Multi-level determinants of inward FDI ownership

In this paper, we empirically analyse the determinants of FDI ownership into developing countries. We do this by using firm-level data obtained from the Enterprise Surveys data of the World Bank and country level data from various sources. Using a multi-level logit model, we analyse how institutional and structural variables at both firm and country levels impact inward FDI. In our view, there is a gap between analysis at the country level studies and firm level studies on inward FDI. In this paper, we fill the gap by doing a multi-level regression analysis, taking into account both firm variables and country characteristics to explain inward FDI ownership. We find that firm structural characteristics and obstacles they face most affect inward FDI. While some macroeconomic variables such as GDP per capita, inflation and openness have a significant influence, other variables that measure institutional quality of a country do not have any statistically significant influence on FDI inflow

The Mirage of Action-Dependent Baselines in Reinforcement Learning

Policy gradient methods are a widely used class of model-free reinforcement learning algorithms where a state-dependent baseline is used to reduce gradient estimator variance. Several recent papers extend the baseline to depend on both the state and action and suggest that this significantly reduces variance and improves sample efficiency without introducing bias into the gradient estimates. To better understand this development, we decompose the variance of the policy gradient estimator and numerically show that learned state-action-dependent baselines do not in fact reduce variance over a state-dependent baseline in commonly tested benchmark domains. We confirm this unexpected result by reviewing the open-source code accompanying these prior papers, and show that subtle implementation decisions cause deviations from the methods presented in the papers and explain the source of the previously observed empirical gains. Furthermore, the variance decomposition highlights areas for improvement, which we demonstrate by illustrating a simple change to the typical value function parameterization that can significantly improve performance

The MERG Suite: Tools for discovering competencies and associated learning resources

This is an Open Access article distributed under the terms of the Creative Commons Attribution Licens

Data envelopment analysis in financial services: a citations network analysis of banks, insurance companies and money market funds

Development and application of the data envelopment analysis (DEA) method, have been the subject of numerous reviews. In this paper, we consider the papers that apply DEA methods specifically to financial services, or which use financial services data to experiment with a newly introduced DEA model. We examine 620 papers published in journals indexed in the Web of Science database, from 1985 to April 2016. We analyse the sample applying citations network analysis. This paper investigates the DEA method and its applications in financial services. We analyse the diffusion of DEA in three sub-samples: (1) banking groups, (2) money market funds, and (3) insurance groups by identifying the main paths, that is, the main flows of the ideas underlying each area of research. This allows us to highlight the main approaches, models and efficiency types used in each research areas. No unique methodological preference emerges within these areas. Innovations in the DEA methodologies (network models, slacks based models, directional distance models and Nash bargaining game) clearly dominate recent research. For each subsample, we describe the geographical distribution of these studies, and provide some basic statistics related to the most active journals and scholars

The Past and Future of Evolutionary Economics : Some Reflections Based on New Bibliometric Evidence

This document is the Accepted Manuscript version of the following article: Geoffrey M. Hodgson, and Juha-Antti Lamberg, ‘The past and future of evolutionary economics: some reflections based on new bibliometric evidence’, Evolutionary and Institutional Economics Review, first online 20 June 2016. The final publication is available at Springer via doi: http://dx.doi.org/10.1007/s40844-016-0044-3 © Japan Association for Evolutionary Economics 2016The modern wave of ‘evolutionary economics’ was launched with the classic study by Richard Nelson and Sidney Winter (1982). This paper reports a broad bibliometric analysis of ‘evolutionary’ research in the disciplines of management, business, economics, and sociology over 25 years from 1986 to 2010. It confirms that Nelson and Winter (1982) is an enduring nodal reference point for this broad field. The bibliometric evidence suggests that ‘evolutionary economics’ has benefitted from the rise of business schools and other interdisciplinary institutions, which have provided a home for evolutionary terminology, but it has failed to nurture a strong unifying core narrative or theory, which in turn could provide superior answers to important questions. This bibliometric evidence also shows that no strong cluster of general theoretical research immediately around Nelson and Winter (1982) has subsequently emerged. It identifies developmental problems in a partly successful but fragmented field. Future research in ‘evolutionary economics’ needs a more integrated research community with shared conceptual narratives and common research questions, to promote conversation and synergy between diverse clusters of research.Peer reviewedFinal Accepted Versio

The geographic dimensions of institutions

In this paper we examine the role of institutions relative to economic performance, absolute geography and financial performance of a country. In order to do this, we use the spatial principal component analysis and a spatial canonical correlation analysis to obtain multi-dimensional measure of institutions, economic performance, absolute geography and financial performance of countries. Our analysis shows that the first canonical functions in all the cases give us results that conform to current literature. That is, we find that a higher level of development is correlated to a higher level of institutional quality, deeper financial structure as well as "good" geography of the Jeffery Sachs variety. From the second canonical functions we find that economic growth is correlated to market steering. We further find that geographic conditions need not define the institutional set up of countries. A similar institutional set up need not result in a similar financial structure in countries. We show that there is a necessity to take spatial interactions with neighbouring countries into account while analysing the relationships between institutions, geography, economic and financial performance of a country. We find that space indeed has a strong influence on the prevailing institutional and economic conditions of countries. While the impact of space on geography is very obvious, we find that it has no bearing on the financial performance of countries

Economic development, growth, institutions and geography

In this paper, we test the Rodrik et al (2004) framework to explain differences in development levels across countries by using a broader set of definitions for institutions, geography and economic variables. We use a multi-faceted database to measure institutions in an attempt to go beyond the single-dimension measures that are often employed. We find that institutions trump other factors (geography and trade) when we use GDP per capita as an independent variable. When we expand the dependent variable to include other aspects of development, such as growth and investment, we find that institutions, growth and geography are all important variables. In this case, institutions no longer trump the other factors. In this case, we also find that the same institutions variable that was positively associated to GDP per capita is now negatively correlated with the more dynamic development variable