Margherita Velucchi

Size, innovation and internationalization: a survival analysis of Italian firms

Firms’ survival is often seen as crucial for economic growth and competitiveness. This article focuses on business demography of Italian firms, using an original database, obtained by matching and merging to gain the intersection of three firm level datasets. This database allows us to simultaneously consider the effect of size, technology, trade, FDIs and innovation on firms’ survival probability. We show that size and technological level positively affect the likelihood of survival. Internationalized firms show higher failure risk: on average competition is stronger in international markets, forcing firms to be more efficient. However, large internationalized firms are more likely to ‘survive’. An Italian internationalized firm to be successful and to survive, should be high-tech, large and innovative.

Volatility Spillovers in East Asian Financial Markets: A Mem-Based Approach

We model the interrelations of equity market volatility in eight East Asian countries before, during, and after the Asian currency crisis. Using a new class of asymmetric volatility multiplicative error models based on the daily range, we find that dynamic propagation of volatility shocks occurs through a network of interdependencies, and shocks originating in Hong Kong may be amplified in their transmission throughout the system, posing greater risks to the region than shocks originating elsewhere. Although this partly explains the severity of the currency crisis, we also find evidence that parameters shifted, making the system more unstable during the crisis.

A MEM-Based Analysis of Volatility Spillovers in East Asian Financial Markets

Transmission mechanisms in financial markets reflect the degree of integration of capital markets, as well as the relative importance of real economies. Market volatility has components which may behave differently across quiet and turbulent periods, but appear to behave in similar ways from market to market. In this paper we suggest a Multiplicative Error Model (MEM) approach to study volatility spillovers among a set of markets, using as a proxy, the market daily range. We model the dynamics of the expected volatility of one market including interactions with the past daily ranges of other markets, building a fully interdependent model. We analyze eight East Asian markets in the period 1995-2006, devoting particular attention to the treatment of the 1997-1998 turbulence period. We find no evidence of independent markets while several interdependence relationships can be stressed. Hong Kong turns out to be the most important market while Taiwan seems to have suffered quite limited effects from the crisis. Impulse response functions and multiperiod forecast profiles are developed and suggest a build-up in the spillover effects.

Heterogeneity in managerial strategies and internationalization of firms: the case of Italy

The recent empirical literature on firm performance has highlighted the multidimensional concept of managerial strategies. The paper analyzes the nexus between these strategies and performance based on specific entrepreneurs’ characteristics, corporate strategies, organizational capabilities and firms’ approaches to internationalization. Using a dataset obtained by matching and merging Capitalia, ICE-Reprint and AIDA surveys we investigate the possible non-linear impact of managerial strategies on firm performance in Italy. While the specific entrepreneurs’ characteristics do not seem to have a significant impact on firm performance, the mode of internationalization plays an important role. Important non-linearities arise when we singled out the role of skilled workers and managers in determining a firm’s success in highly competitive markets.

Regime switching: Italian financial markets over a century

The frequency of crashes and the magnitude of crises in international financial markets are growing more severe over time. Recent financial crises are not singular events portrayed in recent accounts, rather, they erupt in circumstances that are very similar to the economic and financial environments of the earlier eras. This paper analyzes the Italian stock market in two very peculiar periods (1901–1911 and 1993–2004): the “Second” and the “Third industrial revolution”. We use Markov Switching Models to test whether the Italian stock market volatility has increased in the long run and whether it can be represented by different regimes. We find that volatility regimes exist; that Banking sector has a central role and “New economy” sectors perform quite well while traditional sectors do not, in both periods.

A MEM Analysis of African Financial Markets

In the last few years, international institutions stressed the role of African financial markets to diversify investors’ risk. Focusing on the volatility of financial markets, this paper analyses the relationships between developed markets (US, UK and China) and some Sub-Saharian African (SSA) emerging markets (Kenya, Nigeria and South Africa) in the period 2004–2009 using a Multiplicative Error model (MEM). We model the dynamics of the volatility in one market including interactions from other markets, and we build a fully interdependent model. Results show that South Africa and China have a key role in all African markets, while the influence of the UK and the US is weaker. Developments in China turn out to be (fairly) independent of both UK and US markets. With the help of impulse-response functions, we show how recent turmoil hit African countries, increasing the fragility of their infant financial markets.

The demography of manufacturing firms (1911–1971)

The dynamic of size distribution highlights three very interesting statistical inter-industrial regularities. Firstly, the dynamic distribution of the major firms shows a convergence towards the bottom of the size distribution, i.e. these firms grow but, the absolute size does not grow much because the firms that reach the highest stages recede. In fact, the entire universe of firms shows an extended series of leaping frogs, namely of firms that in the different phases, move many positions forward in the ranking of size classes, but also jump backwards, i.e. they do not remain stable.

Diverse twins: analysing China’s impact on Italian and German exports using a multilevel quantile regressions approach

ABSTRACT Germany and Italy are the largest manufacturing producers in Europe and export over 70% of their products to OECD countries. While they share many characteristics, they are also diverse in term of specialization and destination markets. Italy has a productive structure largely based on labour intensive sectors, while Germany is mainly specialized in high-tech goods. We study whether these characteristics make the two countries vulnerable in different ways to the competitive pressure by emerging economies, especially China, which experienced the strongest increase in export market share during the last decades. We discuss the impact of China on the export performance of Italy and Germany on OECD markets. Using data for the period 1995–2009, we implement a novel model to account for two important data characteristics: their hierarchical hidden structure (captured by a multilevel model) and the heterogeneity of the export shares (captured by a quantile approach). Results show that Chinese competition on Italy’s and Germany’s market shares differ by sectors, but, on average, Italy is not more vulnerable than Germany. These results are relevant for policy implications and for an ex-post analysis of the ‘best response’ to the Chinese competition.

Italian Firms’ Geographical Location in High-tech Industries: A Robust Analysis

Recent debates in economic-statistical research concern the relationship between firms’ performance and their capabilities to develop new technologies and products. Several studies argue that economic performance and geographical proximity strongly affect firms’ level of technology. The aim of the paper is twofold. Firstly, we propose to generalize this approach and to develop a model to identify the relationship between the firm’s technology level and some firm’s characteristics. Secondly, we use an outlier detection method to identify units that affect the analysis results and the estimates stability. This analysis is implemented using a generalized regression model with a diagnostic robust approach based on forward search. The method we use reveals how the fitted regression model depends on individual observations and the results show how the firms’ technology level is influenced by their geographical proximity.

On the Interaction between Ultra–high Frequency Measures of Volatility

We analyze several measures of volatility (realized variance, bipower variation and squared daily returns) as estimators of integrated variance of a continuous time stochastic process for an asset price. We use a Multiplicative Error Model to describe the evolution of each measure as the product of its conditional expectation and a positive valued iid innovation. By inserting past values of each measure and asymmetric effects based on the sign of the return in the specification of the conditional expectation, one can investigate the information content of each indicator relative to the others. The results show that there is a directed dynamic relationship among measures, with squared returns and bipower variance interdependent with one another, and affecting realized variance without any feed-back from the latter.