Some reflections on past and future of nonlinear dynamics in economics and finance

This paper offers an overview of the literature on the economic and financial applications of theory of nonlinear dynamics, especially bifurcation theory. After a short introductory discussion of the first nonlinear dynamic models in social sciences and the economic relevance of the zoo of bifurcations and complicated dynamics that such models can generate, we present an overview of the literature on nonlinear dynamic models in the areas of underdevelopment, environmental poverty traps, the management of common goods, industrial organization and financial markets. The review of the literature is enriched by reflections and ideas for future research.     

The effects of COVID-19 containment measures on the Asia-Pacific region

As the COVID-19 pandemic spread across the world, governments introduced significant containment measures to control the spread of the virus. In this paper, we leverage inputs from IMF desk economists to construct a novel narrative index of containment measures for 11 countries in the Asia-Pacific region. A key innovation in our index is that it distinguishes between economic sectors (services, industry, retail), thus providing a more granular view of restrictions related to economic activity. Using this index, along with other high-frequency data, we find that containment measures have been successful in reducing the spread of the virus (though with some heterogeneity) but have also been associated with large short-term economic costs. Furthermore, exploiting the granularity of our index, we find that differences in strategies across countries regarding the closing of the industrial sector have mattered: imposing less severe restrictions on industry has been associated with lower economic costs without leading to worse health outcomes, possibly reflecting the less contact intensive nature of industrial activity.     

Nonlinear economic growth: Some theory and cross-country evidence

This paper aims to test the existence of different growth regimes, that is of different relationships between growth rate and income level. We propose a simple nonlinear growth model and test its empirical implications by estimating Markov transition matrices and stochastic kernels. We show that growth is indeed nonlinear: a first phase of slow or zero growth is followed by a take-off and, finally, by a phase of deceleration. We discuss the relevance of these results with respect to the issue of convergence and reversibility of development, in the light of models of structural change and technological diffusion.     

Productivity,innovation strategies and industrial relations in SMEs. Empirical evidence for a local production system in northern Italy

The paper aims to provide an original contribution to evaluating several kinds of relations between four areas of innovation activities – training, technology, organization, ICT (information and communication technologies) – and industrial relations and firm’s economic performance. Quantitative evidence for a SME‐based local production system is provided by exploiting two datasets: the first is derived from a direct survey carried out in 2005 collecting data on innovations, labour flexibility and industrial relations; the second is represented by a panel of official balance sheets data for the period 1998–2004. The analysis is divided in two consequential parts. We first examine the drivers of different innovation strategies and subsequently we exploit innovation indicators as potential drivers of firm’s productivity. The results show that training activities and organizational changes have strong links with many industrial relations indicators, thus emerging as industrial relations driven innovations. On the contrary, ICT and technological innovation seem to be more influenced by firms’ past performances than by industrial relations. The analysis on labour productivity drivers shows that training activities are the most relevant factors; then, ranked consequently, technological innovation, organisational innovations and, finally, ICT also appear to impact on productivity levels. It is worth noting that the role of ICT emerges more robustly when endogeneity is specifically addressed. Finally, the role of firm size seems here to be overshadowed by other drivers.     

Unit nonresponse errors in income surveys: a case study

A survey on the economic and social conditions of households in the city of Modena was carried out in 2002 and in 2006 (two waves) by the CAPP (Centre for Analyses of Public Policies). In the first wave of 2002, each designated sampling unit (i.e., the family) had three units as reserves. If the first refused to be interviewed, the interviewer contacted the three reserves, one after the other, until obtaining either one respondent or four non-participant units. At the end of the survey four categories of units were distinguished: interviewees, refusals, noncontacts, and unused reserves. All units were matched with their corresponding record in the databases of the Ministry of Finance of 2002 and the Census of 2001. The resulting data set permitted the analysis of unit or total nonresponses. The distribution of fiscal income showed different shapes for the four categories, implying a selective participation of the families. The interviewees yielded a positive bias of about 600?, holding constant other factors. The selection of the significant factors affecting nonresponse was performed via backward elimination in a logit model and with the lasso method. Participation increased as fiscal income and age increased and by education level (secondary school and university degree), while it decreased among entrepreneurs, independent workers, managers, and medium-to-low skilled workers.     

Stable Asymptotics for M‐estimators

We review some first‐order and higher‐order asymptotic techniques for M‐estimators, and we study their stability in the presence of data contaminations. We show that the estimating function (ψ) and its derivative with respect to the parameter play a central role. We discuss in detail the first‐order Gaussian density approximation, saddlepoint density approximation, saddlepoint test, tail area approximation via the Lugannani–Rice formula and empirical saddlepoint density approximation (a technique related to the empirical likelihood method). For all these asymptotics, we show that a bounded ψ (in the Euclidean norm) and a bounded (e.g. in the Frobenius norm) yield stable inference in the presence of data contamination. We motivate and illustrate our findings by theoretical and numerical examples about the benchmark case of one‐dimensional location model.     

Threshold bipower variation and the impact of jumps on volatility forecasting

This study reconsiders the role of jumps for volatility forecasting by showing that jumps have a positive and mostly significant impact on future volatility. This result becomes apparent once volatility is separated into its continuous and discontinuous components using estimators which are not only consistent, but also scarcely plagued by small sample bias. With the aim of achieving this, we introduce the concept of threshold bipower variation, which is based on the joint use of bipower variation and threshold estimation. We show that its generalization (threshold multipower variation) admits a feasible central limit theorem in the presence of jumps and provides less biased estimates, with respect to the standard multipower variation, of the continuous quadratic variation in finite samples. We further provide a new test for jump detection which has substantially more power than tests based on multipower variation. Empirical analysis (on the S&P500 index, individual stocks and US bond yields) shows that the proposed techniques improve significantly the accuracy of volatility forecasts especially in periods following the occurrence of a jump.     

Whatever works: Uncertainty and technological hybrids in medical innovation

The persistent uncertainty that looms over the search for solutions to health problems offers important conceptual insights for the study of technological change. This paper explores the notion of hybridization, namely the embodiment of multiple competing operational principles within a single medical device, as strategy to deal with the practical shortcomings due to said uncertainty. The history of the development of the hybrid artificial disc affords the elaboration of an alternative view of hybridization and, at the same time, the articulation of a dualism between medical science as area of basic research (e.g. what disease is) and as practical knowledge (e.g. how disease can be tackled).     

The Open Innovation Journey: How firms dynamically implement the emerging innovation management paradigm

Open Innovation is currently one of the most debated topics in management literature. Nevertheless, there are still many unanswered questions in Open Innovation research. Especially two issues require further investigation: (i) understanding the relevance of Open Innovation beyond high-tech industries and (ii) studying how firms implement Open Innovation in practice. The paper addresses these topics by studying, through an in-depth case study, the journey that the Italian leading cement manufacturer, has undergone to move from a Closed to an Open Innovation paradigm.The paper shows that the Open Innovation paradigm is implemented along a three-phase process that comprises the stages of unfreezing, moving and institutionalising. Moreover, it emerges that the changes through which Open Innovation has been implemented involve four major dimensions, i.e. networks, organisational structures, evaluation processes and knowledge management systems. They should be therefore conceived as the managerial and organisational levers an innovating firm can act upon to streamline its journey toward Open Innovation. Theoretical and managerial implications of using these levers for implementing Open Innovation are discussed at length.