if this message does not display correctly, click here | Table of Contents Sergei Kovbasyuk, EIEF Giancarlo Spagnolo, Stockholm School of Economics (SITE), Centre for Economic Policy Research (CEPR), University of Rome 'Tor Vergata', EIEF Luca Gori, University of Geona - Department of Law and Economics - G.L.M. Casaregi Enrico Lupi, University of Rome, Tor Vergata - Department of Economics and Finance Piero Manfredi, Universita di Pisa - Dipartimento di Statistica e Matematica Applicata Mauro Sodini, Dipartimento di Statistica e Matematica Applicata all’Economia, Università di Pisa Leopoldo Catania, University of Aarhus - School of Business and Social Sciences Stefano Grassi, University of Rome, Tor Vergata, Faculty of Economics, Department of Economics, Law and Institutions | |
CEIS: CENTRE FOR ECONOMIC & INTERNATIONAL STUDIES Vincenzo Atella - Director "Memory and Markets" CEIS Working Paper No. 415 SERGEI KOVBASYUK, EIEF Email:
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GIANCARLO SPAGNOLO, Stockholm School of Economics (SITE), Centre for Economic Policy Research (CEPR), University of Rome 'Tor Vergata', EIEF Email:
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In many environments, including credit and online markets, past records about participants are collected, published, and erased after some time. We study the effects of erasing past records on trade and welfare in a dynamic market where each seller's quality follows a Markov process and buyers leave feedback about sellers. When the average quality of sellers is low, unlimited records always lead to a market breakdown. Appropriately deleting records, instead, can sustain trade in the long run. Positive and negative records play very different roles, and welfare is maximized for short positive records and long but bounded negative records. "Can HIV Alter the Quantity-Quality Switch and Delay the Fertility Transition in Sub-Saharan Africa?" CEIS Working Paper No. 416 LUCA GORI, University of Geona - Department of Law and Economics - G.L.M. Casaregi Email:
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ENRICO LUPI, University of Rome, Tor Vergata - Department of Economics and Finance Email:
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PIERO MANFREDI, Universita di Pisa - Dipartimento di Statistica e Matematica Applicata Email:
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MAURO SODINI, Dipartimento di Statistica e Matematica Applicata all’Economia, Università di Pisa Email:
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According to the conventional theory of the demographic transition, mortality decline has represented the major trigger for fertility decline and eventually sustained economic development. In Sub-Saharan Africa (SSA), the HIV/AIDS epidemic has had a devastating impact on mortality, by dramatically reversing, in high HIV-prevalence countries, the long-term positive trend in life expectancies. Despite the fact that SSA as a whole is suffering a delayed and slow fertility transition compared to other world’s regions, and despite evidence for halting or even reverting fertility decline in countries with severe HIV epidemics, there seems to be little concern amongst international policy makers about the ultimate impact that HIV might have on SSA fertility. This work reports model-based evidence of the potential for a HIV-triggered reversal of fertility in high HIV-prevalent SSA countries induced by the fall in education and human capital investments following the drop in life expectancy for young adults. This eventually breaks down the virtuous circle promoting the switch quantity-to-quality of children. This result suggests that the current evidence on fertility halting and declining education in high HIV-prevalent SSA countries should be seriously taken into consideration to prioritise current international interventions. "Modelling Crypto-Currencies Financial Time-Series" CEIS Working Paper No. 417 LEOPOLDO CATANIA, University of Aarhus - School of Business and Social Sciences Email:
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STEFANO GRASSI, University of Rome, Tor Vergata, Faculty of Economics, Department of Economics, Law and Institutions Email:
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This paper studies the behaviour of crypto-currencies financial time-series of which Bitcoin is the most prominent example. The dynamic of those series is quite complex displaying extreme observations, asymmetries and several nonlinear characteristics which are difficult to model. We develop a new dynamic model able to account for long-memory and asymmetries in the volatility process as well as for the presence of time-varying skewness and kurtosis. The empirical application, carried out on a large set of crypto-currencies, shows evidence of long memory and leverage effect that has a substantial contribution in the volatility dynamic. Going forward, as this new and unexplored market will develop, our results will be important for investment and risk management purposes. | | ^top
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