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on International Finance |
| By: | Alessandra Bonfiglioli; Rosario Crinò; Gino Gancia |
| Abstract: | We use transaction-level data to study changes in the concentration of US imports. Concentration has fallen in the typical industry, while it is stable by industry and origin country. The fall in concentration is driven by the extensive margin: the number of exporting firms has grown, and the number of exported products has fallen relatively more for top firms. Instead, average revenue per product of top firms has increased. At the industry level, top firms are converging, but top firms within country are diverging. Finally, higher concentration from an origin country is associated with a fall in prices, foreign entry and industry growth. These facts suggest that intensified competition in international markets coexists with growing concentration among national producers. |
| Keywords: | superstar firms, concentration, US imports, firm heterogeneity, international trade |
| JEL: | E23 F12 F14 L11 R12 |
| Date: | 2021 |
| URL: | http://d.repec.org/n?u=RePEc:ces:ceswps:_8986&r=all |
| By: | Umberto Collodel (PSE - Paris School of Economics - ENPC - École des Ponts ParisTech - ENS Paris - École normale supérieure - Paris - PSL - Université Paris sciences et lettres - UP1 - Université Paris 1 Panthéon-Sorbonne - CNRS - Centre National de la Recherche Scientifique - EHESS - École des hautes études en sciences sociales - INRAE - Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement, PJSE - Paris Jourdan Sciences Economiques - UP1 - Université Paris 1 Panthéon-Sorbonne - ENS Paris - École normale supérieure - Paris - PSL - Université Paris sciences et lettres - EHESS - École des hautes études en sciences sociales - ENPC - École des Ponts ParisTech - CNRS - Centre National de la Recherche Scientifique - INRAE - Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement) |
| Abstract: | The paper develops an Early Warning System (EWS) to identify the build up of vulnerabilities in the external sector of 31 Emerging Markets (EMs) across the period 1995-2017 and avoid the painful sudden reversal of capital flows associated to them. It contributes to the literature on the prediction of financial discontinuities in three ways. First, it uses a discrete choice model to calculate and compare the marginal effect of different domestic and global factors on the probability of a sudden stop materializing. Second, it analyzes the performance of the model with a recursive framework that reflects accurately the information set available to policymakers at the time of the prediction. Third, it investigates the relationship between ex-ante probability of a sudden stop and the ensuing output loss. We find that domestic and global factors contribute to the reversal of capital flows in a comparable way. Our model calls half of the pre-crisis periods, exhibiting a high specificity and a proper timing. Moreover, we find a positive link between the ex-ante probability of a sudden stop and the associated ex-post loss. These results call for an active use of Early Warnings in the policy-making sphere. |
| Keywords: | Early Warning System,Sudden Stops,Emerging Markets,External Crisis |
| Date: | 2021–03 |
| URL: | http://d.repec.org/n?u=RePEc:hal:wpaper:halshs-03185520&r=all |
| By: | Areejit Samal; Sunil Kumar; Yasharth Yadav; Anirban Chakraborti |
| Abstract: | Over the last two decades, financial systems have been studied and analysed from the perspective of complex networks, where the nodes and edges in the network represent the various financial components and the strengths of correlations between them. Here, we adopt a similar network-based approach to analyse the daily closing prices of 69 global financial market indices across 65 countries over a period of 2000-2014. We study the correlations among the indices by constructing threshold networks superimposed over minimum spanning trees at different time frames. We investigate the effect of critical events in financial markets (crashes and bubbles) on the interactions among the indices by performing both static and dynamic analyses of the correlations. We compare and contrast the structures of these networks during periods of crashes and bubbles, with respect to the normal periods in the market. In addition, we study the temporal evolution of traditional market indicators, various global network measures and the recently developed edge-based curvature measures. We show that network-centric measures can be extremely useful in monitoring the fragility in the global financial market indices. |
| Date: | 2021–01 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:2102.00070&r=all |