Alex Coad 교수

Much progress has been made in empirical research into firm growth in recent decades due to factors such as the availability of detailed longitudinal datasets, more powerful computers and new econometric techniques. This book provides an up-to-date catalogue of empirical work, as well as a coherent theoretical structure within which these new results can be interpreted and understood. It brings together a large body of recent research on firm growth from a multidisciplinary perspective, providin

Research into firm growth has been accumulating at a terrific pace, and Alex Coad's survey of this multifaceted field provides a detailed, comprehensive overview of the latest developments. Much progress has been made in empirical research into firm growth in recent decades due to factors such as the availability of detailed longitudinal datasets, more powerful computers and new econometric techniques. This book provides an up-to-date catalog of empirical work, as well as a coherent theoretical

High-growth firms (HGFs) have attracted considerable attention recently, as academics and policymakers have increasingly recognized the highly skewed nature of many metrics of firm performance. A small number of HGFs drives a disproportionately large amount of job creation, while the average firm has a limited impact on the economy. This article explores the reasons for this increased interest, summarizes the existing literature, and highlights the methodological considerations that constrain an

We apply a panel vector autoregression model to a firm-level longitudinal database to observe the co-evolution of sales growth, employment growth, profits growth and the growth of research and development (R&D) expenditure. Contrary to expectations, profit growth seems to have little detectable association with subsequent R&D investment. Instead, firms appear to increase their total R&D expenditure following growth in sales and employment. In a sense, firms behave ‘as if’ they aim for a roughly

Abstract Structural vector‐autoregressive models are potentially very useful tools for guiding both macro‐ and microeconomic policy. In this study, we present a recently developed method for estimating such models, which uses non‐normality to recover the causal structure underlying the observations. We show how the method can be applied to both microeconomic data (to study the processes of firm growth and firm performance) and macroeconomic data (to analyse the effects of monetary policy).

This article offers many new insights into the processes of firm growth by applying a vector autoregression model to longitudinal panel data on French manufacturing firms. We observe the coevolution of key variables such as growth of employment, sales, gross operating surplus, and labor productivity growth. Preliminary results suggest that employment growth is succeeded by the growth of sales, which in turn is followed by growth of profits. Generally speaking, however, growth of profits is not f

We provide a broad discussion of the dark side of innovation, before introducing the papers of the special issue. We start with a critical reply to optimists, complementing the list of indicators showing steady human progress with a list of indicators that show sustained deterioration (largely due to innovation). We then outline some relevant dimensions of harmful innovation, before distinguishing between the types of harm brought on by innovation. We conclude with an overview of the SI papers.