Manfred M. Fischer

Wirtschaftsuniversität Wien | WU · Department of Socioeconomics

US yield curve dynamics are subject to time‐variation, but there is ambiguity about its precise form. This paper develops a vector autoregressive (VAR) model with time‐varying parameters and stochastic volatility which treats the nature of parameter dynamics as unknown. Coefficients can evolve according to a random walk, a Markov switching process,...

Groundwater is exploited uncontrollably due to population growth and industrialization in different parts of the world. The purpose of this study is to evaluate the groundwater potential by advanced machine learning algorithms using topographical, hydrological, environmental and geological criteria. To do this, three advanced machine learning algor...

Geospatial artificial intelligence (GeoAI) has emerged as a subfield of GIScience that uses artificial intelligence approaches and machine learning techniques for geographic knowledge discovery. The non-regularity of data structures has recently led to different variants of graph neural networks in the field of computer science, with graph convolut...

Time-varying parameter (TVP) regressions commonly assume that time-variation in the coefficients is determined by a simple stochastic process such as a random walk. While such models are capable of capturing a wide range of dynamic patterns, the true nature of time variation might stem from other sources, or arise from different laws of motion. In...

The Handbook of Regional Science is a multi-volume reference work providing state-of-the-art information, prepared by respected scientists in the field. This second edition includes new sections on the history of regional science, and on regional policy. It has been thoroughly updated to reflect new developments, including new chapters on R&D colla...

Faced with the problem that conventional multidimensional fixed effects models only focus on unobserved heterogeneity, but ignore any potential cross-sectional dependence due to network interactions, we introduce a model of trade flows between countries over time that allows for network dependence in flows, based on sociocultural connectivity struc...

The focus is on cross-sectional dependence in panel trade flow models. We propose alternative specifications for modeling time-invariant factors such as sociocultural indicator variables, e.g., common language and currency. These are typically treated as a source of heterogeneity that is eliminated using fixed effects transformations, but we find e...

Big Data on cities and regions bring new opportunities and challenges to data analysts and city planners. On the one side, they hold great promise to combine increasingly detailed data for each citizen with critical infrastructures to plan, govern and manage cities and regions, improve their sustainability, optimize processes and maximize the provi...

This paper explores the relationship between household income inequality and macro-economic uncertainty in the United States. Using a novel large-scale macroeconometric model, we shed light on regional disparities of inequality responses to a national uncertainty shock. The results suggest that income inequality decreases in most states, with a pro...

This paper uses a factor‐augmented vector autoregressive model to examine the impact of monetary policy shocks on housing prices. To simultaneously estimate the model parameters and unobserved factors we rely on Bayesian estimation and inference. Policy shocks are identified using high‐frequency surprises around policy announcements as an external...

This chapter offers a review on modern entrepreneurship analysis, against the background of regional development. Regions with an entrepreneurial culture tend to be forerunners in a competitive economic process. After a conceptual discussion on the importance and the measurement of entrepreneurship, the contribution discusses critical success facto...

The focus is on cross-sectional dependence in panel trade ow models. We propose alternative speci cations for modeling time invariant factors such as socio-cultural indicator variables, e.g., common language and currency. These are typically treated as a source of heterogeneity elim- inated using xed effects transformations, but we nd evidence of c...

This paper develops a Markov switching factor-augmented vector autoregression to investigate the transmission mechanisms of monetary policy for distinct stages of the US business cycle. We assume that autoregressive parameters and covariance matrices of the error terms are regime-dependent, driven by an unobserved Markov indicator. Endogenously det...

This article presents a theoretical growth model that accounts for technological interdependence among regions in a Mankiw-Romer-Weil world. The reasoning behind the theoretical work is that technological ideas cannot be fully appropriated by investors and these ideas may diffuse and increase the productivity of other firms. We link the diffusion o...

This paper uses a global vector autoregressive (GVAR) model to analyze the relationship between foreign direct investment (FDI) inflows and output dynamics in a multicountry context. The GVAR model enables us to make two important contributions: First, to model international linkages among a large number of countries, which is a key asset given the...

Spatial interaction models of the gravity type are widely used to describe origin-destination flows. They draw attention to three types of variables to explain variation in spatial interactions across geographic space: variables that characterize the origin region of interaction, variables that characterize the destination region of interaction, an...

