In 1989 when the Berlin Wall collapsed there was very little foreign direct investment (FDI) in Central and Eastern Europe (CEE), but more than 15 years later there is about 90 billion US dollars per annum flowing into the CEECs. Consequently, there has been a significant increase in empirical literature on the determinants of FDI in CEECs since then, however, most of the literature has analysed the scale of investment, where the determinants of the size of investment between different pairs of countries are modelled. The few studies that investigate where MNEs choose to invest rely either on Multinomial logit (MNL) or Nested logit (NL) models. These models, however, are not sufficiently flexible to analyse the investment location choices of MNEs. The MNL model is subject to restrictive assumptions regarding the substitution patterns across investment location alternatives and the absence of random taste heterogeneity across decision-makers, while the NL model only partially relaxes the independence of irrelevant alternatives (IIA) assumption in order to accommodate the substitution across alternatives to a limited degree. Furthermore, the existing literature on the determinants of FDI usually uses country- and industry-level data and does not incorporate investing firm characteristics, whereas the decision where to invest does not only depend on opportunities offered by foreign markets and industries but also on investing firms’ individual characteristics.

This paper therefore makes two principal contributions. First, it applies the Latent Class (LC) model to investigate investment location choices by MNEs for the first time, merely allowing for investing firms’ heterogeneity by the segmentation of investing firms into a predetermined number of classes and the estimation of parameters separately for each class. The LC model is superior to the Mixed logit (ML) model in that it does not require choosing distributions for random parameters, which is one of the most challenging tasks in the specification of the ML model, instead the investing firm heterogeneity is captured with discrete distribution. The investment location choices of MNEs will not only depend on observed attributes, but also on latent heterogeneity that varies with unobserved factors.

Second, this paper makes use of a multi-level data set – allowing firm, industry (or sector) and country effects to simultaneously determine the firm-level FDI location decisions. The data covers 1,108 investment location choices of firms in the EU15, Norway, Switzerland, Russia, Japan and the USA into 13 Central and Eastern European Counties (CEECs) – the 12 recent EU member states excluding Cyprus and Malta, but including Croatia, Russia and Ukraine - over an eleven year period from 1997 to 2007. The estimation result shows that firms investing in different sectors and firms of different size and profitability benefit from location factors to a different degree.