The effect of university and regional knowledge spillovers on firms’ performance: an analysis of the Spanish USOs

Previous empirical studies of university spin-off (USO) growth have applied a firm-based approach without modelling how contextual factors may influence firm growth. By adopting an ‘interactionist approach’, this paper tests the hypothesis that the regional and university contexts may partly determine USO growth, together with firms’ internal resources. Using a sample of 531 Spanish USOs located in 16 Spanish regions and launched by 51 universities over the 2001–2013 and applying multilevel modelling with macro- and micro-data, the findings confirmed that regional context, together with firm-specific characteristics, are important for explaining USO growth. More specifically, the presence of venture capitalists, the capacity to generate internal funds, and operating in high-tech industries have a positive effect on USO growth. On the basis of the results, we propose some policies for fostering USO growth.     

Multilevel analysis of the changing relationship between class and party in Britain 1964–1992

Previous analyses of the changing relationship between class and vote in Britain have assumed that the British Election Surveys constitute simple random samples. In fact, they are all clustered samples, and the number of sampling points has varied substantially over time. The paper uses the statistical technique of multi-level modelling to investigate the effects of this clustering and compares the results with those obtained with single-level logistic models. In general, the multilevel and single-level models lead to similar conclusions about the changing relation between class and vote; they both show evidence of a change in the class/vote relationship over time. However, the multilevel models also show that, while the clustering does not affect conclusions about the class dealignment debate, there are other important substantive findings which emerge from the multilevel approach. First, there is clear evidence of substantial constituency differences in the intercepts; that is, individuals had very different propensities to vote Conservative in different constituencies. Second, there were also significant constituency differences in class voting, that is, constituencies seemed to vary in their level of class polarization.     

Explaining Total Factor Productivity at Firm Level in Italy: Does Location Matter?

Abstract

This study analyses how firms' internal variables and regional factors affect total factor productivity (TFP) of Italian manufacturing firms. Due to the hierarchical structure of our data, we employ a multilevel model that allows for a clear distinction between firm and region-specific effects. Results refer to 2004–2006 and show, as expected, the importance of firm-specific determinants of TFP. At the same time, they indicate that location matters in the sense that the context where firms operate plays a crucial role in determining the level of TFP. In more detail, we find that the regional endowment of infrastructure, the efficiency of local administration and the investments in R&D exert a positive effect on firms' performance.     

Firm-specific wage growth and changes in the labor market for managers

This paper analyzes recent changes in the employment relationships between managers and firms. In both Becker's and Lazear's models of firm-specific wage growth, compensation is deferred from early in an employee's tenure with a firm until later in the contract. The deferred compensation bonds the worker to the firm. Based on cross-sectional data from Current Population Surveys, rates of firm-specific wage growth are estimated for the managerial labor market. The findings show that the rate of wage growth that is firm-specific for managers in manufacturing industries declined significantly during the early 1980s. It is estimated, for example, that a manager with 12 years of tenure in a manufacturing firm enjoyed, on average, a 25% wage premium in 1979 over an otherwise similar manager who was a new hire in a firm. By 1983 the firm-specific wage premium for a manager with 12 years of tenure was only 5%. These changes represent a significant reduction in the strength of the employment bond between firms and managers, and a reduction in the incentive effects previously enjoyed by firms from the use of deferred-compensation schemes. This change is consistent with the significant increases in the displacement rates of managers that occurred during the 1980s.     

The New Keynesian Phillips Curve and staggered price and wage determination in a model with firm-specific labor

We develop a DSGE model with firm-specific labor where wage and price setting are subject to Calvo-type staggering. This is in general an intractable problem due to complicated intertemporal dependencies between price and wage decisions. However, the problem is significantly simplified if we, in line with empirical evidence, assume that prices can be changed whenever wages are. We show that the price- and wage-setting relationships are substantially altered by the introduction of firm-specific labor. Specifically, the inflation response is substantially dampened, whereas the wage inflation response is increased as compared to models with freely mobile labor. These distinctive features of the model with firm-specific labor are supported by empirical evidence from a structural VAR.     

