Ground States for a Stationary Mean-Field Model for a Nucleon

In this paper we consider a variational problem related to a model for a nucleon interacting with the $\omega$ and $\sigma$ mesons in the atomic nucleus. The model is relativistic, and we study it in a nuclear physics nonrelativistic limit, which is of a very different nature than the nonrelativistic limit in the atomic physics. Ground states are shown to exist for a large class of values for the parameters of the problem, which are determined by the values of some physical constants

Symmetric ground states for a stationary relativistic mean-field model for nucleons in the nonrelativistic limit

In this paper we consider a model for a nucleon interacting with the $\omega$ and $\sigma$ mesons in the atomic nucleus. The model is relativistic, but we study it in the nuclear physics nonrelativistic limit, which is of a very different nature from the one of the atomic physics. Ground states with a given angular momentum are shown to exist for a large class of values for the coupling constants and the mesons' masses. Moreover, we show that, for a good choice of parameters, the very striking shapes of mesonic densities inside and outside the nucleus are well described by the solutions of our model

A Meta-Analysis of the Robustness of Market Size and Labour Cost Determinants of FDI

This paper applies a meta-regression analysis to systematically summarise, integrate and synthesise the results of empirical studies that include market size and labour costs as determinants of FDI. Random effects panel estimation is employed separately for the sample of primary studies that use OLS estimation to analyse the effect of market size and labour costs on FDI and for the sample of primary studies that employ discrete choice models to estimate the effect of market size and labour costs on FDI. A number of factors related to model specifications, dataset characteristics and methodologies in the primary studies explain the variation in the estimated t-statistics of the effect of market size and labour costs on FDI across the studies. Most tests for publication bias indicate that the empirical literature on the effect of market size on FDI favours positive estimates while empirical literature on the effect of labour costs on FDI favours negative estimates. None of the literature, however, favours statistical significance.meta-regression analysis, foreign direct investment, market size and labour costs, publication bias

The Location of Foreign Direct Investment in the Central and Eastern European Countries: A Nested Logit and Multilevel Data Approach

This paper generalizes the existing empirical literature on the determinants of the location of FDI, using a nested logit (NL) model and a novel three-level dataset to examine the factors explaining 1,108 foreign investment location decisions into 13 Central and Eastern European countries (CEECs) between 1997 and 2007. The NL model relaxes the multinomial logit model assumption of independence of identically distributed error terms and allows for testing if national boundaries affect the investment location choices of MNEs in the CEECs. In contrast to the existing empirical literature on the investment location choices, the Heteroskedastic Extreme Value model is used as a tool to reveal an appropriate nesting structure. The highly significant empirical results, based on a general underlying economic model of imperfect competition, show that the responsiveness of FDI in the CEECs to country-level variables differs both across sectors and across firms of different sizes and profitability. Hence the results of previous studies that used only country-level data or only industry- and firm-level data may be misleading.Nested logit model, foreign direct investment, multi-level data, heteroskedastic extreme value model

The Location of Foreign Direct Investment in the Central and Eastern European Countries: A Mixed Logit and Multilevel Data Approach

This paper uses the Mixed logit (ML) model and a novel three-level dataset to examine the factors explaining 1,108 foreign direct investment (FDI) location decisions into 13 Central and Eastern European countries (CEECs) over an eleven-year period between 1997 and 2007. The ML model approach is superior to other discrete choice methods in that it allows for random taste variation, unrestricted substitution patterns and correlation in unobserved factors over time. The highly significant empirical results, based on a general underlying economic model of imperfect competition, show that the responsiveness of the probabilities of choices to invest in a particular country in CEE to country-level variables differs both across sectors and across firms of different sizes and profitability. The results generalise previous studies that used only country-level data or only industry- and firm-level data to give a more accurate explanation of the firm-specific investment location decisions.Mixed logit model, random parameters, foreign direct investment, multi-level data, Halton draws

The Latent Heterogeneity in Investment Location Choices of Multinational Enterprises

The heterogeneity of investing firms is an important determinant of the distribution of foreign direct investment (FDI) location decisions. This paper, for the first time, explicitly allows for firms’ heterogeneity by using a latent class discrete choice model and a new multi-level data set to examine over 1100 individual firm FDI-location decisions over an 11-year period. The highly significant empirical results show that the responsiveness of the probabilities of choices to invest in a particular country location to country-level variables differs both across sectors and across firms of different sizes and profitability. Therefore, controlling for investing firms’ heterogeneity is important if robust estimates are to be obtained.d.Latent Class model, firm heterogeneity, foreign direct investment, multi-level data

An Empirical Investigation of the Determinants of the Location of Foreign Direct Investment in the Central and Eastern European Countries Using Multilevel Data

This paper employs a novel multi-level data set and a multinomial logit model - to examine the factors explaining 1,223 foreign investment location decisions by firms in the EU(15), Japan, Norway, Russia, Switzerland and the US in 12 Central and Eastern European countries (CEECs). The highly significant empirical results, based on a general underlying model of imperfect competition, show that the responsiveness of foreign direct investment in the CEECs to country-level variables differs significantly both across sectors and across firms of different sizes and profitability. In particular, in addition to the traditional importance of market size and distance, firm size and the effective corporate tax rate are also important for the location of investment.Multi-level data, foreign direct investment, multinomial logit model

The influence of habitat quality on the foraging strategies of the entomopathogenic nematodes Steinernema carpocapsae and Heterorhabditis megidis

Entomopathogenic nematodes (EPN) are soil-transmitted parasites and their foraging strategies are believed to range from ‘ambush’ to ‘cruise’ foragers. However, research on their behaviour has not considered the natural habitat of these nematodes. We hypothesized that EPN behaviour would be influenced by soil habitat quality and tested this hypothesis using 2 EPN species Steinernema carpocapsae (an ‘ambusher’) and Heterorhabditis megidis (a ‘cruiser’) in 2 contrasting habitats, sand and peat. As predicted from previous studies, in sand most S. carpocapsae remained at the point of application and showed no taxis towards hosts, but in peat S. carpocapsae dispersed much more and showed a highly significant taxis towards hosts. H. megidis dispersed well in both media, but only showed taxis towards hosts in sand. In outdoor mesocosms in which both species were applied, S. carpocapsae outcompeted H. megidis in terms of host finding in peat, whereas the opposite was true in sand. Our data suggest that these 2 EPN may be habitat specialists and highlight the difficulties of studying soil-transmitted parasites in non-soil media