables in the survey-based models where not identical, although rather similar, to the ones used in the all-Russia models. One model (hypothesis 4) was entirely based on the publicly available regional information.

# **3. Analysis of Impact of Regional Price Policy, Administrative Barriers and Other Factors of Demand for Land**

**_Hypothesis 1:_** _Demand for land ownership is influenced by the pricing policy_<sup>23</sup> _implemented by regional authorities, and also by non-price factors, such as administrative barriers, duration and cost of procedures, etc._

In the Russian Federation, as mentioned above, most businesses, even those who own their own buildings, do not own the land under their buildings, which is usually owned by the municipal authorities (or owned by another public sector body and administered by the municipality). In this context, land sales prices and rental rates, as _administered prices_ , are constrained by law. While data on land prices are readily available, rental rates are both more variable and less accessible. Therefore, the full range of information one would want for a thorough analysis was not available. Thus while there are some opportunities to study factors affecting demand, one can not look for a normal, market-driven supply curve.

To explain the variation in _the number of land parcel sales (i.e., completed transactions) in Russian regions in 2004,_ we tested several variables. Since only land privatization procedures are relevant for the substantiation of this hypothesis, only observations related to those procedures were selected (Procedure 3А, see Page 10 for the list of procedures). Consequently, any observations related to procedures for leasing a land plot were not included in the regression model.<sup>24</sup> Initially, we tried to fit models with the data from the 15 regions where the surveys were conducted (see, for example, Table 2 above for the list of surveyed regions). Due to a limited number of observations, we had to restrict ourselves to the following three simple models that each tested for the dependent variable<sup>γ</sup> , where:

> 22 Due to limited availability of regional data, this number was even less, mostly 14 or 13 observations depending on a model.

> 23 Federal policy allows sub-national authorities to set the price of land for privatization between specified minima and maxima. According to the Article 2 of the Federal Law on Enactment of the Land Code, "the RF Subject shall adopt the following land prices in the settlements with the following population  numbers:

> (i) More than 3 million inhabitants ─  in the amount from five to thirty times the land tax for one square unit of a land plot;

> (ii) From 500  thousand to  3 million inhabitants  ─  in the amount from five to seventeen times the land tax for one square unit of a land plot;

> (iii) Up to 500 thousand inhabitants, as well as out of the borders of the settlements ─ in the amount from three to ten times the land tax for one square unit of a land plot (for the beginning of the current tax year).”

> 24 Also, while pricing policies for land privatization are Federally regulated and relevant data are available, rental rates for land owned by sub-national authorities is subject to less regulation and comparable data are not available.

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