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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.

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.

This paper follows a knowledge production function approach to assess the contribution of R&D spending, the purchase of new machinery, and producers-users interaction to the productivity performance of German and Italian firms in manufacturing. For this purpose it employs micro-aggregated 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 producers-users interaction prove significantly to influence the productivity level of firms in certain industries.

How do political connections affect firm dynamics, innovation, and creative destruction? To answer this question, we build a firm dynamics model, where we allow firms to invest in innovation and/or political connection to advance their productivity and to overcome certain market frictions. Our model generates a number of theoretical testable predictions and highlights a new interaction between static gains and dynamic losses from rent-seeking in aggregate productivity. We test the predictions of our model using a brand-new dataset on Italian firms and their workers. Our dataset spans the period from 1993 to 2014, where we merge: (i) firm-level balance sheet data, (ii) social security data on the universe of workers, (iii) patent data from the European Patent Office, (iv) the national registry of local politicians, and (v) detailed data on local elections in Italy. We find that firm-level political connections are widespread, especially among large firms, and that industries with a larger share of politically connected firms feature worse firm dynamics. We identify a leadership paradox: when compared to their competitors, market leaders are much more likely to be politically connected but much less likely to innovate. In addition, political connections relate to a higher rate of survival, as well as growth in employment and revenue, but not in productivity - a result that we also confirm using a regression discontinuity design.

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.