Spatial interaction models represent a class of models that are used for modeling origin-destination flow data. The interest in such models is motivated by the need to understand and explain the flows of tangible entities such as persons or commodities or intangible ones such as capital, information or knowledge between regions. These models attemp...

In this paper, we distinguish three constrained variants of the gravity model of spatial interaction: doubly constrained, production constrained and attraction constrained exponential gravity models. These model variants include origin and/or destination specific balancing factors that act as constraints to ensure that the estimated rows and column...

This paper focuses on Austrian outbound foreign direct investment (FDI, measured by sales of Austrian affiliates abroad) in Europe over the period 2009–2013, using a spatial Durbin panel data model specification with fixed effects, and a spatial weight matrix based on the first-order contiguity relationship of the countries and normalised by its la...

The Poisson gravity model along with pseudo maximum likelihood (ML) methods has become a popular way to model international trade flows. This approach has several econometric advantages that we outline in the paper. We argue that estimating the parameters by ML would only be justified statistically if the trade flows were independent. Such an assum...

This article reviews some of the special properties of spatial data and the ways in which these properties have influenced developments in spatial data analysis. The discussion focuses on exploratory and model-driven (confirmatory) modes of analyzing spatial data, in particular spatial point patterns and area data, which occupy a prominent position...

The focus of this paper is on cross-region R&D collaboration funded by the 5th EU Framework Programme (FP5). The objective is to measure distance, institutional, language and technological barrier effects that may hamper collaborative activities between European regions. Particular emphasis is laid on measuring discrepancies between two types of co...

This article considers the most important aspects of model uncertainty for spatial regression models, namely, the appropriate spatial weight matrix to be employed and the appropriate explanatory variables. We focus on the spatial Durbin model (SDM) specification in this study that nests most models used in the regional growth literature, and develo...

This study suggests a two-step approach to identifying and interpreting regional convergence clubs in Europe. The first step involves identifying the number and composition of clubs using a space-time panel data model for annual income growth rates in conjunction with Bayesian model comparison methods. A second step uses a Bayesian space-time panel...

The Handbook of Regional Science is a multi-volume reference work providing a state-of-the-art knowledge on regional science composed by renowned scientists in the field. The Handbook is intended to serve the academic needs of graduate students, and junior and senior scientists in regional science and related fields, with an interest in studying lo...

This study focuses on the spatial structure of scientific collaboration across Europe on the level of regions. Scientific collaboration between two regions is captured by co-publication activities among organizations collaborating within the EU Framework Programme. While previous studies have been usually based on project participation only, this p...

The Handbook of Regional Science is a multi-volume reference work providing a state-of-the-art knowledge on regional science composed by renowned scientists in the field. The Handbook is intended to serve the academic needs of graduate students, and junior and senior scientists in regional science and related fields, with an interest in studying lo...

The objective of this study is to explore the determinants of inter-organizational knowledge generation within European networks of R&D collaboration. It is argued that social capital is a key determinant for successful knowledge generation. Thus, factors that influence the development of social capital like geographical separation, or collaboratio...

The focus of this study is on regional knowledge production in Europe, with special emphasis on the interplay between intra- and inter-regional research collaboration. The objective is to identify and measure effects of research collaboration on knowledge production at the level of European regions. We use a panel version of the spatial Durbin mode...

In this paper, we distinguish three constrained variants of the gravity model of spatial interaction: doubly constrained, production constrained and attraction constrained exponential gravity models. These model variants include origin- and/or destination-specific balancing factors that act as constraints to ensure that the estimated rows and colum...

Spatial interaction models approximate mean interaction frequencies between origin and destination locations by using origin-specific, destination-specific and spatial separation information. The focus is on models that are based on the theory of feedforward neural networks. This contribution considers the functional form of neural spatial interact...

In this article, a Poisson gravity model is introduced that incorporates spatial dependence of the explained variable without relying on restrictive distributional assumptions of the underlying data-generating process. The model comprises a spatially filtered component-including the origin-, destination-, and origin-destination-specific variables-a...

The authors develop an empirical approach to examine static and dynamic knowledge externalities in the context of a regional total factor productivity (TFP) relationship. Static externalities refer to current period scale or industry-size effects that have been labeled localization externalities or region-size effects known as agglomeration externa...