CONVERGENCE AND ECONOMIC PERFORMANCE IN GREECE: EVIDENCE AT REGIONAL AND PREFECTURE LEVEL

The purpose of this paper is to test regional convergence and to investigate interregional disparities in terms of per capita income in Greece. The novelty of our study lies in the use of a disaggregated dataset for an extended time period (1971–2003) at two regional levels (NUTS II & NUTS III). Our results indicate that there is β convergence between prefectures but not among regions, while no evidence of σ convergence is found at both regional levels. Also, the GDP geographic concentration and population density have a negative impact on growth, which outweighs the positive growth effect of population geographic concentration and GDP spatial inequality. Thus, policies aiming at the decentralization of economic activity in Greece might enhance growth and regional equality simultaneously. Finally, we do not find economic dualism across geographic areas; however, rich prefectures seem to converge faster than poor ones.     

Spatial Growth Regressions: Model Specification,Estimation and Interpretation

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 neighbouring region characteristics, the spatial connectivity structure of the regions, and the strength of spatial dependence. Given this, the search for regional characteristics that exert important influences on income levels or growth rates should take place using spatial econometric methods that account for spatial dependence as well as own and neighbouring region characteristics, the type of spatial regression model specification, and weight matrix. The framework adopted here illustrates a unified approach for dealing with these issues.     

Fixed and random effects models: making an informed choice

This paper assesses the options available to researchers analysing multilevel (including longitudinal) data, with the aim of supporting good methodological decision-making. Given the confusion in the literature about the key properties of fixed and random effects (FE and RE) models, we present these models’ capabilities and limitations. We also discuss the within-between RE model, sometimes misleadingly labelled a ‘hybrid’ model, showing that it is the most general of the three, with all the strengths of the other two. As such, and because it allows for important extensions—notably random slopes—we argue it should be used (as a starting point at least) in all multilevel analyses. We develop the argument through simulations, evaluating how these models cope with some likely mis-specifications. These simulations reveal that (1) failing to include random slopes can generate anti-conservative standard errors, and (2) assuming random intercepts are Normally distributed, when they are not, introduces only modest biases. These results strengthen the case for the use of, and need for, these models.

     

Innovation in cultural and creative industries firms with an academic origin (CCI-USOs): The role of regional context

Previous literature has focused on either the direct or indirect contribution of cultural and creative industries (CCI) firms to the innovation capability of the wider economy, while the reverse approach, that is, the effect of region on CCI firms’ innovation, has been completely neglected. In this paper, it is argued that the innovative performance of CCI firms with an academic origin (CCI-USOs) may be influenced by the regional context where they operate. In so doing, it is defended that the study of innovation in CCI firms can be advanced through the development of a more integrative framework. Relying on a sample of 92 Spanish CCI-USOs over the period 2001–2010 and applying multilevel modelling, this study sheds light on how regional and firm level factors simultaneously impact on CCI-USOs’ innovation. The findings show that the regional context determines the innovative performance of CCI-USOs. In addition, firm age has a negative effect on the probability of having patent activity, while firm size and venture capital exerts a positive influence on innovative performance. On the basis of these results, some policies for fostering innovation in CCIs are proposed.     

A Dynamic Panel Data Approach to the Forecasting of the GDP of German Länder

Abstract

In this paper, we make multi-step forecasts of the annual growth rates of the real GDP for each of the 16 German Länder simultaneously. We apply dynamic panel models accounting for spatial dependence between regional GDP. We find that both pooling and accounting for spatial effects help to improve the forecast performance substantially. We demonstrate that the effect of accounting for spatial dependence is more pronounced for longer forecasting horizons (the forecast accuracy gain is about 9% for a 1-year horizon and exceeds 40% for a 5-year horizon). We recommend incorporating a spatial dependence structure into regional forecasting models, especially when long-term forecasts are made.     

Inequality and Growth in European Regions: Towards a Place-based Approach

Abstract

Does agglomeration matter for growth? This paper addresses this question by evaluating the impact that intra-regional income distribution has on regional growth in Europe. By using a spatially augmented Solow growth model, we investigate the convergence process among 188 EU regions between 1991 and 2004 and extend the traditional growth models to account for the impact of regional inequality on growth, as well as the effects of interaction among regions. Our assumption is that existing levels of inequality between sub-regional territorial units could positively contribute to regional economic growth in Europe, through the positive effects generated by the emergence of agglomeration economies. Our results show that while we cannot find any overall significant relationship in Europe between agglomeration and growth, once we distinguish between Objective 1 and Non-objective 1 regions we are able to find that agglomeration positively impacts subsequent growth, but only in the less developed regions.     

