Is firm growth proportional? An appraisal of firm size distribution

The aim of this paper is to shed light on the phenomenon of firm growth, analyzing the evolution of young firms within some selected industries. We find that the firm size distribution is fairly skewed to the right during the infancy stage, whereas it converges towards a more symmetric distribution, via selection mechanisms, with the passing of time.

Industry Dynamics and the Distribution of Firm Sizes: A Non-Parametric Approach

The aim of this paper is to analyze the evolution of the size distribution of young firms within some selected industries, trying to assess the empirical implications of different models of industry dynamics: the model of passive learning (Jovanovic 1982), the model of active learning (Ericson and Pakes, 1995), and the evolutionary model (Audretsch, 1995). We use a non-parametric technique, the Kernel density estimator, applied to a data set from the Italian National Institute for Social Security (INPS), consisting in 12 cohorts of new manufacturing firms followed for 6 years. Since the patterns of convergence to the limit distribution are different between industries, we conclude that the model of passive learning is consistent with some of them, the active exploration model with others, the evolutionary model with all of them.Cohorts; Gibrats Law; Kernel; Industry Dynamics; Non-parametric; Shakeouts.

The Post-entry Size Adjustment of New small Firms

The hypothesis underlined in this paper is that apart from infant mortality there is another relevant phenomenon taking place within new-born Small Business Enterprises (SBEs) in the period immediately after entry; namely that the smaller ones among them, having entered with a marked sub-optimal scale,adjust their size towards the mean size exhibited by larger SBEs. In the paper this hypothesis is tested using a cohort of 1,570 new firms, and applying a Gibrat-like specification with sample selection. The hypothesis of a size adjustment by smaller new entrants immediately after entry is confirmed in most selected industries in Italian manufacturing; more specifically, surviving smaller new SBEs show higher rates of growth in the first year (in one case in the first two) immediately after start-up, while they converge towards the average rate of growth of the whole cohort of new SBEs in the following years.-

The survival of family firms: the importance of control and family ties

The aim of this paper is to analyze the survival patterns of a group of family firms which have already spent at least twenty-five years in the market. To this end, we use the Kaplan-Meier product limit estimator supplemented with qualitative information gathered by direct observation and discussions with entrepreneurs. The main findings of the paper are that small family firms which have reached their thirtieth year in the market face a very high risk of sudden exit, increasing with firm age. Further control carried out by means of interviews with entrepreneurs identifies problems connected with succession as one of the main causes of the decision to close down

Industry dynamics and the distribution of firm sizes: a non-parametric approach

The aim of this paper is to analyze the evolution of the size distribution of young firms within some selected industries, trying to assess the empirical implications of different models of industry dynamics: the model of passive learning (Jovanovic 1982), the model of active learning (Ericson and Pakes, 1995), and the evolutionary model (Audretsch, 1995). We use a non-parametric technique, the Kernel density estimator, applied to a data set from the Italian National Institute for Social Security (INPS), consisting in 12 cohorts of new manufacturing firms followed for 6 years. Since the patterns of convergence to the limit distribution are different between industries, we conclude that the model of passive learning is consistent with some of them, the active exploration model with others, the evolutionary model with all of them

Industry Dynamics and the Distiribution of Firm Sizes: A Non-Parametric Apporoach.

The aim of this paper is to analyze the evolution of the size distribution of young firms within some selected industries, trying to assess the empirical implications of different models of industry dynamics: the model of passive learning (Jovanovic 1982), the model of active learning (Ericson and Pakes, 1995), and the evolutionary model (Audretsch, 1995). We use a non-parametric technique, the Kernel density estimator, applied to a data set from the Italian National Institute for Social Security (INPS), consisting in 12 cohorts of new manufacturing firms followed for 6 years. Since the patterns of convergence to the limit distribution are different between industries, we conclude that the model of passive learning is consistent with some of them, the active exploration model with others, the evolutionary model with all of them

R&d, embodied technological change, producers-users interaction, and productivity at the firm level: a Germany-Italy comparison

This paper follows a knowledge production function approach to assess the contribution of R&D spending, the purchase of new machinery, and producersusers interaction to the productivity performance of German and Italian firms in manufacturing. For this purpose it employs microaggregated data from the First Community Innovation Survey. The regression analysis confirms the results of previous studies that technological change embodied in new machinery and capital equipment is a major factor affecting the productivity level of manufacturing firms in most industries (in particular in Italy), although the role of R&D activities is crucial for most firms in both countries, and that this is also the case in traditional consumer goods industries such as textiles, clothing, and leather & leather products. Conversely, only for Germany does producersusers interaction prove significantly to influence the productivity level of firms in certain industries

Innovative Output, Infra-Industry Spilloves, and R&D Cooperation: Theory and Evidence.

We analyse both the theoretical and empirical side of the issue of R&D spillover. Each firm`s R&D costs are increasing in the amount of the information transmitted to the other firms , and we account for the possibility that the firms control spillovers. We consider both Cournot-Nash and Cornot-Stackelberg behavior. The empirical analyst suggests that (i) firms` control on spillovers is relatively low; (ii) the cost-saving effect associated to joint ventures or R&D cartels is confermed for industries where firms rely mainly upon own R&D as a source of innovation; (iii) R&D cooperation may increase informationsharing, thereby enhancing spillovers

Gibrat’s law and market selection in the radio, tv & telecommunications equipment industry

According to Gibrat’s Law of Proportionate Effect, the growth rate of a given firm is independent of its size at the beginning of the period examined. In contrast to the previous literature on the subject, this paper seeks to test the Law by taking account of both the entry process and the role of survival/failure in reshaping a given population of firms over time. It does so by focusing on the entire population of firms (including newborn ones) in the Italian Radio, TV & Telecommunications equipment industry and tracking them over seven years. Consistently with the previous literature, it finds that - in general - Gibrat’s Law is to be rejected, since smaller firms tend to grow faster than their larger counterparts. However, the paper’s main finding is that this rejection of Gibrat’s Law may be due to market dynamics and selection. In other words, it is due to the entry process and the presence of transient smaller firms. Indeed, whilst it is found that Gibrat’s Law has to be rejected over a seven-year period during which both incumbent and newborn firms are considered, for both sub-populations of surviving firms a convergence towards Gibrat-like behavior over time can be detected. Thus, market selection "cleans" the original population of firms and the resulting industrial "core" (mature, larger, well-established and most efficient firms) does not seem to depart from a Gibrat-like pattern of growth

Does Gibrat’s Law Hold in the Case of Young, Small Firms?

According to Gibrat’s Law of Proportionate Effect, the growth rate of a given firm is independent of its size at the beginning of the examined period. This paper investigates whether Gibrat’s Law holds for new entrants in a given industry: that is for new small firms in the early stage of their life cycle. The main finding is that in some (but not in all) selected industries in Italian manufacturing Gibrat’s Law fails to hold in the years immediately following start-up, when smaller firms have to rush in order to achieve a size large enough to enhance their likelihood of survival. Conversely, in subsequent years the patterns of growth of smaller firms do not differ significantly from those of larger ones, and the Law is therefore confirmed