This paper directs interest on country-specific labour market discrimination Roma may suffer in South East Europe. The study lies in the tradition of statistical Blinder-Oaxaca decomposition analysis. We use microdata from UNDP’s 2004 survey of Roma minorities, and apply a Bayesian approach, proposed by Keith and LeSage (2004), for the decompositio...

The focus of this article is on precompetitive research and development (R&D) cooperation across Europe, as captured by R&D joint ventures funded by the European Commission in the time period 1998-2002, within the Fifth Framework Programme. The cooperations in this program give rise to a bipartite network with 72,745 network edges between 25,839 ac...

This paper presents a theoretical growth model that extends the Mankiw–Romer–Weil (MRW) model by accounting for technological interdependence among regional economies. Interdependence is assumed to work through spatial externalities caused by disembodied knowledge diffusion. The transition from theory to econometrics leads to a reduced-form empiric...

The phenomenon of interest in this chapter may be described in most general terms as interactions between populations of actors and opportunities distributed over some relevant geographic space. Such interactions may involve movements of individuals from one location to another, such as daily traffic flows in which case the relevant actors are indi...

Spatial interaction models of the types discussed in the previous chapter take the view that inclusion of a spatial separation function between origin and destination locations is adequate to capture any spatial dependence in the sample data. LeSage and Pace (J Reg Sci 48(5):941–967, 2008), and Fischer and Griffith (J Reg Sci 48(5):969–989, 2008) p...

Exploratory spatial data analysis is often a preliminary step to more formal modelling approaches that seek to establish relationships between the observations of a variable and the observations of other variables, recorded for each areal unit. The focus in this chapter is on spatial regression models in a simple cross-sectional setting, leaving ou...

Here in this chapter, we first consider the visualisation of area data before examining a number of exploratory techniques. The focus is on spatial dependence (spatial association). In other words, the techniques we consider aim to describe spatial distributions, discover patterns of spatial clustering, and identify atypical observations (outliers)...

The focus of this article is on precompetitive research and development (R&D) cooperation across Europe, as captured by R&D joint ventures funded by the European Commission in the time period 1998–2002, within the Fifth Framework Programme. The cooperations in this program give rise to a bipartite network with 72,745 network edges between 25,839 ac...

The objective is to combine insights from two research traditions, spatial interaction modelling and spatial autocorrelation modelling, to deal with the issue of spatial autocorrelation in spatial interaction data analysis. First, the problem is addressed from an exploratory perspective for which a generalisation of the Getis–Ord G statistic is pre...

Spatial interaction models of the gravity type are used in conjunction with sample data on flows between origin and destination locations to analyse international and interregional trade, commodity, migration and commuting patterns. The focus is on the classical log-normal model version and spatial econometric extensions that have recently appeared...

This paper uses data for 255 NUTS-2 European regions over the period 1995–2003 to test the relative explanatory performance of two important rival theories seeking to explain variations in the level of economic development across regions, namely the neoclassical model originating from the work of Solow (Q J Econ 70:65–94, 1956) and the so-called Wa...

Neural spatial interaction models represent the most recent innovation in the design of spatial interaction models. They are receiving increasing attention in recent years because of their powerful universal approximation properties. In essence they are devices for non-parametric statistical inferences, providing an elegant formalism for spatial in...

The focus in this paper is on knowledge spillovers between high-technology firms in Europe, as captured by patent citations. The European coverage is given by patent applications at the European Patent Office (EPO) that are assigned to high-technology firms located in Europe. By following the paper trail left by citations between high-technology pa...

The focus of this paper is on the role of human capital in explaining labor productivity variation among 198 European regions within a regression framework. Human capital is measured in terms of educational attainment using data for the active population aged 15 years and older that obtained tertiary education. The existence of unobserved human cap...

Multivariate interaction between two or more classes (or species) has important consequences in many fields and may cause multivariate clustering patterns such as spatial segregation or association. The spatial segregation occurs when members of a class ...

This article investigates the impact of knowledge capital stocks on total factor productivity (TFP) through the lens of the knowledge capital model proposed by Griliches (1979), augmented with a spatially discounted cross-region knowledge spillover pool variable. The objective is to shift attention from firms and industries to regions and to estima...

This paper develops an agent-based model of the biotechnology innovation system with the purpose to analyze the effects of public RTI (Research, Technology and Innovation) funding on innovative performance. Biotechnology is characterized as a research-intensive field where industrial and scientific agents operate in a highly dynamic environment. In...