Real rigidities, productivity improvements and investment dynamics

The theoretical literature on business cycles predicts a positive investment response to productivity improvements, a prediction we question from theoretical and empirical perspectives. We show that a short-term negative response of investment to a positive technology shock is consistent with a reasonably parameterized new Keynesian dynamic stochastic general equilibrium (DSGE) model in which firm-specific capital introduces an additional real rigidity, and monetary policy is not fully accommodative. Employing Bayesian techniques, we provide evidence that permanent productivity improvements have short-term, contractionary effects on investment. Although this result can be obtained from both firm-specific and rental capital models, only in the case of the former is the average price duration in line with the microeconometric evidence.     

International Differences in Conditional Conservatism – The Role of Unconditional Conservatism and Income Smoothing

Abstract

Prior research documents that conditional conservatism, measured as the asymmetric timeliness of earnings reflecting bad vs. good news, varies with cross-country differences in institutional regimes. In this paper, we examine the determinants of conditional conservatism and related earnings attributes internationally. First, using panel data, we investigate whether competing earnings attributes such as unconditional conservatism and income smoothing affect conditional conservatism and its international differences. We find that these attributes are predictably correlated with conditional conservatism. Second, we address the question whether income smoothing and conditional conservatism are two fundamentally different earnings attributes. We show theoretically that both attributes yield different earnings distributions and that the motivations for producing earnings which possess these attributes differ. To test these predictions empirically, we calculate firm-specific time-series measures of asymmetric timeliness, using a novel trigonometric measure based on the standard Basu (1997)-type regression. Using this cross-sectional data, we test whether conditional conservatism and income smoothing are different and find them to be only weakly correlated for a broad international sample. Also, we demonstrate that income smoothing explains international differences in conditional conservatism. Finally, we estimate simple determinant models of conditional conservatism and income smoothing, showing that both earnings attributes are driven by different explanatory firm-level factors: Conditional conservatism increases with the importance of debt financing, while income smoothing increases with the importance of dividends. Despite some important limitations, we believe our results to be meaningful because they show that cross-country differences in conditional conservatism are influenced by the effects of other accounting properties, predominantly income smoothing. Especially, legal regime appears to drive income smoothing while losing its explanatory power for conditional conservatism when firm-specific factors are controlled for.     

Multilevel theory and the underspecification of multilevel models

This article emphasises the importance of the adequate specification of models of multilevel analysis in accordance with multilevel theories. Until recent times, multilevel theories tried only to explain the direct effect of group characteristics on an individual's characteristic. It seems to be more suited to adopt a more general theoretical approach, in which it is assumed that group characteristics affects individual processes. There a treshold effect and a process effect have to be distinguished. The propositions result in a model specification within the random coefficient model of multilevel analysis. The theory and model recommended are illustrated by means of data of Dar and Resh's (1986) study into social learning environment.     

Does class matter more than school? Evidence from a multilevel statistical analysis on Italian junior secondary school students

This paper assesses the differences in educational attainments between students across classes and schools they are grouped by, in the context of Italian educational system. The purpose is to identify a relationship between pupils' reading test scores and students' characteristics, stratifying for classes, schools and geographical areas. The dataset contains detailed information about more than 500,000 students at the first year of junior secondary school in the year 2012/2013. By means of multilevel linear models, it is possible to estimate statistically significant school and class effects, after adjusting for pupil's characteristics, including prior achievement. The results show that school and class effects are very heterogeneous across macro-areas (Northern, Central and Southern Italy), and that there are substantial discrepancies between and within schools; overall, class effects on achievement tend to be larger than school ones.     