Exxon Mobil and ConocoPhillips stock price has been predicted using the difference between core and headline CPI in the United States. Linear trends in the CPI difference allow accurate prediction of the prices at a five to ten-year horizon.

The main focus in this chapter is on knowledge spillovers between high-technology firms in Europe, as captured by patent citations. High-technology is defined to include the ISIC sectors aerospace (ISIC 3845), electronics-telecommunication (ISIC 3832), computers and office equipment (ISIC 3825), and pharmaceuticals (ISIC 3522). The European coverag...

Spatial data are an important source of scientific information. The development of high capacity and fast desk and laptop computers and the concomitant creation of geographic information systems has made it possible to explore georeferenced or mapped data as never before. This Handbook summarizes, explains, and demonstrates the nature of current mo...

This paper presents a theoretical neoclassical growth model with two kinds of capital, and technological interdependence among regions. Technological interdependence is assumed to operate through spatial externalities caused by disembodied knowledge diffusion between technologically similar regions. The transition from theory to econometrics yields...

The focus of this paper is on pre-competitive R&D cooperation across Europe, as captured by R&D joint ventures funded by the European Commission in the time period 2002-2006, within the 5th Framework Program. The cooperations in this Framework Program give rise to a collaborative network, with network nodes representing actors (i.e. organizations i...

Spatial interaction models of the gravity type are widely used to model origin-destination flows. They draw attention to three types of variables to explain variation in spatial interactions across geographic space: variables that characterize an origin region of a flow, variables that characterize a destination region of a flow, and finally variab...

Abstract We attempt to clarify a number of points regarding use of spatial regression models for regional growth analysis. We show that as in the case of non-spatial growth regressions, the effect of initial regional income levels wears off over time. Unlike the non-spatial case, long-run regional income levels depend on: own region as well as neig...

A novel rough set approach is proposed in this paper to discover classification rules through a process of knowledge induction which selects decision rules with a minimal set of features for classification of real-valued data. A rough set knowledge discovery framework is formulated for the analysis of interval-valued information systems converted f...

This paper presents a continuous version of the model of distribution dynamics to analyse the transition dynamics and implied long-run behaviour of the EU-27 NUTS-2 regions over the period 1995–2003. It departs from previous research in two respects: first, by introducing kernel estimation and three-dimensional stacked conditional density plots as...

This paper investigates the impact of knowledge capital stocks on total factor productivity through the lens of the knowledge capital model proposed by Griliches (1979), augmented with a spatially discounted cross-region knowledge spillover pool variable. The objective is to shift attention from firms and industries to regions and to estimate the i...

This paper uses data for 255 NUTS-2 European regions over the period 1995-2003 to test the relative explanatory performance of two important rival theories seeking to explain variations in the level of economic development across regions, namely the neoclassical model originating from the work of Solow (1956) and the so-called Wage Equation, which...

This paper suggests an empirical framework for analysing income distribution dynamics and cross-region convergence in the European Union of 27 member states, 1995-2003. The framework lies in the research tradition that allows the state income space to be continuous, puts emphasis on both shape and intra-distribution dynamics and uses stochastic ker...

The objective of this study is to identify knowledge spillovers that spread across regions in Europe and vary in magnitude for different industries. The study uses a panel of 203 NUTS-2 regions covering the 15 pre-2004 EU-member-states to estimate the impact over the period 1998-2003, and distinguish between five major industries. The study impleme...

We apply a Bayesian hierarchical Poisson spatial interaction model to the paper trail left by patent citations between high-technology patents in Europe to identify and measure spatial separation effects of interregional knowledge flows. The model introduced here is novel in that it allows for spatially structured origin and destination effects for...

The paper examines the application of the concept of economic efficiency to organizational issues of collective information processing in decision making. Information processing is modeled in the framework of the dynamic parallel processing model of associative computation with an endogenous setup cost of the processors. The model is extended to in...

The objective of this study is to identify knowledge spillovers that spread acrossregions in Europe and vary in magnitude for different industries. The study uses a panel of203 NUTS-2 regions covering the 15 pre-2004 EU-member-states to estimate the impactover the period 1998-2003, and distinguish between five major industries. The studyimplements...