Changing Trends in Regional Economic Development Policy Governance: The Case of Northern Ontario,Canada

This article analyses the changing trends in regional economic development policy delivery in multilevel governance systems. Although the imperatives of coordination of public policy interventions across multiple levels has generally been recognized, not enough attention has been given to how different political systems actually adapt their institutional and policy designs to effectively operate in the emergent complexity of multilevel governance systems. The article focuses on regional economic development policy governance in the province of Ontario, Canada over the past three decades, drawing insights from new regionalism, organization theory and governance literature to examine the prospects and challenges of policy delivery in politically complex multilevel systems. The case study illustrates how regional economic development policy is increasingly dictated by complex environmental and institutional forces of multilevel governance that are shaped by the particular character of a political system.     

Evaluating the accuracy of value-at-risk forecasts: New multilevel tests

We propose independence and conditional coverage tests which are aimed at evaluating the accuracy of Value-at-Risk (VaR) forecasts from the same model at different confidence levels. The proposed procedures are multilevel tests, i.e., joint tests of several quantiles corresponding to different confidence levels. In a comprehensive Monte Carlo exercise, we document the superiority of the proposed tests with respect to existing multilevel tests. In an empirical application, we illustrate the implementation of the tests using several VaR models and daily data for 15 MSCI world indices.     

Counteracting innovative constraints: insights from four case studies of African knowledge-intensive metalworking and automotive clusters – ‘the Akimacs’

We respond to repeated calls over the years to further develop cluster theory specifically in an African context. Our contribution is to construct a framework which integrates theories focusing on path dependency, transaction cost economics (efficiency and systemic interdependency models) and regional development (lock in models). Our focus is on the innovativeness of African clusters and constraints on such innovation. Thus, drawing on cluster literature on constraints to innovation coupled with insights from current empirical work within African automotive clusters, we examine the challenges of counteracting the multilevel constraints which hinder innovation in African clusters. We develop a model for counteracting cluster constraints focusing on the impact of variations in innovative frequency, diffusion of innovations, innovative speed and protection of innovation. The model emphasizes the opportunities that arise when new entrant and incumbent firms interact to neutralize constraints at transactional, social, ecological and knowledge levels.     

A goal programming model for the siting of multilevel EMS systems.

Facility siting models known as location covering techniques have proven to be useful particularly for emergency medical services (EMS) planning, given the importance of ambulances responding to demand within some maximum time constraint. These models represent a set of methods which focus the health planner's attention on the access of people to health care, since they attempt to “cover” people in need of service within some specified time standard.This research develops a technique for the locational planning of sophisticated EMS systems, characterized by multiple levels of emergency health services. Specifically, a two-tiered system with “basic life support” and “advanced life support” capabilities is modeled as a goal program.By applying location covering techniques within a goal programming framework, this study develops a method for the siting of multilevel EMS systems so that (1) each service level maximizes coverage of its own demand population, and (2) “back-up” coordination between levels is assured. The usefulness of this goal program as a health planning tool is evidenced in the model's explicit articulation of EMS policy objectives and its ability to link system levels in terms of “goal-directed behavior”. The working of this multilevel covering model is demonstrated by reference to EMS planning scenarios and related numerical examples.     

How does news sentiment impact asset volatility? Evidence from long memory and regime-switching approaches

This paper examines the dynamic relationship between firm-level return volatility and public news sentiment. By using the new RavenPack News Analytics ⿿ Dow Jones Edition database that captures over 1200 types of firm-specific and macroeconomic news releases and their sentiment scores at high frequencies, we investigate the circumstances in which public news sentiment is related to the intraday volatility of the constituent stocks in the Dow Jones Composite Average (DJN 65). Two different conditionally heteroskedastic models are employed: the Fractionally Integrated Generalized Autoregressive Conditionally Heteroskedastic (FIGARCH) and the two-state Markov Regime-Switching GARCH (RS-GARCH) models. For most of the DJN 65 stocks, our results confirm the significant impact of firm-specific news sentiment on intraday volatility persistence, even after controlling for the potential effects of macroeconomic news. Compared with macroeconomic news sentiment, firm-specific news sentiment apparently accounts for a greater proportion of overall volatility persistence. Moreover, negative news has a greater impact on volatility than positive news. Furthermore, the results from the RS-GARCH model indicate that news sentiment accounts for a greater proportion of volatility persistence in the high-volatility regime (turbulent state) than in the low-volatility regime (calm state). In-sample forecasting performance and residual diagnostic tests suggest that FIGARCH generally outperforms RS-GARCH.